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==== Front
Virtual Real
Virtual Real
Virtual Reality
1359-4338
1434-9957
Springer London London
728
10.1007/s10055-022-00728-1
Original Article
Application of virtual reality for peritoneal dialysis exchange learning in patients with end-stage renal disease and cognitive impairment
Lee Connie M. S. 12
http://orcid.org/0000-0001-5909-4847
Fong Kenneth N. K. [email protected]
1
Mok Maggie M. Y. 3
Lam M. K. 4
Kung Y. 4
Chan Paven P. W. 4
Ma Maggie K. M. 4
Lui S. L. 3
Kwan Lorraine P. Y. 3
Chu W. L. 3
Hui P. C. 3
Yau Christina S. F. 5
Kwan Ivan W. L. 5
Chan Kelsey Y. M. 5
Chan T. M. 4
1 grid.16890.36 0000 0004 1764 6123 Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, SAR China
2 grid.415550.0 0000 0004 1764 4144 Department of Occupational Therapy, Queen Mary Hospital, Hong Kong, SAR China
3 grid.417349.c 0000 0004 1799 6705 Department of Medicine, Tung Wah Hospital, Hong Kong, SAR China
4 grid.415550.0 0000 0004 1764 4144 Department of Medicine, Queen Mary Hospital, Hong Kong, SAR China
5 grid.417349.c 0000 0004 1799 6705 Department of Occupational Therapy, Tung Wah Hospital, Hong Kong, SAR China
3 12 2022
113
20 4 2022
21 11 2022
© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Cognitive impairment is not uncommon in patients with end-stage renal disease and can make it more difficult for these patients to carry out peritoneal dialysis (PD) on their own. Their attempts to do so may result in adverse consequences such as peritonitis. PD exchange is a complex procedure demanding knowledge and skill which requires close supervision and guidance by a renal nurse specialist. In this study, a non-immersive virtual reality (VR) training program using a Leap motion hand tracking device was developed to facilitate patients’ understanding and learning of the PD exchange procedure before attempting real task practice. This study was a two-center single-blinded randomized controlled trial on 23 incident PD patients. Patients in the experimental group received 8 sessions of VR training, while patients in the control were provided with printed educational materials. The results showed that there were significant differences between the two groups in performance of the overall PD exchange sequence, especially on the crucial steps. VR had a patient satisfaction rate of 89%, and all patients preferred to have the VR aid incorporated in PD training. Our findings conclude VR can be a useful aid in the training and reinforcement of PD exchange procedures, with distinct merits of being free from restrictions of time, space, and manpower.
Keywords
Virtual reality
End-stage renal disease
Peritoneal dialysis
Cognitive impairment
http://dx.doi.org/10.13039/501100003808 Hospital Authority TRAS-18-03 (01/18/213) Lee Connie M. S.
==== Body
pmcIntroduction
Chronic kidney disease (CKD) is a very serious non-communicable disease that affects many people worldwide. CKD is defined as kidney damage or glomerular filtration rate (GFR) of less than 60 mL/min/1.73 m2 for three months or more, irrespective of cause (Levey et al. 2005). There are five stages of CKD, with end-stage renal disease (ESRD) referring to the final stage of the disease, when GFR is less than 15 mL/min/1.73 m2. If uremia is present, patients with ESRD receive renal replacement therapy (RRT), which acts to replace some of the functions of a kidney, particularly removal of waste products and excess fluids. The three types of RRT are peritoneal dialysis (PD), hemodialysis (HD), and renal transplant. There were 8510 patients on RRT in 2013 as compared to 3312 patients in 1996 in Hong Kong (Leung et al. 2015). This increase in patients has occurred at the same time as the region’s implementation of a “Peritoneal Dialysis (PD) - first” policy, which has seen continuous ambulatory peritoneal dialysis (CAPD) provided to all patients as the default dialysis treatment option in the absence of medical contraindications (Kwong and Li 2015). As a result, more than 80% of ESRD patients requiring dialysis are put on PD, among whom 86% are on CAPD, while the remainder are on automated peritoneal dialysis (APD).
Furthermore, CKD itself is a significant risk factor for cognitive impairment, beginning with those at stage 3 (i.e., patients with GFR of 45–60 ml/min/1.73 m2) and becoming more prevalent among those who have reached ESRD (Kurella et al. 2005; Murry and Knopman 2010; Etgen et al. 2012). The major areas of cognitive deficit in ESRD patients on RRT are attention, memory, processing speed and executive function. Around 70% of patients aged over 55 have been found to exhibit moderate-to-severe cognitive impairment (Radic et al. 2010; Kalirao et al. 2011). Recent local studies also showed that cognitive impairment was common in those with ESRD, with a prevalence of 28.9% among patients who had recently started PD (Shea et al. 2016a, b). Being older than 65 and having lower levels of education were shown to be independent risk factors for cognitive impairment (Shea et al. 2016a, b). More significantly, one third of ESRD patients on PD demonstrate moderate-to-severe impairment in executive function, which poses a considerable risk of hazard during self-administered PD, particularly due to reduced abilities in organization, planning, sequencing and procedural memory (Kalirao et al. 2011).
PD exchange is a complex task that demands multiple aspects of cognitive function, including adhering correctly to procedures, sequencing, time estimation and safety awareness, and the detection of problems encountered during the exchange. Cognitive impairment among patients with ESRD who perform PD exchange themselves may leave them at risk of medical complications such as peritonitis resulting from errors in handling of the complex PD exchange procedure. Given these various requirements, and the risks involved in carrying out procedures incorrectly, it would be better for patients to learn using errorless learning, enabling them to make use of their learning ability using implicit memory through repetitive practice. This method reduces the burden on conscious and logical recall of learned materials (Baddeley and Wilson 1994). In current local practice, it is usual that ESRD patients learn and practice PD exchange in a clinical setting and under the instruction of a renal nurse 1 week prior to carrying out the procedure at home. Most patients do not acquire knowledge and understanding of the procedure or the necessary precautions until after formal training commences. There is no doubt that cognitively impaired patients face extra difficulty in handling this complex task, which requires both accuracy and strict adherence to safety procedures. However, the common remedies for this barrier to understanding among cognitively impaired patients are limited to the provision of visual cues (such as an instruction sheet listing a series of steps to be followed) and signage (e.g., attached to indicate the positions of items to be put), while the need for additional and needs-specific training on performing PD is not addressed. There is a limited amount of evidence on effective intervention for training cognitively impaired renal patients in self-administering PD.
VR can be viewed as an advanced computer-based technology that allows users to interact and immerse within a multi-sensory three-dimensional simulated environment and receive augmented feedback on performance (Rizzo et al. 1997; Costa et al. 2000). Interaction and immersion is a key characteristic of any VR system, offering the user total engagement in an activity’s characteristic features, including human interaction, tools and environment, and goal-directed actions and reactions that demand responses from multiple cognitive functions (Joseph et al. 2012; Panerai et al. 2019, 2021). Being actively engaged in the activity means that the user’s awareness and attention are enhanced. Moreover, less motor skill is demanded as compared with actual performance, meaning there are less barriers to engagement by users with physical disabilities (Zhang et al. 2003). Furthermore, practicing skills within simulated environments that bear close resemblance to real situations has several advantages. It allows for generalization of skills learned in the virtual training environment to the real-life environment (Costa et al. 2000). It also enables the user to practice procedures that are not easily deliverable and controlled in reality, and it reduces the manpower needed for supervision purposes while increasing the number of practice repetitions that can be undertaken in one session (Christiansen et al. 1998; Joseph et al. 2012). Moreover, controlled delivery of a wide range of VR environments during practice offers flexibility in the range of different training conditions under which patients can practice, which may not be feasible in reality. In addition, systematic and hierarchical presentation of challenges and augmented feedback on performance are believed to improve motivation and awareness, since these enable users to better understand their own performance and successes, hence improving their self-efficacy in performing tasks (Faria et al. 2016; Hwang and Lee 2017).
It is inevitable that cognitively impaired patients with ESRD will be required to perform CAPD by themselves. Since learning of the PD exchange procedure is complicated, and may pose risks if steps are missed or done incorrectly, particularly in patients with cognitive deficits; therefore, this study proposed and developed a non-immersive VR training program to serve as an innovative method in occupational therapy for restorative task-specific training within a simulated context that permits implicit learning of skills and explicit formation of knowledge about PD exchange, as well as optimizing transfer of training to real-life situations. The objective of this study was to investigate whether the application of a VR training program in learning PD exchange could assist ESRD patients with cognitive impairment more than a conventional educational approach using printed educational materials.
Methods
Participants
ESRD patients who were newly starting PD were recruited consecutively by convenience sampling from the Division of Nephrology at Queen Mary Hospital and from Tung Wah Hospital in Hong Kong over a 2-year period. The inclusion criteria were: (i) using the Ultrabag (Baxter) Dialysis Delivery system, (ii) Cantonese-speaking, and (iii) failed in “alternating trail making” or “verbal fluency”, or recall less than three “delayed recall” items on the Hong Kong version of Montreal Cognitive Assessment (HK-MoCA) (Yeung et al. 2014). The exclusion criteria were: (i) using automated peritoneal dialysis or other alternative dialysis systems, (ii) having previous experience in PD, (iii) requiring an assistive device during PD exchange, (iv) receiving cognitive rehabilitation elsewhere, and (v) incompetent to give their own consent.
This study was a two-center single-blinded randomized controlled trial, in which the outcome assessors were blinded to the group allocation. Written consents from eligible patients were obtained before the study began. Patients recruited into the study were randomly assigned to either the experimental group or the control group by an independent renal doctor. The randomization schedule was generated using the website Randomization.com (http://www.randomization.com). To assure a balanced allocation ratio across conditions, a block randomization method with block size of 10 was adopted for each research center. The allocation sequences were concealed, and only the researchers were informed of the group assigned to the participant. Ethical approvals were sought from the Human Subjects Research Ethics Committee of The Hong Kong Polytechnic University (Reference number HSEARS20180502004) and the Research Ethics Committee of the Hong Kong West Cluster/University of Hong Kong (IRB reference number UW 17-463).
Equipment
The VR computer program used in this study is a non-HMD type that participants use to interact with a simulated three-dimensional environment presented on a notebook computer monitor. The virtual environment simulates the layout of PD exchange, with standard equipment and device displayed for each step. The user navigates and interacts with the environment through the Leap motion hand tracking device, as illustrated in Fig. 1. The VR application was developed using the software Unity 3D game engine version (version 2017.4.20f2, Unity Technologies, San Francisco, US). It was a cross-platform game engine designed to support and develop 2D and 3D video games, and virtual reality in desktop and mobile devices. The control functions in the VR environment were coded by the Unity3D using the C# programming language. The model objects for the VR application were designed and constructed base on real equipment set for renal dialysis by using the software 3D Studio Max version 2017 (Autodesk Inc., San Rafael, US). The VR program was designed by the investigators based on the comments from an expert panel, which consisted of 10 persons including 2 nephrologists, a renal nurse consultant, 2 renal nurse specialists, 2 occupational therapists, and 3 patients receiving PD exchange, and was written by an IT programmer. Multiple user testing was done to refine the sensitivity of the device in capturing user’s response and graphics displayed on the screen. The program composed of three modules (i) real case video demonstration of the whole PD exchange, (ii) VR PD assessment mode, and (iii) VR PD training mode. The content was based on real task of PD exchange using Ultrabag (Baxter) Dialysis Delivery system. The whole PD exchange procedure is divided into eight sub sections, and each sub section consists of multiple steps. Patients are requested to complete the steps of each section in a correct order. The total number of correct responses is recorded as the assessment result.Fig. 1 The experimental setup
The objects used in each step are presented on the computer monitor, and the user is required to initiate each action in the sequence within 10 s. The object selected by the user will be highlighted (Fig. 2a), and any transfer of the object from one place to another will be demonstrated on the screen as immediate visual feedback. A vocal message is produced to notify the user that an action has been successfully completed, for example, “The blood pressure is taken.” An image of a timer is also displayed in the right-hand lower corner of the screen, which indicates the time remaining for the user to react (Fig. 2b). If the user fails to make a correct response within 10 s, a pop-up written message of the action that should be taken will show on the screen together with a vocal message, serving as a reminder to the user (Fig. 2c). However, if either no response or an incorrect response is made by the user within the subsequent 10 s, the program will automatically execute the correct step and move to the next step (Fig. 2d). This design guarantees that the program proceeds through to the final step of the PD exchange procedure, at which point the user’s total score is calculated. Figure 2 shows screenshots of selected steps of the program.Fig. 2 a–d Samples of the VR training steps
The only difference between the training mode and the assessment mode is that the former does not assign scores to the user’s response. Apart from its training purpose, the training mode can also be used to familiarize patients with the VR program and so that the occupational therapist can identify an optimal environment before actual assessment starts.
In assessment mode, patients’ performance at each step is evaluated, with scores assigned in the form of total score (0–96 points) and sub section scores (Preparation of workstation: 0–24, checking of new dialysate: 0–18, connection to new dialysate: 0–16, drain-out: 0–6, wash drain: 0–4, drain-in: 0–6, disconnection: 0–14, completion: 0–8). A higher score indicates more correct responses made by the user. The scoring system is based on the number of correct responses made with or without cues at each individual step, with a maximum of three cues available per step (Fong et al. 2010). A brief description of the scoring system is given in Table 1.Table 1 Scoring system of the assessment mode
Points User’s performance at each step
2 Correct response is made without any cue
1 Correct response is made with visual cue and auditory message
0 No response, or an incorrect response, is made by the user, even following visual cue and auditory message; the program automatically executes the correct step
Intervention
At the beginning of the study, patients in both groups watched a real case video demonstrating the whole PD exchange process. They then underwent a set of pre-treatment outcome measurements within the same week. All patients received routine twice-weekly intermittent peritoneal dialysis (IPD) in the hospital for 8–10 weeks. Patients in the control group were given at the first IPD session educational materials concerning management of CAPD, including knowledge of the disease, various kinds of renal replacement therapy, multidisciplinary support, and common problems encountered by patients, etc. Patients in the experimental group were given, apart from usual IPD, an additional minimum of eight sessions of VR training on PD exchange, with one to two sessions per week given by an occupational therapist during their hospital stay for IPD. Since patients undergoing IPD were restricted to bed, the VR training was conducted at bedside, with the Leap motion sensor and notebook computer set up there for use. Patients in the experimental group also received the same educational materials as the control group. Upon completion of IPD, all patients received 1 week of CAPD training at the day center, where they were instructed in the PD exchange procedure by the renal nurse specialist. Patients engaged in sufficient practice sessions in carrying out PD exchange under nurse supervision to ensure safe and accurate self-administering of CAPD following discharge. All patients underwent the same set of post-treatment outcome measurements, administered by the researchers, within this week, while their performance in carrying out the PD exchange technique was assessed by the renal nurse specialist at the final session of CAPD training. For the experimental group, a two-item patient satisfaction survey was conducted to collect information on patients’ perception of (i) the usefulness of the VR training in learning the PD exchange procedure and (ii) their preference for VR training as a technique for learning PD exchange. The survey used a four-point ordinal scale ranging from “strongly agree” to “strongly disagree”.
Outcome measurements
Outcome measurements were taken at baseline (pre-treatment), within the first week after recruitment into the study, and at post-treatment, within the week that patients received CAPD training at the day center. All outcome measurements were conducted by blinded researchers, except in the case of the PD exchange technique assessment, which was carried out by the renal nurse specialist. The study employed three primary outcome measures to assess the task domain. These measured knowledge proficiency, procedure competence and self-efficacy in PD exchange. (i) Knowledge proficiency regarding peritoneal dialysis was measured by a PD knowledge test composed of ten key questions about PD exchange in the format of multiple choice questions. Each correct answer earns respondents one point, with total score ranging from 0 to 10. (ii) Procedure competence was measured by using the PD steps sequence test, administered through the VR computer program. The total number of correct responses is recorded as the assessment result. Apart from the total score, we further categorized the eight sub sections into three sections—“Start”, “Main” and “After” with these section scores analyzed in this study. The “Start section” included preparation of workstation and checking of new dialysate, which was a setup phase; the “Main section” included connection to new dialysate, drain-out, wash drain and drain-in, which were considered as the critical steps; the “After section” included disconnection and completion, the final stages of the procedure. (iii) Self-efficacy of PD exchange was assessed using the Chinese General Self-Efficacy Scale (Chinese-GSE) and four-item self-constructed supplementary questions. The Chinese-GSE scale consists of ten items measuring how confident a person is in dealing with novel or demanding situations regarding their abilities and employs a four-point ordinal scale. Total score ranges from 10 to 40, with a higher score indicating higher confidence. The scale was found to have excellent internal consistency (0.92–0.93) and very good to excellent test re-test reliability (0.75–0.94) in schizophrenia (Chiu and Tsang 2004). The four-item self-constructed supplementary confidence questionnaire was specifically designed for assessing patients’ self-efficacy in PD exchange, using a 10-point scale to measure “knowledge of PD exchange steps and sequence”, “knowledge of key points in PD exchange”, “ability to self-administer CAPD” and “incorporation of CAPD into daily living”. Zero represents the least confidence, while 10 represents absolute confidence. Total score ranges from 0 to 40, with higher scores indicating greater confidence in PD exchange. (iv) The PD exchange technique assessment administered by the renal nurse specialist is a 10-item test addressing PD exchange preparation and procedure using a five-point Likert scale, with responses corresponding to “completely satisfactory”, “satisfactory”, “acceptable”, “dissatisfactory” and “completely dissatisfactory”. Patients were rated by the renal nurse specialist according to their ability in carrying out real PD exchange at the final session of CAPD training before discharge. Patients’ possible scores range from 10 to 50, with higher scores indicating more satisfactory performance.
Two secondary outcome measures were used to assess the cognitive domain. These included an everyday memory scale and an executive functioning test. (i) The Rivermead Behavioural Memory Test—version 3 (RBMT-3) consists of eleven subtests addressing visual, verbal and visuospatial memory, with a total standardized profile score ranging from 0 to 24 (Wilson et al. 2008). The Hong Kong version of the assessment we used in this study showed excellent internal consistency (with a Cronbach’s alpha of p = 0.859), high inter-rater reliability (with correlation coefficient ranging from 0.74 to 0.95, p = 0.000), and test–retest reliability (t = − 3.4, p = 0.002) (Fong et al. 2017). The Sum of Scaled Scores (SSS) and the General Memory Index (GMI) were both analyzed. (ii) The Wisconsin Card Sorting Test—Computer version 4 (WCST-CV4) is a measure of executive function that is administered on-screen. It tests the ability to shift mental sets and to update and monitor working memory representations. Patients are requested to sort cards according to matches in either color, form or number of figures, and according to different criteria that change discreetly without the patient being informed (Heaton et al. 1993). The WCST has been employed extensively in the study of multiple kinds of disease, including focal and diffuse brain damage. The validity of WCST as a measure of executive function in adults has been supported, with the preservative errors of the instrument found to load on the factor of operational reasoning ability (Shute and Huertas 1990), while preservative responses (r = 0.63) and total number of errors (r = 0.62) were related to attribute identification (Perrine 1993). Total number of trials administered, total correct responses and total errors made were each analyzed in this study. Figure 3 summarizes the workflow of the study.Fig. 3 Workflow of the study. Note: CAPD continuous ambulatory peritoneal dialysis, Chinese-GSE Chinese General Self efficacy Scale, ERSD end-stage renal disease, HK-MoCA Hong Kong version of Montreal Cognitive Assessment, IPD intermittent peritoneal dialysis, OT Occupational Therapist, PD peritoneal dialysis, RBMT-3 The Rivermead Behavioural Memory Test—version 3, WCST-CV4 The Wisconsin Card Sorting Test—Computer version 4
Statistical analysis
Demographic and baseline outcome measurements for all patients were reported using descriptive statistics. Independent t testing (continuous data) and Chi-square testing (categorical data) were performed to compare any difference between the control group and the experimental group. Intention-to-treat analysis was applied using the last observation carried forward (LOCF) method for dropouts. Repeated measures analysis of covariance (RANCOVA) was used to analyze the within-subject effect (time effects) and between-subject effect (group effects) on the outcome measurements. The difference in PD exchange technique between the two groups was analyzed by independent t test. All statistical analyses were calculated using the statistical software SPSS version 21.0. The level of significance was set at p < 0.05 (two-tailed).
Results
Figure 4 shows the CONSORT flowchart of participants. A total of 25 patients with ESRD were assessed for eligibility, of whom two refused to join the study. A total of 23 patients were recruited and randomly allocated to control group (n = 11) and experimental group (n = 12). Among the 11 patients in the control group, there was one patient who did not complete the pre-treatment VR computer program and WCST; and there were four patients who completed only parts of the post-treatment outcome measurements due to change of mode of dialysis to either APD or HD. Among the 12 patients in the experimental group, two did not complete the pre-treatment WCST, and three did not complete the whole set of post-treatment outcome measurements. The data for a particular assessment were either excluded for analysis if the baseline could not be obtained back, or filled in using the group mean score if parts of the post-treatment outcome measurements were missing.Fig. 4 CONSORT flow diagram of patients recruited into the study. Note: ERSD end-stage renal disease, IPD intermittent peritoneal dialysis
The mean age ± standard deviation (SD) of patients was 63.6 ± 11.5 in the control group and 62.7 ± 5.5 in the experimental group. There were six males (55%) and five females (45%) in the control group and nine males (75%) and three females (25%) in the experimental group. The mean HK-MoCA score was 23.7 ± 4.5 for those in the control group and 23.3 ± 4.4 for those in the experimental group. The mean years of education was 8 ± 1.3 for those in the control group and 8.3 ± 1.3 for those in the experimental group. There was no significant difference in demographics or in any pre-treatment outcome measurements between the two groups (Table 2).Table 2 Comparison of demographics and baseline characteristics
Experimental group Control group p
(n = 12) (n = 11)
Demographics
Age (year), mean ± SD 62.7 ± 5.5 63.6 ± 11.5 0.82
Gender (%)
Male 9 (75) 6 (55)
Female 3 (25) 5 (45) 0.30
HK-MoCA, mean ± SD 23.3 ± 4.4 23.7 ± 4.5 0.80
Education level (year), mean ± SD 8.3 ± 1.3 8 ± 1.3
Pre-treatment assessment
mean ± SD
PD knowledge test 4.8 ± 2.0 5.7 ± 2.3 0.29
PD steps sequence test
VR-total 63.0 ± 18.7 53.0 ± 25.1 0.31
VR-start 32.7 ± 8.8 30.2 ± 12.4 0.60
VR-main 17.6 ± 7.6 12.3 ± 7.7 0.12
VR-after 12.8 ± 3.8 10.50 ± 6.5 0.35
Chinese-GSE 28.4 ± 5.6 29.0 ± 5.7 0.81
4-item supplementary confidence 25.7 ± 5.8 26.7 ± 6.2 0.70
RBMT-3
RBMT-SSS 123.1 ± 20.1 125.0 ± 10.8 0.78
RBMT-GMI 88.4 ± 13.2 88.8 ± 8.4 0.93
WCST-CV4
WCST-administer 107.0 ± 33.0 115.5 ± 14.1 0.45
WCST-correct 70.2 ± 13.4 77.3 ± 11.6 0.24
WCST-error 46.8 ± 21.3 38.2 ± 18.1 0.33
HK-MoCA Hong Kong version of Montreal Cognitive Assessment, VR-total total number of correct responses in VR program, VR-start total number of correct responses in VR program “Start” section, VR-main total number of correct responses in VR program “Main” section, VR-after total number of correct responses in VR program “After” section, Chinese-GSE Chinese General Self-efficacy Scale, RBMT-3 The Rivermead Behavioural Memory Test—version 3, RBMT-SSS Sum of Scaled Scores of RBMT-3, RBMT-GMI General Memory Index score of RBMT-3, WCST-CV4 The Wisconsin Card Sorting Test—Computer version 4, WCST-administer number of trials administered in WCST-CV4, WCST-correct total number of correct responses in WCST-CV4, WCST-error total number of errors in WCST-CV4
For the analysis of primary outcomes, several factors were considered as covariates, including age, gender, baseline cognitive performance measured using HK-MoCA, years of education and duration of training received in terms of attendance at training sessions. After being entered as covariates in RANCOVA, only age and gender were found to be significant covariates (p = 0.005 and p = 0.014 respectively) and kept for further analysis. There were between-group effects in VR-total (F = 4.59, p < 0.05), VR-main (F = 6.55, p < 0.05) and VR-after (F = 5.94, p < 0.05). The mean scores for VR-total, VR-main and VR-after at pre-/post-treatment occasions are presented in Table 3. Patients in the experimental group performed significantly better than patients in the control group in performance of the overall PD exchange procedure, especially in the crucial steps of connection and disconnection of the tenckhoff catheter with the dialysate, correct sequence of opening and closing of clips during drain-in and drain-out processes, and rounding up of the whole procedure. No significant differences in between-group effects were observed in other primary outcomes such as PD knowledge test, GSE and self-constructed supplementary confidence questionnaire. Though there was no statistically significant difference between the two groups in the secondary outcome measurements across the two occasions (Table 3), there were gains in RBMT-SSS, RBMT-GMI and WCST-correct scores among patients in the experimental group, whereas there were losses in these scores among patients in the control group at post-treatment time. There were no overall significant within-subject effects in either primary or secondary outcome measurements.Table 3 Comparison of outcomes for the two groups across two occasions
Outcomes Experimental group Control group F p
(n = 12) (n = 11)
Primary outcomes
PD knowledgea
Baseline 4.8 ± 2.0 5.7 ± 2.3
Posttreatment 7.4 ± 2.2 6.7 ± 2.0 0.11 0.75
PD steps sequence test
VR-totala
Baseline 63.0 ± 18.7 53.0 ± 25.1
Posttreatment 76.6 ± 21.8 57.7 ± 32.7 4.59 0.05*
VR-starta
Baseline 32.7 ± 8.8 30.2 ± 12.4
Posttreatment 32.9 ± 13.1 29.6 ± 15.9 1.62 0.22
VR-maina
Baseline 17.6 ± 7.6 12.3 ± 7.7
Posttreatment 24.4 ± 8.9 16.3 ± 10.8 6.55 0.02*
VR-aftera
Baseline 12.8 ± 3.8 10.5 ± 6.5
Posttreatment 16.5 ± 4.5 11.8 ± 7.2 5.94 0.03*
Chinese-GSEa
Baseline 28.4 ± 5.6 29.0 ± 5.7
Posttreatment 30.3 ± 5.5 30.0 ± 4.6 0.03 0.86
4-item supplementary confidencea
Baseline 25.7 ± 5.8 26.6 ± 6.2
Posttreatment 31.4 ± 5.7 30.6 ± 6.1 0.00 0.97
PD technique assessmentb
Baseline NA NA
Posttreatment 41.3 ± 5.4 45.8 ± 4.7 − 1.85 0.08
Secondary outcomes
RBMT-3
RBMT-SSSa
Baseline 123.1 ± 20.1 125.0 ± 10.7
Posttreatment 125.9 ± 21.1 122.8 ± 13.3 0.01 0.92
RBMT-GMIa
Baseline 88.4 ± 13.2 88.8 ± 8.36
Posttreatment 91.5 ± 15.6 87.7 ± 10.4 0.11 0.75
WCST-CV4
WCST-administera
Baseline 107.0 ± 33.0 115.5 ± 14.1
Posttreatment 103.3 ± 34.7 108.9 ± 20.9 0.72 0.41
WCST-correcta
Baseline 70.2 ± 13.4 77.3 ± 11.6
Posttreatment 74.7 ± 11.9 75.7 ± 8.4 1.94 0.18
WCST-errora
Baseline 46.8 ± 21.3 38.2 ± 18.1
Posttreatment 38.6 ± 20.3 33.2 ± 17.4 0.41 0.53
*p ≤ 0.05; aBetween-subject effects between the two groups (with age and gender as covariates); bIndependent t test between two groups
VR-total total number of correct responses in VR program, VR-start total number of correct responses in VR program “Start” section, VR-main total number of correct responses in VR program “Main” section, VR-after total number of correct responses in VR program “After” section, Chinese-GSE Chinese General Self-Efficacy Scale, RBMT-3 The Rivermead Behavioural Memory Test—version 3, RBMT-SSS Sum of Scaled Scores of RBMT-3, RBMT-GMI General Memory Index score of RBMT-3, WCST-CV4 The Wisconsin Card Sorting Test—Computer version, WCST-administer number of trials administered in WCST-CV4, WCST-correct total number of correct responses in WCST-CV4, WCST-error total number of errors in WCST-CV4
Regarding patient satisfaction with the use of VR training as a method of learning PD exchange, 89% of participants in the experimental group agreed that it was helpful, and 100% said they would like it to be incorporated into conventional PD exchange learning.
Discussion
Our study showed that patients who had received VR training sessions demonstrated significantly more correct responses in performing the PD exchange procedure than patients who had not received such training. This shows that VR training is an effective method of procedural learning for use as an adjunct to conventional PD exchange education, particularly for ERSD patients with cognitive deficits. The non-immersive VR applied in this study provided a type of interactive experience, based on “learning-by-doing,” the efficacy of which is supported in the findings of previous studies (Panerai et al. 2021; Dalgarno and Lee 2010). Training within a virtual environment that explicitly displays the PD exchange process allows patients to see themselves completing the task, which in turn better enables them to problem solve their way out of difficulties and gradually improve their method. As well as being physically immersed in the task environment, the user’s mental immersion generates a sense of presence in the task that reinforces active engagement in the learning process (Jennett et al. 2008). This then has the effect of strengthening the user’s initial understanding of the PD exchange concept, including its multimedia representation through traditional forms of educational leaflet or videos (Fowler 2015). Moreover, the provision of instant performance feedback via vocal and written message further promotes learning from experience and reflective thinking, which are important in boosting learning outcomes (Zhang et al. 2017). Another distinguishing feature of VR training is its focus on learning-by-doing. This approach boosts users’ learning in various ways, including by providing opportunities to become familiar with the simulated environment, fostering memories through the performance of actions, and allowing users to go through the learning cycle of extending effort, making mistakes and reflecting on performance (Riva 2017). Furthermore, the study results demonstrated that patients in the experimental group performed significantly better in those crucial and critical steps of the PD exchange procedure, which are regarded to minimize risk of peritonitis. Therefore, we believed that the use of VR training can definitely be a helpful remedy to resolve the difficulties encountered by patients with cognitive impairment.
Regarding another outcome measuring knowledge proficiency, the PD knowledge test, the absence of significant findings in post-treatment assessment of the two groups did not tally with the results of the PD steps sequence test. The possible reason for this might be that the context of the PD knowledge test, composed of questions about both the PD exchange steps sequence as well as essential knowledge about PD exchange more generally, might not be explicitly manifested in the VR training program. In order to facilitate a more comprehensive learning of PD exchange, it is suggested that a minor modification be made to the current VR training program by revising vocal messages to offer detailed explanations and rationales to users upon successful completion of actions in the PD exchange sequence. This would enhance patients’ understanding and working memory in ways that have been shown to promote learning (Raw et al. 2019).
Despite that an insignificant difference between-group findings on real-life PD exchange technique was obtained as measured by renal nurse specialist assessment, the benefit of VR training on real task performance could not be overruled. A possible reason for this could be the time gap between the training sessions and real practice. Patients in both groups underwent 1-week CAPD training after the IPD period, during which time they were provided with equal opportunities to learn the task and to undertake intensive daily practice under nurse supervision at the day center. Patients were required to perform to a standard level in the PD exchange technique assessment in order to qualify for at-home CAPD. Since the VR training developed to serve as a supplementary mode of PD exchange learning, which was not expected to be equivalent to real task training provided by renal nurses. Conversely, the training efficiency between the groups was not taken into account in our study.
Though we failed to find any significant improvement in the cognitive domain as measured by secondary outcomes such as RBMT-SSS, RBMT-GMI and WCST-correct, our results did show post-intervention improvements in these measurements among patients in the experimental group, whereas those in the control group performed worse (as compared with pre-treatment performance). These non-significant findings may be a result of small sample size and study power. Nonetheless, the possibility that VR training may have some impact on effecting improvements in cognitive functions should not be dismissed out of hand.
In terms of patient satisfaction, the feedback from patients on their experience of VR training was consistent with that collected in other studies on the use of non-immersive VR for the learning of functional living skills (Panerai et al. 2021). Perception of satisfaction is defined as one of the effective outcomes of learning experience in education and training (Sharda et al. 2004). The fact that all patients in the experimental group of this study enjoyed adopting VR training as one of the modalities for learning PD exchange indicates that it was an effective learning experience. However, it was observed that some patients, who may have lacked experience in the use of computerized devices, needed extra time and the expending of additional effort in order to familiarize themselves with either the motion sensor or the program, increasing the likelihood of fatigue and impatience, and thus leading to reduced focus on the task. To address this issue, familiarization training could be provided to help patients adapt to the system and give them the necessary time to determine an optimal setup. This would promote a smooth operation and improve patients’ engagement.
Limitations
This study has several limitations. First, the sample size was small. The data collection process was interrupted during the period of the COVID-19 pandemic, meaning that patient recruitment may be unrepresentative of ESRD patients with cognitive impairment. Furthermore, because of the small sample size, we could not stratify participants according to their levels of cognitive impairment for further analysis on whom might benefit from the VR training. On the other hand, given the improvements in patients’ performance of the PD exchange process after VR training, the conclusion that this positive finding is due to practice effect is inevitable. Regarding the transfer of skills to real-life practice, this was an area that was difficult to fully examine due to the high risk of hazard posed by improper PD exchange. It would be possible, however, for patients to undertake PD exchange technique assessments on a simulated dummy prior to the real task training, which minimizes the effect of real task training on the study result, and this is an approach that is recommend for consideration in future studies. Concerning the contents of the VR training program, improvements could be made through the provision of more detailed explanations of the rationale and precautions involved in each step of the PD exchange. This could enrich patients’ understanding and further enhance their learning experiences. In future, we can transfer the contents of the VR from using the Leap Motion hand tracking device to immersive head-mounted display based on the program written by Unity 3D. In addition, the findings of this study were based on a summative evaluation approach which focused on investigating the effectiveness of VR training on learning PD exchange by ESRD patient with cognitive impairment, in order to understand the successful elements as well as reasons of failure for further refinement of the intervention protocol, a formative evaluation approach is therefore suggested. Since the PD steps sequence test was developed based on the real task analysis and comments from an expert panel, it has the potential of becoming the “gold standard” for performance evaluation of PD exchange procedure, and further study on its standardization and validation is needed. Though an expert panel involving professional personnel and patients was formed to give comment and advice while developing the VR training program, a comprehensive process evaluation is important to understand any factor affecting the outcomes and reasons that induce discrepancies of expected and observed results, including the number of training sessions that can be done to perform the PD safely and independently, and to provide insights for further development.
Conclusion
PD exchange is a complex procedure requiring both accuracy and attention to safety concerns. Patients with cognitive impairments can encounter great difficulty in handling the task by themselves. The present study explored the application of VR training as a preliminary process for ESRD patients learning PD exchange and demonstrated its effectiveness in helping these patients to master the procedure sequence. While it is undoubtedly the case that patients must also acquire considerable skills and knowledge prior to a real task practice, we believe that the use of a non-immersive VR program, use of which is not constrained by considerations of time, space and manpower, and which is, more importantly, risk-free, should be fully adopted within clinical settings as an adjunct to conventional techniques for educating ESRD patients on PD exchange. Future studies, with larger sample sizes and a refined VR training program, are warranted to further examine the effect of VR training on cognitive function and the transfer of skills to real-life practice.
Acknowledgements
We thank the staff at the Division of Nephrology and the Department of Occupational Therapy at Queen Mary Hospital and Tung Wah Hospital for their collaboration in the study.
Funding
This research was partially funded by the Training and Research Assistance Scheme of Queen Mary Hospital, Hospital Authority, Hong Kong SAR (Reference Number: TRAS-18-03 (01/18/213)).
Data availability
Data cannot be made available for the reason of patients’ privacy in their consents for the study.
Declarations
Conflict of interest
All authors declared that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734863 | NO-CC CODE | 2022-12-14 23:28:31 | no | Virtual Real. 2022 Dec 3;:1-13 | utf-8 | Virtual Real | 2,022 | 10.1007/s10055-022-00728-1 | oa_other |
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Review
Covid-19 infection in children and adolescents and its association with type 1 diabetes mellitus (T1d) presentation and management
Karavanaki Kyriaki 1
Rodolaki Kalliopi 2
Soldatou Alexandra 1
Karanasios Spyridon 1
http://orcid.org/0000-0002-7993-8418
Kakleas Kostas [email protected]
2
1 grid.5216.0 0000 0001 2155 0800 Diabetes and Metabolism Unit, 2nd Department of Pediatrics, National and Kapodistrian University of Athens,“P&A Kyriakou” Children’s Hospital, Athens, Greece
2 First Department of Pediatrics, National and Kapodistrian University of Athens,“Aghia Sophia” Children’s Hospital, Athens, Greece
3 12 2022
116
28 10 2022
17 11 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Children seem to be affected by the new SARS-CoV-2 virus less severely than adults, with better prognosis and low mortality. Serious complications of COVID-19 infection in children include multisystem inflammatory response syndrome in COVID-19 infection (MIS-C), myo-or pericarditis and, less frequently, long COVID syndrome. On the other hand, adults with type 1 (T1D) or type 2 diabetes (T2D) are among the most vulnerable groups affected by COVID-19, with increased morbidity and mortality. Moreover, an association of SARS-CoV-2 with diabetes has been observed, possibly affecting the frequency and severity of the first clinical presentation of T1D or T2D, as well as the development of acute diabetes after COVID-19 infection. The present review summarizes the current data on the incidence of T1D among children and adolescents during the COVID-19 pandemic, as well as its severity. Moreover, it reports on the types of newly diagnosed diabetes after COVID infection and the possible pathogenetic mechanisms. Additionally, this study presents current data on the effect of SARS-CoV-2 on diabetes control in patients with known T1D and on the severity of clinical presentation of COVID infection in these patients. Finally, this review discusses the necessity of immunization against COVID 19 in children and adolescents with T1D.
Keywords
COVID-19
Diabetes
Children
Epidemiology
Pathogenesis
Complications
==== Body
pmcIntroduction
In December 2019 a novel infectious disease was identified in Wuhan, China, caused by a new coronavirus, which was named SARS-CoV-2. Ever since, the disease has spread throughout the world, and in March 2020 the World Health Organization (WHO) officially declared the Covid-19 Pandemic [1]. Although the disease presents mainly with respiratory symptoms, all systems of the human body can potentially be affected [1]. Countries all over the world took drastic measures to prevent the spread of the virus such as: hygiene measures (protective masks, keeping distances, hand washing on a regular basis), molecular and antigen diagnostic tests, detection of antibodies against the virus, quarantine and isolation at home, temporary lockdown of stores, schools and public services and most importantly vaccination against the virus. Despite the effect of the aforementioned measures on controlling the new pandemic, the disease continues to present in waves with variable severity and impact on humanity [2].
Although children and adolescents have been relatively spared by COVID-19 compared to adults, high-risk groups at risk of severe infection have been identified and pediatric complications, including MIS-C, myocardiac involvement, and long COVID syndrome have been observed [3]. Adults in general are more severely affected by COVID infection; this is particularly true for adult patients with diabetes of any type, obesity, metabolic syndrome (hypertension, dyslipidemia, impaired glucose metabolism), smoking, and other chronic conditions who are at increased risk of hospitalization and ICU admission, and have increased mortality rates [4].
SARS-CoV-2 has been reported to specifically bind to pancreatic β-cells, among other tissues, and to affect the development of new cases of diabetes (acute diabetes) or to accelerate the development of T1D or T2D [5]. There are conflicting results, however on the effect of COVID-19 pandemic on the incidence of newly diagnosed T1D, or acute DM in childhood. Moreover, there are limited data on the impact of COVID infection in children with known T1D, in terms on their glycemic control or the severity of COVID infection. Thus, to bridge these gaps the aims of the current review were to: 1. report on the incidence and severity of T1D among children and adolescents during the COVID-19 pandemic, 2. explore the types of newly diagnosed diabetes after COVID-19 infection and the possible underlying pathogenetic mechanisms, 3. describe the effect of the pandemic on diabetes control and on the severity of clinical presentation of COVID-19 infection in children and adolescents with known T1D, and finally, 4. highlight the necessity of immunization against COVID 19 in children and adolescents with T1D.
Methods
A literature search on three databases (PubMed, Google Scholar and Scopus) was conducted by two researchers independently. Keywords used were: “Diabetes mellitus type 1, pediatric, child, adolescent, COVID-19, SARS-CoV-2, epidemiology, pathogenesis, complications, pediatric diabetes, adults”. Limitations included: a. articles in English, b. patients aged 0–18 years, c. approved treatment for pediatric T2D, d. publication date between 01/01/2020-31/08/2022. Duplicates and pertinence were deemed according to title and abstract if available. Full-text articles for all relevant studies were reviewed. Following independent revision, the researchers met to resolve disagreement by discussion. In the absence of consensus, a third researcher would review the article.
Results
Literature search was performed in three stages (Table 1). A. Initially articles that were studying the epidemiology and complications of children and adolescents without diabetes and COVID-19, were searched in the databases. Of the 46 articles found, 25 articles were excluded (2 were duplicates and 23 were excluded by title and abstract) and 21 remained. B. Secondly, articles on children and adolescents with diabetes and COVID-19, epidemiology and complications were searched in the databases. Of the 56 articles found, 2 were excluded by abstract and title and 54 remained. C. Finally articles on adults with diabetes and COVID-19, epidemiology and complications were searched in the databases. Of the 36 articles found, 5 were excluded by abstract and title and 5 were duplicates; thus 26 remained. In total 101 articles were included in the references. After consideration, the two researchers agreed on the use of a total of the above 101 articles.Table 1 Prisma Flow diagram
Covid-19 infection in children and adolechents
1a) Clinical presentation of COVID-19 infection in childhood
Children and adults share the same possibility to be infected with COVID-19 [6]. Disease transmission in childhood usually occurs within the family or at school, while vertical transmission is rare [7, 8].
Many children remain asymptomatic, and as a group, even when symptomatic, they exhibit milder symptoms, shorter disease duration and better prognosis than adults. Children usually present similarly to adults with symptoms such as fever, rhinitis, fatigue, headache, muscle aches, as well as lower respiratory tract and gastrointestinal symptoms [9]. The commonest symptoms appear at a lower frequency than adults, i.e., fever (56% vs 71%), cough (54% vs 80%) headache (28% vs 58%), diarrhea (13% vs 31%) [10]. The clinical presentation of COVID-19 symptoms in childhood and its severity varies by age group. Among neonates, 12% have been reported to present in severe clinical condition and 40% of them with dyspnea. Among infants aged <12 months, 42.5% present with mild clinical symptoms, 39.6% moderate and 10.6% severe, with 2% of them treated in the ICU (death in 0.08%). Children older than one year of age and adolescents present with fever (51.6%), lower respiratory tract symptoms, i.e., cough (48.5%), pneumonia (64.9%), while severe clinical condition presents less frequently (2.5%) than infants, with 0.2% cases treated in the ICU and 1 reported death [9, 11].
A multicenter study from 82 hospitals in 25 European countries, including 582 children with COVID-19 infection, reported the absence of lower respiratory symptoms in 87% of children, the necessity for hospitalization in 62%, intensive care unit (ICU) treatment in 8% with a median patient age of 5 years, and the use of mechanical ventilation only in 4% of patients for a mean duration of 7 days [12].
Risk factors for ICU admission include: a) Age <1 month, b) male sex c) preexisting lower respiratory symptoms on admission [13].
1b) Risk factors for severe COVID-19 infection in children
Infants are at greatest risk for severe COVID -19 infection, with the respiratory system being mainly affected. This is attributed to the fact that infants have narrower airways, and at the same time the immune system is still immature; moreover, they may have a lower gene expression of the angiotensin converting enzyme-2 (ACE2) receptors [14]. There are also ethnic differences regarding the risk for severe respiratory system involvement from COVID-19. African and Hispanic populations are at greatest risk for acute respiratory distress syndrome. Children and adolescents with T1D, obesity, hypertension, immunodeficiencies, malignancies, chronic respiratory diseases (cystic fibrosis, severe asthma etc), and other chronic diseases are more susceptible to developing severe disease [13]. Moreover, among adolescents, pregnancy and smoking (even passive smoking) are additional factors for severe disease presentation. Moreover, genetic polymorphisms of angiotensin converting enzyme 2 (ACE2) gene have been associated with Multisystem Inflammatory Response Syndrome in Childhood (MIS-C) presentation [13]. Finally, patients with blood group A have been reported to have a 45% higher risk of Covid-19 infection, whereas those with blood group O have the lowest risk [15] (Table 2).Table 2 Risk factors for severe COVID-19 infection in children and adolescents (Sinaei et al 2020) [13]
• Age (<1 year). Race and ethnicity (Africans and Hispanic)-> Increased risk of P-ARDS
• Underlying diseases (congenital heart diseases, neurologic, genetic, metabolic)
▓ Diabetes Mellitus type 1 and 2, obesity
▓ Hypertension, cardiovascular diseases
▓ Immunodeficiencies, immunosuppression, malignancy
▓ Chronic respiratory diseases (cystic fibrosis, severe asthma)
▓ Chronic hematologic disorders (thalassemia, sickle cell disease)
▓ Chronic hepatic disease
• Pregnancy, smoking (incl. passive)
Key to Table 2:
P-ARDS pediatric acute respiratory distress syndrome, Incl including
1c. Severe conditions due to COVID-19 in children
Children infected with COVID -19 may rarely face certain critical conditions like multisystem inflammatory response syndrome (MIS-C) and the pediatric acute respiratory distress syndrome (P-ARDS), pericarditis, myocarditis and long COVID syndrome. The mortality rate of pediatric patients with P-ARDS has been reported to be very low, in contrast to that of adults with ARDS, which is very high (75%) [16].
Multisystem inflammatory response syndrome in COVID-19 infection (MIS-C)
The multisystem inflammatory response syndrome is an entirely new entity, affecting children and adolescents recently infected with COVID -19. The clinical manifestations of MIS-C include prolonged fever, hypotension, multiorgan involvement (at least two organs), increased levels of inflammatory markers, D-dimmers and ferritin. The differential diagnosis of MIS-C includes Kawasaki disease, toxic shock syndrome and secondary macrophage activation syndrome [17].
The pathophysiology of MIS-C can be explained by the binding of the coronavirus glycoprotein S to the T- lymphocyte receptors, which results in the creation of a new complex, called T-cell receptor (TCR). This process renders SARS-CoV-2 to act as a superantigen, which stimulates the activation of a severe inflammatory reaction with the release of numerous proinflammatory and anti- inflammatory cytokines [18].
Kawasaki disease, an angiopathy also occurring in childhood, has many similarities with MIS-C. However, it affects younger children aged 6 months–7 years, while MIS-C seems to affect older children and adolescents aged 7–20 years. Among other differences between MIS-C and Kawasaki disease, are the type and the level of inflammatory cytokines’ elevation. In particular, MIS-C presents with markedly increased TNF-a and IL-10, while Kawasaki syndrome is characterized by mild elevation of pro-inflammatory cytokines (IL-1, IL-2, and IL-6 but not IL-10). TNF-a seems to play a crucial role in the etiopathogenesis both of MIS-C and Kawasaki disease [17].
1e. Myocarditis and pericarditis associated with COVID-19 infection
Among the cells that SARS-CoV-2 is specifically attached to, are the cardiac myocytes. During the early phase of the disease (viremia), acute pericarditis, myocarditis, or cardiomyopathy related to sepsis may occur. During myocarditis, elevated levels of cardiac enzymes (troponin, NT-pro-BNP) as well as CRP and ESR levels are observed, accompanied by impaired ECG, 2D Echo Doppler and cardiac MRI. Delayed cardiac presentations include multisystem inflammatory syndrome in children and adolescents, coronary artery dilation or aneurysms, and late myocarditis, which may occur in the weeks following COVID-19 acute infection. During delayed presentations, PCR testing for SARS-CoV-2 is negative. Thus, these reactions seem to be due to a hyperinflammatory response following the viral infection. However, the long-term cardiac consequences COVID-19 are unknown. [19].
1f. Long term sequelae of COVID-19 in childhood
The range of long-term clinical conditions following COVID-19 in adults is well recognized. However, due to the paucity of long-term trials in childhood, the epidemiology and risk factors of long COVID-19 (or post-COVID-19 syndrome) in children are less understood. Thus, recent studies have shown that children with mild or asymptomatic SARS-CoV-2 infection may develop long-term symptoms, that include cough, fatigue, and lethargy. Additionally, it was observed that the epidemiology of common childhood respiratory viruses, such as respiratory syncytial virus (RSV) changed during the pandemic, while a type of hepatitis of unknown cause emerged in children with SARS-CoV-2 infection, possibly attributed to adenovirus type 41 [20].
These findings support the necessity of immunization programs for SARS-CoV-2 in children, and also infection surveillance on the epidemiology of other pediatric viral infections, such as adenovirus type 41 and RSV, in order to develop and administer relevant effective vaccines. Childhood immunization programs are being implemented globally to prevent the aforementioned direct and indirect medical consequences of COVID-19 including severe complications (e.g., MIS-C) and the long-COVID syndrome, as well as the indirect impacts of prolonged community and school closures on education, social and behavioral development, and mental health of children and adolescents. [21].
1g. Why children do not experience severe respiratory disease from COVID-19
Evidence suggests that children and adolescents are more likely to present with mild symptoms from COVID-19 infection and minimal involvement of the respiratory system. Different theories have been developed based on children’s unique characteristics, such as the presence of a large amount of immature T lymphocytes and the expression of few ACE2 receptors. On the contrary, adults with severe Covid-19 infection present with severe immune derangement, characterized by lymphopenia and extreme production of pro-inflammatory cytokines (cytokine storm), leading to a severe immune reaction in the second phase of the disease [14].
Covid-19 and diabetes mellitus in children and adolechents
Diabetes mellitus and obesity, which usually accompanies type 2 diabetes, constitute two serious risk factors for the development of severe COVID-19 infection, especially in adults. It has been observed that COVID-19 infection has an impact on the frequency and the severity of both newly diagnosed and existing diabetes. Specifically, COVID-19 infection has been associated with:A. Controversial effect on the frequency of newly diagnosed T1D in children and adolescents during the pandemic [22–24].
B. Notable increase in the frequency as well as the severity of diabetic ketoacidosis (DKA) during COVID-19 infection both at the time of T1D diagnosis, but also in the course of the disease [25].
2a. The prevalence of newly-diagnosed T1D during the COVID-19 pandemic
Most studies concerning the incidence of newly diagnosed T1D during the ongoing pandemic have conflicting results. Some studies report increased incidence [22], while others decreased [26] or unchanged incidence before and during the pandemic [23].
In a multicenter study from the United Kingdom including 30 children aged between 23 months and 16.8 years from March till June of 2020, a significant increase in the number of new cases of T1D and incidents of diabetic ketoacidosis (DKA) in comparison with the previous 5 years was observed [22]. Specifically, 70% of patients presented with DKA, of whom more than 50% had severe DKA. The prevalence of DKA in COVID-19 positive patients was higher compared to COVID-19 negative ones (80% vs 68%, respectively). Among the COVID-19 positive patients, three out of five encountered severe DKA with persistent hypokalemia, while one patient with severe hypokalemia presented with cardiac arrest, which was managed successfully in ICU [22].
A study of children with T1D registered to the Finish Diabetes Registry demonstrated that the incidence of newly diagnosed T1D increased from 38.7/100000 per year in 2016–2019 to 56.0/100 000 per year in 2020 with an IRR of 1.45 (95% CI 1.13–1.86) [26]. Nevertheless, none of the children who participated in the study tested positive for SARS-CoV-2 antibodies, hence this increase could not be attributed to the virus directly [26].
In a most recent study by Barett et al in the United States the diagnosis of new cases of diabetes in children younger than 18 years was 166% more likely to occur within 30 days post COVID-19 infection compared to those without COVID-19 during the pandemic [27]. It was also 116% more likely to occur in patients with COVID-19 compared to patients with other infections of the respiratory tract. The authors have attributed this increase to the effect of COVID-19 on the pancreatic b-cells. The limitations of this study included the low specificity in the definition of diabetes as it was based on the ICDM-10-CM code inserted in the registry, the lack of diagnosis confirmation for some patients classified as COVID positive and the non-examination of covariates, such as race/ethnicity, obesity and prediabetes status, that may have affected the association between COVID-19 and diabetes [27].
In another recent study by Shulman et al. [28] from data from the Canadian Diabetes Registry which included 2,700,178 children and adolescents aged 1–17 years, during the years 2017–2021, it was found that overall, during the pandemic, there was no difference in observed vs expected relative rates (RRs) of new diabetes presentations (RR, 1.09 [95% CI, 0.91–1.30]). However, RRs of new diabetes presentations decreased in the first 3 months of the pandemic (15–32% lower from March to May 2020), with a subsequent increase to higher-than-expected rates (33–50% higher between February to July 2021). The results of this study are very important as they come from one of the countries with the highest incidence of T1D and it includes epidemiological data on a large childhood population of a diabetes Registry. Nevertheless, these results should be confirmed by other large studies. Moreover, Tittel et al. reported no elevation in the frequency of T1D during the pandemic [23]. This study included data from 217 Pediatric Centers in Germany, from March 2020 till May 2020. The results revealed that the prevalence of newly diagnosed T1D during the first wave of the Pandemic in patients <18 years was 23.4/100.000 patient years, which did not differ significantly from the predicted incidence (22.1/100.000 patient years). Nevertheless, an increase in the incidence of T1D was found in boys (28.1 vs 23.1/100.00 patient years). The unchanged incidence of newly diagnosed T1D during the first wave of the pandemic and lockdown was attributed to the reduced incidence of most infections, which are important trigger factors for the manifestation of T1D [23]. Similarly, studies from Kuwait [29] and Canada [30] have found no increase in the prevalence of T1D new cases during the pandemic, compared to the previous years.
Finally, certain studies report a decreased frequency of COVID-19 infection in children with T1D. In particular, studies from China and Italy do not report cases of COVID-19 infection in patients with T1D [31]. The researchers attribute these results to [31]: 1) the younger age and the low prevalence of patients with T1D, 2) the increased protection measures against COVID-19 (quarantine) 3) and finally to the increased expression of CD8 + lymphocytes in T1D, which exerts protective effects against infections. CD8 + lymphocyte apoptosis is highly elevated in COVID-19 infection in adults, which leads to lymphopenia, a phenomenon that does not occur in pediatric patients. Nevertheless, pediatric patients with T1D are also infected by Sars-COV2 and some of them may need hospitalization, especially those with poor diabetic control [32].
2b) Frequency and severity of DKA during COVID-19 infection in children
Despite the questionable effect on the frequency of newly diagnosed T1D in children and adolescents of the COVID-19 pandemic, most studies concur that the pandemic has contributed to the increased frequency and severity of DKA during T1D diagnosis. This is confirmed by the study of Basatemur E et al from the United Kingdom [25]. The authors reported that 5 years before the pandemic a seasonal variation in the incidence of T1D was observed with an increase during winter and fall months and a reduction during summer and spring. A great reduction of T1D incidence was observed during the first wave of the pandemic. Regarding the incidence of DKA at diabetes diagnosis, the monthly distribution of DKA cases during the prior 5 years did not reveal any seasonal differences. Yet during the first wave of the pandemic, the frequency of DKA was increased [25].
Moreover, other studies from different countries have reported increased frequency of DKA in children with T1D during the pandemic [26, 27, 29, 30, 33]. Salmi et al. and Abdulrazaqq et al. have also reported an increased number of pediatric patients with DKA who required admission to the pediatric intensive care unit during the pandemic [26, 29], whereas Barret et al., Ho et al., and McGlaken et al. have also found an increased severity of DKA [27, 30, 33]. A meta-analysis of 20 studies showed that the risk of DKA and severe DKA was 35% and 76% higher in the COVID-19 era group compared to the prior to COVID-19 era group, respectively. Additionally, the risk of DKA in the newly diagnosed COVID-19 era group was higher (44%), compared to the prior to COVID-19 era group [34]. Two studies reported that the risk of DKA among T1D patients with established T1D was not significantly different during the pandemic, however it was noted that healthcare systems should take all necessary measures to prepare for an increase of DKA cases [34].
2c) Causes of increased frequency of DKA during newly diagnosed or former T1D
The increase in the frequency and severity of DKA in patients with T1D during the pandemic has been attributed to various factors such as the delay in diagnosis due to avoidance of hospital visits or due to the overload of Health Care systems [35], and also to the diabetogenic action of SarsCov2 virus [22] (Table 3). In more detail Salmi et al have reported that while ED visits were reduced by 45%, the diagnosis of DKA was delayed due to social distancing measures, the prioritization of COVID-19 infection control from the public health authorities and the parental fear of contracting COVID-19. McGlacken et al have highlighted that apart from the fear of COVID-19, other factors such as the limitations of remote patient consultations, the lack of appreciation by parents of the severity of the disease and the difficulties in accessing healthcare services have also contributed to the increased frequency and severity of DKA during the pandemic. The authors also stated that children from families with T1D had less severe DKA and reduced hospitalizations [30].Table 3 Causes of increased frequency of DKA for patients with newly diagnosed or preexisting T1D:
Α. Delay in the diagnosis of DKA in patients withs newly diagnosed T1D due to: [43]
• Parental avoidance of hospital visits due to the fear of getting COVID-19 infection, restriction of transportation during lockdown periods etc.
• Delayed medical diagnosis because of:
▓ Exclusive use of numerous hospitals for COVID-19 patients
▓ Overlapping of DKA and COVID-19 infection symptoms
• COVID-19 infection increases the risk for DKA due to an increase in insulin resistance
Β. Delay in the diagnosis of DKA in patients with preexisting T1D:
• Irregular follow-up by the Pediatric Endocrinologist → metabolic dysregulation
• Difficulties in acquiring insulin and diabetic expendable equipment (e.g blood glucose Test Strips and sensors, pump expendables)→ metabolic dysregulation
• Lifestyle alterations due to quarantine (decreased exercise, unhealthy diet)
• Online school courses (increased screen time)
Similarly, Abdulrazaqq et al. have reported that a family history of diabetes was associated with lower risk of presentation with DKA and admission to the PICU [29]. Ho et al. emphasize on the negative effect of medical staff redeployment and increased workload during the pandemic as well as the limitations of virtual clinics as causes for the increased frequency of DKA [30].
2d) The impact of lockdowns on diabetic control
Most of the studies from Europe and the USA agree that the quarantine had a beneficial effect on the diabetic control of children and adolescents with T1D [36–38]. According to these studies, the continuous glucose monitoring (CGM) devices yield better results in children and adults with T1D, while worse glucose levels were reported in adolescents. Furthermore, an improvement of metabolic control was reported in poorly controlled pediatric patients. Namely, the factors which contributed to this improvement of diabetic control were older age, stress, increased exercise, the use of CGM devices, the use of telemedicine and enhanced parental supervision of pediatric patients during the quarantine [36–38].
On the other hand, a study from Malaysia reported a deterioration in diabetic control due to the lockdown measures [39]. The study included 93 children and adolescents <18 years with T1D and 30 with T2D. Although an improvement in the metabolic control in children with T1D due to increased parental monitoring was reported, a deterioration of glycemic control during the quarantine was shown for male patients, adolescents and patients with T2D. This was associated with the reduced number of meals, the elimination of breakfast, reduced exercise, increased screen time, sleep deprivation, weight gain in patients with T1D, and weight reduction in patients with T2D, possibly due to the deterioration of their glycemic control. In conclusion, this study overall reported that the quarantine had a negative impact on glycemic control and the lifestyle of male patients, adolescents and patients with T2D [39].
Types of diabetes during covid-19 infection
COVID -19 infection has been associated with the development of certain types of DM (Table 4): a) triggering an acute newly-diagnosed DM in children, adolescents, and adults (which has also been reported with SARS-CoV-1 and MERS) [40] and is characterized by the lack of pancreatic autoimmunity. Furthermore, COVID-19 infection may b) accelerate the manifestation of newly diagnosed T1D or T2D [41], or c) provoke severe metabolic dysregulation and life-threatening DKA in preexisting or newly diagnosed T1D [42]. Finally, it is assumed that SARS-CoV-2 may d) induce pancreatic autoimmunity in patients, with the possibility of T1D manifestation even years later [43].Table 4 Types of diabetes after COVID-19 infection
A. Possible triggering of acute DM
B. Acceleration of newly-diagnosed diabetes manifestation (T1D or T2D)- development of severe DKA
C. In children with known T1D: severe metabolic derangement and DKA
D. COVID -19 infection possibly induces pancreatic autoimmunity in previously healthy children
Covid-19 infection and diabetes pathogenesis
Diabetes mellitus type 1 belongs to the family of autoimmune diseases, occurring in people with genetic predisposition. Pancreatic autoimmunity may be triggered by various environmental factors, such as viral infections, reduced sun light exposure, resulting to vitamin D insufficiency, as well as severe acute or chronic stress [44]. Factors including the enteric microbiota, early exposure to cow’s milk, early introduction of solid foods and cereals and increased birth weight have been increasingly recognized to play an important role in the development of pancreatic autoimmunity [45, 46]. On the contrary, exclusive breast feeding has been reported to have a protective effect against T1D development [45].
COVID-19 infection triggering acute DM
One type of T1D associated with the presence of viral infections is the acute diabetes type 1β-non autoimmune (fulminant) (90%). It is most commonly encountered among adults and it seems to be caused by direct lytic action of the virus on the pancreatic b-cells [47].
Most commonly, this type of diabetes is preceded by upper respiratory tract or gastrointestinal infections due to mumps virus, HHV6, HSV, Coxsackie B3-B4, hepatitis A, Influenza B, Parainluenza and recently SARS-CoV-2 etc. [48, 49]. Features of this type of diabetes include the presence of diabetic ketoacidosis, the short duration of symptoms (approximately 7 days), the absence of pancreatic autoantibodies, very low levels of endogenous production of insulin (C-peptide), increased levels of pancreatic enzymes and HbA1c < 8.5% at diagnosis [43].
Possible pathogenetic mechanism
SARS-CoV-2 infects and replicates in cells of the human endocrine and exocrine pancreas [50]. This has been confirmed by studies of autopsy samples, where the virus was found in β-cells [51]. The development of acute DM during COVID-19 infection can be explained by previous studies on SARS-CoV-1 virus, which has many similarities with SARS-CoV-2, published in the last decade [40]. The Angiotensin-converting enzyme 2 (ACE2) receptor is widely expressed in pancreatic β-cells and binds to SARS-CoV-1 and SARS-CoV-2 viruses. It was assumed that SARS-CoV-1 enters the pancreatic β-cells through the binding with the ACE2 receptor, which in turn results in cellular lysis. Lysis is facilitated through a) direct multiplication of the virus or b) circulatory antigens of the virus. The outcome is the development of transient diabetes. Studies in patients presenting with SARS-CoV-1 infection, have revealed an acute destruction of β- cells, without the presence of anti-pancreatic autoantibodies (T1D type 1B). The same mechanism may also underlie the action of SARS-CoV-2. Furthermore, pro-inflammatory cytokines produced during the infection, increase the expression of ACE2 in β-cells, and as a consequence enhance the susceptibility to COVID-19 infection [43, 52].
Moreover, Kazakou et al. in a recent review have reported that the SARS-CoV-2 virus may trigger the presentation of newly diagnosed diabetes mellitus, via a direct effect on pancreatic beta-cells [53]. In more detail, COVID-19 can have a direct cytolytic effect on β-cells, which in turn results in reduced insulin production and subsequent development of diabetes. Additionally, the virus results in the development of an immune response, with the release of chemokines and cytokines that affect pancreatic β-cells and impair their ability to sense glucose concentrations and release insulin. The cytokines produced may further affect the ability of liver, muscles, and other peripheral organs to uptake glucose [54]. This effect is mediated via the presence of ACE2 on the surface of β-cells, where the virus binds, which in turn results in inflammatory cytokine release, β-cell apoptosis, and decreased insulin secretion [55].
Additionally, ACE2 plays a crucial role in β- cell function and glucose homeostasis, according to studies in mice. A high fat diet may reduce the number of ACE2 receptors, while ACE2 deletion in diabetic mice promotes hyperglycemia, increases oxidative stress of β-cells, and reduces insulin secretion [56]. The angiotensin-converting enzyme 2/angiotensin (1–7)/Mas axis protects the function of pancreatic β-cells by improving the function of islet microvascular endothelial cells [57]. ACE2 deficiency reduces β-cell mass and impairs β-cell proliferation in obese C57BL/6 mice [58]. The above explain why the binding of SARS-CoV-2 on ACE2 receptors affects β-cell function and glucose homeostasis.
Acceleration of preexisting pancreatic autoimmunity
It is believed that the exposure to SARS-CoV-2 accelerates the development of ongoing T1D or T2D, through the release of cytokines and the activation of CD8 + T lymphocytes in people with a genetic predisposition, which leads to quicker destruction of β-cells (insulitis) and to earlier T1D or T2D presentation [22].
SARS-CoV-2 as a superantigen
The development of T1D with severe DKA, possibly occurs due to the action of SARS-CoV-2 as a superantigen [18]. Superantigens are produced during infection from bacteria (e.g., streptococcus, staphylococcus) or viruses (e.g., EBV, CMV, HIV). Superantigens induce the non-specific activation of T lymphocytes and the secretion of cytokines and interferon γ, which intensifies the secretion of cytokines. In this way, the superantigens cause a surge of proinflammatory cytokines, which lead to the development of multisystem inflammatory syndrome (MIS-C) [18]. MIS-C manifestation in patients with T1D occurs rarely [59].
COVID-19 infection and the pathogenesis of pancreatic autoimmunity
COVID-19 infection has been implicated in the development of pancreatic autoimmunity and subsequently T1D years after the infection.
The following mechanisms can theoretically explain the development of pancreatic autoimmunity [43]:A. Molecular mimicry
Viruses carry epitopes which are similar to the β-cell epitopes. Presentation of the viral epitopes by antigen presenting cells activate autoreactive T cells that bind to both self and non-self antigens and induce β-cell destruction [60].
B. Bystander activation
Viral infections, by evoking β-cell damage, promote the release of self-antigens, which are then presented via specific antigen presenting cells (APCs) to the CD4 + T lymphocytes in the local lymph nodes, triggering the production of pro-inflammatory cytokines, and causing not only the destruction of the affected by the virus pancreatic β-cells, but also of the adjacent healthy α and δ cells of the islets. The destruction of β-cells leads to inadequate transformation of pro-insulin to insulin, thus reduced insulin production [61]. This hypothesis can explain the beginning of the autoimmune process.
C. Chronic destruction of β-cells
Some viruses, such as CMV and possibly SarsCOV-2 [62] may cause a state of chronic inflammation (as it was revealed by studies in organ donors). The MHC-1 molecules are proteins existing on the cell surface and contribute to their identification from the immune system, especially from the T-lymphocytes and the natural killer cells (NK). During inflammation both type α and β-interferons are released in the circulation and activate the immune system. Chronic inflammation leads to chronic over-expression of MHC-1 and to continuous presentation of the destroyed β cells to the immune system, leading to pancreatic autoimmunity [62].
Clinical presentation and course of disease in patients with newly diagnosed DM during Covid-19 infection
Acute DM in adults during COVID-19 infection
There are a few case reports on acute DM during COVID-19 infection in the literature. Kuchay MS et al report on three cases of adult men (ages 30, 34, and 60), who presented with acute DM and DKA during COVID-19 infection [63]. All three patients were overweight, without other underlying conditions. One presented with bacterial pneumonia and severe DKA, while the other two had DKA of moderate severity.
At DM diagnosis, the patients had elevated levels of HbA1c: 9.6–12.6%, IL-6, ferritin and d-dimmers. The PCR SARS-CoV-2 was positive, while the anti-pancreatic autoantibodies (anti GAD) were negative. The patients were admitted to the Intensive Care Unit (ICU) and treated according to the DKA protocol, with intravenous fluids and insulin, while the patient with pneumonia received further antiviral factors (Remdesivir), empirical antibiotic treatment and corticosteroids. After DKA management, the patients were treated with sc basal/bolus insulin regime (4 injections/24 h), received diabetes education and were discharged in the third week after admission. Six weeks after the onset of symptoms, the total daily insulin dose was gradually reduced and patients were commenced on oral antidiabetic medication (metformin and sitagliptin), with further gradual reduction of insulin daily requirements. The eighth week, insulin treatment was discontinued and patients remained only on oral antidiabetic agents. Approximately three months later, they maintained optimal diabetic control (HbA1c: 6.2–7.4%) [63].
Furthermore, a study from Germany reported the case of a 19-year old male who developed insulin dependent DM and DKA without the presence of antipancreatic antibodies 5–7 weeks after symptomatic COVID-19 infection [47]. In conclusion, the three patients contracted COVID-19 infection in the stage of prediabetes or asymptomatic T2D, and they presented with symptomatic T2D and DKA via the acute cytotoxic action of the virus resulting in acute insulin insufficiency. After many weeks/months there was a gradual reduction in insulin requirements, and continued on oral antidiabetic medication as T2D patients. However, the fourth patient developed acute T1D after COVID-19 infection, due to the acute destruction of β-cells and was managed with basal/bolus sc insulin regime.
Children and adolescents with COVID-19 and newly-diagnosed T1D
Current literature describes four cases of newly diagnosed T1D in children and adolescents during COVID-19 infection [59, 64–66]. The patients were three males and one female, with ages ranging between 8 months and 16 years (Table 5). All patients reported a history of classic diabetes symptoms for 1–2 weeks before the diagnosis of T1D. They presented to the hospital with fever, dehydration, tachypnea and respiratory distress. All had elevated glycose levels (300–571 mg/dl), whereas two patients had severe and two mild DKA. One patient also presented with severe hypokalemia (K: 2.7 mEq/lt) which was treated with high doses of KCL. HbA1c levels were increased in all children, C- peptide was low, and all patients had elevated levels of anti-pancreatic autoantibodies. Two out of 3 patients presented with severe respiratory disease, and one of them also developed MIS-C. All children were treated according to the DKA protocol, while COVID-19 infection and its complications were treated appropriately (Table 5). The patient with MIS-C required high doses of sc insulin to achieve diabetes control (1.4 IU/kg/24 h) [59]. All patients were discharged from the hospital in a good clinical condition on a multiple daily injection insulin regime and their clinical course remained stable (Table 5).Table 5 Clinical presentation of T1D during COVID-19 infection in childhood
Authors Clinical presentation Laboratory testing Imaging Treatment Follow-up
Benyakhlef et al. [64] 3-year-old male, polyuria & polydipsia Glu: 300 mg/dl, pH:7.25, K:2.7 mEq/lt, PCT:3.4 ng/L, HbA1c:10%, anti-GAD: 60 U/ml (<5) Chest CT: Bilateral ground glass opacity and infiltrations IV insulin→ sc, IV fluids + KCL, high flow NC Ο2 Basal/bolus insulin regimen
Robazadeh et al. [65] 16-year-old male, polyuria, polydipsia, weight loss,
Τ: 38.2 ºC, SaO2:94%,
Glu:512 mg/dl, pH:6.9, HCO3: 8 mEq/lt, CRP:44 g/Lt, HbA1c: 8.5%, c-peptide: 0.25 ng/ml Chest CT: unremarkable IV insulin→ sc, IV fluids + KCL, hydroxychloroquine +Lopinavir /ritonavir Basal/bolus insulin regimen
Soliman et al. [66] 8-month-old male, lethargy, fever, tachypnea, dehydration Glu: 571 mg/dl, pH: 7.08, HCO3: 7 mEq/Lt, K: 5.6mEq/lt, HbA1c: 12.9%, CRP:4.2 g/L, anti-GAD:34 U/lt(<5), c-peptide: 0.43 ng/ml Chest X-ray: unremarkable IV insulin + IV fluids Basal/bolus insulin regimen
Naguib et al. [59] 8-year-old female, polyuria, polydipsia, conjunctivitis, cough, MIS-C Glu: 429 mg/dl, pH:7.3, HCO3:14 mEq/Lt, K:3.4 mEq/lt, CRP: 2.41 g/lt. Fibrinogen: 8.16 g/L,
D-dimers: 955 ng/ml, HbA1c:12%, SARSCoV2 IgG:9.7 (N < 0.7)
Chest X-ray: pleural effusions Sc insulin, total daily dose: 1.4 IU/kg/day, methylprednisolone: 1mg/kg BID, IVIG: 2g/kg, infliximab: 10 mg/kg Basal/bolus insulin regimen (dose 1.1 U/kg/day), HbA1c (in 1 month):7.8%
In bold are the abnormal laboratory testing results and imaging findings
The development of MIS-C in patients with T1D and DKA during COVID-19 infection is a rare complication and could be explained as follows: the increased levels of proinflammatory cytokines during severe DKA [67] may further be aggravated by the presence of COVID-19 infection, which also stimulates the release of numerous proinflammatory and anti- inflammatory cytokines, leading to the development of MIS-C [18].
The association of DKA with MIS-C implies that children may be vulnerable to the post-COVID-19 immunological and inflammatory side-effects [68].
Complications after Covid-19 infection and T1d in children and adolechents
Pediatric patients with newly diagnosed T1D during COVID-19 infection or with pre-existing diabetes may face the following complications:Increased frequency of severe DKA
Increased risk of severe and refractory hypokalemia during DKA
Increased risk of MIS-C during DKA (rarely encountered) [34].
The possible pathophysiological mechanism for the development of these complications are described as follows:
DKA pathogenesis during COVID-19 infection [34]
Impaired glycemic control and increased susceptibility to infections
Hyperglycemia alters normal immune response, resulting in the production of increased levels of proinflammatory cytokines, which are increased in parallel with the degree of severity of DKA [67]. This increase in turn leads to pro-inflammatory and pre-thrombotic state. Thus, there is elevated secretion of TNF-a, IL-6 and D-dimmers, increasing the risk of bacterial and viral infections (SARS-CoV-2) [42]. On the other hand, the glycosylation of ACE2 receptors (necessary for the entrance of the virus in the cells) is increased during prolonged hyperglycemia and subsequently enhances the vulnerability to SARS-CoV-2 infection. Therefore, the importance of optimal glycemic regulation is vital for the better management of COVID-19 infection [69].
Mechanisms of insulin resistance during COVID-19 infection
COVID-19 infection results in severe hyperglycemia due to an increase in insulin resistance. This results in massive secretion of proinflammatory cytokines (TNF-a, IL-1b, Il-6, MCP-1, C3), which are related to insulin resistance and subsequently leads to the development of DKA in patients with preexisting or newly diagnosed DM [70].
Furthermore, the inflammatory response which is triggered by the virus, induces the secretion of compensatory hormones (cortisol, adrenaline), which further aggravate hyperglycemia and activate the renin angiotensin-aldosterone-system (RAAS); this leads to β-cell destruction either by direct lytic action of virus to the cells or through the production of proinflammatory cytokines which is stimulated by the virus. In this way the manifestation of diabetes is accelerated during COVID-19 infection [71].
Thus, Boddu et al. [43] report that there is a two-way correlation between COVID-19 infection and diabetes. On one hand, the infection may cause acute β-cell destruction exacerbating the manifestations of ongoing T1D or T2D or resulting in the presentation of acute diabetes. COVID-19 infection also increases insulin resistance and leads to metabolic dysregulation and DKA in patients with preexisting diabetes. Additionally, COVID-19 can result in hyperglycemia in two possible ways. Firstly, the use of steroids or antiviral agents for the management of COVID-19 infection may occasionally cause transient hyperglycemia and insulin resistance [72] and secondly, the increase in the body mass index due to the pandemic lockdown measures [27]. On the other hand, in patients with diabetes and poor glycemic control, the susceptibility to COVID-19 infection is increased due to glycosylation of the ACE2 receptors, which are necessary for the viral entrance into the cells, resulting in reduced immune response of these patients [73]. Taking into account the global rise in diabetes prevalence, it has been reported that the two pandemics (COVID -19 and diabetes) interact with each other [74]. This situation highlights the importance of the optimal diabetic control for better outcome of the COVID-19 infection.
Mechanisms of severe hypokalemia during DKA in COVID-19 infection
Another complication encountered in pediatric patients with newly diagnosed T1D and DKA during COVID-19 infection is refractory and severe hypokalemia [75]. A case of a child with COVID-19 infection and newly diagnosed T1D and DKA, who developed cardiac arrest due to severe hypokalemia successfully treated in the ICU, was reported [22].
Refractory hypokalemia in patients with COVID-19 infection and DKA can be explained by the following mechanism: COVID-19 infection is associated with low expression of ACE2 receptors, leading to reduced degradation of angiotensin II and increased aldosterone production, which is accompanied by potassium loss in the urine. Urine potassium loss worsens the hypokalemia, that usually follows DKA and is due to the movement of potassium cations during metabolic acidosis from the extracellular to the intracellular space due to insulin administration [76]. This, in association with potassium urine loss, could result in severe hypokalemia during COVID-19 infection and the need for high doses of potassium chloride for its management [74].
The severity of Covid-19 in children with T1d in comparison with healthy children and adults with T1d
Increased mortality was observed in adult patients with diabetes and COVID-19 infection. In Italy, 35.5% of patients who died from COVID-19 infection had DM, a three times higher rate than the general population [77]. Patients with DM were admitted to the ICU 4 times more frequently (22.2% vs 5.9%, p = 0.009) and presented with ARDS 2.3 times more frequently (p = 0.002). Moreover, they had increased severity of COVID-19 infection, multisystem impairment and increased mortality comparing with the general population [77].
Risk for hospitalization in children with T1D and COVID-19
On the contrary, children, adolescents and young people with T1D (<25 years) seem to have a different course of COVID-19 infection compared to healthy people of the same age [78].
A study from Italy that included 15.500 children with T1D reported that only 11 were infected with SARS-CoV- 2 and none of them needed hospitalization [79]. According to two more studies from the USA and Spain including 755 and 734 children with T1D respectively, only a few children had COVID-19 infection (2 and 3, respectively) and one had severe disease requiring hospitalization [80]. Studies from Italy and China [79, 80] with increased COVID-19 infection incidence report on low infection rates in children with T1D. This has been attributed to: 1. The younger age of T1D patients, 2. The low prevalence of children and adolescents with T1D, 3. Increased measures for Covid-19 prevention in different countries (lockdown etc), 4. Increased expression of CD8 + T lymphocytes in T1D patients, which exerts a protective role during COVID-19 infection [79].
The frequency and severity of DKA in children with T1D and COVID-19 infection was reported in a study including 266 children <19 years old with known T1D from 46 Diabetes Centers in the USA [81]. From the total study population, only 61 children (22,9%) needed hospitalization. DKA was the most severe complication and was reported in 72% of hospitalized children. Other severe complications, such as severe hypoglycemia [only in three patients (4.9%)], were rare. Severe respiratory distress occurred only in three patients (4.9%), of whom two were intubated, one patient developed MIS-C and ten patients were hospitalized for other reasons [81].
This study identified risk factors for hospitalization in children with T1D and COVID-19 such as belonging to an ethnic minority, poor diabetic control (HbA1c:11% vs 8,2%, p = 001), and less frequent use of diabetes technology (insulin pumps or continuous glucose monitoring devices (CGM) (pumps:26% vs 54%, p = 0,001, CGM devices: 39% vs 75% p = 001) [81]. Therefore, they concluded that children with T1D do not have increased risk for hospitalization due to COVID-19 infection and when infected, usually do not present with severe disease like adults. However, poor glycemic control was the major risk factor for hospitalization in pediatric patients with T1D during COVID-19 infection [81, 82].
Why children with T1D are less severely affected by COVID-19 compared to adults?
As it is reported by Tatti et al., children with T1D seem to be protected against COVID-19 infection in comparison with the adult population [83]. This can be explained by the strong Th1 immunity in young ages, which is mainly proinflammatory and mediated through T-lymphocytes via the secretion of IL-6 and interferon γ, the principle mechanism of action against viruses (e.g SARS-CoV-2) [84]. Th1 immunity is also related to the pathogenesis of autoimmunity (i.e.,T1D, Hashimoto thyroiditis, celiac disease etc) [85]. On the contrary, Th2 immunity which is common in older ages, is mediated through B-lymphocytes and the production of antibodies [86].
Hence, the milder form of COVID-19 infection in children with T1D is attributed to the higher prevalence of Th1 against Th2 immunity. Furthermore, the overexpression of CD8 + lymphocytes in children encountered in T1D may also have a protective effect against COVID-19 infection [77].
Vaccination against COVID-19 in children with T1D
Vaccines have been developed to contribute to the fight against COVID-19 pandemic. To date two vaccines have received authorization for use in children, the Pfizer vaccine (from the age of 5 years) and Moderna mRNA vaccine (from 12 years) [87, 88]. The recommendations regarding vaccination of children against COVID-19 vary according to the country.
Although the duration and severity of clinical presentation of COVID-19 in children and adolescents is lower than in adults, there are rare severe complications, such as MIS-C, myo-or pericarditis and Long COVID syndrome [16–21]. Moreover, lockdown measures have negatively affected education and social development of children and adolescents [89]. Thus COVID-19 vaccination of those aged <18 years has been considered an additional measure for disease control [90].
The role of COVID-19 vaccine in patients with diabetes has been extensively reviewed and clinical data supports prioritization of adult patients with T1D or T2D for receiving the vaccine, as the infection has poor prognosis and is associated with more complications [91, 92].
Although children and adolescents with T1D do not present with severe clinical symptoms during COVID-19 in comparison with adult patients, they may present metabolic derangement and especially those poorly controlled, leading to DKA [21, 42], or very rarely MIS-C [59]. The side-effects of vaccination for pediatric populations are mild and more frequent after the second dose, without severe unfavorable outcomes [93]. Regarding the effect of COVID-19 vaccination in children and adolescents with T1D older than 12 years, it has been reported that it is safe, without significant effect on their glycemic control [94].
The various Pediatric Diabetes and Endocrine Societies have conflicting recommendations regarding COVID vaccination for children and adolescents. A study from the USA has recommended vaccination against COVID-19 in children to prevent the development of T1D associated with the disease [92]. The European Society for Pediatric Endocrinology (ESPE) does not recommend vaccination against COVID-19 in well controlled endocrine conditions, but only in those with poorly controlled T1D or those with severe obesity, who are at increased risk for severe disease [95].
The Israeli Pediatric Association has conducted a risk–benefit analysis regarding the vaccination of children and adolescents older than 5 years and concluded that vaccines are safe and effective and are recommended for all children aged 5 to 11 years to protect them from COVID-19 and its complications and to reduce community transmissions [96]. Similarly, the American Diabetes Association (ADA) follows the CDC recommendation to vaccinate all children aged 5 years and older [97, 98]. Moreover, a multi-model aggregation study suggests that, expanding vaccination to children 5-11 years old would be directly beneficial to this age group and indirectly to the all-age U.S. population, including protection against more transmissible variants [99].
Thus, based on the current reports on the risks and benefits of vaccination against COVID-19 in the pediatric age-group and the benefit of the prevention of disease transmission, it is concluded that vaccination against COVID-19 in childhood is safe and effective and is recommended for all children and adolescents older than 5 years, especially those belonging to the high-risk groups for severe disease, such as those with poorly controlled T1D, obesity, or other comorbidities.
Conclusion
This review summarizes the current data regarding the association of COVID-19 infection with diabetes in childhood. It seems that children present with milder disease and shorter duration than adults, better prognosis and low mortality. Serious complications of COVID-19 infection in children include MIS-C, myo-or pericarditis and, less frequently, long COVID syndrome.
There are conflicting results in terms of the prevalence of newly diagnosed T1D in children during the pandemic. Nevertheless, all studies agree that there is an increase in the frequency and severity of DKA during T1D diagnosis. The types of diabetes associated with COVID-19 infection include acute newly diagnosed DM, the acceleration of development of T1D or T2D and the development of pancreatic autoimmunity. Children with T1D are less severely affected by COVID-19 than adults, while a deterioration of glycemic control in both adults and children with known DM has been observed.
Thus, the best way to prevent severe COVID-19 infection among adult patients with known T1D is to improve glycemic control. Moreover, due to the association of COVID-19 infection with diabetes presentation, clinicians should be alert for the identification of signs and symptoms of diabetes during or after COVID-19 infection to make the diagnosis promptly and prevent the development of DKA.
Author contributions
“All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by K. Kakleas, A.R. and K. Karavanaki. The first draft of the manuscript was written by A.R. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.”
Compliance with ethical standards
Conflict of interest
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36462147 | PMC9734866 | NO-CC CODE | 2022-12-14 23:28:31 | no | Endocrine. 2022 Dec 3;:1-16 | utf-8 | Endocrine | 2,022 | 10.1007/s12020-022-03266-7 | oa_other |
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Indian J Otolaryngol Head Neck Surg
Indian J Otolaryngol Head Neck Surg
Indian Journal of Otolaryngology and Head & Neck Surgery
2231-3796
0973-7707
Springer India New Delhi
3206
10.1007/s12070-022-03206-x
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Kanchewad Resident Gajanan S. [email protected]
1
1 grid.466718.a 0000 0004 1802 131X Department of ENT, GMC Miraj, Miraj, Maharashtra India
2 Department of Radiology, GGMC and Sir J.J group of Hospitals, Mumbai, Maharashtra India
8 12 2022
18
8 7 2022
23 9 2022
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Aim: To assess the clinical improvement after single dose topical application of 1% clotrimazole cream in otomycosis and follow up for recurrence at the end of first and the third month. Materials and Methods: A prospective observational study was carried out at Government Medical college hospital. Patients with KOH diagnosed fungal infection of external auditory canal were included in the study. After obtaining informed written consent from the participating patients, a detail clinical history was taken. Single topical application of 1% clotrimazole cream in otomycosis. The fungal debris was removed with the help of suction aspiration and dry mopping. A single topical application of 1% clotrimazole cream was applied under all aseptic precautions. On the 3rd day the applied cream was cleaned with help of suction under ear microscope. Patients were advised to follow up after one month and three months. During each follow up patients were assessed clinically and examined for residual fungal debris. Result: Otomycosis was seen predominantly in middle aged females, housewives and laborers by occupation. Earache was most common symptom seen in 65.2%. Unilateral involvement was seen in 89.3% cases. The most common organism isolated in otomycosis was Aspergillus niger. At the end of one month of treatment with a single dose of 1% clotrimazole cream, 102 (91.0%) patients were recovered and 10 (9.0%) patients were with persistence or recurrence of the symptoms. At the end of third month, the recovery rate was 84.8% and recurrence rate was 6.3%. Conclusion: Single topical application of 1% clotrimazole cream is effective in treating otomycosis.
Supplementary Information
The online version contains supplementary material available at 10.1007/s12070-022-03206-x.
Keywords
External ear
Fungal infection
Otomycosis
Recurrence rate
Aspergillus.
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pmcIntroduction
Otomycosis is caused by saprophytic fungi. It is known to contribute 30% of ear infections globally [1]. Though the prevalence varies according to geographical regions, it is widely present in the tropics and also in the subtropical areas.
The clinical manifestations of otomycosis include pruritus, scaling, discharge, and pain [2, 3]. It is known to involve individuals in different age groups ranging from infancy to old age [4]. The common causative organisms include saprophytic fungi (70%) including Aspergillus spp. and Fusarium spp., yeasts (20–25%) and dermatophytes (5%) [5]. The majority of the cases report Aspergillus niger saprophytes and Candida albicans yeasts as the leading causative organisms in cases of otomycosis [6].
Its diagnosis is based on the isolation of fungi mycelium, pseudomycelium and yeasts from ear discharge, wax or the scrapes from the external auditory canal. The perfect investigation for the diagnosis of otomycosis must be a triple confirmation such as positive KOH smear, positive culture and clinical examination [7]. The specificity for culture in diagnosing otomycosis is 84.6% and the sensitivity is 87.5% [8].
The primary line of treatment depends on the type of fungus isolated and includes commonly used, antifungal agents. More recently, azoles in the form of topical ketoconazole, miconazole and clotrimazole have become the mainstay of treatment options for otomycosis. Single-dose topical clotrimazole cream has been largely used to treat otomycosis with variable success rates. Among topical antifungals, single dose topical clotrimazole cream appears to be a good treatment option [9, 10]. Usually, otomycosis is treated by antifungal drops but to prevent recurrence it should be used for at least three weeks. Patients with otomycosis are not willing for a longer duration of treatment. Additionally, it is convenient to the patient and does not require multiple visits to the hospital.
The purpose of this study is to evaluate the antifungal efficacy of a single application of topical clotrimazole cream for providing symptomatic relief and to assess its effectiveness in the prevention of recurrence of otomycosis.
Materials and Methods
A prospective observational study was carried out from 1 to 2020 to 30 July 2021 at the Government Medical college hospital. The study was approved by the Institutional Ethical Committee. Patients in 18 to 60 yrs age group with KOH diagnosed fungal infection of the external auditory canal were included in the study. Patients with a history of tympanic membrane perforation, vertigo, giddiness, immunodeficiency and known history of allergy to clotrimazole cream were excluded. After obtaining informed written consent from the participating patients, a detailed clinical history was taken.
A clinical diagnosis of otomycosis was made after visualization of cotton woolly mass, black mycological plug and soft debris in the external auditory canal. Specimen of the aural swab (fungal debris) was collected with a sterile cotton swab. Each sample was divided in to two parts. One part was directly examined under a microscope with 10% KOH whereas the second part was mounted on Sabourad dextrose agar with 0.05 mg/ml of chloramphenicol. After confirmed by fungal culture, patients were thoroughly examined under an ear microscope for fungal debris.
The fungal debris was removed with the help of suction aspiration and dry mopping. A single topical application of 1% clotrimazole cream was applied under all aseptic precautions. Any irritation, redness and swelling in the external auditory canal after application of cream were noted. On the 3rd day, the applied cream was cleaned with help of suction under an ear microscope. Patients were advised to follow up after one month and three months. During each follow-up visit the patients were evaluated for resolution of symptoms. Patients were examined under ear microscope.
Successful treatment outcome was defined as resolution of all symptoms as well as the absence of fungal infection on otoscopic and microscopic examination.
Results
The present study 112 otomycosis patients were included.
Age
In the present study, 87 (77.6% ) of the patients were below the age of 50 years, 26 (23.3%) cases were among the age group of 31–40 years, 25 (22.3%) were among the age group of 21–30 years and 24 (21.4%) cases were among the age group of ≤ 20 years. The mean age of the study participants was 36.1 years.
Gender
In the present study, 67 (59.8%) were females and 45 (40.2%) were males. (Fig. 1)
Fig. 1 Sex distribution in study group
Occupation
In the present study, 49 (44%) were housewife, 23 (20%) were labourer, 18 (16%) were students, 13(12%) were businessmen and 9 (8%) were farmers by occupation.
Presenting Complaints
In the present study, the commonest presenting complaint was pain in the right ear in 70 (65.2%) patients (Table 1).
Table 1 Distribution in study group as per presenting complaints
Presenting Complaints Number Percentage (%)
Pain in right ear 70 62.5
Itching in left ear 32 28.6
Aural fullness in right ear 32 28.6
Aural fullness in left ear 27 24.1
Itching in right ear 25 22.3
Pain in left ear 23 20.5
Itching in both ear 9 8
Aural fullness in both ear 8 7.1
Pain in both ears 8 7.1
Decreased hearing in in right ear 7 6.3
Wax
In the present study, only 6 (5.4%) patients showed the presence of wax along with fungal infection, 106 (94.60%) showed only of fungal debris in the external ear canal on otoscopic examination.
Laterality Distribution
In the present study, unilateral involvement of otomycosis was seen in 100 (89.3%) patients. Among them 61 (54.5%) patients were of right side and 39 (34.8%) patients were of left side. Bilateral involvement was seen in 12 (10.7%) of them.
Fungal Distribution
In the present study, the most common organism isolated was Aspergillus niger, seen in 52 (46.4%), candida albicans in 36 (32.1%), Aspergillus fumigatus in 17 (15.2%) and Aspergillus flavus in 7 (6.3) patients (Table 2).
Table 2 Distribution in study group according to isolated organisms
Isolated organisms Number Percentage
Aspergillus niger 52 46.4
Candida albicans 36 32.1
Aspergillus fumigatus 17 15.2
Aspergillus flavus 7 6.3
Total 112 100
Symptoms at the end of One Month
In the present study, at the end of one month, patients with persistent symptoms were 10 (9.0%), patients without fungal debris and asymptomatic were 102 (91.0%) (Fig. 2).
Fig. 2 Distribution of cases according to symptoms at the end of one month
Symptoms at the end of Three Months
In the present study, at the end of three months, 10 (8.9%) patients were symptomatic and 95 (84.8%) patients were asymptomatic. Hence the recurrence rate at the end of the third months of treatment was 6.3% (Fig. 3).
Fig. 3 Distribution of cases according to symptoms at the end of three months
Discussion
Otomycosis is worldwide in distribution with prevalence ranging from 9 to 30% among the patients presenting with signs and symptoms of otitis externa and discharging ear. [1] High incidence can be attributed to a high degree of humidity, heat and a large proportion of the population doing outdoor labour and low socioeconomic status. Other contributing factors might be habits such as cleaning the ear with a match stick, contamination by fingertips and installation of oil in the ear [11].
Age
Kaur R et al. (2000) and Zaror L et al. (1991) explained in their study that Otomycosis usually occur more frequently in adults and less in children [11].
According to the study by Mgbe R et al. [12], 33.8% of the otomycosis patients were in the 21–30 years age group.
According to Ozcan K.M et al., otomycosis was seen commonly among the 31–60 Year age group, probably due to religious practice of head coverings as a predisposing factor [13]. Studies conducted by Kiakojuri K et al. (2019), Gharaghani M et al. (2015), Anwar K, and Gohar MS (2014) also showed that incidence of otomycosis was prevalent in the age group 20–40 years [14],[15],[16].
In the present study, fungal infection was more common in the middle age group. 75 (66.7%) cases in the present study were among the 18–40 years age group. This could be explained by the fact that this age group is the active age group in the outdoor environment leads to more exposure to several predisposing factors for otomycosis such as tropical climates with high humidity and high temperatures [13, 17].
Gender
According to Yehia MM et al. (1990) study, the incidence of otomycosis was found more among females. [18] Ozcan K M et al. study showed a higher incidence of otomycosis in females (80.5%) [13]. A study conducted by Pradhan B et al. (2003) shows that otomycosis occurs more commonly in females [19]. According to Ho T et al. (2006) study, females were more often affected by otomycosis [2]. Female preponderance was observed in studies conducted by Aneja K R et al. (2010) [20] and Fasunla J et al. (2008) [21].
In the present study, 67 (59.8%) females and 45 (40.2%) males were with otomycosis which indicates female predominance. Housewives and fields workers, working in damp, cold conditions in houses and fields lead to exposure to dust and deposition of fungal spores. The unhygienic practice of self-cleaning the ear canal with dirty fingers, hair pins and match sticks hastens the deeper invasion of the fungus.
Occupation
A study conducted by Yehia MM et al. showed that housewives frequently clean and sweep the floor of their houses [18] and the resulting dust containing fungal spores mixed with the air of the atmosphere to act as predisposing agent for the initiation of the disease.
In the present study, 44% of cases were Housewives living in villages and towns with the cold damp working atmosphere in kaccha houses. The next group of highest cases was labourers (20%) in environments like machinery and moving parts of machines which generate heat and prepare the ground for ideal hot humid and dusty conditions for initiation of the disease. Students who play sports were exposed to a similar environment.
Presenting Complaints
According to studies conducted by Mohanty JC et al. (1999), 94.4% of patients had pain as the presenting complaint and 92.5% of patients had itching [22]. Also, studies by Nwabuisi C, Ologe FE and Kombilla M et al. showed otalgia and pruritis as the most common symptoms [23, 24]. In the study carried out by Pradhan B et al. (2003), the predominant complaints were itching and ear discharge, followed by earache, ear blockage, hearing loss and tinnitus [19]. In a study conducted by Ho T et al. (2006), otalgia was reported as the major symptom followed by otorrhoea and hearing loss [2]. Studies conducted by Jimenez-Garcia L et al., (2019) [25] also described pruritus, diminished hearing and discharge as the major clinical symptoms in cases of otomycosis. The fungal hyphae cause irritation of the ear canal leading to itching and fullness in the ear. The mechanical blockade caused by the fungal hyphae as well as the debris and wax accumulated in the ear canal in the case of otomycosis was the cause of hearing loss. Nevertheless, typically, these symptoms are also observed with a few differences in other kinds of bacterial infections of the ear as reported in a study by Bineshian F et al. (2006) [26].
In the present study, pain in the ear was commonest presenting complaint. 83% of patients were presented with pain in the ear. 52.7% of patients were presented with aural fullness. 50.9% of patients were presented with itching and 6.3% of patients were presented with decreased hearing.
Wax
A study conducted by Gutierrez PH et al. (2005) and Oliveri S et al. (1984) showed that Antimycotic and bacteriostatic properties of secretions of the apocrine and sebaceous glands (cerumen) protect the healthy ear from invading organisms and fungal infections occur after the damage of these glands by bacteria or some other agents. Therefore the absence of cerumen increases the chances of fungal and bacterial infections [27]. According to a study conducted by Kaur R et al. (2000), presence of excessive cerumen in patients with poor personal hygiene favours the germination of spores and conidia [11].
Scratching of the ear canal in order to remove the cerumen and to get relief from itching can cause minor trauma in the skin of EAC which may get deposited by fungal spores that later on germination can cause fungal infection.
In the present study, only 6 (5.4%) patients showed the presence of wax in the external auditory canal on otoscopic examination whereas, all the cases showed the presence of debris in the external ear canal on otoscopic examination. In the present study, the presence of cerumen in the ear canal was seen in 5.4% which was similar to other studies conducted by Adegbiji, W A, et al. (2014) [28] and Czechowicz JA, et al. (2010) [29].
Laterality Distribution
Otomycosis is commonly unilateral disease. A study carried out by Anwar et al. (2014), was found that unilateral involvement was commonly seen in otomycosis [30]. According to a study conducted by Nowrozi H et al. (2014), otomycosis was mainly reported as unilateral in immunocompetent patients [31]. A study conducted by Yehia MM et al. (1990) and Aneja KR et al. (2010) reported that a major chunk of unilateral ear involvement with the right side was more common possibly because it was on side of the dominant hand [18],[20] However, Prasad SC et al. (2014) mentioned that 5% of cases were bilateral [32].
In the present study, unilateral involvement of otomycosis was seen in 100 (89.3%) patients. Among them, 61 (54.5%) patients were on the right side and 39 (34.8.0%) patients were on the left side. Bilateral involvement was seen in 12 (10.7%) of them.
Fungal Distribution
Though otomycosis is multifactorial with several etiological agents responsible for it, the commonest one being fungi. Among the fungi causing otomycosis, Aspergillus niger and Candida albicans are by far the most common offenders [6]. Aneja KR et al. (2010) observed that Aspergillus was a ubiquitous mould identified as the causative organism in various infections and diseases. Aspergillus can be found in the form of minute conidia that can be easily propelled into the air with dust and other particles, making this its primary route of transmission [20]. Beany and Broughton (1967) found that Aspergillus species produce antibiotics, which eliminate bacterial competitors. This could be attributed to the fact that Aspergillus more common than candida in the isolates [33].
The studies conducted by Chander J et al. (1996), Mohanty JC et al. (1999), and Yassin A et al. (1998) showed that, Aspergillus spp were the most common fungi isolated, followed by C albicans [22]. In the present study, Aspergillus niger was the commonest causative organism observed in 52 patients (46.4%) and Candida albicans in 36 patients (32.1%) which is similar to the above studies. Aspergillus fumigatus was seen in 17 patients (15.2%) and Aspergillus flavus was seen in seven patients (6.3%).
Treatment of Otomyosis with 1% Topical Clotrimazole Cream
As per Malik AA et al. (2012) and Ologe FE et al. (2002), clotrimazole is the most widely used topical azole [34, 35].
Regarding antifungals, the imidazole group showed an 80% resolution rate in the initial application with a scant probability of recurrence according to the Malik study [34]. According to Jadhav VJ et al. (2003), Malik AA et al. (2012), and Ahmed Z et al. (2010), clotrimazole was considered free of ototoxic effects [34, 36, 37]. Studies by Munguía R (2008), Jadhav VJ et al. (2003), Khan F et al. (2013) and Vega-Nava CT et al. (2015) reported effectiveness rates of clotrimazole between 50–100%36, [38–40].
According to Dundar R and Iynen I, the efficacy of single dose clotrimazole 1% was good for the treatment of otomycosis [41]. Jackman A also states Clotrimazole as the most popular and effective treatment [42].
In the present study, at the end of the first month after treatment with a single dose of 1% clotrimazole cream, 102 patients (91.0%) and at the end of 3 months 95 patients (84.8%) were relieved of their symptoms. The present study showed significant relief of symptoms with a single dose of 1% clotrimazole cream in otomycosis at the end of first and third months of follow-up.
In the present study, 84.8% of patients had a significant reduction of symptoms at the end of the first month. This is in accordance with a study conducted by Paulose KO, et al. (1989) who found improvement in the range of 89% by using clotrimazole [43]. The study conducted by Jia X et al. (2012), Anwar K (2014), Nemati S et al. (2014) and Naqi S et al. (2014) reported that a treatment failure rate between 9–17% [44–47]. In the present study, the recurrence rate was 6.3% at the end of 3 months of follow up with a single dose of 1% clotrimazole cream application. This failure can be attributed to factors such as resistance of the causative organism, comorbidities, non-compliance to therapeutic course, genetic variations, surgery or use of hearing aids etc. A study by Kazemi et al. (2015) reported lower relapse rates with a recurrence observed in only 3.1% [48]. This may be due to the factors such as younger populations in studies and a lack of other predisposing factors in study populations. Higher otomycosis relapse rates of 48% were also reported by Anwar K (2014) studies [45]. Majority of the relapses were observed in those with concomitant inflammation and ulceration of the ear canal and tympanum. Therefore, 1% clotrimazole cream for a single local application is highly effective in not only treating otomycosis but is also effective in the prevention of relapse.
Conclusion
A single dose topical application of 1% clotrimazole cream in patients of otomycosis saves both time and cost, and is effective in treating otomycosis.
Limitations of the Study
Long term follows up and large number of study population was not possible due to Covid 19 pandemic.
Electronic Supplementary Material
Below is the link to the electronic supplementary material.
Supplementary Material 1
Supplementary Material 2
Supplementary Material 3
Supplementary Material 4
Supplementary Material 5
Acknowledgements
We acknowledge department of microbiology, GMC, Miraj, Maharashtra, India.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
All procedures performed in studies involving human participants were in accordance with ethical standards of the institutional ethical committee as per ICMR guidelines and University protocol by letter. No. GMCM/IEC-C 30 /2019 and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent
Informed consent was obtained from all individual participants included in the study.
Consent for Publication of data
Informed written consent for publication of data was obtained from all individual participants included in the study.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Sims Belinda 2
Colpe Lisa 2
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2 grid.416868.5 0000 0004 0464 0574 National Institute of Mental Health (NIMH), Bethesda, USA
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25 11 2022
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Notable increases in youth mental health problems combined with strains on the already stretched mental health workforce raise concerns that there will be an ensuing increase in youth suicide thoughts, behaviors, and even deaths. Schools are recognized as crucial settings for youth mental health support and suicide prevention activities, yet schools also face staff shortages and ever-increasing responsibilities for student well-being. Evidence is emerging that prevention programs originally designed to improve problem-solving skills and social-emotional functioning in youth have demonstrated downstream, “crossover effects,” that is, unanticipated benefits, on youth suicidal behavior. Relatively little research on crossover effects has been conducted within school settings, despite the strong potential for commonly administered programs to have an impact on later suicide risk. We review key suicide risk factors and their proposed mechanisms of action; we also discuss factors that may protect against suicide risk. We then identify upstream prevention programs targeting the same factors and mechanisms; these programs may hold promise for downstream, crossover effects on youth suicide risk. This paper is intended to provide a framework to help researchers, practitioners, and policymakers as they consider how to prevent youth suicide using existing school-based resources. Rigorous investigation of upstream prevention programs is urgently needed to determine ideal approaches schools and communities can deploy to prevent youth suicide.
Keywords
Youth
Suicide
School
Prevention
Crossover
Upstream
http://dx.doi.org/10.13039/100000025 National Institute of Mental Health R21MH128522 Ayer Lynsay
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pmcIntroduction
Following a stressful 3 years of the COVID-19 pandemic including remote or hybrid schooling, many are concerned that observed increases in youth mental health problems combined with strains on the already stretched mental health workforce (Health Resources & Services Administration, 2022) and will result in an increase in youth suicide deaths (Curtin et al., 2021; Diliberti & Schwartz, 2022; Office of the Surgeon General, 2021). While overall youth suicide deaths remained relatively stable from 2019 to 2020, it is too soon to tell whether that pattern will hold, and for whom (Ehlman et al., 2022). Concerning suicide rates among certain groups of youth suggest the pandemic may exacerbate risk. For instance, populations of marginalized youth, such as American Indian/Alaska Natives, have had elevated risk for decades (U.S. Senate, 2015). From 2014 to 2019, Asian or Pacific Islander and Black youth aged 15–24 experienced increases in suicide rates over time, whereas White youth did not (Ramchand et al., 2021). Bridge and colleagues (2018) reported that the suicide rate (2001–2015) in Black children aged 5 to 11 was twice the rate of White children (Bridge et al., 2018). The pandemic has hit these same communities particularly hard (Rossen et al., 2021), and the resulting effects of trauma and loss may add to existing risk. In addition, there are signs the pandemic may have exacerbated suicide risk for adolescent girls. Emergency department data show an increase in visits for suspected suicide attempts for adolescent girls during 2020 and 2021 relative to the same time periods in 2019; rates among boys remained stable (Yard et al., 2021). Sexual and gender minority (SGM) youth were also at elevated risk for suicide thoughts and behaviors prior to the pandemic compared to non-SGM youth (di Giacomo et al., 2018). For some SGM youth, isolation from support systems and living within unsupportive family environments during pandemic-related school closures may have compounded risk (Ormiston & Williams, 2022).
Schools are increasingly recognized as crucial settings for youth mental health support and suicide prevention activities, with recent data from the National Survey on Drug Use and Health (NSDUH) showing that very similar proportions of youth receive mental health care from schools as from outpatient mental health settings (Ali et al., 2019). Specifically, 35% of adolescents (ages 12–17) received mental health treatment in a school setting only; 23% received treatment in both school and non-school settings; and 42% received treatment in a non-school setting (e.g., specialty or general medical setting) (Ali et al., 2019). Even before the COVID-19 pandemic, state and federal legislatures enacted policies requiring schools to enhance and broaden suicide prevention training and programming, such that 13 states now require all school staff to have at least annual training in suicide prevention (American Foundation for Suicide Prevention, 2020). Schools are particularly important resources for racial and ethnic minority and low-income youth with mental health needs and suicide risk, with these groups significantly more likely than White and higher-income youth to receive treatment only in educational settings (Ali et al., 2019).
With an influx of additional funding from the American Rescue Plan and other federal, state, and local pandemic funding packages, many schools have found that they have increased financial resources to bolster their suicide prevention efforts. However, suicide is not the only behavioral health issue schools are tasked with addressing. Schools must also respond to multiple, simultaneous problems ranging from attention-deficit hyperactivity disorder (ADHD), posttraumatic stress disorder (PTSD), and depression to substance use and risky sexual behavior. Due to the pandemic, schools are also addressing new or exacerbated challenges like learning lags related to remote schooling, food insecurity, COVID-19 testing, masking and vaccination policies, and a lack of consensus on school curricula (Diliberti & Schwartz, 2022). It is not surprising that with this “perfect storm” of pressing issues and responsibilities, on top of the already challenging task of providing a high-quality academic education to children, school staff well-being has decreased, and mental health problems are more concerning than ever (Diliberti & Schwartz, 2022).
As schools consider effective and feasible suicide prevention efforts in this context, it is important to determine how and whether existing school mental health programs may already be addressing suicide risk (e.g., efforts that can prevent mental health problems and self-injurious thoughts and behaviors from happening in the first place). Prior research shows that mental health interventions designed to target emotional and behavioral problems that share risk factors with youth suicide can also help to decrease suicide thoughts and behavior (STB). For instance, interventions originally designed to decrease substance use or depression in youth have demonstrated “crossover effects,” i.e., unanticipated benefits, for youth suicidal thoughts (Connell et al., 2019; Kerr et al., 2014; Sandler et al., 2016; Vidot et al., 2016). For example, a study on the long-term impact of the Good Behavior Game (GBG), a program for elementary-aged children designed to prevent risky behavior and aggression by improving problem-solving skills and social-emotional functioning, observed a reduced risk for suicidal thoughts and behaviors in young adulthood (ages 19–21) among intervention groups compared to control groups (Wilcox et al., 2008). Besides this GBG example, however, relatively little research on crossover effects has been conducted within the school setting, despite the strong potential for many common programs to have an impact on later suicide risk. For instance, social-emotional learning (SEL) is now a common component of most elementary school curricula and is intended to strengthen youth capacities like emotion regulation and social connectedness, which are both factors that protect against suicide risk (Wyman, 2014). If such programs are proven to be effective in reducing or preventing STB, this could have a major impact on the approach and resources that schools leverage. Rather than funding, implementing, and testing new suicide prevention initiatives, schools could save money, time, and potentially lives, by enhancing and expanding existing school-based programs demonstrating crossover effects on suicide risk.
The goal of this paper is to provide a roadmap for future research to test whether existing school-based programs have crossover effects on STB (defined to include self-harm with and without suicidal intent). First, we review some of the key suicide risk factors and proposed mechanisms of action. We also discuss factors that protect against STB. It is important to highlight, as Cha and colleagues (Cha et al., 2018) do, that the current suicide literature is often inconsistent in its use of operational definitions and terms, including terms such as “factor” and “mechanism.’ To eliminate any potential confusion caused by those inconsistencies, we have included operational definitions and adhere to them in the discussion below. Such consistent use of terminology could aid the field in disseminating clear and consistent syntheses and recommendations. For the purposes of our discussion, risk factors are those environmental, biological, or psychological factors associated with a higher likelihood of experiencing suicidal thoughts and/or behaviors but—due to lack of evidence—cannot be assumed to directly cause those thoughts and behaviors. In contrast, protective factors are associated with a reduction in STB. A mechanism is the process by which a certain set of factors leads to (or protects against) suicide risk.
Upstream prevention programs targeting such factors and mechanisms may hold the most promise for having downstream, crossover effects on youth suicide risk. Using SEL programs as one example to illustrate this point, Fig. 1 shows how an elementary school SEL program could have unanticipated benefits for reducing later STB. We will assume that the evidence-based SEL program has its intended impact on improving students’ ability to regulate their emotions when faced with stressful situations. Meta-analysis shows that these impacts can be observed years later, into adolescence (e.g., middle school) (Taylor et al., 2017). Because emotion regulation skills deficits are thought to be central to youth STB risk (Miller & Prinstein, 2019)—and in fact are the primary target of evidence-based treatments for youth with STB (Asarnow et al., 2021)—we would then expect those strong emotion regulation skills developed through SEL programming in elementary school to ultimately result in lower risk for STB in later years.Fig. 1 Example of how existing programs could have crossover effects on youth suicide risk
Next, we summarize the state of the science on three common types of school-based programs that target some of these same factors and mechanisms: (1) SEL programs, (2) substance use prevention programs, and (3) cultural affirmation programs designed to enhance a sense of cultural pride and belonging for marginalized youth. Because “upstream” prevention is likely to yield the most widespread and cost-effective benefits for youth and schools (National Institute on Drug Abuse, 2016; Robertson et al., 2016; Substance Abuse and Mental Health Services Administration & Center for Substance Abuse Prevention, 2008), we do not cover clinical treatment interventions (e.g., cognitive behavioral or dialectical behavioral therapy). We also focus this review on school-based programs from pre-K through 12th grade. For a review of suicide prevention in the college setting, we refer readers to two other recent papers (Black et al., 2021; Wolitzky-Taylor et al., 2020).
Contemporary Theories of Suicide, Mechanisms of Risk, and Targets for Intervention
Suicide and suicide thoughts and behavior are rarely explained by one single factor and most contemporary theories of suicide acknowledge some interaction between one or more biological, environmental, social, and/or psychological factors. In a review of the research on youth suicide risk factors, Cha et al. (2018) found evidence supporting several risk factors for youth STB in the domains of demographic characteristics (e.g., age, gender), environmental factors, psychological factors, and biological factors (Cha et al., 2018). Schools are most likely to be able to modify environmental and psychological risk factors, so we focus on those here. Cha et al.’s (2018) review found that psychological STB risk factors with moderate to strong evidence included feeling worthless, low self-esteem, hopelessness, lack of positive affect (anhedonia), emotion dysregulation and maladaptive coping, impulsivity, and loneliness/lack of social connectedness. Two environmental factors also demonstrated strong associations with youth STB: child maltreatment and bullying. One mechanism by which child maltreatment and bullying might impact the development of youth STB is through the aforementioned psychological factors (Cha et al., 2018; Miller et al., 2013). For example, youth who are abused by their caregivers or bullied by their peers may feel worthless, lonely, disconnected from their family and friends, and experience mental health symptoms and negative emotions like sadness, anger, and anxiety that are difficult to manage (Hertz et al., 2013; Miller et al., 2013).
Building upon the foundational review by Cha et al. (2018), school-based suicide prevention research and practice should also be guided by empirically supported theories about the mechanisms by which the aforementioned risk factors impact youth STB. In Table 1, we briefly describe risk factors and mechanisms of risk for some of the most common contemporary theories of suicide and highlight corresponding targets for preventive interventions. Where available, we highlight findings from applications of these theories to youth. Of note, none of the theories in the table below have been tested with children younger than 12 years old. While aspects of these theories may also apply to younger ages, additional work is needed to develop and test them.Table 1 Suicide theories, mechanisms of risk, and intervention targets
Name of theory Mechanisms of suicide risk Intervention targets Research with youth
Interpersonal-psychological theory of suicidal behavior (IPTS) (Van Orden et al., 2008) When individuals who feel disconnected from others or lack strong interpersonal relationships (i.e., thwarted belongingness) experience and event that makes them feel like they are a burden to others (i.e., perceived burdensomeness) they may exhibit suicidal thoughts and behaviors Cultivating a sense of belonging
Strengthening relationships with peers, family, other social groups (e.g., school staff)
Evidence for IPTS in adolescents not as strong as adult studies; central constructs of IPTS may hold in adolescents, though pathways are likely different (Stewart et al., 2017)
Acute stress response theory (Miller & Prinstein, 2019) Individuals experience suicidal thoughts and behaviors when an event triggers acute stress and they are unable to dissipate or counteract that stress through biological responses Strengthening coping skills/strategies Period of adolescence creates a unique vulnerability due to coinciding of biological changes with increased interpersonal stressors (Miller & Prinstein, 2019)
Biosocial theory (Crowell et al., 2009; Linehan, 1993) Individuals who have persistent and severe difficulty regulating their emotions (emotion dysregulation) employ suicidal thoughts and behaviors as a way to manage their emotions. Emotion dysregulation arises from a biological predisposition combined with an environment that negates or discredits an individual’s emotions Strengthening emotion regulation skills
Strengthening coping skills/strategies
Creating supportive environment
The interaction between biological vulnerabilities and an invalidating environment can lead to self-harm behavior as coping mechanism for youth (Crowell et al., 2009)
Cognitive-behavioral model of suicidality (Rudd, 2000) When individuals who have difficulty managing emotions experience strong negative emotions (e.g., guilt, anxiety) in reaction to an event and these strong negative emotions combine with feelings such as unlovability, helplessness, and hopelessness, the “suicidal mode” can be triggered. The suicidal mode is a temporary crisis period in which an individual is consumed by the impulse to die and exhibits suicide planning behaviors Strengthening coping skills/strategies None found
Minority stress theory (Meyer, 2003) Individuals who experience chronic social stress begin to constantly expect such stress and feel they must always remain on the lookout for triggers (e.g., discrimination, victimization). This constant vigilance combined with the internalization of negative societal attitudes can lead to an array of mental health problems, including suicidal thoughts and behaviors Strengthening coping skills/strategies
Promoting positive perception of self in context of minority identity
Creating supportive environment
Minority stress experiences (e.g., discrimination, victimization) may heighten susceptibility to suicidal behavior in youth through their effect on more proximal risk factors (Polanco-Roman et al., 2021) (e.g., hopelessness, depression) and/or via cumulative exposure to multiple experiences (Green et al., 2021; Mustanski & Liu, 2013)
As illustrated in Table 1, contemporary theories of suicide point to multiple pathways and differing mechanisms for suicide risk. Some mechanisms (e.g., lack of strong social connections combined with an event in which the individual perceives they are a burden to others leads to hopelessness and STB) may be more malleable than others (e.g., a combination of emotions and biological factors that interact to lead to vulnerability). Although all theories acknowledge the role of an individual’s social and/or environmental context—either directly or through experienced stress—some frameworks give these elements more weight in ultimately contributing to STB. Indeed, theories that take into consideration cultural influences such as racism and stigma and the role they play in STB are still relatively sparse (Chu et al., 2010). Also sparsely covered in the current suicide literature are studies that focus exclusively on protective factors and mechanisms even though such framing can help reduce stigma and point toward solutions. While most frameworks listed in Table 1 have been tested with youth, all but the acute stress response theory (Miller & Prinstein, 2019) were initially conceptualized using adult populations and may not adequately consider factors related to the unique developmental processes that occur during childhood and adolescence. Despite this complexity, there are many overlapping targets for suicide risk reduction across contemporary theories.
Common Types of School-Based Programs with Promise for Crossover Effects on Youth STB
As Table 1 demonstrates, there are common risk factors across contemporary suicide frameworks. Specifically, these theories point to three clear risk factors—the inability to regulate emotions, a lack of coping skills, and/or a lack of social connection/sense of belonging—that can lead to increased suicide risk when they interact with specific events or environmental or biological factors. In this section, we highlight some widely implemented school-based programs—SEL, substance use prevention, and cultural affirmation—that may have crossover effects on youth STB because they target these key risk factors and mechanisms. We also summarize their evidence of effectiveness relevant to youth STB.
Social Emotional Learning (SEL) Programs
SEL programs are designed to foster the development of five key competencies: self-awareness, self-management, social awareness, relationship skills, and responsible decision-making (CASEL, 2020). High-quality SEL instruction also seeks to establish a safe, caring environment and provide students opportunities to contribute to their class and school community, creating a sense of belonging. Within this overarching framework, there are a multitude of individual programs designed for different settings, age groups, and instructional approaches. Some of these programs have been assessed for outcomes but many have not. For example, the Collaborative for Academic, Social, and Emotional Learning (CASEL) maintains a Program Guide to Effective Social and Emotional Learning Programs, a Consumer Reports style publication designed to support schools in selecting SEL programs that fit their goals and students’ needs (CASEL, 2022). To be included, programs must meet several criteria including written documentation of approach and at least one evaluation study with a comparison group. The 77 different programs included in the Guide represent only a selection of SEL programs currently implemented in schools.
With the caveat that not all SEL programs are created equal, there is substantial evidence of their effectiveness in improving student outcomes. In their meta-analysis of findings from 213 universal, school-based SEL programs conducted between 1955 and 2007, Durlak and colleagues found that, compared to control students, students participating in SEL programs had improved skills and abilities related to emotion recognition, stress-management, empathy, problem-solving, and decision-making (Durlak et al., 2011). One notable limitation of the Durlak analysis is that the follow-up period for included studies was 6 months, leaving questions about the durability of these effects. A more recent meta-analysis by Taylor et al. (2017), looked at 82 school-based programs implemented between 1981 and 2014 and included studies with a mean follow-up period from 56 to 195 weeks (Taylor et al., 2017). The analysis included 7 outcomes of interest, among them social and emotional skills (e.g., identifying emotions, perspective taking, self-control, interpersonal problem-solving, conflict resolution and coping strategies, and decision-making) and attitudes toward self (e.g., self-efficacy, self-concept) and school (e.g., school bonding, connectedness, or belonging). While the effect sizes for these longer follow-up periods were diminished, the direction of the findings remained: students who participated in SEL programs had significantly improved social and emotional skills and attitudes toward self and school as compared to students who had not participated in these programs. In addition, Taylor and colleagues collapsed all 7 outcomes of interest into a single intervention level outcome and found that significant positive effects for SEL program participants were found across all demographic groups (including race and socio-economic status). While the existing evidence that SEL programs can improve many of the factors associated with attenuated suicide risk (e.g., emotion regulation, coping skills) is strong, to our knowledge, there have been no published studies that directly measure the effects of traditional, universal, school-based SEL programs on suicide outcomes. This represents a much-needed area for research.
Substance Use Prevention
Substance use elevates risk for youth STB, and substance use and STB share many risk factors such as impulsivity, emotion dysregulation, and maladaptive coping skills (Esposito-Smythers & Spirito, 2004; Lowry et al., 2014; Pompili et al., 2012). Therefore, substance use prevention programs that address these common risk factors or that effectively prevent substance use may have beneficial crossover effects on youth STB (Wyman, 2014).
Substance use prevention is a common element of public-school curricula in the USA, with most states having requirements or standards for school-based substance use prevention (Bruckner et al., 2014). Reviews of school-based substance use prevention programs suggest that their outcomes are somewhat mixed, where universal prevention and early intervention approaches in elementary and middle school appear to have relatively modest and short-term effectiveness in preventing substance use (Benningfield et al., 2015; Hopfer et al., 2010). These programs typically teach children about substance use and its negative consequences and work on changing perceptions about the acceptability and prevalence of substance use (i.e., norms) (Benningfield et al., 2015; Hopfer et al., 2010). Early, elementary school substance use prevention often focuses more specifically on strengthening skills that can protect youth from substance use later in life, such as inhibitory control, coping skills, and self-esteem (Benningfield et al., 2015; Hopfer et al., 2010; Onrust et al., 2016). As noted previously in this paper, researchers found that the Good Behavior Game, a universal elementary school program that is effective in preventing substance use and risky behaviors (Kellam et al., 2014), also reduces STB in young adulthood (Wilcox et al., 2008). Results showed that peer social preference partially mediated the relationship between the GBG and the associated reduction of risk for later suicide attempts by adulthood (by 22–30 years), specifically among children characterized by their first grade teacher as highly aggressive and/or disruptive (Newcomer et al., 2016).
Examination of the impact of substance use prevention programs on youth STB is an area in need of much further research, including research to explore the mechanisms by which such programs may simultaneously reduce both substance use and STB risk in youth.
Cultural Affirmation Programs
Much of the empirical and theoretical literature emphasizes the importance of belonging, social connection, cultural identity, and self-esteem as protective factors for STB and mental health (Meyer, 2003; Polanco-Roman et al., 2021; Whitlock et al., 2014). Supporting this is research showing that “acculturative stress” (Berry, 1998) defined as “stress related to adapting to the beliefs, practices and values of a dominant culture” (p. 1466 in Gomez et al., 2011) (which may be hostile to or unaccepting of minority racial and ethnic and sexual and gender identities) is related to an increased risk for STB (Gomez et al., 2011). Indeed, the groups of youth at highest risk for STB are often those who have been marginalized. For example, concerning trends show that sexual minority, American Indian/Alaska Native (AI/AN), Black, and Asian/Pacific Islander youth are increasingly vulnerable to STB (Lindsey et al., 2019; Marshal et al., 2011; Ramchand et al., 2021; Russell & Fish, 2016; Sheftall et al., 2021). Intersectionality research shows that youth with multiple minority identities (e.g., Black and American Indian bisexual youth) may be at particularly high risk for certain types of STB (Baiden et al., 2020). For example, using data from the Youth Risk Behavior Surveillance System (YRBS), Baiden et al. (2020) found that youth who were SGM as well as racial and ethnic minorities were more likely to report suicide attempts but less likely to report suicidal ideation compared to youth who were White and/or not SGM. In this section, we focus on the promise of school-based cultural affirmation programs for SGM and racial and ethnic minority youth separately because this reflects how research and practice have conceptualized each aspect of identity until recently. However, we acknowledge that this is a limited approach given the importance of considering intersectionality.
Sexual and Gender Minority Youth
In reviewing the literature, Postuvan et al. (2019) concluded that unaccepting school and other social environments increase STB risk for SGM youth (Postuvan et al., 2019). They recommended that suicide prevention for SGM youth take this into account, for instance, by focusing on changing school climates to be more accepting of SGM identities. Studies have found the presence of Gay-Straight Alliances (GSAs) protect SGM youth from suicide-related risk factors like peer victimization and mental health problems (Marx & Kettrey, 2016). However, recent research suggests that GSA presence could be just one proxy for school climate and SGM identity-affirming school staff (Colvin et al., 2019). When supportive school climate and supportive school personnel are more comprehensively and directly measured, the presence of a GSA was no longer associated with youth mental health (Colvin et al., 2019). Cross-sectional evidence suggests that a sense of school belonging, and a supportive school climate may be protective for SGM youth suicidality (Hatchel et al., 2019), but longitudinal research is lacking. Thus, it is not yet clear whether supportive, programs that enhance support and belonging among SGM youth could have direct impacts on STB.
Racial and Ethnic Minority Youth
Similar patterns have emerged among racial and ethnic minority youth, where racial and ethnic affirmation and acceptance in school and at home is related to youth self-esteem, feelings of belonging, and academic outcomes (Dee & Penner, 2017; Hernandez et al., 2014; Hughes et al., 2009). For example, according to the Indian Health Service, factors that protect AI/AN youth and young adults against suicidal behavior are a sense of belonging to one's culture, a strong tribal/spiritual bond, the opportunity to discuss problems with family or friends, feeling connected to family, and positive emotional health (Indian Health Service, 2022).
Loyd and Williams (2017) presented a conceptual framework to consider ways that youth programs—including school-based programs—can improve ethnic-racial identity (Loyd & Williams, 2017). They posit that critical components include several common to the STB prevention literature, such as the improvement of interpersonal interactions, coping, and self-esteem. A recent systematic review found promising evidence for the effectiveness of culturally affirming African-centered interventions on Black youth self-concept, behaviors, cultural identity, and academic achievement (Lateef et al., 2022). However, similar to a review on culturally sensitive interventions for Native American youth (Jackson & Hodge, 2010), the authors concluded that additional, more rigorous research is needed to measure the extent to which such approaches improve different aspects of youth wellbeing. Further, to our knowledge, these programs have not been examined for their downstream or crossover effects on youth STB. One example of a school-based culturally affirming program is Brothers of Ujima (Belgrave et al., 2011; Graves & Aston, 2018), a 14-week, culturally responsive program for African American boys with goals to improve self-esteem, ethnic identity, and prosocial behavior. Initial evidence from a pilot study in 6th and 7th graders found statistically significant improvement from pre- to post-intervention in Afrocentric values but did not find evidence of improvement in resiliency or racial identity. However, this was a small pilot study with no control/comparison group and measures of suicide risk were not included. While we are not aware of any past studies that have examined the impact of school-based, culturally affirming programs for racial and ethnic minority youth on STB, it is a promising area for exploration in the future.
Discussion
With youth mental health problems causing alarm across the USA, schools are being recognized as key players in the prevention of youth suicide. However, school-based programs focused specifically on suicide prevention are challenging to study and have shown little impact on youth STB to date, partly because such studies require longer term follow up periods (e.g., into adolescence or young adulthood) (Singer et al., 2019). Furthermore, ever-increasing demand on schools to address a multitude of child and family concerns underscores a pressing need to identify school-based programs and initiatives that can efficiently address multiple problems at once. In this paper, we used theoretical and empirical evidence to highlight key youth STB protective factors as well as risk factors and mechanisms that may already be the focus of ubiquitous school-based programs and which therefore have the potential to reduce STB risk downstream. SEL, substance use prevention, and cultural affirmation programs are examples of widely implemented school-based programs that hold promise in preventing STB. While little research has been conducted to investigate whether this is the case, this brief review and summary shows that there is a theoretical, mechanistic, and empirical grounding upon which researchers can build such studies. Because these programs are so widely implemented, researchers have an opportunity to conduct more fully powered studies using the large samples needed to investigate youth STB outcomes like suicide attempts which can be rare in smaller community samples. Should these different programs demonstrate an impact on STB, schools and policymakers could save resources by focusing on bolstering and sustaining these existing programs rather than launching new, non-evidence-based ones. As noted above, attempts to be consistent in our definitions of terms like “risk factor,” “mechanism,” and “protective factor” will augment the interpretability and, ultimately, the impact of this work. In addition, insufficient attention has been paid to protective factors in the literature, and some factors—such as coping skills—are cited as conveying risk and protection without further distinction (e.g., lack of coping skills is considered a risk factor while strong coping skills are protective). Research that focuses primary on protective factors and mechanisms may be a fruitful way to advance suicide prevention research and turn the focus toward strengths rather than weaknesses.
This paper is intended to provide a framework to help researchers, practitioners, and policymakers as they consider how to prevent youth suicide using existing school-based resources effectively and efficiently. However, our approach comes with limitations. Namely, this was not a systematic review of the literature; there may be other school-based programs that hold promise for preventing suicide not covered here. We focused on reviewing interventions that did not target STB directly but did address youth suicide risk and protective factors. We did not review clinical interventions that specifically address ways to manage STBs in individual youths. Schools will continue to need to address urgent cases of suicide risk since broader prevention efforts will not prevent all instances of acute STB (Substance Abuse & Mental Health Services Administration, 2020). In addition, we recognize the recent media coverage of some communities calling into question the appropriateness of schools to address the mental health needs of students. In addition, some states have begun to prohibit schools from discussing racial and ethnic identity, sexual and gender identity, and the discrimination experienced by individuals with minority racial and ethnic and sexual and gender identities (e.g., Florida House Bill 1557 of 2022; Texas Senate Bill 3 of 2021). These policies may impact the ability of many schools and researchers to implement and evaluate SEL and cultural affirmation programs. However, current trends in risk for youth suicide and the need for evidence-based approaches underscore the importance of rigorous studies to determine whether existing school-based programs have an impact (whether beneficial, as we hypothesize, or harmful) on youth STB. This type of research can inform policymakers of the potential for unanticipated consequences (harms and benefits) of laws that limit vs. expand the availability of SEL, cultural affirmation, and other programs.
Amid converging health and mental health crises, schools face a building pressure to address youth suicide risk as they simultaneously face staff shortages, burnout, and a myriad of competing demands (Diliberti & Schwartz, 2022). It is possible that programs schools are already implementing may, in fact, have crossover effects on suicide prevention even when these programs are not specifically designed to address STBs. Researchers can support schools by examining whether existing school-based programs that target emotional and behavioral problems that share risk factors with youth suicide are already having an impact on youth STB. In some cases, these studies could leverage existing data to answer key questions, further enhancing their efficiency. In other cases, new measures and assessments would be needed. For example, researchers who have access to data from a prior study of, say, an elementary school SEL program could conduct a follow-up with those participants to assess STB later in childhood, adolescence, or even adulthood. Consistent with the NIMH’s focus on experimental therapeutics (Gordon, 2017), these studies could also examine whether change in the original program targets (e.g., emotion regulation skills) mediate or partially explain outcomes. Because youth STBs are uncommon and therefore require larger sample sizes, integrating data sets from multiple school-based studies of the same intervention may be advantageous (Wilcox et al., 2016). In addition to consideration of unanticipated benefits for STB outcomes, it will also be important for such research to examine whether school-based programs have any unintended harms. While we emphasize that there is no evidence to suggest that such harms would occur, objective and valid measurement of the feared and imagined harms (based on recent uproar and controversy over certain school-based programs [e.g., SEL, cultural affirmation]) would strengthen schools’ abilities to respond to such criticisms. Rigorous investigation of existing, promising school-based approaches, such as the ones covered in this paper, is urgently needed to advance evidence-based suicide prevention in schools.
Acknowledgements
We are grateful for feedback from Susannah Allison, Ph.D., of NIMH, for helpful comments on a previous version of this manuscript.
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| 36484887 | PMC9734872 | NO-CC CODE | 2022-12-14 23:28:31 | no | Prev Sci. 2022 Dec 9;:1-11 | utf-8 | Prev Sci | 2,022 | 10.1007/s11121-022-01473-2 | oa_other |
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Original Paper
Mandatory vaccinations, the segregation of citizens, and the promotion of inequality in the modern democracy of Greece and other democratic countries in the era of COVID-19
http://orcid.org/0000-0002-0480-7499
Mavridis Charalampos [email protected]
1
http://orcid.org/0000-0001-8774-4261
Aidonidis Georgios [email protected]
2
Evangelou Marianna [email protected]
3
http://orcid.org/0000-0002-3270-1771
Kalogeridis Athanasios [email protected]
4
1 grid.8127.c 0000 0004 0576 3437 Medical School, University of Crete, Voutes Campus, 710 03 Heraklion, Greece
2 grid.414782.c 0000 0004 0622 3926 Interbalkan Medical Center, Thessaloníki, Greece
3 Independent Researcher, Larissa, Greece
4 grid.4793.9 0000000109457005 2nd Department of Internal Medicine, Aristotle University of Thessaloniki, Hippokration General Hospital, Thessaloníki, Greece
7 12 2022
2022
44 4 7220 5 2022
4 11 2022
© Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
During the COVID-19 pandemic, the Greek authorities enforced a vaccination mandate for healthcare workers (HCWs). At the same time, multiple concerns were raised about the epidemiological profile of Greece in addition to the ethical status of the harsh measures and their impact on employees, organizations, society, and public health. According to the World Health Organization (WHO), considerations regarding the evidence of vaccine safety and effectiveness, necessity, and proportionality should be clearly evaluated by before imposing mandatory vaccination policies. We discuss the issues regarding the mechanics of the transmission and contraction of SARS-CoV-2, the toxicity of COVID-19 vaccines, and the impact of the suspension of HCWs who did not vaccinate versus the potential expected benefits in addition to whether the vaccine mandates were justified considering the overall epidemiological context.
Keywords
Mandatory vaccination
COVID-19 democracy
SARS-CoV-2 immunity
Health care workers Greece
COVID-19 transmission
Pandemic politics
issue-copyright-statement© Springer Nature Switzerland AG 2022
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pmcIntroduction
COVID-19 is undoubtedly one of the most important human health issues, with more than 6,000,000 deaths worldwide to date (Dong et al., 2020). Each country’s government was tasked with taking several measures to protect public health without causing additional direct or indirect harm, either in the short or the long term, to its citizens. Vaccinations for infectious diseases are undeniably the most effective preventive measure, as we have historically seen with diseases such as smallpox, which have essentially disappeared (Belongia & Naleway, 2003). However, in every medical practice, the costs must be weighed against the benefits, and science has the responsibility of providing guidance, without any bias or partiality, to ensure the maintenance of public health at the lowest possible cost. As of July 2022, searches of the Medline database reveal over 165,000 articles on COVID-19 and about 2,100 related meta-analyses. As we are still in a period of learning, during which a massive amount of medical data are constantly added on a daily basis, implementing guidelines is a great challenge.
The pandemic came to Greece at the end of February 2020 with the official announcement of the first case of COVID-19 (Reuters, 2020). The first death was recorded on 12.3.2020 (ANA-MPA, 2020), while the number of cases up to the first official report of the EODY (ΕΟΔΥ—Hellenic National Public Health Organization) on 20.3.2020 was 495 (Eody, 2020). By July 2022, 31,337 deaths attributed to COVID-19 had been counted (Hannah Ritchie et al., 2020). Greece is a country of about 10.5 million people, but in total, receives more than 30 million tourists annually (Reuters, 2020), leading to the logical consequence of increasing the required reserves of the health system, especially in situations of healthcare crises, such as the one brought on by COVID-19. This means that healthcare workers (HCWs) face various challenges; apart from the obvious potential of SARS-CoV-2 infection, higher workloads, social exclusion, stigmatization, and mental disorders (Gupta et al., 2021; Razu et al., 2021) are likely to increase at times (e.g., coinciding with increased tourist arrivals). Consequently, in order to cope with the challenges facing the health system, specific strategies need to be implemented in order to increase staffing, equipment and the adequacy of pharmaceutical agents, as well as provide the possibility of home care (primary health care) for patients such that hospitals are not overburdened (Levin et al., 2007). The role of general practitioners and nurses is of paramount importance in the overall management of the pandemic (Sarango et al., 2021; Van Poel et al., 2022). Unfortunately, according to Organisation for Economic Co-operation and Development OECD data, Greece entered the pandemic (2019) with the lowest ratio of nurses and general practitioners per 1,000 inhabitants among all European countries. Specifically, there are only 3.4 nurses and 0.44 general practitioners per 1,000 inhabitants, while in Germany, the corresponding ratios are 11.79 and one, respectively (Fig. 1) (OECD.). Moreover, it is essentially impossible to hope for home care for COVID-19 patients in a country with a seriously undermanned and fragmented primary healthcare system that has not yet been properly established (Kondilis et al., 2012). Thus, COVID-19 patients have followed instructions over the telephone given by doctors with whom they were personally acquainted, if available, or visited hospitals.Fig. 1 Comparative bar charts of European countries with OECD data: A practicing nurses per 1,000 population (head counts); B generalist medical practitioners per 1,000 population (head counts) (OECD.Stat, 2019a, 2019b)
During the pandemic, Greek HCWs have served with admirable self-sacrifice to uphold public health. The “heroes”, as they were called, have been working under conditions of incredible pressure in a healthcare system experiencing staff and equipment shortages, and some of them unfortunately lost their lives in the battle with COVID-19 (Tovima.gr, 2020). Since 1.9.2021, the Greek government has enforced a COVID-19 vaccination mandate for HCWs and medical nursing students, which has placed the unvaccinated and non-recently convalescent HCWs in unpaid suspension. In addition, Greek lawmakers imposed severe restrictions on all unvaccinated citizens, who were essentially subject to ongoing “social exclusion” for six months (4.11.2021–2.5.2022), prohibited from remaining indoors in restaurants or bars, participating in-person at scientific conferences, attending cinemas, entering stadiums, or visiting museums, even with a negative PCR or rapid test, despite the relaxation of preventive measures in many European countries, including the United Kingdom and those of Scandinavia, which had started much earlier than February 2022 (Gijs & Duxbury, 2022; Schengenvisainfo.com, 2022; Stokel-Walker, 2022; Thelocal.no, 2022). In addition, the duration of the temporary “Green Pass” (i.e., the immunity certificate), issued to recently convalescent individuals, was reduced to three months only, though it was recently re-instated to six months (4.4.2022). Lastly, unvaccinated citizens over 60 years old had to pay a fine of EUR 100 every month, starting on 15.1.2022, a measure that seems to have been temporarily paused since April 2022. According to the World Health Organization (WHO), considerations regarding necessity and proportionality; sufficient evidence of vaccine safety, efficacy, and effectiveness; public trust; and ethical frameworks should be explicitly assessed by authorities before imposing mandatory vaccination either on the general population or on certain groups, such HCWs (O’Sullivan, 2022).
Our purpose was to analyze whether the imposing of vaccine mandates on Greek HCWs can be justified according to the WHO considerations as well as under the context of the specific conditions present in Greece. We also aim to raise concerns about the current COVID-19 vaccinations as well as the social repercussions of the medico-political decisions, providing an open invitation to a critical debate within the scientific community.
Discussion
The proportionality of the measures taken against the pandemic, which can include the use of masks, COVID passes, lockdowns, fines, and mandatory vaccination, varies considerably from country to country. However, global trends tend to merge in the fact that transparency in the conveying of information and the promotion of educated self-choice are linked with more rational, humane, and effective management of the pandemic (Kerr et al., 2021). In their attempt to manage the pandemic, the Greek government recruited several doctors and scientists who urged people, through persistent television broadcasts, to get vaccinated, while the media highlighted dramatic medical cases and deaths of young patients and parents from COVID-19 in order to promote vaccination (Protothema.gr, 2022; Skai.gr, 2021a, 2021b). For example, the Deputy Minister of Health (who is a pulmonologist), after the death of a 20-year-old, highlighted that "COVID-19 disease is severe, resulting in death so often" (Skai.gr, 2021b). Another example is an ICU director who emphatically declared on TV that "I was faced with a tragic dilemma, a living nightmare, where I had a 22-year-old young patient with leukemia who needed admission in the ICU, but I had no available beds, and at the same time, an unvaccinated 62-year-old COVID-19 patient, who also needed admission in the ICU" (Ethnos.gr, 2021a). These claims were, however, later refuted by the Ministry of Health (Protothema.gr, 2021). The opinion of experts, as displayed on television and the media, carries the lowest degree of scientific credibility and recommendation according to the definition of evidence-based medicine. In science, "severe" and "often" imply numbers and data, so such phrases may create public confusion and unbalanced fear. For example, as shown in a systematic review and meta-analysis, the infection fatality rate for COVID-19 in the age group of 0–34 years old is 0.004 (0.003–0.005) (Levin et al., 2020). Confusion, fear, and distrust can also result from the inconsistencies in the claims between politicians and doctors, especially when the latter are ICU directors. Although fear of COVID-19 infection seems to be negatively correlated with vaccine hesitancy (Willis et al., 2021), the implementation of fear as a means of coercing should not be accepted from an ethical point of view, as it creates distress and anxiety (Hastings et al., 2004). On the other hand, several studies on social marketing show that the implementation of fear and guilt should be substituted with more educative/informative approaches, as the former is more likely to result in inaction rather than voluntary compliance (Brennan & Binney, 2010; Szmigin et al., 2011). Consistent with its generally strict policies, the Greek government also decided to place unvaccinated HCWs on unpaid suspension, supposedly to protect public health, and may have unwittingly created the false impression that the patients’ health is primarily endangered by these HCWs, as the Prime Minister asserted that "it is unacceptable for HCWs, who are supposed to protect the most vulnerable patients from COVID-19, to be potential carriers and transmitters of the virus themselves" and "it is inconceivable for an unvaccinated nurse to provide care to an immunocompromised cancer patient" (Ethnos.gr, 2021b). In the first year of the pandemic, when there were no vaccinations, and until 31.8.2021, the same HCWs responsibly protected vulnerable patients by carrying out frequent testing and taking all preventive measures. After the advent of vaccines, the stigmatization and ostracism of the unvaccinated HCWs might have had some basis if being vaccinated against COVID-19 meant being "sterile" and being unvaccinated meant being infectious, i.e., if the vaccines provided almost 100% protection against transmission. In the following sections, we analyze our concerns about the mechanics of COVID-19 transmission and contraction, toxicity of COVID-19 vaccines, and suspension of HCWs and its impact on employees, hospitals, and society.
Considerations regarding the mechanics of COVID-19 transmission and contraction
The facts concerning the ability of vaccines to prevent the contraction and transmission of the disease should certainly have been taken into consideration when issuing vaccine mandates for HCWs or citizens. The initial data from phase III clinical trials showed that the number needed to vaccinate (NNTV) to prevent one case of COVID-19 was about 119, and to prevent severe disease, about 2,380 (Fig. 2) (Polack et al., 2020). It is well known that SARS-CoV-2 can be transmitted from vaccinated HCWs (Hetemäki et al., 2021; Ioannou et al., 2021; Keehner et al., 2021; Pollett et al., 2022; Shitrit et al., 2021). After the fourth dose, although there is still a high efficacy of the vaccine against symptomatic COVID-19 disease, there is, unfortunately, a significantly reduced efficacy against preventing infection with SARS-CoV-2, with the virus still being well transmitted to and from vaccinated HCWs (Regev-Yochay et al., 2022).Fig. 2 Calculation of the number needed to vaccinate (NNTV) for symptomatic and severe COVID-19 occurrence. Data used were from the phase III clinical trial of BNT16b2 (Polack et al., 2020)
A careful review of the weekly and very thorough COVID-19 Vaccine Surveillance Reports of the UK Health Security Agency (UKHSA), beginning from Week 37 of 2021 (UKHSA, 2021a), which is based on data from 18.8.2021 to 3.9.2021 and onwards, displays a constant and repeating pattern, which is that in the age groups from 30 to 80 years old, after the prevalence of the Delta strain, the number of new COVID-19 cases per 100,000 of the respective population (unadjusted case rate) is invariably higher in the fully vaccinated individuals compared with the unvaccinated. The unajusted case rate among vaccinated individuals also increased in the remaining age groups, with the exception of the < 30 and > 80 years old. One can verify this pattern by running through the following weekly reports: Week 37 (p.13), Week 38 (p.13), Week 39 (p.14), Week 40 (p.13), Week 41 (p.13), Week 42 (p.13), Week 43 (p.19), Week 44 (p.20), Week 45 (p.22), Week 46 (p.23), Week 47 (p.33), Week 48 (p.44), Week 49 (p.35), Week 50 (p.39), and Week 51 (p.40) (UKHSA, 2021a, 2021b, 2022). Starting in Week three of 2022 (p.38), the UKHSA started to produce these tables by counting only the people who had undergone a booster vaccination, i.e., at least three doses in total, in the vaccinated group, and the same pattern can still be observed. Unfortunately, moving forward to the most recent reports in 2022, in Week nine (p.45), Week 10 (p.45), Week 11 (p.45), and so on, the pattern seems to become worse, with the unadjusted case rate among the booster-vaccinated individuals in the aforementioned age groups climbing to three or even four times higher than among the unvaccinated (UKHSA, 2021b, 2022). The aforementioned tables correctly point out that the proportionate unadjusted rates of ER admissions and deaths are definitely lower in the vaccinated group compared to the unvaccinated, progressively increasing in proportion with age. However, this difference has been narrowed considerably and has become almost even in terms of younger age groups with the prevalence of the Omicron strain.
In accordance with this, reports from the Robert Koch Institute (RKI) in Germany demonstrated that breakthrough infections are possible also among vaccinated staff at a similar viral load (Koch-Institut, 2021). Data from previous months from RKI underline that the vaccinated constituted 66% of new cases (Koch-Institut, 2022), although vaccine effectiveness against hospitalization and ICU-treatment was preserved. In Israel, a new in-hospital outbreak recently occurred, where the source was a fully vaccinated patient with COVID-19 (Kampf, 2021a, 2021b). The US Center for Disease Control and Prevention (CDC) announced four of the top five counties with the highest percentages of fully vaccinated populations (84.3–99.9%) as "high" transmission counties (Kampf, 2021a, 2021b). Moreover, a large study by Subramanian and Kumar showed that vaccination for COVID-19 cannot control its spread regardless of the level of vaccination coverage, with data from 68 countries and 2,947 counties in the United States (Subramanian & Kumar, 2021). Consequently, by taking all these facts into consideration, vaccination against COVID-19 seems to be an individual rather than a collective one protective measure. In addition, relying solely on mass vaccination without controlling the horizontal and vertical transmission of the infectious disease potentially carries significant public health issues, negating any expected benefits (Gandon et al., 2001; Read et al., 2015).
The validity of the “Green Pass” of convalescent individuals in Greece was reduced to only three months, and only recently (April 2022) re-instated to six months, although the duration of naturally acquired immunity, especially that acquired after infections from pre-Omicron strains, has been demonstrated to last much longer than six months. An additional unequal measure was put into effect after 7.2.2022, allowing vaccinated HCWs to continue working provided they underwent regular rapid testing, with negative results, after the expiry of their vaccination certificate, which was arbitrarily set at seven months post-vaccination. On the other hand, the convalescent unvaccinated HCWs could work only at three months post-infection.
The potency and duration of naturally acquired immunity have been demonstrated by many studies. Firstly, we will refer to a recent report from the CDC (León et al., 2022), which studied 18% of the population of the United States and showed that naturally acquired immunity was more potent by up to five times and longer-lasting compared with vaccine-acquired immunity against the Delta variant. In addition, the systematic review and meta-analysis by Chivese et al. covering a total of 18 countries and 12,011,447 patients demonstrated the strong immune memory of COVID-19 patients, lasting for at least eight months with a 0.2% probability of reinfection (Chivese et al., 2022), and there are studies showing protection against reinfection for two years as well as protection against severe infection for several years, even after asymptomatic COVID-19 infections (Le Bert et al., 2021; Wei et al., 2021). This hesitancy to acknowledge the duration and quality of naturally acquired immunity seems to be out of alignment with evidence-based studies (Kojima & Klausner, 2022). Against the Omicron variant, which probably has an increased breakthrough infection rate among the vaccinated, as mentioned, as well as a generally more benign epidemiological course (Lewnard et al., 2022), naturally acquired immunity still provides excellent protection against reinfection and serious disease (Altarawneh et al., 2022; León et al., 2022). By taking all of the above into consideration, “forcing” individuals with naturally acquired immunity to vaccinate may not be justified.
Considerations regarding the toxicity of COVID-19 vaccines
An important factor when considering mass vaccination of the population, and particularly the mandatory vaccination of a specific social or professional group, such as HCWs, without any individualization, e.g., in regard to age, comorbidities, etc., is the fact that the molecular and physiological mechanisms of action of the currently available vaccines are still under continuous investigation. Along with this, the deadlines for the completion of studies by pharmaceutical companies are 2023 and 2024 (ClinicalTrials.gov, 2022). Most vaccines are designed to target the surface spike (S) protein of SARS-CoV-2 because it binds strongly to ACE2 receptors and mediates entry into host cells (Salvatori et al., 2020). We also know that the S protein of SARS-CoV significantly induces the production of neutralizing antibodies, showing high immunogenicity (Salvatori et al., 2020). For these reasons, the S protein appears an optimal target (Salvatori et al., 2020). The translation product of the new vaccine technologies, namely the isolated S protein, appears to modify the normal function of ACE2 receptors and trigger several molecular mechanisms via signal transduction pathways. It can be briefly summarized that the S protein alone could cause either impairment of the DNA repair mechanism, inducing dysfunction of the tumor suppressor proteins p53 and BRCA1, or downregulate the ACE2 receptors and inhibit mitochondrial function, resulting in serious damage to vascular endothelial cells (Jiang & Mei, 2021; Lei et al., 2021; Singh & Bharara Singh, 2020). In addition, it appears that other pathways of cellular signaling are activated, such as MEK and ERK, which are known for their involvement in key molecular mechanisms of cell growth (Suzuki & Gychka, 2021; Zhang & Liu, 2002). The improper activation of such pathways, combined with the possible presence of established mutations or polymorphisms and/or the possible inhibition of the DNA reparative mechanisms, increases the chances of tumorigenesis given the diversity of the genetic profile in the general population. Correspondingly, mRNA vaccines could trigger a pathophysiological mechanism, resulting in the suppression of innate immunity (Seneff et al., 2022). This dysregulation is related to the interferon type I (IFN-1) pathway and could potentially lead to an increased risk of carcinogenesis (Seneff et al., 2022). The suppression of IFN-1 could also increase vulnerability to future infectious diseases (Seneff et al., 2022). We should also take into consideration some reports that have shown that the S protein could migrate and circulate via exosomes for at least four months after vaccination (Bansal et al., 2021), possibly at higher levels than in severely ill COVID-19 patients (Röltgen et al., 2022). High levels of S protein-carrying exosomes could lead to serious inflammation and the development of neurodegenerative diseases (Seneff et al., 2022). This probably explains, to a degree, the findings of a study, demonstrating that the immunological functions of vaccinated individuals eight months after the administration of two vaccine doses were lower than those of the unvaccinated (Yamamoto, 2022). The European Medical Agency proposed that the frequent booster doses for COVID-19 could negatively impact the immunological response (Yamamoto, 2022). Thus, as a security measure, it is advised that further vaccinations be abandoned, since they also seem to be an important risk factor for infection, especially in seriously ill patients (Yamamoto, 2022).
Regarding the mRNA technology itself, a recent study (Aldén et al., 2022) showed the presence of DNA sequence unique to BNT162b2 as a product of reverse transcription as well as upregulation of the endogenous reverse transcriptase long interspersed nuclear element-1 (LINE-1) protein expression, in a human hepatic cellular line as early as six hours after BNT162b2 exposure. Although the probability of this phenomenon is extremely low, it is generally known that molecules are transported to and from the nucleus via nuclear pore complexes. In particular, the transport of various proteins and RNAs can take place by binding with importin-b (Oka & Yoneda, 2018). Furthermore, since vaccine mRNA could be detected up to 60 days post-vaccination in lymph nodes (Röltgen et al., 2022), there are multiple questions that arise with regard to the accuracy, quantity, and quality of the ongoing mRNA translation. During the pandemic, the antibody-dependent enhancement (ADE) of infection is a possible critical factor, since the present strains are different from the original, with potentially unfavorable consequences (Yahi et al., 2021). Although ADE and antibody-enhanced disease (AED) are theoretically rare phenomena for genetic vaccines, they should be studied more extensively (Gartlan et al., 2022). Since vaccine-associated enhanced disease (VAED) was observed in the SARS-CoV-1 pandemic, the same trials to investigate VAED should be repeated for the current SARS-CoV-2 pandemic (Gartlan et al., 2022). Additionally, the increased hospital and ICU admission rates in fully vaccinated patients are a cause for concern, as according to Munoz F.M. et al., the criteria with a possible diagnostic certainty for VAED are met (Munoz et al., 2021). In particular, the recent large-scale study of Lewnard J.A. et al. showed that for the Omicron variant, the risk of an unvaccinated person being put on mechanical ventilation is 76% reduced compared with the Delta variant (statistically significant), while for a vaccinated person, the risk is 50% increased (not statistically significant) (Lewnard et al., 2022).
Concomitantly, reports of myocarditis due to direct toxic effects predominantly in young males (Diaz et al., 2021), along with the detection of unusual thrombotic events such as cerebral sinus thrombosis (implicating blood–brain barrier penetration) (Wittstock et al., 2022), cardiovascular deaths, including sudden cardiac deaths attributed to the particular pathophysiology of the well-described Kounis syndrome (Kounis et al., 2021), as well as other miscellaneous adverse events with the common underlying pathophysiology of an activated inflammatory and thrombogenic process (Guardiola et al., 2022), compose a dynamic profile of a vaccine that constitutes a continuous safety alert (Edler et al., 2021). At the same time, a very recent Israeli study showed that acute cardiovascular events, including sudden cardiac deaths, among vaccinated individuals under 40 years old are significantly associated with the rates of first and second vaccine doses but not with COVID-19 infection rates. Furthermore, it mentions that “while not establishing causal relationships, the findings raise concerns regarding vaccine-induced undetected severe cardiovascular side effects and underscore the already established causal relationship between vaccines and myocarditis, a frequent cause of unexpected cardiac arrest in young individuals” (Sun et al., 2022). As for cardiovascular events, endothelial dysfunction is a possible side effect of vaccination (Lei et al., 2021) that is not benign, since it is linked with the development of atheromatosis and coronary disease (Berenji Ardestani et al., 2020; Landmesser et al., 2004). This possible pathogenetic mechanism is demonstrated in a published abstract, where the five-year predicted risk of developing an acute coronary event in a group of patients was increased from 11 to 25%, on average, for those who received two doses of an mRNA vaccine, with the changes persisting for at least 2.5 months after the second dose (Gundry, 2021). We summarize the key points of possible mid- and long-term side effects of vaccines in Table 1. The questions that arise need to be transparently clarified through properly structured randomized clinical trials and meta-analyses investigating the molecular pathways and clinical events in more samples. Moreover, knowledge about the vaccines’ mechanisms of action and their possible side effects seems to increase the intention to vaccinate (Andrade et al., 2022). We must also consider that we may need to research additional pharmacological and non-pharmacological preventive alternatives to establish health and social equilibrium in order to avoid the “nightmare” in which the public’s confidence in medicine declines (Hellerstein, 2020).Table 1 Synopsis of publications related to possible mid- and long-term vaccine side effects included in the present study
Reference(s) Possible mechanism—causes Side effect Term of effect
Gundry (2021)
Lei et al. (2021)
Endothelial inflammation—Dysfunction CVD Mid/Long
Seneff et al., (2022)
Singh and Bharara Singh (2020)
Jiang and Mei (2021)
Suzuki and Gychka (2021)
Reduced INF-1 response
Dysfunction of p53 and BRCA1
Impairment of DNA repair
Improper activation of MEK and ERK pathways
Tumorigenesis Long
Yamamoto (2022)
Seneff et al. (2022)
ADE, OAS, SP, LNPs Reduced INF-1 response Decrease in immunity Mid
Seneff et al. (2022) Reduced INF-1 response, SP Demyelinating injury (e.g., Guillain–Barre) Mid
Bansal et al. (2021)
Seneff et al. (2022)
Exosomes with SP
Reduced BRCA1 expression
Neurodegenerative disease (e.g., Alzheimer’s) Mid/Long
ADE antibody-dependent enhancement, BRCA1 breast cancer gene 1, CVD cardiovascular disease, DNA deoxyribonucleic acid, ERK extracellular signal-regulated kinase, INF-1 interferon type I, LNPs lipid nanoparticles, MEK mitogen-activated protein kinase, OAS original antigenic stimulus, SP spike protein
Considerations regarding the suspension of HCWs due to vaccine mandates
The vaccination of HCWs theoretically provides multiple benefits, as it safeguards their health, protects the health of vulnerable patients, and may stand as an “advertising campaign” to encourage the vaccination of citizens, creating a climate of trust. However, as previously stated, the intention to impose mandatory vaccination on a specific population group must be thoroughly weighed against necessity, proportionality, evidence of vaccine safety/efficacy, and ethics (O’Sullivan, 2022). Out of the 27 countries of the European Union, only six (Greece, Germany, France, Italy, Latvia, and Hungary) have decided on a strict framework of compulsory vaccination for HCWs (Diaz Crego et al., 2022). In Estonia and, until 6.3.2022, also in Hungary, employers were authorized to impose such requirements on their employees (Diaz Crego et al., 2022). Austria initially voted for compulsory vaccination of all adults under the threat of very severe penalties, which was never implemented, formally declaring that it was “no longer needed” (Reuters, 2022). Germany, although having recently (15.3.2022) voted for vaccine mandates, does not seem to have implemented corresponding laws, since out of approximately 190,000 unvaccinated HCWs, only 70 entry bans have been recorded up to July 2022 (Welt, 2022). Italy seems to have allowed unvaccinated HCWs to be transferred to other duties (Paterlini, 2021). In the remaining countries, HCWs are allowed to continue working on the provision of carrying out timely diagnostic tests with appropriate results (Table 2) (Diaz Crego et al., 2022). The United Kingdom considered vaccine mandates for HCWs but postponed the measure until 1.4.2022, when the hard winter would be over, in order to not lose a single HCW. Later, a House of Lords committee refused to acknowledge the need for a mandate, declaring it not economically, scientifically, nor morally supported (Kmietowicz, 2021). This has led to a total revoke of the measures for mandatory HCW vaccination and the vaccination-as-condition-of-deployment (VCOD) in the United Kingdom, as officially stated in the Government resolution of 1.3.2022 (DHSC, 2022).Table 2 Mandatory vaccinations for healthcare workers (HCWs) in EU countries and the United Kingdom (DHSC, 2022; Diaz Crego et al., 2022; Paterlini, 2021)
Country Mandatory Vaccination to HCWs
Austria No
Belgium No
Bulgaria No
Croatia No
Cyprus No
Czechia No
Denmark No
Estonia No (decided by employers)
Finland No (contact with at-risk patients—tested on site)
France Yes (from 5.8.2021)
Germany Yes (from 15.3.2022, no known suspensions to date)
Greece Yes (from 1.9.2021)
Hungary Yes (from 15.9.2021)
Ireland No
Italy Yes (from 1.5.2021, optionally transferring to other duties)
Latvia Yes (from 1.11.2021)
Lithuania No
Luxembourg No
Malta No
Netherlands No
Poland No
Portugal No
Romania No
Slovakia No
Slovenia No
Spain No
Sweden No
United Kingdom No (from 1.4.2022, rolled back)
Theoretically, one reason for introducing compulsory vaccination in Greece would be a low vaccination coverage among HCWs. Another reason would be to coerce citizens to get vaccinated through the indirect threat of future fines or other restrictions in cases of non-compliance, especially in a period of high number of cases. In addition, citizens’ confidence in COVID-19 vaccines could theoretically increase if their family doctors were 100% vaccinated. However, in reality, according to the POEDIN (ΠΟΕΔΗΝ, the official national association of hospital healthcare workers) data, 94.7% of doctors and more than 80% of nurses were already vaccinated before the mandatory vaccinations were imposed (Naftemporiki.gr, 2021). In the United Kingdom, for example, and specifically in London, only 79% of HCWs were vaccinated before the introduction of compulsory vaccination in Greece (BBC, 2021), and even in January 2022, 5.4% of all NHS HCWs remained unvaccinated (Iacobucci, 2022). In Sweden, the percentage of vaccinated doctors was reported as 96% (Ljung et al., 2022), and in the Czech Republic, and 69.8% overall vaccination coverage of HCWs was reported in some tertiary hospitals (Štěpánek et al., 2021). Regarding the overall vaccination coverage of citizens, by 12.7.2021 (when the impending law about mandatory vaccinations was announced), Greece ranked 11th among 28 countries in the European Union and including the United Kingdom (Fig. 3) (Hannah Ritchie et al., 2020). Moreover, Greece and Finland had the fewest confirmed COVID-19 cases relative to their population compared with the other countries (Fig. 4) (Hannah Ritchie et al., 2020). Consequently, there seems to be no significant evidence for the Greek government to decide to issue vaccine mandates at that point.Fig. 3 Vaccination coverage among 27 EU countries and the United Kingdom (12.7.2021) (Hannah Ritchie et al., 2020)
Fig. 4 Confirmed cumulative cases per million people among 27 EU countries and the United Kingdom (12.7.2021) (Hannah Ritchie et al., 2020)
The vaccine mandate for HCWs, as an ultimate and extreme measure in a panicked attempt to manage the pandemic, and with the resulting suspension of unvaccinated HCWs, could not be implemented without serious complications. It has had an impact on the HCWs themselves, hospitals and medical departments (e.g., ICUs), public health, and society. For more than 11 months, unvaccinated HCWs have been confined to unpaid suspension and, moreover, are prohibited from seeking employment anywhere, not only in the healthcare sector but in any other job, as they are bound by the legal terms that govern their status as public servants. The potential harm caused to unvaccinated HCWs is multifactorial. The most likely damage they are subject to is financial. An unpaid, suspended HCW will enter into an impoverished state, which will affect the members of their household (children, spouse, and dependent members). Unfortunately, some HCWs have faced serious issues with survival, resorting to fundraisers, selling lottery tickets, or borrowing money, and some HCWs have also been on a hunger strike. Another possible harm concerns their scientific development and education since, for the previous 11 months, they have not had the right to attend various scientific conferences, meetings, or seminars in person, even with a negative PCR test. They could also be harmed by their long-term absence from the scientific community. In some cases, the harm may involve their professional expertise, since, for example, a surgeon needs to perform a minimum number of annual procedures to maintain their learning curve (depending on the procedure). There are also concerns about stigmatization. The prestige of an unvaccinated HCW may be harmed in their workplace due to the stigmatization of a long absence as well as the negative propaganda against them and their peers. Moreover, the long absence could create false impressions for a physician’s patients, whose confidence in the physician may be shaken. The physician could be falsely stigmatized as “inefficient”, “antisocial”, and “non-scientific”, facts that may cause irreparable damage to their scientific entity and represent the most dramatic volte face to the admiration they received during the previous 18 months of the pandemic for their valiant and self-sacrificial efforts. In addition, the medical confidentiality regarding the person has been violated (Law 3418/2005), as everyone knows their vaccination status through the imposed penalty of suspension. The “side effects” of compulsory vaccinations do not only affect the unvaccinated HCWs; the remaining HCWs are being led to physical and emotional exhaustion in compensating for their absence. There were mass resignations of doctors due in part to the suspensions of HCWs since September 2021 (Efsyn.gr, 2021). They were forced to do 20 resident on-calls in a month. The same situation exists today, where waves of resignations are occasionally observed (Efsyn.gr, 2022).
A major issue arising from the reduction in the available number of HCWs in countries where mandatory vaccinations are implemented is the quantitative and qualitative understaffing of health-care units. The availability, level of training, and specialization of health personnel are definitive factors in increasing mortality (Aiken et al., 2002; Tourangeau et al., 2006). Department understaffing could result in an increase in the mortality of each inpatient by 3% daily (Griffiths et al., 2019). On the contrary, countries that have invested in the steady improvement of medical services have achieved a reduction in ICU mortality over time (Karagiannidis et al., 2021). The number of substantive medical staff shortages in Greek hospitals was estimated to be 5,000 doctors, without including the suspended staff, but the actual urgent demands are quantified as being higher (Panagiota Karlatira, 2022). The respective shortages in other healthcare professions (nursing, etc.) are estimated to be even worse, reaching about 30,000 (In.gr, 2020). In addition, as departmental understaffing worsens, with hundreds of quarantined HCWs due to breakthrough COVID-19 infections (Iatronet.gr, 2022), we have unfortunately seen some ICUs or whole departments temporarily closed (In.gr, 2021). Recently, on 30.6.2022, a young patient lost a liver transplant due to a shortage of anesthesiologists (News4health.gr, 2022).
Regarding in public health, the general picture that Greece has presented since the introduction of compulsory vaccinations is, unfortunately, not the most promising, especially in comparison to other EU countries and the United Kingdom. Out of 28 countries, it ranks as low as 17th in confirmed deaths from COVID-19 per million people as well as in excess mortality in general (Fig. 5) (Hannah Ritchie et al., 2020). These facts do not necessarily mean that the suspensions of HCWs are solely responsible for the overall crisis in Greece, but they probably played a detrimental rather than a beneficial role, as we explained in the previous sections.Fig. 5 Comparative charts of 27 EU countries and the United Kingdom (1.9.2021 to 31.5.2022) showing A cumulative COVID-19 deaths per million people; B percent excess mortality (Hannah Ritchie et al., 2020)
Other considerations regarding politics and policies
During the pandemic, the government discussed decisions with a multidisciplinary committee of experts, who have developed the guidelines. By definition, medical guidelines apply recommendations regardless of the level of evidence. Two major limitations in the development of guidelines are the consideration of patient co-morbidities and potential conflicts of interest for the members of the panel of experts. The inability to provide individualized guidance is probably associated with serious drug-related adversity in a patient with multiple co-morbidities (Franco et al., 2020). In addition, it has been estimated that in the panel of experts, approximately half of the members may have had conflicts of interest (Franco et al., 2020). The expert committee’s role should be to express recommendations, and to provide a background of concepts that constitute the framework under which specific policy decisions will be discussed and implemented (Barros, 2017). Ideally, misguided political decisions could be avoided through properly structured and continuous discussions with the expert group (Barros, 2017). The experts should always be on alert to adapt their guidance in accordance with fluctuations in the pandemic’s course as well as the consequences of imposed measures. Authorities should be flexible in renewing guidelines and adapting to new concepts regarding COVID-19 (Ioannidis, 2021). Moreover, they should be open to complementary advice or criticism from external experts, even from the international community. In this way, proper political choices could be adopted to improve citizens' lives (Barros, 2017). Politics, as a science, carries the role of society’s doctor (Lepawsky, 1967). As the doctor investigates the symptoms and the ailment of a patient, searching for the proper cure, politics should also investigate and formulate treatments for the ailments of society. These two different sciences can be distinguished, though with difficulty, in modern societies (Krakauer, 1992). Although their effective cooperation can be socially beneficial, it is crucial that there exists a clear distinction between them in order for medicine to function independently, without being politically manipulated (Krakauer, 1992; Merskey, 1978). The doctor probably needs to maintain a degree of distance from politics, always following the Hippocratic principles of “First, do no harm” (“primum non nocere”), or more correctly “Help, or do not harm” (ὠφελέειν, ἢ μὴ βλάπτειν), as was originally stated (Krakauer, 1992).
In regard to the legal status of applying compulsory vaccinations to HCWs, in addition to statements by the House of Lords committees, we will mention the decisions of the courts in the United States and India. Foremost amongst them is the decision of the US District Courts for the Western District of Louisiana and the Eastern District of Missouri, both of which found the mandatory vaccination of HCWs in the United States to be defective and entered preliminary injunctions against its enforcement (Louisiana v. Becerra, 2021 WL 5,609,846 (30.11.2021); Missouri v. Biden, 2021 WL 5,564,501 (29.11.2021)). In each case, the Government moved for a stay of the injunction from the relevant Court of Appeals, which was dismissed by the Supreme Court of the United States on 13.1.2022 (Nos. 21A240 and 21A241, cited as 595 US (2022)). Similarly, the Supreme Court of India recently underlined that bodily autonomy and integrity are protected under Article 21 of the Constitution, issued such that no person can be forced to get vaccinated against COVID-19, and directed the central government to make the adverse effects of vaccination public (Vani Mehrotra, 2022). On the contrary, Germany’s top court approved the vaccine mandates for HCWs (Euronews, 2022), but as we reported, the measure has not been implemented in practice.
Therefore, it can be deduced that the imposition of draconian measures, cultivation of an irrational fear of an infectious agent, and segregation of citizens carry the risk of stigmatizing persons or groups. Stigmatization and segregation are unacceptable in civilized societies, as they can lead to further major public health and social issues (Yuan et al., 2021). An increase in domestic violence and suicide attempts among young people has already been demonstrated (Kourti et al., 2021; Yard et al., 2021). There have also been reports of appalling events worldwide, including a student’s suicide due to bullying about his vaccination status in the United States (Joshua Rhett Miller, 2022). Consequently, a published correspondence noted that “stigmatizing unvaccinated people is unjustified” according to the cumulative data of the pandemic (Günter Kampf, 2021a, 2021b), and from an ethical point of view, the justification and imposition of mandatory vaccinations requires robust scientific evidence that the policy will achieve the intended goal in addressing a health emergency of dramatic proportions (e.g., extreme death rate) (An Roinn Sláinte Department of Health, 2021). By definition, a government should be intolerant to situations that involve the creation of excluded, marginalized, or segregated citizens and constantly strive to address concomitant social inequalities and the related issues that arise (O'Donnell et al., 2021). According to the World Health Organization (WHO) Director for Europe, Dr. Harry Klug, vaccine mandates could be a risky approach, increasing social inequalities (Ashleigh Furlong, 2021). In addition, according to WHO, even in hypothetical situations where they can be justified, the re-deployment of HCWs who refuse to vaccinate is definitely a better, more humane, and, colloquially, a “win–win” situation compared to the profoundly harsh punishment of unpaid suspension (O’Sullivan, 2022). Thus, it is utterly dismaying when the political authorities could promote inequalities and social exclusion. As clearly pointed out by Viladrich A, “Without drastically enforcing antidiscrimination laws for all federal employees—including top-ranked politicians—inclusive language and educational booklets against stigmatization will merely remain ‘lip service’”. This essentially means that if the political authority is not somehow subjected to control, the democratic principles that form the basis of Western civilization are placed at risk (Viladrich, 2021). Segregation and inequality create a strong oxymoron in Greece, the country that gave birth to democracy 2,500 years ago.
Conclusions
In summary, mandatory vaccinations for COVID-19 can raise medical, social, and ethical concerns. Politics and medicine are completely disparate, but through their transparent cooperation, they can be life-saving in times of a health crisis, contributing to multidimensional healthcare. Mandatory vaccination of HCWs in Greece does not seem to have improved the pandemic’s outcomes and, in addition, has produced a quantitative and qualitative shortage of staff that may have contributed to increased inpatient mortality. In addition, vaccinated individuals can contract and transmit SARS-CoV-2, so the mandatory requirement does not seem to be in a potent factor in pandemic management. Furthermore, it is necessary to design and complete randomized controlled trials to address the critical issues discussed in this paper, especially regarding the mid- and long-term adverse events of current vaccines. We sincerely hope that the scientific community will re-evaluate bioethics principles and the medical data toward maintaining the fundamental Hippocratic principles. Our duties as scientists are to ensure that our actions promote well-being and avoid harm to the public and individuals, and this includes avoiding silently backing a potentially flawed political model of pandemic management in such a complicated and unclear medical and scientific challenge.
Acknowledgements
We would like to thank Dr. Georgios Syrpis (Psychiatrist, Hippokration General Hospital) and lawyer Sotirios Gekopoulos (BSc Law School, BSc School of Economics and Political Sciences, Aristotle University of Thessaloniki) for their assistance. We also want to thank Dr. Konstantinos Poulas (Associate Professor of Biochemistry, Dept. of Pharmacy, Univ. of Patras Director of BioHealth Hub, Patras Science Park) for critical reading.
Funding
This research received no external funding.
Declarations
Competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36477872 | PMC9734873 | NO-CC CODE | 2022-12-14 23:28:31 | no | Hist Philos Life Sci. 2022 Dec 7; 44(4):72 | utf-8 | Hist Philos Life Sci | 2,022 | 10.1007/s40656-022-00548-1 | oa_other |
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AI Soc
AI Soc
Ai & Society
0951-5666
1435-5655
Springer London London
1592
10.1007/s00146-022-01592-y
Original Article
Characterizing the perception of urban spaces from visual analytics of street-level imagery
Freitas Frederico 1
Berreth Todd 2
Chen Yi-Chun 3
Jhala Arnav [email protected]
3
1 grid.40803.3f 0000 0001 2173 6074 Department of History, NC State University, Raleigh, USA
2 grid.40803.3f 0000 0001 2173 6074 Department of Art and Design, NC State University, Raleigh, USA
3 grid.40803.3f 0000 0001 2173 6074 Department of Computer Science, NC State University, Raleigh, USA
4 12 2022
111
30 5 2021
25 7 2022
© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
This project uses machine learning and computer vision techniques and a novel interactive visualization tool to provide street-level characterization of urban spaces such as safety and maintenance in urban neighborhoods. This is achieved by collecting and annotating street-view images, extracting objective metrics through computer vision techniques, and using crowdsourcing to statistically model the perception of subjective metrics such as safety and maintenance. For modeling human perception and scaling it up with a predictive algorithm, we evaluate perception predictions across two points in time separated by economic changes in the urban core of Raleigh, North Carolina, in the aftermath of the 2008 Great Recession. We hypothesize specific socioeconomic processes can be substantially reflected in the built environment of cities and, thus, render themselves visible at the street level. This paper describes the process of incorporating subjective visual ratings across two datasets of temporally separated street-view images, an algorithm, and a visualization tool. This work serves as a case study for utilizing AI and visualization techniques in a richer characterization of urban spaces that includes both objective metrics such as income (that operates at a broader scale) and subjective metrics such as perception of individuals (that operates at a narrower scale at specific locations). We outline an interdisciplinary methodology to test this hypothesis in streetscape data from Raleigh, NC, from 2008 to 2020. We describe the results of training algorithms that utilized image features with crowdsourced human perception ratings. We provide a comparison of the results with income data. The analysis and interpretation of this comparison provide insight into the challenges and opportunities for using AI technology in characterizing changes in urban environments. One challenge is the ability of human domain experts to interpret the output of algorithms through manipulation and to integrate these results into their workflow. This is addressed with a novel interface designed for interactive analysis and visualization. We conclude with a discussion of some of the benefits and limitations of integrating AI models in the human expert’s decision-making process in the presence of both subjective and objective metrics.
Keywords
Urban studies
Interactive analytics
Feature mapping
Machine learning
Computer vision
Streetscape photography
Geographic information systems
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pmcIntroduction and motivation
This project studies AI-based tools to characterize human perception of urban spaces at the level of street photographs. This is done using state-of-the-art machine learning and computer vision techniques to model perception of inequality in terms of safety, maintenance, and architectural features. Between the late 2000s and mid-2010s, the Great Recession ravaged most countries’ economies and societies. It was a global crisis gestated and realized in cities, but its effects on the physical urban landscape are still poorly understood. We hypothesize that the effects of the crisis were substantially reflected in the built environment of cities and visible at the street level. To test this hypothesis, we analyze the streetscapes of neighborhoods in Raleigh, NC (USA) in the 2008–2020 period. For such a study, urban history researchers must utilize computational interfaces and methods to analyze streetscapes at scale. For about a decade, the crisis’s effects unfolded visually in the urban environment, which is reflected in the data available from Google Street View (GSV). In addition to traditional quantitative metrics (i.e., spatialized measures of income, housing, employment, etc., over time), this visual assessment of streetscape change could help social scientists and policymakers with an additional tool to either corroborate or dispute the expected spatial distribution of the crisis across a metro area. The distinctions between these distributions can illuminate how changes in the visible streetscape diverge from, lag, precede or parallel other changes in the human condition during economic recessions.
In this paper, we demonstrate that predictors trained using generic image features and annotated with human perception scores of street-level indicators of economic health of neighborhoods from a crowdsourced study can be utilized to scale up analysis to larger regions. We evaluate the predictive power of different image features commonly used for scene understanding and illustrate how these models can be useful for social scientists, urban planners, and policymakers in their analysis. We discuss how expert interactions with AI predictions and human-in-the-loop ML interpretive interfaces (exploratory geovisualizations) often allow an expert to accommodate for a model’s weaknesses through expert knowledge. Our approach is validated by comparing the changes observed in household income data and its correlation with changes in image ratings from similar periods. We annotate images between 2011–2013 and 2016–2017 and add household income data for these periods. The periods are chosen based on the availability of a sufficient number of images for statistical comparison.
From a social science perspective, we seek to improve the understanding and characterization of the effects of economic recessions observed at multiple scales. Several significant advances in this research area have been made with the use of generalized socioeconomic data as well as detailed (although highly localized) social science surveys (Hwang and Sampson 2014; Hwang 2015; Moye 2014; Pfeiffer and Lucio 2015). Our project expands research in this field through the integration of AI technology in the analysis process by:Grounding the analysis of urban renewal and decline at the street level by providing human analysts with the tools to access features of the visual environment processed by computer vision techniques.
Presenting novel methods of interactive exploratory geovisualization that integrate geographic and multidimensional views of street attribute data produced by artificial intelligence algorithms.
Introduce a process for augmenting AI models with crowdsourced subjective ratings for interpretation by urban studies experts.
The perception of safety and reality
There are several metrics that could be utilized to characterize safety of a specific street, neighborhood, or city. Crime data is being systematically collected and analyzed across the world at different regional scales. Sources such as City Data1 organize and show detailed crime statistics by city by crime category (theft, vandalism, murders, etc.) and change of safety measures over time. Figure 1 shows the interface for crime data in Raleigh at the city level in terms of crime per 100 k residents with comparison to nearby towns.Fig. 1 Crime map and safety score based on crimes per 100 K residents from city-data.com
Such metrics are useful at a high level, similar to income, zoning, and real-estate data to characterize the safety at the city level. A comprehensive study of how crime data matches street-level perception of safety promises to offer rich insight as further work on this topic. This process will benefit from ongoing work by entities like the Smart Cities Council2 that is looking at crime rate and response times across many regions consistent with international standard ISO 37120:2014 that provides clearly defined performance metrics and the process of collection and reporting. Further data from these and other similar standard sources would add to the depth of analysis coupled with the human perception approach outlined in this paper.
Threats to validity and the risk of Code Hubris
The choice of algorithms, survey instruments, and statistical tests all impact the results and their interpretation. In terms of data collection and human annotation, the quality of images is important because annotators looking at higher quality images on larger screens are able to see more detail that could affect their perception rating. The social, economic, and cultural background also affects the interpretation of subjective metrics. From a modeling perspective, this work utilizes a Bayesian ranking algorithm for modeling the relative perception of images. This assumes that the images are sampled from a normal distribution over their perceived ratings. In the absence of the availability of the true underlying distribution, this is a reasonable initial assumption. This model also allows us to directly compare this work with previous work from the StreetScore and PlacePulse projects that make a similar assumption. The statistical tests are appropriately chosen for determining the significance of the statistical correlation between features. As with all scientific research, progressive improvements are expected with an improved understanding of the underlying phenomena and feature relationships. Finally, the amount of data needed for pairwise rankings depends on the number of domain features and consistency of annotators.
It is essential to explicitly state that the work presented in this paper neither claims to offer a completely automated approach to prediction nor does it claim to accurately characterize/provide commentary on the underlying subjective social and cultural factors that are a critical part of the visual imagery and its perception. This work introduces a set of tools and a methodology for using the tools that provide human researchers with observations, processing methodology, and visual insight into the problem that has as yet not been seen from this perspective. Much work needs to be done with these tools as expert quantitative geographers adopt them in their tradecraft. As Birhane (2021) states in a recent paper, “… the more socially complex the problem is, the less accurate machine learning systems are of accurately classifying, predicting …” We understand that researchers, policymakers, and stakeholders are equally challenged by the complexity of such social phenomena. Still, we recognize that the current availability of untapped data (e.g., GSV images) opens new opportunities for a critical inquiry into the use of algorithmic tools. That said, the paper puts social science questions as primary drivers of this project with the tools engineered to support these questions because this allows us to work with real data and real questions. Unlike Rey’s (2019) characterization of data scientists’ work that claims expertise in application domains, we have an interdisciplinary group of social scientists, humanities scholars, visual designers, and engineers that are represented in this project and the process that the paper describes.
Background
Historical and urban studies background
The Great Recession started in cities with the burst of the US subprime mortgage bubble in December of 2007, and from there, it spread to the rest of the globe. Several studies have characterized the different scales of the crisis as interconnected and mutually constitutive, pointing out the linkages between the global economic downturn and the fate of local urban geographies such as neighborhoods. Given the importance of homeownership in the US economy, US cities constituted ground zero for the crisis (Newman and Schafran 2013; Aalbers 2012). The recession and the austerity measures taken to address its effects were not equally felt across the North Atlantic economies, affecting some regions and nations more than others (Kitson et al. 2011; Harvey 2012). The crash also brought fiscal retrenchment and the down-streaming of austerity policies to the level of local city governments. The housing slump and mortgage foreclosures affected local city revenue, especially in the United States, where public services disproportionately rely on property taxes (Peck 2012; Donald et al. 2014). At the local scale, the Great Recession had an uneven effect, with mass foreclosures leading to the clustering of low-income groups in particular neighborhoods and areas harboring many ethnic or racial minorities undergoing a rapid process of decline (Zwiers et al. 2016). These regressive trends also, at times, opened space to unorthodox and countering forms of urbanism in newly vacant spaces (Tonkiss 2013).
Since the height of the crisis, studies have used various quantitative and qualitative methods to assess the effects of the great recession on the urban landscape. In their study of Phoenix, Pfeiffer and Lucio (2015) used property-level data on real estate transactions and subsidized housing vouchers to demonstrate that foreclosed homes purchased by investors expanded the geography of opportunity for low-income renters. Using city data for Philadelphia, Moye (2014) showed how the pre-crisis housing boom allowed a modest process of racial integration to occur, with some African-Americans moving into predominantly white neighborhoods. Minn et al. (2015) used Landsat imagery to assess the upkeep of lawns and gardens in urban and suburban lots in Maricopa County (AZ) before and after the housing crisis. These case studies reveal the diversity of processes in place in different cities in the United States during and after the Great Recession. However, they fail to capture a crucial dimension of the production of urban spaces—the visible changes occurring at the street level.
In her classic study of urban life, The Death and Life of the Great American City, Jane Jacobs used street-level observation to understand the social processes that make a neighborhood safe (Jacobs 1992; Perrone 2019). Her observation of city life informed her theory of how the built environment affects how people act on the street. This type of visual assessment of urban life rooted in the experience of city dwellers is also present in other influential studies. In The Image of the City, Lynch (1960) analyzed how people perceive—and find their way through—the urban space utilizing visual elements such as paths and edges. These studies and others that follow in this vein conclude that the visible, physical form of public space is crucial in reflecting and producing the human condition. People experience urban spaces through their senses—primarily through sight—and images of a city can provide essential information about the development of a cityscape. This project draws on the insights of Jacobs and Lynch to propose a visual assessment of the effects (e.g., gentrification, decay) of the Great Recession on the landscape of a city (Criekingen and Decroly 2003). It does that at scale, employing machine learning (Reades et al. 2019) and computer vision techniques to expand spatially and temporally what a surveyor, or a group of surveyors, could capture solely by walking the streets of the selected cities (Yoshimura et al. 2018).
As one of the fastest-growing urban areas in the United States in the past decades, Raleigh offers an ideal case study for testing an image-based tool for assessing urban change. Between 2010 and 2019, the population of Raleigh grew 17 percent, from about 404,000 inhabitants to 474,000. The increase in the size of the city was also spatial, particularly in the suburbs, reflecting the urban sprawl of many cities in the North American Sun Belt. Like many other North American cities growing spatially, Raleigh also experienced a period of urban decline in its core areas before the 1980s. This decay started to be reversed in the last decades, first with the listing of the Oakwood neighborhood as one of the first National Register of Historic Places Districts in North Carolina. Designated in 1975, the nineteenth-century neighborhood of Victorian homes became an example of the use of historical preservation tools to prevent highway development and disruption (Schulman 1991; Raleigh Historic Development Commission 2021). From the 1990s on, Raleigh has also experienced accelerated growth driven by the boom in the technology industry stemming from the consolidation of the Research Triangle Park as a major technological hub in the United States (O’Mara 2005; Cummings 2020). Such growth has induced changes in Raleigh’s urban core, with the gentrification of traditional working-class neighborhoods in the city’s south and eastern areas, a process that intensified despite the effects of the Great Recession (Badger et al. 2019). As a mid-sized city that has experienced different types of suburbanization, urban decay, and, more recently, gentrification, Raleigh offers an excellent case study to test our method of assessing urban change through the visual analysis of a changing streetscape.
Computer vision and the built environment
In recent years, computer science and urban studies researchers have increasingly used computer vision and machine learning techniques in the visual study of cities and other types of locations. They employed pre-annotated datasets of geo-tagged images to train convolutional neural network algorithms (CNNs) to identify visual features and then used these algorithms to analyze larger datasets of images without annotation. For example, researchers used trained CNNs to define the visual identities of 21 cities across the globe (Zhou et al. 2014); to correctly determine the location of a photo with no geographical metadata (Weyand et al. 2016); and to measure visual similarities between architectural designs by different architects (Yoshimura et al. 2018). The rapid explosion of nearly comprehensive street-level geo-tagged image panoramas for most cities on the planet has offered a new source of consistent urban images for studies that use computer vision. Doersch et al. (2012) produced an earlier study using GSV images to discover the architectural elements that define specific urban spaces. They found, for example, that what makes a city like Paris look like Paris was not so much the presence of famous landmarks such as the Eiffel Tower but rather a set of stylistic architectural elements reproduced throughout Paris but not present in other cities. Another project extracted 22 million distinct vehicles from GSV images of 200 US cities to correlate the year, make, model, and body type of cars and trucks to socioeconomic and voter preferences data. They found out that pickup trucks are spatially related to areas with a more robust Republican voter turnout across the United States (Gebru et al. 2017).
Another avenue of inquiry opened by machine learning techniques is the study of the perception of urban spaces. The Place Pulse 1.0 (Salesses et al. 2013) project was one of the first computational studies on the visual perception of cities. Using GSV images from New York and Boston and captured images from two Austrian cities as data, this crowdsourcing project invited participants to rank pairs of streetscape images in response to the question “Which place looks safer?” They aimed to capture how people perceive some places as safer than others, a dimension that only partially correlates to quantitative measures of income and crime. A step beyond was taken by the StreetScore project (Naik et al. 2014). The researchers led by Nikhil Naik used the original Place Pulse data, which was produced by humans on a limited dataset of GSV images from two cities (New York and Boston), to train a computational model of visual classification. They intended to reproduce a similar ranking of perceived visual safety for a larger corpus of GSV images of 21 cities in the US Northeast and Midwest. After classifying the images, they confirmed the predictive power of the StreetScore algorithm through the use of income data as a proxy metric of accuracy for cities absent from the original crowdsourced study. They also produced an interactive online visualization featuring five cities included in their study. They concluded that scores of perceived safety from a crowdsourced study (e.g., Place Pulse) could be used to train an algorithm to accurately predict the perceived safety scores of streetscapes not used in the original dataset. Quercia et al. (2014) conducted a similar study, using the crowdsourced annotation of pairs of images, but correlating it to visual features in the streetscape images such as color and texture. Others have expanded the work of StreetScore, using different CNNs to rank the crowdsourced image annotations (Porzi et al. 2015); combining data on visual perception or the urban landscape with other datasets such as mobile phone use or real estate value (De Nadai et al. 2016; Fu et al. 2019); or adding crime event records to test the difference between the perception and the reality of safety (Liu et al. 2017).
However, StreetScore had two critical limitations addressed in follow-up studies. First, the algorithm was unscalable, for it was trained with crowdsourced data from Place Pulse 1.0 produced with images of only New York and Boston. StreetScore performed well in predicting the perception of safety for cities in the Northeast and Midwest United States but lacked accuracy for other urban areas. Place Pulse 2.0 (Dubey et al. 2016) attempted to solve the problem by expanding its training dataset to 56 cities in 28 countries. The training dataset was produced with a combination of crowdsourcing and machine learning techniques. A new set of questions was introduced to measure perceived beauty, boredom, and wealth. Second, StreetScore did not incorporate temporal change. This latter limitation was first addressed by Naik et al. (2017), who took advantage of the fact that GSV captures images of the same streets in different years. Using GSV images from 2007 and 2014, they calculated StreetScore indexes for street blocks in Baltimore, Boston, Detroit, New York, and Washington DC and calculated the StreetChange index—the difference between the StreetScore of the two years. A StreetChange positive value meant an upgrade in physical appearance; a negative value meant a decline. Recently, Ilic et al. (2019) followed the Pulse Place protocol to create their own crowdsourced dataset of street-view annotations for Ottawa, asking participants about property improvement instead of safety. Their interest was to map gentrification, a process characterized by changes in space over time. Thus, they incorporated time in their analysis, using CNNs to detect change in GSV images in five different periods between 2007 and 2015.
Data collection and annotation
We created a dataset of images from a 64 km2 square encompassing the urban core of Raleigh, NC, from GSV images. We algorithmically corrected the perspective for each GSV image and split the 360º image into four two-dimensional images (i.e., front, back, and two sides).
Algorithmic annotation—Our project leverages two popular machine-learning techniques and open-source software libraries. The first, used to build the base image feature datasets, is a CNN-based computer vision object detection system (currently YOLOv3) (Redmon et al. 2018). We are able to train desired image classifiers (e.g., what does a building facade, commercial sign, window, or mailbox look like), which are then used to autonomously mine photographic archives and extract these features (and their associated geolocation/temporal metadata), depositing the results in a database. The second, used to process the image feature datasets, is an ML technique for dimensionality reduction, either t-SNE (van der Maaten et al. 2008) or UMAP (McInnes et al. 2018), useful for visualizing high-dimensional datasets without human training.
Human annotation—It has been shown that statistical models provide better results in predicting subjective questions when trained on data on relative comparison of items by humans rather than their ordinal ratings of individual items (Yannakakis and Martinez 2015). A well-established and interpretable model of preference ranking is the TrueSkill algorithm that learns to rank based on a trained Bayesian factor graph of features (Herbrich et al. 2006). For this study, we collected 6000 pairs of street-level images and compiled over 7200 pairwise ratings from US and Canada-based annotators on Amazon’s Mechanical Turk platform. The 6000 pairs contained repeated individual images in both orders (left and right) and were matched with images with different feature profiles for pairing. Some image pairs were also assigned to different annotators for measuring agreement. Each annotator was shown a pair of images, A and B. Then they were asked to choose on a four-point forced-choice scale (A, B, Both, Neither) to answer five questions about their perception of which location looked safer, wealthier, newer, better maintained, and more occupied.
Household income—To compare algorithm prediction to external markers, we took household income by region from previous census data. This household income data are from 2011–2013 to 2016–2017. These two periods were chosen based on the total number of available street-level images and their distribution in a variety of neighborhoods of Raleigh in our image dataset. The income dataset is available as aggregates in regions (i.e., census blocks). We assigned average income to each image based on the geolocation of our images inside income regions. We will make the income annotated data along with associated scripts for geolocation and income assignment available to the research community for reproducibility and further research.
Bayesian model for subjective perception measures
To train a prediction model based on pairwise comparison ratings from human annotators, we adapt the TrueSkill algorithm (Minka et al. 2018) developed at Microsoft for generating player rankings on their multiplayer game platform. The algorithm assumes that all image ratings fit a normal distribution regarding the features in question (safety, wealth, occupancy, maintenance, and age). Each image has a rating μ and a confidence σ2. The Bayesian factor graph of features is then trained on human ratings of pairs of images by updating the skill and confidence of each image. In this project, we treat each image as a player playing against the other image and the human rating as the result of their matchup. The resulting trained model provides a prediction of unseen images and is able to offer a ranking of all the images in our dataset.
To illustrate the approach's usefulness, we analyzed the rated images in our dataset of images from a 64 km2 area in the Raleigh urban core. Figure 2 shows the distribution of predicted safety values by the model overlayed on the geolocation of the respective images. Sample images that are present in different score levels are also shown. In terms of real-estate, economic, and crime data, the region closer to downtown and on the southeast side is perceived as being less safe. There are spots on the northwest side that are perceived as less safe. These images correspond to some industrial developments. Our tool affords filtering and region selection. For illustrative purposes, we divided the region into four quadrants. The tools afford more specific groupings such as neighborhoods or subdivisions.Fig. 2 (Above) Distribution of predicted safety values on a map of Raleigh. (Right) Images and corresponding predicted safety scores. The four images shown illustrate examples from 4 levels of safety
Interactive visualization and analysis
The data collection algorithm and scripts and the ranking algorithm are not readily accessible to urban studies experts. It is challenging to model error in terms of specific features due to the subjective nature of the task. To better integrate the computational tools and algorithms with the analysis methods for scholars, we designed a novel interactive interface called the Street-Feature Location Mapping Tool (SFMLT). This tool provides a visualization of images clustered in the visual feature space, on the geospatial map, and overlays of predicted scores.
The street-feature location mapping tool
This project developed an interactive visualization tool that features a two-panel mapping interface where the right panel has a geospatial map with selection and annotation tools, and the left panel harbors an assortment of 2D/3D scatter plots and cluster-grid thumbnails of the street-level photographic corpora, with similar selection tools. The tool allows expert users to work back and forth between these two panels to select and prune a collection of images, which are visualized as a spatial heatmap in the right panel and a cluster visualization on the left panel. These selections can be exported and saved for later use (Fig. 3). Combined with maps based on our enhanced GSV analysis, the tool allowed researchers to compare and contrast the effects between urban areas, reveal the narratives and dynamics, and extract data derived from GSV coupled with other spatial information. This visualization tool ultimately offers a system based on the application of artificial intelligence/machine learning modalities and computer vision techniques to massive multi-year databases of street-level photography. It provided a platform featuring several novel interactive interfaces, making it possible to navigate and explore data and extract visual features for the case study.Fig. 3 Street Feature Location Mapping Tool: grid-based clustering of commercial facades in a 64 km2 region of Raleigh, NC
Fig. 4 Top left-Images clustered in feature space and visualized on a grid. Highlighted group represents images of churches, clustered by the algorithm based on architectural features. On the top right are the geo-locations of the images. SFLMT tool allows interactive analysis in both feature and location spaces
For such image corpora analysis, the use of unsupervised ML dimensionality-reduction techniques (e.g., t-SNE, UMAP, or PCA—van der Maaten et al. 2008; McInnes et al. 2018) and supervised ML techniques such as CNNs is well established as are the functionalities of GIS for spatial mapping and analysis. However, spatially tagged photographic corpora are a unique use case for image analysis, and a geospatial dimension can provide a critical context for finding meaning in ML-derived query results. In this sense, SFLMT’s hybrid interface offers interactants the capacity to work fluidly between the ML-produced computational feature space (CFS), and a more traditional cartographic space (CS), allowing complex queries and explorations into spatially tagged image corpora (image data points have a representation in each space). Users can explore relationalities and potential narratives within the corpus through a bi-directional process of navigation, selection, and pruning, thus tweaking the parameters of each map to curate a collection of images (and subsequent geospatial mapping) derived out of the corpus.
With SFLMT, users can move back and forth between computational and cartographic spaces to find correlations between the configurations of the data points in each spatial context (their relationalities, densities, and absolute positioning). They can selectively plot these features—along with other potentially relevant data points (socioeconomic data, etc.)—to locate feature clusters (singly or in compound queries) across urban landscapes. Conversely, users are able to delineate geographic regions in the CS and see mappings within the CFS. Researchers can pursue open-ended questions as they explore and modify the properties and parameters of each space and visualize patterns between representations.
In our initial design, the CFS is contained in the left panel; it is a graph space where the images are located either as points in a 2D point cloud or scatter plot (graphing two desired image features or location-related variables) or compressed into a grid raster representation (for ease of navigation and manipulation, by necessity distorting the original plot). The CS is contained in the right panel; it is a 2D map representing the locations of the photographs, with positional pins and added visualization features such as overlayed density heatmaps (emphasizing the densities and gradients of the image distributions). The panels have identical tools for selecting and deselecting items or regions, undoing actions, providing research annotations, and saving selections; selection and deselection actions in any panel affect all panels (Fig. 4).
This implementation of the SFLMT (HTML/Javascript/WebGL) allows for the interactive visualization of clusters of tens of thousands of street-level image features (e.g., building facades, street signs, people, and vehicles) or more granular street-level visual features (e.g., architectural details), scraped autonomously from geolocated street-level photographic corpora (such as GSV). Our project leverages two popular machine-learning techniques and open-source software libraries. The first, used to build the base CFS image feature datasets, is a CNN-based computer vision object detection system (currently YOLOv3) (Redmon et al. 2018). The second, t-SNE, is a popular dimensionality reduction and visualization technique, which we use to analyze all images in our particular feature corpus—i.e., all building facades—and autonomously cluster visually similar images together in a 2d spatial plot. It can roughly cluster building facades into groupings suggesting architectural style or usage without training. Initial experiments of one urban corpus (all GSV images from a 64 km2 region of Raleigh, NC, within a 3-years period) found feature clusters of Victorian, Neoclassical, and Modern Ranch houses, functional categories like skyscrapers, strip malls, and churches, though also oddities such as cottages with white picket fences, and even begin to cluster abandoned/dilapidated buildings. The adjacencies are not perfect—these techniques are as much of an art as a science. They require designing interfaces that allow the user to begin to organize, cull, or reconfigure the tools and results, teasing out valuable patterns. Phenomena such as gentrification, urban decay, the spread of architectural styles, the use of different building materials, textual analysis of urban signs, social uses of public space, urban flora, etc., are explorable through these techniques and types of interfaces.
While this prototype deals specifically with streetscape image features, the SFLMT could be used to work with any geospatially tagged digital media objects (not just images). The critical innovation involves linking the CS with one or multiple CFSs for interactive engagement and curation by the user. For example, an ornithologist might interactively explore a collection of geospatially tagged bird call audio samples, working between a CFS (for example, a t-SNE clustering plot of audio data points by Tan and MacDonald (2018)) and the CS showing sample locations, to curate a collection of bird calls, and potentially ascertain territorial regions of a particular species. This curation task might be improved by adding other CFS panels, which analyze other aspects of the audio samples, the combined linked spaces allowing a more refined curation.
Analysis of street-level markers of recession in Raleigh’s urban core
We analyzed the distribution of predicted ratings along the dimensions of safety, wealth, occupancy, maintenance, and age in the area in and around Raleigh. The upper right chart in Fig. 5 shows the distribution of predicted safety scores of images from the four axis-aligned quadrants on the map. We rank all images based on their absolute safety scores and group them in four quartiles from highly safe (Blue/Level 4) to unsafe (Red/Level 1). The northwest quadrant of Raleigh has the most images labeled by the algorithm as safe, and the southeast quadrant has the lowest number of images labeled safe. There are fewer images labeled unsafe on the northern half of Raleigh compared to the southern one.Fig. 5 Distribution of ratings per quadrant in the Raleigh urban core
The mid-right chart in Fig. 5 shows the distribution of predicted wealth scores of images from the four axis-aligned quadrants on the map. We rank all images based on their absolute safety scores and group them into four quartiles from wealthy (Blue/Level 4) to poor (Red/Level 1). Results indicate that the northeast region has the most images associated with higher wealth. The southeast region has the least number of images labeled as indicating wealth.
The mid-left chart in Fig. 5 shows the distribution of predicted occupancy scores of images from the four axis-aligned quadrants on the map. We rank all images based on their absolute safety scores and group them into four quartiles from occupied (Blue/Level 4) to unoccupied (Red/Level 1). Results indicate a pattern of predominant moderate occupancy ratings across the four quadrants, which is different from the two previous indices (safety and wealth). Furthermore, the southern half of the urban core presents a higher rate of unoccupied and moderately unoccupied buildings when compared to the northern quadrants.
The bottom left chart in Fig. 5 shows the distribution of predicted maintenance scores of images from the four axis-aligned quadrants on the map. We rank all images based on their absolute safety scores and group them in four quartiles from well-maintained (Blue/Level 4) to not maintained (Red/Level 1). Results indicate high maintenance ratings for the northern half compared to the southern half, which is consistent with safety, wealth, and occupancy ratings.
The bottom right chart in Fig. 5 shows the distribution of predicted new development scores of images from the four axis-aligned quadrants on the map. We rank all images based on their absolute safety scores and group them into four quartiles from newer (Blue/Level 4) to older (Red/Level 1). Results indicate newer development in the northeast region and older areas in the southeast.
Comparison with income data
To directly compare algorithm-predicted ratings and other economic markers, we annotated each image with household income data at the census block level. We chose time periods 2011–2013, with 2393 images in our dataset, and 2016–2017, with 1883 images. We labeled each image in the dataset with a corresponding median household income value in that region based on geolocation data. To analyze the relationship between perceived scores predicted by the algorithm and income, we first take the entire dataset of 5930 images where income data is available in the neighborhood and run the Pearson correlation test on safety perception scores without considering the time feature. This yields a correlation coefficient of 0.41 with a p value < 0.001, indicating a moderate positive correlation. Increase in perceived scores correlates with increase in household income values.
We next split the dataset into images from two different time periods and run the correlation test on each time period separately to see whether there is a significant difference between the relationship between income data and ratings. Table 1 shows the results of the correlation tests for separate time periods for five different perception ratings. All of the results are statistically significant. Safety, Completeness, and Maintenance have a moderate correlation. Occupancy rating has a low correlation coefficient. The newer (Age) rating correlation with perception scores has significant differences across the two time periods. In 2016–2017 the perception of safety for the age of buildings is higher. This may be due to the construction of several new condominium buildings in 2016–2017 in downtown that were not there in 2011, particularly in the east and southeast parts of the city.Table 1 Pearson correlation test between predicted ratings and household income data for the two time periods between 2011–2013 and 2016–2017
2011–2013 2016–2017
Complete Coefficient 0.29 Coefficient 0.31
N 2393 N 1883
T statistic 14.6 T statistic 13.99
DF 2391 DF 1881
p value 3E − 46 p value 2E − 42
Safe Coefficient 0.328803 Coefficient 0.31
N 2393 N 1883
T statistic 17.02 T statistic 14.36
DF 2391 DF 1881
p value 2E − 61 p value 2E − 44
Maintained Coefficient 0.27 Coefficient 0.3
N 2393 N 1883
T statistic 13.92 T statistic 13.53
DF 2391 DF 1881
p value 2E − 42 p value 7E − 40
Occupied Coefficient 0.15 Coefficient 0.19
N 2393 N 1883
T statistic 7.2 T statistic 8.6
DF 2391 DF 1881
p value 8E − 13 p value 2E − 17
Newer Coefficient 0.17 Coefficient 0.28
N 2393 N 1883
T statistic 8.4 T statistic 12.66
DF 2391 DF 1881
p value 8E − 17 p value 3E − 35
N is the number of images, DF is the degree of freedom
Discussion and relevance to future work in AI and society
By studying the effects of the last global economic crisis (2008–2016) on the visible built environment of urban neighborhoods in Raleigh, this project offers a case study of the use of automatic visual data analysis at scale and predictive models for how future urban spaces will develop in response to global economic crises, including the currently ongoing Covid-19 disruption. We provide a systematic process for data collection, annotation, development of predictive models, and validation of constructed AI models. Precisely for this project, we outlined the challenges of data collection in the form of panoramic street-view imagery across a period of time, design of human annotation tasks through crowdsourcing, a Bayesian model for automatic prediction of several high-level features such as safety, occupancy, and maintenance from street-level imagery, and finally a validation step to compare the predicted model ratings to an economic indicator of median income. Our results indicate that using such AI models is promising and adds a tool to the human analyst’s toolbox. But the interpretation of results from the model and their utilization in framing the analysis report requires additional skills in terms of understanding and characterizing the noise in the data and the accuracy and confidence of the computational model. Safety scores in Raleigh neighborhoods correlate with income levels. The rapidly changing neighborhoods in downtown with new condominium buildings affect the changes in the correlation between perceived age and income. The statistically significant changes between 2011–2013 and 2016–2017 are seen at the street level in terms of correlation within each time frame with income markers. A deeper comparison across the time frames is challenging due to the lack of comparable quantity and quality of data across the time periods. We aim to follow-up with conscious data collection and annotation efforts that will lead to better models of comparison across future periods. Another dataset related to crime would also enhance analysis and prediction. Current datasets for crime reporting in our recent analysis period are sparse and unstructured. Departments of public safety are increasingly collecting more structured and nuanced data with better reporting. This is a promising avenue both for the work presented in this paper and to guide the improvement of our public data infrastructure. Early prediction of such phenomena that indicate signs of gentrification could potentially be helpful as a tool for city leaders in policymaking and interventions. It is worth noting that reported income data lags in terms of being available compared to visible signs of change that are apparent in photographs.
The project also introduces a methodology for collaboration between humanities and social scientists, designers, and computer scientists. This experience has provided an interesting insight into communication, collaboration, and trust in systems. Computational models, even as black boxes, could be useful if users can test hypotheses and validate known data. For humanities scholars in particular, it is crucial to articulate research questions and frame analytical arguments based on understanding the limitations of features expressed in the computational models.
Careful design of interactive interfaces is essential so that they are both intuitive and expressive. The current project opens up several possibilities. We plan, for example, to compare the visible effects of the crisis at the street and neighborhood scales within 15 metropolitan areas in the three largest countries in the Americas: the United States, Mexico, and Brazil. By studying these 15 cities, we will understand how global economic recessions more broadly affect the built environment of cities at the street and neighborhood levels. Our selected group of 15 metropolitan areas offers a diverse array of population size, density, and economic activity. They allow us to understand the impact of a global crisis on different urban neighborhoods and how these effects are tied to factors such as development vs. underdevelopment, industrialization vs. deindustrialization, and centrality vs. peripherality in the international system.
The project offers insights into the use of AI technology for three stakeholders. First, it provides tools to help urban planners, policymakers, and government agencies understand the dynamics of phenomena such as the 2007–20009 economic downturn, allowing them to incorporate the crisis’s lesson into mitigating the urban effects of future recessions, including the current Covid-19 disruption. Second, it introduces a methodology that uses computation and new data sources to expand the toolkits of geographers, historians, and other social scientists. Finally, it presents innovative geovisualization methods to integrate traditional GIS and multidimensional data to facilitate exploration and interpretation by scholars in multiple disciplines.
Acknowledgements
This work was carried out with support from the NCSU provost office for the interdisciplinary research cluster in Visual Narrative. Perspective correction of 360° Google Street View images was done with the help of Dr. Tianfu Wu’s research group at NCSU. We would like to thank Amazon’s Mechanical Turk platform workers for providing annotations. The quality of the manuscript was significantly enhanced due to feedback and insightful comments from the reviewers and editors of the AI in Society special issue.
Data availability
The code and data related to this project that was developed at NCSU will be provided on GitHub upon publication. Street view images and external data sources are the property of their respective owners and their availability and usage rights at the time of use will apply. A small sample of data and annotations for reproducibility will be provided by authors upon request.
1 http://www.city-data.com
2 https://www.smartcitiescouncil.com/article/dissecting-iso-37120-how-safe-your-city-hint-run-numbers-homicides-and-response-times.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734874 | NO-CC CODE | 2022-12-14 23:28:31 | no | AI Soc. 2022 Dec 4;:1-11 | utf-8 | AI Soc | 2,022 | 10.1007/s00146-022-01592-y | oa_other |
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J Autism Dev Disord
J Autism Dev Disord
Journal of Autism and Developmental Disorders
0162-3257
1573-3432
Springer US New York
36484966
5822
10.1007/s10803-022-05822-6
Original Paper
Contrasting Views of Autism Spectrum Traits in Adults, Especially in Self-Reports vs. Informant-Reports for Women High in Autism Spectrum Traits
Taylor Sara C. 123
Gehringer Brielle N. 12
Dow Holly C. 12
Langer Allison 12
Rawot Eric 12
Smernoff Zoe 12
Steeman Samantha 12
Almasy Laura 245
Rader Daniel J. 2
Bučan Maja 12
http://orcid.org/0000-0003-1417-7838
Brodkin Edward S. [email protected]
1
1 grid.25879.31 0000 0004 1936 8972 Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3535 Market Street, Suite 3080, Philadelphia, PA 19104-3309 USA
2 grid.25879.31 0000 0004 1936 8972 Department of Genetics, Perelman School of Medicine, Clinical Research Building, 415 Curie Boulevard, University of Pennsylvania, Philadelphia, PA 19104-6145 USA
3 grid.25879.31 0000 0004 1936 8972 Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
4 grid.239552.a 0000 0001 0680 8770 Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA USA
5 grid.239552.a 0000 0001 0680 8770 Lifespan Brain Institute, Children’s Hospital of Philadelphia, Philadelphia, PA USA
9 12 2022
113
8 11 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
There is uncertainty among researchers and clinicians about how to best measure autism spectrum dimensional traits in adults. In a sample of adults with high levels of autism spectrum traits and without intellectual disability (probands, n = 103) and their family members (n = 96), we sought to compare self vs. informant reports of autism spectrum-related traits and possible effects of sex on discrepancies. Using correlational analysis, we found poor agreement between self- and informant-report measures for probands, yet moderate agreement for family members. We found reporting discrepancy was greatest for female probands, often self-reporting more autism-related behaviors. Our findings suggest that autism spectrum traits are often underrecognized by informants, making self-report data important to collect in clinical and research settings.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10803-022-05822-6.
Keywords
Autism spectrum
Adult
Self-report
Phenotype
Female
http://dx.doi.org/10.13039/100000025 National Institute of Mental Health F31MH125539 Taylor Sara C. Autism Spectrum Program of Excellence
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pmcIntroduction
Autism spectrum disorder (ASD) can be thought of as a pattern of quantitative variation along several behavioral domains. In addition to the core ASD behavioral domains of social communication and restricted/repetitive behaviors and interests (RRB), as defined by the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5) (American Psychiatric Association, 2013), autistic individuals often show various degrees of alterations in social cognition, social anxiety, and executive functioning (Johnston et al., 2019; Maddox & White, 2015; Morrison et al., 2019; Spain et al., 2018). A key question for the field is how to best measure these autism spectrum-related dimensional traits in adults. Valid quantitative measures of adult autism spectrum traits are crucial both for genetics studies using quantitative phenotypes, as well as for clinical trials in which investigators need to assess quantitative changes in behaviors following a treatment. One major unanswered question is whether informant report measures and self-report measures of adult autism spectrum traits provide comparable or different sets of information.
Differences between self-reporting and proxy/informant-reporting for adults has been well-studied in fields other than autism research (e.g. in dementia, terminal illness, etc.), (Roydhouse et al., 2021). Also, in an expansive set of studies, discrepancy between child/adolescent self-reports and informant-reports about family relationships, victimization experiences, and other clinically relevant domains have been shown to predict clinical and behavioral outcomes independent of the scores themselves (e.g. De Los Reyes et al., 2010, 2019; Goodman et al., 2010; Laird & De Los Reyes, 2013). This body of work shows the potential power of reporter discrepancy – beyond identifying a measurement error – as a useful clinical metric (de Los Reyes, 2011; De Los Reyes et al., 2013). However, studies of reporter differences in autism have been limited, especially in adults. There are many reasons why self-and informant-reporting may differ, including (but not limited to) some aspects of autism phenotype being internal states and not directly observable, observer bias (e.g. Mandell et al., 2007; Obeid et al., 2020), and possible intentional efforts to mask/camouflage. Most studies of reporter differences in autism have focused on the degree of agreement among multiple informants for autistic children and youth (e.g. Stratis & Lecavalier, 2015). Previous work comparing parent vs. child/adolescent reports of ASD traits and associated symptoms has focused primarily on males and has not examined the effect of sex on self/informant report agreement (Johnson et al., 2009; Kalvin et al., 2020; Kenworthy et al., 2021; Lerner et al., 2012; Schwartzman & Corbett, 2020).
Among the very limited number of published studies comparing self vs. informant reports in adults with diagnosed autism spectrum disorder, Sandercock and colleagues compared self-reports of autistic adults without intellectual disability (ID) vs. informant (caregiver)-report accounts of ASD traits, daily living skills, and quality of life. They found good agreement for ASD traits, yet discrepancy in the reports of daily living skills and quality of life (Sandercock et al. 2020). Additionally, a study in young adult autistic males without ID compared interview, self-report, and parent-report measures and found discrepancies in the following areas: “peer interaction problems”, “difficulties with social cues”, and “narrow interest” (Cederlund et al., 2010). However, there is a need for more studies of self-informant report discrepancies in core autism spectrum traits in adults, as well as studies that examine potential contributors to such discrepancies. In addition to the core autism spectrum traits, other traits associated with the autism spectrum may have a major impact on adult quality of life, including executive functioning difficulties (Bishop-Fitzpatrick et al., 2016; Wallace et al., 2016). A study focusing on reporter differences of executive functioning found poor agreement between self vs. parent assessments of executive functioning as measured by the BRIEF in autistic adolescents, with autistic adolescents self-reporting fewer executive functioning difficulties than their parents reported (Kenworthy et al., 2021). A difference between self-reported and parent-reported executive functioning was not observed in the neurotypical sample (Kenworthy et al., 2021). Additionally, a previous meta-analysis showed that self-report BRIEF scales performed better in terms of clinical ASD discrimination than informant-report BRIEF scales (Leung & Zakzanis, 2014). Given the importance of executive functioning to overall adult functioning and quality of life, self/informant report discrepancies in reporting on executive functioning should be examined among autistic adults to extend the work previously done in an adolescent sample (Kenworthy et al., 2021).
Given the growing literature on sex differences in autism, one factor that might potentially affect self vs. informant report differences in autistic adults is sex assigned at birth. Sex assigned at birth is based on biological and physiological factors in prenatal development and at birth, while gender is socially and personally constructed across postnatal development. This distinction is especially important to be clear about when discussing autism, given the high gender diversity within the autistic population (e.g. George & Stokes, 2018). The vast majority of work has focused on sex assigned at birth (male/female), rather than gender, as a variable of interest. Several reviews have found that autistic males express more RRB than autistic females (Lai & Szatmari, 2020; Mandy & Skuse, 2008; Rubenstein et al., 2015; Van Wijngaarden-Cremers et al., 2014; Werling & Geschwind, 2013). Additionally, Lai and Szatmari point out that autistic females show culturally-defined “female-gender-typical narrow interests”, higher attention to social cues and interest in friendships, and greater linguistic abilities than autistic males, which (among other factors) can lead to delays in recognition and ASD diagnosis in females (Lai & Szatmari, 2020). Also, there is quite a bit of evidence that autistic females engage in more camouflaging (behaviors that would tend to conceal the ASD diagnosis) than autistic males, both in childhood and adulthood (Dean et al., 2017; Jorgenson et al., 2020; Lai et al., 2017; Schuck et al., 2019; Wood-Downie et al., 2021). However, work has also shown that autistic males (based on sex assigned at birth) as well as autistic cis-gender men and nonbinary individuals (based on gender identity) also engage in camouflaging (Hull et al., 2020; Lai et al., 2017). Variation in reported sex differences may be partly attributable to variation among studies in the types of assessments used (i.e. different questionnaires, teacher-report, parent-report, or clinical interview) (Kaat et al., 2021; Mandy & Skuse, 2008; Ratto et al., 2018). Taken together, previous evidence suggests that there are sex and possible gender differences in ASD phenotypes, which are also affected by camouflaging and possibly by assessment methods.
Overall, previous work has been limited in its use of self-report measures, and in examining self-report/informant-report agreement or discrepancy among adults on the autism spectrum. Additionally, previous work has been limited in its exploration of how sex may affect this self-report/informant-report agreement or discrepancy, despite the accumulation of evidence that ASD traits may be expressed and/or viewed differentially on the basis of sex. Clarifying self-report/informant report discrepancies for overall autism spectrum traits as well as executive functioning, and possible effects of sex on these discrepancies, would have very important implications for clinical assessment, quantitative genetics studies, and measurement of treatment outcome.
We sought to test the hypothesis that there would be self/informant report discrepancies regarding core autism spectrum traits and executive functioning in adults who are high in autism spectrum traits, but not in their family members who we expected to be lower in autism spectrum traits. In other words, we hypothesized that self/informant report discrepancies would be more likely in a group that is higher in autism spectrum traits. Given the high levels of camouflaging reported in females on the autism spectrum and the identified differences in the ASD phenotype among females compared to males (Frazier et al., 2014; Lai et al., 2017), we sought to test the hypothesis that there would be greater self-report/informant-report discrepancies in measures of autism-related traits for females on the spectrum than for males. To assess self-report vs. informant-report discrepancies in core autism spectrum-related traits, we used the self- and informant-report versions of the Social Responsiveness Scale-2 Adult (SRS-2A) (Constantino et al., 2003). To assess self-report vs. informant-report discrepancies in executive function, which is often affected in parallel with core autism spectrum traits, we used the self- and informant-report versions of the Brief Rating Inventory for Executive Function (BRIEF-A) (Donders & Strong, 2016; Rabin et al., 2006; Wilson et al., 2011).
Method
Participants
We recruited 103 adults high in autism spectrum traits as probands and 96 of their family members as part of an autism genetics study. Recruitment was via several sources, including from study ads placed on social media and the radio, as well as from local mental health clinicians. Study procedures were reviewed and approved by the appropriate Institutional Review Board. The following inclusion criteria were set for probands: (1) clinical and developmental history that documented meeting ASD criteria as defined by DSM-5 (American Psychiatric Association, 2013) and (2) verbal IQ above 70, as estimated by the Shipley-2 (Western Psychological Services, 2009). Verbal IQ values for probands in the current sample ranged from 76 to 144, with a mean of 118.3 and standard deviation of 14.6. These scores, interpreted qualitatively, indicate that probands were largely in the average to well above average verbal IQ range. To increase the capacity of individuals to participate, clinical and developmental history was collected via an extended (typically 1–2 h) telephone semi-structured interview conducted by one of the members of the research team supervised by the principal investigator. The interview was based on the diagnosis/intake questions used by the principal investigator in their clinical work as a psychiatrist specialized in autism in adulthood. Moreover, detailed information was gathered on psychiatric history, social communication behavioral history (e.g. eye contact, understanding nonliteral language and nonverbal social cues), RRB history (e.g. strong interests, repetitive behaviors, routines), sensory behavioral history (e.g. sensory hypersensitivity, hyper- or hypo-sensitivity to pain), treatment history, medication history, and genetic testing. Additionally, questions on developmental history, including details on pregnancy and child behavior development (e.g. mimicry of behavior, eye contact, motor coordination, imaginative play) were asked of a parent, caregiver, or other informant who knew the proband well as a child, when possible (n = 86) and of the proband when no informant was available (n = 17). This information was integrated with any prior clinical reports that participants could provide, when available. Because information was collected remotely in many cases, and partially during the COVID-19 pandemic, the Autism Diagnostic Observation Schedule (ADOS) was not conducted.
Information from the phone screen, in combination with prior clinical records and the Social Communication Questionnaire (SCQ, see below), was reviewed in a case conference including the research team and the principal investigator, a psychiatrist specializing in adult ASD, to determine if the potential proband met DSM-5 criteria for ASD and therefore was eligible for enrollment. Because not all probands had a prior clinical diagnosis of ASD, and gold-standard, in-person diagnostic assessments could not be conducted, we refer to probands as “high in ASD traits” rather than definitively having ASD diagnoses. Exclusion criteria for participation in the study were: (1) history of intellectual disability (ID), 2) recent (last 4 weeks) severe mood or psychotic symptoms, (3) recent severe aggressive or self-injurious behaviors, and (4) history of major neurological disorder (e.g. dementia, severe head trauma, recent seizures). Family members were included on the basis of their relationship to the probands and included first-, second-, third-, and fourth-degree relatives. The exclusion criteria for family members were: (1) recent severe mood or psychotic symptoms and (2) recent severe aggressive or self-injurious behaviors. Additionally, only family members who did not report any psychiatric diagnoses, neurological diagnoses, or neurodevelopmental disorders in the medical history battery were included in analyses, n = 96. Demographic information (i.e. sex assigned at birth, age, race, and gender identity) was self-reported by each participant during a telephone interview and through an online questionnaire. Sample demographics and sample size are reported in Table 1.Table 1 Demographics data for participants and their informants are reported for probands and family members separately
Probands Family members
Sample size (n) 103 96
Prior clinical ASD diagnosis (n, %) 76, 74 0, 0
Assigned sex at birth χ2 (1) = 2.50, p > 0.05
% Female 38 50
% Male 62 50
Gender identity NA
% Cis-female 34 –
% Cis-male 61 –
% Trans-female 1.0 –
% Trans-male 2.9 –
% Non-binary 1.0 –
Race Fisher’s exact test p = 0.50
% Asian 1.9 5.2
% American Indian/Alaska Native 1.0 2.1
% Black 2.9 4.2
% Middle Eastern 1.0 0
% White 90.3 89
% Decline to answer 2.9 0
Age (range, years) 18–78 19–87
Age (mean (SD), years) 36 (16) 52 (15) t (197) = −7.04, p < 0.001
Highest education attained χ2 (4) = 7.62, p > 0.05
% High school graduate 14 8.3
% Some college 31 18
% College degree 24 33
% Master’s degree 21 29
% Doctoral degree 9.7 11
Informant for SRS-2A sex χ2 (1) = 0.44, p > 0.05
% Female 56.3 64.6
% Male 21.4 32.3
% Missing data 22.3 3.1
Informant for BRIEF-A sex χ2 (1) = 0.55, p > 0.05
%Female 60.2 65.6
% Male 20.4 30.2
% Missing data 19.4 4.2
Only family members who did not report any psychiatric diagnoses, neurological diagnoses, or neurodevelopmental disorders in the medical history battery were included. Gender identity was not collected for family member participants. Results of statistical group comparisons (between probands and family members) are recorded in the last column. Pearson’s chi-square test was used for comparing proportions of sex, education level, and informant sex; Fishers exact test was used for comparing race proportions; and a two-sample t-test was used for comparing mean age. ASD Autism Spectrum Disorder, SRS-2A Social Responsiveness Scale – 2 Adult, BRIEF-A Behavior Rating Inventory of Executive Function – Adult
Measures
Measures included a screening questionnaire—Social Communication Questionnaire (SCQ)—as well as two additional questionnaires – Social Responsiveness Scale-2 Adult (SRS-2A) and the BRIEF-Adult (BRIEF-A). The SCQ was collected as an informant-report only for probands, if a parent was available to complete it. The SRS-2A and BRIEF-A were collected as both self-report (participant answering questions about themselves) and informant-report (another person answering questions about the participant) versions. For the informant-report versions of the SRS-2A and BRIEF-A, the informants varied in their relationship to the probands and family members and included parents, siblings, offspring, therapists, friends, children, and spouses. Relationship information for informants is included in Supplementary Materials. The informant for each participant was selected in collaboration with the participant, based on who knew the participant the best, was available, and was ≥ 18 years old. For probands, there were 106 unique informants (greater than the number of proband participants because sometimes the informant for the SRS-2A was different than the informant for the BRIEF-A). Note unique informants are defined by the identity of the informant, not the participant, so if a participant had different people complete their SRS and BRIEF, then they would count as two unique informants. In contrast, if an informant completed reports for multiple participants, they would still only count as one unique informant. Of these informants, 17 of them were enrolled as family member participants. For family members, there were 83 unique informants (fewer than the number of family member participants because some informants rated multiple people – an average of 1.18 other people). Of those informants, 46 were also enrolled as family members (so they contributed a self-report on their own behavior as well as an informant-report on another participant). Additionally, 8 of the informants on family members were enrolled as probands in the present study.
SCQ
The SCQ is an informant-report measure designed as a diagnostic tool for autism and pervasive developmental disorder (Berument et al., 1999). The SCQ was developed as a companion screening measure for the Autism Diagnostic Interview – Revised (ADI-R). The SCQ items were deliberately chosen to match the ADI-R items that were found to have discriminative diagnostic validity. A meta-analysis of the use of the SCQ as a screening tool found that it had acceptable accuracy for the identification of ASD (AUC = 0.827) (Chesnut et al., 2017). In this study, the SCQ was used as one of several sources of information to determine eligibility for individuals to participate as probands in the study. Probands had a mean SCQ score of 14.6 with a standard deviation of 7.6.
SRS-2A
The SRS-2A is a 65-question measure, available as both informant-report and self-report, composed of five subscales measuring social cognition, social communication, social motivation, RRB, and social awareness. The SRS has good agreement with the ADI-R across multiple symptom domains (r = 0.60–0.79) as well as good inter-rater reliability (r = 0.75–0.91) (Constantino et al., 2003). In addition to being used as a diagnostic tool, the SRS has been used to quantify autism-related behaviors in the general population (Constantino & Todd, 2003). In this study, it was collected as both a self-report and informant-report measure for both probands and family members. The raw total SRS-2A score was used in analyses.
BRIEF-A
The BRIEF-A is a 75-question measure of executive functioning. Executive functioning subdomains measured in the BRIEF-A include the following abilities: inhibit, shift, emotional control, initiate, working memory, plan/organize, organization of materials, and monitor (Roth et al., 2005). The BRIEF has good reliability with an internal consistency of 0.80–0.98 across multiple raters and with a test–retest reliability of 0.76–0.85 (Gioia et al., 2000). The BRIEF has been used in both autistic and non-autistic populations (e.g. Donders & Strong, 2016; Granader et al., 2014; Kenworthy et al., 2021; Rabin et al., 2006; Wilson et al., 2011). In this study, it was collected as both a self-report and informant-report measure for both probands and family members. The raw Global Executive Composite score was used for analysis.
Assessing Demographic Differences Between Probands and Family Members
Possible confounding demographic differences between proband and family members were examined using a two-sample t-test for comparing mean age. Additionally, Pearson’s chi-square test was used to evaluate differences in proportions of sex, education level, and informant sex, and Fisher’s exact test was used for race. The Fisher’s exact test was used for comparing the proportions of different racial identities as there were multiple small/zero values in categories that prevented precise estimation of chi-square statistic or p-value using the Pearson’s chi-square test.
Examining Agreement and Inter-Rater Reliability of Self- and Informant-Report SRS-2A and BRIEF-A Scores Using Correlation Analysis
Agreement was visualized using Bland–Altman plots and tested using (1) Spearman correlation between self- and informant-report versions of the same questionnaires measuring autism spectrum-related behaviors (SRS-2A) and executive functioning (BRIEF-A) and 2) intra-class correlation (ICC) analysis. Spearman correlation coefficients were used as the data had non-normal, varied distributions. ICC was used to quantify inter-rater reliability between self- and informant-report for the SRS-2A raw total score, as well as for the BRIEF-A raw Global Executive Composite score. A one-way random effects model with absolute agreement as the output was run first to assess the validity of a single score. Raw scores were used to test the relationship of the scores with sex and age without any possible obscuring via T-score transformation. Analyses were conducted for probands and family members separately. The Benjamini–Hochberg correction for multiple comparisons was used. Exploratory analyses comparing correlation strengths were conducted using Fisher r-to-z transformation.
Comparing Self- vs. Informant-Report Discrepancies Between Groups
For both the SRS-2A and the BRIEF-A, discrepancies between the self- and informant-reports were quantified as discrepancy scores, which were calculated by subtracting the self-report score from the informant-report score. Positive discrepancy scores indicate that the informant-report score was higher than the self-report score, while negative discrepancy scores indicate that the self-report score was higher than the informant-report score. Following tests for normality and for equal variance, analysis of covariance (ANCOVA) was used to compare the discrepancy scores for SRS-2A and BRIEF-A between groups, as defined immediately below, while accounting for the potential confounding variable(s). Analyses were conducted for probands and family members separately, investigating first the effect of the sex of the individual self-reporting and being reported on (referred to as participant sex). Exploratory analyses examined the effect of gender identity of the individual self-reporting and being reported on (referred to as participant gender) and effect of the sex of the informant (referred to as informant sex) on discrepancy. Gender identity was not reported for informants, so informant gender was not examined. The Benjamini–Hochberg correction for multiple comparisons was used.
Results
Examining Agreement and Inter-Rater Reliability of Self- and Informant-Report
For the SRS-2A in probands, the mean discrepancy score was −18.50 points (indicating higher levels of self-report SRS-2A scores relative to informant-report SRS-2A scores, on average) with a standard deviation of 42.28, upper 95% confidence interval value of 64.38, and lower 95% confidence interval value of −101.38 (see Fig. 1). For the BRIEF-A in probands, the mean discrepancy score was −11.24 points with a standard deviation of 35.65, upper 95% confidence interval value of 58.64, and lower 95% confidence interval value of −81.13. Range, mean, and standard deviation for raw scores, from which discrepancy scores were calculated from, are reported in Table 2. In Spearman correlation analysis among probands, there was no significant association between the self-report and informant-report total scores on the SRS-2A (r = 0.08, p > 0.05), nor was there a significant association between the self-report and informant-report scores on the BRIEF-A (r = 0.07, p > 0.05). This lack of significant correlation between self-report and informant-report versions of the same measures suggests that there is a strong impact of who is reporting for these domains, self vs. informant (see Fig. 1). Additionally, in intra-class correlation (ICC) analysis among probands, there was poor inter-rater reliability between self-report and informant-report for the SRS-2A (ICC = 0.01, 95% confidence interval (CI) [−0.19, 0.20] and for the BRIEF-A (ICC = 0.00, 95% CI [−0.19, 0.20]). Neither the ICC coefficient for SRS-2A nor the ICC coefficient for BRIEF-A was significantly different from zero (F(97,98) = 1.01, p > 0.05; F(97,98) = 1.01, p > 0.05).Fig. 1 Lack of agreement between self-report and informant-report scores for the same measures in adults high in autism spectrum traits. A, B Bland–Altman plots. Difference between measurements is calculated by subtracting the self-report score from the informant-report score. Average measurement is calculated by taking the average of the self-report and the informant-report score. Mean difference between measurements (aka discrepancy) is shown with a solid black line. The dashed red lines represent 95% upper and lower limits of agreement for the measures. A Bland–Altman plot for self-report and informant-report total raw scores for the SRS-2A in probands. Mean discrepancy (shown by the solid black line) below zero for the SRS-2A for probands. B Bland–Altman plot for self-report and informant-report score for the BRIEF-A raw Global Executive Composite (GEC) Score. Mean discrepancy (shown by the solid black line) below zero for the BRIEF-A. C Correlation between self- and informant-report scores on the SRS-2A in probands. Spearman's rho and the associated p-value are reported. No significant correlation between self-and informant-report score for SRS-2A total for probands. D Correlation between self- and informant-report scores on the BRIEF-A GEC in probands. Spearman's rho and the associated p-value are reported. No significant correlation between self-and informant-report score for BRIEF-A GEC score for probands. SRS-2A Social Responsiveness Scale-2 Adult, BRIEF-A Behavioral Rating Inventory for Executive Functioning-Adult
Table 2 Range, mean, and standard deviation of the scores for the measures collected as self-report and informant-report (SRS-2A and BRIEF-A) and later used in discrepancy analyses
Probands Family members
SRS-2A self-report raw total
Range 24–155 3–89
Mean (SD) 101.5 (27.2) 28.0 (16.1)
SRS-2A informant-report raw total
Range 14–160 0–162
Mean (SD) 83.3 (35.4) 27.7 (28.0)
BRIEF-A self-report raw GEC
Range 83–194 70–170
Mean (SD) 143.4 (22.5) 101.2 (20.7)
BRIEF-A informant-report raw GEC
Range 74–195 71–193
Mean (SD) 132.2 (28.7) 95.6 (24.5)
SRS-2A Social Responsiveness Scale – 2 Adult, BRIEF-A Behavior Rating Inventory of Executive Function – Adult, GEC Global Executive Composite score
For the SRS-2A in family members, the mean discrepancy score was 0.02, with a standard deviation of 26.76, upper 95% confidence interval of 52.47, and lower 95% confidence interval of −52.42 (See Supplement Fig. 1). For the BRIEF-A in family members, the mean discrepancy score was -5.64, with a standard deviation of 27.47, upper 95% confidence interval of 48.20, and lower 95% confidence interval of −59.48. In contrast to probands, for Spearman correlation analysis with family members, there was a moderate association between the self-report and informant-report total scores for the SRS-2A (r = 0.38, p < 0.05) and for the BRIEF-A (r = 0.34, p < 0.05) (See Supplement Fig. 1). Among family members in intra-class correlation (ICC) analysis, there was poor inter-rater reliability between self-report and informant-report for the SRS-2A (ICC = 0.34, 95% confidence interval (CI) [0.15, 0.51] and for the BRIEF-A (ICC = 0.26, 95% CI [0.06, 0.44]). In contrast to the probands, the ICC coefficient for the SRS-2A and the ICC coefficient for BRIEF-A were significantly different from zero (F(91,92) = 2.03, p < 0.001; F(91,92) = 1.7, p < 0.01).
Comparing Discrepancy Between Groups
Results for comparing potentially confounding demographic variables between groups are in Table 1. After identifying age as a potentially confounding variable, we investigated the impact of participant sex, participant gender, and informant sex on discrepancy scores for both the SRS-2A and BRIEF-A for probands and family members separately. Among probands, females (M = −30.1, SD = 36.4) had significantly greater magnitude (directionally more negative) SRS-2A discrepancy scores than males (M = −10.8, SD = 43.9) while accounting for participant age (F(1,100) = 6.66, p < 0.05) with a medium effect size of participant sex (η2 = 0.06; see Fig. 2A). Recall that the negative discrepancy scores indicate higher levels of self-report SRS-2A scores relative to informant-report SRS-2A scores. There was not a statistically significant sex effect for BRIEF-A discrepancy scores in probands (F(1,99) = 4.00, p = 0.05; η2 = 0.04). For family members, there were no differences based on sex on the SRS-2A (F(1,95) = 0.17, p > 0.05; η2 = 0.00) or on the BRIEF-A (F(1,91) = 0.02, p > 0.05; η2 = 0.00) (see Supplementary Fig. 2A & C). For descriptive and exploratory purposes, we examined the effect of participant gender on discrepancy within our sample. Among probands, there was an effect of gender identity on SRS-2A discrepancy (F(4,97) = 2.75, p < 0.05) with a medium effect size of η2 = 0.10 and a non-statistically significant effect on BRIEF-A discrepancy (F(4, 96) = 1.69, p > 0.05) with a medium effect size of η2 = 0.06 (see Fig. 2B and D). For family members, gender identity was not systematically collected, so no additional analyses were run.Fig. 2 Effects of participant sex, participant gender, and informant sex on discrepancy between self- and informant-report scores for probands. There was a significant effect of participant sex and of informant sex on discrepancy scores in the SRS-2A (calculated from total raw scores) in probands, with a marginal effect of participant gender. However, there were no significant effects of participant sex, participant gender, or informant sex differences on discrepancy scores for the BRIEF-A raw Global Executive Composite (GEC) score. Discrepancy scores were calculated by subtracting the self-report scores from informant-report scores. A discrepancy score of 0 indicates no discrepancy between self- and informant reports. Negative discrepancy scores indicate higher self-report scores relative to informant-report scores. Conversely, positive discrepancy scores indicate higher informant report scores than self-report scores. A Significant sex differences in SRS-2A raw total discrepancy scores for probands. B Marginal effect of gender identity on SRS-2A raw total discrepancy scores for probands. C Significant effect of informant sex on SRS-2A raw total discrepancy scores for probands. D No significant sex differences in BRIEF-A GEC discrepancy for probands E No significant effect of participant gender on BRIEF-A GEC discrepancy for probands F No significant effect of informant sex on BRIEF-A GEC discrepancy for probands. *indicates p < 0.05 after correction for multiple comparisons using the Benjamini–Hochberg correction. SRS-2A Social Responsiveness Scale-2 Adult, BRIEF-A Behavioral Rating Inventory for Executive Functioning-Adult, GEC Global Executive Composite Score of the BRIEF-A
We also examined the effect of informant sex on discrepancy for exploratory purposes. When reporting on probands, male informants (M = −42.7, SD = 37.4) and female informants (M = −11.1, SD = 37.7) differed in SRS-2A discrepancy scores (F(1,77) = 9.89, p < 0.01) with a medium effect size of informant sex (η2 = 0.11; see Fig. 2C). Generally, SRS-2A discrepancy scores were greater in magnitude with male informants and were in the negative direction, indicating higher levels of self-reported symptoms by probands relative to informant-reported symptoms when informants were males. There were no significant effects of informant sex on discrepancy scores for the BRIEF-A among probands (F(1,90) = 3.90, p > 0.05; η2 = 0.04), the SRS-2A among family members (F(1,90) = 1.12, p > 0.05; η2 = 0.01), or the BRIEF-A among family members (F(1,88) = 0.91, p > 0.05; η2 = 0.01) (see Fig. 2F and Supplementary Fig. 2).
Discussion
We found a lack of agreement and inter-rater reliability between self-report and informant-report scores for the same measures for probands, yet moderate agreement and low inter-rater reliability between self-report and informant-report measures in their family members. Additionally, we found a pattern of negative discrepancy scores between self and informant-reporting of autism-related behaviors for female probands, such that female probands reported more autism-related behaviors for themselves than their informant did about them. In exploratory analyses, we found a difference in discrepancy in reporting autism-related behaviors of probands according to the sex of the informant. Specifically, SRS-2A discrepancy scores were of greater magnitude and in a negative direction with male informants, indicating higher levels of self-reported symptoms by probands relative to informant-reported symptoms when informants were males.
Our findings related to discrepancy in reporting autism spectrum traits build on work previously done in child samples finding parent–child reporting discrepancies (e.g. Lerner et al., 2012) but differ from the small number of previous conflicting reports in autistic adults. One previous study found good self/other agreement on the SRS2-A among autistic adults (80% male sample) (Sandercock et al., 2020), while another study (with a male-only sample) reported poor self/other agreement but in the opposite direction of what we observed in our sample, with men reporting having fewer ASD symptoms in relation to their informant (Cederlund et al., 2010). Much of the previous work across all age ranges examining the agreement between self- and informant-report measures have relied on predominantly male participants (> 70%) and have either found good agreement or the effect of lower reporting of ASD symptoms according to self-report (Cederlund et al., 2010; Johnson et al., 2009; Lerner et al., 2012; Sandercock et al., 2020; White et al., 2012). In contrast, our sample had a relatively high representation of female probands (46.3%). Informants’ lower reporting of autism spectrum traits in female probands in our sample potentially could be related to camouflaging of ASD behaviors by probands. This would be in line with camouflaging work showing that while autistic individuals across sexes and gender identities camouflage, there seems to be higher rates of camouflaging among women (e.g. Hull et al., 2017; Lai et al., 2017). It also may be due to sex differences in the expression of autism-related behaviors in males and females (e.g. Lai & Szatmari, 2020) leading to informants identifying fewer autism-related traits in women. The impact of gender on discrepancy cannot be fully investigated in the present study. Given the lack of enrichment of trans and non-binary individuals, our sample lacks the necessary statistical power to do so. Recent work has taken multiple approaches to examine the intersection of gender diversity and the autism spectrum (George & Stokes, 2018; Manjra & Masic, 2022; Moore et al., 2022; Strang et al., 2020; Warrier et al., 2020). Future studies into reporter discrepancy, in addition to topics related to autism more broadly, are needed with larger numbers of trans and non-binary individuals, which would enable investigators to assess both the effects of gender, as well as sex assigned at birth.
While female probands, on average, had discrepancies that were greater in magnitude than male probands, our data demonstrate that many probands – male and female – had large discrepancies between self-report and informant-report scores. This suggests that self-reports and informant-reports may be carrying different sets of information for autistic adults. Recent work looking at ASD behaviors from childhood to young adulthood suggests that self-reports may be especially important in adults (Riglin et al., 2021). Riglin et al. focused on identifying trajectories of change and / or maintenance of levels of ASD traits (2021). They found that, by age 25 years, there were parent-reported differences between trajectory groups but not self-reported differences, concluding that incorporating self-report assessment, as well as a variety of measures, may be important for accurately assessing ASD traits in autistic adults (Riglin et al., 2021).
The lack of agreement and inter-rater reliability between self and informant reporting of executive functioning using the BRIEF among probands is in contrast to the studies examining self/other agreement in some other populations, but our results are generally aligned with findings in autistic adolescents (Donders & Strong, 2016; Kenworthy et al., 2021; Rabin et al., 2006; Wilson et al., 2011). However, the levels of concordance for executive function found among autistic adolescents were higher in Kenworthy et al., 2021 than those found in the present sample. This may be due to the difference in the mean age of the two samples, and/or due to some methodological differences between the present study and Kenworthy et al., 2021, including the following: (1) the studies use different versions of the BRIEF (BRIEF-2 child form in Kenworthy et al. vs. BRIEF-A adult form in the current study), (2) the studies use different forms of the GEC score (T-score transformed in Kenworthy et al. vs. raw score in the present study), and (3) ICC calculation methods vary, with the Kenworthy et al. study using a two-way random effects model testing for consistency (which cancels out systematic rating errors) and using an average score (Kenworthy et al., 2021). In contrast, the present study was testing for absolute agreement (do the raters produce the same score) to assess the validity of a single score, based on the current field practices to rely on one reporting method for adults (either self-report or informant-report). Our results emphasize the importance of collecting both self- and informant-report information in order to capture the full expanse of autism spectrum related behaviors and abilities, including executive functioning.
There are many possible sources for the self- vs. informant-report discrepancies in autistic adults. Informants may lack understanding due to a neurotypical viewpoint, in line with the concept of dialectical misattunement between neurotypical and autistic individuals or the double empathy problem, i.e. the idea that social communication difficulties are not solely reliant on the autistic individual’s inherent social ability, but are also dependent on their neurotypical social partner (Bolis et al., 2017; Milton, 2012). The effect of informant sex in particular suggests that the interpretation of autism-related behaviors may be more difficult when the informant does not share social context with the self-reporting participant (i.e. the informant and the participant are of different sexes). Additionally, informants may lack awareness of traits/thoughts that are not easily observable, have bias towards over- or under-assignment of autism spectrum traits, or have other factors influencing how they report. On the other side, the individual self-reporting may actively camouflage their behaviors. The self-reporter may also possess greater or lesser degrees of self-awareness or have individual bias in the way they view themselves that could affect their self-reports (Huang et al., 2017).
Among family members in the present study, there was poor agreement between self and informant report measures as measured by ICC, which was significantly different from zero but lower than values found in previous samples estimating self/other agreement for parents of autistic individuals (De la Marche et al., 2015; Möricke et al., 2016). It may be that the variability in the types of family members studied (not just parents of autistic children, as in some previous studies) and variability in the relationship between the family member and their informant contributed to lower self/informant report agreement compared to previous work. An additional consideration in the assessment of self/informant report correlations in probands vs. family members is that it is possible that differences between probands and family members in phenotype variability could affect agreement, e.g. that lower variability (generally high SRS and BRIEF scores) in proband phenotypes might partially account for the lack of self/informant report correlations in probands. But because variability in phenotypes in probands was fairly robust in our sample (with higher SRS and BRIEF standard deviations seen in probands than in family members, as shown in Table 2), this does not seem to account for the findings in our dataset. Nevertheless, this is an issue that deserves further research in future samples, using one or more additional measures of autism-related behaviors.
A limitation of this study is the lack of diversity related to certain demographics – namely gender identity, race, and education level. While our proband sample had a variety of gender identities reported, not enough non-binary and transgender people were included to investigate an effect of gender on discrepancy. A more balanced sample in terms of education level (as a rough proxy for socioeconomic status) and racial identity is necessary to ensure generalizability of the results. Additionally, this sample also only included those with a verbal IQ above 70 and cannot address the reporting/phenotype collection challenges related to those with lower IQ and/or intellectual disability. Another limitation of this study is the lack of consistency in the informant’s relationship to the participant. While we secured informant reports from parents or other close family members whenever possible, this was not possible in all cases, as some participants had family members who were unavailable (e.g. uncomfortable with participating). Incorporating probands in the study who did not have a parent informant allowed for broader inclusion but likely added variability and inconsistency in the type of knowledge and experience each informant had with the proband. This challenge in securing an informant with a consistent relationship to the proband seems to be specific to research involving autistic adults (as opposed to research with autistic children in which a parent, caregiver, and/or teacher is often available) and is another reason to collect both self-report and informant-report data in adults. Additionally, as described in the Methods and further detailed in Supplementary Materials, the informants were not from an entirely independent group. Even with this overlap in participants and informants in which many informants also served as family member participants, the discrepancy between self-report and informant-report scores for probands observed (mean of −18.5 points for SRS-2A and −11.2 points for BRIEF-A) is still a concerning observation and an area for future consideration and study.
To extend this study’s findings regarding self-report vs. informant-report discrepancies, future studies should investigate possible contributions to these discrepancies, including camouflaging, potential biases when reporting on autism-related behaviors, degree of shared social context of probands and informants, and the impact of an informant’s general autism-related knowledge on their reporting. Future work should also look for possible differences in agreement / discrepancy across different domains of autism-related traits (such as perspective taking, social engagement, repetitive motor behaviors), as these domains will vary in the degree to which an informant is able to observe them. Additionally, future work should examine the influence of different domains of cognition and/or behavior on discrepancy (for instance, does higher perspective taking abilities of the autistic adult or the informant relate to decreased self/informant discrepancy). Given the known variation in autism-related traits across sexes, this may be an especially important avenue to help disentangle whether the group effects observed here are in fact due to sex, are a simplified gender effect, are measurement or sampling effects, or emerge from different distributions of cognitive and behavioral phenotypes across genders. Future research should also look at how self and other reports align with diagnostic histories (e.g., age of ASD diagnosis, experience of misdiagnosis) and treatment histories (eg type of treatment received, when treatment began, etc.). Finally, looking at agreement in self-informant reporting for multiple measures in each domain, as well as agreement of self- and informant-reported measures with clinician ratings and laboratory performance-based measures will be an important check on the generalizability of the results of the present study. The presence of the discrepancies in the present study suggests that it is vital to use both self-report and informant-report measures in future research studies and clinical assessments, as they carry different sets of information, both of which are important. Not collecting self-report information for autistic adults may lead to missing important information about their experiences and phenotype.
Citation Diversity Statement
Recent work in several fields of science has identified a bias in citation practices such that papers from women and other minority scholars are under-cited relative to the number of such papers in the field (Caplar et al., 2017; Dion et al., 2018; Dworkin et al., 2020; Maliniak et al., 2013; Mitchell et al., 2013). Here we sought to proactively consider choosing references that reflect the diversity of the field in thought, form of contribution, gender, race, ethnicity, and other factors. First, we obtained the predicted gender of the first and last author of each reference by using databases that store the probability of a first name being carried by a woman (Dworkin et al., 2020; Zhou et al., 2020). By this measure (and excluding self-citations to the first and last authors of our current paper), our references contain 27.94% woman(first)/woman(last), 18.33% man/woman, 27.06% woman/man, and 26.67% man/man. This method is limited in that a) names, pronouns, and social media profiles used to construct the databases may not, in every case, be indicative of gender identity and b) it cannot account for intersex, non-binary, or transgender people. Second, we obtained predicted racial/ethnic category of the first and last author of each reference by databases that store the probability of a first and last name being carried by an author of color (Ambekar et al., 2009; Sood & Laohaprapanon, 2018). By this measure (and excluding self-citations), our references contain 6.29% author of color (first)/author of color(last), 18.85% white author/author of color, 20.76% author of color/white author, and 54.11% white author/white author. This method is limited in that a) names and Florida Voter Data to make the predictions may not be indicative of racial/ethnic identity, and b) it cannot account for Indigenous and mixed-race authors, or those who may face differential biases due to the ambiguous racialization or ethnicization of their names. We look forward to future work that could help us to better understand how to support equitable practices in science.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 112 KB)
This study was supported by the Autism Spectrum Program of Excellence at the University of Pennsylvania as well as the National Institute of Mental Health (F31MH125539). We would like to thank all of the participants for their time, for sharing their experiences, and for all of their efforts which made this study possible.
Author Contributions
Conceptualization: SCT, DJR, MB, ESB; Methodology: SCT, BNG, HCD, AL, ER, ZS, SS, LA, DJR, MB, ESB; Formal analysis and investigation: SCT, LA, ESB; Writing - original draft preparation: SCT, ESB; Writing - review and editing: SCT, BNG, HCD, AL, ER, ZS, SS, LA, DJR, MB, ESB; Funding acquisition: DJR, MB, ESB; Resources: DJR, MB, ESB; Supervision: DJR, MB, ESB.
Declarations
Conflict of interest
The authors have no competing interests, financial or otherwise, to declare.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36484966 | PMC9734875 | NO-CC CODE | 2022-12-14 23:28:31 | no | J Autism Dev Disord. 2022 Dec 9;:1-13 | utf-8 | J Autism Dev Disord | 2,022 | 10.1007/s10803-022-05822-6 | oa_other |
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J Autism Dev Disord
J Autism Dev Disord
Journal of Autism and Developmental Disorders
0162-3257
1573-3432
Springer US New York
36484966
5822
10.1007/s10803-022-05822-6
Original Paper
Contrasting Views of Autism Spectrum Traits in Adults, Especially in Self-Reports vs. Informant-Reports for Women High in Autism Spectrum Traits
Taylor Sara C. 123
Gehringer Brielle N. 12
Dow Holly C. 12
Langer Allison 12
Rawot Eric 12
Smernoff Zoe 12
Steeman Samantha 12
Almasy Laura 245
Rader Daniel J. 2
Bučan Maja 12
http://orcid.org/0000-0003-1417-7838
Brodkin Edward S. [email protected]
1
1 grid.25879.31 0000 0004 1936 8972 Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3535 Market Street, Suite 3080, Philadelphia, PA 19104-3309 USA
2 grid.25879.31 0000 0004 1936 8972 Department of Genetics, Perelman School of Medicine, Clinical Research Building, 415 Curie Boulevard, University of Pennsylvania, Philadelphia, PA 19104-6145 USA
3 grid.25879.31 0000 0004 1936 8972 Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
4 grid.239552.a 0000 0001 0680 8770 Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, PA USA
5 grid.239552.a 0000 0001 0680 8770 Lifespan Brain Institute, Children’s Hospital of Philadelphia, Philadelphia, PA USA
9 12 2022
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8 11 2022
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There is uncertainty among researchers and clinicians about how to best measure autism spectrum dimensional traits in adults. In a sample of adults with high levels of autism spectrum traits and without intellectual disability (probands, n = 103) and their family members (n = 96), we sought to compare self vs. informant reports of autism spectrum-related traits and possible effects of sex on discrepancies. Using correlational analysis, we found poor agreement between self- and informant-report measures for probands, yet moderate agreement for family members. We found reporting discrepancy was greatest for female probands, often self-reporting more autism-related behaviors. Our findings suggest that autism spectrum traits are often underrecognized by informants, making self-report data important to collect in clinical and research settings.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10803-022-05822-6.
Keywords
Autism spectrum
Adult
Self-report
Phenotype
Female
http://dx.doi.org/10.13039/100000025 National Institute of Mental Health F31MH125539 Taylor Sara C. Autism Spectrum Program of Excellence
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pmcIntroduction
Autism spectrum disorder (ASD) can be thought of as a pattern of quantitative variation along several behavioral domains. In addition to the core ASD behavioral domains of social communication and restricted/repetitive behaviors and interests (RRB), as defined by the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5) (American Psychiatric Association, 2013), autistic individuals often show various degrees of alterations in social cognition, social anxiety, and executive functioning (Johnston et al., 2019; Maddox & White, 2015; Morrison et al., 2019; Spain et al., 2018). A key question for the field is how to best measure these autism spectrum-related dimensional traits in adults. Valid quantitative measures of adult autism spectrum traits are crucial both for genetics studies using quantitative phenotypes, as well as for clinical trials in which investigators need to assess quantitative changes in behaviors following a treatment. One major unanswered question is whether informant report measures and self-report measures of adult autism spectrum traits provide comparable or different sets of information.
Differences between self-reporting and proxy/informant-reporting for adults has been well-studied in fields other than autism research (e.g. in dementia, terminal illness, etc.), (Roydhouse et al., 2021). Also, in an expansive set of studies, discrepancy between child/adolescent self-reports and informant-reports about family relationships, victimization experiences, and other clinically relevant domains have been shown to predict clinical and behavioral outcomes independent of the scores themselves (e.g. De Los Reyes et al., 2010, 2019; Goodman et al., 2010; Laird & De Los Reyes, 2013). This body of work shows the potential power of reporter discrepancy – beyond identifying a measurement error – as a useful clinical metric (de Los Reyes, 2011; De Los Reyes et al., 2013). However, studies of reporter differences in autism have been limited, especially in adults. There are many reasons why self-and informant-reporting may differ, including (but not limited to) some aspects of autism phenotype being internal states and not directly observable, observer bias (e.g. Mandell et al., 2007; Obeid et al., 2020), and possible intentional efforts to mask/camouflage. Most studies of reporter differences in autism have focused on the degree of agreement among multiple informants for autistic children and youth (e.g. Stratis & Lecavalier, 2015). Previous work comparing parent vs. child/adolescent reports of ASD traits and associated symptoms has focused primarily on males and has not examined the effect of sex on self/informant report agreement (Johnson et al., 2009; Kalvin et al., 2020; Kenworthy et al., 2021; Lerner et al., 2012; Schwartzman & Corbett, 2020).
Among the very limited number of published studies comparing self vs. informant reports in adults with diagnosed autism spectrum disorder, Sandercock and colleagues compared self-reports of autistic adults without intellectual disability (ID) vs. informant (caregiver)-report accounts of ASD traits, daily living skills, and quality of life. They found good agreement for ASD traits, yet discrepancy in the reports of daily living skills and quality of life (Sandercock et al. 2020). Additionally, a study in young adult autistic males without ID compared interview, self-report, and parent-report measures and found discrepancies in the following areas: “peer interaction problems”, “difficulties with social cues”, and “narrow interest” (Cederlund et al., 2010). However, there is a need for more studies of self-informant report discrepancies in core autism spectrum traits in adults, as well as studies that examine potential contributors to such discrepancies. In addition to the core autism spectrum traits, other traits associated with the autism spectrum may have a major impact on adult quality of life, including executive functioning difficulties (Bishop-Fitzpatrick et al., 2016; Wallace et al., 2016). A study focusing on reporter differences of executive functioning found poor agreement between self vs. parent assessments of executive functioning as measured by the BRIEF in autistic adolescents, with autistic adolescents self-reporting fewer executive functioning difficulties than their parents reported (Kenworthy et al., 2021). A difference between self-reported and parent-reported executive functioning was not observed in the neurotypical sample (Kenworthy et al., 2021). Additionally, a previous meta-analysis showed that self-report BRIEF scales performed better in terms of clinical ASD discrimination than informant-report BRIEF scales (Leung & Zakzanis, 2014). Given the importance of executive functioning to overall adult functioning and quality of life, self/informant report discrepancies in reporting on executive functioning should be examined among autistic adults to extend the work previously done in an adolescent sample (Kenworthy et al., 2021).
Given the growing literature on sex differences in autism, one factor that might potentially affect self vs. informant report differences in autistic adults is sex assigned at birth. Sex assigned at birth is based on biological and physiological factors in prenatal development and at birth, while gender is socially and personally constructed across postnatal development. This distinction is especially important to be clear about when discussing autism, given the high gender diversity within the autistic population (e.g. George & Stokes, 2018). The vast majority of work has focused on sex assigned at birth (male/female), rather than gender, as a variable of interest. Several reviews have found that autistic males express more RRB than autistic females (Lai & Szatmari, 2020; Mandy & Skuse, 2008; Rubenstein et al., 2015; Van Wijngaarden-Cremers et al., 2014; Werling & Geschwind, 2013). Additionally, Lai and Szatmari point out that autistic females show culturally-defined “female-gender-typical narrow interests”, higher attention to social cues and interest in friendships, and greater linguistic abilities than autistic males, which (among other factors) can lead to delays in recognition and ASD diagnosis in females (Lai & Szatmari, 2020). Also, there is quite a bit of evidence that autistic females engage in more camouflaging (behaviors that would tend to conceal the ASD diagnosis) than autistic males, both in childhood and adulthood (Dean et al., 2017; Jorgenson et al., 2020; Lai et al., 2017; Schuck et al., 2019; Wood-Downie et al., 2021). However, work has also shown that autistic males (based on sex assigned at birth) as well as autistic cis-gender men and nonbinary individuals (based on gender identity) also engage in camouflaging (Hull et al., 2020; Lai et al., 2017). Variation in reported sex differences may be partly attributable to variation among studies in the types of assessments used (i.e. different questionnaires, teacher-report, parent-report, or clinical interview) (Kaat et al., 2021; Mandy & Skuse, 2008; Ratto et al., 2018). Taken together, previous evidence suggests that there are sex and possible gender differences in ASD phenotypes, which are also affected by camouflaging and possibly by assessment methods.
Overall, previous work has been limited in its use of self-report measures, and in examining self-report/informant-report agreement or discrepancy among adults on the autism spectrum. Additionally, previous work has been limited in its exploration of how sex may affect this self-report/informant-report agreement or discrepancy, despite the accumulation of evidence that ASD traits may be expressed and/or viewed differentially on the basis of sex. Clarifying self-report/informant report discrepancies for overall autism spectrum traits as well as executive functioning, and possible effects of sex on these discrepancies, would have very important implications for clinical assessment, quantitative genetics studies, and measurement of treatment outcome.
We sought to test the hypothesis that there would be self/informant report discrepancies regarding core autism spectrum traits and executive functioning in adults who are high in autism spectrum traits, but not in their family members who we expected to be lower in autism spectrum traits. In other words, we hypothesized that self/informant report discrepancies would be more likely in a group that is higher in autism spectrum traits. Given the high levels of camouflaging reported in females on the autism spectrum and the identified differences in the ASD phenotype among females compared to males (Frazier et al., 2014; Lai et al., 2017), we sought to test the hypothesis that there would be greater self-report/informant-report discrepancies in measures of autism-related traits for females on the spectrum than for males. To assess self-report vs. informant-report discrepancies in core autism spectrum-related traits, we used the self- and informant-report versions of the Social Responsiveness Scale-2 Adult (SRS-2A) (Constantino et al., 2003). To assess self-report vs. informant-report discrepancies in executive function, which is often affected in parallel with core autism spectrum traits, we used the self- and informant-report versions of the Brief Rating Inventory for Executive Function (BRIEF-A) (Donders & Strong, 2016; Rabin et al., 2006; Wilson et al., 2011).
Method
Participants
We recruited 103 adults high in autism spectrum traits as probands and 96 of their family members as part of an autism genetics study. Recruitment was via several sources, including from study ads placed on social media and the radio, as well as from local mental health clinicians. Study procedures were reviewed and approved by the appropriate Institutional Review Board. The following inclusion criteria were set for probands: (1) clinical and developmental history that documented meeting ASD criteria as defined by DSM-5 (American Psychiatric Association, 2013) and (2) verbal IQ above 70, as estimated by the Shipley-2 (Western Psychological Services, 2009). Verbal IQ values for probands in the current sample ranged from 76 to 144, with a mean of 118.3 and standard deviation of 14.6. These scores, interpreted qualitatively, indicate that probands were largely in the average to well above average verbal IQ range. To increase the capacity of individuals to participate, clinical and developmental history was collected via an extended (typically 1–2 h) telephone semi-structured interview conducted by one of the members of the research team supervised by the principal investigator. The interview was based on the diagnosis/intake questions used by the principal investigator in their clinical work as a psychiatrist specialized in autism in adulthood. Moreover, detailed information was gathered on psychiatric history, social communication behavioral history (e.g. eye contact, understanding nonliteral language and nonverbal social cues), RRB history (e.g. strong interests, repetitive behaviors, routines), sensory behavioral history (e.g. sensory hypersensitivity, hyper- or hypo-sensitivity to pain), treatment history, medication history, and genetic testing. Additionally, questions on developmental history, including details on pregnancy and child behavior development (e.g. mimicry of behavior, eye contact, motor coordination, imaginative play) were asked of a parent, caregiver, or other informant who knew the proband well as a child, when possible (n = 86) and of the proband when no informant was available (n = 17). This information was integrated with any prior clinical reports that participants could provide, when available. Because information was collected remotely in many cases, and partially during the COVID-19 pandemic, the Autism Diagnostic Observation Schedule (ADOS) was not conducted.
Information from the phone screen, in combination with prior clinical records and the Social Communication Questionnaire (SCQ, see below), was reviewed in a case conference including the research team and the principal investigator, a psychiatrist specializing in adult ASD, to determine if the potential proband met DSM-5 criteria for ASD and therefore was eligible for enrollment. Because not all probands had a prior clinical diagnosis of ASD, and gold-standard, in-person diagnostic assessments could not be conducted, we refer to probands as “high in ASD traits” rather than definitively having ASD diagnoses. Exclusion criteria for participation in the study were: (1) history of intellectual disability (ID), 2) recent (last 4 weeks) severe mood or psychotic symptoms, (3) recent severe aggressive or self-injurious behaviors, and (4) history of major neurological disorder (e.g. dementia, severe head trauma, recent seizures). Family members were included on the basis of their relationship to the probands and included first-, second-, third-, and fourth-degree relatives. The exclusion criteria for family members were: (1) recent severe mood or psychotic symptoms and (2) recent severe aggressive or self-injurious behaviors. Additionally, only family members who did not report any psychiatric diagnoses, neurological diagnoses, or neurodevelopmental disorders in the medical history battery were included in analyses, n = 96. Demographic information (i.e. sex assigned at birth, age, race, and gender identity) was self-reported by each participant during a telephone interview and through an online questionnaire. Sample demographics and sample size are reported in Table 1.Table 1 Demographics data for participants and their informants are reported for probands and family members separately
Probands Family members
Sample size (n) 103 96
Prior clinical ASD diagnosis (n, %) 76, 74 0, 0
Assigned sex at birth χ2 (1) = 2.50, p > 0.05
% Female 38 50
% Male 62 50
Gender identity NA
% Cis-female 34 –
% Cis-male 61 –
% Trans-female 1.0 –
% Trans-male 2.9 –
% Non-binary 1.0 –
Race Fisher’s exact test p = 0.50
% Asian 1.9 5.2
% American Indian/Alaska Native 1.0 2.1
% Black 2.9 4.2
% Middle Eastern 1.0 0
% White 90.3 89
% Decline to answer 2.9 0
Age (range, years) 18–78 19–87
Age (mean (SD), years) 36 (16) 52 (15) t (197) = −7.04, p < 0.001
Highest education attained χ2 (4) = 7.62, p > 0.05
% High school graduate 14 8.3
% Some college 31 18
% College degree 24 33
% Master’s degree 21 29
% Doctoral degree 9.7 11
Informant for SRS-2A sex χ2 (1) = 0.44, p > 0.05
% Female 56.3 64.6
% Male 21.4 32.3
% Missing data 22.3 3.1
Informant for BRIEF-A sex χ2 (1) = 0.55, p > 0.05
%Female 60.2 65.6
% Male 20.4 30.2
% Missing data 19.4 4.2
Only family members who did not report any psychiatric diagnoses, neurological diagnoses, or neurodevelopmental disorders in the medical history battery were included. Gender identity was not collected for family member participants. Results of statistical group comparisons (between probands and family members) are recorded in the last column. Pearson’s chi-square test was used for comparing proportions of sex, education level, and informant sex; Fishers exact test was used for comparing race proportions; and a two-sample t-test was used for comparing mean age. ASD Autism Spectrum Disorder, SRS-2A Social Responsiveness Scale – 2 Adult, BRIEF-A Behavior Rating Inventory of Executive Function – Adult
Measures
Measures included a screening questionnaire—Social Communication Questionnaire (SCQ)—as well as two additional questionnaires – Social Responsiveness Scale-2 Adult (SRS-2A) and the BRIEF-Adult (BRIEF-A). The SCQ was collected as an informant-report only for probands, if a parent was available to complete it. The SRS-2A and BRIEF-A were collected as both self-report (participant answering questions about themselves) and informant-report (another person answering questions about the participant) versions. For the informant-report versions of the SRS-2A and BRIEF-A, the informants varied in their relationship to the probands and family members and included parents, siblings, offspring, therapists, friends, children, and spouses. Relationship information for informants is included in Supplementary Materials. The informant for each participant was selected in collaboration with the participant, based on who knew the participant the best, was available, and was ≥ 18 years old. For probands, there were 106 unique informants (greater than the number of proband participants because sometimes the informant for the SRS-2A was different than the informant for the BRIEF-A). Note unique informants are defined by the identity of the informant, not the participant, so if a participant had different people complete their SRS and BRIEF, then they would count as two unique informants. In contrast, if an informant completed reports for multiple participants, they would still only count as one unique informant. Of these informants, 17 of them were enrolled as family member participants. For family members, there were 83 unique informants (fewer than the number of family member participants because some informants rated multiple people – an average of 1.18 other people). Of those informants, 46 were also enrolled as family members (so they contributed a self-report on their own behavior as well as an informant-report on another participant). Additionally, 8 of the informants on family members were enrolled as probands in the present study.
SCQ
The SCQ is an informant-report measure designed as a diagnostic tool for autism and pervasive developmental disorder (Berument et al., 1999). The SCQ was developed as a companion screening measure for the Autism Diagnostic Interview – Revised (ADI-R). The SCQ items were deliberately chosen to match the ADI-R items that were found to have discriminative diagnostic validity. A meta-analysis of the use of the SCQ as a screening tool found that it had acceptable accuracy for the identification of ASD (AUC = 0.827) (Chesnut et al., 2017). In this study, the SCQ was used as one of several sources of information to determine eligibility for individuals to participate as probands in the study. Probands had a mean SCQ score of 14.6 with a standard deviation of 7.6.
SRS-2A
The SRS-2A is a 65-question measure, available as both informant-report and self-report, composed of five subscales measuring social cognition, social communication, social motivation, RRB, and social awareness. The SRS has good agreement with the ADI-R across multiple symptom domains (r = 0.60–0.79) as well as good inter-rater reliability (r = 0.75–0.91) (Constantino et al., 2003). In addition to being used as a diagnostic tool, the SRS has been used to quantify autism-related behaviors in the general population (Constantino & Todd, 2003). In this study, it was collected as both a self-report and informant-report measure for both probands and family members. The raw total SRS-2A score was used in analyses.
BRIEF-A
The BRIEF-A is a 75-question measure of executive functioning. Executive functioning subdomains measured in the BRIEF-A include the following abilities: inhibit, shift, emotional control, initiate, working memory, plan/organize, organization of materials, and monitor (Roth et al., 2005). The BRIEF has good reliability with an internal consistency of 0.80–0.98 across multiple raters and with a test–retest reliability of 0.76–0.85 (Gioia et al., 2000). The BRIEF has been used in both autistic and non-autistic populations (e.g. Donders & Strong, 2016; Granader et al., 2014; Kenworthy et al., 2021; Rabin et al., 2006; Wilson et al., 2011). In this study, it was collected as both a self-report and informant-report measure for both probands and family members. The raw Global Executive Composite score was used for analysis.
Assessing Demographic Differences Between Probands and Family Members
Possible confounding demographic differences between proband and family members were examined using a two-sample t-test for comparing mean age. Additionally, Pearson’s chi-square test was used to evaluate differences in proportions of sex, education level, and informant sex, and Fisher’s exact test was used for race. The Fisher’s exact test was used for comparing the proportions of different racial identities as there were multiple small/zero values in categories that prevented precise estimation of chi-square statistic or p-value using the Pearson’s chi-square test.
Examining Agreement and Inter-Rater Reliability of Self- and Informant-Report SRS-2A and BRIEF-A Scores Using Correlation Analysis
Agreement was visualized using Bland–Altman plots and tested using (1) Spearman correlation between self- and informant-report versions of the same questionnaires measuring autism spectrum-related behaviors (SRS-2A) and executive functioning (BRIEF-A) and 2) intra-class correlation (ICC) analysis. Spearman correlation coefficients were used as the data had non-normal, varied distributions. ICC was used to quantify inter-rater reliability between self- and informant-report for the SRS-2A raw total score, as well as for the BRIEF-A raw Global Executive Composite score. A one-way random effects model with absolute agreement as the output was run first to assess the validity of a single score. Raw scores were used to test the relationship of the scores with sex and age without any possible obscuring via T-score transformation. Analyses were conducted for probands and family members separately. The Benjamini–Hochberg correction for multiple comparisons was used. Exploratory analyses comparing correlation strengths were conducted using Fisher r-to-z transformation.
Comparing Self- vs. Informant-Report Discrepancies Between Groups
For both the SRS-2A and the BRIEF-A, discrepancies between the self- and informant-reports were quantified as discrepancy scores, which were calculated by subtracting the self-report score from the informant-report score. Positive discrepancy scores indicate that the informant-report score was higher than the self-report score, while negative discrepancy scores indicate that the self-report score was higher than the informant-report score. Following tests for normality and for equal variance, analysis of covariance (ANCOVA) was used to compare the discrepancy scores for SRS-2A and BRIEF-A between groups, as defined immediately below, while accounting for the potential confounding variable(s). Analyses were conducted for probands and family members separately, investigating first the effect of the sex of the individual self-reporting and being reported on (referred to as participant sex). Exploratory analyses examined the effect of gender identity of the individual self-reporting and being reported on (referred to as participant gender) and effect of the sex of the informant (referred to as informant sex) on discrepancy. Gender identity was not reported for informants, so informant gender was not examined. The Benjamini–Hochberg correction for multiple comparisons was used.
Results
Examining Agreement and Inter-Rater Reliability of Self- and Informant-Report
For the SRS-2A in probands, the mean discrepancy score was −18.50 points (indicating higher levels of self-report SRS-2A scores relative to informant-report SRS-2A scores, on average) with a standard deviation of 42.28, upper 95% confidence interval value of 64.38, and lower 95% confidence interval value of −101.38 (see Fig. 1). For the BRIEF-A in probands, the mean discrepancy score was −11.24 points with a standard deviation of 35.65, upper 95% confidence interval value of 58.64, and lower 95% confidence interval value of −81.13. Range, mean, and standard deviation for raw scores, from which discrepancy scores were calculated from, are reported in Table 2. In Spearman correlation analysis among probands, there was no significant association between the self-report and informant-report total scores on the SRS-2A (r = 0.08, p > 0.05), nor was there a significant association between the self-report and informant-report scores on the BRIEF-A (r = 0.07, p > 0.05). This lack of significant correlation between self-report and informant-report versions of the same measures suggests that there is a strong impact of who is reporting for these domains, self vs. informant (see Fig. 1). Additionally, in intra-class correlation (ICC) analysis among probands, there was poor inter-rater reliability between self-report and informant-report for the SRS-2A (ICC = 0.01, 95% confidence interval (CI) [−0.19, 0.20] and for the BRIEF-A (ICC = 0.00, 95% CI [−0.19, 0.20]). Neither the ICC coefficient for SRS-2A nor the ICC coefficient for BRIEF-A was significantly different from zero (F(97,98) = 1.01, p > 0.05; F(97,98) = 1.01, p > 0.05).Fig. 1 Lack of agreement between self-report and informant-report scores for the same measures in adults high in autism spectrum traits. A, B Bland–Altman plots. Difference between measurements is calculated by subtracting the self-report score from the informant-report score. Average measurement is calculated by taking the average of the self-report and the informant-report score. Mean difference between measurements (aka discrepancy) is shown with a solid black line. The dashed red lines represent 95% upper and lower limits of agreement for the measures. A Bland–Altman plot for self-report and informant-report total raw scores for the SRS-2A in probands. Mean discrepancy (shown by the solid black line) below zero for the SRS-2A for probands. B Bland–Altman plot for self-report and informant-report score for the BRIEF-A raw Global Executive Composite (GEC) Score. Mean discrepancy (shown by the solid black line) below zero for the BRIEF-A. C Correlation between self- and informant-report scores on the SRS-2A in probands. Spearman's rho and the associated p-value are reported. No significant correlation between self-and informant-report score for SRS-2A total for probands. D Correlation between self- and informant-report scores on the BRIEF-A GEC in probands. Spearman's rho and the associated p-value are reported. No significant correlation between self-and informant-report score for BRIEF-A GEC score for probands. SRS-2A Social Responsiveness Scale-2 Adult, BRIEF-A Behavioral Rating Inventory for Executive Functioning-Adult
Table 2 Range, mean, and standard deviation of the scores for the measures collected as self-report and informant-report (SRS-2A and BRIEF-A) and later used in discrepancy analyses
Probands Family members
SRS-2A self-report raw total
Range 24–155 3–89
Mean (SD) 101.5 (27.2) 28.0 (16.1)
SRS-2A informant-report raw total
Range 14–160 0–162
Mean (SD) 83.3 (35.4) 27.7 (28.0)
BRIEF-A self-report raw GEC
Range 83–194 70–170
Mean (SD) 143.4 (22.5) 101.2 (20.7)
BRIEF-A informant-report raw GEC
Range 74–195 71–193
Mean (SD) 132.2 (28.7) 95.6 (24.5)
SRS-2A Social Responsiveness Scale – 2 Adult, BRIEF-A Behavior Rating Inventory of Executive Function – Adult, GEC Global Executive Composite score
For the SRS-2A in family members, the mean discrepancy score was 0.02, with a standard deviation of 26.76, upper 95% confidence interval of 52.47, and lower 95% confidence interval of −52.42 (See Supplement Fig. 1). For the BRIEF-A in family members, the mean discrepancy score was -5.64, with a standard deviation of 27.47, upper 95% confidence interval of 48.20, and lower 95% confidence interval of −59.48. In contrast to probands, for Spearman correlation analysis with family members, there was a moderate association between the self-report and informant-report total scores for the SRS-2A (r = 0.38, p < 0.05) and for the BRIEF-A (r = 0.34, p < 0.05) (See Supplement Fig. 1). Among family members in intra-class correlation (ICC) analysis, there was poor inter-rater reliability between self-report and informant-report for the SRS-2A (ICC = 0.34, 95% confidence interval (CI) [0.15, 0.51] and for the BRIEF-A (ICC = 0.26, 95% CI [0.06, 0.44]). In contrast to the probands, the ICC coefficient for the SRS-2A and the ICC coefficient for BRIEF-A were significantly different from zero (F(91,92) = 2.03, p < 0.001; F(91,92) = 1.7, p < 0.01).
Comparing Discrepancy Between Groups
Results for comparing potentially confounding demographic variables between groups are in Table 1. After identifying age as a potentially confounding variable, we investigated the impact of participant sex, participant gender, and informant sex on discrepancy scores for both the SRS-2A and BRIEF-A for probands and family members separately. Among probands, females (M = −30.1, SD = 36.4) had significantly greater magnitude (directionally more negative) SRS-2A discrepancy scores than males (M = −10.8, SD = 43.9) while accounting for participant age (F(1,100) = 6.66, p < 0.05) with a medium effect size of participant sex (η2 = 0.06; see Fig. 2A). Recall that the negative discrepancy scores indicate higher levels of self-report SRS-2A scores relative to informant-report SRS-2A scores. There was not a statistically significant sex effect for BRIEF-A discrepancy scores in probands (F(1,99) = 4.00, p = 0.05; η2 = 0.04). For family members, there were no differences based on sex on the SRS-2A (F(1,95) = 0.17, p > 0.05; η2 = 0.00) or on the BRIEF-A (F(1,91) = 0.02, p > 0.05; η2 = 0.00) (see Supplementary Fig. 2A & C). For descriptive and exploratory purposes, we examined the effect of participant gender on discrepancy within our sample. Among probands, there was an effect of gender identity on SRS-2A discrepancy (F(4,97) = 2.75, p < 0.05) with a medium effect size of η2 = 0.10 and a non-statistically significant effect on BRIEF-A discrepancy (F(4, 96) = 1.69, p > 0.05) with a medium effect size of η2 = 0.06 (see Fig. 2B and D). For family members, gender identity was not systematically collected, so no additional analyses were run.Fig. 2 Effects of participant sex, participant gender, and informant sex on discrepancy between self- and informant-report scores for probands. There was a significant effect of participant sex and of informant sex on discrepancy scores in the SRS-2A (calculated from total raw scores) in probands, with a marginal effect of participant gender. However, there were no significant effects of participant sex, participant gender, or informant sex differences on discrepancy scores for the BRIEF-A raw Global Executive Composite (GEC) score. Discrepancy scores were calculated by subtracting the self-report scores from informant-report scores. A discrepancy score of 0 indicates no discrepancy between self- and informant reports. Negative discrepancy scores indicate higher self-report scores relative to informant-report scores. Conversely, positive discrepancy scores indicate higher informant report scores than self-report scores. A Significant sex differences in SRS-2A raw total discrepancy scores for probands. B Marginal effect of gender identity on SRS-2A raw total discrepancy scores for probands. C Significant effect of informant sex on SRS-2A raw total discrepancy scores for probands. D No significant sex differences in BRIEF-A GEC discrepancy for probands E No significant effect of participant gender on BRIEF-A GEC discrepancy for probands F No significant effect of informant sex on BRIEF-A GEC discrepancy for probands. *indicates p < 0.05 after correction for multiple comparisons using the Benjamini–Hochberg correction. SRS-2A Social Responsiveness Scale-2 Adult, BRIEF-A Behavioral Rating Inventory for Executive Functioning-Adult, GEC Global Executive Composite Score of the BRIEF-A
We also examined the effect of informant sex on discrepancy for exploratory purposes. When reporting on probands, male informants (M = −42.7, SD = 37.4) and female informants (M = −11.1, SD = 37.7) differed in SRS-2A discrepancy scores (F(1,77) = 9.89, p < 0.01) with a medium effect size of informant sex (η2 = 0.11; see Fig. 2C). Generally, SRS-2A discrepancy scores were greater in magnitude with male informants and were in the negative direction, indicating higher levels of self-reported symptoms by probands relative to informant-reported symptoms when informants were males. There were no significant effects of informant sex on discrepancy scores for the BRIEF-A among probands (F(1,90) = 3.90, p > 0.05; η2 = 0.04), the SRS-2A among family members (F(1,90) = 1.12, p > 0.05; η2 = 0.01), or the BRIEF-A among family members (F(1,88) = 0.91, p > 0.05; η2 = 0.01) (see Fig. 2F and Supplementary Fig. 2).
Discussion
We found a lack of agreement and inter-rater reliability between self-report and informant-report scores for the same measures for probands, yet moderate agreement and low inter-rater reliability between self-report and informant-report measures in their family members. Additionally, we found a pattern of negative discrepancy scores between self and informant-reporting of autism-related behaviors for female probands, such that female probands reported more autism-related behaviors for themselves than their informant did about them. In exploratory analyses, we found a difference in discrepancy in reporting autism-related behaviors of probands according to the sex of the informant. Specifically, SRS-2A discrepancy scores were of greater magnitude and in a negative direction with male informants, indicating higher levels of self-reported symptoms by probands relative to informant-reported symptoms when informants were males.
Our findings related to discrepancy in reporting autism spectrum traits build on work previously done in child samples finding parent–child reporting discrepancies (e.g. Lerner et al., 2012) but differ from the small number of previous conflicting reports in autistic adults. One previous study found good self/other agreement on the SRS2-A among autistic adults (80% male sample) (Sandercock et al., 2020), while another study (with a male-only sample) reported poor self/other agreement but in the opposite direction of what we observed in our sample, with men reporting having fewer ASD symptoms in relation to their informant (Cederlund et al., 2010). Much of the previous work across all age ranges examining the agreement between self- and informant-report measures have relied on predominantly male participants (> 70%) and have either found good agreement or the effect of lower reporting of ASD symptoms according to self-report (Cederlund et al., 2010; Johnson et al., 2009; Lerner et al., 2012; Sandercock et al., 2020; White et al., 2012). In contrast, our sample had a relatively high representation of female probands (46.3%). Informants’ lower reporting of autism spectrum traits in female probands in our sample potentially could be related to camouflaging of ASD behaviors by probands. This would be in line with camouflaging work showing that while autistic individuals across sexes and gender identities camouflage, there seems to be higher rates of camouflaging among women (e.g. Hull et al., 2017; Lai et al., 2017). It also may be due to sex differences in the expression of autism-related behaviors in males and females (e.g. Lai & Szatmari, 2020) leading to informants identifying fewer autism-related traits in women. The impact of gender on discrepancy cannot be fully investigated in the present study. Given the lack of enrichment of trans and non-binary individuals, our sample lacks the necessary statistical power to do so. Recent work has taken multiple approaches to examine the intersection of gender diversity and the autism spectrum (George & Stokes, 2018; Manjra & Masic, 2022; Moore et al., 2022; Strang et al., 2020; Warrier et al., 2020). Future studies into reporter discrepancy, in addition to topics related to autism more broadly, are needed with larger numbers of trans and non-binary individuals, which would enable investigators to assess both the effects of gender, as well as sex assigned at birth.
While female probands, on average, had discrepancies that were greater in magnitude than male probands, our data demonstrate that many probands – male and female – had large discrepancies between self-report and informant-report scores. This suggests that self-reports and informant-reports may be carrying different sets of information for autistic adults. Recent work looking at ASD behaviors from childhood to young adulthood suggests that self-reports may be especially important in adults (Riglin et al., 2021). Riglin et al. focused on identifying trajectories of change and / or maintenance of levels of ASD traits (2021). They found that, by age 25 years, there were parent-reported differences between trajectory groups but not self-reported differences, concluding that incorporating self-report assessment, as well as a variety of measures, may be important for accurately assessing ASD traits in autistic adults (Riglin et al., 2021).
The lack of agreement and inter-rater reliability between self and informant reporting of executive functioning using the BRIEF among probands is in contrast to the studies examining self/other agreement in some other populations, but our results are generally aligned with findings in autistic adolescents (Donders & Strong, 2016; Kenworthy et al., 2021; Rabin et al., 2006; Wilson et al., 2011). However, the levels of concordance for executive function found among autistic adolescents were higher in Kenworthy et al., 2021 than those found in the present sample. This may be due to the difference in the mean age of the two samples, and/or due to some methodological differences between the present study and Kenworthy et al., 2021, including the following: (1) the studies use different versions of the BRIEF (BRIEF-2 child form in Kenworthy et al. vs. BRIEF-A adult form in the current study), (2) the studies use different forms of the GEC score (T-score transformed in Kenworthy et al. vs. raw score in the present study), and (3) ICC calculation methods vary, with the Kenworthy et al. study using a two-way random effects model testing for consistency (which cancels out systematic rating errors) and using an average score (Kenworthy et al., 2021). In contrast, the present study was testing for absolute agreement (do the raters produce the same score) to assess the validity of a single score, based on the current field practices to rely on one reporting method for adults (either self-report or informant-report). Our results emphasize the importance of collecting both self- and informant-report information in order to capture the full expanse of autism spectrum related behaviors and abilities, including executive functioning.
There are many possible sources for the self- vs. informant-report discrepancies in autistic adults. Informants may lack understanding due to a neurotypical viewpoint, in line with the concept of dialectical misattunement between neurotypical and autistic individuals or the double empathy problem, i.e. the idea that social communication difficulties are not solely reliant on the autistic individual’s inherent social ability, but are also dependent on their neurotypical social partner (Bolis et al., 2017; Milton, 2012). The effect of informant sex in particular suggests that the interpretation of autism-related behaviors may be more difficult when the informant does not share social context with the self-reporting participant (i.e. the informant and the participant are of different sexes). Additionally, informants may lack awareness of traits/thoughts that are not easily observable, have bias towards over- or under-assignment of autism spectrum traits, or have other factors influencing how they report. On the other side, the individual self-reporting may actively camouflage their behaviors. The self-reporter may also possess greater or lesser degrees of self-awareness or have individual bias in the way they view themselves that could affect their self-reports (Huang et al., 2017).
Among family members in the present study, there was poor agreement between self and informant report measures as measured by ICC, which was significantly different from zero but lower than values found in previous samples estimating self/other agreement for parents of autistic individuals (De la Marche et al., 2015; Möricke et al., 2016). It may be that the variability in the types of family members studied (not just parents of autistic children, as in some previous studies) and variability in the relationship between the family member and their informant contributed to lower self/informant report agreement compared to previous work. An additional consideration in the assessment of self/informant report correlations in probands vs. family members is that it is possible that differences between probands and family members in phenotype variability could affect agreement, e.g. that lower variability (generally high SRS and BRIEF scores) in proband phenotypes might partially account for the lack of self/informant report correlations in probands. But because variability in phenotypes in probands was fairly robust in our sample (with higher SRS and BRIEF standard deviations seen in probands than in family members, as shown in Table 2), this does not seem to account for the findings in our dataset. Nevertheless, this is an issue that deserves further research in future samples, using one or more additional measures of autism-related behaviors.
A limitation of this study is the lack of diversity related to certain demographics – namely gender identity, race, and education level. While our proband sample had a variety of gender identities reported, not enough non-binary and transgender people were included to investigate an effect of gender on discrepancy. A more balanced sample in terms of education level (as a rough proxy for socioeconomic status) and racial identity is necessary to ensure generalizability of the results. Additionally, this sample also only included those with a verbal IQ above 70 and cannot address the reporting/phenotype collection challenges related to those with lower IQ and/or intellectual disability. Another limitation of this study is the lack of consistency in the informant’s relationship to the participant. While we secured informant reports from parents or other close family members whenever possible, this was not possible in all cases, as some participants had family members who were unavailable (e.g. uncomfortable with participating). Incorporating probands in the study who did not have a parent informant allowed for broader inclusion but likely added variability and inconsistency in the type of knowledge and experience each informant had with the proband. This challenge in securing an informant with a consistent relationship to the proband seems to be specific to research involving autistic adults (as opposed to research with autistic children in which a parent, caregiver, and/or teacher is often available) and is another reason to collect both self-report and informant-report data in adults. Additionally, as described in the Methods and further detailed in Supplementary Materials, the informants were not from an entirely independent group. Even with this overlap in participants and informants in which many informants also served as family member participants, the discrepancy between self-report and informant-report scores for probands observed (mean of −18.5 points for SRS-2A and −11.2 points for BRIEF-A) is still a concerning observation and an area for future consideration and study.
To extend this study’s findings regarding self-report vs. informant-report discrepancies, future studies should investigate possible contributions to these discrepancies, including camouflaging, potential biases when reporting on autism-related behaviors, degree of shared social context of probands and informants, and the impact of an informant’s general autism-related knowledge on their reporting. Future work should also look for possible differences in agreement / discrepancy across different domains of autism-related traits (such as perspective taking, social engagement, repetitive motor behaviors), as these domains will vary in the degree to which an informant is able to observe them. Additionally, future work should examine the influence of different domains of cognition and/or behavior on discrepancy (for instance, does higher perspective taking abilities of the autistic adult or the informant relate to decreased self/informant discrepancy). Given the known variation in autism-related traits across sexes, this may be an especially important avenue to help disentangle whether the group effects observed here are in fact due to sex, are a simplified gender effect, are measurement or sampling effects, or emerge from different distributions of cognitive and behavioral phenotypes across genders. Future research should also look at how self and other reports align with diagnostic histories (e.g., age of ASD diagnosis, experience of misdiagnosis) and treatment histories (eg type of treatment received, when treatment began, etc.). Finally, looking at agreement in self-informant reporting for multiple measures in each domain, as well as agreement of self- and informant-reported measures with clinician ratings and laboratory performance-based measures will be an important check on the generalizability of the results of the present study. The presence of the discrepancies in the present study suggests that it is vital to use both self-report and informant-report measures in future research studies and clinical assessments, as they carry different sets of information, both of which are important. Not collecting self-report information for autistic adults may lead to missing important information about their experiences and phenotype.
Citation Diversity Statement
Recent work in several fields of science has identified a bias in citation practices such that papers from women and other minority scholars are under-cited relative to the number of such papers in the field (Caplar et al., 2017; Dion et al., 2018; Dworkin et al., 2020; Maliniak et al., 2013; Mitchell et al., 2013). Here we sought to proactively consider choosing references that reflect the diversity of the field in thought, form of contribution, gender, race, ethnicity, and other factors. First, we obtained the predicted gender of the first and last author of each reference by using databases that store the probability of a first name being carried by a woman (Dworkin et al., 2020; Zhou et al., 2020). By this measure (and excluding self-citations to the first and last authors of our current paper), our references contain 27.94% woman(first)/woman(last), 18.33% man/woman, 27.06% woman/man, and 26.67% man/man. This method is limited in that a) names, pronouns, and social media profiles used to construct the databases may not, in every case, be indicative of gender identity and b) it cannot account for intersex, non-binary, or transgender people. Second, we obtained predicted racial/ethnic category of the first and last author of each reference by databases that store the probability of a first and last name being carried by an author of color (Ambekar et al., 2009; Sood & Laohaprapanon, 2018). By this measure (and excluding self-citations), our references contain 6.29% author of color (first)/author of color(last), 18.85% white author/author of color, 20.76% author of color/white author, and 54.11% white author/white author. This method is limited in that a) names and Florida Voter Data to make the predictions may not be indicative of racial/ethnic identity, and b) it cannot account for Indigenous and mixed-race authors, or those who may face differential biases due to the ambiguous racialization or ethnicization of their names. We look forward to future work that could help us to better understand how to support equitable practices in science.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 112 KB)
This study was supported by the Autism Spectrum Program of Excellence at the University of Pennsylvania as well as the National Institute of Mental Health (F31MH125539). We would like to thank all of the participants for their time, for sharing their experiences, and for all of their efforts which made this study possible.
Author Contributions
Conceptualization: SCT, DJR, MB, ESB; Methodology: SCT, BNG, HCD, AL, ER, ZS, SS, LA, DJR, MB, ESB; Formal analysis and investigation: SCT, LA, ESB; Writing - original draft preparation: SCT, ESB; Writing - review and editing: SCT, BNG, HCD, AL, ER, ZS, SS, LA, DJR, MB, ESB; Funding acquisition: DJR, MB, ESB; Resources: DJR, MB, ESB; Supervision: DJR, MB, ESB.
Declarations
Conflict of interest
The authors have no competing interests, financial or otherwise, to declare.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734877 | NO-CC CODE | 2022-12-14 23:28:31 | no | Orth Unfallchir. 2022 Dec 6; 12(6):74-75 | latin-1 | null | null | null | oa_other |
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Minciunescu Andrei
Genovese Leonard
http://orcid.org/0000-0002-0660-4943
deFilippi Christopher [email protected]
grid.417781.c 0000 0000 9825 3727 Inova Heart and Vascular Institute, 3300 Gallows Rd, Falls Church, VA 22042 USA
3 12 2022
2023
5 1 1515 11 2022
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Cardiovascular and renal physiology are interrelated. More than a decade ago this was codified in guidelines defining the five subtypes of the cardiorenal syndrome. Morbidity and mortality for those with the cardiorenal syndrome is high compared to demographically matched individuals without cardiorenal disease, acute or chronic. The focus of this review will be the epidemiology, the impact of chronic kidney disease on cardiac structure and function, and associated clinical symptoms, outcomes, and potential treatments for patients with chronic reno-cardiac syndrome, or cardiorenal syndrome type 4. Cardiac structural changes can be profound and are described in detail both at a cellular and physiologic level. Integrating therapies for the treatment of causative or resulting comorbidities may ultimately slow progression of both cardiac and renal disease as well as minimize symptoms and death.
Keywords
Chronic renal insufficiency
Cardiorenal syndrome
Left ventricular hypertrophy
Fibrosis
Arterial stiffness
issue-copyright-statement© Springer Nature Switzerland AG 2023
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pmcMethods
The predominant source of information was obtained through PubMed searching terms including mesh terms (keywords as listed above and here: Chronic renal insufficiency, Cardiorenal syndrome, Left ventricular hypertrophy, Fibrosis, Arterial stiffness. The latter three terms were linked via “and” to the first mesh terms and “renal disease.” The citations of individual papers were then reviewed for additional primary source documentation. In addition, for epidemiologic data, we utilized data directly from the United States Renal Data System (https://www.usrds.org/annual-data-report/).
Introduction
The relationship between the cardiovascular and renal systems has long been recognized. In 2008, the acute dialysis quality initiative (ADQI) released consensus guidelines formally defining cardiorenal syndrome (CRS) and outlining five subtypes based on chronicity, primary organ of injury, and resultant pathophysiology (Table 1) [1, 2]. Much research interest remains in studying the population with chronic reno-cardiac syndrome, also known as CRS type 4, which is defined as cardiac dysfunction secondary to primary chronic renal disease [2]. Epidemiologic studies suggest that not only do chronic kidney disease (CKD) patients have a ten-fold increase in mortality risk compared to the general population [3, 4], but among this group greater than 50% of deaths are from cardiovascular disease (CVD) causes, including coronary artery disease, valvular dysfunction, arrhythmias, and cardiomyopathies [2, 3, 5–7]. As research aims to better characterize the interface between these two organ systems, understanding the pathophysiologic consequences of renal disease and resultant structural changes within the heart remains an important area of interest.Table 1 Cardiorenal syndrome definitions.
Adapted from Ronco et al. 2010 [2]
Syndrome Definition
Type I (acute cardiorenal) Sudden decline in heart function leading to acute kidney injury and dysfunction
Type II (chronic cardiorenal) Chronic impairment in heart function leading to chronic kidney disease
Type III (acute reno-cardiac) Sudden decline in kidney function leading to cardiac injury and dysfunction
Type IV (chronic reno-cardiac) Chronic kidney disease leading to heart injury, disease, or dysfunction
Type V (secondary Cardiorenal syndrome) Systemic illness leading to simultaneous cardiac and renal impairment
Epidemiology
The prevalence of chronic kidney disease in the USA, based on the United States Renal Data System (USRDS) reporting from 2003 to 2018, has remained stable at 14.4%, representing roughly 37 million Americans [8, 9]. This has led to an average annual Medicare cost of $114 billion U.S. dollars to care for these patients. The prevalence of advanced CKD, defined as stages 3–5, decreased from 2003 to 2006 compared to 2015–2018, with the greatest reduction in stage 3 from 6.3 to 5.8%. Within this same period, prevalence of all stages declined the most among individuals greater than age 65, from 43.2 to 36.8%, while remaining constant at 8.6% among those less than age 65. Given an aging population, such trends represent overall improvement, likely as a result of better treatment options and improved management strategies of associated risk factors [10].
Presence of CVD (defined as acute myocardial infarction [AMI], cerebral vascular attacks [CVA], and heart failure [HF]), is much greater among the CKD population at 66.6%, compared to 37.5% among individuals without CKD (Fig. 1) [8, 11]. As the degree of CKD worsens, HF becomes more prevalent (Fig. 2), and is the most common cardiac manifestation within this population, with a prevalence in 2018 of 27.7% (11.5% HF with reduced ejection fraction [HFrEF], 9.6% HF with preserved ejection fraction [HFpEF], 6.5% undefined), which is roughly 4 times higher than in similar individuals without CKD [8, 12].Fig. 1 Prevalence of various cardiovascular disease in CKD and non-CKD patient populations. Based on 2018 epidemiology data. Graph transcribed from USRDS Annual Data Report. 2020 [8]. Cardiovascular disease (CVD); heart failure (HF); acute myocardial infarction (AMI); valvular heart disease (VHD); peripheral artery disease (PAD); cerebral vascular attack (CVA); transient ischemic attack (TIA); atrial fibrillation (AF); sudden cardiac arrest (SCA); venous thromboembolism (VTE); pulmonary embolism (PE)
Fig. 2 Increasing prevalence of heart failure in worsening stages of CKD. Based on 2018 epidemiology data. Graph from USRDS Annual Data Report. 2020 [8]
Patients with both CKD and CVD have increased risk of hospitalizations, need for intensive-unit level of care, and death [12]. For these reasons, cardiorenal syndromes remain a significant public health burden, and as such, gaining a comprehensive understanding of pathophysiology is all the more necessary towards developing new management strategies.
Cardiorenal Syndromes
Cardiac and renal dysfunction results in a nuanced spectrum of disease with several shared risk factors and whose biochemical and hemodynamic pathways still have much to be discerned. As a result of this fine interplay and limited mechanistic understanding, several challenges exist in formulating an accurate definition and classification system. The National Heart, Lung, and Blood Institute attempted to encompass cardiorenal disease with a broad definition, whereby worsening renal function leads to worsening cardiovascular outcomes [13]. This definition, however, failed to encompass all observations seen in clinical practice and describe a clear mechanistic pathway.
The ADQI consensus guidelines established in 2008 remain the principal definitions used in practice today [2]. Cardiorenal disease was classified into five subtypes, defined by primary organ injury, resultant secondary organ insult, and chronicity: either acute or chronic. This definition was appealing in that it encompassed clinical presentations of cardiorenal disease, which better identified affected populations that helped facilitate development of therapeutic strategies [1, 14, 15]. Several mechanistic questions still persist, however as the definitions did not elaborate on the exact underlying pathophysiologic mechanisms of each disease state [1, 14].
Type 4 Cardiorenal Syndrome
Given the large prevalence of CKD in the general population, and the associated high morbidity and mortality of CVD events described above, it is important to understand the features of Type 4 CRS, also known as chronic reno-cardiac syndrome, with the intent to better establish therapeutic options going forward.
CRS type 4 is defined as longstanding CKD leading to cardiac injury and/or dysfunction [2]. According to the kidney disease improving global outcomes (KDIGO) guidelines in 2012 and 2019, CKD is defined as renal function with persistently reduced estimated glomerular filtration rate (eGFR) of < 60 ml/min/1.73 m2, or at least one indicator of kidney damage for greater than 3 months, including albuminuria, elevated urine sediment, or histological and structural renal abnormalities (Table 2) [12]. Physiologically, GFR is maintained at approximately 140 ml/min/ 1.73 m2 until age 40 (though epidemiologic cross-sectional analyses suggest decline begins as early as age 20), and gradually declines by 8 ml/min/1.73 m2 per decade afterwards [16, 17]. The presence of albuminuria, measured as a random urine albumin/Cr ratio (ACR) of 30 to 300 mg/g, also indicates CKD regardless of eGFR. Shared risk factors, including diabetes, hypertension, dyslipidemia, physical inactivity, smoking, and relevant family history harm both organ systems [8]. Both eGFR and degree of microalbuminuria have been shown to be independent contributors to risks of acute kidney injury (AKI), AMI, HF, CVA, or death.Table 2 CKD Stages one through five categorized according to eGFR and degree of albuminuria, with corresponding estimated percentages among the US general population surveyed between 2015 and 2018. From USRDS Annual Data Report. 2020 [8]
Cardiovascular risk factors such as hypertension, volume overload, anemia, iron-deficiency, nutritional deficiencies, bone disease, and uremic toxin buildup begin to develop once eGFR falls below 60 ml/min/1.73 m2 [4, 18]. Such factors trigger myocardial and endothelial dysfunction, resultant inflammation and oxidative stress, leading to vascular microcalcification and myocardial fibrosis. The cascade then manifests on a macrovascular level with reduced myocyte contractility, left ventricular hypertrophy (LVH) and/or dilation, ensuing heart failure (Fig. 3). At the level of the kidneys, glomerular sclerosis and renal parenchymal fibrosis are concomitantly observed [1, 3, 4, 7, 14, 19].Fig. 3 Overview of pathophysiologic mechanisms implicated in cardiovascular structural changes in the setting of CKD. Figure from Ronco et al. (2008) [20]
Microvascular Pathways and Changes
Cardiorenal syndrome can be thought of as a spectrum of disease with several microvascular pathways and mediators which all culminate in the final common denominator of fibrosis. An important aspect to consider is that many of these microvascular mechanisms are closely interlinked; thus, it is difficult to independently define a specific pathophysiologic role to each one individually.
The Renin–Angiotensin–Aldosterone System and Sympathetic Nervous System
The neurohormonal axis, composed of the renin–angiotensin–aldosterone system (RAAS) and sympathetic nervous system (SNS) is one such pathway. Chronic, persistent RAAS activation observed in renal disease patients occurs due to dysregulated renal blood flow. In addition to the net effect of sodium and water retention, elevated levels of aldosterone, and angiotensin II have numerous downstream implications within the inflammatory cascade and cardiac myocytes. Angiotensin II, a powerful vasoconstrictor, reduces coronary blood flow, and ensuing ischemia triggers an inflammatory cascade which then facilitates myocardial injury and necrosis, that then stimulates myocardial fibrosis and causes maladaptive remodeling and hypertrophy on the macrovascular level [21, 22]. Interestingly, in vivo studies on mice also suggested that circulating levels of angiotensin II may be cardioprotective following ischemic reperfusion injury [23], with one proposed mechanism stipulating that reduced coronary blood flow reduces the arrival of inflammatory mediators and thus limits inflammation; a hypothesis that will need validation in other models. Furthermore, several smaller peptides believed to be cleaved from angiotensin II, referred to angiotensin 1–7, can have cardioprotective effects [23]. Ongoing research is required to further delineate such mechanisms.
In conjunction with the RAAS, dysregulated and persistent SNS activation, a sequala of CKD, furthers maladaptive cardiac remodeling and dysfunction. Catecholamine release induces vasoconstriction within the kidneys, heart, and peripheral vasculature. Renal vasoconstriction triggers renin release and RAAS activation. Coronary vasoconstriction leads to myocyte ischemia. Catecholamines, in conjunction with angiotensin II and renin, stimulate tumor necrosis factors and interleukins, which in turn trigger endothelial dysfunction, myocyte apoptosis and necrosis, and fibroblast activation [23].
Inflammation and Cellular Mediators of Remodeling
The inflammatory cascade is important to consider as one of the principal drivers of structural heart changes observed in the setting of CKD. As previously discussed, reduction in eGFR below 60 ml/min/1.73m2 correlates with onset of a chronic inflammatory state [4, 7]. Neurohormonal activation, angiotensin II, catecholamines, uremic toxins activate pro-inflammatory cytokines such as tumor necrosis factor alpha (TNFα), interleukin-1 (IL-1), interleukin-6 (IL-6), and transforming growth factor beta (TGFβ) [1, 15, 21, 24, 25]. Renal impairment causes a systemic imbalance of superoxide and reactive oxygen species, which also contributes [22]. Such molecules trigger endothelial dysfunction and disrupt the delicate homeostasis of cellular membranes and mitochondria, leading to premature apoptosis and necrosis. Excessive endothelin-1 production within cardiomyocytes, for example, has been implicated in onset of LVH, as has persistent oxidative stress [1, 21, 24, 26, 27]. In particular, IL-6, a pro-inflammatory cytokine that has received significant attention as a result of its deleterious effects associated with severe COVID-19 infection, is also involved in regulating gene transcription among inflammatory, metabolic, and cell death pathways, and can have such deleterious effects on cardiac myocytes if left unregulated. Decreased nitric oxide availability due to endothelial dysfunction further propagates the above changes [15, 22].
Immune cells including macrophages, mast cells, neutrophils, and fibroblasts subsequently infiltrate the area of injured myocardium, remove the debris, and activate anti-inflammatory cytokines and fibroblasts, which, in mechanisms mediated by toll-like receptors (TLRs), damage-associated molecular patterns (DAMPs) among others, deposit collagen matrix, leading to fibrosis, reduced contractility, and hypertrophy [22]. While several molecules and mechanisms have been identified, the nuanced complexity carried among these systems remains an active area of research and must be further delineated before being effectively carried over to clinical treatments.
Fibroblast growth factor-23 (FGF23) is another mediator that has garnered interest, and, along with the transmembrane protein Klotho, are regarded as potentially having key roles in cardiac remodeling in the presence of CKD [28, 29]. Elevated levels of FGF23 have been implicated in the increased prevalence of LVH and mortality in CKD patients [30]. While the fibroblast growth factor proteins are involved in cellular development, proliferation, and differentiation, FGF23 works within the kidney to regulate phosphorus homeostasis by increasing phosphorus excretion within the proximal convoluted tubule and decreasing concentration of active vitamin D. CKD patients have impaired phosphorus excretion, thus elevated levels of FGF23 [30]. These pathologically elevated levels, in a dose-dependent manner, have been linked to greater risk of cardiovascular events and increased mortality. The study conducted by Faul et al. [30] sought to explain the pathophysiologic link associated with increased circulating FGF23 and CVD. In their proposed model, FGF23 acts upon the FGF receptor (FGFR) signaling cascade within cardiac myocytes, activating a host of tyrosine kinases implicated in signaling pathways that act upon the nucleus to upregulate gene transcription relating to growth and differentiation [30]. Similarly, there is research into the role of micro-RNA and myocyte development. In a model proposed by Bao et al. [31], FGF23, in addition to uremic toxins and TGFβ suppress cardiac micro-RNA 30 (miR-30) expression, a molecule abundant within cardiac myocytes that is implicated in regulation of cell hypertrophy [32–34]. Loss of miR-30 results in unregulated hypertrophy.
Klotho, a transmembrane protein principally expressed in the kidney and parathyroid glands, has been postulated as an important mediator of protective mechanisms against LVH. Klotho acts as a co-receptor which increases binding affinity of FGF23 to FGFR [30]. Though it was originally believed that Klotho and FGF23 acted in conjunction, Faul et al. demonstrated induction of LVH in mice where FGF23 levels were abnormally elevated, but Klotho was absent. Therefore, the role of Klotho ultimately remains to be further delineated for this reason [28]. However, longitudinal cohort studies among dialysis and pre-dialysis patients also did not detect a significant relationship between levels of circulating klotho and cardiovascular outcomes [35].
Fibrosis as the Final Common Pathway
While the initial cardiorenal syndrome classifications defined the different clinical presentations of disease, many questions remained about the underlying pathophysiology. Rather than think of each presentation as a distinct phenotype, cardiorenal syndrome is better described as a spectrum of disease, with tightly woven and interconnected pathways and mediators which ultimately result in tissue fibrosis on the microvascular level [14]. While the main intent of these mechanisms is to preserve cellular function and organ structure, the end result manifests as myocyte hypertrophy, increased stiffness with impaired contractility, chamber dilation, and subsequent HF symptoms. In the kidney, similar fibrotic pathophysiology occurs mediated by many of the same processes [14].
Macrovascular Pathways and Changes
Left Ventricular Hypertrophy and Increased Left Ventricular Mass
In conjunction with microvascular mechanisms, macrovascular changes also contribute to structural changes within the heart, kidneys, and peripheral vasculature. Post-mortem autopsies of CKD patients have identified LVH, diffuse coronary, valvular, and aortic calcifications, in addition to thickened, calcified pericardia [3]. In a study of 120 post-mortem evaluations of end-stage kidney disease (ESKD) patients, treated with hemodialysis (HD) with more than 1 year, 51% had dilated ventricles [36]. Similar findings have been observed using echocardiography. In a retrospective study of 567 ESKD patients initiating hemodialysis, the most common structural abnormality found at baseline was an increased left atrial volume index (81%), followed by grade 2 diastolic dysfunction (78%) and LVH (49%) [37]. Cardiac structural changes begin early during CKD. Individuals with stage 2 or 3 CKD, without prior cardiovascular heart disease, have subtle left ventricular dysfunction with reduced ventricular global systolic strain and higher left ventricular mass index, though overall LVEF remained preserved [38, 39]. Interestingly, the changes in cardiac structure and function with CKD is beyond the hemodynamic effects of concomitant disorders such as hypertension. In a study comparing 293 individuals with stages 2–5 CKD and hypertension to 289 individuals with hypertension without CKD. The CKD cohort had a significantly higher prevalence of echocardiography determined LVH and diastolic dysfunction of 62.8% versus 51.9% in those with only hypertension [40]. Finally, a cross-sectional study with cardiac magnetic resonance imaging of 134 nondiabetic, pre-dialysis patients with CKD stages 2–5 revealed increased myocardial T1 time, suggestive of increased interstitial fibrosis, with decreasing renal function, all in the setting of increased serum biomarker levels of fibrosis [41].
These studies underscore the observations that morphologic changes to the left ventricle begin to manifest in early stages of CKD, though LVEF remains preserved. Those progressing to ESKD carry a high prevalence of increased left ventricular mass, diastolic dysfunction, and impaired contractility by the time dialysis is initiated [21].
Hemodynamic Pathway
In terms of a mechanistic explanation of the abovementioned morphologic changes, several hemodynamic factors come into play [7, 21, 42–45]. As the RAAS system remains activated among CKD patients, this leads to a net retention of sodium and water, causing intravascular volume expansion. Resultant increase in central venous pressure causes elevated renal venous pressure, which reduces renal perfusion and further stimulates renin secretion and SNS activation. Interestingly, the right ventricle may play a greater role than previously thought, though the exact mechanism is unclear due to lack of studies highlighting presence of CRS in isolated right heart disease and absent left heart failure [46]. One proposed hypothesis is that increased RV afterload leads to a reduction in RV filling, thus reducing LV filling and output. Persistent RV pressure overload leads to RV wall dilation, which, within the confines of the pericardial sac can cause septal mechanical dyssynchrony with septal bowing into the LV, further reducing LV filling and stroke volume [1, 46]. Presence of RV dysfunction carries an independent association with increased mortality among a cohort of ESKD patients about to initiate hemodialysis [37], therefore further research is necessary on RV mechanistic properties.
At the microvascular level, peripheral venous congestion stresses vascular endothelium, causing phenotypic conversion of these cells into a pro-inflammatory state, accelerating calcification and fibrosis [1, 47]. Anemia of CKD is another contributor to hemodynamic imbalance, whereby reduced oxygen delivery to the endocardium perpetuates myocardial ischemia and triggers fibrosis, increased ventricular mass, and eventual reduced systolic function [48].
Afterload-related factors, such as chronic hypertension and decreased peripheral vascular compliance increase systemic vascular resistance. Arterio-venous fistula creation for hemodialysis can serve as high volume circulatory shunts, worsening intravascular volume overload and right ventricular workload [3, 12, 21]. Maladaptive myocardial cell thickening and concentric LVH in response to these factors may preserve LVEF during early course of CKD, but ultimately can lead to systolic failure [14, 21].
Peripheral Arterial Stiffness
Reduced peripheral vascular compliance also plays an important role in progressive left ventricular dysfunction in patients with CKD. It has been independently associated with increased cardiovascular risk, whereas reduced stiffness is associated with improved survival [25]. Arterial fibrosis occurs via similar microvascular pathways described above for the myocardium, leading to inflammation, calcification, and fibrosis of the artery vessel wall. In a mechanism set forth by Zanoli et al., elevated levels of circulating TNFα and decreased endothelial nitric oxide synthase (eNOS) expression allows for the local increase in oxygen radicals that trigger endothelial injury [25]. TNFα also upregulates low-density lipoprotein receptors, increases alkaline phosphatase expression, and reduces α-smooth muscle actin protein expression, ultimately stimulating inflammation and microcalcifications within vessel walls [25, 49]. Studies involving patients with inflammatory conditions such as rheumatoid arthritis and inflammatory bowel disease showed that anti-TNF agents may lead to reversal of inflammation-dependent aortic stiffening, and thus may represent a class of therapies to investigate in CKD patients as well [25].
Hemodialysis and Renal Transplant Implications on Cardiac Structure
Currently, medical options for ESKD patients aimed at reducing cardiovascular complications are limited. Evidence does exist that increasing the number of dialysis sessions reduces ventricular mass and lowers risk of cardiovascular-related hospitalizations and death [21, 50]. However, this potential benefit must be weighed against the risk of vascular access issues, complications, and infection [12]. Renal transplantation can also provide some degree of reversal in cardiac dysfunction, though this reversal is less prominent in those who have been undergoing hemodialysis for a longer period [51–54].
Arrhythmogenicity and Sudden Cardiac Death
Compared to the general population, patients with CKD have increased risk of atrial fibrillation, ventricular arrhythmias, and a 4–20 times greater risk of sudden cardiac death (SCD), with risk increasing as renal function declines [55, 56]. The mechanism is thought to be due to cardiac fibrosis, which causes high-resistance pathways within the electrical conduction system that delay the physiologic action potential, favors re-entry pathways and induces arrhythmogenicity [21].
To date, no therapy has been shown to decrease the risk of SCD. In a recent prospective, randomized controlled trial 200 ESRD patients on hemodialysis with an LVEF of ≥ 35% underwent implantable cardioverter-defibrillator (ICD) insertion with the intent to prevent SCD; however, the study was stopped due to futility as both arms experienced similar rates of SCD and 5-year survival [19]. Prophylactic implantable cardioverter-defibrillator therapy did not reduce the rate of SCD suggesting that terminal tachy- or bradyarrhythmia’s may be more related to systemic processes than immediately reversible cardiac etiologies [19].
Atrial fibrillation is the most pervasive arrhythmia within the CKD population and stage progression. Although no distinct causative relationship has been demonstrated between CKD and atrial fibrillation, the association is strong as both diseases share several risk factors including inflammation, oxidative stress, and fibrosis [56]. With regard to treatment strategies, the risk of stroke must be weighed carefully against the risk of bleeding, particularly in ESKD, as the overall benefit in this population is offset due to a greater risk of bleeding. Currently, there are no proven approaches to guide clinical decision making within this population, further compounded by a lack of randomized controlled trials [57]. Though apixaban has been approved for use in end-stage renal disease, it has never been studied in randomized control trials with respect to efficacy [56].
Conclusion
Cardiorenal syndromes are a spectrum of diseases with many clinical phenotypes. Though fibrosis represents a common final mechanistic pathway resulting in symptoms of HF, arrhythmias, and death, preceding fibrosis are several microvascular mechanisms are at play. These can be finely interwoven with renal pathophysiology such that it is challenging to isolate a particular point to develop a therapeutic strategy. The RAAS system is perhaps the best understood, and pharmacologic control of this system via ACE or ARB blockade has been used to attenuate the maladaptive remodeling responses within the heart and kidneys and improve outcomes in HF patients as well as attenuate CKD progression. Finally, the recent successes with sodium-glucose cotransporter-2 (SGLT2) Inhibitors in diabetic patients with early stages of CKD to prevent both CVD and reduce CKD progression is an exciting development and with increased mechanistic insights may open the door to additional effective treatment paradigms for patients with type 4 cardiorenal syndrome [58, 59].
Abbreviations
ACR Albumin creatinine ratio
ADQI Acute dialysis quality initiative
AKI Acute kidney injury
AMI Acute myocardial infarction
CKD Chronic kidney disease
CVA Cerebral vascular accident
CVD Cardiovascular disease
eGFR Estimated glomerular filtration rate
ESKD End-stage kidney disease
FGFR Fibroblast growth factor receptor
FGF23 Fibroblast growth factor-23
HD Hemodialysis
HF Heart failure
HFpEF Heart failure with preserved ejection fraction
HFrEF Heart failure with reduced ejection fraction
IL Interleukin
KDIGO Kidney disease improving global outcomes
LDL Low-density lipoprotein
LVEF Left ventricular ejection fraction
LVH Left ventricular hypertrophy
MI Myocardial infarction
MMP Matrix metalloproteinases
RAAS Renin-angiotensin-aldosterone system
SCD Sudden cardiac death
TGFβ Transforming growth factor beta
TIA Transient ischemic attack
TNFα Tumor necrosis factor alpha
USRDS United States renal data system
Author Contribution
AM and LG were the primary authors who reviewed the literature and wrote the initial draft of this review manuscript. Cd reviewed the manuscript for accuracy and edited the contents prior to submission. All authors take responsibility for the accuracy and content of the manuscript.
Data Availability
All data used to create this review manuscript is publicly available and cited in the references.
Declarations
Conflict of Interest
None associated with this manuscript. Unrelated to the manuscript include Dr. deFilippi receives consulting income from Abbott Diagnostics, FujiRebio, Ortho Diagnostics, Quidel, Roche Diagnostics, and Siemens Healthineers. Dr. deFilippi receives royalties from UpToDate. Other authors have no COI or competing interests to declare.
This article is part of the Topical Collection on Medicine
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| 0 | PMC9734879 | NO-CC CODE | 2022-12-14 23:28:31 | no | SN Compr Clin Med. 2023 Dec 3; 5(1):15 | utf-8 | SN Compr Clin Med | 2,022 | 10.1007/s42399-022-01347-2 | oa_other |
==== Front
Child Youth Care Forum
Child Youth Care Forum
Child & Youth Care Forum
1053-1890
1573-3319
Springer US New York
9722
10.1007/s10566-022-09722-9
Original Paper
Early Childhood Teachers’ Work Environment, Perceived Personal Stress, and Professional Commitment in South Korea
http://orcid.org/0000-0002-5950-6431
Byun Sooyeon [email protected]
12
Jeon Lieny 12
1 grid.21107.35 0000 0001 2171 9311 School of Education, Johns Hopkins University, 2800 North Charles Street, Baltimore, MD 21218 USA
2 grid.27755.32 0000 0000 9136 933X Present Address: School of Education and Human Development, University of Virginia, 405 Emmet St. S., Charlottesville, VA 22903 USA
9 12 2022
121
28 11 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Background
Teachers’ professional commitment is essential for providing high-quality early care and education (ECE) to young children. Previous studies suggest that teachers’ perceptions of low levels of personal stress and a satisfactory work environment are both likely to be associated with their greater commitment to work.
Objective
The current study examined the incremental validity of work environment as a predictor of professional commitment beyond personal stress perceived by ECE teachers in South Korea. Specifically, we hypothesized that teachers’ satisfactory work environment would predict a significant amount of variance in professional commitment beyond personal stress.
Methods
Survey data were collected from 322 ECE teachers in center-based programs in Korea. Confirmatory factor analysis (CFA) was used to examine the factor structure of the professional commitment latent variable. Hierarchical regression models were tested in structural equation modeling with the professional commitment latent variable.
Results
CFA for professional commitment demonstrated that a one-factor model was the best solution. The final model explained 40% of the variance in professional commitment (RMSEA = .067; CFI = .906). Findings indicated the incremental validity of work environment in predicting professional commitment beyond personal stress.
Conclusions
The current findings emphasize the importance of teachers’ experiences around having a satisfactory work environment and personal stress, either job-related or not, to retain teachers in ECE settings long-term. Program and policy level support to promote teachers’ well-being in their personal lives as well as professional lives may be critical to improve teachers’ professional commitment.
Keywords
Early childhood
Early care and education
Teacher stress
Teacher well-being
Teacher work environment
Professional commitment
==== Body
pmcIntroduction
Professional commitment is defined as “the relative strength of identification with, and involvement in, one’s profession” (Aranya et al., 1981, pp. 40–41). For early care and education (ECE) teachers, this indicates their commitment to care and education for children. Having professional commitment is critical for ECE teachers to create a positive environment for young children. Committed ECE teachers are likely to provide more positive support to children, create high-quality ECE settings, and perceive themselves as a valuable part of the ECE community (Doherty et al., 2006; Lee & Mun, 2021; Thomason & La Paro, 2013). Given the vital role of professional commitment, this study investigates the incremental validity of ECE teachers’ perceptions of a satisfactory work environment as a predictor of their professional commitment beyond personal stress in South Korea. In this study, we operationalize professional commitment as teachers’ satisfaction and intention to remain in the ECE workforce.
Previous studies have found that teachers’ stress is an important predictor of ECE teachers’ professional commitment (e.g., Yoo & Kwon, 2017). Although it is not widely studied, in a cross-country comparison study, South Korean ECE teachers reported higher levels of personal stress than teachers in other countries (e.g., Byun et al., 2022). Moreover, a cross-national comparison survey by OECD (2020) demonstrated that, compared to other countries, South Korean teachers more frequently identify various sources of stress, including a high volume of administrative work, keeping up with changing requirements from authorities, addressing parents’ and guardians’ concerns, and additional duties such as cleaning. One of the possible explanations for these findings is the collectivistic cultural characteristics in the South Korean society. Being a collectivistic society traditionally under Confucian ideologies, the South Korean society tends to value harmonious interpersonal relationships (Kim et al., 1994; Triandis, 1995). Therefore, South Korean teachers often experience high levels of stress related to parent-teacher interactions (e.g., Chung, 2018; Hwang et al., 2012), which might be because teachers are under the pressure of maintaining a harmonized relationship with parents regardless of the context. Furthermore, reflecting collectivistic norms and values, the South Korean ECE system (across various dimensions such as curriculum, tuition, and operation) is centralized to the government (e.g., Ministry of Health & Welfare, 2021). This may be associated with the high levels of stress related to administrative duties and efforts that teachers may experience as they try to meet governmental requirements.
According to the Job Demands-Resources Theory (JD-R; Bakker & Demerouti, 2017), job demands and resources consist of physical, psychological, social, and organizational features. Job resources facilitate an achievement of one’s work goals and personal growth and can lead to higher levels of work engagement and commitment among employees. On the contrary, job demands consume individuals’ physiological or psychological efforts and can lead to higher levels of job strain, which in turn, reduce employees’ work engagement and commitment (Bakker & Demerouti, 2017). However, having sufficient job resources can attenuate the association between job demands and job strain (Bakker & Demerouti, 2017). The JD-R theory suggests that ECE teachers’ satisfaction with their work environment, which serves as a job resource, may additively predict their professional commitment beyond teachers’ psychological stress. Based on this theoretical framework, we hypothesized that teachers’ perceptions of a positive work environment would show incremental validity in predicting greater professional commitment in the ECE context beyond lower levels of personal stress.
Relevance of Teachers’ Work Commitment
Work commitment has multiple features, such as organizational commitment and professional commitment (Morrow & Wirth, 1989). Organizational commitment refers to an individual’s identification, involvement, and loyalty to one’s organization (Mowday et al., 1982). Professional commitment is commitment to one’s profession, rather than the organization itself. For teachers, professional commitment is their commitment to the teaching profession and to educational practice. Teachers with strong professional commitment identify their professional goals and values related to teaching children, get involved in teaching activities, and show loyalty to remain in teaching profession (Tyree, 1996).
Ro (2004) identified three subcomponents of professional commitment among South Korean teachers, such as professionalism, affection, and a passion for education. Altogether and individually, these three components of professional commitment were found to be closely related to diverse aspects of ECE contexts in South Korea (e.g., Kang & Shon, 2017; Lee & Mun, 2021). For example, when ECE teachers had strong professionalism and affection for education, they tended to perceive themselves as having a positive influence in their ECE program community (S.-M. Lee & Mun, 2021). Moreover, when ECE teachers reported professional commitment, parents were more likely to be satisfied with the program (M.-K. Kim & Park, 2019).
Despite the importance of professional commitment among ECE teachers, a survey conducted in 2018 revealed that 12.2% of South Korean ECE teachers in childcare centers indicated an intention to leave the profession, and about half of them had actual plan to leave the workforce (Kang, 2019). This rate is about six times higher than elementary teachers’ turnover rate in the same year (2.1%; Korean Educational Development Institute, 2019). The low level of professional commitment among ECE teachers is a severe concern to maintain the quality of ECE. Therefore, it is essential to understand how teachers’ personal and job-related factors are associated with their professional commitment, and ultimately, how to retain more teachers in the ECE field in South Korea.
Association Between Perceived Personal Stress and Professional Commitment
Previous literature suggests that teachers’ personal stress is important because personal stressors that are potentially unrelated to their job might be associated with their job performance or commitment (e.g., Buettner et al., 2016). Perceived personal stress originates from the perception of unpredictability, uncontrollability, and overloading of overall challenging life situations, not constrained to event-specific stress (Cohen et al., 1983). Therefore, it captures individuals’ cognitive appraisal of stressors whether those are work-related or not, providing a more holistic understanding of individuals’ psychological states that may have unique associations with their work (Lee et al., 2013; Wright & Cropanzano, 2000).
Previous studies identified the association between South Korean ECE teachers’ job-related stress and work commitment. For example, in South Korea, ECE teachers’ job-related stress was negatively associated with their organizational commitment (Jung & Lee, 2016; Kim & Chung, 2014; Lee & Kim, 2016; Yoo & Kwon, 2017) and positively associated with their turnover intention (Jang & Kim, 2019; Jeong & Yoon, 2016; Yoo & Kwon, 2017). Still, few studies on South Korean ECE teacher focused on personal stress beyond their job-related stress (Jeong et al., 2021). Unfortunately, among ECE teachers, personal stress has been found to play a unique role that is different from job-related stress (Jeon et al., 2019). Given the paucity of studies, the current study attempts to understand the association between perceived personal stress and professional commitment among South Korean ECE teachers.
Association Between a Satisfactory Work Environment and Teachers’ Commitment
Above and beyond teachers’ perceived personal stress, teachers’ perceptions of a positive and satisfactory work environment may also be a significant predictor of work commitment. Jorde-Bloom (1988) identified five key indicators of a satisfactory work environment for ECE teachers: co-worker relations, supervisor relations, the nature of the work itself, pay and opportunities for promotion, and general working conditions. First, co-worker relations refer to having trustful, respectful, and close relationships with colleagues. Second, supervisor relations indicate having social, emotional, and professional support from leadership of the program. Third, the nature of the work itself means perceiving joy and value of the ECE work per se. Fourth, pay and opportunities for promotion include overall aspects of payment, benefits, and career opportunities. Finally, general working conditions refer to the structural and contextual characteristics of the workplace, such as work hours, classroom structure, and physical work environment (Jorde-Bloom, 1988).
The association between ECE teachers’ perceptions of work environment and commitment appears in various national contexts. In her original research, Jorde-Bloom (1988) found that each of the five proposed indicators were significantly associated with organizational commitment among ECE teachers in the United States. Grant et al., 2019) also demonstrated that ECE teachers’ perceptions of a chaotic classroom work environment were negatively associated with their work commitment in the U.S. Furthermore, Pek-Greer and Wallace (2017) found that ECE teachers’ payment and benefits, work condition, and professional development opportunities were associated with their intention to continue working in the ECE field in Singapore.
Findings with South Korean ECE teachers have been consistent with studies from other countries. Similar to Jorde-Bloom’s (1988) study, Seo and Lee (2002) found that all five indicators of the satisfactory work environment had positive correlations with ECE teachers’ organizational commitment and negative correlations with their turnover intentions in South Korea. A qualitative study by Lee and Kim (2010) also demonstrated that factors such as teacher–child ratios, payments, professional support for instruction and instruments, and social and emotional support from directors, coworkers, and parents were related to the work commitment of ECE teachers in toddler classrooms. Likewise, Kim et al. (2017) identified that ECE teachers’ perceptions of a practical and reasonable organizational culture were positively associated with their commitment to teaching, whereas teachers’ perceptions of a hierarchical organizational culture were negatively associated with their commitment to teaching. Finally, Kang and Shon (2017) reported that ECE teachers’ perceptions of a positive and supportive organizational culture were associated with their organizational commitment as well as their commitment to the teaching profession in South Korea.
Incremental Validity of the Work Environment Beyond Personal Stress
Notably, when ECE teachers perceive a positive work environment, they tend to report low levels of stress (Jeon & Ardeleanu, 2020). For South Korean ECE teachers, Kwon (2010) found that teachers’ perceptions of a positive, intimate, and collaborative ECE climate were associated with lower levels of job-related stress. In addition, when teachers perceived their ECE programs as not having common motivation or professionalism among teachers, they reported higher levels of job-related stress (Kwon, 2010). Furthermore, payments, benefits, work hours, and support for professional development were significantly associated with ECE teachers’ job-related stress (Hwang et al., 2012; Kim & Moon, 2016; Lee & Lim, 2017; Oh, 2014).
However, teacher-perceived work environment can potentially have a unique role beyond perceived personal stress. For example, even though teachers do not feel stressed, they may still experience ergonomic pains, which is common among ECE educators due to the physical demands of the job (e.g., frequent lifting and carrying of children) (Kwon et al., 2021). Due to possible physical health conditions, teachers might ultimately leave the profession regardless of their stress. Furthermore, regardless of their stress, if they are not satisfied with pay and promotion opportunities or the state of facilities, they may consider leaving the job. Considering these characteristics of the work environment, teachers’ perceptions of this environment may account for unique variances in their professional commitment.
There have been ongoing policy efforts to improve ECE teachers’ work environment in South Korea. For example, the South Korean government started to mandate a daily rest time and regular working hours for ECE teachers under the Labor Standards Act (2019). Moreover, government-supported substitute teachers are now provided when teachers take a vacation or participate in professional development (e.g., Child Care Act, 2019). Nonetheless, there are still substantial variations in work environments between kindergartens and childcare centers, and between public and private programs (Cha & Park, 2019; Kim, 2022). These discrepancies might be associated with weak professional commitment among teachers. In this context, the current study attempts to better understand the role of teachers’ perceptions of a satisfactory work environment in predicting their professional commitment beyond perceived personal stress.
The Present Study
This study investigates the incremental validity of work environment as a predictor of professional commitment beyond personal stress perceived by ECE teachers in South Korea. Specifically, we hypothesize that (1) teachers’ perceived personal stress will be significantly associated with professional commitment; and (2) teachers’ perceptions of a satisfactory work environment will predict a substantial amount of variance in their professional commitment beyond perceived personal stress.
We also include potential covariates related to the associations among ECE teachers’ work environment, personal stress, and professional commitment. First, the literature demonstrates that teachers’ personal and professional characteristics, and characteristics of the ECE program are associated with teachers’ psychological and professional well-being (e.g., Byun et al., 2022; Clayback & Williford, 2021; Hall-Kenyon et al., 2014; Kwon et al., 2021). For example, Byun et al., (2022) suggests that teachers’ ability to regulate their emotions are closely associated with their stress levels as well as their performance. Also, K.-A. Kwon et al. (2021) indicates that teachers’ physical well-being is associated with their psychological well-being. Therefore, to understand the associations among teachers’ perceptions of the work environment, personal stress, and commitment, the present study adjusts for teachers’ personal and professional characteristics (i.e., emotion regulation, age, years of experiences, health conditions, and educational attainment), and program characteristics (i.e., kindergarten vs. childcare, and public vs. private).
Method
Participants
A total of 322 ECE teachers from South Korea participated in this study. Among the participants, 96.6% were female, and 72% had a bachelor’s degree or higher. Teachers’ mean age was 32.9 years old. On average, teachers had 7.67 years of experience in the ECE field. Forty-seven percent of teachers were working in public or private kindergartens which include children of ages 3 to 5 (equivalent to preschools in the U.S.), while the rest of them were working in public or private childcare centers which care for children of ages 0 to 5. Thirty-three percent of teachers were working in public programs (kindergartens or childcare centers).
Procedure
This study was approved by the University Institutional Review Board. The case-level data are archived; however, they are not available for dissemination because the data includes sensitive private information (e.g., intention to leave the job) and we did not obtain informed consent to disseminate the data publicly from the participants at the time of data collection. The data collection was administered in summer 2019 with support from a private university located in Seoul, South Korea. Though the research team is based in the U.S., we visited South Korea during this time to facilitate recruitment and data collection.
ECE teachers in South Korea were recruited using snowball sampling. Teachers from both kindergartens and childcare centers, and across all types of programs, including public, private, home-based, employment-supported, and corporate-organizational programs were eligible to participate. Teachers were recruited from Seoul, Gyeonggi-do, and Gangwon-do regions where approximately a half of licensed ECE programs in South Korea are located (Korean Educational Statistics Service, 2020; MHW, 2019).
A total of 375 teacher surveys were mailed to each participating ECE program. A survey packet for each center included individual anonymous surveys for each teacher to complete and anonymous return envelopes for each teacher to seal their survey. For informed consent, respondents were informed that, by completing the survey, this constituted provision of consent to participate in the survey. Once teachers completed the surveys, programs recollected the sealed survey envelopes and sent them back to the research team. Among the distributed surveys, 322 surveys were returned (86% response rate).
Measures
The survey was initially designed in English using measures developed in English. If the measures had pre-existing Korean translation, the translated versions were included in the survey. Otherwise, a research team member whose first language is Korean translated the survey items into Korean. Then, another research team member whose first language is Korean reviewed the translation. Finally, an early childhood researcher working in South Korea confirmed the validity of translation.
Professional Commitment
ECE teachers’ professional commitment was estimated as a latent variable. Five items were used as indicators of the professional commitment latent variable. The first three items were adapted from the Schools and Staffing Survey (National Center for Education Statistics, 2012). Teachers indicated the degree to which they agreed or disagreed with the following items using a 5-point Likert scale (1 = “Strongly disagree”, 5 = “Strongly agree”): “Knowing what I do now, if I could decide all over again, I would become an early childhood educator again”; “Within the next 12 months, I will continue to be an early childhood educator”; and “This job is a short-term career for me.” The third item was reverse coded to allow higher composite scores to indicate higher levels of professional commitment. Teachers also answered two additional items adapted from Buettner et al. (2016), using a 7-point Likert scale (1 = “Strongly disagree”, 7 = “Strongly agree”): “I am satisfied with being an early childhood educator” and “I am satisfied with my current position.” The original scale, validated using a sample of U.S. ECE teachers, included one additional item asking about to what extent teachers will remain in their current programs within the next 12 months (Buettner et al., 2016).
We conducted factor analysis with the original six items to examine whether all six items load onto a single factor. However, in the current study, the additional item was excluded due to low factor loading, and a one-factor solution with remaining five indicators was taken (see details in the Results section). The excluded item describes commitment to their current programs while other five items measure commitment to the profession. The five items included in this study demonstrated Cronbach’s alpha of 0.82.
Satisfactory Work Environment
The short form of the Work Attitudes Questionnaire (Baker et al., 2010), which is adapted from Jorde-Bloom (1988), was used to assess teachers’ satisfaction with their work environment. Teachers were asked to answer each of the five items using a 5-point Likert scale (1 = “Not at all like my ideal”, 5 = “Is my ideal”): relationships with co-workers, relationships with director, the work itself, working conditions, and pay and promotion opportunities. In the current study, this scale had an acceptable reliability (Cronbach’s alpha = 0.75).
Perceived Personal Stress
Teachers’ perceived personal stress was measured by the Korean translation of the Perceived Stress Scale (PSS; Cohen et al., 1983; Park & Seo, 2010). Teachers responded to 10 items examining perceived levels of personal stress during the past month using a 5-point Likert scale (1 = “Never”, 5 = “Very often”). The sum of 10 items was used as a composite score representing the level of each teacher’s personal stress. A higher score indicated a higher level of perceived personal stress. In our sample, the PSS demonstrated Cronbach’s alpha of 0.82.
Covariates
We included eight covariates in the current study to adjust for teachers’ personal and professional backgrounds, health conditions, emotion regulation, and program characteristics. First, teachers’ age was calculated by subtracting the year of birth from the year of survey participation, and it was included as a continuous variable. The number of years working in the ECE field was also included as a continuous variable. Teachers’ educational attainment was included as a binary variable (1 = “Have a bachelor’s degree or higher”, 0 = “Less than a bachelor’s degree”). In addition, teachers’ overall perceived health conditions were assessed by one item adapted from the Respondent-Assessed Health Status Scale (Adams et al., 2012). Teachers’ emotion regulation strategies were measured by two subscales (i.e., reappraisal and suppression) under the Emotion Regulation Questionnaire (Gross, 1998) (Cronbach’s alpha = 0.78 and 0.77, respectively). Finally, two binary variables on program types were included; one item estimated whether the program is a kindergarten or a childcare center (1 = “Kindergarten”, 0 = “Childcare center”), and another item estimated whether the program is public or private (1 = “Public”, 0 = “Private”).
Analytic Plan
The current study used a cross-sectional and non-experimental/correlational design to explore the incremental validity of teachers’ satisfactory work environment as a predictor of professional commitment beyond perceived personal stress. All study variables demonstrated multivariate normality, showing the skewness and kurtosis values within the thresholds of acceptable normality (i.e., +/− 2 for skewness and +/− 7 for kurtosis; Hair et al., 2018). Descriptive statistics and pairwise correlations were used to investigate preliminary characteristics of each variable. To confirm the latent factor structure of indicators representing teachers’ commitment, a confirmatory factor analysis (CFA) was conducted using Stata 17.0. The 0.40 threshold was used to decide whether each item would be retained or not (Pituch & Stevens, 2016). Error terms were allowed to covary only when the covariances were suggested by model modification indices and theoretically justified.
With the professional commitment latent variable set in CFA, the incremental validity of work environment beyond personal stress was examined by hierarchical regression in structural equation modeling (SEM) based on Hunsley and Meyer’s (2003) approach. We fit three hierarchical models using SEM with professional commitment as a latent variable. Covariates were included in the first model, personal stress was added in the second model, and work environment was added in the third model. Any non-significant covariances were constrained to be 0 to estimate the most parsimonious model. Several model fit indices were considered to identify the overall model fit: chi-squared test (χ2) (expected to be non-significant, with a p-value greater than 0.05), a root mean square error of approximation (RMSEA) (expected to be less than 0.05), and a comparative fit index (CFI) (expected to be greater than 0.90) (Browne & Cudeck, 1993). To deal with the missing data, the Full Information Maximum Likelihood (FIML) estimation was used throughout all the analyses. This approach allows relationships among all available data to be preserved (Arbuckle, 1996). No auxiliary variables were included in addition to the variables included in the fitted models. All fitted models were overidentified.
Results
Missing Data Analysis
There were 0–0.62% of missing data in indicators of the professional commitment latent variable, 0.31% in the work environment, 0.93% in perceived personal stress, and 0–3.73% in covariates. No significant differences were found between participants with missing data and those with complete data. Therefore, we assumed missing at random and used FIML estimation for CFA and hierarchical regression models in SEM.
Descriptive Statistics and Bivariate Correlations
Descriptive statistics and correlations among key study variables are presented in Tables 1 and 2. Mean scores of indicators of teachers’ commitment were found to be above average, except for “Become an ECE teacher again.” All indicators of professional commitment were significantly correlated with each other. These items demonstrated significant correlations with satisfactory work environment and perceived personal stress as well. Teachers’ satisfactory work environment and perceived personal stress were also significantly correlated with each other.Table 1 Descriptive statistics of the study variables
Variable N % Missing M/% SD Min Max
Professional commitment indicators – – – – – –
Become an ECE teacher again 320 0.62 3.09 1.27 1 5
Continue to be an ECE teacher 321 0.31 4.34 0.93 1 5
Short-term careera 320 0.62 4.01 1.17 1 5
Satisfied being an ECE teacher 322 0.00 5.13 1.37 1 7
Satisfied with the current position 322 0.00 4.86 1.47 1 7
Remain at the program (dropped) 320 0.62 4.11 1.09 1 5
Perceived personal stress 319 0.93 18.13 4.68 4 33
Satisfactory work environment 321 0.31 3.45 0.68 1.40 5
Relationships with co-workers 319 0.93 3.95 0.88 1 5
Relationship with director 319 0.93 3.66 0.99 1 5
The work itself 316 1.86 3.08 1.01 1 5
Working conditions 321 0.31 3.42 0.90 1 5
Pay and promotion opportunities 319 0.93 3.09 0.97 1 5
Covariates
Reappraisal emotion regulation 321 0.31 5.04 1.00 2.33 7
Suppression emotion regulationb 320 0.62 4.36 1.25 1 7
Years of ECE experience 310 3.73 7.67 6.38 0.25 31
Health condition 322 0.00 2.74 0.96 1 5
Age 312 3.11 32.89 8.48 21 57
BA or higher 322 0.00 72% – 0 1
Kindergartenc 317 1.55 47% – 0 1
Public programd 317 1.55 33% – 0 1
aShort-term career is reverse coded, in the way that higher scores indicate greater commitment
bHigher scores indicate lower suppression emotion regulation (i.e., healthier emotion regulation)
cReference category is childcare centers (both public and private childcare centers)
dReference category is private programs (both private kindergartens and private childcare centers)
Table 2 Correlations among key study variables
1 2 3 4 5 6 7
1. Become an ECE teacher again –
2. Continue to be an ECE teacher .29*** –
3. Short-term careera .40*** .40*** –
4. Satisfied being an ECE teacher .60*** .40*** .50*** –
5. Satisfied with the current position .45*** .45*** .49*** .77*** –
6. Remain at the program (dropped) .12* .69*** .23*** .25*** .37*** –
7. Perceived personal stress − .34*** − .20*** − .24*** − .41*** − .39*** − .08 –
8. Satisfactory work environment .15** .21*** .22*** .24*** .30*** .25*** − .27***
*p < .05; **p < .01; ***p < .001
aShort-term career is reverse coded, in the way that higher scores indicate greater commitment
Confirmatory Factor Analysis
The measurement model with one factor was estimated for six indicators of teachers’ commitment following Buettner et al. (2016). To handle different measurement scales for included items (i.e., 5-point and 7-point Likert scales), indicator variables were standardized before examining the factor model. However, one of the indicator variables (“I will remain in the current program within the next 12 months”) demonstrated a factor loading of 0.34, which is lower than the 0.40 cutoff. Theoretically, this item was not aligned with other indicators because this item represents organizational commitment, while all other items represent professional commitment to ECE. This item also showed unique trend in its association with perceived personal stress, compared to other five items. Taken together, this item was excluded from the model. A one-factor solution with remaining five indicators demonstrated factor loadings greater than 0.40, with an adequate fit, χ2 (2) = 2.22, p = 0.330, RMSEA = 0.019, 90% CI [0.000, 0.114], CFI = 1.000.
Hierarchical Regression in SEM
Model fit indices and results of all three fitted hierarchical regression models implemented in SEM are presented in Table 3 and Fig. 1. As shown in Table 3, all three models demonstrated adequate fits. The results indicated that, as expected, teachers’ perceptions of their work environment demonstrated incremental validity as a predictor of their professional commitment beyond perceived personal stress. Specifically, in Model 1, the model only including covariates explained 32.53% of the variance in the professional commitment latent variable. Among the covariates, engaging in reappraisal emotion regulation (β = 0.29, SE = 0.05, p < 0.001), having positive health conditions (β = 0.37, SE = 0.05, p < 0.001), and working in public programs (β = 0.16, SE = 0.06, p = 0.010) appeared to be significantly associated with teachers’ professional commitment.Table 3 Hierarchical multiple regression implemented in structural equation modeling
Model 1 (covariates) Model 2 (personal stress) Model 3 (work environment)
Covariates
Reappraisal emotion regulation .29 (0.05)*** .22 (0.05)*** .20 (0.05)***
Suppression emotion regulationa .00 (0.05) − .07 (0.05) − .05 (0.05)
Years of ECE experience .06 (0.09) .05 (0.08) .02 (0.08)
Have BA or higher − .08 (0.05) − .07 (0.05) − .05 (0.05)
Health condition .37 (0.05)*** .28 (0.05)*** .27 (0.05)***
Age .05 (0.08) .01 (0.08) .02 (0.08)
Kindergartenb − .01 (0.06) .03 (0.06) .03 (0.06)
Public programc .16 (0.06)* .15 (0.06)* .17 (0.06)**
Key predictors
Perceived personal stress − .27 (0.06)*** − .24 (0.06)***
Satisfactory work environment .16 (0.05)**
R2 .3253 .3726 .3958
Change in R2 .0473 .0232
Model fit indices
χ2 (df) 105.88 (41)*** 112.04 (46)*** 134.54 (55)***
χ2 difference test – .29 .007
RMSEA [90% CI] .070 [.054, .087] .067 [.051, .083] .067 [.053, .082]
CFI .919 .920 .906
N = 322. FIML estimation. Standardized coefficients are reported
*p < .05, **p < .01, ***p < .001
aHigher scores indicate lower suppression emotion regulation (i.e., healthier emotion regulation)
bReference category is childcare centers (both public and private childcare centers)
cReference category is private programs (both private kindergartens or private childcares)
Fig. 1 The results of hierarchical regression in SEM. Note. Standardized coefficients and standard errors (in parentheses) are presented. Paths from the covariances among indicators of the professional commitment latent variable, and covariates (i.e., emotion regulation, years of ECE experience, educational attainment, health condition, age, and program type) were omitted from the diagram. *p < .05; **p < .01; ***p < .001. aShort-term career is reverse coded, in the way that higher scores indicate greater commitment
Next, by adding personal stress, the model explained an additional 4.73% of the variance in professional commitment in Model 2. Perceived personal stress was significantly and negatively associated with teachers’ professional commitment (β = –0.27, SE = 0.06, p < 0.001). However, the Chi-square difference test indicated that the model was not substantially improved compared to the previous model, χ2 difference (5) = 6.16, p = 0.29.
Finally, by adding work environment in Model 3, the model explained an additional 2.32% of the variance in professional commitment, and the model was significantly improved, χ2 difference (9) = 22.50, p = 0.007. In this final model, teachers’ satisfactory work environment was significantly and positively associated with professional commitment (β = 0.16, SE = 0.05, p = 0.001). After including work environment, teachers’ perceived personal stress still remained as a significant and negative predictor of professional commitment, although the association between personal stress and professional commitment was slightly weakened (β = –0.24, SE = 0.06, p < 0.001).
Discussion
The current study examined the incremental validity of ECE teachers’ satisfaction with their work environment as a predictor of professional commitment beyond perceived personal stress in South Korea. Consistent with our initial hypotheses, teacher-perceived work environment and personal stress were both significant predictors of teachers’ professional commitment. Also, work environment exhibited incremental validity in predicting professional commitment beyond personal stress.
Professional Commitment Among South Korean Teachers
It was interesting to find that the factor structure of professional commitment was different from the previous study on U.S. teachers. In Buettner et al. (2016) which examined the factor structure using the same set of indicators on a U.S. sample, all six indicators demonstrated high factor loadings. However, in the current study on a South Korean sample, one item asking about teachers’ commitment to the program had a low factor loading, so this item was excluded from the model. In addition, unlike the five included indicators, this item was not significantly correlated with perceived personal stress in the current sample. The item was significantly correlated with personal stress along with five other indicators in Buettner et al. (2016).
These findings are meaningful because they suggest that first, professional and organizational commitments may be conceptually different features, and second, the associations between teachers’ perceived personal stress, and their professional and organizational commitments can be varied by national contexts. Consistent with Wallace (1993), the variable representing organizational commitment and indicators of professional commitment were significantly correlated, but they played different roles for teachers. Also, the differences in factor structure between the U.S. and South Korea support Wallace’s (1993) finding that the association between professional and organizational commitments is sensitive to the presence of moderators (e.g., potential cross-country variations in characteristics of the ECE sector).
For example, in South Korea, teachers enter the ECE profession by getting a national ECE teacher certificate through a centralized and standardized procedure (e.g., credit requirements and several weeks of full-time apprenticeship) (Child Care Act, 2019; Early Childhood Education Act, 2017). Thus, moving to a different program is relatively easier for South Korean teachers as well. The U.S. teacher qualification system, however, varies by states and in fact, many states do not have required qualifications (McLean et al., 2021). This may indicate that U.S. teachers are likely to enter the ECE profession by being hired in a certain ECE program. Due to these different contexts, teachers in South Korea may perceive a commitment to the ECE profession and a commitment to the program as distinct features, whereas U.S. teachers may closely associate commitment to the profession with commitment to the program. Furthermore, when teachers have challenges in the program, South Korean teachers might perceive the challenges as more manageable, compared to U.S. teachers who might perceive them to be more uncontrollable. One of the key features of perceived personal stress is the perception of uncontrollability (Cohen et al., 1983). Thus, this cross-country variation may have been illustrated as the stronger association between commitment to the program and perceived stress among U.S. teachers. The differential factor structure of teachers’ commitment, and associations between perceived stress and commitment between South Korea and the U.S. are insightful examples of how investigating and comparing ECE teachers’ characteristics and well-being in diverse contexts can benefit the field.
Work Environment, Personal Stress, and Professional Commitment
In this study, teachers’ perceptions of a satisfactory work environment showed incremental validity as a predictor of their professional commitment beyond personal stress. Associations between the work environment and professional commitment, and stress and professional commitment are consistent with previous findings from other studies (e.g., Kang & Shon, 2017; Kim et al., 2017; Yoo & Kwon, 2017). However, while few studies have examined the role of personal stress (not job-related stress) on teachers’ professional commitment, this study adds to the evidence that perceived personal stress is also a significant predictor of professional commitment in the South Korean ECE context, similar to other countries (Buettner et al., 2016).
Notably, while the current study was conducted prior to the COVID-19 pandemic, this finding might be particularly relevant to the COVID-19 context. ECE teachers have suffered from additional stressors during the COVID-19 crisis such as managing safety measures and hybrid instructional forms (Park et al., 2020; Yu et al., 2021), in addition to general COVID-19 stressors common across all populations. Under these exceptional circumstances, teachers might have perceived increased levels of personal stress through challenges in both personal and professional realms of life, which further highlights the importance of understanding the association between perceived personal stress and professional commitment.
Furthermore, South Korean ECE teachers’ perceptions of a satisfactory work environment uniquely predicted professional commitment after accounting for personal stress. Considering the negative association between health conditions and perceived personal stress in our sample, it may be the case that a less satisfactory ECE work environment involves greater levels of physical demands and challenges teachers’ health conditions, which are likely to reduce their professional commitment regardless of their levels of personal stress. Our findings indicate that simultaneously improving teachers’ satisfaction with their work environment as well as their personal well-being might benefit their professional lives.
Yun and Lee’s (2020) case study provides a great example of how both the professional and personal lives of ECE teachers can potentially contribute to teacher turnover in the South Korean ECE context. In this study, the author described a process that a teacher, who was an acclaimed and highly achieving ECE professional, struggled with the negative spillover between work and family while going through marriage, pregnancy, and parenthood, and ended up leaving the profession. Interestingly, the teacher in Yun and Lee (2020) experienced a high level of stress even though she received diverse support to improve her work environment. For instance, the administrators of the program demonstrated deep understanding of the challenges that the teacher would have experienced as a working mother, and they accommodated her schedule so that she could take care of her child more easily. However, the accommodation of this teacher’s schedule added burdens to other teachers in the program, so her relationships with colleagues became awkward (Yun & Lee, 2020). This example may indicate that the work environment and personal stress might have unique roles although they are closely associated with each other. The example also suggests the importance of teachers’ satisfaction with all aspects of the work environment. If teachers have difficulties with one or two aspects of their work environment, those challenges might still be associated with their reduced professional commitment.
The descriptive statistics of individual items constructing the satisfactory work environment composite score suggested potential strategies to improve teachers’ satisfaction with their work environment in South Korea. Among the five items reflecting various aspects of the work environment, ECE teachers in the current sample reported the lowest level of satisfaction with items regarding “ECE work itself,” and “salary and promotion opportunities.” Hwang et al. (2012) identified that South Korean ECE teachers experienced high levels of job-related stress when they were overwhelmed by the excessive amount of work, and when parents were complaining or being disrespectful to teachers. Another study indicated that South Korean teachers had low expectations about pay and promotion opportunities, which were significantly associated with low levels of self-esteem as an ECE teacher, and low professionalism (Lee & Kim, 2017). Considering these examples, collective efforts involving ECE administrators and educators, parents, and the government might be needed to effectively manage work challenges among South Korean teachers.
Improvement in pay and promotion opportunities is, in fact, a complex issue in the South Korean ECE context. In South Korea, the government provides strict guidelines about the amount of tuition and additional costs that accredited programs can charge families, which are applied to both public and private programs (Ministry of Health & Welfare, 2021). Therefore, the flexibilities in budgeting in South Korean ECE programs is very limited, restricting the possibilities of improving pay and promotion opportunities for teachers. Due to this policy, teachers’ salary levels in the South Korean context are highly dependent on the government’s financial support, resulting in teachers in public programs receiving substantially higher salaries than teachers in private programs (Cha & Park, 2019). In 2019, 45% of kindergartens and 88% of childcare centers were operated in private sectors (Korean Educational Development Institute, 2019; Ministry of Health & Welfare, 2019). Either providing more financial support to increase teachers’ salary levels across ECE programs in both public and private sectors, or allowing more flexibilities in tuition and additional costs for private programs might improve pay and promotion opportunities among ECE teachers across all programs.
Limitations
While this study adds knowledge of the associations among ECE teachers’ perceptions of a satisfactory work environment, personal stress, and professional commitment in South Korea, it is not free of limitations. First, this study used cross-sectional data, not longitudinal data. Therefore, causal claims should be avoided because there are possibilities that the associations are bidirectional. For instance, teachers’ commitment can influence their perceived personal stress, or perceived personal stress can shape teachers’ perceptions of a satisfactory work environment (e.g., Jepson & Forrest, 2006).
Another limitation of the study is that all included measures are based on teachers’ self-report. Although it is important to explore teachers’ perceptions in understanding their commitment, there are two potential issues associated with this. First, these measures have increased risks of response bias. Teachers might have reported more positively or negatively on the included measures due to various reasons, such as social desirability, acquiescence, or the tendency to respond in extreme ways (Paulhus, 1991). Second, using the same method for all measures, the study is prone to common method bias (Podsakoff et al., 2003). Therefore, the findings of the current study should be interpreted with caution.
To add, there are concerns related to the generalizability of the findings. The current sample was recruited by snowball sampling; thus, there are possibilities of sampling bias. At the same time, a lack of data on some of the key sociodemographic characteristics might have limited our understanding of diversity within our sample. For example, we did not collect data on race/ethnicity and the first language of teachers because the ethnic and language composition of South Korea is highly homogeneous (e.g., the proportion of foreign migrants in the population was 2.3% in 2019, and 1.2% on average for the past 20 years; United Nations, 2019). Data on teachers’ marital status and their household income levels were also unavailable. Failing to include these potentially important variables leaves a possibility that the current study may have not accounted for potential variations of teachers’ demographics. Furthermore, while we did not collect data on the urbanicity of programs, the sample was primarily recruited from urban metropolitan areas in South Korea. Although the majority of ECE programs in South Korea are concentrated in urban and suburban areas (Ministry of Health & Welfare, 2019), the current sample underrepresents programs located in other regions of the country.
Implications and Future Research
Even though the study has these potential limitations, the current findings provide insightful knowledge to promote ECE teachers’ well-being in South Korea. First, considering that professional and organizational commitments show distinct features among South Korean teachers, approaches to enhance teachers’ organizational commitment and professional commitment may need to be differentiated. For instance, efforts to retain teachers in the same program for a longer period may have to focus on the relationships between coworkers within the program, whereas efforts to keep the teachers in the ECE field may have to address teachers’ fundamental needs at a policy level.
Second, the current findings encourage the continued efforts to promote ECE teachers’ satisfaction with their work environment in South Korea. Specifically, the study suggests that the potential areas of improvement might be the nature of ECE work (e.g., working with parents) and pay and promotion opportunities. More in-depth research, for example, qualitative studies using interviews or focus groups, might provide a better understanding of specific tasks and duties that challenge ECE teachers, and their realistic expectations about pay and promotion opportunities.
Third, to promote professional commitment among ECE teachers, it may be critical to support both a satisfactory work environment and reduced perceived personal stress. Reducing sources of teachers’ stress in their personal lives may be as important as improving a work environment to enhance ECE teachers’ professional commitment. For example, ECE policies allowing more flexibilities in maternity leave (e.g., allowing teachers to have longer leave so that they can come back when they are ready) or work hours (e.g., allowing teachers to work for reduced hours and providing substitute teachers for an extended period) might effectively support teachers with balancing their professional and personal lives (Yun & Lee, 2020). These efforts may be particularly important in South Korea, which is one of the collectivistic countries under Confucian ideologies, where family-to-work spillover appears more prominently than individualistic countries (Allen et al., 2015). In addition, given that teachers’ healthy use of emotion regulation and health conditions are associated with reduced levels of personal stress, interventions targeting improved emotion regulation strategies and health conditions might be helpful to reduce teachers’ stress levels.
Finally, the current study provides informed guidance for future research on ECE teachers’ well-being in South Korea. Some of the proposed areas to be studied include the identification of more specific needs of teachers, and strategies to simultaneously support ECE teachers’ satisfactory work environment and the well-being of children and families who they work with. Interdisciplinary collaboration between professionals from diverse areas, such as public policy, child development, education, and economics, may help the ECE field devise effective strategies to better support ECE teachers and their young children. In addition, given that our finding of incremental validity potentially indicates the mediating role of personal stress in the relationship between the work environment and professional commitment (Weems & Stickle, 2012), investigating temporal mediation models using longitudinal data might provide more clear understanding of the underlying mechanism of associations among the satisfactory work environment, personal stress, and professional commitment.
Author Contributions
All authors contributed to the study conception, design, and data collection. Funding was acquired by LJ. Data analysis and preparation for the first draft of the manuscript was led by SB, under the supervision of LJ. The initial draft was reviewed and revised by both SB and LJ. Both authors read and approved the final manuscript.
Funding
The study was supported by the Johns Hopkins University School of Education Dean’s Office.
Data Availability
The data used to support this study’s findings are not available for dissemination due to identifiable information. Please address any data-related questions to the corresponding author.
Declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
Ethical Approval
The project was approved by the Johns Hopkins University Homewood Institutional Review Boards to ensure protection of human subjects in this study.
Informed Consent
Informed consent was obtained from all individual participants included in the study.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734881 | NO-CC CODE | 2022-12-14 23:28:31 | no | Child Youth Care Forum. 2022 Dec 9;:1-21 | utf-8 | Child Youth Care Forum | 2,022 | 10.1007/s10566-022-09722-9 | oa_other |
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J Racial Ethn Health Disparities
J Racial Ethn Health Disparities
Journal of Racial and Ethnic Health Disparities
2197-3792
2196-8837
Springer International Publishing Cham
36469289
1481
10.1007/s40615-022-01481-6
Article
COVID-19 Pandemic Associations on Mental and Physical Health in African Americans Participating in a Behavioral Intervention
http://orcid.org/0000-0001-6710-4195
Bernhart J. A. [email protected]
12
Fellers A. W. 3
Wilson M. J. 24
Hutto B. 2
Bailey S. 4
Turner-McGrievy G. M. 1
1 grid.254567.7 0000 0000 9075 106X Department of Health Promotion, Education and Behavior, Arnold School of Public Health, University of South Carolina, Room 536, 915 Greene Street, SC 29208 Columbia, USA
2 grid.254567.7 0000 0000 9075 106X Prevention Research Center, Arnold School of Public Health, University of South Carolina, 921 Assembly Street, Columbia, SC 29208 USA
3 grid.254567.7 0000 0000 9075 106X University of South Carolina School of Medicine, 6439 Garners Ferry Road, Columbia, SC 29209 USA
4 grid.254567.7 0000 0000 9075 106X Department of Health Services, Policy, and Management, Arnold School of Public Health, University of South Carolina, 915 Greene Street, Columbia, SC 29208 USA
5 12 2022
17
7 7 2022
1 11 2022
23 11 2022
© W. Montague Cobb-NMA Health Institute 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The COVID-19 pandemic has had disproportionate effects on communities of color, with higher death rates among African Americans (AA). The purpose of this study was to assess associations in African Americans’ mental and physical health with the COVID-19 pandemic. Data for this study came from a larger nutrition intervention of AAs in the Southeastern United States, the Nutritious Eating with Soul study. Data collected before and after March 15, 2020 (the day when local South Carolina schools and businesses closed), were analyzed to assess the association of the pandemic on participants’ stress, control of healthy eating, physical activity, and body mass index. Repeated measures analysis of covariance using full maximum likelihood estimation to handle missing data was used. At the onset of the COVID-19 pandemic, 150 participants were enrolled in the study (48.2 ± 10.6 years old, 79% female, 75% with college degree or higher). Participants’ reporting of stress did not show statistically significant change over time. Cognitive control increased 1.43 points (F = 20.60, p < 0.0001) and body mass index increased 0.72 kg/m2 (F = 10.68, p = 0.001). Future longitudinal studies should investigate how the COVID-19 pandemic continues to present challenges to understanding and improving health among African Americans. The study is registered at www.clinicaltrials.gov NCT03354377.
Keywords
Stress management
Nutrition
Exercise/physical activity
Health disparities/research methodology
http://dx.doi.org/10.13039/100000050 National Heart, Lung, and Blood Institute R01HL135220 Turner-McGrievy G. M. University of South Carolina115700-20-54014 Bernhart J. A.
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pmcIntroduction
Compared to other race and ethnicity populations, African Americans have disproportionately higher rates of obesity and cardiovascular disease [1, 2]. These disparate health conditions are also prevalent comparing populations living in the southeastern areas of the USA to other areas [3]. Healthy behaviors such as stress management, healthy eating, and physical activity are known to mitigate obesity and cardiovascular disease. However, African Americans have reported how a lack of knowledge or self-efficacy, social support, and environmental influences make it difficult to begin and maintain behavior changes [4].
As researchers develop, deliver, and redesign interventions and programs to facilitate positive health behavior changes in African Americans, external circumstances and events may occur, impacting participants’ trajectory of behavior changes [5]. For example, one type of event that may impact positive behavior change is natural disasters. Research has demonstrated the negative side effects of natural disasters on a community’s social, emotional, and physical health [6, 7]. Hurricanes have been documented to produce negative effects on stress levels and health [8], and the physical damage caused by hurricanes exacerbates existing disparities African Americans may face regarding accessing healthy foods [9, 10].
Similar to a natural disaster, the COVID-19 pandemic was an external circumstance which caused an abrupt and unplanned closure of businesses, schools, and places of worship [11]. These unexpected changes and closures led to stay-at-home orders, creating major shifts in peoples’ daily routines and behaviors such as working remotely and not traveling to visit friends and family, which led to high levels of stress [12]. Furthermore, many people changed regular patterns in food consumption [13] and engaged in less physical activity [14]. Even more, COVID-19 mortality has been higher in African Americans compared to other race and ethnic groups [15]. Research has also found that African Americans struggled to maintain health during the COVID-19 pandemic [16]. For example, African Americans engaged in less exercise [17], experienced an increase in food insecurity [18] which may impact healthful eating patterns [19], and also have had difficulty managing stress and mental health [20, 21].
The Nutritious Eating with Soul (NEW Soul) study began in 2018 and recruited African American adults living in the Southeastern United States to participate in a 2-year dietary lifestyle intervention focused on soul food [22]. Participants were randomized to two groups, a vegan or low-fat omnivorous diet, for 2 years. Before the COVID-19 pandemic closures, participants attended in-person classes learning about nutrition education and receiving social support for following their assigned diet. Closures caused by the COVID-19 pandemic forced intervention delivery from in-person to online.
Adaptations to continue data collection of assessing participants on a delayed schedule were made which made a unique opportunity to conduct a sub-study related to how the pandemic was affecting a population of African American participants’ health related to stress, physical activity, and healthy eating during the early months of the COVID-19 pandemic. The primary research question for this study is as follows: How did the mental and physical health (i.e., stress, control of healthy eating behaviors, self-efficacy for healthy eating, physical activity, weight management) of African Americans participating in a dietary intervention change during the early months following the onset of the COVID-19 pandemic?
Methods
Study Design and Recruitment
Participants in this sub-study came from the NEW Soul study, described in detail previously [22] and described briefly here. The parent study was delivered to two separate 2-year cohorts, separated by 1 year. African American adults (N = 159) were randomized to a vegan or low-fat omnivorous diet and attended classes in a university-based teaching kitchen where they learned nutrition information, observed and participated in cooking demonstrations, and engaged in discussions and activities to facilitate adherence to their assigned diet. Participants completed study assessments at five regular time points throughout the study. The first cohort of the study occurred May 2018–August 2020, and the second cohort of the study occurred June 2019–June 2021.
Intervention delivery transitioned from in-person to online due to COVID-19 closures on March 15, 2020, the day local schools and the university where this study was hosted closed. Briefly, in-person intervention components of nutrition education, facilitated discussion around successes and challenges to healthy eating, and cooking demonstrations were maintained during online intervention sessions. Online intervention sessions were hosted using Zoom.
For this sub-study, data came from eligible participants (n = 150) active in the study on March 15, 2020. All participants provided signed informed consent at baseline to enroll in the study. An amendment was submitted and approved by the University Institutional Review Board to conduct this sub-study.
Data Collection
Table 1 displays the timeline for data collection for the two cohorts. Data were collected as part of already scheduled assessments during study. To assess the association that the COVID-19 pandemic was having on the health of NEW Soul participants, two time points were identified for each cohort to assess changes from before and after the onset of the COVID-19 pandemic. For participants in the first cohort, data collection for their final 24-month assessments was underway prior to March 15, 2020. Fifteen participants had completed their 24-month surveys prior to March 15 and were assigned to a pre-COVID onset group. These 15 participants were sent an additional survey with the same questions (see the “Measures” section) in June 2020 as the regularly scheduled surveys to be included in the post-COVID onset group. Participants received a $25 Amazon e-gift card for completing the additional survey. For participants in cohort 2, the participants who completed their 6-month survey and assessments in November–December 2019 were assigned to a pre-COVID onset group. Twelve-month assessments for cohort 2 were conducted in July 2020, and participants who completed their 12-month survey and assessments were assigned to the post-COVID onset group.Table 1 Timeline for data collection pre-COVID and post-COVID onset
Pre-COVID onset Post-COVID onset
Cohort 1 March 2020, as part of planned final 24-month assessments June 2020, additional survey sent to 15 participants
Cohort 2 November–December 2019, part of planned 6-month assessments July 2020, as part of planned 12-month assessments
Measures
Psychosocial outcomes
Due to the negative impact of the COVID-19 pandemic on stress [12] and eating behaviors [23, 24], stress and eating-related psychosocial measures were selected for this sub-study. Participants’ stress was measured using the 10-item Perceived Stress Scale where participants respond to situations using a 5-point Likert scale (i.e., 0 to 4) [25]. Scores 0–13 correspond to low stress, 14–26 to moderate stress, and 27–40 to high stress.
Self-efficacy for healthy eating was assessed with a shortened Weight Efficacy Lifestyle Questionnaire [26], where participants responded to ten situations using a 4-point Likert scale (i.e., 1 means not at all confident and 4 means very confident). Higher scores correspond to higher self-efficacy for healthy eating.
Lastly, cognitive control, disinhibition, and susceptibility to hunger were assessed using the Three-Factor Eating questionnaire [27]. Cognitive control refers to the degree of restraint involved in food consumption and is measured using 21 items. Disinhibition refers to the loss of control of food intake during negative emotional states or palatable foods and is measured using 16 items. Susceptibility to hunger refers to one’s sensitivity to hunger cues and is measured using 14 items. The first 36 items are true or false (true = 1 and false = 0), the next 13 items are measured on a 4-point Likert scale (i.e., 1 means rarely and 4 means very much), and the final question is scored on 6-point Likert scale (i.e., 1 means eat whatever you want, whenever you want it, and 6 means constantly limiting food intake, never “giving in”). Higher scores in each subsection correspond to higher levels of cognitive control, disinhibition, or susceptibility to hunger.
Physical activity
Physical activity was assessed using the International Physical Activity-Short Form (IPAQ-SF), a reliable and widely used measure in intervention studies [28]. Respondents reported physical activity over the past 7 days including the number of days and time spent each day in moderate- and vigorous-intensity physical activity, and walking. Respondents also reported sedentary time with the typical number of hours spent sitting on a weekday. Under normal assessment protocol procedures, a sensor measure of physical activity using an ActiGraph GTM accelerometer was used. Due to social distancing restrictions, the study team requested access to physical activity data from participants who reported wearing a Fitbit before and after March 15. An API database was created to sync participant data from Fitbit to the team.
Body mass index
Height was assessed using a wall-mounted stadiometer during in-person baseline lab assessments for cohort 1 in April and May 2018 and cohort 2 in May and June 2019. Body weight was measured during in-person lab assessments using a calibrated scale. For cohort 1, the most recent weight assessment prior to March 15, 2020, was in March and April 2019 as part of 12-month assessments. For cohort 2, the most recent weight assessment was in November 2019 as part of 6-month assessments. After March 15, 2020, weight was measured remotely in June 2020. Remote weight assessments were completed using the FitIndex Bluetooth Body Fat Scale (www.fit-index.com) which was mailed directly to participants’ (n = 75) homes. Instructions were sent to participants to set up their scale and create an account that linked to the research team for data collection [29].
Data Analysis
First, descriptive statistics summarized study participant demographics and mental and physical health using survey responses for stress, cognitive control, disinhibition, susceptibility to hunger, self-efficacy, and physical activity. Participants who completed weight assessments prior to March 15 were provided with FitIndex Bluetooth Scales to measure weight and assess body mass index. Second, repeated measures analysis of covariance using Full Maximum Likelihood Estimation to handle missing data was used to examine changes in each of the outcomes from the two time points before and after March 15 (one model for each outcome). Full Maximum Likelihood Estimation allows for unbiased estimates under a missing at random assumption when one time point was missing. All models controlled for participants’ age, cohort, sex, education, and class attendance (dichotomous high attendance (> 80% of classes attended from January 1, 2020) or low attendance (< 30% of classes attended since January 1, 2020)). A covariate of cohort was included to account for the different lengths in time for participants in each cohort between completing assessments in the pre-COVID onset and post-COVID onset groups.
Similar to weight and collecting a standardized measure for each participant after March 15, physical activity was to be assessed with a sensor measure; however, an unexpectedly lower number of participants (n = 18) linked their Fitbit to the API database. Of the 18 participants, only 9 had complete data during the desired time. Due to the lower number of participants with complete Fitbit data, these results were not included in the analysis for this study. All data were analyzed using SAS v.9.4.
Results
The demographic characteristics of participants active in the sub-study (n = 150) are presented in Table 2. Participants were mostly female (79%) and African American (100%), and had an average age of 48.2 ± 10.6 years.Table 2 Demographics of active participants (N = 150) in the NEW Soul study on March 15, 2020
NEW Soul study (N = 150)
Characteristic Total
Mean ± SD n %a
Age, years 48.2 ± 10.6
Sex
Male 32 21
Female 118 79
Diet group
Vegan (intervention) 71 47
Omnivorous (control) 79 53
Attendanceb
High 87 58
Low 63 42
Education
High school or equivalent, some college 38 26
College or advanced degree 112 75
Employment
Employed for wages 112 75
Retired 13 9
Other (self-employed, home maker, student, out of work, unable to work) 25 17
Child (< 18 years old) household makeup
0 60 67
1 20 22
2 + 10 11
Missing 60
Adult (18–64 years old) household makeupc
0 19 19
1 29 28
2 + 54 53
Missing 48
Older adult (65 + years old) household make up
0 63 80
1 13 16
2 + 3 4
Missing 71
aDue to rounding, percentages may exceed or not sum to 100
bHigh or low attendance refers to participants’ attendance leading up to the transition of intervention delivery from in-person to online. High attendance is > 80% and low attendance is < 30%
cDoes not include the participant in the study
Results of changes from pre-COVID onset to post-COVID onset in the psychosocial measures, physical activity, and body mass index are displayed in Table 3. For the Three-Factor Eating Questionnaire, cognitive control increased 1.43 points (F = 20.60, p < 0.0001). Self-efficacy for diet behaviors non-significantly decreased 0.11 points (F = 2.62, p = 0.11). The IPAQ met-minutes per day decreased, but was not significant (F = 0.03, p = 0.86). Body mass index significantly increased 0.72 kg/m2 (F = 10.68, p = 0.001).Table 3 Pre-COVID onset and post-COVID onset changes in psychosocial and physical health measures
Measure Possible range of measure n in models Pre-
LSM ± SE Post-
LSM, SE Time effect, F p
Perceived Stress Scale 0 to 40 113 19.65 ± 0.38 19.58 ± 0.43 0.03 0.87
Self-efficacy for Diet Behaviors 0 to 40 113 2.84 ± 0.07 2.73 ± 0.08 2.62 0.11
Three-factor Eating Questionnaire
Cognitive control 0 to 21 113 8.96 ± 0.39 10.39 ± 0.45 20.60 < 0.0001
Disinhibition 0 to 16 113 4.06 ± 0.32 4.61 ± 0.36 3.51 0.06
Susceptibility to hunger 0 to 14 113 3.58 ± 0.27 3.59 ± 0.28 0.00 0.95
Physical activity
IPAQ-SF (MET-minutes per day) – 113 2636.25 ± 302.10 2575.70 ± 349.16 0.03 0.86
Body mass index (kg/m2) – 116 36.18 ± 0.77 36.90 ± 0.80 10.68 0.001
LSM, least squares mean; SE, standard error. Each model adjusted for age, cohort, sex, education, and a dichotomous attendance level (high/low). Models accounted for missing data using Full Information Maximum Likelihood Estimation
Discussion
The NEW Soul study had a unique opportunity to assess the mental and physical health associations of COVID-19 on a population of African Americans participating in a dietary lifestyle intervention. The purpose of this study was to describe associations in participants’ stress, control of healthy eating behaviors, self-efficacy, physical activity, and body mass index with the onset of the COVID-19 pandemic.
Findings revealed no time effect regarding participants’ reported levels of stress, eating behaviors, and physical activity. First, stress levels exhibited no change over time after the pandemic began. This finding was very surprising as it does not align with previous research that determined individuals experienced higher levels of stress after the onset of the COVID-19 pandemic [12]. One possible explanation of this unexpected finding is that participants’ pre-COVID stress levels were already at a moderate level with scores between 14 and 26 on the Perceived Stress Scale [25]. Therefore, a ceiling effect may have been observed where participants would be less likely to report even higher levels of stress given reported stress as already at a moderate level prior to March 15, 2020.
Second, regarding healthy eating and weight management, cognitive control and body mass index increased over time; however, no significant time effect was found in participants’ reporting of disinhibition or susceptibility to hunger. Even more, only body mass index changed in the hypothesized direction, which aligns with previous research about risk factors for increased weight gain as a result of COVID-19 [30, 31]. Considering the importance of energy balance in losing or maintaining weight, with many people confined to their home unable to engage in regular outlets of physical activity, it follows that weight loss and management may prove difficult [32].
In addition, we attempted to collect a standard measure of participants’ body weight by sending Bluetooth scales directly to participant homes. This methodology seemed appropriate given a timely report about the use of Bluetooth scales in research [33]. However, only half of study participants elected to receive a scale. Additional analyses to understand factors affecting participant uptake, willingness, and engagement with Bluetooth scales determined that older participants and females were more likely to sign up to receive a scale for remote weight assessment [29].
Participants reported an increase in cognitive control regarding eating behavior. This finding was unexpected given how the pandemic altered daily life for many leading to disordered eating behaviors [34] and higher consumption of unhealthy foods [35]. For example, individuals who were working from home and commuting less may have experienced increased opportunities to engage in snacking and mindless eating. One possible explanation for this unexpected finding may have been that participants spending additional time at home were able to better control food intake than when under normal circumstances of living a busier schedule with more commitments and travel. However, research supporting this idea is limited.
Lastly, although also not significant, physical activity levels trended in the expected direction as participants reported spending less time doing physical activity via the IPAQ-SF and the Fitbit data. COVID-19 restrictions prevented the distribution of accelerometers for a sensor measure of physical activity; however, we attempted to test an innovative way of remotely collecting sensor-measured physical activity through participants’ Fitbit devices. Fewer participants than expected synced their Fitbit accounts to the research database, and even fewer of synced accounts had usable data. Overall, this study’s finding does align with a previous study that identified negative trends in physical activity levels due to COVID-19 [14].
This study was not without limitations. One limitation relates to collecting physical health data of weight and physical activity using standard procedures and equipment. For remote weight collection using Bluetooth scales, even though the same scales were ordered and distributed to participants, measurement consistency in each participants’ weight assessment in their home (i.e., weighing early in the morning, ensuring participants wore light clothing) could not be controlled. Physical activity data were primarily collected using self-report methods which often leads to response bias and over-reporting [36]. Second, this brief, longitudinal study lacked another point in time for data collection following the onset of the COVID-19 pandemic which continues to be an ongoing issue affecting individuals and research projects. Had in-person restrictions continued into fall 2020, at least another weight measurement from the Bluetooth scales would have been collected. For this study, data within a relatively short and early time window after the COVID-19 pandemic began were analyzed. Using data and findings from the overall 2-year NEW Soul intervention may further explain the impact of COVID-19 on participants. Lastly, due to different timelines for data collection between the cohorts, there was substantial loss to follow-up between pre-COVID onset and post-COVID onset groups. These differences in timelines and loss to follow-up may bias results. This limitation of loss to follow-up also substantially underpowered any analyses of differences in findings by cohort or socio-demographics.
Despite these limitations, this study had notable strengths. First, this longitudinal study design allowed for the assessment of relevant health behaviors disrupted by COVID-19 where cross-sectional studies are limited by temporality [37]. Given that the cohorts had staggered pre-post COVID-19 onset data collection time points, analyses controlled for participants’ cohort. This study also incorporated objective measures of weight and used validated surveys to assess stress, self-efficacy, and eating behaviors. Second, this study worked with all African American adults, a population at higher risk of complications from COVID [15, 38].
This study did not identify the hypothesized associations between the onset of the COVID-19 pandemic and health behaviors in African Americans. It is important to note that this work was exploratory during the early months of the COVID-19 pandemic. Given that the effects of the COVID-19 pandemic continue to persist and present a unique set of challenges to researchers and African Americans, further work is needed to understand impacts on psychosocial health and best strategies to positively impact behaviors related to stress, healthy eating, and physical activity in African Americans.
Acknowledgements
The authors would like to thank the participants for being in the study. We would also like to thank Mr. Brent Hutto for his assistance with the statistical analysis.
Author Contribution
Gabrielle Turner-McGrievy and John Bernhart obtained funding for the study and contributed to the study conception and design. Material preparation, data collection, and analysis were performed by John Bernhart, Ashley Fellers, Mary Wilson, and Shiba Bailey. The first draft of the manuscript was written by John Bernhart. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by the National, Heart, Lung, and Blood Institute of the National Institutes of Health under award number R01HL135220. The content is the sole responsibility of the authors and does not necessary represent the official views of the National Institutes of Health. The work was also supported by the Office of Research at the University of South Carolina under award number 115700–20-54014.
Data Availability
The data underlying this article cannot be shared publicly due to protections of participant confidentiality.
Declarations
Ethics Approval
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the University of South Carolina.
Consent to Participate
Informed consent was obtained from all individual participants included in the study.
Consent for Publication
Informed consent explaining the study team’s intent to publish was obtained from all individual participants included in the study.
Competing Interests
The authors declare no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36469289 | PMC9734885 | NO-CC CODE | 2022-12-14 23:28:31 | no | J Racial Ethn Health Disparities. 2022 Dec 5;:1-7 | utf-8 | J Racial Ethn Health Disparities | 2,022 | 10.1007/s40615-022-01481-6 | oa_other |
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Curr Emerg Hosp Med Rep
Curr Emerg Hosp Med Rep
Current Emergency and Hospital Medicine Reports
2167-4884
Springer US New York
255
10.1007/s40138-022-00255-y
Critical Care and Resuscitation (A Malik, Section Editor)
Current Considerations in Emergency Airway Management
Pirotte Andrew [email protected]
123
Panchananam Vivek [email protected]
4
Finley Matthew [email protected]
4
Petz Austin [email protected]
1
Herrmann Tom [email protected]
1
1 grid.412993.4 0000 0004 0607 262X Department of Emergency Medicine, University of Kansas Health System and University of Kansas Medical Center, 4000 Cambridge Street, Kansas City, KS 66160 USA
2 grid.412993.4 0000 0004 0607 262X Delp Academic Society, University of Kansas Health System and University of Kansas Medical Center, 4000 Cambridge Street, Kansas City, KS 66160 USA
3 grid.412993.4 0000 0004 0607 262X Office of Student Affairs, University of Kansas Health System and University of Kansas Medical Center, 4000 Cambridge Street, Kansas City, KS 66160 USA
4 grid.412993.4 0000 0004 0607 262X University of Kansas Health System and University of Kansas Medical Center, 4000 Cambridge Street, Kansas City, KS 66160 USA
3 12 2022
2022
10 4 7386
26 10 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Purpose of Review
Emergency airway management is populated by many new concepts, evolving equipment, and contemporary strategies for optimal procedural success. This review aims to discuss various topics within these realms and to continue the ongoing conversation regarding improvement of emergency airway management.
Recent Findings
Various literature, opinion pieces, podcasts, and trials have prompted renewed interest in the field of emergency airway management. Though common threads can be found, there is significant debate on optimal practice. Accompanying these conversations is continuous production of new equipment which can be beneficial to providers. However, this ongoing accumulation of material, data, and pathways can create challenges in remaining up to date. Rather than a comprehensive review of current literature and discussion of research findings, this article aims to discuss selected and impactful concepts in real time context and provide potentially immediate additions to emergency airway manager practice.
Summary
As emergency airway management evolves, it remains a significant task to maintain up to date on current trends, data, and new equipment. This article aims to discuss several of these items in a digestible fashion and provide immediate impact for emergency airway providers.
Keywords
Airway
Intubation
Respiratory failure
Emergency medicine
issue-copyright-statement© Springer Science+Business Media, LLC, part of Springer Nature 2022
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pmcIntroduction
Emergency airway management has evolved dramatically in recent years. This brief article aims to highlight contemporary topics in the realm of emergency airway management, offer insight into advancing technologies, and discuss potential future steps. This is not intended as a comprehensive airway review, but rather as commentary on assorted airway management techniques, technology, and strategies of current interest. There are a myriad of pathways for successful emergency airway management and equally diverse opinions on optimizing this intervention. We hope to stimulate further consideration of these topics, continue dialogue on emergency airway management, and contribute our enthusiasm to this ever-evolving and advancing practice.
Section 1: Oxygenation
Apneic Oxygenation
Apneic oxygenation has impacted emergency airway management profoundly [1••]. This strategy employs use of nasal cannula (NC) or high-flow nasal cannula (HFNC) during the preoxygenation phase and throughout the apneic phase of rapid sequence intubation (RSI). In contrast to previous practice in which the apneic phase did not include active oxygenation, this pathway leaves the nasal cannula in place and flowing throughout apnea. The passive flow of oxygen into the nose, across the turbinates (if present), creates laminar flow and passive flow down into the larynx, trachea, and lungs, and provides ongoing oxygenation. In addition, as oxygen is consumed in the bloodstream, a chemical gradient is created that actively draws oxygen from the relatively oxygen rich environment of the lungs to the relatively oxygen poor environment of the blood [1••, 2]. This is to say, a chemical vacuum forms, actively pulling oxygen into the bloodstream. With apneic oxygenation employed, much longer safe apnea times become present during laryngoscopy, often with minimal or no desaturation.
Very high flow rates can be achieved with simple nasal cannula and high-flow nasal cannula. Interestingly, despite the oxygen flowmeters prompting many providers to view 15 L/min as maximum flow, these devices can deliver much higher flow rates. Some reviews suggest flow rates as high as 60 L/min [2]. The 15 L/min maximum is likely related to many oxygen flowmeters measuring only that volume. To achieve higher flow rates, the provider can simply continue to open the oxygen flowmeter control valve. The maximum flow rate is achieved when the valve is maximally opened mechanically (i.e., turn the valve until it stops turning). This has been labeled “flush rate.” Of note, this creates very high flow rates; each airway manager should be aware of two issues that accompany this strategy: (1) The flow rates are high enough to blow the oxygen tubing off of the flowmeter; the tubing must be pushed onto the flowmeter adaptor (“Christmas tree”) sufficiently to prevent this occurrence. (2) The high flow rates create significant noise in the room and are often uncomfortable for patients. Our experience suggests flush rate is best initiated once sedation medication has been delivered during rapid sequence intubation (RSI). Use of flush rate is likely more optimal with HFNC rather than NC, though more investigation would be of value.
Of note, this strategy does not replace bagging during the initial paralysis phase or between laryngoscopy attempts. The nasal cannula can remain in place during bagging, which may augment oxygenation, but ventilation provided by BVM is critical.
High-Flow Nasal Cannula (HFNC)
Similar to standard nasal cannula, the high-flow nasal cannula (HFNC) can deliver very high flow rates (~ 50 LPM). The devices typically have moderately larger nasal ports than standard NC. Ease of use, quick placement, and relative availability make these devices excellent resources in emergent settings. Beyond airway alone, HFNC offers several impactful characteristics for the care of critically ill patients:
These devices can reduce anatomical dead space which improves carbon dioxide (CO2) removal [3]. This is due to HFNC decreasing minute ventilation and improving respiratory efficiency aiding in clearance of CO2 in anatomical dead space [4].
HFNC is also an impactful tool for management of respiratory failure. Regarding hypercapnic respiratory failure, a systematic meta-analysis of five randomized trials (198 patients with acute COPD exacerbations) showed HFNC reduced partial pressure of carbon dioxide (PaCO2) levels when compared to noninvasive ventilation (NIV) or conventional oxygen therapy (COT) [5–8].
For patients in severe respiratory distress, HFNC can reduce respiratory rate and work of breathing (WOB) [9, 10]. Additionally, for patients with mild-to-moderate respiratory depression, HFNC can provide better thoracoabdominal synchrony, when compared to techniques utilizing low-flow oxygen. Considering these effects on anatomical dead space, HFNC is a great resource to reduce the work of breathing (WOB). This was also shown to be beneficial in infants with respiratory distress, as HFNC can reduce respiratory rate and improve thoracoabdominal movement [11].
For patients in an immunocompromised state, when compared to NIV or COT, HFNC was a better tool to reduce intubation rate, mortality at 90 days, and the amount of ventilator-free days at day 28 [12].
A simple and easily accessible device, requiring low-cost material and standard oxygen flowmeters, HFNC can add significant value to emergency providers’ care of respiratory patients in prevention of intubation, oxygenation during the peri-intubation phase, and safe apnea during RSI.
The use of heated-high flow nasal cannulas (HHFNC) should be considered here as well. Though these devices have profoundly impacted respiratory patient care globally (particularly during the COViD-19 pandemic), the additional benefit for airway management may not be quite as profound. The use of apneic oxygenation discussed above is most commonly employed with nasal cannula or high-flow nasal cannula. This pathway can also be employed using the heated-high flow nasal cannula, though the additional benefit may not be pronounced [13]. HHFNC can deliver very high flow rates (e.g., 60L/min) and even likely provide a small amount of positive end expiratory pressure (PEEP), which may further enhance oxygenation. The additional benefit is likely in care of respiratory distress and severely hypoxic patients. Use of these devices for preoxygenation and apneic oxygenation in the peri-intubation phase (in comparison to HFNC) may be limited, though more data is needed.
Bifurcated Oxygen Flowmeters
A common barrier to optimal preparation for airway management is access to oxygen sources. Use of bifurcated oxygen trees helps circumvent this challenge by doubling the available oxygen sources. In a typical emergency department room, there may be one or two oxygen ports in the wall or resuscitation box. The bifurcation devices double access for oxygen. Each port can then hold two oxygen flowmeters, enhancing access to two to four ports. This is exemplified in Fig. 1. This enhances and simplifies oxygen delivery. With increased ports, more oxygen can be delivered, and the need to switch ports during the airway is minimized.Fig. 1 Bifurcated oxygen port. This allows two oxygen flowmeters to connect to a single wall port
A setup utilized by the authors of this paper is thus:Flowmeter port #1: High-flow nasal cannula (HFNC)
Flowmeter port #2: Non-rebreather (NRB)
Flowmeter port #3: Bag-valve mask (BVM)
Flowmeter port #4: Ventilator
The use of this setup gives direct access to multiple oxygenation devices and forgoes the need to switch out tubing during the intubation process. For example: During the pre-intubation phase, the HFNC and NRB are placed on the patient and initiated at flow tolerable to the patient. During the apneic oxygenation phase, the HFNC remains in place, and flow is increased to flush rate, the NRB is removed, and the patient is bagged with the BVM. During intubation the HFNC remains in place at flush rate. Following intubation the ventilator is connected to the endotracheal tube. At no point during the intubation process does the provider need to change oxygen ports. This removes not only a cognitive challenge, but also a physical action during the intubation process, augmenting oxygenation while simplifying the overarching task.
Section 2: Laryngoscopy
Video Laryngoscopy
Video laryngoscopy (VL) is one of the most innovative contemporary advances in emergency airway management. Macintosh, Miller, and angulated blades are all now available as video laryngoscopy devices, and new additional devices with unique orientation are also becoming more widespread. With appropriate use, video laryngoscopy increases first pass success and helps navigate expected and unexpected difficulties during laryngoscopy [14•, 15]. Video laryngoscopy is also a powerful tool in teaching and instruction for airway learners. Most notably, in contrast to direct laryngoscopy (DL), as each airway evolves, all providers present can view the anatomy and procedural progression. While only one provider has hands-on experience during an intubation attempt, each viewing provider can have an impactful and beneficial procedural experience. Moreover, supervising providers can provide real-time feedback of airway management techniques.
Direct laryngoscopy and video laryngoscopy overlap significantly, but are distinct pathways. With traditional geometry blades (Macintosh, Miller), the pathway of laryngoscopy can be similar (sweep tongue right to left, move midline, expose larynx). There is some discussion when using VL, that sweeping the tongue is not necessary, but rather a direct midline approach can be taken [15, 16]. Though this does result in adequate glottic exposure, it can lead to difficulty passing the endotracheal tube (ETT). These authors theorize that this is due to the tongue acting as a fulcrum, causing pressure in the midshaft of the stylet or bougie, thereby causing the devices to miss posteriorly. Sweeping of the tongue helps take the tongue out of anatomic position and allow easier passage of the stylet or endotracheal tube. An additional benefit of sweeping the tongue while using video laryngoscopy: As the geometry of the VL blade matches traditional direct laryngoscopy blades, a VL blade can be used as a direct blade in the instance that the camera is obscured, though the technique mentioned below can help reduce this possibility.
Angulated blades, however, are the exception to this rule. A midline approach is appropriate as the hyperangulated rigid stylets can simply maneuver around the tongue, and the tongue-as-a-fulcrum issue is bypassed. Recall as well that utilization of angulated blades negates the possibility of direct laryngoscopy; that is to say, there is no direct view available with use of angulated blades.
Regarding limitations of VL, the often-cited concern regarding occlusion or obstruction of the video laryngoscope cameras can be often prevented or bypassed [16]. One such maneuver to accomplish this task is to stay “high” in the airway and to incrementally lead with the suction catheter while keeping the laryngoscope blade as anterior as possible. Rather than “scoop and lift,” the blade is intentionally slid along the surface of the tongue, along the posterior oropharynx and into the vallecula (or over the epiglottis when using Miller blade) with constant upward and anterior pressure of the blade, following a leading suction catheter. Avoidance of a posteriorly placed blade and “scooping” helps keep the video laryngoscope screen clear of the secretions. In addition, by using suction catheter techniques that will be discussed later, a provider can clear the airway of blood and secretions prior to advancing the laryngoscope blade, keeping the screen free of debris.
In addition to the clinical impact and real-time teaching, video laryngoscopy allows recording of airway management. These videos can then be examined after the procedure and saved for future review and teaching. The University of Kansas Medical Center and the University of Kansas Health System, with our first author’s guidance, have developed an Airway Video Database in which hundreds of these videos are captured. To maintain patient and practitioner anonymity, all patient information has been removed, the videos begin and end at the teeth and lips, and there is no link to the providers or chart. With these contingencies and precautions in place, the videos are uploaded to the database and are reviewable asynchronously by learners of all levels. This provides an excellent opportunity to review anatomy, understand and discuss troubleshooting techniques, evaluate a series of cases (e.g., burn, trauma, pediatrics), and to enhance overall understanding of the dynamics of emergency airway management. If interested in reviewing the database, please email Dr. Andrew Pirotte ([email protected]).
Section 3: Suction
Large-Bore Suction Catheters
Pictured below is the “DuCanto” suction catheter in Fig. 2a, b. This is not intended to specifically endorse a product, but rather to illustrate the impact a large bore suction catheter can have in successful airway management. The traditional suction catheter (typically a Yankauer) is not an optimal device for airway management, especially in an emergency scenario. Given the dynamics of any difficult airway, including the character of secretions encountered (blood, saliva, vomitus, pulmonary edema, etc.), the traditional catheter does not provide optimal suction [17, 18]. Prior to the introduction of large-bore suction catheters, occlusion of traditional catheters was a common experience. In such circumstances, not uncommonly these catheters would be removed, and the suction tubing itself would be used in an improvised attempt to clear the airway of secretions. Though this increased the diameter of the suction device and improved efficiency of suction, the tubing did not allow optimal navigation of the airway, often kinking when encountering resistance. The large bore suction catheter provides powerful suction, cannot kink, and rarely occludes.
Suction-Assisted Laryngoscopy For Airway Decontamination (SALAD)
First described by Dr. James DuCanto, suction-assisted laryngoscopy for airway decontamination (SALAD) is a novel concept of dynamic suctioning during intubation [19•]. This allows management of high-volume secretions throughout laryngoscopy and during intubation, rather than two separate phases of the procedure. High-volume bleeding in the setting of hematemesis, hemoptysis, trauma, or high-volume pulmonary edema can diminish optimal intubation environments. SALAD helps navigate this barrier, keeping the view of the airway more available during intubation.
The SALAD technique involves placing and leaving a suction catheter in the posterior oropharynx. The suction catheter can be placed behind the intubating provider’s left hand and left in the airway (“parked”) to provide constant suction (demonstrated in Fig. 6a) [19•]. By placing the suction catheter out of the way, the constant suction can continuously clear blood, pulmonary edema, or other secretions while the intubating provider lets go of the catheter, leaving it in the airway, to continue the intubation attempt with a bougie or stylet. This technique allows the user to place and leave the suction catheter in the posterior oropharynx to provide constant suction, even while the endotracheal tube or bougie is inserted and advanced. SALAD is shown in the following Figs. 3, 4, and 5, provided by Dr. James DuCanto with permission for use in this manuscript:Fig. 2 a and b Large bore (“DuCanto”) suction catheters
Fig. 3 Laryngoscopy with large volume secretions and large bore suction catheter
Fig. 4 Transitioning suction catheter from traditional right side to left side (“parking”)
Fig. 5 Suction catheter in right side position (“parked”). This position allows continuous suction while providing adequate space on the right side of the oropharynx for passage of intubating devices
Figures 3–5: Mannequin demonstration of SALAD (“parking”). Photos compliments of Dr. James DuCanto, Staff Anesthesiologist, Advocate Aurora Health Care, Milwaukee, Wisconsin.
Moreover, large bore suction catheters can be utilized to facilitate intubation of the airway itself (for example in high-volume pulmonary edema). This technique requires the suction catheter to be placed in the glottic opening, removal of suction tubing followed by introduction of the bougie through the catheter and into the trachea. The suction catheter can then be removed over the bougie and exchanged with an endotracheal tube, which can then be passed down into the trachea. This is possible as a bougie fits through the lumen of the catheter (see Fig. 6b below). Fig. 6 a “Parked” suction catheter while intubating with a bougie (left) and b large bore suction catheter and an intubating bougie (right). If needed, the suction catheter can be placed directly into the glottis and the bougie can be inserted through the suction catheter into the airway
Section 4: Airway Adjuncts
Bougie
The bougie is far from new, but continues to significantly impact airway management. Recent literature has shown conflicting results, though from an observational experience by these authors, the bougie provides a profoundly positive impact on airway management [20, 21]. The combination of video laryngoscopy and bougie is a powerful pathway for optimal airway management, though provider technique impacts this greatly. The following are several pearls for optimal use of the bougie:
Hold the bougie in a “pencil grip,” rather than the shaft of the bougie running along the palm with the thumb facing cranially.
Adduction of the shoulder improves position and alignment. Avoid abduction of the shoulder (“chicken wing” position), which malpositions the bougie and causes the device to frequently miss left posterolateral to the larynx. This technique primarily works by keeping the bougie in line with the airway axis and parallel to the trachea. See Figs. 7 and 8 below.
Fig. 7 Adduction of shoulder (“chicken wing”) causes suboptimal bougie entrance angle and left posterolateral malposition in relation to airway
Fig. 8 Abduction of shoulder (“tucking the elbow”) produces optimal entrance angle for bougie and alignment with airway
3. If possible, avoid direct contact of the bougie with the tongue, as this can cause the midshaft of the bougie to bend (tongue acts as a fulcrum) and miss posteriorly (see Fig. 9 below). This barrier can be avoided by sweeping the tongue to the left, as is used in direct laryngoscopy, or displacing the tongue anteriorly with the blade of the laryngoscope (particularly with DL). If during use of bougie the device continues to miss posteriorly, we recommend removal of blade, intentional displacement of tongue anteriorly or left, and again advancing bougie. Bimanual laryngoscopy (either right hand under occiput or manipulating larynx anteriorly) can also be of great aid.
4. Additionally, there is a strategy for bougie use in which the endotracheal tube is placed on the bougie prior to intubation. The “Kiwi grip” and the “D grip” are well described [22]. These pathways can be of great value but should be pursued individually and mindfully as the presence of the endotracheal tube (ETT) can reduce the typical flexibility of the bougie and essentially transition the bougie into a stylet.
Articulating Bougie
Several proprietary devices are now available that utilize the technology of the bougie, but advance the pathway with an articulating tip. The articulating end of the device can help navigate laryngoscopy and endotracheal tube placement. The articulating bougie can reduce challenging intubation in settings of anterior airways, or in the setting of prominent soft tissue and tongue. The most common difficulty with this adjunct, as observed by these authors, is the inability for a typical bougie to advance into the airway when the tongue acts as a fulcrum on the midshaft of this device. This fulcrum subsequently manipulates the angle of the bougie and forces it more posterior than is optimal (discussed above). The articulating bougies can often bypass this either through increased rigor of the material (e.g., hard rather than flexible plastic), a greater anterior angle of the device tip, and the ability to manipulate the distal device end dynamically. This final characteristic is the hallmark of these devices. Active manipulation of the distal end can aid providers in navigating a challenging airway. This mobility is accomplished in a variety of ways, but primarily seeks the same result of dynamic motion of the device tip. Though more expensive, these devices are excellent backups should the initial pass(es) with stylet or bougie fail.
Disposable Endoscopes
Disposable endoscopes are a recent impactful advance in airway management. Though endoscopes are well-established technology, in previous iterations, the reusable version of these devices was costly to purchase, required special cleaning and handling, and frequently broke or necessitated repair servicing. The disposable version of these devices has increased access to complementary metal-oxide semiconductor (CMOS) and fiberoptic technology and may represent another profoundly positive phase of airway management [23].
Diagnostically, use of disposable endoscopes via flexible laryngoscopy is a critical tool for evaluating the airway. Angioedema is a common case example in which this modality is utilized. In the setting of angioedema, flexible laryngoscopy helps inform the airway manager if the airway is emergent, or is stable (e.g., tongue swelling but no involvement of airway structures). This pathway can help prevent unnecessary intubation, allowing observation rather than prompting airway securement as a preventive measure. In addition to angioedema, flexible laryngoscopy can be useful in a myriad of clinical scenarios: Burn and inhalation injury, head and neck trauma, allergic reaction and anaphylaxis, foreign body aspiration, and evaluation of stridor. Previously, the devices required for this procedure were often prohibitively expensive or not readily available in the emergency department. Arrival of the disposable version of these devices increases access to this critical pathway.
Beyond flexible laryngoscopy, disposable endoscopes advance providers’ access to technology that allows troubleshooting of challenging airways (Fig. 10). Most notably, the disposable endoscopes may be used as an articulating bougie (with the addition of a camera view). In this pathway, two providers pursue the airway simultaneously, as demonstrated in Figs. 11 and 12. The first provider advances the laryngoscope and exposes what structures are visible. The second provider then advances the endoscope with the pre-loaded endotracheal tube. The articulating end of the endoscope then navigates the airway, advances into the larynx, with the endotracheal tube then advanced. Fig. 9 Note the tongue spilling over the right side of the laryngoscope blade with this midline approach. In this position the tongue acts as a fulcrum for the bougie and bends the distal end posteriorly. A practitioner could re-sweep the tongue left to right prior to advancing the blade on this intubation attempt to reduce the possibility of a tongue fulcrum
Fig. 10 Flexible laryngoscopy as a method to view the vocal cords and epiglottis if indicated
Section 5: Additional Considerations
Airway Checklist
Use of checklists enhances airway care dramatically. Particularly in emergency airway management, it is easy to overlook simple tasks that significantly impact optimal care. Checklists help prevent unforced errors in airway management. An example of an airway checklist is shown in Fig. 13, and it is the current version utilized at the University of Kansas Medical Center Emergency Department, created by Dr. Andrew Pirotte of University of Kansas Medical Center.Fig. 11 Depiction of two device intubation technique with video laryngoscopy and endoscope employed simultaneously
Many medical institutions supplement these checklists to ensure communication among providers and patient safety. In the context of COVID19, an Airway Response Team (ART) at Massachusetts General Hospital employed the following practices. When identifying signs of respiratory insufficiency the following strategy in Fig. 14 was utilized:Fig. 12 Demonstration of two provider intubation techniques with video laryngoscope and disposable endoscope used to assist intubation [24]
After identifying a critical situation, the airway team can obtain relevant medical information from the primary team about the patient. Some examples are listed in Fig. 15.Fig. 13 Airway checklist
These checklists and communication aids allow the team to monitor respiratory distress in patients, create a plan for early intubation, and provide awareness of patient comorbidities [25]. Checklists provide impactful structure for intubation. Additionally, airway checklists can provide helpful feedback to improve knowledge gaps for learners [26].
Difficult Airway Response Team (DART)
A new phase of airway management includes development and implementation of difficult airway response teams. The John Hopkins Hospital initially described the formation and implementation of such a team [27]. Our institution has implemented a similar pathway at the University of Kansas Health System. This team coalesces providers and equipment rapidly and efficiently, positively impacting patient care. When initiating the DART response team, it was important to identify the types of critical airway encountered. Types of difficult airways include: (1) anatomical, (2) physiological, (3) environmental, and (4) circumstantial. Anatomically difficult airways consist of specific structural abnormalities that create physical challenges to intubation. Physiologically difficult airways are those burdened by chronic disease such as pulmonary hypertension that compromise cardiopulmonary function [28]. Environmentally difficult airways occur when clinical management is affected by the physical working environment (e.g., outside of clinical care areas, such as a patient collapsing in the hospital cafeteria) [29]. Circumstantially difficult airways refer to situations in which there are deficiencies in available staff, equipment, or education.
The DART pathway for mobilization of providers, resources, equipment, and information allows for swift, comprehensive care for patients with any of the aforementioned difficult airway scenarios.
While DART protocols may differ between institutions, the following Fig. 16 is an example checklist for use during a typical DART response at the authors’ home institution.Fig. 14 Suggested criteria for notification of a COVID-19 airway response team (ART) [25]
Fig. 15 Relevant information to communicate during airway response team (ART) consultation [25]
Fig. 16 Difficult airway response team intubation checklist
This pathway is complex and requires endorsement across a multidisciplinary team. Though more study needs to be pursued regarding optimal practice, the benefit of rapid resource activation certainly seems sound. Acknowledging the significant resource use and the substantial institutional support required, the service provided to patients is impactful and can positively influence patient safety and outcomes [27].
Ketamine
Ketamine was previously used rarely and often thought to be unsafe for many patients (e.g., intracranial hemorrhage) [30]. However, time disproved the previous tacit about the harms of Ketamine, and now it is a commonly utilized agent for procedural sedation and sedation during RSI [31]. The increased use of ketamine has dramatically impacted patient care and RSI.
In addition to routine use, ketamine can be of great value in high risk airways. Particularly during emergent airway scenarios when a patient will not tolerate apnea, ketamine can be used as a dissociative anesthetic that allows the patient to maintain their airway. This characteristic can be profoundly impactful for safe airway management. For example, in a patient with severe asthma, a patient with structural airway compromise (e.g., angioedema/anaphylaxis), or a patient suffering from severe agitation or anxiety (e.g., not participating in care) ketamine can be utilized without immediate subsequent paralysis [32]. In these scenarios, the patient experiences dissociation and anxiolysis, thereby providing an opportunity for the provider to enhance airway preparations, improve oxygenation, and (in some case scenarios) visualize the glottis without paralysis. These effects of ketamine impact a provider’s ability to safely proceed with airway management. If a structural issue that would preclude intubation is encountered, the attempt can be aborted and a new airway plan pursued (e.g., surgical airway). This strategy has been described as “delayed sequence intubation” (DSI) and is informed significantly by agents such as ketamine [33].
Of note, delayed sequence intubation was described in use during the initial phases of the COVID-19 pandemic. During this data collection period, patients were commonly hypoxic and agitated, creating oxygenation and intubation barriers. Utilizing DSI, these patients were successfully oxygenated and intubated [34]. Further, a DSI prospective observational study found oxygen saturations increased from a mean of 89.9% before DSI to a mean of 98.8% after DSI, an increase of 8.9% (95% confidence interval 6.4% to 10.9%). Additionally, some patients in this final study were identified as having a high potential for critical desaturation, defined at pre-DSI saturation ≤ 93%. When DSI was administered to these critical patients, 91% of these patients increased their saturation post-DSI to > 93% [35].
Ongoing Vasopressors for Rapid Sequence Intubation (RSI)
Push dose vasopressors have long been used in the peri-intubation phase to hemodynamically support patients and help prevent post-intubation hypotension and cardiovascular collapse. There is ongoing consideration of expanding this practice to include vasopressor drips during the peri-intubation phase. This is to say, rather than push-dose vasopressor only, the patient receives continuous vasopressor (even low dose) during intubation. If the hemodynamics are stable following intubation, the vasopressor is subsequently stopped. This is not intended for hypertensive patients or patients at risk of hypertensive complications (e.g., hemorrhagic stroke patients requiring intubation). Further study would be of value, though the concept appears sound.
End-Tidal Oxygen Monitoring
Though not currently widely available, end-tidal oxygen (ETO2M) monitoring has the potential to improve emergency airway care dramatically. Though use in the Emergency Department remains relatively uncommon, ETO2M is a tool considered feasible and has potentially significant benefits to preoxygenation [36]. These devices continuously monitor partial pressure of oxygen (PaO2), rather than pulse oximetry (SpO2). The quantification of oxygen content in the bloodstream could profoundly impact safe airway management. While pulse oximetry measures a maximal O2 of 100%, without an arterial blood gas, the provider cannot confidently discern if the Pa02 is 120 mm Hg or 350 mm Hg. With this example in mind, these two values have a significantly different safe apnea time during intubation. With use of end-tidal oxygen monitoring, the provider could theoretically monitor (in real time) the evolution of the PaO2, rather than relying on the SpO2 alone. In the above example, the transition from hyperoxia to hypoxia could be anticipated earlier and more reproducibly [36].
In a single study regarding use of ETO2M in the peri-intubation phase, 67% (n = 67, CI: 57 to 76%) of study participants with use of ETO2M achieved an ETO2 level > 85%, while 26% (n = 26, CI: 18 to 36%) of control participants achieved the same ETO2 level. This study additionally found ETO2M particularly useful in the induction phase of intubation. With the use of only bag-valve-masks (BVM), induction was 80% successful in control patients, while the study group used BVM plus ETO2M and achieved 90% successful inductions. Additionally, the prevalence of hypoxemia (SpO2 < 90%) was 18% (n = 18, 95% CI: 11 to 27%) in the control group, while only 8% in the study group (n = 8, 95% CI: 4 to 15%) [33]. Another study found the use of ETO2M during rapid sequence intubation in the ED allowed for maximal preoxygenation in 44% (95% CI 29.6 to 55.8) more patients [37]. Future investigation should be completed with larger participant groups to further understand the benefits and limitations of ETO2M on preoxygenation and hypoxia, though use of ETO2M may be of great benefit for enhancing airway management safety.
Conclusion
Emergency airway management is an ever-evolving field that will continue to expand as new techniques and technologies become available. Advancing technologies, strategies, and methods enhance provider ability to provide safe respiratory failure management and intubation care for patients. Continued effort in the airway community to equitably share information and innovations, continue conversations on best practice, and pursue an optimized and comprehensive care pathway will positively impact care locally, regionally, nationally, and globally.
Declarations
Conflict of Interest
The authors declare no competing interests.
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References
Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance
1. •• Silva LOJe, Cabrera D, Barrionuevo P, et al. Effectiveness of apneic oxygenation during intubation: a systematic review and meta-analysis. Ann Emerg Med Int J. Elsevier. Published May 2018. Accessed 30 Jul 2022. This study represents a comprehensive evaluation of literature regarding apneic oxygenation, and continued affirmation of this modality’s broad impact and value of use. Over 1300 studies were screened, 77 of which were included for full text review. :Within these data sets, apneic oxygenation was associated with decreased hypoxia (OR 0.66). :Apneic oxygenation was also associated with increased first-pass success rates (OR 1.59) Lowest SpO2s during intubation phase were higher when apneic oxygenation was utilized (weighted mean difference 2.2%).
2. Semler MW, Janz DR, Lentz RJ. Randomized trial of apneic oxygenation during endotracheal intubation of the critically ill. Am J Respir Crit Care Med. ATS Journals. Published September 30, 2015. Accessed 30 Jul 2022.
3. Spicuzza L Schisano M High-flow nasal cannula oxygen therapy as an emerging option for respiratory failure: the present and the future Therapeutic Advances in Chronic Disease 2020 11 204062232092010 10.1177/2040622320920106
4. Onodera Y Akimoto R Suzuki H A high-flow nasal cannula system with relatively low flow effectively washes out CO2 from the anatomical dead space in a sophisticated respiratory model made by a 3D printer Intensive Care Med Exp 2018 10.1186/s40635-018-0172-7
5. Pisani L Astuto M Prediletto I Longhini F High flow through nasal cannula in exacerbated COPD patients: a systematic review Pulmonology 2019 25 348 354 10.1016/j.pulmoe.2019.08.001 31591056
6. Di Mussi R Spadaro S Stripoli T High-flow nasal cannula oxygen therapy decreases postextubation neuroventilatory drive and work of breathing in patients with chronic obstructive pulmonary disease Crit Care 2018 10.1186/s13054-018-2107-9
7. Lee HW Choi SM Lee J Reduction of PaCO2 by high-flow nasal cannula in acute hypercapnic respiratory failure patients receiving conventional oxygen therapy Acute Crit Care 2019 34 202 211 10.4266/acc.2019.00563 31723929
8. Jing G Li J Hao D Comparison of high flow nasal cannula with noninvasive ventilation in chronic obstructive pulmonary disease patients with hypercapnia in preventing postextubation respiratory failure: a pilot randomized controlled trial Res Nurs Health 2019 42 217 225 10.1002/nur.21942 30887549
9. Sztrymf B Messika J Bertrand F Beneficial effects of humidified high flow nasal oxygen in critical care patients: a prospective pilot study Intensive Care Med 2011 37 1780 1786 10.1007/s00134-011-2354-6 21946925
10. Sztrymf B Messika J Mayot T Impact of high-flow nasal cannula oxygen therapy on intensive care unit patients with acute respiratory failure: a prospective observational study J Crit Care 2012 10.1016/j.jcrc.2011.07.075
11. Lavizzari A Veneroni C Colnaghi M Respiratory mechanics during NCPAP and HHHFNC at equal distending pressures Archives of Disease in Childhood - Fetal and Neonatal Edition 2014 10.1136/archdischild-2013-305855
12. Frat J-P Ragot S Girault C Effect of non-invasive oxygenation strategies in immunocompromised patients with severe acute respiratory failure: a post-hoc analysis of a randomized trial Lancet Respir Med 2016 4 646 652 10.1016/s2213-2600(16)30093-5 27245914
13. Frat JP, Coudroy R, Marjanovic N, Thille AW. High-flow nasal oxygen therapy and noninvasive ventilation in the management of acute hypoxemic respiratory failure. Annals of Translational Medicine. 5(14):297. Published July 2017. Accessed 11 Aug 2022.
14. • Rothfield KP, Russo SG. Videolaryngoscopy: should it replace direct laryngoscopy? A pro-con debate. Journal of Clinical Anesthesia. Published October 23, 2012. Accessed 30 Jul 2022. This impactful article discusses the ongoing and often multi-faceted conversations (or arguments) regarding the relationship between video laryngoscopy and direct laryngoscopy. :There are meaningful arguments both defending and arguing against the continued use of direct laryngoscopy. :This conversation also extends beyond the procedure in isolation, but includes impacts on education and learner experience.
15. Karalapillai D, Darvall J, Mandeville J, Ellard L, Graham J, Weinberg L. A review of video laryngoscopes relevant to the Intensive Care Unit. Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine. Published July 2014. Accessed 30 Jul 2022.
16. Mosier J, Stolz U, Chiu S, Sakles J. Difficult airway management in the emergency department: GlideScope videolaryngoscopy compared to direct laryngoscopy. The Journal of Emergency Medicine. Volume 42, Issue 6, P629–634. Published June 1, 2012. Accessed 30 Jul 2022.
17. Andreae MC, Cox RD, Shy BD, et all. 319 Yankauer outperformed by alternative suction devices in evacuation of simulated emesis. Annals of Emergency Medicine, An International Journal. Volume 68, Issue 4. Published October 01, 2016. Accessed 11 Aug 2022.
18. Kei J, Mebust MP. Comparing the effectiveness of a novel suction set-up using an adult endotracheal tube connected to a meconium aspirator vs. a traditional Yankauer suction instrument. J Emerg Med. 552(4):433–437. Published April 01, 2017. Accessed 11 Aug 2022.
19. • Root CW, Mitchell OJL, Brown R, et al. Suction assisted laryngoscopy and airway decontamination (salad): a technique for improved emergency airway management. Resuscitation Plus. Published May 27, 2020. Accessed 30 Jul 2022. Airway management is often accompanied by challenges presented by high-volume secretions, bleeding, or foreign bodies. :Previous use of traditional suction catheters (e.g., Yankauer) was populated by many challenges. Additionally, even with use of large-bore suction catheters, high-volume secretions or bleeding can prevent successful airway management. This article describes the SALAD technique described by Dr. James DuCanto and furthers the support of its use. :The SALAD technique includes “parking” a suction catheter on the left side of the mouth and oropharynx to provide ongoing suction during laryngoscopy.
20. Driver BE, Prekker ME, Klein LR. Effect of use of a Bougie vs endotracheal tube with stylet on successful intubation on the first attempt among critically ill patients undergoing tracheal intubation: a randomized clinical trial. JAMA. Published June 5, 2018. Accessed 30 Jul 2022.
21. Driver B, Dodd K, Klein LR, et al. The Bougie and first-pass success in the emergency department. Ann Emerg Med Int J. Published October 2017. Accessed 9 Aug 2022.
22. Nickson C. Bougie. Life in the fastlane, critical care compendium. Published Nov 03, 2020. Accessed 11 Aug 2022.
23. Matek J, Kolek F, Klementova O, Michalek P, Vymazal T. Optical devices in tracheal intubation-state of the art in 2020. MDPI. Diagnostics 2021, 11(3), 575. Published March 22, 2021. Accessed 30 Aug 2022.
24. Advanced Airway Visualization System, demonstration of GlideScope Core. Verathon. https://www.verathon.com/glidescope-visualization-systems/. Updated 2022. Accessed 26 Aug 2022.
25. Sullivan EH Gibson LE Berra L In-hospital airway management of COVID-19 patients Crit Care 2020 10.1186/s13054-020-03018-x
26. Şimşek T Preoperative airway management checklist: the transfer of knowledge into clinical practice by video based feedback Southern Clinics of Istanbul Eurasia 2020 10.14744/scie.2019.82787
27. Mark LJ, Herzer KR, Cover R, et al. Difficult airway response team: a novel quality improvement program for managing hospital-wide airway emergencies. Anesthesia and analgesia. U.S. National Library of Medicine. Published July 2015. Accessed 30 Jul 2022.
28. Cai SR Sandhu MR Gruenbaum SE Airway management in an anatomically and physiologically difficult airway Cureus 2020 10.7759/cureus.10638
29. McNarry AF, Cook TM, Baker PA, O’Sullivan EP. The airway lead: opportunities to improve institutional and personal preparedness for airway management. Br J Anaesth. 2020. 10.1016/j.bja.2020.04.053.
30. Cohen L, Athaide V, Wickham ME, Doyle-Waters MM, Rose NGW, Hohl CM. The effect of ketamine on intracranial and cerebral perfusion pressure and health outcomes: a systematic review. Ann Emerg Med. Published July 23, 2014. Accessed 28 Aug 2022.
31. Merelman AH, Perlmutter MC, Strayer RJ. Alternatives to rapid sequence intubation: contemporary airway management with ketamine. The western journal of emergency medicine. Nat Lib Med. 20(3): 466–471. Published April 26, 2019. Accessed 11 Aug 2022.
32. Stollings JL, Diedrich DA, Oyen LJ, Brown DR. Rapid-sequence intubation: a review of the process and considerations when choosing medications. Ann Pharm. Published November 4, 2013. Accessed 28 Aug 2022.
33. Apfelbaum JL, Hagberg CA, Connis RT, et al. 2022 American Society of Anesthesiologists practice guidelines for management of the difficult airway. Anesthesiology. 2021;136:31–81. 10.1097/aln.0000000000004002.
34. Castro de Oliveira BM de Souza RL Advantages of delayed sequence intubation in selected patients with COVID-19 Anesth Analg 2020 10.1213/ane.0000000000004977
35. Weingart SD Trueger NS Wong N Delayed sequence intubation: a prospective observational study Ann Emerg Med 2015 65 349 355 10.1016/j.annemergmed.2014.09.025 25447559
36. Oliver M Caputo ND West JR Emergency physician use of end-tidal oxygen monitoring for rapid sequence intubation J Am Coll Emerg Phys Open 2020 1 706 713 10.1002/emp2.12260
37. Oliver M Caputo N Randall West J 44 impact of end-tidal oxygen monitoring on the efficacy of preoxygenation during rapid sequence intubation in the emergency department Ann Emerg Med 2019 10.1016/j.annemergmed.2019.08.047
| 0 | PMC9734887 | NO-CC CODE | 2022-12-16 23:17:51 | no | Curr Emerg Hosp Med Rep. 2022 Dec 3; 10(4):73-86 | utf-8 | Curr Emerg Hosp Med Rep | 2,022 | 10.1007/s40138-022-00255-y | oa_other |
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Journal of Outdoor and Environmental Education
Journal of Outdoor and Environmental Education
2206-3110
2522-879X
Springer Nature Singapore Singapore
119
10.1007/s42322-022-00119-9
Original Paper
Is climate change the ‘elephant in the room’ for outdoor environmental education?
Fox Robyn [email protected]
1Robyn Fox
is an Associate Lecturer in outdoor and environmental education at the University of the Sunshine Coast. She has worked in outdoor and environmental education for over 30 years in Australia and overseas. Her research areas include the integration of climate responsive and sustainability education within outdoor environmental studies programs.
http://orcid.org/0000-0001-9556-5255
Thomas Glyn [email protected]
2Glyn Thomas
currently works at the University of the Sunshine Coast in Queensland, Australia. He started the Bachelor of Recreation and Outdoor Environmental Studies program there in 2016 which now has more than 250 students enrolled. He has worked across a range of education sectors and is committed to helping people to feel a connection with natural places so that they are more inclined to care for those places in the future. His research interests focus on facilitator education, outdoor leadership, and fieldwork pedagogies. He is a keen birder, climber, paddler, and golfer.
1 grid.1034.6 0000 0001 1555 3415 University of the Sunshine Coast, Sippy Downs, Australia
2 grid.1034.6 0000 0001 1555 3415 University of the Sunshine Coast in Queensland, Sippy Downs, Australia
9 12 2022
121
24 11 2022
© Crown 2022
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The impacts of climate change are undeniable, and it is becoming increasingly difficult to dispute the science. What is less clear is the role of outdoor environmental education in educating participants with the knowledge and motivation to act. Experiential programs that take students outdoors seemingly provide the ideal context to equip students with knowledge and skills to be the vital change agents that the world needs. If outdoor educators are unconvinced of the impacts of climate change, then recent impacts on outdoor programming and practices should call attention to the issue. Changing climatic factors include increased temperatures, droughts, increased severity and frequency of storms, bushfires and floods, and national park closures. The implications of such impacts have not been widely considered, and our research aims to elucidate these concerns. This article uses a systematic literature review to examine the prevalence of climate change as a focus for published research in JOEE and its predecessor, AJOE. We conducted a qualitative analysis of the abstract of every single peer-reviewed paper and six themes emerged from our analysis of these articles. Findings from this review indicate that there is not a substantive focus on climate change in refereed articles published in the journal as only 14 of the 251 peer-reviewed articles published in AJOE/JOEE mentioned climate change. We conclude that more research needs to be undertaken to ascertain how outdoor environmental educators can facilitate a climate change curriculum and how outdoor environmental education programs in Australia are impacted by climate change.
Keywords
Climate change
Outdoor environmental education
Climate change curriculum
Climate action
Climate-worry
Environmental justice
==== Body
pmcCurrent perspectives on climate change
The recent catastrophic and record-breaking floods along Australia’s East coast and Western New South Wales have been described as “climate change playing out in real time” (Verlie & Rickards, 2022, para 1). Flood events are one example of increasing catastrophic natural disasters impacting human and natural systems, infrastructure, mental health, and well-being. The floods have also impacted outdoor environmental education (OEE) programs where we work as academics at the University of the Sunshine Coast in Southeast Queensland, Australia. OEE is not impervious to climate change and anecdotally, we have witnessed an intensifying impact over the 30 years of our engagement in the outdoor education profession. For example, over the last two years floods have forced temporary closures of National Parks and forced the cancellation, rescheduling, or relocation of many of our own OEE field trips.
The degree to which climate change issues, and the pressing need for climate change adaptation, are addressed in outdoor education programs is unclear. However, the foreseen long-term impacts of climate change on outdoor education programs warrant further exploration and research. When we discuss climate change in this article, we define it as “long-term trends or shifts in climate over many decades. These changes may be due to natural variations (such as changes in the Earth’s orbit) or caused by human activities changing the atmosphere’s composition” (CSIRO, 2020, para. 2).
Climate change has been termed a ‘wicked’ problem due to its interconnected nature and the complexities in solving it. It intertwines political, economic, social, and environmental knowledge bases and interests (Head, 2014). Climate change in Australia and worldwide has accelerated at an alarming pace, causing more frequent and intense weather events (Grose & Bettio, 2020), such as “increased extreme heat days, to longer bushfire seasons and more intense rainfall events” (Quicke, 2021, p. 6). These events are predicted to escalate, bringing about further environmental, economic, and social impacts unless, according to the 2015 United Nations (UN) Climate Change Conference (COP), society can limit global warming to 1.5 °C above pre-industrial levels (UNFCCC, 2022b).
At the 2021 COP Summit, progress was noted as nations reaffirmed their commitment to fulfilling their climate pledges (UNFCCC, 2022a). However, at COP27 in 2022, UN Secretary-General António Guterres said “The world still needs a giant leap on climate ambition.... We can and must win this battle for our lives” (UNCA, 2022, para. 1). Numerous authors have shared concerns that society has adopted a ‘business as a usual’ approach focusing on the “continued widespread political prioritisation of gross domestic product” (Raworth, 2017, p. e49), neoliberal agenda and frameworks (Warner et al., 2020), and climate coloniality legacies (Sultana, 2022) placing profit over the planet and halting or stifling the opportunity for change. An example of this is the Australian Government’s decision to allow the Adani Coal Mine in the Queensland Galilee Basin to go ahead, even though some have argued it “represents a huge setback in terms of Australia’s efforts to mitigate climate change” (Stutzer et al., 2021, p. 3). Furthermore, Australia’s inaction to transition to cleaner or renewable energy sources to achieve a net-zero emission plan was highlighted by being awarded the ‘colossal fossil’ award at the recent COP26 summit, exemplifying its continued dependence on coal and fossil fuel exports (Milman, 2021). Brett (2020) termed Australia’s dependence on coal “the coal curse” (p. 1) due to political denialism of climate change and the inaction to move away from a coal funded and fuelled society. Whitehouse (2021) deduces that this political denialism and its associated inaction has resulted in the lack of federal and state government commitment to climate education policies, investment, and support, resulting in an often non-existent, ad-hoc education curriculum on climate change.
In the seven years since the signing of the Paris Agreement, anthropogenic climate change impacts have been evidenced by the breaching of many rapid and irreversible tipping points (Lontzek et al., 2015) and planetary boundaries (Biermann, 2012). For example, Williams and de la Fuente (2021) have identified “long-term changes in populations of rainforest birds in the Australian Wet Tropics bioregion” as a “climate-driven biodiversity emergency” (p. 1). Intense and frequent heat waves are the main driving factors in the bird population’s demise and contraction to higher elevations. Williams and de la Fuente (2021) are not alone in their concern about the imminent impacts of climate change. According to The Climate of the Nation 2021 report, “75% of Australians are concerned about climate change” (Quicke, 2021, p. 4), this percentage reflects the highest level of concern since the report’s inception in 2007, whilst 67% concur that Australia should be a world leader in climate change solutions (p. 34). The need for urgent climate action resonates through terms such as ‘climate emergency’ (Flannery, 2020), ‘code red for humanity’ (United Nations, 2021), ‘climate-worry’ (Sciberras & Fernando, 2022), ‘climate action’ (United Nations, 2022), ‘adapting to climate change’ (Naughtin et al., 2022) and ‘Youth Climate Movement’(Hilder & Collin, 2022).
‘Outdoor Learning’ as a curriculum connection in the Australian F-10 rationale aims for students to develop “relationships, essential for the well-being and sustainability of individuals, society and our environment” and equip students with “the skills and understandings to move safely and competently” in natural environments (Australian Curriculum Assessment and Reporting Authority (ACARA), 2014, para. 6). At a tertiary level, seven threshold concepts guide and detail what OEE university graduates know and can do. These include place-responsive, social, and environmental justice pedagogies and practices, continual upskilling of knowledge and expertise, and understanding of safety, risk management and aversion to fatalities (Thomas et al., 2019). However, given Australia’s increased concerns regarding the real and present threats and impacts of climate change, combined with the pedagogical intent of outdoor learning and tertiary OEE programs, it is not clear if outdoor environmental education in Australia is leveraging or fulfilling its moral imperative to enact its curriculum, educate students about climate change, equip them with climate adaption and resilience skills, and instil in them the motivation to advocate for climate action.
Climate inaction impacts Australians in various ways through: increased insurance fees; damage to, or loss of, property; disruption to supply chains; loss of income; and impacts on people’s mental and physical health (Quicke, 2021). Climate inaction has also undermined, diffused and fragmented the development of a climate change curriculum. Colliver (2017) exemplifies this as she finds it “puzzling, given climate change is a major issue for humankind, that the Australian Curriculum does not make more explicit mention of climate change as a topic for learning” (p. 75). Stewart in Quay et al. (2020) refers to climate change as a ‘wicked problem’ that “has been the elephant in the room for some time” (p. 110). The phrase ‘elephant in the room’ is a metaphorical term, highlighting an issue, topic or question that is potentially controversial or challenging that is being ignored despite its obvious presence. Climate change is a significant issue. However, it is rarely addressed, referred to, or discussed, as it has the potential to cause controversy. Stewart highlights the dramatic impact climate change is currently having on OEE programs in Australia and worldwide, including changing environmental contexts, changes in precipitation, snowfall patterns, and temperatures. These climate change impacts have resulted in shorter time frames or windows in which to run OEE activities and venue accessibility has also become an issue. Additionally, environmental safety concerns are escalating with climate change increasing the exposure to the risk of injuries, loss of life, mid-program evacuations, and the postponement and cancellation of programs. Increasing financial pressures of changing climate on OEE programs include the loss of income and additional funds needed for training and resource needs (Miller, 2022). Despite these concerns and pressures mounting, it may be plausible that some outdoor environmental education business models, programs, policies, and practices perpetuate the realities of anthropogenic climate change through their ingrained association with neoliberal capitalism and consumerism (Giroux, 2015).
There appears to be a paucity of literature describing how OEE can enact a climate change pedagogy which supports young people and adult learners to build the knowledge, skills and capability needed to participate in and contribute to a climate-resilient future. (Victorian State Government, 2022). Outdoor Environmental Education seems ideally placed as a learning platform, pedagogy, and vehicle for climate change education through its unique disposition incorporating practical and experiential learning opportunities, place-based pedagogies, and connection to Country that other disciplines may not offer. Wayman (2018) encapsulates these thoughts, explaining that “outdoor and adventure education offers a unique chance to correlate issues such as … climate change and sustainability … into everyday life and connect them to similar ideas, to the lived experiences of participants” (p. 176). One example occurred for Robyn (lead author), when teaching at Mt Seewah Lookout during a multi-day expedition circumnavigating the Cooloola National Park on the Sunshine Coast in Queensland, Australia. Whilst on the lookout, the group, caught glimpses of humpback whales breaching in the Coral Sea to the East and watched sailboats in the shallow bracken waters of Lake Cootharaba to the West. Amidst the spectacle and beauty, a discussion ensued about rising sea levels. Students deliberated whether this area would be accessible for them to run similar multi-day trips in the future with the impact of climate change causing rising sea levels (CSIRO & BOM, 2020). We concur with Cutter-Mackenzie and Rousell’s (2019) view that climate change education is an innovative, effective, and emerging field of practice and research that moves beyond the discipline boundaries of education for sustainability, sustainable development and environmental education. In this way, climate change education is viewed as “fundamentally responsive and accountable to the rapidly changing environmental conditions of everyday life” (Cutter-Mackenzie & Rousell, 2019, p. 101), which includes children and youth perspectives, experiences, and advocacy. Insights gained from these significant life experiences and formative influences (Howell & Allen, 2019) signify the value of experiential learning and reflective pedagogies (Thomas, 2015) used in OEE. Furthermore, it highlights the possibilities of an OEE climate education pedagogy in which climate change is positioned front and centre.
The purpose of this article is to explore the extent to which climate change is a focus in research and writing published in the Journal of Outdoor and Environmental Education (JOEE) and the superseded Australian Journal of Outdoor Education (AJOE) since 1998. To facilitate this exploration, we conducted a systematic literature review to ascertain the extent to which climate change is being discussed, researched, and showcased in the journals’ peer-reviewed articles and to identify themes, gaps, and future research opportunities regarding the inclusion of climate change foci in OEE.
Methodology
The methodological approach taken in this academic inquiry is that of a systematic literature review. We have used a comprehensive, protocol and parameter-driven, quality-focused approach to searching, selecting, and summarising literature pertinent to our research focus (Bearman et al., 2012). This literature review focused solely on peer-reviewed articles published in the AJOE and JOEE from 1998 (volume 3, issue 1—when articles were first peer-reviewed), to 2021 (volume 24, issue 3). Editorials and book reviews were excluded from the review. This study incorporated, and built on, the data collected and analysed by Thomas et al. (2009) and utilised the framework they used when they analysed articles published in three outdoor/experiential journals. Thomas et al. (2009) to “provide an overview of the peer reviewed research that has been published in the last decade in order to reveal strengths, weaknesses, gaps, and what we perceive to be blind spots” (pp. 16–17). In this study, we utilised some of their existing data analysis and continued the analysis of articles published in AJOE/JOEE beyond 2007 up to the present time.
The article analysis we conducted categorised and coded all the published articles in the following areas: Author affiliation, the type of article, the context of each article, and the article focus (primary and secondary). The definitions of the categories and the codes used within each category are shown in Table 1. We checked the coding of all the AJOE articles published between 1998 and 2007 analysed by Thomas et al. (2009) before continuing to code all the articles published in the AJOE/JOEE from 2007. In total, 251 articles were coded and included in the data set. Having clear code definitions ensured coding consistency and reliability. A cross-checking process between coders was also employed to ensure consistency and increase trustworthiness. We did this by cross-checking a random sample (N = 20) of the new articles published since 2007 to confirm consistency with the original coding completed in the research conducted by Thomas et al. (2009).Table 1 Categories and codes used by Thomas et al. (2009) and adopted in this study
Category Intent Codes Used
Author Affiliation The intent of this category was to get a sense of the countries or regions that authors come from. The coding focused on the location of the author (or lead author) Asia/Middle East, Australia, Canada, Europe, New Zealand, United Kingdom & the United States
Type of Article This category described the nature of the scholarly work that contributed to the article. Drawing on Mertens’ (2005) work describing research paradigms, we categorised the research-based articles as postpositivist, constructivist, or transformational. We contrasted literature reviews with position papers by defining the latter as persuasive arguments made to support a particular position Action research, Constructivist, Literature review, Position paper, Positivist, Research methodology &Transformational
Context The context descriptor chosen for each article was used to identify the target audience for whom the article was written. This was sometimes explicitly identified by the author/s and other times it was inferred Adventure education, Adventure/ wilderness therapy, Environmental activism, Expeditions, Experiential education, Forest Schools, Nature kindergartens, Nature tourism, Outdoor education, Outdoor environmental education, Outdoor leadership, Outdoor recreation, Place pedagogy, & Service learning
Focus This category was used to identify the primary and secondary foci of each article. We adopted the codes used by Thomas et al. (2009) but refined some of them to reflect developments in the outdoor environmental field since 2007. The codes used were: Adventure, Anthropocene, Climate change/crisis, Curriculum issues, Environmental/ecological/ spiritual, Outcomes/effects/participant experiences, Professional /professional issues, Program design/facilitation, Relationships with nature/others/self, Research processes, Risk management, Safety management, Social justice/gender/ diversity /inclusion, Sustainability/ stewardship, Teaching/teacher issues, & Theoretical foundations
The plan was to then highlight the articles that had a primary and secondary focus on climate change and then conduct a more detailed analysis of those articles. However, the fact that there was only one (N = 1) article had a secondary focus on climate change led us to take a different approach to expand the data set. Hence, we conducted a search of the remaining 250 articles for any references to climate change, which resulted in a data set of 13 articles that addressed climate change in some way. The relevant sections from the single article with a secondary focus on climate change, and the additional 13 articles that addressed climate change, were then imported into Nvivo (a data analysis software) and scrutinised for relationships, trends, and patterns (D. Gough et al., 2017). Based on this analysis, six themes emerged; the nature of climate change, the citing of climate change in reports, the transboundary nature of climate change impacts, climate change impacts on OEE programs, education and climate change and a call to action. The 14 articles were also analysed to determine author affiliation, the type of article, the context, and the focus (primary and secondary). These data will also inform the discussion that follows.
Findings and discussion from the systematic literature review
The analysis of the primary and secondary foci of the 251 articles is outlined in Table 2. The most common foci of the articles were Outcomes/effects/participant experiences (38.2% of all 251 articles) and Program design and facilitation (35.9%), which is consistent with the findings reported by Thomas et al. (2009). Authors of articles in the Journal of Outdoor and Environmental Education are still primarily focused on program outcomes and how a program can be designed and facilitated to achieve those outcomes. A further four foci feature prominently across the total 251 articles: Theoretical foundations (18.7%); Relationships with nature/self/others (18.7%); Curriculum issues (12.7%); and Profession/professional issues (12.4%). Of specific interest to this article, only a limited number of articles had a primary or secondary focus on either the Anthropocene (0.4%) or Climate change/crisis (0.4%).Table 2 The primary and secondary focus of all the articles (N = 251)
Category Number of articles with this primary focus Number of articles with this secondary focus Overall emphasis
(% of total articles)
Outcomes/effects/participant experiences 45 51 38.2
Program design/ facilitation 39 51 35.9
Theoretical foundations
Relationships with nature/others/self
34
32
13
15
18.7
18.7
Curriculum issues 16 16 12.7
Profession/professional issues 20 11 12.4
Teaching/teacher issues 14 20 9.2
Social justice/gender/diversity/inclusion 16 1 6.8
Environmental/ecological/spiritual 5 10 6.0
Safety management 11 3 5.6
Risk management 8 4 4.7
Sustainability/stewardship 3 5 3.2
Research processes 4 1 2.0
Adventure 3 0 1.2
Anthropocene 1 0 0.4
Climate change/crisis 0 1 0.4
The paucity of articles focused on climate change/crisis in the JOEE (as shown in Table 2) is concerning, and it is unclear why there has been so little focus on this topic in the journal. Whilst the data needs to be interpreted carefully, the underrepresentation of climate change/crisis in the JOEE indicates that climate change has not been a priority focus of research and writing by outdoor environmental education researchers, or they are choosing to publish that research elsewhere. It is possible that outdoor environmental education researchers are publishing their work in journals with a stronger climate change focus. Another explanation for the apparent gap in the literature may be the lack of reference or acknowledgement of the need for climate change education in the Australian Curriculum. For instance, the 2019 Alice Springs (Mparntwe) Education Declaration, which sets out the educational goals for all young people for the next ten years, has omitted reference to climate change, which was included in the previous 2009 Melbourne Declaration (A. Gough, 2020). It is unclear how outdoor environmental educators in Australia, and other countries, might educate their students on climate change and mitigate against its impacts if researchers and writers do not address the issue in journals such as JOEE.
Additional analysis of articles that mention climate change in the systematic literature review
Although only one article contained a secondary focus on climate change/crisis, as seen in Table 2, 14 articles (5.6% of the 251 articles) specifically mention or refer to climate change (refer to Table 3 for details). Of those 14 articles, the overall primary focus was spread across ten focus areas, with the two most significant representations being Relationships with nature/self/others (36%) and Sustainability/stewardship (14%). The other categories included: the Anthropocene (7%); Curriculum Issues (7%); Environmental/ecological/spiritual (7%); Profession/professional issues (7%); Program design/ facilitation (7%) and Research processes (7%). Interestingly, no articles in this data set included the term climate change in its title.Table 3 AJOE/JOEE articles published between 1998 and 2021 that mention climate change
Year Author/s Title Author Affiliation Context Article Type Times climate change mentioned
2007 Annette Gough Outdoor and Environmental Studies: More challenges to its place in the curriculum Australia Outdoor Environmental Education Position Paper 7
2008 Brian Wattchow Phillip G Payne Slow pedagogy and placing education in post-traditional outdoor education Australia Place Pedagogy Position Paper 1
2012 Allen Hill Developing approaches to outdoor education that promote sustainability education New Zealand Adventure Education Research Report 4
2018 Sophie Alcock Jenny Ritchie Early childhood education in the outdoors in Aotearoa New Zealand New Zealand Forest Schools Position Paper 2
2018 Sean Blenkinsop Daniel Ford The relational, the critical, and the existential: three strands and accompanying challenges for extending the theory of environmental education Canada Place Pedagogy Position Paper 2
2018 Marcus Morse Bob Jickling John Quay Rethinking relationships through education: wild pedagogies in practice Australia Place Pedagogy Position Paper 2
2019 Rebecca A. Johns Rachelle Pontes Parks, rhetoric, and environmental education: challenges and opportunities for enhancing ecoliteracy United States of America Outdoor Environmental Education Research Report 7
2020 Andreas Skriver Hansen Mattias Sandberg Reshaping the outdoors through education: exploring the potentials and challenges of ecological restoration education Europe Outdoor Education Position Paper 2
2020 Quay, Gray, Thomas et al. What future/s for outdoor and environmental education in a world that has contended with COVID-19? Australia Outdoor Environmental Education Position Paper 9
2020 Nathan W. Meltzer Andrew J Bobilya Denise Mitten W. Brad Faircloth Rese M. Chandler An investigation of moderators of change and the influence of the instructor on outdoor orientation program participants’ biophilic expressions United States of America Outdoor Education Position Paper 1
2020 Bruce A. McGregor Ann M. McGregor Communities caring for land and nature in Victoria Australia Service Learning Position Paper 2
2020 Zeenat Abdul Haq Imran Muhammad Shabbir Ahmad Umer Farooq Environment, Islam, and women: a study of eco-feminist environmental activism in Pakistan Asia/ Middle East Environmental Activism Position Paper 19
2021 Chris A. B. Zajchowski Daniel L. Dustin Eddie L. Hill “The freedom to make mistakes”: youth, nature, and the Anthropocene * United States of America Outdoor Education Position Paper 11
2021 Genevieve Blades Making meanings of walking with/in nature: embodied encounters in environmental outdoor education mentions Anthropocene’s global heating and climate destabilization Australia Outdoor Environmental Education Research Report 1
The authors of the 14 articles in the data set were affiliated with institutions from Australia (43%), the United States (21%), NZ (14%) with Canada (7%), Europe (7%) and Asia/ Middle East (7%). Of note, none of the lead authors published more than one article on climate change in the data set. A possible explanation for this maybe that climate change in OEE has not been a central research area for outdoor environmental education academics.
In terms of the types of articles in the data set, position papers and research reports accounted for 78% and 22%, respectively as shown in Table 3. These results illustrate that more empirical research is warranted to rigorously explore the impacts of changing climate on OEE programs and practices, how OEE programs address these impacts, and how OEE might effectively contribute to climate change education. Furthermore, the contexts of various articles that referred to climate change reflect the diversity of OEE, consistent with the findings reported by Thomas et al. (2009). For example, 29% of the articles focused on outdoor environmental education, 21% on place pedagogy, 21% on outdoor education, and 7% on each of adventure education, environmental activism, forest schools, and service learning.
The term ‘climate change’ was referred to 70 times within the 14 articles in the data set as reflected in Table 4 below. Gough’s (2007) article was the first to mention climate change. The article referred to climate change seven times regarding curriculum issues within outdoor education (OE) on integrating the Education for Sustainable Development Agenda. The article which incorporated the most references to climate change was Haq et al. (2020) article regarding environmental activism in Pakistan. Their article was categorised with a secondary focus on climate change/crisis, referring to climate change 19 times. Over time, the number of citations regarding ‘climate change’ in the JOEE has increased, with the term being cited 83% more in the last four years, from 2018 to 2021. Also noted were periods of infrequent use of the term; these periods were from 2008 until 2011 and then from 2013 to 2018.Table 4 The use of the term climate change and its occurrence in the JOEE from 1998–2021
Years Times used in text
2007 7
2008 1
2012 4
2018 6
2019 7
2020 33
2021 12
Total 70
Other phrases associated with climate change within the articles included ‘global warming’ (A. Gough, 2007; Haq et al., 2020), ‘increasingly rapid change in climate’ (Morse et al., 2018), ‘climate-threatened resources’ (Zajchowski et al., 2021), ‘Anthropocene global heating and climate destabilisation’ (Blades, 2021), ‘abruptly changing weather patterns,’ ‘climate changes,’ ‘climate emergency,’ ‘climate exposures’ (Haq et al., 2020), ‘changes in climate’ (McGregor & McGregor, 2020), ‘climate crisis’ (Quay et al., 2020), and ‘climate regimes’ (Zajchowski et al., 2021). The wide variety of words and phrases used to describe climate change, and its impacts in the JOEE potentially dilute the importance and impact of the issue for OEE policymakers, programmers, and practitioners. Implementing a common language framework regarding climate change would help it gain more clarity, voice, and agency.
Findings and discussion from the thematic analysis of the articles that refer to climate change
The six distinct themes that emerged through the thematic analysis of the articles that referred to climate change are: the nature of climate change, the citing of climate change in reports, the transboundary nature of climate change impacts, climate change impacts on OEE programs, education and climate change; and a call to action. These themes provide a snapshot of the breadth of writing regarding climate change in the JOEE, helping to identify potential literature gaps and describing the impacts that climate change has caused in the context of OEE. These six themes will now be described and summarised in more detail.
The nature of climate change
This theme highlights the complex range of contexts used when describing climate change found in the data set of articles in the JOEE. Eight of the 14 JOEE articles on climate change contributed to this theme. These contexts included: weather and climate events; phenomena related to weather and climate extremes; climate change impacts human systems and the more-than-human world, and climate change impacts human health and well-being.
Weather and climate events referred to in the JOEE include heatwaves, cloudbursts, cyclones, floods, and sea intrusion (Haq et al., 2020), sea-level rise (Hill, 2012), droughts (Gough, 2007; Quay et al., 2020) and bushfires (Quay et al., 2020). Phenomena related to weather and climate extremes were outlined by Hill (2012), as he referred to human-induced (anthropogenic) climate change, citing increased greenhouse gas emissions as a significant contributor to climate change in Australia.
Climate change impacts, regarding human systems, and the more-than-human world mentioned in the JOEE, underly many challenging environmental issues of climate change (Meltzer et al., 2020). This challenge is reflected by Haq et al. (2020), who describe heightened levels of human vulnerability caused by increased air pollution, deforestation, urbanisation, famine, and water scarcity. Morse et al. (2018) bring a sense of urgency to the discussion of climate change using words such as ‘tipping points,’ ‘irreversible changes,’ caused by the “emerging geological epoch, sometimes called the Anthropocene,” regarding the “loss of species, habitats and entire ecosystems” (p. 244). Quay et al. (2020) also highlight the devastating impacts of climate change through droughts, habitat destruction, and the 2019–2020 Australian bushfires, emphasising the impacts beyond humans, including those to the more-than-human world. However, climate change impacts are not always visible and are often only observable over long periods of time. Blades (2021) captures this sentiment as she refers to the “macro-scale impacts of climate change over time on mountainScape” in her descriptive summary of her first research question, “What is afforded and felt whilst walking with/in nature(s)?” (p. 305). This description paints a picture of the devastation climate change renders upon areas we use for bushwalking and other outdoor activities over time. This slow, occurring change may not be readily observed on OEE trips unless participants repeatedly visit an area over an extended time frame. Hence, the change(s) would most likely be needed to be explicitly highlighted and taught. The nature of climate change is reflected in human health and well-being. Blenkinsop and Ford (2018) discuss some of the psychological responses felt by learners, such as “regret, sadness, and loss” (p. 236), as participants feel alienated from and unable to respond to threats to the natural world.
The citing of climate change reports
Several of the JOEE articles in the data set for this study cite United Nations and Governmental reports and documents, which enhances the credibility and relevance of that writing. For example, Gough (2007) referred to the United Nations Decade Education for Sustainable Development (ESD) framework. Morse et al. (2018) referred to two Intergovernmental Panel on Climate Change (IPCC) reports, whilst Hill’s (2012) article referred to the 2011 United Nations Framework Convention on Climate Change. At a national level, Haq et al. (2020) refer to Pakistan’s 2017 Climate Change Act, enabling climate change to be “accepted and addressed as a serious issue” (p. 287). Finally, McGregor and McGregor’s (2020) article referred twice to documents signed by the Victorian Minister for Energy, Environment and Climate Change at a state level.
Referring to these documents improves credibility (Lampert, 2020), enhances the agreed understanding of the term climate change, and shows how climate change has been addressed over time. For example, The Climate Change 2021 IPCC report is compiled by a team of 234 scientists worldwide who reviewed over 14,000 articles (Spera, 2021). Thomas et al. (2019) describe seven threshold concepts that detail what OEE university graduates know and can do. Threshold concept number four stipulates, “outdoor educators advocate for social and environmental justice” (p. 10). Promoting the use of key climate change documents by OEE facilitators in provocations, discussions and debates regarding climate change and human impact on the planet will provide authenticity and help mitigate fake news, misinformation, hearsay, and climate change denial.
Climate change and impacts on OEE
Climate change is already impacting OEE programs by changing the accessibility of locations closed by land managers, by creating scheduling difficulties for programs caused by dangerous weather and fire risks, and other safety and risk considerations caused by extreme weather conditions. For example, Quay et al. (2020) highlight the disruptive nature of climate change and the need to rethink OEE pedagogy and curriculum, as fires caused “widespread cancellation or deferral of OEE programs across the south-eastern parts of the country” (p. 109). This sentiment had been discussed by Gough (2007) nearly 15 years prior as she highlighted the impacts of drought on inland waterways reducing the locations where outdoor activities were able to be undertaken. However, these were the only two examples from the JOEE which explicitly showcased or highlighted the impact of climate change on OEE programs.
The transboundary nature of climate change impact
Climate change influences and impacts are not confined to a physical location or single context: in this respect, they are transboundary (Zajchowski et al., 2021). For this reason, climate change has often been termed a ‘wicked’ problem and ‘threat multiplier’ due to its interconnected nature and complexities, as it intertwines political, economic, social and environmental knowledge bases and interests (Head, 2014). The transboundary nature of climate change impacts highlighted within the JOEE reflects its complex nature and its direct and indirect impacts on OEE programs in both the human and more-than-human spheres. It also raises the questions of how we plan for, and who is responsible for, transboundary climate impacts?
Protected areas, such as National and State Parks, where many OEE programs are undertaken, are impacted by the transboundary nature of climate change. For example, Zajchowski et al. (2021) highlight the “transboundary challenges of ecosystem management in the Anthropocene” (p. 93). They use Australia’s ‘Great Barrier Reef’ as an example, highlighting the impacts of geological, social, cultural, and economic activities external to the protected area, impacting the reef and its associated ecosystems.
The impacts of climate change, exemplified in times of “global environmental threats, social issues and economic instability” raised by Hill (2012, p. 16), are still relevant and have implications for OEE. Quay et al. (2020) stress the interrelated issues of COVID-19, climate change and the neoliberal capitalist system, which “unleashed untold destruction across the globe... for residential centres and outdoor professions, the pandemic has been a disaster” (p. 107). Quay et al.’s article provides acumen for the outdoor environmental education sector moving forward post-COVID-19. It proposes how OEE’s core values could guide the shift away from a neoliberal capitalist system as it seeks to incorporate Indigenous knowledge, the more-than-human entities, student and planetary health and well-being, and students’ voices and advocacy into critical conversations. These core values would be taught through OEE practices utilising inclusive, student-centred, placed-based learning and community-building engagements in natural environments.
Another aspect showcasing the transboundary nature of climate change in the JOEE is the social-ecological transboundary impact of climate change. Zajchowski et al. (2021) examine this tension through the premise of ‘last-chance tourism.’ They question if last-chance tourists feel ambivalent and hold the mindset that they are at the “Earth’s going out of business sale” (p. 95). Therefore, they participate in the experience in ways that perpetuate climate change’s impacts absolve them of any responsibility or environmental ethic. However, they explain that these ‘tourism experiences’ can be crafted and facilitated in ways that allow participants to connect with nature and develop pro-environmental actions, often fostered through immersive outdoor experiences, service learning, or ecological restoration education projects (Hansen & Sandberg, 2019).
The failings of politics, short term governance and political decisions regarding climate change and nature preservation, potentially impacting freedoms for future generations, reflect the transboundary impacts of climate change inaction over time. Zajchowski et al. (2021) raise concern, citing the variances in climate policies and initiatives between the Obama and Trump terms of office, asking the question of who is responsible “when accounting for international impacts of climate change on outdoor recreation?” (p. 92). Questions such as these, could be used as prompts or provocations for OEE stakeholders (facilitators, students, and policymakers) to debate and discuss as they advocate “for social and environmental justice” through the lens of OEE (Thomas et al., 2019, p. 178). In this way, OEE programs could engage all stakeholders in critical discourses and engagements regarding politics and climate change, cultivating ways to foster a sense of hope, action, and responsibility.
Education and climate change
The presence of discussion relating to climate education and climate change’s impacts on education in the JOEE was minimal, given education’s crucial role in advocating for a sustainable future. The concerns raised in Gough’s (2007) article regarding the coverage and reference to climate change in the VCE OES curriculum studies design (Victorian Curriculum and Assessment Authority, 2005); considering its prominence, being designated one of the critical environmental perspectives of the education for sustainable development framework and “the widespread impact climate change could have on outdoor activities” (p. 26) still hold true 15 years later. Current pedological practices and policies should support young people and their concerns about the future. It is disappointing that the current 2019 Alice Springs (Mparntwe) Education Declaration does not refer to climate change (Gough, 2020).
Another significant aspect of climate education highlighted by Johns and Pontes (2019) is the need for continual informal adult eco-literacy. They have noticed a gap in adults’ eco-literacy skills, expressing that many adults lacked the skills to critically engage in complex discussions regarding climate change, biodiversity loss, and greenhouse gas emissions, inferring that these skills would become intergenerational.
The impacts of “climate change disruptions” expressed by Stewart in (Quay et al., 2020, p. 111) highlight the vulnerability of OEE’s position in the Higher Education (HE) sector. Stewart conveys that academics need to “rethink OEE pedagogy and curricula” (p. 111), ensuring its viability and relevance in uncertain times within HE, as it is times of vulnerability (highlighted by the deferment and cancellations, albeit floods or fires) that in the past OEE programs: often considered small niche fields in universities, have been cut from HE funding and programs. The vulnerability of OEE discourse in the HE sector was also expressed by Dyment and Potter (2020). They encourage OEE programs to align themselves with universities’ critical strategic plans, which parallel many OEE theoretical foundations of sustainability, place-based education, and social and environmental justice.
A call to action
Outdoor Education Australia, the owner of the JOEE, provides a resource hub for outdoor educators. Their webpage identifies OEE as a pedagogical practice that ‘calls people to action’ through the ideals of “stewardship and sustainability” (Outdoor Education Australia, 2015, para 5.). The concepts of environmental action, stewardship and sustainability resonate in diverse ways throughout the JOEE articles concerning climate change. For example, the Blenkinsop and Ford (2018) article identified that the fields of OEE have aligned themselves with “making the world a just and caring place” (p. 319) with the need to “create something ready to respond to the educational challenge par excellence of today – an adequate response to the massive social/ecological/cultural destructions happening right now” (p. 320). They, along with (Morse et al., 2018), proposed that this change could be undertaken under the ‘wilding of pedagogies education.’
Environmental activism is another way in which people can advocate for climate action. Haq et al. (2020) highlight youth activism’s rising prominence and role through the ‘Global Youth Strike Movement’ raising awareness and advocating for environmental and climate action through marches, clean-ups, education, and awareness campaigns. Another form of environmental activism, cultural ecofeminism, was discussed by (Haq et al., 2020), in which women advocate for environmental justice as “their environmental knowledge can execute climate change issues more effectively” (p. 277) due to the role that they play as the primary supervisors of the family unit and the ecological knowledge embedded within this role.
Alcock and Ritchie, in their (2018) article regarding Forest Schooling in New Zealand, encourage and challenge educators not to over romanticise the concepts of natural and wild places, nature and Forest School pedagogy, which they claim “perpetuate colonial legacies” (p. 86). Instead, they encourage readers to apply “Indigenous Māori worldviews of humans inter and intra-actively living, playing, knowing, and relating within a forest and other wild spaces” in an era of “increasing threats of climate change disturbances” (p. 86). Blades (2021) shares a similar sentiment as she invites her readers to question and challenge “enduring colonial legacies” (p. 294) through their OEE pedagogies, practices and research in the times of the “Anthropocene’s global heating and climate destabilization play havoc with Australian natural and social environments, including Education” (p. 294). Embedding the Aboriginal and Torres Strait Islander Histories and Cultures priority (ACARA, 2016) and the OEE university threshold concept, “outdoor educators are place-responsive, and see their work as a social, cultural and environmental endeavour” (Thomas et al., 2019, p. 177), should act as a catalyst for critical discussion and nuanced ways of undertaking decolonisation practices.
The need to embed sustainable principles and practices into OEE programs is another ‘call to action’ in the data set of articles in this study. Hansen and Sandberg (2019) challenge humans to reduce their current ecological footprint and act as “socio-ecologically responsible citizens”(p. 65), preserving the world for future generations at a time in which the world is undergoing “rapid climate change and fiery debates regarding human responsibility” (p. 65). Through the success of integrating ecological restoration education projects into OEE programmes in Nordic counties, they encourage these restoration projects to be adopted worldwide. Furthermore, ecological restoration education provides students with direct experiences in nature, shedding “new light on the role of humans in the biosphere” (Hansen & Sandberg, 2019, p. 66), connecting them to the more-than-human world whilst fostering “greater concern and knowledge about the loss of biodiversity and climate change” (p. 58). The diversity of literature in the JOEE regarding a ‘call to action’ concerning climate change highlights the multiple ways in which all OEE stakeholders can undertake climate action and mitigate against the impacts of a changing climate.
Conclusions and recommendations
This systematic literature review has highlighted the extent to which ‘climate change’ has been a focus of the research published in the JOEE and AJOE. The findings identify that climate change is not a prominent focus area of articles published in these journals, reflected by the low number of articles (N = 14) that refer to climate change, the fact that none of the articles had a primary focus on climate change, and that no lead authors have published more than one article on this topic within the JOEE. Although some discussion of climate change was noted in the 14 articles across the six identified themes, as well as a sharp rise reported (83%) in reference to ‘climate change’ citations in the four years, from 2018 to 2021, the discussion of how climate change could and is impacting OEE programs is limited, and there was little discussion of how OEE could enact an effective climate adaptive curriculum. It is unclear why the topic of climate change has not been discussed in more detail within the JOEE, given the compounding implications that it is and will have for OEE programs and the profession. It may be that the challenge of embedding a climate change curriculum in OEE has not been tackled due to its controversial nature, depressing content, and the lengthy time frames required to effectively study climate change.
Acknowledging the impacts of a changing climate and embedding a climate education curriculum in OEE, could also be seen as a double-edged sword. The positives of doing so, could be viewed through the lens of transformative change. The benefits might include empowering youth advocacy, developing deeper connections to Country and the more than human world, upskilling youth and OEE practitioners with resilience, critical thinking and adaptability skills to participate in and respond to a climate-resilient future. At the other edge of the sword, hard work would be needed to develop new OEE policies, programs, and practices. Funds, time and energy would need to be redirected from the perceived ‘bread and butter’ of OEE, adventure education, to incorporate emergent practices, train staff to understand the science behind climate change and the impacts of climate change and provide them with the knowledge and skills to advocate for environmental justice to assist students to deal with climate-worry. Finally, parents and schools would need to buy into a different way of doing OEE, based on deep connections to Country and place.
This article has identified the need for future research regarding the impact of climate change in the Australian OEE space. There is also a need to explore the development and implementation of a climate change curriculum within OEE, relevant to the Australian context. This research might include, but not be limited to: a systematic review of other journals (for example, the Australian Journal of Environmental Education) concerning climate change; a study regarding current climate change impacts on OEE programs in Australia; a review of climate change education in OEE settings; and a study regarding the OEE profession’s preparedness to ensure outdoor educators are equipped to cope with the impacts of climate change and students’ climate-worry and grief. To raise the profile of climate change dialogue within the JOEE, a special edition of the JOEE calling for articles on climate change in OEE would be helpful. This could assist with the development and use of a common language framework and give voice and agency to OEE stakeholders who can write on the issue.
As practitioners who have collectively spent over 60 years facilitating OEE experiences, it would be devastating to see the OEE programs rendered inoperable in Australia due to climate change impacts, especially when much can be done to alleviate the impacts of a changing climate. We urge all OEE stakeholders to become more active in this space, advocating and providing a voice for the health and prosperity of the human and the more-than-human world. As explained by John Lewis (Loyd, 2020) “If not us, then who? If not now, then when?” (para.1).
Acknowledgements
We acknowledge that our use of the expression ‘elephant in the room’ in our title was first used in the context of climate change in OEE by Alistair Stewart in Quay et al. (2020).
Data Availability
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734888 | NO-CC CODE | 2022-12-14 23:28:31 | no | Journal of Outdoor and Environmental Education. 2022 Dec 9;:1-21 | utf-8 | null | null | null | oa_other |
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Arch Dermatol Res
Arch Dermatol Res
Archives of Dermatological Research
0340-3696
1432-069X
Springer Berlin Heidelberg Berlin/Heidelberg
36477587
2492
10.1007/s00403-022-02492-3
Original Paper
Towards successful implementation of artificial intelligence in skin cancer care: a qualitative study exploring the views of dermatologists and general practitioners
https://orcid.org/0000-0003-0948-5801
Sangers Tobias E.
https://orcid.org/0000-0001-8578-901X
Wakkee Marlies
Moolenburgh Folkert J.
https://orcid.org/0000-0001-9940-2875
Nijsten Tamar
https://orcid.org/0000-0002-4117-2154
Lugtenberg Marjolein [email protected]
grid.508717.c 0000 0004 0637 3764 Department of Dermatology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Doctor Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
7 12 2022
19
9 6 2022
17 10 2022
21 11 2022
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Recent studies show promising potential for artificial intelligence (AI) to assist healthcare providers (HCPs) in skin cancer care. The aim of this study is to explore the views of dermatologists and general practitioners (GPs) regarding the successful implementation of AI when assisting HCPs in skin cancer care. We performed a qualitative focus group study, consisting of six focus groups with 16 dermatologists and 17 GPs, varying in prior knowledge and experience with AI, gender, and age. An in-depth inductive thematic content analysis was deployed. Perceived benefits, barriers, and preconditions were identified as main themes. Dermatologists and GPs perceive substantial benefits of AI, particularly an improved health outcome and care pathway between primary and secondary care. Doubts about accuracy, risk of health inequalities, and fear of replacement were among the most stressed barriers. Essential preconditions included adequate algorithm content, sufficient usability, and accessibility of AI. In conclusion, dermatologists and GPs perceive significant benefits from implementing AI in skin cancer care. However, to successfully implement AI, key barriers need to be addressed. Efforts should focus on ensuring algorithm transparency, validation, accessibility for all skin types, and adequate regulation of algorithms. Simultaneously, improving knowledge about AI could reduce the fear of replacement.
Supplementary Information
The online version contains supplementary material available at 10.1007/s00403-022-02492-3.
Keywords
Artificial Intelligence
Augmented intelligence
Skin cancer
Dermatology
Focus groups
SkinVisionUnrestricted research grant Unrestricted research grant Unrestricted research grant Unrestricted research grant Unrestricted research grant Sangers Tobias E. Wakkee Marlies Moolenburgh Folkert J. Nijsten Tamar Lugtenberg Marjolein
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pmcIntroduction
Artificial Intelligence (AI) has become a popular topic in medicine over recent years. In dermatology, deep neural networks (DNNs) have been reported to achieve, and even outperform, the level of accuracy of dermatologists when classifying images of skin lesions [1, 2]. Although previous studies mainly focused on AI algorithms as a potential substitute for clinicians in skin cancer detection[1–3], recent studies also demonstrate promising potential for this technology to assist rather than replace clinicians in skin cancer related clinical decision making, also referred to as augmented intelligence (AuI) [4–6]. Experts have hypothesized that the use of DNNs in skin cancer care can facilitate skin cancer screening in primary care and allows rapid triage of difficult skin lesion cases in both primary and dermatological practice [7].
The promises of AI to improve skin cancer detection are impressive, but successful implementation by healthcare providers (HCPs) in routine care will ultimately determine the benefits of this novel technology. Actual numbers regarding the current implementation of AI in skin cancer care are lacking. However, recent survey studies among dermatologists in the United States, Europe, and China have revealed a positive attitude towards the potential of AI within the field of dermatology [8–10]. In contrast, GPs see only limited potential for AI in primary care in general. This is mainly attributed to a perceived narrow scope of use cases of AI in primary care and cynicism about the capabilities of AI to support in undertaking diagnoses [11]. However, their views towards AI specifically in skin cancer care remain unclear.
A critical step in the implementation of complex interventions is to gain an in-depth understanding of potential users’ views towards the use of AI in skin cancer care [12]. Nevertheless, an exploration of HCPs’ views towards AI when used in the hands of physicians in skin cancer care (e.g., AuI) is currently lacking. This qualitative study aims to fill this knowledge gap by exploring the views of Dutch dermatologists and GPs regarding successful implementation of assistive AI for HCPs in skin cancer care. Results of this study can be used to improve strategies for the future implementation of AI in skin cancer care, as well as to align the development of medical devices that use DNNs for skin cancer detection with the expectations of GPs and dermatologists.
Materials and methods
Study design
A qualitative study design was chosen as this is ideally suited to provide an in- depth picture of participants’ opinions, thoughts, and experiences [13, 14]. Focus groups (FGs) were considered most appropriate as group dynamics stimulate participants to reflect on each other, resulting in more diverse conversations than individual interviews [15]. Due to COVID-19, the focus groups were hosted online using Microsoft Teams. The reporting of this study followed the Standards for Reporting Qualitative Research (SRQR) [16].
Selection of participants
Dutch dermatologists and GPs were eligible for participation in the FGs. Purposive sampling was used to reach a variable sample of participants in terms of prior knowledge and/or experience with AI, gender, and age. Participants were recruited on social media (LinkedIn, Facebook, WhatsApp/Telegram dermatologist and GP group chats), and via email. In addition, participants were invited through the Dutch Society of Dermatology and Venereology’s newsletter. The invitations included an information leaflet, and participants were offered a €30 gift card. Participants applied via a web form.
Data collection
A prespecified topic guide based on existing literature regarding the acceptance and implementation of new technology in healthcare and previous experiences from our multidisciplinary research group (supplement 1). [13, 17, 18] was used to generate a semi-structured discussion during the FGs. Written informed consent and demographic questionnaire was obtained from participants. Before starting the FGs, the moderators explicitly explained that no consensus had to be reached. The 90-min sessions were moderated by two medical doctors (MDs) (TS,FM), of whom one had previous experience with qualitative research, under supervision of an experienced qualitative researcher (ML).
Data analysis
We performed a thorough inductive thematic content analysis using elements from Grounded Theory (Fig. 1), embedded in a constructivist paradigm [19]. All focus groups were audio-taped and transcribed verbatim. The transcripts were analyzed using NVivo v.12. Open coding of the first four FGs was independently done by two researchers (TS,FM), resulting in an unstructured list of codes [19]. Next, these codes were axially coded, i.e. categorized in more abstract codes resulting in a coding scheme of first concepts. This coding scheme was then discussed and refined by the multidisciplinary team of researchers (TS,FM,ML). Two additional FGs with GPs and dermatologists were organized as data saturation was not yet reached. The transcripts of the additional FGs were simultaneously openly and axially coded by two researchers (TS,FM) using this structured coding scheme and discussed with a senior qualitative researcher (ML). Based on this, the coding scheme was further refined and initial main themes and sub-themes were identified. Data saturation, meaning that no new insights were identified during the analysis[19], was reached after analysing six FGs. After selective coding, i.e. the stage in which more abstract and analytical categorization is performed, the final main themes and subthemes were determined based on discussion within the multidisciplinary research team (TS,FM,ML,MW). Demographic characteristics were analysed using SPSS Statistics v.15.Fig. 1 Qualitative data analysis process overview
Ethical considerations
The Erasmus MC medical ethical committee waived the need for ethical approval after reviewing the study protocol (MEC-2020–764).
Results
Characteristics of participating dermatologists and GPs are presented in Table 1, and individual characteristics in supplement 2 (eTable 1). In total, 3 main themes consisting of 13 sub-themes were identified (Fig. 2).Table 1 Participant characteristics. GPs: General Practitioners. IQR, Interquartile Range
Participants, n Median age (years), (IQR) Female, n (%)
Focus group 1 (GPs) 4 32 (32–34) 2 (50%)
Focus group 2 (GPs) 5 42 (35–53) 2 (40%)
Focus group 3 (Dermatologists) 4 49 (42–57) 2 (50%)
Focus group 4 (Dermatologists) 5 41 (35–52) 2 (40%)
Focus group 5 (GPs) 8 34 (32–35) 6 (75%)
Focus group 6 (Dermatologists) 7 39 (33–43) 5 (71%)
Total 33 36 (33–42) 19 (58%)
Fig. 2 Overview of main themes and sub-themes regarding the views of dermatologists and GPs towards the implementation of AI in skin cancer care
Perceived benefits
A first important benefit of the use of AI in skin cancer care, according to dermatologists and GPs, is that it is thought to improve the health outcome for skin cancer patients in primary and secondary care. This improvement was mainly attributed to the improved diagnostic accuracy when AI is used for skin cancer detection by dermatologists and GPs, leading to fewer missed skin cancer diagnoses and less unnecessary biopsies and excisions of benign skin lesions. As a result of the improved detection accuracy, GPs indicated expecting to be more confident when they use AI in the management of suspicious skin lesions.
“I thought: ‘Oh this is really a harmless mole’ and it turned out to be a melanoma that was flagged by that app. I got a warning notification and called the patient and said: ‘Well, go to the dermatologist today’. It was a young man of about 24 years with a melanoma which I would have missed otherwise”. (GP, FG 6).
Besides an improved diagnostic accuracy and confidence, dermatologists and GPs expected AI to improve the follow-up of skin lesions by offering the possibility to standardize the analysis and storage of dermoscopic and clinical images of skin lesions. When AI can provide a lesion description with treatment advice as well, GPs expected to save time and, simultaneously, make the way skin lesions are described and analyzed more universal. Dermatologists also noted AI to be useful for the comparison of lesion pictures longitudinally. By comparing lesion changes over time with AI guidance, they expected to make more scientific based decisions regarding the management of skin lesions, ultimately leading to improved patient outcomes.
The second identified benefit of the implementation of AI in skin cancer care is the improved care pathway between primary and secondary care. Both dermatologists and GPs expected the use of AI during the assessment of skin lesions to significantly reduce the number of unnecessary referrals for benign skin lesions from primary to secondary care. In addition to the reduction of referrals for benign lesions, dermatologists and GPs expected the use of AI to facilitate substitution of low-risk skin cancer care (e.g., low-risk basal cell carcinomas, actinic keratosis) from the dermatologist to the GP practice. Furthermore, the improved care pathway was thought to lead to a cost reduction of skin cancer care due to a lower number of unnecessary referrals and a substitution of skin cancer care from secondary to primary care.
‘I would like to see that used in practice. Particularly in order to separate out certain patient groups so that you provide tailored care and don't try and waste a lot of time on things that don't really matter.’ (Dermatologist, FG 3).
Finally, dermatologists indicated AI to be useful for dismissing patients and reducing the amount of follow-up visits. This was proposed to be accomplished either by GPs having the ability to accurately classify suspicious skin lesions with AI or by providing patients with smartphone applications that use AI for the classification of skin lesions.
The educational function of AI was identified as a third benefit. According to GPs, AI can offer a possibility to provide insight into why a lesion is considered suspicious or benign, thereby enhancing their knowledge of dermatology. This educational aspect of AI for GPs was also recognized by dermatologists, describing it as a possibility to train GPs, relieving them from spending time on the education of GPs.
‘I would like it to receive feedback from the application and compare it to my own interpretation to see if I’m right. I think you can learn a lot in that way.’ (GP, FG 5).
Perceived barriers
The first identified main barrier to the use of AI in skin cancer care as perceived by GPs and dermatologists was doubts about the accuracy of AI. This was first of all related to a perceived lack of integration of clinical findings in the assessment of an algorithm. Participants considered palpation and medical history to be essential for an accurate skin cancer diagnosis, whereas AI algorithms were thought to focus on visual information from a lesion photo. Moreover, the inability to compare a lesion – especially nevi – to other lesions on the skin of the patient was considered as another crucial component in the evaluation of skin lesions at which an algorithm falls short, according to dermatologists. They believed it to be nearly impossible for AI to distinguish ‘ugly duckling’ lesions solely based on a lesion photo without an overview of other lesions on the skin. The second reason for dermatologists and GPs to doubt the accuracy of AI was a perceived lack of algorithm transparency. Algorithms were considered to be ‘black boxes’, and both GPs and dermatologists explained it being difficult to understand on what grounds the output of an algorithm is based. This made it unclear to know when the assessment of an algorithm is accurate or not.
‘You want to see such a thing in the light of what kind of patient you have in front of you, with what kind of skin type, sun exposure, eye color etc. So, I'm just missing a whole lot to comfortable rely on an algorithm.’ (Dermatologist, FG 3).
The second identified main barrier was the risk of health inequalities. Concerns were raised about a bias towards lighter skin types among algorithm training data that could potentially cause health inequalities based on skin type. Moreover, dermatologists and GPs were concerned of accuracy differences between hospitals and GP practices who use and those do not use AI for skin cancer detection, leading to health inequalities depending on the hospital or GP practice a patient visits.
‘I think it is also important to check whether it [AI] works on people with a black skin, for a lot of AI performs well on people with a white skin in particular.’ (GP, FG 5).
A third barrier mentioned by dermatologists was a fear of being replaced by AI. Participants worried that the necessity for a dermatologist may be lower once AI can make diagnostic decisions on-par with a dermatologist. Others, however, were confident that AI should be seen as an assistive tool for dermatologists instead of a replacement. GPs and dermatologists both expected a shift of clinical tasks towards a more treatment-based role instead of a diagnostic role. A perceived crucial pitfall of using AI for skin cancer diagnostics, especially for young dermatologists, was to follow AI advice without a critical clinical evaluation. Hence, concerns were raised about a potential decline in experience in skin cancer recognition and therefore AI replacing their own diagnostic capabilities in the longer term.
‘… such an algorithm is based on knowledge, on input from dermatologists, but when you start as a young dermatologist, or as a resident, or as a general practitioner, then you don't have that knowledge, so then you are more likely to blindly rely on such an algorithm and I don't think that would be good.’ (Dermatologist, FG 3).
GPs mentioned the extra time it will take to use AI as fourth barrier. They considered it laborious to get acquainted with AI-software, master the software, and to take pictures with a medical device (e.g., an algorithm-enhanced dermoscope) during already limited consultation time.
Dermatologists and GPs also raised commercialization and associated privacy concerns, which was identified as fifth main barrier. These concerns were related to the costs that could be associated with the use of commercially available AI tools for skin cancer diagnosis. Elaborating on this, GPs reported to be suspicious about the storage of patient data, questioning the privacy of their patients when shared with these companies.
Preconditions for implementation
The first precondition for successfully implementing AI in skin cancer care expressed by dermatologists and GPs was adequate algorithm content, consisting of three elements. First, participants expected AI to perform at sufficient accuracy, although it appeared difficult to state the minimally accepted accuracy, ranging from 75%-95% sensitivity. Nevertheless, participants agreed that the accuracy will never reach 100%. Second, algorithms were expected to be transparent, meaning that a clinician can understand how the output of an algorithm is calculated. Third, participants expressed a need for binary advice (e.g., perform biopsy or do not perform biopsy) from AI, instead of other forms of advice (e.g., estimating percentage of malignancy).
The second precondition identified was sufficient usability and accessibility of AI. GPs expressed that AI software should be easy to learn and use. Dermatologists stressed that AI needs to be compatible with existing patient administration systems, and should provide a possibility to share data effortlessly with colleagues. In addition, GPs mentioned the need for data of patients to be safely stored when using a medical device which uses AI technology for the assessment of skin lesions. In terms of accessibility, equal functionality of AI for all skin types was considered essential by dermatologists and GPs.
The need for adequate validation and regulation of AI algorithms was identified as third precondition, expressed by both dermatologists and GPs. Research performed by an independent organization was considered adequate validation, similar to efficacy studies of therapeutics. Moreover, dermatologists reported a preference to validate the accuracy of an algorithm for skin cancer detection themselves. In addition to proper validation, adequate regulation was considered a prerequisite in ensuring the continuous safety of algorithms when implemented in skin cancer care. In particular, the possibility to frequently update AI algorithms was considered a potential challenge for regulators, which should be addressed before successful implementation can take place.
‘AI that the dermatologist uses, and so really makes a prediction whether it [a lesion] is good or bad, should really be tested by an authoritative organization with independent research, at least two preferably. So just like you register a drug.’ (Dermatologist, FG4).
Fourth, dermatologists and GPs expected endorsement by national medical societies. National skin cancer guidelines recommending the use of AI, indicating which algorithm or medical device is accurate and safe to use, before implementing it in their own practice was considered essential by GPs. They also considered it appropriate for government regulatory agencies to take interest in validation, on the condition that they are independent and transparent. Positive feedback from other GPs concerning certain AI technologies was mentioned as possible validation as well. Dermatologists expected the national association of dermatology to recommend which AI is accurate, and added the importance of AI to be reviewed regularly to hold this confidence. Furthermore, they expressed a preference to be involved in the design and implementation process of AI applications.
Clear liability was identified as fifth and final precondition. Both dermatologists and GPs expressed a need for clear liability regulations regarding the use of AI applications. Some GPs believe to be insured for mistakes made by AI when the specific AI software is endorsed in the national guideline, whereas others thought that a mistake made by AI was their responsibility or the responsibility of the developer. Dermatologists stressed caution in trusting organizations who validate AI because in the end liability is always one’s own responsibility.
‘.. what I do worry about is indeed liability, as to what extent are you fully responsible, or is there a part in which the application itself or the developer is responsible.’ (GP, FG1).
Discussion
The convergence of human and artificial intelligence in medicine offers the potential to profoundly transform skin cancer care in the coming decades [7, 20]. This in-depth qualitative study reveals key benefits, barriers, and essential preconditions for the successful implementation of AI in skin cancer care as perceived by dermatologists and GPs.
An important finding was the perceived benefit of AI to improve the care pathway between primary and secondary care. Both dermatologists and GPs expected AI to result in a reduction of unnecessary referrals, substitution of low-risk care, and cost reduction and subsequently in an improved care pathway. In theory, skin cancer detection accuracy on-par with dermatologists in the form of AI could indeed become available in primary care, which would mean a significant improvement of the current low sensitivity of GPs to detect skin cancer. [21] Although research focusing on AI in primary care is still scarce, a recent study showed an improvement of diagnostic accuracy of primary care physicians when using an algorithm in a teledermatology setting [6]. Real-world studies are needed to confirm this improvement in a clinical setting.
A second important and related benefit of AI, stressed by both dermatologists and GPs, was the educational function of AI to train GPs in skin cancer management. This is a significant finding, as limited and restricted education in skin cancer management have previously been identified as a barrier for GPs to treat skin cancer in primary care [22–24]. In line with this, providing post-graduate skin cancer education to GPs has demonstrated to improve the diagnostic accuracy of primary care physicians [25–27]. However, post-graduate training of GPs typically involves dermatologists to provide education, which can be labor-intensive and costly, and refresher material seems critical to maintaining acquired skills [28]. AI may be a useful complementary educational tool in addition to human teaching, which may prove helpful to scale post-graduate education of GPs and can be used according to their individual needs. Nevertheless, prospective studies are needed to demonstrate to which extent AI is effective in educating GPs.
A critical barrier to the implementation of AI in skin cancer care, perceived by both dermatologists and GPs, was doubts about its accuracy. This was particularly related to the lack of integration of clinical findings, such as a lack of complete skin examination, in the assessment of an algorithm. Consistent with this, a recent survey among US dermatologists reported the inability to perform a total body skin examination (TBSE) to be AI’s greatest weakness [8]. Several solutions have already been provided to address accuracy related perceived limitations. A recent study reported an algorithm to compare lesions on an overview photo taken with a smartphone and recognize suspicious lesions with high accuracy [29]. Moreover, several algorithms have demonstrated to integrate lesion symptoms, patient characteristics and other risk factors [30]. Yet, in a clinician-computer collaboration (e.g., AuI), it could also be argued that it is in fact the clinician's role to integrate clinical findings and patient preferences with the assessment of the algorithm [4]. Currently, the optimal collaboration between clinicians and computers is still poorly understood. Future studies should focus on HCPs’ views on the perceived optimal task distribution between humans and computers during the assessment of a patient with a suspicious skin lesion.
A second identified key barrier in this study which only applied to dermatologists, was the perceived fear of replacement by AI, which was also reported in three previous surveys among dermatologists [8–10]. It has also been found in other medical specialties, including radiology and pathology [31, 32]. However, it is argued that this fear is not rational because AI will change, instead of replace, the role of medical specialties [33]. Furthermore, as argued by Topol, the use of AI and AuI may make medicine less artificial and more ‘human’ by allowing less time spent on diagnostics and more on empathy [34]. In line with this, participants of our study explained to expect a shift of the diagnostic role of the dermatologist and GPs towards a more treatment-based role. Research among radiologists shows that fear of replacement is associated with limited AI-specific knowledge [31], which may be applicable to dermatologists as well. Hence, improving their knowledge about AI could be an effective strategy to reduce replacement fears.
Both type of HCPs regarded adequate algorithm content, and sufficient usability and accessibility of AI as essential preconditions for successful implementation. To meet both preconditions, transparency plays a crucial role, which may be challenging to fulfil. For example, the black box aspect of AI obscuring the explainability of algorithm decisions remains a critical challenge [35–37]. Although several techniques, e.g. heatmaps, Gradient-weighted Class Activation Mapping (GRAD-cam), and Local Interpretable Model-Agnostic Explanations (LIME), exist to gain insight into the outcome of an algorithm, these techniques are prone to confirmation bias when used by clinicians to understand the algorithm output [35, 38–40]. Recently, researchers even hypothesize that we may never reach a satisfactory level of explainable AI. Instead, proper validation of algorithms may be the only alternative for algorithm transparency [35]. While this may seem a viable alternative, a recent review revealed that not only algorithms lack transparency, but also the research that is published about the training and validation of these algorithms [41]. Hence, aside from continued efforts to break the black box of algorithms, researchers play a crucial role in meeting the preconditions with regards to adequate algorithm content by transparent research reporting, which can be achieved by sharing data sets, clear descriptions of data set characteristics, and reducing data label noise [41, 42].
Strengths and limitations
A strength of this study is its comprehensive scope of including the perspectives of both dermatologists and GPs, thereby providing a broad overview of key stakeholders’ views on the implementation of AI in skin cancer care. Moreover, by conducting separate FGs, we were able to compare the views of the groups. Our results show that the views of dermatologists and GPs largely overlap, with only a few remarkable differences as mentioned above.
This study also has some limitations. Although qualitative research is always context-specific to some extent [19], focusing only on HCPs within the Dutch healthcare system where the GP is positioned as gatekeeper to specialized care could limit the generalizability of our findings to other countries. Although the benefits of an improved care pathway may be slightly different in other countries, benefits such as an improved skin cancer detection accuracy, barriers such as a fear of replacement, and preconditions such as the need for adequate validation and regulation are more generally applicable. Another limitation of this study is that we explored the views of HCPs before actual implementation, which means that the results in this study reflect the views of HCPs mainly without having any experience with using AI in skin cancer care. While it is crucial to perform qualitative research before actual implementation [12], the views may change during actual implementation and warrant follow-up qualitative research in the future. Finally, our study did not include an exploration of the perspectives of HCPs towards AI for skin cancer screening (i.e. smartphone applications) by laypersons. Although previous research explored the patient’s and general public’s views [43], future research is needed to study the perspectives of HCPs.
Conclusion
In conclusion, the results of this study indicate that HCPs perceive significant benefits from implementing AI in skin cancer care. To successfully implement AI, key barriers such as doubts about its accuracy and the risk of health inequalities need to be addressed. Efforts should be focused on ensuring algorithm transparency, validation, accessibility for all skin types, and adequate regulation of algorithms. Concurrently, the unrealistic fear of replacement needs to be addressed by improving knowledge about AI. As such, these findings can contribute to developing an optimized strategy of integration of AI in the hands of physicians in the coming years.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 23 KB)
Author contributions
Conceptualization, TS, MW, and ML; methodology, TS and ML; validation, TS, FM, and ML.; formal analysis, TS, FM, and ML.; investigation, TS, MW, FM, TN, and ML; resources, TS, FM, MW, TN, and ML.; data curation, TS and FM.; writing original draft preparation, TS; writing review and editing, MW, FM, TN, and ML; visualization, TS, and ML; supervision, TN and ML; project administration, TS; funding acquisition, TN. All authors have read and agreed to the published version of the manuscript.
Funding
This study was initiated by the Erasmus MC Cancer Institute and was supported by an unrestricted research grant from SkinVision. SkinVision was not involved in the design of the study, data collection, data analysis, manuscript preparation or in the decision to publish this study.
Data availability statement
Participants of this study did not agree for their data to be shared publicly, so supporting data is not available.
Declarations
Conflict of interest
The Department of Dermatology of the Erasmus MC Cancer Institute has received an unrestricted research grant from SkinVision. Tamar Nijsten serves on the SkinVision advisory board and has equity in the company. There was no input from SkinVision on any aspect of data collection, data analysis or manuscript preparation.
Ethical approval
The need for ethical approval was waived by the medical ethical committee of the Erasmus MC University Medical Center after review of the study design (MEC-2020–764). Written informed consent was obtained from all participants.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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18. Sangers TE Wakkee M Kramer-Noels EC Nijsten T Lugtenberg M Views on mobile health apps for skin cancer screening in the general population: an in-depth qualitative exploration of perceived barriers and facilitators Br J Dermatol 2021 185 5 961 969 10.1111/bjd.20441 33959945
19. Green J Thorogood N Qualitative methods for health research 2018 4 SAGE Publishing Ltd 285 311
20. Topol EJ High-performance medicine: the convergence of human and artificial intelligence Nat Med 2019 25 1 44 56 10.1038/s41591-018-0300-7 30617339
21. Jones O Jurascheck L van Melle M Hickman S Burrows N Hall P Dermoscopy for melanoma detection and triage in primary care: a systematic review BMJ Open 2019 9 8 e027529 10.1136/bmjopen-2018-027529
22. Noels EC Wakkee M van den Bos RR Bindels PJE Nijsten T Lugtenberg M Substitution of low-risk skin cancer hospital care towards primary care: a qualitative study on views of general practitioners and dermatologists PLoS One 2019 14 3 e0213595 10.1371/journal.pone.0213595 30889211
23. Hayes SF Early detection of melanoma is key, so let’s teach it BMJ 2009 338 a3138 10.1136/bmj.a3138 19126609
24. van Rijsingen MCJ van Bon B van der Wilt GJ Lagro-Janssen ALM Gerritsen MJP The current and future role of general practitioners in skin cancer care: an assessment of 268 general practitioners Br J Dermatol 2014 170 6 1366 1368 10.1111/bjd.12935 24601950
25. Bedlow C Melia M Seyan H Impact of skin cancer education on general practitioners' diagnostic skills Clin Exp Dermatol 2000 25 2 115 118 10.1046/j.1365-2230.2000.00590.x 10733633
26. Gerbert B Bronstone A Wolff M Maurer T Berger T Pantilat S Improving primary care residents’ proficiency in the diagnosis of skin cancer J Gen Intern Med 1998 13 2 91 97 10.1046/j.1525-1497.1998.00024.x 9502368
27. Youl PH Raasch BA Janda M Aitken JF The effect of an educational programme to improve the skills of general practitioners in diagnosing melanocytic/pigmented lesions Clin Exp Dermatol 2007 32 4 365 370 10.1111/j.1365-2230.2007.02414.x 17433042
28. Harkemanne E Baeck M Tromme I Training general practitioners in melanoma diagnosis: a scoping review of the literature BMJ Open 2021 11 3 e043926 10.1136/bmjopen-2020-043926
29. Soenksen LR Kassis T Conover ST Marti-Fuster B Birkenfeld JS Tucker-Schwartz J Using deep learning for dermatologist-level detection of suspicious pigmented skin lesions from wide-field images Sci Transl Med 2021 13 581 eabb3652 10.1126/scitranslmed.abb3652 33597262
30. Höhn J Hekler A Krieghoff-Henning E Kather JN Utikal JS Meier F Integrating patient data into skin cancer classification using convolutional neural networks: systematic review J Med Internet Res 2021 23 7 e20708 10.2196/20708 34255646
31. Huisman M Ranschaert E Parker W Mastrodicasa D Koci M de Santos DP An international survey on AI in radiology in 1041 radiologists and radiology residents part 1: fear of replacement, knowledge, and attitude Eur Radiol 2021 31 9 7058 7066 10.1007/s00330-021-07781-5 33744991
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36. Price WN Big data and black-box medical algorithms Sci Transl Med 2018 10 471 eaao5333 10.1126/scitranslmed.aao5333 30541791
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38. Selvaraju RR Cogswell M Das A Vedantam R Parikh D Batra D Grad-CAM: visual explanations from deep networks via gradient-based localization Int J Comput Vision 2020 128 2 336 359 10.1007/s11263-019-01228-7
39. Samek W Binder A Montavon G Lapuschkin S Müller K Evaluating the visualization of what a deep neural network has learned IEEE Trans Neural Netw Learn Syst 2017 28 11 2660 2673 10.1109/TNNLS.2016.2599820 27576267
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| 36477587 | PMC9734890 | NO-CC CODE | 2022-12-14 23:28:31 | no | Arch Dermatol Res. 2022 Dec 7;:1-9 | utf-8 | Arch Dermatol Res | 2,022 | 10.1007/s00403-022-02492-3 | oa_other |
==== Front
Chin J Integr Med
Chin J Integr Med
Chinese Journal of Integrative Medicine
1672-0415
1993-0402
Springer Nature Singapore Singapore
36477450
3689
10.1007/s11655-022-3689-2
Original Article
Effect of Shengmai Yin on Epithelial-Mesenchymal Transition of Nasopharyngeal Carcinoma Radioresistant Cells
Wang Ze-tai 1
Peng Yan 1
Lou Dan-dan 1
Zeng Si-ying 1
Zhu Yuan-chao 1
Li Ai-wu 2
Lyu Ying 2
Zhu Dao-qi 1
Fan Qin [email protected]
1
1 grid.284723.8 0000 0000 8877 7471 School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, 510515 China
2 grid.416466.7 0000 0004 1757 959X Department of Traditional Chinese Medicine, Nanfang Hospital, Guangzhou, 510515 China
7 12 2022
18
18 7 2022
© The Chinese Journal of Integrated Traditional and Western Medicine Press and Springer-Verlag GmbH Germany, part of Springer Nature 2022
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Objective
To investigate the mechanism by which Chinese medicine Shengmai Yin (SMY) reverses epithelial-mesenchymal transition (EMT) through lipocalin-2 (LCN2) in nasopharyngeal carcinoma (NPC) cells CNE-2R.
Methods
Morphological changes in EMT in CNE-2R cells were observed under a microscope, and the expressions of EMT markers were detected using quantitative real-time PCR (RT-qPCR) and Western blot assays. Through the Gene Expression Omnibus dataset and text mining, LCN2 was found to be highly related to radiation resistance and EMT in NPC. The expressions of LCN2 and EMT markers following SMY treatment (50 and 100 µ g/mL) were detected by RT-qPCR and Western blot assays in vitro. Cell proliferation, migration, and invasion abilities were measured using colony formation, wound healing, and transwell invasion assays, respectively. The inhibitory effect of SMY in vivo was determined by observing a zebrafish xenograft model with a fluorescent label.
Results
The CNE-2R cells showed EMT transition and high expression of LCN2, and the use of SMY (5, 10 and 20 µ g/mL) reduced the expression of LCN2 and reversed the EMT in the CNE-2R cells. Compared to that of the CNE-2R group, the proliferation, migration, and invasion abilities of SMY high-concentration group were weakened (P<0.05). Moreover, SMY mediated tumor growth and metastasis in a dose-dependent manner in a zebrafish xenograft model, which was consistent with the in vitro results.
Conclusions
SMY can reverse the EMT process of CNE-2R cells, which may be related to its inhibition of LCN2 expression. Therefore, LCN2 may be a potential diagnostic marker and therapeutic target in patients with NPC.
Keywords
epithelial-mesenchymal transition
lipocalin-2
nasopharyngeal carcinoma
radiation therapy
Shengmai Yin
Chinese medicine
==== Body
pmcAcknowledgement
The authors gratefully acknowledge generous support by of the Radiotherapy Department of Nanfang Hospital.
Supported by the National Natural Science Foundation of China (No. 82074132), Project of Administration of Traditional Chinese Medicine of Guangdong Province of China (No. 20213009) and the Science and Technology Plan Project of Guangzhou City (No. 202102080405)
Conflict of Interest
The authors declare no conflicts of interest.
Author Contributions
Wang ZT and Peng Y conducted experimental research, collected the test data, elucidated the results. Lou DD designed this research and wrote the manuscript. Zeng SY and Zhu YC took part in the experiment. Li AW and Lyu Y provided constructive suggestions. Fan Q and Zhu DQ directed the project and managed the funds. All authors read and approved the final version for publication.
==== Refs
References
1. Lin G Yu B Liang Z Li L Qu S Chen K Silencing of c-jun decreases cell migration, invasion, and EMT in radioresistant human nasopharyngeal carcinoma cell line CNE-2R Onco Targets Ther 2018 11 3805 3815 10.2147/OTT.S162700 30013361
2. Sun Y Lin H Qu S Li L Chen K Yu B Downregulation of CD166 inhibits invasion, migration, and EMT in the radio-resistant human nasopharyngeal carcinoma cell line CNE-2R Cancer Manag Res 2019 11 3593 3602 10.2147/CMAR.S194685 31114384
3. Yuan X Zhang L Huang Y Liu D Peng P Liu S Induction of interleukin-6 by irradiation and its role in epithelial mesenchymal transition and radioresistance of nasopharyngeal carcinoma cells Head Neck 2021 43 757 767 10.1002/hed.26531 33150659
4. Ashrafizadeh M Zarrabi A Hushmandi K Kalantari M Mohammadinejad R Javaheri T Association of the epithelial—mesenchymal transition (EMT) with cisplatin resistance Int J Mol Sci 2020 21 4002 10.3390/ijms21114002 32503307
5. Zhou D Ye C Pan Z Deng Y SATB1 knockdown inhibits proliferation and invasion and decreases chemoradiation resistance in nasopharyngeal carcinoma cells by reversing EMT and suppressing MMP-9 Int J Med Sci 2021 18 42 52 10.7150/ijms.49792 33390772
6. Huang Y Zhang M Li Y Luo J Wang Y Geng W miR-183 promotes radioresistance of lung adenocarcinoma H1299 cells via epithelial-mesenchymal transition Braz J Med Biol Res 2021 54 e9700 10.1590/1414-431x20209700 33825780
7. Kim SL Lee ST Min IS Park YR Lee JH Kim DG Lipocalin 2 negatively regulates cell proliferation and epithelial to mesenchymal transition through changing metabolic gene expression in colorectal cancer Cancer Sci 2017 108 2176 2186 10.1111/cas.13389 28859238
8. Santiago-Sanchez GS Pita-Grisanti V Quiones-Diaz B Gumpper K Cruz-Monserrate Z Vivas-Mejía PE Biological functions and therapeutic potential of lipocalin 2 in cancer Int J Mol Sci 2020 21 4365 10.3390/ijms21124365 32575507
9. Cheng J Chen J Zhao Y Yang J Xue K Wang Z MicroRNA-761 suppresses remodeling of nasal mucosa and epithelial—mesenchymal transition in mice with chronic rhinosinusitis through LCN2 Stem Cell Res Ther 2020 11 151 10.1186/s13287-020-01598-7 32272958
10. An X Duan L Zhang YH Jin D Zhao S Zhou RR The three syndromes and six Chinese patent medicine study during the recovery phase of COVID-19 Chin Med 2021 16 44 10.1186/s13020-021-00454-x 34099015
11. Li S Qian Y Xie R Li Y Jia Z Zhang Z Exploring the protective effect of ShengMai-Yin and Ganmaidazao decoction combination against type 2 diabetes mellitus with nonalcoholic fatty liver disease by network pharmacology and validation in KKAy mice J Ethnopharmacol 2019 242 112029 10.1016/j.jep.2019.112029 31216433
12. Ming S Kan M Liu L Zhang Z Liu X Liu Y Protective effect of shengmaiyin in myocardial hypertrophy-induced rats: a genomic analysis by 16S rDNA Evid Based Complement Alternat Med 2022 2022 3188292 10.1155/2022/3188292 36118100
13. Miao M Li Q Liu YR Chemo-sensitivity enhancing effects of Shengmai Injection on various chemotherapeutic drugs Chinese Traditional and Herbal Drugs 2013 44 875 880
14. Liu S Wang Z Zhu D Yang J Lou D Gao R Effect of Shengmai Yin on the DNA methylation status of nasopharyngeal carcinoma cell and its radioresistant strains J Pharm Anal 2021 11 783 790 10.1016/j.jpha.2020.11.010 35028184
15. Liu S Wang Z Zhu D Yang J Lou D Gao R Effect of Shengmai Yin on the DNA methylation status of nasopharyngeal carcinoma cell and its radioresistant strains J Pharm Anal 2021 11 783 790 10.1016/j.jpha.2020.11.010 35028184
16. Zhu D Huang M Fang M Li A Liu Z Shao M Induction of radioresistant nasopharyngeal carcinoma cell line CNE-2R by repeated high-dose X-ray irradiation Int J Radiat Res 2019 17 47 55
17. Tsering J Hu X Triphala suppresses growth and migration of human gastric carcinoma cells in vitro and in a zebrafish xenograft model Biomed Res Int 2018 2018 7046927 10.1155/2018/7046927 30643816
18. Wu JQ Zhai J Li CY Tan AM Wei P Shen LZ Patient-derived xenograft in zebrafish embryos: a new platform for translational research in gastric cancer J Exp Clin Cancer Res 2017 36 160 10.1186/s13046-017-0631-0 29141689
19. Chen YP Chan A Le QT Blanchard P Sun Y Ma J Nasopharyngeal carcinoma Lancet 2019 394 64 80 10.1016/S0140-6736(19)30956-0 31178151
20. Sun XS Li XY Chen QY Tang LQ Mai HQ Future of radiotherapy in nasopharyngeal carcinoma Br J Rad 2020 92 20190209 10.1259/bjr.20190209
21. Zackrisson B Mercke C Strander H Wennerberg J Cavallin-Ståhl E A systematic overview of radiation therapy effects in head and neck cancer Acta Oncol 2003 42 443 461 10.1080/02841860310014886 14596506
22. Suna ZMZ Chao Z Wang W Haihua Y Wenguang YE The role of epithelial-mesenchymal transition in regulating radioresistance Crit Rev Oncol Hematol 2020 150 102961 10.1016/j.critrevonc.2020.102961 32361589
23. Lu Y Dong B Xu F Xu Y Pan J Song J CXCL1-LCN2 paracrine axis promotes progression of prostate cancer via the Src activation and epithelial-mesenchymal transition Cell Commun Signal 2019 17 118 10.1186/s12964-019-0434-3 31500632
24. Hu C Yang K Li M Huang W Zhang F Wang H Lipocalin 2: a potential therapeutic target for breast cancer metastasis Onco Targets Ther 2018 11 8099 8106 10.2147/OTT.S181223 30519052
| 36477450 | PMC9734894 | NO-CC CODE | 2022-12-14 23:28:31 | no | Chin J Integr Med. 2022 Dec 7;:1-8 | utf-8 | Chin J Integr Med | 2,022 | 10.1007/s11655-022-3689-2 | oa_other |
==== Front
J Mater Sci
J Mater Sci
Journal of Materials Science
0022-2461
1573-4803
Springer US New York
8012
10.1007/s10853-022-08012-y
Electronic Materials
Three-dimensional AgNps@Mxene@PEDOT:PSS composite hybrid foam as a piezoresistive pressure sensor with ultra-broad working range
Zhen Ye
http://orcid.org/0000-0002-6542-2904
Reddy Vundrala Sumedha [email protected]
Ramasubramanian Brindha
Ramakrishna Seeram
grid.4280.e 0000 0001 2180 6431 Department of Mechanical Engineering, Centre for Nanotechnology and Sustainability, National University of Singapore, Singapore, 119260 Singapore
Handling Editor: Till Froemling.
7 12 2022
2022
57 48 2196021979
11 8 2022
22 11 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Piezoresistive pressure sensors are becoming increasingly popular for their applications in human motion detection, wearable electronics, health monitoring, and man–machine interfaces. Sensors with superior sensitivity and a broad range of sensing are desirable for practical implementation. To achieve those, a low-cost, scalable and simple fabrication technique of dip coating Ti3C2 (MXene), PEDOT:PSS, and AgNPs onto a melamine foam is proposed. The prepared sensor demonstrated sensitivity of 414.27 kPa−1 at (4.17–12.98 kPa), 182.52 kPa−1 at (12.98–94.55 kPa), 317.78 kPa−1 at (94.55 kPa–1.94 MPa), 164.32 kPa−1 at (> 1.94 MPa), extraordinaire detecting range 977.6 N and outstanding repeatability. The sensor was successfully applied for the real-time detection of heartbeat pulse, limb movement, human weight and powered an LED. Furthermore, an integrated circuit design with sensors had the ability to identify spatial pressure distribution and visualize it on a pressure map.
Graphical Abstract
Supplementary Information
The online version contains supplementary material available at 10.1007/s10853-022-08012-y.
Sustainable Tropical Data CenterR265000A50281 NUS COVID-19 Research Seed Funding NUSCOVID19RG-11R265000A01133 issue-copyright-statement© Springer Science+Business Media, LLC, part of Springer Nature 2022
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pmcIntroduction
For decades, people have been working on wearable technology. With the advancement of the electronic industry, wearable technology has reached its pinnacle [1]. Wearables combined with wireless and smartphone technologies can help in real-time monitoring of body movements, heartbeat, blood pressure, and other vital indications. Wearable technology is frequently used in health care due to these benefits. Wearable health devices help measure health indicators at home during early diagnosis, therapy, and post-treatment. It is easier to manage, minimizes the logistics of visiting the hospital, and saves time while being stress-less and hassle-free [2]. Sensors are essential in wearable technologies. These sensors, affixed to an individual's skin, detect and transmit impulses. Chemical and physical sensors are the most common types. Physical sensors offer information on bodily mobility, vibrations, pulses, etc. Chemical pressure utilizes the chemical reaction to affect the conductivity and further detect the pressure change [3]. Pressure sensors are typical physical wearable sensors with four distinct functioning mechanisms. Except these two types, bio-based pressure senor is another unique type pressure. Sensor is design based on bioreaction like immunoreaction[4–6], electrochemical reactions[7], chemical reaction[3]. The types of physical mechanisms involve piezoelectric [8], capacitive [9], triboelectric [10] and piezoresistive [11–14]. Among these, piezoresistive sensors have become increasingly popular due to their ease in the signal grouping, controllable sensing range, stability and applications in integrated devices, machine–human interface, healthcare monitoring etc. Piezoresistance came in 1856 (nineteenth century) when the change of resistance in copper and iron wires during elongation was discovered by William Thomson (Lord Kelvin) [15]. The piezoresistive effect was introduced by Cookson in 1935, who defined it as the change in conductivity with stress [12].
Traditional piezoresistive sensors have been based on brittle sensing materials built on hard surfaces [13]. Following this, the properties of the next-generation piezoresistive sensors for wearable healthcare monitoring have been emphasized to have high flexibility, compressibility, stretchability, and bending capabilities, in addition to increased sensitivity. Sensitive sensing material selection and appropriate geometric electrodes should be used for a synergistic effect when designing such a piezoresistive sensor [14]. The basic principle behind the working of piezoresistive sensor mainly depends on the change in resistance of the material with varying external mechanical deformation. These sensors transform external force or pressure into current and resistance. [16]
Based on the material and device construction, a piezoresistive sensor can sense small vibrations in the human body, such as pulse, breath, and large stress or load. The flexible pressure sensor with high sensitivity, outstanding flexibility, and low cost can convert the external force information into electrical signals in real time [17, 18]. And it has potential to applied as electronic skin and healthcare detection systems for sensing biophysical signals such as pulse waves, respiration, and intraocular pressure [19]. Lot of soft material can play as the carrier of pressure sensor, such as polyurethane (TPU) substrate[19], poly (vinylidene fluoride) (PVDF)[20], cotton[6], polypyrrole (PPy) foam[18]. In this work, we choose commercial foam and used a low-cost and straightforward fabrication technique of dip coating for easily accessible foam.
Foam has a porous or fibrous structure with elasticity. It helps in obtaining high sensitivity to the wearable piezoresistive sensors. These criteria necessitate a series of fabrication processes, making large-scale production problematic. As a conventional material, foam can be found in our daily life, for example, as a foam washer, an acoustic absorber foam, a fireproof foam, a foam cushion etc. Due to the specific characteristics of the sponge, such as its energy absorption [21], elasticity [22], porosity [23], light-weightiness, low cost, and environmental friendliness, it acts as an ideal substrate for the wearable pressure sensor. By exploiting the porosity of the foam, piezoresistance can be induced by a series of steps involving carbonization [24], dipping-coating [16, 25], followed by layer-by-layer assembly [26] of the sensor. These techniques facilitate compacting the foam while creating contact paths for current. Some recent research efforts are discussed to explore the current state-of-the-art. In 2018, Weijie et al.[24]. fabricated a carbonized (heat treatment to obtain carbon) foam at 800 °C in a nitrogen flow. It could detect slight pressure as low as 3 Pa. In addition to its 9 Pa detection limit, its endurance was remarkable, with 90% performance persisting after 11000 press-release cycles. Its performance can be linked to the carbon foam's flexible and soft character. Another easy procedure is dip-coating, which involves immersing the substrate in the material solution. Amit et al.[27]. demonstrated the working of reduced graphene oxide (rGO) based piezoresistive sensor. The sensor was fabricated by dipping polyurethane (PU) foams into rGO solution. Even after 5000 cycles of testing, there was almost no decrease in performance. It is profiting from 2-dimension (2D) material graphene, whose conductivity is better than 1-dimension (1D) material.
Moreover, 2D material can create a larger connect area facilitating the transfer of more electrons from one side to another. A different study involves free-standing graphene super light foam fabricated by Yarjan et al. [28]. Remarkably, a 30% compressive load on the foam increased its resistance to 120% of its initial value.
Mxene is a 2D material that has recently come to light. It was first reported by Naguib et.al in [29] Mxene can be produced by selectively etching MAX phase. MAX phase is the ternary carbides and nitrides with a Mn+1AXn formula. M is an early transition metal, A is an A-group (mostly groups 13 and 14) element, and X is C and/or N. In the present study, we are using Ti3AlC2 (MAX phase). The ultra-thin Ti3C2 Mxene nanosheets are produced after acid etching process. The synthesis can be carried out by suspending a MAX phase in hydrofluoric acid (HF) [25, 30]. Due to the strong corrosivity of HF, Ghidiu et al. [31]. found an alternative synthesis technique which is easier and safe. The team immersed Ti3AlC2 in lithium fluoride (LiF) and concentrated aqueous hydrogen chloride (HCl) solution. 2D nanosheets were formed in ultrasonic treatment under protected gas flow. Mxene is a promising candidate for supercapacitor applications due to its excellent electrical conductivity and 2D structure [32], pressure sensor [33], battery electrode [34], electromagnetic interference shielding [35], antibacterial activity [36], and in water and air purification [37]. Mxenes often have a negative charge due to the abundance of –OH, –O, and –F functional groups at their surface terminals [38]. Positively charged molecules are electrostatically adsorbed on the surface of Mxenes, providing the composite with improved sensing capabilities [39, 40].
In this work, we designed a robust piezoresistive melamine foam sensor. The foam was sequentially coated with PEDOT:PSS and Mxene. To further increase its conductivity, silver nanoparticles (Ag Nps) were mixed with Mxene solution. A simple dipping and coating approach was employed to prepare AgNps-Mxene@PEDOT:PSS sensor. It was possible to acquire a detection range that was greater than that of already accessible works [41, 42](from 0.417 to 817.8 N). This hybrid foam sensor can tolerate more than 90% deformation under a 977.6 N load, providing a stable response in a broad load range.
A comparison of various foam-based pressure sensor performances is listed in Table 1, showing the standing of our present work.Table 1 Foam-based piezoresistive pressure sensors
Material Fabrication method Cycle of durability test Detecting range Sensitivity Reference
Mxene@AgNps@PEDOT:PSS Dip-coating 5000 4Kpa –8178Kpa (8.178 MPa) 414.27 kPa−1 at (4.17–12.98 kPa)
182.52 kPa−1 at (12.98–94.55 kPa)
317.78 kPa−1 at (94.55–1.94 MPa)
164.32 kPa−1 at (> 1.94 MPa)
Present work
Melamine foams Carbonization at 800 degrees 11000 3 Pa–10 kPa 100.29 kPa−1 [24]
Mxene Dip-coating 10000 9 Pa–18.56 kPa 147 kPa−1 at (0–5.37 kPa)
442 kPa−1 at (5.37–18.56 kPa)
[16]
Chitosan@ Mxene Dip-coating 5000 9pa–245.7 kPa 0.014 kPa−1 at (0–6.5 kPa)
0.015 kPa−1 at (6.5–85.1 kPa) 0.001 kPa−1 at (85.1–245.7 kPa)
[43]
Reduced graphene oxide (rGO)@ multiwalled carbon nanotubes (MWNTs) Dip-coating 5000 2.22 − 16.4 kPa 0.022 kPa−1 at (0–2.7 kPa)
0.088 kPa−1 at (2.7–10.8 kPa)
0.034 kPa−1 at (10.8–48.8 kPa)
[27]
Polyurethane (TPU)@polydopamine (PDA)@MXene combination of directional freezing and dip-coating method 5000 10 Pa–122.5 kPa 0.039 kPa− 1 at (10–490 Pa)
0.0302 kPa− 1 at (490 Pa–30 kPa)
0.0068 kPa− 1 at (30–122.5 kPa)
[44]
Poly(3,4-ethylenedioxythiophene):poly- (styrenesulfonate) (PEDOT:PSS) Dip-coating 1000 5.9–35 K pa N.A [42]
Silver nanowires (AgNWs) Carbonization and Dipping-coating 1000 30–50 kPa 4.97 kPa−1 [41]
Cellulose nanofiber @ carbon black (CNF@CB) conductive layer Dip-coating 1000 Not mention-29Kpa 0.35 kPa−1 at (0–2.2 kPa)
0.082 kPa−1 at (2.2–7.9 kPa)
0.015 kPa−1 at (> 7.9 kPa)
[45]
Reduced graphene oxide (rGO) Dip-coating 10 000 cycles, at 0–35 kPa 20 kPa–1.94 Mpa 0.0152 kPa−1 [46]
Experimental section
Materials
Commercially available Melamine sponge. Poly (3,4-ethylenedioxyiophene)-poly(styrenesulfonate) (PEDOT:PSS), Mxene (Ti3AlC2) power, Lithium fluoride (LiF) power, Sliver nanoparticle (AgNps) and Hydrochloric acid were purchased from Sigma-Aldrich (Singapore). The substrate used is commercially available melamine foam with 90% porosity. A simple dipping and coating method was used to fabricate Mxene@PEDOT:PSS@AgNps foam sensor. Step-wise fabrication of the composite foam has been discussed below.
Synthesis of 2D Mxene sheet
Mxenes are layered structures derived from MAX phase. Mxene sheets are synthesised by etching A-element atomic layers from the Mn+1Xn adjacent layers from the MAX phase (i.e., Al layer in Ti3AlC2 is dissolved by acid). The etching process results in a terminated multi-layered Mxene powders with the 2D layers held together by hydrogen and van der Waals bonds [29, 47]. Layer “A” can be easily dissolved using hydrofluoric acid (HF)[29, 48, 49].Ti3AlC2+3HF=AlF3+3/2H2+Ti3C2
Ti3C2+2H2O=Ti3C2OH2+H2
Ti3C2+2HF=Ti3C2F2+H2
Even in small quantities, HF remains dangerous. Considering the risk assessment and required safety procedures, severe corrosivity, we dissolved the A-layer using lithium fluoride-hydrochloric acid (LiF-HCl), instead of HF.
To obtain single- or few-layer Mxenes, sonication was performed and later replaced by intercalation of dimethyl sulfoxide (DMSO), which proved to be more efficient [50]. In this study, we solely synthesized multi-layered 2D Ti3C2X nanoflakes with intact structure for sensor application. To separate nanosheets, we used sonification procedure to increase the surface and contact area. To get a single layer nanosheet, it require more critical treatment. The beneficial impact of sonification has been discussed in subsequent section. Intensive processes are needed to produce a single-layer nanosheet.
Mxene nanosheets were fabricated by acid etching the Ti3AlC2 powder. Initially, 0.5 g Lithium Fluoride is added into 10 ml HCl (9 M) slowly and stirred for 10 min until LiF was completely dissolved. This step can produce LiF-HCl acid to react with Ti3AlC2 powder. In this solution, a total of 0.5 g Ti3AlC2 powder was added gradually in small amounts. This mixture was stirred continuously for 24 h at 40 °C on hot plate. Different HF acid concentration require different processing time for the complete reaction to happen. Mohamed Alhabeb et al. address this period under varied HF acid concentration. 5, 18, and 24 h for 30, 10, and 5 wt% HF, respectively. [47] The obtained solution was washed with deionized (DI) water and centrifuged at 4000 r/min for 10 min each time until the pH value was around 7 (the acceptable pH range is 5–7). After each centrifuge cycle, powder gets collected at the tube's bottom, drain the liquid. Then, add new DI water to the tube, until the PH level was maintained around 7. The Mxene powder settles at the bottom, and the top liquid was then drained off. Finally, to acquire a homogeneous Mxene aqueous dispersion, the resultant was placed into a three-necked, round-bottomed flask and ultrasonicated in an ice bath under protective nitrogen flow.
Fabrication of AgNps-Mxene@PEDOT:PSS foam
Melamine was taken as a primary foam here with film (thickness is 2 mm) cut into 1 cm x 1 cm cube (size comparison with a 20 cents SGD coin (Fig. S1)). Firstly, the foam cube was washed with DI water. Secondly, it was dipped in the 95% ethyl alcohol and ultrasonicated for 20 min to get rid of unwanted foreign residue. Thirdly, rinsed and ultrasonicated while immersed in DI water for 20 min. Finally, the foam cube was dried in the oven at 60 °C for 4 h. The obtained clean foams were then dip-coated in 1.3wt% PEDOT:PSS solution. After the PEDOT:PSS coated foam was allowed to dry in the oven for 4 h, it was dipped in AgNps-Mxene solution. Forty milligram AgNps were added to 10 ml prepared Mxene nanosheet aqueous solution and stirred for 2 h to prepare AgNps-Mxene solution. PEDOT:PSS-coated foam was immersed into AgNps-Mxene solution and put in the vacuum oven at 30 °C for 24 h. Finally, it was then dried at 60 °C for 4 h to obtain the composite foam. The foam at different stages: plain, with PEDOT:PSS and AgNps-Mxene@PEDOT:PSS foam is shown from left to right in Fig S1.
Assembly of AgNps-Mxene@PEDT:PSS foam pressure sensor
This foam sensor was assembled in a sandwich structure as shown in Fig. 1a. Bottom layer is an interdigital electrode, which was stacked with 0.5 cm*0.5 cm PVDF-HFP nanofiber spacer. Lastly, AgNps-Mxene@PEDT:PSS foam was placed as the top layer. This sensor setup was sealed properly by biomedical transparent tape.Figure 1 a Schematic illustration of AgNps@Mxene@PEDT:PSS foam sensor assembly. b Work diagram of spacer. c The device testing set up
Nanofiber spacer
A pure PVDF-HFP nanofiber film fabricated by the electrospinning technique was utilized here. PVDF-HFP solution was prepared using the solvents acetone and N N-dimethylacetamide (DMAc) in the ratio of 1:1 with 16 wt% of PVDF-HFP pellets. The solution was vigorously stirred at room temperature for 48 h in order to obtain a homogeneous mixture. The solution was loaded into the syringe, and electrospinning was carried out while maintaining the parameters of 19 keV voltage, 200 rpm roller drum speed, collection width of 20 mm and a steady flow rate of 2 ml/hr. The spacer is a nonconductive layer which facilitates in separating of foam and electrode, drastically reducing the contact area Fig. 1b. The tensile test of PVDF-HFP nanofiber presented good elasticity and mechanical strength Fig S2.
We designed our experiments to discuss the effect of type and concentration of material. The layman's concept of piezoresistive sensors is that: in its usual form, the foam should be nonconducting, but when pressure is applied, it becomes conductive based on the additives and formation of conducting paths. PEDOT:PSS and Mxene are the essential materials in this case. Because of hydrophilicity and electrical conductivity, Mxene has a lower resistance at increasing concentrations. However, research has shown that the performance of the sensor is restricted by Mxene concentration. The sensor's performance starts to decrease when the foam is highly concentrated by Mxene. This happens due to shorting with the interdigital electrode due to the complete conductivity of the foam. This limitation is addressed by the addition of a spacer layer.
We observed that Mxene powder is spilt from the foam structure during the pressure pressing procedure due to weak adherence of Mxene to the foam. As a result, the sensor became unstable and underperformed. In order to overcome his issue, we incorporated another conductive material PEDOT:PSS, which is in the liquid form that helps in adhering the particles. It can be easily absorbed and attaches tightly to the foam after drying. We added silver nanoparticles to increase the conductivity further as the insertion of a spacer eliminates the limitation of conductivity in sensor performance. Thus, the hybrid foam sensor was fabricated using step-by-step layer fabrication. In this study, we studied the effect of Mxene concentration while keeping the PEDOT:PSS concentration fixed. Three different concentrations of Mxene: 1 mg/ml, 2 mg/ml, 4 mg/ml were considered. The assembled device is shown in Fig. S3.
Result and discussion
Hybrid-coated foam
The conflict between high sensitivity and wide sensing range greatly limits the extensive application of flexible pressure sensors. To produce a sensor with both high sensitivity and wide range is still a challenging work. [51] In this work, we utilize the 2D-material Mxene to achieve a ultra-high sensitivity and detection range. The hybrid sensor is design based on a foam sensor. Commercial foam has a porous structure, which can be easily fabricated as a wearable sensor.
Sensitivity and detecting range are related to conductivity of our sensor. Figure 2c indicates the relationship between performance and conductivity (Mxene concentration). High conductivity further limits performance of sensor, as resistive response is necessary. Due to the limitation, we designed spacer layer. It can isolate foam and interdigital electrode to increase the detecting range (discussed in subsequent section). We further introduce the silver nano particle (AgNps). As a conductive metal, silver can help to create conductive pathways, boost sensor sensitivity, and shorten response times simultaneously. It is commonly employed in sensors. B.Cai et.al achieved 4.97 kPa−1 sensitivity with a silver-coated carbonization foam. [41] Combination of Mxene and AgNps increase conductivity, but high concentration brings instability for sensor hence we controlled the composition. Both Mxene and AgNps are powder. The coated powder would disperse during compression or pressure application and the sensor’s stability would be unable to achieve. In order to hold the components together, we introduced liquid phase, poly (3,4-ethylenedioxythiophene): poly(styrenesulfonic acid) (PEDOT:PSS), well-known as the most remarkable conducting polymer. Apart from coalition, the polymer also provides high transparency, tunable conductivity, excellent thermal stability and good film-forming properties. [52] As, after drying, the PEDOT:PSS thin film can attach on foam structure tightly. As a result of this combination, our hybrid foam sensor could present high sensitivity in ultra-high detecting range.Figure 2 a I–V curve based on Mxene@PEDOT:PSS@AgNps sensor and its fitting curve. b Current present as y-axis for different concentration Mxene@PEDOT:PSS foam. c Performance present as y-axis for different concentration Mxene@PEDOT:PSS foam. d Different load pressure test, y-axis label is log10 due to high sensitivity. e Relationship between current and load. f Sensor response between 0 and10 N g) Sensitivity of hybrid foam in different section h) Durability test, 5000 tests in total, only 1000 cycles are present here
Pressure model and sensing properties of AgNps-Mxene@PEDT:PSS hybrid sensor
The piezoresistive properties are detected and tested by a group of the electrical signal test system and mechanical test setup present in Fig. 1c. The testing load range of the mechanical testing setup was 0.01–1000 N. The minimum detectable current of Keithley 2450 multi-source meter is 0.0001 nA. The sensitivity and performance of the fabricated sensor was calculated by using the equations below, and the respective abbreviations are given in Table 2.Table 2 Abbreviations of variables used in performance and sensitivity descriptions
Variable Meaning
ΔI Variable quantity of current
I Testing current
I0 Initial current
P Pressure
Performance
1 Performance=ΔII0
2 ΔI=I-I0
Sensitivity
3 Sensitivity=ΔII0P=PerformanceP
Sensor assembly have already been mentioned before. Each sensor is appropriately sealed as an independent unit. Each unit was connected with an extending wire (connect by sliver paste) for testing (in order to keep a distance from the testing site to avoid any disturbance). The sensor unit is placed on the mechanical testing device holder. The electrode ends were connected to Keithley multi-source meter. All the current and other values are read by this measure meter. Both values on the source meter and mechanical testing setup are sent to the computer. All tests were conducted under external power (voltage). The standard testing voltage is 0.5 V, which is used as default in all the tests if not explicitly mentioned.
In Fig. 2a a linear relationship between voltage and current is observed after curve fitting, with voltage ranging from −1.5 to 1.5 V. Under the same load (28 N ± 3 N or pressure is 280 Kpa) and voltage (0.5 V), 4 mg/ml group showed the highest current value (up to 460 μA) as depicted in Fig. 2b. Concurrently, the current of 2 mg/ml group was 72 μA only, and there was a 435 μA gap between 4 and 1 mg/ml. The initial current of 4 mg/ml was higher than in other groups. The initial currents were 1.48*10–10, 1.45*10–10, 1.97*10–06 nA for 1 mg/ml, 2 mg/ml, 4 mg/ml samples respectively. As displayed in Fig. 2c, 2mg/ml group showed the highest sensitivity (ΔII0) of 5.72043*105, where the performance of 4 mg/ml sample only reached around 25. For each concentration, we prepared at least 4 samples. It was observed that, as concentration goes lower, the coating tends to be nonuniform. As a result, under the same concentration, different samples produced different performances. Hence due to inconsistency in the performance and sensitivity, they cannot be utilized as reliable sensors.
Here, the nanofiber spacer helps in increasing the detection range. The spacer can create a gap between the foam and the interdigital electrode. It can isolate them and reduce the connection points, which helps in further increasing the resistance of the whole unit. This phenomenon can be explained as follows. The resistance of the overall device may be categorized into two segments: (i) Contact resistance between MXene-sponge and electrode and (ii) MXene-sponge resistance. In a static state, adding the nanofiber enhances the interface contact resistance between the electrode and MXene-sponge, improving device functionality. The contact area between the MXene-sponge and the electrode is minimal without pressure, resulting in a comparatively low current. When an external force is exerted, the resistance of the MXene-sponge effectively reduces on one hand of the human. In contrast, on the other hand, the contact area between MXene-sponge and electrode expands significantly, lowering contact resistance and increasing the output current. The current change versus pressure curves may be separated into two linear regions: low-pressure and high-pressure regions [16]. Before we added the spacer, the initial current of 4 mg/ml sample was 1.97*10–06 nA. After introducing it, the current was reduced to 1.2*10–11 nA, increasing the detecting range immediately. The design of a spacer makes the high conductivity no longer a limitation to the sensor sensitivity. To further improve its sensitivity, we added silver nanoparticles to Mxene solution and fabricated the Mxene@PEDOT:PSS@AgNps sensor. Figure 2d presents the sensitivity of the hybrid foam under different loads. With introduction of the spacer and more conductive materials, the performance of hybrid foam is increasing dramatically (performance, ΔII0 is presented by log function). The sensitivity increased and the detection range drastically broadened when compared to other existing piezoresistive sensor. Load limit that the sample can bear reached 977.6 N (surface area of the sensor is 1 cm2, equal to 9776 Kpa). This means that it can suffer an adult human weight easily. Figure 2e presents a curve between load and sensitivity. It was observed that when the load reached 700 N, the current increase rate was slower. When the load touched 817.8 N, the current almost hit the limit and stopped increasing.
Figure 2e also indicate that the increase of current almost follows a liner law. It can distinguish pressure levels clearly. In Fig. 2f it is represented that a minuscule load can also be detected by this sensor by using a more precise load meter of testing range between 0 and 10 N. The current was observed to go from 0.0558 to 0.37 nA and it kept increasing. The rapid increase of the current from 169 to 1060 nA in the beginning stops at 0.684 N. The current stabilizes and a steady increase when load surpass 0.684 N is observed. These results show high sensitivity in small load (0.417–0.684 N) and steady performance when applied a relatively higher load. To employ our sensor in different detecting ranges, we presented sensitivity ((ΔI/I0)P) of sensor in each range Fig. 2g. It has been divided into four Sects. 414.27 K Pa−1 at (4.17–12.98 K Pa), 182.52 K Pa−1 at (12.98–94.55 K Pa), 317.78 K Pa−1 at (94.55 K Pa–1.94 M Pa), 164.32 K Pa−1 at (> 1.94 M Pa). In the most conventional range, 94.55 K Pa to 1.94 M Pa, our sample presented a relatively good sensitivity. The highest sensitivity was found in the lower pressure range (4.17–12.98 K Pa), which can facilitate accurate and clear detection of tiny press/motion. A durability test is essential to evaluate the sensor lifespan. The good elasticity of the foam allows it to withstand thousands of pressing-releasing cycles. Our present Mxene@PEDOT:PSS@AgNps sensor could endure more than 5000 cycles. We performed 5 rounds of durability tests with each round consisting of 1000 cycles. Figure 2h displays this durability test and proves that the sensitivity remains the same after 5000 cycles. The current signal exhibits little attenuation and approximately the same amount of current variation after each compressing–releasing cycle, indicating that the device is stable and has an extended operational life. Here the response time was also observed to be consistent over the whole load range.
Material characterization
BET surface area was calculated using the adsorption data in a relative pressure (P/P0) range from 0.05 to 0.30. The total pore volume was assessed by converting the amount of nitrogen gas adsorbed at a relative pressure (P/P0) ≈0.99 to the volume of the liquid adsorbate. Pore size was calculated based on the adsorption isotherm by the Barret–Joyner–Halenda (BJH) model. The surface area was high for AgNps@Mxene@PEDOT:PSS ~ 1190.7 m2/g as shown in Fig. 3a–d, with the pore size of 2.4 nm followed by 800.21 m2/g for Mxene sheet, 253.2 m2/g for Ag Nps [53, 54]. The impurity level was low in AgNps@Mxene@PEDOT:PSS, as shown in Fig. 3e, with C, Ag, O and Ti corresponding to 64.81 wt%, 15.3 wt%, 8.4 wt%, 7.2 wt%. Traces of Mn, Fe and Al were also found [54].Figure 3 a BET of pure AgNps. b Composite coating (AgNps@Mxene@PEDOT:PSS). c Pure Mxene sheet. d PEDOT:PSS . e EDX element analysis of hybrid foam sensor. f XRD analysis. g FTIR of coating material with various surface functionalization (scanned from 400 to 4500 cm−1)
To access the structure of the hybrid foam sensor with coating materials, powder XRD of Mxene, Ag nanoparticles and Mxene@AgNPs powder obtained from hybridization were performed. XRD patterns of ultrasonicated 2D nanosheets of Mxene had similar peaks to that of hybrid Mxene@AgNPs. The characteristic peaks of the MXene at (104), (105), and (110) are observed in Fig. 3f. [55]Ag NPs XRD pattern (Fig. 3f) confirmed the FCC structure is attributed to the (111), (200), (220), and (311) crystallographic planes of the face-centred cubic silver crystals showing peaks at 2θ of 38.18°, 44.25°, 64.72°, and 77.40°respectively [56]. As the coatings were to serve the purpose of distinct layers on the foam, there should not be any reaction among Mxene and Ag NPs. The lack of any other new peaks at AgNPs@Mxene confirmed the absence of chemical reaction and other impurities.
The functional groups of delaminated MXene, Ag NPs, PEDOT:PSS and AgNPs@Mxene were analyzed by FTIR in attenuated total reaction mode (Fig. 3g). Spectrum of MXene shows distinctive peaks at 624, 1239, and 3463 cm−1 corresponding to Ti–O, –COOH, and –OH groups. [55]. In Fig. 3g FTIR spectra of silver nanoparticles exhibited prominent peaks at 1384, and 3429 cm−1, corresponding to –H and C–C; C–N stretching [57]. PEDOT:PSS FTIR spectrum shows peaks at 578 and 3409 analogous to C–S and C = C stretching. The slight shift in the peak positions of AgNPs@Mxene attributes to the OH/H2O adsorption.
The SEM image verifies the fiber network structure of the foam (Fig. 4a). Once the MAX phase is converted to Mxene, the Mxene sheets are stacked closely. This can be observed in Fig. 4b. They were then processed further to segregate the layers. Mxene 2D nanosheets that have been separated by ultrasonication have a larger surface area, as shown in Fig. 4c. Ag nanoparticles were evaluated to ensure equal distribution, lack of agglomeration, and moisture absorption (Fig. 4d). Figure 4e shows PEDOT:PSS, Mxene, and Ag nanoparticles coated and connected to a foam framework. Figure 4f shows the SEM image of a PVDF-HFP nanofiber spacer. The nanofiber's diameter was measured to be between 200 and 300 nm Fig S4.Figure 4 a 3D structure of hybrid foam. b 2D Mxene sheet without ultrasonication. c Mxene sheets after ultrasonication. d Silver nanoparticles (AgNps). e AgNps and Mxene sheet attach on foam skeleton. f PVDF-HFP nanofiber network
AgNps@Mxene@PEDOT:PSS foam sensor for human motion monitoring and heat mapping
Benefitting from high sensitivity and detecting range, we employed the hybrid sensor for detecting human body motion ranging from tiny pressure of the pulse to as high as human weight. A random finger pressing test (pressing with different pressure, frequency and holding time) was carried out to verify the piezoresistive property of the foam (Fig. 5a). Sensor was placed at different joints of the human body; the location is placed inset to the readings. Relative to the bending and pressure suffered, varying current has been observed to be generated.Figure 5 Hybrid foam sensor-based human body motion monitoring and heat map (a) finger press in different frequency (b) Front side elbow bending test (sensor is pasted on inner side of elbow). c Back side elbow bending test (sensor is pasted on outside of elbow). d Wrist band. e Finger banding angle detecting. f Real-time artificial pulse wave monitoring, plus here is 90 times per min. Hybrid foam sensor based human body motion monitoring and heat map. g Practical pressure map, start from circuit design to generate heat map
The type of force exerted by the human body is not singular but rather a complex mixture of pressure, strain, and torque, so we placed the sensor on the opposite side of the elbow as well as at the elbow along with the wrist and finger joints. The performance observed was an average peak of 2.2*102 nA (Fig. 5b), 7.0*10 nA (Fig. 5c) and 90 nA (Fig. 5d), respectively, for either side of the elbow and wrist joint. A clear depiction of varying output current with the difference in bending angle (45°, 75°, 90°) at the finger joint has been represented (Fig. 5e). For a 23-year-old male, a steady pulse was detected and noted to be 80 times/min approximately (Fig. 5f) which was within range of 70 to 90 times/min for a healthy human.
We have also designed a simple 3*3 matrix circuit with the interdigitated electrode to fabricate real-time 2D detection map, as shown in (Fig. 5g). We sealed 9 samples of Mxene@PEDOT:PSS@AgNps foam on this circuit to generate a pressure heat map. We put different coins and a tiny plastic container on top of each sample on the circuit. It was noticed that the current output was different when different loads were applied. The figure shows that pixelated sensor arrays are able to monitor the weight laid on the matrix. All the objects are taken from daily life, coins and plastic box possess different weights, and a corresponding heat map was generated. The coins chosen were from 10 cents to 1 Singapore dollar (SGD). One dollar coin is placed on the left side of the matrix, which is the heaviest. The height of each pi xel bar on a reconstructed map corresponding to the object distribution can be used to calibrate specific weight. This pressure sensor matrix might possibly be used in human–machine interactions, e.g., keyboards, especially super silent keyboards, since foam does not generate any noise.
We performed a series of pressure testing. The first one was the grip (squeeze) test presented in Fig. 6a. In the grip test by Mathiowetz V et al., they suggested that a healthy young woman aged between 20 and 24 could generate 70.4 pounds on average (equal to 313.28 N approximately) by grabbing, this was hundred times than finger joint bending. (in our testing, test by a young female student in this age range) [58]. A short and clean peak was observed in the test with a testing subject of a similar demographic Fig. 6a when we squeezed and released the hybrid foam sensor periodically. To further test the limit of our sensor, we performed walking tests and human body weight testing. As shown in Fig. 6b, the walking test was divided into two parts, forward and backward motion. The backward direction showed a broader peak because the hold time is usually higher (people are less skilled in walking backwards). Each step had a longer hold and the total walking period (numbers of steps are the same in both walking directions) was more as well. The detecting limit of our hybrid sensor is 977.6 N, which converts 97.76 kg. This detecting range is sufficient for human body weight detection. Three distinctive peaks in Fig. 6c correspond to different body weights 67 kg, 85 kg, 70 kg, respectively, of the subjects that took part in the experiment. One foot was lifted in the air, and we tried to apply whole body weight to the sensor.Figure 6 a Grip test b Forward and backward motion monitoring (sensor is pasted on bottom of foot). c Human body weight detecting test. d Hybrid foam-based LED circuit (e–f) different pressure level applied on the foam sensor and its corresponding output
Another test facilitating the piezoresistive property of the sensor is a continuously variable switch Fig. 6d. Sensor is the switch itself. The resistance of the sensor will change when the external force is applied. This property can control the current value in the circuit and further affect the brightness of the LED. Here, we designed a circuit to achieve this correlation of brightness and resistance. The change in brightness of the green LED diode with increasing pressure can be observed in Fig. 6e–g. Other colored LED diodes have also been tested, as shown in Fig. S5.
Conclusion
In summary, this hybrid sensor can be fabricated on a large scale with the facile dip-coating method, which is economical and quick. Due to the flexibility and elasticity of melamine foam, commercial melamine foam is used as the substrate to carry PEDOT:PSS@Mxene@AgNps mixture. Our sensor can be attached to human skin comfortably. And the unique structure with nanofiber spacer eliminates the limitation of conductivity, in turn providing a large detecting range for hybrid sensor (from 0.417 to 817.8 N). It was further verified by human body weight testing. At the same time, a low detection limit of 0.417 N allows the sensor to detect pulse steadily and easily. Based on these excellent characteristics of hybrid foam, we believe it can be utilized in the healthcare industry, such as human motion monitoring, weight measuring, and an electronic skin. Detailed fabrication process and working mechanism is provided in supplementary data.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 2742 KB)
Supplementary file2 (MOV 60171 KB)
Supplementary file3 (MOV 115790 KB)
Supplementary file4 (MP4 1086 KB)
Acknowledgements
This work was supported by the Sustainable Tropical Data Center: R265000A50281; NUS COVID-19 Research Seed Funding NUSCOVID19RG-11: R265000A01133
Author contributions
YZ helped inconceptualization, methodology, writing original draft preparation. VSR contributed to writing writing-reviewing and editing, testing, investigation. BR performed resources, modifications. SR supervised the study.
Declarations
Conflict of interest
There is no conflict of interests to disclose.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734898 | NO-CC CODE | 2022-12-15 23:15:22 | no | J Mater Sci. 2022 Dec 7; 57(48):21960-21979 | utf-8 | J Mater Sci | 2,022 | 10.1007/s10853-022-08012-y | oa_other |
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J Assist Reprod Genet
J Assist Reprod Genet
Journal of Assisted Reproduction and Genetics
1058-0468
1573-7330
Springer US New York
36469256
2673
10.1007/s10815-022-02673-z
Gamete Biology
A comprehensive investigation of human endogenous retroviral syncytin proteins and their receptors in men with normozoospermia and impaired semen quality
Tas Gizem Gamze 1
Soygur Bikem 12
Kutlu Omer 3
http://orcid.org/0000-0002-1801-2021
Sati Leyla [email protected]
1
1 grid.29906.34 Department of Histology and Embryology, Akdeniz University School of Medicine, 07070 Antalya, Turkey
2 grid.266102.1 0000 0001 2297 6811 Department of Obstetrics, Gynecology and Reproductive Sciences, Center for Reproductive Sciences, Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA USA
3 grid.29906.34 Department of Urology, Akdeniz University School of Medicine, Antalya, Turkey
5 12 2022
115
27 7 2022
25 11 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Purpose
The study aims to investigate first the presence of Syncytin 2 and its receptor, MFSD2, in human sperm, and second whether the expressions of Syncytin 1, Syncytin 2, and their receptors, SLC1A5 and MFSD2, differ between normozoospermic, asthenozoospermic, oligozoospermic, and oligoasthenozoospermic human sperm samples.
Methods
The localization patterns and expression levels of syncytins and their receptors were evaluated in normozoospermic (concentration = 88.9 ± 5.5 × 106, motility = 79.2 ± 3.15%, n = 30), asthenozoospermic (concentration = 51.7 ± 7.18 × 106, motility = 24.0 ± 3.12%, n = 15), mild oligozoospermic (concentration = 13.5 ± 2.17 × 106, motility = 72.1 ± 6.5%, n = 15), moderate oligozoospermic (concentration = 8.4 ± 3.21 × 106, motility = 65.1 ± 8.9%, n = 15), severe oligozoospermic (concentration = 2.1 ± 1.01 × 106, motility = 67.5 ± 3.2%, n = 15), and oligoasthenozoospermic (concentration = 5.5 ± 3.21 × 106, motility = 18.5 ± 1.2%, n = 15) samples by immunofluorescence staining and western blot.
Results
Syncytins and their receptors visualized by immunofluorescence showed similar staining patterns with slight staining of the tail in all spermatozoa regardless of normozoospermia, asthenozoospermia, oligozoospermia, or oligoasthenozoospermia. The localization patterns were categorized as equatorial segment, midpiece region, acrosome, and post-acrosomal areas. The combined staining patterns were also detected as acrosomal cap plus post acrosomal region, the midpiece plus equatorial segment, and midpiece plus acrosomal region. However, some sperm cells were categorized as non-stained. Both syncytin proteins were most intensely localized in the midpiece region, while their receptors were predominantly present in the midpiece plus acrosomal region. Conspicuously, syncytins and their receptors showed decreased expression in asthenozospermic, oligozoospermic, and oligoasthenozoospermic samples compared to normozoospermic samples.
Conclusion
The expression patterns of HERV-derived syncytins and their receptors were identical regardless of the spermatozoa in men with normozoospermia versus impaired semen quality. Further, asthenozoospermia, oligozoospermia, and oligoasthenozoospermia as male fertility issues are associated with decreased expression of both syncytins and their receptors.
Keywords
Syncytin 1
Syncytin 2
MFSD2
SLC1A5
Human sperm
Akdeniz Üniversitesi, The Scientific Research Projects Coordination UnitTSA-2021-5689 Sati Leyla
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pmcIntroduction
Membrane fusion is a fundamental process in multicellular organisms important for many events in reproduction, immune reactions, and neurotransmission [1]. Therefore, understanding the mechanism of membrane fusion is essential to understanding several biological processes that can lead to disease [2]. Despite the common features of membrane fusion across different organisms, tissue-specific mechanisms of membrane fusion may vary and have not been fully elucidated [1, 3, 4].
During fertilization, a series of membrane fusion events are required to ensure this process and placenta formation. It occurs through the interaction of spermatozoa and the cumulus-oocyte complex, adhesion, attachment, penetration of spermatozoa into the zona pellucida, and membrane fusion of oocyte and sperm cells. In fact, mammalian fertilization has been extensively studied for many years to discover key factors to elucidate the molecular mechanisms underlying sperm and oocyte fusion [3]. In recent years, especially the discovery of the clustered regularly interspaced short palindromic repeat-knock out (CRISPR-KO) system has enabled the efficient screening and investigation of genes responsible for male fertility in vivo [5]. Four essential factors of the sperm and oocyte fusion have been identified; CD9 and JUNO are expressed in oocytes while modulating female fertility, whereas IZUMO1 and fertilization-affecting membrane protein (FIMP) regulate fusion in sperm [6–8]. In addition to these molecules, other molecules have been identified that participate in membrane fusion on oolemma (integrins, GPI-1-associated protein) and spermatozoa (disintegrin and a metalloprotease (ADAM) [8–10]. Integrins have also been described to participate in sperm-oocyte adhesion [11, 12]. The use of CRISPR-Cas9 technology has led to the recent identification of six new factors as essential factors required for mammalian fertilization: sperm oocyte fusion required protein 1 (SOF1), sperm acrosome membrane–associated protein 6 (SPACA6), transmembrane protein 95 (TMEM95), fertilization influencing membrane protein (FIMP), and dendrocyte expressed seven transmembrane protein domain-containing 1 and 2 (DCST1/2) [5, 6, 13]. However, the details of sperm-oocyte interactions remain a relative mystery despite many decades of research and new discoveries of many candidate molecules.
Human endogenous retroviruses (HERVs) are RNA viruses that can infect the human germline [14–17]. They first entered the primate genome between 25 and 40 million years ago, reviewed by our group [18] and others [15, 16, 19–21]. The HERV family is a class 1 viral fusion protein, akin to those found in viruses such as coronaviruses, influenza viruses, Ebola virus, Lassa virus, and human immunodeficiency virus [22]. HERVs make up about 8% of the human genome [14]. Although most of these viruses have been eliminated through mutations and deletions, some members have been evolutionarily conserved and maintain their expressions. Among these genes, particularly two key genes have been determined to induce cell–cell fusion and placenta formation in humans [23]. These genes encode HERV-W Env glycoprotein (Syncytin 1) [19, 24–26] and HERV-FRD Env glycoprotein (Syncytin 2) [27]. Syncytin 1 is introduced in human syncytiotrophoblasts, and its fusogenic activity is demonstrated in cytotrophoblasts [24]. It induces syncytium formation in placenta by interacting with the D-Type mammalian retrovirus receptor (ASCT2, SLC1A5, neutral amino acid transporter) [25, 28]. Therefore, Syncytin 1 is increasingly expressed in syncytiotrophoblast cells throughout pregnancy [24, 25, 29]. On the other hand, Syncytin 2 (HERV-FRD) is another member of the HERV family with fusogenic activities as a placental membrane protein [27, 30]. While syncytins induce cell fusions, their physiologic roles may go beyond that, for instance Syncytin 1 may also regulate the production of inflammatory mediators [31]. Syncytin 2 differs from Syncytin 1 by having an immunosuppressive domain that potentially plays a role in the protection of fetus from the maternal immune system [27, 30] and by interacting with a different receptor, major facilitator superfamily domain containing 2 (MFSD2), to mediate cell–cell fusion [32].
Altered expressions of syncytin proteins and their receptors were reported in various placental pathologies such as preeclampsia [33, 34], intrauterine growth restriction (IUGR) [35–37], and gestational diabetes mellitus [38, 39]. In addition to their fusogenic activity in placenta, syncytins are involved in cell fusion events in bone marrow (osteoclasts) [40], various cancers [41–49], and in different cell lines such as muscle [50], endometrial [45], colorectal [51], and breast tumor [52].
Considering the well-studied fusogenic activity of syncytin proteins, Bjerregaard and colleagues investigated the presence of Syncytin 1 and its receptor in human gametes [53]. The study revealed that Syncytin 1 is expressed at both mRNA and protein levels in human spermatozoa. The localization of Syncytin 1 is mainly observed in the acrosomal region or equatorial segment of spermatozoa together with mild expression in the midpiece and the tail. Its receptor, SLC1A5, is expressed in the acrosomal and tail regions of spermatozoa. Interestingly, Syncytin 1 expression is not detected in human oocytes, while its receptor SLC1A5 is present in oocytes [53]. However, samples with only normal semen quality were included. In line with this study, Enoiu and colleagues investigated Syncytin 1 and other membrane fusion proteins in spermatozoa from men experiencing total fertilization failure during IVF by immunofluorescence [54]. The authors reported a similar localization pattern with previous study by Bjerregaard and colleagues that Syncytin 1 was present predominantly in the acrosomal cap region and also slightly in the midpiece and tail regions of human sperm [54]. Bergallo and colleagues also showed that there are several retroviral mRNAs including Syncytin 1 in the human sperm, although in low amounts [55]. However, to the best of our knowledge, there is only one study available regarding the presence of Syncytin 2 in human sperm showing that Syncytin 2 is transcribed in spermatozoa, although at lower levels than Syncytin 1 by real-time PCR experiments at mRNA level [55]. Thus, no information is currently available on the localization patterns of Syncytin 2 or the existence of its receptor in human gametes.
One of the most serious social problems faced by developed countries today is the decreasing fertility rate. Impairment of male fertility may occur in the case of insufficient number of motile sperm, unsuccessful sperm-zona pellucida interaction, incomplete acrosome reactivity, and insufficiency of sperm function such as oocyte penetration [56]. However, assessment of male infertility potential is based on standard semen analysis (total sperm number, total and progressive motility, vitality, sperm concentration, sperm morphology) [57]. According to the World Health Organization, men whose sperm parameters are below normal values are considered to have male factor-related infertility [58]. Oligozoospermia is a male reproductive problem characterized by low sperm counts, and the sperm concentrations that drop below 15 million sperm per milliliter in the semen sample. Severe oligozoospermia is often accompanied by poor sperm motility, viability, and morphology reflecting qualitative and quantitative defects in spermatogenesis [59–61]. Natural fertility prospects are also poor with extreme oligozoospermia [59, 60]. In addition, there is an increased incidence of total fertilization failure and a low fertilization rate during conventional in vitro fertilization treatments involving men with poor sperm motility [62, 63]. Given the high fusogenic potential of syncytin proteins, our study aimed to investigate first the presence of Syncytin 2 and its receptor, MFSD2, in human sperm, and then, to evaluate whether the protein localization patterns and expression levels of syncytins and their receptors differ between normozoospermic, asthenozoospermic, oligozoospermic, and oligoasthenozoospermic human sperm samples.
Materials and methods
Selection of study samples
After routine semen analyses at the Andrology Laboratory, Department of Urology, Akdeniz University School of Medicine, Antalya, Turkey, the leftover de-identified semen samples were studied. Normozoospermic (concentration = 88.9 ± 5.5 × 106, motility = 79.2 ± 3.15, n = 30), asthenozoospermic (concentration = 51.7 ± 7.18 × 106, motility = 24.0 ± 3.12, n = 15), oligozoospermic, and oligoasthenozoospermic (concentration = 5.5 ± 3.21 × 106, motility = 18.5 ± 1.2%, n = 15) human sperm samples were included in the study. Oligozoospermia was further classified as mild oligozoospermia (between 10 and 15 million sperm/mL), moderate oligozoospermia (between 5 and 10 million sperm/mL), and severe oligozoospermia (less than 5 million sperm/mL) [64]. The comparisons of mild oligozoospermic (concentration = 13.5 ± 2.17 × 106, motility = 72.1 ± 6.50%, n = 15), moderate oligozoospermic (concentration = 8.4 ± 3.21 × 106, motility = 65.1 ± 8.9%, n = 15), and severe oligozoospermic (concentration = 2.1 ± 1.01 × 106, motility = 67.5 ± 3.2%), n = 15) sperm samples were also performed. The average ages of the patients in the normozoospermic, asthenozoospermic, mild oligozoospermic, moderate oligozoospermic, severe oligozoospermic, and oligoastenozoospermic groups were 38.00 ± 1.48, 36.00 ± 1.08, 37.00 ± 2.55, 35.00 ± 1.88, 38.00 ± 1.53, and 36.00 ± 1.15, respectively. However, there was no statistically significant age difference between the patient groups (p = 0.357). The samples were collected by masturbation into sterile wide mouth plastic jars following 2–5 days of sexual abstinence. Samples were allowed to liquefy at room temperature; then, sperm concentrations and motility were assessed according to WHO criteria 2010 [65]. Patients with ages of 18–40, sperm count not less than 1 million, the duration of sexual abstinence not less than 2 days or more than 5 days, have no known health problem, cancer, urogenital or genetic disease, no drug used continuously that can affect sperm parameters recently, those who have not received any treatment or surgery in the past due to the male factor, no chronical use of cigarettes, alcohol, and addictive substances were included in the study. All studies were approved by Ethical Committee of Akdeniz University School of Medicine (2012-KAEK-20).
Preparation of sperm samples and immunofluorescence staining
The preparation of sperm samples was carried out similarly as previously reported [66–68]. A sufficient amount of saline-imidazole (SAIM) solution was added to the fresh semen and centrifuged at 500 g for 18 min. After discarding the supernatant, 1–2 ml of SAIM solution was added to the pellet and resuspended. Small drops of suspension were placed on Poly-L-lysine-coated slides drawn with pap-pen, and 5% PB-sucrose (PBS + sucrose) solution was dripped onto it, paying attention to the absence of excessive sperm under the microscope. The slides were kept at + 4 °C overnight. The next day, the solution on the slides was removed, fixation solution was dripped onto the slides and kept at room temperature for 20 min. The excess solution was removed, and PB-sucrose solution was dripped 3 times on the slides. In the last step, the PB-sucrose solution was removed, and the slides were dried at room temperature.
Slides were washed three times with PB-sucrose at room temperature and blocked with 3% bovine serum albumin (BSA) for 1 h at room temperature. Primary antibodies (syncytin 1, syncytin 2, SLC1A5 and MFSD2) were diluted with 0.1% BSA and incubated at + 4 °C overnight (Table 1). Samples were washed three times with PB-sucrose at room temperature and incubated with secondary antibodies for 45 min at room temperature (Table 1). Following the washing step, slides were incubated with fluorescein isothiocyanate (FITC)-labeled Avidin D (Vector Laboratories) diluted in PB-sucrose for 30 min at room temperature. After washing with PB-sucrose, DAPI solution was added and the slides were kept in the dark for 10 min, washed with PB-sucrose solution three times for 5 min and mounted with antifade solution. Samples were left in the dark for 1–2 h and examined using a fluorescent microscope (Olympus BX61 Fully Motorized Fluorescence Microscope). At least 200 sperm cells were counted from each patient, and sperm cells were categorized according to their staining patterns as previously described [69].Table 1 Primary and secondary antibodies used for immunofluorescence (IF) staining and Western blot
Protein extraction from semen samples
The volume, concentration, and motility of freshly collected semen samples were calculated. Up to 10 ml of PB-sucrose solution was added to the tubes containing semen samples, centrifuged at + 4 °C, 2500 rpm for 10 min. The pellets of sperm samples were resuspended in lysis buffer and protease inhibitor cocktail (Sigma-Aldrich, MO, USA), further incubated, and homogenized by using a sonicator. After 1 h of incubation at + 4 °C, samples were centrifuged for 15.000 g at + 4 °C. The supernatants were collected, and stored at − 20 °C.
SDS-PAGE and Western blotting
Immunoblotting of semen samples was carried out as previously described [70]. The protein concentration was determined by a detergent compatible protein assay (Bicinchoninic Acid Kit for Protein Determination BCA1-1KT, Sigma). Samples (50 µg) were loaded on 10% Tris–HCl gels, electrophoretically separated, and electroblotted onto PVDF membrane (Bio-Rad Laboratories, CA, USA). The membranes were blocked with 5% non-fat dry milk in Tris buffered saline (TBS) containing 0.1% Tween 20 (TBS-T) for 1 h to reduce non-specific binding. The membranes were incubated at + 4 °C overnight with primary antibodies (Table 1), washed in TBS-T for 1 h then incubated with horseradish peroxidase (HRP) conjugated secondary antibodies for 1 h at room temperature. Following the final wash in TBS-T, the membranes were incubated with the Super Signal Chemiluminescence (CL)-HRP substrate system (Thermo Scientific, USA) for 5 min and the signals on the membranes were transferred to the hyperfilm (Amersham Biosciences; Buckinghamshire, England) in the dark room. Protein levels of syncytin 1, syncytin 2, SLC1A5, and MFSD2 were compared semiquantitatively with ImageJ 1.46 (NIH) analysis by normalizing to GAPDH.
Statistical analysis
All data was exported directly to the SigmaStat® 3.5 (Systat Software; San Jose, USA) program. The data obtained from patients with different impaired semen quality groups were compared with the data obtained from normozoospermic patient groups. The quantitative data was submitted to normality tests by the Kolmogorov–Smirnov test. Data were compared using one-way ANOVA followed by Holm–Sidak post hoc test for the data passed the normality test; otherwise, the Kruskal–Wallis test was followed by Dunn’s test. All data were expressed as mean ± SEM and statistical significance was defined as p < 0.05.
Results
Immunolocalization of Syncytin 1 and its receptor SLC1A5 in normozoospermic, asthenozoospermic, oligozoospermic, and oligoasthenozoospermic human sperm samples
Detailed immunocytochemical analysis revealed similar localization pattern for Syncytin 1 and SLC1A5 with a slight staining of the tail in all spermatozoa. Both proteins were also localized in the regions of (1) the equatorial segment, (2) the acrosomal cap, (3) the post acrosomal region, (4) the acrosomal cap plus post acrosomal region, (5) the midpiece plus equatorial segment, (6) the midpiece region, and (7) the combined midpiece plus acrosomal region (Fig. 1). Comparison of the expression these patterns between normozoospermic, asthenozoospermic, oligozoospermic (mild, moderate, severe), and oligoasthenozoospermic samples revealed differences with varying percentages. There was a decreased percentage of Syncytin 1 immunoreactivity in the equatorial segment, the acrosomal cap, the midpiece plus equatorial segment, only the midpiece region, and the combined midpiece plus acrosomal region of asthenozoospermic and oligoasthenozoospermic sperm samples when compared to normozoospermic sperm samples (p < 0.001) (Fig. 2a, b, g). A significant decrease was detected in the percentage of sperm with the post acrosomal region and the acrosomal cap plus post acrosomal region staining patterns in the oligoasthenozoospermic sperm samples compared to the normozoospermic sperm samples (p < 0.05) (Fig. 2g). On the other hand, we found a significant decrease in the percentage of acrosomal cap, only the midpiece region, the combined midpiece plus acrosomal region staining patterns and unstained sperm in oligoasthenozoospermic sperm samples compared to asthenozoospermic sperm samples (p < 0.001) (Fig. 2g).Fig. 1 Immunofluorescence staining patterns of syncytins and their receptors. a The equatorial segment, b the acrosomal cap, c the post acrosomal region, d the acrosomal cap plus post acrosomal region, e the midpiece plus equatorial segment, f the midpiece region, g the combined midpiece plus acrosomal region, h non-stained sperm. Green: FITC; blue: DAPI. The scale bars represent 50 µm
Fig. 2 Immunofluorescence localization of Syncytin 1 (a, b, c) and its receptor SLC1A5 (d, e, f) in normozoospermic, asthenozoospermic, and oligozoopermic human sperm samples. The percentage (%) of immunofluorescence staining patterns for Syncytin 1 (g, i) and SLC1A5 (h, j). Eq, equatorial segment; Acr, acrosomal cap; Post Acr, post acrosomal region; Acr + Post Acr, acrosomal cap and post acrosomal region; Mp + Eq, midpiece region and equatorial segment; Mp, midpiece region; Mp + Acr, midpiece region and acrosomal cap; NS, non-stained sperm. Green: FITC; blue: DAPI. The scale bars represent 50 µm. p values indicate the statistical comparisons between the sperm samples with normozoospermia and different patient categories. #p < 0.05, *p < 0.001
Regarding oligozoospermic sperm samples, we detected a decreased percentage of Syncytin 1 immunoreactivity in the equatorial segment, the acrosomal cap, the midpiece plus equatorial segment, only the midpiece region, and the combined midpiece plus acrosomal region of all oligozoospermic sperm samples when compared to normozoospermic sperm samples (p < 0.001) (Fig. 2a, c, i). On the other hand, a significant decrease was observed in both moderate and severe oligozoospermia groups compared to the mild oligozoospermia group especially in the midpiece region and combined midpiece plus acrosome region staining patterns (p < 0.001) (Fig. 2i). The decrease in the severe oligozoospermia was also statistically significant for the percentages of midpiece region and combined midpiece plus acrosome region staining compared to the percentages for moderate oligozoospermia (p < 0.001). In addition, a significant decrease was determined in the staining patterns of the midpiece plus equatorial segment, and the percentage of non-stained sperm in the severe oligozoospermia group compared to the mild and moderate oligozoospermia patient groups (p < 0.001) (Fig. 2i) even though no significant differences were found between the mild and moderate oligozoospermia groups for these localization patterns (p > 0.05) (Fig. 2i).
SLC1A5 immunoreaction was significantly decreased in the equatorial segment, the acrosomal cap, the midpiece plus equatorial segment, only the midpiece region, and the combined midpiece plus acrosomal region of asthenozoospermic and oligoasthenozoospermic sperm samples compared to the normozoopermic sperm samples (p < 0.001) (Fig. 2d, e, h). Moreover, there was a significant decrease in the percentage of the midpiece region and the combined midpiece plus acrosomal region staining patterns in oligoasthenozoospermic sperm samples compared to asthenozoospermic sperm samples (p < 0.001) (Fig. 2h). In contrast, no significant difference was observed in the percentage of the post acrosomal region, the acrosomal cap plus post acrosomal region staining patterns and the percentage of non-stained sperm between these patient categories (p > 0.05) (Fig. 2h).
Similarly, a statistically significant decrease in SLC1A5 expression was detected for the percentage of equatorial segment, the acrosomal cap, only the midpiece region, and the combined midpiece plus acrosomal region staining patterns in all of the oligozoospermic sperm samples compared to the normozoospermic samples (p < 0.001) (Fig. 2d, f, j). When the subcategories of oligozoospermic patients were compared, a significant decrease was determined in both moderate and severe oligozoospermia patient groups compared to the mild oligozoospermic patient groups in the midpiece region and combined midpiece plus acrosome region localization patterns (p < 0.001) (Fig. 2j). The decreased percentage of staining patterns in the midpiece region and combined midpiece plus acrosome region were also statistically significant in the severe oligozoospermia compared to moderate oligozoospermia (p < 0.001) (Fig. 2j). In fact, there were no statistically significant differences in the percentage of staining patterns for post acrosomal region, the acrosomal cap plus post acrosomal region, and the percentage of non-stained sperm (p > 0.05) (Fig. 2j).
Immunolocalization of Syncytin 2 and its receptor MFSD2 in normozoospermic, asthenozoospermic, oligozoospermic, and oligoasthenozoospermic human sperm samples
Syncytin 2 and its receptor MFSD2 proteins were detected in (1) the equatorial segment, (2) the acrosomal cap, (3) the post acrosomal region, (4) the acrosomal cap plus post acrosomal region, (5) the midpiece plus equatorial segment, (6) the midpiece region, and (7) the combined midpiece plus acrosomal region (Fig. 1) in the sperm samples from normozoospermic, asthenozoospermic, oligozoospermic (mild, moderate, severe), and oligoasthenozoospermic patients (Fig. 3). As observed in Syncytin 1 and SLC1A5, a slight staining of the tail were also noted for Syncytin 2 and its receptor MFSD2 in all spermatozoa. The immunoreaction of Syncytin 2 was found to be most prominent in the midpiece region of human sperm among the different staining patterns. In contrast, MFSD2 immunoreaction was predominantly observed in the combined midpiece plus acrosomal region as well as in the midpiece region of sperm.Fig. 3 Immunofluorescence localization of Syncytin 2 (a, b, c) and its receptor MFSD2 (d, e, f) in normozoospermic, asthenozoospermic, and oligozoopermic human sperm samples. The percentage (%) of immunofluorescence staining patterns for Syncytin 2 (g, i) and MFSD2 (h, j). Eq, equatorial segment; Acr, acrosomal cap; Post Acr, post acrosomal region; Acr + Post Acr, acrosomal cap and post acrosomal region; Mp + Eq, midpiece region and equatorial segment; Mp, midpiece region; Mp + Acr, midpiece region and acrosomal cap; NS, non-stained sperm. Green: FITC; blue: DAPI. The scale bars represent 50 µm. p values indicate the statistical comparisons between the sperm samples with normozoospermia and different patient categories. #p < 0.05, *p < 0.001
When asthenozoospermic and oligoasthenozoospermic sperm samples were compared to the normozoospermic sperm samples by means of Syncytin 2 immunoreactivity, there was a decreased percentage of staining patterns in the equatorial segment, the acrosomal cap, the midpiece plus equatorial segment, only the midpiece region, and the combined midpiece plus acrosomal region of asthenozoospermic and oligoasthenozoospermic sperm samples (p < 0.001) (Fig. 3a, b, g). A significant decrease was detected in the percentages of sperm stained for post acrosomal region (p = 0.003) and the acrosomal cap plus post acrosomal regions (p = 0.034) compared to the normozoospermic groups in the only oligoasthenozoospermic patient group (Fig. 3g). A significant decrease in the percentage of sperm with acrosomal cap, the midpiece region and the combined midpiece plus acrosomal region staining patterns was detected in oligoasthenozoospermic samples compared to asthenozoospermic sperm samples (p < 0.001) (Fig. 3g). In contrast, we observed no significant difference in the percentage of the non-stained sperm between these patient groups (p > 0.05) (Fig. 3g).
Syncytin 2 immunoreaction was significantly decreased in the equatorial segment, the acrosomal cap, the midpiece plus equatorial segment, only the midpiece region, and the combined midpiece plus acrosomal region of all oligozoospermic sperm samples with different subcategories when compared to normozoospermic sperm samples (p < 0.001) (Fig. 3a, c, i). However, a significant decrease was observed particularly in the percentages of midpiece region and combined midpiece plus acrosome region in both moderate and severe oligozoospermia groups compared to the mild oligozoospermia patient group (p < 0.001) (Fig. 3i). The statistical evaluation was also indicated a significant decrease in severe oligozoospermia samples compared to moderate oligozoospermia samples for these staining patterns (p < 0.001) (Fig. 3i). Furthermore, there was a significant decrease in percentage of the post acrosomal region and the acrosomal cap plus post acrosomal region in severe oligozoospermic sperm samples compared to normozoospermic sperm samples while no difference was detected in the mild or moderate oligozoospermic sperm samples (p < 0.001) (Fig. 3i). As observed with asthenozoospermic and oligoasthenozoospermic sperm samples, we found no statistically significant difference in the percentage of non-stained sperm between different oligozoospermic patient subcategories and normozoospermic patient groups (p > 0.05) (Fig. 3i).
A statistically significant decrease in MFSD2 immunoreaction was observed in the equatorial segment (p < 0.001), the acrosomal cap (p < 0.001), the midpiece plus equatorial segment (p < 0.001), only the midpiece region (p < 0.001), and the combined midpiece plus acrosomal region (p < 0.001) in asthenozoospermic and oligoasthenozoospermic sperm samples and all of the oligozoospermic patient subcategories compared to the normozoospermic sperm samples (Fig. 3d, e, f, h, j). On the other hand, there was a statistically significant decrease in the percentage of the acrosomal cap, the midpiece region and the combined midpiece plus acrosomal region staining patterns in oligoasthenozoospermic samples compared to asthenozoospermic sperm samples (p < 0.001) (Fig. 3h). A significant decrease was also determined in the acrosomal cap, the midpiece region and combined midpiece plus acrosome region staining in both moderate and severe oligozoospermia patient groups compared to patients with the mild oligozoospermia (p < 0.001) (Fig. 3j). In addition, there was a significant decrease in the percentage of equatorial segment and the midpiece plus equatorial segment in the sperm samples from severe oligozoospermia group compared to samples from mild oligozoospermia (p = 0.018, p = 0.0145, respectively). We found a significant decrease in the post acrosomal region (p = 0.015) and the acrosomal cap plus post acrosomal region staining patterns (p = 0.002) in severe oligozoospermic sperm samples compared to normozoospermic sperm samples while no statistical difference was analyzed in mild and moderate oligozoospermic sperm samples (p > 0.05) (Fig. 3j). In contrast, there was no statistically significant difference between patient groups in the percentage of non-stained sperm for either men with oligozoospermia, asthenozoospermia or oligoasthenozoospermia (p > 0.05) (Fig. 3h, j).
Protein expression levels of syncytin proteins and their receptors in normozoospermic, asthenozoospermic, oligozoospermic, and oligoasthenozoospermic human sperm samples
Western blot analysis of Syncytin 1 (60 kDa) and its receptor SLC1A5 (54 kDa) showed a statistically significant decrease in the asthenozoospermic, mild, moderate, and severe oligozoospermic and oligoasthenozoospermic sperm samples compared to the normozoospermic sperm samples by ImageJ analysis (p < 0.001) (Fig. 4a, b). When patient groups were compared to each other, we found a statistically significant decrease in both Syncytin 1 and SLC1A5 protein expression in oligoasthenozoospermic sperm samples compared to asthenozoospermic sperm samples (p < 0.001) (Fig. 4a, b). On the other hand, Syncytin 1 protein expression was significantly decreased in both moderate and severe oligozoospermic sperm samples compared to the mild oligozoospermic group (p < 0.001) (Fig. 4a, b). The statistically significance decrease was also observed between in severe oligozoospermic sperm samples compared to moderate oligozoospermic sperm samples (p < 0.001) (Fig. 4a, b). SLC1A5 protein expression was decreased only in the severe oligozoospermic sperm samples compared to the mild oligozoospermic sperm samples (p = 0.024), but no significant difference was found between severe oligozoospermic sperm samples versus moderate oligozoospermic sperm samples or moderate oligozoospermic sperm samples versus mild oligozoospermic sperm samples (p > 0.05).Fig. 4 Western blot analysis of Syncytin 1 (60 kDa), Syncytin 2 (59 kDa), SLC1A5 (54 kDa), and MFSD2 (60 kDa) proteins in the human sperm samples (a). The expression of GAPDH (37 kDa) was used to confirm equivalent amounts of total proteins loaded per lane. The optical density (OD) values of relevant proteins were normalized to the OD values of GAPDH bands and then graphed (b, c). N, normozoospermia; A, asthenozoospermia; MIO, mild oligozoospermia; MO, moderate oligozoospermia; SO, severe oligozoospermia; OA, oligoasthenozoospermia. #p < 0.05, *p < 0.001
Syncytin 2 (59 kDa) and MFSD2 (60 kDa) protein expressions were found to be significantly decreased in the asthenozoospermic, mild, moderate, and severe oligozoospermic and oligoasthenozoospermic sperm samples compared to the normozoospermic sperm samples as observed for Syncytin 1 and its receptor (p < 0.001) (Fig. 4a, c). A statistically significant decrease in both Syncytin 2 and MFSD2 protein expression was observed in oligoasthenozoospermic sperm samples compared to asthenozoospermic sperm samples (p < 0.001) (Fig. 4a, c). When oligozoospermic patient groups were compared among themselves, Syncytin 2 protein expression showed a significant decrease in both the moderate and severe oligozoospermic groups compared to the mild oligozoospermic group (p < 0.001) (Fig. 4a, c). In addition, a significant decrease was determined in the severe oligozoospermic sperm samples compared to the moderated oligozoospermic sperm samples (p < 0.001) (Fig. 4a, c). Even though MFSD2 protein expression was decreased significantly in severe oligozoospermic group compared to mild oligozoospermic group (p < 0.001), and also severe oligozoospermic sperm samples compared to moderate oligozoospermic sperm samples, no significant difference was observed between mild and moderate oligozoospermic patient groups (p > 0.05) (Fig. 4a, c).
Discussion
Here, we demonstrate the detailed expression profiles of syncytin proteins and their receptors in normozoospermic, asthenozoospermic, oligozoospermic (mild, moderate, severe), and oligoasthenozoospermic human sperm samples and revealed a significant decrease in the expression of syncytin 1, syncytin 2, and their receptors, SLC1A5 and MFSD2, in the patients with asthenozoospermia, oligozoospermia, and oligoasthenozoospermia. Although the presence of Syncytin 1 [53–55] and its receptor SLC1A5 [53] was reported in human sperm, the potential contributions of altered syncytin protein levels to sperm parameters such as reduced sperm motility and low sperm count or both were not demonstrated previously. Considering the dramatic increase of male infertility all over the World [71], unveiling the underlying mechanisms that could potentially contribute to reduced fertility is critical to understand, and then to improve the fertility outcomes.
Bjerregaard and colleagues indicated that a strong Syncytin 1 expression was present in the sperm acrosome or the equatorial segment and a weak staining pattern was observed in the midpiece and tail regions [53]. Recently, a similar expression pattern was also reported by Enoiu and colleagues with visible diffusion to the entire head in all sperm samples [54]. While the expression of Syncytin 1 in the acrosome, equatorial segment, midpiece, and tail regions of sperm is similar to the previous studies, here, we demonstrated that there is a more complex expression profile of Syncytin 1 suggesting a heterogeneity in human spermatozoa.
In addition to its crucial role in placentation, Syncytin 1 appears to play a role in fertilization and implantation. Among the other endogenous retroviruses, the higher level of Syncytin 1 transcript in human sperm [55] supports the potential role of Syncytin 1 in oocyte-sperm fusion. Syncytins and their receptors were present in the equatorial segment which has considerable functional importance to fertilization. The equatorial segment is crucial as it remains intact after the acrosome reaction, underlies the domain of the plasma membrane involved in fusion with the oocyte membrane, and is the site where breakdown of the sperm nuclear envelope is initiated after fertilization [72]. Interestingly, the percentage of the positively stained sperm samples for the equatorial segment staining pattern were significantly decreased in patients with asthenozoospermia, all oligozoospermia patient subcategories (mild, moderate, severe), and oligoasthenozoospermia for syncytins and their receptors. In fact, the molecular basis of sperm-egg recognition is unknown, but is likely to require interactions between receptor proteins displayed on their surface [7]. Since the percentages of the unstained sperm were also striking, the competence or development potential of syncytin-expressing or non-expressing sperm should be investigated further by utilizing mouse homologous conditional knockout models of syncytins and their receptors to investigate whether they will be functionally related to male infertility. Therefore, the best way to reveal these molecular mechanisms is possibly to design mouse/animal models with partial or complete absence of syncytin 1, syncytin 2, or their receptors in gametes, and test them for fertilization capacity.
Furthermore, the expression of Syncytin 1 in the trophectoderm directly beneath the inner cell mass of human blastocysts [73] suggests that Syncytin 1 may play role in embryo implantation. The decreased expression of Syncytin 1 and its receptor may cause failure by negatively affecting fertilization and embryo growth and can be used as important biomarker molecules in the development of new strategies in IVF treatments. A recent study by Enoiu and colleagues investigated the fusion proteins including Syncytin 1 in spermatozoa from men in couples experiencing total fertilization failure during IVF [54]. However, the study reported that there were not any significant changes in the expression of Syncytin 1 between the total fertilization failure and control groups [54]. However, the number of spermatozoa expressing Syncytin 1 was found to be higher in the control group compared with total fertilization failure even though it was not statistically significant. Thus, high expression profile of Syncytin 1 may contribute to successful gamete membrane fusion, an important step in fertilization.
To the best of our knowledge, no information was available on the localization pattern of Syncytin 2 or its receptor in human gametes. Previously, Syncytin 2 has been shown transcribed in spermatozoa, although the transcription level was lower than Syncytin 1 [55]. However, we report here for the first time that Syncytin 2 is preferentially expressed in the midpiece and combined midpiece plus acrosomal regions. This high expression pattern associated with the sperm midpiece where mitochondria are located might indicate a metabolism related function of these proteins. Taken together, our data demonstrating the presence of Syncytin 2 and its receptor in human sperm further support the idea that Syncytin 2 might also contribute to gamete fusion during fertilization.
Unfortunately, there is only one study in the existing literature related to syncytins and its receptors in the oocyte reporting that Syncytin 1 receptor, ASCT-2, was expressed in oocytes with different stages of oocyte maturation including germinal vesicle (GV) and MI and MII stages [53]. The study with 80 oocytes indicated that there was a significantly higher expression of Syncytin 1 receptor in mature MII stage oocytes compared to the immature GV stage. Although the expression of Syncytin 1 was not present in any of the oocytes examined by quantitative RT-PCR [53], it seems that the mRNA level of Syncytin 1 receptor increases as the oocytes mature from the GV to the MII stage. Thereafter, one can speculate that the presence of the Syncytin 1 receptor on the oocytes may be utilized in pharmaceutical or culture related interventions as an indicator of the developmental competence of the oocytes [53]. However, the question still remains whether the fusogen Syncytin 1 and its receptor could be involved in membrane fusion of the human gametes since Syncytin 1 is present and localized at the right place in spermatozoa and Syncytin 1 receptor is present in the mature oocytes.
Syncytins, as noted, belong to an endogenous retrovirus family and can function as a true retroviral envelope protein [74–76]. Syncytin therefore has the ability to block its own receptor if co-expressed with its receptor [76]. In this study, we found that syncytin 1, syncytin 2, and their receptors were expressed in similar localization patterns on spermatozoa from different patient groups, but their percentages in these patterns were different. Therefore, it can be speculated that co-expression of Syncytin 1 and its receptor SLC1A5 or Syncytin 2 and its receptor MFSD2 on spermatozoa inhibit membrane fusion at the designated sites and act as a regulator of syncytins.
The most important function of the acrosome reaction is to induce changes in the sperm membrane [77]. Although SPACA6, TMEM95, SOF1, FIMP, and DCST1/DCST2 have been shown among the new proteins required for sperm-oocyte fusion that occurs after the acrosome reaction, the importance and roles of these protein interactions are not clear [8]. However, studies suggested that the previously discovered tetraspanins CD9 and CD81 both play an important role in fertilization [78] and participate in membrane fusion as regulators of fusion platforms for membrane fusion to occur [79]. Cell–cell fusion following the acrosome reaction is facilitated by the interaction of the oocyte plasma membrane with a highly localized area of the sperm plasma membrane lining the equatorial segment [9]. The demonstration of syncytin 1, Syncytin 2 and their receptors on the equatorial segment of spermatozoa all together conforms to this model proposed by Nixon and colleagues [9].
Furthermore, it is known that any structural or functional acrosomal abnormality can disrupt sperm fusion and ultimately cause infertility. Studies have shown that intra-cytoplasmic insemination with sperm containing acrosomal abnormalities does not lead to successful fertilization even in the absence of fertilization barriers, as the oocyte cannot be activated efficiently [80, 81]. Our immunofluorescence staining results showed that both syncytin 1, Syncytin 2 and their receptors were significantly reduced in the acrosome region in the asthenozoospermic, oligozoospermic and oligoasthenozoospermic sperm samples compared to normozoospermic sperm samples. Syncytin 1 has been previously reported to have a tendency to gather at the equatorial segment following progesterone-induction of the acrosome reaction suggesting a translocation of Syncytin 1 to the equatorial segment during the acrosome reaction and a potential involvement in this biological process [54]. It is likely that high expression of syncytins and their receptors may facilitate gamete membrane fusion, while low levels or absence of these proteins may suggest IVF treatments. Therefore, our study may have a significant impact on both clinical and research investigations of male fertility status and may advance our understanding of the role of these proteins in human health and fertility. The lower amount of these fusion proteins in patients with impaired semen quality may be an important marker for the evaluation of a man's reproductive potential with fertility implications.
Key events, including motility, capacitation, and acrosomal exocytosis, are important in the acquisition of fertilization ability by spermatozoa [82]. Low sperm count and/or quality is present in 90% of couples with fertility problems [83]. Oligozoospermic men have a very high rate of defective sperm-zona pellucida interactions, consistent with low natural fertility or low fertilization rates in conventional IVF [84]. On the other hand, the relationship between the degree of motility and the reproductive outcomes should also be emphasized. Sources of variability in sperm motility are found at different levels such as between sperm cells, ejaculates (from the same individual) and individuals [85]. It is also known that oxidative stress increases in samples with low sperm motility [86], and motility shows an inverse relationship with DNA fragmentation [87, 88]. Although controversial, extensive damage to sperm DNA can result in poor fertilization or embryo development rates and increased miscarriage rates [89–92]. In line with this, our data regarding the decreased expression of these fusogenic proteins and their receptors in the patients with asthenozoospermia, oligozoospermia, and oligoasthenozoospermia may lead to reduced fertilization success due to the inadequate interaction that occurs during the gamete membrane fusion. In fact, syncytins and their receptors were significantly decreased in the men with oligoasthenozoospermia compared to other groups. Therefore, the decrease in both concentration and motility may have also worsened the fertilization potential by causing a decrease in sperm function and its success in the female reproductive system. Thus, syncytins and their receptors might also clinically reflect the quality of semen samples.
It is also of note that even though Bjerregaard and colleagues reported that Syncytin 1 was present in all samples by quantitative RT-PCR analysis, protein levels varied between donors [53]. Therefore, further studies with large cohort sizes and specific patient groups such as male versus female factor infertility may offer further insight into whether differential expression of syncytins and their receptors adversely affects fertilization, implantation and embryo growth. On the other hand, we used immunofluorescence staining technique to visualize the different localization patterns in human sperm. The techniques itself include steps such as fixation and permeabilization that can affect cell morphology and/or produce artifacts. Since we used the washed semen samples, the sperm preparation does not reflect the whole sperm population, and in men with impaired semen quality, the number of mature spermatozoa thus selected is usually high. Moreover, the ejaculated semen contains not only spermatozoa but also round cells (mainly leucocytes and immature germ cells) whose concentration is often high in infertile patients with altered semen parameters [93]. Although western blot is validated as a highly specific method to detect the total proteins extracted from cells, the ability of this technique to detect syncytins and their receptors in such human semen samples may be limited. Thus, this possible interference needs to be further evaluated. In addition, it still remains to be answered whether or not syncytins and their receptors have important roles in oocyte-sperm fusion in humans, and whether these retroviral proteins alter pregnancy, implantation, IVF miscarriage rates, and male fertility potential in infertility treatments in the clinics. Therefore, our results may have a significant impact on clinical decision making in the context of reduced fertility, infertility, and sperm physiology studies as these proteins might potentially play a variety of roles in sperm biology and function.
Acknowledgements
We sincerely thank the patients for their participation and support in this study.
Author contribution
LS designed the experiment and interpreted the data; BS, GGT, OK, and LS performed the experiments, collected the data, and analyzed the results; GGT and LS wrote the manuscript. All authors edited the manuscript and have given approval for publication of the present version of this manuscript.
Funding
This work was supported by a research grant from the Akdeniz University, The Scientific Research Projects Coordination Unit (TSA-2021–5689).
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the guidelines of the Declaration of Helsinki and was approved by the Ethical Committee of Akdeniz University School of Medicine (2012-KAEK-20), and informed consents from patient were obtained before the initiation of the study. All the authors consented to participate in this study.
Consent for publication
All the authors consented for publication.
Conflict of interest
The authors declare no competing interests.
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36469256 | PMC9734899 | NO-CC CODE | 2022-12-14 23:28:31 | no | J Assist Reprod Genet. 2022 Dec 5;:1-15 | utf-8 | J Assist Reprod Genet | 2,022 | 10.1007/s10815-022-02673-z | oa_other |
==== Front
Appl Biochem Microbiol
Appl Biochem Microbiol
Applied Biochemistry and Microbiology
0003-6838
1608-3024
Pleiades Publishing Moscow
8491
10.1134/S0003683822060126
Article
Microalgae in Terms of Biomedical Technology: Probiotics, Prebiotics, and Metabiotics
Oleskin A. V. [email protected]
1
Boyang Cao 2
1 grid.14476.30 0000 0001 2342 9668 Department of Biology, Moscow State University, Moscow, Russia
2 Shenzhen MSU-BIT University, Shenzhen, China
4 12 2022
2022
58 6 813825
14 4 2022
1 7 2022
4 7 2022
© Pleiades Publishing, Inc. 2022, ISSN 0003-6838, Applied Biochemistry and Microbiology, 2022, Vol. 58, No. 6, pp. 813–825. © Pleiades Publishing, Inc., 2022.Russian Text © The Author(s), 2022, published in Prikladnaya Biokhimiya i Mikrobiologiya, 2022, Vol. 58, No. 6, pp. 635–648.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Green, red, brown, and diatomic algae, as well as cyanobacteria, have been in the focus of attention of scientists and technologists for over 5 decades. This is due to their importance as efficient and economical producers of food additives, cosmetics, pharmaceuticals, biofertilizers, biofuels, and wastewater bioremediation agents. Recently, the role of microalgae has increasingly been considered in terms of their probiotic function, i.e., of their ability to normalize the functioning of the microbiota of humans and agricultural animals and to produce biologically active substances, including hormones, neurotransmitters, and immunostimulators. A separate brief subsection of the review deals with the potential functions of microalgae with respect to the brain and psyche, i.e., as psychobiotics. Moreover, algal polysaccharides and some other compounds can be broken down to short fragments that will stimulate the development of useful intestinal microorganisms, i.e., function as efficient prebiotics. Finally, many components of microalgal cells and chemical agents produced by them can exert important health-promoting effects per se, which indicates that they are as potentially valuable metabiotics (the term preferred by late Prof. B.A. Shenderov), which are alternatively denoted as postbiotics in the literature.
Keywords:
microalgae
aquatic ecosystems
biotechnology
biofuel
functional nutrition
biological fertilizers
wastewater treatment
bioremediation
cosmetics
pharmacology
neurotransmitters
immunostimulators
probiotics
psychobiotics
prebiotics
metabiotics
issue-copyright-statement© Pleiades Publishing, Inc. 2022
==== Body
pmcThe present work deals with an interdisciplinary topic that represents an intersection point between ecology, biotechnology, and medicine [1–6]. It is concerned with the potential functions of microalgae in the human body, as probiotics, psychobiotics, prebiotics, and metabiotics. All these functions can be fulfilled by microalgae within the framework of the human (animal) body–microbiota consortium. This consortium is of significant importance in physiological and medical terms and it resembles other multispecies associations that include microalgae as essential components involved in trophic and regulatory interactions within the framework of natural and human-made ecosystems in water bodies and in soil.
Using microalgae in biotechnology. In accord with a somewhat arbitrary classification, algae are subdivided into two main groups: the macro- and the microalgae. While macroalgae are macroscopic multicellular organisms that are up to 65 m in size, microalgae that are considered in this work are microscopic unicellular, colonial, or filamentous organisms; their size is ~1 to ~900 μm. Presumably, about 800 000 species of microalgae exist; at least 50 000 species have been described [7]. The large number of microalgal species is a prerequisite for a wide spectrum of their possible applications. In terms of taxonomy, many microalgae are eukaryotes, including representatives of the kingdom Viridiplantae such as green (division Chlorophyta) and red (division Rhodophyta) algae and of the kingdom Stramenophila (yellow–green algae including Ochrophyta and Prymnesiophyta). Other microalgae are prokaryotes; they belong to cyanobacteria (divisions Nostocales, Oscillatoriales, etc.). Microalgae are of paramount importance as sources of pharmaceuticals, nutraceuticals (e.g., food additives), cosmetics, biofuel, biofertilizers, animal feed, and wastewater treatment agents [5]. All the aforementioned uses of microalgae are related to biotechnology as “industrial application of biological processes and agents on the basis of highly efficient forms of microorganisms and the cultures of plant/animal cells and tissues with desired properties” [8], or, according to an alternative definition of biotechnology, of any technological application that uses biological systems, living organisms, or derivatives thereof, to make or modify products or processes for specific use (https://www.cbd.int/convention/text, see also [9]).
The “work horses” of modern biotechnology (Table 1) include a large number of species of green algae of the genera Chlorella, Dunaliella, Scenedesmus, Haematococcus, Chlamydomonas, Botyococcus, and Chlorococcum that are actually used or potentially applicable in pharmaceutical, dietary, and cosmetic terms. Biotechnology, including its medical subfields, also involves microscopic red algae (division Rhodophyta), e.g., the species of the genus Porphyridium. As for cyanobacteria, widely used producers of valuable compounds ranging from cosmetics and food additives to drugs are of note. They include the species of the genera Arthrospira (e.g., A. platensis, the outdated name is Spirulina platensis) that were used as food long ago by Aztecs in Central America and tribes that inhabited the region around Lake Chad in Africa), Nostoc (N. commune finds application in bioremediation of industrially polluted soils [10]), Anabaena, and Aphanizomenon.
Table 1. Examples of microalgae (including cyanobacteria) used in biomedical technologies
Genus and representative species Important applications [4, 5, 14–16, 19]
Cyanobacteria
Arthrospira
A. platensis
A. maxima
Functional food additive (FFA), cancer and allergy treatment, cosmetics
Nostoc
N. commune
FFA, cosmetics
Aphanizomenon
А. flos-aquae
FFA (necessity of toxicity tests is emphasized in the literature)
Green algae (Chlorophyta)
Chlorella
С. vulgaris
C. pyrenoidosa
FFA, immunostimulant, cosmetics
Scenedesmus
S. quadricauda
S. obliquus
FFA, cosmetics
Dunaliella
D. salina
D. maritima
FFA, source of pharmaceutics based on β-carotene and glycerol, cosmetics, cardioprotector
Haematococcus
H. pluvialis
FFA, source of astaxanthin as an antioxidant, cosmetics, obesity treatment
Chlorococcum
C. infusionum
Source of astaxanthin
Red algae (Rhodophyta)
Porphyridium
P. cruentum
Cosmetics, cardioprotector, anti-inflammatory agent
Ochrophyta
Phaeodactylum
P. tricornutum
FFA, obesity treatment
Nitzschia
N. frigida
Obesity treatment
Chaetoceros
C. affinis
Antimicrobial agent
Nannochloropsis
N. oculate
FFA (enriched in ω-3PUFAs), cosmetics, obesity treatment
Haptophyta
Isochrysis
I. galbana
Cosmetics, cardioprotector, anti-inflammatory agent
FFA is a functional food additive; this term implies a microbiota-normalizing and physical and mental health-promoting effect along with a more specific influence of the microalgae in question on the organism (exemplified by rejuvenating, tranquilizing, or anti-allergenic activities).
It has recently been estimated that the global market of microalgal products in 2022 will be worth 3.3 billion USD and the most important contribution will be made by pharmaceutical and food industry, taking the fact into account that people are concerned about their health and interested in environment-friendly alternatives to chemically synthesized products especially as chronic diseases are increasingly widely spread around the globe [5]. The leading companies in the field of biotechnology include Algae Tec (Australia), Pond Biofuels Incorporated (Canada), Cyanotech (United States), and Algae Systems (United States).
The prospects of modern biotechnology and especially its biomedical aspects are largely associated with synthetic biology as the engineering approach to the genome that can be modified and rearranged in order to change gene functions [11]. As an example, a microalga can be developed that will flocculate (form a sediment easily separable by filtration for harvesting the biomass) whenever it is necessary for a biotechnologist; it will also synthesize the target product in response to supplementing the medium with bacterial quorum-sensing signals provided that the necessary genes are inserted into the microalgal genome from bacterial DNA [11].
Further prospects for using microalgae in biotechnology are also associated with widely used phenomics that is based on extensive databases containing the important features (phenotypes) of microalgae. Phenomics enables target-oriented screening of natural and genetically modified (GM) organisms for obtaining optimum biotechnological producers that combine a high growth rate with a high specific yield of the target product, such as the antioxidant asthaxanthine that is expected to produce health-promoting effects [11].
In addition, the Internet of Things (IoT) is of significant practical importance; it involves automatons, sensors, and learning robots for developing self-adaptable biotechnological processes that respond to and the adjust to environmental changes; a biotechnological process is supplemented with its sensors-provided information-dependent digital “twin,” i.e., a virtual process that enables predicting the development of the actual process and making necessary technological changes for increasing the yield of biomass and target products and reducing the waste product amounts [11].
Medical applications. Microalgae and their products hold much promise for revolutionizing the pharmaceutical industry because they represent an environmentally friendly alternative to chemically synthesized preparations for treating or preventing diverse diseases including various types of diabetes, metabolic syndrome and obesity, cardio-vascular problems, malignant tumors, inflammatory processes, Alzheimer’s disease, depression, and other psychiatric disorders, as well as various bacterial, fungal, and viral infections. The medically useful effects of microalgae are caused by their components that exhibit antioxidant, light-protective, gel-forming, moistening, antimicrobial, and other activities. They are due to the presence of polysaccharides (especially their sulfated derivatives), carotenoids, phycobiliproteins (in cyanobacteria), lipid components (especially polyunsaturated fatty acids (PUFAs)), vitamins, and a large number of other chemical compounds [4–6, 12–17].
The capacity of algal components to quench free radicals is of paramount clinical importance. In particular, microalgal carotenoids can use at least three different reactions to quench free radicals, especially reactive oxygen species; this is one of the main factors that are responsible for their light-protective, anti-inflammatory, rejuvenating, and anticarcinogenic effects [18]:
Car + R* → Car+ + R– (electron transfer),
Car + R* → [Car…R] (formation of the radical adduct),
Car + R* → Car(-H)* + RH (proton transfer),
where Car is a carotenoid and R* is a free radical. The above processes are particularly characteristic of astaxanthin, an active radical quencher that contains polar groupings interacting with radicals [18].
Both separate microalgal components and whole biomass preparations find application as pharmaceuticals and preventives. Chlorella sp. biomass promotes the healing of gastric ulcers and wounds, accelerates muscular tissue synthesis, and increases the secretion of anabolic hormones. Per diem addition of 6 g of chlorella biomass to food substantially reduces the risk of pregnancy-associated complications (anemia, proteinuria, and edema) [5, 18].
In their capacity as food products or food additives, the microalgae of the genera Chlorella, Dunaliella, and Haematococcus and the cyanobacteria of the genera Arthrospira, Aphanizomenon, and Nostoc conform with the Generally Regarded As Safe (GRAS) designation but a prerequisite for their practical use is a test for toxicity [4, 19]. Microalgae are important protein sources (the global demand for algal protein exceeded 700 million USD in 2019, which has continued increasing [5]). It has been predicted that, by the mid-21st century, up to 18% of the protein in the global market will be provided by algae [20]. Microalgae are valuable sources of essential amino acids, carbohydrates, e.g., glucose and starch, vitamins В1, В2, В5, В6, В9, В12, A, C, E, and biotin, as well as carotenoids and other nutritionally and pharmacologically important pigments, including the phycobiliproteins of cyanobacteria [12, 13, 20].
Microalgae are used either as self-contained food items, in the form of liquid cultures, capsules, pills, powders, or as additives to diverse food products (sauces, desserts, yoghurts, cheeses including molten and cottage cheese, pasta, bread, steaks, sausages, etc. [4, 5, 19]). Gel-forming and stabilizing properties of the biomass components of many algae and their application as food thickeners provide the development of a wide range of biomass-derived products such as alginate and carrageenan [19].
The main component of chlorella biomass, β-1,3-glucan, is an immunostimulant and an antioxidant; it also decreases lipid concentrations in the blood [4, 5]. In the capacity of nutraceuticals and biologically active additives (BAAs), C. vulgaris and other chlorella species are produced by such companies as Chlorella Manufacturing and Co. (Taiwan), Klötze (Germany), and Ocean Nutrition (Canada) [5]. In Russia, a popular trademark is Orgtium® (tableted chlorella; https://fitomarket.ru/catalog/zdorovoe_pitanie/superfudy/khlorella; the same trademark applies to Arthrospira biomass denoted Spirulina). There is a Chinese analog, Natural Chlorella Tablet, that is manufactured by the Qingdao Vital Nutraceutical Ingredients Bioscience Co. company (https://www.made-in-china.com/products-search/hot-china-products) (see also [21]).
The use of polysaccharides, especially those with sulfate groups, that are obtained from microalgae including cyanobateria and possess antioxidant, anti-inflammatory, immunomodulating, and antiviral properties, is of considerable interest; these are also used for treating joint problems. Popular microalgal species include Tetraselmis sp., Isochrysis sp., Porphyridium cruentum, and Porphyridium purpureum, in addition to various chlorella species [22].
The advantages of chlorella biomass include high concentrations of ascorbic acid and K+, Na+, Mn2+, and Ca2+ ions. Chlorella vulgaris competes with Arthrospira platensis as a valuable vegetarian source of vitamin В12 contained in chlorella biomass in the biologically active form of methylcobalamine that is suitable for the human body [23]. Cultivation at a low light intensity facilitates the accumulation of valuable PUFAs, in particular, α-linolenic acid, in chlorella biomass [5].
The global market features such microalgal pharmaceutically important substances as astaxanthin from Haematococcus pluvialis under the trademark Spirulina (Earth Spirulina Group, ES Co., South Korea) that is recommended for decreasing lipid content [24, 25], eicosapentaenoic acid (EPA) from Nannochloropsis sp. (Almega®PL and Qualitas Health, United States) that reduces the cholesterol level in the blood [5, 26], and docosahexaenoic acid (DHA) from Schizochytrium limacinum (Maris DHA Oil, IOI, Germany), a drug for rheumatoid arthritis [27].
Apart from asthaxanthin, biotechnologically important microalgal pigments include other carotenoids, especially β-carotene, lycopene, zeaxanthin, canthaxanthin, etc. The intensely colored orange β-carotene is the precursor of visually and immunologically important vitamin A, and it also possesses antioxidant properties and is used as a valuable food dye (colorant) [4, 5]. The green microalga Dunaliella salina contains up to 12–14% of β-carotene (by dry weight). β-Carotene from D. salina is produced by the companies Earthrise Nutritionals (United States) and Nature Beta Technologies Cognis (Australia). Due to a lack of a rigid cell wall and its high protein content, the biomass of the algae of the genus Dunaliella is easily ingested; it is used in baking industry and also as feed for fish and cattle [5, 13, 28–30].
Microalgae are employed for preparing extracts (used, e.g., in beauty salons), alginic acids (as masks), and essential oils. The useful effects of microalgal preparations are due to their efficiency as skin moisturizers (or, conversely, excessive liquid removers), thickeners, pigments, sunscreens, and rejuvenating and skin-bleaching agents [4, 5, 22].
The products of genetically modified (GM) microalgae find increasingly wide application [12]. As an example, antibodies [31], vaccines, erythropoietin, viral protein 28 (VP 28) [32], and immunoconjugated cytotoxins for target-oriented elimination of cancer cells [11] were obtained from Chlamydomonas reinhardtii using genetic engineering techniques. Antibodies in the form that enables immediate introduction into the body and elimination of pathogens therein are released into the medium by GM cells of Phaeodactylum tricornutum [11].
Microalgae as probiotics. The actual and prospective clinical applications of microalgae raise the possibility that they can be used as probiotics. This term was originally coined by the German nutritionist Werner Collath in 1950; he contrasted probiotics with risky antibiotics [33]. According to the World Health Organization [34], probiotics are live organisms that, “when administered in adequate amounts, confer a health benefit on the host.”
The term probiotic derives from the Greek words pro and bios that mean “for life”; it predominantly refers to microorganisms that promote the health of their consumers, provided that they are ingested in adequate doses and form a part of a well-balanced diet [13]. Probiotics enter the market in the form of biologically active food additives and wholefood ingredients.
Probiotics and their advantages were considered in recent works by Prof. Boris A. Shenderov [35–39].
A debatable issue is whether microalgae are to be regarded as probiotics. Serious objections have been raised in the literature. Even though addition of live microalgae to the feed improves the health and viability of marine animals (fish and invertebrates), for most of them there is no evidence that these microalgae are efficient probiotics. The fate of microalgae administered with feed and their impact on the intestinal microbiota have not yet been elucidated [13]. No convincing data have been obtained on the survival of microalgae and the retention of a sufficiently dense microalgal population in the gut, in contrast to classical probiotics, such as lactobacilli, lactococci, bifidobacterial, and others. Nonetheless, the authors believe that special hopes should be pinned on the heterotrophic lifestyle that is characteristic of a sufficiently large number of microalgae. For comparison, it should be noted that probiotic lactobacilli are expected to persist in the gut as a robust population with a minimum density of 106 colony-forming units per 1 g of intestinal content [40].
In the global literature available to the authors no evidence has been presented that microalgae conform to all requirements met by probiotics, such as tolerance to the conditions of the gastro-intestinal tract (GIT) including specific physical and chemical stress caused by low pH values, a high redox potential, and a high osmotic pressure [30].
There is no direct evidence that microalgae can attach to the host gut mucosa, which is considered a prerequisite for the probiotic role in a large number of recent publications [35, 41–43]. Nonetheless, such attachment seems to be possible in view of the proclivity of many microalgae for biofilm formation with adherence to substrates. The authors of the present review article are planning to conduct target-oriented research at their laboratory to test the capacity of prospective probiotic microalgae to attach to the gut mucosa.
Recently, much attention has been given to mixed cultures of microalgae and probiotic bacteria, both in natural water bodies (in aquaculture) and under laboratory conditions. The components of such a mixed culture produce a synergistic effect that results in accelerating the growth of probiotic bacteria and algae and stimulating the synthesis of products that are important for the health of the host organism. Data have been presented on the acceleration of the growth of the microalga Isochrysis galbana in mixed cultures with various probiotic microorganisms [44]. In aquaculture, addition of microalgae along with bacterial probiotics enables improving the functioning of the gut and increasing the production yield in experiments with fish, mussels, and shrimp [40, 45, 46]. Introducing a Chlorella sorokiniana culture together with the probiotics Lactobacillus plantarum and Bifidobacterium longum results in prolonging the survival period of these probiotics in a cooled flan (at 4°С). In addition, C. sorokiniana-produced metabolites enhance the antiviral effect of both probiotics vis-à-vis rotaviruses [47].
In the following, the applicability of some other important probiotic criteria to microalgae will be discussed, drawing on a number of recent publications [29, 30, 39].
1. Probiotics facilitate the optimization of the qualitative and quantitative composition of the GIT microbiota; they increase its stability and robustness and suppress noxious microorganisms (competitive exclusion) by competing for ecological niches, nutrients and growth factors in the host organism and by producing antimicrobial compounds (short-chain fatty acids, bacteriocines and their analogs, hydrogen peroxide, nitric oxide, etc.) [48–50]. Although of paramount importance, this probiotic function has not been sufficiently tested in studies with microalgae. However, it was established that, e.g., Arthrospira platensis stimulates the development of such useful symbiotic bacteria of the GIT as Lactobacillus casei, L. acidophilus, Streptococcus thermophilus, and Bifidobacteria. The microalga inhibits the growth of the opportunistic pathogens Proteus vulgaris, Bacillus subtilis, and B. pumulis [13, 51–55]. Due to their polysaccharides, Chlorella pyrenoidosa and C. ellipsoidea suppress the proliferation of the cells of the pathogenic bacterium Listeria monocytogenes and the yeast Candida albicans [13, 51]. A significant positive influence is exerted on the intestinal microbiota by microalgae-produced omega-3-unsaturated fatty acids [56].
There is evidence for a probiotic effect of microalgae on animal microbiota. Administering Nannochloropsis oculata to the seahorse Hippocampus reidi or feeding the microalgae Chaetoceros sp., Pavlova sp., and Isochrysis sp. (separately or in combination) to oysters promoted the survival of these animals and decreased the quantity of viable pathogenic bacteria in their organisms [13, 57]. Importantly, probiotics do not disrupt the operation of the symbiotic microbiota of the GIT, in contrast to antibiotics [43]. Taken together, these facts raise the possibility of using microalgae as new therapeutics for maintaining a healthy microbial consortium of the GIT [13].
2. Probiotics eliminate toxins and metabolites that are harmful for the host organism. This probiotic function was emphasized by Boris Shenderov [30, 37–39, 48–50]; it is characteristic of classical bacterial probiotics. Nevertheless, it is to be expected that a mixed algae–bacteria culture will prove to be still more efficient in eliminating nocuous substances, since a synergistic stimulatory effect is typical of such a mixed culture and involves both its components [40]. In addition, microalgae per se actively bind various harmful substances. They effectively purge the environment of compounds containing sulfur, selenium, and, still more important, heavy metals including zinc, copper, lead, mercury, chrome, cadmium, nickel, iron, manganese, and vanadium [5, 58, 59]. All these elements accumulate in water and soil and affect humans and agricultural animals; this is the reason that this potential biotechnological niche of microalgae as candidate probiotics is so important. Of special interest in this context are yoghurts, juices, and other microalgal biomass-supplemented beverages that enable reducing the transfer of metals and other noxious agents into the human organism, especially under urban conditions. Thanks to their active enzymes, many microalgae can detoxify harmful organic compounds, including those accumulating in drinking water and food and deriving from pharmaceutics and cosmetics. As an example, Scenedesmus obliquus and Chlorella pyrenoidosa break down the hormone-based contraceptives progesterone and norgestrel [11, 60].
3. Probiotics form low-molecular-weight nutrients, antioxidants, protective compounds, and other biologically active substances (BASs) that influence the water-salt, lipid, amino acid, and energy metabolism, the redox balance at the local (intestinal) and systemic (organismic) levels, and the development and operation of the peripheral and central nervous system; they regulate host gene expression, impact the functioning of the innate and adaptive immune system, and eliminate toxic and carcinogenic compounds [30, 37, 48–50]. These capacities of probiotics remain to be further tested with respect to microalgae. Nonetheless, microalgal components, especially carotenoids, undoubtedly possess antioxidant properties, which enables their cardioprotective and anti-atherosclerotic effects. Dunaliella salina, which contains up to 10–13% of β-carotene, protects both mice and humans against the development of atherosclerosis. The D. salina-specific mixture of trans- (~40%) and cis-isomeres of β-carotene reduces the levels of total lipids, cholesterol, and triglycerides in the organism to a greater extent than synthetic β-carotene that contains the trans-isomer only [61, 62]. The cis-isomer of β-carotene from Dunaliella bardawil suppressed the development of atherosclerosis in aged mice that were on a fat-enriched diet [63, 64]. Cardioprotective properties are characteristic of PUFAs, especially of omega-3 acids produced by a number of microalgal species, e.g., Porphyridium purpureum and Isochrysis galbana that lower the blood cholesterol level and facilitate the normalization of the blood pressure. Docosahexaenoic acid (DHA) preparations are commercially available [5]. A Nannochloropsis sp. strain exposed to bright sunlight in an open pond produced significant amounts of eicosapentaenoic acid (EPA) that formed the basis of the commercial preparation A2EPA PureTM (United States) [65].
Under the rubric of BASs, of note are numerous signal molecules including hormones and neurotransmitters. As an example, neuroactive biogenic amines also serve as a chemical language for communication between the host organism and the microbiota, including putative probiotic microalgae. Biogenic amines (norepinephrine, dopamine, serotonin, histamine, etc.) bring about specific responses such as growth stimulation and accelerated development of microalgal cultures exemplified by Chlorella vulgaris, Scenedesmus quadricauda, and a number of other species [66–71].
4. Probiotics exert an anticarcinogenic effect. This is characteristic of a large number of microalgae and their components, such as astaxanthin, β-carotene, luteine, violaxanthin, fucoxanthin, and other microalgal carotenoids, as well as of the phycobiliproteins of cyanobacteria including Arthronema africanum and Arthrospira platensis [5, 12, 13, 72]. Ñ-phycocyanin exerts an inhibitory influence on the liver cancer (HepG2) [73], leukemia (Ê562) [74], and lung cancer (À549 and NSCLC) [75, 76] cell lines. It was established that phycocyanin from Limnothrix sp. potentiates the effect of the antitumor drug topotecan on the prostate cancer cell line [77]. Monoacylglycerides forming a part of Skeletonema marinoi lipids can activate caspase 3/7 and, therefore, induce the apoptosis (programmed death) of colon cancer (HCT-116) and hematological cancer (U-937) cells but not normal cells [56]. PUFA-containing microalgal lipids exhibit antitumor activity with respect to cervical and breast cancer. EPA and DHA suppress blood vessel growth in the tumor tissue and enhance peroxide-dependent stress in the endoplasmic reticulum, which results in tumor cell destruction [56]. The sulfated polysaccharide fucoidan from Fucus vesiculosis, Sargassum henslowianum, Cladosiphon fucoidan, and Coccophora longdorfii inhibits blood vessel formation and metastasis development by inducing, via caspase 3/7 activation, the apoptosis of the lymphoma, melanoma, lung carcinoma, promyeloid leukemia, colon and breast cancer cell lines [78]. Anticarcinogenic activity was found to be exhibited by violaxanthin that is synthesized, e.g., by Dunaliella tertiolecta [22].
5. Probiotics are characterized by anti-inflammatory, anti-allergic, and antidiabetic activities. The anti-inflammatory effect that is largely associated with the impact on the immune system (see a special passage below) is typical of the sulfated polysaccharides of Chlorella spp., Tetraselmis sp., Isochrysis sp., Porphyridium spp. [22], and other algae as well as of their pigments, especially β-carotene and astaxanthin that are in the focus of attention of influential international networks such as the International Carotenoid Society, Eurocaroten, IBERCAROT, and CaRed [13]. In experiments with rats as models, the dried powder of Dunaliella bardawil biomass mitigated acetic acid-induced small intestine inflammation [79]. As for patients with nonalcoholic fatty liver disease (NAFLD), treating them with tableted C. vulgaris biomass resulted in a verifiable decrease in proinflammatory cytokine TNF-á content [79]. Arthrospira phycocyanins inhibit the NADPH oxidase enzyme that is implicated in inflammatory processes [12, 80]. Astaxanthin, a red pigment (a food and cosmetic colorant) and an antioxidant that is particularly characteristic of Haematococcus pluvialis, mitigates the “cytokine storm” (excessive immune system activator production) during the COVID-19 infection [12, 80]. The PUFAs of algae facilitate the treatment of inflammatory diseases including arthritis [13, 81].
A bacterial probiotics-specific antidiabetic effect was revealed, e.g., in the cyanobacteria of the genus Arthrospira, which is attributable to their high vitamin and γ-linolienic acid content [12]. Antidiabetic activity is also exhibited by the aforementioned astaxanthin [13] and phycocyanin [82] pigments. A debatable issue is whether microalgae produce an anti-allergic effect. In the authors’ opinion, they should be first tested for an opposite effect, i.e., they might cause allergic complications during systematic administration to patients.
6. Probiotics facilitate metabolism normalization, body weight reduction, and obesity (metabolic syndrome) treatment. In addition, probiotics can be used to treat diametrically opposite health problems, i.e., anorexia and emaciation. It was experimentally demonstrated that probiotics contribute to normalizing the health state of a rodent after food deprivation [83]. Therapeutical effects were revealed in in vitro and in vivo studies, including clinical tests, for the microalgae Euglena gracilis, Phaeodactylum tricornutum, Arthrospira maxima, A. platensis, and Nitzschia laevis. Microalgae suppress the differentiation of preadypocytes (adipose tissue cell precursors) and reduce total lipogenesis (lipid synthesis) and, more specifically, triacylglyceride accumulation [82]. The resulting increased lipolysis and fatty acid oxidation are accompanied by enhanced energy loss via thermogenesis activation in the brown adipose tissue and the browning of the white adipose tissue. Along with reduced fat accumulation in the organism, microalgal treatment mitigates other symptoms in obese people, including an increased plasma lipid level, insulin resistance (posing the diabetes threat), and mild chronic systemic inflammation [82]. Addition of Arthrospira platensis or Chlorella sp. biomass powder to bread or cookies helps decrease lipid and cholesterol levels and replace the feeling of hunger with that of satiety [13].
7. Our hopes for staving off progressive senescence symptoms are pinned on probiotics. This statement, made in the work by Shenderov [48–51], draws on the ideas suggested by Elia Metchnikoff in Etudes sur la nature humaine; essai de philosophie optimiste [84] and is in line with data on the aging-decelerating and rejuvenating influence of microalgae, which, in turn, is linked to their antioxidant, protective, anti-inflammatory, and metabolism-normalizing effects.
Skin aging is associated with a decrease in the synthesis of the structural components of the skin matrix (collagen, elastin, and hyaluronic acid) and concomitant activation of proteases that degrade these components. Accordingly, aging deceleration and rejuvenation caused by microalgal preparations are partly due to their restrictive effect on matrix component proteolysis. Of significant importance is also the fact that microalgae contain antioxidant effects-producing substances that quench free radicals, especially reactive oxygen species (ROS). Microalgal carotenoids including β-carotene (Dunaliella salina), lutein (D. salina, Scenedesmus spp., Chlorella spp., and Mougeotia sp.), and lycopene protect the skin from the ultraviolet light effect, quench ROSs and slow down skin aging. The rejuvenating influence of microalgae is also attributed to the regulatory effect of their phytohormones (auxins, cytokinins, abscisic acid, gibberellins, etc.) on the human body [5, 22].
8. Probiotics promote blood vessel growth (angiogenesis) in the intestinal tissue by producing vascular endothelial growth factor (VEGF) [43]. In traditional Chinese medicine, spirulina (denoted as Arthrospira platensis currently) and a number of other microalgae (https://www.ginsen-london.com/blog/benefits-of-spirulina, see also [85]) are used for treating duodenal ulcer because they speed up vascularization, i.e., blood vessel elongation, in the gut wall. Target-oriented research aimed at enabling the biosynthesis and release into the medium of VEGF or its functional analogs represents a growth point in the area of research dealing with the probiotic functions of microalgae. Of interest in the context of angiogenesis stimulation in the intestinal tissue is the important therapeutical influence of microalgae including those of the genus Chlorella on the leaky gut syndrome, with chlorella contributing to gut wall tissue regeneration [86].
9. Some probiotics exert a prominent pain-relieving effect. This effect is characteristic of the aqueous extracts of Chlorella stigmatophora and Phaeodactylum tricornutum, which is attributed to their polysaccharide components [22, 87, 88]; these extracts also exhibit anti-inflammatory activity and can quench free radicals.
10. Probiotics mitigate stress; this is not only typical of classical bacterial probiotics such as the bifidobacteria and lactobacilli that form a part of fermented dairy products [89]. Such dairy items can be enriched with microalgal preparations that produce anti-stress effects. As an example, evidence was presented that Chlorella vulgaris possesses not only anti-infection and anticarcinogenic, but also anti-stress properties. In experiments with Wistar rats that were exposed to stress (placing in wet cages or tanks with cold or hot water, disrupting the day–night rhythm, etc.), a C. vulgaris culture mitigated : (1) the behavioral consequences of stress such as anhedonia, i.e., a lack of interest in drinking sucrose solution that rats normally find tasty (after administering chlorella, the rats return to normal behavior: they prefer sweetened solution to plain water); (2) the biochemical effects of stress, such as an increase in blood cholesterol level; chlorella verifiably decreased this level [90].
11. Probiotics interact with gut epithelial cells and, therefore, regulate the activity of the immune system and, in direct fashion, of its intestinal part, the gut-associated lymphoid tissue (GALT); they modulate immune responses, normalize the balance between pro- and anti-inflammatory cytokines, and decrease the antigen pressure exerted on the GALT. Probiotics reduce gut wall permeability, increase immunoglobulin IgA secretion, activate anti-inflammatory Treg cells [91], and facilitate the production of anti-inflammatory interleukin IL-10.
For microalgae as “candidate probiotics,” an active immunostimulatory influence was detected with β-1,3-glucan and other polysaccharides (containing the residues of mannose, glucose, rhamnose, arabinose, etc.) of the representatives of the genus Chlorella [13, 22, 79]. One of the mechanisms of immune system regulation involves stimulation of monocyte, macrophage, and neutrophil proliferation and an increase in phagocyte activity and secretion of immune mediators such as cytokines. Polysaccharide-containing Chlorella stigmatophora, Skeletonema costatum, and S. dohrni extracts activated macrophage-dependent phagocytosis in the abdominal cavity of mice [79]. Omega-3 PUFAs contained in microalgal biomass also stimulate macrophage activity [56]. Administering Chlorella vulgaris biomass as dried powder to human subjects increased natural killer activity in the monocyte fraction of peripheral blood and the interferon γ and interleukin IL-1β and IL-12 content in the blood serum [79]. In similar fashion, feeding dried Dunaliella salina biomass to mice resulted in activating their macrophages and natural killers (NK cells) and also increased the viability of mice with leukemia [79].
The literature available to the authors contains no data on the direct impact of microalgae and preparations obtained therefrom on the activity of the intestinal part of the immune system (GALT) that is inherent in many representatives of classical bacterial probiotics [29, 30]. This area of research remains a sufficiently important growth point for subsequent studies. A similar issue (also related to immune system activity) to be raised is whether microalgae, their components, and preparations obtained therefrom regulate the activity of natural barriers such as the gut–blood barrier and the blood–brain barrier (BBB) via enhancing the expression of proteins involved in intercellular tight contacts. The capacity for strengthening the BBB and other important barriers was detected with respect to bacterial probiotics [92]. Under stress, probiotics improve the protective function of the intestinal barrier, decrease the concentrations of circulating corticosteroids and proinflammatory cytokines and concomitantly increase those of anti-inflammatory cytokines. They are implicated in restoring the integrity of the BBB and the gut–blood barrier and mitigate systemic inflammation [93].
12. The useful effects of probiotics on the nervous system, the operation of the brain, and psychological features including cognitive capacities, memory and social behavior give grounds for classifying some probiotics into the subgroup of psychobiotics. These are live microorganisms that when administered in adequate amounts, confer a health benefit on patients with psychiatric problems [94, 95]. An increasing body of evidence indicates that probiotics can influence the brain, behavior, and, most important, mood and cognitive capacities, both in the experimental and the clinical setting [96]. As an example, it was demonstrated that the psychobiotic strain Lactobacillus rhamnosus JB-1 acted on the GABA-dependent system in the brain and suppressed the anxious behavior of mice in a complex maze and in an illuminated open field as well as their depressive behavior in a forced swimming test [97, 98]. It was hypothesized that humans would not be able to achieve the modern-day level of cognitive capacities without the microbiota [99].
As far as microalgae are concerned, important data have been obtained recently on the neuroprotective effects of various microalgae and their components such as polysaccharides, lipids (especially those with PUFAs), carotenoids, phycobilins, and other compounds. The nervous system is protected by them against oxidative stress, aging, and neurodegenerative disorders (Alzheimer’s and Parkinson’s disease, dementia, etc.). It suffices to point out that representatives of the genus Arthrospira possess neuroprotective properties and facilitate the performance of normal brain functions [40]. Their extracts improve brain fatigue symptoms, prevent or mitigate cerebral circulation problems, and promote cognitive, locomotive, and verbal capacities. This was established in studies in which undernourished children were treated with Arthrospira (“Spirulina”) preparations [40].
Microalgal PUFAs, especially DHA and EPA, are mandatory for the normal development of the nervous system and serve as an important supplement for baby formula products, vitamin-enriched foods and drinks, and dietary food additives. As an example, the baby formula that is produced by the Dutch State Mines Company (Netherlands) contains preparations from the biomass of the dinoflagellate Crypthecodinium cohnii; DHA accounts for up to 60% of its total acid fraction [11].
Probiotic bacteria are known to produce substances involved in the operation of the nervous system (neurotransmitters) or their precursors that can reach the brain via the BBB. Such precursors include 2,3-dihydrophenylalanine (DOPA), the catecholamine precursor, and 5-hydroxytryptophan (5-HTP), the serotonin precursor [29, 30, 39]. Of much interest in this context is the fact that many algal species (exemplified by representatives of Chlorophyta, Charophyta, Ochrophyta, Rhodophyta) synthesize significant amounts of dopamine, serotonin, histamine, tyramine, acetylcholine, and other neurotransmitters [66]; such algae are to be envisaged as potential probiotics, and they could be used to improve the functioning of the brain, promote mental health, and treat brain disorders, e.g., Parkinson’s disease associated with dopamine deficiency in the substantia nigra of the brain.
Importantly, each of the useful effects of probiotics is due not only to individual microbial substances but also to intricate complexes of low-molecular-weight compounds that are produced by probiotic microorganisms either in their functional form or as precursors [37, 38]. These complexes of microbial substances affect the host and its microbiota against the background of the impact of other biologically active substances that either enter with food or are produced by the resident microbiota. In connection with the probiotic role of microalgae, it should be noted that various phenols, fatty acids, indole, terpenes, acetogenins, and some volatile halogenated hydrocarbons obtained from microalgae exhibit antimicrobial activity. Supercrticical (СО2-extracted) extracts of the microalga Chaetoceros muelleri produce antimicrobial effects because of their lipid composition [100]. Another growth point of present-day research involves studies on the antibacterial, antiprotozoal, antifungal, and antiviral activities of many microalgae and their components [12].
Microalgae as prebiotics. Apart from the aforementioned data in support of the probiotic function of microalgae, the question is raised in the literature of whether microalgal polysaccharide components and other organic constituents perform a prebiotic function. Prebiotics are indigestible food components that bring about specific changes in the composition and/or activities of the GIT microbiota and, therefore, exert a positive influence on health. In accord with the official WHO/FAO definition, prebiotics are to be construed as nonliving edible products that improve health by altering the microbiota [101].
Typical representatives of probiotics are indigestible oligosaccharides degradable by beneficial microorganisms in the gut, which produce short-chain fatty acids and other organic compounds holding much value for the host [42]. Optimizing the diet by enriching it in such prebiotics as fructans should contribute to the proliferation of useful bacteria such as Bifidobacterium [49, 102]. Prebiotics can exert anti-inflammatory effects that are attributable to polysaccharides’ capacity for direct interaction with the intestinal epithelium, regardless of gut bacteria, which significantly reduces the production of proinflammatory cytokines [93].
Importantly, the polysaccharide components of microalgae can be broken down to short fragments (oligosaccharides) that possess prebiotic properties. They are exemplified by inulin, galactooligosaccharides, xylooligosaccharides, and the oligosaccharides that are obtained from agarose, alginate, and carrageenan, as well as by arabinoxylans, galactans, and β-glucans [13, 14]. Microalgal oligosaccharides are either not fermented or only partially degraded by the usual gut microbiota of humans or animals. However, these compounds selectively stimulate the growth and activity of specific beneficial bacteria exemplified by lactobacilli and bifidobacterial, provided that the oligosaccharides translocate to the colon in order to promote the host’s health, i.e., to function as prebiotics [13].
Presumably, the prebiotic components of microalgae contribute to the aforementioned (see item 1 in the list of the potential probiotic features of microalgae) positive influence on the host microbiota, as exemplified by the stimulatory effect of Arthrospira platensis on the viability of bacteria that form a part of the intestinal microbiota, including Lactobacillus casei, Streptococcus thermophilus, Lactobacillus acidophilus, and Bifidobacteria as well as its negative impact on the pathogens Proteus vulgaris, Bacillus subtilis, and Bacillus pumulis that were suppressed by A. platensis [13] in in vitro studies.
The prebiotic and the probiotic roles of microalgae are mutually complementary: algae can be used as live cultures and produce the probiotic effects listed above; in addition, their carbohydrate components can provide the raw material for preparing efficient prebiotics in order to stimulate the beneficial microbiota and, therefore, to promote human health.
Microalgae as sources of metabiotics. Metabiotics were defined in the literature as biologically active substances that are produced as a result of the metabolic activities of symbiotic (probiotic) microorganisms and exert a positive influence on various kinds of physiological processes [35]. The meaning of the term metabiotics actually is closely related to that of the relatively popular term postbiotics. It denotes bacterial products that, in the absence of viable bacterial cells, can exert an influence, in analogy to those cells, on the signaling pathways and the barrier functions of the organism. Metabiotics contain bacteriocins, organic acids, ethanol, and diacetyl [29, 30, 35, 43]. Metabiotics are exemplified by heated cells of probiotic bacteria; polysaccharide A formed by Bacteroides fragilis that activates the immune system and protects mice (in an experiment) from Helicobacter hepaticus-induced colitis; and the preparation skeleton P-CWS (Propionibacterium acne cell wall fragments) that increases the cytotoxic activity of macrophages and, therefore, produces an anticarcinogenic effect [30].
In the authors’ opinion, the aforementioned interpretation of metabiotics is generally applicable to microalgae-produced valuable products that improve human physical and mental health, including carotenoids (β-carotene, astaxanthin, lycopene, luteine, zeaxanthin, violaxanthin, canthaxanthin, fucoxanthin, etc.); chlorophylls; phycobiliproteins (especially phycocyanin, allophycocyanin, and phycoerythrin); carbohydrates (exemplified by β-glucan, fucoidan, and other sulfated polysaccharides); lipids (especially PUFA-containing triacylglycerides); vitamins; plant hormones (auxins, cytokinins, etc.), and other regulatory molecules; K+, Na+, Mn2+, and Ca2+ ions; and other important components [5, 12, 13, 16–18, 24]. Interestingly, PUFAs facilitate the treatment of cardiovascular diseases, hypertension [13], thrombosis of heart coronary vessels, malignant tumors, asthma, bowel inflammatory diseases, and psychiatric problems such as schizophrenia and anxiety disorders [15].
To sum up, the present work is focused on the present-day knowledge concerning the practical applications of microalgae, including cyanobacteria, as agents used for treating and preventing various diseases, promoting health, and decelerating aging. Despite a lack of sufficient data on the long-term survival of useful microalgal cultures in the human/animal gastro-intestinal tract, the statement can be made that a large number of algal cultures fully conform to many important probiotic criteria. Some of their components, e.g., polysaccharides, seem to provide the raw material for producing short fragments to be used as prebiotics, or, alternatively, hold much pharmaceutical and dietary value as metabiotics, as emphasized by Boris Shenderov [35, 36].
ACKNOWLEDGMENTS
This work was carried out in terms of the state assignment of the Interdisciplinary Scientific and Educational School of Moscow State University titled The Future of the Planet and Global Environmental Changes.
COMPLIANCE WITH ETHICAL STANDARDS
The authors declare that they have no conflicts of interest. This article does not contain any studies involving animals or human participants performed by any of the authors.
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| 0 | PMC9734902 | NO-CC CODE | 2022-12-14 23:28:31 | no | Appl Biochem Microbiol. 2022 Dec 4; 58(6):813-825 | utf-8 | Appl Biochem Microbiol | 2,022 | 10.1134/S0003683822060126 | oa_other |
==== Front
Clin Exp Nephrol
Clin Exp Nephrol
Clinical and Experimental Nephrology
1342-1751
1437-7799
Springer Nature Singapore Singapore
36469196
2300
10.1007/s10157-022-02300-2
Review Article
Predictive value of suPAR in AKI: a systematic review and meta-analysis
http://orcid.org/0000-0002-1338-0597
Huang Yan [email protected]
Huang Shengchun [email protected]
Zhuo Xueya [email protected]
Lin Mintao [email protected]
grid.490148.0 Department of Clinical Laboratory, Foshan Hospital of Traditional Chinese Medicine, 6 Qinren Road, Chancheng District, Foshan City, 528000 Guangdong Province China
5 12 2022
111
1 7 2022
18 11 2022
© The Author(s), under exclusive licence to The Japanese Society of Nephrology 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Background
Some clinical trials have shown that soluble urokinase-type plasminogen activator receptor (suPAR) has good predictive value for acute kidney injury (AKI), but there is still a lack of evidence-based proof. Therefore, we conducted this systematic review and meta-analysis to evaluate the predictive value of suPAR for AKI.
Methods
Pubmed, EMBASE, Cochrane Library, and Web of Science databases were searched until December 2021 to obtain the literature on the prediction of suPAR for AKI. The quality of the included studies was assessed using the QUADAS-2 scoring system, and a bivariate random-effect model was used for the meta-analysis. The present study has been registered on PROSPERO (Registration No. CRD42022324978).
Results
Seven articles were included, involving 2,319 patients, 635 of whom were AKI patients. The meta-analysis results showed that the combined sensitivity of suPAR in predicting AKI was 0.77 (95% CI 0.67–0.84); the specificity was 0.64 (95% CI 0.53–0.75); the odds ratio of diagnosis was 6 (95% CI 3–10); the pooled positive likelihood ratio was 2.2 (95% CI 1.6–2.9); the pooled negative likelihood ratio was 0.36 (95% CI 0.26–0.52); and the area under the summary receiver-operating characteristic (SROC) curve was 0.77 (95% CI 0.12~0.99). Deek’s funnel plot suggested no potential publication bias among included studies.
Conclusion
suPAR is a valuable biomarker for the prediction of AKI with relatively high predictive accuracy, but its clinical application needs improvements. SuPAR should be considered as an indicator in the subsequent development of more effective predictive tools for AKI.
Keywords
Soluble urokinase-type plasminogen activator receptor
suPAR
Acute kidney injury
Meta-analysis
Predictive test
Peak Climbing Project of Foshan Hospital of Traditional Chinese Medicine202000205
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pmcIntroduction
Acute kidney injury (AKI) is a common and severe clinical syndrome that occurs in approximately 0.15 of hospitalized patients, and its morbidity has been reported in more than half of patients in the intensive care unit (ICU), with a high mortality rate [1–3]. Currently, the diagnosis of AKI is still based on the rapid increase in serum (or plasma) creatinine, a decrease in urine volume, or both [4–6]. However, the concentration of creatinine is affected by multiple clinical variables, such as hydration, nutritional status, muscle metabolism, or drug effects, and serum creatinine does not alter until the glomerular filtration rate (GFR) is reduced by about 0.50 [7, 8]. Owing to these limitations, creatinine remains an insufficient predictor of AKI. As a result, there is an urgent need for an accurate and timely biomarker to predict the occurrence or progression of AKI.
Soluble urokinase plasminogen activator receptor (suPAR) is a novel biomarker. SuPAR molecules are derived from the proteolytic cleavage of membrane-bound urokinase plasminogen activator receptor (uPAR, cd87), and can be detected in different body fluids, such as blood, urine, peritoneal fluid, and cerebrospinal fluid. Moreover, suPAR is highly stable, and the concentration of suPAR in serum is not affected by diet, drugs, inflammation, and time of collection throughout the day [9]. SuPAR is a signal transduction glycoprotein that is believed to be involved in the pathogenesis of kidney diseases [10]. Previous studies have shown that the systemic inflammatory biomarker suPAR is an important biomarker for the early identification of AKI [11, 12]. Hayek et al. have recently found that elevated suPAR is associated with an increased risk of AKI in patients undergoing coronary angiography or cardiac surgery and in those hospitalized in intensive care units [10]. However, there is still no evidence that suPAR can be used as a marker to predict the occurrence of AKI, or that high suPAR levels are associated with AKI. Therefore, we conducted this systematic review and meta-analysis to evaluate the predictive value of suPAR for AKI.
Materials and methods
Literature retrieval
The search databases for this study were EMBASE, Cochrane Library, PubMed, and Web of Science, and the search time was as of December 2021. The search strategy was a combination of subject headings and free words, and minor adjustments might be made to each database. The search terms in PubMed included “Acute Kidney Injury” [Mesh], and “Receptors, Urokinase Plasminogen Activator [Mesh]”. The detailed retrieval strategy is shown in Appendix 1. The present study has been registered on PROSPERO (Registration No. CRD42022324978).
Literature inclusion and exclusion criteria
Inclusion criteria: (1) The literature type was cohort study, cross-sectional study, or diagnostic trial study; (2) English literature; (3) Studies containing the gold standard for the definite diagnosis of AKI and non-AKI cases; (4) Studies in which the four-grid diagnostic table could be directly or indirectly extracted from outcome indicators.
Exclusion criteria: (1) Non-clinical studies, such as reviews, medical records, and conference abstracts; (2) In vitro or animal experiments; (3) Studies from which the diagnostic four-grid table could not be directly or indirectly extracted.
Literature screening and data extraction
The EndNote software was used for literature management, and the literature was screened according to the inclusion and exclusion criteria. After the final included studies were determined, information extraction was performed, including the first author, country, sample size, AKI occurrence background, number of true positives, number of false positives, number of true negatives, number of false negatives, sensitivity, specificity, and ROC curve.
The literature screening and information extraction were carried out independently by two researchers (Y.H. and S.C.H.), and cross-examination was conducted after completion. If there was any disagreement, a third researcher (X.Y.Z.) was invited to assist in adjudication.
Quality evaluation
In the present study, two investigators (Y.H. and S.C.H.) independently used QUADAS-2 to assess the methodological quality of included studies. They cross-checked the results after the evaluation was completed. If there was any disagreement, a third investigator (X.Y.Z.) assisted in adjudication. The application of the QUADAS-2 has four phases: summarize the review question, tailor the tool and produce review-specific guidance, construct a flow diagram for the primary study, and judge bias and applicability.
Statistical analysis
A complete meta-analysis was performed using Stata 15.0 (Stata Corporation, College Station, TX), and a bivariate mixed model was used to pool effect sizes. The combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio with 95% confidence interval (95%CI) were analyzed. A sensitivity analysis was performed to evaluate the stability of meta-analysis results, and Deek’s funnel plot asymmetry test was adopted to assess publication bias. Owing to the small number of included studies, we did not perform meta-regression. In this study, p < 0.05 indicated that the difference was statistically significant.
Results
Retrieval results
A total of 215 relevant studies were retrieved, 157 of which were left after removing duplicate or irrelevant literature. According to the title and abstract, 125 studies that did not meet the criteria were excluded. After a full-text review of the remaining 32 studies, 7 studies were finally included in this meta-analysis. The literature screening process is shown in Figure 1.Fig.1 Flow chart of literature screening
Basic information
The seven included studies were published between 2017 and 2021, with patients from four countries and multiple ethnicities, including two from Denmark [13, 14], three from Germany [12, 15, 16], one from China [17], and one from the United States [18]. The study design was mainly retrospective. A total of 2319 patients were included, comprising 635 AKI patients and 1684 non-AKI patients, and most of them were middle-aged and elderly. Most trials were done on critically ill patients, including those who had undergone cardiac surgery (extracorporeal circulation), elderly patients in the emergency department, patients in the ICU after colostomy or with sepsis, and hospitalized adults with COVID-19. The basic characteristics of all the included literature are presented in Table 1.Table 1. Basic characteristics of the included literature
AKI Total Gender Mean AKI definition suPAR testing time Kit/methodology
First Author, Year Study Design and type Country Cases cases (M/F) Age background for AKI
Anne Byriel Walls [13] Retrospective cohort study Denmark 33 339 127/212 Elderly patients in the 77.6 emergency department An increase in serum creatinine (Scr) by ≥ 0.3 mg/dL (≥ 26.5 µmol/l) or increase in Scr to ≥ 1.5 times baseline within 48 h after enrolment At enrolment (Day 0) Nr. A001 suPARnostic® Elisa Kit /ELISA
Sven H. Loosen [15] Prospective cohort study Germany 12 104 63 Colon cancer resection An increase in Scr by ≥ 0.3 mg/dL (≥ 26.5 µmol/l) or increase in Scr to ≥ 1.5 times baseline within 48 h after surgery Before operation Nr. A001 suPARnostic® Elisa Kit./ELISA
Sebastian Roed Rasmussen [14] Retrospective cohort study Denmark 327 924 738/186 67 Heart surgery An increase in Scr by ≥ 0.3 mg/dL (≥ 26.5 µmol/l) or increase in Scr to ≥ 1.5 times baseline within 48 h after surgery.
KDIGO stage: AKI Stage 1 was defined as a rise in Scr to 1.5–1.9 times baseline or an absolute rise of ≥ 26.5 µmol/l within 48 h. Stage 2 was defined as a rise in Scr to 2.0–2.9 times baseline, and stage 3 was 3.0 or more times baseline, or initiation of RRT.
Before operation suPARnostic® Elisa Kit./ELISA
Yuhan Qin [17] Prospective cohort study China 65 399 262/137 Percutaneous coronary
65 intervention
Scr level increased by ≥ 0.3 mg/dl (26.5 μmol/l) over the baseline value within 48 hours after contrast medium exposure;
or Scr increased by ≥ 1.5 times over the baseline value within 7 days after contrast medium exposure;
or a urinary volume of less than 0.5 mL/kg/h and persists for at least 6 hours after exposure.
Before angiography suPARnostic® Elisa Kit./ELISA
Jana C. Mossanen [12] Prospective cohort study Germany 21 107 77/30 69 Heart surgery Patients with an increase in Scr by ≥ 0.3 mg/dL (≥ 26.5 µmol/l) or increase in Scr to ≥ 1.5 times baseline stated in the KDIGO criteria within the first four days after operation were defined as AKI patients. Before operation suPARnostic® Elisa Kit./ELISA
Tariq U. Azam 18] Retrospective cohort study USA 91 352 202/152 Hospitalized adult
61 patients with COVID-19
KDIGO stage: AKI Stage 1 was defined as a 1.5–1.9-fold rise in Scr compared to the admission value or an absolute increase in Scr by ≥ 0.3 mg/dl. Stage 2 was defined as a 2.0–2.9-fold rise in Scr above admission levels. Lastly, Stage 3 was defined as a threefold rise in Scr relative to admission levels, a rise in Scr to ≥ 4 mg/dl, or initiation of RRT. Within 2 days after admission suPARnostic® Elisa Kit./ELISA
Christian Nusshag [16] Prospective cohort study Germany 86 94 60/34 64.5 ICU Sepsis Scr increased to ≥ 1.5 times baseline within the past 7 days. At enrolment (Day 0) R&D Systems,/ELISA
AKI acute kidney injury, suPAR soluble urokinase Plasminogen Activator Receptor, suPARnostic® Elisa Kit suPARnostic assay, Viro-Gates, Birkerød, Denmark, ELISA enzyme-linked immunosorbent assay, R&D Systems R&D Systems, Minneapolis, MN, USA, RRT renal replacement therapy, M Male, F Female, Scr serum creatinine
Methodological quality evaluation
According to the evaluation items of QUADAS-2, the risk of bias was assessed in four domains: case selection, trial to be evaluated, reference standard, and flow and timing. The clinical applicability of the first three domains was evaluated at the same time. The risk of bias assessment showed that the quality of all included studies was relatively good, and the high risk items were mainly in the case selection domain, as shown in Figure 2.Fig. 2 Literature quality evaluation (Red indicates a high risk of bias; Yellow indicates insufficient information for risk assessment; Green indicates a low risk of bias)
Meta-analysis results
The pooled sensitivity of suPAR in predicting AKI was 0.77 (95%CI 0.67–0.84); the pooled specificity was 0.64 (95%CI 0.53–0.75); the pooled predictive odds ratio was 6 (95%CI 3–10); the pooled positive likelihood ratio was 2.2 (95% CI 1.6–2.9); the pooled negative likelihood ratio was 0.36 (95% CI 0.26–0.52), and the area under the summary receiver-operating characteristic (SROC) curve was 0.77 (95% CI 0.12–0.99). The sensitivity, specificity, and SROC are presented in Figure 3.Fig. 3 Sensitivity, Specificity and Pooled SROC (A Forest plot of sensitivity and specificity; B: SROC curve of the meta-analysis)
In this meta-analysis, the heterogeneity I2 was 0.93 (95% CI 88–99), and the box plot revealed that the studies of Anne Byriel Walls [13] and Yuhan Qin [17] might be the main sources of heterogeneity. In addition, Deek’s funnel plot showed no apparent publication bias among the studies (p = 0.06). The bivariate boxplot for heterogeneity is shown in Figure 4A, and Deek’s funnel plot is shown in Figure 4B.Fig. 4 Heterogeneity and Deek’s Funnel plot (A bivariate boxplot for heterogeneity. Studies outside the shadow may introduce major heterogeneity. B Deek’s Funnel plot for publication bias)
Fagan’s plot was employed to reflect the clinical applicability of suPAR in predicting AKI. The incidence of AKI varies significantly in different contexts and even at different income levels. It is estimated to range from 0.01 to 0.66, and exceeds 0.50 in the ICU [1, 19]. Therefore, assuming a prior probability of 0.27, the probability of the diagnosis of AKI is 0.46 in the case of a positive likelihood ratio of 2, and the probability of the diagnosis of no AKI is 0.12 in the case of a negative likelihood ratio of 0.35. The clinical application is shown in Figure 5.Fig. 5 Clinical application
Discussion
This meta-analysis showed that suPAR could be used as a predictor of AKI, with a comprehensive sensitivity of 0.77 and a comprehensive specificity of 0.64. There was no significant publication bias among the included studies. The prediction effect of suPAR seemed to be different in various AKI occurrence backgrounds. Among the seven included articles, the sensitivity of serum suPAR in the diagnosis of AKI ranged from 0.63 to 0.90, and the specificity varied from 0.40 to 0.83, with significant difference. This may be attributed to the differences in the research design and experimental methods in response to various population levels or diseases, resulting in different detection thresholds. The testing instruments and diagnostic reagents used in different countries were not identical, and differences also existed at the operator level. The box plot for heterogeneity reflected that the studies of Anne Byriel Walls [13] and Yuhan Qin [17] might be the main sources of heterogeneity.
In the recent years, the discovery and application of new biomarkers for early diagnosis of AKI have become one of the hot spots in kidney disease research. A previous study showed that plasma suPAR was an incidental phenomenon associated with the inflammatory shedding of receptors on neutrophils, monocytes, and macrophages [20]. A mechanistic study on models of kidney disease showed that circulating suPAR (derived from inflammatory cells) interacted with αvβ3 integrins on podocytes, and elevated plasma suPAR levels could predict the occurrence of nephropathy in seemingly healthy individuals and those at risk of chronic kidney disease [21]. This suggested that suPAR played a role in the pathogenesis of AKI. Targeting suPAR has therapeutic promise as it is pathogenic. In experimental mouse models, the use of anti-suPAR MABs eliminated the adverse effects of suPAR on the kidney, indicating that suPAR is a promising therapeutic target for alleviating AKI [10, 22, 23]. Therefore, eliminating suPAR from circulation or neutralizing its biological effects may be a reasonable strategy to reduce the incidence, morbidity, and mortality in AKI. In clinical trials, biomarkers such as suPAR have the advantage of identifying AKI at an early stage and predicting AKI [24].
In this study, Fagan’s plot was used to reflect the clinical applicability of suPAR in predicting AKI. Assuming that the probability before diagnosis is 0.50, the probability of the diagnosis of AKI is 0.68 in the case of a positive likelihood ratio of 2, and the probability of the diagnosis of no AKI is 0.27 in the case of a negative likelihood ratio of 0.36. Most importantly, if AKI can be predicted, there will be more testable therapeutics, since the majority of AKI interventions identified in preclinical studies are effective only when implemented before injury[25]. The current biomarkers under study, such as neutrophil gelatinase-associated lipid calin (NGAL), kidney injury molecule 1, urinary IL 18, and plasma cystatin C, are also early markers of AKI [26]. Studies have found that ROC analysis of suPAR and NGAL yielded an area under curve (AUC) of 0.69 and 0.78, respectively, without a significant difference (p = 0.117). The AUC of suPAR combined with NGAL was 0.80, significantly higher than that of suPAR alone (p = 0.032) [13]. Furthermore, tissue inhibitor of metalloproteinases-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) were found to be promising biomarkers for risk stratification in infectious AKI patients requiring renal replacement therapy (RRT) and predictors of AKI in out-of-hospital cardiac arrest survivors [27]. Compared with [TIMP-2] × [IGFBP7], baseline suPAR values have already been reported to have the ability to predict the demand for RRT with good diagnostic accuracy. Urinary [TIMP-2] × [IGFBP7] can be used as an early predictor of moderate and severe AKI as well as a potential tool to monitor the treatment of Kidney-oriented sepsis [28, 29]. Therefore, combining multiple markers can more effectively predict AKI and provide more accurate predictive value for clinical practice. Several studies have demonstrated that using these biomarkers in combination with recommended AKI care practices (e.g., avoidance of nephrotoxins and optimization of hemodynamics) can improve patients’ prognosis [28, 30].
This study has the following advantages. First, it is the first to discuss the predictive value of suPAR for AKI. The analysis results show that suPAR or its related indicators should be considered in the subsequent development or optimization of AKI prediction tools/scoring systems. Second, the quality of the included literature is ideal, and there is no bias in the results based on the data. Meanwhile, this study also has the following limitations. On the one hand, although we conducted a comprehensive and systematic search, there are still few studies included in this meta-analysis. On the other hand, with a limited number of included studies, there is no sufficient evidence to support our discussion on the predictive effect of AKI under different occurrence backgrounds.
Conclusion
SuPAR may be a valuable biomarker for predicting AKI, suggesting that suPAR or its related indicators should be considered in subsequent development or optimization of predictive tools/scoring systems for AKI. Although a comprehensive search was performed, the number of included articles is relatively small. Large-scale studies are desired to verify our findings in the future.
Acknowledgements
We would like to thank the researchers and study participants for their contributions.
Author contributions
YH and SH: wrote the main manuscript and fully participated in all analyses. XZ and SH: contributed to the study concept and design. YH and ML: participated in literature search, data extraction, and quality assessment. All authors read and approved the final manuscript.
Funding
This study was funded by Peak Climbing Project of Foshan Hospital of Traditional Chinese Medicine. ID: (202000205)
Data availability
Data sharing not applicable to this article as no datasets were generated or analysed during the current study
Declarations
Conflict of interest
The authors declare that they have no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36469196 | PMC9734903 | NO-CC CODE | 2022-12-14 23:28:31 | no | Clin Exp Nephrol. 2022 Dec 5;:1-11 | utf-8 | Clin Exp Nephrol | 2,022 | 10.1007/s10157-022-02300-2 | oa_other |
==== Front
Gene Ther
Gene Ther
Gene Therapy
0969-7128
1476-5462
Nature Publishing Group UK London
36482074
376
10.1038/s41434-022-00376-9
Brief Communication
Potential of an anti-bevacizumab idiotype scFv DNA-based immunization to elicit VEGF-binding antibody response
Silva Tábata Almeida 1
http://orcid.org/0000-0002-7687-3495
Aguiar Rodrigo Barbosa [email protected]
1
Mori Marcelo 2
Machado Gabriel Esquitini 1
Hamaguchi Barbara 1
Machado Marcelo Ferreira Marcondes 1
http://orcid.org/0000-0003-2812-5887
Moraes Jane Zveiter [email protected]
1
1 grid.411249.b 0000 0001 0514 7202 Department of Biophysics, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP Brazil
2 grid.411087.b 0000 0001 0723 2494 Instituto de Biologia, Universidade Estadual de Campinas, Campinas, SP Brazil
8 12 2022
15
14 1 2022
8 11 2022
15 11 2022
© The Author(s), under exclusive licence to Springer Nature Limited 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Anti-idiotype antibodies have been considered for vaccination approaches against different diseases, including cancers. Based on that, we previously described an anti-bevacizumab idiotype monoclonal antibody, 10.D7, that revealed detectable antitumor effects on a vascular endothelial growth factor (VEGF)-dependent tumor model. Herein, we evaluated the possible applicability of a single-chain variable fragment (scFv) for the 10.D7 antibody in a gene immunization strategy. After checking that mammalian cells transfected to express the 10.D7 scFv are recognized by bevacizumab, it was explored the ability of our scFv construction, in a gene-based scheme, to elicit an immune response containing VEGF-binding antibodies. The results provide evidence that the designed 10.D7 scFv construct maintains the anti-bevacizumab idiotype features and has potential to activate an immune response recognizing VEGF.
Subject terms
DNA vaccines
Gene therapy
https://doi.org/10.13039/501100003593 Ministry of Science, Technology and Innovation | Conselho Nacional de Desenvolvimento Científico e Tecnológico (National Council for Scientific and Technological Development) Fundaçao de Amparo à Pesquisa do Estado de Sao Paulo, FAPESP
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pmcIntroduction
Based on the idiotype network theory [1], an anti-idiotype (Id) antibody reacts with the binding site of a particular antibody, presenting features that make it behave as an antigen surrogate. Anti-Id antibodies have been proposed to be used in vaccination against diseases, including those autoimmune [2], infectious [3], and neoplastic [4], especially for inducing antibody responses targeting proper or difficult-to-emulate conformational determinants [5–7]. Although several of the anti-Id applications use full-length monoclonal antibodies (mAbs) [8], polyclonal antibodies and immunoglobulin-derived recombinant formats have also been considered as immunogen [9]. An artificial antibody construction frequently used for that purpose is the single-chain variable fragment (scFv), which consists of the variable regions of the immunoglobulin heavy and light chains joined by a flexible linker [10].
The vascular endothelial growth factor (VEGF) is a self-glycoprotein known to participate in many physiologic and pathologic events [11]. This molecule is the main target of antiangiogenic strategies for cancer treatment. The first and most promising therapeutic product against a pro-angiogenic factor is a humanized anti-VEGF mAb, called bevacizumab. This antibody was initially approved by US FDA for use in colorectal carcinoma and, later, also in non-small cell lung carcinoma, cervical cancer, progressive glioblastoma, and renal cell carcinoma, among others [12].
We have formerly described an anti-bevacizumab idiotype mAb, 10.D7, that elicits VEGF-binding antibodies and shows considerable therapeutic potential in a tumor mouse model [13]. Herein, we report a proof-of-concept study aimed to evaluate whether an scFv for the 10.D7 mAb would maintain the anti-Id property of the corresponding full-length mAb and activate a VEGF-binding antibody response when used as an immunogen.
Materials and methods
Cell culture
HEK 293 T cells (ATCC, Manassas, VA, USA) were cultured in DMEM (Thermo Fisher Scientific, Waltham, MA, USA), and B16-F10 cells (ATCC) in RPMI-1640 (Thermo Fisher Scientific). Both media were supplemented with 10% fetal bovine serum (FBS; Thermo Fisher Scientific). 10.D7 hybridoma cells were maintained in RPMI-1640 containing 10% FBS and 50 μM 2-mercaptoethanol. All cells were cultured at 37 °C in a humidified atmosphere with 5% CO2 and were regularly checked for mycoplasma contamination.
Construction of 10.D7 scFv gene
Total RNA was isolated from 106 10.D7 hybridoma cells with TRIzol (Thermo Fisher Scientific). The cDNA of VH and VL were synthesized with oligos A and C, respectively, using High-capacity cDNA reverse transcription kit (Applied Biosystems, Waltham, MA, USA) (Table 1), as previously described [14]. Briefly, a solution containing 1 μg RNA in 5 μl of sterile water, 1 μl of 10 × buffer, 0.4 μl dNTP at 100 mM, 1 μl 10x random primer, 0.5 μl MultiScribe reverse transcriptase (Thermo Fisher Scientific) at 50 U/µl, and 2.1 µl of sterile water, totaling a 10-µl final volume, was prepared. The reaction was conducted in a thermocycler at 25 °C for 10 min, 37 °C for two hours, and 85 °C for 5 min.Table 1 Sequence of primers used for the isolation of VH and VL from 10.D7 mAb.
Primer ID Sequence
A 5′-AG GT{G/C} {A/C}A{A/G} CTG CAG {G/C}AG TC{A/T} GG-3′
B 5′-TGA GGA GAC GGT GAC CGT GGT CCC TTG GCC CC-3′
C 5′-GAC ATT GAG CTC ACC CAG TCT CCA-3′
D 5′-CCG TTT GAT TTC CAG CTT GGT GCC-3′;
5′-CCG TTT TAT TTC CAG CTT GGT CCC-3′;
5′-CCG TTT TAT TTC CAA CTT TGT CCC-3′;
5′-CCG TTT CAG CTC CAG CTT GGT CCC-3′
The DNA fragments encoding for the VH and VL domains of 10.D7 mAb were then amplified by PCR using A + B and C + D oligo pairs (1 μM each), respectively (Table 1). PCR work solution was prepared according to the manufacturer’s instructions: 5 µl of cDNA diluted 1:100 in sterile water, 0.25 µl of sense primer and 0.25 µl of antisense, 12.5 µl of Master Mix (Thermo Fisher Scientific), and 7 µl of sterile water. The antibody heavy chain amplification conditions were: 94 °C for 3 min; 40 cycles at 94 °C for 1 min, 62 °C for 30 s, and 72 °C for 1 min; and a final incubation of 5 min at 72 °C. The light chain amplification conditions were: 94 °C for 3 min; 40 cycles at 94 °C for 1 min, 60 °C for 30 s and 72 °C for 1 min; 5 min at 72 °C. The products were analyzed by electrophoresis on a 1% agarose gel in TAE (40 mM Tris-acetate, 1 mM EDTA). The DNA bands were detected with SYBR Safe DNA stain (Thermo Fisher Scientific) on a Gel Doc EZ Imager system (Bio-Rad, Hercules, CA, USA). DNA fragments corresponding to VH and VL were purified from the agarose gel with Geneclean (MP Biomedicals, Solon, OH, USA) and further analyzed using BigDye Terminator Ready (Thermo Fisher Scientific) on a genetic analyzer sequencer. The 10.D7 scFv was designed in the VH-linker-VL orientation, using (Gly4Ser)3 as a linker [15], and was synthesized by a gene service (GenScript, Piscataway, NJ, USA) into a pcDNA3.1 expression vector containing the EcoRI and HindIII restriction sites. To confirm the final product, the plasmid vector was digested with EcoRI and HindIII, and the insert englobing the scFv gene was sequenced.
Animals
6–8-week-old male C57Bl/6 mice were obtained from “Centro de Desenvolvimento de Modelos Experimentais para Medicina e Biologia” (CEDEME/UNIFESP, Brazil) animal facility and maintained with a 12:12 h light:dark cycle and water ad libitum. Experiments were performed after anesthetic induction with ketamine (100 mg/kg; Syntec, Brazil) and xylazine (10 mg/kg; Syntec). Mice were euthanized by anesthetic overdose. All procedures were in accordance with the guidelines of the US National Research Council for care and use of laboratory animals [16].
Enzyme immunoassay (ELISA) studies
Cell-bound ELISA was performed to assess whether 10.D7 scFv gene-transfected cells are recognized by bevacizumab. For that, HEK 293 T cells were transfected with pcDNA3.1(+) containing or not the scFv gene, using the Superfect Transfection Reagent (Qiagen, Germany) following the manufacturer’s instructions. Transfected cells were plated on a 96-well plate (2 × 104 cells/well) and fixed with 0.05% glutaraldehyde (Sigma). Endogenous peroxidase was neutralized with 1% H2O2 (Sigma). After blocking with 1% bovine serum albumin (BSA; Sigma) in phosphate-buffered saline (PBS), wells were incubated for 1 h at 37 °C in the presence or absence of 1 µg/ml bevacizumab (Avastin; Roche, Switzerland). After washes with PBS containing 0.1% BSA and 0.05% Tween 20 (Sigma), wells were incubated with biotin-conjugated anti-human IgG (Sigma).
Indirect ELISA was carried out to detect VEGF-binding antibodies in serum samples. 96-well plates were coated with 50 ng/ml recombinant VEGF (Thermo Fisher Scientific), blocked with 1% BSA in PBS, and incubated overnight at 4 °C with bevacizumab (1 μg/ml) or serum samples from animals immunized with pcDNA3.1 or pcDNA3.1-scFv10.D7. Sera were obtained by bleeding the retro-orbital plexus of ketamine/xylazine-anesthetized mice 15 days after the last immunization dose. After washes, wells were incubated with anti-mouse or anti-human IgG secondary antibody (Thermo Fisher Scientific), both conjugated with biotin.
In both assays, after incubation with peroxidase-streptavidin (Sigma) for 30 min at room temperature, the wells were developed with o-phenylenediamine substrate (Sigma). The reaction was stopped with 4 N H2SO4 (Merck, Germany) and absorbance values were read at 490 nm.
Mouse immunization
For gene immunization studies, animals were intramuscularly injected with DNA plasmid (50 µg in each quadriceps) four times at 15-day intervals. Immediately after each administration, six electric pulses (100 V; 40 milliseconds per pulse; 1-second interval) were applied through 10-mm tweezer electrodes (T820-BTX; Genetronics, San Diego, CA, USA) positioned close to the injection sites [17, 18].
In vivo tumor growth
The potential antitumor effect of immunization with 10.D7 scFv gene was assessed in a subcutaneous tumor model. For that, on the 15th day after the last immunization dose, mice were subcutaneously challenged with 5 × 105 B16-F10 cells in the left flank. Tumor growth was monitored daily with a caliper. Two groups: pcDNA3.1-scFv10.D7-immunized, and pcDNA3.1-immunized (empty vector control) mice. Tumor volume was calculated considering the equation: Volume = (large diameter) × (small diameter)2 × 0.52 [19].
Statistical analyses
Statistical analyses were performed with GraphPad Prism, version 7.0 (GraphPad Software, La Jolla, CA, USA). Data were analyzed by Student’s t-test, when two groups were compared, or by one-way ANOVA followed by Bonferroni’s post-test, in the case of multiple comparisons, as indicated in the figure legends. The differences were considered significant when p < 0.05.
Results and discussion
Pre-clinical and clinical studies using plasmid DNA have been described to prevent or treat several diseases, including cancers, and their results are promising [20]. DNA is considered a valuable biomaterial to develop vaccines [21], with some attractive characteristics, such as its good stability. Also, DNA preparations are cost-effective and relative easy to be obtained compared to proteins [20].
In this work, we evaluated the potential of a DNA vaccine strategy, based on the idiotype network theory [1], to trigger immune response containing antibodies that bind to the vascular endothelial growth factor (VEGF). For that, the gene coding a single-chain variable fragment (scFv) [10] for the 10.D7 anti-idiotype (Id) mAb [13] was obtained. The genes of the variable (Fv) regions of the light (L) and heavy (H) chains were isolated from the 10.D7 hybridoma cells, sequenced, and used to construct a conventional scFv in the VH-VL orientation. Figure 1a shows 340-bp and 324-bp bands, referring to purified FvH and FvL products, respectively. BLAST analyses of these sequences showed ~94% and ~97% homology with other FvH and FvL mouse immunoglobulin chains, respectively.Fig. 1 Construction of a plasmid encoding the 10.D7 scFv.
a Gel electrophoresis of RT-PCR amplified products of VH and VL genes from 10.D7 hybridoma cells. VH- and VL-related bands have, respectively, ~340 and ~324 bp. A 1 kb Plus DNA ladder (Thermo Fisher Scientific) was used as a size marker. b Digestion products of pcDNA3.1-scFv10.D7 with EcoRI/HindIII (different clones). ~830-bp band insert, relative to a 100 bp DNA ladder (Promega, Madison, WI, USA), may comprise the 10.D7 scFv gene. Both analyses were performed on a 1% agarose gel.
The designed 10.D7 scFv gene was inserted along with a signal peptide into pcDNA3.1(+) vector to then functionally evaluate the encoded protein. As indicated in Fig. 1b, the digestion of the constructed plasmid DNA with EcoRI/Hindlll releases an insert of ~830-bp, which may correspond to the scFv gene. By using the obtained vector, our scFv gene was first checked whether it expresses a product recognized by bevacizumab. That analysis was performed by cell-bound ELISA in HEK 293 T cells transfected to express or not the 10.D7 scFv. Figure 2a shows that the bevacizumab binding to cells transfected with pcDNA3.1-scFv10.D7 plasmid is significantly higher than the detected in the empty vector group (p < 0.001; one-way ANOVA, followed by Bonferroni’s post-test). This result indicates that the designed scFv may preserve the bevacizumab-binding ability of the parental full-length mAb and, if any mismatched VH-VL arrangement occurred, which was already found for other scFvs [22, 23, 24], it does not seem to have affected the antibody anti-Id feature.Fig. 2 Evaluation of the 10.D7 scFv binding and the antitumoral activities of the designed vaccine.
a Cell-bound ELISA detection of bevacizumab recognition of HEK 293 T cells transfected with pcDNA3.1-scFv10.D7. Cells transfected with pcDNA3.1 (empty vector) were used as control. Bevacizumab binding was detected with biotin-conjugated anti-human IgG antibodies followed by peroxidase-streptavidin. Assay performed in quadruplicate. Mean ± SD. **p < 0.001; one-way ANOVA/Bonferroni’s post-test. b In vivo experimental design. c ELISA detection of VEGF-binding antibodies in 1:100-diluted serum samples collected 15 days after the last immunization dose. Bevacizumab was used as a positive control. Negative control, pre-immune serum. Assay performed in quadruplicate. Mean ± SD. **p < 0.001; one-way ANOVA/Bonferroni’s post-test. d B16-F10 tumor growth curves. Mice were immunized with pcDNA3.1-scFv10.D7 (n = 9) or pcDNA3.1 (empty vector; n = 10). Tumor volume was calculated from the measured perpendicular diameters. Mean ± SD. *p < 0.005; **p < 0.001; Student’s t-test. e Tumor mass (mean ± SD) on the 14th day after tumor cell injection. Assay performed in quadruplicate. **p < 0.001; Student’s t-test.
Thereafter, the designed 10.D7 scFv was explored as a DNA vaccine administered intramuscularly. In our approach, the scFv gene was delivered by electroporation, which was already reported to enhance the expression of plasmid genes [25] and elicit humoral immunity superior to that obtained when used the intramuscular route alone [26, 27]. It has been described the need for up to three doses to generate neutralizing antibodies sufficient to have detectable DNA vaccination efficacy [28]. We evaluated the presence of VEGF-binding antibodies after two and four doses, and the results, despite varying between animals, revealed in most cases the same antibody levels at both time points. However, we also had mouse whose antibody response was detected only in the last sample point considered (Supplementary Fig. 1), which led us to use in this work a four-dose protocol with the intention to maximize the number of responders. The vaccination protocol, provided in Fig. 2b, was designed based on the described previously [18].
VEGF-binding antibodies were assessed 15 days after the fourth immunization dose. For that, sera from C57BI/6 mice immunized with pcDNA3.1 or pcDNA3.1-scFv10.D7 vectors were analyzed by ELISA. The comparison between the experimental and empty vector control groups shows a significant difference (p < 0.001; one-way ANOVA/Bonferroni’s post-test) (Fig. 2c), which suggests that the expressed 10.D7 scFv may mimic VEGF and induces an immune response containing antibodies reactive to VEGF, which is a phylogenetically conserved molecule. Thus, this result indicates that the 10.D7 scFv immunization surpass an immune tolerance to a self-antigen [29].
The detected anti-anti-Id antibody levels were relatively low, which is not unexpected. The magnitude of the observed antibody response seems to be consistent with the one in the report used as a base for the 10.D7 scFv vaccination protocol. Like us, such work also showed modest ELISA results after the intramuscular-electroporation delivery of four doses of the gene of an anti-Id scFv that mimics a self-protein [18].
Despite the weak ELISA signals, it was enough to detect an antitumor activity. The application of the 10.D7 scFv gene in an immunization scheme was assessed in the B16-F10 subcutaneous tumor model, which is known to be dependent on VEGF [30]. Animals receiving the pcDNA3.1-scFv10.D7 plasmid showed reduced tumor growth compared to the empty vector control group (Fig. 2d). The average tumor mass at the end of the experiment, on the 14th day after tumor cell injection, was significantly lower in the scFv group than the detected in the control one (p = 0.0002; Student’s t-test) (Fig. 2e). These findings point out that the previously described antitumor effect resulting from full-length 10.D7 mAb immunization [13] is also detected following a 10.D7 scFv gene-based strategy, without the need to have a protein immunogen purified.
Our data bring evidence of a potential vaccine application of the gene of an anti-Id construction conceived from a commercial VEGF-targeting antibody, bevacizumab. Id vaccines have long been considered a treatment option for cancers [31]. The strategy not only has shown potential to influence tumor growth [32], but also has demonstrated some clinical benefits in phase I-III trials [33, 34], which reinforces the relevance of the Id approaches.
The gene vaccine development consists of a multistep process, going from the immunogen formulation format to the immunization regimen, which includes the gene delivery and the number of doses [21]. Although all these aspects can be optimized in the proposed anti-Id vaccine, the used protocol, based on a well-succeeded previous one [18], was useful to detect the potential of the 10.D7 scFv gene to trigger antibodies reacting with VEGF.
Together, our results reveal a promising scFv that may retain the anti-bevacizumab Id features of the previously described parental mAb. Based on the idiotype network, the designed construction has potential to be explored in DNA (or even mRNA) vaccines to activate VEGF-binding responses.
Supplementary information
Supplementary Fig. 1
Supplementary information
The online version contains supplementary material available at 10.1038/s41434-022-00376-9.
Acknowledgements
This work was supported by São Paulo Research Foundation (FAPESP; Grant Number 16/14358-2), and the Brazilian National Research Council (CNPq).
Author contributions
RBA and JZM conceived the experiments. TAS and GEM performed the assays. BH offered technical support. MM and MFMM contributed to scFv construction. All authors analyzed the results. RBA and JZM wrote and revised the manuscript.
Data availability
The data that support the reported results are available from the corresponding authors upon reasonable request.
Competing interests
The authors declare no competing interests.
Ethics approval
Animal procedures were approved by the ethics committee (CEUA) of the “Universidade Federal de São Paulo” (Protocol no. 6710130416).
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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15. de Aguiar RB, da Silva TA, Costa BA, Machado MFM, Yamada RY, Braggion C, et al. Generation and functional characterization of a single-chain variable fragment (scFv) of the anti-FGF2 3F12E7 monoclonal antibody. Sci Rep. 2021; 10.1038/s41598-020-80746-8.
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| 36482074 | PMC9734904 | NO-CC CODE | 2022-12-14 23:28:31 | no | Gene Ther. 2022 Dec 8;:1-5 | utf-8 | Gene Ther | 2,022 | 10.1038/s41434-022-00376-9 | oa_other |
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Gene Ther
Gene Ther
Gene Therapy
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Brief Communication
Potential of an anti-bevacizumab idiotype scFv DNA-based immunization to elicit VEGF-binding antibody response
Silva Tábata Almeida 1
http://orcid.org/0000-0002-7687-3495
Aguiar Rodrigo Barbosa [email protected]
1
Mori Marcelo 2
Machado Gabriel Esquitini 1
Hamaguchi Barbara 1
Machado Marcelo Ferreira Marcondes 1
http://orcid.org/0000-0003-2812-5887
Moraes Jane Zveiter [email protected]
1
1 grid.411249.b 0000 0001 0514 7202 Department of Biophysics, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP Brazil
2 grid.411087.b 0000 0001 0723 2494 Instituto de Biologia, Universidade Estadual de Campinas, Campinas, SP Brazil
8 12 2022
15
14 1 2022
8 11 2022
15 11 2022
© The Author(s), under exclusive licence to Springer Nature Limited 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Anti-idiotype antibodies have been considered for vaccination approaches against different diseases, including cancers. Based on that, we previously described an anti-bevacizumab idiotype monoclonal antibody, 10.D7, that revealed detectable antitumor effects on a vascular endothelial growth factor (VEGF)-dependent tumor model. Herein, we evaluated the possible applicability of a single-chain variable fragment (scFv) for the 10.D7 antibody in a gene immunization strategy. After checking that mammalian cells transfected to express the 10.D7 scFv are recognized by bevacizumab, it was explored the ability of our scFv construction, in a gene-based scheme, to elicit an immune response containing VEGF-binding antibodies. The results provide evidence that the designed 10.D7 scFv construct maintains the anti-bevacizumab idiotype features and has potential to activate an immune response recognizing VEGF.
Subject terms
DNA vaccines
Gene therapy
https://doi.org/10.13039/501100003593 Ministry of Science, Technology and Innovation | Conselho Nacional de Desenvolvimento Científico e Tecnológico (National Council for Scientific and Technological Development) Fundaçao de Amparo à Pesquisa do Estado de Sao Paulo, FAPESP
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pmcIntroduction
Based on the idiotype network theory [1], an anti-idiotype (Id) antibody reacts with the binding site of a particular antibody, presenting features that make it behave as an antigen surrogate. Anti-Id antibodies have been proposed to be used in vaccination against diseases, including those autoimmune [2], infectious [3], and neoplastic [4], especially for inducing antibody responses targeting proper or difficult-to-emulate conformational determinants [5–7]. Although several of the anti-Id applications use full-length monoclonal antibodies (mAbs) [8], polyclonal antibodies and immunoglobulin-derived recombinant formats have also been considered as immunogen [9]. An artificial antibody construction frequently used for that purpose is the single-chain variable fragment (scFv), which consists of the variable regions of the immunoglobulin heavy and light chains joined by a flexible linker [10].
The vascular endothelial growth factor (VEGF) is a self-glycoprotein known to participate in many physiologic and pathologic events [11]. This molecule is the main target of antiangiogenic strategies for cancer treatment. The first and most promising therapeutic product against a pro-angiogenic factor is a humanized anti-VEGF mAb, called bevacizumab. This antibody was initially approved by US FDA for use in colorectal carcinoma and, later, also in non-small cell lung carcinoma, cervical cancer, progressive glioblastoma, and renal cell carcinoma, among others [12].
We have formerly described an anti-bevacizumab idiotype mAb, 10.D7, that elicits VEGF-binding antibodies and shows considerable therapeutic potential in a tumor mouse model [13]. Herein, we report a proof-of-concept study aimed to evaluate whether an scFv for the 10.D7 mAb would maintain the anti-Id property of the corresponding full-length mAb and activate a VEGF-binding antibody response when used as an immunogen.
Materials and methods
Cell culture
HEK 293 T cells (ATCC, Manassas, VA, USA) were cultured in DMEM (Thermo Fisher Scientific, Waltham, MA, USA), and B16-F10 cells (ATCC) in RPMI-1640 (Thermo Fisher Scientific). Both media were supplemented with 10% fetal bovine serum (FBS; Thermo Fisher Scientific). 10.D7 hybridoma cells were maintained in RPMI-1640 containing 10% FBS and 50 μM 2-mercaptoethanol. All cells were cultured at 37 °C in a humidified atmosphere with 5% CO2 and were regularly checked for mycoplasma contamination.
Construction of 10.D7 scFv gene
Total RNA was isolated from 106 10.D7 hybridoma cells with TRIzol (Thermo Fisher Scientific). The cDNA of VH and VL were synthesized with oligos A and C, respectively, using High-capacity cDNA reverse transcription kit (Applied Biosystems, Waltham, MA, USA) (Table 1), as previously described [14]. Briefly, a solution containing 1 μg RNA in 5 μl of sterile water, 1 μl of 10 × buffer, 0.4 μl dNTP at 100 mM, 1 μl 10x random primer, 0.5 μl MultiScribe reverse transcriptase (Thermo Fisher Scientific) at 50 U/µl, and 2.1 µl of sterile water, totaling a 10-µl final volume, was prepared. The reaction was conducted in a thermocycler at 25 °C for 10 min, 37 °C for two hours, and 85 °C for 5 min.Table 1 Sequence of primers used for the isolation of VH and VL from 10.D7 mAb.
Primer ID Sequence
A 5′-AG GT{G/C} {A/C}A{A/G} CTG CAG {G/C}AG TC{A/T} GG-3′
B 5′-TGA GGA GAC GGT GAC CGT GGT CCC TTG GCC CC-3′
C 5′-GAC ATT GAG CTC ACC CAG TCT CCA-3′
D 5′-CCG TTT GAT TTC CAG CTT GGT GCC-3′;
5′-CCG TTT TAT TTC CAG CTT GGT CCC-3′;
5′-CCG TTT TAT TTC CAA CTT TGT CCC-3′;
5′-CCG TTT CAG CTC CAG CTT GGT CCC-3′
The DNA fragments encoding for the VH and VL domains of 10.D7 mAb were then amplified by PCR using A + B and C + D oligo pairs (1 μM each), respectively (Table 1). PCR work solution was prepared according to the manufacturer’s instructions: 5 µl of cDNA diluted 1:100 in sterile water, 0.25 µl of sense primer and 0.25 µl of antisense, 12.5 µl of Master Mix (Thermo Fisher Scientific), and 7 µl of sterile water. The antibody heavy chain amplification conditions were: 94 °C for 3 min; 40 cycles at 94 °C for 1 min, 62 °C for 30 s, and 72 °C for 1 min; and a final incubation of 5 min at 72 °C. The light chain amplification conditions were: 94 °C for 3 min; 40 cycles at 94 °C for 1 min, 60 °C for 30 s and 72 °C for 1 min; 5 min at 72 °C. The products were analyzed by electrophoresis on a 1% agarose gel in TAE (40 mM Tris-acetate, 1 mM EDTA). The DNA bands were detected with SYBR Safe DNA stain (Thermo Fisher Scientific) on a Gel Doc EZ Imager system (Bio-Rad, Hercules, CA, USA). DNA fragments corresponding to VH and VL were purified from the agarose gel with Geneclean (MP Biomedicals, Solon, OH, USA) and further analyzed using BigDye Terminator Ready (Thermo Fisher Scientific) on a genetic analyzer sequencer. The 10.D7 scFv was designed in the VH-linker-VL orientation, using (Gly4Ser)3 as a linker [15], and was synthesized by a gene service (GenScript, Piscataway, NJ, USA) into a pcDNA3.1 expression vector containing the EcoRI and HindIII restriction sites. To confirm the final product, the plasmid vector was digested with EcoRI and HindIII, and the insert englobing the scFv gene was sequenced.
Animals
6–8-week-old male C57Bl/6 mice were obtained from “Centro de Desenvolvimento de Modelos Experimentais para Medicina e Biologia” (CEDEME/UNIFESP, Brazil) animal facility and maintained with a 12:12 h light:dark cycle and water ad libitum. Experiments were performed after anesthetic induction with ketamine (100 mg/kg; Syntec, Brazil) and xylazine (10 mg/kg; Syntec). Mice were euthanized by anesthetic overdose. All procedures were in accordance with the guidelines of the US National Research Council for care and use of laboratory animals [16].
Enzyme immunoassay (ELISA) studies
Cell-bound ELISA was performed to assess whether 10.D7 scFv gene-transfected cells are recognized by bevacizumab. For that, HEK 293 T cells were transfected with pcDNA3.1(+) containing or not the scFv gene, using the Superfect Transfection Reagent (Qiagen, Germany) following the manufacturer’s instructions. Transfected cells were plated on a 96-well plate (2 × 104 cells/well) and fixed with 0.05% glutaraldehyde (Sigma). Endogenous peroxidase was neutralized with 1% H2O2 (Sigma). After blocking with 1% bovine serum albumin (BSA; Sigma) in phosphate-buffered saline (PBS), wells were incubated for 1 h at 37 °C in the presence or absence of 1 µg/ml bevacizumab (Avastin; Roche, Switzerland). After washes with PBS containing 0.1% BSA and 0.05% Tween 20 (Sigma), wells were incubated with biotin-conjugated anti-human IgG (Sigma).
Indirect ELISA was carried out to detect VEGF-binding antibodies in serum samples. 96-well plates were coated with 50 ng/ml recombinant VEGF (Thermo Fisher Scientific), blocked with 1% BSA in PBS, and incubated overnight at 4 °C with bevacizumab (1 μg/ml) or serum samples from animals immunized with pcDNA3.1 or pcDNA3.1-scFv10.D7. Sera were obtained by bleeding the retro-orbital plexus of ketamine/xylazine-anesthetized mice 15 days after the last immunization dose. After washes, wells were incubated with anti-mouse or anti-human IgG secondary antibody (Thermo Fisher Scientific), both conjugated with biotin.
In both assays, after incubation with peroxidase-streptavidin (Sigma) for 30 min at room temperature, the wells were developed with o-phenylenediamine substrate (Sigma). The reaction was stopped with 4 N H2SO4 (Merck, Germany) and absorbance values were read at 490 nm.
Mouse immunization
For gene immunization studies, animals were intramuscularly injected with DNA plasmid (50 µg in each quadriceps) four times at 15-day intervals. Immediately after each administration, six electric pulses (100 V; 40 milliseconds per pulse; 1-second interval) were applied through 10-mm tweezer electrodes (T820-BTX; Genetronics, San Diego, CA, USA) positioned close to the injection sites [17, 18].
In vivo tumor growth
The potential antitumor effect of immunization with 10.D7 scFv gene was assessed in a subcutaneous tumor model. For that, on the 15th day after the last immunization dose, mice were subcutaneously challenged with 5 × 105 B16-F10 cells in the left flank. Tumor growth was monitored daily with a caliper. Two groups: pcDNA3.1-scFv10.D7-immunized, and pcDNA3.1-immunized (empty vector control) mice. Tumor volume was calculated considering the equation: Volume = (large diameter) × (small diameter)2 × 0.52 [19].
Statistical analyses
Statistical analyses were performed with GraphPad Prism, version 7.0 (GraphPad Software, La Jolla, CA, USA). Data were analyzed by Student’s t-test, when two groups were compared, or by one-way ANOVA followed by Bonferroni’s post-test, in the case of multiple comparisons, as indicated in the figure legends. The differences were considered significant when p < 0.05.
Results and discussion
Pre-clinical and clinical studies using plasmid DNA have been described to prevent or treat several diseases, including cancers, and their results are promising [20]. DNA is considered a valuable biomaterial to develop vaccines [21], with some attractive characteristics, such as its good stability. Also, DNA preparations are cost-effective and relative easy to be obtained compared to proteins [20].
In this work, we evaluated the potential of a DNA vaccine strategy, based on the idiotype network theory [1], to trigger immune response containing antibodies that bind to the vascular endothelial growth factor (VEGF). For that, the gene coding a single-chain variable fragment (scFv) [10] for the 10.D7 anti-idiotype (Id) mAb [13] was obtained. The genes of the variable (Fv) regions of the light (L) and heavy (H) chains were isolated from the 10.D7 hybridoma cells, sequenced, and used to construct a conventional scFv in the VH-VL orientation. Figure 1a shows 340-bp and 324-bp bands, referring to purified FvH and FvL products, respectively. BLAST analyses of these sequences showed ~94% and ~97% homology with other FvH and FvL mouse immunoglobulin chains, respectively.Fig. 1 Construction of a plasmid encoding the 10.D7 scFv.
a Gel electrophoresis of RT-PCR amplified products of VH and VL genes from 10.D7 hybridoma cells. VH- and VL-related bands have, respectively, ~340 and ~324 bp. A 1 kb Plus DNA ladder (Thermo Fisher Scientific) was used as a size marker. b Digestion products of pcDNA3.1-scFv10.D7 with EcoRI/HindIII (different clones). ~830-bp band insert, relative to a 100 bp DNA ladder (Promega, Madison, WI, USA), may comprise the 10.D7 scFv gene. Both analyses were performed on a 1% agarose gel.
The designed 10.D7 scFv gene was inserted along with a signal peptide into pcDNA3.1(+) vector to then functionally evaluate the encoded protein. As indicated in Fig. 1b, the digestion of the constructed plasmid DNA with EcoRI/Hindlll releases an insert of ~830-bp, which may correspond to the scFv gene. By using the obtained vector, our scFv gene was first checked whether it expresses a product recognized by bevacizumab. That analysis was performed by cell-bound ELISA in HEK 293 T cells transfected to express or not the 10.D7 scFv. Figure 2a shows that the bevacizumab binding to cells transfected with pcDNA3.1-scFv10.D7 plasmid is significantly higher than the detected in the empty vector group (p < 0.001; one-way ANOVA, followed by Bonferroni’s post-test). This result indicates that the designed scFv may preserve the bevacizumab-binding ability of the parental full-length mAb and, if any mismatched VH-VL arrangement occurred, which was already found for other scFvs [22, 23, 24], it does not seem to have affected the antibody anti-Id feature.Fig. 2 Evaluation of the 10.D7 scFv binding and the antitumoral activities of the designed vaccine.
a Cell-bound ELISA detection of bevacizumab recognition of HEK 293 T cells transfected with pcDNA3.1-scFv10.D7. Cells transfected with pcDNA3.1 (empty vector) were used as control. Bevacizumab binding was detected with biotin-conjugated anti-human IgG antibodies followed by peroxidase-streptavidin. Assay performed in quadruplicate. Mean ± SD. **p < 0.001; one-way ANOVA/Bonferroni’s post-test. b In vivo experimental design. c ELISA detection of VEGF-binding antibodies in 1:100-diluted serum samples collected 15 days after the last immunization dose. Bevacizumab was used as a positive control. Negative control, pre-immune serum. Assay performed in quadruplicate. Mean ± SD. **p < 0.001; one-way ANOVA/Bonferroni’s post-test. d B16-F10 tumor growth curves. Mice were immunized with pcDNA3.1-scFv10.D7 (n = 9) or pcDNA3.1 (empty vector; n = 10). Tumor volume was calculated from the measured perpendicular diameters. Mean ± SD. *p < 0.005; **p < 0.001; Student’s t-test. e Tumor mass (mean ± SD) on the 14th day after tumor cell injection. Assay performed in quadruplicate. **p < 0.001; Student’s t-test.
Thereafter, the designed 10.D7 scFv was explored as a DNA vaccine administered intramuscularly. In our approach, the scFv gene was delivered by electroporation, which was already reported to enhance the expression of plasmid genes [25] and elicit humoral immunity superior to that obtained when used the intramuscular route alone [26, 27]. It has been described the need for up to three doses to generate neutralizing antibodies sufficient to have detectable DNA vaccination efficacy [28]. We evaluated the presence of VEGF-binding antibodies after two and four doses, and the results, despite varying between animals, revealed in most cases the same antibody levels at both time points. However, we also had mouse whose antibody response was detected only in the last sample point considered (Supplementary Fig. 1), which led us to use in this work a four-dose protocol with the intention to maximize the number of responders. The vaccination protocol, provided in Fig. 2b, was designed based on the described previously [18].
VEGF-binding antibodies were assessed 15 days after the fourth immunization dose. For that, sera from C57BI/6 mice immunized with pcDNA3.1 or pcDNA3.1-scFv10.D7 vectors were analyzed by ELISA. The comparison between the experimental and empty vector control groups shows a significant difference (p < 0.001; one-way ANOVA/Bonferroni’s post-test) (Fig. 2c), which suggests that the expressed 10.D7 scFv may mimic VEGF and induces an immune response containing antibodies reactive to VEGF, which is a phylogenetically conserved molecule. Thus, this result indicates that the 10.D7 scFv immunization surpass an immune tolerance to a self-antigen [29].
The detected anti-anti-Id antibody levels were relatively low, which is not unexpected. The magnitude of the observed antibody response seems to be consistent with the one in the report used as a base for the 10.D7 scFv vaccination protocol. Like us, such work also showed modest ELISA results after the intramuscular-electroporation delivery of four doses of the gene of an anti-Id scFv that mimics a self-protein [18].
Despite the weak ELISA signals, it was enough to detect an antitumor activity. The application of the 10.D7 scFv gene in an immunization scheme was assessed in the B16-F10 subcutaneous tumor model, which is known to be dependent on VEGF [30]. Animals receiving the pcDNA3.1-scFv10.D7 plasmid showed reduced tumor growth compared to the empty vector control group (Fig. 2d). The average tumor mass at the end of the experiment, on the 14th day after tumor cell injection, was significantly lower in the scFv group than the detected in the control one (p = 0.0002; Student’s t-test) (Fig. 2e). These findings point out that the previously described antitumor effect resulting from full-length 10.D7 mAb immunization [13] is also detected following a 10.D7 scFv gene-based strategy, without the need to have a protein immunogen purified.
Our data bring evidence of a potential vaccine application of the gene of an anti-Id construction conceived from a commercial VEGF-targeting antibody, bevacizumab. Id vaccines have long been considered a treatment option for cancers [31]. The strategy not only has shown potential to influence tumor growth [32], but also has demonstrated some clinical benefits in phase I-III trials [33, 34], which reinforces the relevance of the Id approaches.
The gene vaccine development consists of a multistep process, going from the immunogen formulation format to the immunization regimen, which includes the gene delivery and the number of doses [21]. Although all these aspects can be optimized in the proposed anti-Id vaccine, the used protocol, based on a well-succeeded previous one [18], was useful to detect the potential of the 10.D7 scFv gene to trigger antibodies reacting with VEGF.
Together, our results reveal a promising scFv that may retain the anti-bevacizumab Id features of the previously described parental mAb. Based on the idiotype network, the designed construction has potential to be explored in DNA (or even mRNA) vaccines to activate VEGF-binding responses.
Supplementary information
Supplementary Fig. 1
Supplementary information
The online version contains supplementary material available at 10.1038/s41434-022-00376-9.
Acknowledgements
This work was supported by São Paulo Research Foundation (FAPESP; Grant Number 16/14358-2), and the Brazilian National Research Council (CNPq).
Author contributions
RBA and JZM conceived the experiments. TAS and GEM performed the assays. BH offered technical support. MM and MFMM contributed to scFv construction. All authors analyzed the results. RBA and JZM wrote and revised the manuscript.
Data availability
The data that support the reported results are available from the corresponding authors upon reasonable request.
Competing interests
The authors declare no competing interests.
Ethics approval
Animal procedures were approved by the ethics committee (CEUA) of the “Universidade Federal de São Paulo” (Protocol no. 6710130416).
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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==== Front
Univers Access Inf Soc
Univers Access Inf Soc
Universal Access in the Information Society
1615-5289
1615-5297
Springer Berlin Heidelberg Berlin/Heidelberg
958
10.1007/s10209-022-00958-9
Long Paper
Integrating online meta-cognitive learning strategy and team regulation to develop students’ programming skills, academic motivation, and refusal self-efficacy of Internet use in a cloud classroom
http://orcid.org/0000-0002-6698-7747
Tsai Chia-Wen [email protected]
1
Lee Lan-Yu [email protected]
2
Cheng Yih-Ping [email protected]
3
Lin Chih-Hsien [email protected]
4
Hung Min-Ling [email protected]
5
Lin Jian-Wei [email protected]
6
1 grid.411804.8 0000 0004 0532 2834 Department of Information Management, Ming Chuan University, No.5 De-Ming Rd., Guishan, Taoyuan, 333 Taiwan, ROC
2 grid.411804.8 0000 0004 0532 2834 International Business and Trade Program, Ming Chuan University, 250 Zhong-Shan N. Road Sec. 5, Taipei, Taiwan, ROC
3 grid.411804.8 0000 0004 0532 2834 Department of Information Management, Ming Chuan University, 250 Zhong-Shan N. Road Sec. 5, Taipei, Taiwan, ROC
4 grid.411804.8 0000 0004 0532 2834 International Academic Publications Research Center, Ming Chuan University, 250 Zhong-Shan N. Road Sec. 5, Taipei, Taiwan, ROC
5 grid.411804.8 0000 0004 0532 2834 Teacher Education Center, Ming Chuan University, 5 De Ming Rd., Gui Shan District, Taoyuan, 333 Taiwan, ROC
6 grid.412566.2 0000 0004 0596 5274 Department of Information Technology and Management, Shih Chien University, No.70, Dazhi St., Zhongshan Dist., Taipei, 104 Taiwan, ROC
3 12 2022
116
24 11 2022
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With the development of technology and demand for online courses, there have been considerable quantities of online, blended, or flipped courses designed and provided. However, in the technology-enhanced learning environments, which are also full of social networking websites, shopping websites, and free online games, it is challenging to focus students’ attention and help them achieve satisfactory learning performance. In addition, the instruction of programming courses constantly challenges both teachers and students, particularly in online learning environments. To overcome and solve these problems and to facilitate students’ learning, the researchers in this study integrated two teaching approaches, using meta-cognitive learning strategy (MCLS) and team regulation (TR), to develop students’ regular learning habits and further contribute to their programming skills, academic motivation, and refusal self-efficacy of Internet use, in a cloud classroom. In this research, a quasi-experiment was conducted to investigate the effects of MCLS and TR adopting the experimental design of a 2 (MCLS vs. non-MCLS) × 2 (TR vs. non-TR) factorial pre-test/post-test. In this research, the participants consisted of four classes of university students from non-information or computer departments enrolled in programming design, a required course. The experimental groups comprised three of the classes, labelled as G1, G2, and G3. G1 concurrently received both the online MCLS and TR intervention, while G2 only received the online MCLS intervention, and G3 only received the online TR intervention. Serving as the control group, the fourth class (G4) received traditional teaching. This study investigated the effects of MCLS, TR, and their combination, on improving students’ programming skills, academic motivation, and refusal self-efficacy of Internet use in an online computing course. According to the results, students who received online TR significantly enhanced their programming design skills and their refusal self-efficacy of Internet use a cloud classroom. However, the expected effects of MCLS on developing students’ programming skills, academic motivation, and refusal self-efficacy of Internet use were not found in this study. The teaching strategy of integrating MCLS and TR in an online programming course in this study can serve as a reference for educators when conducting online, blended, or flipped courses during the COVID-19 pandemic.
Keywords
Online meta-cognitive learning strategy
Online team regulation
Programming skills
Academic motivation
Refusal self-efficacy of Internet use
http://dx.doi.org/10.13039/501100004663 Ministry of Science and Technology, Taiwan MOST 109-2628-H-130-001- Tsai Chia-Wen
==== Body
pmcIntroduction
As an interdisciplinary field, the learning sciences are related to psychology, cognitive science, computer science, education, and sociology [77], well grounded in theory and methodology, along with a significant amount of empirical research that is relevant for the development, implementation, and application of educational technologies [30, 56]. Existing studies indicate that many students find the learning of programming difficult due to its conceptual complexity, including algorithms, variables, arrays, loops, and functions in programming languages, which may further raise barriers for learning programming and reduce students’ learning motivation [107]. Thus, it is necessary to include and integrate innovative teaching methods with technologies to help students achieve better learning performance in programming courses.
In this study, the researchers considered and designed an online programming course according to students’ specific needs for programming concepts and skills to help them develop essential computer competence needed in the workplace. Thus, the researchers adopted effective and appropriate online pedagogies to design a cloud classroom-based programming course aimed to meet students’ needs and programming education goals appropriately. The following subsections introduce these.
Adoption of meta-cognitive learning strategy
Learning programming is considered as a difficult and challenging task for many novice programmers with high withdrawal rates from introductory programming courses [80]. In addition, learning programming may result in resistance to learn among non-information or non-computer majors when their learning experiences and performances are worse than those of computer science majors [25]. It is reported that programming courses typically have a large number of students who fail or drop out, whether computer science majors or not [104]. Many students regard programming courses as difficult and lowly motivating [2, 3, 14, 59, 104]. It is mentioned that the two key reasons for students’ high failure rates in programming courses are teaching methods and curriculum organization [106]. The importance of and need for re-designing and re-developing introductory programming courses is indicated by educators [25].
In this regard, the researchers in this study searched for an effective and practical teaching method; meta-cognitive learning strategy (MCLS) is selected for improving non-computer students’ learning outcomes. MCLS involves active control of learning through the phases of planning, monitoring, and evaluating learning processes [4, 23, 66, 88, 90], and it is noted that some educators provide or use different names for these phases [124]. It is reported that MCLS is a main factor influencing students’ academic achievement [1, 87]. Thus, the researchers adapted MCLS in an online programming course and investigated its effects on developing students’ programming skills, academic motivation, and refusal self-efficacy of Internet use in a cloud classroom.
The need for team regulation
Environmental structuring commonly refers to the digital and physical environments, which may result in students’ distraction [121]. It is reported that the distracting nature of social media and technology may extremely increase the possibility of the mind wandering when students are engaged in an online learning environment [47]. For example, in online learning environments, it is difficult to help students concentrate on coursework due to the distraction of social networking websites (such as Twitter and Facebook), online games, and shopping websites [22, 108]. Therefore, developing and understanding students’ regulation of attention during learning are important factors in the age of digital distraction [119].
In this regard, the researchers adopted team regulation (TR), which is aimed at the coordination between team members [101], to develop students’ regular learning habits and achieve better learning effects in an online learning environment. Within a team, the leader may perform the function of planning, such as assigning tasks to members or allocating roles, so that remaining team members may engage in monitoring activities during the process [28]. In such a collaborative learning environment, learners should manage to regulate their joint activities as well as their individual tasks at hand throughout the learning process [102]. When students study in a collaborative environment, they not only have to regulate their individual learning process but also deal with collaborative activities. For instance, when students are assigned to a team, they have to understand the tasks at hand and communicate with other team members, exchange ideas, give explanations to confused members, and even negotiate about the designated workload [20, 102]. Therefore, the researchers in this study integrated TR with related educational technology to develop students’ regulated learning habits and further improve their programming skills, academic motivation, and refusal self-efficacy of Internet use in a cloud classroom.
The instruction of programming courses faces great challenges all over the world (Martins, de Almeida Souza Concilio & de Paiva Guimarães, [84]). Many educators have indicated that various difficulties emerge in terms of programming instruction [7, 39, 45, 122], including lack of linking theory with practical education and low motivation for learning programming [17]. The limited availability of educational technology matched with appropriate teaching methods for learning programming can lead to students’ low motivation for learning [114]. In order to help students develop practical programming skills, academic motivation, and refusal self-efficacy of Internet use, the researchers integrated MCLS and TR with educational technologies and investigated their effects in this research. For example, students’ programming skills were measured based on the six success dimensions of D&M IS Success Model [27], and the difference between MCLS and non-MCLS groups, or TR and non-TR groups was investigated, to demonstrate whether MCLS and TR could improve students’ programming skills. The research questions (RQ) are listed below.RQ1: Could online MCLS lead to students’ better development in programming skills, academic motivation, and refusal self-efficacy of Internet use in a cloud classroom?
RQ2: Could online TR lead to students’ better development in programming skills, academic motivation, and refusal self-efficacy of Internet use in a cloud classroom?
RQ3: Could the combined intervention of online MCLS and TR lead to students’ better development in programming skills, academic motivation, and refusal self-efficacy of Internet use in a cloud classroom?
This paper first introduces the challenges in programming courses and the problems in online learning environments in Sect. 1. Related literature about the effects and validity of online MCLS, TR, and the dependent variables (programming skills, academic motivation, and refusal self-efficacy of Internet use) are individually portrayed in Sect. 2. Subsequently, Sect. 3 presents the research methodology, the experimental design and procedure, the intervention of online MCLS and TR, along with how students’ programming skills, academic motivation, and refusal self-efficacy of Internet use were evaluated. Then, Sect. 4 illustrates the testing and analysis of data collected, and Sect. 5 discusses the findings in this study and the related literature that supports our research results. Finally, Sects. 6 provides the conclusion and implications for educational institutions and online educators.
Literature Review
Meta-cognitive learning strategy
The term “meta-cognitive learning strategies” (MCLS) and “meta-cognitive strategies” can often be seen used interchangeably in many studies. As Zahedi [124] mentioned, in the past, many scholars have developed their own theories or definitions surrounding the original concept of metacognition but may use different nomenclature. Overall, MCLS can be summarized as learners managing and thinking about the learning process and controlling their own cognition [23, 90, 124]. For the purpose of this study, the definition of MCLS refers to a learner’s awareness of managing, controlling and regulating their learning as well as their thinking process [72], or, put more simply, “thinking about thinking” [4, 124].
Early on, the concept of meta-cognition was introduced by Flavell [31], who suggested it is comprised of meta-cognitive experiences or regulation and meta-cognitive knowledge. In O'Malley and Chamot’s [88] opinion, meta-cognitive strategies include three major categories: self-planning, self-monitoring, and self-evaluating. Meta-cognitive strategies allow students to organize their learning activities, in other words, to plan, monitor, and evaluate the learning process. Nowadays, these strategies are widely used by teachers in different subjects, including language learning, mathematics and chemistry, and in different levels of educational institutions [8, 51, 63, 74, 96, 127].
Summarizing from several existing studies, it is found that there is a positive correlation between the use of MCLS with students’ performance, whether it is in the reading comprehension field [16, 50, 126], computer-related courses, or other subjects [100, 127], and this effect is also observed in the MOOCs environment [58]. These studies show that deploying MCLS can lead students to better academic performance. Furthermore, some studies focus on other positive effects of MCLS; for example, the findings in Ho and Kuo’s [46] study reveal that the positive impact on learning outcomes of students’ attitudes was broadened by the feeling of being in control and the sense of concentration during the learning activity, as well as curiosity and intrinsic interest. Therefore, MCLS was adopted and implemented in our re-designed programming course in an online learning environment, and this research also explored the impact of MCLS on improving students’ learning effects.
Team regulation
Team regulation (TR) is defined as the dynamic means through which “team members share their understanding of their task and environment, interpret their team feedback in comparison to their stated objectives, and enact coordinated effort toward their team goal” [61]: 276; [92]. In some studies, TR is referred to as co-regulation [15, 36, 102], which requires metacognitive interactions between group members, whether it is about sharing opinions, monitoring task processes, or evaluating learning progress [40, 65, 69]. These activities include communicating among team members, planning of activities, and monitoring of team [20, 102].
As team members set up their collective goals and act according to their assigned roles, they may receive feedback for their collective performance. Some researchers focus on the social aspects of TR, such as the influence of team feedback [93], and their findings show that feedback to teams could have significant effect on future team outcomes. De Jong and colleagues [26] found that, when in teams, students put more focus on interactive activities such as sharing opinions and reaching common ground. In addition, it is reported that group feedback (in the form of team performance appraisals or evaluation) and group goals are closely related (Van der Vegt, Emans & Van De Vliert [112]).
Moreover, it is also mentioned that students who are learning in computer-based learning environments require regulation in their learning process in order to avoid ill-structured learning tasks. Students who are assigned in teams often need to make extensive learning choices and need to keep monitoring and evaluating throughout the process. When they are assigned to teams, regulation of the collaborative learning process is essential to the outcomes of their learning [5]. There are also studies which point out that students perform better in monitoring progress and creating meaningful thinking or discussion when computer-based communication tools are provided [102]. Furthermore, it is also indicated that a user-friendly online learning platform could be helpful for the development of students’ programming skills (Buyrukoğlu, in press, Moodle meets this criterion [37]) and was used as a platform in this study. Therefore, the researchers in this study adopted online TR to develop students’ programming skills, academic motivation, and refusal self-efficacy of Internet use in an online programming course in this study.
Students’ programming skills
Computer programming is a subject that requires strategies to develop students’ ability of solving problems and involves many programming logic activities [41]. The practice of computer programming is a mechanism for students’ development of computational thinking (CT) ([78], Restrepo‐Calle, Ramírez Echeverry & González, [98]). However, it is indicated that developing students’ programming skills is a very complex and hard task with a high rate of failure [53]. Moreover, it is important to evaluate students’ work when they learn about computer programming (Restrepo‐Calle, Ramírez Echeverry & González, [98]). The existing literature indicates that the efficiency of summative and formative assessment for novice programmers can be improved based on a computer-based or technology-enhanced learning environment which can provide comprehensive and strong feedback [10]. In this study, the researchers regard students’ programming skills as their ability to design and develop a program, system, or application by using Visual Basic for Applications (VBA) with purposive functions. Then, the effects of online MCLS and TR on improving students’ programming skills were investigated.
Academic motivation
Academic motivation refers to a set of motives associated with distinct achievement goals and includes both intrinsic and extrinsic motivation [67, 68, 111]. It is demonstrated to be an important element in both traditional and online learning environments when the positive relationship of students’ grades with academic motivation was investigated [49]. For example, students’ academic motivation as a substantial predictor of academic success has been demonstrated in online learning space [33, 52, 89, 123].
It is revealed that self-regulation and academic motivation are two of the critical “soft skills” for students to develop [38, 82, 99, 110]. It is also reported that SRL positively affects a sense of learning achievement, as well as learners’ motivation and behaviour (Lee, Watson & Watson, 2019). Moreover, existing literature indicates that academic motivation is one of the crucial features when designing an effective online course [6]. Thus, the researchers in this study extended SRL to TR and integrated it with MCLS to help students achieve better development of academic motivation and programming skills in an online course.
Refusal self-efficacy of internet use
With the advancement of technology, Internet use, smartphones, and web-based applications have become an essential part of modern life. Despite the numerous advantages it brings, excessive Internet use can result in negative or even hazardous effect on people [44, 57, 117, 118]. The convenient and inexpensive Internet environment has resulted in generations of heavy users among college students [21]. Furthermore, due to the educational conditions in Taiwan, compared to their pre-college life, college students may be freer from restraints on using the Internet. Studies surrounding the topic of Internet addiction have increased in recent years, and diverse measurements of this worldwide phenomenon have been developed [44, 71, 75].
In the existing literature, refusal self-efficacy of Internet use is defined as an individual’s belief that she/he can purposely refuse or resist using the Internet in a high-risk situation, such as when a smartphone or computer is turned on [75]. As it is difficult to help students concentrate on coursework in an online learning environment [108], it is critical to develop students’ regular learning habits and their ability to refuse to use Internet before providing online courses to them. Thus, the researchers in this study integrated MCLS and TR in an online programming course to help students develop their refusal self-efficacy of Internet use and further improve their learning performance.
Empirical study
Course setting
In this research, the involved course was a semester-long, two credit-hourly course titled ‘Programming Design’, targeting first-year undergraduate students of a comprehensive university in Taiwan. This course mainly focuses on developing students’ programming skills and concepts by using Visual Basic for Applications (VBA). The teacher in this course first introduced the algorithm, syntaxes, macros, and basic functions of VBA. Then, the teacher applied the approach of MCLS described in section ‘3.3.1. Intervention of meta-cognitive learning strategy’, as well as the strategies of TR introduced in subsection ‘3.3.2. Intervention of team regulation’ for the experimental groups. Then, from the 16th week of the semester, presentations by students began of the programs, applications, or systems they had designed.
Participants
In the context of the present research, the participants from non-computer, non-information departments took a compulsory course titled ‘Programming Design’ for two hours a week. There were 126 undergraduates from four class sections, all with the same instructor. These students comprised 31 males and 95 females. The mean age of participants was 18.89 years. Prior to taking the course, students possessed an average of 1.06 certifications each, related to Microsoft PowerPoint or Microsoft Word. The researchers set up four groups following this experimental design: the MCLS and TR class (G1, n = 26), the MCLS and non-TR class (G2, n = 29), the non-MCLS and TR class (G3, n = 44), and the non-MCLS and non-TR class (G4, control group, n = 27). The experimental design of the four groups is shown in Fig. 1.Fig. 1 The different instructional designs for this study
Experimental design and procedure
The experimental design comprised a 2 (MCLS vs. non-MCLS) × 2 (TR vs. non-TR) factorial pre-test/post-test design. G1 concurrently received the intervention of online MCLS and TR; G2 received only the intervention of online MCLS; G3 received only the intervention of online TR, with these three as the experimental groups. The non-MCLS and non-RL group (G4) received the traditional teaching method and served as the control group. The course schedule followed is illustrated in Fig. 2.Fig. 2 Schedule of the course and assessment during the semester
Intervention of meta-cognitive learning strategy (for G1 and G2)
In the existing literature, meta-cognitive models for instructing students have been developed by Winne and Hadwin [116] and Pintrich [94]. The former model suggests that learners initiate a process of four basic stages: defining tasks at hand, setting goals and constructing plans, enacting learning strategies, and making adjustments according to performance. The second model presented by Pintrich [94] is structured similarly, with forethought, planning and activation, monitoring, control, reaction, and reflection as its components [24]. In addition, meta-cognitive learning strategies such as goal setting, strategic planning, and self-evaluation are included in the useful strategies applied by MOOCs users [58].
When looking for the proper model for practical instruction in a programming course, the researchers discussed and reflected on previous teaching and adopted the Cognitive Academic Language Learning Approach (CALLA) first presented by Chamot & O'Malley [13]. The CALLA model consists of five steps: preparation, presentation, practice, evaluation, and expansion [1, 24]. Although it was originally used in language learning, the core concept of MCLS can be employed in other subjects. Thus, CALLA was adopted for students in G1 and G2 with the following approaches:Preparation: In this initial phase, the educator provided assistance to learners who are developing their meta-cognitive awareness and made sure they realize the significance of meta-cognitive learning strategies;
Presentation: The educator further explained the nature of meta-cognitive learning strategies to learners through various examples, such as its characteristics, usefulness, and applications, so that they gained explicit instructions regarding how to use these strategies;
Practice: The learners had the opportunity to start employing the meta-cognitive learning strategies with the tasks at hand. They became aware of the multiple strategies available and understand the appropriate use of them;
Evaluation: Evaluation is one of the keys in meta-cognitive learning strategies, and the educator asked learners to document and evaluate their learning progress in the course;
Expansion: In the final phase, the educator encouraged learners to find out which are the most effective meta-cognitive learning strategies for them, let them discover new ways of applying these strategies (i.e. other subjects or aspects), or guided them to share their own combinations and interpretations of meta-cognitive learning strategies.
Intervention of team regulation (for G1 and G3)
Self-regulation-related theories have been extended to the team level [92], such as the team regulatory focus for team function and performance [73]. TR is associated with the process by which team members share individual knowledge regarding their task and environment, analyse and respond to team feedback, and coordinate actions toward team goal [61, 92]. TR focuses on coordination of the collaboration between students, while the intrinsic factors comprise planning of their activities and monitoring of their team process [101].
TR processes are critical factors of team performance and have the potential to be applied in a variety of interventions such as training, leadership, and provision of goals and feedback [62]. It is indicated that, given the potential for information technology to leverage TR, there has been little significant effort to apply this practical set of research findings [60]. In order to effectively implement TR in this study, the researchers in this study adopted Fleishman & Zaccaro’s [32] and Kozlowski & Ilgen’s [62] team performance functions to help G1 and G3 students benefit from this intervention, including the following seven functional categories:Orientation functions, including information exchange regarding team member resources and limitations;
Resource-distribution tasks, which involve balancing the workload across team members;
Timing functions, which indicate when activities are conducted;
Response-coordination functions, including the synchronization and timing for coordination;
Motivational functions, comprising such aspects as balancing attention on goals of individuals and of the team;
Systems-monitoring functions, which enable the corrections of team and individual activities in response to errors. It is also reported that monitoring goal progress is a critical mechanism through which teams can attain the positive outcomes of team efficacy [97],
Procedure maintenance, which includes monitoring of general procedures and activities.
Furthermore, as it is reported that many students engage on social networks for considerable time, educational institutions could use this habit and technology for educational purposes [79]. Thus, in the implementation of TR, students from G1 and G3 were also required to form groups in an online chat APP (e.g. LINE, WeChat, or even Facebook), for goal setting, information sharing, interaction, reminder, monitoring, and resource sharing.
Intervention for control group (G4)
Students in the control group G4 received the identical learning materials, assignments, practice time, and class hours as those in G1, G2, and G3; however, they did not have to adopt MCLS nor implement TR. The teaching in the control group focused on traditional lectures on basic syntaxes and functions of VBA and required completion of the applications with expected functions by the involved students.
Measurement
Pre-tests of students’ computing skills, academic motivation, and refusal self-efficacy of Internet use
Programming skills In this programming course, the researchers in this study took students’ learned programming skills as their learning effect. In order to investigate whether our interventions of MCLS or TR were effective or not, the researchers in this study first checked if students had ever learned how to write programming code, had an experience of programming, or learned how to use VBA prior to this programming course. This could reduce the possibility and potential threat from students’ initial differences in programming skills that might result in bias of evaluation. Thus, in the first week of the semester, all students were asked if they had the experience of programming or had learned VBA before this course, and none of them reported having done so. Therefore, it is believed that students in the course had similar levels of writing programming code prior to their receiving the intervention of MCLS and/or TR.
Academic motivation Students from the four groups were asked to complete the questionnaire of Motivated Strategies for Learning Questionnaire (MSLQ), developed by Pintrich et al. [95] as a pre-test of their academic motivation before the course started. MSLQ integrates knowledge of different research domains, including instructional psychology, traditional and online educational research [86], and cognitive psychology [85]. MSLQ includes 81 items and can be divided into two broad categories: (1) a motivation category (31 items) and a learning strategy category (50 items). All items are scored on a 7-point Likert scale, ranging from 1 (not at all true of me) to 7 (very true of me) [86]. In the pre-test, the researchers in this study investigated if any difference of students’ academic motivation existed among the four groups before they received the intervention of MCLS and/or TR.
Refusal self-efficacy of Internet use The measurement of students’ refusal self-efficacy of Internet use in the pre-test could confirm whether they had similar levels of refusal self-efficacy of Internet use in this computing course before the experiment begins. The refusal self-efficacy of Internet use questionnaire is a 6-point Likert scale self-reported questionnaire developed by Lin, Ko, and Wu [75]; it is a self-reported questionnaire measured with a 6-point Likert scale, with 1 being totally unconfident (0%) in resisting or refusing Internet use and 6 being 100% confident in resisting or refusing Internet use. When a person scores low on this questionnaire, it represents the person’s level of refusal of Internet use is lower than a person who has a high score. The version of the questionnaire used in this study was adapted from the work of Lin et al. [76] and contains 19 items from the original questionnaire of 33 items, so the total score ranges from 19 to 114. All of the study participants were required to complete this refusal self-efficacy of Internet use pre-test.
Post-tests of students’ programming skills, academic motivation, and refusal self-efficacy of Internet use
Programming skills In this research, students presented the program or application they designed in the 16th week of the semester. The teacher and researchers mainly graded these according to D&M IS Success Model, which includes six success dimensions: system quality, service quality, usage, user satisfaction, information quality, and net benefits [27]. The more complete and the more functions included in students’ programs or applications, the higher the scores they received.
During students’ presentations, the teacher in this study asked questions and provided comments on students’ designed programs and presentations. Based on the rubrics mentioned above, the teacher graded students’ system demonstration and their oral presentations and recorded the grades. In general, the same grade was given to students on the same team according to the rubric. However, students’ individual grades may have varied because of individual presentation quality and his/her responses to the teacher’s questions.
Academic motivation The post-test measurement of students’ academic motivation was identical to that in the pre-test. In the post-test, all four groups of participants completed the MSLQ in the 17th week of the semester. Then, the differences among the four groups of students regarding academic motivation were analysed and reported.
Refusal self-efficacy of Internet use Students completed the same refusal self-efficacy of Internet use questionnaire adapted from the work of Lin et al. [76], in the seventeenth week for the post-test. The differences among the four groups of students regarding refusal self-efficacy of Internet use in this cloud classroom and course were analysed.
Cloud classroom used in the study
A cloud classroom was provided by the researchers, teacher, and university for students’ learning. Besides the course website (Moodle), students in this study could also log in to the university-developed cloud classroom to use the learning material they needed. They could log in to this cloud classroom via a personal computer or Tablet PC, and review or practice the learned programming skills after class. The necessary software and materials were provided in this cloud classroom for students’ use if they did not own them themselves.
Design of the course website
The involved programming courses in this study were delivered via Microsoft Teams. Moodle was also used as the teaching website for students in the four groups. The synchronous online classes were taught and recorded in Microsoft Teams, where students could review the course content after classes. In addition, the Moodle learning management system was used for providing course description, syllabus, learning materials, assignments, homework submissions, and course-related information. Moreover, students could download the necessary learning files to review or preview. Students from the same class could conduct team discussions or team-on-team discussions using the Moodle forum.
Results
Pre-tests
The researchers in this study attempted to avoid measurement bias before implementing the MCLS and TR teaching approaches by conducting pre-tests. According to the one-way ANOVA pre-tests shown in Table 1, the difference of students’ academic motivation and the level of refusal self-efficacy of Internet use among G1, G2, G3, and G4 are not significant. Moreover, the authors analysed students’ programming skills before the course began. During the first week of the semester, the teacher queried if students had previously learned the programming design tools that were about to be used. Students who knew the required programming skills would have been excluded from this experiment; however, prior to this course, none of them had learned how to program. According to the analysis in the pre-test and the teacher’s precautions, it is believed that participating students possessed equal levels of programming skills, academic motivation, and levels of refusal self-efficacy of Internet use at the initiation of the experiment. Thus, the potential threat of pre-existing variance among students can be excluded.Table 1 One-way ANOVA: pre-test of students’ academic motivation and refusal self-efficacy of Internet use
Dependent variable Group (I) Group (J) Mean difference (I–J) Std. error Sig F p
Academic motivation G1 G2 – 0.111331 0.192011 0.953 1.364 0.257
G3 0.077315 0.188735 0.983
G4 0.219341 0.172859 0.658
G2 G1 0.111331 0.192011 0.953
G3 0.188646 0.186883 0.797
G4 0.330672 0.170835 0.295
G3 G1 – 0.077315 0.188735 0.983
G2 – 0.188646 0.186883 0.797
G4 0.142026 0.167144 0.868
G4 G1 – 0.219341 0.172859 0.658
G2 – 0.330672 0.170835 0.295
G3 – 0.142026 0.167144 0.868
Self-efficacy of Internet use G1 G2 0.505001 0.287474 0.382 1.676 0.176
G3 0.494179 0.282569 0.387
G4 0.534684 0.258801 0.239
G2 G1 – 0.505001 0.287474 0.382
G3 – 0.010822 0.279797 1.000
G4 0.029683 0.255770 1.000
G3 G1 – 0.494179 0.282569 0.387
G2 0.010822 0.279797 1.000
G4 0.040505 0.250245 0.999
G4 G1 – 0.534684 0.258801 0.239
G2 – 0.029683 0.255770 1.000
G3 – 0.040505 0.250245 0.999
Post-tests
Meta-cognitive learning strategy
To investigate the effects of web-based MCLS, the independent samples t test was applied to analyse and compare students’ programming skills, academic motivation, and the level of refusal self-efficacy of Internet use in the MCLS group (G1 + G2) and non-MCLS group (G3 + G4). Table 2 shows that none of students’ programming skills, academic motivation, or refusal self-efficacy of Internet use in the MCLS group were significantly different (p > 0.05). The results in Table 2 indicate that students who received MCLS did not have significant contribution to their development of programming skills, academic motivation, or the level of refusal self-efficacy of Internet use.Table 2 Comparison of students’ programming skills, academic motivation, and the level of refusal self-efficacy of Internet use between MCLS and non-MCLS groups
Dependent variable Group t df Sig. (two-tailed)
MCLS non-MCLS
n M SD SE n M SD SE
Programming skills 55 77.25 9.314 1.256 71 78.00 6.780 0.805 – 0.500 124 0.618
Academic motivation 55 4.28211 0.777874 0.104889 71 4.29396 0.745564 0.088482 – 0.087 124 0.931
Refusal self-efficacy of Internet use 55 3.22010 1.032611 0.139237 71 3.08228 0.996620 0.118277 0.758 124 0.450
Team regulation
To investigate the effect of web-based TR, comparison of students’ programming skills, academic motivation, and the level of refusal self-efficacy of Internet use in the TR group (G1 + G3) and non-TR group (G2 + G4) was carried out via the independent samples t test. The results shown in Table 3 reveal a significant difference (p < 0.05) in student’s programming skills and level of refusal self-efficacy of Internet use between the TR group (G1 + G3) and non-TR group (G2 + G4). However, Table 3 shows that for those who received TR treatment, their academic motivation had no significant increase in this research (p > 0.05).Table 3 Comparison of students’ programming skills, academic motivation, and refusal self-efficacy of Internet use between TR and non-TR groups
Dependent variable Group t df Sig. (two-tailed)
TR non-TR
n M SD SE n M SD SE
Programming skills 70 78.96 7.180 0.858 56 76.07 8.638 1.154 2.048 124 0.043*
Academic motivation 70 4.22581 0.757933 0.090590 56 4.36751 0.754708 0.100852 – 1.045 124 0.298
Refusal self-efficacy of Internet use 70 3.31203 1.042334 0.124583 56 2.93045 0.936143 0.125097 2.136 124 0.035*
*p < 0.05
Meta-cognitive learning strategy and team regulation
One-way ANOVA was again applied to analyse students’ programming skills (grades), academic motivation, and the level of refusal self-efficacy of Internet use under the four conditions (groups). Table 4 reveals that learners of G1, who received the intervention of web-based MCLS and TR, did not have better performance than other groups (G2 receiving MCLS & non-TR teaching method, G3 receiving non-MCLS & TR teaching method, and G4 receiving traditional teaching method). However, it is found that G3 had better development in programming skills than G4 (the control group).Table 4 One-way ANOVA: post-test of students’ programming skills, academic motivation, and refusal self-efficacy of Internet use
Dependent variable Group(I) Group(J) Mean difference (I–J) Std. error Sig F p
Programming skills G1 G2 – 1.086 2.145 0.968 3.089 0.030*
G3 – 3.570 1.981 0.359
G4 2.056 2.181 0.828
G2 G1 1.086 2.145 0.968
G3 – 2.484 1.868 0.623
G4 3.142 2.079 0.518
G3 G1 3.570 1.981 0.359
G2 2.484 1.868 0.623
G4 5.625 1.909 0.038*
G4 G1 – 2.056 2.181 0.828
G2 – 3.142 2.079 0.518
G3 – 5.625 1.909 0.038*
Academic motivation G1 G2 – 0.253708 0.210621 0.694 0.642 0.590
G3 – 0.131970 0.194476 0.927
G4 – 0.250000 0.214124 0.715
G2 G1 .0253708 0.210621 0.694
G3 0.121737 0.183401 0.932
G4 0.003708 0.204118 1.000
G3 G1 0.131970 0.194476 0.927
G2 – 0.121737 0.183401 0.932
G4 – 0.118030 0.187414 0.941
G4 G1 0.250000 0.214124 0.715
G2 – 0.003708 0.204118 1.000
G3 0.118030 0.187414 0.941
Refusal self- efficacy of Internet use G1 G2 0.398215 0.276656 0.560 1.707 0.169
G3 0.217360 0.255449 0.867
G4 0.598928 0.281258 0.215
G2 G1 – 0.398215 0.276656 0.560
G3 – 0.180855 0.240902 0.904
G4 0.200713 0.268115 0.905
G3 G1 – 0.217360 0.255449 0.867
G2 0.180855 0.240902 0.904
G4 0.381568 0.246173 0.496
G4 G1 – 0.598928 0.281258 0.215
G2 – 0.200713 0.268115 0.905
G3 – 0.381568 0.246173 0.496
Discussion and implications
Online education is currently implemented at all levels of educational institutions worldwide to provide students alternative channels for learning during the COVID-19 pandemic [120]. In addition, it is indicated that the adoption of web-enhanced active learning has been emphasized by online educators [81]. Thus, this study redesigned innovative online teaching methods to help students develop programming skills, as well as improve their academic motivation and level of refusal self-efficacy of Internet use in online programming courses. The researchers believe that this research could contribute to e-learning theory in three different ways, particularly during this time of COVID-19 pandemic. First of all, this research may specify how teachers can develop students’ practical programming skills, academic motivation, and refusal self-efficacy of Internet use by applying MCLS in an online learning environment. Secondly, the adoption and implementation of online TR learning strategy is shown to help students develop regular learning habits and further improve their learning performance in the online environment, which is full of social networking websites, shopping websites, and free online games [22]. Finally, this research may be among the first efforts to explore the effects of the various combinations of MCLS, TR, and cloud classroom in an online programming course. For example, in the implementation of MCLS, the teacher asked students to document and evaluate their learning progress in the course. Students had to submit their progress of programming skills and learned knowledge to the course website (Moodle) every week. In addition, in the implementation of TR, students in were required to submit a screenshot of their interaction and discussion for TR via in an online chat APP as homework every week. The teacher could thus take advantage of educational technologies to know and check students’ development progress in programming skills. Based on these contributions, this study may provide references for researchers and educators responsible for online courses, who desire to design appropriate teaching methods, particularly for programming courses.
Effect of meta-cognitive learning strategy
In a recent trend, society and workplaces are beginning to be aware that information ability is a necessary competence for college students to cultivate, as developing computer skills and programming design skills is found to be increasingly crucial [12, 19, 109]. According to previous research [34, 113], MCLS could be more effective in developing students’ programming skills with the integration with educational technology. Thus, the authors in this study were encouraged to apply MCLS in an online programming course to enhance students’ learning performance and to investigate if MCLS could improve students’ academic motivation, and refusal self-efficacy of Internet use.
With respect to our first RQ, the data in Table 2 indicate that MCLS did not significantly improve the MCLS group student’s programming skills (p = 0.618), academic motivation (p = 0.931), or the level of refusal self-efficacy of Internet use (p = 0.450), when compared with the non-MCLS group. Although the expected effects of the online MCLS method on developing students’ programming skills, academic motivation, or refusal self-efficacy of Internet use were not exhibited in this study, the non-significant results and differences may result from the following possible factors. First, based on the researchers’ fifteen-year teaching experiences in private university in Taiwan, teachers have to follow overall policy, such as helping students pass licensure examinations and thus receive official certificates, and accepting the designed syllabus, schedule of teaching in each week, even using the unified textbooks [70]. In such teaching environments, teachers hardly have the freedom to design their courses according to their profession and experience to benefit their students. In this study, the teacher faced the abovementioned restrictions and thus could not effectively expand the effects of MCLS. That is, the expected effects of MCLS can hardly be found in the deadlocked framework of requirements (e.g. unified textbooks, pre-set syllabus) for teachers and students. Second, the length of the experiment period may be another factor of influence. It is pointed out that the one-semester experiment may be too short to result in significant development in students’ learning [64, 108]. Nevertheless, it is still suggested that teachers can integrate MCLS in online courses in the teaching environments with full freedom for a longer period, to help students benefit from the intervention of MCLS and educational technologies.
Effect of team regulation
As the COVID-19 pandemic has led people and students to quarantine and isolation, it is critical to build a sense of community by developing the socio-emotional climate, reducing students’ feelings of isolation and anxiety, and establishing environments for interaction in online courses [91, 105, 115]. Encouraging students’ contributions and prompting discussion are important components of teaching presence in online learning environments [42]. In addition, it is reported that promoting students’ autonomous and regular learning, that involves regulating their learning processes and emotions in different environments, is one of the main challenges in online and higher education [35]. In the present study, the authors adopted online TR and demonstrated its effects on facilitating students’ learning.
As for the second RQ, according to the data shown in Table 3, students who received TR have significantly enhanced programming skills (p = 0.043) and level of refusal self-efficacy of Internet use (p = 0.035). This result is similar to existing research that TR had a positive effect on improving student’s learning processes and outcomes [29, 101–103]. As students from G1 and G3 received the intervention of TR, when they presented their designed applications or systems in a team, the teacher asked questions, provided comments, and graded them based on D&M IS Success Model. However, their individual grades may be different due to each presenter’s work quality and performance.
The data collected show that the difference of students’ academic motivation between the TR group and the non-TR group did not reach statistical significance (p = 0.298). It is indicated that students’ high engagement could limit their distractions; however, it may also lead to a loss of motivation [55]. That is, in the implementation of TR, teachers should pay attention to students’ responses so as to not result in too much pressure and engagement. Based on the results, the authors suggest that teachers could consider applying TR in online programming courses to help students concentrate on their learning and further contribute to their learning performance.
Combined effects of online meta-cognitive learning strategy and team regulation
For our final RQ, we investigated whether the combined intervention of online MCLS and TR led to students’ better development in programming skills, academic motivation, and refusal self-efficacy of Internet use. The data in Table 4 indicate that students who received both online MCLS and TR (G1) did not have significantly better development of programming skills, academic motivation, or refusal self-efficacy of Internet use than those who received traditional teaching (G4). The potential reasons for these non-significant results may be due to the inefficiency of MCLS, which are reported in subsection ‘5.1. Effect of Meta-Cognitive Learning Strategy’. That is, the intervention of online MCLS did not lead to expected effects for G1 students. Thus, the difference of students’ programming skills, academic motivation, and refusal self-efficacy of Internet use between G1 and G4 is not statistically significant.
Although the combined intervention of MCLS and TR did not contribute to better development in students’ programming skills, academic motivation, and refusal self-efficacy of Internet use, as the outcomes suggest, the sole treatment of online TR is found to be effective in developing students’ programming skills. In Table 4, it is seen that G3 students (who only received the online TR intervention) had better development in their programming skills than those in G4 (p = 0.038). Thus, it is believed that the intervention of TR could contribute to students’ learning effects in an online programming course.
Finally, based on the data shown in Table 4, there is a warning signal for teachers who are forced to provide online courses due to the COVID-19 pandemic. Teachers who plan to transform their traditional courses in the classrooms into online form, without re-designing the course or integrating practical and effective teaching methods, may find it hard to help their students gain satisfactory learning outcomes. For example, students who adopted neither MCLS nor TR, in G4, had the lowest programming skills, and refusal self-efficacy of Internet among the four groups, though insignificantly (see Table 4). According to our analysis and findings in this research and recommendations from a previous study [22], it is suggested that online teachers should first analyse their students’ specific needs, adopt appropriate and innovative teaching methods, and redesign their courses, instead of directly transforming their course to the blended, flipped, or fully online form.
Potential problems and limitations of this study
In the present study, the researchers re-designed an online programming course, integrated the innovative and effective teaching methods of MCLS and TR with educational technologies, and examined their effects on improving students’ programming skills, academic motivation, and refusal self-efficacy of Internet use in this course and in a cloud classroom. Conclusions drawn from a quasi-experimental design may inherently have some threats to validity, resulting in the potential of a few limitations and potential problems in drawing solid research conclusions from this research.
All of the students were first checked for previous experience with programming before this course and completed a pre-test to measure their academic motivation and refusal self-efficacy of Internet use before class. However, the researchers did not measure students’ level of programming skills, rather assumed they had similar low level of skills, based on an oral check. Students’ programming skills may not have been the same before they entered this course, and this may potentially affect the results. In addition, each student’s computer competency and readiness for online learning may not necessarily be the same at the start of this course, even though a pre-test was conducted, which may result in bias in the evaluation. Moreover, some potential factors or experimental validity problems, such as Hawthorne effect, may have influenced students’ learning effects. Hence, the validity of the results may potentially be affected by these factors. Teachers who are considering to adopt MCLS and TR in their online, blended, or flipped courses should be cognizant of these individual differences and problems associated with quasi-experimental design, as they may have affected the results and the claimed effects in this study.
Conclusion and directions for future work
As a result of rising demand for online courses, a considerable number of online or blended courses have been designed [83]. In addition, the importance of teachers’ ability to design learning tasks and materials, and appropriately apply technologies in education is internationally recognized [48, 125]. Innovative teaching approaches, new learning strategies, and the use of innovative technologies are necessary to develop students’ generic and specific competencies [11]. In this semester-long experiment, the TR strategy helped students significantly develop their programming skills and increased the level of refusal self-efficacy of Internet use; thus, the authors of this study propose that the TR strategy could enhance students’ learning performance. However, the effect of MCLS teaching strategy on students’ programming skills, academic motivation, and refusal self-efficacy of Internet use, did not show a significant increase in this experiment. Although the MCLS group cannot effectively expand the effects in this research, the MCLS strategy could still be effective with further adjustments and integrated with a flexible teaching environment.
In order to apply educational technology effectively in teaching, educators have to be able to integrate pedagogy, content, and technology well [43]. The findings of this study suggest that teachers of online courses could adopt TR and/or MCLS with appropriate modifications according to their situations, environments, challenges, or students’ abilities and readiness. Finally, the authors suggest that online educators, researchers, and teachers could adapt and re-design their teaching methods and courses based on students’ particular needs and characteristics, to aid them in achieving satisfactory learning performance.
Acknowledgements
The authors would like to express appreciation for the financial support of NSC 109-2628-H-130-001- from the National Science and Technology Council, Taiwan, ROC.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734909 | NO-CC CODE | 2022-12-14 23:28:31 | no | Univers Access Inf Soc. 2022 Dec 3;:1-16 | utf-8 | Univers Access Inf Soc | 2,022 | 10.1007/s10209-022-00958-9 | oa_other |
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NeuroTransmitter
NeuroTransmitter
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10.1007/s15016-022-2998-1
Fortbildung
MS-Versorgung heute und Vision für die Zukunft - eine Rolle für die ASV?
Korsukewitz Catharina 15016109425001
Mäurer Mathias 15016109425002
Wiendl Heinz 15016109425001
15016109425001 grid.16149.3b 0000 0004 0551 4246 Klinik für Neurologie, Universitätsklinikum Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany
15016109425002 grid.492110.f 0000 0001 0697 6942 Stiftung Juliusspital Würzburg, Chefarzt der Klinik für Neurologie, Juliuspromenade 19, 97070 Würzburg, Germany
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pmcDie Behandlung von Menschen mit Multipler Sklerose (MS) wird zunehmend komplexer. Neue Therapiemethoden erfordern die Zusammenarbeit verschiedener Fachleute, um eine bestmögliche Versorgung zu garantieren. Die "Ambulante Spezialfachärztliche Versorgung" soll nun auch für MS die Möglichkeit bieten, Defizite zu überwinden.
Die "Ambulante Spezialfachärztliche Versorgung" (ASV) umfasst die Diagnostik und Behandlung komplexer, schwer therapierbarer und seltener Erkrankungen. Die Grundvoraussetzung für die Teilnahme an der ASV ist die Zusammenarbeit eines interdisziplinären Teams. Spezialisierte Ärztinnen und Ärzte verschiedener Fachrichtungen übernehmen gemeinsam und koordiniert die Diagnostik und Behandlung der in der ASV definierten Erkrankungen.
Die ASV-Teams sind in mehreren Ebenen strukturiert: Neben einer Teamleitung existieren ein Kernteam sowie weitere hinzuzuziehende Ärztinnen und Ärzte. Der Gemeinsame Bundesausschuss (G-BA) definiert dabei die Qualifikation des ASV-Teams sowie den diagnostischen und therapeutischen Leistungsumfang. Bislang liegen erkrankungsspezifische ASV-Anforderungen für unterschiedliche medizinische Leistungsbereiche vor, unter anderem für rheumatologische, verschiedene onkologische, aber auch für neuromuskuläre Erkrankungen. Zum Jahreswechsel 2023 soll nach langer Vorbereitungszeit das Angebot der ASV nun auch auf Patientinnen und Patienten mit MS ausgeweitet werden.
MS-Versorgung - aktueller Stand
Auf Basis der Analyse von Krankenkassendaten konnten epidemiologische Studien zeigen, dass in Deutschland zwischen 200.000 und 250.000 Menschen an MS erkrankt sind [1, 2]. Der in den Studien ermittelte Prävalenzwert von 278 pro 100.000 Einwohnerinnen und Einwohner übersteigt deutlich den häufig noch in Lehrbüchern genannten Wert von circa 149 MS-Erkrankten auf 100.000 Personen, der im Jahr 2000 auf Grundlage einer repräsentativen Befragung von Arztgruppen ermittelt wurde. Die Zahl der MS-Erkrankten in Deutschland ist somit wesentlich höher als lange Zeit angenommen.
Die MS ist die weitaus häufigste neurologische Erkrankung, die im jungen Erwachsenenalter zu bleibenden Behinderungen führen kann. Sie hat daher eine erhebliche sozialmedizinische Bedeutung, der bei der Versorgung Rechnung getragen werden muss.
Die Zahlen aus Deutschland werfen, auch mit Blick auf die weltweite Entwicklung der MS-Prävalenz, die Frage auf, ob die Häufigkeit von MS zunimmt, unter anderem weil mit bestimmten "westlichen" Lebensgewohnheiten die Anfälligkeit für Autoimmunerkrankungen generell steigt. So könnte zum Beispiel eine zu starke Hygiene vor allem im Kleinkindalter dazu führen, dass das Immunsystem eine unzureichende Toleranz entwickelt. Ernährungsgewohnheiten wie eine zu salz- und fettreiche Ernährung können ebenfalls Autoimmunität fördern.
Zusätzlich dürften auch die immer sensitiver werdenden Diagnosemethoden einen Anteil am Anstieg der Prävalenz haben. Seit Mitte der 1980er-Jahre ist die Magnetresonanztomografie (MRT) zunehmend flächendeckend verfügbar, was die Diagnosestellung von entzündlichen ZNS-Erkrankungen erleichtert. Die Integration der MRT-Befunde in die MS-Diagnosekriterien seit Anfang der 2000er-Jahre macht es zudem möglich, MS früher und sensitiver zu diagnostizieren [3].
Parallel zu der diagnostischen Verbesserung wurden zahlreiche Medikamente zugelassen (Abb. 1), mit denen der Verlauf der Erkrankung erfolgreich moduliert werden kann. Mittlerweile sind weit über ein Dutzend unterschiedlicher MS-Medikamente mit verschiedenen Wirkansätzen verfügbar. Diese rasante Entwicklung war vor allem durch das zunehmende Verständnis der Pathophysiologie von MS möglich. Im Fokus der Therapieforschung standen neben der Verhinderung der Immunzell-Transmigration über die Blut-Hirn-Schranke in das ZNS vor allem immunregulatorische Netzwerke mit T- und B-Zellen. Insbesondere der Erfolg B-Zell-depletierender Therapien zur Unterdrückung von Inflammation und somit der Krankheitsprogression unterstreicht die Bedeutung der immunregulatorischen Netzwerke.
Zudem konnte mithilfe von Registerdaten (real-world evidence) gezeigt werden, dass ein früher Einsatz hochwirksamer Therapien den Krankheitsverlauf nachhaltig modulieren kann. Die Erkrankung kann mit den derzeitigen Konzepten zwar nicht geheilt, jedoch bei frühem und konsequentem Einsatz der verfügbaren anti-inflammatorischen Therapien der Verlauf und damit die Lebensqualität vieler Patientinnen und Patienten mit MS nachhaltig verbessert werden [4].Unmet needs in der Versorgung von MS-Betroffenen Notwendige und zukünftige Maßnahmen Beteiligte Fachdisziplinen
Frühe und sichere Diagnose — klinisch und elektrophysiologisch
— MS-spezifisches MRT
— Liquordiagnostik
— mögliche Zusatzuntersuchungen
— zukünftig: Biomarker
— Neurologie/Neuropädiatrie
— Radiologie
— Neurologie/Labormedizin
— zum Beispiel Rheumatologie
— Neurologie
Frühe und effektive Therapie — Kenntnis der Prognoseparameter
inklusive potenzieller Biomarker
— Risiko/Nutzenanalyse der Therapie
— Vorbereitung vor Therapie
(Laborwerte, Impfberatung)
— Berücksichtigung von Lebensumständen/Komorbidität
— Neurologie
— Neurologie
— Neurologie/Allgemeinmedizin
sowie gegebenenfalls weitere Fachabteilung (z. B. Hepatologie)
— Neurologie sowie gegebenenfalls Gynäkologie/Innere Medizin und andere
Monitoring der Wirkung — klinisch, elektrophysiologisch
— MS-spezifisches MRT
— Kognitionsprüfung
— zukünftig: digitale Hilfsmittel, Biomarker
— Neurologie
— Radiologie
— Neurologie/Neuropsychologie
— Neurologie
Monitoring und Behandlung von Nebenwirkungen — klinisch/Zusatzdiagnostik
— MRT (z. B. PML)
— laborchemisch
— substanzspezifisch weitere Untersuchungen
— Neurologie
— Radiologie
— Allgemeinmedizin/Neurologie/Innere Medizin
— zum Beispiel Ophthalmologie/Dermatologie/ Kardiologie
Erfassung und Behandlung von Symptomen — Kognition/Fatigue
— Motorik/Sensibilität
— Blasen-/Mastdarmstörungen
— Schmerzen
— Neurologie/Neuropsychologie
— Neurologie/Ergotherapie /Physiotherapie
— Neurourologie/Gynäkologie
— Neurologie/Schmerz- und Psychotherapie
Sozialmedizinische und Versorgungsaspekte — Hilfsmittelversorgung
— Hilfe bei Antragstellungen
— Rehabilitation
— Anpassung der Arbeits- und Lebensbedingungen
— Neurologie/Allgemeinmedizin/Ergotherapie
— Arbeits-/Sozialmedizin
— spezialisierte Rehabilitationseinrichtungen
— Pflegedienste/Sanitäts- und Rehabilitationstechnik
— Selbsthilfegruppen
Angesichts dieser erfreulichen, aber sicher noch nicht ausreichenden Entwicklung werden neue Parameter gesucht, mit denen das Ansprechen auf eine Therapie besser kontrolliert werden kann. Vor allem bildgebende Verfahren haben ein hohes Potenzial. Man weiß mittlerweile, dass graue und weiße Substanz gleichermaßen betroffen sind und versucht dies mit Atrophiemessungen und Spezialsequenzen, zum Beispiel zur Eisendetektion, besser abzubilden. Darüber hinaus werden lösliche Biomarker, die Inflammation und Degeneration im ZNS anzeigen, in Zukunft eine zunehmende Bedeutung für die Therapieauswahl und Steuerung bekommen.
Die optimierten Diagnose- und Therapieverfahren haben dazu geführt, dass die MS heutzutage Menschen einer größeren Altersspanne betrifft, unter anderem weil die Langzeitprognose verbessert wurde [5]. Bei Diagnose und Therapie im Kindesalter bedarf es einer sorgfältigen Abstimmung mit der Neuropädiatrie, insbesondere im Hinblick auf die Transition in die Erwachsenenmedizin. Die verbesserten Therapiemöglichkeiten ziehen außerdem spezifische Fragen zur Therapie auch im höheren Lebensalter nach sich. Komorbiditäten, sei es im Herz-Kreislauf-Bereich oder in der Onkologie, spielen eine immer bedeutsamere Rolle.
Die Infektionsprophylaxe durch Impfungen und Schutzmaßnahmen bei Vorliegen einer Autoimmunerkrankung unter Anwendung von Immuntherapien hat ihre Bedeutung als Teil der Beratung von MS-Betroffenen nicht zuletzt in der COVID-19-Pandemie gezeigt.
Nicht zu vergessen sind die Entwicklungen im Segment der symptomatischen Therapie und der Rehabilitationswissenschaften. Moderne Konzepte zur Behandlung und zum Monitoring von MS-spezifischen Symptomen wie Blasenstörungen, Spastizität, Fatigue, Depression und kognitiven Einschränkungen sind hier gefragt. Neben der Kenntnis spezifischer symptomatischer Therapien ist eine Zusammenarbeit mit Therapeutinnen und Therapeuten der Physio-, Logo- und Ergotherapie sowie mit Neuropsychologinnen und -psychologen erforderlich.
Ziel jeglicher therapeutischen Bemühungen ist es, MS-Betroffenen ein normales Leben zu ermöglichen. Hierzu gehört die Beratung von MS-Patientinnen und ihrer Partnerinnen und Partner im Hinblick auf Kinderwunsch und Familienplanung. Die Verfügbarkeit moderner Medikamente macht es möglich, Schwangerschaften aus einer stabilen Erkrankungsphase heraus zu planen beziehungsweise Patientinnen mit hochaktiver MS unter bestimmten Nutzen-Risiko-Abwägungen eine Schwangerschaft zu ermöglichen.
Dieser Abriss zum Stand der Entwicklung in der Versorgung von MS-Kranken macht deutlich, welche komplexen Anforderungen die Betreuung mit sich bringt. Sie verlangt von Neurologinnen und Neurologen erhebliche Kenntnisse nicht nur im Hinblick auf Diagnose und Differenzialdiagnose, sondern vor allem auf die differenzierte Immuntherapie inklusive Risiken und Nebenwirkungen. Daneben besteht angesichts vielfältiger Symptome und alltagsrelevanter Fragestellungen die Notwendigkeit zur interdisziplinären Zusammenarbeit. Die MS ist daher eine Erkrankung, die in besonderem Maße für eine ASV geeignet ist.
Defizite in der Versorgung von MS-Betroffenen
Angesichts der großen Anforderungen ist es nachvollziehbar, dass noch Defizite in der Versorgung von MS-Betroffenen bestehen. Sie sind in der Geschwindigkeit des Fortschritts ebenso begründet wie im Mangel an personellen und zeitlichen Ressourcen, die eine Vernetzung verschiedener Fachdisziplinen und Berufsgruppen erschweren. Verbesserungspotenzial besteht weiterhin auf dem Gebiet der zerebralen und spinalen Bildgebung, obwohl Ärztinnen und Ärzte der Neurologie und Radiologie aufgrund der überragenden Bedeutung des MRTs seit Jahren intensiv zusammenarbeiten. So werden nationale und internationale Empfehlungen zur Durchführung der MRT im Hinblick auf Sequenzen, Schichtführung, Repositionierung oder Kontrastmittelgabe nicht immer umgesetzt [6], was sowohl die Diagnose der MS selbst als auch den Vergleich von Aufnahmen im Verlauf deutlich erschwert. Auch die Erfassung von Atrophiedaten sowohl zerebral als auch des zervikalen Myelons hat trotz erheblicher Bedeutung in der klinischen Forschung bisher kaum Eingang in den klinischen Alltag gefunden.
Neben der Harmonisierung und Weiterentwicklung der Bildgebung stellt auch die strukturierte und multidimensionale Verlaufsbeurteilung von MS-Betroffenen bei knappen Ressourcen eine Herausforderung dar. Das birgt sowohl die Gefahr, alltägliche Probleme nicht zu erfassen und unzureichend zu werten, als auch eine schleichende Verschlechterung verzögert zu erkennen. So leiden zum Beispiel viele Betroffene bereits früh unter kognitiven Einschränkungen [7], die unzureichend erfasst werden, da die zeitlichen, personellen und finanziellen Voraussetzungen für eine neuropsychologische Diagnostik fehlen. In Zukunft sind durch die Digitalisierung neue Möglichkeiten zur Erfassung des Gesundheitsstatus von MS-Betroffenen zu erwarten [8], aber diese müssen natürlich mit Ressourcenaufwand in Kliniken und Praxen etabliert werden.
Die wachsende Zahl verlaufsmodifizierender Medikamente bietet die Chance einer personalisierten Therapie. In Bezug auf ihre sichere Anwendung erfordern jedoch einige der neuen Präparate ein Monitoring, für das Spezialärztinnen und -ärzte anderer Fachdisziplinen zu Rate gezogen werden sollten. Nicht immer erfolgt dies im angemessenen Umfang, zu nennen wäre zum Beispiel die regelmäßige Kontrolle der Immunglobulinspiegel unter einer B-Zell-depletierenden Therapie oder das Hautscreening unter einer Therapie mit S1P-Modulatoren. Etablierte Diagnostik- und Therapiepfade können helfen, das Monitoring und damit die sichere Anwendung von Präparaten zu verbessern.
Nicht zuletzt kann beobachtet werden, dass die Sorge vor Nebenwirkungen einer Immuntherapie häufig im Vordergrund von Therapieentscheidungen steht und damit MS-Betroffenen die richtigen Medikamente zur richtigen Zeit vorenthalten werden. Für eine realistische Nutzen-Risiko-Abwägung bedarf es einer umfassenden Kenntnis einer Substanz sowie ausreichende Zusatzinformationen, zum Beispiel hinsichtlich bildgebender Befunde oder über individuelle Risikofaktoren. Darüber hinaus ist die Kenntnis und sichere Anwendung von De-Risking-Strategien zu nennen - als Beispiel soll die Bestimmung und Bewertung des JCV-Index unter Therapie mit Natalizumab dienen.
Die Rolle der ASV
Vor dem Hintergrund der dynamischen Entwicklungen im MS-Feld und den bekannten Defiziten in der praktischen Versorgung könnte die Einführung der ASV große Chancen bieten: In erster Linie wird sie den komplexen Entwicklungen der Therapielandschaft gerecht werden, zum anderen wird der Auftrag zur interdisziplinären Zusammenarbeit Defizite in der Versorgung verbessern.
Die genaue ASV-Richtlinie für MS ist zwar noch nicht bekannt, es ist aber davon auszugehen, dass die Teamleitung ausschließlich durch Neurologinnen und Neurologen erfolgen und das Kernteam aus Expertinnen und Experten der Neurologie und Neuropädiatrie bestehen wird. An hinzuzuziehenden Fachärztinnen und -ärzten ist zu erwarten, dass Kooperationen mit den Fachgebieten der Augenheilkunde, der Inneren Medizin mit speziellem Fokus auf die Kardiologie, der Radiologie, der Labormedizin, der Psychiatrie, der Urologie, der Gynäkologie und der Pathologie genannt werden.
Es ist weiterhin wahrscheinlich, dass die ASV für Erkrankte mit MS vorgesehen ist, die aufgrund der Ausprägung der Krankheit eine interdisziplinäre Versorgung benötigen. Aufgrund der Komplexität der Erkrankung dürfte sich dies auf alle MS-Verlaufsformen und demyelinisierende ZNS-Erkrankungen beziehen (ICD G35.-, G36.-, G37.-). Es ist für die MS grundsätzlich zu Beginn nicht vorherzusagen, welches Ausmaß an Behinderung mittel- und langfristig zu erwarten ist. Somit ist jede MS als potenziell schwerwiegend anzusehen. Die Erkrankung erfordert daher in allen Stadien ein kontinuierliches, multidisziplinäres Monitoring zur Erfassung ihrer Aktivität und eine angemessene therapeutische Reaktion.
Geht es zu Beginn um eine genaue Identifikation der Krankheitsaktivität mit Abwägung des individuellen Risikos der Erkrankung gegen das der einzusetzenden Therapie mit entsprechendem Monitoring, stehen im Verlauf vor allem Edukation und Krankheitsbewältigung im Vordergrund. Angesichts der Bedeutung von Komorbiditäten und Lebensstilmanagement für den Verlauf der Erkrankung ist eine frühzeitig einsetzende, kontinuierliche multidisziplinäre Betreuung von Bedeutung.
Die medikamentöse Therapie der MS unterliegt nach wie vor einem rasanten Wandel, wird zunehmend individueller und damit komplexer. Grundsätzlich werden Immuntherapien frühzeitig nach Diagnosestellung eingeleitet, wobei ein multidisziplinäres Management eine optimale Wirksamkeit und Sicherheit gewährleistet.
Trotz bester kausal orientierter Therapie wird es zudem nicht gelingen, jede Patientin oder jeden Patienten ohne das Auftreten relevanter Einschränkungen durch die Erkrankung zu begleiten. Insbesondere in späten Phasen, in denen sich neurologische und internistische Störungen zu einem komplexen Ausfallsbild aufaddieren, ist eine multidisziplinäre Begleitung zur Planung einer optimalen symptomatischen Therapie unerlässlich. Management von Spastik, Blasenstörungen und Schmerzen bedürfen der engen Abstimmung von Physiotherapie, Hilfsmittelversorgung, Urologie, Gynäkologie, Schmerztherapie und psychosomatischer Betreuung. Eine Interaktion mit Trägerinnen und Trägern von Rehabilitationsmaßnahmen sowie der Hilfsmittelversorgung und, wenn verfügbar, der Selbsthilfe ist essenziell.
Auch das Beenden einer Immuntherapie bei chronischer Entwicklung braucht Vorbereitung und (Nach-)Monitoring. Mögliche kognitive Einschränkungen der Betroffenen erschweren diese Prozesse. Übergänge in betreutes Wohnen und Pflegeeinrichtungen, die kaum für jüngere Menschen existieren, müssen gebahnt werden.
Obgleich die Herausforderungen in verschiedenen Stadien der Erkrankung unterschiedlich sind, ist die Behandlung, Betreuung und Versorgung von Personen mit MS über den gesamten Krankheitsverlauf hinweg mit einem erheblichen Ressourcenaufwand verknüpft, der durch ein multiprofessionelles Team unter spezialisierter neurologischer Leitung erbracht werden muss. Die ASV bietet eine sinnvolle Möglichkeit, die Versorgung zu verbessern und Barrieren und Defizite zu überwinden, auch weil sie die Verbindung von niedergelassenen Neurologinnen und Neurologen, akademischen Zentren, Schwerpunktpraxen beziehungsweise -zentren fördern kann.
GKV-Spitzenverband, KBV und DKG unter dem Dach des G-BA geben zwar die oben genannten Rahmenbedingungen vor, werden jedoch keine konkreten Vorschläge zur inhaltlichen Ausgestaltung und zur Qualitätssicherung machen. Daher ist die Einführung dieser neuen sektorübergreifenden Versorgungsform dazu geeignet, Qualitätsstandards und Behandlungspfade zu definieren, um eine bestmögliche Versorgung von MS-Betroffenen von Anfang an sicherzustellen und damit generelle Maßstäbe zu setzen. Demnach sind die Neurologinnen und Neurologen als verantwortliche Teamleitungen gefragt, Standards zu definieren. Dieses Angebot sollte mit Engagement angenommen werden.
Dr. med. Catharina Korsukewitz Klinik für Neurologie mit Institut für Translationale Neurologie am Universitätsklinikum Münster
Albert-Schweitzer-Campus 1
48149 Münster
[email protected]
Prof. Dr. med. Mathias Mäurer Klinik für Neurologie, Klinikum Würzburg Mitte
Juliuspromenade 19
97070 Würzburg
[email protected]
Prof. Dr. med. Heinz Wiendl Direktor der Klinik für Neurologie mit Institut für Translationale Neurologie am Universitätsklinikum Münster
Albert-Schweitzer-Campus 1
48149 Münster
[email protected]
==== Refs
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2. Dippel FW et al. Krankenversicherungsdaten bestätigen hohe Prävalenz der Multiplen Sklerose. Akt Neurol 2015;42:191-6
3. Thompson AJ et al. Diagnosis of multiple sclerosis: 2017 revisions of the Mc Donald criteria. Lancet Neurol. 2018;17(2):162-73
4. Wiendl H et al. Multiple Sklerose Therapie Konsensus Gruppe: Positionspapier zur verlaufsmodifizierenden Therapie der Multiplen Sklerose 2021 (White Paper). Nervenarzt. 2021;92(8):773-801
5. Sorensen PS et al. The apparently milder course of multiple sclerosis: changes in the diagnostic criteria, therapy and natural history. Brain. 2020;143(9):2637-52
6. Wattjes MP et al. Magnetic Resonance Imaging in Multiple Sclerosis study group; Consortium of Multiple Sclerosis Centres; North American Imaging in Multiple Sclerosis Cooperative MRI guidelines working group. 2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol. 2021;20(8):653-70
7. Benedict RHB et al. Cognitive impairment in multiple sclerosis: clinical management, MRI, and therapeutic avenues. Lancet Neurol. 2020;19(10):860-71
8. Dillenseger A et al. Digital Biomarkers in Multiple Sclerosis. Brain Sci. 2021;11(11):1519
| 0 | PMC9734911 | NO-CC CODE | 2022-12-14 23:28:31 | no | NeuroTransmitter. 2022 Dec 9; 33(12):32-37 | utf-8 | null | null | null | oa_other |
==== Front
Early Child Educ J
Early Child Educ J
Early Childhood Education Journal
1082-3301
1573-1707
Springer Netherlands Dordrecht
1429
10.1007/s10643-022-01429-9
Article
‘Staying Afloat’: A Mixed Methods Study of the Financial and Psychological Well-being of Early Childhood Educators
http://orcid.org/0000-0003-2230-2408
Vesely Colleen K. [email protected]
1
Brown Elizabeth Levine 1
Mehta Swati 1
Horner Christy Galletta 2
1 grid.22448.38 0000 0004 1936 8032 College of Education and Human Development, George Mason University, Fairfax, VA 22030 USA
2 grid.253248.a 0000 0001 0661 0035 College of Education and Human Development, Bowling Green State University, Bowling Green, OH 43403 USA
8 12 2022
112
16 11 2022
© The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Early childhood educators play a critical role in the lives of young children, especially through their sensitive interactions. Educators’ capacities to engage in high-quality interactions are shaped by their mental health. Studies examining early childhood educators’ mental health often focus on psychopathology or negative aspects of mental health, despite the importance of understanding mental health through a well-being lens. This study explores the connection between two important areas of well-being: psychological and financial well-being. Using mixed methods, we examined 123 early childhood educators’ financial well-being and psychological well-being. Financial well-being predicted psychological well-being, but the relationship was curvilinear; those with the highest and lowest financial well-being had the highest psychological well-being. Qualitative findings suggest possible buffers for psychological well-being among educators with low-financial well-being and highlight struggles of those with low psychological well-being. Implications for how early childhood educators’ well-being might be supported with policy and practice initiatives are discussed.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10643-022-01429-9.
Keywords
Teacher well-being
Financial well-being
Psychological well-being
Early childhood educators
Early childhood education
==== Body
pmc“The research picture is clear—quality of care and education matters to the lives of young children, and teachers and caregivers are central to providing that quality,” (National Academy of Sciences, 2012, p. ix). Specifically, early childhood (EC) educators working with children and families living in poverty, facing systemic inequalities, and living in historically disinvested communities, play an even more critical role (Johnson et al., 2020).
“Good quality care requires an environment that values adults as well as children,” (Whitebook et al., 1989, p. 2). Research shows that educators face pressures to conform to professional standards and navigate increased workloads, and challenges to their practice, autonomy, and well-being (Day & Smethen, 2009), which contribute to their emotionally sensitive and cognitively stimulating relationships with children (NICHD, 2006; Shonkoff & Phillips, 2000; Vandell & Wolfe, 2000). EC educators are expected to be “everyday heros” (Johnson et al., 2020, p. 973), especially in the context of the COVID-19 pandemic, and thus more research is necessary to support their health and well-being (Eadie et al., 2021; Jennings et al., 2020). This study begins to explore the connection between two areas of well-being for EC educators: psychological and financial well-being.
Early Childhood Educators’ Well-being
Dual Factor Model of Mental Health: Situating Psychological Well-being
The Dual Factor Model of Mental Health integrates psychopathology (i.e., mental illness including depression) and aspects of subjective well-being (i.e., positive psychology including happiness), or how individuals perceive, experience, or evaluate these objective aspects of well-being and their lives more generally (Diener, 1984; Fox et al., 2020) for a holistic understanding of mental health. Studies focused on EC educators’ mental health (Whitaker et al., 2013), have been specifically focused more on psychopathology or negative aspects of mental health, including stress (Corr et al., 2014; Curbow et al., 2000; Johnson et al., 2020; Zhai et al., 2011), burnout (Blochliger & Bauer, 2018; Rentzou, 2012) and depression (Hindman & Bustamante, 2019; Jeon et al., 2014). Early childhood educator mental health literature related to psychopathology (e.g., stress and depression) is growing; however, inconclusive connections between EC educator mental health and child outcomes remain (Johnson et al., 2020). These inconsistent findings may be explained by the narrow conceptualization of EC educator mental health solely focused on psychopathology or negative psychology, without consideration for the role of psychological subjective well-being. Hall-Kenyon et al. (2014) implored the importance of deepening our understanding of EC educators’ well-being by understanding “the everyday emotional lives of teachers [that] are messy, complex and intertwined” (p. 159).
Ryff’s (1989) multidimensional model of psychological well-being specifically conceptualized psychological subjective well-being to consider both social and emotional influences of an individual’s perception of what does it mean to be well, psychologically? Ryff and Keyes (1995) confirmed that psychological subjective well-being is a “multidimensional structure” (pp. 723–724) with six components: positive relations with others, autonomy, environmental mastery, purpose in life, personal growth and self-acceptance. Positive relations with others refers to how trusting and satisfied one feels about relationships with others. Autonomy reflects independence and how an individual regulates behavior using an internal locus of control based on personal standards and guideposts. Environmental mastery includes how an individual seeks and creates contexts to promote personal needs. Purpose in life is described as meaning in life derived from having goals and directions for the future. Personal growth addresses the evolution of self-knowledge and how an individual perceives new experiences as informing their growth and development. Self-acceptance reflects the individual's positive attitude towards oneself inclusive of seeing both good and bad qualities (Ryff & Keyes, 1995).
Research recently illustrated direct relations between these areas of psychological subjective well-being among EC educators; however, most studies were conducted in international K-12 educational contexts (Greenier et al., 2021; Poormahmood et al., 2017; Villarosa & Ganotice, 2018). Results show that making strong connections with other teachers (Jones et al., 2019) or positive relations with others, and autonomy of teaching environment related to work schedules and freedom to express ideas about practice, informed enhanced psychological well-being (Royer & Moreau, 2016). Jones et al. (2019) showed relationships of EC educators’ psychological well-being to workplace flow and input on environmental mastery. The significant role of environmental mastery for EC educators’ well-being was also found in a study of Finnish educators that described limited control regarding “insurmountable demands” related to administrative work that left less time for work with children (Ylitapio-Mäntylä et al., 2012). Despite these important contributions, psychological well-being may vary by country, especially in terms of environmental mastery and purpose in life (Özü et al., 2017) necessitating the expansion of research on US EC educators’ psychological well-being.
Financial Well-being
Early childhood educators’ wages today–without other household earnings–would classify them as low-income or at about 150% of the poverty threshold (Assistant Secretary for Planning & Evaluation, 2015; Whitebook et al., 2014). This financial strain may lead to higher rates of stress experienced by EC educators (Ryu & Fan, 2022). For instance, data show among EC educators with higher wages, children experience higher quality interactions with their peers and educators (Whitebook et al., 1989, 1990, 2014).
Beyond compensation, financial well-being can account for household income. Household income encompasses the sum of incomes earned by a sole household (Pew Research Center, 2015). Families with lower household incomes are at heightened risks of stress, and thus, greater conflict, chaos and marital strain (Dearing, 2014), and deficits in cognitive, social, emotional and physical attributes of well-being (Conger & Donnellan, 2007). However, compensation and household income alone, are objective representations of financial well-being, not fully reflecting EC educators’ satisfaction with their financial situation (e.g., compensation, cost of living, perceptions of debt), nor the control one feels regarding finances (abilities to navigate changes in finances and financial goals) (Vlaev & Elliot, 2014). Comprehensive investigation of financial well-being includes how much one decides is ‘needed’ (Prawitz et al., 2006; Vlaev & Elliot, 2014), and an individual’s assessment of their economic condition (Joo & Grable, 2004).
Early Childhood Educator Financial Well-being and Mental Health
Research points to initial connections between financial well-being and mental health (worry and stress) among EC educators. A study of over 600 educators working in Head Start and public Pre-K programs in one state, found EC educators reported high levels of worry and anxiety regarding their financial situations with over half the sample expressing worry related to barriers to pay for basic expenses of living including food, housing, transportation, and health care (Whitebook et al., 2014). These authors also found that educators with lower worry were working in the highest quality programs. However, worry represents an indicator of psychopathology (Purdon & Harrington, 2006), which has revealed inconsistent connections to child outcomes (Johnson et al., 2020). This encourages further examinations of connections between EC educators’ financial well-being and psychological subjective well-being.
In this study, we examined EC educators’ subjective psychological and financial well-being via a mixed method approach asking two research questions: (1) How do early childhood educators describe their financial well-being and psychological well-being? and (2) What is the relationship between early childhood educators’ financial well-being and psychological well-being?
Method
We employed an integrated mixed methods approach (Creamer, 2017) with a qualitative emphasis, concurrent data collection and iterative data analysis (QUAL + quant) to promote triangulation and expansion (Johnson & Onwuegbuzie, 2004). To achieve triangulation, we addressed the central research questions both qualitatively and quantitatively and continuously assessed convergence of the data. We achieved expansion by examining the qualitative data to deepen our sensemaking of the quantitative findings and used integrative blending (Greene, 2007) between qualitative and quantitative analysis phases with each phase informing the next.
Participants and Sites
Following Institutional Review Board (IRB) approval, researchers recruited participants from publicly funded early childhood education (ECE) programs in a major metropolitan area. To yield variation, we used purposive sampling (Patton, 1990) to ensure our participants were educators with varied experience and education, and role (i.e., lead or assistant educator1) in the program. We recruited from program staff meetings where we explained and answered questions about the study.
Participants included 123 early childhood educators working in six publicly funded ECE programs (Head Start (n = 76); programs funded by local and/or state governments (n = 47)) in a metropolitan area of the US. We recruited educators from programs that worked with families living in poverty. Three of these programs were Head Start programs; two programs received state universal preschool; one program received city funding (see Table 1). About one-third of participants had at least a four-year degree (n = 42) and were in their late 40 s, earning on average $30,000 per year. Of 123 educators, a subsample of 27 agreed to participate in follow-up interviews related to their well-being. See Tables 2 and 3 for full participant and subsample participant demographics and Tables 4 and 5 for average income and years of experience by six programs for the full sample and subsample.Table 1 Descriptive information about six programs
Site Number of in-depth interview participants (n = 27) Predominant funding source Age of children (in years) Program hours (all are Monday–Friday) Community-based program OR school-based program Single site or multi-site program Enrollment of children living in poverty only (Yes/ No)
1 2 Head Start 3–5 8:30AM–3:00PM Community-based Multi-site Yes
2 2 Universal Pre-K (state) 3–5 7:00AM–5:00PM Community-based Single site No
3 1 Head Start 3–5 8:30AM–3:00PM School-based Multi-site Yes
4 8 Head Start 3–5 9:00AM–5:00PM Community-based Single site Yes
5 7 City 4–5 7:30AM–3:30PM Community-based Multi-site Yes
6 7 Universal Pre-K (state) 3–5 8:00AM–3:00PM Community-based Multi-site No
Table 2 Demographic information for all participants (n = 123)
Total teachers (N = 123) Lead teachers (n = 56) Assistant teachers (n = 67)
Age
Mean age (in years) 48.50 49.32 47.81
Education
High school 27 5 22
2-year college 35 15 20
4-year college 42 25 17
Master’s degree 11 9 2
Mean Income
Annual $28,189 $31,392 $25,513
Household $47,985 $53,714 $43,197
Race/Ethnicity
African American 56 31 25
White 30 16 14
Latino/a 26 4 22
Asian/ Pacific Islander 6 2 4
Years of experience 11.96 13.59 10.61
Some teachers declined to answer demographic questions: 12 did not report their age, 28 did not report their income, 36 did not report their household annual income, five did not report their race/ethnicity, and one did not report years of experience
Table 3 Demographic information for the subsample (n = 27)
Total teachers (N = 27) Lead Teachers (n = 15) Assistant Teachers (n = 12)
Age
Mean age (in years) 49.29 48.92 49.66
Education
High school 3 1 2
2-year college 8 4 4
4-year college 9 4 5
Master’s degree 6 6 0
Mean Income
Annual $30,297 $35,929 $24,666
Household $43,303 $46,622 $39,984
Race/Ethnicity
African American 13 8 5
White 7 5 2
Latino/a 6 1 5
Asian/ Pacific Islander 1 1 0
Years of experience 14.66 14.56 14.79
Table 4 Mean income and average year of experience for all participants by programs (n = 123)
Site Mean income Average years of experience
Annual Household
1 $28,587 $42,930 11.53
2 $28,890 $79,496 10.47
3 $28,361 $45,494 11.52
4 $28,572 $51,096 14.32
5 $28,824 $40,392 10.16
6 $26,059 $43,870 13.32
Table 5 Mean income and average year of experience for the subsample by programs (n = 27)
Site Mean income Average years of experience
Annual Household
1 $33,500 $45,000 6.19
2 $31,500 $66,500 11
3 – – 30
4 $32,000 $50,800 16.88
5 $31,609 $36,077 13.19
6 $24,047 $32,750 15.17
The information on annual and household income was missing from participants in the ECE program numbered 3
Data Collection
Participants (1) completed a survey instrument (n = 123), which included demographic and closed-ended questions, and (2) participated in a qualitative interview (n = 27).
Measures
Subjective Psychological Well-being
We used the psychological well-being subscale from the Midlife in the United States (MIDUS) survey (Ryff, 1989). Participants responded to 18 items like “I am good at managing the responsibilities of daily life” on a seven-point Likert scale (1 = strongly disagree, 7 = strongly agree). The MIDUS is widely used with considerable reliability and validity evidence (Ryff & Keyes, 1995, van Dierendonck et al., 2008, see Ryff, 2014 for further review). There is some evidence for the use of six subscales, but reliability testing in previous studies (e.g., Keyes et al., 2002) yielded low to moderate alpha coefficients. Our sample also demonstrated low to moderate internal consistency for these subscales; therefore, we used the average of all items to capture overall psychological well-being with acceptable internal consistency (α = 0.71).
Perceived Financial Well-being
The InCharge Financial Distress/Well-being Scale (IFDFW, Prawitz et al., 2006) captured EC educators perceived financial distress and well-being. Educators responded to eight items on 10-point scales with higher scores indicating financial well-being and lower scores indicating financial distress. These 10-point scales aligned with four descriptors across each continuum that ranged from “Overwhelming Stress” to no “Stress at All”, or “All the Time” to “Never”, or “No Confidence” to “High Confidence.” The items measured educators’ level of financial stress associated with their current financial situation and their level of financial stress in general, along with satisfaction and feelings for their current personal financial situation (Prawitz et al., 2006). Prior testing for reliability and validity of the eight-item IFDFW Scale found one construct of financial distress/financial well-being with robust internal consistency (α > 0.9) (Prawitz et al., 2006); we found excellent internal consistency in our sample as well (α = 0.94).
In-Depth Qualitative Interviews
Interviews followed a semi-structured protocol exploring EC educators’ perceptions about their financial well-being and psychological well-being (e.g., How would you describe you/ your family’s financial well-being? How do you feel when you work with the children/families in your class? How can ECE programs can help improve the well-being of educators?). Interviews ranged 45 to 90 min and were recorded and transcribed. Sample size was determined based on reaching saturation, or no longer hearing new information (Daly, 2007).
Data Analyses
To maximize the potential for meta-inferences across qualitative and quantitative findings, we engaged in two phases of iterative qualitative and quantitative data analyses (see Greene, 2007; Creamer, 2017).
Initial Qualitative Analyses
The first phase of qualitative analysis comprised open, axial, and selective coding (LaRossa, 2005). During open coding, we created initial a priori codes based on sensitizing concepts that reflected the literature (i.e., stress; spillover; role of administration; perspectives on compensation) and the research question (e.g., connections between areas of well-being). Constant comparison was used to determine whether a previously created code fit or a new code should be created (Glaser & Strauss, 1967). During axial coding, each of the salient categories (e.g., financial concerns, connections across areas of well-being, feeling valued, role of colleagues on well-being) or codes that emerged during open coding were examined by looking across cases to understand the various dimensions of each category. During selective coding, we made connections across the most salient codes (LaRossa, 2005). To understand an emergent connection between financial and psychological well-being, we turned to the quantitative data.
Quantitative Analyses
Initial quantitative analysis was guided by the question: Does early childhood educators’ financial well-being predict their psychological well-being, even after accounting for household income? We first examined scatter plots; they appeared to depict a U-shaped curvilinear relationship between financial and psychological well-being. That is, while financial well-being seemed to be positively associated with psychological well-being as expected, a number of participants reported low financial well-being but high psychological well-being. Therefore, we conducted a hierarchical multiple regression in SPSS 24 to test the non-linear effect of financial well-being on psychological well-being while controlling for household income. We median-centered the independent variables and created a new variable, financial well-being squared (FWB2). Then, we performed a linear regression in two steps. The first block included only financial well-being, and the second included both financial well-being and FWB2. We used this method (rather than quadratic curve estimation) to observe the R2 change from the first to the second model.
Mixed Methods Analyses
To understand the curvilinear relationship between financial and psychological well-being, we returned to the qualitative data. We divided the sample into two groups based on the quantitative variables (higher financial well-being, and lower financial well-being, split on the median). Using simple linear regression, we observed the relationship between household income and psychological well-being at each level of financial well-being. Then, we purposely selected participants groups based on their position on the curvilinear shape (the quadratic relationship between financial and psychological well-being) depicted in Fig. 2. First, we first numbered the cases in a scatterplot with the curvilinear regression line plotted. Then, we drew circles to define each of three positions on the curvilinear regression line. We selected all quantitative participants who also had participated in qualitative interviews that fell within each of the three circles for further analysis (additional cases that fell within these areas did not have qualitative data). Figure 2 illustrates this selection process. Through focused coding, we examined these groups of cases looking for commonalities, differences, and possible explanations of the relationship between financial and psychological well-being.
Results
These results illustrate the connection between perceived financial well-being and subjective psychological well-being. Broader dimensions of EC educators’ finances, professional relationships and family lives examined across qualitative and quantitative analyses highlight the complex relations between financial well-being, psychological well-being, and household income.
Determining an Association Between Perceived Financial Well-being and Subjective Psychological Well-being
Initial Qualitative Findings
Initial qualitative analyses showed that psychological well-being, evidenced through discussions on positive relations, environmental mastery, and autonomy, connected to experiences of financial well-being. Because many participants did not earn enough to live close to their programs, they often moved away from their previously established personal networks, leaving them disconnected from important positive relationships and challenging their psychological well-being. Long commutes were stressful and limited the time participants were able to spend with their own families, straining relationships at home also. Taylor, a lead teacher, felt socially isolated: “…when I first got down here, I didn’t have many friends. I didn’t live near any of them …It was a little lonely.”
Data reflected the importance of environmental mastery, control over their contexts, as well as autonomy, independence to structure daily routines, as connected to their perceptions of financial well-being. At work, participants noted frustration with meeting on-going, often last- minute administrative demands, amidst teaching. For some, limited autonomy and environmental mastery was also present in their home lives. For example, Claudia, an assistant teacher with 11 years of experience, described how her husband was unemployed and provided limited support to the family. She noted that if she and her husband could afford living separately, they would be separated, but his unemployment and her low wage made that impossible. In this way, her limited environmental mastery or autonomy was informed by her financial well-being.
Quantitative Findings
Given the nature of the connections in the qualitative data between financial and psychological well-being, as well as the importance of partners’ earnings (which shaped household income), we hypothesized that financial well-being would predict psychological well-being even after controlling for household income. We found that household income and financial well-being explained 16.5% of the variance in psychological well-being, (F(3,77) = 4.861, p = 0.004). Financial well-being explained variance in psychological well-being over and above the variance explained by household income alone; both household income and financial well-being were significant predictors of psychological well-being (p = 0.02; p = 0.007, respectively) in the final model, model 3. Table 6 shows the regression results for each model, and Table 7 shows descriptive statistics for psychological well-being, financial well-being, and household income.Table 6 Hierarchical multiple regression analysis predicting psychological well-being by household income and financial well-being
Models
Model 1 Model 2 Model 3
Blocks of predictors B β p B β p B β p
HH income .008 .273 .015 .009 .284 .015 .008 .246 .029
Financial WB −.012 −.044 .704 −.025 −.088 .429
Financial WB2 .032 .304 .007
∆R2 0.1% 8.9%
Total R2 7.5% 7.6% 16.5%
F, p (model) 6.135 .015 3.106 .051 4.861 .004
Predictor variables are centered on the median. HH income = annual household income in thousands of dollars; Financial WB = financial well-being. Each progressive block included the variable(s) previously entered
Table 7 Descriptive statistics
N Range Min Max M SD
Financial Well-being 117 9.00 1.00 10.00 5.25 2.31
Psychological Well-being 108 3.00 3.94 6.94 5.79 0.63
Household income 82 82,000 $18,000 $100,000 $42,728.61 $20,202.40
It is notable that the relationship between financial well-being and psychological well-being is non-linear. Financial well-being was not a significant predictor in model 2, but became significant with the addition of the quadratic term, which increased the R2 from 0.076 to 0.165, thus explaining an additional 8.9% of the variance in psychological well-being. Figure 1 shows the shape of this relationship, which was a surprising finding as we hypothesized a linear relationship.Fig. 1 Curvilinear relationship between financial and psychological well-being
Role of Household Income
Next, we sought insight into this relationship using both the quantitative survey data and the qualitative interview data (presented in the next section). First, we tested for an interaction between household income and financial well-being. The interaction term did not contribute significantly to predicting psychological well-being or increase the variance explained, so we did not include it in Table 6.
Because of the relatively small sample size, we next divided the sample into two groups: a high financial well-being group and a low financial well-being group divided on the median score of 5.25 (this score corresponds with 0 in Fig. 1, because the variable in the figure is centered on the median). We used household income to predict psychological well-being within each group to see if this relationship differed. Indeed, we found that for the group with low financial well-being (n = 44, financial well-being mean = 3.36; annual household income minimum = $18,000, maximum = $100,000, mean = $38,865; psychological well-being mean = 5.81), annual household income did not predict psychological well-being (F(1,39) = 1.001, p = 0.323). But, for the high group (n = 38; financial well-being mean = 7.1; annual household income minimum = $19,200, maximum = $100,000, mean = $47, 202; psychological well-being mean = 5.8), annual household income was a significant predictor (F(1,37) = 17.653, p < 0.001), explaining 32.9% of the variance in psychological well-being. This indicates that while household income explains a rather large amount of the variance in psychological well-being for those with higher financial well-being, for those with low financial well-being, factors other than household income must explain the variance in psychological well-being.
Examining Experiences Across the Curve: Links Between Financial and Psychological Well-being
Next, we examined three groups of qualitative participants (exemplar cases) based on their position on the regression line (see Fig. 2): low financial but high psychological well-being, low financial and low psychological well-being high financial and high psychological well-being. These analyses revealed interesting qualitative differences in how participants described their well-being, which we describe next.Fig. 2 Extreme case sampling: three groups of qualitative participants
‘I have all of their smiles…’: Low Financial Well-being and High Psychological Well-being
Low financial and high psychological well-being scores represented the top left of the curvilinear model. The four extreme cases highlighted here had some of the lowest financial well-being scores. Many referenced “making ends meet” as a formidable financial struggle. All four participants described limited raises commensurate with increases in costs of living, and living in a high cost area in the US. Alanya, an assistant teacher with 16 years of experience in ECE, noted not having a raise “since President Bush took office.” However, she stayed at this Head Start program because she had friends who lived closer to her home, who made far less money. Bennett, a lead teacher with 14 years of experience, echoed a similar sentiment,I feel like [with] all the things that we do here why are we not compensated. I’ve been here 10 years, almost and I’ve only had cost of living raises not pay raises…And I have to live so I even have to choose what I’m going to eat or to get gas in my car to get here.
Soniya, a lead teacher with 14 years of experience, worked a second job until 10 PM most evenings to “make ends meet”.
Alanya, Aliyah, and Bennett emphatically shared their love of children and how this key element of their teaching reflected within their professional identities kept them in the field despite low wages. Aliyah described how seeing the children always made their moods more positive, explaining aspects of their high psychological well-being. Aliyah, a lead teacher with 30 years of experience, described:Because I see all of these little faces coming towards me. ‘Hi Ms. Aliyah! Hi Ms. Aliyah!’ Truthfully, I forget whatever is bothering me because I have all of their smiles…and truthfully it goes all out the door. And I focus on them.
Bennett similarly noted that she does not work in early childhood for the money but for her love of children, “I’m not here for paycheck. I do this for love. This is my passion” Aliyah went on and further echoed these sentiments when asked if she would consider leaving her job, given the low pay; she indicated that would only happen if she found a job as rewarding.
Beyond their profound love and enjoyment of young children, all four of these ECE educators had emotional support at home either from family or close friends deepening our understanding of their psychological well-being. However, unlike the right curvilinear side (i.e., high financial well-being and high psychological well-being) these participants on the top/left side of the curve were either single or did not have partners with high incomes which helped explain their struggling financial well-being. For example, Bennett lived by herself expressing challenges to pay rent while also denoting the role of her mother “to talk regularly with.” Although home support was positive for these four extreme cases, work support was mixed.
Alanya and Aliyah felt less supported by other teachers and administrators at work but created boundaries and a strong separation between home and work to bolster their psychological well-being. Soniya indicated the importance of her co-educator, Ana, whom she had worked with for seven years, as key to her enjoyment of work. For these participants having strong relationships at home and/or at work seemed to buffer the negative psychological impacts of their financial well-being.
‘Staying Afloat’: Low Financial Well-being and Low Psychological Well-being
Low financial and low psychological well-being scores represented the bottom of the curvilinear model. The four extreme cases highlighted here described earning just enough to pay their bills (e.g., food and rent), or “staying Afloat”, and how these feelings of financial satisfaction aligned with their psychological well-being. All four cases here expressed living paycheck to paycheck or needing a second job. However, unlike the top/left of the curvilinear model (low financial, high psychological), these participants experienced psychological demands along with these financial strains. For some this was linked to meager financial support at home and feelings of financial concern that accompanied. Zainab, a lead teacher with seven years of experience, shared that her husband was unemployed, and simultaneously questioned any purchases that Zainab made, as well as her abilities to manage money, “I need this money…the only bread winner in my household is me, not my husband…I bought a house and I have a mortgage and I have bills to come one after the other.”
Despite low perceptions of financial well-being, these four cases described how they budgeted to survive on low and stagnant wages, by “making things work”, “living “a simple life” and only buying what was needed and nothing “extra.” Despite these strategies to try to cushion concerns of financial well-being, their psychological well-being was compromised by low social support.
These four exemplar cases noted challenges with co-workers, paperwork, and “last minute requests” coupled with ineffective communication as implications on their autonomy, environmental mastery and overall satisfaction with the job. Zainab detailed the difficulties she and a co-educator experienced when the co-educator did not address tasks necessary for planning and preparation, and generally disrespected Zainab. Zainab gave an example of something her co-educator said to her: ‘I’ve been here…girl, what you are saying to me, I’ve been here longer than you. You don’t have to explain to me.’ In addition, Zainab, felt emotionally unsupported at home by her husband, further explaining her psychological well-being.
All four of these participants indicated challenges related to timely communication and last-minute requests made by administrators, which made them at times feel “devalued”, contributing to their low psychological well-being. Majida, a lead teacher with 25 years of teaching experience, repeatedly indicated her lack of control over elements of her practice was most stressful in her job. It was not that she disagreed with the administrative request, but rather she felt discouraged not having the pedagogical resources and administrative support to complete them. For these participants, with challenged relationships at home and work, the negative psychological impacts of their financial well-being were not buffered.
‘We’re making it good…’: High Financial Well-being and High Psychological Well-being
High financial and high psychological well-being scores represented the top right curvilinear point. The three extreme cases highlighted here described financial stability with support of a long-term partner. As Julieta, an assistant teacher with two years of teaching expressed: “I’m good, because my husband pay(s) everything” further indicating that her job does not influence her family’s finances. Gail, a lead teacher with 30 years of experience echoed, “I think we’re making it good. We don’t have any financial struggles.” All three participants acknowledged that there were financial struggles for early childhood educators in general, but that their own employment supplemented their partner’s earnings. Sofia, a lead teacher with seven years of experience, and Julieta even noted that, from a financial standpoint, they did not need their job but they remained in the field as they enjoyed their work. Julieta felt “lucky” she did not worry about the financial struggles that many of her colleagues encounter and her psychological well-being was bolstered more because of her feelings about work “Why stay at home if I can get here and help and be here for families and sometimes a lot of families…”.
Like Julieta, the other two participants also expressed happiness at work and a supportive social network. Gail and Sofia spoke specifically about support from their students, coworkers and administrators. Sofia, shared how she “expresses” what she feels to her co-workers, and that her connections with coworkers were what made her feelings about the job positive. For these participants, experiencing positive relationships at home and at work coupled with limited concerns related to their finances shaped their high psychological well-being.
Discussion and Implications for Research, Practice and Policy
Importance of Positive Relationships with Others and Mental Health Supports
Our qualitative extreme case sampling analyses revealed that for those who feel as though they are really struggling financially, it may be that positive relations with others, is an important aspect of subjective psychological well-being. Like Roffey (2012), our work suggested that EC educators’ workplace relationships mattered for fostering one’s emotions and feelings about the job (e.g., self-acceptance) and oneself (Cole et al., 2000). Ryff (1989) highlighted how trusting interpersonal relationships, and empathy and concern for others were key elements of positive relations with others. The EC educators with high psychological well-being here, expressed the importance of relationships with others including children, colleagues, administrators, and their own families and friends, even if concerned with finances. Further, research on ECE educator mental health speaks to role of relationships with colleagues (Løvgren, 2016; Rentzou, 2012), specifically the importance of time, space, and energy to nurture these professional relationships during the day and across the school calendar (Johnson et al., 2020). Fostering supportive relationships at work for greater psychological well-being (Jovanovic, 2013) may reduce the deep need for social support outside of work and in turn provide greater equity for professional success for all early childhood educators regardless of their personal and home lives. As the US faces a growing educator shortage in the wake of the COVID-19 pandemic (Steiner & Woo, 2021) these relational supports and connections at work are increasingly important (Pate, 2020).
In addition, ECE programs ought to build their knowledge regarding educator mental health, inclusive of well-being, and acquire resources for dissemination. Specifically creating policies to that focus on supporting EC educators’ mental health and well-being, including adding educator mental health and well-being to Quality Rating and Improvement Systems (QRIS). This might include educators having access to Infant-Early Childhood Mental Health (IECMH) consultants to not only support their work with children’s mental health needs but also their own mental health and well-being needs (Smith & Lawrence, 2019). As educators experience pressures amplified by the pandemic, all educators, even those with high levels of financial and psychological well-being, require ongoing structural supports.
Autonomy of Instructional Practices and the Classroom
For participants who experienced autonomy of instructional practice and environmental mastery of the classroom, they described how these feelings created a sense of belonging, value, and connectedness, in their classrooms and programs. EC educators with higher psychological well-being noted feeling valued and confident in their roles, despite potential financial challenges faced in the profession, which may further explain experiences of the participants on the left side of the U curve.
Research indicates the importance of open communication and transparency between EC educators and administrators for educator well-being (Fox et al., 2020). School leaders that foment cultures of trust, mutual respect, and open communication while also prioritizing and protecting educators’ time, experience higher educator morale and satisfaction (Kraft et al., 2020). It seems that more opportunities for promoting autonomy and fostering environmental mastery vis-a-vis providing increased time for planning, decreased last minute requests from administrators, and ensuring educators have input into their co-teaching partnerships, are important. Moreover, further understanding on how these aspects of psychological well-being operate similarly or differently across EC educators depending on their role (e.g., lead or assistant) will be important for future research.
Beyond Compensation
Despite ongoing advocacy to address compensation issues over the last 25 years (see Whitebook et al., 2014) raising EC educator compensation to livable wages remains elusive. Recent recommendations put forth by the Power to the Profession National Task Force (2020) indicate ensuring that early childhood educators who are “professionally prepared” are “professionally compensated” (p. 2). Achieving parity across ECE programs requires government intervention and support, and cannot be placed solely on individual ECE programs or teachers.
In extension of the importance of compensation, EC educators who had both high financial and psychological well-being had one thing in common: a partner who shouldered much or most of the households’ financial burden. Uniquely for participants with low financial well-being, factors other than household income explained the variance in psychological well-being, and perhaps other factors acted as buffers (e.g., access to various supports). These findings further highlight how the ECE field, historically, has been organized to accommodate educators who are already situated in privileged circumstances and further marginalize educators who are already disenfranchised, particularly in terms of family structure and socioeconomic status. This remains a critical area of continued research, especially as we emerge from the Covid-19 pandemic, and as educators continue to leave the field (or not return to the field post pandemic) in search of better employment options for their financial and psychological well-being (Coffey & Khattar, 2022; Walker, 2022).
Limitations, Future Research and Conclusions
Limitations of this study require consideration, particularly in reference to future research. First, despite tapping into participants’ previous experiences, in-depth interviews were retrospective, not longitudinal, and thus the data were limited in terms of elucidating the nature of EC educators’ well-being in relation to time. Educators’ well-being experiences likely change over their careers, across each individual year given the varying pressures at different times of the school year, and with changing family circumstances. Future research might examine EC educators’ well-being longitudinally to understand how the intersection of financial and psychological well-being may shift. Second, we did not have enough statistical power due to our sample size to examine different aspects of psychological well-being using the MIDUS. Although the results provide relevance for exploring psychological well-being among early childhood educators, future studies should consider using the individual subscales of the MIDUS (i.e., Positive Relations with Others, Self-Acceptance, Autonomy, Environmental Mastery, Personal Growth, and Purpose in Life) to understand connections among different aspects of psychological well-being. Third, future research may consider examining educators’ workplace relationships and educators’ home supports to further understand how these contribute to psychological and financial well-being.
Teachers are ‘everyday heros’ (Johnson et al., 2020). However, the demands and stressors of the job, inclusive of financial and psychological strains, have only increased since the onset of the COVID-19 pandemic. How teachers feel about their daily work and the value of their impact has consequences on their instruction, classroom relationships and student outcomes (Jennings & Greenberg, 2009). This study elucidates how EC educators’ financial and psychological well-being serve as critical components in the ongoing discussions regarding ECE quality care in support of educator and student outcomes.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 33 KB)
Supplementary file2 (DOCX 16 KB)
Acknowledgements
The data used in this paper were collected with support from the Center for the Advancement of Well-being at George Mason University in Fairfax, Virginia.
1 Despite differences in role and title, in an independent samples t-test we found no significant different between lead teachers and assistant teachers on financial well-being t (115) = 1.09, p = .278”. or psychological well-being t(106) = 1.442, p = .152”.
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| 0 | PMC9734917 | NO-CC CODE | 2022-12-14 23:28:31 | no | Early Child Educ J. 2022 Dec 8;:1-12 | utf-8 | Early Child Educ J | 2,022 | 10.1007/s10643-022-01429-9 | oa_other |
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Mol Neurobiol
Mol Neurobiol
Molecular Neurobiology
0893-7648
1559-1182
Springer US New York
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3150
10.1007/s12035-022-03150-5
Article
CRISPR/Cas9 Mediated Therapeutic Approach in Huntington’s Disease
http://orcid.org/0000-0003-0482-8246
Alkanli Suleyman Serdar [email protected]
12
http://orcid.org/0000-0002-3745-8838
Alkanli Nevra [email protected]
3
http://orcid.org/0000-0002-8412-091X
Ay Arzu [email protected]
4
http://orcid.org/0000-0002-6005-5164
Albeniz Isil [email protected]
1
1 grid.9601.e 0000 0001 2166 6619 Department of Biophysics, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
2 grid.9601.e 0000 0001 2166 6619 Department of Biophysics, Istanbul Faculty of Medicine, Institute of Health Sciences, Istanbul University, Istanbul, Turkey
3 grid.444292.d 0000 0000 8961 9352 Department of Biophysics, Faculty of Medicine, Haliç University, Istanbul, Turkey
4 grid.411693.8 0000 0001 2342 6459 Department of Biophysics, Faculty of Medicine, Trakya University, Edirne, Turkey
9 12 2022
113
1 11 2022
26 11 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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The pathogenic mechanisms of these diseases must be well understood for the treatment of neurological disorders such as Huntington's disease. Huntington's Disease (HD), a dominant and neurodegenerative disease, is characterized by the CAG re-expansion that occurs in the gene encoding the polyglutamine-expanded mutant Huntingtin (mHTT) protein. Genome editing approaches include zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs) and Clustered Regularly Interspaced Short Palindromic Repeats/Caspase 9 (CRISPR/Cas9) systems. CRISPR/Cas9 technology allows effective gene editing in different cell types and organisms. Through these systems are created isogenic control of human origin induced pluripotent stem cells (iPSCs). In human and mouse models, HD-iPSC lines can be continuously corrected using these systems. HD-iPSCs can be corrected through the CRISPR/Cas9 system and the cut-and-paste mechanism using isogenic control iPSCs. This mechanism is a piggyBac transposon-based selection system that can effectively switch between vectors and chromosomes. In studies conducted, it has been determined that in neural cells derived from HD-iPSC, there are isogenic controls as corrected lines recovered from phenotypic abnormalities and gene expression changes. It has been determined that trinucleotide repeat disorders occurring in HD can be cured by single-guide RNA (sgRNA) and normal exogenous DNA restoration, known as the single guideline RNA specific to Cas9. The purpose of this review in addition to give general information about HD, a neurodegenerative disorder is to explained the role of CRISPR/Cas9 system with iPSCs in HD treatment.
Keywords
Huntington’s Disease
Neurodegenerative Disorders
CRISPR/Cas9
Genome Editing Systems
iPSC
Isogenic Cell Lines
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pmcIntroduction
Neurological disorders have a negative impact on public health and have been associated with impaired central or peripheral nervous systems [1]. Specific neurodegenerative diseases are characterized by prominent clinical profiles depending on age. Loss of neuronal function, movement disorders and cognitive disorders occur in neurodegenerative diseases, characterized by progressive atrophy of neurons and tissue. Molecular properties such as mitochondrial dysfunction, axonal damage and abnormal protein aggregation are observed before neuronal death and dysfunction in neurodegenerative diseases. Complex and distinctive pathophysiological profiles appear in various neurodegenerative proteinopathies. The reason for this may be processing and aggregation of misfolded proteins. The most important of these diseases are Alzheimer’s disease, Parkinson’s disease and Huntington’s disease. Alzheimer’s disease is characterized amyloid beta plaques and phosphorylated Tau tangles. Parkinson’s disease is characterized by alpha synuclein-related Lewy bodies. It is also known that HD characterized by inclusion bodies containing mHTT. These aggregate proteins cause neuronal axon damage and dysfunction. There are many pathogenic mutations associated with protein processing and aggregation [2].
HD is a serious neurodegenerative disorder and stems from an autosomal dominant mutation that occurs in the first exon of the Huntingtin gene encoding the Huntingtin protein [3]. In HD pathology, expansion of cytosine-guanine-adenine (CAG) repeats occurs on chromosome 4 (4p16.3) encoding the HTT gene [4]. Although there are 16–20 CAG repeats in the HTT gene in healthy individuals; HD patients usually have more than 40 CAG repeats. mHTT contains an expanded polyglutamine stretch, which leads to misfolding of the protein aggregate formations. It is known that these aggregates affect a wide variety of molecular and cellular processes. Striatal and cortical neurons death occurs as a result of the end of these processes. In most cases diagnosed with HD, basic HD symptoms, such as movement disorders, cognitive disorders, and psychiatric disorders, occur in middle ages. A significant relationship is reported between the age of onset of HD and CAG repeats. The higher number of CAG repeats is associated with the earlier onset of the disease and the development of more serious forms [3].
Although autosomal dominant mutation, which is effective in HD pathogenesis, has been described much earlier, disease-related pathways have not been fully elucidated. Symptomatic treatment is generally used in the treatment of this disease [3]. Symptomatic treatments such as caspases targeting glutamate and dopamine pathways, aggregation inhibition, mitochondrial dysfunction, and transcriptional dysregulation are used for improving of HD [4].
HD is a slowly progressing disease. Various analyes such as transcriptom analysis, bioinformatics analysis are applied ın the investigation of disease progression mechanisms. However, in these methods, interactions between genes, proteins and cellular organelles during disease progression cannot be fully explained. Therefore, modern gene editing approaches are applied in scientific researches. DNA sequences and the expression of target genes may be changed in consequence of these approaches [3]. In addition to the symptomatic treatments applied in HD improvement, new therapeutic approaches that target the mHTT protein and the HTT gene have been used recently. Thanks to these gene editing techniques, CAG repeats can be reduced and gene editing techniques are thought to be useful, especially when applied in hereditary, neurodegenerative disorders [4].
These modern gene editing approaches include approaches such as ZFNs, TALENs, CRISPR/Cas9 [3]. These approaches enable the recognization of enlarged CAG domains in normal cells or correction of mutations in cells derived from the patient. Thus, it is aimed to create isogenic cell lines with the same genetic background. Isogenic cell lines play an important role in the study of disease mechanisms and cell-based highly productive compound scanning [5, 6]. In addition, these approaches are highly effective in multiplex analysis and functional scanning of genes associated with HD pathogenesis in neurodegenerative processes. Cells that have corrected HTT are very important in autologous cell therapy and it is thought that mutant allele-specific gene regulation may play an effective role in in vivo HD gene therapy [3].
Based on this, our aim in this study is to contribute to the literature by explaining the mechanism of HD and summarizing the studies related to the CRISPR/Cas9 approach applied with iPSC, which is one of the genome editing systems used in HD treatment.
Huntington’s Disease
HD is characterized by psychiatric symptoms, motor disturbances, cognitive deficits, sleep disturbances, and weight loss. HD is a genetic neurodegenerative disease and is characterized by neuron loss, motor dysfunction [7]. HD, which is a progressive genetic disease, has symptoms such as choroic movements, behavioral and cognitive disorders, dementia. HD symptoms vary in the early stages of HD pathology, the genetic basis of which was discovered in 1993. The same pathologies occur in all patients together with the progression of the disease. The earliest observed obvious damage, occurs in the neostriatum, consisting of the caudate nucleus and putamen. It is thought that the neurons most vulnerable against damage in HD are medium spiny neurons (MSNs) in the striatum [8].
When examined neuropathologically, HD is characterized by neurodegeneration that progresses in the striatum and to a lesser extent in the cortex. In HD, HTT misfolded in neurons and HTT protein aggregates containing molecules that can interact with HTT occur [9]. HD, which is an incurable neurodegenerative disorder, also includes loss of GABAergic MSN, progressive motor, psychiatric, and cognitive symptoms in the striatum. GABAergic MSNs with dopaminergic and glutamatergic inputs are projection neurons. While striatum takes dopaminergic inputs from the pars compacta of substantia nigra, takes glutamatergic inputs from the cortex and thalamus. Some MSNs besides dopaminergic and glutamatergic receptors, also express cholinergic and adenosinergic receptors [10].
Various animal models have been developed in the investigation of HD pathogenesis. It is aimed that mHTT protein levels can be reduced and change the affected neurons with the experimental approaches used in HD treatment [7]. In studies with HD animal models, it has been shown that disease phenotypes may be improved and neuropathology may be reversed as a result of reducing mHTT [8].
In addition to experimental animal models in therapy for HD, embryonic stem cells, mesenchymal stem cells, neuronal stem cells may be used [7]. Nowadays, proximally targeted treatments are being developed in HD pathogenesis using HTT, DNA, RNA and protein. As a result of these approaches, it is aimed to reduce mHTT levels and to improve pathogenic effects [8].
Pathological Mechanisms of Huntington’s Disease
The CAG codon encodes the alpha amino acid. It is known that glutamine is synthesized from glutamate and ammonia by glutamine synthetase enzyme. Glutamate, the precursor of the neurotransmitter glutamine, is mainly produced in the muscles, lungs and brain. CAG with non-toxic, has glutamine amino acids in the HTT gene. As a result of polyglutamine expansion, aggregate formation emerges and becomes toxic. Aggregates in the brain are an important factor in the emergence of HD. Inflammatory responses, mitochondrial dysfunction, apoptosis, excitotoxicity, and transcriptional regulation develop as a result of aggregate formations. The first exon of the HTT gene has a CAG nucleotide repeat and polyQ stretch occur at the N-terminus of the HTT protein in translation [4].
CAG repeats in HD onseting in adults, reaches 40 or more expansions. However, in patients (with Juvenile HD) less than 20 years old, a mutation with more than 55 CAG repeats is usually described. The presence of HTT exon 1 mRNA was determined in fibroblasts of juvenile HD patients and was detected especially in the post-mortem brains of early HD individuals [11].
Wild-type HTT has a complex structure with multiple interaction domains. So, it is thought to be wild-type HTT, a scaffolding protein that helps coordinate other proteins and cellular functions [12]. Wild-type HTT plays an important role in transcriptional regulation, in the production of brain-derived neurotrophic factor (BDNF). BDNF is an important factor for the survival of striatal and cortical neurons. Also wild-type HTT plays an important role in axonal transport, exchange of endosomes and organelles and vesicular recycling [13]. mHTT causes disease through a dominant toxic function gain mechanism [14, 15]. These pathological mechanisms include mechanisms such as early transcription dysregulation, synaptic dysfunction, proteasome dysfunction, aggregate pathology, oxidative damage, mitochondrial dysfunction and extrasynaptic excitotoxicity [16, 17].
It is thought that as one of these pathological mechanisms, proteasome dysfunction to be effective in the pathogenesis of HD. There are uncertainties regarding the regulation of proteasome activity in stem cells and somatic cells affected by HD. It has been determined that HD-iPSCs show high proteasome activity. It has been detected that neural progenitor cells (NPCs) derived from HD-iPSC exhibit lower levels of proteasome activity. It has also been shown that HD-NPCs form HTT aggregates under oxidative stress [9].
HTT Gene as Therapeutic Target
It is known that the HTT gene responsible for HD was identified many years ago. A polymorphic region containing CAG repeats encoding a glutamine domain called polyQ is found in first exon of the HTT gene. Various approaches have been developed to block mHTT expression and prevent toxic neurodegeneration. Gene silencing strategies are applied involving RNA interference (RNAi) and Antisense Oligonucleotide (ASO) compounds to induce partial degradation of the target mRNA. Also, in these approaches continuous expression is required for therapeutic molecules. HTT gene regulation is a treatment approach that causes permanent inactivation of the HTT gene. Genome editing systems are used in neurodegenerative diseases such as HD. Genome regulation is implemented as disease-modifying therapy, and this regulation has certain stages [18].
Current Treatment Approaches of Huntington’s Disease
The HTT protein is required for neuronal development, and mutations in this protein have also been associated with HD development. In the mutated HTT protein, increased CAG repeats within the HTT gene result in expansion of the polyglutamine pathway. The molecular basis of HD is known, but there is no known treatment for the disease other than the symptomatic treatment approach. In addition to treatment approaches developed for specific symptoms in HD, disease-modifying treatments should also be explored. In HD, striatal medium spiny neurons (MSN) degenerate and mutHTT toxicity affects this degeneration more. The causes of striatal MSN loss are not fully known, but a significant loss of striatal MSN has been identified in HD patients compared to healthy individuals. Various therapeutic strategies are being investigated in preclinical models and clinical trials. Therapeutic approaches to decrease mutHTT content at transcription and translation levels, therapeutic approaches that induce mutHTT proteosomal degradation are very important. In addition, post-translational modification of mutHTT as a pharmacological approach is also being investigated. Besides these approaches, stem cell therapies targeting patient-derived induced pluripotent stem cells to replace lost striatal neurons are also important therapeutic strategies. Therapeutic approaches for HD may be classified as therapies associated with mutHTT modification and degradation, therapies associated with signaling pathways, therapies associated with decreased mutHTT content, stem cell therapies, and pharmacological therapies [19] (Fig. 1).Fig. 1 Current treatment approaches for HD [19]
Drugs that Prevent Excitotoxicity
Riluzole, which is among the drugs that inhibit excitotoxicity, is a glutamate inhibitor and provides reduction of abnormal movement especially in Amyotrophic Lateral Sclerosis (ALS) disease. In a previous study, it was determined that Riluzole is not neuroprotective and is not effective in the reduction of HD symptoms. Memantine, an antagonist of extrasynaptic N-methyl-D-aspartate (NMDA) receptors, plays an important role in Alzheimer’s disease and mild-low dementia. It is known that memantine prevents the progression of HD by decreasing striatal cell death. Thus, HD-related cognitive functions may develop [4]. In another study, it was determined to prevent Memantine and Risperidone combination, motor symptoms, cognitive decline, and predicted progression of psychosis [20]. In a study conducted on rodents, it was determined to reduce pathology by applying Memantine at a low dose. Also, in the same study, it was reported that high doses of Memantine support cell death. Tetrabenazine (TBZ) inhibits vascular monoamine transporter type 2. Thus, the dopamine pathway is also inhibited. The existing dopamine in the synapse reduce and its interaction with the postsynaptic dopamine receptors is limited. Deutetrabenazine containing deuterium atom is also known as vascular monoamine transporter type 2 inhibitor. In some treatment studies, it has been found that Deutetrabenzine more is tolerated than TBZ. In studies conducted by creating mouse models, it was determined that TBZ improve motor symptoms and reduce striatal neuronal cell loss [4].
Targeting of Caspase Activities
Minocycline, known as a tetracycline analog, plays a role in inhibiting caspase-3 and caspase-1 expression by crossing the blood–brain barrier. In patients treated with minocycline, it was determined that neuroprotective effect occurred and improvement was observed in disease phenotype. In a trial study conducted with human, motor and cognitive improvements were observed in HD patients who received 100 mg of Minocycline for 6 months. In another pilot study, motor and cognitive improvements were observed in HD patients applying Minocycline treatment for 6 months [4].
Targeting of HTT Aggregation and Clearance
It is known that dye called as Congo Red bind to beta layers containing amyloid fibrils. When this dye is injected into mice with HD, it has been determined that the dye is effective in the recovery of motor functions by preserving normal protein synthesis and degradation. The dye also supports the clearance of enlarged polyQ repeats, thereby prevents polyglutamine oligomer formation. Besides these, there are also studies showing that this dye prevents ATP exhaustion and caspase activation. Trehalase disaccharide is effective in inhibiting the formation of nuclear residues. In studies carried out with mice, it has been reported that modified motor functions improve. The C2-8 compound, which inhibits polyglutamine aggregates in brain slices and cell cultures, may reduce the amount of neuronal atrophy by improving motor functions [4]. The mammalian target of rapamycin (mTOR), which phosphorylates many proteins, is an important protein kinase and plays a role in various cellular functions such as autophagy and transcription. It is known that mTOR interacts with mHTT. As a result of this interaction, mTOR activity, autophagy and mHTT clearance decrease. mTOR phosphorylates S6K1, an important regulator of cell volume. mTOR disorder, which is known to be associated with mHTT, is an important factor in explaining brain atrophy in HD. In some studies in HD mouse models, it has been determined that Rapamycin develops motor performance and decreases striatal neuropathology [21–23].
Targeting of Mitochondrial Dysfunction
In previous studies, creatinine which has antioxidant properties decreases serum 3-hydroxy-2-deoxyguanosine levels. In addition, it was determined that creatine administration delays the functional decrease in the early emergence of HD. In another study, it has been reported that creatine treatment administered at a certain dose, improved muscle function capacity in neuromuscular diseases. However, there is also a study showing it was not improved in the I–III stages in HD, in the cognitive conditions and neuromuscular functions. It has been determined that Coenzyme Q cofactor, which plays a role in ATP production in the electron transport chain of mitochondria, improves mitochondrial functions in HD patients [24]. In another study performed with mice, it has been detected that coenzyme Q provides neuroprotective effect and delays motor deficiency, atrophy, inclusion [4]. However, coenzyme Q was not effective in phase II randomized clinical trials [25]. Ethyl-Eicosapentaenoic Acid (EPA) is known as a derivative of EPA that binds to the peroxisome proliferator-activated mitochondria receptor [26]. It is thought that Ethyl-EPA be able to reduce mitochondrial damage by inhibiting caspase, thereby improving neuronal function [4]. However, in a study conducted with stage III HD patients, significant difference was not determined between Ethyl-EPA and placebo on the total motor score 4 scale [27]. It has been detected that a significant improvement in this scale in patients with fewer CAG repeats. In a phase III randomized control trial, it was determined that Ethyl-EPA did not improve cognitive functions [28]. It has been determined that cystamine and 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) blockers increase the survival effect in HD cells by preventing oxidative damage [29]. It has also been shown that Meclizine, an antihistamine drug showing neuroprotective effect in the Drosophila model, inhibits oxidative metabolism and apoptosis [4].
Targeting of Transcriptional Dysregulation
In a study performed with N171-82Q symptomatic mice, when sodium phenylbutyrate was administered to these mice, less brain atrophy has been observed. It has been determined that sodium phenylbutyrate is effective in regulating caspases that play a role in apoptosis. In studies conducted with HD mouse models, DACi4b known as Histone deacetylase (HDAC) inhibitor, has been also determined to reduce neurodegeneration by improving motor impairment. There are also studies showing that HDACi4b regulates mRNA expression. In studies conducted with transgenic mice, it was determined that histone acetylation in the brain increased with Suberoylanilide Hydroxamic Acid (SAHA) and thus motor disorders were improved. Mitrahramycin and Chromomycin treatments known as anthracycline derivatives form the basis for clinical studies for HD. It has been reported that these derivatives support epigenetic histone modifications in transgenic cell lines [4].
Targeting of mHTT
Modified ASO, known as Peptide Nucleic Acid (PNA), selectively recognizes the mutant allele. In addition, it has been determined that ASO selectively inhibit mHTT expression in human fibroblasts [30]. RNAi, which plays a role in the development of motor behavior, may play an effective role in HD treatment by reducing neuropathy. In various studies conducted with transgenic mice with HD using intrabodies and artificial peptides, it has been determined that they play a role in the development of motor and cognitive functions [4].
Therapeutic Approaches Targeting DNA
DNA targeting approaches include ZFNs, TALENs, and CRISPR/Cas9 approaches. Each of these approaches has different mechanisms in terms of DNA binding and modes of action. Zinc finger Proteins (ZFPs), one of the highest protein groups play an important role in the regulation of DNA, RNA and protein functions. They may be connected to specific DNA sequences using therapeutic compounds. ZFPs that do not affect wild-type HTT expression reduce mHTT expression. CRISPR/Cas9, which is associated with viral defense mechanisms of bacteria that recognize and destroy foreign DNA, plays a role in excising CAG repeats to silence mHTT expression. In studies performed with mice, it has been shown that the CRISPR/Cas9 system may be applied in improving motor functions by reducing mHTT [4].
Therapeutic approaches targeting HTT DNA modulate gene transcription and they are effective in genome regulation by modifying the HTT gene directly. In approaches towards DNA targeting, a specific form of DNA binding element is used, combined with effector elements such as nucleases, epigenetic modulators or transcription factors. While DNA binding elements ensure productive and precise DNA targeting, effector elements alter gene sequence or expression. Nuclease effectors are considered as genomic scissors. These effectors separate the targeted DNA to produce double strand break that stimulates the endogenous DNA repair mechanisms of the cell. They then repair DNA damage using repair mechanisms [31].
Genome Editing Systems
In gene editing prosess, a double-strand break (DSB) is produced in the targeted DNA sequence. Four important nuclease systems are used for the induction of DSBs. ZFNs, TALENs, meganucleases and CRISPR/Cas9 nuclease systems are found among these nuclease regulation systems (Fig. 2) [32–34]. In the administration of the CRISPR/Cas9 approach, a sgRNA sequence complementary to any desired target region is designed and Cas9 nuclease is directed to this region. Unlike this system ZFNs, TALENs and meganuclease systems are based on the production of a new protein specific to the individual target DNA sequence. In CRISPR/Cas9 system that only at the same time multiple sgRNA can be used multiplex gene changes are possible [33].Fig. 2 ZFN, TALEN and CRISPR Genome editing approaches [34]
Genome editing is a technology that involves the formation of genome modifications at specific regions in the genomes of living organisms. These genome editing technologies are based on engineered endonucleases and these nucleases consist of sequence-specific DNA binding domains [35]. Genome editing systems are developed from prokaryotic systems so that relevant genes can be specially modified [18]. ZFN, TALEN and CRISPR/Cas are commonly used genome editing tools. These tools cover processes such as cell and nucleus entry, transcription and post-process alteration, gene expression alteration [36]. ZFN and TALEN are the first systems that are determined and applied in gene therapy. In these systems, a target sequence is recognized and separated via designed site-specific nucleases. These nucleases have protein recognition domains, and these domains are designed to potentially recognize any sequence of the genome. CRISPR/Cas9, another genome-editing system, is characterized by regular intermittent clustered short palindromic repeats derived from the bacterial immune system, and this system is RNA-guided nuclease (RGEN), which can provide precise modification of genes by recognizing DNA DSBs. ZFN and TALEN may utilize protein-DNA interactions to recognize the target genomic DNA. However, RGENs use synthetic guide Protospacer adjecent motif (PAM). Since CRISPR/Cas9 can target more than one gene at the same time, it has an easier design than other systems [18]. The major advantage of the CRISPR system is the ability to target more sites using a Cas 9 protein and multiple sgRNAs. Moreover, the efficiency of the method is due to the fact that it diverts uniform expression of each sgRNA using a single co-promoter [36].
CRISPR system is also a system that may be widely used in genome editing, gene expression, epigenetic regulation and cell imaging. In gene editing administrations, a PAM must follow the target sequence (for spCas9 protein) and, PAM consists of NGG/NAG nucleotides. sgRNA consists of approximately 20 nucleotides targeting the gene and a scaffold RNA domain that can interact with the nuclease. sgRNA directs Cas9 nuclease to the target sequence [18].
It is known that genome editing systems are used in the treatment of diseases in recent years. The use of these systems enables the study of the functions of genes and regulatory sequences that will facilitate the knock-out of target locus. In addition, hereditary disease models are constituted using these systems and may develop new methods for the treatment of these diseases. These systems have various structures that mediate some important functional parameters [3].
ZFNs
ZFN is a chimeric nuclease and consists of two parts. The first part consists of 3–4 zinc finger domains. Nuclease domain of endonuclease Fok-1 is known as the second part. Nuclease domains may form double chain breakage after dimerization of two ZFN subunits close together, and these nuclease domains are the same [37, 38]. The transcriptional repressor protein or specific nuclease is connected to the DNA-binding element consisting of a series of multiple zinc-finger peptides. Each zinc-finger can interconnect 3 or 5 different nucleotide sequences of the DNA strand [39]. Zinc-finger proteins do not have nuclease activities and ZFPs only can bind to DNA and reduce gene expression levels. Thus, gene transcription is also prevented. ZFPs are designed to be selectively linked to extended CAG repeats. Thus, they can specifically connect to the mHTT gene. Zinc-finger transcriptional repressor approaches can reduce mHTT levels by targeting without changing the DNA. In contrast, direct genome editing approaches, such as CRISPR/Cas9, may permanently correct CAG expansion causing disease in HD by disrupting or correcting the mutant gene. ZFNs use the nuclease effector domain linked to a DNA recognition domain, and TALENs are similar to ZFNs [3].
TALENs
TALENs consist of an artificial DNA binding domain and the DNA cleavage domain of endonuclease Fok-1, such as ZFN. DNA binding domains consist of monomers containing consecutive repeats of 34 amino acids. These monomers that localized at 12 and 13 positions are those with variable sequence repetition and they are responsible for recognizing the nucleotide. There are Repeat Variable Diresidues (RVD) in the target DNA region that bind the A, T, G, C nucleotides, respectively. It is known that the DNA binding domains of the two subunits are known to be associated with DNA chains, and the C-terminal Fok-1 domains dimerize and divide the target DNA region [40]. It is known that TALEN has higher effectivity and specificity than ZFN. However, TALEN requires T in the 5' end of the target region which limits the options of the target sequences. TALEN uses a number of specific amino acid repeats that bind to a specific nucleotide. Different combinations of amino acid repeats are produced to recognize the specific DNA sequences. The TALEN-based approach has higher efficiency and specificity than the ZFN-based approach. However, TALENs require a specific nucleotide and this nucleotide may limit targets at the end of the DNA sequence [3]. In studies conducted in HD fibroblasts using the TALEN-based approach, a reduction was determined in mHTT expression and aggregation. It has been shown that it is possible for allele-specific HTT gene modification using the TALEN-based approach [8].
CRISPR/Cas9 Approach
The CRISPR/Cas9 system can target specifically any region in the genome. This system, which can lead to undesirabe changes in non-target areas, enables genome editing with high efficiency. Genomic imbalance may develop as a result of the emergence of non-target effects. Genomic imbalance can impair the functionality of normal genes. Therefore, a new modified Cas9 nuclease is created. Cas9 specificity has been developed with translocations in the Cas9 sequence. These displacements cause some hydrogen bonds to block between Cas9 and the target DNA chain. As a result of these modifications, the energy of the Cas9-sgRNA complex change, thereby off-target binding and off-target effects reduce [3]. CRISPR is a commonly used method as genome editing technology in basic biomedical research. This technology which is used in the research and treatment of human diseases, is applied to correct DNA mutations that can cause disease in cell and animal models. CRISPR/Cas9 gene regulation, besides the treatment of genetic diseases, it is also used in immunology-focused therapies to support AIDS treatment or anti-tumor immunotherapy. The CRISPR/Cas9 system acts as an adaptive immune defense based on the destruction of viral pathogens by cutting of the target DNA with Cas nucleases at the end of the CRISPR sequences. Cas nucleases have been made specific to the pathogen by the specific feature of the enzyme required for an RNA guide that activates the enzyme and selectively targets the nuclease complementary DNA sequences. Cas nucleases are applied as high quality nuclease in this respect and DNA breaks or notches can be produced in any region of genomic DNA in vivo by these nucleases. The specific CRISPR/Cas9 system has two basic components as Cas9 nuclease and the required sgRNA. The function of sgRNA is to determine the specificity of a target DNA sequence by linking to complementary DNA sequences through the base pair. Cas9 co-localizes in the same specific region by connecting of sgRNA, it causes in cuts and DSB formation in the DNA backbone. sgRNA and Cas9 are introduced to the cells through vectors that depends on administration using recombinant DNA technology [33]. CRISPR/Cas9 system is an approach that recognizes and destroys foreign DNA and forms the basis of the bacterial immune system [41]. In the CRISPR/Cas9 approach, the Cas9 protein is known as an RNA-guided nuclease, which separates double strand breaks in certain DNA regions. In this approach, Cas9 nuclease does not use a protein-based DNA recognition domain. To target specific regions of DNA, Cas9 protein is directed by specific guide RNAs. In gene editing administrations, it should be followed by a specific recognition region known as the PAM sequence. PAM usually contains 2 or 5 nucleotides and it consists of PAM, NGG or NAG nucleotides for the first protein used in gene editing [42]. Cas9 nuclease forms are combined with synthetic guide RNAs so ribonucleoprotein structures (RNP) can be produced that can be targeted to selected DNA regions [31]. The CRISPR/Cas9 approach, alter the HTT gene encoding without permanent genome modification and it is an effective therapeutic approach for HD (Fig. 3) [3, 43, 44]. The CRISPR/Cas9 system is also used to inactivate mHTT genes that target genetic variations associated with the CAG-expanded allele in fibroblasts derived from patients. Thus, a total decrease occurs in RNA and mHTT protein [45]. It has been showed that using this method, mHTT expression in the brain inactivated in mouse models targeting genetic variations associated with CAG expansion and in differentiated iPSCs in humans [46, 47].Fig. 3 CRISPR/Cas9 approach to reduction and permanent inactivation of HD [43]
Applications of CRISPR/Cas 9 System
CRISPR/Cas 9 system applications are classified as research applications, therapeutic applications, and diagnostic applications. The CRISPR/Cas 9 system has been applied in genetic studies, the production of cellular models, and the production of animal models. Therapeutic gene editing or gene therapy is used for various diseases such as cardiovascular disorders, hematological diseases, different types of cancer and neurodegenerative disorders. These approaches are accomplished by ex vivo manipulation of cells or in vivo delivery of genome editing tools. In addition, the CRISPR/Cas 9 system is used as an important diagnostic tool for microbial diseases and other diseases. CRISPR-based nucleic acid detection methods are applied in the diagnosis of COVID-19. This system is also applied in the detection of viral, fungal and bacterial pathogens, in the diagnosis of infectious diseases and various types of cancer [48].
DNA Repair Pathways in Genom Editing Systems
Cellular mechanisms repair the defect after Cas9-mediated DNA cleavage. These cellular mechanisms are classified as nonhomologous end joining (NHEJ) and homologous-directed repair (HDR). NHEJ, which is more prone to error, is usually characterized by insertion or deletion (INDEL) mutations (Fig. 4) [18, 49, 50]. When sgRNA targets 5' end of a coding sequence, it causes frame shift and early stop codon. Thus, the functional impairment of the gene occurs. HDR system is a weakly active system in postmitotic cells. In this system, endogenous or exogenous DNA templates are used around the target sequence to repair DSB [18]. The HDR mechanism uses another DNA sequence to correct the fragmentation. In genome editing applications, exogenous DNA sequence with a desired sequence is formed by using nuclease. Then the new DNA sequence is introduced directly to the target area and repair is provided [31].Fig. 4 DNA repair mechanisms in gene editing systems [49]
Stem Cells in Regenerative Medicine
Regenerative medicine is a therapeutic approach using stem cells. The aim of regenerative medicine is to restore the functions of injured and affected cells, tissues, and organs. This therapeutic approach is integrated with CRISPR/Cas technology. Various diseases may be treated with cell-based therapeutic strategies. In these cell-based therapies, single cell suspensions of stem cells are cultured and these cells are delivered to the target specific organ by direct injection. Stem cells are unique cells that can transform into specific cell types and regenerate damaged tissues. Induced pluripotent stem cells (iPSCs), one of the stem cells that form the basis of regenerative medicine, are used in various disorders such as organ failures, spinal cord injuries, skin disorders, neurological damages. CRISPR/Cas systems result in applications based on iPSC stem cells. iPSC stem cell sources through the CRISPR/Cas system are used in the production of various regenerative drugs. iPSCs are known as patient-specific pluripotent stem cells and play an important role in therapeutic applications of neurodegenerative disorders. CRISPR/Cas 9 genome editing technology allows editing the genome of stem cells using modified stem cells as regenerative drugs in therapeutic applications [51]. The CRISPR/Cas 9 system is also used for live cell imaging of genomic loci and for monitoring RNA in living cells [52].
Huntington’s Disease Treatment Approach in Cell and Animal Models
CRISPR/Cas9 approach is applied to individuals with specific genetic diseases in the treatment of the disease through the production and characterization of patient-derived iPSCs derived from these individuals. The production of human iPSCs derived from the disease occur through advanced translational research. It was known that iPSCs are used in in vitro modeling in neurodegenerative disorders such as Alzheimer’s disease, Parkinson’s Disease, and Huntington’s disease. The CRISPR/Cas9 system is also used in the modeling of human diseases in vivo and in the production of genome-regulated animals carrying genetic mutations responsible for human diseases. These models are very important in defining the pathology of the diseases and thus in developing the treatments for the diseases. In CRISPR/Cas9-mediated gene editing therapy, it is aimed to correct the mutations causing diseases in vivo [33].
Features of iPSC
iPSCs are similar to embryonic stem cells in terms of self-renewal and pluripotent properties. They are obtained from virus-mediated through induction from human iPSC fibroblasts. It has been reported that HD-iPSC line with different CAG repeat lengths and control iPSC lines has been created in HTT [10]. iPSCs derived from patients can be differentiated into disease-related neurons, thereby therapeutic strategies are developed by in vitro modeling. iPSCs derived from patients can be used for modeling of neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease [2]. It was determined that cells derived from HD patients show cellular changes, protein expression changes and mitochondrial dysfunction compared to control cell lines [10]. Patient somatic cells can be reprogrammed to iPSCs so that disease-related cells can be produced in in vitro disease modeling. Human iPSCs can differentiate into any cell type in the human body. Therefore, these cells may play a role in genetic variations associated with pathogenesis. iPSCs can be used in human disease models such as developmental and adulthood diseases. The use of these cells can be in the form of two-dimensional (2D) cell cultures or three-dimensional (3D) organoids. Cells derived from patient iPSCs are used to determine the phenotypes of various human neurodegenerative diseases. In addition, phenotype-based drug screening can be performed on disease target cells produced from iPSCs. Gene editing technologies are combined with derived iPSCs from patient. Thus, a series of genetically identifiable human iPSC lines can be created for disease modeling. iPSCs have organizational ability themselves. These capabilities are extremely important for progenitor region organization, neurogenesis, and gene expression [2].
iPSC-based Disease Modelling in Huntington’s Disease
HD, which is an autosomal dominant, monogenic, fatal, progressive neurodegenerative disease, is characterized by exonic CAG repeats in the HTT gene. The extended CAG repeats encode a polyglutamine region. CAG repeats cause a toxic function gain and lead to preferential deaths of GABAergic projection neurons in the striatum. It is known that HD symptoms occur in middle age. Although there is a specific treatment for HD, there is generally no available treatment [53]. It is known that the main sensitive cell type in HD is MSNs. Human iPSCs are used to form the MSNs. For HD modeling, it is possible to form MSNs from iPSCs derived from HD patients. Thus, HD-related phenotypes such as neuronal degeneration and mHTT protein aggregation can be determined in nerves derived from HD-iPSCs. There are studies showing that the formation of mHTT aggregates in HD-iPSC-derived neurons is rare. Better in vitro HD modeling can be performed by creating isogenic HD-iPSC pairs. HD-iPSCs can provide to improving of CAG locus in HTT gene (Fig. 5) [3, 54]. Recovery of disease phenotypes such as mitochondrial abnormalities can be achieved by neurons derived from isogenic lines. In addition, the production of genetically corrected isogenic lines for in vitro neuronal induction may be carried out using the CRISPR/Cas9 system. In various studies, neurons derived from iPSCs are used to investigate HD pathogenesis and develop effective therapeutic strategies for HD [2].Fig. 5 CRISPR gene editing with human iPSCs [54]
CRISPR/Cas9 Approach with iPSC for HTT Gene Editing
In a previous study, it has been shown that HD-iPSCs can be genetically correctable. In this study, cellular HDR system was used together with antibiotic selection. There are also studies showing that some of the iPSC clones can be corrected after antibiotic selection using a pair of sgRNA and Cas9 D10A nickase. Wild-type Cas9 protein catalyzes sgRNA-targeted DSBs. In contrast, Cas9 D10A nickase create sgRNA-targeted single-strand break in DNA. Therefore, it is thought that Cas9 D10A shows improved target sequence specificity. In another study, it was found that the HTT allele carrying the CAG expansion was selectively inactivated by CRISPR/Cas9 mediated excision in fibroblasts derived from HD patients. Suppression of non-target effects in non-consensus areas should be ensured in order for CRISPR/Cas9-mediated gene therapy to be widely used in the clinical environment [10].
Conclusion
HD is an inherited neurodegenerative disease and degrades motor and cognitive functions by targeting striatal MSNs. As a result of the expansion of the PolyQ pathway, the mutHTT protein becomes toxic to neurons. Therapeutic strategies are being investigated in various preclinical models and clinical trials. These therapeutic strategies have been associated with a reduction in mutHTT content at the level of genome, mRNA, or protein degradation. There are also therapeutic strategies associated with post-translational modification of mutHTT. In addition to these, stem cell therapy may also be used due to the loss of striatal neurons. As a result of these clinical studies, important biomarkers may be obtained for the treatment of HD disease. Comprehensive modeling and analysis of human diseases at cellular and molecular levels are possible by developing new technologies for gene editing. The ZFN, TALEN, CRISPR/Cas9 approaches reveal different modifications. These systems regulate gene expression in different cell types, such as iPSCs and gene sequences. These systems, which are used to create isogenic cell lines carrying different numbers of CAG repeats, can also be used to correct mutations that cause HD. In recent years, many studies have been carried out to modeling molecular mechanisms and genetic diseases. ZFN and TALEN are the first artificial nuclease. These systems are simpler than CRISPR system. Human iPSCs are used to create cell types associated with diseases to investigate the mechanisms underlying human diseases. In order to explain cellular progression for neurodegeneration in vitro, iPSCs derived from the patient can spread to specific neuronal subtypes and can be differentiated effectively. Differentiated iPSCs can be used in various neurodegenerative disease modeling such as Alzheimer’s disease, Parkinsons disease, and Huntington’s disease. Many obstacles must be overcome in order for iPSC-based technology to be used in clinical administrations. However, the combination of iPSC technology with genome editing technology will enable the development of new treatments and drugs for human neurodegenerative diseases.
Author Contribution
SSA and NA conceived the idea for the article. SSA, NA, AA and IA searched the literature. SSA and NA wrote the manuscript. SSA created the figures. All authors read and approved the final manuscript. The corresponding author attests that all listed authors meet the authorship criteria and that no other authors meeting the criteria have been omitted.
Data Availability
Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
Declarations
Consent for Publication
The author, SSA, NA, AA and IA have read and approved the final manuscript for submission. We confirm the figures are original for this article.
Conflict of Interest
The authors declare no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
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J Med Toxicol
J Med Toxicol
Journal of Medical Toxicology
1556-9039
1937-6995
Springer US New York
36469243
920
10.1007/s13181-022-00920-4
Editorial
Demand for Medical Toxicology Fellowship Training Is at an All-Time High
http://orcid.org/0000-0002-1196-6930
Pizon Anthony F. [email protected]
1
Kao Louise 2
Mycyk Mark B. 3
Wax Paul M. 4
1 grid.21925.3d 0000 0004 1936 9000 Division of Medical Toxicology, Department of Emergency Medicine, University of Pittsburgh School of Medicine, 3600 Forbes Ave, Iroquois Building, Suite 400, Pittsburgh, PA 15213 USA
2 grid.257413.6 0000 0001 2287 3919 Department of Clinical Emergency Medicine, Indiana University School of Medicine, Indianapolis, IN USA
3 grid.428291.4 Department of Emergency Medicine, Cook County Health, Chicago, IL USA
4 grid.488395.b 0000 0000 8821 6711 American College of Medical Toxicology, Phoenix, AZ USA
Supervising Editor: Andrew Chambers, DO
5 12 2022
13
23 11 2022
23 11 2022
28 11 2022
© American College of Medical Toxicology 2022
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Keywords
NRMP Match
Fellowship
Medical Toxicology
ERAS
ACMT
==== Body
pmcThe American Board of Medical Specialties formally recognized Medical Toxicology as a specialty in 1993. Seven years later, Medical Toxicology fellowships received approval in the USA by the Accreditation Council for Graduate Medical Education (ACGME). Less than 3 decades as a formal specialty, the 2023 NRMP (National Residency Matching Program) Match results confirm demand for this relatively young specialty has increased significantly in the last few years and is now at an all-time high.
A medical toxicologist specializes in the prevention, evaluation, and treatment of illness from exposure to drugs, chemicals, and radiological and biological agents. The specialty also focuses on the diagnosis and management of addiction, which includes the treatment and prevention of withdrawal conditions. Some key attributes of medical toxicologists are their intimate knowledge of pharmaceuticals, chemicals, and venoms and how to treat patients with such exposures. This unique knowledge positions the medical toxicologist as skilled clinician, educator, researcher, and administrator. This scope of opportunity has made Medical Toxicology an intriguing specialty for many residents looking for a career with advanced expertise and high job satisfaction [1, 2].
Due to the breadth and depth of knowledge required for this specialty, the expertise of Medical Toxicology spans many disciplines in medicine. These include, but are not limited to, emergency medicine, pediatrics, occupational medicine, critical care, internal medicine, psychiatry, nephrology, clinical pharmacology, and others. Medical Toxicology is truly a multidisciplinary specialty. Though most residents enter the specialty through emergency medicine, applicants from all specialties are invited to apply [3]. The diversity of expertise is needed and welcomed in Medical Toxicology. We still have much work to do to encourage applicants from other specialties [4].
As interest in the specialty has grown, the American College of Medical Toxicology (ACMT) Fellowship Directors Committee has made several strategic moves to ease the application process. In 2013, for the 2014 appointment year, Medical Toxicology fellowships joined the NRMP. This allowed programs to coordinate the application cycle while applicants complete all desired interviews before entertaining offers. In 2022, Medical Toxicology fellowships implemented ERAS (Electronic Residency Application System). Not only does ERAS professionalize the application process, but applicants can also more simply submit the numerous required documents to programs across the country. These two steps improved the efficiency of the busy recruitment season for both fellowship directors and applicants.
Since implementation of the NRMP, Medical Toxicology fellowships have seen a slow, albeit steady rise in applicants (see Table 1) [5, 6]. November 16, 2022, signified the most current Match Day for Medical Toxicology fellowships. This was a momentous day for both fellowships and applicants as it signified the culmination of a hectic recruitment season. More importantly, this Match Day was particularly historic as the busiest in Medical Toxicology history. For the first time since joining the NRMP, all Medical Toxicology fellowships filled, and a record number of applicants vied for one of 49 available fellowship positions across the country.Table 1 Medical Toxicology applicant data since entering the NRMP (5, 6).
Matriculation year Programs % programs filled Positions % positions filled Applicants # applicants per position % matched % unmatched
2014 25 48.0% 37 54.1% 24 0.6 83.3% 16.7%
2015 25 60.0% 40 70.0% 35 0.9 80.0% 20.0%
2016 26 34.6% 41 46.3% 21 0.5 90.0% 10.0%
2017 26 65.4% 47 74.5% 42 0.9 83.3% 16.7%
2018 27 66.7% 47 74.5% 40 0.9 87.5% 12.5%
2019 28 50.0% 54 66.7% 41 0.8 87.8% 12.2%
2020 26 61.5% 51 76.5% 46 0.9 84.8% 15.2%
2021 28 60.7% 50 68.0% 36 0.7 94.4% 5.6%
2022 28 85.7% 54 92.6% 58 1.1 86.2% 13.8%
2023 28 100.0% 49 100.0% 70 1.4 71.4% 28.6%
The fellowship directors also adapt well. In particular, the COVID-19 pandemic has greatly impacted post-graduate recruitment. Program directors quickly moved to virtual interviews when needed and have currently migrated to a hybrid approach. The ability to perform interviews in this fashion has empowered applicants to explore more programs while allowing individual fellowships to meet a deeper and broader pool of talented applicants. This strategy also strives to right-size an important equity issue. Virtual and hybrid options afford trainees with limited resources and time the opportunity to interview with programs beyond their means. This is critically important as we seek to increase diversity within our programs. This flexibility among fellowship directors, and therefore our programs, should be viewed as a strength. In part, our ability to recruit strong and diverse applicants can be attributed to the flexible nature of the interviewing process.
Likewise, the future of the Medical Toxicology specialty is healthy. As fellowships succeed, the specialty will continue advancing. There is a well-defined need for medical toxicologists to thrive in value-driven health care. We clearly provide better health, better care, and lower costs [7, 8]. Notably, we have most recently demonstrated our positive impact with patients suffering from substance use disorder [9]. Our growth allows opportunities to have even greater impact in areas such as the prevention of adverse drug events and pharmaceutical stewardship [10]. There is great demand for our expertise, and both applicant and medicine-at-large recognize the demand.
ACMT will continue to work diligently to advance our specialty as a valued and recognized contributor to improved health care within the country and across the globe. Rather than becoming complacent, we will continue our unwavering commitment for steady growth and positive impact to patient care. Medical Toxicology is committed to diversity and equity, and our healthy Match and current trajectory will allow us to reflect on these important priorities as we continue to expand our reach, elevate our standards, and continue to welcome interested applicants who will meaningfully contribute to our developing specialty.
Sources of Funding
None.
Declarations
Conflicts of Interest
The authors (AP, LK, MM, PW) are currently members of the ACMT Board of Directors, and two authors (AP, LK) currently serve as program director of a fellowship training program.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
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| 36469243 | PMC9734919 | NO-CC CODE | 2022-12-14 23:28:31 | no | J Med Toxicol. 2022 Dec 5;:1-3 | utf-8 | J Med Toxicol | 2,022 | 10.1007/s13181-022-00920-4 | oa_other |
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Arch Comput Methods Eng
Arch Comput Methods Eng
Archives of Computational Methods in Engineering
1134-3060
1886-1784
Springer Netherlands Dordrecht
9858
10.1007/s11831-022-09858-w
Review Article
Advances Towards Automatic Detection and Classification of Parasites Microscopic Images Using Deep Convolutional Neural Network: Methods, Models and Research Directions
http://orcid.org/0000-0002-0030-3023
Kumar Satish [email protected]
1
Arif Tasleem 1
Alotaibi Abdullah S. 2
Malik Majid B. 3
Manhas Jatinder 4
1 Department of Information Technology, BGSB University Rajouri, Rajouri, J&K 185131 India
2 grid.449644.f 0000 0004 0441 5692 Computer Science Department, Shaqra University, Shaqra, Kingdom of Saudi Arabia
3 Department of Computer Sciences, BGSB University Rajouri, Rajouri, J&K 185131 India
4 grid.412986.0 0000 0001 0705 4560 Department of Computer Sciences & IT, University of Jammu, Jammu, J&K India
3 12 2022
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17 3 2022
19 11 2022
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In the developing world, parasites are responsible for causing several serious health problems, with relatively high infections in human beings. The traditional manual light microscopy process of parasite recognition remains the golden standard approach for the diagnosis of parasitic species, but this approach is time-consuming, highly tedious, and also difficult to maintain consistency but essential in parasitological classification for carrying out several experimental observations. Therefore, it is meaningful to apply deep learning to address these challenges. Convolution Neural Network and digital slide scanning show promising results that can revolutionize the clinical parasitology laboratory by automating the process of classification and detection of parasites. Image analysis using deep learning methods have the potential to achieve high efficiency and accuracy. For this review, we have conducted a thorough investigation in the field of image detection and classification of various parasites based on deep learning. Online databases and digital libraries such as ACM, IEEE, ScienceDirect, Springer, and Wiley Online Library were searched to identify sufficient related paper collections. After screening of 200 research papers, 70 of them met our filtering criteria, which became a part of this study. This paper presents a comprehensive review of existing parasite classification and detection methods and models in chronological order, from traditional machine learning based techniques to deep learning based techniques. In this review, we also demonstrate the summary of machine learning and deep learning methods along with dataset details, evaluation metrics, methods limitations, and future scope over the one decade. The majority of the technical publications from 2012 to the present have been examined and summarized. In addition, we have discussed the future directions and challenges of parasites classification and detection to help researchers in understanding the existing research gaps. Further, this review provides support to researchers who require an effective and comprehensive understanding of deep learning development techniques, research, and future trends in the field of parasites detection and classification.
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pmcIntroduction
Parasites are organisms that grow in or on a host and obtain food from the host. Parasites are too tiny and not visible clearly with naked eyes however, they can be observed under a microscope. The parasites community that cause disease in humans includes protozoa, helminths and ectoparasites. It is estimated that 357 million cases of morbidity, mostly infected by protozoa, Cryptosporidium, Entamoeba, and Giardia, resulted in 33,900 deaths and the loss of 2.94 million disability per year [1] and more than 1.4 billion people are infected with helminths [2]. Various other parasites act as pathogenic and cause diseases also in plants, and other living organisms. They are responsible for causing various deadly diseases like Giardia (through contaminated water), toxoplasmosis (spread by cats), malaria etc. [3]. One of the helminths parasites globally causes infection in more than 800 million people [4]. In developing countries including East Asia, South America, Saharan Africa etc. there are more than 100 human intestinal parasite species that produce 200,000 eggs per day and annually 41,500 human deaths are reported due to parasitic infections [2, 5]. Infection caused by these diseases display a wide range of clinical explanations ranging from malnutrition to asymptomatic anaemia and even cause cancer [6, 7]. Conventional light microscopic examination remains the gold standard method for diagnosis of several parasites diseases, such as malaria [8].
There are numerous shortcomings of these methods, which have serious potential to sway the results of clinical examinations, such as variable sensitivity, resource and time-consumption. Another drawback of the traditional clinical parasitology classification and detection is maintaining staff competency and engagement. The clinical parasitology laboratory also suffers from two major aspects firstly, educated technologists increasingly gravitate toward technology-driven and automated disciplines of laboratory and secondly, shortage of adequately trained personnel [9] to keep them staffed. Results based on diagnosis of parasites are often obtained from clinical signs and symptoms that are susceptible to human errors which may lead to higher mortality and buying of unnecessary drugs leading to economic burden [10] and despondency. In consequence, alternate methods are required which help to generate quality diagnosis results. To date, to the best of our knowledge, there have been no significant technological advancements for the detection of protozoa in human stool specimens using permanently stained slides (e.g., trichrome, modified acid-fast, and modified safranin).
The objective of this review is to establish the vital aspect of deep learning in parasite microscopic image classification and detection to make it easy for researchers to have a clear image of deep learning for parasitology from this survey paper. Further, this systematic review of deep learning models for microscopic images helps people discover more about recent growth in this field. In this review, we analysed deep learning techniques applied in parasitological image application and in turn made the following contributions:We demonstrated that how a pre-trained Convolution Neural Network (CNN) performance improves by fine-tuning different layers.
We demonstrated CNN and transfer learning potential to detect and classify human parasites taken from images along with state-of-the-art architectures.
In this review, we cover challenges faced in deep learning including small-scale training data, noised image, data interpretability, and model compression, uncertainty scaling, over-fitting and vanishing gradient problems.
This review provides a broad survey of the most important aspects of parasite microscopic image analysis using deep learning. This review depicted in Fig. 1 is organized as follows. Section 2 describes the fundamentals concepts of deep learning, which include convolution layers components, methods & models and evaluation metrics. In Sect. 3, we discuss methodology used to conduct this review including research questions, paper retrieval and filtering process. In Sects. 4 and 5, detailed gist of each machine learning and deep learning method and model elaborated in selected research papers has been provided respectively. Summary of each research paper and their future scope is presented in the form of tables. In Sect. 6 various results have been discussed that will provide research directions in parasites image detection and classifications. Finally, In Sect. 7 conclusion and future scope is presented.Fig. 1 Systematic organization of the review
Background
The following subsections provide a succinct explanation of various concepts and technologies associated with the work presented in this paper. Section 2.1 provides an overview of Deep Learning, Sect. 2.2 discusses about CNNs and Sect. 2.3 provides a gist of CNN models and parasite datasets.
Deep Learning Overview
In this section, we present the analysis of deep learning fundamentals that addresses wide range of issues including medical images detection, segmentation and classification. The section begins with an introduction to deep learning, then on to cover various techniques, and concludes with transfer learning techniques and models built on CNNs to increase the effectiveness of automatic parasite identification and categorization. Deep learning is a subfield of machine learning inspired by the structure and function of the human brain neural network. In medical diagnosis, deep learning methods and models operate on large amounts of medical image data to transfer the given dataset to some specific labels (Fig. 2).Fig. 2 Comparison between two techniques: a workflow vs. b deep learning workflow. Traditional Computer Vision algorithms employed pre- processing, feature extraction, wise feature selection to achieve the classification and deep learning techniques automate the several tasks of machine learning algorithms
A large number of artificial neural network layers are used in the development and design of deep learning, with each layer carrying out a different evaluation based on the information it receives. [11, 12]. Conventional machine learning algorithms employ various steps to achieve the classification tasks like pre- processing, feature extraction, feature selection and learning. Conversely, Deep learning techniques automate several tasks of machine learning algorithms [12, 13], as shown in Fig. 1. Deep learning gained popularity in recent years due to exponential growth of data [14]. Deep learning methods and models have the potential to enhance human lives with accuracy in diagnosis including pathogen detection and classification such as malaria, intestinal parasite and tuberculosis, etc. In recent times i.e. after the onset of COVID-19 pandemic, Deep learning (DL) is playing a vital role in the automatic diagnosis of novel coronavirus [15]. DL methods and models include Deep Feedforward Neural Network (DFNN), Convolutional Neural Network (CNN) [16], Recurrent Neural Network (RNN) and Auto-encoder. The overview of prominent DL-model architectures is depicted in Fig. 3, which can be used to enhance the efficiency of automatic parasite classification and detection. Due to it high accuracy, speed and flexibility deep learning is being applied in microscopic examination of parasite species. The end-results may include classification, detection and segmentation. Classification task is applied for recognition of multi-parasite species where microscopic images contain mixed infections. Detection is used to acquire the position of individual parasites or similar group of parasites. Segmentation task’s objective is grouping similar regions or segments of a parasitic image under their respective class. Classification and detection of microscopic parasites are usually performed by CNN and RCNN series models [48, 70].Fig. 3 Overview of deep learning models architectures: a Simple Neural Network with hidden layers, b Recurrent Neural Network for sequence and time series data, c Convolution Neural Network for computer vision
Convolutional Neural Networks (CNN)
CNN structure perform computations based on the structure of human visual cortex and is a popular choice for automatic extraction of relevant features from large amounts of data [17]. A CNN is designed with a sequence of convolution layers, sampling layers followed by fully connected layer as shown in Fig. 3a. Input layers of CNN model is arranged in the 3-dimensions (height, width, and depth), m × m × r. The depth (r) represents the number of channels [14]. In each convolutional layer, several filters are applied and these filters are also organized in 3D, (n × n × q), but values of both n and q are smaller than m and r respectively. The convolutional layer evaluates the product of inputs and weights, as shown in Eq. 1.1 hk=fWk∗x+bk
To accelerate the training process and to handle the overfitting of a model, the down-sampling is applied to layers to extract features. Finally, mid and low-level features are fed to fully connected layers to obtain the high-level of abstraction.
CNN Layers
This subsection discusses each layer of CNN basic architecture along with their functions to deal with parasitic image classification and detection as elaborated below.Convolution Layer: Every CNN architecture includes an important component called convolution layer and each CNN layer is comprised of several filters (kernels). Over N-dimensional metrics of an input image, convolution operations are performed with these kernels to obtain output features. Firstly, the filters are convolved over the entire input image horizontally and vertically during the forwarding pass, then, the product of input images and the filters is determined. It generates a two dimensional visual of image that shows the output of filters at spatial location of the image. The entire process is repeated for input images until there is no possibility of sliding.
Stride is a component of convolutional neural networks that is streamlined for image data compression. Stride is a CNN filter parameter that regulates the amount of movement all over the image. For instance, if the stride of a neural network is set to 1, the filter will move one pixel at a time. Since the filter size influences the encoded output volume, stride is frequently set to a whole integer rather than a fraction or decimal. Padding is also applied to determine the border size information of the input image. It is a technique to maintain the size of image that reduces as a result of strides. Consider the input parasitic image of size H×H×C, suppose F implies number of filters, S implies stride, and P for padding. The following formula can used to determine the output image size:2 Iout=H-F+2PS+1
The output size of parasitic image will be Iout×Iout×Cout
Pooling Layer: Pooling is another important component in CNN architecture to reduce the dimensionality of the feature map. This approach shrinks the large joint feature representation size into small valuable information. The same process of convolution layer is applied in the pooling layer. There are different types of pooling methods that are applied to different pooling layers. These are min pooling, max pooling, average pooling, global average pooling, global max pooling and tree pooling. Three familiar pooling operations are shown in Fig. 4.
Activation Function: Activation functions are nonlinear functions and neural networks utilize different activation functions to map the input values to output. The input to activation evaluate by summation of the dot product of weights and inputs along with bias.
Loss Function: In CNN architecture the final classification is obtained from the output layer. CNN model utilizes several loss functions in the output layer to evaluate the error predicted during training. Next, this error is applied to optimize the CNN learning process. Literally, the loss function is calculated by two parameters. First is the predicted output of the CNN model and the second parameter is the actual output
Fig. 4 Pooling layers operations
Evaluation Metrics
Evaluation metrics play a major role in achieving the optimized classifier to detect and classify the parasite species using deep learning. The performance metrics for parasitic image classification generally include Accuracy, Sensitivity or Recall, Specificity, Precision, F1-Score, J Score, False Positive Rate (FPR) and Area Under the ROC Curve. The evaluation metrics of parasitic egg detection include average precision (AP), precision recall curve, mean average precision (mAP) and area under curve (AUC). The Accuracy is the relationship between the predicted value and the target value. Accuracy evaluates how close the predicted value is to the target value. Sensitivity calculates the predicted output with respect to the change in input, which means sensitivity shows the ratio of the true positives that are correctly identified. In contrast specificity, which calculates the ratio of true negatives that are correctly identified. TN and TP are the number of negative and positive instances, respectively, for successfully classification and detection of parasites. Further, FN and FP are defined as the number positive and negative instances respectively, for misclassification. The parasitic images classification and detection based on deep learning are measured with the help of following formula:Accuracy measures the ratio of correct predicted value to the total number of instance evaluated.3 Accuracy=TP+TNTP+TN+FP+FN
Sensitivity or Recall measures the fraction of positive values that are correctly classified4 Sensitivity=TPTP+FN
Specificity measures the fraction of negative values that are correctly classified.5 Specificity =TNFP+TN
Precision measures the positive values that are correctly predicted by all predicted values in a positive class.6 Precision =TPTP+FP
F1-Score measures the harmonic average between recall and precision rates.7 F1-Score= 2*Precion*RecallPrecion+Recall
J Score also called as Youdens J statistic.8 J-Score= Sensitivity+Specificity-1
False Positive Rate (FPR) measures the possibility of a false alarm ratio9 FPR= 1 -Specificity
Area Under the ROC Curve (AUC) is used to measure comparisons between learning algorithms, as well as to construct an optimal learning model. The following equation is used to measure the AUC value for two-class problem.10 AUC =sp-np(np+1)2npnn
CNN Models and Parasite Datasets
Over the last two decades, numerous CNN models have been proposed to perform different tasks [35]. CNN architecture has been updating from time to time from 1989 up to this day. Updating in CNN includes regularization, structural reformulation, parameter optimizations and more. In this subsection, the authors discuss the most popular CNN models starting from the AlexNet model to the EfficentNet model, as shown in Fig. 5. The overview of popular CNN architectures along with model depth, dataset used, parameter error rate and input size are presented in Table 1.Fig. 5 Overview of CNN architectures over a timeline (1998–2020)
Table 1 An overview of CNN architectures with brief detail
Model Main finding Depth Dataset Parameters (M) Error rate Input size References
AlexNet Used Dropout and ReLU 8 ImageNet 60 16.4 227 × 227 × 3 [17]
VGG Increased depth, small filter size 19 ImageNet 138 7.3 224 × 224 × 3 Simonyan and Zisserman [18]
GoogLeNet Increased depth, different filter size, concatenation 22 ImageNet 4 6.7 224 × 224 × 3 Szegedy et al. [19]
Inception-V3 Utilizes small filter size, better feature representation 48 ImageNet 23.6 3.5 229 × 229 × 3 Szegedy et al. [20]
Inception-V4 Divided transform & integration concepts 70 ImageNet 35 3.08 229 × 229 × 3 Szegedy et al. [21]
ResNet Robust for over-fitting 152 ImageNet 25.6 3.57 224 × 224 × 3 He et al. [22]
Inception-ResNet-v2 Use residual links 164 ImageNet 55.8 3.52 229 × 229 × 3 Szegedy et al. [21]
Xception Convolution followed by a point wise convolution 71 ImageNet 22.8 0.05 229 × 229 × 3 Chollet [23]
DenseNet Used blocks of layers 201 ImageNet, CIFAR-100, 25 3.46, 5.54 224 × 224 × 3 Huang et al. [24]
MobileNet-v2 Inverted residual structure 53 ImageNet 1.677 – 224 × 224 × 3 Sandler et al. [25]
HRNetV2 High-resolution representation – ImageNet 45.2 5.4 224 × 224 × 3 Ke Sun et al. [26]
Parasite Datasets
In order to enhance the deep learning method and models to diagnose the parasitic diseases using microscopic images, various parasite datasets have been used which are summarized and described in Table 2. The Table includes the dataset of Plasmodium, Toxoplasma and Intestinal parasites. This review contains some important datasets of other parasites also, such as Leishmania, Babesia and Trichomonad. These datasets are mostly used for classification and detection tasks. Some publicly available microscopic images of parasites from representative datasets for deep learning are shown in Fig. 6.Table 2 Represent publicly available microscopic image datasets of protozoan parasites
Parasite types and image number Descriptions Dataset source References
Plasmodium falciparum-2703 Annotated image dataset with bounding boxes of 50,255 parasites. The dataset also contains 1182 thick blood smear images with bounding boxes of 7245 parasites https://air.ug/microscopy/ [27]
Plasmodium-15,927, Babesia-1100 This dataset contains totally 23,463 microscopic images of multi-stage Plasmodium, Babesia and host cells (RBCs
and Leukocytes) under ×1000 magnification
https://github.com/senli2018/DTGCN_2021 [28]
Toxoplasma gondii-8,156 with 400×, 6969 with 1000× This FCGAN dataset also includes 4979 host cell images at ×400 and 8023 host cell images at ×1000 magnification https://github.com/senli2018/FCGAN/b [29]
Chula-ParasiteEgg-11 1000 and 250 images/class for training and testing Chula-ParasiteEgg-11 training dataset contains 11 types of parasitic eggs from faecal smear samples Each category has 1000 images https://icip2022challenge.piclab.ai/dataset/ [30]
Fig. 6 Three different datasets of publicly available protozoan parasite for deep learning. a Intestinal parasitic dataset [29]. The dataset contains 11 types of parasitic eggs from faecal smear samples. Each category has 1000 images. b Depict the parasites images from dataset [38]. This dataset includes six types of parasites species images (Toxoplasma, Leishmania, Babesia, Plasmodium, Trichomonad, Trypanosome) and RBCs and Leukocyte host cells in the cropped patches. c The dataset contains Plasmodium falciparum cropped image patches from parasitized and uninfected RBCs [17]
Survey Methodology
To organize a systematic review, first, we frame the research questions for conducting this research and then present our analysis of the relevant deep learning-based research papers in the concerned domain, in chronological order. Next, we demonstrate the summary of existing methods and models along with the results based on the review of some potential techniques. Finally, we introduce the future directions and outline prominent challenges in parasites detection and classification. We reviewed 70 related technical papers from 2012 to the present. This work will act as a guide to researchers for a comprehensive understanding of the present state-of-the-art, future challenges and trends in the research area of parasites detection and classification.
Research Questions
This review aims to provide insights into cutting-edge machine learning and deep learning methods for parasite detection and classification based on microscopic images, as well as an analysis and summarization of previous work on deep computer vision. From that perspective, the authors develop the research questions to be addressed through the research methodologies implemented by researchers. These research questions are shown in Table 3. In the end, this systematic review paper also responds to these research questions posed here.Table 3 Research questions
Q1 What suitable domain knowledge exists for the diagnosis and treatment of human parasites diseases?
Q2 What are the DL based methods and models applied by researchers for parasites image detection and classification?
Q3 What are the various measures applied to evaluating the performance of DL models?
Q4 How has the CNN based transfer learning techniques based developed over time?
Q5 What are the challenges and future direction in parasitology with DL?
Paper Retrieval and Filtering Process
By applying deep learning, we have conducted a potential investigation in the field of image detection and classification of various parasites. As shown in Fig. 7, online databases and digital libraries were searched in order to collect sufficient relevant or related paper collections. The focus was to collect papers from the most reputed publishers, such as ACM, IEEE, ScienceDirect, Springer, and Wiley Online Library.Fig. 7 Search and filter information
The search and filtering process of papers involved in this review is shown in Fig. 8. In the papers retrieving stage, we firstly explore an arbitrary collection of the successive words or phrases in ACM, IEEE, ScienceDirect, Springer, and Wiley Online Library: “machine learning or parasites” and “deep learning or parasites”, “CNN or microscopic images” along with detection, classification, where 298 papers were retrieved. We gathered an additional 50 papers from the references of the retrieved papers. In total, we collected 348 papers in the searching stage. We remove collected papers in two steps during the filtering stage. In the first step, we filtered papers by checking whether the paper was duplicated or not, 21 papers were excluded on this account. In step two, 54 papers were selected for traditional machine learning, 48 papers for deep learning, 15 for both classical image processing and traditional machine learning and 10 papers are related to potential methods, which include visual transformer-based methods.Fig. 8 The search and filter process of papers
Traditional Machine Learning Based Methods and Models
In recent decades, traditional ML methods have gained popularity as a research area and have been applied in a variety of fields, including Natural Language Processing (spam detection, text mining), Computer Vision (Face Recognition, picture deletion and classification), and others. The majority of ML-based techniques and models used today are for object recognition. Related efforts on parasite identification and classification using ML are chronologically discussed in Sect. 4.1.
Machine Learning Related Works in Proposed Field
This section demonstrates related works on parasite detection and classification based on ML, including methods, models, results, and experimental data collection.
In the year 2001, Yang et al. [31] proposed a framework based on an artificial neural network classifier and digital image processing techniques for automatic detection of helminth eggs of humans on microscopic faecal specimens. Digital image processing techniques were applied to extract the morphometric characteristics of eggs of human parasites in faecal specimens from microscopic images. The dataset contained 82 microscopic images of seven common human helminth eggs, which were used to train the proposed model. The proposed ANN model performed identification of human helminth eggs in two stages. In stage first, ANN-1 isolated eggs from confusing artefacts and in stage two, ANN-2 classified eggs by species, as shown in Fig. 9.Fig. 9 Overall processing steps of proposed ANN-based models for both isolation and classification of helminth eggs. For localization and classification of helminth eggs from obtained images. a Digital image processing methods are applied to get meaningful entities and extract their features. b Two stage ANN applied to classified them based on their features
In the same year, Tchinda et al. [32] presented a machine learning technique to recognize intestinal parasite cysts from microscopic images. Probabilistic neural network approach trained by using image pixels feature was employed. It is an effective machine learning approach for classification problems. In this approach parasites separated from microscopic images and then resized to 12 × 12 pixels images. Principal component analysis basis projection is used to reduce the dimensionality. The proposed model was trained on 540 human parasite cyst images. The trained model successfully classified intestinal parasites into 9 different kinds.
In year 2002, K. W. Widmer et al. [33] proposed a ANN based system for Cryptosporidium parvum oocysts detection to reduce the analysis time and achieve the high accuracy of diagnostic process. A total of 525 images of labelled oocysts, fluorescent microspheres, and other miscellaneous nonoocyst images were collected and employed in the training of the ANN. Each type of digital images were separated into 20% for training datasets and 80% for test datasets. Result shows that the correct identification of authentic oocyst images ranged from 80 to 97%, and the correct identification of nonoocyst images ranged from 77 to 82%, on test dataset.
Widmer et al. [34] developed an ANN-based model for automatic identifications of Cryptosporidium oocyst and Giardia cyst digital images. The digital images were captured using a camera at ×400 magnification and converted into a binary array. The ANN for Cryptosporidium oocyst was trained with 1,586 images whereas the ANN for Giardia cyst was trained with 2,431 images. After training these networks were validated with unseen 500 images (250 positives, 250 negatives) of Cryptosporidium oocyst and 282 (232 positives, 50 negatives) images of Giardia cysts. Experimental result of proposed model shows that the ANNs correctly identify the Cryptosporidium oocyst and Giardia cyst images with an accuracy of 91.8% and 99.6% respectively.
Chen et al. [35] proposed a model based on machine learning that performed classification and counting of bacterial colonies from Petri dish images. This model recognized both achromatic and chromatic images effectively. Support Vector Machine approach was used for classification based on morphological features. Two types of Petri-dish were used for experiment. The proposed model predicted comparable performance to accomplish automation of the bacterial colony. The proposed machine learning model achieved 96% accuracy level, For 75 achromatic images 97% accuracy obtained and for 25 chromatic images 95%.
An automatic and rapid detection model based on neural network was developed by Kumar et al. [36] for pathogens in foods. The proposed model involved identification in two stages. In stage first, background correction is applied to distinguish the treated image from the image background using better approaches. In stage second, collecting the images of the local region. Thereafter textural, optical and geometrical features of processed pathogen images are collected. Finally, the proposed model based on Probabilistic Neural Network applied to classify the microorganisms from collected.
Osman et al. [37] developed a model based on image processing and genetic neural network techniques for automatic detectioin of Mycobacterioum tuberculosis in tissues. The proposed model is divided into two steps: step one invoved K-means clustering methods for image segmentation and step second involved GANN method for feature selection, classification and feature extraction purposes. After applying a genetic algorithm to select features, a multilayer perceptron was trained for the final classification of bacteria (true TB and Possible TB). Dataset collection includes 960 total object images of which 360 for true TB and 600 for possible TB. The proposed model was trained on 400 images and the rest of 280 images used for testing purposes. Experimental results demonstrated that proposed approach able to produce 84.9% accuracy with fewer input features.
Hiremath et al. [38] presented identification and classification of a bacterial cell of cocci data collection using machine learning technique. The proposed model was developed using 3α, KNN classifiers and a selected neural network to recognize the pattern of cocci bacterial cells. The data is processed by applying a neural network pipeline that includes inputs layers, output layers, gradient descent and backpropagation function. In this experiment 500 different types (sarcinae, streptococci, diplococci, cocci and tetrad) of digital bacterial images were used. Using the proposed model up to 94% level accuracy was achieved based on the 3α classifier. With KNN classifier where k = 1, 75% to 100% accuracy achieved and up to 100% accuracy achieved with Neural Network classifier.
A ML based approach was implemented by Ghazali et al. [39] for human fecal parasite detection based on computerized image analysis. The presented model contains three stages as shown in Fig. 10. In stage first, the pre-processing techniques were applied to enhance features. In stage second, a features extraction mechanism was used with three characteristics (shape, shell smoothness and size). In stage third, filtration with Steady Determinations Thresholds System method was used to identify and classify the types of parasites based on features values. The final result predicted success rates of Ascarislumbricoides and Trichuristrichiura almost 93% and 94% respectively.Fig. 10 Overview of three different Pre-processing methods: (Pre-method 1) Content noise reduction with median filter, (Pre-method 2) Content edge detection using canny filter and (Pre-method 2) Content edge enhancement using unsharp filter
In [40] developed a model based on machine learning for automatic classification and segmentation of human intestinal parasites. The proposed model classifies into two stages, in stage first segmentation process was performed using image transformation, quantization border enhancement and ellipse matching, as seen in Fig. 11. In the second stage, classification was performed with different ML algorithms like ANN-MLP cum Adaboost, optimum path forest classifier, SVM and SVM cum Adaboost. After investigating the performance of different ML algorithms, the optimum path forest classifier prediceted a good result for classification images. The experiment result shows that the proposed ANN based model classify 155 images from the test dataset with 98.22% accuracy.Fig. 11 Overview segmentation pipeline include operation like Quantization for colored conversion, Border enhancement for quantized image border with Sobel Gradient operator, and Ellipse matching: objects having higher degree of ellipse matching considered as parasite candidate
Nugroho et al. [41] developed a model based on image processing techniques to recognize three phases of malaria parasite cell host in microscopic images i.e. schizont, trophozoite and gametocyte plasmodium falciparum. The proposed model develops in two phases. In phase first image pre-processing was implemented with median filter and contrast stretching. In phase second k-means method was applied for image segmentation. Finally, a multilayer perception backpropagation technique was employed for classification. The data collection contained 60 images of trophozoite, gametocyte and schizont. The proposed model achieved accuracy level of 87% with specificity 90% for detection.
In the year 2016, Seo et al. [42] developed a machine learning model for classification of staphylococcus species. In this experiment, the authors used five different types of species of staphylococcus bacteria namely aureus, haemolyticus, hyicus, sciuri and simulans. Mahalanobis distance method was applied to eliminate the outliers, after that wavelength selection performed using correlation coefficient. The proposed model classified the staphylococcus bacteria species using Partial least square discriminant analysis and support vector machine. With the proposed model 89.8% accuracy was achieved using Support Vector Machine and 97.8% accuracy using Partial least square discriminant analysis.
In [43] purposed an approach that utilized the multi-scale wavelet counter detection to detect the parasites. Jointly active contours and Hough Transform were used to perform detection and segmentation of parasites images. The proposed model involved Principal Component Analysis and Probabilistic Neural Network. Principal Component Analysis was used to extract and reduce the features acquired from parasites images pixels and a probabilistic neural network model was used for the classification task. This model is tested on 15 intestinal parasites species with 900 microscopies images. Using this approach, the correct rate of classification obtained was 100%.
Nkamgang et al. [44] has purposed neuro-fuzzy approach to automatic detection and classification of human intestinal parasites. This model is based on segmentation and training of classifier. In this approach, parasites were localized using circular Hough transform and after that distance regularized level was initialized for segmentation. Finally, classification was performed by applying a trained neuro-fuzzy classifier. The proposed model has been applied for identification and classificatoin of 20 type’s human intestinal parasites. For every 20 classes of intestinal parasites satisfactory classification result was obtained and 100% recognized rate was achieved.
Vakilian et al. [45] developed a model based on image processing techniques and an artificial neural network for recognizing two types of fungi that are responsible for spreading infection in cucumber plant leaves. The proposed scheme contained total 300 images of healthy and infected plants. Among these, 250 images were used for training ANN model and the remaining were used for inspection. In this experiment, the training dataset indicated good fit. The relationship between the outputs and the inputs for validation and test dataset was 0.9.
Liu et al. [46] focused on KNN classifier to classify the morpho type bacterial species based on morphological features. Total 1937 digital images were collected for the proposed system. Among these, 1271 cells images were applied to train the classifier which exhibits 96% accuracy and 466 test cell images exhibit 97% accuracy.
Inayah et al. [47] worked on a Randomly Wired Neural Network for recognize the parasites from red blood cells. Secondary data set is used in this model collected from the National Library of Medicine (NLM). In this model total of 27,558 images of red blood cells were used as data. The proposed model worked on feedforward and backpropagation techniques. Using this model, average accuracy 95.08% was achieved in fivefold cross-validation.
Summary
In the past two decades, traditional ML methods for parasite detection and classification have been updated from time to time. Table 4 displays the related research works, including references, publication date, methods, objectives, species categories, and data details evaluation metrics, limitations, and future scope.Table 4 Summary of reviewed research works on traditional machine learning methods and models as applied for detection and classifications used objective, dataset details which include class (C), total images (T.I), training (Tr.), test (Ts.) and evaluation metrics which include accuracy (Acc.), precision (Pre.), recall (Rec.), sensitivity (Sn.), specificity (Sp.)
References Date Method Type of features Objective Parasites (species) Dataset details Evaluation metrics Limitations Future scope
[31] 2001 ANN Pixel intensity Automatic detection of human helminth eggs Helminth eggs C = 2
T.I = 82
Acc. = 86.1% Small dataset An enhanced model proposed to classify helminth eggs
[32] 2001 ANN Pixel intensity Automatic Identification of human helminth eggs Helminth Eggs C = 7
T.I = 82
Det. = 86.1% Small dataset To improve results large dataset may be used
[34] 2005 ANN Shape feature Classification of Giardia cyst (GC) and Cryptosporidium oocyst(CO) Giardia cyst and Cryptosporidium oocyst C = 2
Tr. = 2431(GC), 1586(CO)
Ts. = 100
Acc.(GC) = 91.8
Acc.(CO) = 99.6
Insufficient dataset More tests from food matrices need to be continued to validate & confirm HMI methods
[35] 2009 SVM Shape feature automated bacterial colony counting and classification Bacterial colony C = 2
T.I = 100
Acc = 96%
Pre. = 0.97
Rec. = 0.96
F1-Score = 0.96
Clustered colonies of bacteria’s are not distinguishes Model may improve for better classification
[36] 2010 ANN Shape feature Rapid detection of microorganisms Microorganisms C = 5
TI = 1
Acc. = 100% Small dataset
[37] 2010 GA-NN Shape feature GA-neural network approach for mycobacterium tuberculosis detection mycobacterium tuberculosis C = 2
T.I. = 960
Tr. = 400
Ts. = 280
Acc. = 89.64% In sufficient Evaluation Criteria Improving the performance of the bacteria colony classification
[38] 2011 K-NN, ANN Geometric features Identification and classification of cocci bacterial cells cocci bacterial cells C = 6
T.I = 350
Acc. = 99% Over lapped cells not considered in purposed model Improving the limitation of proposed model
[39] 2013 F-SDTS Shape feature Automated system for diagnosis intestinal parasites by Ascaris lumbri- coides (ALO),
Trichuris trichiura ova (TTO)
C = 2
T.I (ALO) = 100
T.I (TTO) = 100
Acc.(ALO) = 93%
Acc.(TTO) = 94%
limited to the basic diagnosis parasitic worms An enhanced model proposed to diagnosis parasite worms
[40] 2013 ANN,SVM Shape feature Classification of human intestinal parasites Human intestinal parasites C = 16
TI = 5763
Tr. = 2881
Te. = 2
Sn. = 90.38%
Sp. = 98.22%
Insufficient dataset Improve conventi onal slides impurities, by applying parasite- ological techniques
[42] 2016 SVM Shape feature Identification of Staphylococcus species Staphylococcus species C = 5 Acc. = 97% Insufficient dataset Size of dataset may be increased for validation
[41] 2015 ANN Shape feature Classification for detection malaria parasites Trophozoite, schizont, and gametocyte C = 3
T.I = 180
Acc. = 8708%
Sn. = 81.7%
Sp. = 90.8%
Insufficient dataset Increase
classification with more feature extraction methods
for identification
[44] 2018 neuro-fuzzy classifier Shape and texure feature Automated detection and classification of human intestinal parasites Human intestinal parasites C = 20
T.I = 1800
Tr. = 600
Ts. = 1200
Rec. R. = 100% Imbalance dataset Model may be improved to detect and classify different types of parasites
[43] 2018 ANN Shape feature Automated medical diagnosis system for intestinal parasitosis Intestinal parasites C = 15
T.I = 1800
Tr. = 900
Ts. = 900
C.R = 100% Insufficient dataset Model may be upgraded to obtain better result and classify other parasites too
[47] 2020 Randomly Wired Neural Network – Classification of falciparum parasite Falciparum parasite T.I = 27,558 Acc. = 95.08%
Pre. = 93.62%
Rec. = 96.44%
F1-Score = 95.05%
DL model significantly improve the working efficiency
DL Based Methods and Models
In recent years, high-stake applications have been implemented using deep learning methods and models for microscopic image diagnosis. An extensive literature review and study is carried out for the proposed topic of convolutional neural network techniques based on deep learning for detection and interpretation using clinical intestinal protozoa microscopic images. In this section, an overall reviewed summary of methods and models of related subjects is prepared.
DL Related Works in Proposed Field
Hung et al. [48] presented the task of detection of individual cells and their respective classes using Faster Region-based Convolutional Neural Network (Faster R-CNN). The proposed model contains two sub-module, as seen in Fig. 12. Sub-module first apply Faster R-CNN to detect individual cells from the image by generating a bounding box around cells like red blood cells or non-red blood cell and in submodule second AlexNet model was used for further classification of cells from images. The data collection contain 1300 images and after pre-processing these images contain 100,000 labelled cells. Experimental results predicted an accuracy of 98% for the proposed model.Fig. 12 Detail of how proposed two stage deep learning model for recognition and classification is applied to images during test phase. a An original image is fed into Faster R-CNN model to recognize objects and label them as RBC or other. b The labelled objects as other are sent to AlexNet model to undergo more fine-grained classification
M. Górriz et al. [49] used U-Net, a deep convolution neural network to classify and segment the Leishmaniosis Parasite, which causes thousands of deaths in some undeveloped countries annually, as shown in Fig. 13. The number of images used in this task includes 45 having size 1500 × 1300pixels captured with light microscopic with the magnification of ×50 to facilitate image analysis. Evaluation of F1-Score based on pixel-wise classification of classes Background, Cytoplasm, Nucleus, Promastigote, Adhered and Amastigote is 0.980, 0.896, 0.950, 0.491, 0.457, 0.777respectively. Jaccard Index (j) is used to automatic detection of class Promastigote, Adhered and Amastigote and their evaluation when j > 0.75 is 0.50, 0.12, 0.55 respectively.Fig. 13 Overview of the proposed model for detecting Leishmaniasis Parasites
Viet et al. [50] developed an automatic Parasite worm egg detection and classification model by applying the deep learning Faster R-CNN method in microscopy stool images. Faster R-CNN uses RPN (a fully CNN) network to generate proposal regions that simultaneously predicts object bounds and object scores at each position. RoI Pooling layer draw interests region along with convolutional features as input to generate the bounding box around objects. The experiment result shows that the Faster R-CNN model performs better with an accuracy 97.67%.
Yang et al. [51] worked on a model that recognized the parasites in microscopic images of blood smear. The author divided this model into two parts, first to detect the parasites entities Iterative Global Minimum Screening technique used and second, the authors used a customized Convolutional Neural Network to classify each entity from images of either parasites or background. For this model, the authors collected 1819 thick smear digital images from 150 patients. The proposed model gave an accuracy of 93.46% and an AUC of 98.39%.
Khoa Pho et. al [52] proposed a model based on transfer learning and data augmentation techniques to detect and identify the images of systs and oocysts of various species like Iodamoeba butschilii, Toxoplasma gondi, Giardia lamblia, Cyclospora cayetanensis, Balantidium coli, Sarcocystis, Cystoisospora belli and Acanthamoeba, which have round shapes in common and affect seriously to human and animal health. The proposed modedl RetinaNet automatically detect and identify the protozoa’s. Even though there were lack of data in the training data, the proposed model still achieves good accuracy.
Mathison et al. [53] used a deep convolution neural network for detection of intestinal protozoa in Trichrome-Stained stool specimens from scan digital microscopic images. Traditionally, the ova-and-parasite (O&P) inspection method is used to manually microscopic evaluation of stool. It is a resource and time-consuming method. The purpose of this research is to develop a novel CNN model along with scan high-resolution digital side images to recognize intestinal parasites from stool, as shown in Fig. 14. The whole task is divided into three parts. Part I, collect the digital scan microscopic images of intestinal protozoa containing target classes. Part II, input the collected microscopic images into CNN model for training so as to detect defined classes. Part III, perform the validation and prediction of the trained model. The author collected and prepared one hundred twenty-seven slides of 11 categories of protozoa to train the model. During the model development, various training steps were executed and analysis of model performance was evaluated with the resulting metrics. All images were resized to 250 by 250-pixel images, of which 10% of label images of all classes were used for validation of CNN after training. The proposed intestinal detection model architecture is RGB CNN based on the SSD Inception V2 transfer learning model. The based model pertained with COCO image dataset. The trained model was shown the collection of 250 by 250-pixel images scenes to recognize the parasites. The model created a label image box to detect the parasite. The precision recall plot were used to view the model performance on the basis of per labelled parasite image box. The slide-level agreement is used to calculate the accuracy of the model, the positive agreement achieved was 98% and the negative was 98.11%.Fig. 14 Workflow of training for CNN
Baek et al. [54] developed a model with Fast Regional Convolutional Network (Fast R-CNN) based on DL to quantify and classify five cyanobacteria. The proposed Fast R-CNN model includes two stages, in stage first classify cyanobacteria species taken from microscopic images using the fast R-CNN method and in step second CNN technique is used to quantify the cyanobacteria cells. The dataset collection covered 200 images of five species of cyanobacteria (Microcystiswesenbergii, Microcystis aeruginosa, Dolichospermum, Aphanizomenon and Oscillatoria). Experiment results show that the Fast R-CNN based model was able to achieve a reasonable accuracy for classification and yielding average precision (AP) values of 0.929, 0.973, 0.829, 0.890, and 0.890 for respective species.
Kang et al. [55] purposed an expensive deep learning network which utilized 1D CNN, Long-Short Term Memory Network (LSTM) and Deep Residual Network (ResNet). The proposed hybrid deep learning model define as Fusion-Net perform the classification of foodborne bacteria at a single-cell level. The Fusion-Net formation was performed in three parts comprising hyper parameter optimization, multiple deep learning architecture selections, and Fusion-Net construction. The dataset was prepared by collecting 5000 bacterial cells images of five foodborne bacterial cultures, of which 72% are used for training, 18% are used for validation and10% are used for the test dataset. Results show that the proposed model yields classification accuracy up to 98.4%.
Luo et al. [56] report a deep learning-based model for predicting Cryptosporidium and Giardia in drinking water. The proposed system merged imaging flow cytometry with MCellnet an efficient neural network. Figure 15 shows the architecture of MCellNet. The dataset collection included millions of raw images of which 80,146 images were selected for the final image database and each image from the database was patched to 120 × 120 pixels. 13 classes of Cryptosporidium (2082 images), Giardia (3569 images) were included in the dataset. The image data set is randomly split into a training data set (38,469 images), a validation data set (9618 images) and a test data set (32,059 images) that contained 48%, 12%, and 40% images respectively. The proposed model for multiclass and binary classifications achieves accuracies of 99.69% and 99.7%, respectively.Fig. 15 MCellNet architecture includes a convolutional layer, six inverted residual blocks, one flattened layer, and one fully connected layer. The input to MCellNet model is Cryptosporidium and Giardia images of 120 × 120 pixels, and the output is the probability of each class
Nakasi et al. [57] evaluate the performance of the AlexNet and GoogleNet model based on transfer learning for the diagnosis of scan digital intestinal parasites stool microscopic images. The authors compared these two models with trained Convolution Neural Network for the same work. Models are evaluated on the system having low specification which shows that models can be deployed to tackle real word diagnostics problems. A total of 6500 (10.9% positive) image patches were applied in AlexNet, 6461 image patches (11% positive) applied in GoogleNet and 2071 image patches (30.5% positive) applied in Custom CNN. From proposed models, the AlexNet attained accuracy ROC AUC of 1.00 and GoogleNet attained ROC AUC of 99.
Lee et al. [58] developed a Helminth Egg Analysis Platform (HEAP) that help medical technicians to diagnosis parasite infections. The authors integrated the various deep learning techniques (SSD, Single Shot MultiBox Detector, U-net, and Faster R-CNN, Faster Region-based Convolutional Neural Network) to recognize the helminth egg specimens as shown in Fig. 16. The proposed model also includes pixel level based methods image binning and egg-in-edge algorithm to improve performance. HEAP exhibit effective performance in counting and recognizing the helminth eggs from digital images.Fig. 16 Functionality of HEAP-assisted parasite egg investigation. In stage first, all the specimen preparation measures are applied. Then, an automatic microscope image system was used to digitalize the specimen slides. Multiple focusing planes were required to gather all the images. HEAP carried out the egg recognition and egg counting using cloud computing. Finally, medical expert verify the model prediction result using computer client on internet
Litjens et al. [59] investigated a deep convolution neural network to improve the efficiency and accuracy of cancer diagnosis in H and E images. This model is used to perform two different tasks, first prostate cancer recognition from biopsy samples, and second breast cancer recognition from sentinel lymph nodes. Pre-processing pipeline of the model consists of 4 convolution layers for features extraction, 3 max-pooling layers to reduce the dimensionality and a dense layer for classification. Dataset for prostate cancer includes 225 glass slides of which 100 are selected for training, 75 for testing and remaining for validation. Dataset collection for breast cancer sentinel lymph nodes for the experiment includes 271 slides of which 98 for training, 33 for validation and remaining for testing the model. Optimal percentiles were obtained using the validation set for both ROC curves and the highest specificity that was the median and 90th percentile for both.
Panicker et al. [60] work on end to end selective auto-encoder approach based on convolution neural network to recognize complex soybean cyst nematode eggs from microscopic images. The soybean cyst nematode eggs training patches were used to train the proposed convolutional neural network. The trained model was validated with validation images. Figure 17 depict the architecture of the proposed Convolution auto-encoder model. The dataset collection included 644 nematode microscopic images that were used to investigate soybean cyst nematode eggs. 80% of images were used to train the model and the rest of the images were used for validation. Experimental results predicted accuracy of 94.33% for the proposed model.Fig. 17 Convolutional auto-encoder architecture to recognize complex soybean cyst nematode eggs from microscopic images
Tahir et al. [61] develop a Convolution Neural Network based on deep learning for the detection and classification of five different types of fungus spores and dirt. Around 40,800 annotated RGB images of 6 classes were developed for fungus detection and classification. The model was trained on 30,000 fungus images and each class contain 5000 images. The test set comprises 10,800 fungus images with 800 images per class. The accuracy achieved by the purposed model is 94.8%.
Oomman et al. [62] developed an automatic approach based on deep convolution neural network for the detection of Tuberculosis bacilli from microscopic images. The proposed model was developed in two stages, stage first done image binarisation with Otsu threshold algorithm and in second stage classification of detected regions done using a convolutional neural network. The dataset collection included 120 images along with ground truth, each image in the dataset has 2816 × 2112 pixel resolution. For CNN training and testing the images were cropped to 900 negative patches and 900 positive patches. From the total of 1800 patches, 80% were used for training purposes and 20% used for testing. Experimental results show that the proposed model achieved a recall of 97.13%, a precision of 78.4% and an F-score of 86.76%.
Treebupachatsaku et al. [63] purposed a method based on deep learning for the detection of a genus of a bacterium from microscopic bacterial images using the Tensorflow framework. More than 800 sample images of S. aureus and L. delbruekii datasets were collected. Eighty percent of images from both datasets were applied to train the proposed model and the remaining images were used for testing. The proposed model achieved 96% of validation accuracy.
Pedraza et al. [64] worked on deep learning-based neural to check the diatom detection from water. The authors determined the diatom detection with two popular transfer learning techniques i.e. RCNNs (Region-based Convolutional Neural Networks), which applies convolution operation on candidate region and YOLO (You Only Look Once) which applies a neural network over the whole image. These two methods were trained on 11,000 microscopic images of diatom from 10 species. Diatom detection results of RCNN and YOLO are depicted in Fig. 18. The experimental result shows that the YOLO model performs better with 84% F-Measure than RCNN.Fig. 18 Detection results of the proposed model. Left column: a with false positive regions; Centre column: b with false negative regions; Right column c YOLO evaluation
Sajedi et al. [65] proposed a model to recognize bacterial species from solid culture plates. Two methods based on deep learning were applied to detect action bacterial strains. In the first method, a two-level wavelet transform was utilized on action bacterial strains images. In the second method, two operations are performed i.e. data augmentation for blurring, cropping, and horizontal rotation and classification using transfer learning technique ResNet. The dataset collection was prepared from UTMC.V1.DB and UTMC.V2.DB databases containing 703 images from 55 different classes and 1303 images from 97 different classes from respectively. The experimental result exhibits that the former method acquired an accuracy of 80.81% and 84.81% on both datasets. The secondary method acquired accuracy of 90.24% and 85.96% on both datasets.
Zhou et al.[66] implemented a model by applying a transfer learning approach based on a convolution neural network to automatic analyses diatom from digital whole-slide images. The proposed model applied the GoogLeNet Inception-V3 transfer learning technique for training to recognize the diatom, as shown in Fig. 19. The dataset collection comprised 53 digital whole-slide images of which 43 slides were selected for training and 10 slides for validation. Experimental results show that the transfer learning model using the augmented database achieved accuracy of 97.67% and AUC: 99.51%.Fig. 19 The CNN architecture implemented with the GoogLeNet Inception-V3 CNN
Qian et al. [67] demonstrated a novel multi-target deep learning framework developed with Faster R-CNN for algae detection and classification. The proposed extensive model was trained on a large-scale coloured microscopic algae dataset, as depicted in Fig. 20. The dataset collection was prepared with 1859 images of 37 algae as well as annotations of genera and classes. In this experiment, 80% of images of genera were collected in the training set to train the model and the remaining were collected for the testing set. The experimental result show that the successful identification rate achieved at genus level by the proposed model was 74.64% and at class level it was 81.1%Fig. 20 Model architecture depicts 3 branches simultaneously outputs the genus, bounding box, and a biological class of the algae and orange component extended classification branch. Branch-1 is used to predict the genus of algae. Branch-2 is used for algal detection and localization. Branch-3 is used to predict the class of algae
Salido et al. [68] focus on mitigating the Diatom detection for specimen counting and sample classification challenge with the YOYO and SegNet network based on deep learning. The dataset prepared collects microscopic images of 80 species of diatoms and each species contain hundreds of images. Detection of diatoms for faster diatom counting by using YOLO for on-time inferences with an average sensitivity of 84,6%, specificity of 96.2%, and precision of 72.7%.
Holmström et al.[69] focuses on deep learning methods for accurate and fast detection of helminths and Schistosoma haematobium. The author used 8,342,769 echocardiograph images of 276 patients. 80 images were used to train the model and the remaining were used for testing and validation of the model. Train model showed 97% accuracy without any over-fitting. The model achieved the same test accuracy on low-resolution images among 15 views. Evaluation represented using confusion matrices also detect similarities and classification based on relevant image features.
Peixinho et al. [70] proposed a deep learning-based approach ConvNet that recognize the image features effectively for human intestinal parasite images. Random kernels are defined for hyper-parameters optimization CNN architecture. For the experiments, the dataset contained 16,437 objects including the 15 most common species of human intestinal parasites. Using the proposed approach effective accuracy was obtained for the classification of human intestinal protozoa’s and eggs.
López et al. [71] implement a model based on CNN to detect the mycobacterium tuberculosis (MT). Dataset consist of 9770 positive and negative smears patches prepared from 492 digital images. Three types of patches (grey-scale, RGB, R-G) were used to train the proposed CNN based model. The proposed model includes three layers to perform the classification of patches into two classes i.e. positive or negative MT. The proposed model accomplished 96% accuracy level.
Zieliski et al. [72]developed a hybrid deep learning model for the classification of bacterial species from digital images. In the proposed model deep convolutional neural network is used to recognize image descriptors, subsequently features vectors are generated with the pooling encoder method and finally Support Vector Machine was used for classification. The dataset used in this model includes 33 bacteria species with 20 digital images of each bacterium. The proposed model used 50% data of the dataset for training purposes and 50% for testing. The results exhibit that the proposed DL based model is 96.82% accurate in the classification of bacterial species from digital images.
Wahid et al. [73] implement a model by using a transfer learning technique to automate the classification and recognition task using a deep convolution neural network. The proposed inspection DCNN model was trained using 500 digital microscopic images of five bacterial species. The dataset was split into the training (80% images) and testing (20% images) parts. The detection and classification rate of the proposed model is 85%
Ahmed et al. [74] Implemented a hybrid approach to classify microscopic bacterial images using the SVM and Inception-V3 model. In the proposed model image processing techniques like image cropping, converting images from grayscale to RGB, image flipping, image translation and feature extraction by Inception-V3 Deep CNN method were used. The SVM was used to classify the microscopic bacterial images into defined classes. The authors used 800 bacterial images to train the proposed model and 200 images for testing. Based on the proposed model 75% accuracy in the classification of bacterial species from digital images was achieved.
In [75] performed an experiment on datasets of In Situ plankton images using deep learning techniques. Proposed model extract features from various planktonic images datasets i.e. Imaging Flow Cytobot (IFCB), Scripps Plankton Camera System (SPC) and Situ Icthyoplankton imaging system (ISIIS). The authors train CNN model by using IFCB and ISIIS plankton images datasets. The dataset SPC was small in size and so it was used for testing purposes. To train the proposed CNN model images of plankton were resized to 256 by 256. Experimental results of the proposed model work well on the feature extraction from planktonic images using CNN.
In [76] determined the classes of microalgae using convolution neural network technique of deep learning. FlowCam practical analyser used to extract microalgae images from water extracted from South Atlantic Ocean. The dataset contained 29,449 microalgae images that are further classified into 19 classes. The data augmentation technique was used to increase the size of the dataset. From this dataset, 70% of images were used to train the model and 30% were used for validation. The proposed model obtained experimental results with 88.59% accuracy.
In [77] presented a deep learning-based approach to classify bacterial colonies. The authors used Deep Convolutional neural network (CNN) to obtain image descriptors and support vector machine (SVM) and Random forest for classification, as shown in Fig. 21. Features based on shapes namely spiral, cylindrical and spherical were extracted. The dataset consisted of 660 images with 33 different genera and species of bacteria. The experimental results predicted the accuracy of recognition to be 97.24%.Fig. 21 Flowchart of deep learning-based approach to classify bacterial colonies
Hay et al. [30] presented a convolutional neural network-based tool for differentiating bacteria images from non-bacterial images using three-dimensional microscopy data of gut bacteria found in larval Zebrafish. The authors used TensorFlow framework to implement 3D convolutional neural network and compared the performance of the model with support vector machine and random forest classifiers. The proposed model performed better with 89.3% accuracy whereas random forest classifier and support vector machine classifiers achieved accuracy of around 78.5% and 83.1% respectively.
In [78] developed a CNN based model using transfer learning approaches for automatic classification of parasites with low quality microscopic scanned images, as shown in Fig. 22. The patches based technique was used to search the location of eggs from images. The dataset collection contained ×10 magnification microscopic images of four different types of parasites i.e. Ascarislumbricoides (67 images), Hymenolepisdiminuta (27 images), Fasciolopsisbuski (32images) and Taeniaspp. (36 images). Before applying data augmentation and the patch overlapping, grayscale conversion and contrast enhancement are performed on the parasite egg image collection. The grayscale conversion operation decreases the depth of the input parasite image from three channels of RBG to one channel of grayscale. Further, the visualisation of low magnification of images is enhanced with contrast enhancement. Each parasitic image was split into small patches, which allowed the model to extract features from the image by examining the local areas. In order to encapsulate the mentioned parasites, patch size set to 100 × 100 pixels. The data augmentation technique was applied to increase the size of the dataset, approximately 10,000 patches per egg type. In order to implement the proposed framework, a transfer learning technique was employed with fine-tuning pretrained models. These models have been trained on large dataset of images collected from different specific applications. The last two layers of these models were replaced with a fully connected layer and a softmax layer to classify images into five classes. Grayscale conversion operation decreases the depth of the input parasite image from three channels of RBG to one channel of grayscale. Further, the visualisation of low magnification of images is enhanced with contrast enhancement. Each parasitic image was split into small patches, which allowed the model to extract features from the image by examining the local areas. In order to encapsulate the mentioned parasites, patch size set to 100 × 100 pixels. The data augmentation technique was applied to increase the size of the dataset, approximately 10,000 patches per egg type. In order to all implement the proposed framework, a transfer learning technique was employed with fine-tuning pertained models. These models have been trained on large dataset of images collected from different specific applications. The last two layers of these models were replaced with a fully connected layer and a softmax layer to classify images into five classes. For object detection, AlexNet is a cutting-edge model that improved CNN execution performance, whereas ResNet50 is a more sophisticated architecture that performs better for image classification tasks. The dataset of parasite egg images was split into two parts, part first contained 60% of the images for training purposes, and the second contained 40% of the images for testing purposes. Based on the proposed framework, experiment results represented state-of-the-art parasitic egg detection and classification task. Based on the proposed framework, experiment results represented state-of-the-art parasitic egg detection and classification.Fig. 22 Overview of the proposed architecture for training and testing CNN model. In stage first, model trained on the pre-processed collected specimen images. In stage second, testing is performed on trained model with test data set
Quinn et al. [27] authors purposed a framework based on Deep CNN to evaluate the performance with different microscopy tasks i.e. intestinal parasite eggs in stool samples, tuberculosis in sputum samples, and diagnosis of malaria in thick blood smears. The experts mark bounding boxes around each interested entity in all images. Finally, prepared, plasmodium was annotated (7245 entities in 1182 images) in thick blood smear images, tuberculosis bacilli were annotated (3734 entities in 928 images); in sputum samples, and, the eggs of hookworm, Taenia and Hymenolepsis nana were annotated (162 entities in 1217 images) in stool samples. The proposed model is trained on the collected images. After training the resulting model was applied to the test set: plasmodium detection set, which contains 261,345 test patches, tuberculosis set contain 315,142 test patches and hookworm set contains 253,503 patches. In all cases, experiment results show that accuracy was higher and better than traditional medical imaging techniques.
Butpoly et al. [75] proposed DL based method for classification of Ascaris lumbeicodes parasites images. The proposed model recognize three types of eggs of Ascaris lumbeicodes with effective approach of deep learning. The dataset collection included training and testing data. Both training and testing dataset included three types Ascaris lumbeicodes eggs namely infertile eggs, fertile eggs and decorticate eggs. For this experiment the training dataset consist of 200 of each type (total images 600). Experimental results predicted 93.33% classification accuracy of the parasites eggs.
Avic et al. [76] implemented methodology based on multi-class support vector machine for classification of human parasites eggs from digital microscopic images. The proposed model consists of four steps. These steps are pre-pre-processing feature extraction, classification and testing. In pre-processing step, the image processing methods, such as contrast enhancement, thresholding, noise reduction are applied. In second step i.e. feature extraction, the invariant moments of parasites images obtained in step first are evaluated. In classification step, the multi-class support vector machine was applied to classified feature collected in feature extraction step. The proposed model was tested with test data. The proposed approach achieved average accuracy of 97.70% for classification of human parasites.
Summary
In the past two decades, traditional deep learning methods for parasite detection and classification have been updated from time to time. Table 5 displays the related research works, including references, publication date, methods, objectives, species categories, data-details evaluation metrics, limitations, and future scope.Table 5 Summary of reviewed research works on deep learning methods and models as applied for detection and classifications used objective, dataset details which include class (C), total images (T.I), training (Tr.), validation (V), test (Ts.) and Evaluation metrics which include accuracy (Acc.), precision (Pre.), recall (Rec.), area under the ROC curve (AUC), mean average precision (mAP), sensitivity (Sn.) and specificity (Sp.)
References Date Types of features Method Objective Parasites (species) Dataset details Evaluation Limitations Future scope
[48] 2015 Deep features Faster R-CNN Object detection on malaria images jane Plasmodium vivax –- Acc. = 98% Validation of our model needs to be done Intend to test the model on more reliable ground truth and test for robustness by testing on samples prepared in a different lab
[70] 2016 Deep features CNN Diagnosis of human intestinal parasites Intestinal parasites C = 15
T.I = 16,437
Acc. = 0.9649 ± 0.0043 Clinical laboratory validation was not employed Intend to further extend the work to diagnosis of parasites in animals
[71] 2017 Deep features CNN Classification of Mycobacterium tuberculosis Mycobacterium tuberculosis C = 2
T.I = 9770
AUC = 96% Insufficient data The proposed model can be used in sliding for detecting the parasite in full smear microscopy images
[75] 2017 Deep features AlexNet Deep feature extraction for planktonic images Planktonic images T.I = 30,336(ISIIS),53,239 (IFCB) Qualitative Small set of classes Include more image data from plankton domains to improve classification accuracy
[60] 2018 Deep features CNN Automatic detection of Tuberculosis bacilli Tuberculosis bacilli C = 2
T.I = 1800 (900 + ve & 900 –ve patches)
Rec. = 97.13%
Pre. = 78.4%
F-score = 86.76%
Insufficient dataset An enhanced model proposed to diagnosis
tuberculosis bacilli
[49] 2018 Deep features U-net model Leishmaniasis parasite segmentation and classification g Promastigote
Adhered
Amastigote
C = 3
T.I = 45
Promastigote (J > 0.54)
Adhered(J > 0.82)
Amastigote(J > 0.88)
Imbalance dataset Results that could be improved using larger databases
[61] 2018 Deep features CNN Fungus detection Fungus species C = 5
T.I = 40,800
Tr. = 10,800
Ts. = 5000
Acc. = 94.8% Evaluation details are not described explore regional convolutional neural network and transfer learning for the fungus detection
[63] 2019 Deep features LeNet CNN Bacteria classification using DL S. aureus and L. delbruekii C = 2
T.I = 800
Acc. = 96% Small dataset limited to only two species of bacteria Apply another CNN methodology for comparison such as ResNET, AlexNET
[50] 2019 Deep features Faster R-CNN Parasite worm egg automatic detection Parasite species C = 8 mAP = 97.67% Less dataset details mentioned Advanced techniques
applied for
better results
[53] 2020 Deep features D-CNN Detection of intestinal protozoa Intestinal Protozoas (10 Catg.) T.I = 910 Rec. = 98% Clinical laboratory validation was not employed Collection of additional slides in order to enrich the data set and refine the model
[54] 2020 Deep features R-CNN Identification and enumeration of cyanobacteria species Cyanobacteria species C = 5 AP = 0.929, 0.973, 0.829, 0.890, and 0.890 for five classes Less dataset details mentioned Research recommended to improve the cell-count accuracy
[55] 2020 Deep features Fusion-Net Single-cell classification of foodborne pathogens Pathogens C = 5 Acc. = 98.4% Insufficient dataset Collection of images in order to enrich the data set and refine the model
[57] 2021 Deep features AlexNet & GoogleNet Intestinal parasite detection in Intestinal parasite – AlexNet AUC = 1.00
GoogleNet = 0.99
No details about quantity of database Transfer learning could be used to analyze the data further to understand why
[51] 2019 Deep features Faster-RCNN Parasite detection in thick blood smears based Parasites T.I = 2967 Detection rates on image and patient level = 96.84% & 96.81%, respectively Evaluation details
are not described
Focus on reducing false positives
[69] 2017 Detection of soil-transmitted helminths and Schistosoma haematobium Helminths and Schistosoma haematobium
[56] 2021 Deep features MCellNet
(CNN)
Deep learning-enabled predicting Cryptosporidium and Giardia in drinking water Cryptosporidium and Giardia C = 2
Tr. = 38,469
Ts. = 32,059
Val. = 9618
Acc. = 99.0%
Pre. = 98.66%
F1-Score = 99.09%
Insufficient dataset High-quality training data, MCellNet could be extended to detect other types of bioparticles in high speed
[58] 2021 Deep features Single Shot Detector (SSD), U-net and Faster R-CNN Helminth egg identification and quantification based on the integration of deep learning Helminth egg C = 17 Qualitative Evaluation details
are not described
Model improved by integrating increasing number of human validated samples
[78] 2021 Deep features AlexNet and ResNet50 Parasitic egg detection using transfer learning Ascaris lumbri -coides (AL), Hymenolepis diminuta (HD), Fasciolopsis buski (FB) and Taenia spp. (Tn) C = 4
T.I = (AL), 27 (HD), 32 (FB) and 36(Tn)
Acc. = 87.69 (AlexNet) &
90.77(ResNet50)
The poor-quality microscopic image with insufficient detail Enhance the model to learn more complex features of the parasite eggs
Discussion
We compiled traditional machine learning and deep learning-based methods for microscopic image classification and detection of various parasites in this paper. All the research studies discussed here show that both ML and DL methods and models are effectively used by researchers. Traditional machine learning methods and models include, as stated in the review, k-NN, SVM, ANN, GA-NN, and Neuro-fuzzy classifier. An overview of the processing flow of traditional machine learning detection and classification algorithms is shown in Fig. 23. In this review, we found that the most potential model of machine learning used for microscopic parasite image classification and detection is the Support Vector Machine. SVM is a supervised algorithm used for both linear and non-linear data. It defines the classification by constructing the set of hyperplanes in feature space [79]. In SVM, kernel functions are used to perform the transformation in the hyperplane. The most commonly used kernel functions are linear, polynomial, sigmoid, and radial basis functions. A better classification is achieved with the hyperplane maximum distance to the nearby training data point of classes [80]. However, this model is not effective for multiple species classification and detection. Fig. 23 Overview of a processing flow of traditional machine learning detection and classification algorithms
The deep learning methods and models surveyed in this paper are playing a major role in parasitological research. Furthermore, it supports tackling similar problems within several other subdomains. Deep learning models handle more complex tasks than traditional machine learning, such as object detection, image segmentation, image recognition, and classification. Figure 24 shows CNN-based transfer learning models used in parasite classification and detection. Popular classical deep learning models, such as CNN and its offspring methods and models, are constantly used in the task of parasite classification and detection, such as CNN mentioned in [60, 61, 70], AlexNet and GoogleNet mentioned in [57], AlexNet and ResNet50 mentioned in [78], Faster R-CNN mentioned in [50], and R-CNN mentioned in [54]. According to the survey on deep learning methods and models for parasites, the most popular detection and classification model is Faster R-CNN. In [50, 51] Faster R-CNN is mentioned. In comparison to R-CNN, Faster R-CNN implemented with the Regional Proposal Network (RPN) technique performs better because in Faster R-CNN, RPN improves the performance and accuracy of detection. Moreover, it also exhibits end-to-end detection [81]. The main limitations of Faster R-CNN are that it cannot detect objects in real time and that it performs large amounts of computations due to the RPN extraction method.Fig. 24 CNN based transfer learning models used in parasites classification and detection. The horizontal line in the middle shows time line. One-stage detection models are lie above the time line, and two-Stage detection models shown below the time line
Conclusion and Research Directions
In this systematic review, we demonstrated a significant investigation of parasites microscopic image detection and classification methods and models based on traditional machine learning and modern deep learning technologies. In Sect. 1, we discussed certain fundamentals to understand parasites along with diseases and diagnosis approaches, including motivation and research position. In Sect. 2, we outline the basic concepts of deep learning, which include CNN models for visual recognition. In Sect. 3, we have outlined the research progress of traditional and modern methods and models of parasite detection and classification in chronological order. In Sects. 4 and 5, we have organized various methods and models of traditional machine learning and deep learning, respectively. Finally, in Sect. 6, i.e., the discussion part, we analyse the two categories of methods and models and further present the performance of each method. After a detailed review on parasites detection and classification using deep learning, the experimental results show that deep learning is a better and more effortless approach than the traditional machine learning approach that employs hand-engineered features, which is a challenging and time-consuming task. Several deep learning methods and models have been extensively used for the detection and classification of parasite microscopic images. Some of the state-of-the-art techniques in the deep learning framework are CNN, F-RCNN, VGG-Net for detection and classification purposes. The native paper researchers hardly examined a few species of parasites due to the limited size of the data collection. The performance of methods and models falls short of expectations due to the scarcity of datasets. Deep learning methods and models achieve sophisticated development and produce better results than the traditional machine learning methods on various benchmarks. In spite of this, deep learning techniques are too immature in the field of visual recognition. Based on the analysis of deep learning techniques in Sect. 5, the authors found some major gaps, which are outlined as future directions for further enhancement for parasites detection and classification based on microscopic images. The summary of all CNN based methods and models along with their best scores and datasets is mentioned in Table 5. The AlexNet and Fast R-CNN models yield the best results for the detection and classification of parasites in digital images. They are followed by R-CNN, GoogleNet, LeNet, and U-Net models. Moreover, fine-tuning of concerned methods also outperforms whatever the network model may be. This approach provides a significant improvement in multiclass datasets.
The future development trends and challenges in deep learning are predicted on the basis of the development of parasites classification and detection methods and models. To detect and classify parasitic species in deep learning, the most promising development could be to combine existing transfer learning techniques. Due to the successful application of transfer learning-based models in computer vision, at present, many researchers are applying transfer learning to detect and classify objects from microscopic images. Combining transfer learning models with others can result in improved parasite detection and classification performance. In this domain, the most challenging task is real-time detection and classification. With the recent development in related methods and models, the performance of detection and classification is improving significantly. In deep learning, two parameters that run against experimental results and also act as a major challenge for parasites detection and classification are, complication in obtaining good quality parasite images data collection, and high processing costs, which affect generating good quality datasets.
Funding
No funds, Grants, or other support was received.
Declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
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| 0 | PMC9734923 | NO-CC CODE | 2022-12-14 23:28:31 | no | Arch Comput Methods Eng. 2022 Dec 3;:1-27 | utf-8 | Arch Comput Methods Eng | 2,022 | 10.1007/s11831-022-09858-w | oa_other |
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Eur J Pediatr
Eur J Pediatr
European Journal of Pediatrics
0340-6199
1432-1076
Springer Berlin Heidelberg Berlin/Heidelberg
36484863
4748
10.1007/s00431-022-04748-6
Research
Cardiac MRI in midterm follow-up of MISC: a multicenter study
http://orcid.org/0000-0002-2538-8238
Benvenuto Simone [email protected]
1
Simonini Gabriele 2
Della Paolera Sara 3
Abu Rumeileh Sarah 4
Mastrolia Maria Vincenza 2
Manerba Alessandra 5
Chicco Daniela 3
Belgrano Manuel 6
Caiffa Thomas 3
Cattalini Marco 7
Taddio Andrea 13
1 grid.5133.4 0000 0001 1941 4308 University of Trieste, Via dell’Istria 65/1, Trieste, Italy
2 grid.8404.8 0000 0004 1757 2304 NEUROFARBA Department, Rheumatology Unit, Anna Meyer Children’s Hospital, University of Florence, Florence, Italy
3 grid.418712.9 0000 0004 1760 7415 Institute for Maternal and Child Health, IRCCS “Burlo Garofolo”, Trieste, Italy
4 grid.8404.8 0000 0004 1757 2304 Rheumatology Unit, Meyer Children’s Hospital, University of Florence, Florence, Italy
5 grid.412725.7 Pediatric Cardiology, ASST Spedali Civili Di Brescia, Brescia, Italy
6 grid.5133.4 0000 0001 1941 4308 Department of Radiology, Azienda Sanitaria Universitaria Giuliano Isontina and University of Trieste, Trieste, Italy
7 grid.7637.5 0000000417571846 Pediatric Clinic, University of Brescia, ASST Spedali Civili Di Brescia, Brescia, Italy
Communicated by Peter de Winter
9 12 2022
110
22 7 2022
25 10 2022
30 11 2022
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In this multicenter retrospective study we aimed to evaluate the outcome of cardiac involvement in children affected by multisystem inflammatory syndrome (MIS-C), assessed through cardiac magnetic resonance (CMR). Children referring to three Italian tertiary pediatric centers between February 2020 and November 2021 with a diagnosis of MIS-C, who underwent CMR during a follow-up visit, were enrolled. Demographic, clinical, laboratory, treatment, and outcome data were collected. Twenty MIS-C patients (aged 9–17, median 12 years) were included in the study. Heart involvement at onset was testified by hypotension/shock (55%), laboratory evidence of myocardial involvement (100%), reduced LV ejection fraction (EF) on echocardiography (83%), and/or need for inotrope agents (40%); they all presented good clinical, laboratory, and echocardiographic response to treatment. CMR was performed after a median interval of 3 months from discharge. Pericardial effusion and myocardial edema were found in 5% of patients. Mild residual left ventricular (LV) dysfunction was found in 20% of patients, all showing normal echocardiographic LVEF at discharge. Minimal myocardial scars were found in 25% by late gadolinium enhancement (LGE). One patient was evaluated at two consecutive time points, showing partial resolution of a myocardial scar after 7 months from its first finding.
Conclusion: Despite the severity of heart involvement in the acute MIS-C phase, the mid-term cardiac outcome is good. Direct cardiac tissue viral invasion may be involved in MIS-C pathogenesis. What is Known:
• Heart involvement is common in MIS-C, but conflicting findings have been shown regarding cardiac outcome when assessed through cardiac MRI.
What is New:
• Midterm cardiac MRI shows mild abnormalities in patients recovered from MIS-C with any grade of severity of cardiac involvement at presentation.
Keywords
COVID-19
MIS-C
Cardiac MRI
Myocarditis
Outcome
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pmcBackground
Since its appearance in late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection showed a milder disease course in children when compared to adults [1]. However, children may develop a hyperinflammatory response to SARS-CoV-2 infection, called multisystem inflammatory syndrome (MIS-C) [2]. Heart involvement is common in MIS-C: myocarditis, ventricular dysfunction, valvular regurgitation, and pericardial effusion are more frequently reported than coronary artery abnormalities (CAA) [3]. Despite the severity of clinical manifestations at onset, an excellent cardiac outcome has been reported when evaluated through echocardiography at a 3-month follow-up [4]. However, conflicting findings concerning cardiac outcome have been shown when performing CMR in the acute phase of MIS-C [4–8]. Moreover, exhaustive data on cardiac recovery are lacking, so that cardiac follow-up recommendations for patients with MIS-C are still uncertain, being mostly derived from those applied for Kawasaki disease (KD) and viral myocarditis in the pre-COVID era [9, 10].
In this multicenter study, we aimed to evaluate the outcome of cardiac involvement in patients affected by MIS-C, assessed through CMR.
Methods
Study design and population
In this multicenter retrospective study, all MIS-C patients referring to three Italian tertiary pediatric centers (Institute for Maternal and Child Health, IRCCS “Burlo Garofolo”, Trieste; ASST Spedali Civili, Brescia; Meyer Children’s University Hospital, Florence) from February 1, 2020, to November 31, 2021 were enrolled. For the purpose of this study, only patients who underwent CMR, prescribed by the treating physician as standard of care, during follow-up visits were taken into account. Demographic, clinical, laboratory, treatment, and outcome data were collected in an anonymized database. Diagnosis of MIS-C was based on the WHO case definition [11].
CMR protocol and image analysis
Cardiac MRI was performed on 1.5-Tesla magnetic resonance scanners (Philips Intera®, Philips Ingenia®) with a cardiac phased-array receiver surface coil, ECG-gating, and breath-hold technique, using a dedicated cardiac software. The three centers presented similar protocols. Cine images in two-, three-, and four-chamber views and a stack of contiguous short-axis slices from the atrioventricular plane to the apex were acquired using balanced steady-state free precession (bSSFP) pulse sequence. T2-weighted short tau inversion recovery (STIR) or turbo spin echo (TSE) with fat suppression pulse sequences were acquired with the same slice coverage as cine images. Approximately 10 min after intravenous administration of 0.1 mmol/kg gadolinium-based contrast agent, late gadolinium enhancement (LGE) images were acquired using segmented T1-weighted inversion-recovery prepared gradient-echo or phase sensitive inversion recovery (PSIR) pulse sequences, individually adjusting inversion time to optimize nulling of apparently normal myocardium. Pre- and post-contrast T1-mapping was conducted with a MOLLI sequence in three short axis slices (basal, midventricular and apical). T2 mapping was conducted with a GRASE sequence in the same short axis slices. Studies were evaluated by a radiologist and/or a cardiologist with specific expertise in cardiac MRI at each center.
LV and RV volumes and function were measured using the standard volumetric technique from the cine short axis stack, with the endocardial border traced at end-diastole and end-systole for each slice and the epicardial border traced at end-diastole [12]. Volume and mass measures were indexed to body surface area. On T2-weighted images, edema was considered present when a signal hyperintensity was observed in two orthogonal planes and/or the ratio of signal intensity between the myocardium and the mean signal intensity of the skeletal muscle was ≥ 2 [13, 14]. Presence of LGE was defined by the presence of areas with increased signal intensity following administration of contrast medium in two orthogonal planes. Global T1 and T2 values were obtained by averaging all segmental T1 and T2 values, respectively.
Data analysis
Categorical variables were reported as absolute numbers and percentages. Continuous variables were expressed as means and standard deviations (SD) or as median and inter-quartile ranges (IQR), if not normally distributed.
Results
Population characteristics
Twenty children with a previous diagnosis of MIS-C had been evaluated with a cardiac MRI during their follow-up and were therefore included in the study. Data regarding their demographic characteristics, evidence of previous SARS-CoV-2 infection, and baseline symptoms at hospital admission for MIS-C, as well as laboratory markers, echocardiographic findings, treatment, and time of stay, are shown in Table 1.Table 1 Patient characteristics and clinical data
ID Age (years) Sex Ethnicity Positive Serology for SARS-CoV-2 or previous PCR or exposure Symptoms Blood count abnormalities CRP (mg/L) hs-TnI or hs-TnT (× ULN) NT-proBNP (× ULN) Echocardiographic abnormalities Treatment PICU admission (days) Time of hospitalization (days)
1 15 M Caucasian PCR Fever, oral mucositis – 75 hs-TnT ×142 – Myopericarditis NSAIDs, colchicine – 9
2 11 M Caucasian IgG, PCR, exposure Fever, rash, conjunctivitis, vomiting, diarrhea, hypotension Anemia 126 hs-TnI ×4 ×12 LVEF 45–55%, mild mitral regurgitation IVIG, MTP, inotropes 3 19
3 12 M Caucasian IgG, PCR Fever, conjunctivitis, vomiting, diarrhea Anemia, lymphopenia 75 Normal ×5 Normal IVIG, MTP – 17
4 17 M Caucasian IgG, PCR Fever, vomiting, diarrhea, hypotension, hepatosplenomegaly Lymphopenia 154 hs-TnI ×2 – LVEF 35–45%, CA aneurysm, pericardial effusion IVIG, MTP, ASA – 21
5 9 M Asian IgG, IgM Fever, rash, conjunctivitis, dyspnea Lymphopenia, thrombocytopenia 300 hs-TnT ×7 ×12 LVEF <35% IVIG, MTP (pulses), anakinra, inotropes, heparin 16 30
6 12 M Caucasian IgG, exposure Fever, rash, conjunctivitis, vomiting, diarrhea, hypotension, hepatomegaly Anemia, thrombocytopenia – hs-TnI ×30 ×11 LVEF 50%, CA dilation IVIG, MTP, anakinra, heparin 5 46
7 11 M Caucasian IgG, IgM Fever, conjunctivitis, vomiting, diarrhea, dyspnea – 150 hs-TnT ×6 ×4 Pericardial effusion IVIG, MTP (pulses), heparin 6 19
8 14 F Caucasian IgG, IgM, exposure Fever, vomiting, diarrhea, headache, dyspnea Lymphopenia 291 hs-TnT ×16 ×110 – IVIG, MTP (pulses), anakinra, inotropes, heparin - 26
9 14 M Caucasian - Fever, headache, lymphadenopathy, hypotension Neutrophilia 339 hs-TnT ×23 – LVEF 35–45%, mild mitral regurgitation IVIG, inotropes 6 15
10 10 F Caucasian IgG, IgM, PCR Fever, rash, conjunctivitis, vomiting, diarrhea, hypotension Anemia, lymphopenia, thrombocytopenia 231 hs-TnT ×2 ×36 LVEF 45–55% IVIG, MTP, inotropes 9 28
11 12 M African IgM, PCR, exposure Fever, vomiting, diarrhea, headache, dyspnea, cardiac arrest Lymphopenia, neutrophilia 31.5 – ×43 LVEF <35% IVIG, MTP, Anakinra, inotropes, heparin 16 31
12 15 M Caucasian Exposure Fever, vomiting, diarrhea Lymphopenia 197 – ×2.5 – IVIG, MTP, heparin – 9
13 9 F Middle Eastern IgG, IgM, exposure Fever, rash, conjunctivitis, dyspnea, hypotension Lymphopenia 136 – ×7 LVEF 45–55% IVIG, MTP, heparin 15 20
14 11 M Caucasian IgG, PCR Fever, cheilitis, conjunctivitis, vomiting, diarrhea, headache, hypotension Lymphopenia, thrombocytopenia 226 TnI ×13 ×6 LVEF 50% IVIG, MTP, ASA – 10
15 12 M Middle Eastern IgG, exposure Fever, rash, cheilitis, conjunctivitis, hypotension – 167 TnT ×28 – LVEF 45–55%, mild mitral and tricuspid regurgitation IVIG, MTP, ASA – 12
16 12 M Caucasian IgG Fever, rash, cheilitis, conjunctivitis, vomiting Lymphopenia 84 TnI ×209 ×35 LVEF 45–55%, pericardial effusion, mild mitral regurgitation IVIG, MTP, ASA – 8
17 11 F Caucasian IgM, exposure Fever, oral mucositis, lymphadenopathy, diarrhea, headache, dyspnea, hypotension, arthralgia Lymphopenia 114 TnT ×24 ×190 LVEF <35%, CA aneurysms, moderate mitral and tricuspid regurgitation IVIG, MTP, ASA, inotropes, heparin 7 19
18 12 F Caucasian PCR Fever, rash, diarrhea, oliguria Neutrophilia 243 TnI ×6 ×115 LVEF 48% IVIG, MTP, ASA – 11
19 17 M Caucasian IgG Fever, rash, oral mucositis, conjunctivitis, lymphadenopathy Thombocytopenia 141 TnI ×7 ×3 Normal IVIG, MTP, ASA – 10
20 15 M Caucasian IgG, IgM, exposure Fever, diarrhea, headache, cough, myositis Lymphopenia 340 TnT ×118 Normal LVEF 35–45% IVIG, MTP, anakinra, remdesevir, inotropes, heparin 8 29
PCR Polymerase Chain Reaction, CRP C-Reactive Protein, TnT Troponin T, hs-TnI High-Sensitivity Troponin I, ULN Upper Limit of Normal, NT-proBNP N-Terminal Prohormone of Brain Natriuretic Peptide, PICU Pediatric Intensive Care Unit, LVEF Left Ventricular Ejection Fraction, CA Coronary Artery, NSAIDs Non-Steroidal Anti-Inflammatory Drugs, IVIG Intravenous Immune Globulins, MTP Methylprednisolone, ASA Acetylsalicylic Acid
Most of the children were male (15/20, 75%) and Caucasian (16/20, 80%), with an age ranging from 9 to 17 years (median 12, IQR 11–14). Evidence of previous SARS-CoV-2 infection was based on detectable IgG and/or IgM antibodies in 16/20 children (80%), and a positive nasopharyngeal swab assessed by RT-PCR in 11/20 (55%); for two patients with negative serology and no reported positive RT-PCR, diagnosis of MIS-C was based on a recent contact with a subject with COVID-19 patient and on typical clinical presentation (with fever, myocarditis, shock, markedly elevated inflammatory markers, and no microbial cause) respectively.
All the patients presented with fever on admission. Gastrointestinal involvement (vomiting, diarrhea, abdominal pain) was present in 14/20 patients (70%); conjunctivitis, rash, and cheilitis/oral mucositis were present in 11/20 (55%), 9/20 (45%), and 6/20 (30%) patients respectively; dyspnea and/or cough in 7/20 (35%); and headache in 6/20 (30%). Remarkably, 11/20 patients (55%) presented with hypotension and/or shock. Six patients (30%) received oxygen support, with 2 of them requiring non-invasive ventilation (NIV); one patient needed mechanical ventilation (MV) and was the only one in our cohort to experience a cardiac arrest.
Markers of inflammation were markedly increased in all of our patients, with a median value of CRP of 152 mg/L (IQR 109–234). Laboratory evidence of myocardial involvement was found in all patients as well, either as elevated high-sensitivity troponin-T (hs-TnT, median 338 pg/mL, IQR 197–708), high-sensitivity troponin-I (hs-TnI, median 135 pg/mL, IQR 84–322), or NT-proBNP (median 5158 pg/mL, IQR 2110–28,941).
Echocardiography was performed in 18/20 patients (90%) on admission, resulting normal in two patients only (11%). Remarkably, reduced LVEF was found in 15/18 patients (83%), mostly with a mild (9/15; 60%) or moderate (3/15; 20%) depression; severely reduced LVEF was observed in the remaining 3 patients (20%, 15% of the entire cohort). Valvular regurgitation and pericardial effusion were found in 5/18 (28%) and 3/18 (17%) patients, respectively. Three patients (17%) experienced CA abnormalities, one with ectasia of the left anterior descending CA and two with aneurysms (left circumflex and left main CAs, respectively).
Apart from patient 1, who was treated with non-steroidal anti-inflammatory drugs (NSAIDs) and colchicine, all the other patients (19/20, 95%) received intravenous immune globulins (IVIG, 2 g/kg), combined with intravenous methylprednisolone in 18/20 (90%), either with a 1–2-mg/kg/day dosing regimen (10/18, 56%) or with 30-mg/kg pulses (8/18, 44%). Low-dose aspirin was started in 7/20 cases (35%). Eight (40%) patients required inotrope agents (such as adrenalin, dopamine, milrinone) and five (25%) biological therapy (anakinra) to control the disease. Ten patients (50%) were admitted to pediatric intensive care unit (PICU), either because requiring inotropes or non-invasive or mechanical ventilation, for a median time of 7.5 days (IQR 6–13.5), while the median total time of hospitalization was 19 days (IQR 11–26).
All the patients showed a good response to treatment and were discharged free of symptoms and with normal (9/20 patients, 45%) or markedly reduced (11/20 patients, 55%) levels of CRP, troponin, and NT-proBNP. Echocardiography was performed at discharge in most of our patients (19/20, 95%), with normal findings in most of them (15/19, 79%). Patients 15 and 16 (10%) showed residual mildly depressed LVEF, although improved compared to the ultrasound (US) at disease onset, and mild mitral regurgitation. Patient 16 showed residual pericardial effusion as well. Signs of residual myopericarditis were found in patients 1 and 9. No CA abnormalities were found.
Cardiac MRI
Apart from patient 1 who was studied 10 days after MIS-C onset, all of the patients received cardiac MRI with an interval of at least 1 month, with a median of 3 months (IQR 2–6) and a maximum of 9 months. Cardiac MRI was performed at two consecutive time points in patient 20, at 2 and 9 months respectively. Data regarding cardiac volumetric, functional and tissue characteristics are shown in Table 2.Table 2 Cardiac MRI results at follow-up
ID Time at follow up (months) LV EF (%) RV EF (%) LV EDVI (ml/m2) RV EDVI (ml/m2) LV CO (L/min/m2) RV CO (L/min/m2) T1 mapping T2 mapping T2W LGE Pericardial effusion
1 0.3 48 48 81 72 – – – – Normal Lateral subepicardial, mid-wall inferoseptal No
2 1 50 53 105 115 4.1 4 Normal Normal – No No
3 1 58 53 Normal Normal Normal Normal Normal Normal – No No
4 1 66 47 98 103 – – – – Normal No No
5 2 69 67 56 63 4 4.4 Normal Normal – Inferoseptal and lateral mid-wall No
6 2 61 55 93 95 4.6 4.2 Normal Normal – Anteroseptal and inferolateral mid-wall No
7 2 62 60 74 81 3.7 3.9 Normal Normal – No No
8 2 57 54 Normal Normal Normal Normal Normal Prolonged – No No
9 2 Normal Normal Normal Normal – – – – Normal No No
10 3 54 62 68 60 2.8 2.9 Normal Normal – No No
11 3 50 43 88 104 3.5 3.5 Normal Normal – No Thin layer
12 3 61 56 74 80 – – Normal Normal – No No
13 4 43 47 112 96 4.1 3.8 Prolonged Normal – No No
14 5 65 58 86 97 – – Prolonged Normal – Inferolateral subepicardial No
15 6 64 51 69 86 – – – – Normal No No
16 6.5 62 57 108 113 - - Normal Normal – No No
17 7 Normal Normal Normal Normal – – – – Normal No No
18 8 65 62 67 72 – – Prolonged Normal – No No
19 9 57 47 94 113 – – Normal Normal – No No
20 2 64 62 83 87 3.1 3.2 Normal Normal – Lateral subepicardial No
20 9 63 58 80 83 3.3 3.1 Normal Normal – Lateral subepicardial (reduced) No
LV Left Ventricle, RV Right Ventricle, EF Ejection Fraction, EDVI End-Diastolic Volume Index, CO Cardiac Output, LGE Late Gadolinium Enhancement
Sixteen patients (80%) had normal biventricular volumes and function. Mildly reduced LVEF was found in all of the remaining 4/20 (20%): patient 1, with the shortest follow up and signs of myopericarditis on discharge, and patients 2, 11, and 13 who all showed normal LVEF on echocardiography at discharge. Notably, patient 13 was also the only with increased indexed left ventricular size (LVEDVI 112 ml/m2). Prolonged T1 time as a sign of either persisting myocardial edema or fibrosis was found in 3/20 cases (15%), who were studied with an interval ranging from 4 (patient 13) to 8 months (patient 17). Prolonged T2 time as a more specific sign of myocardial edema was found in patient 8 only (1/20, 5%), who was studied with an interval of 2 months. A thin layer of pericardial effusion was revealed in patient 11 only (5%). Minimal late gadolinium enhancement (Fig. 1) was shown in 5/20 participants (25%), with patient 20 presenting it at a maximum 9-month interval after MIS-C onset, although reduced in entity compared to his previous MRI evaluation performed after 2 months; apart from patient 1, all of the remaining patients showing LGE (no. 5, 6, 14, and 20) had normal echocardiography at discharge.Fig. 1 CMR imaging in a patient with previous MIS-C, showing subepicardial/intramyocardial LGE in the basal inferolateral wall of the left ventricle (red arrows). CMR, cardiac magnetic resonance; MIS-C, multisystem inflammatory syndrome in children; LGE, late gadolinium enhancement
Discussion
This is a multicenter study to evaluate cardiac involvement evolution of MIS-C patients through cardiac MRI.
Heart involvement is common in MIS-C, and the most frequent clinical manifestations are ventricular dysfunction, valvular regurgitation, arrhythmias, pericardial effusion, and CAA. In a study including 503 patients with MIS-C evaluated through echocardiography, depressed LVEF was found in 34%, being severely depressed in 22% of them, while CA aneurysm, mostly mild (93%), were found in 13% [3]. In another study including 286 MIS-C cases who underwent echocardiography, 42% had mitral regurgitation and 28% showed pericardial effusion [4]. Adequate supportive therapy and immune-modulatory treatment lead to complete resolution within days to weeks with low mortality rates [15]. Cardiac outcomes evaluated through echocardiography at a 3-month follow-up are excellent, with normalized LVEF and CA aneurysm resolution in nearly all patients [3, 4].
However, conflicting findings concerning cardiac outcome have been shown when performing CMR in the acute phase of MIS-C (i.e., within 1 month from onset). While a small case series [5] reported no myocardial damage, myocardial edema was demonstrated in all of the four patients from another case series [6]. In another study [7], myocardial edema was found in half of the 20 reported children, depressed LVEF in 35%, and a subendocardial scar in one patient. In another cohort including 17 children [8], 35% showed LGE, 12% pericardial effusion, and only one (6%) myocardial edema. Finally, in the large cohort studied by Valverde et al. [4], cardiac MRI was performed in 42 children showing myocardial edema in one-third, pericardial effusion in 24%, and LGE in 14%.
Remarkably, in our cohort, all the patients presented a severe acute disease and suffered from acute cardiac involvement, with an 83% prevalence of depressed LVEF (being severely reduced in 20%) which is at least two times higher than reported frequency in non-selected MIS-C patients [3]. CA abnormalities, valvular regurgitation, and pericardial effusion frequencies in our cohort were instead in line with existing literature [3, 4]. More than half of them presented with hypotension and/or shock, similarly to larger studied cohorts [4]; a nonfatal cardiac arrest was observed as well. LV systolic dysfunction was still present in 10% at discharge, comparably to other reports [16]. In fact, our data, although limited to a few cases, are to consider representative of children with any grade of severity of cardiac involvement from MIS-C.
The interval occurred between MIS-C onset, and cardiac MRI in our cohort was variable, as a result of the multicenter design and the retrospective protocol of our study, with patient 1, in particular, being evaluated in the acute phase of the MIS-C episode. The findings in this patient of a mildly depressed LVEF and of LGE are not therefore surprising when considering other cohorts evaluated in the acute phase [4–8], with a considerable prevalence of myocardial edema, depressed LVEF, pericardial effusion, and LGE as an expression of a recent cardiac involvement, as mentioned above.
A few other studies have evaluated MIS-C cardiac involvement evolution through cardiac MRI at a midterm timepoint. In the case series by Tannoury et al. [17], cardiac MRI was performed in two MIS-C patients 3.5 and 1.5 months after recovery respectively, showing mild myocardial scarring as evident by LGE in the latter. In contrast, in the retrospective study by Bartoszek et al. [18], 19 patients with evidence of previous MIS-C cardiac involvement were studied through cardiac MRI 3 months after recovery, showing no signs of LGE nor depressed LVEF, but pericardial effusion in 16% and myocardial edema as assessed through T2 signal intensity ratio (though with normal T1 and T2 mapping values) in only 1 patient (5%). In their prospective controlled study, Webster et al. [19] did not find depressed LVEF or myocardial edema in any of 6 MIS-C patients at a median of 2 months from the acute phase, although elevated troponin had been found in only two of their MIS-C participants and only two had showed reduced LVEF on echocardiography during initial admission. Moreover, they did not evaluate LGE as no gadolinium contrast agent was administered. Finally, Barris et al. [20] reported of 9 MIS-C patients with cardiac involvement in the acute phase, as testified by either elevated troponin or reduced LVEF, who underwent cardiac MRI after a median 9.4-month interval, with no evidence of depressed LVEF or LGE but a considerable prevalence (44%) of myocardial edema. Of note, the latter was assessed through T2 signal intensity ratio and not through T1 and T2 mapping, which can overcome some of its limitations [21].
In contrast to all of these studies, we found a 20% prevalence of mildly reduced LVEF, at a maximum interval of 4 months after MIS-C onset. Persisting mild LV dysfunction at a 4–9-month interval, although infrequent, has been described in a pediatric MIS-C cohort evaluated through echocardiography [22]. However, the clinical relevance of this finding remains unclear considering that all of our patients with reduced LVEF when assessed through cardiac MRI had normal echocardiography at discharge. Notably, the two techniques are not directly comparable when assessing cardiac volumes and function, since cardiac MRI allows a three-dimensional measurement while echocardiography relies on a summation-of-disks approach (Simpson’s biplane rule). It would therefore be interesting to compare cardiac MRI and echocardiography data obtained at the same time for each patient, data that unfortunately were not available in our cohort. Such a comparison would be of great help in MIS-C patients when questioning if the differences we observed between the two techniques actually rely on an MRI overinterpretation, an ongoing pathological process leading to scarring and fibrosis (although all but one of the patients presenting LGE in our cohort had normal LVEF on cardiac MRI), or a more precise measurement through cardiac MRI as observed in patients affected by other disorders [23].
The MRI protocol in our study included T2 mapping, through which we found a 5% prevalence of myocardial edema, as a sign of ongoing myocarditis persisting up to 2 months after the acute phase. Moreover, we found a 5% prevalence of persisting minimal pericardial effusion at 3 months after the onset. These results confirm the findings by Bartoszek et al. [18].
Finally, in contrast to all of the previous observations, we observed LGE as an expression of persisting scars in 25% of our patients, although minimal in the entity. MIS-C is considered the result of an abnormal immune response to SARS-CoV-2 where cardiac involvement could recognize its pathophysiology in postinfectious myocarditis, similarly to Kawasaki-related myocarditis [24], which usually occurs without residual myocardial fibrosis [25]. Nevertheless, myocardial scars are typical findings in either viral or immune-mediated myocarditis [26]. In particular, in a prospective study including 18 adolescents with acute myocarditis in the “pre-COVID era,” cardiac MRI performed after 6–9 months revealed a 44% prevalence of persisting scars [27]. Given the post-mortem findings showing virus particles in the cardiac tissue of patients died for MIS-C [28], a direct viral invasion could be hypothesized as the cause of damage in MIS-C. Remarkably, the long-term risk of a major adverse cardiac event such as ventricular arrhythmias or sudden cardiac death in patients with myocarditis is more than doubled in presence of persistent scars, even though their extent should be considered when assessing this risk [29]. We are not able to assess such a risk in our cohort, and, more importantly, to predict the evolution of myocardial scars in MIS-C patients. Of note, the one patient (no. 20) in our cohort receiving two consecutive cardiac MRI evaluations showed a reduction of LGE entity after 7 months from its first finding.
In conclusion, our data suggest that despite the severity of heart involvement in the acute MIS-C phase, the cardiac outcome is good. Larger longitudinal studies are needed on MIS-C patients in order to confirm this positive evolution and to establish the effective need and duration for physical activity restrictions or specific cardioprotective treatment [30].
Our study has four main limitations. Firstly is the small sample size, which carries a risk of selection bias, although attenuated by the multicenter design of our study; secondly, the variable time interval between acute MIS-C and cardiac MRI scan; thirdly, the heterogeneity of the radiologists who analyzed cardiac MRI results, without any double or triple check to evaluate inter-reader variability; and finally, the lack of a control group, which could help to avoid MRI findings overinterpretation [31].
Authors’ contributions
All the authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Simone Benvenuto, Sara Della Paolera, Sara Abu Rumeileh, Thomas Caiffa, Marco Cattalini, and Andrea Taddio. The first draft of the manuscript was written by Simone Benvenuto, and all the authors commented on previous versions of the manuscript. All the authors read and approved the final manuscript.
Funding
Funded by Italian Ministry of Health, RC 12/20.
Availability of data and materials
The datasets generated and/or analyzed during the current study are not publicly available due to individual privacy reasons.
Declarations
Ethics approval
Obtained by the Institutional Review Board of the Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste, Italy (RC 12/20).
Consent to participate and consent for publication
Retrospective study.
Competing interests
The authors declare no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Bex Alix 1
http://orcid.org/0000-0002-9182-5846
Mathon Bertrand [email protected]
2345
1 grid.413914.a 0000 0004 0645 1582 Department of Neurosurgery, CHR Citadelle, Liege, Belgium
2 grid.411439.a 0000 0001 2150 9058 Department of Neurosurgery, Sorbonne University, APHP, La Pitié-Salpêtrière Hospital, 47–83, Boulevard de L’Hôpital, 75651 Cedex 13 Paris, France
3 grid.425274.2 0000 0004 0620 5939 ICM, INSERM U 1127, CNRS UMR 7225, UMRS, Paris Brain Institute, Sorbonne University, 1127 Paris, France
4 grid.50550.35 0000 0001 2175 4109 GRC 23, Brain Machine Interface, APHP, Sorbonne University, Paris, France
5 grid.462844.8 0000 0001 2308 1657 GRC 33, Robotics and Surgical Innovation, APHP, Sorbonne University, Paris, France
6 12 2022
2023
46 1 5© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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Stereotactic brain biopsy is one of the most frequently performed brain surgeries. This review aimed to expose the latest cutting-edge and updated technologies and innovations available to neurosurgeons to safely perform stereotactic brain biopsy by minimizing the risks of complications and ensuring that the procedure is successful, leading to a histological diagnosis. We also examined methods for improving preoperative, intraoperative, and postoperative workflows. We performed a comprehensive state-of-the-art literature review. Intraoperative histology, fluorescence, and imaging techniques appear as smart tools to improve the diagnostic yield of biopsy. Constant innovations such as optical methods and augmented reality are also being made to increase patient safety. Robotics and integrated imaging techniques provide an enhanced intraoperative workflow. Patients’ management algorithms based on early discharge after biopsy optimize the patient’s personal experience and make the most efficient possible use of the available hospital resources. Many new trends are emerging, constantly improving patient care and safety, as well as surgical workflow. A parameter that must be considered is the cost-effectiveness of these devices and the possibility of using them on a daily basis. The decision to implement a new instrument in the surgical workflow should also be dependent on the number of procedures per year, the existing stereotactic equipment, and the experience of each center. Research on patients’ postbiopsy management is another mandatory approach to enhance the safety profile of stereotactic brain biopsy and patient satisfaction, as well as to reduce healthcare costs.
Keywords
Neurosurgery
Stereotactic brain biopsy
Robotics
Brain tumor
Brain surgery
Diagnostic yield
Safety
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pmcIntroduction
Brain biopsy is one of the most frequently performed brain surgeries in neurosurgical centers that manage patients with brain tumors or non-neoplastic cryptogenic neurological diseases [11]. Various surgical methodologies can be employed to achieve a brain biopsy [32]. Among these, stereotactic brain biopsy is a minimally invasive neurosurgical technique used to acquire pathological brain tissue using a dedicated stereotactic needle. This procedure is indicated for multiple, deep-seated brain lesions and/or frail patients or those with poor prognosis. The goal of surgery is to obtain viable tissue representative of the lesion in order to provide a comprehensive histological analysis. The procedure uses imaging technologies, such as magnetic resonance imaging (MRI) or computed tomography (CT), to safely and precisely reach specific areas of the brain. Image-guided brain biopsy began with frame-based approaches incorporating CT scans for surgical planning [66]. For the past several years, frameless stereotactic systems using preoperative MRI have tended to supplant frame-based methods. The standard-of-care method for stereotactic brain needle biopsy involves the insertion of a 1.6- to 2-mm diameter needle cannula through a burr hole placed along a predetermined trajectory. The two cannulas had side windows that aligned when the target point was reached. The brain tissue was lodged into the cannula using suction and then cut by sliding the inner cannula up into the mandrel.
Complications following a brain biopsy are rare, but like all neurosurgical procedures, they carry some risks, such as seizures, brain edema, or infection [52]. The most specific and frequent complications related to this procedure are negative sampling, requiring a second biopsy procedure [8], and brain hemorrhage with potentially serious consequences [53]. In a mission to become safer and more effective, constant innovations are being made in this field of neurosurgery.
This literature review aims to expose the latest cutting-edge and updated technologies and innovations available to neurosurgeons to safely perform stereotactic brain biopsy by minimizing the risks of complications and ensuring that the procedure is successful, leading to a histological diagnosis. We also examined methods for improving preoperative, intraoperative, and postoperative workflows.
Innovations to increase biopsy diagnostic yield
One of the main risks of stereotactic biopsy is to provide a sample that is non-contributory to a diagnosis. In a case series of patients with brain tumors, the rate of negative biopsies is close to 5%, exposing the patient to a second biopsy with potential morbidity and additional health care costs [8, 20, 53]. In patients biopsied for cryptogenic neurological disease, this rate reaches 30% [3, 36–38]. Innovations are partly driven by the causes of biopsy failures, from misguidance of the biopsy needle due to technical pitfalls and limitations [69] to uncertainties surrounding the pathological nature of the biopsy samples during the procedure (Fig. 1).Fig. 1 Advances and innovations in stereotactic brain biopsy diagnostic yield improvement. 5-ALA, 5-aminolevulinic acid; CT, computed tomography; MRI, magnetic resonance imaging. Figure created with BioRender.com
Intraoperative histopathological examination
Smear or frozen section
Intraoperative rapid smear or frozen-section histopathology is the oldest, but also the most reliable method to determine the presence of tumor or pathological tissue in biopsy specimens [10]. In 2019, Mathon et al. conducted a 2-year retrospective study on 145 patients for which a smear was performed during MRI-guided frame-based stereotactic biopsies [35]. They compared the negative biopsy rate between a historical cohort of 1638 patients brain-biopsied over a 10-year period (2007–2016) and the group of patients for which an intraoperative smear was performed. In the historical control group, the rate of negative biopsies was 2.6%, while there was no negative biopsy in the “smear group.” In five patients (3.4%), the first intraoperative smear was initially considered non-diagnostic; thus, further biopsies were performed deeper along the trajectory. The second smear resulted in a diagnosis in all patients. Another study reported that an intraoperative smear reduced the risk of negative biopsy from 11.1 to 3.7% [31].
Compared to frozen sections, the smear method has numerous advantages. It is faster and uses smaller amounts of tissue, allowing more tissue to be spared for definitive histopathological examination and molecular analysis. Moreover, contrary to frozen sections, the smear allows examination of the thin glial or neuronal cytoplasmic processes and identification of the glial or neuronal phenotype of tumor cells, or the presence of reactive astrocytes or a fibrillary background. Sharp nuclear details were also more visible in smears.
The intraoperative smear takes only a few minutes and does not unduly prolong the biopsy procedure [35]. However, the neuropathology laboratory must be located close to the operative room to receive the intraoperative sample without delay. The neuropathologist could also be in the operating room (OR) with a microscope because this gives the most reliable and instantaneous feedback to the operating surgeon [13]. Skilled and experienced neuropathologists should examine intraoperative smears to ensure a high level of reliability. This technique could thus be implemented in the surgical workflow to limit non-contributory biopsies and ultimately a second intervention.
Raman spectroscopy
Recently, stimulated Raman scattering microscopy, a label-free optical imaging method, was developed to quickly generate in the OR digital hematoxylin-and-eosin-stained-like images for intraoperative near real-time histopathological tissue analysis. Using this new tool, Neidert et al. analyzed 429 stimulated Raman histology (SRH) samples from 108 patients and evaluated the use of this technology in the surgical workflow. This device can be used for intraoperative diagnosis, research, and quality control. During the first experiments, they had to improve process optimization regarding the tissue treatment; nevertheless, it was easily implemented in the surgical workflow in a “plug-and-play” manner [44]. In a second study, the same team quantified the neuropathological interpretability in a routine clinical setting without specialized training [61]. They tested the device on 117 samples of pathological tissue from 73 patients and a neuropathologist assessed image quality by scoring subjective tumor infiltration and stated a diagnosis based on the SRH images. The SRH imaging quality was high, and the detection of tumor cells classified as inconclusive was observed only in 4.2% of the cases. The diagnostic accuracy of SRH images was 87.7%.
In a multicenter prospective clinical trial including 278 patients, Hollon et al. combined SRH and artificial intelligence (i.e., deep convolutional neural networks trained on over 2.5 million SRH images) and showed that this diagnostic method was non-inferior to pathologist-based interpretation of conventional histological images (accuracy 94.6%) [21]. Using the same artificial intelligence process, Reinecke et al. demonstrated that SRH can reliably detect the microscopic presence of tumor and discriminate from non-neoplastic brain tissue in stereotactic biopsy specimens [49].
In conclusion, the interpretation of intraoperative histological images with SRH is rapid (within a few minutes) and independent of a traditional laboratory or an unevenly distributed pathology workforce. Hence, this new tool may pave the way for intraoperatively confirming the positivity of a biopsy sample.
Intraoperative fluorescence
In the neurosurgical field, tumor delimitation based on 5-aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PpIX) or fluorescein sodium fluorescence is frequently used. Patients receive 5-ALA (20 mg/kg of body weight) approximately 4 h prior to the biopsy procedure. Administration of 5-ALA to the patient leads to the accumulation of red fluorescent PpIX in highly proliferating cells, such as tumor cells. As PpIX is only produced by vital cells, necrotic parts of the tumor do not show PpIX fluorescence. This is a useful tool for tumor delineation in resection surgery and for verifying tissue specimens during stereotactic biopsy sampling [67]. Millesi et al. compared the diagnostic yield from stereotactic brain tumor biopsies with the assistance of 5-ALA-induced fluorescence and those with the assistance of intraoperative histology [40]. The diagnostic rate was comparable between both strategies (98% vs. 100%, respectively). In addition, a positive predictive value of 100% was reported by the same team for all samples with strong or vague fluorescence-containing diagnostic lymphoma tissue according to histopathological examination [25].
Singh et al. studied the use of intravenous fluorescein sodium fluorescence to confirm pathological tissue samples in brain biopsies of gadolinium-enhancing tumors [57]. Their prospective observational study included 23 consecutive patients from whom 93 specimens were obtained and examined for the presence of fluorescence using a microscope with this visualization capability. They calculated the sensitivity and specificity of fluorescein detection based on histopathological confirmation. Overall, of the 93 specimens obtained, 58 were fluorescent samples, and all contained diagnostic tissue useful for tumor grading. Of the 35 non-fluorescent samples remaining, 12 (34.3%) did not contain any tumoral tissue, 11 (31.4%) contained minor hypercellularity or gliosis, and 12 (34.3%) contained a high proportion of necrotic tumor tissue. They concluded that the sensitivity and specificity of fluorescein fluorescence were 83% and 100%, respectively. This could be a useful and cost-effective tool to improve diagnostic accuracy by detecting pathological tissue in stereotactic brain biopsies and accelerating the procedure.
In a paper that was published in 2022, Xu and his team described their experience with 45 fluorescein-guided biopsies in 44 patients over a 5-year period and identified the distribution patterns in various histological diagnoses to create strategies to improve the effectiveness and precision of this procedure [68]. They carried out 25 frame-based and 20 frameless Varioguide (BrainLAB AG, Feldkirchen, Germany) image-guided biopsies. The intraoperative fluorescein uptake of 347 biopsy samples, with an average of eight samples per patient, was assessed, and the results were compared to the definitive histology. Sixty-three percent of the specimens obtained were fluorescein-positive. The specificity was 70%, and the sensitivity for high-grade gliomas was 85%. The specificity of fluorescein for contrast-enhancing lesions was 84%. Three samples were required to identify contrast-enhancing lesions, and five samples were required to provide a definitive histological diagnosis. Even though there was no indication of gadolinium enhancement, it is interesting to note that in the IDH-mutant WHO grade III group, astrocytomas showed fluorescein uptake. According to this patient series, fluorescein-guided stereotactic biopsy improves the chances of a successful neuropathological diagnosis and can reduce the number of samples required by half for contrast-enhancing lesions.
These two previous studies are the largest and most recent, but fluorescence has already been investigated by Thien et al. a few years ago on a smaller cohort with similar results [62]. Additionally and more recently, Thien et al. developed a low-cost and stand-alone device called Fluoropen to detect fluorescence in brain tumor tissue obtained by fluorescence-guided stereotactic needle biopsy [63]. The pen consisted of a light source fitted with color filters to create the required emission and visualization wavelengths. The proof-of-concept study consisted of four consecutive patients; a total of six samples were obtained, and each sample was examined for the presence of fluorescence using Fluoropen and compared with a microscope. Fluoropen was shown to have 100% concordance with the microscope and therefore could be a valid alternative to facilitate and expedite the procedure.
In conclusion, the literature supports the value of photodiagnosis and its high diagnostic yield, especially for high-grade tumors [50]. Although, its value seems more important in resection operations, fluorescence assistance during stereotactic biopsy of contrast-enhancing tumors may provide real-time confirmation of tumor tissue, increase the diagnostic yield, spare tissue samples, and reduce the time of intervention [7]. It represents a credible alternative for neurosurgical departments that have not undergone intraoperative histopathological examination by a neuropathologist.
Intraoperative imaging techniques
Both frame-based and frameless stereotactic biopsies are dependent on preoperative images and intraoperative anatomic registration to reach the target after careful planification and precalculated measurements in 3-dimensional space [66]. The limitation of these techniques is correlated to their relative inability to adapt to the shift of intracranial structures, to the anatomy, or to assure accuracy through real-time imaging and sampling on the target.
To overcome these limitations, Mohyeldin et al. developed a platform to integrate high Tesla intraoperative MRI (iMRI) with percutaneous frameless stereotactic biopsy [41]. Before that, the advantage of real-time feedback using iMRI technology in phantom experience [43, 55], non-human primate studies [51], and deep brain stimulation surgeries [30, 56, 59] has been investigated. The use of their platform was performed on five consecutive patients and showed that it would considerably lower the rate of misdiagnosis due to faulty targeting using real-time feedback, correction of the needle trajectory, confirmation of accurate position, and direct imaging of eventual complications [42]. This technology is best suited for small deep brain lesions found near important neurovascular structures. As the system works percutaneously, it can also be used for targets that may require an anterior starting point, such as the subfrontal approach to the hairline. The average operating time was approximately 2 h and tended to decrease with increasing experience [41].
Using frameless stereotactic brain biopsy with intraoperative CT (iCT), Ikeda et al. studied the use of this adjuvant technique to assess the real target registration error and reported their preliminary experience on 10 patients [23]. During the procedure the iCT was conducted twice: once immediately before the biopsy with the 3-pin head holder and reference frame in place for self-registration of the navigation system and a second time for the precise confirmation of the localization of the inserted biopsy needle [23]. It provides a more reliable and accurate registration tool avoiding registration errors, especially in a prone or lateral position. One of the shortcomings of this technique is the double radiation exposure in one surgery, but it can be aided by the use of a low-dose-irradiated iCT. A similar surgical workflow using intraoperative verification with a mobile CT unit in combination with frameless neuronavigation-guided stereotaxy and preoperative MRI-based trajectory planning confirmed targeting accuracy with minimal radial trajectory deviation [5].
Novel biopsy techniques and needles
Recently, Ogiwara et al. reported a preliminary study on 26 patients of a novel biopsy method called “boring biopsy” [45]. The technique is based on a biopsy needle with a cylindrical tool able to gather columnar continuous specimens from the surface in the normal brain tissue to the tumor margin and within the lesion. They believe that continuous specimens are useful for improving the accuracy of histopathological diagnosis based on cellular changes and differentiation from normal tissues to the core of the lesion. Diagnosis was established in all cases, and no major complications were reported.
In an experimental on fresh swine brains, Trojanowski et al. compared the diagnostic histopathological quality obtained with different vacuum pressures (from 0 to 60 kPa), a novel needle rotation method, and using two needle types (Laitinen, Umea, Sweden, or Nashold, Radionics, USA) [64]. After analyzing 800 biopsy samples, they concluded that those are better for histopathological examination when obtained with higher vacuum pressure or with Laitinen needle.
Innovations to improve patient’s safety
The most serious consequences of minimally invasive stereotactic biopsy are vessel damage and subsequent bleeding. The rate of postbiopsy symptomatic hemorrhage is reported to be between 0.9 and 8.6% [26, 53]. When considering all bleeding observed on systematic postoperative CT scans (symptomatic or asymptomatic), the range is much higher, up to 60% [27, 52].
The smooth and rounded tip of the biopsy needle protects the vessels by pushing them aside. Although the forward movement of the needle represents a risk of hemorrhage along the trajectory, the risk of vessel injury is higher with the suction and sliding movement of the biopsy needle during tissue acquisition. Therefore, more than a preoperative examination for navigation at an anatomical level, neurosurgeons need intraoperative feedback to improve the safety of biopsy sampling. Different techniques have been developed to enhance the safety of this critical step of the procedure (Fig. 2).Fig. 2 Advances and innovations in safety of patients undergoing stereotactic brain biopsy. OCT, optical coherence tomography. Figure created with BioRender.com and Freepik.com
Optical methods
Intravascular contrast detection
Göbel et al. conducted a clinical pilot trial on a minimally invasive endoscopic probe that can be inserted into the tissue through a regular biopsy needle [16]. The same fiber optics is used for both illumination and image detection enabling a clear demarcation of healthy tissue, tumorous tissue, and vasculature based on tissue autofluorescence, PpIX fluorescence, and indocyanine green (ICG) fluorescence. For vasculature, a dose of 200 mg/kg body weight ICG was administered intravenously immediately before starting the experiment, which allowed the surgeon to detect blood vessels at distances below 1 mm, which would be sufficient to change the propulsion path. ICG is frequently used in open vascular neurosurgery, but the detection of deep vessels might be altered due to the fast redistribution and possible leakage of blood that, if in contact with the probe, would result in false-positive measurements.
Similarly, in a study published in 2021, Richter et al. used a forward-looking probe to get direct feedback on PpIX fluorescence and blood flow detection on 20 stereotactic biopsies [54]. With this tool, they expect to shorten the time for the procedure, improve the diagnostic yield, and reduce the risk of bleeding complications.
Laser Doppler flowmetry
A 2.2-mm diameter forward-viewing probe that uses fluorescence detection in conjunction with laser Doppler flowmetry was described in two studies. The probe was designed to fit a Leksell stereotactic system. Laser Doppler flowmetry can assess brain perfusion and blood flow by measuring the frequency shift in the 780-nm backscattered laser light caused by cell movements in the capillaries [1].
Haj-Hosseini et al. developed a forward-looking fiber optic probe integrating real-time fluorescence spectral detection and laser Doppler spectroscopy with the goal of reducing the risk of artery injury and securely targeting tumor tissue during stereotactic brain biopsy procedures [19]. They described the use of the dual-mode probe in three stereotactic biopsy procedures. They measured PpIX fluorescence, autofluorescence, microvascular blood flow, and total light intensity along the trajectories in real-time in the OR. The signals were correlated with the radiology images and histopathology. The main goal of the studies was to establish whether there was a correlation between the measured blood flow and the anatomy along the trajectory, but it also showed that the system provided a clinically feasible method to increase the operational safety and efficiency.
These tools can aid in determining the optimal strategy for biopsy samples and patient safety by using real-time intraoperative information.
Optical coherence tomography
Optical coherence tomography (OCT) was initially presented by Kut et al. as a label-free technique for differentiating pathological and non-pathological human brain tissues at 1- to 1.5-mm penetration depth [28]. Later on, Ramakonar et al. demonstrated that OCT can accurately identify solid tissue and vessels in live patients with only minimal disruption to the current clinical workflow [48]. In 11 patients, they were able to intraoperatively detect blood vessels (diameter > 500 μm) with a sensitivity of 91.2% and a specificity of 97.7%. The only limitation of the device is that it is a side-viewing probe that performs imaging through the tissue-cutting window, so it does not prevent intracranial hemorrhage during needle penetration. Although the rate of hemorrhage is significantly reduced when there is no suction, indicating that bleeding occurs during tissue cutting, this does not completely eliminate the risk of hemorrhage.
Markwardt et al. conducted a study on ex vivo tissue using dual-wavelength remission spectrometry with a two-fiber probe to detect ≥ 100–500-μm diameter vessels at a maximal distance of 800 μm within the suction window [34]. Similarly, Pichette et al. conducted a sensitivity analysis to establish intrinsic vessel detection limits of interstitial optical tomography using brain tissue phantoms. They showed that they could detect vessels with diameters of > 300 μm located up to > 2 mm from the outer surface of the biopsy needle, corresponding to the volume of tissue aspirated during tissue extraction. The only limitation they pointed out was that when the surgeon had a high absorbance signal, they could not distinguish a single blood vessel from a dense cluster of small capillaries [46].
Augmented reality
The use of augmented reality is expanding at an exponential rate each year, and it is most likely to be used in numerous fields of neurosurgery in the future. In a neurosurgical OR, the surgeon needs to have 3D vision and precise knowledge of the anatomy to go beyond anatomical borders through small surgical corridors to avoid injuring important neural and vascular structures. The use of a virtual access pathway, which can then be superimposed to guide surgery, might be a useful tool for avoiding potential problems before starting the procedure.
Very recently, Gibby et al. conducted a study to quantify the navigational accuracy of an advanced augmented reality device combining the VisAR system with Hololens 2 (Microsoft), a technology that converts DICOM data into holographic images [15]. With the help of this device, the surgeon has a virtual line of sight from which to design his route safely. More research is necessary for this new use of augmented reality, it could provide the surgeon with a significant advantage by eliminating the need to cognitively transform 2D data into a surgical field and enable safer target planning for stereotactic biopsies.
Measurement of aspiration pressure in cannula biopsy
Considering that excessive vacuum aspiration during stereotactic biopsy increases the risk of hemorrhage, Chan et al. assessed the optimal aspiration vacuum pressure for application in brain tumor biopsies and correlated this data with ultrasound elastography [9]. They recorded vacuum aspiration pressures using a T-connector pressure sensor during 11 biopsies. According to previous results provided by a preclinical study [64], they found that a vacuum pressure range of 40–66 kPa is safe and adequate for sampling various types of tumors with heterogeneous elastographic properties. Ultrasonographic elastography is an affordable tool that can indicate the minimum vacuum pressure required to achieve stereotactic brain biopsy in real time.
Innovations to improve perioperative workflow
Several tools have recently been developed to improve operative workflow. The purpose of these technologies is to shorten surgeries, simplify the flow of actions, and improve the comfort of both the patients and workers. Most of the technologies described below have been developed in recent years, and this sector is constantly growing to assist surgeons in achieving their objectives.
Imaging techniques
Various imaging systems integrated into the surgical workflow can increase the efficiency and comfort of the patient and surgeon. Preoperative preparation for planning a frame-based stereotactic brain biopsy is associated with important logistical effort and burden on the patient. Recently, Enders et al. developed and applied a new method for intraoperative acquisition in the planning dataset using a multiaxial robotic C-arc system called Artis Zeego ((AZ) Siemens) [12]. Fourteen patients with an indication-customized dose-reduced protocol underwent intraoperative imaging with AZ. The control group consisted of 10 patients who underwent conventional preoperative cranial computed tomography imaging. They compared the outcomes with regard to target deviation, diagnostic value of the biopsies, complications, and procedure time. A suitable intraoperative planning dataset was acquired using AZ. The total procedure time was significantly shorter, and biopsy was contributory for 12 patients (86%) in the AZ. Only 8 patients were diagnosed in the control group. There were no significant differences in target size, trajectory, or target deviation. They concluded that intraoperative imaging using AZ in frame-based stereotactic biopsy is an easy and feasible method with an accuracy comparable to that of conventional CT, with reduced radiation exposure. This system can significantly reduce the procedure length and undeniably improve the comfort of the patient and staff.
In contrast, in a retrospective study of 33 patients, Algin et al. investigated the safety and feasibility of CT and 3-T MR-guided freehand biopsy with 18/20-gauge coaxial needles in a single imaging unit [2]. The procedure was conducted under sedation and local anesthesia in their radiology department. They concluded that this technique was safe and feasible and that the biopsy workflow was simplified. This tool could be a valuable alternative for stereotaxic biopsies in centers that do not have stereotaxic equipment or experience.
In 2022, Sterk et al. reported the initial safety data and user experience of SmartFrame array (ClearPoint Neuro) on ten stereotactic procedures [60]. The SmartFrame array system is a MRI compatible frame placed on the skull with four 19-mm bone screws. After the placement of the frame, the next step of the procedure is optimization of the stereotactic trajectory based on real-time MRI. The goal of the frame was to support multitrajectory biopsies without additional adjustments. The accuracy of the frame is good because the radial error of the system is < 2 mm, and they achieved diagnostic tissue for all subcentimeter lesions biopsied. The safety profile revealed no procedural morbidity or mortality. This series suggested an average time of 80 min for a single-trajectory procedure. One advantage of real-time MRI biopsy is that there is no ionizing radiation and the same imaging technique is used for treatment planning and intra- and postbiopsy control.
Robotics
For nearly two decades, robotics has profoundly modified the neurosurgical landscape, particularly for stereotactic procedures. In recent years, major advances in robotics have been made in terms of steric hindrance and ease of use.
Mallereau et al. conducted a 12-year long, prospective, single center study to compare two frameless systems for brain biopsies: ROSA (Zimmer Biomet) Robotic-Assisted Stereotaxy and BrainLab Varioguide (BrainLab) image-guided stereotaxy [33]. They analyzed various parameters such as diagnosis, periprocedural complication, length of the procedure, and learning curve for each operator. They performed 526 biopsies on 516 consecutive patients, 314 with the ROSA robot, and 212 with the Varioguide. They found that a positive histological diagnosis was achieved in 97.4% of cases in the ROSA group versus 93.3% in the Varioguide group. However, no statistically significant differences were found in the percentage of postoperative complications and length of the procedure. For example, the hemorrhagic complication rate was 3.5% in the ROSA group and 4.7% in the Varioguide group. This study confirms that robotic surgery is safe, accurate, and reliable. A limitation of this study was that they compared two frameless robotic and image-guided surgery systems to prove the efficiency and safety of robotic surgery without a frame-based control group. In another study, Hu et al. compared the SINO (Sinovation Medical Technology Co., Ltd., Beijing, China) surgical robot-assisted frameless brain biopsy with standard frame-based stereotactic biopsy in terms of efficacy, accuracy, and complications [22]. Although there was no significant difference in diagnostic yield and postbiopsy complications between the frame-based group and the SINO robot-assisted group, the entry and target point errors were smaller in the robot-assisted group.
Based on the same idea as in the previous study, Spyrantis et al. proposed an experimental phantom study to compare the mechanical accuracy of the ROSA robot and the Leksell stereotactic frame [58]. Fifty trajectories were analyzed for each method. For both procedures, X-rays were used to precisely record the final cannula position; then, the coordinates were merged with the planning data, and the deviations were calculated. After analysis, similar to a previous study, they concluded that both methods proved to be very precise, but they recorded a higher degree of accuracy in robotic procedures.
The literature highlights the advantages of the robotized technique over the standard stereotactic technique. Robots have accurate, predefined, and reprogrammable trajectories. It minimizes the error that could be made by the surgeon in the various steps of manual settings or fixation and reduces inaccuracies due to the stereotactic frame or frameless surface-matching registration. It also allows repetition of the same trajectory numerous times with the same precision, without tremor or tiredness. However, despite numerous studies proving the higher accuracy of stereotactic robots compared to frame-based or frameless procedures, the positive clinical impact of robotics on diagnostic yield and safety appears negligible.
YAG lasers
A new tool has recently been described by Ha et al. using laser technology to make brain biopsy less invasive, faster, and safer [18]. In this “proof of principle” study, they used the yttrium aluminum garnet (YAG) laser as a high precision bone cutting technology that would perform a miniaturize necessary burr hole and also allow for a trajectory angulation much more tangential to the bone surface. The laser was used on a navigated multiaxial robotic arm and performs a “cold ablation” with a pulse energy of 650 mJ and pulse duration of 200 μs. Laser technology can be used to cut with high precision and low thermal strain to adjacent tissues when compared to mechanical bone drilling. The transmitted energy is nearly exclusively absorbed by the water molecules in the surrounding tissue. Potential future applications of this technology would be to miniaturize the hole in the skull bone to such an extent that the laser-created canal could serve as a guide for the biopsy needle with sufficient accuracy. In addition, the necessary skin incision can either be created by the laser itself or be much shorter when using a conventional scalpel. This technological advancement could provide neurosurgeons with the opportunity to sample biopsies of brain areas that are usually inaccessible or too hazardous.
Combined biopsy needle
Giannakou et al. studied phantoms using a new frameless MRI-guided robotic system that has the advantage that, with a single catheter insertion, the biopsy needle can perform both tissue suction and ablation of the lesion using high-intensity therapeutic ultrasound in cases of localized malignant tumors [14]. This new tool is useful for diagnosis, and if a tumor is proven malignant, its size allows it to ablate the lesion in a single surgery. It would reduce the surgical morbidity of multiple surgeries and possibly the hospitalization time.
Advances to improve postbiopsy workflow and patient’s management
We showed above that technological innovation is the cornerstone of stereotactic brain biopsy. Nevertheless, research on patients’ postbiopsy management is another fundamental way to optimize patient safety and personal experience and to make the most efficient possible use of the available hospital resources.
Early postbiopsy imaging
As little consensus exists on the postoperative care of patients undergoing stereotactic biopsy, several teams have sought to establish novel algorithms for their postoperative management and notably investigated the location of postbiopsy imaging. Recently, Riche et al. retrospectively examined 1500 consecutive cases to analyze the severity, timeline, risks factors, and management of complications after stereotactic brain biopsies [53]. The team proposed an algorithm for a better and safer postoperative management of stereotactic biopsy based on the results of the study and their experience. They pointed out that half of the symptomatic complications occurred within the first hour and three-quarters of complications occurred within the first 2 h following the biopsy. Consequently, they recommend close monitoring for 2 h in the recovery unit or the intensive care unit (ICU) and systematic CT scan after 2 h. The few existing studies on this topic also tended toward a short postbiopsy observation time to spot a complication or not in the patient [24, 29, 65]. ICU monitoring is continued for patients with a postbiopsy new neurological deficit. They also showed that more than 80% of delayed complications (i.e., after 2 h) occurred after 48 h and were mainly related to brain edema and seizures, which might have been prevented if cases were considered in the group of patients at risk using their algorithm. Indeed, the authors highlighted the strong value of a CT scan 2 h after the procedure. Thus, asymptomatic hemorrhage visible on CT scan was associated with delayed complications, and they recommended prescriptions of corticosteroids and antiepileptic medications to prevent brain edema and/or seizures.
Outpatient biopsy
The concept of outpatient management for stereotactic brain biopsies was introduced in the 2000s in North America [4, 24]. Early studies investigated the feasibility of outpatient care. This practice for patient management has become increasingly popular because it improves patient satisfaction and, ultimately, reduces costs and has been developed by several teams in the USA [6, 47], before reaching the British healthcare system [17].
More recently, another European team refined the outpatient stereotactic brain biopsy protocol by taking into account the location and findings of the systematic early postbiopsy CT scan. As discussed above [39], following the outpatient care management provided for 40 patients who underwent stereotactic brain biopsy, the authors indicated that all of the patients were discharged the same day and no patients had to be readmitted for complications in the month after the procedure. To safely perform ambulatory stereotactic brain biopsies, the latter suggested management recommendations and a prebiopsy checklist. The patient’s willingness, the distance between the hospital and the patient’s house, an overnight caregiver, and early morning surgery were some of the elements on the checklist. Other medical comorbidities, poor neurological state, uncontrolled seizures, and age > 80 years were excluded.
For selected cases, this is a promising adaptation to improve patient care; it can be easily implemented in other neurosurgical centers without lowering the level of care or endangering patient safety. A shorter hospital stay limits the risk of hospital-based complications, such as thromboembolic events and nosocomial infections, in addition to the well-known psychological benefits of the patient and family. This is particularly true during the COVID-19 pandemic, when patients are exposed to hospital clusters and, consequently, nosocomial contamination. However, the neurosurgical community should remember that early discharge should not be the primary aim, but rather the result of effective care and satisfying patient health status. Neurosurgeons must decide if outpatient brain biopsy is feasible in each individual case.
Conclusion
Many new trends are emerging, constantly improving patient care and safety, as well as surgical workflow. In particular, future advances in augmented reality as well as in artificial intelligence could enhance both preoperative planning of the biopsy trajectory and its intraoperative real-time viewing. A parameter that must be considered is the cost-effectiveness of these devices and the possibility of using them on a daily basis. Some of the technologies, such as 5-ALA to increase the diagnostic yield, ICG fluorescence to prevent vascular injury, or robotized stereotactic systems, are already used in other fields of neurosurgery, and an extension to the stereotactic biopsy procedures might be easily implemented. The decision to implement a new instrument in the surgical workflow should also be dependent on the number of procedures per year, the existing stereotactic equipment, and the experience of each center. Research on patients’ postbiopsy management is another mandatory approach to enhance the safety profile of stereotactic brain biopsy and patient satisfaction, as well as to reduce healthcare costs.
Author contribution
Conceptualization, B.M.; methodology, B.M.; validation, B.M. and A.B.; investigation, B.M. and A.B.; writing—original-draft preparation, A.B. and B.M.; writing—review and editing, A.B. and B.M.; supervision, B.M. All authors have read and agreed to the published version of the manuscript.
Data availability
Not applicable.
Declarations
Ethical approval and consent to participate
Not applicable.
Human and animal ethics
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Disclosure
All authors had access to the data and a role in writing the manuscript.
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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References
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| 36471144 | PMC9734929 | NO-CC CODE | 2022-12-14 23:28:31 | no | Neurosurg Rev. 2023 Dec 6; 46(1):5 | utf-8 | Neurosurg Rev | 2,022 | 10.1007/s10143-022-01918-w | oa_other |
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Liverp Law Rev
Liverp Law Rev
The Liverpool Law Review
0144-932X
1572-8625
Springer Netherlands Dordrecht
9317
10.1007/s10991-022-09317-3
Article
Construing Climate Change Adaptation as Global Public Good Under International Law: Problems and Prospects
http://orcid.org/0000-0002-2383-6252
Trivedi Abhishek [email protected]
[email protected]
1
Jolly Stellina [email protected]
2
1 grid.448881.9 0000 0004 1774 2318 Institute of Legal Studies and Research, GLA University,, Mathura, Uttar Pradesh India
2 grid.452738.f 0000 0004 1776 3258 Faculty of Legal Studies, South Asian University, Akbar Bhavan, Chanakyapuri, New Delhi, India
5 12 2022
126
1 11 2022
© The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Article 7 of the Paris Agreement recognizes that adaptation is a ‘global challenge faced by all with local, regional and international dimensions.’ It further establishes the ‘global goal on adaptation focusing on enhancing adaptive capacity, strengthening resilience and reducing vulnerability to climate change, with a view to contributing to sustainable development.’ However, the lack of international cooperation between the global north and global south challenge the formulation and implementation of climate change adaptation strategies. This paper brings in the concept of global public goods (GPGs) to the lexicon of climate adaptation and highlights that adverse impacts of climate change such as climate-induced global migration are global public bad. Hence, the measures taken to respond to such impacts, which consequently enhance the resilience of affected countries, make them more adaptive to those adverse impacts, and deliver common values of universal character, should be construed as the global public good. The paper argues that that the idea of GPGs with its universality offers a normative and practical foundation for understanding, addressing, and strengthening the international community’s climate adaptation actions and cooperation.
Keywords
Adaptation
Climate change
Climate-induced migration
Global public good
Paris Agreement
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pmcIntroduction
Climate change is undoubtedly a global crisis that disproportionately affects people across geo-politico boundaries.1 At the same time, it is to be noted that the climate impacts significantly differ from country to country and region to region and are of immediate concern for many nations disproportionately impacted by climate change.2 Countries that are most vulnerable to climate change’s adverse impacts have relatively less capacity to adapt to damage caused by climate change.3 In addition, even if the international efforts to mitigate climate change prove effective, climate impacts are unavoidable due to the already present greenhouse gas (GHG) emissions in the atmosphere. Hence, to reduce the negative impacts of the climate change, international community need to adapt.
Article 7 of the Paris Agreement, 2015, recognizes climate change adaptation4 as a ‘global challenge faced by all with local, regional and international dimensions.’5 It further establishes a global goal on adaptation listed below:To enhance adaptive capacity and resilience;
To reduce vulnerability and contribute to sustainable development;
And ensuring an adequate adaptation response in the context of the goal of holding average global warming well below 2 degrees C and pursuing efforts to hold it below 1.5 degrees C.6
The attainment of the adaptation goal necessitates a global governance of climate change adaptation. Adaptation measures can increase society's resilience and adaptive capacity as a whole, reducing its vulnerability to climate change effects. However, planning an adaptation policy is rife with challenges since climate change and vulnerability manifest themselves differently and change over time. Such a volatile scenario makes it hard to determine the kind of policies and measures for adaptation. To complicate the matter, climate change impacts manifest in different forms ranging from flood to drought to saline intrusion. As such, adaptation needs, measures, and goals are highly context-specific and difficult to measure.7 In addition, the climate change adaptation at the global level is characterized by the lack of international cooperation between and within the global north and global south.8
There are many explanations given for this lack of international cooperation. For example, the provisions of article 7 are vaguely drafted in the sense that they reflect a low level of legalisation.9 Second, high uncertainty amongst States about the distribution of climate impacts globally has led the Paris negotiation on climate adaptation to a low level of precision where each State can interpret article 7 according to what suits best to its domestic preferences.10 Third, States are also not sure about how to compare climate vulnerability globally as a basis for their collective global efforts to address adaptation globally.11 Fourth, there is ambiguity around the concept of adaptation itself as it has been normatively construed differently. For instance, States regard climate adaptation as a contested global goal, mainly due to climate change’s localized and regional impact, making international cooperation difficult.
In this background of lack of international cooperation, the idea of adaptation as global public goods (GPG) offers a normative and practical foundation for understanding, addressing, and strengthening the international community’s collective action and promoting sustainable development. The GPGs are goods with benefits and costs that potentially extend to all countries, people, and generations.12 The idea of GPG can also enhance cooperation or overcome the lack of cooperation since counties find practical incentive/interest in the production and delivery of GPGs. This paper explores whether and in what forms climate change adaptation could be construed as a GPG in the context of sustainable development and in light of the Paris Agreement’s long-term goals.13 The paper examines the contours of ‘global goal on adaptation’ in a broader sense, linked to the adaptation and adaptation-related elements.14 This paper illustratively focuses on displacement/migration caused by climate change and attempts to construe the efforts to address climate displacement as delivering GPGs.
With this aim in mind, the paper is structured as follows. Part I explains the methodological considerations and assumptions. Part II explores the concept of public goods followed by its position under international law. Part III attempts to construe climate adaptation as a GPG. Part IV identifies and assesses the major problems in providing GPGs and enhancing global cooperation.
Methodological Considerations and Key Assumptions
This paper sets out the following methodological considerations and key assumptions. First, it employs relevant public goods literature to understand and contextualize the concept of GPGs and analyze how the same could provide value-add to the study of climate adaptation. Although climate change adaptation deals with local, national, regional, and international aspects of climate change threats, this paper primarily focuses on international dimensions of climate change adaptation. However, in doing so, it is neither feasible nor desirable to completely rule out other regional or local aspects of the climate adaptation that indirectly contribute to GPGs. Secondly, since international cooperation is affected by ‘prisoners dilemma,’ the paper proposes an ‘integrated approach’ to overcome the prisoner’s dilemma to enhance international cooperation on the global climate adaptation governance. Thirdly, the paper uses international law and international institutions—as essential tools—that help facilitate international cooperation in areas like climate change, where global cooperation is necessary to deliver global public benefits. Fourth, the paper heavily relies on the methodological guidance proposed by Scott Barrett, in envisaging and operationalizing GPGs, including aggregate efforts, weakest-link, single best efforts, financing and burden sharing, and development and domestic issues.15 Finally, the paper considers that the problem of free-riding is inherent and can not be eliminated and ignored completely in providing GPGs. However, an attempt has been made to understand how to mitigate this problem. Therefore, the discussion on free-riding is scattered throughout the paper.
Understanding Global Public Good
Since the focus of this paper is to locate climate adaptation in the broader context of GPG, it is necessary to understand the characteristics of public good from a global perspective. The global public goods concept is an economical method of classifying goods and services based on two parameters-Rivalry in consumption and
Excludability.16
Well-known examples are traffic lights and lighthouses.17 Public goods espouse that their benefit extends to all, and their consumption by one does not diminish the consumption by another.18 They are public as opposed to private and global as opposed to strictly national.19 Numerous definitions proposed on the parameters, contours, and applicable categories of public goods promoted a better understanding of GPGs. The International Task Force on Global Public Goods defined GPGs as ‘issues that are broadly conceived as important to the international community, that for the most part cannot or will not be adequately addressed by individual countries acting alone and that are defined through a broad international consensus or a legitimate process of decision-making.’20 Further, the task force endorsed the categories of public goods developed by Barrett based on their effects.21
World Health Organization (WHO) categorizes GPGs as outcomes (for example—eradication of Covid-19) and contributory (international rules attempting to curtail the spread and reduce the vulnerability of Covid-19).22 GPG is further defined as an ‘outcome’ or intermediate product that tends towards universality—that benefits not just one nation or just a particular group of population groups and generations.23 At a minimum, a GPG requires the following criteria: its benefits extend to not just one group of people or private individuals and do not discriminate against any population group or any set of generations (present and future).
As for the relevant areas of GPGs, reiterating the non-rival and non-excludable nature of public goods, the World Bank identifies five areas of GPGs: ‘the environmental commons, communicable diseases, international trade, international financial architecture, and global knowledge for development.’24 Kaul and Mendoza extend the categories of GPGs and emphasize the basic human rights for all people, global public health management, global security and peace, communication and transportation across borders, institutional infrastructure for global cooperation, concerted management of the global natural commons to promote their sustainable use, among other things.25
In sum, it is stated that GPG must satisfy three requirements: first, it covers more than one group of countries; second, its benefits must reach out not only a broad spectrum of countries but also a broad spectrum of the global population; and third, it meets the needs of present generation without jeopardizing those of future generation. Hence, the notion of GPG is not merely geographical but multidimensional which include ‘geographical, sociological, and temporal’ dimension. With the help of this analysis, it is submitted that a GPG is characterized by universality—where it benefits all countries, people and generation and does not discriminate against any population (based on gender, race, age etc.) or set of generation. Though there is no firm consensus on the list of GPGs, the GPGs have come to encompass everything from the global environment, international financial stability, peace, and security through the broad contours proposed by scholars and organizations.26 In light of the above-highlighted understating of GPGs, they have advantages in the field of climate change governance. GPGs can, for instance, enhance cooperation in climate adaptation given the fact that, first, Paris Agreement recognizes climate adaptation as a ‘global challenge’ and thus establish it as a ‘global goal’ to be achieved. Second, measures taken to address climate adaptation can provide several cross-cutting benefits extending to more than one group of county, people and generation. Third, since GPGs are by their definition and nature beneficial to all, they encourage countries to cooperate to address a problem in their common interest. Therefore, construing climate change adaptation as GPG can facilitate cooperation amongst countries. In the background of the expanded notion of GPGs, the next part of the paper attempts to contextualize it under international law and analyses its utility for climate adaptation.
Contextualizing ‘Global Public Good’ in Relation to International Law
International law is a latecomer to GPGs discourse.27 Greg Shaffer and Daniel Bodansky note that international law was mostly missing from the study of GPGs undertaken by the United Nations Development Programme (UNDP) in its three large volumes published in 1999, 2002, and 2006.28 Although international law does not expressly recognize the category of GPG, few international law concepts/principles resemble a close relationship to it. First, international law includes obligations of erga omnes character, which the States owe to the international community of States as a whole rather than to a particular State.29 The obligations erga omnes are by their nature the concerns of the international community as a whole since all States have legal interest and benefit in their protection. For instance, all States are obligated to outlaw acts of agression and genocide and protect the basic rights of human persons, such as protection from slavery and discrimination.30
Second, international law recognizes the concept of ‘common concern of humankind’ where the protection of specific resources is in the interest of all people.31 The concept requires ‘collective action’ to address those shared global problems which transcend national boundaries and reflect a ‘global set of values and interests independent of the interests of a particular State.’32 Some scholars have designated ‘common concern of humankind’ a status of ‘principle’ of international environmental law against the ‘interlinked backdrop of poverty eradication, economic development, energy availability and use, and climate change.’33 Many environmental treaties attempt to address shared global problems by using various phrases that reflect the notions of ‘common concerns’ of humanity’,34 climate change is also a ‘common concern of humankind’35 and, if addressed globally, provides non-excludable and non-rival benefits to world countries. Paris Agreement, while acknowledging climate change as a ‘common concern of humankind,’ asks the States, when taking actions to address climate change, to respect and promote their respective human rights obligations towards indigenous peoples, local communities, migrants, children, persons with disabilities and people in vulnerable situations.36 The incorporation of idea of human rights and protection of vulnerable community resemble the notions of GPGs that the benefits of climate change’s measures should be reached to last section of society. GPG, with its notion of collective benefit, is closely connected to the concepts of obligation erga omnes and common concern of humankind. These three concepts could be perceived as those that protect or conceive the notions of ‘collective or common interest’ and serve the international community of States.37 Putting it differently, if an obligation primarily relates to the protection of GPG (e.g., strengthening the resilience of climate refugee) or protection against global public bad (e.g., protection against global pandemic), then the obligation is considered to be one protecting ‘collective’ or ‘common’ interest of the international community as a whole. Thus, the structure and substantive content of international law already ingrain the concept of GPGs.
However, the question is what makes the idea of GPGs so special that it should be studied in relation to climate adaptation, given the fact that international law does have similar concepts like obligations erga omnes and common concerns of humankind? Firstly, as stated earlier, GPG encourage states to cooperate notwithstanding the fact that the concept of GPG lacks legal force, while obligation erga omnes and common concern of humankind are well recognized concepts in international law. Secondly, international cooperative theory believes that cooperation in a particular field becomes easy if States find some incentives in that filed. GPGs by its definition and nature provides incentives to all nations and therefore cooperation becomes easy because each State finds some incentive/interest in GPG. For instance, reductions in GHG emissions will slow global warming. It will be impossible to exclude any country from benefiting from this, and each country will benefit without preventing another from getting so. Thus, chances of cooperation becomes higher. However, it does not mean that States are denying cooperation considering their commitment as part of obligations erga omnes or common concerns of humankind. But the alternative argument this paper is proposing is that if climate adaptation could be construed as GPG, it can further enhance cooperation. Thirdly, understanding of incentive/benefits should be understood in a broader sense and thus not necessarily limited to monetary incentives. The incentives can come in various form like strengthening the rule of law, democratic and human rights value system. In short, the paper proposes that if climate adaptation could be construed as GPG, it can deliver GP benefits in these various forms and will provide an additional layer of normative foundation for firming international cooperation as the basis of international law. The following section will explore how adaptation can be construed as GPGs.
Construing Adaptation as Global Public Good
Intergovernmental Panel on Climate Change (IPCC) defines adaptation as ‘adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities.’38 Various types of adaptation can be distinguished, including anticipatory and reactive adaptation, private and public adaptation, and autonomous and planned adaptation.39 IPCC Third Assessment Report further states that adaptation ‘has the potential to reduce adverse impacts of climate change and to enhance beneficial impacts, but will incur costs and will not prevent all damages.’40 Since the climate impacts are varied and numerous, adaptation to climate change also assumes numerous strategies and operates at different levels. Examples of adaptation include constructing sea walls to tackle sea-level rise, setting up early warning systems for cyclones, and adopting drought-resistant seeds for drought-hit areas, among other things. Though a lop-sided emphasis on mitigation characterizes the international climate change regime, adaptation has gradually been gaining legal and policy attention.
This paper argues that climate change stability and mitigation is already considered a GPG, as it satisfies the GPG criteria of non-rivalry, non-exclusivity, and larger benefit because each country’s emissions of GHGs contribute cumulatively to the increase of the overall concentration, and each country’s abatements will contribute to climate stability in the long run.41 In addition, free riding, which charecterises public good, is also prevalent in climate change since some countries may not wish to take serious action against climate change and will still enjoy the benefit of others' abatement. The free riding involved in GPG has been highlighted by Bodansky, who notes that, like public goods in general discourse, GPGs in relation to international law involve externalities writ large—meaning thereby, the GPGs are not free from free-riding problems associated with the supply chain.42 For instance, developing an international regime like the UNFCCC and Kyoto Protocol is envisaged to benefit all countries worldwide (if implemented in the fullest sense). Still, it created a free-riding tension since all countries did not view climate change with the same seriousness and taken measures to address climate change.43
In the context of climate adaptation, the Paris Agreement requires all Parties, as appropriate, to engage in adaptation planning and implementation through, e.g., national adaptation plans, vulnerability assessments, monitoring and evaluation, and economic diversification.44 Notably, almost two-thirds of world countries have adopted national-level law/policy instruments on adaptation.45 It implies that many countries treat climate adaptation as a ‘key component’ of the Paris Agreement’s long-term global goal, even though the adverse impacts may not always span over several countries at a time. The understanding is that their large-scale implications could still affect other countries indirectly. However, the Agreement does not quantify or indicate the adaptation strategies, policies, and outcomes that qualify as ‘global goal on adaptation.’ Therefore, a challenge is to identify which ‘global goal on adaptation’ can be construed as delivering GPG since climate adaptation comes in various forms; a few reflect local, national and regional public good quality, while some can provide GPG. The literature on climate adaptation governance entails divergence of opinion, where some scholars and developed countries consider adaptation a local or national issue yielding only local or domestic benefits.46 In contrast, other scholars and developing and Small Island States (SISs) argue that the negative impacts of climate change (e.g., a threat to the continuation of statehoods of SISs, international climate-induced migration, the purchasing power of vulnerable communities, global public health challenges) should be seen as ‘global public bad[s]’ (GPBs).47 The reviewed literature, however, does not examine the nature of adaptation as GPG or GPB based on the criteria highlighted above, which include the elements of non-rivalry and non-excludability (for the generic meaning of public good) and elements of universality in terms of countries, population groups and generation (for the contextual meaning of GPGs).
The paper argues that climate adaptation strategies, even if conceived and implemented locally, have a global spillover benefit for current and future generations. For instance, in response to the increased droughts in western India, policy measures to promote drought-prone resistant seeds are adopted. Along with producing an immediate local benefit, the measures will contribute to the country's food security. They will also reduce the financial burden on the import of food crops. If the policy mechanism is implemented in a non -discriminatory and non-arbitrary manner, this will fulfill the criteria of non-exclusiveness and non-rivalry. This may also prevent people in the region affected by the droughts from migrating to other regions and causing instability and burden on the receiving State. In addition, if the drought-resistant seeds were not introduced, the locality or the region would have been unable to adapt to climate change and suffered loss and damage. It would have consequently led to the demand for adequate compensation.48 However, countries in practice are reluctant to endorse the view that adaptation is a global goal, which, in their view, would entail the responsibility and cooperation of all states (specially developed) to act upon and assist the affected states.
Generally, the international legal structure is characterized by states that accept reciprocal constraints on action to generate a stable social contract.49 International law is thus based on the prisoner’s dilemma structure of self-interested behaviour.The prisoner’s dilemma is that it would be mutually beneficial if two states cooperate, but there is enough self-interest for the states to defect without undergoing suffering.50 The central aspect of the prisoner's dilemma highlights the problem of balancing the uncertain relationship between a state's selfish behaviour and its commitment to international legal norms.51 This paper argues that if designed in an integrated manner and implemented globally through international cooperation and in the context of sustainable development, climate adaptation measures can overcome the prisoner’s dilemma and provide potential equity effects, and deliver global public benefits. The integrated approach as how it is useful is discussed in the following section in relation to climate displacement.
The paper, as an illustration, argue that transboundary adverse impacts of climate change (such as climate-induced global migration) that affect a sizeable number of States are the GPBs. Therefore, the measures taken to respond to such impacts, which consequently enhance the resilience of affected countries, make them more adaptive to those adverse impacts, and deliver common values of universal character, should be construed as GPGs. Thus, climate change adaptation is so construed as the GPG would eventually deliver global public benefits in various forms and mitigate the burden of adverse impacts of climate change. This paper illustratively adopts the case of climate migration/displacement as an example to provide a viable context to demonstrate climate adaptation as GPG and legal avenues of cooperation.
Providing GPG While Addressing Climate-induced Migration: A Call for Enhanced International Cooperation
Climate-induced transboundary migration52 is a complex phenomenon and takes place at different levels where around the range of hundreds of millions of people are projected to migrate within and beyond States by 2050.53 Not only climate displacement itself should be considered as public bad, but the underlying causes54 identified by the IPCC and the United Nations High Commissioner for Refugees (UNHCR) can also arguably be treated as public bad[s], in which cases their large scale impacts could decide the actual nature of climate displacement whether the latter should be construed as global, regional, national, or local, public bad. Most of the underlying causes are attempted to be addressed, directly or indirectly, by the Paris Agreement provisions of strengthening the resilience and adaptive capacities of States to adapt to climate change’s adverse impacts, including climate displacement.55 Therefore, the measures taken to respond to the underlying causes of climate displacement could arguably be considered global or regional public goods as they contribute to strengthening the adaptive capacity of the affected countries. Suppose the measures that have been adopted are extended to the national, regional, or international level, given that the adopted measures are non-discriminatory and do not exclude the potential beneficiaries based on religion, region, race, caste, creed, or any other similar grounds. In that case, they satisfy the non-rivalrous and non-excludable aspects of public goods. For instance, a planned relocation of the climate-affected population in the Maldives or Bangladesh will not only provide a non-rivalrous and non-excludable national benefit but will also contribute to regional stability and enhance international human rights protection, and will help the attainment of Paris Agreement objectives.
However, it is not easy to conceive how the normative framework and institutional arrangements create practical incentives for the States to cooperate in addressing climate displacement at the international level. For this, it is essential to understand that climate displacement poses a long-term threat to humanity, increases world vulnerability, and adversely affects several people's individual and collective human rights.56 Rich countries are less prone to climate displacement since they are relatively more able to prevent and adapt to such displacement.57 In contrast, developing countries might not be sufficiently able to initiate adaptation programs,58 leading to displacement as an undesirable outcome. In these situations, adequate protection and international support and cooperation become essential, regardless of whether climate displacement is internal or transnational.59 Countries have incentives and real impulses to cooperate at a large scale if transnational migration occurs widely where, for instance, at least one geographical region is affected. These incentives could include the material benefits and countries’ perceptions that if transboundary migration is not stopped or mitigated, it could lead to several socio-economic challenges for a host country as it could create resource burden or lead to local conflicts as well.60 Therefore, if transboundary migration is not managed globally, it could potentially affect home and host countries along with indirect implications for countries that may have other interests in preventing such migration.
Furthermore, States’ increased capacity itself could be maneuvered to deliver global public benefits because it would benefit the funding as well the receiving States. It would directly help poor (developing) countries enhance their adaptive capacity, strengthen resilience, and reduce vulnerability to climate change. Suppose the funding States are (rich) developed countries and champions of democracy. In that case, they will indirectly benefit from reducing global conflict and gender/race-oriented violence, strengthening democracy, and fostering the domestic and the international rule of law. This is significant because studies have highlighted the strong correlation between climate displacement, female trafficking, and human rights violations. The term ‘benefit’ used here should therefore be interpreted broadly to include non–monetary parameters. Notably, global cooperation should not be looked at from the prism of funding only: it can come in various ways and facilitate an institutional cooperative mechanism for technical cooperation and policy planning. Second, it would contribute to the attainment of sustainable development—a context in which the provisions of the Paris Agreement and the SDGs targets, including climate change adaptation, have to be implemented.61
Climate displacement happens because of the inability to adapt. Therefore, adaptation to climate displacement is considered one of the possible measures/solutions to the global migration crisis.62 Nevertheless, a question should be asked how the States’ capacity could be increased to adapt to climate displacement. Here, the term ‘capacity’ should be construed broadly, encompassing normative framework and institutional arrangements necessary to enhance the States’ capacity to address climate displacement issues. As for the normative framework, specific international legal protection standards as set out under international refugee and human rights regimes could be applied in the context of climate displacement by way of their expansive interpretation.63 The UNHCR, as an international institution, can perform a significant role, although controversial,64 both in influencing the decision-making process and implementing the global standards for refugee protection. Fostering coordination in the global management of climate-displaced populations by UNHCR is expected to provide global public benefits as awareness, information exchange, and sharing of best practices and better preparedness. In this regard, this paper suggests a hybrid approach (an approach towards integration of substantive norms from different branches of international law, an amalgamation of norms of different legal status, and assimilation of the role of State and non-state actors, including international organizations) to be adopted to deal with normative deficiencies associated with climate migration.65 Rather than review the existing bulky literature on international refugee and human rights legal regimes, an attempt is made here to underline that these regimes with all the drawbacks provide a normative backbone to facilitate and legitimize the delivery of GPGs in relation to climate displacement. It should be emphasized that, adaptation plans and normative standards are not enough; the actual problem lies in the implementation part, which requires several cross-cutting measures to adopt, such as financing and an integrated planning process. Having made a case for considering climate adaptation and illustratively highlighting addressing climate displacement as providing GPGs, the paper identifies and addresses the major problems in providing GPGs and global cooperation.
Identifying and Addressing Major Problems in Providing GPGs and Promoting Global Cooperation
Scott Barrett identifies some problems (as mentioned above in the methodological part) in providing GPGs. He discusses these problems using different international law examples without contextualizing those examples concerning climate adaptation. Therefore, along with ICT scholarship, this paper uses and contextualizes these problems in the context of climate adaptation.
Aggregate Effort Problems
The first problem is related to ‘aggregate effort problems.’66 For instance, climate change mitigation—a kind of GPG—requires aggregate efforts of all world countries, including a country that contributes minimally to causing climate change. Free-riding is a big problem in climate change mitigation. This problem becomes enlarged in climate adaptation, consequently reducing the possibility of global cooperation for many reasons. First, there is a view that climate change impacts are diverse where ‘catastrophic’ climate change (such as rise in sea level and erosion of land area) is too remote to take centuries. Meanwhile, potentially affected countries will be able to adjust. However, ‘abrupt climate change can cause serious, if not ruinous, problems and is likely to occur more rapidly, rather than taking centuries.67Thus, the level of international cooperation would depend on the magnitude of climate change impacts. Second, because of climate change’s diverse impact as it affects world countries differently (where the most vulnerable are affected severely), countries have fewer incentives to be provided to cooperate and address the problems associated with climate adaptation. However, an analysis of the rationale behind international cooperation reveals that the cooperation does not merely depend on an analysis of cost–benefit. Countries cooperate to resolve environmental issues based on numerous incentives, including the desire to project an image of a responsible nation.
For instance, the decision of Japan to ratify the Montreal Protocol on Ozone Depletion is influenced by its desire to project an international image of a nation serious regarding environmental protection.68 This desire triumphed over the potential economic cost–benefit analysis. Similarly, the decision of the United States not to ratify the Convention on Biological Diversity (CBD) has prompted many nations to ratify the CBD immediately. Signature and ratification of the Convention became a popular act of protest by the nations.69 Similarly, India was criticized by many nations for opposing any binding climate mitigation obligations despite being one of the largest gross GHG emitters. Hence, India was eager to project an image of seriousness as regards climate change. The leadership provided by India for the establishment of the International Solar Alliance needs to be seen in this background.70As explained, the desire to cooperate and take leadership in solving international environmental issues can be based on numerous factors which can encourage cooperation.
Third, there is a divergence of opinion on whether climate adaption provides GPG: if yes, then in what forms; if no, then why do States cooperate. However, as explained in the earlier part of the paper, climate adaptation can qualify as GPGs as the measures taken for climate adaptation can reduce the vulnerabilities, enhance the resilience of affected countries, and deliver common benefits that are indivisibly spread among the entire community. Fourth, climate adaptation has economic consequences where the cost is a significant factor in providing GPG of adaptation.71 Further, addressing this problem could require diverting limited resources from other good causes, which provides greater benefits than investing in climate adaptation. However, this paper considers that an integrated approach to climate adaptation could reduce this problem by mitigating free-riding problems, providing co-benefits, and consequently lifting the prisoner’s dilemma.72
The hybrid/integrated approach offers a platform for forging cooperation in solving issues of global commons. For instance, attempting to address climate change only by focusing on United Nations Framework Convention on Climate Change (UNFCCC), Kyoto Protocol, and the Paris Agreement is meaningless, as these legal instruments do not address many sources of GHG emissions.73 Studies suggest that international shipping and civil aviation contribute to GHG emissions.74A coordinated attempt between these institutions is essential for addressing climate change; it may also provide incentives for cooperation between nations as the tradeoff and interest each nation has in these areas are different. For instance, UNFCCC and Kyoto Protocol were founded on the concept of Common but Differentiated Responsibilities and Respective Capabilities (CBDR-RC); however, the same cannot be extended to international shipping and civil aviation. Hence, the obligations can be imposed on countries like India and China, thus obliterating the asymmetry obligations raised by the United States against these countries in the climate negotiations. Varied interests of the nations in different foras can be leveraged for international cooperation.
Another way to promote international cooperation in climate adaptation could be by linking it with SDG goals in general and SDG-13 in particular concerning climate change. Since adaptation cannot be a single policy, but a comprehensive one in the context of poverty reduction, agricultural development, water resources development, and disaster prevention,75the attainment of SDGs is a probable indicator where states are expected to cooperate in actions which can provide a fillip to the attainment of SDG goals and sustainable development.
As an integrated approach, the paper considers the hybrid mechanism in climate migration/displacement. The hybrid law approach advanced in this paper proposes that law makers borrow the best practices and principles from existing branches of international law instead of creating a new one. Thus, for issues concerning climate refugees cutting across issues of human rights, refugee law, and environmental norms, hybrid law provides the foundation to forge the composition of a new eclectic legal regime considering the norms and institutional coordination from the international climate change framework, human rights and refuges laws to address the climate displacement in a coordinated manner. The Nansen Protection Agenda for the Cross-Border Displaced Persons in the Context of Disasters and Climate Change76and the UN Compact for Safe, Orderly and Regular Migration, a non-legally binding, cooperative framework that builds on the commitments agreed upon by the UN Member States in the New York Declaration for Refugees and Migrants reflect a set of hybrid law mechanisms covering cross-cutting, interdependent and people-centered guiding principles and is based on international cooperation, national sovereignty, the rule of law, sustainable development and human rights.77 Further, there are enough practical reasons and incentives for nations to evolve regional cartels as a measure of adaptation for the time being and gradually promote an ‘aggregate efforts’ of all countries. Hence, international law has enough existing mechanisms and hooks to enhance international cooperation.
Weakest-Links Problem
The second problem is related to the ‘weakest-links problem.’78 Some GPGs are to be produced with the participation of ‘all’ countries—i.e., global cooperation—and if one or a few countries are excluded, it could defeat the very purpose of providing GPG. An example in this regard is the Kyoto Protocol, whose effectiveness was challenged by the decision of the United States not to be a party. Another prominent example given in this regard is the disease of Smallpox, which was considered to be a serious health problem during the late twentieth century.79 However, with the mass vaccination program globally, it is almost disappeared. Similarly, the Covid-19 pandemic (a kind of GPB) could be another contemporary example, where its complete eradication should be considered ‘weakest-link’ GPG because its benefits are both non-excludable and non-rival as well as it requires global cooperation. If one country (weakest-link) is excluded from accessing the Covid-19 vaccine (a kind of GPG), it can defeat the very purpose of attaining complete elimination of the Covid-19 pandemic. Global cooperation is possible in providing this kind of GBG if each country has an ‘incentive’ and is assured that all other countries would play their part. This ‘assurance’ plays a vital role in producing incentives towards the supply of this GPG. In Covid-19, the ‘assurance’ makes sense since all countries are affected and have ‘incentives’ to get out of this pandemic. Although Covid-19 is not a result of climate change, it made vulnerable the most vulnerable.
In the context of climate adaptation, the weakest-link problem may not assume significant proportions. Climate adaptation is envisaged as a response to the climate impacts, ranging from local, national, regional, and global concerns. It has generally been noted that the countries impacted by climate change are eager to envisage adaptive mechanisms. If they are not able to envisage measures, it is due to the lack of financial or technological assistance. The challenge is to promote international cooperation among nations that may not be seriously impacted by climate change in the short term. The international climate regime has provided for technological, financial, and scientific cooperation.80The State parties to the UNFCCC and Paris Agreement have not objected to the requirement indicating their willingness to contribute. The acceptance of financial assistance by the developed nations is significant since many countries view compliance with international law or participation in the global legal order as an essential part of their identity and constitutive commitments and are expected to cooperate in good faith.81
Furthermore, unlike the global pandemic, even if one or two nations are left out of the adaptation policies and strategies, it may not entirely defeat the efforts of adaptation by other nations. In addition, climate adaptation also leaves scope for regional cooperation, and hence the ‘weakest link’ inherent in the GPGs can be overcome. Since many climate impacts are felt on a regional scale, for instance, sea-level rise and the consequent displacement, regional cooperation can be the primary strategy. In this regard, an analysis of South Asian Cooperative Strategies includes the Dhaka Declaration on Climate Change,82 the SAARC Action Plan on Climate Change,83 and the Thimphu Statement on Climate Change.84All these initiatives have underscored the importance of adaptation as a crucial area of concern and an area for strengthening regional cooperation to address the extreme vulnerabilities of climate change in the region.85
The Thimphu Statement on Climate Change noted that South Asia is particularly prone to climate change and related disasters making the need for a regional response to meet the challenges of climate change more urgent and compelling. The statement also noted that South Asia could benefit from cooperative regional initiatives and approaches, exchange of experiences, knowledge, transfer of technology, and best practices to address the challenges posed by climate change. It recognized the urgency of ‘regional cooperation and climate change responsive measures, such as formulating a ‘comprehensive regional strategy’ against climate change, including adaptation.86
Single-Best-Effort Problems
The third problem is related to single-best-effort (SBE) issues.87 Unlike aggregate effort problems, SBE problems arise where the GPGs are delivered by individual actors or a group of few actors, thus creating many free riders.88 The SBE hardly poses many confrontations at the production level as it does not necessarily require universal cooperation because the country itself involves and finds sufficient self-interest in the production of GPG.89
It is difficult to conceive the SBE problems concerning climate adaptation crisis as the crisis, by definition, involves the aggregate efforts of all countries. However, free riding and SBE problems can still be a significant concern for climate adaptation efforts. Despite the chances of free-riding problems, the situation—like climate change–can push countries to be involved in mitigation and adaptation since climate change raises an existential threat for humanity. However, it still requires international cooperation at a large scale, not only for investing in Research and Development (R&D) to either get prepared for or prevent future climate calamity but also in the dissemination of produced GPG to the last and most vulnerable person of society, making it a true GPG. In the case of climate adaptation in general, SBE’s example of providing regional public good could be given where, for instance, India dedicated a self-made South Asia Satellite for monitoring climatic variation, among other things.90Another typical example at the international level is the Scandinavian countries, often taking the lead in environmental negotiations and taking unilateral measures above and beyond their commitments.91
International Financing and Burden-Sharing Arrangements
The fourth problem is related to international financing and burden-sharing arrangements.92 GPGs of any type require international funding. Mobilization of finance for climate adaptation is a complicated and challenging phenomenon, and a lack of funding could seriously jeopardize the capacity-building measures that are inevitable in climate adaptation. Thus, lack of funding resources could be the major challenges in providing GPGs in climate adaptation. Despite having specific funding mechanisms (such as Green Climate Fund and Special Adaptation Fund), a pertinent question nevertheless arises—who should finance climate adaptation and why the same should be mobilized at a large scale, if not globally.
Again, the incentives that the countries will gain and the assurance that all other countries will share and play their part are the factors that would motivate the States and institutions to cooperate and invest in financing. Financing in technological transformation, which can relatively be more suitable for adaptation, could require aggregate efforts of all countries, mainly developed countries. Financial aid, however, raises the issues of burden-sharing and allocation. A huge gap remains in financing for developing countries. Annual adaptation costs in developing countries are estimated at USD 70 billion, and this figure is expected to reach USD 140–300 billion in 2030 and USD 280–500 billion in 2050.93 Therefore, public and private financing needs to step in with some normative arrangements, including principles to govern the allocation.
Allocation of climate change finance is another problem where developed countries focus on financing mitigation plans despite the articulation of developing countries to finance adaptation.94 Therefore, the allocation should be done following the Paris Agreement's norm of increasing adaptation finance from current levels and providing appropriate technology and capacity-building support. Moreover, increased public and private adaption financing should be backed by the notion of a sustainable financing system. Adaptation financing needs to be sustainable, and it must develop new tools of sustainability investment criteria, climate-related disclosure principles, and mainstreaming of climate risks into investment decisions. The multiscale and integrated model of finance arrangement substantiates the argument of an integrated approach advanced throughout the paper. An integrated approach could motivate states and other actors to invest in enhancing climate resilience. Another reason is that a total world expenditure on climate adaptation does not outweigh the loss the world communities suffer from climate change’s adverse impacts each year. In this regard, further empirical research should be done to assess the ‘cost’ of climate displacement and the potential benefits of appropriate measures, if, taken in advance.
Development, Domestic, and Legitimacy Issues
The fifth problem is related to development, domestic, and legitimacy issues.95In most GPGs, development is a ‘latent potential benefit.’96 However, to fully realize the development-related benefits of GPGs, it requires effective domestic institutions to ensure the supply of these benefits to everyone. Under-supply of regional and global public goods can adversely affect the poor and weak States. Putting it differently, strengthening domestic institutions at a large scale and overcoming the deficiencies is itself a GPG since it would also indirectly benefit rich and advanced countries. However, domestic issues and sometimes individual leadership motivated by ideological considerations influence the international cooperation process and affect the delivery of GPGs. For instance, in the case of climate change, it happened when the USA and Australia declined to accept the Kyoto Protocol, which in their view, created free-riding problems by excluding emerging major pollutants, India and China.97 However, the Democrats in the USA hold a different perspective; a recent example of this was to signify a willingness to rejoin the Paris Agreement.98 Therefore, fighting against any global concerns and consequently against its adverse consequences would require ‘wide-scale and multisectoral coordination’ to deliver GPGs by equitable sharing of burdens and to protect the human rights and needs of the most vulnerable. In this regard, relevant international organizations must undertake ‘multisectoral collaboration’ to make global cooperation feasible. These organizations include, but are not limited to, the International Meteorological Organisation, United Nations Framework on Climate Change (UNFCCC), International Civil Aviation Organisation (ICAO), International Maritime Organisation (IMO), and UNHCR. These organizations can provide a model for collaborative governance needed to adapt to climate change’s social, economic, and health consequences. They could also be used as a reference point for developing effective global coordination mechanisms in climate adaptation by placing migration and adaptation on the global and domestic political agendas list and raising general awareness and democratic response. General public awareness can immensely contribute to climate adaptation. For instance, if an adaptation technique of cyclone warning is adopted nationally, knowledge of it and its dissemination globally can help enhance adaptation.
Though cooperation forms the foundation of the international environmental law framework, broad state interests characterize a quintessential environmental negotiation with some states favouring environmental protection and some opposed. This scenario makes cooperation difficult between nations and makes it appear aspirational. It may even be challenging to determine what kind of cooperation is required to address the environmental crisis in some cases.99 It has also been historically noted that developed countries preferred environmental protection over developing nations.100 In climate change, there are additional divisions, such as between island nations and other developing nations like India and China. In this context, trade-offs are used to facilitate Agreement. For example, the developed nations brought the financial fund mechanism to encourage developing nations’participation.101 Similarly, the Reducing Emissions from Deforestation and Forest Degradation (REDD) mechanism was introduced to facilitate cooperation between the developed north and developing south.102 Though it is possible to envisage coordinated policies, conflicts must be recognized and addressed in time. For instance, the REDD mechanism provides forest users economic incentives to protect and sustainably manage forests in developing countries. However, this might entail restricted access to those forests by indigenous communities, which has an immediate negative impact on the socio-economic security of groups not included in the system.
In addition, environmental agreements are based on consensus, and nations often indulge in coercion tactics to force and facilitate cooperation.103 The numerical majority of developing nations can elicit some force in making sure international agreements provide incentives for climate adaptation. The explicit mention of the ‘global goal on adaptation’ indicates the persistence of the developing nations. Finally, the involvement and influence of non-state actors in the decision-making process of production and delivery of GPGs raise legitimacy concerns of different degrees under international law. The authors do not have a predicate solution to resolve all these problems but acknowledge that further database research is required in each highlighted scenario.
Concluding Remarks
In sum, it is reiterated that the process of applying the concept of (global) public good in relation to climate change adaptation is not easy as it involves multiple actors (states and non-state actors), legal norms of different status (hard and soft law), diverse challenges (domestic and international), and variety of incentives that are necessary to enhance international cooperation at the global level. However, although climate adaptation has been normatively construed differently, it can still deliver GPGs in multiple forms. This paper substantiates that if climate adaptation measures responding to climate change’s adverse impacts are adopted at a large scale and integrated with the Paris Agreement's long-term goals, they can deliver global or regional benefits, making global or regional cooperation easy. However, the challenges would always be there regarding free-riding issues that could be mitigated or managed by following the integrated approach suggested in this paper. The paper argues that extending the concept of GPGs to climate adaptation can be a powerful tool in promoting global benefits because it marshals the arguments of self-interest. It can be used to identify areas in which global collective action is needed, specify where the costs and benefits will rest, and communicate why spending on climate adaptation thousands of kilometers around the world is not a waste of their tax dollars. This paper finally acknowledges that more empirical study is required in each sector (climate adaptation and migration) to transpose and contextualize the study of GPGs in relation to international law in general and climate change law in particular.
Declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
1 Allen et al. (2018, pp. 1–24, 9–13).
2 Claire Mcguigan et al. (2002, pp. 4–14). Skoufias et al. (2011, p. 1). Leichenko and Silva (2014, pp. 2–8).
3 Pörtner, H.-O et al. (IPCC, 2022 P. 11). Lesnikowski et al. (2017, p. 825).
4 This paper uses the terminology of climate change adaptation and climate adaptation interchangeably.
5 Decision 1/CP.21: FCCC/CP/2015/10/Add.1, 21 (2016, article 7).
6 Paris Agreement (n 5) art 7(1).
7 Bisaro and Hinkel (2016, p. 354). Field et al. (2014).
8 Khan and Roberts (2013, pp. 171–189).
9 Here the low level of legalisation means a low level of ‘precision and obligation’ of norms/commitment. Many provisions of article 7 are couched in the language of ‘should’ and ‘will,’ thus create a kind of ‘expectation’ from, rather than imposing ‘obligation’ upon, the State parties. Although few provisions are drafted using the language of ‘shall,’ but qualified with conditions such as ‘as appropriate’ and ‘inter alia.’See Rajamani (2016, pp. 337–358).
10 Magnan and Ribera, (2016, p. 1280).
11 Magnan and Ribera, (2016, p. 1280).
12 Stoll, (2008, pp. 116–136).
13 Paris Agreement lays down three broad global long-term goals for States to achieve. These are mitigation, adaptation, and cooperation towards international support in providing financial assistance, facilitating technology transfer, and investing in capacity-building measures of developing countries. See Decision 1/CP.21: FCCC/CP/2015/10/Add.1, 21 (2016, articles 2.1, 3, 4.1, 4.19, 7.2, 9, 10, and 11). These goals include mitigation (article 4), adaptation (article 7), and international support (financial and technological – articles 9 and 10).
14 General Assembly Resolution 70A/1 (2015).
15 Barrett (2007).
16 Kaul and Mendoza (2003, pp. 78–111). See also World Bank (2016, p. 75). Kaul et al. (1999, p. xxiii).
17 Long and Woolley (2009, pp. 107–08).
18 Long and Woolley (2009, p. 109).
19 Long and Woolley (2009, p. 109).
20 International Task Force on Global Public Goods (2006, p. 13).
21 International Task Force on Global Public Goods (2006, p. 14) (explaining local, national, regional, and global public goods in terms of ‘benefits’ accruing, respectively, to the members of a locality, people in a country, countries belonging to a regional group based on geography, and all countries and all persons).
22 Anne Ress (2013).
23 Kindleberger (1986, pp. 1–13).
24 World Bank (2016, p. 75).
25 Kaul and Mendoza (2003, p. 98).
26 Long and Woolley (2009).
27 Very few research articles are written on GPGs in relation to international law. See generally Nollkaemper (2012, pp. 769–791). Aaken (2018, pp. 67–79). Bodansky (2012). Morgera (2012, pp. 743–767). Cafaggi and Caron (2012, pp. 643–649. Shaffer (2012, pp. 669–693). Maskus and Reichman (2004, pp. 279–320). Tyler Cowen (1992, pp. 249–267).
28 Shaffer (2012, p. 670). Bodansky (2012, p. 656).
29 Barcelona Traction (ICJ, 1970 , paras. 33–34). Bodansky (2012, p. 657).
30 Barcelona Traction (ICJ, 1970 , para. 34).
31 See Wijkman (1982, pp. 511-536).
32 Shelton (2009, p. 83).
33 Soltau (2016, p. 203).
34 For instance, the International Convention for the Regulation of Whaling (1946) states that “wild animals in their innumerable forms are an irreplaceable part of the earth’s natural system which must be conserved for the good of mankind. Similarly, the 1959 Antarctic Treaty affirms that ‘it is in the interest of all mankind that Antarctica shall continue forever to be used exclusively for peaceful purposes. See also other treaties articulating similar ideas: The Tokyo Convention for the High Seas Fisheries of the North Pacific Ocean (1952), the Bonn Convention on the Conservation of Migratory Species of Wild Animals (1979),
35 Paris Agreement (2015, preambular recital 11). See also, Convention on Biological Diversity (1992, preambular recital 3) affirming that conservation of biological diversity is a common concern of humankind.
36 Paris Agreement (2015, preambular recital 11).
37 Bodansky (2012, p. 657).
38 Smith and Pilifosova. (IPCC, 2001, p. 879).
39 McCarthy et al. (2001, pp. 877–913). Warner (2011).
40 McCarthy et al. (2001, pp. 877–913).
41 Marco Grasso (2004, pp. 1–23).
42 Bodansky (2012, p. 658).
43 Harris (1999, pp. 27–28).
44 Decision 1/CP.21: FCCC/CP/2015/10/Add.1, 21 (2016, article 7(2).
45 Khan and Roberts (2013).
46 Neil Adger et al. (2001, pp. 681–715). Neil Adger, Arnell and Tompkins (2005, pp. 77–86). Bisaro and Hinkel (2016, pp. 1–5). Hinkel (2016, pp. 1–5).
47 Khan and Roberts (2013, pp. 171–189). Khan (2014). Magnan and Ribera (2016, pp. 1280–82). Ciplet, Roberts and Khan (2015).
48 The history of L&D in the context of climate negotiations dates back to 1991 when the Alliance of Small Island States called for a mechanism that would compensate countries affected by sea-level rise. L&D is climate impacts that were not prevented by adaptation and mitigation measures. See Mace and Verheyen (2016, pp. 197-214). Simlinger and Mayer (2019, pp. 179–204).
49 Parisit and Ghei (2003, pp. 93–124).
50 Chinen (2001, pp. 143–189).
51 Norman and Trachtman (2005, pp. 541–580) 99(3). McAdams (2009, pp. 209–237). Weiss and Agassi (2020, pp. 1–23). Conybeare (1984, pp. 5–22).
52 This paper uses the terminologies of climate displacement and climate-induced migration interchangeably.
53 Jolly and Trivedi (2019, pp. 69–100).
54 These causes include, but not necessarily limited to, extreme weather impacts precipitated by hurricanes and flooding, gradual environmental deterioration, slow-onset disasters, sea-level rise and submersion of low-lying island states, coastal erosion, loss of housing due to flooding or mudslides in the mountains, loss of living resources such as water, energy, and food supply, loss of social and cultural resources, and loss of cultural property, neighborhood or community networks mainly because of a devastating flood. See Guterres (2008, pp. 4–5). Edenhofer et al. (2014, pp. 20, 288, 299).
55 See General Assembly Resolution 70A/1 (2015, SDG-13). SDG-13 urges the states to take urgent action to combat climate change and its impacts.
13.1 Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries.
13.2 Integrate climate change measures into national policies, strategies, and planning.
13.3 Improve education, awareness-raising, and human and institutional capacity on climate change mitigation, adaptation, impact reduction, and early warning.
13.a Implement the commitment undertaken by developed-country parties to the United Nations Framework Convention on Climate Change to a goal of mobilizing jointly $100 billion annually by 2020 from all sources to address the needs of developing countries in the context of meaningful mitigation actions and.
transparency on implementation and fully operationalize the Green Climate Fund through its capitalization as soon as possible.
13.b Promote mechanisms for raising capacity for effective climate change-related planning and management in the least developed countries and small island developing States, including focusing on women, youth, and local and marginalised communities.
56 See Allen et al. (2018).
57 See Guterres (2008).
58 Guterres (2008).
59 Scheffran (2012, pp. 1–25).
60 1951 Refugee Convention, preamble recital 4 also recognizes that ‘the grant of asylum may place unduly heavy burdens on certain countries…; see further Inder (2017, pp. 523–554).
61 See Decision 1/CP.21: FCCC/CP/2015/10/Add.1, 21 (2016, article 2.1 (Agreement aims to strengthen the global response to the threat of climate change, in the context of sustainable development and efforts to eradicate poverty, including…). Besides the Paris Agreement, the UN 2030 Agenda mentions that the 17 SDGs goals and 169 targets are integrated and indivisible and balance the three dimensions of sustainable development: the economic, social, and environmental. See General Assembly Resolution 70A/1 (2015, preambular recital 3).
62 Afifi et.al (2016, pp. 254–274). Jolly and Ahmad (2019, p. 73) .
63 Jolly and Ahmad (2015, pp. 227–246).
64 Mayer and Crépeau (eds) (2017, pp. 1–15).
65 Jolly and Trivedi (2019, p. 87), Corendea (2016, p. 29), Heyvaert (2009, pp. 1–27).
66 Barrett (2007, pp. 74–102).
67 Committee on Understanding and Monitoring Abrupt Climate Change and Its Impacts (2014).
68 Ott (1991, pp. 188–208).
69 Raustiala and Victor (1996, pp. 16, 19).
70 Mohapatra (2019).
71 United Nations Environment Programme (2021). The recently adopted UN Compact for Safe, Orderly, and Regular Migration, a non-legally binding, cooperative framework that builds on the commitments agreed upon by the UN Member States in the New York Declaration for Refugees and Migrants.
72 See Kraemer et al. (2017, pp. 1–9). Stapleton et al. (2017).
73 Nordhaus (1999).
74 International shipping accounted for about 2–3% of global GHG emissions, international aviation emitted annually, or 1.2% of global GHG emissions. Climate Action Tracker (2022). 'International Aviation. https://climateactiontracker.org/sectors/aviation/. Accessed on 3 April 2021.
75 International Cooperation Bureau (2007).
76 The Nansen Initiative (2015).
77 UNGA:A/CONF.231/3 (2018, paras. 1–3, 6, 7, and 15). See also Solomon and Sheldon (2019, pp. 1–7). Guild (2019, pp. 1–3).
78 Barrett (2007, pp. 47–73)., pp. 53–63).
79 Gostin and Taylor (2008, pp. 53–63
80 Decision 1/CP.21: FCCC/CP/2015/10/Add.1, 21 (2016, articles 9, 10, and 11).
81 David Ohlin (2011, pp. 869–900).
82 SAARC Environment Ministers Dhaka Declaration on Climate Change (2008b).
83 SAARC Action Plan on Climate Change (2008a).
84 Thimphu Statement on Climate Change (2010).
85 Das and Bandyopadhyay (2015, pp. 40–54). See also Shahab (2018, p. 76).
86 Thimphu Statement on Climate Change (2010).
87 Barrett (2007, pp. 22–46).
88 Barrett (2007, pp. 22–46).
89 Barrett (2007, pp. 22–46).
90 Roche (2017).
91 O'Nell (2009).
92 Barrett (2007, pp. 103–132).
93 See generally Adaptation Gap Report 2020.
94 Bodansky, Brunnee and Rajamani (2017, pp. 240–242).
95 Barrett (2007, pp. 166–189. Bodansky (2012, p. 656).
96 Barrett (2007, p. 166).
97 Loy (2001, pp. 152–155, 202. Honkonen (2009, pp. 257–267P. Jolly and Naik (2021).
98 Press Statement Agreement’ (2021).
99 Craik (2020, pp. 1–20).
100 Terai (2012, pp. 297–308). Sullivan (2011, pp. 1–17).
101 Terai (2012). Zahar (2017).
102 Decision 1/CP.13, FCCC/CP/2 007/6/Add.1 (2007a, para 1.a.iii). Decision 2/CP.13, FCCC/CP/2007/6/Add.1 (2007b). Streck and Scholz (2006, pp. 861, 866). Takacs (2010, pp. 521–573). Schwarte (2010, pp. 55–81). Godden et al. (2010, p. 139). Boyd (2010, pp. 843–918).
103 Steinberg (2007, pp. 485–532).
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| 0 | PMC9734930 | NO-CC CODE | 2022-12-14 23:28:31 | no | Liverp Law Rev. 2022 Dec 5;:1-26 | utf-8 | Liverp Law Rev | 2,022 | 10.1007/s10991-022-09317-3 | oa_other |
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Mol Biol Rep
Mol Biol Rep
Molecular Biology Reports
0301-4851
1573-4978
Springer Netherlands Dordrecht
36462086
8133
10.1007/s11033-022-08133-2
Review
Picobirnaviruses in animals: a review
http://orcid.org/0000-0002-0026-866X
Reddy Mareddy Vineetha [email protected]
1
http://orcid.org/0000-0002-8104-3584
Gupta Vandana [email protected]
1
http://orcid.org/0000-0003-1794-086X
Nayak Anju [email protected]
1
Tiwari Sita Prasad [email protected]
2
1 grid.418821.6 0000 0004 6074 7966 Department of Veterinary Microbiology, College of Veterinary Science & Animal Husbandry, Nanaji Deshmukh Veterinary Science University, Jabalpur, M.P India
2 grid.418821.6 0000 0004 6074 7966 Nanaji Deshmukh Veterinary Science University, Jabalpur, M.P India
3 12 2022
113
2 9 2022
16 11 2022
© The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Picobirnaviruses (PBVs) are small non enveloped viruses with bi-segmented ds RNA. They have been observed in a wide variety of vertebrates, including mammals and birds with or without diarrhoea, as well as in sewage samples since its discovery (1988). The source of the viruses is uncertain. True hosts of PBVs and their role as primary pathogens or secondary opportunistic agents or innocuous viruses in the gut remains alien. The mechanisms by which they play a role in pathogenicity are still unclear based on the fact that they can be found in both symptomatic and asymptomatic cases. There is a need to determine their tropism since they have not only been associated with viral gastroenteritis but also been reported in the respiratory tracts of pigs. As zoonotic agents with diverse hosts, the importance of epidemiological and surveillance studies cannot be overstated. The segmented genome of PBV might pose a serious public health issue because of the possibility of continuous genetic reassortment. Aware of the growing attention being given to emerging RNA viruses, we reviewed the current knowledge on PBVs and described the current status of PBVs in animals.
Keywords
Picobirnavirus
Bi-segmented RNA
Prokaryotic virus
Opportunistic
Zoonotic potential
Emerging viruses
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pmcIntroduction
Worldwide, gastro-intestinal tract infections are recognized as a major public health issue, as well as one of the major challenges to the livestock industry and human population [1]. Diarrhoea is a common occurrence in all species of animals, and it can result from several factors, including nutritional imbalance, poor management, coccidia, chlamydiae, and viruses. The pathogen species or strains associated with two or more infectious agents may act synergistically and cause greater pathogenesis, increasing the overall disease burden on the host, this may be true both individually and collectively in a herd [2]. There are several causes for the emergence of enteric viruses, which account for over 100 viruses, including re-emerging, emerging, and novel pathogens that affect animals and/or humans at various stages of their lives. Acute gastroenteritis is caused by viruses such as enteric Coronaviruses, Bocavirus, Kobuvirus, Rotavirus as well as later recognized viruses such as Picobirnavirus (PBV) [3].
Discovery
Picobirnavirus (PBV) was accidentally discovered in Brazil in 1988 in faeces from the black footed pigmy rice rat (Oryzomys nigripes) [4] and human [5] as 2 bands/segments following polyacrylamide gel electrophoresis (PAGE). The large segment of the genome of rabbit PBV was first sequenced ten years after the virus’s discovery and recently, it has been suggested that PBV may exist as a quasispecies [6].
Taxonomy
Picobirnavirus is the only genus in the Picobirnaviridae family placed under the order “Diplornavirales”. The two species under the genus are Human Picobirnavirus (type species) and Rabbit Picobirnavirus (designated species) by the International Committee on Taxonomy of Viruses (ICTV) in 2008 [7]. The nomenclature of PBV is based on the structural characteristics of the virus: the prefix “Pico” (in Spanish) refers to the small size of the virion (35–40 nm in diameter) and “birna” (bi in Latin) due to the bi-segmented double stranded RNA (dsRNA) of the viral genome [8]. Monopartite genomes of PBV were also reported [9, 10]. It has been reported from the pooled serum samples of six horses. They found the presence of multiple divergent PBV large contigs of 4.2 kb containing both segment 1 and 2. Fused PBV genome (containing segments 1 and 2) was confirmed by nested PCR bridging segments 1 and 2. Upon sequencing, the result confirmed to be a junction between both segments 1 and 2. In addition to the fused genome, 3 complete copies of segment 2 and segment 1 each were also reported [10]. The heterogeneous nature of PBV can be attributed to its segmented genome and remarkable genome flexibility that includes frequent recombination among structural and non-structural genomic regions over long evolutionary timescales, lateral gene transfer among virus and host, gene gain and loss complex genome rearrangements [9].
Family: Picobirnaviridae.
Genus: Picobirnavirus.
Type species: Human Picobirnavirus.
Designated species: Rabbit Picobirnavirus.
Virion morphology
The virion is small, non-enveloped and spherical with a higher buoyant density in caesium chloride (CsCl) of 1.38 to 1.4 g/ml [11]. The first description of the icosahedral arrangement of the simple core capsid was made by Duquerroy et al. [12] using 3.4 A˚ resolution X-ray diffraction crystallography. In baculovirus expression studies, they demonstrated the structure of a rabbit PBV as virus like particles (VLPs) encoded by ORF (Open Reading Frame)-3 within segment 1. The coat protein has a 3-dimensional fold, composed of 60 two-fold symmetric dimers. According to their study, PBV is structurally unrelated to Birnaviruses with respect to host, virion size, capsids, RNA polymerase, genome size and organization. In vitro studies have demonstrated the ability of PBV particles to disrupt biological membranes, which indicates the evolution of animal cell invasion properties that result from its 120 subunits capsid. It appears that PBV either has a large genome profile (2.3–2.6 kbp and 1.5–1.9 kbp for segments1 and 2, respectively) or a small genome profile (1.75 and 1.55 kbp for larger and smaller segments, respectively) depending upon the migration pattern of the bisegmented dsRNA in PAGE experiments [7].
Viral genome
The total size of the genome is about 4.2 kb. The nucleotide composition is balanced with a GC content of 46.1%. The 5′ non- coding region is AU rich and the polyadenylation signal (AAUAAA) is absent, and the 5′ end five nucleotides, GUAAA are conserved in both genomic segments [13]. The gene segment-1 of Human PBV genogroup I strain Hy005102 (GenBank accession number AB186897), which is 2525 bp length consists of 2 or 3 open reading frames (ORFs), designated as ORF1, ORF2 and ORF3 from the 5′ end. The ORF 3 begins at position nt 828–830 and terminates at position nt 2484–2486, leaving position nt 2487–2525 untranslated fragments at the 3′ end. As a precursor to the major capsid protein, ORF3 encodes a 552 amino acid protein that undergoes catalytic cleavage to form it. ORF 2 which begins at position nt 157–159 and terminates at UGA position nt 829–831 thus encodes a protein (224 aa in length) of unknown function. The presence of ORF 1 is still in question. The termination codon (UGA) for ORF2 and the initiation codon (AUG) for ORF 3 in segment 1 are overlapped. The gene segment-2 of Human PBV genogroup I strain Hy005102 (GenBank accession number Ab186898) which is 1745 bp length, contains a single large ORF, which begins with AUG position nt 94–96 and terminates with UGA at position nt 1696–1698 which encodes for the RNA- dependent RNA polymerase (RdRp). In total 2 segments encode for a total of 3–4 proteins. RdRp forms a complex with the viral genome during encapsidation [14]. On the basis of the RdRp gene of prototype strains, there are two groups; 4-GA-91 (genogroup II) and 1-CHN-97(genogroup I) [15]. These genogroups contain PBV RdRp sequences that use standard genetic code for translation. The PBV RdRp catalyzes RNA synthesis. Most of the strains belonged to genogroup I and infect a wide range of host species compared to genogroup II. One putative genogroup III was identified in Picobirnaviruses [16] (Fig. 1).Fig. 1 Organization of genome of human PBV genogroup-I strain Hy005102. A There are three putative open reading frames (ORF) in gene segment-1 (GenBank accession number AB186897) of PBV strain Hy005102: ORF1, ORF2 and ORF3. The ORF3 codes for a precursor of the viral capsid protein (GenBank accession number AB186897). B Gene segment-2 of PBV strain Hy005102 contains a single ORF that encodes the viral RNA-dependent RNA polymerase (RdRp) (GenBank accession number AB186898) [13]
Viral genome of picobirnavirus in some species
Otarine Picobirnaviruses
The segment 1 of PF080915 strain is 2347 bp long with a GC content of 42.8%. The segment 2 is 1688 bp long with a GC content of 47.45%. 5′ non coding regions of both segments are AU rich. The segment 1 encodes for 2 ORFs while segment 2 encodes for 1 ORF. Segment 1 of strain PF080915 contain 40.9% GC content and 88 bases at 5′ non coding region and 71.4% GC content and 28 bases at 3′ non coding region. Segment 2 of strain PF080915 contain 28.3% GC content and 46 bases at 5′ non coding region and 46.5% GC content and 43 bases at 3′ non coding region [14].
Bovine Picobirnaviruses
Gene segment 2 of RUBV-P is 1758 bp long with AU rich untranslated 5′ region. 5′- (GUAAA) and 3′- (ACUGC) are conserved in end sequences of gene segment 2 of bovine strain [14].
Lapine Picobirnaviruses
The length of segment 1 of strain 35,227/89 is 2362 bp. There are 3 ORFs in the segment 1. Because of the presence of 2 stop codons at nucleotides 213–215 and 530–532 there might be 2 frame shifts taking place to produce 1 long protein from nucleotides 51 to 2312 [14].
Nomenclature
Typically, the PBV strain name starts with genogroup I or genogroup II, followed by PBV, host species, three letter country code, strain name and isolation year, separated by slashes [6]. Example: Ganesh et al. [13] reported the first incidence of detection and molecular characterization of Porcine PBV in faeces of domestic pigs from India using the human PBV genogroup I specific primer pair (PicoB25 + and PicoB43 −) is designated as genogroup I PBV/Pig/India/BG-Por-2/2010.
Diagnosis of picobirnavirus
Electron microscopy
The PBV’s structure may be visualized using electron microscopy. Viruses with an average diameter of 34 nm and uniform morphology were seen in clusters and as single viruses. Most of the particles were spherical with a smooth outline, and in many of them, there was a distinct core, which was narrowly separated from the outer rim. PBVs have an outer rim of about 3 nm thickness [11]. The detection of dsRNA bisegmented genomes based on PAGE (Polyacrylamide Gel Electrophoresis) and silver staining (S/S) is the mainstay of laboratory diagnosis since there is no animal model of infection or disease.
Poly acrylamide gel electrophoresis (PAGE)
Direct visualization of dsRNA can be done by PAGE in conjunction with silver staining. The use of PAGE for the detection of Rotavirus has continued long after commercial antigen detection assays were developed, during the time Picobirnaviruses were accidentally discovered. PAGE and S/S are reliable tests for the detection of PBV since they are simple, economic, fast, and based on the electrophoretic mobility of the viral genomic segments and allow for the differentiation of strains. The PAGE and S/S tests can be used to detect PBV, but since large amounts of viral load are required to visualize the viral genome of PBV, they are relatively insensitive [6, 12]. PBV-positive samples were invariably negative in PAGE once they had been frozen and thawed numerous times, probably because the virus is labile [11].
PAGE and S/S has been used by many researchers for detection of PBV in clinical samples. Correct position of PBV segments can be assessed by comparison with migratory pattern of segments of group A Rotavirus on PAGE. Ghosh et al. reported the presence of PBV (RUBV-P) from a calf via PAGE and noticed that larger segment of PBV appeared to be slightly larger than the segment 2 (VP2 gene) (2684 bp) of rotavirus strain DS-I, while the smaller band of PBV (1.5–1.9 kbp) of RUBV-P appeared between segment 4 (VP4) (2328 bp) and segment 5 (NSP1) (1461 bp) genes of rotavirus strain DS-I [17]. Malik et al. detected the presence of PBV via PAGE and found larger band of PBV paralleled segment 2 of rotavirus with size of 2.6 kbp, while smaller band of PBV migrated closer to segment 5 of rotavirus (size 1.6 kbp) [18].
A study conducted by Ludert and Liprandi, among children with diarrhoea showed the presence of 3 bands (2.92, 2.37, 1.32 kbp) in PAGE analysis and named it “Picotrirnavirus” [19].”. The studies conducted in chicken [20, 21] and dogs in Brazil [22, 23] also reported the presence of Picotrirnavirus. Although it is unclear if these strains are new viral entities with three dsRNA genomic segments or represent a mixed infection with multiple strains [13]. In many studies, researchers have noticed that PBV segments were not detectable by PAGE and S/S but detected by RT-PCR. Periera et al. (Brazil) [24] and Ludert and Liprandi (Venezuela) [19] noticed very low frequency of PBV detection by PAGE suggesting that the dsRNA concentration of the tested sample was below the detection limit of the applied PAGE- S/S, which is plausible given the fact that PAGE is poorly (≈ 100-fold less) sensitive than RT-PCR and detects only dsRNA viruses present with high viral load.
Reverse transcriptase polymerase chain reaction (RT-PCR)
Molecular based test like RT-PCR gained importance in detection for cloning and sequencing of the genome because of the poor sensitivity of PAGE and S/S. The frequency of PBV detection was increased with the usage of RT-PCR amplification techniques and sequencing. Carruyo et al. [25] noticed a PBV detection rate of 60% using RT-PCR which is very high in comparison to PAGE which showed a detection rate of only 27%. Martinez et al. [26] in 2010 also observed similar results i.e., higher detection rates of PBV by RT-PCR than PAGE.
To detect the PBVs, PCR amplification strategies based on single and double primers are used. A single amplification strategy created by Lambden et al. [27] uses, viral RNA and oligonucleotide as a matrix and an adapter, respectively. Viral RNA is then ligated with an oligonucleotide and a complementary adapter primer is used for the cDNA synthesis [17]; Boros et al. [28] used this strategy in their studies. This strategy is further modified by Wakuda et al. [29] to prepare a full-length cDNA of Human PBV genome (strain Hy005102). This strategy is generally used for characterization of full length PBV genome segments. The second strategy of specific amplification uses a pair of primers selected for RdRp gene of the segment 2 of PBV (RT-PCR) assay.
The primers developed by Rosen et al. were widely used for characterization of human PBV and some PBV strains of animals [30]. Narrow specificity of primers restricted the recognition of all circulating PBV strains of human and animals [25] and also failed in amplifying many PBV strains from human and animal species which were earlier detected positive through PAGE and S/S [31]. In order to enhance specificity Malik et al. [32] later developed a primer sequence for the detection of the sequences of genomic segments of PBV (Table 1).Table 1 Primer sequences used for RT-PCR detection of PBV
Primer Genogroup and strain Polarity Nucleotides Sequence
PicoB23 Genogroup II (4-GA-91) + 685–699 CGG TAT GGA TGT TTC [30]
PicoB24 Genogroup II(4-GA-91) − 1039–1053 AAG CGA GCC CAT GTA [30]
PicoB25 Genogroup I(1-CHN-97) + 665–679 TGG TGT GGA TGT TTC [30]
PicoB43 Genogroup I(1-CHN-97) − 850–865 A(GA)T G(CT)T GGT CGA ACT T [30]
PBV-7F Genogroup I(GPBV10) + 754–771 GCN TGG GTT AGC ATG GA [32]
PBV-7R Genogroup I(GPBV10) − 1028–1011 CAY GGN ATG GSA TSB GG [32]
In PAGE-S/S, both genomic profiles (small and large) were found, but only the large profiles were successfully amplified by RT-PCR using the primer pair PicoB25+ and PicoB43- [30]. PBV with a large genome profile was detected most frequently in diarrhoeic sample suggesting that in calves diarrhoea was associated with large genome profile [8].
Metaviromic approaches
The development of bioinformatic tools for sequence analysis and advancement in sequencing techniques have changed the approach to studying viruses. Increasingly, viral metagenomics is being accepted as a method for characterizing viral sequences that is unbiased. By using metaviromics, it is possible to identify viral genomes from samples containing a single or very low number of viral species efficiently and straightforwardly regardless of the presence of non-viral background sequences. There have been many authors who have used this approach [33] [34] [35] [36]. Novel PBV sequences were found from clinical and environmental samples through this approach.
Xiao et al. [33] used metaviromic analysis and investigated faecal, oral, blood and skin samples form 10 lab rabbits. Picobirnavirus was detected from faecal sample, along with other viruses viz., Polyomaviridae, Parvoviridae and Microviridae. Ramesh et al. [34] performed metagenomic next-generation sequencing on 9 swine slurry and 3 environmental samples from a USA farm operation and identified novel viruses. They discovered a total of 1792 viral genome, of which 554 were novel. Among the 1637 Picobirnavirus genome segments, 538 were found to be novel. A total of 638 RdRp and 1033 capsid segments greater than 1 KB were assembled across all 9 slurry samples but no viral genomes would be assembled from the farm environment samples. On phylogenetic analysis of all complete RdRp segments (354/638) identified in this study and all complete PBV genomes from NCBI indicates PBV’s are highly diverse and belongs to GGI and GGII [34]. Chauhan et al. [35] investigated the diversity of oral RNA virome from 3 samples of backyard swine oral secretion, using total viral RNA extraction followed by deep sequencing using Illumina HiSeqX. The assembled nucleotide sequences were analysed using the PhyML phylogenetic tree. Sequence analysis identified a high diversity of swine enteric viruses in the saliva samples obtained from backyard wine farm 2 and 3 while only few viruses were identified from farm 1. On characterization of viruses in saliva samples of South African backyard swine, found the presence of multiple PBV species viz., Dog PBV, chicken PBV, Green monkey PBV, Roe deer PBV and Feline PBV suggested the possible interactions of the backyard swine with other wild and domestic animal species [35]. Lojkic et al. (2016) evaluated the faecal virome of juvenile and adult foxes from peri urban areas in central Croatia, and found the presence of fox picobirnavirus and parvovirus. Fox Picobirnaviruses were closely related to porcine and human picobirnavirus than to known fox PBV [36].
Various authors detected the presence of PBV in samples using PAGE-S/S, RT- PCR (Table 2) and metaviromics. As PBV is not isolated yet, these methods provide the only way of detecting its presence in samples. The primers mentioned in Table 1 have been used by various authors to detect PBV from different species of animals. If seeking for PBV in a particular clinical sample, then using a targeted approach would be a better option. Since Picobirnaviruses have flexible segmented genome, it can undergo genetic reassortment, it also has broad host range allowing for genetic recombination between host and viral genome; thereby, leading to the emergence of novel PBV which may or may not be detectable by published primers. The detection of novel PBVs can therefore be made more reliable through metaviromics.Table 2 Detection of PBV in domestic animals by PAGE, RT- PCR and Sequence Analysis
Year of publication Authors PAGE % Positive in PAGE RT-PCR % Positive in RT-PCR Sequence Analysis
Porcine
1989 Gatti et al ✔ 106/912 = 11.6% - - NA
1990 Chasey et al ✔ - - - NA
1991 Ludert et al ✔ 27/244 = 11.1% - - NA
1993 Alfieri et al ✔ 5/75 = 6.7% - - NA
1996 Pongsuwanna et al ✔ 2/557 = 0.4% - - NA
2008 Banyai et al ✔ 2/20 = 10% ✔ 13/20 = 65% ✔
2009 Carruyo et al ✔ 39/144 = 27% ✔ 87/144 = 60.4% ✔
2010 Martinez et al ✔ 56/265 = 21.1% ✔ - ✔
2010 Giordano et al ✔ 19/64 = 30% ✔ 6/19 = 32% ✔
2011 Smits et al NA - ✔ 16/60 = 27% for GG I
4/60 = for GG II
3/60 = 5% for both GGI & GG II
✔
2012 Ganesh et al ✔ 2/11 = 18.2% ✔ 2/11 = 18.2% ✔
2014 Banyai et al NA - ✔ 1/1 = 100% ✔
2014 Chen et al NA - ✔ 39/187 = 20.9% ✔
2016 Wilburn et al NA - ✔ 112/380 = 29.4% ✔
2019 Kylla et al ✔ 2/457 = 0.4% ✔ - NA
2020 Joycelyn et al NA - ✔ 49/65 = 75.38% ✔
Bovine calves
1989 Vanopdenbosch and Wellemans ✔ - NA - NA
1991 Villacorta et al ✔ - NA - NA
1997 Chandra ✔ - NA - NA
2003 Buzinaro et al ✔ 4/576 = 0.69% NA - NA
2003 Novikova et al ✔ - - - NA
2009 Ghosh et al ✔ 1/78 = 0.01% ✔ 1/1 = 100% ✔
2011 Malik et al ✔ 5/136 = 3.67% NA - NA
2013 Malik et al ✔ - ✔ 1/1 = 100% ✔
2013 Mondal et al ✔ 4/113 = 3.53% NA - NA
2014 Mondal and Joardar ✔ 2/89 = 2.25% ✔ 2/2 = 100% NA
2014 Malik et al NA - ✔ 1/1 = 100% ✔
2016 Takiuchi et al ✔ 24/289 = 8.30% ✔ 15/24 = 62.5% ✔
2018 Navarro et al NA - ✔ 18/77 = 23.4% ✔
2018 Prasad et al ✔ ✔ 52/408 = 13% NA
2019 Woo et al NA - ✔ 3/51 = 5.9% for GG I
1/51 = 1.9% for GG II
✔
2021 Nazaktabar et al ✔ 5/485 = 1% ✔ 5/5 = 100% ✔
2021 Huaman et al - - - - -
2022 Atasoy et al NA - ✔ 9/127 = 7.08% ✔
Foals (Equine)
1991 Browning et al ✔ - NA - NA
2011 Ganesh et al ✔ 0/7 = 0% ✔ 1/7 = 14.3% ✔
Lambs (Ovine)
1996 Munoz et al ✔ - ✔ - ✔
2018 Kunz et al ✔ 5/100 = 5% ✔ 62/100 = 62% ✔
Lambs and kids (Ovine and caprine)
2018 Malik et al NA - ✔ 143/400 = 35.75% ✔
Birds (Chicken) and turkeys
1989 Alfieri et al ✔ 17/120 = 14.2% - - NA
1990 Leite et al ✔ 44/257 = 17.1% - - NA
1991 Monteiro et al ✔ - - - NA
2003 Tamehiro et al ✔ 13/378 = 3.4% - - NA
2010 Day et al NA - - - ✔
2012 Bezerra et al ✔ - ✔ - ✔
2014 Silva et al ✔ 13/85 = 15.3% ✔ 42/85 = 49.4% ✔
2018 Pankovics et al NA - - - ✔
2019 Ribeiro et al ✔ 3/85 = 3.5% ✔ 10/85 = 11.76% ✔
Dogs (Canine)
2001 Volotao et al ✔ 5/1041 = 0.48% - - NA
2004 Costa et al ✔ 3/163 = 1.84% - - NA
2009 Fregolente et al ✔ 3/349 = 0.85% ✔ 2/349 = 0.6% ✔
2017 Navarro et al NA - ✔ 1/42 = 2.3% ✔
✔ = Attempted, NA Not attempted
Molecular characaterization of PBV from different animals
Porcine
The molecular characterization of picobirnavirus is done by subjecting the suspected picobirnavirus samples to RNA-PAGE, RT-PCR targeting RdRp gene of segment II and whole genome analysis. The inability to grow/isolate PBV in any cell culture or animal model leaves us with no other option than going for PAGE and RT-PCR. However, the genetic diversity found among PBV strains in a single animal suggest that PBV exists as quasispecies. Banyai et al. [37] screened 20 intestinal samples from weaned pigs via PAGE & S/S and RT-PCR which yielded positive results of 2/20 and 13/20 for PBV, respectively suggesting that RT-PCR is sensitive compared to PAGE. Six of thirteen positive RT-PCR samples on cloning revealed that most belonged to genogroup I PBVs and also found genetic relatedness between a porcine PBV to a Hungarian human PBV strain suggesting the genetic diversity found among PBV strains in the pig intestinal tract. Carruyo et al. [25] reported the partial and molecular characterization of genomic segment-2 from porcine isolates. On phylogenetic analysis they found that these porcine isolates were more closely related (78.5%) to human PBV belonging to genogroup I. Stool samples from 7 to 56-day age was collected and subjected to PAGE which showed the prevalence of 10–12%. They developed a specific RT-PCR assay for detection of virus in faeces of porcine. Over the period of 5 years, Martinez et al. [26] in 2010 conducted a study on porcine PBV and determined the prevalence from 265 faecal samples from animals which were grouped based on the physiological status and age. Additional 103 samples collected from follow up studies which were subjected to PAGE & S/S and RT-PCR analysis and concluded that PBV establishes persistent infection with periods of silence and interspersed with periods of low and high viral excretion. High and low PBV excretion levels were detected by PAGE and RT-PCR, respectively. Giordano et al. [38] conducted a study on faecal specimens collected from humans and piglets via RT-PCR which showed that 14 out of 74 samples were positive for PBV. An analysis of phylogenetic relationship revealed similarities between human and porcine PBV strains collected in Argentina, as well as genetic diversity among human and porcine PBV strains from other countries. Presence of closely related human and porcine PBV strains suggests interspecies transmission. Smits et al. [39] in 2011 detected PBV from respiratory tracts of pigs and identified both genogroup I and II explaining the PBV diversity and tropism. The genetic relationship between porcine respiratory and human enteric PBV suggest cross species transmission between pigs and human implying zoonotic aspect of PBV. First reported case study on Porcine PBV from India was conducted by Ganesh et al. [13] in which 11 faecal samples collected from pigs of different ages were screened for porcine PBV by PAGE & S/S (2/11) and RT-PCR (2/11). On sequence and phylogenetic analysis showed close genetic relatedness between human, porcine as well as murine PBV strains which is in agreement with the findings of Carruyo et al. [25] and Giardano et al. [38]. Chen et al. [40] studied around 187 stool samples from pig over the period of 8 months. Thirty nine out of 187 (20.9%) samples were positive for PBV by RT-PCR, and among the positive samples 84.6% belonged to genogroup I, 38.5% came from genogroup II, rest 23.1% had both genogroup I and II. Nineteen and eleven representative strains from genogroup I and genogroup II, respectively were analyzed phylogenetically which suggested the prevalence of multiple PBV from pigs in China. Wilburn et al. (2016) [41] determined the prevalence and genetic diversity of porcine PBV by studying 380 faecal samples from both diarrhoeic and non-diarrhoeic piglets. PBV was detected in 86 of 265 (32.5%) diarrhoeic and 26 of 115 (22.6%) non-diarrhoeic piglets using RT-PCR for RdRp gene. All these strains show high similarity between them and were also closely related to genogroup I PBV Chinese porcine strain. They concluded that PBV infection is seen irrespective of diarrhoea in faecal samples of piglets. Some researchers like Kylla et al. [2] concluded that PBV coinfects with Salmonella Typhimurium causing piglet diarrhoea. They collected a total of 457 fresh faecal samples from organised (225) and unorganised (232) pig farms from different regions of Northeast region of India and screened them using PAGE & S/S and RT-PCR and noticed higher prevalence of coinfection from unorganised farms and crossbred pigs compared to organised farm and local indigenous pigs with higher detection in summer.
Bovine
The very first report of PBV came from Brazil in 2003 where Buzinaro and coworker [42] while screening for the presence of Rotavirus using PAGE from diarrhoeic and non diarrhoeic faecal samples from calves of age 1–45 days reported the occurrence of bisegmented genome suggesting the presence of PBV. Ghosh et al. [17] reported the presence of bovine genogroup I strain from a month-old diarrhoeic calf on molecular characterization. On sequence and phylogenetic analysis of gene segment 2 revealed low nucleotide identities (51.2–64.9%) with and distant genetic relatedness to other genogroup I suggesting that bovine strain RUBV-P might be different from genogroup I of human and other animals. Over a period of 3 years, Malik et al. in 2011 [43] screened a total of 136 faecal samples for the presence of PBV in buffalo and cattle calves by RNA PAGE. PAGE analysis confirmed 3.67% (5/136) positivity for PBV, suggesting the presence of sporadic infection of PBV in bovine calves. For the first time from western India PBV was reported in 2013 in cattle and buffalo. A total of 113 diarrhoeic faecal samples were screened for the presence of Rotavirus via PAGE during which they also found PBV in four samples [44]. Malik et al. [18] reported the presence of genogroup I of PBV from faecal samples of buffalo. A sequence analysis revealed 44.5% and 45.1% homology, respectively between the human PBV prototype from China and bovine PBV prototype from India. A unique PBV isolate from buffalo showed a separate lineage from genogroup I and genogroup II PBV sequences suggesting the emergence of new heterogenous group of viruses with a distinct lineage. Mondal and Jaordar [45] screened 89 diarrhoeic faecal samples from cattle calves in West Bengal and found 2/89 (2.25%) positive for PBV using both PAGE and RT-PCR and both the samples belonged to genogroup I. Considering the fact that genogroup II is uncommon, first report of genogroup II of PBV strains in a diarrhoeic bovine calf was done by Malik et al. [15]. Takiuchi et al. [8] screened a total of 289 faecal samples using PAGE and found 24 samples positive for PBV. Among these 24 positive PBV samples, 5 showed small electrophoretic profile which was the first detection of small genome profile of PBV like strains in bovine. Based on phylogenetic analysis the bovine strain identified in Turkey had an 81% nucleotide identity with the bovine strain identified in Turkey. Prasad et al. [46] detected presence of PBV in 52 samples out of 408 diarrhoeic buffalo calf faecal samples, all belonging to genogroup I using RT-PCR and PAGE. None of the samples were positive for genogroup II. Navarro et al. [47] analyzed 77 diarrhoeic and non diarrhoeic faecal samples from bovine in Brazil and found 18/77 = 23.4% positive for genogroup I of PBV using RT-PCR. On phylogenetic analysis high diversity among the sequences were reported at nucleotide level revealing heterogenous phylogenetic clustering profiles. Nazaktabar [48] in 2021 reported the presence of PBV in bovine diarrhoeic faecal samples from Iran. A total of 485 stool samples collected from 1 month old diarrhoeic calves, were subjected to PAGE and RT-PCR. Out of which only 5 samples were positive in PAGE (1%). Nazaktabar-14 strain phylogenetic analysis showed a low similarity with bovine PBV sequences and closer relationship with isolates from other hosts. This is the first report on PBV occurrence in Iran. From Australia, Huaman et al. [49] in 2021 detected the presence of genogroup I and genogroup II of PBV from respiratory tract of wild deer and cattle. They screened for the presence of RdRp gene of segment 2 of PBV in various samples like serum, faeces, spleen, lung, nasal swabs and trachea collected from cattle and wild deer. The presence of PBV in respiratory tract addresses the question regarding its tropism and pathogenicity. Atasoy et al. [50] investigated the frequency of bovine rotavirus (BRV) and bovine coronavirus (BCoV) and PBV in causing gastro enteritis in young calves associated with diarrhoea. Out of 127 diarrhoeic bovine faecal samples screened for 3 viruses, BRV and BCoV had the frequency of 38.58% and 29.92%, respectively whereas 7.08% of bovine calf samples were positive for genogroup I. Sequence analysis of PBV revealed high genetic heterogeneity.
Broiler
The occurrence of PBV dsRNA was detected in chickens from 2 to 7-week-old showing pasty consistency of faecal material Tamehiro et al. [51] screened a total of 378 faecal samples from broiler chicken aged 1–7 weeks using PAGE. They found characteristic migration profile of dsRNA of avian rotavirus (AvRV), reovirus (Arv) and PBV in 32 (8.5%), 7(1.8%) and 13(3.4%) samples, respectively. Silva et al. [52] reported the first gene sequence of avian PBV in Brazilian broiler chickens. Sequencing of these strains demonstrated a considerable RdRp gene heterogeneity that ranged from 56.1 to 100% at the nucleotide level compared with prototypes of different species and water sewage and from 50.3 to 100% among themselves. Around 85 samples were collected and analyzed by PAGE and RT-PCR which showed a positivity of 15.3% (13/85) by PAGE and 49.4% (42/85) by RT-PCR. A novel picobirnavirus was detected in a cloacal sample from broiler breeder chicken by Pankovics et al. [53] using viral metagenomics and molecular techniques. Segment 1 of chicken PBV genome showed low amino acid sequence identity to the corresponding proteins of marmot and dromedary PBV, whereas segment 2 showed higher amino acid sequence identity to a wolf PBV protein sequence. Ribeiro et al. [54] were first to report the presence of PBV -2 in birds which showed high genetic similarity from the isolates obtained from Korea and high diversity was reported with other species of animals (swine, humans, cattle, nonhuman primates). They analyzed 85 samples from chicken faeces, for the presence of PBV using RT-PCR (RdRp) and PAGE followed by sequencing. Out of 85 samples PBV was detected in 10 samples (11.76%) and only 3 samples were positive by PAGE. Seven out of 10 samples were sequenced and analyzed phylogenetically.
Turkey
Day and Zsak [55] developed a diagnostic assay which targets RdRp gene of novel turkey-origin PBV and produces 1135 bp amplicon, on phylogenetic analysis of Turkey PBV, suggested that it is unique because it does not group closely with the recognized PBV circulating in mammalian hosts.
Canine and feline
Costa et al. [23] in 2004 reported the detection of PBV in faecal samples from Rio de Janeiro, Brazil. They collected 163 diarrhoeic faecal samples from dog and 3 samples were positive for PBV by PAGE. Navarro et al. [56] reported molecular characterization of complete genomic segment 2 of PBV strains of cat (K40) and dog (RVC7) on the Caribbean Island of St. Kitts, using non-specific primer-based amplification method and stated that the strains exhibited a high genetic similarity among themselves and between PBVs from other hosts. PBV strain detected in cats and dogs were characterized molecularly for the complete genomic segment-2 and was reported for the first time.
Small ruminant population
Kunz et al. [57] reported the detection of partial RdRp gene in 100 faecal samples in meat sheep flock from southern Brazil. 62% were found to be positive for PBV by RT- PCR, which showed high genetic variability within the same flock. Malik et al. in 2018 [58] screened 400 faecal samples of small ruminant population (ovine and caprine) in India via RT- PCR assay and found that 143 samples (35.75%) were positive for PBV. Out of 143, 83 belonged to caprine and 60 belonged to ovine. On genogrouping found 38.47% belonged to genogroup I, 3.49% belonged to genogroup II and 38.47% belonged to both genogroup I and genogroup II.
Others
Woo et al. [59] discovered a novel otariine PBV from faecal samples of California sea lions [59]. Yinda et al. [60] in 2018 identified PBV from fruit bats using an alternate mitochondrial genetic code. This was the first report about PBV like sequences in bats. Junior et al. [61] detected the PBV in 1/23 (4.34%) faecal samples from wild birds which belonged to genogroup I of PBV from Brazil. Their findings also reported the circulation of Rotavirus A, Rotavirus D, Rotavirus F, Rotavirus G and PBV suggesting the possible interspecies transmission. Kleyman et al. [62] detected genogroup I PBV in 29 out of 82 (35.3%) non diarrhoeic faecal samples from small Indian mongoose and identified novel RdRp gene sequence that uses alternate mitochondrial code for translation.
Host diversity of PBV
Picobirnaviruses have been detected from prokaryotic and eukaryotic organisms. Moreover, the presence of ribosomal binding site (RBS) sequences in the PBV gene segment, which is generally found in viruses that infect prokaryotes suggest wide host range of PBV.
Picobirnavirus Might be a prokaryotic virus
The Shine-Dalgarno sequence/ Ribosomal binding site sequences which is a conserved hexamer (AGGAGG) or their subsets (4-, 5-, or 6-mer of AGGAGG), has been identified upstream of putative ORF/s in PBV gene segment-1 and -2 sequences, which has a classically defined prokaryotic motif. It has been shown that a number of viruses that infect prokaryotes contain a high proportion of RBS sequences example Cystoviridae having segmented dsRNA genome. Sequences of PBV obtained from animals, humans, and environmental samples have been found to contain the conserved RBS sequence. PBVs showed a higher degree of enrichment for RBS sequences than any other known prokaryotic viral family, suggesting PBVs as prokaryotic viruses. It has been hypothesized that PBVs may have a greater tendency of infecting bacteria having highly conserved RBS sequences for their own genes [14].
To date, PBVs have not been propagated successfully in eukaryotic cell cultures, supporting the hypothesis on prokaryotic hosts. It does not preclude the possibility that PBVs are animal viruses despite the absence of cell culture platform. When attempts were made to grow PBVs in prokaryotic cells by inoculating it into brain heart infusion broth no amplification of PBV through RT-qPCR assays was noticed, even after the culture was grown at both aerobic and anaerobic conditions for 2 weeks. The same study demonstrated the in vivo functionality of RBS-containing segments of PBV segment-1 in Escherichia coli using recombinant segments tagged with 6xHis. Additionally, viral RNA has been identified in faeces from several animal species and in persistent faecal shedding by asymptomatic animals, suggesting that PBVs are prokaryotic viruses inhabiting the gut microbiome [28].
Picobirnavirus might be a mitovirus
Mitoviruses generally consist of plus stranded RNA virus-like elements that replicate within the mitochondria of fungus. The viral genome of mitoviruses contains a single long ORF which codes for a protein having conserved motifs of RdRp gene from virus. Analysis of Cameroonian PBV- like sequences revealed mitochondria like genetic code, which was needed to translate the RdRp, absence of PBV like capsid and clustering of these sequences with mitoviruses. The event of these PBV like arrangements without an evident capsid is suggestive to that of mitoviruses [60]. The phylogenetic analysis of viral RdRp sequences from a myriapod, bat and mongoose that makes use of alternate genetic code for translation clustered independently from the PBVs using standard genetic code for translation. Based on all the points discussed PBV’s might actually invade the gut microbiome of mammals rather than the cells of mammals themselves [63].
Picobirnavirus is a protozoan virus?
Human faecal samples containing cryptosporidium oocysts also revealed the presence of atypical PBV. They are probably Cryptosporidia viruses or PBV that replicate more easily with Cryptosporidia present [64].
Evidence of viral persistence
Shedding of PBV in faeces was studied using RNA-PAGE experiments or RT-PCR. Haga et al. in 1999 [65] mentioned that there is a prolonged period of virus shedding in three giant anteaters (Myrmecophaga tridactyla) in captivity in Brazilian zoo and claimed that adult animals infected with PBV could be asymptomatic carriers persistently infected, serving as reservoirs of infection. They stated that prolonged virus shedding with chronic infection was the consequence of persistent virus infection and not the result of re-infections in the affected animals. Masachessi et al. [66] in 2007 observed that there was PBV shedding for prolonged periods in animal excreta where Armadillos shed PBV for at least 6 months, and Orangutans shed PBV for 7 months using RNA- PAGE. Martinez et al. [26] in 2010 conducted a follow up study on pigs of different age groups and physiological status. In the early first week after weaning, PAGE and silver staining (PAGE S/S) negative samples were positive by RT-PCR, and two months later PAGE S/S also detected the virus. RT-PCR detected PBV excretion sporadically, followed by almost six months with no virus detection by PAGE S/S, occasionally detected by RT-PCR.
In addition to RT-PCR, PAGE-S/S could also be used to identify virus during 1st gestation and farrowing period which correspond to the virus excretion period. The pattern of PBV excretion was continuous during this period. PBV excretion followed a similar pattern in the third and fourth reproductive cycles, although positive samples were only detected by RT-PCR, suggesting that lower viral loads were shed than during the first cycle. They finally stated that PBV establishes a persistent infection in the host with periods of silence intermingled with periods of low and high viral excretion. Periods of silence may be because of production of some antibody levels. Stress caused by pig farming practices or physiological stress conditions such as lactation and farrowing results in the production of cortisol, which affects the lymphoid cells and reduces the lymphocyte proliferation which in turn decreases the antibody formation. Hence, the resistance to infection is decreased leading to shedding of PBV. This probably suggests the association between excretion levels of virus and immunosuppression or a particular physiological status of the animal. These findings suggest that it is possible to acquire PBV infection early in life and then establish a persistent infection, with periods of high viral activity interspersed with periods of silence.
Pathogenicity
Although some scientists have attempted to associate picobirnavirus with manifestations of gastroenteritis, its pathogenicity is still not well defined since picobirnavirus have been identified in both normal and diarrhoeic animals. Gatti et al. [67] in 1989 stated that PBVs are more frequently found in diarrhoeic animals while Ludert et al. [68] in 1991 stated similar proportions of PBV detection in diarrhoeic and healthy animals.
Zoonotic potential
Banyai et al. [37] (Europe) and Carruyo et al. [27] (Latin America) detected and sequenced genogroup I PBVs from pigs and noticed close relationship to human genogroup I PBVs. Equine strains which were detected followed by sequencing from faeces of domestic foals in Kolkata, India [69] revealed close relationship with human strains [31] and PBV strains of environmental samples from USA [70]. Similarly, the PBVs detected from diarrhoeic children in an urban slum in Kolkata, India showed genetic relatedness to porcine PBV strain reported from Hungary, Venezuela and Argentina. Genetic relatedness between human PBV strains and strains isolated from foxes [36] and also genetic similarity between PBV isolated from human and bats were also reported. Yinda et al. [60] stated that hunting and eating of bats in Cameroon might be the cause of zoonotic transmission of PBVs to human. These findings suggest the mark of zoonotic nature of PBV infections.
Interspecies transmission
Viruses with segmented genomes are potential candidates for segment reassortment, thus explaining the heterogeneity of their genomes [37]. Through evolution, PBVs acquired the capability of interspecies transmission through genetic reassortment which could result to the emergence of virulent progeny [71]. As a result of this reassortment of segments of their genomes, multiple PBVs from different species may simultaneously infect a single cell [72]. Mutation, recombination, genome segment reassortment and combination of these molecular events might lead to viral emergence. Hence, they pose a serious threat to humans and animals.
Conclusion
Picobirnaviruses have been detected in faeces of diarrhoeic and free-living healthy animals, sewage water and broad range of zoo animals and wild birds and not only alimentary tract harbors the PBV but has also been reported from the respiratory tract of wild deer and cattle, suggesting its ubiquitous distribution. The exact role of PBV’s in causing gastroenteritis is still not fully understood as we are not able to cultivate/isolate the PBV in any cell culture or any animal model, thus impeding virus isolation and its clinical and pathological studies. There are convincing arguments provided by the various authors suggesting the PBV infecting prokaryotic cells, but this assumption remains hypothetical unless a host system is identified for PBV propagation. There are findings which suggest a close genetic relatedness between PBVs from different species, which implies the zoonotic aspect of picobirnavirus. Considering the fact, that PBV have segmented genome makes them the potential candidate to undergo genetic reassortment and become potentially more pathogenic, keeping these facts under consideration it is utmost important to have the continuous monitoring of circulating strains from different species and to develop a model for isolation of this virus.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Research involving human and animals rights
This article does not contain any studies with human participants or animals performed by any of the authors.
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45. Mondal A Joardar SN Detection of genogroup I picobirnavirus in diarrhoeic faecal samples of calves from West Bengal, India J Immunol Immunopathol 2014 16 40 43 10.5958/0973-9149.2014.01076.4
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53. Pankovics P Boros Á Nemes C Kapusinszky B Delwart E Reuter G Molecular characterization of a novel Picobirnavirus in a chicken Adv Virol 2018 163 12 3455 3458
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| 36462086 | PMC9734933 | NO-CC CODE | 2022-12-14 23:28:31 | no | Mol Biol Rep. 2022 Dec 3;:1-13 | utf-8 | Mol Biol Rep | 2,022 | 10.1007/s11033-022-08133-2 | oa_other |
==== Front
Nat Rev Cancer
Nat Rev Cancer
Nature Reviews. Cancer
1474-175X
1474-1768
Nature Publishing Group UK London
536
10.1038/s41568-022-00536-4
Review Article
Biology, vulnerabilities and clinical applications of circulating tumour cells
Ring Alexander 12
Nguyen-Sträuli Bich Doan 13
http://orcid.org/0000-0002-2924-8080
Wicki Andreas 2
http://orcid.org/0000-0001-9579-6918
Aceto Nicola [email protected]
1
1 grid.5801.c 0000 0001 2156 2780 Department of Biology, Institute for Molecular Health Sciences, ETH Zurich, Zurich, Switzerland
2 grid.412004.3 0000 0004 0478 9977 Department of Medical Oncology and Hematology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
3 grid.412004.3 0000 0004 0478 9977 Department of Gynecology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
9 12 2022
117
7 11 2022
© Springer Nature Limited 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
In recent years, exceptional technological advances have enabled the identification and interrogation of rare circulating tumour cells (CTCs) from blood samples of patients, leading to new fields of research and fostering the promise for paradigm-changing, liquid biopsy-based clinical applications. Analysis of CTCs has revealed distinct biological phenotypes, including the presence of CTC clusters and the interaction between CTCs and immune or stromal cells, impacting metastasis formation and providing new insights into cancer vulnerabilities. Here we review the progress made in understanding biological features of CTCs and provide insight into exploiting these developments to design future clinical tools for improving the diagnosis and treatment of cancer.
As well-established players in the metastatic cascade, circulating tumour cells (CTCs) hold promise for improved cancer diagnosis and disease monitoring. In this Review, Ring et al. overview the current understanding of CTC biology, highlighting specific opportunities and vulnerabilities for future CTC-focused therapies.
Subject terms
Metastasis
Tumour biomarkers
==== Body
pmcIntroduction
Despite advances in cancer research and treatment, metastasis remains the leading cause of cancer-related death worldwide1. The limitation of current clinical diagnostic tools to predict metastatic progression and detect minimal residual disease is a major hurdle to improve outcomes. Standard-of-care (SOC) approaches such as tissue biopsies, imaging modalities and tumour markers are often limited in their ability to capture all relevant aspects of a patient’s cancer due to insufficient diagnostic thresholds, sampling bias related to temporal and spatial tumour heterogeneity, and limited access to metastatic lesions2,3.
Blood-based tumour-derived materials provide an alternative, real-time and minimally invasive method for early detection, prognosis and prediction of response to anticancer agents4,5. Among the most intriguing liquid analytes are circulating tumour cells (CTCs), which are shed from primary and/or metastatic tumours into the bloodstream to eventually seed metastases at distant sites. As pioneers of the metastatic process, CTCs are extraordinary cells that offer an opportunity to capture and interrogate the most aggressive cancer clones, providing a privileged insight into the biology and vulnerabilities of blood-borne metastasis5,6.
An entire research field dedicated to the investigation of CTCs as a liquid biopsy analyte has produced remarkable progress and led to the translational implementation of CTCs as biomarkers in the setting of clinical trials7,8. However, despite scientific advances and technological innovations, the rare nature of CTCs poses considerable challenges, and as a consequence, their use in routine clinical practice has been slow5,9–12. Moving use of CTCs forward to realize their full potential as a highly accurate and predictive tool for antimetastatic therapies has both opportunities and challenges.
Here we provide a current and comprehensive overview of state-of-the-art developments in this dynamic field, with a focus on the role of CTCs in blood-borne metastasis. We describe various aspects influencing the metastatic potential of CTCs, including the formation of homotypic (cancer cells only) and heterotypic (cancer cells together with immune or stromal cells) clusters. We further review current technologies for CTC detection, capture and downstream analysis. Clinical translational aspects are discussed in reference to current and future trials aimed at targeting CTCs. Finally, we highlight key challenges and necessary research priorities to foster translational applications.
Progression of CTCs to metastasis
Patterns of metastatic cancer dissemination
Metastasis occurs via direct intravasation of tumour cells into blood vessels or the lymphatic system and, less frequently, by their direct spreading into neighbouring tissues. Although the tumour, node and metastasis (TNM) staging system uses positive lymph node status as a marker of advanced cancer13, to date there is limited experimental evidence that cancer cells must traverse the lymphatic system before seeding distant metastasis. In contrast, a larger body of literature supports the haematogenous route as a main metastasis conduit14,15. We therefore focus this Review on blood-borne dissemination of cancer.
While decades of scientific research has revealed detailed pathogenetic mechanisms leading to primary tumour formation, the biological foundations of metastatic disease remain inadequately understood. Nevertheless, over the past 20 years important progress has been made in elucidating key aspects in this regard. Metastasis is a multistep process contingent on invasive, metastasis-competent cell clones in the primary tumour (or metastatic lesions) that escape via intravasation and transit the bloodstream as CTCs. When they reach a point of extravasation, CTCs can home to distant niches and grow into secondary lesions14,15.
Two mechanistic models of cancer cell dissemination have been proposed: (1) the linear or late dissemination model and (2) the parallel progression or early dissemination model. The former postulates that natural selection within the primary tumour will lead to the dissemination of the fittest tumour cell clones over time to give rise to metastasis, where only small degrees of divergence should be present between metastatic and primary lesions16. Along these lines, primary tumour and metastatic tissue typically demonstrate high level of genetic similarities, including in metachronous lesions17,18. However, contradictory observations of genetic discrepancies between metastases and primary tumours favour the notion that tumour cell escape may occur early during tumour evolution19,20, perhaps even at preneoplastic stages21,22, following the logic of a parallel progression model19,21,23,24. Opponents of this theory argue that extensive intratumour heterogeneity might obscure shared but rare metastasis-competent subclones, which are not detected by current sequencing technologies.
These models of metastatic spread were enriched by phylogeny studies applying evolutionary principles, which revealed additional, and more complex than originally anticipated, patterns of metastasis-to-metastasis dissemination and tumour self-seeding25–28. Although plausible and repeatedly confirmed in both mouse models and patient samples of various cancer types29–32, this concept has been challenged too, given the knowledge that complete phylogeny is difficult to achieve with current methods and their limitations (for example, insufficient sequencing depth, sampling bias and heterogeneity, and different bioinformatics approaches)25,28. Nevertheless, the analysis of unique subclonal somatic mutations that occur during branching and progression of cancer cell lineages has revealed that metastatic spread follows intricate patterns, with monoclonal or polyclonal seeding between metastatic lesions29,31,33,34. Consequently, cancer cell dissemination is likely not only a solitary endeavour but may also occur via polyclonal events that play a central role in diversifying the metastatic process, far away in both space and time from the primary tumour35–37.
Step-by-step sequence of metastatic events
The first critical step in metastatic dissemination is cancer cell invasion, followed by intravasation into the proximal blood vessels (Fig. 1a,b). Access to the circulation can be achieved via passive shedding or active cell invasion38. In the case of passive shedding, tumour fluid dynamics and reduced barrier function of immature tumour neovasculature facilitate physical expulsion of tumour cells into the periphery38–40. However, the frequency and exact conditions leading to passive tumour cell shedding remain poorly understood.Fig. 1 Stepwise progression of the metastatic cascade.
a, Invasion of cancer cells. The formation of invasive features (for example, invadopodia) and hypoxic conditions (indicated by a blue haze) favour release of cancer cells away from the primary tumour site via upregulation of hypoxia inducible factor 1α (HIF1α), NMYC downstream-regulated gene 1 protein (NDRG1) and vascular endothelial growth factor A (VEGFA). This is further enhanced by metastasis-promoting features, including the expression of CXC-chemokine receptor 4 (CXCR4) and angiopoietin-like protein 4 (ANGPTL-4), the secretion of matrix metalloproteinases (MMPs), decreased expression of phosphoglycerate dehydrogenase (PHGDH) and cytoskeletal rearrangements. External conditions conducive to spreading are further provided by physical factors (for example, fluid pressure and stiffness) and surrounding cells (for example, cancer-associated fibroblasts and endothelial cells) in the tumour microenvironment. Mechanical stimuli from the tumour microenvironment promote pro-metastatic conditions by activating Yes-associated protein 1 (YAP)–transcriptional co-activator with PDZ-binding motif (TAZ) in cancer associated fibroblasts, favouring cancer cell invasion. Further, paracrine factors secreted by endothelial cells may reduce PHGDH levels in cancer cells, potentiating cell migration and invasion. Intravasation (part b) and circulation (part c). Circulating tumour cells (CTCs) and their clusters have a short half-life in circulation, due to hostile conditions, including physical forces (that is, shear stress) and anoikis. CTCs can escape the immune system via downregulation of major histocompatibility complex class I (MHC-I), expression of immune checkpoint molecules (for example, programmed cell death protein 1 (PD1) ligand 1 (PDL1) and CD47) or through support from platelets and neutrophils. Cell-intrinsic factors (for example, expression of anti-apoptotic factors) enhance CTC survival and successful transit, while circadian rhythmicity (and related hormone fluctuations) dictates the timing of CTC intravasation events, reaching a peak during the rest phase. d, Extravasation. The efficiency of extravasation relies upon the expression of adhesion molecules (for example, CD44, mucin 1 (MUC1) and sialyl-Lewis A (sLeA)/sialyl-Lewis X (sLeX), chemokine release, physical properties (for example, CTC cluster size and deformability) and supporting cells (for example, neutrophils via the formation of neutrophil extracellular traps (NETs)). Signalling via transforming growth factor-β (TGFβ)/SMAD family member 3 (SMAD3) leads to the upregulation of various adhesion-related molecules and facilitates CTC vascular adhesion. e, Successful homing into a new environment is dependent on niche factors (that is, various organ-specific cell types), but is also influenced by the preset metastatic potential of CTCs. f, CTCs may spread from the primary tumour or from metastatic lesions to either seed new metastasis (metastasis-to-metastasis dissemination) or return to the primary tumour site (tumour self-seeding). DTC, disseminated tumour cell; HIFPH2, hypoxia-inducible factor prolyl hydroxylase 2; NK natural killer; N-WASP, neural Wiskott–Aldrich syndrome protein.
Active cancer cell invasion can be triggered by hypoxia41. Hypoxia-inducible factor 1α (HIF1α) increases expression of the adhesion molecules L1 cell adhesion molecule (L1CAM; via angiopoietin-like protein 4 (ANGPTL4) signalling)42 and CXC-chemokine receptor 4 (CXCR4)43, resulting in enhanced CTC–endothelium binding and intravasation. Hypoxia has further been linked to the formation and intravasation of CTC clusters, via upregulation of cell–cell adhesion molecules41 (Fig. 1a). Expression of HIF prolyl hydroxylase 2 (HIFPH2) by endothelial cells promotes escape of tumour cells into blood vessels by impeding endothelial integrity and vessel maturation44. Transient binding of tumour cells to perivascular macrophages further increases endothelial permeability through the production of vascular endothelial growth factor A (VEGFA), in a HIF1α-independent manner45. Vascular endothelial cells can induce metabolic changes in cancer cells, such as the downregulation of phosphoglycerate dehydrogenase (PHGDH), to further facilitate cancer cell invasion via activation of the hexosamine–sialic acid pathway and increased sialylation of integrin αVβ3 (ref.46) (Fig. 1b). Tumour cell-intrinsic factors contributing to active invasion include the loss of function of nuclear receptor subfamily 2 group F member 1 (NR2F1), accompanied by increased canonical Wnt signalling, the expression of epithelial-to-mesenchymal transition (EMT)-related transcription factors (for example, TWIST1 and zinc-finger E-box-binding homeobox (ZEB1))47 and the formation of invadopodia via neural Wiskott–Aldrich syndrome protein (N-WASP)-directed cytoskeletal reorganization48 (Fig. 1a).
Although as many as 1 × 106 cancer cells per gram of tumour tissue are estimated to be shed into the circulation49, metastatic efficiency of CTCs appears to be low, with estimates around 0.01%50,51. CTCs generally exhibit short circulation times (25–30 min for single CTCs and 6–10 min for CTC clusters), where the shorter circulation time of clusters may be ascribed to a rapid arrest and homing at distant sites. A rapid escape and less exposure to hostile conditions in blood may ultimately contribute to CTC survival. These hostile circulatory conditions include high shear stress causing deformation, anoikis, fragmentation and cell death52. Remarkably, the process of fragmentation can trigger the priming and accumulation of pro-metastatic immune cells (for example, myeloid cells), promoting successful metastatic colonization of surviving CTCs52 (Fig. 1c). Moderate levels of shear stress can also lead to transcriptional changes, favouring motility and migration53. CTCs in circulation can enter cell cycle arrest or increase the expression of anti-apoptotic proteins such as BCL-2 (refs.54,55). To evade clearance by immune cells, CTCs can express programmed cell death protein 1 (PD1) ligand 1 (PDL1) or CD47 (refs.56–58) (Fig. 1c). Neutrophils support CTCs in circulation by enhancing their proliferation and survival59, as well as suppressing the host’s adaptive immune system (CD8+ T cells)60 and innate immune system (natural killer (NK) cells)61 (Fig. 1c).
Extravasation, in analogy to intravasation, may be promoted passively or actively. Both mechanical trapping (with capillaries as small as a few micrometres in diameter) and active adhesion may depend on CTC configuration (for example, single CTC versus CTC cluster)62, cluster composition (homotypic versus heterotypic)63,64 and geometrical shape65. Active CTC extravasation mimics diapedesis of leukocytes in terms of cytoskeletal and signalling changes66, including the expression of ligands and receptors for direct endothelial cell wall interaction67 (Fig. 1c). For example, expression of sialylated carbohydrate ligands (sialyl-Lewis A and sialyl-Lewis X)68, mucin 1 (MUC1)69 or CD44 (ref.70) by cancer cells and their ligation to selectins, intercellular adhesion molecule 1 (ICAM1) or β1 integrin on endothelial cells triggers CTC rolling and subsequent adhesion, enabling transendothelial migration (Fig. 1d). Endothelial adhesion is further enhanced via inflammatory mediators such as CXC-chemokine 12 (CXCL12)71. Reactive oxygen species (ROS) and SMAD family member 3 (SMAD3) enhance CTC adhesion via transforming growth factor-β (TGFβ) signalling72. The secretion of ANGPTL4, VEGF, matrix metalloproteinases and CC-chemokine ligand 2 (CCL2) by cancer cells or a disintegrin and metalloproteinase 12 (ADAM12) by endothelial cells increases endothelial permeability to facilitate extravasation73–75. CTC-induced damage to endothelial cells presents another means of escape, mediated by programmed endothelial cell necrosis via receptor-interacting serine/threonine-protein kinase 1 (RIPK1)76. Furthermore, various other cell types besides endothelial cells extrinsically support CTC extravasation. Platelets, for example, facilitate extravasation via ATP–P2Y purinoceptor 2 (P2Y2) interaction, causing endothelial retraction64. Neutrophils immobilized via endothelial glycocalyx binding create a pro-inflammatory local milieu through secretion of interleukin-8 (IL-8) and CXCL1, resulting in vascular leakiness61,77, release of neutrophil extracellular traps78, macrophage 1 antigen (MAC-1)-mediated ‘docking’ platforms79 or matrix metalloproteinases61 that promote dissemination (Fig. 1c,d). Experimental mouse and zebrafish models show that endothelial cells themselves may act as accomplices by wrapping around and expulsing arrested CTCs40.
After exiting the bloodstream, CTCs may home into their new metastatic site as disseminated tumour cells (DTCs) (Fig. 1e). While a comprehensive review of metastatic colonization upon extravasation is beyond the scope of this Review and has been provided well elsewhere80–82, we briefly discuss several key factors dictating DTC fate. Homing may be influenced by anatomical features, as well as by biological characteristics, of CTCs. For instance, in the case of colorectal cancer, a ‘direct’ vascular connection between the primary site and the metastatic site enables rapid entrapment of CTCs in the liver83. On the molecular side, CTCs may undergo chemotaxis to the bone marrow via expression of CXCR4 (ref.84). When travelling as heterotypic clusters with platelets, CTCs attract granulocytes that help establish neoplastic lesions at secondary sites85.
In the metastatic niche, the associated microenvironment exerts a critical influence on CTCs as they stop and possibly enter a stage of dormancy82. Organ-specific cell types have been suggested to provide DTC sanctuaries and promote dormancy, including perivascular osteoblasts in bone86,87, NK cells and hepatic stellate cells in the liver88, astrocytes in the brain89 and haematopoietic stem cells in the bone marrow90 (Fig. 1e). Activation and proliferation of DTCs can be subsequently prompted by inflammatory stimuli or osteoclast activity via calcium-associated signalling91,92. Whether physical factors differ between organs and influence metastasis remains poorly understood.
Physical and metabolic hallmarks of CTC biology
Tumour mechanics and physical properties are intricately linked with the state and function of cancer cells, tumour progression and metastasis93. Typically, tumours are stiffer than healthy tissue, often due to changes in their extracellular matrix94. Rigidity can lead to gene expression changes promoting tumour cell motility, while perpendicular alignment facilitates spread (sometimes referred to as ‘highways’ for tumour cell invasion)39,95. Leaky tumour vasculature can cause fluid accumulation, which, in combination with space constraints present in a rapidly growing tumour mass, results in high interstitial pressure and flow gradients, creating permissive avenues for tumour cell escape39,95. Cancer cells can actively migrate by repurposing their nucleus to create hydrostatic pressure, pulling and releasing the nucleus, akin to an engine piston, via actomyosin contractility96. Mechanical stimuli from the tumour microenvironment promotes pro-metastatic conditions via Yes-associated protein 1 (YAP)–transcriptional co-activator with PDZ-binding motif (TAZ)-dependent cancer-associated fibroblast (CAF) activation and enhanced cell invasion and migration97,98. Once in the bloodstream, CTCs experience various shear stress levels, where high levels lead to cellular fragmentation52 and intermediate levels may promote endothelial adhesion and extravasation40.
Homeostatic and metabolic stimuli affect CTCs throughout the metastatic passage. ROS from myeloid-derived suppressor cells lead to the upregulation of NOTCH1 expression on CTCs through the ROS–nuclear factor erythroid 2-related factor 2 (NRF2)–antioxidant response element axis, and NOTCH1 relays proliferative signals via its ligand JAGGED1, promoting proliferation and survival99. Studies using the 4T1 syngeneic mouse model of breast cancer reveal that CTCs, compared with the primary tumour, have elevated mitochondrial biogenesis and respiration via peroxisome proliferator-activated receptor-γ co-activator 1α (PGC1A) upregulation, as well as increased mitochondrial DNA and ATP production100,101. In human epidermal growth factor receptor 2 (HER2)-positive breast cancer, oxidative stress transitions CTCs to a HER2-negative status, providing one possible explanation for the observed phenotypic discrepancy between primary lesions and metastatic lesions102. In the study cited, both HER2-positive cells and HER2-negative cells exhibited comparable tumour-initiating capacity, but HER2-negative CTCs were less proliferative. Oxidative stress experienced by metastasizing cancer cells can be counteracted via fatty acid oxidation driven by nuclear receptor subfamily 4 group A member 1 (NUR77) and mitochondrial trifunctional enzyme subunit-β signalling to maintain NADPH and ATP levels103. CTC clustering enhances metastatic potential by ROS clearance via mitophagy and HIF1α activity104.
Metabolic features of CTCs can also influence the metastatic process. CTCs can increase their survival and metastatic potential by dynamically adapting to organ-specific requirements via metabolic changes that counteract oxidative stress in the oxygen-rich lung environment105,106. Mice receiving a fat-rich diet show increased release of CTCs with excess free fatty acids incorporated into the cellular membrane, promoting tissue invasion and increased lung metastasis107. Palmitic acid has been shown to increase metastatic capability of cancer cells via CD36-mediated signalling108. Lipid rafts and raft-specific proteins, such as caveolin and flotillin, are also emerging as important regulators of metastatic potential, CTC survival and, therefore, patient prognosis109. The metastatic potential of CTCs is additionally enhanced by extracellular glucose via the exchange factor directly activated by cAMP 1 (EPAC)–RAP1 and O-linked β-N-acetylglucosamine pathways110, pyruvate metabolism via α-ketoglutarate-induced collagen remodelling111 or the production of superoxide via a mitochondrial overload through aerobic glycolysis112. Interestingly, heterogeneity in glucose metabolism affects metastatic potential and growth capabilities differently; while the downregulation of PHGDH increases invasive and migratory potential, high PHGDH expression is required for tumour growth at the primary or metastatic sites46. Protein catabolism113 via proline dehydrogenase, iron metabolism via stabilization of pro-metastatic collagen lysyl hydroxylase dimers114 or acidic conditions via cathepsin B-mediated degradation of extracellular matrix115 further contribute to increasing metastasis. Collectively, these data allude to the extraordinary physical and metabolic plasticity of CTCs, allowing them to surmount adverse conditions to successfully spread.
Biological features of CTCs
CTC phenotypic heterogeneity and CTC clusters
Epithelial cells typically undergo anoikis upon losing touch with their surrounding environment; thus, metastatic seeding is generally inefficient50,51,116. Therefore, this raises the following question: what properties do CTCs have that sanction their successful metastatic dissemination? Enhanced survival and tumour-seeding capacity seems to be contained within a small fraction of tumour-initiating cells or metastasis-initiating cells with stem-like properties15,117–119. EMT has been proposed as a crucial requirement for metastasis, because it increases both contact-independent survival (that is, resistance to anoikis) and invasive potential15,118,120. Preclinical studies have demonstrated that EMT transcription factors, such as SNAIL and TWIST, suppress cell–cell contact and increase motility and invasiveness in vitro121,122. However, silencing of SNAIL and TWIST could reduce but not completely inhibit metastasis in vivo, challenging the necessity of EMT-related transcriptional regulators for the metastatic process123,124. Remarkably, in various models based on EMT lineage tracing, loss of epithelial cadherin (E-cadherin) or modulation of TWIST expression demonstrated that EMT prevents the successful seeding of metastatic tumours123–125. Observations of epithelial-to-mesenchymal plasticity suggest that this transformation need not be binary and irreversible but rather may be fluent and transitional, functioning as an influencer rather than a driver of metastasis126–128. Accordingly, an intermediate level of EMT has been described in CTCs, and correlates with plasticity, stem cell-like characteristics, poor treatment response and disease progression118,119,128. Such hybrid states have been observed at the invasive edge of xenografts and patient tumour tissues of common carcinoma types22,128–130, yet their functional contribution to invasion, dissemination and metastatic colonization requires further investigation.
Both plasticity-dependent and plasticity-independent routes of metastasis may exist in parallel127. An essential counterargument to the necessity of EMT was provided by observations of cell contact-dependent, collectively migrating and highly metastatic CTC clusters, which were first described several decades ago131,132. The polyclonal nature of metastatic colonies29,31,33,34 and the mutually beneficial or synergistic interactions between subclones133,134 indicate that cancer spread occurs not only via single CTCs but also via heterogeneous CTC clusters35–37. Several studies show that CTC clusters, comprising a minority of the total CTC events in the peripheral circulation, display up to a 100-fold increase in metastatic potential compared with individual CTCs35–37,125,135. Evidence from patient samples and mouse models demonstrate that intratumour hypoxia triggers the upregulation of genes encoding proteins involved in cell adhesion to enable collective CTC cluster shedding41. We and others have demonstrated that homotypic clustering enhances various cellular properties, including upregulating stem-like features37,136–138 via methylation of metastasis suppressor genes136 and hypomethylation of binding sites for the transcription factors OCT4, SOX2 and NANOG137 (Fig. 2a). Clustering may further be enhanced by circulating galectin 3 or cancer-associated MUC1 (ref.139), homotypic ICAM interactions138 or CD44 interacting with p21 protein–activated kinase 2 (PAK2)37. It can also increase survival and self-renewal capacity via CDK6 or via increased size or number of desmosome and hemidesmosomes35,36. CD44 was among the first markers to identify breast cancer cells with increased tumour-initiating capacity in solid tumours117, and was later shown, together with MET, epithelial cell adhesion molecule (EpCAM) and CD47, to characterize highly metastatic subpopulations118. Importantly, CD44 expression is ubiquitous in the haematopoietic cell compartment, and therefore should be cautiously used as a CTC marker on its own140. Expression of CK14, previously ascribed to stem-like cells, is enriched in CTC clusters compared with single CTCs and is required for distant metastasis36. A phenotypic signature in CTCs with stem-like features (EpCAM–, HER2+, EGFR+, heparanase (HPSE)+, NOTCH1+) was shown to confer competency for brain and lung metastasis141.Fig. 2 Biological features of circulating tumour cell clusters.
Clustering of circulating tumour cells (CTCs) may occur exclusively between tumour cells (homotypic CTC clusters), as well as between tumour cells and other cell types (heterotypic CTC clusters). This results in enhanced proliferation and survival in the circulation, enabling superior metastatic proficiency. a, Homotypic clustering of CTCs leads to the creation of typically oligoclonal clusters, kept together by cell adhesion molecules (for example, plakoglobin, claudins and CD44). Expression of these molecules and cluster formation are promoted by hypoxic conditions. CTC clustering triggers epigenetic changes (for example, hypomethylation of binding sites for OCT4, NANOG and SOX2), leading to stem-like cell behaviour, which facilitates metastasis seeding. b, Heterotypic CTC clusters (for example, between tumour cells and neutrophils, cancer-associated fibroblasts or platelets) display increased proliferation, invasion and homing at the metastatic site, as well as protection against immune surveillance. E-cadherin, epithelial cadherin; GPIb-IX-V, glycoprotein Ib–IX–V; GPVI, glycoprotein VI; N-cadherin, neural cadherin; VCAM1, vascular cell adhesion molecule 1.
Clustering occurs not only between CTCs (homotypic) but also between CTCs and other cell types (heterotypic clusters), including platelets, myeloid cells and CAFs59,85,99,142–147 (Fig. 2b). The interaction of CTCs with platelets occurs rapidly in the circulation143, promoting plasticity and metastasis-initiating capacity142, for example via RhoA–MYPT1–PP1-mediated YAP1 signalling63 and increased vascular permeability via platelet-derived ATP–P2Y2 interaction64. Platelets provide protection against T cell-mediated clearance via the glycoprotein A repetitions predominant (GARP)–TGFβ axis145, as well as NK cell-mediated clearance via platelet-derived major histocompatibility complex class I (ref.144). We demonstrated for the first time that neutrophils are another accomplice in forming heterotypic CTC clusters59. Neutrophils are recruited by CXCL5- and CXCL7-dependent chemotaxis85, and establish cell contact with CTCs via vascular cell adhesion molecule 1 (VCAM1)-mediated adhesion, increasing their proliferative and metastatic potential59 (Fig. 2b). They also facilitate adhesion and extravasation via the formation of neutrophil extracellular traps78 or IL-1β and matrix metalloproteinase secretion61 (Fig. 1c). Neutrophils also offer CTCs protection from immune surveillance60,61, a benefit similarly observed for CTC clustering with myeloid-derived suppressor cells and macrophages99,148. Heterotypic adherens junctions between invasive cancer cells and stromal CAFs mediated by E-cadherin and neural cadherin (N-cadherin), respectively, have been shown to promote collective invasion, where CAFs function as leader cells with migratory–invasive features146,147 and support metastasis (tumours bring their own soil)149 (Fig. 2b). Beyond the biological implications of clustering, mathematical models propose that cluster shape additionally affects CTC behaviour in the circulation. Compact clusters flow closer to the endothelial wall than linear ones150, yet passage of clusters through narrow capillaries occurs in ‘single chains’151. Together, the phenotypic plasticity and variations in clustering profoundly impact the ability of CTCs to metastasize, highlighting possible strategies to interfere with the metastatic process.
Molecular heterogeneity of CTCs
CTCs are dynamic cell populations that are constantly replenished from multiple tumour regions and anatomical locations, enabling a snapshot assessment of tumour heterogeneity. By studying the genomic, transcriptomic and epigenetic profile of CTCs, we can further explore their biology. The development of single-cell technologies and sophisticated bioinformatics tools has allowed the dissection of rare CTC populations at single-cell resolution152. For example, single-CTC analysis has uncovered copy number variants, therapeutic targets (for example, HER2) and resistance mutations (for example, in PIK3CA) that only partially overlap with primary tumours or metastatic lesions from the same patient102,153,154. Dynamically regulated HER2 expression in CTCs differs from HER2 expression in primary tumours: HER2-positive CTCs may activate multiple redundant pathways (for example, insulin receptor, MET and IGF1), while HER2-negative cells show activation of Notch and DNA damage components102. Mutationally defined metastasis-prone CTC subclones exhibit similarities but also private alterations compared with primary tumours155, including mutations in genes encoding proteins regulating motility (for example, dynein axonemal heavy chain 8 (DNAH8), ephrin B receptor 1 (EPHB1)156, microtubule–actin crosslinking factor 1 (MACF1) and neural precursor cell-expressed developmentally downregulated protein 9 (NEDD9)157). Activation of stem cell-like signalling pathways such as Wnt and Notch158,159 and dedifferentiation via loss of NK2 homeobox 1 (NKX2-1)160 further enhance the metastatic potential of CTCs. An in vivo loss-of-function CRISPR screen identified specific molecular dependencies required by CTCs for successful completion of the metastatic cascade161. For example, knockout of the gene encoding PLK1 led to a remarkable reduction in CTC intravasation, as well as metastasis formation161. Other regulatory elements, including long non-coding RNAs such as colon cancer-associated transcript 1 (CCAT1) and HOX transcript antisense RNA (HOTAIR), have been shown to function as key pro-metastatic contributors by inducing microenvironmental changes that promote invasion, migration and organotropic colonization via the TGFβ–ZEB1/ZEB2 axis or the nuclear factor-κB (NF-κB) pathway162. CTCs from different primary tumours exhibit ‘preset’ organotropism, and CTCs captured from different vascular sites exhibit distinct molecular features163. For instance, a series of seminal studies identified gene expression features that mediate metastasis of breast cancer to the lungs, brain or bone164–166. Tropism to bone has also been linked to SMAD signalling167 and ZEB1 activity in breast cancer cells with an epithelial phenotype168. MYC was identified as a crucial regulator for tropism and adaptation to the brain microenvironment169. Differences at the molecular level between CTC clusters and single CTCs include the higher expression of the cell–cell junction molecules plakoglobin and claudins35,137, hypomethylation of binding sites for stem cell-like transcription factors (that is, NANOG, OCT4 and SOX2) and increased proliferation in clusters137. In summary, CTC phenotypic and molecular heterogeneity fuels the adaptive processes required for metastasis.
Timing of CTC release
In addition to the aforementioned dimensions of heterogeneity, propagation dynamics of CTCs is emerging as an equally important element for tumour cell dissemination170,171. The role of the circadian rhythm for tumour onset172–175 and growth dynamics176,177 has been investigated and explored clinically via the concept of chronotherapy. This aims to increase the efficacy of antineoplastic drugs by administering treatment at optimized times178–180. However, the effect of the circadian rhythm on CTC release and metastatic dissemination was determined only recently170,171. Current practice for detecting CTCs assumes that peripheral blood counts do not change significantly throughout the day. This has potentially caused inconsistent results, limiting the clinical implementation of CTCs as a liquid biopsy analyte. Observations from use of fluorescence in vivo flow cytometry in orthotopic mouse models of human prostate cancer suggested that CTCs are subject to circadian rhythmicity171. Our laboratory recently elucidated those temporal dynamics of CTC intravasation, which vary dramatically based on circadian rhythm, both in mouse models and in patients with breast cancer, and are dictated by rhythmic variations in hormone levels (for example, melatonin) that result in the highest CTC counts during sleep170 (Fig. 1c). That study also demonstrated marked differences in Ki67 expression in both the primary tumour and CTCs, reaching a peak during the rest phase, suggesting the need to standardize the timing of tissue biopsies used for prognostic and predictive information (that is, directly influencing clinical decision-making). These findings argue for a re-evaluation of current biopsy standards and suggest innovative, time-controlled clinical trials exploring their translational value.
Detection and analysis of CTCs
Implementing CTCs as a liquid biopsy analyte in the clinic will require unbiased, effective, rapid and affordable capture technologies to reliably isolate sufficient numbers of CTCs. These capture technologies must also be compatible with advanced sequencing tools and functional assays, to generate data for accurate patient stratification and therapeutic decision-making (Fig. 3a). When isolated in a viable form, CTCs are also amenable to an exceptional range of molecular and functional investigations of the biology and vulnerabilities of metastatic cancer (Fig. 3a). Since they may represent aggressive subclones with high metastatic propensity, CTCs fulfil a unique role as a liquid biopsy analyte. We speculate that their phenotypic and molecular analysis might reveal more relevant information than classical tissue biopsies (isolation of random subclones)181,182 or analysis of other circulating analytes such as circulating tumour DNA (detection of dying subclones)183. However, this will need to be further investigated. Access through minimally invasive blood draws could allow frequent, longitudinal assessment of the effect of clinical interventions and may enable early detection of cancer or recurrence184. This renders CTCs as an ideal source of biomarkers for real-time clinical applications and personalized medicine. Due to their rare nature, however, capturing CTCs remains challenging, and efficient CTC enrichment is critical for reproducible downstream analysis and applications.Fig. 3 Circulating tumour cell capture, analysis and clinical trial designs.
Available circulating tumour cell (CTC) detection technologies and examples of how CTCs can be included in clinical trial designs. a, CTC capture tools include antigen-dependent technologies (for example, immune capture via immobilized antibodies, antibody coated beads or coated intravascular guidewires) and antigen-independent technologies (for example, density gradient centrifugation, microfluidic systems based on deformability and size, size-based filtration systems, electrical charge-based technologies or cytapheresis). The latter do not require a priori knowledge of phenotypic profiles and are thought to capture more heterogeneous CTC populations compared with antigen-dependent methods. Downstream analysis of CTCs includes direct drug phenotyping, the creation of CTC-derived xenograft ‘avatar’ models and multi-omics interrogations at the single cell-level: epigenomic, proteomic, genomic and transcriptomic. b, Validation of the use of CTCs in the setting of innovative clinical trials includes randomizing and benchmarking CTCs against standard-of-care (SOC) diagnostic and therapeutic approaches or other liquid biopsy analytes (for example, circulating tumour DNA (ctDNA)) and testing of CTC-based treatment strategies. The figure shows various possibilities for CTC-based clinical trial design: randomization of CTC-based liquid biopsies versus tissue biopsies to guide the choice of therapy; randomization based on the presence of CTCs (positive versus negative) to guide the choice of therapy (that is, experimental or targeted versus SOC); randomization of patients who are positive for CTCs to treatment with different targeted or experimental drugs; randomization according to longitudinal or repeated CTC assessment to guide subsequent lines of therapy (for example, targeted or experimental treatment versus SOC); randomized trials which compare either use of CTCs alone with SOC diagnostic approaches (for example, medical imaging) or use of other liquid biopsy analytes (for example, ctDNA) or each individual modality with combined use of modalities.
The past decade resulted in several technological advances to improve CTC detection and analysis3,185, exploiting distinct characteristics and phenotypes of CTCs. Broadly speaking, these can be divided into antigen-dependent and antigen-independent methods (Fig. 3a). To date, the most widely used approaches use antigens expressed on CTCs and minimally expressed on other cells in circulation to enable positive selection. To improve discrimination, this approach is often combined with depletion of haematopoietic cells via CD45-based negative selection. Both the US Food and Drug Administration (FDA)-approved CellSearch system (Menarini Silicon Biosystems, Italy) and AdnaTest CTC Select (QIAGEN, Germany) use immunomagnetic selection based on EpCAM expression186,187. Further markers, including pan-CK and CD45, are applied to increase sensitivity and specificity, respectively. The magnetic-activated cell separation (MACS) technology (Miltenyi Biotec, Germany) applies antibody-coated magnetic beads for CTC capture119. The geometrically enhanced differential immunocapture (GEDI) method combines microfluidics with different antibodies depending on the tumour type (for example, HER2 for breast cancer, and PMSA for prostate cancer) and cytokeratin positivity for enumeration188.
Antigen-agnostic detection technologies exploit physical properties such as size, charge, density or elasticity for CTC enrichment. Filter-based devices, density gradient centrifugation, capture surfaces and microfluidic systems such as ISET (Rarecells Diagnostics, France), CTC-iChip (TellBio, USA), Smart Biosurface Slides and the FDA-cleared Parsortix (ANGLE, UK) all enable detection of CTCs based on physical properties189–193. Multimodality approaches are being developed to further increase sensitivity and specificity. For instance, Isoflux (Fluxion Biosciences, USA) combines flow control and immunomagnetic beads194, while the Cyttel system (CYTTEL Biosciences, China) is an image-based detection tool that sequentially combines centrifugation, immunohistochemistry and fluorescence in situ hybridization to identify CTCs195. The microfluidic platforms Parsortix and CTC-iChip can also be combined with marker-based positive and negative selection (for example, EpCAM, EGFR, HER2 and CD45), imaging and micromanipulation to isolate pure CTC subsets41,59,137,189.
To tackle low CTC numbers in peripheral blood samples, innovative in vivo CTC detection technologies have been developed. For instance, direct intravascular CTC-catching guidewires coated with EpCAM-directed antibodies (CellCollector (GILUPI, Germany)) allow direct extraction of CTCs from the circulation system196. Cytapheresis enables cell fraction enrichment from large blood volumes, and combined with antigen-dependent selection, it appears to be promising for CTC isolation197. However, implementation of this approach in routine clinical practice may be difficult due to the length and invasiveness of the procedure, as well as the poor vascular health of heavily treated patients with cancer. Studies comparing different approaches to gain access to the vasculature demonstrate higher CTC numbers in tumour-draining vessels than in peripheral locations in patients with early-stage non-small-cell lung cancer184,198. This principle offers an attractive liquid biopsy scenario for patients with early-stage cancer treated with surgery. Although important, implementation of these findings remains impractical for routine CTC assessment or for patients with advanced-stage disease who do not undergo surgery.
The advances in capture technologies enabled CTC research to move far beyond mere enumeration. Detailed molecular and functional analysis has enabled the dissection of genomic, epigenomic, transcriptomic, proteomic and functional properties of CTCs at the bulk and single-cell levels. Comprehensive reviews have extensively covered these developments152,185,199,200, and therefore we mention only aspects of cell multi-omics and functional assessment of CTCs. For instance, single-cell interrogation of individual CTCs and CTC clusters combined with drug phenotyping can identify biological dependencies and potential therapeutic targets137. Single-cell resolution mass spectrometry201 and bead-based immunoassays on microfluidic platforms have been developed to characterize CTC proteins and secreted factors202,203. Although demonstrated in experimental proof-of-principle studies204–206, the low success rates of ex vivo CTC cultures represent a considerable challenge for their clinical translation.
Generally, while CTC capture and downstream analysis seems feasible and clinically relevant, many of the techniques outlined are far from being routinely applied today. Available CTC technologies have limitations that must be addressed to enable a robust entry into the clinical setting. This includes a better understanding of epitope expression and plasticity, as well as addressing issues relating to cell loss due to size and deformability differences, low CTC purity, device clogging, the large amounts of blood needed, the time required and difficulties with automation. Additional challenges relate to the improvement of functional assays (for example, more efficient culture methods and CTC-derived xenografts), as well as rigorous validation of molecular analysis (for example, accounting for stochastic variations, low sequencing coverage, amplification bias and high error rates, as well as variation in bioinformatics approaches152). Overcoming these challenges could eventually propel CTCs into the limelight of personalized medicine as minimally invasive, yet comprehensively informative sources of biomarkers.
CTC-based clinical applications
Vulnerabilities and targeting of CTCs
Current strategies for eliminating metastasis are identical to those applied to primary tumours: targeting growth and tumorigenesis instead of the metastatic process itself207,208. Surgery or systemic therapy for the primary tumour will not necessarily remove the source of metastasis, as dissemination may have already occurred19,21,24,32. Most antineoplastic drugs are initially tested in the metastatic setting and then reused in the adjuvant setting to prevent metastatic disease, with only partial success209. This paucity of truly metastasis-targeting agents is being challenged by several preclinical studies and thoughts for future clinical trial designs207,210. Because metastatic cancers represent the progeny of CTCs, which may be derived from selected subpopulations in tumours, targeting CTCs at various steps of the metastatic cascade would, in principle, directly interrupt the metastatic progression (Fig. 4).Fig. 4 Circulating tumour cell-targeting strategies.
Outlined here are various potential circulating tumour cell (CTC)-targeting strategies that are proposed on the basis of recent experimental work. a, Inhibition of cancer cell intravasation via normalization of the hypoxic tumour microenvironment; for example, by ephrin B2 Fc chimaera protein (EpB2) treatment leading to modulation of vascular endothelial growth factor receptor (VEGFR) signalling and vascular normalization, blockade of intravasation-relevant proteins (for example, Polo-like kinase (PLK1) inhibition) or blocking of cellular interactions between cancer and endothelial cells (for example, integrin-targeted antibodies). b, Dissociation of CTC clusters or prevention of their formation, for example via Na+/K+-ATPase inhibition, heparanase (HPSE) inhibition, stimulation with the urokinase-type plasminogen activator (urokinase) or inhibition of platelet receptors on CTCs. c, Targeting CTC survival via metabolic interference by increasing oxidative stress and inhibition of pyruvate or proline metabolism, or by use of E-selectin/tumour necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL)-coated nanoliposomes that mimic the activity of natural killer (NK) cells. d, ‘Demasking’ CTCs for immune clearance by targeting immune evasion via immune checkpoint inhibitors against programmed cell death protein 1 (PD1) and PD1 ligand 1 (PDL1), cytotoxic T lymphocyte-associated antigen 4 (CTLA4) or CD47. e, Use of engineered CTCs as therapeutic vehicles (for example, prodrug conjugates) or CTCs for tumour vaccine development. f, CTC-based chronotherapy (that is, delivering treatments to be maximally effective at the times of greatest CTC production). VCAM1, vascular cell adhesion molecule 1.
Targeting hypoxia-induced cluster release using vascular normalization-inducing agents (for example, ephrin B2 Fc chimaera protein, which fine-tunes VEGF receptor (VEGFR) signalling211) has been suggested as a strategy to prevent metastasis in a preclinical models41 (Fig. 4a). The PLK1 inhibitor BI 2536 also prevents CTC intravasation161, and its clinical use could therefore provide a method to curb metastatic spread (Fig. 4a). Intravasation and extravasation could also be prevented by targeting integrins, cadherins and cell-surface glycoproteins212, targeting of invadopodia (for example, via N-WASP inhibition)48,66, or antibody targeting of CD36 and P-selectin or αIIbβ3 and α6β1 integrin antagonists212 (Fig. 4a). One class of drug currently under development aims to inhibit HPSE, which induces ICAM1-mediated cell adhesion in CTC clusters213. Urokinase, a thrombolytic agent that dissolves fibrin, also suppresses clustering in vitro and decreases the number of CTC clusters in mice214. Further, Na+/K+-ATPase inhibitors (for example, digoxin) show great promise due to their cluster-dissociation capabilities in vivo, ultimately leading to metastasis suppression in mice137 (Fig. 4b). Currently, a single-arm, proof-of-mechanism, therapeutic exploratory phase I study of digoxin in patients with advanced or metastatic breast cancer is investigating whether cardiac glycosides are able to disrupt CTC clusters in patients with breast cancer (NCT03928210)215. Heterotypic clustering can also be disrupted through cell–cell dissociation. Disrupting platelet–cancer cell interactions by blocking key platelet receptors on CTCs, such as glycoprotein Ib–IX–V and glycoprotein VI, reduces metastatic potential85,216,217 (Fig. 4b). Disrupting cell–cell interactions in CTC–neutrophil clusters via VCAM1 targeting curbs proliferation and metastatic efficiency59. On the other hand, VCAM1-mediated affinity of CTCs for neutrophils could be exploited for immune-based targeting by arming the latter with nanoscale liposomes carrying tumour necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) and the E-selectin adhesion receptor to functionalize those neutrophils by mimicking the cytotoxic activity of NK cells218 (Fig. 4c). Metabolic and homeostatic vulnerabilities could also be targeted by inhibiting pyruvate metabolism by preventing α-ketoglutarate-induced activity of prolyl 4-hydroxylase (P4HA), hampering proline metabolism or increasing oxidative stress100,111,113 (Fig. 4c). Immune checkpoint inhibitors could mark CTCs for killing by T cells57 (Fig. 4d), and dual targeting of EpCAM or HER2 in combination with use of an immune checkpoint inhibitor (that is, PD1, PDL1 or cytotoxic T lymphocyte-associated protein 4 (CTLA4)) produces greater cancer cell killing compared with single-agent therapy219,220. CTCs can also be used for cancer vaccine production using mechanically disrupted CTCs as nanolysates221 (Fig. 4e). The capacity of CTCs to home to existing tumour microenviroments26 could be exploited therapeutically through the identification of homing signals and the delivery of therapeutic payloads (Fig. 4e). As a proof of principle, systemically administered CTCs engineered to express the prodrug-converting enzyme cytosine deaminase–uracil phosphoribosyl transferase were able to convert non-toxic 5′-fluorocytosine into the cytotoxic compound 5′-fluoruridine monophosphate, resulting in CTC suicide upon homing to neoplastic tissues and killing of surrounding cancer cells as a bystander effect222. Lastly, given recent findings regarding the rhythmicity of CTC release into the bloodstream170, currently available therapeutic opportunities could be optimized, through chronotherapy-based designs, to achieve maximal effects during peaks of CTC production (Fig. 4f). These approaches offer exciting opportunities for targeting CTCs in future studies; however, given the complexity of the metastatic process, and the limited history of approaches purposely designed to target metastatic cells, their implementation in the clinical setting and demonstration of clinical value will require highly innovative and ambitious trial designs.
Prognostic and predictive value of CTCs
As of 10 October 2022, the search term ‘circulating tumour cells’ yielded 366 studies at ClinicalTrials.gov, of which 218 studies were in progress, reflecting the growing interest in CTCs as biomarkers for precision oncology. In the setting of such trials, CTCs have been detected in the peripheral blood of all major carcinomas, and their prognostic value has been demonstrated in breast, prostate and colorectal cancer, as well as in small cell and non-small-cell lung cancers223–227. In patients newly diagnosed with metastatic breast cancer, elevated CTC counts before therapy are predictive of shorter disease-free and overall survival225,228,229. Negative correlation between pretreatment CTC numbers and clinical prognosis has also been reported for patients with colorectal230 and prostate231,232 cancers. Importantly, several studies have demonstrated that changes in CTC numbers in response to therapy provide superior prognostic information compared with baseline CTC status, with persistence of CTCs after therapy conferring a worse prognosis9,233,234. Evaluation of CTC cluster abundance, in addition to single-CTC counts, significantly improves the prognostic value in patients undergoing therapy235. However, given that most of these studies were performed with antigen-dependent CTC technologies, enumeration in this context poses the risk of generating false-negative results.
CTCs counts are detectable 7–9 weeks before clinical manifestation of the disease, suggesting that CTC analysis in patients can aid in the prognostication of minimal residual disease and relapse in late stages of disease236, as well as providing a tool for early cancer detection193,237. CTCs collected at surgery revealed high mutational overlap with metastasis detected 10 months later (91%) in non-small-cell lung cancer184. Despite the value of CTCs for risk stratification, therapeutic patient stratification using CTCs has been explored in several clinical trials so far with limited success, including longitudinal monitoring of response and occurrence of therapy resistance9,10,238. While the interventional SWOG-S0500 trial failed to show a benefit of CTC count-guided intervention versus physician’s choice at disease progression9, the METABREAST STIC CTC trial demonstrated instances whereby CTC count can be helpful in guiding therapeutic decisions238.
Several interventional studies have explored the benefit of therapy choice based on molecular characteristics of CTCs239–242. Two proof-of-principle studies targeted HER2-positive CTCs in HER2-negative metastatic breast cancer with trastuzumab–emtansine or lapatinib (HER2-targeted therapies)240,241. Thus far, the studies have revealed only a marginal benefit, although one study (DETECT III) still awaits completion242. In metastatic prostate cancer, androgen receptor splice variant 7 (AR-V7) expression in CTCs predicts outcome in patients treated with endocrine therapy (PROPHECY trial)243,244. This led to a phase II trial focused on the response of patients with metastatic castration-resistant prostate cancer and AR-V7-positive CTCs to the microtubule inhibitor cabazitaxel11. Nevertheless, given the recent negative result in that trial, the European Society for Medical Oncology guidelines do not endorse AR-V7 testing in this setting, as there is no benefit over current decision algorithms11,12,245.
In summary, CTCs have been incorporated into the fifth edition of the WHO Classification of Tumours: Breast Tumours246 and the seventh edition of the AJCC Cancer Staging Manual247. The term ‘cM0 (i+)’ indicates that there is no overt metastasis but tumour cells have been detected in blood, bone marrow or lymph nodes. However, CTCs have yet to be included in clinical practice guidelines of major cancer societies, including the European Society for Medical Oncology or the American Society for Clinical Oncology. Arguably, the true power of CTCs lies in their potential to represent highly metastatic tumour subclones and their richness as up-to-date sources of biomarkers for molecular and functional studies. CTCs as living cells are, in principle, amenable to ex vivo cell culture and drug phenotyping, potentially in a timely manner and suitable to inform treatment decisions204,205,248, although such workflows will have to be significantly improved to reach the clinical side. Innovative, randomized and prospective interventional trials will reveal whether there are clear benefits from using CTCs as diagnostic tools against SOC techniques in specific cancer types (Fig. 3b). The predicted strengths of CTCs should be prioritized in future validation efforts, specifically the detection of minimal residual disease, expression of clinically actionable targets for therapy selection and longitudinal follow-up (Fig. 3b).
Future challenges and priorities for CTC research
Outlining key challenges in CTC biology on one hand and promoting their clinical implementation on the other is intended to help define research priorities that address the development of CTCs as superior sources of biomarkers for improved personalized cancer care (Box 1). A formidable task lies in the better understanding of tumour clonality and its relationship with CTCs. Are CTCs part of the most aggressive clones, and are they relevant to treatment decisions? How many CTCs need to be analysed to provide such information? In vivo models of spontaneous metastasis using barcoding to track tumour clones and subsequently analyse their molecular characteristics will be instrumental in this regard. Elucidating mechanisms that dictate intravasation and extravasation will provide alternative therapeutic targets for antimetastatic therapies. Although drug phenotyping of CTCs in patients with advanced disease is currently hampered by insufficient material and limited tools, the development of technologies that allow efficient capture and improved culture conditions for CTCs may enable real-time drug testing. Timing of CTC interrogation will be critical to enable meaningful and representative application of liquid biopsies. The current standard of clinical diagnostic procedures relying on traditional work schedules will require re-evaluation in light of the circadian dependency of tumour biology. Incorporating this knowledge into diagnostic algorithms could dramatically influence the clinical value of CTCs as a liquid biopsy analyte and even change treatment schedules to maximize clinical outcome. The timing of CTC dissemination also closely relates to the presence of DTCs249–251. Evidence for the early dissemination of CTCs19 and parallel progression of cancer23,252 argues for a detailed consideration of potential CTC reservoirs (primary tumour, macrometastatic and micrometastatic lesions, as well as DTCs) to unlock the full prognostic and predictive potential of CTCs. While single CTCs and CTC clusters are responsible for haematogenous seeding of proliferating macrometastatic tumours, logically they are by extension also the source of dormant and micrometastatic lesions. When and how CTCs and their clusters enter dormancy remains elusive, and this aspect warrants further investigation. This knowledge could lead to novel biomarkers and therapeutic strategies to target minimal residual disease and prevent further disease spread.
Priorities addressing the clinical application of CTCs should focus on improving the detection of cancer via liquid biopsies over SOC technologies. In the setting of early-stage cancers this is of particular importance but faces serious challenges regarding sensitivity and specificity. This could be addressed by benchmarking CTCs side-by-side with other circulating analytes (for example, circulating tumour DNA and exosomes) to increase the positive and negative predictive value, or by comparing and combining liquid biopsies with SOC modalities (Fig. 3b). CTCs have already been validated as independent prognostic markers, and have therefore extended the traditional TNM system. Beyond enumeration, we expect CTCs to unleash their potential as predictive biomarkers for patient stratification based on the detection of therapeutic targets or resistance mechanisms, including longitudinal surveillance. Whether treatment decisions based on CTC readouts will complement or even surpass treatment decisions based on standard tissue biopsies needs testing and validation in interventional and time-controlled clinical trials.
Box 1 Challenges and priorities in circulating tumour cell research and clinical implementation Unanswered questions in circulating tumour cell (CTC) biology: How can we distinguish disease-relevant CTCs from disease-irrelevant CTCs?
How truly representative are CTCs of tumour heterogeneity and the most aggressive tumour subclones? How many CTCs need to be analysed to answer this?
Which aspects of CTC biology will be crucial for the development of CTC- and metastasis-targeted therapies?
How do interactions between CTCs and non-neoplastic cells determine their metastatic tropism and capability?
How do physical features of CTCs determine their metastatic tropism and capability?
Can organotropism in CTCs be exploited for diagnostic and therapeutic purposes?
How can we increase the currently low culture efficiency of CTCs?
Are different culture conditions required for different CTC populations?
Unanswered questions on the clinical implementation of CTC biology: Can we use CTCs for the early detection of cancer and associated relapses?
How can we extend the clinical validity of CTCs beyond enumeration and prognostication?
How does the effect of circadian rhythm on intravasation and metastatic activity impact the timing of sampling and therapy?
How does the location of sampling (that is, tumour-draining vessel versus peripheral vasculature) influence CTC abundance and characteristics?
How do current treatments affect CTC abundance and metastatic abilities?
Are there clinically used therapies that unknowingly release CTCs?
Can we exploit the findings underlying CTC biology to interrupt the metastatic cascade and improve patient outcomes?
Can CTC-based drug phenotyping result in better treatment opportunities for patients with advanced cancers?
Conclusion
Metastasis remains a formidable obstacle to improve outcomes for patients with cancer as it corresponds to most cases of cancer-related death1,253. A deeper understanding of the biological processes underlying the capacity of tumour cells to seed tumours at distant sites is beginning to materialize, driven partly by rigorous investigations into CTCs as precursors of blood-borne metastasis. Early observations of CTC clusters190,254–256 and more recent dissection of their biological traits have highlighted their complexity but have also exposed vulnerabilities and, therefore, targetable opportunities. The intrapatient heterogeneity of CTCs offers an intriguing alternative to a comprehensive biopsy of a patient’s cancer, especially considering that CTCs may be enriched in metastasis-forming cells compared with the bulk of the tumour. A plethora of observational studies and a handful of interventional trials validating the use of CTCs for prognostication and therapy stratification have emerged over the past decade. Realizing the full potential of CTCs will, however, require an evolution from mere enumeration and prognostication towards highly controlled molecular characterization to develop precise predictive biomarkers. Technology and innovation are likely to pave the way for enhanced detection and detailed characterization of rare, yet precious CTC populations, thereby overcoming current diagnostic and therapeutic limitations.
Even now, major efforts are under way to move metastasis into the focus of therapeutic strategies (with the likes of the Metastasis Working Group)207. Successful translation of our knowledge of metastasis biology and implementation of efficient CTC capture methods in innovative clinical trial design and clinical–translational frameworks will substantially strengthen these efforts. We envision a future where CTCs might have a key role inpatient stratification and therapeutic decision-making by enabling the timely identification of aggressive tumour subclones, which is relevant for designing highly effective cancer therapies. Ultimately, targeting CTCs and their clusters may prevent further metastatic spread and favour survival.
Acknowledgements
The authors thank members of and collaborators with the Aceto laboratory for scientific feedback and discussions. A.R. is supported by University Hospital Zurich, the Kurt and Senta Herrmann Foundation, the Walter and Gertrud Siegenthaler Foundation and the Swiss Cancer Foundation. B.D.N.-S. is supported by University Hospital Zurich, the Sassella Foundation and the Iten Kohaut Foundation in collaboration with the USZ Foundation and the Theodor and Ida Herzog-Egli Foundation. The Aceto laboratory is supported by the European Research Council (101001652), the strategic focus area of personalized health and related technologies at ETH Zurich (PHRT-541), the Future and Emerging Technologies programme of the European Commission (801159-B2B), the Swiss National Science Foundation (212183), the Swiss Cancer League (KLS-4834-08-2019), the Basel Cancer League (KLbB-4763-02-2019) and ETH Zurich.
Author contributions
A.R., B.D.N.-S. and A.W. researched data and wrote the article. N.A. reviewed and edited the manuscript before submission. All authors contributed substantially to discussion and writing of the article.
Competing interests
N.A. co-founded and is a member of the board of PAGE Therapeutics AG, Switzerland, is listed as an inventor on patent applications related to CTCs, is a paid consultant for Swiss Re Group, Bracco Group, Tethis S.p.A., Thermo Fisher and ANGLE PLC, and is a Novartis shareholder.
Glossary
Adjuvant setting A clinical setting in which a therapy is given in addition to the primary therapy to maximize its effectiveness, in an attempt to reduce the risk of cancer relapse.
Anoikis The induction of programmed cell death (apoptosis) in anchorage-dependent cells (for example, epithelial cells) after their detachment from the extracellular matrix or neighbouring cells.
Antigen-agnostic Without a priori knowledge of antigenic epitope expression.
Biomarkers Measurable parameters of biological processes that have diagnostic, prognostic or predictive significance; they can be used to monitor pathological processes or therapeutic interventions.
Cancer vaccine A form of immunotherapy that uses tumour-associated antigens to activate and condition the patient’s immune system against the patient’s cancer.
Circadian rhythm Endogenous (internal) rhythms driven by biochemical oscillators with a period of approximately 24 hours that have major influences on the functions of an organism.
Cytapheresis A procedure in which various cells are separated from withdrawn blood and retained so that large amounts of plasma and cellular components can be harvested for transfusions and various other purposes.
Diapedesis The final step of the leukocyte extravasation cascade when leukocytes transmigrate across the blood endothelial cell barrier in response to acute inflammation.
Glycocalyx The protein or lipid-bound carbohydrate portion of the extracellular side of the cell membrane of eukaryotic or prokaryotic cells.
Immunomagnetic selection Isolation of cells via antibody-conjugated magnets, based on cell surface antigen expression.
Lipid rafts Specialized microdomains in the membrane of eukaryotic cells containing dynamic assemblies of cholesterol, sphingolipids and glycosphingolipids; they are involved in the activation of signalling cascades by favouring specific protein–protein interactions.
Metachronous lesions Two (or more) independent primary malignancies, of which the second (or third, fourth, fifth and so on) arises more than 6 months after the diagnosis of the first.
Minimal residual disease Malignant cells that remain in patients after therapy without symptoms or overt signs of disease.
Mitophagy The selective degradation of mitochondria by autophagy.
Necrosis Passive, uncontrolled cell death due to damaging insults (for example, the result of mechanical injury, exposure to toxins, hypoxia, hypothermia or infection), resulting in an uncontrolled release of cellular contents into the surrounding environment, promoting inflammation.
Organotropism The affinity for cancerous growth in particular organs, organ systems or somatic tissues leading to a nonrandom distribution of metastatic cancer cells.
Personalized medicine The tailoring of treatment to the individual patient based on the patient’s predicted response or risk of disease based on the fundamental understanding of the molecular basis of disease.
Phylogeny The study of relationships among or within cancer cells that focuses on observed heritable traits, such as DNA or amino acid sequences or morphology.
Private alterations Rare gene mutations that are usually found only in a single cell or in a small population of cells, as opposed to public mutations, which occur in founder clones and therefore all tumour cells.
Shear stress Tangential or frictional force tending to cause mechanical stress and deformation of a material by slippage along a plane or planes parallel to the imposed stress.
Stem-like A characteristic of cancer cells with traits akin to haematopoietic stem cells, including the ability to self-renew, differentiate, and generate progeny cells.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36494603 | PMC9734934 | NO-CC CODE | 2022-12-14 23:28:31 | no | Nat Rev Cancer. 2022 Dec 9;:1-17 | utf-8 | Nat Rev Cancer | 2,022 | 10.1038/s41568-022-00536-4 | oa_other |
==== Front
Schmerz Nachr
Schmerz Nachrichten
2076-7625
2731-3999
Springer Vienna Vienna
87
10.1007/s44180-022-00087-y
Presidents's Corner
Junge Schmerzmedizin
Young Pain MedicineStromer Waltraud [email protected]
12
1 Abteilung für Anästhesiologie und Intensivmedizin, Landesklinikum Horn, Horn, Österreich
2 Österreichische Schmerzgesellschaft (ÖSG), Wien, Österreich
7 12 2022
2022
22 4 194194
© The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, ein Teil von Springer Nature 2022
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
issue-copyright-statement© Springer-Verlag GmbH Austria, ein Teil von Springer Nature 2022
==== Body
pmcSehr geehrte Damen und Herren, liebe Kolleg*innen!
Auch 2023 wird die Österreichische Schmerzgesellschaft (ÖSG) eine Reihe neuer Initiativen starten. Für mich ganz wesentlich wird dabei das Bemühen, Jungärzt*innen für die Schmerzmedizin zu begeistern und sie – im Idealfall – zu einer Mitarbeit in unserer Fachgesellschaft einzuladen. Damit wollen wir rechtzeitig die Weichen für die Zukunft der ÖSG stellen und deren Entwicklung nachhaltig absichern. Den Auftakt unserer Bemühungen bildet eine Fortbildungsveranstaltung, deren Programm wir sehr zielgerichtet auf die Anliegen und Bedürfnisse von Jungmedizinern ausgerichtet haben. Die Veranstaltung trägt den Titel: „Zukunft der Schmerzmedizin: Rising Stars – The Next Generation“, und findet am 4. März 2023 in Linz statt (Online-Anmeldung unter: bit.ly/RisingStars2023).
Auch in den SCHMERZ NACHRICHTEN wollen wir unserem Nachwuchs mehr Raum für ihre Ideen und Informationsbedürfnisse geben. Die neu implementierte Rubrik „Die junge Schmerzmedizin“ bietet ab der Ausgabe 1/2023 eine Plattform an, gestaltet von Jungmediziner*innen für Jungmediziner*innen. Geplant für 2023 ist in den SCHMERZ NACHRICHTEN 2023 außerdem ein „Schmerzquiz“, das in Form von Case Studies Fragen zur leitlinienkonformen Schmerztherapie stellen wird. Unter den richtigen Antworten verlosen wir eine Gratisteilnahme beim nächsten ÖSG-Kongress.
Ich lade alle interessierten Jungmediziner*innen ein, sich mit ihren Ideen einzubringen und sich zu engagieren. Im ÖSG-Vorstand wird Dr. Thomas Weber die Aktivitäten koordinieren (Kontakt: [email protected]).
Österreichische Schmerzwochen 2023
Eine bereits etablierte Initiative, um mehr Awareness für die Schmerzmedizin auch außerhalb unserer Expert*innen-Community zu erreichen, sind die Schmerzwochen. Den Startpunkt der Schmerzwochen 2023 wird eine Pressekonferenz am 18. Jänner 2023 in Wien bilden, in deren Rahmen der ÖSG-Vorstand über aktuelle Entwicklungen in der Schmerzmedizin informieren wird. Eingeladen werden dazu nicht nur Journalisten der Fachpresse, sondern auch von Publikumsmedien, Fernsehen, Radio, Tageszeitungen etc.
Um das Thema Schmerz nicht nur punktuell in der Öffentlichkeit zu platzieren, werden wir zusätzlich auch 2023 thematische Quartalsschwerpunkte setzen und darüber in Form von Presseaussendungen und Veranstaltungen berichten:Quartal I: COVID-19: Schmerztherapie bei Long-COVID etc.
Quartal II: Raritäten von Kopf bis Fuß: Viren und Bakterien als Auslöser chronischer Schmerzen, Morbus Fabry etc.
Quartal III: Female Pain: Chronic Pelvic Pain, Vulvodynie etc.
Quartal IV: Invasive Schmerztherapie: SCS/implantierte Schmerzpumpen, Schmerzblockaden etc.
Weiterführen werden wir 2023 auch unsere intensiven Gespräche auf politischer und Sozialversicherungsebene. Ein zentraler Verhandlungspunkt ist aktuell ein neues Honorierungssystem schmerztherapeutischer Maßnahmen. Damit soll die qualitative Schmerzversorgung unserer Patient*innen vor allem auch für niedergelassene Ärzt*innen lukrativer – und damit attraktiver – werden.
Ihre
Waltraud Stromer
Interessenkonflikt
W. Stromer gibt an, dass kein Interessenkonflikt besteht.
QR-Code scannen & Beitrag online lesen
Hinweis des Verlags
Der Verlag bleibt in Hinblick auf geografische Zuordnungen und Gebietsbezeichnungen in veröffentlichten Karten und Institutsadressen neutral.
| 0 | PMC9734935 | NO-CC CODE | 2022-12-14 23:28:31 | no | Schmerz Nachr. 2022 Dec 7; 22(4):194 | utf-8 | null | null | null | oa_other |
==== Front
Early Child Educ J
Early Child Educ J
Early Childhood Education Journal
1082-3301
1573-1707
Springer Netherlands Dordrecht
1430
10.1007/s10643-022-01430-2
Article
Managing Disruptions in Early Care & Education: Lessons from COVID-19
Cook Kyle DeMeo [email protected]
1
Ferreira van Leer Kevin 2
Gandhi Jill 3
Ayala Carolina 2
Kuh Lisa P. 4
1 grid.189504.1 0000 0004 1936 7558 Boston University, Boston, MA USA
2 grid.253564.3 0000 0001 2169 6543 California State University, Sacramento, Sacramento, CA USA
3 grid.21729.3f 0000000419368729 Columbia University, New York, NY USA
4 Seattle, WA USA
6 12 2022
112
16 11 2022
© The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Families face challenging decisions about early care and education (ECE) for their children. Decisions about what is best for each child and family are constrained by family and contextual factors and are prone to disruptions. This study provides a descriptive look at patterns of ECE settings children were in the year prior to kindergarten, beginning in Fall 2019 through Spring 2021, a period during which most ECE arrangements were disrupted by the COVID-19 pandemic, and into the 2020–2021 kindergarten year. Analyses of survey (N = 121) and interview (n = 25) data from families whose children entered kindergarten in Fall 2020 revealed multiple and cascading disruptions during this time. Disruptions were nearly universal, and families made continual accommodations as they juggled employment needs and children’s ECE needs. Findings from this study have implications for how actual and anticipated disruptions may have a greater influence on families’ child care decision-making into the future.
Keywords
Early education
Childcare
Disruptions
COVID-19
http://dx.doi.org/10.13039/100005165 American Educational Research Association American Educational Research Association Cook Kyle DeMeo
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pmcFamilies have diverse options for early care and education and (ECE) settings for their child in the years before kindergarten. Yet, decisions about the setting that is best for each child and family are constrained by local options and availability, cost, location, and the family’s specific needs and preferences (Meyers & Jordan, 2006). These arrangements are also subject to disruptions based on changing parental employment and high rates of turnover within the early childhood workforce. This has been particularly relevant during the COVID-19 pandemic, during which families faced disruptions in their children’s ECE arrangements due to mandatory closures, health risks, employment changes, and other challenges (e.g., Malik et al., 2020; Patrick et al., 2020). There is limited research on ECE disruptions, yet emerging evidence suggests that while some families are able to anticipate some disruptions and utilize back-up providers, unplanned and forced disruptions can have larger implications, such as on maternal employment instability (Scott & Abelson, 2016; Spiers et al., 2015), the child’s education access and outcomes, and the family resources and well-being.
The objectives of this study were to (1) gain a better understanding of how families experienced unplanned ECE disruptions during the early months of the COVID-19 pandemic; and (2) how they managed, adapted to, and made choices within an environment of dynamic and unpredictable constraints. Disruptions are a regular part of families’ experiences navigating ECE, and the lessons learned from the mass disruptions during the start of the COVID-19 pandemic have implications for the future.
Role of Disruptions
Literature on childcare disruptions provides some insight into the ways the COVID-19 pandemic and the resulting educational and employment disruptions may influence ECE decision-making. Previous research has illustrated the interconnected nature of work and childcare, documenting the challenges families face coordinating work and childcare schedules, especially families with low incomes (Henly & Lambert, 2005; Sandstrom & Chaudry, 2012; Speirs et al., 2015). For families with low-incomes, disruptions to childcare often impact parents’ employment, resulting in unexpected absences, shortened hours, loss of pay (Ferreira van Leer et al., 2021; Usdansky & Wolf, 2008), or even in a parent leaving or losing employment (Miller, 2006). There is less research examining how work disruptions impact family and child well-being. Nonetheless, scholars have increasingly explored the mechanisms through which changes to employment impact children’s development. The Family Stress model posits changes to employment influences parental stress, resulting in more negative parenting and parent-child interactions (Conger et al., 2000). Additional evidence suggests unstable work schedules are associated with decreased parent well-being (Ananat & Gassman-Pines, 2021) and lower-quality parent-child interactions (Henly et al., 2006). Together, research suggests that the types of disruptions resulting from the pandemic – school closures and employment changes – are likely among the most consequential disruptions for families, potentially resulting in parental stress, loss of income, and less access to positive learning environments for children (Chen et al., 2021; Hanno et al., 2022; Patrick et al., 2020; Waxman & Gupta, 2021).
Disruptions During COVID-19
Widespread closures of schools and childcare programs at the start of the COVID-19 pandemic in March 2020 resulted in childcare disruptions for almost all families in the U.S. (Lee & Parolin, 2021). These nearly universal disruptions had implications for families’ work schedules, resources, and well-being (e.g. Chen et al., 2021; Hanno et al., 2022; Patrick et al., 2020; Waxman & Gupta, 2021). Research that examined children and parents’ well-being between March 2020 and June 2020 in households with children under 18 found that 24% reported regular loss of childcare, 27% worse mental health for themselves, and 14% reported more behavioral issues for their children (Patrick et al., 2020), with potentially higher rates for families with young children. Using longitudinal data on families with young children in Massachusetts, Hanno and colleagues (2022) (2021) found significant increases in children’s behavioral challenges, parental mental health issues, parental stress, household chaos, and parent-child conflict after the March 2020 shutdowns compared to the same sample at two earlier time points.
As schools and programs made different decisions about reopening based on federal, state, and local guidance and community positivity rates, families continued to face disruptions and had to make urgent decisions about the types of care to use, their work schedules, and their comfort levels with various risk factors. An analysis of mobile phone data across the United States throughout the pandemic found that two-thirds of child care centers closed in April 2020 (Lee & Parolin, 2021). In December 2020, an analysis of national survey data found that nine months into the pandemic, one out of five adults were working fewer hours than they wanted due to childcare responsibilities (Waxman & Gupta, 2021). In April 2021, one year into the pandemic, Lee and Parolin (2021) found that one-third of child care centers continued to be closed. An analysis of the U.S. Census’s Household Pulse Survey between April and June 2021 found that approximately 1 in 5 households with children reported a child care disruption due to COVID-19 (Chen et al., 2021). These families often reported leaving or losing a job, cutting work hours, supervising children while working, or using paid leave as a result of this disruption.
Accommodation Model
This study is guided by the accommodation model (Chaudry et al., 2010; Meyers & Jordan, 2006) as a framework to understand families’ dynamic childcare decision-making processes. The accommodation model, first outlined by Meyers and Jordan (2006), synthesizes predominant theoretical models of decision-making across the behavioral sciences to better describe how families make decisions about ECE. First, the model draws on the economic consumer choice framework which theorizes that individuals utilize the information at their disposal to make rational, discrete decisions to meet their preferences. Second, the model draws on heuristics and biases frameworks from behavioral psychology (Kahneman & Tversky, 1979). These frameworks posit that individuals utilize heuristics – mental shortcuts or generalizations – to more quickly understand their environments and make decisions. Third, the accommodation model leverages sociological network theory which posits that social interactions with others shape individual decisions (Pescosolido, 1992). This theoretical perspective emphasizes the role of the social network and interpersonal ties. Lastly, Chaundry & colleagues (2010) further refined the accommodation model by grounding it in the life course model of family adaptive strategies (Moen & Wethington, 1992). Life course models center families, rather than individuals, as the locus of decision-making. Through a lens of the family, the life course model asks researchers to attend to the entire family unit, accounting for factors such as whether siblings are present, the birth order of children, children’s ages, and parent’s life and career trajectories when examining the decisions such as childcare. Thus, the temporal dimension of family decisions, a tenet of the life course model, is an important consideration for the accommodation model.
Rather than framing the childcare decision-making process as a static, individual choice, the accommodation model frames the ongoing selection of ECE as an accommodation of competing demands and expectations at multiple levels. For example, parents may hold a preference for a certain type of care arrangement, but their work and family schedules may dictate the types of care that are feasible for them. One of the potential consequences of these constrained choices is that parents may be forced to rely on a care arrangement that works for their families in the short term, but may not be a stable form of care in the long term, making disruptions evitable. The accommodation model is particularly salient when considering the complexity of decision-making during a pandemic, when choices were constrained by both contextual factors based on availability of open programs in a community, lack of information and changing information based on local public health guidelines, and individual family needs based on flexibility (or lack of flexibility) of work schedules, tolerance for health and safety risks, back up care options for disruptions, and overall family needs and preferences.
Present Study
Within the context of a research-practice partnership in a small northeastern United States city, this study used a mixed methods design to provide a descriptive look at patterns of children’s ECE settings from the year prior to kindergarten and into the kindergarten year. The study includes data collection about ECE use during a time of multiple disruptions for families: Fall 2019 through Spring 2021, inclusive of a period when all formal ECE arrangements were closed in the city (March-June 2020) and when the school district was fully remote for kindergarten (September 2020-April 2021). The data was collected in Spring and Summer 2021 providing a prospective look at ECE use during this time period and a retrospective look from Fall 2019-Spring 2021. This study addressed the following descriptive questions:
What are the patterns of ECE arrangements and disruptions for families over the year before and during kindergarten, including the COVID-19 pandemic?
How did families manage and adapt to disruptions in ECE?
Method
This study used an explanatory-sequential mixed methods design (Creswell & Plano Clark, 2017), with a quantitative survey phase first and an open-ended interview phase second. This method allowed for a deeper descriptive look at family patterns of ECE and the ways families experienced disruptions. Using multiple data methods allowed us to gain a better understanding of challenges faced by families beyond what either data source could show alone.
Instruments & Procedures
An online survey asking a series of questions about ECE arrangements from September 2019 through spring 2020 was sent to all kindergarten families (approximately 380) in a mid-sized school district in the northeastern United States in Spring 2021 as part of a larger study on ECE decision-making. One hundred and fifty-five participants responded to the survey. Questions specific to COVID-19 were included at the end of the survey and some participants did not respond to these questions. Since this study focuses specifically on COVID-19, the analytic sample includes survey participants who responded to at least 45% of survey questions and had a child who was in non-parental care for more than 5 h per week in the fall before their kindergarten year (N = 121).
Survey response data were linked to child and family demographic information from district administrative data to minimize the burden on survey participants. Following survey data collection, we followed up with a subsample of families for virtual, one-hour interviews (n = 25) in Summer 2021. The survey and interview protocol were developed by the research team with input from community partners, and were institutional review board (IRB) approved. All interview participants received a $20.00 gift card and survey participants were entered into a drawing to win one of two $50.00 gift cards. All participants gave written consent for the survey and interview.
Survey
The survey consisted of approximately 40 closed-ended questions, with modules on household information, ECE and work arrangements from September 2019-March 2020 (pre-pandemic), ECE arrangements from March 2020-August 2020 (during the pandemic), changes in family work arrangements in March 2020 and the experience of transitioning into kindergarten in Fall 2020. The survey was available in English, Spanish, Portuguese, and Haitian-Creole.
Interview
The interview protocol aimed to build on the survey and gain a rich description of ECE decision-making prior to the pandemic and the changes following the onset of COVID-19 through the end of the child’s kindergarten year. Interviews were conducted in English or Spanish. Unlike the survey, the interviews also asked questions about child care needs during the kindergarten school year when the school district remained in virtual learning.
Sample
Survey
Survey respondents were primarily mothers (83%), with a smaller number of fathers (15%) or other caregivers (2%). Families who participated in the survey were 75% white, 8% Asian, 4% Black, and 12% multiple or another race. 17% of families identified as Latinx. Families spoke multiple languages at home with 67% speaking English as their home language, 13% Spanish, 6% Portuguese, and 16% other (other included 15 different languages reported by 3 or less respondents). 91% of participants completed the survey in English, 5% in Spanish, and 4% in Portuguese. Children whose parents completed the survey were 5.85 years old on average as of January of their kindergarten year, 48% were female, 21% were eligible for free/reduced priced lunch, and 14% were eligible for special education services.
On average, families reported using between 1 and 3 arrangements for their child the year before kindergarten prior to the COVID-19 pandemic (September 2019-March 2020), with an average of just over one (M = 1.37; SD = 0.58). Families reported multiple arrangements, including public school prekindergarten, local center-based care, Head Start, family childcare programs, and family/friend/neighbor care. The most common arrangements included: the district’s public-school prekindergarten program (45%), local center-based care (35%), and family/friend/neighbor care (28%; see Table 1).
Table 1 Characteristics of survey participants
Characteristic Mean (SD) %
Primary ECE Use: Spring 2020 prior to COVID
Public School Prekindergarten Program 45
Center-based care or Family Child Care Program 37
Head Start 12
Family, Friend and/or Neighbor Care 28
Child Age (years) at start of kindergarten 5.85 (0.26)
Number of adults in household 2.24 (0.87)
Number of children in household 1.86 (0.63)
Female 48%
Race/Ethnicity
White
Black
Asian
Multiple or Other
76%
4%
8%
12%
Latinx 17%
Home Language
English
Spanish
Portuguese
Other
67%
13%
5%
16%
Preferred Language for School Communication
English
Spanish
Other
91%
4%
6%
Free/reduced lunch eligible 21%
Special education eligible 14%
Note. N = 121 for primary ECE type and N = 120 for all other variables. Some participants used more than one ECE type. Rounding may also result in columns not equal to 100%
Interviews
Interview participants were recruited from the survey sample with outreach from the research team and the school district. Purposive sampling enabled us to maximize inclusion of non-English speaking households and variation in the types of ECE settings. Outreach was conducted in English, Spanish, Portuguese, and Haitian-Creole with additional outreach efforts to recruit families with low-incomes and families who spoke a language other than English at home. Of the 25 interview participants, 7 were fathers, two were single parents, two had multi-generational households with more than two adults, and one was part of a same-sex parented household. Interviewees utilized center-based care outside of the city (32%), the district’s public school preschool program (28%), center-based care or a family child care program in the city (28%), and Head Start (12%) in the year before kindergarten (up to March 2020). The majority of families who participated reported speaking English at home. Families also spoke Spanish, Portuguese, and Nepali, and other languages. Households were racially and ethnically diverse with seven families who identified as Latinx or discussed one parent with origins from Latin America, four families identified as Asian and white, and two families identified as white and another race/ethnicity. Five households reported their child was eligible for special education and four reported they were eligible for free/reduced lunch (Table 2).
Table 2 Characteristics of interview participants
Characteristic n
Primary ECE Use: Fall 2019
Public School Prekindergarten Program 7
Center-based care or Family Child Care Program in city 7
Center-based care in nearby town 8
Head Start 3
Reported home Language
English 16
Spanish 5
Other 5
Race/Ethnicity
White 23
Other 2
Asian 5
Latinx 7
Free/reduced lunch eligible 4
Special education eligible 5
Note. n = 25. Administrative and interview data used. One interview participant missing from administrative. Other is included under race/ethnicity for participant privacy. Families could be represented under more than one race/ethnicity or language therefore numbers may not add up to 25.
Analytic Plan
To address our research questions, we conducted descriptive analyses of survey data and linked school district administrative data to present demographic means, standard deviations, percentages and cross-tabulations. Qualitative data was transcribed by three members of the research team, two whom are bilingual Spanish-English speakers. Two members of the research team analyzed the data utilizing a modified social constructivist grounded theory analysis approach (Charmaz, 2006). This began with inductive, line-by-line open coding. In this stage, researchers labeled each line of text in the transcript to describe, summarize, or briefly interpret the content. For example, a line of a transcript stating, “my manager is cool and everything. And he knew I was struggling and doing the best I could, but it was clear in meetings – I’m talking to various people and then have to go, ‘I’m sorry, emergency’ and leave the zoom due to [the] kids,” was coded as “having an understanding manager” and “needing to leave meetings for child.” Half of the interviews were separately coded by both researchers who then met to discuss the coding to ensure shared understanding across codes.
After completing open-coding, researchers reviewed all the codes generated and began grouping them into axial codes or themes. In this process we reviewed codes for informational redundancy and scope, identifying patterns in the data that provided inferences related to our research questions. For example, the aforementioned codes were grouped with others into an initial theme, “online school and working from home was a hard balance for parents.” These initial themes were used to go back to the data, where axial codes were applied as labels to the transcripts to ensure that they were grounded in the data. This process allowed researchers to compare data across interviews, better identify the diverse examples captured, and ensure the themes were cohesive in their description and characteristics. This was further explored through conceptual memos researchers wrote throughout the process where they elaborated on the data they labeled with the axial codes to begin describing the themes and their characteristics as they related to the interviews. This resulted in axial codes being modified to better represent the data. Continuing the example, as we applied the label, “online school and working from home was a hard balance for parents” we identified greater number of examples of participants sharing similar sentiments between managing their work, child’s schooling, and care. Thus, the theme was modified and entitled, “Juggling Employment Arrangements with Children’s Education and Care Needs,” to better represent this ongoing dynamic throughout the pandemic. Iterative cycles of coding and conceptual memoing were used to finalize the set of themes that emerged from the data (presented below). The themes were then integrated alongside quantitative findings and examined side-by-side for congruity. The qualitative data and quantitative data were used to triangulate the findings for this study to develop a holistic understanding (Anfara et al., 2002) of how families in this sample navigated ECE disruptions during the pandemic. The research findings from both data sources were integrated and presented together in the results, including a joint display (Fig. 1), commonly used in mixed methods research to integrate and present findings from quantitative and qualitative data (Creswell & Plano Clark, 2017).
Fig. 1 Joint Display of Integrated Results
Results
Across the quantitative and qualitative data, we found that the overarching theme was that child care disruptions were experienced by all families, making them universal, and families made continual accommodations as their needs changed. This finding was the core concern identified by participants and a theme across survey and interview findings. Throughout the pandemic, participants experienced multiple disruptions to their work and child care arrangements. An examination of the interviews revealed specific patterns about the timing of disruptions for families. Some of these disruptions were anticipated, such as the transition to kindergarten in fall 2020. In contrast, other disruptions, such as extended closures of child care centers and remote learning, were unexpected and more difficult to accommodate.
Below we detail the specific factors that shaped families’ child care strategies during the pandemic and the four themes that emerged. For a summary of findings and evidence to support them see Fig. 1.
Theme 1: Families Faced Multiple Disruptions
Responses from surveys paint a picture of the almost universal nature of disruptions at the start of the pandemic. The vast majority (95%) of survey respondents reported that their primary ECE setting for their child closed in March 2020. Formal programs and schools in the city were mandated to close from March-June 2020, with separate programs open only to children of essential workers. Participants reporting that their program did not close included a small percentage of families using private centers and Head Start programs outside of the city.
We found that in addition to this initial disruption at the onset of the pandemic in March 2020, disruptions were common during the following periods: the summer of 2020, the start of the kindergarten year in fall 2020, the winter of 2020–2021, and the resumption of in-person learning within the public school district in spring 2021. These specific time periods often yielded new disruptions which families adapted to through shifts in existing arrangements or by creating new arrangements.
Many interview participants reported that they managed childcare themselves at home during the summer of 2020. Families described uncertainty regarding the pandemic and concerns regarding health and keeping their children at home. For many families, needs changed again in September 2020 when kindergarten began fully remotely. After multiple months of caring for children at home, many parents described attempting a variety of ECE arrangements and strategies as children began their remote year of kindergarten, with varying success. Families described hiring babysitters and “tutors” to support their children with virtual learning, or enrolling their children in limited outdoor programs to support their socialization. We saw a pattern of multiple disruptions and childcare instability as a result of the pandemic during the first five months that began to stabilize in the fall. However, dates for the return to in-person learning for kindergarteners were delayed multiple times and most children did not return to full-time in-person learning until April 2021.
Theme 2: Lack of Availability & Lack of Information
Across interviews parents shared how a lack of easily accessible information and insufficient external child care resources made navigating potential care and education options difficult throughout the pandemic. After the initial shutdowns in March 2020, families began to recognize that the closures may not be brief and began considering new arrangements for work and care. Families described difficulty in finding information such as opening dates, hours and cost, and child eligibility. This included information about child care centers, summer camps, and the public elementary school system. Specifically, parents who searched for center-based child care options or summer programming throughout the pandemic cited difficulty in finding information regarding whether programs planned to reopen. Similarly, families cited lack of information regarding potential reopening from the school district at various points which hindered future planning. One interviewee shared, “They didn’t tell us anything. Everybody’s asking what’s going to happen….When you can open the school? ‘We don’t know. We don’t know. We don’t know’ is what we were told.” Citing anxiety regarding the lack of information by the public school system, a small number of families moved to other school districts or private schools. Another parent shared,We thought it was going to last a few weeks, then we thought it would be three months, the amount of craziness going on in our district with politics. This thing could go on through next school year, right? What if, right, what if we’re in September 2021 and we’re still dealing with this garbage? What is our backup plan? We’re not going to move, so let’s apply to a private school. So, we applied to a few private schools, it was just a backup plan.
While parents understood the difficult circumstances and unforeseeable future, they expressed frustration with the lack of information and described how it hampered their ability to make decisions and multiple disruptions to their work and care arrangements arose.
Parents engaged in trying to find information in various ways. Interviewees discussed checking websites, calling providers, utilizing resources provided by their employer, talking with personal networks, and utilizing social media. Multiple interviewees discussed specific Facebook or WhatsApp groups for parents in the town where information about school closures and openings, and child care availability was shared. Many parents expressed the need for a directory on all of the care options in the area that would include details such as reopening dates, availability, schedule, COVID-19 safety protocols, and cost. A parent expressed:I’m not sure if the hours were universally available, either, across daycares. So there’s a bit of legwork picking up the phone or emailing and gathering the information to make a reasoned choice. That is challenging…Asking for better visibility into what the expected hours are, in the winter, and spring, because right now they’re COVID hours at some of the places, so limited hours.
Alongside the lack of information, parents consistently described a scarcity of available ECE options during the pandemic. Programs were often closed, had reduced availability, or limited schedules. This was most acute for parents of children with special needs, many of whom described limited services that met their children’s specific needs. Multiple parents also described programs reducing or stopping services altogether. One parent shared, “I see other families being able to do these programs. But if your kid has a disability, and a behavioral disability, it’s like there’s nothing for you. There’s no safety net.” Furthermore, they found it difficult to find information regarding available options that were appropriate for their children.
Theme 3: Juggling Employment Arrangements with Children’s Education and Care Needs
A primary tension described by parents in managing disruptions were the ways employment arrangements and ECE decisions influenced each other. Families described changes to work arrangements including modality, schedules, and expectations. Some families described individual parents taking leave or stopping work. These changes in work were compounded by the initial child care and school closures at the onset of the pandemic. Together, families described how work and child care decisions influenced each other.
When reporting about the work situations of adults in the household at the onset of the pandemic, 94% of survey respondents reported at least one change in their work situation. When selecting all situations that applied to them, 70% of participants had at least one adult in their household who was working from home, and 16% had an adult in the household considered an essential worker. Other changes included having hours cut (11%), workplace closures (22%), and having lost or quit their job (20%). In interviews, parents described how remote learning shifted expectations of parents’ roles in their children’s education. Parents felt they were expected to give greater support and supervision during remote classes, including logging children into remote classes and ensuring children were participating appropriately. More than half (55%) of survey respondents reported that they needed some childcare in order to be able to work during the start of the pandemic. Together, shifting work and education expectations often led to the negotiation of competing demands.
Families adopted new strategies to accommodate these competing demands. To address household ECE needs at the onset of the pandemic, survey respondents turned to grandparents (19%), siblings (2%), other relatives (16%), child care centers for children of essential workers (2%), and paid nannies/babysitters (33%). Among the families that reported needing child care to work, 57% indicated that they cared for their child(ren) themselves while simultaneously working from home. Interviews with parents who had the opportunity to work remotely provide additional insight into the strategies that were used to accommodate work and care. Some two-parent families described dividing their work into shifts and taking turns to provide care or supervise remote learning. One parent shared:My wife and I had split the day in half basically. So, I got to work in the morning, she got to work in the afternoons, and we didn’t have any weekends anymore. And we just like did that sort of seven days a week.
Some interviewees recounted how work expectations remained consistent with pre-pandemic levels and struggling to keep up with the expectations alongside increased child care responsibilities. This tension resulted in the adoption of new strategies such as finding nonparental care (e.g., tutors or nannies) or reducing their job responsibilities (e.g., cutting hours). This is exemplified by a parent who explained:We tried to manage it between the two of us and try to keep up with the demands of work. I think by the end of April, we realized it wasn’t working. And we ended up hiring a nanny to take care of the two kids.
Parents also described relying on television or other multimedia to occupy children while they were working. These strategies changed over the course of the pandemic as families wrestled with the long-term nature of remote school and work and new needs to support remote learning when kindergarten started.
Other families continued to work in-person and also adopted new strategies to juggle work and care needs. Some of these parents brought their children to work, asked coworkers to watch children, or made requests of family members to care for their children. One parent turned to her oldest daughter to watch her younger daughter:My oldest, she’s my lifesaver. During her lunch break, because she was doing remote as well, she would run with my little one, her sister, to the daycare program, drop her off, because I think it was at 12:30. So she would drop her off and then run back to start her class. She would literally miss her lunch.
Some of these parents discussed strategically using sick days to take care of their children when arrangements fell through. One parent described taking family medical leave to care for children when it was made available but returned to work in the spring of 2021.
Theme 4: Concerns About Children’s Development Drove some Decisions
Although 95% of survey respondents reported that their primary ECE arrangement closed in March 2020, our interviews indicate that even for families whose programs did not close, many decided to pause use of the program/provider based on health and safety concerns, suggesting that disruptions were nearly universal. About one quarter of the interview sample had a child who was attending the city’s public school prekindergarten program and approximately half attended a center-based program or Head Start. 76% of survey respondents reported that online learning was offered to them during spring 2020.
However, only 31% of survey respondents reported that their child always participated in online learning (30% never and 37% sometimes) during the start of remote learning in March-June 2020. In interviews, parents expressed concern about the quality of learning during remote classes. Parents noted shorter class sessions, limited attention spans, greater distractions, and changes in pedagogy due to the virtual format. Interviews with parents detailed mixed levels of engagement across children through the following school year (2020–2021) during the period of remote kindergarten. Many interviewees felt that their children needed greater supervision from parents or other adults during the remote classes. One interviewee shared, “She’s fidgeting a lot. And you know, she needed a strong hand. Because if you don’t do that, then she’s going to go and watch TV, she’s going to go into dreamworld… she’s not going to focus.” Many parents worried that the changes in learning due to the virtual format negatively influenced their children’s education compared to in-person learning and particularly pointed to their beliefs regarding kindergarten as a critical age for development.
In contrast, some parents interviewed did not express concern over the perceived lack of learning, citing their beliefs that kindergarten was not an academically crucial time or that their children were sufficiently prepared by previous educational experiences. Some also felt that their child received “secondhand kindergarten” from older siblings. While academic learning was the subject of many parents’ discussions, they often noted the speed at which their children mastered new technologies and children’s resourcefulness with virtual classes in interviews.
These considerations influenced child care arrangements. Interviews with families revealed that some families hired tutors or nannies to support children with remote schooling. This was the case with the aforementioned parent who continued, “So we needed to hold her, and I couldn’t do that because I have to work, right? So, I put the money in hiring someone.” Other families turned to older siblings or supplemented remote learning with their own educational activities to address their concerns.
Parents were also concerned about the lack of social interactions for children and themselves. They worried about their children’s social development as they remained at home and isolated from peers. Many interviewees pointed to their beliefs that the kindergarten years were crucial for building friendships and social development and were worried about the lack of relationships their children made. Driven by these concerns, some parents enrolled their children in city-run programming that allowed children to meet outdoors and engage in supervised activities. One illustrated her decision:It was just a play-based thing... But it was just obvious this kid needed to play… And I’m desperate to see her play with other children. So that went really well. She enjoyed it. It was really for both of us.
Other families formed “pods” with other families, where they negotiated norms regarding visiting others and allowed their children to attend remote school and play together. Parents navigated these decisions while considering their perceptions of pandemic risks.
Parents also felt that they, themselves, lacked social interactions with other parents. They noted the differences in community building that existed around their children during in-person school. One parent shared:I remember, at the end of the [kindergarten] year, we were actually finally meeting some of the families and I was, you, you live literally a block away, I mean, counting the number of houses that we are from each other. And we just didn’t know that. Because we never had the opportunity to really do that.
As children returned to in-person learning in spring 2021, parents commented on the changes they noted in their children. They shared that they observed greater learning, excitement about school, and budding friendships. These observations were often used to bolster their concerns about the perceived loss of learning or social deprivation that occurred throughout the pandemic. This is encapsulated by one parent who shared the changes she saw in her daughter after they transitioned to in-person learning:“I think she had tremendous academic growth the last two months of school, like she went from really not being able to read at all, to all of a sudden, like, reading really well. And I think her social, like the social relationships, after it really took off, like a lot, like a lot, the in-person was much better.
Moreover, parents shared that the transitions to in-person learning were largely smooth and appeared to be driven by children’s excitement to be around their peers in school. A smaller number of parents noted increased anxiety in their children as they returned to in-person school.
Discussion
Our study finds that families whose children entered kindergarten in fall 2020 experienced multiple and cascading disruptions in the year before and during kindergarten, which parents described as having implications for children’s learning and family stress. Across the two data sources, it was clear that families universally experienced child care disruptions, with all families in the study experiencing some disruptions during this time period. Families made continual accommodations as their needs changed. While there is hope that mass shutdowns of ECE programs will not happen again in the near future, disruptions for multiple reasons are regular challenges for families with young children. Although these findings focus on the specific experiences of a sample of families, they have implications for ways systems can provide wider universal supports to meet more family needs, while acknowledging the unique needs of individual families. Families faced challenges addressing these multiple disruptions as they balanced work and child development needs, lacked information and lacked availability of options that met their family needs. These challenges drove decisions and accommodations families made within this very constrained decision-making environment. Below we consider implications of these findings and how they fit with the existing literature.
Universal Disruptions but Unequal Consequences
While disruptions were universal, the effects were not always equal in that families who were not able to work remotely, families that did not have resources to hire babysitters and tutors, and families who had children with specific needs faced additional challenges. This is consistent with other research that has highlighted that the pandemic’s challenges have been experienced differently by families with different resources, needs, and preferences (Jalongo, 2021).
The abrupt school closures made it challenging for many young children to adjust from in-person learning to completely remote. This was especially true for children with special needs. Some families expressed their frustration with the lack of resources they had access to for their children with special needs. Averett (2021)’s research on remote learning for children with disabilities had similar findings and explained how it was a struggle for families to accommodate their children’s needs due to the inability of schools to provide services remotely. In addition, Shapiro & Bassok (2022) found that caregivers of children with disabilities had concerns about their children’s development and had a hard time finding programs that met their needs
Competing Demands of Work and Children’s Education
These challenges reverberated across different aspects of family life. The challenges of balancing working from home while supporting their child(ren)’s education has been consistently found in research across parents with various professions and work experiences (Bender et al., 2022; Garbe et al., 2020). For example, Bender et al., (2022) found that participants in their study explained the difficulty in having to establish new schedules that accommodated all family needs, with participants often using the word “chaotic” to describe conflicting needs and schedules. The stress families felt supporting remote learning has also emerged in other studies, with families feeling overwhelmed as they navigated competing demands (Garbe et al., 2020).
These disruptions were often a result of changing child care and education programming and parents’ employment. At the start of the pandemic, survey participants reporting making changes to their work to accommodate caring for their child. Similarly, other studies show that parents who experienced a disruption to child care due to COVID-19 often reported cutting hours at work, supervising children at home while working, and leaving or losing their job (Chen et al., 2021). We found that parents often had to sacrifice the time they were working in order to tend to their children’s academic needs.
Isolation for Children and Parents
Social isolation and remote education drove concerns about the lack of social interactions for children as well as adults, with additional concerns for their children’s academic preparation. The concerns about children’s lack of social interactions and academic preparation during the pandemic have been found in studies with other parents regarding education during the pandemic for young children (Garbe et al., 2020; Timmons et al., 2021). Similar to other studies, we found that the social isolation concerns went beyond children and were challenges parents reported about their own well-being (Egan et al., 2021).
When remote learning became a more long-term solution than originally anticipated, parents in our sample grew concerned for their child(ren)’s learning outcomes as they progressed through kindergarten. Some parents felt that it was important for their child(ren) to have the fundamental learning outcomes from kindergarten because it can construct the academic foundation that can aid their success. Consistent with other research, other parents felt fortunate that their child was only missing kindergarten, and not a higher grade that requires more attention and instruction, and which could potentially be harder to learn online (Timmons et al., 2021).
Strengths & Limitations
These findings shed light on a time in history where families faced universal and unprecedented disruptions and changes in ECE for their children, and work for themselves. A strength of this study is the ability to examine families’ experiences in one geographic area using multiple data sources at multiple time points. However, it is important to note some limitations. First, data was collected in spring (survey) and summer (interview) 2021 where families were asked to report on their experiences from fall 2019 though summer 2021. Given the nature of the COVID-19 pandemic, where global health situations, and individual family circumstances were changing rapidly, the timing of data collection may have altered families’ responses. For example, we may have collected different information from families in fall 2020 compared to spring 2021 even if we asked the same questions. In addition, while some aspects of the pandemic were universal, others were highly driven by local context. This study collected data from families with kindergarten children in 2020–2021, in a community that completely shut down all ECE programs in spring 2020 (with the exception of care for essential workers), and where the local school district only had remote learning for kindergarteners until April 2021. Experiences of families in other communities may have been very different. Despite these limitations, this study extends our understanding of how families face disruptions, and extends our understanding of the accommodation model to consider the greater role stability, health, safety and social interactions play in present time.
Implications
Our findings also reveal the difficulty that parents faced in accessing information about ECE options throughout the pandemic which made planning difficult. Findings from qualitative interviews with parents highlight the lack of information about available child care options and their struggle to assess the accuracy of information they did receive. This corresponds with previous research on information asymmetry between parents’ knowledge of child care options and the actual resources available to them (Akerlof, 2002; Chaundry et al., 2010). Although the ever-evolving nature of the pandemic in the first year and a half certainly exacerbated this issue, our findings support that the idea that parents often struggle to obtain full and accurate information about ECE. These barriers to information have implications for institutions that aim to increase access to formal child care programs, such as local municipalities, child care resource and referral agencies and individual programs. This study sheds light on the need for more supports for families as they navigate child care decision-making, such as centralized places to gain information, and different communication pathways for families. This may be particularly important now that the availability of child care options continues to be limited and disruptions continue (Chen et al., 2021).
The current study provides additional insights into the ongoing nature of work and child care disruptions for families and how families handle these disruptions. While the specific nature of COVID-19 disruptions described in the current study may be a unique phenomenon to this historical period, the effects of the pandemic continue to reverberate, such as with intermittent child care closures for child or staff quarantine needs. Disruptions to work and child care and their consequences for family well-being and parental employment are also likely to continue for pandemic and other unforeseen reasons. Policies that encourage workplace flexibility to allow families to better weather disruptions as well as increasing the availability of child care programs may allow families to better juggle between care and work obligations. Moreover, our findings identify heightened health and safety concerns as well as questions regarding the potential stability of child care arrangements that guided parental decision-making in child care. Such factors may become permanent considerations parents account for moving forward. Practitioners and policymakers must be aware of these new realities and aim to minimize disruptions in order to support families as they navigate child care decision-making.
Acknowledgements
The research team and partners would like to thank all of the families that participated in the study.
Author Contributions
All authors contributed to the study in substantial ways. Kyle DeMeo Cook and Lisa Kuh led the conception and design of the study. Kyle DeMeo Cook and Kevin Ferreira van Leer led data collection efforts, analyzed and interpreted the data and drafted and edited the manuscript. Jill Gandhi and Carolina Ayala contributed to instrument development, data analysis, and writing and editing. Lisa Kuh contributed to instrument development, recruitment, and writing and editing. All authors read and approved the final manuscript.
Funding
This work was partially supported by a grant from the Education Research Service Project (ERSP) program of the American Educational Research Association (AERA) awarded to the first author.
Declarations
Ethics Approval
This study was approved by the St. John’s University Institutional Review Board (IRB) (FY2021-47 & FY2021-189). This study was performed in line with the principles of the Declaration of Helsinki.
Consent to Participate & Publish
All participants provided informed consent to participate and for anonymized information to be published.
Competing Interests
The authors have no relevant financial or non-financial interests to disclose.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
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| 0 | PMC9734937 | NO-CC CODE | 2022-12-14 23:28:31 | no | Early Child Educ J. 2022 Dec 6;:1-12 | utf-8 | Early Child Educ J | 2,022 | 10.1007/s10643-022-01430-2 | oa_other |
==== Front
Am J Crim Justice
Am J Crim Justice
American Journal of Criminal Justice
1066-2316
1936-1351
Springer US New York
9710
10.1007/s12103-022-09710-8
Article
Special Issue: Criminal Justice Reform Guest Editor’s Introduction
Mears Daniel P. [email protected]
Daniel P. Mears Ph.D.
is a Distinguished Research Professor and the Mark C. Stafford Professor of Criminology at Florida State University’s College of Criminology and Criminal Justice, Eppes Hall, 112 South Copeland Street, Tallahassee, FL 32306 − 1273, e-mail ([email protected]), phone (850-644-7376). A Fellow of the American Society of Criminology, he conducts research on crime and policy. His work has appeared in criminology, criminal justice, law, and sociology journals and American Criminal Justice Policy (Cambridge University Press), Out-of-Control Criminal Justice and American Criminal Justice Policy (Cambridge University Press), both of which won the Academy of Criminal Justice Sciences outstanding book award, Prisoner Reentry in the Era of Mass Incarceration (Sage), and Fundamentals of Criminological and Criminal Justice Inquiry (Cambridge University Press).
grid.255986.5 0000 0004 0472 0419 College of Criminology and Criminal Justice, Florida State University, Eppes Hall, 112 South Copeland Street, 32306-1273 Tallahassee, FL USA
7 12 2022
15
16 11 2022
1 12 2022
© Southern Criminal Justice Association 2022
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
==== Body
pmcGuest Editor’s Introduction
Criminal justice reform—it is timeless. Since the founding of the United States, policymakers at federal, state, and local levels have tinkered, sometimes dramatically, with criminal justice. The end result has been reform after reform after reform. And that has been for good reason. Many problems have plagued, and continue to plague, how America addresses crime and achieves justice.
What are the problems? A short list includes: the politicization of crime; a vast array of competing interests that influence criminal justice policy and implementation; massive expenditures on policing, sentencing, and corrections, with questionable returns; little consistent reliance on research evidence when designing, implementing, and evaluating policy; little systematic inclusion or understanding of public opinion when shaping policy; and persistent and increasing concerns about inequality. That barely scratches the surface, but the list highlights the challenges and opportunities that face us.
Given how vast scale of what might count as “criminal justice reform,” it may seem odd to have a special issue devoted to it. Surely a small number of articles cannot do justice to the many and diverse reforms that have surfaced in recent decades. That is a fair concern. Such an issue in fact cannot cover entire literatures on the varied types of reforms that have been contemplated or that are needed for policing, sentencing, court operations, prison and jail systems, and so on.
What it can do, though, is rise above the vast amount of reform and related scholarship to provide a bird’s eye of “big” topics that that bear on efforts to improve criminal justice. A detailed view risks getting lost among the trees. This is especially concerning because many reforms do little to appreciably alter criminal justice in meaningful ways; they target piecemeal change without addressing larger, systemic challenges. A special issue on criminal justice reform thus offers an opportunity focus on the forest. In so doing, it can shed light and provide guidance on a timeless concern of continued and pressing importance in contemporary America.
To this end, the papers each tackle “big” topics. Taken together, they highlight the complexity that attends to criminal justice reform and the need for coherent, systemic change. They illuminate ways in which piecemeal change achieves little. And they identify directions for research and ways to create persistent and large-scale improvements to criminal justice.
In the lead-off essay, Mears describes the “Sisyphean” trap that plagues criminal justice reform efforts. We continue to repeat the same mistakes again and again, wasting resources and missing chances to reduce crime and injustice. A better approach entails identifying the causes of crime, injustice, and inefficiency. That requires research infrastructure. Alone, it is not sufficient. There must also be policymaker and criminal justice system commitment to acting on research and to improving systems rather than tinkering around the edges. The essay identifies ways to do so that are a substantial reach, yet feasible and, indeed, necessary for lasting and meaningful improvements to how we go about producing public safety and justice.
Charis Kubrin and Rebecca Tublitz focus our attention to the need to better understand “policy talk” (i.e., how we define problems and what types of solutions are promoted) versus “policy action” (i.e., the design and implementation of policy) when thinking about criminal justice reform. Failure to do so consigns us to missing ways to better align policy talk with policy action. They argue that clarity about the two dimensions leads to insights about the importance of examining normative views about the goals of punishment, and policy more generally, and practical realities that attend to policymaking. In contrast to accounts that emphasize “evidence-based policy,” they emphasize the importance of the policy change process. This view is not in conflict with a focus on evidence-based policy. To the contrary, it acknowledges that, in the “real world,” a diverse array of factors influence the framing of and response to crime and injustice. Better understanding of these factors and how to improve policymaking processes provides a critical platform for enacting effective reforms.
Pam Lattimore examines the last 50 years of efforts to enact criminal justice reforms to identify how we can do better going forward. Her career in both federal government, working at the U.S. Department of Justice, and RTI International, conducting policy evaluations uniquely position her to provide a “forest”-level view of what has happened and what needs to improve. As part of her account, she provides an overview of major crime trends as well as national policy shifts and their effects. She then explores why reducing recidivism has proven so difficult for the criminal justice system. One of the factors centers on the complex lives of the people who become enmeshed in the criminal justice system. There are no simple “fixes” to the problems that they face. Another factor is the persistent reliance on programs that lack adequate logic models that that frequently are poorly implemented. Lattimore cautions that we should have realistic hopes for what can be achieved. At the same time, she underscores that even small improvements can create meaningful impacts on public safety. There are, in short, many challenges to improved reform, but also many opportunities for creating more effective policy.
Thomas Blomberg, Jennifer Copp, and John Thrasher turn our attention to translational criminology and politics. Researchers tend to focus on “evidence-based policy” but, by and large, do not systematically consider the political aspects of policymaking. Building on their policy-focused research and the insights of Thrasher, who served not only as the President of Florida State University but also spent decades serving in the Florida Legislature, the authors describe important developments in, impediments to, and promising practices for improving translational criminology effectiveness. To ground their discussion, they provide, first, a case study of state-level translational criminology efforts in Florida and then, second, a case study of local-level translational criminology efforts in Palm Beach County. Their account is sobering but also provides grounds for optimism about how criminal justice policy can be improved.
John Roman provides a comprehensive account of different explanations for the crime decline in the 1990s to identify lessons for contemporary policy. He describes not only potential policy-based explanations for the decline but also explanations that focus on changes in society or indirect effects of policies that target social problems other than crime. A central conclusion is that most of the explanation for the crime decline stemmed from factors outside the criminal legal system. That suggests that future efforts to reduce crime might want to concentrate on these factors, especially those, such as consumer behaviors, that might be amenable to policy “nudges.” More generally, Roman argues for a pragmatic approach to improving policy—identify the causes of a problem and target for change those most amenable to policy influence.
William Sabol and Miranda Baumann tackle an issue of central relevance to all of criminal justice but that frequently gets overlooked in research and policy—forecasting. They argue that forecasting, though used by criminal justice agencies to guide some decisionmaking, rarely gets used to formulate or evaluate policy proposals. To illustrate the problems with this situation and the potential for improved policy development and evaluation, they focus on predictive policing and prison population forecasting. Their essay highlights the critical importance of transparency for ensuring that forecasting results in credible information and that it grounds policy in a manner that is legitimate, and that diverse stakeholders view as such. They identify concrete steps that government and agencies can take for using forecasting to create more effective reforms.
Kevin Drakulich focuses on public opinion and criminal justice reform. Especially in a democracy, public views matter, or they are supposed to matter. How, in fact, does public opinion contribute to discussions about criminal justice policy and reform? How can it be used to improve policy and reform efforts? He identifies that, unfortunately, a great many problems exist in how we measure and monitor public opinion. There are problems in public understanding about crime and the criminal justice system. And there are problems in how the public receives information and learns about crime and justice that can make it difficult to enact reforms that can better promote public safety while reducing policy harms and inequalities. Drakulich discusses what we know, where the big research gaps lie, and steps, such as more systematic collection and analysis of public opinion, that can be taken to improve research and policy.
Sarah Wakefield draws attention to a central problem that swirls around any discussion of the criminal justice system and reforms—inequality. As she discusses, a large body of scholarship documents diverse ways in which the criminal legal system is a “stratifying” institution. It reflects societal inequalities, it can worsen existing inequalities in a myriad of ways, and it can create new kinds of inequalities. She highlights that reform strategies might help to reduce the extent to which the legal or justice system worsens existing inequalities or create new ones. These would be important achievements, and she identifies ways that they could be pursued. Such strategies will not, though, appreciably alter societal conditions that create inequalities before individuals are ever arrested or sentenced. This insight points to the possibilities and the limits of reforms that focus only on the criminal justice system, and the need for societal changes that can prevent inequalities in the first place and, by extension, reduce their amplification through law enforcement and punishment policies and practices.
Natasha Frost directs us to an overlooked but critical nuts-and-bolts issue: Who, she asks, is going to do the work of criminal justice reform? The traditional research education model in higher education focuses on training doctoral students, and often that training focuses on academic publications. Many students, though, will not get doctorates and those that do may find that their research training does not equip them well for policy evaluation. These and other insights lead to a focus on a key idea—research training should target undergraduate and graduate students. It should help them to understand the intracies of academic and policy-focused empirical studies. And it should help them appreciate the relevance of research to policy creation and evaluation. Doing so can help to ensure that the people who go on to become legislators or agency officials or personnel can advocate for and use research to create needed reforms. They also can ensure that these reforms have a greater likelihood of being well-implemented and effective. Pie-in-the-sky thinking? No. She identifies a number of strategies for achieving this goal.
Robin Engel, Gabrielle Isaza, and Hannah McManus examine one of the most pressing areas of criminal justice reform in contemporary America—policing. Reflecting on years of experience conducting research in this area and on the voluminous literature on law enforcement, the authors highlight why police reforms have consistently failed. The factors that they identify include reliance on knee-jerk responses to perceived or actual problems, concentrating attention on problems rather than on how to achieve important aspirational goals, and a lack of credible empirical evidence about which reforms are effective and under what conditions they “work.” These are, notably, lessons that generalize beyond policing and extend to many other areas of criminal justice reform. The tendency to be reactive and to not invest in the infrastructure for achieving meaningful improvements plague many reform efforts, as does an absence of large bodies of strong, methodologically rigorous research on effective programs and policies. Engel and colleagues close by highlighting many ways in which policymakers, police executives, and researchers can contribute to stronger, more evidence-based reform.
Finally, McKenzie Jossie, Alfred Blumstein, and J. Mitchell Miller zero in on a pressing contemporary social problem—COVID-19—that has important consequences for society and the criminal justice system, and that can be used to identify the need for systems reform. Their essay alerts us to the importance of understanding the impacts of the COVID-19 pandemic on the criminal justice system and those processed through it. It alerts us to the opportunity that a focus on COVID-19 provides for developing theoretical insights, grounded by empirical research, about such topics as contagion control and tele-justice. As the authors highlight, natural experimental research opportunities abound because of COVID-19 and can be leveraged for new theoretical and policy-relevant insights. Not least, the essay’s focus on COVID-19 points to the importance of understanding criminal justice systems, including the factors that affect their day-to-day operations, variation in how parts of these systems respond to change, and the need for adaptations that can improve the entire criminal justice system.
The need for better research on criminal justice reform, for better reform, and for improved approaches to criminal justice have never been greater. Longstanding challenges to effective policy persist and will not magically go away on their own. As this collection of essays identifies, many opportunities exist to make progress. It will require much of researchers in both academic and non-academic settings. And it will require much from policymakers, criminal justice practitioners, and the public. It is, in short, time for everyone to roll up their sleeves and get to work.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
| 0 | PMC9734938 | NO-CC CODE | 2022-12-14 23:28:31 | no | Am J Crim Justice. 2022 Dec 7;:1-5 | utf-8 | Am J Crim Justice | 2,022 | 10.1007/s12103-022-09710-8 | oa_other |
==== Front
Am J Crim Justice
Am J Crim Justice
American Journal of Criminal Justice
1066-2316
1936-1351
Springer US New York
9710
10.1007/s12103-022-09710-8
Article
Special Issue: Criminal Justice Reform Guest Editor’s Introduction
Mears Daniel P. [email protected]
Daniel P. Mears Ph.D.
is a Distinguished Research Professor and the Mark C. Stafford Professor of Criminology at Florida State University’s College of Criminology and Criminal Justice, Eppes Hall, 112 South Copeland Street, Tallahassee, FL 32306 − 1273, e-mail ([email protected]), phone (850-644-7376). A Fellow of the American Society of Criminology, he conducts research on crime and policy. His work has appeared in criminology, criminal justice, law, and sociology journals and American Criminal Justice Policy (Cambridge University Press), Out-of-Control Criminal Justice and American Criminal Justice Policy (Cambridge University Press), both of which won the Academy of Criminal Justice Sciences outstanding book award, Prisoner Reentry in the Era of Mass Incarceration (Sage), and Fundamentals of Criminological and Criminal Justice Inquiry (Cambridge University Press).
grid.255986.5 0000 0004 0472 0419 College of Criminology and Criminal Justice, Florida State University, Eppes Hall, 112 South Copeland Street, 32306-1273 Tallahassee, FL USA
7 12 2022
15
16 11 2022
1 12 2022
© Southern Criminal Justice Association 2022
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
==== Body
pmcGuest Editor’s Introduction
Criminal justice reform—it is timeless. Since the founding of the United States, policymakers at federal, state, and local levels have tinkered, sometimes dramatically, with criminal justice. The end result has been reform after reform after reform. And that has been for good reason. Many problems have plagued, and continue to plague, how America addresses crime and achieves justice.
What are the problems? A short list includes: the politicization of crime; a vast array of competing interests that influence criminal justice policy and implementation; massive expenditures on policing, sentencing, and corrections, with questionable returns; little consistent reliance on research evidence when designing, implementing, and evaluating policy; little systematic inclusion or understanding of public opinion when shaping policy; and persistent and increasing concerns about inequality. That barely scratches the surface, but the list highlights the challenges and opportunities that face us.
Given how vast scale of what might count as “criminal justice reform,” it may seem odd to have a special issue devoted to it. Surely a small number of articles cannot do justice to the many and diverse reforms that have surfaced in recent decades. That is a fair concern. Such an issue in fact cannot cover entire literatures on the varied types of reforms that have been contemplated or that are needed for policing, sentencing, court operations, prison and jail systems, and so on.
What it can do, though, is rise above the vast amount of reform and related scholarship to provide a bird’s eye of “big” topics that that bear on efforts to improve criminal justice. A detailed view risks getting lost among the trees. This is especially concerning because many reforms do little to appreciably alter criminal justice in meaningful ways; they target piecemeal change without addressing larger, systemic challenges. A special issue on criminal justice reform thus offers an opportunity focus on the forest. In so doing, it can shed light and provide guidance on a timeless concern of continued and pressing importance in contemporary America.
To this end, the papers each tackle “big” topics. Taken together, they highlight the complexity that attends to criminal justice reform and the need for coherent, systemic change. They illuminate ways in which piecemeal change achieves little. And they identify directions for research and ways to create persistent and large-scale improvements to criminal justice.
In the lead-off essay, Mears describes the “Sisyphean” trap that plagues criminal justice reform efforts. We continue to repeat the same mistakes again and again, wasting resources and missing chances to reduce crime and injustice. A better approach entails identifying the causes of crime, injustice, and inefficiency. That requires research infrastructure. Alone, it is not sufficient. There must also be policymaker and criminal justice system commitment to acting on research and to improving systems rather than tinkering around the edges. The essay identifies ways to do so that are a substantial reach, yet feasible and, indeed, necessary for lasting and meaningful improvements to how we go about producing public safety and justice.
Charis Kubrin and Rebecca Tublitz focus our attention to the need to better understand “policy talk” (i.e., how we define problems and what types of solutions are promoted) versus “policy action” (i.e., the design and implementation of policy) when thinking about criminal justice reform. Failure to do so consigns us to missing ways to better align policy talk with policy action. They argue that clarity about the two dimensions leads to insights about the importance of examining normative views about the goals of punishment, and policy more generally, and practical realities that attend to policymaking. In contrast to accounts that emphasize “evidence-based policy,” they emphasize the importance of the policy change process. This view is not in conflict with a focus on evidence-based policy. To the contrary, it acknowledges that, in the “real world,” a diverse array of factors influence the framing of and response to crime and injustice. Better understanding of these factors and how to improve policymaking processes provides a critical platform for enacting effective reforms.
Pam Lattimore examines the last 50 years of efforts to enact criminal justice reforms to identify how we can do better going forward. Her career in both federal government, working at the U.S. Department of Justice, and RTI International, conducting policy evaluations uniquely position her to provide a “forest”-level view of what has happened and what needs to improve. As part of her account, she provides an overview of major crime trends as well as national policy shifts and their effects. She then explores why reducing recidivism has proven so difficult for the criminal justice system. One of the factors centers on the complex lives of the people who become enmeshed in the criminal justice system. There are no simple “fixes” to the problems that they face. Another factor is the persistent reliance on programs that lack adequate logic models that that frequently are poorly implemented. Lattimore cautions that we should have realistic hopes for what can be achieved. At the same time, she underscores that even small improvements can create meaningful impacts on public safety. There are, in short, many challenges to improved reform, but also many opportunities for creating more effective policy.
Thomas Blomberg, Jennifer Copp, and John Thrasher turn our attention to translational criminology and politics. Researchers tend to focus on “evidence-based policy” but, by and large, do not systematically consider the political aspects of policymaking. Building on their policy-focused research and the insights of Thrasher, who served not only as the President of Florida State University but also spent decades serving in the Florida Legislature, the authors describe important developments in, impediments to, and promising practices for improving translational criminology effectiveness. To ground their discussion, they provide, first, a case study of state-level translational criminology efforts in Florida and then, second, a case study of local-level translational criminology efforts in Palm Beach County. Their account is sobering but also provides grounds for optimism about how criminal justice policy can be improved.
John Roman provides a comprehensive account of different explanations for the crime decline in the 1990s to identify lessons for contemporary policy. He describes not only potential policy-based explanations for the decline but also explanations that focus on changes in society or indirect effects of policies that target social problems other than crime. A central conclusion is that most of the explanation for the crime decline stemmed from factors outside the criminal legal system. That suggests that future efforts to reduce crime might want to concentrate on these factors, especially those, such as consumer behaviors, that might be amenable to policy “nudges.” More generally, Roman argues for a pragmatic approach to improving policy—identify the causes of a problem and target for change those most amenable to policy influence.
William Sabol and Miranda Baumann tackle an issue of central relevance to all of criminal justice but that frequently gets overlooked in research and policy—forecasting. They argue that forecasting, though used by criminal justice agencies to guide some decisionmaking, rarely gets used to formulate or evaluate policy proposals. To illustrate the problems with this situation and the potential for improved policy development and evaluation, they focus on predictive policing and prison population forecasting. Their essay highlights the critical importance of transparency for ensuring that forecasting results in credible information and that it grounds policy in a manner that is legitimate, and that diverse stakeholders view as such. They identify concrete steps that government and agencies can take for using forecasting to create more effective reforms.
Kevin Drakulich focuses on public opinion and criminal justice reform. Especially in a democracy, public views matter, or they are supposed to matter. How, in fact, does public opinion contribute to discussions about criminal justice policy and reform? How can it be used to improve policy and reform efforts? He identifies that, unfortunately, a great many problems exist in how we measure and monitor public opinion. There are problems in public understanding about crime and the criminal justice system. And there are problems in how the public receives information and learns about crime and justice that can make it difficult to enact reforms that can better promote public safety while reducing policy harms and inequalities. Drakulich discusses what we know, where the big research gaps lie, and steps, such as more systematic collection and analysis of public opinion, that can be taken to improve research and policy.
Sarah Wakefield draws attention to a central problem that swirls around any discussion of the criminal justice system and reforms—inequality. As she discusses, a large body of scholarship documents diverse ways in which the criminal legal system is a “stratifying” institution. It reflects societal inequalities, it can worsen existing inequalities in a myriad of ways, and it can create new kinds of inequalities. She highlights that reform strategies might help to reduce the extent to which the legal or justice system worsens existing inequalities or create new ones. These would be important achievements, and she identifies ways that they could be pursued. Such strategies will not, though, appreciably alter societal conditions that create inequalities before individuals are ever arrested or sentenced. This insight points to the possibilities and the limits of reforms that focus only on the criminal justice system, and the need for societal changes that can prevent inequalities in the first place and, by extension, reduce their amplification through law enforcement and punishment policies and practices.
Natasha Frost directs us to an overlooked but critical nuts-and-bolts issue: Who, she asks, is going to do the work of criminal justice reform? The traditional research education model in higher education focuses on training doctoral students, and often that training focuses on academic publications. Many students, though, will not get doctorates and those that do may find that their research training does not equip them well for policy evaluation. These and other insights lead to a focus on a key idea—research training should target undergraduate and graduate students. It should help them to understand the intracies of academic and policy-focused empirical studies. And it should help them appreciate the relevance of research to policy creation and evaluation. Doing so can help to ensure that the people who go on to become legislators or agency officials or personnel can advocate for and use research to create needed reforms. They also can ensure that these reforms have a greater likelihood of being well-implemented and effective. Pie-in-the-sky thinking? No. She identifies a number of strategies for achieving this goal.
Robin Engel, Gabrielle Isaza, and Hannah McManus examine one of the most pressing areas of criminal justice reform in contemporary America—policing. Reflecting on years of experience conducting research in this area and on the voluminous literature on law enforcement, the authors highlight why police reforms have consistently failed. The factors that they identify include reliance on knee-jerk responses to perceived or actual problems, concentrating attention on problems rather than on how to achieve important aspirational goals, and a lack of credible empirical evidence about which reforms are effective and under what conditions they “work.” These are, notably, lessons that generalize beyond policing and extend to many other areas of criminal justice reform. The tendency to be reactive and to not invest in the infrastructure for achieving meaningful improvements plague many reform efforts, as does an absence of large bodies of strong, methodologically rigorous research on effective programs and policies. Engel and colleagues close by highlighting many ways in which policymakers, police executives, and researchers can contribute to stronger, more evidence-based reform.
Finally, McKenzie Jossie, Alfred Blumstein, and J. Mitchell Miller zero in on a pressing contemporary social problem—COVID-19—that has important consequences for society and the criminal justice system, and that can be used to identify the need for systems reform. Their essay alerts us to the importance of understanding the impacts of the COVID-19 pandemic on the criminal justice system and those processed through it. It alerts us to the opportunity that a focus on COVID-19 provides for developing theoretical insights, grounded by empirical research, about such topics as contagion control and tele-justice. As the authors highlight, natural experimental research opportunities abound because of COVID-19 and can be leveraged for new theoretical and policy-relevant insights. Not least, the essay’s focus on COVID-19 points to the importance of understanding criminal justice systems, including the factors that affect their day-to-day operations, variation in how parts of these systems respond to change, and the need for adaptations that can improve the entire criminal justice system.
The need for better research on criminal justice reform, for better reform, and for improved approaches to criminal justice have never been greater. Longstanding challenges to effective policy persist and will not magically go away on their own. As this collection of essays identifies, many opportunities exist to make progress. It will require much of researchers in both academic and non-academic settings. And it will require much from policymakers, criminal justice practitioners, and the public. It is, in short, time for everyone to roll up their sleeves and get to work.
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| 0 | PMC9734940 | NO-CC CODE | 2022-12-14 23:28:31 | no | BDJ In Pract. 2022 Dec 5; 35(12):14-17 | latin-1 | null | null | null | oa_other |
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Int J Artif Intell Educ
Int J Artif Intell Educ
International Journal of Artificial Intelligence in Education
1560-4292
1560-4306
Springer New York New York
320
10.1007/s40593-022-00320-3
Article
WhatsApp Discourse Throughout COVID-19: Towards Computerized Evaluation of the Development of a STEM Teachers Professional Learning Community
http://orcid.org/0000-0003-0865-8555
Scherz Zahava [email protected]
http://orcid.org/0000-0001-5796-0158
Salman Asaf [email protected]
http://orcid.org/0000-0003-2676-6912
Alexandron Giora [email protected]
http://orcid.org/0000-0002-5145-3486
Shwartz Yael [email protected]
grid.13992.30 0000 0004 0604 7563 Weizmann Institute of Science, Rehovot, Israel
8 12 2022
125
25 10 2022
© International Artificial Intelligence in Education Society 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
This two-year study followed a professional learning community (PLC) of STEM Teachers Leaders, referred to as L-PLC. The onset of the COVID-19 pandemic accelerated changes in the focus of many professional development frameworks from face-to-face to online communication. We sought for new ways and tools to follow the professional development and the dynamics in our L-PLC. In particular, we explored professional knowledge development and social interactions, as derived from its WhatsApp group (43–48 participants) discourse, before and during the COVID-19 pandemic. Data were extracted from 6599 WhatsApp messages issued during four consecutive semesters (March 2019—March 2021), as well as from participant background questionnaires. The analysis incorporated both structure and content examination of the L-PLC WhatsApp discourse, using social network analysis (SNA), and a distinctive coding scheme followed by statistical analysis, heat map, and bar graph visualizations. These provided insights into whole group (macro), subgroups (meso), and individual (micro) profiles. The results indicated that over time, the participants gradually began to use the WhatsApp platform for professional purposes on top of its initial administrative intention. Moreover, the pandemic seemed to lead to a unique adjustment process, denoted by enhanced professional interactions, regarding content knowledge, professional content knowledge, and technological knowledge, and also accelerated the development of productive community behaviors, such as sharing and social support. The research approach enabled us to detect changes in key PLC characteristics, follow their dynamics under the influence of chaotic changes and navigate the community accordingly. Taken together, WhatsApp exchanges can serve as a rich source of data for a noninvasive continuous evaluation of group processes and progress.
Supplementary Information
The online version contains supplementary material available at 10.1007/s40593-022-00320-3.
Keywords
Professional learning community (PLC)
Professional development
Social network analysis (SNA)
COVID-19
WhatsApp
==== Body
pmcIntroduction
In recent years, Professional Learning Communities (PLCs) have served as central frameworks for Professional Development (PD) for teachers, and have been implemented alongside more traditional structures (Vangrieken et al., 2017). PLCs offer a flexible social-professional environment for collaboration, geared to its participants' needs. PLC providers should constantly evaluate the participants' attitudes, interests, and involvements so they will be able to effectively respond (in real-time) to unexpected changes, stay attuned and relevant and ensure fulfillment of the PLC's objectives. Yet, monitoring PLCs in the era of digital media and emerging online environments for professional development calls for new approaches. The replacement of face-to-face communication with convenient digital interactions creates huge and constant volumes of various data, requiring technological support to analyze and understand the meaning of the digital traces, which in turn could be translated into actionable insights for better decision-making.
The PLC in this study was active before and during the COVID-19 pandemic. Participants utilized the WhatsApp platform as their most prominent channel for spontaneous-unguided online communication, which gave us the opportunity to monitor the participants' performance and needs throughout the period, and to investigate the impact of COVID-19 on activity and performance.
In the following sections, we present a general background about teachers' PLCs, including some theoretical frameworks and models. Then, we elaborate on the WhatsApp environment as an online platform for teachers' PLCs, as well as a research data source. Finally, we address the context in which this study took place.
Background: Professional Learning Community (PLC)
Several theoretical and experimental models in the area of teacher professional development (Bolam et al., 2005; Borko et al., 2010; DuFour, 2004; Grossman et al., 2001; Little, 2012; Vescio et al., 2008), as well as our own research work in the field (Eylon et al., 2020), laid the ground for the following PLC definition, framework, and models.
PLC Definition
DuFour (2004) was among the first to introduce PLC as a framework for teacher professional development and identified three big ideas for PLC: (1) to ensure teacher learning, (2) to create a culture of collaboration, and (3) to focus on outcomes (such as the participents' achievements and attitudes). Shulman and Sherin (2004) claimed that active membership in a PLC can boost teachers' professional development, and will facilitate their goal of becoming accomplished teachers. There is no consensus in the literature regarding the definition of PLC. Influenced by the above, we define a PLC as: A framework for a group of educators to meet regularly and develop norms of trust and sharing. The educators actively investigate their teaching, collect evidence from their students’ learning, reflect collaboratively on their practice, and learn from one another.
Typical key characteristics of teachers' PLCs and their descriptions are presented in Table 1. The PLCs in our project followed these characteristics.Table 1 Characteristics of teachers' PLC*
Characteristics Description / Explanation
Relations of trust and norms of sharing Relations of trust and mutual respect create a safe environment that enables teachers to learn and develop professionally. The PLC serves as a responsive and proficient “safety net” in the event of challenging experiences
Regular meetings and mechanisms, structured processes Optimal learning processes require a well-maintained setup: regular meetings with schedules, meeting times, pleasant physical conditions, and more
Focus on student learning and the connections between teaching and learning Pedagogical discourse in PLCs focuses on student learning and its relationship to teaching
Decision-making based on data collection and evaluation To achieve better learning and teaching, alternative assessment methods are discussed (e.g., systematic analysis of student assignments, classroom observations, interviews) while collecting, understanding, and interpreting classroom data
Reflective dialogues, inquiry, and reflection Effective professional learning involves collective reflection on practice, examining teaching methods, and continuous self-examination, including structured processes for “learning from successes and failures”
* Sources: Benaya et al., 2013; DuFour, 2004
PLC performance can be evaluated in the light of different theoretical frameworks such as the model of teachers knowledge (Shulman, 2015) or linkage between teacher knowledge progression and student learning (Fishman et al., 2003). Vangrieken et al. (2017) mentioned additional parameters, such as development of a discourse, tracing personal growth, meeting stakeholders interests, and following PLC characteristics (e.g., group dynamics, regularities). This study monitored teacher learning with regard to several aspects of teacher knowledge. The first three aspects correlate with Shulman's (1986, 2015) components of teacher knowledge: (a) disciplinary Content Knowledge (CK), which relates to the acquisition and expansion of content areas in the discipline, (b) Pedagogical Knowledge (PK), which relates to the art of teaching and instruction, learning and learners, class management, and assessment methods, and (c) Pedagogical Content Knowledge (PCK), which combines principles of meaningful teaching of disciplinary contents with concrete pedagogical aspects such as student's needs. Later, when technology became an inseparable component of education, Koehler and Mishra (2009) added (d) Technological-Pedagogical-Content-Knowledge (TPCK) component, which is the knowledge required for the successful integration of technology into teaching to ensure meaningful learning and optimal use of a specific technology. In the following years, TPCK grew to a major yet multifaced framework (Brantley-Dias & Ertmer, 2013). Angeli and Valanides (2009) interpreted TPCK as Information Communication Technology (ICT)-related PCK.
PLC Models
Two models emerged from our prior studies on teachers' PLC development and implementation (Eylon et al., 2020; Scherz et al., 2021): the Collaboration Model and the Network Model, both of which influenced subsequent PLC planning and implementation.
The Collaboration Model
Collaboration is defined as a “coordinated, synchronous activity that is the result of a continued attempt to construct and maintain a shared conception of a problem” (Roschelle & Teasley, 1995: 70). In former studies (Eylon et al., 2020; Scherz et al., 2021), we defined a Collaboration Model that specifies four levels of group effort performance, which differ in the intensity of required commitment and complexity (see Table 2).Table 2 The four-level collaboration model
Levels Explanation Examples
Participation Attendance, active presence, following PLC norms Arrive on time
Full attendance
Active in PLC discourse
Sharing Sharing of ideas, experiences, class activities, and PLC practice with other members Present best practice
Present challenges
Offer support
Cooperation Working together on project aspects, teamwork, and sharing responsibilities Group development of learning activities
Group learning
Partnership An arrangement between two or more people to manage projects and share challenges, consequences, and benefits Initiating, leading, and implementing a collaborated PLC project
The Network Model
The Network Model demonstrates relationships between individual participants within a specific teachers' community (PLC), as well as direct and indirect relationships between associated communities. Accordingly, the Network model represents various graphic paths of knowledge transmission as shown in Fig. 1 (Eylon et al., 2020; Scherz et al., 2021). This model is research-based and has emerged from many regional PLCs that were operated under the same project. An initial rigid top-down model gradually evolved into a Network Model that emerged alongside implementation, via analysis of documented evidence-based PLC stories. These PLC stories triggered various knowledge transmissions, both within a single PLC and between PLCs.Fig. 1 PLC Network Model: paths of knowledge transmission among teachers' PLCs ; (Source: Eylon et al., 2020 Scherz et al., 2021)
WhatsApp as an Online Platform for Teachers' PLCs
The ever-growing popularity of social media — such as Facebook, Twitter, WhatsApp, and other platforms — has enabled researchers to scale-up and leverage data-mining techniques in order to collect and analyze the digital footprints left by users. Their importance stems from the fact they can serve as rich resources to characterize and detect various patterns regarding behavior, relationships, and social dynamics (Bakhshinategh et al., 2018; Nettleton, 2013; Romero & Ventura, 2010). Such patterns may be transformed into Learning Analytics, which can denote productive learning or its absence (Clow, 2013; Ferguson, 2012).
WhatsApp has been found to have many potential benefits for teacher development, especially within in-service programs and challenging periods, including the changes brought on by the global COVID-19 pandemic. Studies that focused on WhatsApp communication behavior reported an increased activity following the onset of the pandemic (Seufert et al., 2022; Tan et al., 2021). Regarding teachers' PLCs, English language teachers used their PLC WhatsApp group during remote teaching to share resources, raise questions, and propose solutions and teaching strategies (Defianty & Wilson, 2021). WhatsApp was also used to facilitate communication and coordination between groups of teachers in low-income settings (Varanasi et al., 2021). Discourse in WhatsApp groups of science teachers often relates to specific types of know-how, e.g., field knowledge, pedagogical content strategies, and in-school teaching practices (Cansoy, 2017; Waldman, 2020). In line with these reports, monitoring a WhatsApp group aimed at supporting language teacher development, identified three related themes of usage: interpersonal interactions, professional development, and organizational purposes (Motteram et al., 2020).
Besides its potential contributions to professional development, there are also important gains relating to socioemotional aspects and user well-being. For example, a PLC WhatsApp group reportedly helped teachers to develop a sense of community (Waldman, 2020). Similarly, using WhatsApp supported a social atmosphere that promoted collaboration among PLC members (Bouhnik et al., 2014; Naicker & Ebrahim, 2018; Zahedi et al., 2021). Yet, the effectiveness of using WhatsApp in teachers' PLCs depends on participants' awareness of the context within which the community exists, as well as their willingness to accept differing views and opinions (Moodley, 2019).
Context: Leaders PLC (L-PLC)
A PLCs project was established to create both nation-wide and region-oriented PLCs for STEM teachers, with the ultimate goal of improving student achievements and motivation to study science. The project was launched in 2016 with one Leaders PLC (L-PLC), whose members already served as mentors of regional PLCs. The L-PLC members were carefully selected from different regions of the country and were continuously tutored by the project supervisors, while in parallel, 20 regional PLCs were gradually established and co-mentored by these L-PLC members. Each PLC had 40 h of face-to-face meetings, 8 h of a full-day conference, and 12 h of independent learning (a total of 60 h per year).
Most meetings had a recurrent structure of: (1) a STEM and STEM-education-oriented session, (2) a PLC developing session that was dedicated to leadership, mentoring, and co-mentoring capabilities, and (3) a sharing session where participants shared practices and resources. After each meeting, the participants answered a feedback questionnaire that served for evaluation and to refine meeting contents and structure. Thus, the L-PLC meetings were also intentionally planned, implemented, and explicated as part of our modeling strategy, which was geared to develop the participants as accomplished teachers and PLC leaders.
WhatsApp groups were established in all the PLCs of the project. These groups were initially and mainly meant to be used for administrative and spontaneous messaging, with minimal intervention by the project supervisors. For professional correspondence, email, PLC moodle, and other forms of communication were used as well. The current research follows only the WhatsApp group of the L-PLC.
During the COVID-19 pandemic (which started in March 2020), PLC activities continued, and face-to-face meetings were replaced by online meetings using the ZOOM platform. Following extensive discussions, we — as the supervisors of the PLCs project — decided to stick to its original plan as much as possible by introducing or modifying suitable technological and techno-pedagogical applications.
Research Design
Rationale
The onset of the COVID-19 pandemic accelerated changes in the focus of many world interactions from face-to-face to online communication. Therefore, we sought for new ways and tools to follow the professional development and the dynamics in our L-PLC. Throughout the pandemic, we noticed an unusual volume of activity — “traffic” — in the L-PLC WhatsApp group. Even though such change is expected, as the educational system was forced to move into remote teaching and learning, we noted professional discourse initiated by the teachers themselves, and not by the supervisors. This new level of interaction was more prevalent than before and seemed to present new opportunities for professional sharing and learning. The spontaneous-unguided online communication directed us to investigate participants' interactions, knowledge development, and needs.
Research Questions
Guided by the rationale above, this study sought to answer the following research questions (RQs):What can be learned about community processes and professional knowledge development of L-PLC by analyzing their WhatsApp discourse?
How were L-PLC online dynamics, as reflected in their WhatsApp discourse, influenced by the COVID-19 pandemic?
Methods
The longitudinal development of the L-PLC, and the impact of COVID-19 on it, were analyzed by characterizing the structure, the content, and the participants of the WhatsApp discourse across four consecutive semesters (cohorts). Aside from the intense usage of WhatApp during COVID-19 as a medium for ongoing communication between the L-PLC participants, the decision to trace this discourse as the main data source was also derived from its neutrality, with minimal presence and no interference by the supervisors. Consequently, it presented as a noncompulsive observation tool that reflects the L-PLC participants' needs, activities, state of mind, behaviors, and professional development, which in turn enabled tracing of processes and outcomes. The following paragraphs describe the analysis methods employed and how the results were visualized.
Data Collection
Data for this study were extracted from the log of the L-PLC WhatsApp group between March 2019 and March 2021. The following parameters were collected: the number of L-PLC participants, the number of messages sent by each participant, the message content, and the message timestamp. The dataset contained a total of 6599 messages. In addition, L-PLC participants' names, gender, age, higher education degree, and years of participation in the L-PLC were collected from background questionnaires.
Study Duration and Cohorts
The study covered four academic semesters (2 years), between March 2019 and March 2021, which included two semesters prior to the COVID-19 outbreak, and two semesters during the pandemic. Consequently, the data were divided into the following four cohorts (6 months each).Cohort I: 3–8/2019 (the first half-year before COVID-19 outbreak)
Cohort II: 9/2019–2/2020 (the second half-year before COVID-19 outbreak)
Cohort III: 3–8/2020 (the first half-year during COVID-19)
Cohort IV: 9/2020–2/2021 (the second half-year during COVID-19)
As a result, we were able to compare relevant variables in each periodic cohort in order to identify and characterize various patterns, specifically, those emerging before and during the COVID-19 outbreak in our country. The cohorts were incorporated in all the analyses and visualizations.
Participants
The L-PLC was comprised of 64 college-educated participants, including 7 supervisors, 2 project secretaries, and 55 leading STEM teachers (2 males and 53 females). The actual number of participating teachers per semester varied between 43 and 48, and their ages ranged between 35 and 62 years. The majority of teachers (n = 31) participated in the L-PLC throughout the entire study period, while some left (n = 14) and others joined (n = 19) in the middle. The teachers came from a variety of regional schools, thereby representing different cultures, religions, socioeconomic and personal backgrounds.
Content Analysis
Content analysis was applied by classifying the WhatsApp messages into three main categories defined in a coding scheme that we synthesized for assessing PLC discourse (see Table 3). The coding scheme was designed based on professional knowledge frameworks (Angeli & Valanides, 2009; Koehler & Mishra, 2009; Shulman, 1986, 2015) and characteristics (Benaya et al., 2013; DuFour, 2004), and aimed to capture expressions that indicated: (1) Community Development (e.g., supportive expressions as evidence of a positive social climate, sharing knowledge and practice, norms, level of collaboration, cooperation, and partnership), (2) Knowledge Development, including CK, PCK, and TK. We decided to use these three categories after shared coding of part of the data and finding that PK without content knowledge simply does not exist and by acknowledging that TPCK is part of PCK, and (3) Administrative Issues. The scheme enabled us to identify and annotate relevant and important utterances that function as indications of teachers' learning or PLC development.Table 3 Coding scheme for assessing PLC discourse
Category and Sub-Category (CODE) Description Example
Community Development
Building Community (BC) Community psycho-pedagogical activities I would like to discuss this model of PLC in our meetings… A reflective look on the community?
Collaboration & Cooperation (COOP) Expression of cooperation and/or partnership between members Let's solve it together
Sharing (SHAR) Sharing of instructional tools In this video, there is a beautiful demonstration of diffusion of particles in a vacuum
Positive Feedback (PF) Expressions of politeness, praises, a sense of togetherness, and pride Now that we’ve reached the end of the semester, I dedicate the song in the link to each and every one of you. I listen to the lyrics and literally see before my eyes each one of you who is meaningful to me, and sense a strong commitment to the teaching profession
Professional Knowledge Development
Asking for Content Knowledge (ASK-CK) Questions regarding knowledge of the main topic all participants teach – science and technology How can DNA be extracted from strawberries?
Content Knowledge (CK) Knowledge expressions regarding the main topic all participants teach – science and technology I checked with a physicist: the particles move by force of inertia, they move very fast because there are no other particles that collide with them. Hence, at the macro level, the result is a comparison of pressures
Asking for Pedagogical Content Knowledge
(ASK-PCK)
Questions regarding pedagogy in general, online pedagogy, and pedagogy that is topic-specific (i.e., how to teach specific concepts in science) Does anyone know of a simulation of an experiment in chemistry/biology that gives numerical values?
Pedagogical Content Knowledge (PCK) Knowledge expressions regarding pedagogy in general, online pedagogy, and pedagogy that is topic-specific (i.e., how to teach specific concepts in science) Regarding the electricity item—we suggested changing the reflective question into a multiple-choice item that directly relates to the way you taught: What helped you most to understand the subject?
Asking for Technological Knowledge (ASK-TK) Questions regarding technical aspects of using technology How do I assign students to separate zoom rooms?
Technological Knowledge (TK) Knowledge expressions regarding technical aspects of using technology Here are screenshots of the steps needed to create a game/survey
Administrative Issues
Administrative (ADMIN) Addressing management and secretarial issues (not professional issues) When do we meet today? Please send the zoom link
Media
Professional Media Document, Link
Other Media Sticker, Video, Image, Audio
Not Applicable (NA) Expressions unrelated to the above topics of interest
Table 3 provides a short description and an example for each annotation category and sub-category. The Media category differs between Professional Media which can be inspected and coded, and Other Media which refers to media that were only mentioned in the log and were unaccessible (omitted).
Annotation Procedure
The dataset was annotated by two experts in the fields of STEM and teacher professional development. The unit of analysis was a single WhatsApp message, to which several tags could be assigned (multi-labeled annotation). Also, discursive sequences in the dataset were manually delimited according to the beginning and the end of consecutive related messages. As a result, the flow of messages was transformed into different threads grouped under the same discussions.
Annotations were considered valid only if both annotators agreed on a tag, following a two-fold process. First, after individual training to practice message content classification in accordance with the coding scheme, the annotators jointly annotated 7% of the dataset (456 messages); working together on the same threads, while consolidating and reaching full agreement. Then, both annotators independently tagged the rest of the dataset, while conducting consolidation sessions after annotating a certain amount of the same threads. These sessions aimed to minimize the variance in their annotation, thereby increasing its quality by reaching a higher level of an overall agreement. The final Inter-Rater Reliability (IRR) reached an average agreement of > 95%. Table 4 details the IRR for each annotated message tag (label). In this regard, it is important to note that Media tags were annotated automatically by using the existing remarks in the WhatsApp log — such as “image omitted”, “https://…” etc. — and thus were excluded from Table 4.Table 4 Inter-rater reliability per message tag
Tag Cohen's Kappa Score
BC 0.958
COOP 0.951
SHAR 0.953
PF 0.952
ASK-CK 0.969
CK 0.958
ASK-PCK 0.960
PCK 0.955
ASK-TK 0.960
TK 0.966
ADMIN 0.961
NA 0.963
Heat Map and Bar Graph Visualizations
The annotations were visualized by tailored heat maps and bar graphs. Both forms of visualization enable quick and effective comparison of content frequencies, which in turn, can be translated into discourse trends and patterns. The classic heat map was customized by adding a layer of a vertical bar graph, to illustrate the number of messages sent by each participant, irrespective of the discursive function.
In addition, a Chi-square test was applied to examine differences in the annotated sub-categories between the cohorts. This analysis was applied in two steps: (1) an overall Chi-square test comparing the four cohorts to obtain an overall perspective of development over time; and (2) specific comparisons between cohort clusterings. A cohort was either compared to a sum of a cluster of other cohorts or to a specific cohort, to assess the significance of the change. The alpha (type 1 error) for each comparison was set to 0.01—0.05 divided by the number of comparisons (i.e., 0.05/5 = 0.01).
Social Network Analysis (SNA)
SNA is one of the core methods harnessed for identifying role and power structures within a given network. This method measures and visualizes the relationships between different participants, such as interaction type, frequency, various centrality degrees, and unique meaningful structures (e.g., star graphs, cliques) (Liu et al., 2022; Tabassum et al., 2018). Hence, when integrated with corresponding content analysis, SNA can shed light on patterns relating to PLC productivity and development (Baker-Doyle & Yoon, 2020; Matranga & Silverman, 2020; Polizzi et al., 2019). For these reasons, SNA and content analysis — along with appropriate visualizations — were jointly adopted to investigate the L-PLC discourse.
The structure of the L-PLC WhatsApp discourse was modeled, analyzed, and visualized through SNA, using the open-source software Gephi (Gephi Consortium, 2022). Since the WhatsApp messages appear one after the other — usually directed to all the participants — with no graphical hierarchy or clear indication regarding the direction of the communication, an undirected network graph is utilized to represent the discourse structure.
Figure 2 demonstrates a typical SNA graph of the L-PLC WhatsApp discourse. It is important to emphasize that the edges do not represent sent messages, but rather, interactions. Namely, when a participant took part in a discursive sequence, only one interaction (edge) was counted between him/her and all other participants who also took part in the same discursive sequence. The edge thickness reflects the exchange of interactions between two participants – the thicker the edge, the greater the interaction, also denoted by a corresponding color scale – from black (low) to red (high). Therefore, the more sequences both participants took part in, the thicker and redder the edge drawn between them. Discursive sequences initiated by a participant that did not receive responses are presented as self-loops.Fig. 2 Demonstration of a typical SNA graph of the WhatsApp discourse
Network visualizations were further enhanced by adding two unique graphical layers of information to the graphs: (1) the number of messages sent by a participant, which is marked above each node (representing a unique participant), and (2) the years of participation in the L-PLC, which is denoted by a small colored square. A unique symbol instead of the colored square marks supervisors or secretaries (star or triangle, respectively).
Network Metrics
By employing and integrating various network metrics (as detailed below) with the content analysis annotations, we were able to quantify and measure the overall involvement of each participant in the L-PLC discourse, as well as structural changes, coherence degree, and formation of subgroups (i.e., network clusters).
Weighted Degree Centrality denotes the centrality of a participant by considering both his/her connection to other participants and the frequency of these interactions. Namely, this measure is based on the number of edges for a node but also considers the weight of each edge. In the visualization, the size of the node denotes the centrality degree of a participant. The Average Degree Centrality and the Average Weighted Degree Centrality of the entire network (i.e. taking into account all the participants) were computed as well (Ayyappan et al., 2016).
Modularity measures the strength of division of a network into groups, and thus is utilized as a community detection algorithm that uncovers the number of groups or clusters within a network. A relatively high modularity (coefficient) means that there are dense connections between the nodes within groups, but sparse connections between nodes in different groups. Nodes with identical colors denote participants that belong to the same group (Oliveira & Gama, 2012).
Graph Density quantifies how many edges exist between nodes in the network, compared to the number of theoretically possible edges between nodes; namely, it measures how interconnected the participants are. As a supplementary metric, the Clustering Coefficient measures the average probability that two neighbors of a node are themselves neighbors; in other words, the degree to which participants tend to cluster together, to form a clique. Thus, the more participants "know" each other, the higher the average clustering coefficient will be (Feng & Law, 2021; Hansen et al., 2010).
Results and Discussion
The results and discussion section addresses the two research questions together, referring to both dimensions: community processes and professional knowledge development (RQ1), before and during COVID-19 pandemic (RQ2).
The content analysis results of the WhatsApp messages are detailed in Table 5. The number of annotated tags in almost all the categories increased during the pandemic period (cohorts III and IV), with a notable peak in cohort III, corresponding to the first half-year after the COVID-19 pandemic broke out. While the number of annotated tags dropped in cohort IV, it was still higher as compared to cohort I, and in some categories also compared to cohort II. These findings imply that WhatsApp communication played an important role for teachers during the lockdown, and addressed their need for help when shifting to remote teaching. Interestingly, the overall number of annotated Media tags dropped in cohort III and cohort IV, as these messages usually included pictures generated during face-to-face meetings, which were not held during the pandemic. A moderate decline was observed in several other annotated tags (e.g., PF, PCK) between cohort III and cohort IV, which may reflect adjustment of the L-PLC’s online dynamics to the new reality resulting from the pandemic.Table 5 Content analysis of L-PLC WhatsApp discourse
Variable Cohorts Total
I
(3–8/2019) II
(9/2019–2/2020) III
(3–8/2020) IV
(9/2020–2/2021)
Number of Participants 45 48 43 48 64 *
Number of Messages 1187 1739 2031 1642 6599
Number of Tags 1283 2119 2581 2119 8102
Community Development 428 548 852 595 2423
Professional Knowledge Development 104 330 664 446 1544
Administrative Issues 236 364 457 467 1524
Professional Media 61 119 233 221 634
Other Media 371 669 208 256 1504
Not Applicable 83 89 167 134 473
* The total number of different participants from all four cohorts (the sampled L-PLC)
The original goal of the WhatsApp group — i.e., to support communication regarding administrative issues — was still evident across all four cohorts. In parallel, the L-PLC participants utilized WhatsApp as a tool for professional development – both as part of building and enhancing their community and as a channel for obtaining and sharing professional knowledge, as evidenced by the number of tags relating to professional knowledge, and the numbers of documents and links attached, which were mostly professional in nature, and increased as the pandemic progressed.
The following sub-sections detail results regarding two main areas of professional development: (1) Community Development and (2) Knowledge Development. In this study, Community Development was inferred from integration between the SNA results, presented in Figure 3 and Table 6, and the content analysis of the WhatsApp messages, presented in Figs. 4, 5, and Table 5. Specifically, Knowledge Development outcomes are presented and visualized in Figs. 5 and 6.Fig. 3 SNA graphs of the L-PLC WhatsApp discourse in four consecutive cohorts
Table 6 SNA Metrics of the L-PLC
Network metrics Cohorts
I
(3–8/2019) II
(9/2019–2/2020) III
(3–8/2020) IV
(9/2020–2/2021)
Average Degree Centrality 27.289 29.833 36.093 34.250
Average Weighted Degree Centrality 63.467 62.125 170.744 100.625
Graph Density 0.620 0.635 0.859 0.729
Average Clustering Coefficient 0.816 0.805 0.904 0.847
Modularity 0.066 0.068 0.039 0.047
Number of Groups 3 4 3 3
Fig. 4 Bar graph of the frequency of Community Development sub-categories in WhatsApp messages, and their statistical significance across cohort clusters
Fig. 5 Bar graph of the frequency of Knowledge Development sub-categories in WhatsApp messages, and their statistical significance across cohort clusters
Fig. 6 Tailored heat maps that indicate the frequency of annotated sub-categories of WhatApp messages of individual L-PLC participants in each cohort
The findings were also interpreted using three levels of granularity: macro, meso, and micro. In our case, a macro-level analysis can identify behaviors and patterns of the whole L-PLC, and how they correlate with the PLC characteristics. The meso-level refers to subgroups within the entire community, that share attributes or demonstrate a unique engagement. The micro-level refers to behaviors and professional development of individuals.
Community Development
In this section, the results refer to SNA metrics and visualization that were explicated in the Methods section.
Macro-Level (The Whole Community)
Figure 3 shows the SNA graphs of the L-PLC discourse across four consecutive cohorts; their corresponding network metrics are presented in Table 6. Of note, each network graph should be interpreted as a stand-alone unit, as it was adapted to visualize the information of a specific cohort. Therefore, the sizes of nodes are valid only for a specific cohort and cannot be compared across cohorts. Further support for this point is provided in the supplementary material.
The SNA graphs in Figure 3 show a greater level of interconnectivity regarding the L-PLC networks of cohorts III and IV compared to those of cohorts I and II, as indicated by both the greater number of edges (interactions between participants) and their thickness (frequency). This difference is supported by an increase in both the computed average weighted degree centrality and graph density (see Table 6). Specifically, cohorts I and II — which were active in the period before the COVID-19 outbreak — generally reflected an experienced L-PLC, that already developed a certain level of community characteristics. Cohort III showed notable differences in the network metrics, as well as in the number and frequency of the interactions, with more connections between different participants, denoting an increased level of communication. The pandemic period — cohorts III and IV — showed reinforced L-PLC cohesiveness (graph density of 0.859 and 0.729, respectively), compared to the pre-pandemic cohorts I and II (from a graph density of 0.620 in cohort I to 0.859 in cohort III, and from a graph density of 0.635 in cohort II to 0.729 in cohort IV). In cohort IV, the cohesiveness level was still relatively high, but less compared to cohort III, suggesting the beginning of an adjustment of the L-PLC online dynamics to the new reality resulting from the pandemic. The average weighted degree centrality were also higher in cohorts III and IV (170.7 and 100.6 respectively) than in cohorts I and II (63.5 and 62.1 respectively). This finding indicates a growing number of interactions between the participants in cohorts III and IV, and demonstrates that the L-PLC network became more interconnected.
A significantly higher number of Sharing (SHAR) tags — which refers to shares in teaching and learning materials, instructional apps, and information of scientific contents — was noted in cohorts III and IV, as compared to cohorts I and II. This finding can be attributed to the increased need for remote teaching materials during the COVID-19 pandemic. After the outbreak, the high volume of Sharing was relatively steady, with no significant change between cohort III and cohort IV; indicating that Sharing became a norm in the L-PLC.
A relatively low number of Cooperation (COOP) tags was obtained. This can be explained by the fact that complex and full cooperation mostly occurs in small groups or between two individuals, which requires other means of communication (phone calls, synchronous and face-to-face meetings, or shared documents) and not via WhatsApp only. In addition, the results suggest that group facilitators should elaborate more on the cooperation competency.
We perceive Positive Feedback (PF) as an important norm indicative of a safe environment with mutual respect among PLC participants. In the current analysis, the annotated PF tags were similar in cohorts I, II, and IV, with a statistically significant increase in cohort III. This peak may reflect reinforcement in the forms of sympathy and socioemotional support during a time of crisis.
Building Community (BC) values were significantly higher in cohort II. This may be a result of special time-consuming activities that were conducted during that period, explicitly to enhance collaborative community projects in the L-PLC program.
Meso-Level (Particular Subgroups)
Analysis of each of the four SNA graphs revealed a central cluster of senior participants (defined by the number of years they participated in the L-PLC), who frequently interacted with each other. For example, participants B, Q, R, and K who had been in the L-PLC for more than three years, formed a sort of a core of leaders within the L-PLC. The members of this senior group usually had higher values of weighted degree centrality compared to the participants of the other subgroups. They contributed more to the L-PLC discourse by asking for professional knowledge-related help, providing knowledge to the community, and sharing professional materials. On the other hand, the discourse of the newcomers' subgroup was comprised mainly of messages of positive feedback, indicating that the newcomers were attuned to the L-PLC discourse, and appreciated its value from their comfort zone as reflective observers. The SNA graphs did not identify any disconnected subgroups. In conclusion, the L-PLC proved to be a solid and cohesive community, which became even more unified in response to crisis.
Knowledge Development
The existing repertoire of teacher knowledge assessment tools includes design tasks, observations, teachers' pedagogical discussions, and self-reported tools such as surveys and questionnaires (Brantley-Dias & Ertmer, 2013; Tucker & Quintero-Ares, 2021). Here we suggest another methodology to this set, which is based on teacher communication with colleagues as reflected in their WhatsApp discourse analysis. Professional knowledge was reflected by utterances relating to CK, PCK, and TK, and in questions indicated by ASK-CK/PCK/TK. Figure 5 presents the frequency and significance level of the annotated Knowledge Development sub-categories. In addition, the individual contributions of the L-PLC participants in each cohort to the online WhatsApp discourse were visualized through tailored heat maps (see Fig. 6).
The CK and PCK tags generally increased between the cohorts, indicating positive and enhanced knowledge development processes over time within the L-PLC. Of note, the number of CK and PCK tags was significantly higher in cohorts III and IV compared to pre-COVID cohorts, suggesting that knowledge exchange was accelerated by the COVID-19 outbreak.
Furthermore, there was a significant increase in the number of both TK (from 9 tags in cohort I to 206 tags in cohort III), and ASK-TK (from 6 tags in cohort I to 82 tags in cohort III) tags across cohorts. In particular, the L-PLC participants actively requested and shared technological tools and methods in cohort III. These findings reflect the critical need for technological applications and solutions when shifting to distance teaching and learning. The findings are in line with recent studies which found that extensive pedagogical support is needed when designing digital teaching during the COVID-19 pandemic (Sarı & Keser, 2021). Rap et al. (2020) found that chemistry teachers participating in PLCs' WhatsApp groups during the COVID-19 pandemic mainly requested operational information related to TK and TPCK.
Micro-Level (Individuals)
The personal contributions of each L-PLC participant, in each cohort, are reflected by the content analysis visualized in the heat maps (see Fig. 6). The heat maps indicate high frequency of annotated Knowledge Development in cohort III, as visualized by the growing number and deeper blue squares.
A gradual personal development process of several L-PLC participants (e.g., I, K, and Y) was observed, as indicated by a significant increase in their Knowledge Development tags' values. In addition, the visualization enabled identification of roles taken by different participants. Some participants (e.g., D, I, K, and L) were found to continuously contribute to the knowledge development of the L-PLC, by frequently asking for different kinds of professional knowledge, and by sharing such knowledge with others. Such participants can be considered as knowledge promoters.
We suggest that the method described in this section is a valid and robust means of assessing PLC teachers' knowledge.
Conclusion
Development of Community and Professional Knowledge
In all the cohorts, the structure of the L-PLC demonstrated four network assemblies of connected interactions, with increasing cohesiveness over time. While the L-PLC WhatsApp was initially established as a platform for delivering administrative and formal messages, the participants gradually began to use it for professional purposes as well. The content analysis of the WhatsApp messages indicated that all types of professional knowledge, i.e., CK, PCK, and TK, increased over time, aligning with previously reported qualitative analyses regarding the same L-PLC (Scherz et al., 2020). Interpretation of the data using the Collaboration Model (Eylon et al., 2020), showed that over the two years of the study, the L-PLC developed higher levels of collaboration, which shifted from sharing towards partnership.
These findings echo the concept of “commognition” — a combination of both cognitive and interpersonal communication, coined by Sfard (2020), which suggests that knowledge is being developed through commognitive processes. While Sfard usually refers to face-to-face discourse as a mean of knowledge development, it can also be applied to online discourse, such as in WhatsApp groups. The current research suggests a strong link between professional knowledge development, and the level of community development. These two dimensions are intertwined, supporting, nourishing, and complementing each other.
L-PLC Development During COVID-19 Pandemic
Professional Interactions
During the pandemic period, the WhatsApp group instantaneously became a readily available resource for professional knowledge, in addition to the regular zoom meetings. The outbreak of the pandemic enhanced professional interactions, as evidenced by the increased volume of science and science teaching consulting issues, responses to queries, and sharing of teaching and learning materials, professional-technological applications, and online experiments.
Socioemotional Support
The WhatsApp platform provided an opportunity for community bonding, and served as a source of socioemotional resilience for the L-PLC participants struggling with a complex reality. Thus, without deliberate planning, the scope of support, sharing, and collaboration within the community expanded. As the L-PLC supervisors, we were concerned that the L-PLC may disperse due to COVID-19 lockdowns and the shift to distance teaching and learning. Yet, it appears that the decision we made at the very beginning of the pandemic — namely, to continue with the principal outline and pedagogical approach of L-PLC meetings through technological interfaces — encouraged online interconnections in the community.
Integrating Structure and Content
The findings of this study underscored the importance of integrating both structure and content analyses of the L-PLC's WhatsApp discourse, as also demonstrated in another study with similar goals (Alwafi, 2021). This methodology provided insights into processes and profiles of professional development at the macro, meso, and micro levels. The SNA measured degrees of coherence and types of interactions within the L-PLC, and subsequently illuminated the intensity of various community characteristics. The content analysis exposed the professional knowledge and know-how associated with the L-PLC dynamics. This approach enabled us to identify and monitor changes in key PLC characteristics, and to evaluate their fluctuations under the influence of chaotic changes, like the COVID-19 pandemic.
Implications and Limitations
This study was conducted before and during the first year of the COVID-19 pandemic. While future research will be needed to assess the longevity of shifts and developments detailed in this study, PLCs facing times of lockdown or other challenging situations may benefit from the insights of this study.
This study demonstrated the value of using WhatsApp, by researchers and community leaders, as a source of data for a noninvasive continuous diagnosis of group behavior, relationships, and online dynamics. Thus, it will enable responsive feedback to the community as a whole and to individual participants, as well as fine-tuning of PLC meeting programs.
The study was carried out within an established community, with a previous acquaintance and common professional knowledge, and thus with an appreciation of the value of a PLC. Studies investigating PLC dynamics in communities that were newly established during the pandemic, may yield different results. Therefore, research comparing PLCs with community tradition versus PLCs without is required. In this notion, relevant models of online professional development should be employed (e.g., Duncan‐Howell, 2010; Salmon, 2013).
Our decision to set the unit of analysis as a single WhatsApp message likely affected the results. There is no doubt that in messaging applications, such as WhatsApp, individuals may use multiple messages to talk around the same point. Therefore, while two or multiple messages are utilized by the same user to address the same issue, tagging their content and counting them as stand-alone messages may have biased the analysis. Hence, future studies may choose to set different units of analysis to overcome this potential limitation. However, it is important to note that a message-level analysis is common and acceptable when annotating the content of forums and social media sites (Alwafi, 2021; Cansoy, 2017).
Crossing Boundaries: Computer Science and Professional Development
The growing usage of social media platforms — such as WhatsApp — in online learning and teaching environments, calls for collaborative work between science teaching researchers and data and computer scientists. This will advance the development of appropriate and supportive artificial intelligence-based tools, particularly, by harnessing state-of-the-art Machine Learning and Natural Language Processing techniques. In the absence of such dedicated tools to apply on platforms where rich and big data are generated, it will be difficult for researchers and supervisors to track the online dynamics of a PLC to evaluate their productivity or relevance to the community objectives. Similar tools are used in learning analytics, to understand and optimize learning (Clow, 2013; Ferguson, 2012). Taken together Professional Development Analytics may serve as an authentic means for monitoring community development, and gaining insights into its social and professional knowledge expressions. Indeed, the analytical approach used in this study to identify, understand, and formalize both community and professional development processes within the L-PLC, can be applied to other learning communities.
Supplementary Information
Below is the link to the electronic supplementary material. ESM 1 (JPG 2.09 MB)
Acknowledgements
We would like to acknowledge our colleagues for their valuable contribution to the development of the Science & Technology PLC project along 2019-2021: S. Bismuth, M. Frailich & Y. Harari. We thank the teachers who participated in our leaders' PLCs – for sharing their experiences with us. We thank B. Eilon & A. Yarden for their support and advice, and Y. Varon for her contribution to the statistics.
Funding
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Declarations
Competing Interests
The authors have no relevant financial or non-financial interests to disclose.
Graphics Program Used to Create the Artwork
Adobe Photoshop, Gephi, and Seaborn (a Python data visualization library).
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734941 | NO-CC CODE | 2022-12-14 23:28:31 | no | Int J Artif Intell Educ. 2022 Dec 8;:1-25 | utf-8 | Int J Artif Intell Educ | 2,022 | 10.1007/s40593-022-00320-3 | oa_other |
==== Front
Bull Math Biol
Bull Math Biol
Bulletin of Mathematical Biology
0092-8240
1522-9602
Springer US New York
36463533
1111
10.1007/s11538-022-01111-6
Original Article
The Role of Permanently Resident Populations in the Two-Patches SIR Model with Commuters
http://orcid.org/0000-0002-8515-0838
Rapaport Alain [email protected]
Mimouni Ismail [email protected]
grid.121334.6 0000 0001 2097 0141 MISTEA, Université Montpellier, INRAE, Institut Agro, place Viala, 34060 Montpellier, France
4 12 2022
2023
85 1 313 6 2022
27 11 2022
© The Author(s), under exclusive licence to Society for Mathematical Biology 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
We consider a two-patches SIR model where communication occurs through commuters, distinguishing explicitly permanently resident populations from commuters populations. We give an explicit formula of the reproduction number and show how the proportions of permanently resident populations impact it. We exhibit nonintuitive situations for which allowing commuting from a safe territory to another one where the transmission rate is higher can reduce the overall epidemic threshold and avoid an outbreak.
Keywords
SIR model
Reproduction number
Patches models
Commuters
Mathematics Subject Classification
92D30
34D20
90C31
issue-copyright-statement© Society for Mathematical Biology 2023
==== Body
pmcIntroduction
Since the pioneer work of Kermack and McKendrick (1927), the SIR model has been very popular in epidemiology, as the basic model for infectious diseases with direct transmission (e.g., Anderson and May 1991). It retakes great importance nowadays due to the recent coronavirus pandemic. While early models were not spatialized, the importance of accounting for spatial heterogeneity has been often reported in the literature (see, e.g., Angulo et al. 1979; Sattenspiel and Dietz 1995; Keeling et al. 2004; Keeling and Rohani 2007; Kelly et al. 2016; Li et al. 2021). However, different mechanisms come into play to explain the spatial spreading of a disease. Although diffusion appears to be a natural process to describe the local propagation of an infectious agent among a population, which leads to models with partial differential equations (Murray 2003), it appears to be not well suited for describing long distance spreading. In particular, transportation between cities comes into the picture as a major source of rapid spreading among nonhomogeneous populations (Arino and van den Driessche 2003; Arino et al. 2007; Takeuchi et al. 2007; Liu and Stechlinski 2013; Mpolya et al. 2014; Chen et al. 2014; Yin et al. 2020; Tocto-Erazo et al. 2021; Lipshtat et al. 2021). Meta-populations or multi-patches models are then more appropriate to describe the spatial characteristics of the propagation (Wang and Mulone 2003; Wang and Zhao 2004; Arino and van den Driessche 2006; Gao 2007; Arino 2009), as already well considered in ecology (Hanski 1999; MacArthur 2001). These models require a precise description of the movements between patches, which are most of the time assumed to be linear and thus encoded into a connection matrix (Arino and van den Driessche 2006; Arino 2009). Typically one obtains a system of ordinary differential equations on a graph, which couples the communication dynamics with the epidemiological one.
For diseases spreading among human populations living in different cities, commuters (individuals housing in a city, traveling regularly for short periods in a neighboring city, and coming back to their home city) play a crucial role in the disease propagation among territories (Keeling and Rohani 2002; Keeling et al. 2004; Keeling and Rohani 2007; Mpolya et al. 2014; Yin et al. 2020). Such coupling between patches have been already considered in the literature, distinguishing among populations Ni attached to a city i the subpopulation Nii present in its permanent housing from other subpopulations Nij temporary present in another city j≠i [it can be also seen as multi-groups models as in Clancy (1996), Guo et al. (2006), Iggidr et al. (2012)]. However, such models explicitly assume that the whole population housing in a given city can potentially commute to another one. We believe that this is not always fully realistic and that a subpopulation that never (or very rarely) moves to another city should be distinguished from the subpopulation that visits at a regular basis another city. Therefore, we consider an extension of such models, which explicitly takes into consideration two kinds of movement: an Eulerian one which describes the flow between patches that mixes populations, and an Lagrangian one which assigns home locations of individuals, as described in the more general framework (Citron et al. 2021). The study of this extension, which has not yet been analyzed analytically in the literature, to our knowledge, and how it impacts the disease spreading, is the primary objective of the present work. For this purpose, we establish an analytical expression of the reproduction number [as the epidemic threshold formerly introduced and analyzed in Diekmann et al. (1990), van den Driessche and Watmough (2002), Diekmann et al. (2007), Dhirasakdanon et al. (2007)] for the two patches case (that is also valid for the particular case when the whole populations travel, for which the exact expression of the reproduction number has not been yet provided in the literature).
We also had in mind to consider heterogeneity among territories when disease transmission differs from one city to another one. Typically, non-pharmaceutical interventions (such as reducing physical distance in the population) could be applied with different strength in each city, providing distinct transmission rates. When one territory being isolated presents a higher reproduction number than the other territory, it can be considered as a core group in the epidemiological terminology (Hadeler and Castillo-Chavez 1995; Brunham 1997), and commuters contribute then to spread the epidemics in both territories. We aim at analyzing more precisely how the proportions of commuters in each city can increase or decrease the overall reproduction number. Intuitively, one may believe that the best way to reduce the spreading is to encourage commuters from the city with the lowest transmission rate not to travel to the other city, and on the opposite to encourage as much as possible commuters from the other city to spend time in the safer city. Indeed, we shall see that this is not always true... The second objective of the present work is thus to study the minimization of the epidemic threshold of the two-patches model with respect to these proportions, depending on the commuting rates. This analysis can potentially serve for decisions making to prevent epidemic outbreak [as in Knipl (2016), for instance].
The paper is organized as follows. In the next section, we present the complete model in dimension 18 and give some preliminaries. Sect. 3 is devoted to the analysis of the asymptotic behavior of the solutions of the model. We give and demonstrate an explicit expression of the reproduction number, introducing four relevant quantities qij (i,j=1,2). In a corollary, we also give an alternative way of computation, which is useful in the following. In Sect. 4, we study the minimization of the reproduction number with respect to the proportions of commuters in each patch. Finally, Sect. 5 gives a numerical illustration of the results, considering two territories with intrinsic basic reproduction numbers lower and higher than one. We depict the relative sizes of the permanently resident populations that can avoid the outbreak of the epidemic depending on the commuting rates, and discuss the various cases. We end with a conclusion.
The Model
We follow the modeling of commuters proposed in Keeling and Rohani (2002) between two patches (such as cities or territories), but here we consider in addition that a part of the population in each patch do not commute (the permanently resident subpopulation). We consider populations of size Ni whose home belongs to a patch i∈{1,2}, structured in three groups: permanently resident, being all the time in patch i, whose population size is denoted Nir,
commuters to patch j, but located in patch i at time t, of population size denoted Nii,
commuters to patch j and located in patch j at time t, of population size denoted Nij.
We shall denote Nic=Nii+Nij the size of the total population of commuters with their home in patch i. The individuals commutes to patch j at a rate λi with a return rate μi. For each group g∈{ir,ii,ij} we denote by Sg, Ig, Rg the sizes of susceptible, infected and recovered subpopulations. This modeling implicitly assumes that at any time there is no individual out the territories, that is traveling time is negligible. This assumption is therefore only valid for adjoining territories with short transportation times (by train, road, etc.). It would not be valid between distant territories connected for example by boat or plane with non-negligible crossing times. In this case, it would be necessary to consider additional nodes of in-transit populations, as it has been considered for example in Colizza et al. (2006), Patil et al. (2021) or Ruan et al. (2015) where distance between nodes are explicitly taken into consideration. This would of course complicates the model and its study.
We consider the SIR model assuming that the recovery parameter γ is identical everywhere while the transmission rate βi depends on the patch i but is identical among each group. Typically lifestyle and hygienic measures may differ between two cities, implying different values of β. Moreover, if two cities are on both sides of the border between two countries, the strength of non-pharmaceutical interventions are likely to be different, as is was, for instance, the case between European countries during the SARS-2 outbreak. The model is written as follows (with i≠j in {1,2}).S˙ir=-βiSirIir+Iii+IjiNir+Nii+Nji,I˙ir=βiSirIir+Iii+IjiNir+Nii+Nji-γIir,R˙ir=γIir,S˙ii=-βiSiiIir+Iii+IjiNir+Nii+Nji-λiSii+μiSij,I˙ii=βiSiiIir+Iii+IjiNir+Nii+Nji-γIii-λiIii+μiIij,R˙ii=γIii-λiRii+μiRij,S˙ij=-βjSijIjr+Ijj+IijNjr+Njj+Nij+λiSii-μiSij,I˙ij=βjSijIjr+Ijj+IijNjr+Njj+Nij-γIij+λiIii-μiIij,R˙ij=γIij+λiRii-μiRij
Parameters λi, μi represent switching rates of populations i, leaving home and returning. This modeling implicitly assumes that movements between territories are not synchronized, as often considered in multi-city models (see, e.g., Sattenspiel and Dietz 1995; Keeling and Rohani 2002; Arino and van den Driessche 2003; Wang and Mulone 2003; Wang and Zhao 2004; Keeling et al. 2004; Arino and van den Driessche 2006; Takeuchi et al. 2007; Keeling and Rohani 2007; Liu and Stechlinski 2013; Chen et al. 2014). Note that we also consider, in all generality, that commuting is asymmetrical (i.e., λ1 and λ2 may be different, as well as μ1, μ2). Typically, each territory may offer different activities that attract commuters from the other territory and thus different mean sojourn times. One can check that the population sizes Nir and Nic are constant. Moreover Nii, Nij fulfill the system of equationsN˙ii=-λiNii+μiNij,N˙ij=λiNii-μiNij
whose solutions verify1 limt→+∞Nii(t)=N¯ii:=μiλi+μiNic,limt→+∞Nij(t)=N¯ij:=λiλi+μiNic
We shall assume that populations are already balanced at initial time, i.e., that one has Nii=N¯ii, Nij=N¯ij (constant). For simplicity, we shall drop the notation ¯ in the following and denoteNip:=Nir+Nii+Nji
which represents the (constant) size of the total population present in patch i.
The Epidemic Threshold
We denote the vectorsI=(I1r,I11,I12,I2r,I22,I21)⊤,S=(S1r,S11,S12,S2r,S22,S21)⊤
and consider the state vectorX=IS
which belongs to the invariant domainD:={X∈R+12;MX≤N}
where N is the vectorN=(N1r,N11,N12,N2r,N22,N21)⊤
and M the 6×12 matrix which consists in the concatenation of the identity matrix I6 of dimension 6×6M=[I6,I6]
The disease free equilibrium is defined asX⋆=0N
Let Ri be the intrinsic reproduction number in the patch i (i.e., when there is no connection between patches), that isRi:=βiγ.
We give now an explicit expression of the epidemic threshold when the two patches communicates via commuters.
Proposition 1
Let2 R1,2:=q11+q22+(q22-q11)2+4q12q212
where3 q11=R1N1rN1p+N11N1pγ+μ1γ+λ1+μ1+N21N1pγ+λ2γ+λ2+μ2q22=R2N2rN2p+N22N2pγ+μ2γ+λ2+μ2+N12N2pγ+λ1γ+λ1+μ1q21=R1N11N1pλ1γ+λ1+μ1+N21N1pμ2γ+λ2+μ2q12=R2N12N2pμ1γ+λ1+μ1+N22N2pλ2γ+λ2+μ2
Then, one has the following properties. If R1,2>1, then X⋆ is unstable.
If R1,2<1, then X⋆ is exponentially stable with respect to the variable1I.
If R1=R2:=R, then R1,2=R.
Proof
Write the dynamics of X as X˙=f(X). The Jacobian matrix J of f at X⋆ is of the formJ=A0⋆BwithA=F-V
whereF=β1N1rN1pβ1N1rN1p000β1N1rN1pβ1N11N1pβ1N11N1p000β1N11N1p00β2N12N2pβ2N12N2pβ2N12N2p000β2N2rN2pβ2N2rN2pβ2N2rN2p000β2N22N2pβ2N22N2pβ2N22N2p0β1N21N1pβ1N21N1p000β1N21N1p,V=γ000000γ+λ1-μ10000-λ1γ+μ1000000γ000000γ+λ2-μ20000-λ2γ+μ2
andB=0000000-λ1μ10000λ1-μ10000000000000-λ2μ20000λ2-μ2
Note that F is a nonnegative matrix and V is a non-singular M-matrix. We recall [see, for instance, from van den Driessche and Watmough (2002)] that one has the propertymaxRe(Spec(A))<>0⟺ρ(FV-1)<>1
The computation of the matrix M:=FV-1 gives the following expressionM=R1N1rN1pR1N1r(γ+μ1)N1p(γ+λ1+μ1)R1N1rμ1N1p(γ+λ1+μ1)0R1N1rλ2N1p(γ+λ2+μ2)R1N1r(γ+λ2)N1p(γ+λ2+μ2)R1N11N1pR1N11(γ+μ1)N1p(γ+λ1+μ1)R1N11μ1N1p(γ+λ1+μ1)0R1N11λ2N1p(γ+λ2+μ2)R1N11(γ+λ2)N1p(γ+λ2+μ2)0R2N12λ1N2p(γ+λ1+μ1)R2N12(γ+λ1)N2p(γ+λ1+μ1)R2N12N2pR2N12(γ+μ2)N2p(γ+λ2+μ2)R2N12μ2N1p(γ+λ2+μ2)0R2N2rλ1N2p(γ+λ1+μ1)R2N2r(γ+λ1)N2p(γ+λ1+μ1)R2N2rN2pR2N2r(γ+μ2)N2p(γ+λ2+μ2)R2N2rμ2N1p(γ+λ2+μ2)0R2N22λ1N2p(γ+λ1+μ1)R2N22(γ+λ1)N2p(γ+λ1+μ1)R2N22N2pR2N22(γ+μ2)N2p(γ+λ2+μ2)R2N22μ2N1p(γ+λ2+μ2)R1N21N1pR1N21(γ+μ1)N1p(γ+λ1+μ1)R1N21μ1N1p(γ+λ1+μ1)0R1N21λ2N1p(γ+λ2+μ2)R1N21(γ+λ2)N1p(γ+λ2+μ2)
Let us consider the diagonal matrixD:=R1N1rN1pR1N11N1pR2N12N2pR2N2rN2pR2N22N2pR1N21N1p
and the matrix Q=D-1MD, whose computation gives the expressionQ=R1N1rN1pR1N11(γ+μ1)N1p(γ+λ1+μ1)R2N12μ1N2p(γ+λ1+μ1)0R2N22λ2N2p(γ+λ2+μ2)R1N21(γ+λ2)N1p(γ+λ2+μ2)R1N1rN1pR1N11(γ+μ1)N1p(γ+λ1+μ1)R2N12μ1N2p(γ+λ1+μ1)0R2N22λ2N2p(γ+λ2+μ2)R1N21(γ+λ2)N1p(γ+λ2+μ2)0R1N11λ1N1p(γ+λ1+μ1)R2N12(γ+λ1)N2p(γ+λ1+μ1)R2N2rN2pR2N22(γ+μ2)N2p(γ+λ2+μ2)R1N21μ2N1p(γ+λ2+μ2)0R1N11λ1N1p(γ+λ1+μ1)R2N12(γ+λ1)N2p(γ+λ1+μ1)R2N2rN2pR2N22(γ+μ2)N2p(γ+λ2+μ2)R1N21μ2N1p(γ+λ2+μ2)0R1N11λ1N1p(γ+λ1+μ1)R2N12(γ+λ1)N2p(γ+λ1+μ1)R2N2rN2pR2N22(γ+μ2)N2p(γ+λ2+μ2)R1N21μ2N1p(γ+λ2+μ2)R1N1rN1pR1N11(γ+μ1)N1p(γ+λ1+μ1)R2N12μ1N2p(γ+λ1+μ1)0R2N22λ2N2p(γ+λ2+μ2)R1N21(γ+λ2)N1p(γ+λ2+μ2)
The matrix Q is nonnegative and irreducible. By Perron–Frobenius theorem [see, for instance, Berman and Plemmons (1994)], this matrix admits a unique positive eigenvector (up to a scalar multiplication) that corresponds to the simple (positive) eigenvalue ℓ=ρ(Q)=ρ(M).
Note that the rank of Q is two. We positY=(1,1,0,0,0,1)⊤,Z=(0,0,1,1,1,0)⊤
and define QY, QZ the first and third lines, respectively, of the matrix Q. Then, for any vector X∈R6, one has QX=(QYX)Y+(QZX)Z. We look for an positive eigenvector X of the form X=αY+(1-α)Z with α∈(0,1). One has then4 QX=αQY+(1-α)QZ=α((QYY)Y+(QZY)Z)+(1-α)((QYZ)Y+(QZZ)Z)=(α(QYY)+(1-α)(QYZ))Y+(α(QZY)+(1-α)(QZZ))Z
On the other hand, as X is an eigenvector, one has5 QX=ℓX=αℓY+(1-α)ℓZ
The vectors Y and Z being orthogonal, one obtains from (4)–(5) the conditions6 αQYY+(1-α)QYZ=αℓαQZY+(1-α)QZZ=(1-α)ℓ
Let r=1-αα. Eliminating ℓ in the two previous equations, r is the positive solution of the polynomialr2QYZ+r(QYY-QZZ)-QZY=0
and ℓ=QYY+rQYZ. One obtains the expression of the eigenvalueℓ=QYY+QZZ+(QYY-QZZ)2+4(QYZ)(QZY)2
Finally, from the expression of Q, one getsq11=QYY=R1N1rN1p+N11N1pγ+μ1γ+λ1+μ1+N21N1pγ+λ2γ+λ2+μ2q22=QZZ=R2N2rN2p+N22N2pγ+μ2γ+λ2+μ2+N12N2pγ+λ1γ+λ1+μ1q21=QZY=R1N11N1pλ1γ+λ1+μ1+N21N1pμ2γ+λ2+μ2q12=QYZ=R2N12N2pμ1γ+λ1+μ1+N22N2pλ2γ+λ2+μ2
and thus ℓ=R1,2, which is exactly ρ(M).
i. When R1,2>1, the matrix A has at least one eigenvalue with positive real part and the matrix J as well. The equilibrium X⋆ is thus unstable on D.
ii. When R1,2<1, the matrix A is Hurwitz, but X⋆ is not an hyperbolic equilibrium. However, on can write the dynamics of the vector I as an non-autonomous systemI˙=g(t,I):=β1S1r(t)I1r+I11+I21N1p-γI1rβ1S11(t)I1r+I11+I21N1p-(γ+λ1)I11+μ1I12β2S12(t)I2r+I22+I12N2p+λ1I11-(γ+μ1)I12β2S2r(t)I2r+I22+I12N2p-γI2rβ2S22(t)I2r+I22+I12N2p-(γ+λ2)I22+μ2I21β1S21(t)I1r+I11+I21N1p+λ2I22-(γ+μ2)I21
Note that this dynamics is cooperative and as for any t≥0 one has Sij(t)≤Nij for ij∈{1r,11,12,2r,22,21}, one getsg(t,I)≤g¯(I):=AI,I≥0
Therefore, any solution I(·) of I˙=g(t,I) with I(0)=I0≥0 verifies 0≤I(t)≤I¯(t) for any t≥0, where I¯(·) is solution of the linear dynamics I¯˙=g¯(I¯) with I¯(0)=I0. As A is Hurwitz, we conclude that X⋆ is exponentially stable with respect to I, which proves point ii.
iii. For the particular case R1=R2:=R, the transpose of the matrix M writesM⊤=RN1rN1pN11N1p000N21N1pN1r(γ+μ1)N1p(γ+λ1+μ1)N11(γ+μ1)N1p(γ+λ1+μ1)N12λ1N2p(γ+λ1+μ1)N2rλ1N2p(γ+λ1+μ1)N22λ1N2p(γ+λ1+μ1)N21(γ+μ1)N1p(γ+λ1+μ1)N1rμ1N1p(γ+λ1+μ1)N11μ1N1p(γ+λ1+μ1)N12(γ+λ1)N2p(γ+λ1+μ1)N2r(γ+λ1)N2p(γ+λ1+μ1)N22(γ+λ1)N2p(γ+λ1+μ1)N21μ1N1p(γ+λ1+μ1)00N12N2pN2rN2pN22N2p0N1rλ2N1p(γ+λ2+μ2)N11λ2N1p(γ+λ2+μ2)N12(γ+μ2)N2p(γ+λ2+μ2)N2r(γ+μ2)N2p(γ+λ2+μ2)N22(γ+μ2)N2p(γ+λ2+μ2)N21λ2N1p(γ+λ2+μ2)N1r(γ+λ2)N1p(γ+λ2+μ2)N11(γ+λ2)N1p(γ+λ2+μ2)N12μ2N1p(γ+λ2+μ2)N2rμ2N1p(γ+λ2+μ2)N22μ2N1p(γ+λ2+μ2)N21(γ+λ2)N1p(γ+λ2+μ2)
One can check that one has M⊤U=RU where U=(1,1,1,1,1,1)⊤. As U is a positive vector, we deduce from the Perron–Frobenius theorem that one has ρ(M)=ρ(MT)=R, which ends the proof. □
Remark 1
More generally, the next-generation matrix M=FV-1 can be shown to have a rank equal to the number n of patches and that its Perron vector can be expressed as a convex combination of a family of orthogonal vectors in the image of M. This implies that the positive eigenvalue of M (i.e., the reproduction number) is also the positive eigenvalue of the n-dimensional positive matrix given by the decomposition of the image of this vectors by the matrix M.
Alternatively, one may consider the epidemic spread in a virgin population as a Markov process, to determine the expected numbers of secondary cases in each patch, and obtain this n×n matrix, as described in Diekmann et al. (2013). This method consists in a first-step analysis by determining the mean residence times of an infected individual of each group in each of the patches. Then, for a given patch the expected numbers of new infected present in each path are given by the products of the mean residence times by the transmission rate, averaged by the constant distribution given in (1).
This explains why the formula (2) takes the expression of a root of the characteristic polynomial of a 2 by 2 matrix.
Remark 2
The explicit expression (2) of the epidemic threshold given in Proposition 1 is also relevant in absence of permanently resident populations, which has not been yet provided explicitly in the literature (up to our knowledge).
Corollary 2
One hasminR1,R2≤R1,2≤maxR1,R2.
Proof
Denote by M(R1,R2) the matrix FV-1 for the parameters R1, R2, and let R-:=minR1,R2, R+:=maxR1,R2. From the expression of the nonnegative matrices M, one getsM(R-,R-)≤M(R1,R2)≤M(R+,R+)
which implies [see, for instance, Berman and Plemmons (1994)] the inequalitiesρ(M(R-,R-))≤ρ(M(R1,R2))≤ρ(M(R+,R+))
and thusR-≤R1,2≤R+.
□
Alternatively, the number R1,2 can be determined as follows.
Corollary 3
Assume R2>R1. Then, one has7 R1,2=αR1+(1-α)R2
where α∈[0,1) is the smallest root of the polynomialP(α)=α2(R2-R1)-α(R2-R1+q12+q21)+q12
Proof
One can check, from expressions (3), that one has q11+q21=R1 and q22+q12=R2. Then, from (6), one get8 R1,2=l=αR1+(1-α)R2
where α is a root of the polynomial P obtained from (6) by eliminating l, that isP(α)=α2(R2-R1)-α(R2-R1+q12+q21)+q12
From Corollary 2, we know that α belongs to [0, 1].
Note that one has P(0)=q12≥0 and P(1)=-q21≤0. Therefore, when R2-R1>0, P admits exactly one root in [0, 1) and another one in [1,→). However, if α=1 one should have q21=0 and thus λ1=0, μ2=0, which implies N11=N1c, N12=0, N22=0, N21=N2c. Then, one obtains q11=R1, q22=R2 and from the expression (2) on gets R1,2=max(R1,R2)=R2 which contradicts α=1. We conclude that α belongs to [0, 1) and is thus the smallest root of P. □
Remark 3
When there is no communication between patches (that is N1r=N1p=N1, N2r=N2p=N2), one has q21=0 and q12=0. If R2>R1, resp. R1>R2, one has α=0, resp. α=1, which givesR1,2=max(R1,R2).
We look now for a characterization of the minimum value of the threshold R1,2.
Minimization of the Epidemic Threshold
In this section, we assume that the mixing is fast compared to the recovery rate (as its is often considered in the literature), which amounts to have numbers λi, μi large compared to γ. Our objective is to study how the proportions of commuters in the populations impact the value of R1,2.
Given R1, R2, we consider the approximation R~1,2 of the threshold R1,2 which consists in keeping γ=0 in the expressions (3). For convenience, we posit the numbersηi:=λiλi+μi∈(0,1)(i=1,2)
One has a first result about the variations of R~1,2 with respect to N1c, N2c.
Proposition 4
Fix parameters Ni, βi, γ, λi, μi (i=1,2) such that R2>R1. For any N1c∈(0,N1), the map N2c↦R~1,2(N1c,N2c) is decreasing.
The map N1c↦R~1,2(N1c,N2c) is increasing at (N1c,N2c) when 9 η2(1-η2)N2c>(1-η1)(N2-η2N2c)
The map N1c↦R~1,2(N1c,N2c) is increasing, resp. decreasing, at (N1c,N2c) if the numbers A and B are negative, resp. positive, where A:=R2N22-η1(12-η1)N1c-(32-η2)η2N2cN2-η2N2c+η1N1c-R1N12-(32-η1)η1N1c-η2(12-η2)N2cN1-η1N1c+η2N2c,B:=R2(1-η1)(N2-η2N2c)-η2(1-η2)N2c(N2-η2N2c+η1N1c)2-R1(1-η1)(N1+η2N2c)+η2(1-η2)N2c(N1-η1N1c+η2N2c)2
Proof
Following Corollary 3, one has10 R~1,2=α~R1+(1-α~)R2
where α~ is the smallest root of the polynomialP~(α)=α2(R2-R1)-α(R2-R1+q~12+q~21)+q~12
where q~12, q~21 are the approximations of q12, q21 defined in (3). Let us note that one can write Nii=(1-ηi)Nic, Nij=ηiNic (for j≠i) and also Nip=Ni-ηiNic+ηjNjc, which leads to the following expressions of q~12, q~2111 q~21=R1(1-η1)η1N1c+η2(1-η2)N2cN1-η1N1c+η2N2c,q~12=R2η1(1-η1)N1c+(1-η2)η2N2cN2-η2N2c+η1N1c
For simplicity, we shall drop the notation ~ in the rest of the proof. Note than α being the smallest root of P, it verifies12 α<R2-R1+q12+q212(R2-R1)
Let us differentiate the equality P(α)=0 with respect to q12 and q21:2α∂α∂q12(R2-R1)-∂α∂q12(R2-R1+q12+q21)-α+1=02α∂α∂q21(R2-R1)-∂α∂q21(R2-R1+q12+q21)-α=0
which gives∂α∂q12=1-αR2-R1+q12+q21-2α(R2-R1)∂α∂q21=-αR2-R1+q12+q21-2α(R2-R1)
Then, one can write∂α∂Nic=∂α∂q12∂q12∂Nic+∂α∂q21∂q21∂Nic=(1-α)∂q12∂Nic-α∂q21∂NicR2-R1+q12+q21-2α(R2-R1)(i=1,2)
and from inequality (12), we obtain that the signs of the derivatives ∂α∂Nic are given by the sign of the numbers13 σi:=(1-α)∂q12∂Nic-α∂q21∂Nic(i=1,2)
We begin by the dependency with respect to N2c. One has first∂q12∂N2c=R2η2(1-η2)(N2+η1N1c)+η1(1-η1)N1c(N2+η1N1c-η2N2c)2>0
Note that one has14 q21=R1(N2+η1N1c-η2N2c)R2(N1-η1N1c+η2N2c)q12
and thus∂q21∂N2c=R1(N2+η1N1c-η2N2c)R2(N1-η1N1c+η2N2c)∂q12∂N2c-R1η2(N1+N2)R2(N1-η1N1c+η2N2c)2q12
Then, one gets the inequalityσ2>1-α-αR1(N2+η1N1c-η2N2c)R2(N1-η1N1c+η2N2c)∂q12∂N2c
On another hand, one gets from P(α)=0 the inequality(1-α)q12-αq21=α(1-α)(R2-R1)>0
and with (14)(1-α)q12-αq21=1-α-αR1(N2+η1N1c-η2N2c)R2(N1-η1N1c+η2N2c)q12>0
We then conclude that σ2 is positive, and from (10) we deduce that the map N2c↦R1,2 is decreasing. This proves the point i.
We study now the dependency with respect to N1c. A calculation of the partial derivative gives15 ∂q12∂N1c=R2η1(1-η1)(N2-η2N2c)-η2(1-η2)N2c(N2-η2N2c+η1N1c)2
and16 ∂q21∂N1c=R1η1(1-η1)(N1+η2N2c)+η2(1-η2)N2c(N1-η1N1c+η2N2c)2>0
When ∂q12∂N1c<0, we can conclude that σ1 is negative and R1,2 is thus increasing with respect to N1c. This condition is equivalent to (9). This proves the point ii. When this last condition is not satisfied, having ∂q12∂N1c<∂q21∂N1c with α>12 is another sufficient condition to obtain σ1<0 from expression (13). However, having α>12 amounts to have P(12)>0, that isR2-R14-R2-R1+q12+q212+q12>0
or equivalentlyR22-q12<R12-q21
One can check that this last condition is equivalent to A<0 and that the condition ∂q12∂N1c<∂q21∂N1c is equivalent to B<0. In the same manner, having A>0 and B>0 implies α<12 and ∂q12∂N1c>∂q21∂N1c, which is a sufficient condition to have σ1>0, and thus R1,2 increasing with respect to N1c. This proves the point iii. □
This result suggests that the map N1c↦R~1,2(N1c,N2c) is not necessarily monotonic, differently to the map N2c↦R~1,2(N1c,N2c). We show now that the possibilities of its variations are limited.
Proposition 5
Under hypotheses of Proposition 4, for each N2c∈(0,N2) the map N1c↦R~1,2(N1c,N2c) possesses one of the three properties it is decreasing on (0,N1),
it is increasing on (0,N1),
there exists N1c⋆∈(0,N1) such that it is decreasing on (0,N1c⋆) and increasing on (N1c⋆,N1).
Proof
Fix N2c∈(0,N2). If the map N1c↦R~1,2(N1c,N2c) is not monotonic, there exists N^1c∈(0,N1) such that ∂R~1,2∂N1c(N^1c,N2c)=0. For simplicity, we shall drop the notation ~ in the rest of the proof. Following the proof of Proposition 4, one has R1,2=αR1+(1-α)R2 with∂α∂N1c=(1-α)∂q12∂N1c-α∂q21∂N1cR2-R1+q12+q21-2α(R2-R1):=σ1ν
where ν>0. Therefore, one has ∂α∂N1c=0 and σ1=0 at N1c=N^1c, and thus∂2α∂N1c2N1c=N^1c=∂σ1∂N1cνN1c=N^1c=(1-α)∂2q12∂N1c2-α∂2q21∂N1c2νN1c=N^1c
From expressions (15) and (16), a calculation of the partial derivatives gives∂2q12∂N1c2=-2η1∂q12∂N1cN1-η1N1c+η2N2c,∂2q21∂N1c2=2η1∂q21∂N1cN2-η2N2c+η1N1c
where ∂q21∂N1c>0 and from σ1=0 one gets ∂q12∂N1c>0 for N1c=N^1c. Finally, one obtains∂2R1,2∂N1c2(N^1c,N2c)=-(R2-R1)∂2α∂N1c2(N^1c,N2c)<0
Consequently, any extremum of the map N1c↦R1,2(N1c,N2c) is a local minimizer, which implies that this map has at most one local minimizer. □
Finally, we give conditions for which the minimization of the threshold R1,2 presents a trichotomy.
Proposition 6
Let parameters βi, γ be such that R2>R1 and assume that N1, N2 satisfy N1R2>N2R1. Then, provided that γ is small enough compared to λi and μi, the function (N1c,N2c)↦R1,2(N1c,N2c) admits an unique minimum at (N1c⋆,N2c⋆) with N2c⋆=N2. Moreover, one has the following properties. N1c⋆=0 if η2>1-η1,
N1c⋆=N1 if η1 and η2 are sufficiently small,
there exists η1, η2 for which N1c⋆∈(0,N1).
Proof
We first show that the announced properties are satisfied for the approximate function R~1,2.
From Propositions 4 and 5 , we know that R~1,2 admits an unique minimum at (N^1c,N^2c) with N^2c=N2. For N2c=N2, the condition (9) simply writes η2>1-η1 which implies from point ii. of Proposition 4 that one has N^1c=0 when this condition is fulfilled. This shows that point 1 is verified for the function R~1,2.
One obtains the limitslimη1,η2→0A=R22-R12>0,limη1,η2→0B=R2N2-R1N1>0
which show that numbers A and B are positive when η1, η2 are small, and thus one has N^1c=N1 from point iii of Proposition 4. This shows that point 2 is verified for the function R~1,2.
Take now any N1c∈(0,N1). When η2>1-η1, one has ∂R~1,2∂N1c(N1c,N2)>0, and for η1, η2 small, ∂R~1,2∂N1c(N1c,N2)<0 is verified. Then, by continuity of the function R~1,2 with respect to parameters η1, η2, one deduce that the existence of values η^1, η^2 for which ∂R~1,2∂N1(N1c,N2)=0. As the function R~1,2 cannot have more than a local extremum (see Proposition 5), we deduce that N1c realizes the minimum of the function N1c↦R~1,2(N1c,N2) when η1=η^1 and η2=η^2. This shows that point 3 is verified for the function R~1,2.Table 1 Characteristics numbers of the epidemic
γ β1 β2 R1 R2
0.3 0.27 0.33 0.9 1.1
Table 2 Three sets of commuting parameters
Case λ1 μ1 λ2 μ2 η1 η2
A 10 10 10 1 0.5 0.9090909
B 10 100 10 100 0.009901 0.009901
C 10 10 10 70 0.5 0.125
Table 3 Quality of the approximation R~1,2
Case A B C
∫maxp1,p2|R~1,2-R1,2| 1.910-3 1.410-4 610-4
Finally, note that the exact threshold R1,2 amounts to replace in the expression of q~12, q~21 the numbers ηi by λi+γλi+μi+γ , which is continuous with respect to γ and equal to ηi for γ=0. By continuity of R~1,2 with respect to q~12, q~21 , we deduce that uniqueness of the minimizer of R1,2 and properties 1. to 3. are also fulfilled by the function (N1c,N2c)↦R1,2, provided that γ is small enough. □
Fig. 1 R1,2 as a function of p1 in case A (each curve corresponds to a value of p2∈[0,1]) (Color Figure Online)
Fig. 2 R1,2 as a function of p1 in case B (each curve corresponds to a value of p2∈[0,1]) (Color Figure Online)
Fig. 3 R1,2 as a function of p1 in case C (each curve corresponds to a value of p2∈[0,1]) (Color Figure Online)
Numerical Illustration
We consider two territories of same population size N=N1=N2 with different transmission rates such that one has R1<1<R2 (values are given in Table 1). Typically, some precautionary measures (such as social distance) are taken in the first territory so that the disease cannot spread in this territory if it is closed, while the epidemic can spread in the second territory in absence of communication with territory 1. We aim at studying how the epidemic can die out when commuting occur between territories, depending on the proportions of resident in each population, denotedpi=:=NirN=1-NicN,(i=1,2)
(in other words, how to obtain R1,2<1 playing with p1, p2). Note that when N1=N2, the threshold R1,2 depends on the proportions p1, p2 independently of N.
Conditions of Proposition 6 are satisfied provided that commuting parameters λi, μi are large enough. We have considered three sets of these parameters, given in Table 2, that correspond to the three possible situations depicted in Proposition 6.
The approximate expression R~1,2 turns out to be a very good approximation of the exact value R1,2, even in case A for which γ is not so small compared to μ2 (see Table 3).
Figures 1, 2 and 3 show families of curves p1↦R1,2 for different values of p2∈[0,1]. One can observe that theses curves possess the properties given by Propositions 4 and 5:they are either decreasing, increasing or decreasing down to a minimum and then increasing,
they are ordered and the lower one is obtained for p2=0 (i.e., N2c=N2).
This last feature is intuitive: the more there are commuters from territory 2 (that spend time in territory 1 where the conditions of transmission disease is lower), the less the epidemic spreads. A way to reduce the value of R1,2 is thus to encourage commuting toward territory 1 (whatever are the commuting rates). However, the role of the resident population in territory 1 is far less intuitive because it does depends on the commuting rates. In case A, commuters from territory 2 return more rarely to home than commuters from territory 1 do. The condition of point 1 of Proposition 6 is fulfilled. Then, the threshold R1,2 can be made small (and below 1) when the proportion of resident in territory 1 is high, i.e., when the inhabitants of territory 1 are encouraged not to commute.
In case B, both commuters return rapidly to their home. This means that the numbers of commuters from one territory present in the other one at a given time is low. Then the condition of point 2 of Proposition 6 is fulfilled. Here, it is better to encourage inhabitants of territory 1 to commute to the other territory where the disease spreads yet more easily which is counterintuitive at first sight. Indeed, commuters do not spend much time in the other territory and therefore heuristically have less time to encounter and transmit the disease...
In case C, commuters from territory 2 return more rapidly to home than commuters from territory 1 do, on the opposite of case A. Conditions of points 1 and 2 of Proposition 6 are not fulfilled here, and we are in an intermediate situation for which point 3 of Proposition 6 occurs. It is theoretically possible to have R1,2<1 on the condition that the proportion of commuters of territory 1 is well balanced.
Finally, this example shows that changing only the return rates μ1, μ2 allows to obtain the three possible scenarios, but other changes could also exhibit them.
Conclusion
In this work, we have been able to provide an explicit expression of the reproduction number, although the model is in dimension 18. This expression has allowed us to study its minimization with respect to the proportions of permanently resident populations in each patch. We discovered a trichotomy of cases, with some counterintuitive situations. In each case, it is always beneficial to have commuters traveling to a safer city where the transmission rate is lower. However, for the safer city, three situations occur:either it is better to avoid commuting to the other city,
or on the opposite encouraging commuting to the more risky city reduces the reproduction number,
and in a third case there exists an optimal intermediate proportion of commuters of the safer city which minimizes the epidemic threshold.
In some sense, the permanently resident populations, which have been ignored in former modeling, can play an hidden role in an epidemic outbreak. This is illustrated on an example for which only right proportions of commuters (or permanently resident) avoid the outbreak. This suggests that counterintuitive situations may also occur when considering networks with more than two nodes. The present study focuses on the reproduction number and how it can be reduced. The impacts of resident proportions on other epidemiological characteristics, such as the peak level or the finite size, may be the matter a future work. The extension of the present results to more general networks is also a future perspective.
Acknowledgements
The authors are grateful for the support of the French platform MODCOV19, and the Algerian Government for the PhD grant of Ismail Mimouni. The authors thank the anonymous referee to let us know the alternative approach to obtain the expression of the reproduction number, mentioned in Remark 1.
1 We refer to Vorotnikov (1998) for the definition of partial stability.
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| 36463533 | PMC9734942 | NO-CC CODE | 2022-12-14 23:28:31 | no | Bull Math Biol. 2023 Dec 4; 85(1):3 | utf-8 | Bull Math Biol | 2,022 | 10.1007/s11538-022-01111-6 | oa_other |
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J Child Adolesc Trauma
J Child Adolesc Trauma
Journal of Child & Adolescent Trauma
1936-1521
1936-153X
Springer International Publishing Cham
506
10.1007/s40653-022-00506-w
Original Article
Does Fear of COVID-19 Prolongation Lead to Future Career Anxiety Among Adolescents? The Mediating Role of Depressive Symptoms
Shindi Yousef Abu [email protected]
1
http://orcid.org/0000-0003-4451-9237
Emam Mahmoud Mohamed [email protected]
1
Farhadi Hadi [email protected]
2
1 grid.412846.d 0000 0001 0726 9430 Department of Psychology, College of Education, Sultan Qaboos University, P.O. Box: 32 Al-Khod, P.C.: 123, Seeb, Oman
2 grid.411757.1 0000 0004 1755 5416 Department of Psychology, Faculty of Educational Sciences & Psychology, Islamic Azad University, Isfahan, Khorasgan Iran
7 12 2022
110
29 11 2022
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The outbreak of the COVID-19 pandemic has influenced the lives of individuals from all different age groups. In particular, the prolongation of COVID-19 and the emergence of virus variants, such as Omicron, Delta and Alpha, have caused trauma to university students amid expectations that the associated economic, social, and psychological outcomes could affect their future careers. The current study, therefore, examines how the fear of COVID-19 prolongation may affect future career anxiety (FCA) among adolescents and to what extent depressive symptoms may determine such a relationship. Using a cross-sectional design, a survey was conducted to assess depressive symptoms, FCA, and fear of COVID-19 prolongation among 605 university students in Oman, an Arabic-speaking country located in the Gulf region. Using structural equation modeling, the results showed that there were significant standardized direct effects (unmediated) of fear of COVID-19 on depression from COVID-19 and of depression from COVID-19 on FCA. Additionally, depression from COVID-19 mediated the relationship between fear of COVID-19 and FCA. The results are discussed within the Omani context of mental health service accessibility challenges and the dominant culture of perceiving mental health services with social stigma.
Supplementary Information
The online version contains supplementary material available at 10.1007/s40653-022-00506-w.
Keywords
COVID-19 variants
Career Anxiety
Fear
Depressive Symptoms
Adolescents
Oman
==== Body
pmcIntroduction
Three years have passed since the first confirmed case of coronavirus disease 2019 (COVID-19) in Hong Kong was announced. In 2020, the World Health Organization (WHO) officially declared COVID-19 a global pandemic and labeled the coronavirus a sixth public health emergency of international concern in modern history (Şimşir et al., 2022; Vilca et al., 2022). Several researchers have highlighted the broad range of psychosocial consequences that could be inflicted by the COVID-19 pandemic on the general population (Badahdah et al., 2021; Hasani et al., 2020; Yıldırım et al., 2022) amidst speculations over its continuation for some years to come. Adolescents, in particular, have been more traumatized due to the prolongation of COVID-19 and the emergence of several COVID-19 variants (Bai et al., 2022; Cleveland et al., 2022; Şimşir et al., 2022; Yıldırım et al., 2022). With thousands of people being impacted by the incapacitating effects of COVID-19, certain groups, such as university students, appear to be more vulnerable and at increased risk of psychological problems (Mahmud et al., 2021; Pak et al., 2022). Limited research has examined the impact of COVID-19 prolongation on the mental health of university students in different contexts (El-Khodary et al., 2022; Malik & Javed, 2021).
There is evidence that pandemics create not only socioeconomic crises, but also psychological crises, such as fear, panic, anxiety, insomnia, depression, anger and boredom (Balakrishnan et al., 2022; Özdin & Bayrak Özdin, 2020). Psychological distress arises mainly from individuals’ ideas, which are shaped the media and news about the pandemic. The information, and, at times, misinformation, individuals receive results in fear, depression and anxiety about what may occur in the future (Alimoradi et al., 2022). Moreover, preventive policies implemented by governments to curb the COVID-19 pandemic, such as home confinement, physical distancing, and nationwide lockdowns, have also increased anxiety and fear among individuals and communities (Alimoradi et al., 2022; Bakioğlu et al., 2021). Additionally, published medical and scientific literature, as well as public reports in all types of media, have increased panic, fear, and stigmatization (Pak et al., 2022; Luo et al., 2021).
Psychological Outcomes of COVID-19
Anxiety and depression related to news of the global economy have become a major concern, particularly with forecasts that the prolongation of the pandemic may create a new reality for individuals and communities (Balakrishnan et al., 2022; Özdin & Bayrak Özdin, 2020). Across the globe, industries and economies have struggled to survive (Ciravegna & Michailova, 2022). Worldwide, the demand for various products has dropped, and the economy is falling into a financial depression (Duffin, 2020). Recently, the International Monetary Fund (IMF) predicted. It has been argued that the expected upcoming economic depression resulting from COVID-19 will be bigger than the 1930s Great Depression and could lead countries to face different crises related to the domestic financial crisis, health shocks, cut off of external demands and the collapse in commodity prices (Pavlović et al., 2020; Perez, 2020). Hence, social, economic and career anxiety has been elevated in young men, resulting in enormous psychological and mental health problems (Pak et al., 2022; Yetgin & Benligiray, 2019).
Preuniversity and university education were among the most affected sectors of the COVID-19 pandemic. A sudden shift to online and distance learning has required a change in teaching methods, curriculum, assessment methods, technology and communication skills. As a result, university students were highly affected, as distance learning has heightened the anxiety of not having enough skills to practice certain careers, particularly in applied university specializations (El-Khodary et al., 2022; Vilca et al., 2022). Moreover, the global economic situation has placed university students’ plans for the career market in the near future at risk (Mahmud et al., 2021), which has elevated their worry and concern about the future.
Fear and anxiety of COVID-19, together with quarantine and isolation, have been postulated to generate certain psychological responses, such as emotional distress and maladaptive behaviors among individuals (Pedrosa et al., 2020; Fattah et al., 2021). In the context of the current COVID-19 prolongation, fear is thought to cause trauma that results in mass anxiety and depression. Fear is perceived as one of the primary emotions that are experienced by all ages, cultures, and species (Vilca et al., 2022) and is defined as an appraisal of danger. Fear also plays a vital role in increasing anxiety about the future (Rodriguez et al., 2020). This indicates that fatal epidemic diseases, such as COVID-19, can generate fear in individuals related to their physical and psychological health.
Anxiety, as defined by Barlow (2000), is an unpleasant feeling associated with a physiological reaction when fear is provoked and is a human emotion formed as a result of the perception of future threats. Considering COVID-19 prolongation, it has been observed that fear, panic, and anxiety have been exacerbated among individuals worldwide (Alimoradi et al., 2022; Bakioğlu et al., 2021). Fear and anxiety are elicited not only by the fear of the virus itself, but also by its effect on daily lives in the form of disruption, chaos and uncertainty (Botha & Mostert, 2013). Moreover, as mentioned earlier, global economic circumstances have become a major source of anxiety for the future workforce, particularly university students who are beginning their professional lives. The career development theory states that university students aged 23–25 years start forming their career expectations during their university years (Tsai et al., 2017).
Mann et al. (2020) measured the level of personal economic anxiety in a sample of almost 500 participants from the USA. The results indicated that 85% of participants were experiencing a high level of economic anxiety, whereas only 15% reported low or no economic anxiety (Duplaga & Grysztar, 2021). Financial analysts have also cautioned against the economic recession resulting from COVID-19 continuation, which may place an excessive psychological burden on adolescents as a future workforce (Ciravegna & Michailova, 2022).
Depression from COVID-19 has increased at a significantly higher level in the general population. Several studies (Duan & Zhu, 2020; Huang & Zhao, 2020) have already examined depression as an outcome of COVID-19. Depression is a psychological disorder that is marked by a general loss of interest, despair, self-depreciation and persistent feelings of sorrow (Holtzheimer & Mayberg, 2011). The connection between fear, anxiety, and depression was found by Izard (1977), who pointed out that fear is mostly associated with future emotions, anxiety predicts the threat of the future and depression is related to past or imminent events. Due to the recent global pandemic, fear among the future workforce comes as a result of speculating about their future career plan, which, in turn, triggers career-related anxiety. In addition, uncertainty about obtaining a job due to the downfall in the world economy has reduced individuals’ self-esteem, leading to depression among the future workforce (Pavlović et al., 2020).
Context of the Study
In Oman, the COVID-19 pandemic has imposed an enormous burden on health services, social and economic systems, and the educational system. According to the National Center for Statistics and Information (NCSI 2021), Oman has a population of 4.471.148. The number of confirmed cases in Oman until February 2021 was 139.692. Based on a geospatial modeling analysis, there was an influence of specific demographic and socioeconomic factors on COVID-19, including the percentage of Omani and expatriate populations at various age levels, population density, number of hospital beds, number of households, and purchasing power (Al Kindi et al., 2021). The knowledge, attitudes and practices of the Omani people toward COVID-19 symptoms, modes of transmission, and attitudes toward the disease were shown to be adequate in a sample of Omani individuals with a mean age of 38.27 (Al-Marshoudi et al., 2021). Badahdah et al. (2021) reported a high prevalence of stress, anxiety and poor psychological well-being among health care workers, particularly in females, young health professionals, and frontline care workers who interacted directly with COVID-19 patients. Following the outbreak of COVID-19, misinformation has spread through multiple channels and social media platforms, causing considerable effects and perceptions of the acceptance of COVID-19 social and medical precautionary measures, including vaccines, lockdown, and social distancing. The misinformation caused elevated levels of stress among Omani university students (Malik & Javed, 2021).
As elsewhere in the world, COVID-19 has disrupted education in schools and higher education institutions. Given that teaching and learning are based on direct interaction, preuniversity and university education were negatively affected by the lockdown measures taken by the government as a response to the pandemic. Al-Balushi et al., (2022) used thematic analysis and critical reflection to examine interview data and official documents issued by higher education institutions following the outbreak of COVID-19. Three modes of responses (risky, emergency, and inducing long-term changes) and four challenges (appropriate mode of delivery, teacher and student readiness, learning management system, and alternative assessment methods) characterized different higher education institutions in Oman during the pandemic. Furthermore, teachers and students grappled with the paradigm shift to the use of new technologies, which resulted in emotional and psychological disturbance, particularly as several students did not secure a suitable space in their homes for effective learning and due to the unavailability of internet access in some regions in Oman (Malik & Javed, 2021). These challenges and the abrupt changes represented a trauma to university students, which induced mental health problems, including academic stress and the fear of delay in completing the study program, particularly with expectations of COVID-19 prolongation. Previous research has shown that uncertainty during crisis times has a negative impact on the mental health and well-being of university students (Bai et al., 2022; Cleveland et al., 2022). The impact of COVID-19 on the psychological well-being of Omani university students was aggravated by public emergencies following home confinement and a shift to online learning. Only one study examined the psychological stress of university students in Oman following the outbreak of COVID-19 (Malik & Javed, 2021). While there is prolific literature on the psychological outcomes of COVID-19 among university students in Western countries, little has been published on the Arab region (Yildrim et al., 2022).
In addition, the study examines whether the relationship between fear of COVID-19 prolongation and FCA is influenced by the mediational effect of depression from COVID-19 prolongation. The current study seeks to explore whether fear of COVID-19 prolongation and depression from COVID-19 prolongation have a direct effect on university students’ FCA. The theoretical framework and proposed model is based on the aforementioned documented research on the psychological outcomes of COVID-19 on the mental health well-being of individuals and. The framework shown in Fig. 1 has been proposed and tested:
Fig. 1 Proposed mediation model describing the relationship of fear of COVID-19, depressive symptoms, and future career anxiety in Omani university students
This framework is supported by different theories of emotion. Emotions imply a complex state of feeling that triggers physical and psychological manifestations in behavior and thinking schemas, positively or negatively (Barlow, 2000; Emam et al., 2019). The behavioral outcome of humans as a result of a different form of emotions has been described by different researchers through different theories. James-Lang’s theory and Lazarus’s theory of emotions support the theoretical model tested in the current study. James-Lang theory postulates that physiological responses to any event influence the emotional response of a person. This indicates that there is an event that impacts a person’s physiology, which is then followed by an emotional response (Emam et al., 2019; Pedrosa et al., 2020). Moreover, Lazarus’s theory of emotion states that there shall be an event that is first labeled by a person through personal experiences that instantaneously form emotional and physiological responses. Thus, all forms of emotions, such as fear, anger, and anxiety, can be linked with these prominent theories of emotions (Pedrosa et al., 2020).
To further examine the relationship between fear of COVID-19 prolongation and FCA, the current study explores a possible mediational effect of depressive symptoms on this relationship. Furthermore, such a relationship has been documented in different age groups, including adolescents and adults, with anxiety being strongly related to depressive symptoms, as well as demotivation in academic success due to blurry professional behavior (El-Khodary et al., 2022; Malik & Javed, 2021; Pak et al., 2022; Şimşir et al., 2022). Research on adolescents’ mental health has made a compelling argument that depressive symptoms may result from an interaction between negative cognitions and negative life events (Bai et al., 2022; Cleveland et al., 2022). Such interplay affects adolescents’ ability to manage personal and future goals. Emam et al. (2019) reported that negative life events, as indicated by the view of the self, the view of the world, and the view of the future, conferred vulnerability to depressive symptoms among Omani adolescents. Certainly, the view of the world and view of the future are related to adolescents’ display of depressive symptoms. Nonetheless, more research is needed to fully understand the pattern of relationships that exist between specific situations, such as that of the COVID-19 pandemic, and other related variables as university students plan to transition to postuniversity life. This is particularly essential given the significance of university students’ mental health and wellbeing for long-term trajectories of success and failure by individuals in society.
In summary, the current study extends the theories of emotions by assuming that COVID-19 prolongation has elevated the fear of university students who represent the future workforce; fear is assumed to directly influence career-related anxiety; and depressive symptoms associated with COVID-19 prolongation are assumed to play a mediational role in increasing students’ FCA. The following set of hypotheses were postulated and tested:
H1: There is a significant relationship between fear of COVID-19 prolongation and FCA.
H2: There is a significant relationship between COVID-19 prolongation-related depressive symptoms and FCA.
H3: COVID-19 prolongation-related depressive symptoms act as a mediator in the relationship between fear of COVID-19 prolongation and FCA.
Method
Participants. The study was approved by the institutional internal review board (IIRB). Convenience sampling was used during the data collection phase. Data were collected from March 27 to April 21, 2021. An online survey including the data instruments was sent out via email and social media to university students in different higher education institutions in the Sultanate of Oman. The invitation to participate in the study included information on the study aim and a consent form. Participants were told that the data would be kept private and that their personal information would remain confidential.
After four weeks of data collection, 605 indigenous Omani students from University Colleges completed the survey. Participants included 265 (43.8%) males and 340 (56.2%) females. The majority [512 (84.6%)] of the participants had not been infected with COVID-19, whereas 33 (5.5%) were suffering from chronic illness, 416 (68.8%) were having family members infected with COVID-19, 89 (14.7%) lost family members due to COVID-19, and 330 (54.5%) believed that COVID-19 would continue. Table 1 summarizes the participants’ responses to the demographic section of the online survey.
Table 1 characteristics of study participants
Variable N(%) Variable N(%)
Gender Do you have chronic illness?
Male 265(43.8) Yes 33(5.5)
Female 340(56.2) No 572(94.5)
Study Year Family member diagnosed with COVID-19?
1st 138(22.8) Yes 416(68.8)
2nd 86(14.2) No 189(31.2)
3rd 94(15.5) Family member lost as a result of COVID-19?
4th 112(18.5) Yes 89(14.7)
< 4 175(28.9) No 516(85.3)
Have you been infected with COVID-19 before? You think COVID-19 will ….?
Yes 93(15.4) Continue 330(54.5)
No 512(84.6) Will come to an end soon? 275(45.5)
Instruments
An online survey was used to collect data. The survey included two sections: (1) single indicator variables that required information on the participant’s socioeconomic demographics, including gender, exposure to COVID-19 infection, family members’ infection with COVID-19, decease of a family member due to COVID-19 infection, personal belief about the expected continuity of COVID-19 pandemic, and suffering from a chronic disease of long-lasting health illness; (2) multiple indicator variables that included three scales, namely, fear of COVID-19, depression from COVID-19, and FCA. The scales were translated from English to Arabic using the team translation method (Harkness et al., 2004). This method involves conducting a forward translation holding a consensus meeting followed by a final reconciliation meeting. A group of four, including two of the authors, translated the scales from English to Arabic. Next, the group members discussed the parallel translations for each item and agreed on the adequate translation. Finally, the group members met with an adjudicator, a faculty member from the psychology department who has good command in English and Arabic, to reconcile any disagreements among the translators in case there were any. The three scales are described below.
Fear of COVID-19 Scale
It is a seven-item self-report scale that asks participants to rate their level of agreement on a five-point Likert scale where a total score ranges from 7 to 35, and a higher score indicates greater fear of COVID-19 (Mahmud et al., 2021; Alimoradi et al., 2022; Bakioğlu et al., 2021). The items were adapted to reflect fear of COVID-19 prolongation (e.g., my hands become sweaty when I think about COVID-19 prolongation). For the current study data, the scale has acceptable reliability (Cronbach’s α = 0.85), and the corrected item-total correlation ranged from 0.48 to 0.67. Confirmatory factor analysis (CFA) was used to assess scale construct validity; the indices showed a unidimensional model with a good fit to the participants’ responses (GFI = 0.99, CFI = 0.99, RMSEA = 0.05).
Depression from COVID-19 Scale
Depression symptoms cause persistent feelings of frustration, loss of interest, and sadness. The scale was developed by Mahmud et al. (2021) and consists of 6 positive items that are answered on a four-point response format with a total score ranging from 6 to 24 (e.g., I felt that life is meaningless due to the fear of COVID-19 prolongation). Although Mahmud and his colleagues claimed that the scale assesses depression, it is believed that the scale evaluates depressive symptoms rather than depression as a disorder. The scale has acceptable reliability (Cronbach’s α = 0.82), and the corrected item-total correlation ranged from 0.50 to 0.64. Confirmatory factor analysis (CFA) was used to assess scale construct validity; the indices showed that a unidimensional model is a good fit for the sample’s responses (GFI = 0.97, CFI = 0.95, RMSEA = 0.012).
Future Career Anxiety Scale
Tsai et al. (2017) developed a 25-item scale comprising four dimensions (personal ability, irrational beliefs about employment, employment environment, and professional education training). The present study utilized the dimension of employment environment to measure university students’ FCA given the forecasts of expected continuation of the pandemic (e.g., I worry about future employment because of the increasing unemployment and job cut reported by the mass media for the reason of COVID-19 prolongation). The scale has acceptable reliability (Cronbach’s α = 0.92), and the corrected item-total correlation ranged from 0.75 to 0.84. A confirmatory factor analysis (CFA) was used to assess scale construct validity, and the scale model data fit indices were excellent (GFI = 0.99, CFI = 1.00, RMSEA = 0.01).
Data Analysis
Data were exported to SPSS version 25 for analysis. Descriptive analyses were used to determine the frequencies, means, and standard deviations to describe sample demographics. Structural equation modeling (SEM) was conducted by AMOS version 20 to determine the direct effects of fear of COVID-19 and depression from COVID-19 on FCA and the indirect effect of depression from COVID-19 on FCA. Following Hu and Bentler (1999), the model fit indices were evaluated using RMSEA, CFI, and GFI. The acceptable values for RMSEA are equal to or less than.08, and those for CFI and GFI are equal to or greater than.90. The bootstrap procedure using the maximum likelihood estimates was used to examine each specific indirect effect (Preacher & Hayes 2008).
Results
Multiple Indicator Variables
As shown in Table 2, univariate analyses revealed that no gender differences were observed in the fear of COVID-19, depression from COVID-19, and FCA (F = 0.024, p = 0.877; F = 2.89, P = 0.09; F = 1.3, P = 0.255), no differences were observed between university students in various study years (F = 0.241, P = 0.944, F = 1.02, P = 0.405, F = 1.98, P = 0.079), and similarly, no differences were found as a result of the interaction between gender and the program study year (F = 1.27, p = 0.274; F = 0.548, P = 0.74; F = 1.26 P = 0.278). Independent sample t tests were performed to assess the existence of significant mean differences in the single indicator variables outlined in Table 1. The results indicated that there were mean differences in the fear of COVID-19 due to the diagnosis of a family member with COVID-19, participants who lost one of their family members due to COVID-19, and participants’ beliefs about COVID-19 prolongation. Additionally, participants who lost one of their family members due to COVID-19 showed higher depressive symptoms. Participants who believed that the COVID-19 pandemic would continue for a long time showed higher fear of COVID-19, higher depressive symptoms, and higher FCA.
Table 2 Univariate analysis of fear of COVID-19, depression from COVID-19, future career anxiety (FCA)
Variable Category N fear
M(SD) P depression M(SD) P FCA
M(SD) P
Gender Male 265 7.69(4.63) 0.877 4.18(3.78) 0.09 8.83(4.07) 0.255
Female 340 7.85(3.99) 4.67(3.79) 9.04(4.11)
Study Year pre 42 8.14(4.99) 0.944 3.93(3.51) 0.405 9.12(4.04) 0.079
1st 96 7.80(4.12) 4.36(3.94) 8.82(4.00)
2nd 86 8.09(4.30) 4.63(4.06) 7.93(4.12)
3rd 94 7.85(4.12) 4.64(3.58) 9.20(4.32)
4th 112 7.84(4.42) 5.02(4.01) 9.56(4.52)
< 4 175 7.46(4.21) 4.09(3.59) 8.95(4.09)
Have you been infected with the COVID-19 before? Yes 93 7.53(4.35) 0.533 3.84(3.67) 0.089 9.08(3.84) 0.749
No 512 7.83(4.27) 4.57(3.80) 8.93(4.14)
Do you have chronic illness? No 572 7.76(4.23) 0.526 4.48(3.89) 0.571 8.94(4.11) 0.739
Yes 33 8.24(5.020) 4.09(3.87) 9.18(3.90)
Family member diagnosed with COVID-19? No 189 7.16(3.99) 0.016 4.51(3.74) 0.816 9.11(4.13) 0.530
Yes 416 8.06(4.38) 4.43(3.82) 8.88(4.08)
Family member died by COVID-19? No 516 7.54(4.12) 0.003 4.33(3.71) 0.047 9.07(3.99) 0.095
Yes 89 9.20(4.92) 5.19(4.15) 8.28(4.58)
You think the COVID-19 Will end soon 275 7.22(4.02) 0.003 4.06(3.61) 0.019 8.15(4.20) < 0.001
Continue 330 8.25(4.44) 4.78(3.91) 9.62(3.89)
Table 3 Correlation matrix
Variable Fear of corona Depression of corona Future career anxiety
Fear of COVID-19 1
Depression from COVID-19 0.58 1
Future career anxiety 0.32 0.43 1
Note: Correlations is significant at the 0.01 level
The Structural Model
The Pearson correlation coefficient showed a significant positive association between fear of COVID-19, depression from COVID-19, and FCA. Table 3 provides the correlation matrix between the three variables. The standardized regression weights for scale items were statistically significant and ranged from 0.54 to 0.76 for fear of COVID-19 items, from 0.55 to 0.80 for depression from COVID-19 items, and from 0.71 to 0.90 for FCA items. All item loadings were above the minimum criterion of 0.5, whereas some of them were above the ideal criterion of 0.7 (Hair et al., 2019; Malhotra& dash, 2016). For the structural model, the model fit indices were acceptable (CMIN/DF = 3.38, GFI = 0.92, CFI = 0.95, IFI = 0.95, RMSEA = 0.06). The results of the structural model are shown in Fig. 2. There were significant standardized direct effects (unmediated) of fear of COVID-19 on depression from COVID-19 (0.77) and of depression from COVID-19 on FCA (0.41). Additionally, depression from COVID-19 mediated the relationship between fear of COVID-19 and FCA (0.32) (see Fig. 2).
Fig. 2 Results of the structural equation modelling (SEM) analysis of the mediation of fear of COVID-19, depressive symptoms, and future career anxiety in Omani university students (n = 605), *** = p < 0.001
Discussion
The primary purpose of the current investigation was to examine the relationships between university students’ fear of COVID-19, depression and their FCA. Overall, it is clear that the participants showed high levels of fear, depression and FCA. This shows that major psychological health problems exist among university students due to COVID-19 prolongation, which is consistent with the moderate to severe symptoms of fear, depression, and anxiety observed in previous research following the onset of the pandemic (Alimoradi et al., 2022; Balakrishnan et al., 2022; Luo et al., 2021). There were no gender differences in the fear of COVID-19, depression, or FCA among the participants. This finding is inconsistent with previous research studies on gender differences in fear of COVID-19 (Rodriguez et al., 2020; Bakioğlu et al., 2021). The finding could be interpreted from a contextual perspective, as both male and female students were equally worried about the possible continuation of COVID-19 and how this could affect their study programs (Malik & Javed, 2021), as well as employability after graduation (Cifuentes-Faura et al., 2021). It is suggested that the academic demands of university programs and the uncertain outlook due to possible COVID-19 prolongation has taken its toll on learning and evaluation processes, leading to emotions of fear and depression in both female and male students (Rodriguez et al., 2020).
The results of the current investigation suggest that there are significant relationships between fear of COVID-19, depression, and FCA. As hypothesized, fear of COVID-19 among Omani University students’ was significantly and positively related to COVID-19 prolongation-related depressive symptoms. This finding is congruent with previous research evidence suggesting that adolescents’ fear of COVID-19 and depressive symptoms are strongly associated (Alimoradi et al., 2022; Bakioğlu et al., 2021; Mahmud et al., 2021). Interestingly, several previous studies have shown that depressive symptoms are correlated with several negative episodes and consequences in adolescents (Mahmud et al., 2021; Taylor, 2019). In particular, this relationship was confirmed for female students more than for male students (García-Fernández et al., 2021; Hou et al., 2020). In examining Greek university students’ wellbeing and mental health variables during the COVID-19 pandemic, Kaparounaki et al. (2020) reported that there was a dramatic increase in clinical cases of depression. Additionally, there was a horizontal increase in scores on anxiety, sleep quality and quantity, and other mental health issues (Vilca et al., 2022). Thus, it may be that depressive symptoms and fear of COVID-19 were two primary issues that affected university students’ wellbeing following the pandemic outbreak and prolongation. In a meta-analysis of 20 studies (Şimşir et al., 2022), the results showed a moderate mean weighted between fear of COVID-19 and depression. This finding is consistent with the view that different fears can be associated with depression (Barlow, 2000; Emam et al., 2019). Additionally, the results from 23 studies showed a strong mean weighted between fear of COVID-19 and anxiety. The fear of COVID-19 reflects the psychological nature of a phobia that is classified as a type of anxiety disorder (American Psychiatric Association, 2013).
The second main aim of our investigation was to explore the influence of fear of COVID-19 prolongation and depression on FCA. We designed a theoretical model based on a review of previous research and contrasted it with the collected data. The results obtained in the structural equations showed an excellent fit to the model. In line with our hypotheses, Omani university students’ FCA was significantly related to their depressive symptoms (García-Fernández et al., 2021). It may be that both males and females were thinking deeply about the consequences of COVID-19 prolongation on their future career and employability (Cifuentes-Faura et al., 2021). They may have thought of the economic impact of the pandemic on the country’s public and private institutions. In addition, adolescents’ belief in conspiracy theory as a possible cause of the pandemic, which was documented in previous research (Miller, 2020), may have resulted in mistrust in any scientific reports on the future trajectory of the pandemic. This finding is consistent with previous research suggesting that depression and future anxiety, whether general or specific (e.g., career), tend to co-occur due to the individual’s negative view of self, the world, and the future (Botha & Mostert, 2013; Emam et al., 2019; Pak et al., 2022). In particular, there is research evidence that negative cognitions operate on the aforementioned three aspects for Omani adolescents, which affects their perception of the future (Barlow, 2000; Emam et al., 2019; Izard 1977; Pedrosa et al., 2020).
Thus, our hypotheses were corroborated. As hypothesized, fear of COVID-19 had a direct unmediated effect on depression from COVID-19, and the latter had a direct impact on students’ FCA. Mediational analyses aimed to test our hypothesis that depression from COVID-19 would explain the relationship between fear of COVID-19 prolongation and university students’ FCA. Previous research suggests that depressive symptoms are important in predicting general and specific future anxieties (Bakioğlu et al., 2021; Duplaga & Grysztar, 2021). Consistent with our hypothesis, the participants’ depression from COVID-19 prolongation mediated the relationship between fear of COVID-19 prolongation and FCA. This finding implied that students’ FCA was related indirectly to their fear of COVID-19 prolongation and that students’ depressive syndromes contributed to determining and interpreting this relationship. Thus, the connection between students’ fear of COVID-19 prolongation and their FCA may be explained by depression from COVID-19. This model of relationships received due attention from universities when they planned to provide psychological services during crisis time to support students in avoiding traumatic experiences. Students may benefit from counseling services that prioritize addressing their depressive symptoms, independent of the level of fear of COVID-19 prolongation. The relationship of fear of COVID-19 prolongation with FCA mediated by depression from COVID-19 has not been described before, making this a novel contribution. The conditions in which university students in Oman have to cope with the continuation of the pandemic are extremely adverse in many ways. The emergence of several variants, the large number of people affected, the growing number of deaths, mistrust of the health system, a lack of awareness, and disinformation may have all contributed significantly to the fact that young university students experience fear of COVID-19 prolongation. University students tend to feel more fear when they perceive themselves in a more vulnerable situation and in greater danger. Families often place high expectations on future careers and employment of adolescents. In Oman, study programs in public universities are closely connected with job market needs (Al-Balushi et al., 2022). Therefore, it is reasonable that university students become anxious about their future career and employability as a result of COVID-19 prolongation.
Limitations
The current study is not without limitations. First, the participants were from the top higher education institutions in Oman. Therefore, it could be argued that they hold higher expectations of their future career compared to other students in other universities and colleges. This could diminish the generalizability of the study findings to the larger population of university students in Oman. Second, the findings are based on the use of self-report measures that involve the threat of social desirability. Participants may have exaggerated or underrated their feelings to deliver a message that may not be true of themselves. Therefore, the study results should be interpreted with this assumption in mind. Third, depressive symptoms were tested as a mediator in the model, although other possible variables could have been included, such as stress, religious coping, and resilience. Nonetheless, previous literature was relied upon to build our model. Furthermore, the use of depressive symptoms versus depression was meant to avoid the overlap between depression as a psychological disorder that has diagnostic criteria in the DSM-5 (American Psychiatric Association, 2013). Finally, these findings should be interpreted within the limitations of the cross-sectional methodology that was employed, which does not confirm a causal relationship. Longitudinal data could not be collected, as there was no clear vision of the trajectory of the pandemic.
Implications and Conclusion
Despite the stated limitations, the current study contributed to understanding university students’ FCA during crisis times. University students or adolescents in general represent an interesting population, and therefore, their mental health and wellbeing are of paramount importance to their families and to society. Based on these findings, the uncertainty and the peril perceived by adolescents could turn into a fertile breeding ground for fear, depression and FCA (Pak et al., 2022). Therefore, there is an urgent need to design intervention plans in universities to help these young people better cope with this type of situation and avoid future trauma. University students’ exposure to stressful conditions and crisis’ have increased in modern times, such as with the COVID-19 pandemic. This has resulted in psychological problems and issues with mental health. Consequently, university students who are in aunique developmental period of adolescence should receive adequate psychological services that can be provided within, as well as outside, the university. Based on our structural model, different measures to prevent and alleviate this may be suggested. To reduce fear of COVID-19, it would be advisable to run convincing information campaigns about the disease, with training provided for its prevention and for effective coping strategies.
Although the results of the current investigation were in line with the hypotheses made prior to data collection, further investigation may entail other possible variables that could have a direct or indirect impact on students’ FCA during times of crisis. Examples of these variables may include religiousness, religious coping, family support, and support received from significant others. Given that the number of university students seeking psychological counseling has been on the rise globally, further knowledge should be gained on the characteristics of adolescents, their interplay with the environment, and the trajectories they may take during times of crisis and traumatic events. Health services professionals in clinical and nonclinical settings should be able to address adolescents’ psychological needs in normal, as well as difficult times. Adolescents’ resilience and ability to adapt during difficult times should be examined empirically and targeted by professionals. Culture-specific enablers and obstacles should be explored to present new information on the potential mediators and moderators of the relationship between adolescents’ mental health and the different environments with which adolescents interrelate at various times.
Electronic Supplementary Material
Below is the link to the electronic supplementary material.
Supplementary Material 1
Declarations
Conflict of Interest
The authors claim no conflict of interest. The authors claim responsibility of writing the manuscript following the ethical procedures. The manuscript has not been published or submitted elsewhere and has received no funding.
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| 0 | PMC9734943 | NO-CC CODE | 2022-12-14 23:28:31 | no | J Child Adolesc Trauma. 2022 Dec 7;:1-10 | utf-8 | J Child Adolesc Trauma | 2,022 | 10.1007/s40653-022-00506-w | oa_other |
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J Child Adolesc Trauma
J Child Adolesc Trauma
Journal of Child & Adolescent Trauma
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Springer International Publishing Cham
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10.1007/s40653-022-00506-w
Original Article
Does Fear of COVID-19 Prolongation Lead to Future Career Anxiety Among Adolescents? The Mediating Role of Depressive Symptoms
Shindi Yousef Abu [email protected]
1
http://orcid.org/0000-0003-4451-9237
Emam Mahmoud Mohamed [email protected]
1
Farhadi Hadi [email protected]
2
1 grid.412846.d 0000 0001 0726 9430 Department of Psychology, College of Education, Sultan Qaboos University, P.O. Box: 32 Al-Khod, P.C.: 123, Seeb, Oman
2 grid.411757.1 0000 0004 1755 5416 Department of Psychology, Faculty of Educational Sciences & Psychology, Islamic Azad University, Isfahan, Khorasgan Iran
7 12 2022
110
29 11 2022
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The outbreak of the COVID-19 pandemic has influenced the lives of individuals from all different age groups. In particular, the prolongation of COVID-19 and the emergence of virus variants, such as Omicron, Delta and Alpha, have caused trauma to university students amid expectations that the associated economic, social, and psychological outcomes could affect their future careers. The current study, therefore, examines how the fear of COVID-19 prolongation may affect future career anxiety (FCA) among adolescents and to what extent depressive symptoms may determine such a relationship. Using a cross-sectional design, a survey was conducted to assess depressive symptoms, FCA, and fear of COVID-19 prolongation among 605 university students in Oman, an Arabic-speaking country located in the Gulf region. Using structural equation modeling, the results showed that there were significant standardized direct effects (unmediated) of fear of COVID-19 on depression from COVID-19 and of depression from COVID-19 on FCA. Additionally, depression from COVID-19 mediated the relationship between fear of COVID-19 and FCA. The results are discussed within the Omani context of mental health service accessibility challenges and the dominant culture of perceiving mental health services with social stigma.
Supplementary Information
The online version contains supplementary material available at 10.1007/s40653-022-00506-w.
Keywords
COVID-19 variants
Career Anxiety
Fear
Depressive Symptoms
Adolescents
Oman
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pmcIntroduction
Three years have passed since the first confirmed case of coronavirus disease 2019 (COVID-19) in Hong Kong was announced. In 2020, the World Health Organization (WHO) officially declared COVID-19 a global pandemic and labeled the coronavirus a sixth public health emergency of international concern in modern history (Şimşir et al., 2022; Vilca et al., 2022). Several researchers have highlighted the broad range of psychosocial consequences that could be inflicted by the COVID-19 pandemic on the general population (Badahdah et al., 2021; Hasani et al., 2020; Yıldırım et al., 2022) amidst speculations over its continuation for some years to come. Adolescents, in particular, have been more traumatized due to the prolongation of COVID-19 and the emergence of several COVID-19 variants (Bai et al., 2022; Cleveland et al., 2022; Şimşir et al., 2022; Yıldırım et al., 2022). With thousands of people being impacted by the incapacitating effects of COVID-19, certain groups, such as university students, appear to be more vulnerable and at increased risk of psychological problems (Mahmud et al., 2021; Pak et al., 2022). Limited research has examined the impact of COVID-19 prolongation on the mental health of university students in different contexts (El-Khodary et al., 2022; Malik & Javed, 2021).
There is evidence that pandemics create not only socioeconomic crises, but also psychological crises, such as fear, panic, anxiety, insomnia, depression, anger and boredom (Balakrishnan et al., 2022; Özdin & Bayrak Özdin, 2020). Psychological distress arises mainly from individuals’ ideas, which are shaped the media and news about the pandemic. The information, and, at times, misinformation, individuals receive results in fear, depression and anxiety about what may occur in the future (Alimoradi et al., 2022). Moreover, preventive policies implemented by governments to curb the COVID-19 pandemic, such as home confinement, physical distancing, and nationwide lockdowns, have also increased anxiety and fear among individuals and communities (Alimoradi et al., 2022; Bakioğlu et al., 2021). Additionally, published medical and scientific literature, as well as public reports in all types of media, have increased panic, fear, and stigmatization (Pak et al., 2022; Luo et al., 2021).
Psychological Outcomes of COVID-19
Anxiety and depression related to news of the global economy have become a major concern, particularly with forecasts that the prolongation of the pandemic may create a new reality for individuals and communities (Balakrishnan et al., 2022; Özdin & Bayrak Özdin, 2020). Across the globe, industries and economies have struggled to survive (Ciravegna & Michailova, 2022). Worldwide, the demand for various products has dropped, and the economy is falling into a financial depression (Duffin, 2020). Recently, the International Monetary Fund (IMF) predicted. It has been argued that the expected upcoming economic depression resulting from COVID-19 will be bigger than the 1930s Great Depression and could lead countries to face different crises related to the domestic financial crisis, health shocks, cut off of external demands and the collapse in commodity prices (Pavlović et al., 2020; Perez, 2020). Hence, social, economic and career anxiety has been elevated in young men, resulting in enormous psychological and mental health problems (Pak et al., 2022; Yetgin & Benligiray, 2019).
Preuniversity and university education were among the most affected sectors of the COVID-19 pandemic. A sudden shift to online and distance learning has required a change in teaching methods, curriculum, assessment methods, technology and communication skills. As a result, university students were highly affected, as distance learning has heightened the anxiety of not having enough skills to practice certain careers, particularly in applied university specializations (El-Khodary et al., 2022; Vilca et al., 2022). Moreover, the global economic situation has placed university students’ plans for the career market in the near future at risk (Mahmud et al., 2021), which has elevated their worry and concern about the future.
Fear and anxiety of COVID-19, together with quarantine and isolation, have been postulated to generate certain psychological responses, such as emotional distress and maladaptive behaviors among individuals (Pedrosa et al., 2020; Fattah et al., 2021). In the context of the current COVID-19 prolongation, fear is thought to cause trauma that results in mass anxiety and depression. Fear is perceived as one of the primary emotions that are experienced by all ages, cultures, and species (Vilca et al., 2022) and is defined as an appraisal of danger. Fear also plays a vital role in increasing anxiety about the future (Rodriguez et al., 2020). This indicates that fatal epidemic diseases, such as COVID-19, can generate fear in individuals related to their physical and psychological health.
Anxiety, as defined by Barlow (2000), is an unpleasant feeling associated with a physiological reaction when fear is provoked and is a human emotion formed as a result of the perception of future threats. Considering COVID-19 prolongation, it has been observed that fear, panic, and anxiety have been exacerbated among individuals worldwide (Alimoradi et al., 2022; Bakioğlu et al., 2021). Fear and anxiety are elicited not only by the fear of the virus itself, but also by its effect on daily lives in the form of disruption, chaos and uncertainty (Botha & Mostert, 2013). Moreover, as mentioned earlier, global economic circumstances have become a major source of anxiety for the future workforce, particularly university students who are beginning their professional lives. The career development theory states that university students aged 23–25 years start forming their career expectations during their university years (Tsai et al., 2017).
Mann et al. (2020) measured the level of personal economic anxiety in a sample of almost 500 participants from the USA. The results indicated that 85% of participants were experiencing a high level of economic anxiety, whereas only 15% reported low or no economic anxiety (Duplaga & Grysztar, 2021). Financial analysts have also cautioned against the economic recession resulting from COVID-19 continuation, which may place an excessive psychological burden on adolescents as a future workforce (Ciravegna & Michailova, 2022).
Depression from COVID-19 has increased at a significantly higher level in the general population. Several studies (Duan & Zhu, 2020; Huang & Zhao, 2020) have already examined depression as an outcome of COVID-19. Depression is a psychological disorder that is marked by a general loss of interest, despair, self-depreciation and persistent feelings of sorrow (Holtzheimer & Mayberg, 2011). The connection between fear, anxiety, and depression was found by Izard (1977), who pointed out that fear is mostly associated with future emotions, anxiety predicts the threat of the future and depression is related to past or imminent events. Due to the recent global pandemic, fear among the future workforce comes as a result of speculating about their future career plan, which, in turn, triggers career-related anxiety. In addition, uncertainty about obtaining a job due to the downfall in the world economy has reduced individuals’ self-esteem, leading to depression among the future workforce (Pavlović et al., 2020).
Context of the Study
In Oman, the COVID-19 pandemic has imposed an enormous burden on health services, social and economic systems, and the educational system. According to the National Center for Statistics and Information (NCSI 2021), Oman has a population of 4.471.148. The number of confirmed cases in Oman until February 2021 was 139.692. Based on a geospatial modeling analysis, there was an influence of specific demographic and socioeconomic factors on COVID-19, including the percentage of Omani and expatriate populations at various age levels, population density, number of hospital beds, number of households, and purchasing power (Al Kindi et al., 2021). The knowledge, attitudes and practices of the Omani people toward COVID-19 symptoms, modes of transmission, and attitudes toward the disease were shown to be adequate in a sample of Omani individuals with a mean age of 38.27 (Al-Marshoudi et al., 2021). Badahdah et al. (2021) reported a high prevalence of stress, anxiety and poor psychological well-being among health care workers, particularly in females, young health professionals, and frontline care workers who interacted directly with COVID-19 patients. Following the outbreak of COVID-19, misinformation has spread through multiple channels and social media platforms, causing considerable effects and perceptions of the acceptance of COVID-19 social and medical precautionary measures, including vaccines, lockdown, and social distancing. The misinformation caused elevated levels of stress among Omani university students (Malik & Javed, 2021).
As elsewhere in the world, COVID-19 has disrupted education in schools and higher education institutions. Given that teaching and learning are based on direct interaction, preuniversity and university education were negatively affected by the lockdown measures taken by the government as a response to the pandemic. Al-Balushi et al., (2022) used thematic analysis and critical reflection to examine interview data and official documents issued by higher education institutions following the outbreak of COVID-19. Three modes of responses (risky, emergency, and inducing long-term changes) and four challenges (appropriate mode of delivery, teacher and student readiness, learning management system, and alternative assessment methods) characterized different higher education institutions in Oman during the pandemic. Furthermore, teachers and students grappled with the paradigm shift to the use of new technologies, which resulted in emotional and psychological disturbance, particularly as several students did not secure a suitable space in their homes for effective learning and due to the unavailability of internet access in some regions in Oman (Malik & Javed, 2021). These challenges and the abrupt changes represented a trauma to university students, which induced mental health problems, including academic stress and the fear of delay in completing the study program, particularly with expectations of COVID-19 prolongation. Previous research has shown that uncertainty during crisis times has a negative impact on the mental health and well-being of university students (Bai et al., 2022; Cleveland et al., 2022). The impact of COVID-19 on the psychological well-being of Omani university students was aggravated by public emergencies following home confinement and a shift to online learning. Only one study examined the psychological stress of university students in Oman following the outbreak of COVID-19 (Malik & Javed, 2021). While there is prolific literature on the psychological outcomes of COVID-19 among university students in Western countries, little has been published on the Arab region (Yildrim et al., 2022).
In addition, the study examines whether the relationship between fear of COVID-19 prolongation and FCA is influenced by the mediational effect of depression from COVID-19 prolongation. The current study seeks to explore whether fear of COVID-19 prolongation and depression from COVID-19 prolongation have a direct effect on university students’ FCA. The theoretical framework and proposed model is based on the aforementioned documented research on the psychological outcomes of COVID-19 on the mental health well-being of individuals and. The framework shown in Fig. 1 has been proposed and tested:
Fig. 1 Proposed mediation model describing the relationship of fear of COVID-19, depressive symptoms, and future career anxiety in Omani university students
This framework is supported by different theories of emotion. Emotions imply a complex state of feeling that triggers physical and psychological manifestations in behavior and thinking schemas, positively or negatively (Barlow, 2000; Emam et al., 2019). The behavioral outcome of humans as a result of a different form of emotions has been described by different researchers through different theories. James-Lang’s theory and Lazarus’s theory of emotions support the theoretical model tested in the current study. James-Lang theory postulates that physiological responses to any event influence the emotional response of a person. This indicates that there is an event that impacts a person’s physiology, which is then followed by an emotional response (Emam et al., 2019; Pedrosa et al., 2020). Moreover, Lazarus’s theory of emotion states that there shall be an event that is first labeled by a person through personal experiences that instantaneously form emotional and physiological responses. Thus, all forms of emotions, such as fear, anger, and anxiety, can be linked with these prominent theories of emotions (Pedrosa et al., 2020).
To further examine the relationship between fear of COVID-19 prolongation and FCA, the current study explores a possible mediational effect of depressive symptoms on this relationship. Furthermore, such a relationship has been documented in different age groups, including adolescents and adults, with anxiety being strongly related to depressive symptoms, as well as demotivation in academic success due to blurry professional behavior (El-Khodary et al., 2022; Malik & Javed, 2021; Pak et al., 2022; Şimşir et al., 2022). Research on adolescents’ mental health has made a compelling argument that depressive symptoms may result from an interaction between negative cognitions and negative life events (Bai et al., 2022; Cleveland et al., 2022). Such interplay affects adolescents’ ability to manage personal and future goals. Emam et al. (2019) reported that negative life events, as indicated by the view of the self, the view of the world, and the view of the future, conferred vulnerability to depressive symptoms among Omani adolescents. Certainly, the view of the world and view of the future are related to adolescents’ display of depressive symptoms. Nonetheless, more research is needed to fully understand the pattern of relationships that exist between specific situations, such as that of the COVID-19 pandemic, and other related variables as university students plan to transition to postuniversity life. This is particularly essential given the significance of university students’ mental health and wellbeing for long-term trajectories of success and failure by individuals in society.
In summary, the current study extends the theories of emotions by assuming that COVID-19 prolongation has elevated the fear of university students who represent the future workforce; fear is assumed to directly influence career-related anxiety; and depressive symptoms associated with COVID-19 prolongation are assumed to play a mediational role in increasing students’ FCA. The following set of hypotheses were postulated and tested:
H1: There is a significant relationship between fear of COVID-19 prolongation and FCA.
H2: There is a significant relationship between COVID-19 prolongation-related depressive symptoms and FCA.
H3: COVID-19 prolongation-related depressive symptoms act as a mediator in the relationship between fear of COVID-19 prolongation and FCA.
Method
Participants. The study was approved by the institutional internal review board (IIRB). Convenience sampling was used during the data collection phase. Data were collected from March 27 to April 21, 2021. An online survey including the data instruments was sent out via email and social media to university students in different higher education institutions in the Sultanate of Oman. The invitation to participate in the study included information on the study aim and a consent form. Participants were told that the data would be kept private and that their personal information would remain confidential.
After four weeks of data collection, 605 indigenous Omani students from University Colleges completed the survey. Participants included 265 (43.8%) males and 340 (56.2%) females. The majority [512 (84.6%)] of the participants had not been infected with COVID-19, whereas 33 (5.5%) were suffering from chronic illness, 416 (68.8%) were having family members infected with COVID-19, 89 (14.7%) lost family members due to COVID-19, and 330 (54.5%) believed that COVID-19 would continue. Table 1 summarizes the participants’ responses to the demographic section of the online survey.
Table 1 characteristics of study participants
Variable N(%) Variable N(%)
Gender Do you have chronic illness?
Male 265(43.8) Yes 33(5.5)
Female 340(56.2) No 572(94.5)
Study Year Family member diagnosed with COVID-19?
1st 138(22.8) Yes 416(68.8)
2nd 86(14.2) No 189(31.2)
3rd 94(15.5) Family member lost as a result of COVID-19?
4th 112(18.5) Yes 89(14.7)
< 4 175(28.9) No 516(85.3)
Have you been infected with COVID-19 before? You think COVID-19 will ….?
Yes 93(15.4) Continue 330(54.5)
No 512(84.6) Will come to an end soon? 275(45.5)
Instruments
An online survey was used to collect data. The survey included two sections: (1) single indicator variables that required information on the participant’s socioeconomic demographics, including gender, exposure to COVID-19 infection, family members’ infection with COVID-19, decease of a family member due to COVID-19 infection, personal belief about the expected continuity of COVID-19 pandemic, and suffering from a chronic disease of long-lasting health illness; (2) multiple indicator variables that included three scales, namely, fear of COVID-19, depression from COVID-19, and FCA. The scales were translated from English to Arabic using the team translation method (Harkness et al., 2004). This method involves conducting a forward translation holding a consensus meeting followed by a final reconciliation meeting. A group of four, including two of the authors, translated the scales from English to Arabic. Next, the group members discussed the parallel translations for each item and agreed on the adequate translation. Finally, the group members met with an adjudicator, a faculty member from the psychology department who has good command in English and Arabic, to reconcile any disagreements among the translators in case there were any. The three scales are described below.
Fear of COVID-19 Scale
It is a seven-item self-report scale that asks participants to rate their level of agreement on a five-point Likert scale where a total score ranges from 7 to 35, and a higher score indicates greater fear of COVID-19 (Mahmud et al., 2021; Alimoradi et al., 2022; Bakioğlu et al., 2021). The items were adapted to reflect fear of COVID-19 prolongation (e.g., my hands become sweaty when I think about COVID-19 prolongation). For the current study data, the scale has acceptable reliability (Cronbach’s α = 0.85), and the corrected item-total correlation ranged from 0.48 to 0.67. Confirmatory factor analysis (CFA) was used to assess scale construct validity; the indices showed a unidimensional model with a good fit to the participants’ responses (GFI = 0.99, CFI = 0.99, RMSEA = 0.05).
Depression from COVID-19 Scale
Depression symptoms cause persistent feelings of frustration, loss of interest, and sadness. The scale was developed by Mahmud et al. (2021) and consists of 6 positive items that are answered on a four-point response format with a total score ranging from 6 to 24 (e.g., I felt that life is meaningless due to the fear of COVID-19 prolongation). Although Mahmud and his colleagues claimed that the scale assesses depression, it is believed that the scale evaluates depressive symptoms rather than depression as a disorder. The scale has acceptable reliability (Cronbach’s α = 0.82), and the corrected item-total correlation ranged from 0.50 to 0.64. Confirmatory factor analysis (CFA) was used to assess scale construct validity; the indices showed that a unidimensional model is a good fit for the sample’s responses (GFI = 0.97, CFI = 0.95, RMSEA = 0.012).
Future Career Anxiety Scale
Tsai et al. (2017) developed a 25-item scale comprising four dimensions (personal ability, irrational beliefs about employment, employment environment, and professional education training). The present study utilized the dimension of employment environment to measure university students’ FCA given the forecasts of expected continuation of the pandemic (e.g., I worry about future employment because of the increasing unemployment and job cut reported by the mass media for the reason of COVID-19 prolongation). The scale has acceptable reliability (Cronbach’s α = 0.92), and the corrected item-total correlation ranged from 0.75 to 0.84. A confirmatory factor analysis (CFA) was used to assess scale construct validity, and the scale model data fit indices were excellent (GFI = 0.99, CFI = 1.00, RMSEA = 0.01).
Data Analysis
Data were exported to SPSS version 25 for analysis. Descriptive analyses were used to determine the frequencies, means, and standard deviations to describe sample demographics. Structural equation modeling (SEM) was conducted by AMOS version 20 to determine the direct effects of fear of COVID-19 and depression from COVID-19 on FCA and the indirect effect of depression from COVID-19 on FCA. Following Hu and Bentler (1999), the model fit indices were evaluated using RMSEA, CFI, and GFI. The acceptable values for RMSEA are equal to or less than.08, and those for CFI and GFI are equal to or greater than.90. The bootstrap procedure using the maximum likelihood estimates was used to examine each specific indirect effect (Preacher & Hayes 2008).
Results
Multiple Indicator Variables
As shown in Table 2, univariate analyses revealed that no gender differences were observed in the fear of COVID-19, depression from COVID-19, and FCA (F = 0.024, p = 0.877; F = 2.89, P = 0.09; F = 1.3, P = 0.255), no differences were observed between university students in various study years (F = 0.241, P = 0.944, F = 1.02, P = 0.405, F = 1.98, P = 0.079), and similarly, no differences were found as a result of the interaction between gender and the program study year (F = 1.27, p = 0.274; F = 0.548, P = 0.74; F = 1.26 P = 0.278). Independent sample t tests were performed to assess the existence of significant mean differences in the single indicator variables outlined in Table 1. The results indicated that there were mean differences in the fear of COVID-19 due to the diagnosis of a family member with COVID-19, participants who lost one of their family members due to COVID-19, and participants’ beliefs about COVID-19 prolongation. Additionally, participants who lost one of their family members due to COVID-19 showed higher depressive symptoms. Participants who believed that the COVID-19 pandemic would continue for a long time showed higher fear of COVID-19, higher depressive symptoms, and higher FCA.
Table 2 Univariate analysis of fear of COVID-19, depression from COVID-19, future career anxiety (FCA)
Variable Category N fear
M(SD) P depression M(SD) P FCA
M(SD) P
Gender Male 265 7.69(4.63) 0.877 4.18(3.78) 0.09 8.83(4.07) 0.255
Female 340 7.85(3.99) 4.67(3.79) 9.04(4.11)
Study Year pre 42 8.14(4.99) 0.944 3.93(3.51) 0.405 9.12(4.04) 0.079
1st 96 7.80(4.12) 4.36(3.94) 8.82(4.00)
2nd 86 8.09(4.30) 4.63(4.06) 7.93(4.12)
3rd 94 7.85(4.12) 4.64(3.58) 9.20(4.32)
4th 112 7.84(4.42) 5.02(4.01) 9.56(4.52)
< 4 175 7.46(4.21) 4.09(3.59) 8.95(4.09)
Have you been infected with the COVID-19 before? Yes 93 7.53(4.35) 0.533 3.84(3.67) 0.089 9.08(3.84) 0.749
No 512 7.83(4.27) 4.57(3.80) 8.93(4.14)
Do you have chronic illness? No 572 7.76(4.23) 0.526 4.48(3.89) 0.571 8.94(4.11) 0.739
Yes 33 8.24(5.020) 4.09(3.87) 9.18(3.90)
Family member diagnosed with COVID-19? No 189 7.16(3.99) 0.016 4.51(3.74) 0.816 9.11(4.13) 0.530
Yes 416 8.06(4.38) 4.43(3.82) 8.88(4.08)
Family member died by COVID-19? No 516 7.54(4.12) 0.003 4.33(3.71) 0.047 9.07(3.99) 0.095
Yes 89 9.20(4.92) 5.19(4.15) 8.28(4.58)
You think the COVID-19 Will end soon 275 7.22(4.02) 0.003 4.06(3.61) 0.019 8.15(4.20) < 0.001
Continue 330 8.25(4.44) 4.78(3.91) 9.62(3.89)
Table 3 Correlation matrix
Variable Fear of corona Depression of corona Future career anxiety
Fear of COVID-19 1
Depression from COVID-19 0.58 1
Future career anxiety 0.32 0.43 1
Note: Correlations is significant at the 0.01 level
The Structural Model
The Pearson correlation coefficient showed a significant positive association between fear of COVID-19, depression from COVID-19, and FCA. Table 3 provides the correlation matrix between the three variables. The standardized regression weights for scale items were statistically significant and ranged from 0.54 to 0.76 for fear of COVID-19 items, from 0.55 to 0.80 for depression from COVID-19 items, and from 0.71 to 0.90 for FCA items. All item loadings were above the minimum criterion of 0.5, whereas some of them were above the ideal criterion of 0.7 (Hair et al., 2019; Malhotra& dash, 2016). For the structural model, the model fit indices were acceptable (CMIN/DF = 3.38, GFI = 0.92, CFI = 0.95, IFI = 0.95, RMSEA = 0.06). The results of the structural model are shown in Fig. 2. There were significant standardized direct effects (unmediated) of fear of COVID-19 on depression from COVID-19 (0.77) and of depression from COVID-19 on FCA (0.41). Additionally, depression from COVID-19 mediated the relationship between fear of COVID-19 and FCA (0.32) (see Fig. 2).
Fig. 2 Results of the structural equation modelling (SEM) analysis of the mediation of fear of COVID-19, depressive symptoms, and future career anxiety in Omani university students (n = 605), *** = p < 0.001
Discussion
The primary purpose of the current investigation was to examine the relationships between university students’ fear of COVID-19, depression and their FCA. Overall, it is clear that the participants showed high levels of fear, depression and FCA. This shows that major psychological health problems exist among university students due to COVID-19 prolongation, which is consistent with the moderate to severe symptoms of fear, depression, and anxiety observed in previous research following the onset of the pandemic (Alimoradi et al., 2022; Balakrishnan et al., 2022; Luo et al., 2021). There were no gender differences in the fear of COVID-19, depression, or FCA among the participants. This finding is inconsistent with previous research studies on gender differences in fear of COVID-19 (Rodriguez et al., 2020; Bakioğlu et al., 2021). The finding could be interpreted from a contextual perspective, as both male and female students were equally worried about the possible continuation of COVID-19 and how this could affect their study programs (Malik & Javed, 2021), as well as employability after graduation (Cifuentes-Faura et al., 2021). It is suggested that the academic demands of university programs and the uncertain outlook due to possible COVID-19 prolongation has taken its toll on learning and evaluation processes, leading to emotions of fear and depression in both female and male students (Rodriguez et al., 2020).
The results of the current investigation suggest that there are significant relationships between fear of COVID-19, depression, and FCA. As hypothesized, fear of COVID-19 among Omani University students’ was significantly and positively related to COVID-19 prolongation-related depressive symptoms. This finding is congruent with previous research evidence suggesting that adolescents’ fear of COVID-19 and depressive symptoms are strongly associated (Alimoradi et al., 2022; Bakioğlu et al., 2021; Mahmud et al., 2021). Interestingly, several previous studies have shown that depressive symptoms are correlated with several negative episodes and consequences in adolescents (Mahmud et al., 2021; Taylor, 2019). In particular, this relationship was confirmed for female students more than for male students (García-Fernández et al., 2021; Hou et al., 2020). In examining Greek university students’ wellbeing and mental health variables during the COVID-19 pandemic, Kaparounaki et al. (2020) reported that there was a dramatic increase in clinical cases of depression. Additionally, there was a horizontal increase in scores on anxiety, sleep quality and quantity, and other mental health issues (Vilca et al., 2022). Thus, it may be that depressive symptoms and fear of COVID-19 were two primary issues that affected university students’ wellbeing following the pandemic outbreak and prolongation. In a meta-analysis of 20 studies (Şimşir et al., 2022), the results showed a moderate mean weighted between fear of COVID-19 and depression. This finding is consistent with the view that different fears can be associated with depression (Barlow, 2000; Emam et al., 2019). Additionally, the results from 23 studies showed a strong mean weighted between fear of COVID-19 and anxiety. The fear of COVID-19 reflects the psychological nature of a phobia that is classified as a type of anxiety disorder (American Psychiatric Association, 2013).
The second main aim of our investigation was to explore the influence of fear of COVID-19 prolongation and depression on FCA. We designed a theoretical model based on a review of previous research and contrasted it with the collected data. The results obtained in the structural equations showed an excellent fit to the model. In line with our hypotheses, Omani university students’ FCA was significantly related to their depressive symptoms (García-Fernández et al., 2021). It may be that both males and females were thinking deeply about the consequences of COVID-19 prolongation on their future career and employability (Cifuentes-Faura et al., 2021). They may have thought of the economic impact of the pandemic on the country’s public and private institutions. In addition, adolescents’ belief in conspiracy theory as a possible cause of the pandemic, which was documented in previous research (Miller, 2020), may have resulted in mistrust in any scientific reports on the future trajectory of the pandemic. This finding is consistent with previous research suggesting that depression and future anxiety, whether general or specific (e.g., career), tend to co-occur due to the individual’s negative view of self, the world, and the future (Botha & Mostert, 2013; Emam et al., 2019; Pak et al., 2022). In particular, there is research evidence that negative cognitions operate on the aforementioned three aspects for Omani adolescents, which affects their perception of the future (Barlow, 2000; Emam et al., 2019; Izard 1977; Pedrosa et al., 2020).
Thus, our hypotheses were corroborated. As hypothesized, fear of COVID-19 had a direct unmediated effect on depression from COVID-19, and the latter had a direct impact on students’ FCA. Mediational analyses aimed to test our hypothesis that depression from COVID-19 would explain the relationship between fear of COVID-19 prolongation and university students’ FCA. Previous research suggests that depressive symptoms are important in predicting general and specific future anxieties (Bakioğlu et al., 2021; Duplaga & Grysztar, 2021). Consistent with our hypothesis, the participants’ depression from COVID-19 prolongation mediated the relationship between fear of COVID-19 prolongation and FCA. This finding implied that students’ FCA was related indirectly to their fear of COVID-19 prolongation and that students’ depressive syndromes contributed to determining and interpreting this relationship. Thus, the connection between students’ fear of COVID-19 prolongation and their FCA may be explained by depression from COVID-19. This model of relationships received due attention from universities when they planned to provide psychological services during crisis time to support students in avoiding traumatic experiences. Students may benefit from counseling services that prioritize addressing their depressive symptoms, independent of the level of fear of COVID-19 prolongation. The relationship of fear of COVID-19 prolongation with FCA mediated by depression from COVID-19 has not been described before, making this a novel contribution. The conditions in which university students in Oman have to cope with the continuation of the pandemic are extremely adverse in many ways. The emergence of several variants, the large number of people affected, the growing number of deaths, mistrust of the health system, a lack of awareness, and disinformation may have all contributed significantly to the fact that young university students experience fear of COVID-19 prolongation. University students tend to feel more fear when they perceive themselves in a more vulnerable situation and in greater danger. Families often place high expectations on future careers and employment of adolescents. In Oman, study programs in public universities are closely connected with job market needs (Al-Balushi et al., 2022). Therefore, it is reasonable that university students become anxious about their future career and employability as a result of COVID-19 prolongation.
Limitations
The current study is not without limitations. First, the participants were from the top higher education institutions in Oman. Therefore, it could be argued that they hold higher expectations of their future career compared to other students in other universities and colleges. This could diminish the generalizability of the study findings to the larger population of university students in Oman. Second, the findings are based on the use of self-report measures that involve the threat of social desirability. Participants may have exaggerated or underrated their feelings to deliver a message that may not be true of themselves. Therefore, the study results should be interpreted with this assumption in mind. Third, depressive symptoms were tested as a mediator in the model, although other possible variables could have been included, such as stress, religious coping, and resilience. Nonetheless, previous literature was relied upon to build our model. Furthermore, the use of depressive symptoms versus depression was meant to avoid the overlap between depression as a psychological disorder that has diagnostic criteria in the DSM-5 (American Psychiatric Association, 2013). Finally, these findings should be interpreted within the limitations of the cross-sectional methodology that was employed, which does not confirm a causal relationship. Longitudinal data could not be collected, as there was no clear vision of the trajectory of the pandemic.
Implications and Conclusion
Despite the stated limitations, the current study contributed to understanding university students’ FCA during crisis times. University students or adolescents in general represent an interesting population, and therefore, their mental health and wellbeing are of paramount importance to their families and to society. Based on these findings, the uncertainty and the peril perceived by adolescents could turn into a fertile breeding ground for fear, depression and FCA (Pak et al., 2022). Therefore, there is an urgent need to design intervention plans in universities to help these young people better cope with this type of situation and avoid future trauma. University students’ exposure to stressful conditions and crisis’ have increased in modern times, such as with the COVID-19 pandemic. This has resulted in psychological problems and issues with mental health. Consequently, university students who are in aunique developmental period of adolescence should receive adequate psychological services that can be provided within, as well as outside, the university. Based on our structural model, different measures to prevent and alleviate this may be suggested. To reduce fear of COVID-19, it would be advisable to run convincing information campaigns about the disease, with training provided for its prevention and for effective coping strategies.
Although the results of the current investigation were in line with the hypotheses made prior to data collection, further investigation may entail other possible variables that could have a direct or indirect impact on students’ FCA during times of crisis. Examples of these variables may include religiousness, religious coping, family support, and support received from significant others. Given that the number of university students seeking psychological counseling has been on the rise globally, further knowledge should be gained on the characteristics of adolescents, their interplay with the environment, and the trajectories they may take during times of crisis and traumatic events. Health services professionals in clinical and nonclinical settings should be able to address adolescents’ psychological needs in normal, as well as difficult times. Adolescents’ resilience and ability to adapt during difficult times should be examined empirically and targeted by professionals. Culture-specific enablers and obstacles should be explored to present new information on the potential mediators and moderators of the relationship between adolescents’ mental health and the different environments with which adolescents interrelate at various times.
Electronic Supplementary Material
Below is the link to the electronic supplementary material.
Supplementary Material 1
Declarations
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| 0 | PMC9734944 | NO-CC CODE | 2022-12-14 23:28:31 | no | Coloproctology. 2022 Dec 5; 44(6):442-443 | latin-1 | Coloproctology | 2,022 | 10.1007/s00053-022-00659-0 | oa_other |
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Int Ophthalmol
Int Ophthalmol
International Ophthalmology
0165-5701
1573-2630
Springer Netherlands Dordrecht
36471221
2593
10.1007/s10792-022-02593-y
Original Paper
Population perceived eye strain due to digital devices usage during COVID-19 pandemic
Almalki Ashwaq M. [email protected]
12
Alblowi Mohammed [email protected]
3
Aldosari Ayat M. [email protected]
12
http://orcid.org/0000-0002-3925-1005
Khandekar Rajiv [email protected]
14
http://orcid.org/0000-0002-1070-7232
Al-Swailem Samar A. [email protected]
[email protected]
1
1 grid.415329.8 0000 0004 0604 7897 Research Department, King Khaled Eye Specialist Hospital, 2775 AlUrubah Road, Umm AlHammam AlGharbi, Unit 2, P.O. Box 7191, 11462 Riyadh, Saudi Arabia
2 grid.415254.3 0000 0004 1790 7311 Department of Ophthalmology, King Abdulaziz Medical City, Jeddah, Saudi Arabia
3 Optometry Division, Medical Staff Department, King Khalid Eye Specialist Hospital, Riyadh, Saudi Arabia
4 grid.17091.3e 0000 0001 2288 9830 Department of Ophthalmology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
5 12 2022
19
23 1 2022
12 11 2022
© The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Purpose
To assess the magnitude severity and determinants of eyestrain and the use of digital devices in a Saudi population during the COVID-19 pandemic lockdown.
Methods
This web-based survey was conducted in September 2020 and enrolled only Saudi nationals 15 years or older. Data were collected on demographics, eye strain related symptoms, severity, and the use of optical aids during the COVID-19 lockdown. The frequency and severity of eye strain were calculated. A Computer Vision Syndrome (CVS) score was graded as none/mild moderate and severe, based on the sum of 15-eye strain related signs and symptoms. Correlation analysis was performed for determinants of CVS.
Results
The study sample was comprised of 2009 individuals with median age of 20 years. Among those who used digital devices for more than 6 h daily, the main reasons for use were work and social purposes among 68.4%, and 61% of respondents, respectively. The prevalence of knowledge on CVS and the ’20-20 rule for using digital devices’ was 9.4% and 6.9, respectively. The most common symptoms of eye strain from digital device usage were headache, burning, itching, tearing, and redness of eyes. Six hours of daily usage of digital devices was positively associated to the grade of eye strain severity during the COVID-19 lockdown (P < 0.05)).
Conclusion
The Saudi population experienced eye strain during COVID-19 lockdown due to excessive digital devices usage. Longer duration of digital device usage was associated to eye strain. Health care providers should educate the general population on measures to mitigate eye strain due to digital devices.
Trial registration ID None applicable.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10792-022-02593-y.
Keywords
Computer vision syndrome
Visual problems
Digital devices
Digital eye strain
COVID-19
Eye strain
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pmcIntroduction
After nearly 100 years since the Influenza pandemic, the human population faced the COVID-19 pandemic in 2020 [1, 2]. To prevent high hospitalization rates and mortality, global health organizations recommended personal hygiene, social distancing and restricted mobility especially among high-risk groups [3]. Fortunately, there were alternatives to remain in contact with others by using digital devices such as computers, mobile phones and tablets. [4]. Prior to the pandemic, the estimated utilization of daily computer use was 75% [5, 6].
Factors that cause eye strain include, working with digital devices for a long time, poor illumination, usage at less than the recommended distances and not using the required visual aids for clear vision [7]. Eye strain from digital devices is called Computer Vision Syndrome (CVS) or digital eye strain (DES). CVS is defined as “a complex of eye and vision problems related to near work experienced during prolonged computer, tablet, e-reader and cell phone use” [8].
To combat the pandemic in Saudi Arabia, schools and colleges were initially closed and there was a subsequent transition to online education. This transition often resulted in an excessive use of internet platforms for schoolwork and homework. In the professional environment, many jobs transitioned to an online model mainly using videoconferencing. Thus, the risk of eye strain in the Saudi population increased during the lockdown and pandemic.
Prior to the pandemic, the prevalence of eye strain due to CVS among young Saudi students was 69.8%. [9]. More time spent on computers and digital devices was also found to be a risk factor for CVS. Thus, CVS in the Saudi population was likely to increase during the COVID-19 pandemic. During the period of COVID-19 lockdown, two studies were conducted to study the prevalence of CVS, it’s associated risk factors and common related symptoms associated with the prolonged use of electronic devices perceived signs and symptoms of CVS among the Saudi population aged 18–20 years or older [11, 12]. Known determinants of CVS include female gender, longer duration of work, type of work, refractive status and compliance to spectacle wear [10–13].
This study investigates the scoring for responses of the same CVS Questionnaire, the prevalence of knowledge of CVS and determinants of eyestrain among the Saudi population aged 15 years or older, during the same period.
Materials and methods
A cross-sectional survey was performed in September 2020. The study was approved by the Institutional Research Board (P 0436-20) and adhered to the tenets of the Declaration of Helsinki. Informed consent was electronically obtained from all participants after explaining the aims of the study. For children under 16 years of age, an electronic signature of the parent or legal guardian was obtained.
The study population was comprised of Saudi nationals 15 years or older who had access to digital devices during the study period. Sample size calculations, we assumed that there were 10 million Saudis (15 years or older) using digital devices. Previous literature indicated that the prevalence of eye strain during the COVID-19 pandemic and excessive use of digital devices would be 67.8% [14]. To achieve 95% confidence interval and 3% acceptable error margin with clustering factor of 2, at least 1,864 participants were required for the survey. To compensate for the incomplete data we increased the sample by 10%. Thus, the final sample for the proposed survey was 2,050 Saudi aged 15 years or older. Stat calculator to calculate the sample size for a cross-sectional study [15]. Subjects were excluded if they refused to participate in the study, were not able to complete survey data, had chronic ophthalmic diseases that resulted in vision that could not be fully corrected by spectacles or contact lenses (e.g. diabetic macular edema, macular scar, advanced glaucoma, etc.).
To quantify digital eye strain, the Computer Vision Syndrome Questionnaire (CVS) was used in this study [14]. The CVS has acceptable psychometric properties, making it a valid and reliable tool to control for the visual health of workers who use computer terminals and this survey is appropriate for clinical trials and outcomes research [16].
The survey tool was a web-based questionnaire, which was designed by a research coordinator using a Google form. Investigators and a research coordinator used “Research Survey Invitation e-mail account” to invite all researchers at King Khaled Eye Specialist Hospital (KKESH) to participate in this study. Investigators invited people to participate by posting a link in different social platforms. Both English and Arabic version links were distributed. The survey remained open for a period of 2 weeks. The survey collected data on the profile of participant’s COVID-19/quarantine status, refractive status from pre-existing ophthalmic reports, habitual optical aid usage and usage of digital devices. Data were also collected on the purpose of using digital devices, frequency of digital device usage, duration spent on a digital device, symptoms during digital device usage at least half of the time over the previous week [17]. The behavior and status of optical aid usage was assessed as was the knowledge about the ‘20-20-20 rule’ for using digital devices.
There were 15 questions on eye strain signs and symptoms. For each question, the response choices were never, sometimes and always. Those with signs and symptoms further graded their problem as mild, average and severe (Supplementary Material: 1). According to the American Academy of Ophthalmology, digital device-related eye strain could present as patient complaints of visual blur, achy and tired eyes, dry eyes, or tearing and stinging [12].
Scoring for responses was as follows: (A) frequency of signs/symptoms, never = 0, sometimes = 1, always = 2; (B) severity of sign and symptoms, mild = 1, average = 2 and severe = 3. For each sign and symptom, the total score was calculated using a formula score of A X B. The sum of 15 eye strain related signs and symptoms score was further graded as < 30 = no or mild CVS, 30 to 59 = moderate CVS and more than 60 = severe CVS. To associate the CVS severity to different determinants we grouped the score into no or mild eye strain and moderate to severe eye strain.
The data were transferred into an Excel spreadsheet (Microsoft Corp., Redmond, WA, USA). After consistency checks and coding, it was transferred to Statistical Package for Social Sciences (SPSS 26; IBM Corp., Armonk, NY, USA). Qualitative data are presented as number and percentage. The eye strain scores are presented as median and interquartile range (IQR). The grade of eye strain was associated to determinants and for two subgroups, a 2 × 2 table was used to estimate the Student T test and calculate the Odd’s ratio, the 95% confidence interval (CI) and a two-sided P value. For more than 3 subgroups, the chi-square value was calculated along with the degrees of freedom and two-sided P value. P values less than 0.05 were considered statistically significant.
Results
The study sample was comprised of 2,009 participants with median age 20 years (IQR: 18; 22). Table 1 presents the profile of the study sample.Table 1 Profile of refractive status and usage of digital devices among surveyed Saudi participants
Number Percentage
COVID-19 status Positive
Negative
Don’t know
282
1727
0
14.0
86.0
0
Quarantine status Quarantined
No
Missing
223
932
854
11.1
46.4
42.5
Use of spectacles Spectacles for Clear Vision
Contact lens cosmetic
Spectacles and contact lens
No contact lens or spectacles
393
59
55
1502
19.6
2.9
2.7
74.8
Purpose of visual aids Spectacle for reading
Spectacle for distance
Spectacle for both
Missing
72
222
231
1484
3.6
11.1
11.5
73.9
Last optical check up Within 1 year
1 to 2 year
More than 2 years
Not applicable
79
61
1476
393
3.9
3.0
73.5
19.6
Duration of using optical aids (hours in week) 1–2 times in the week
3 times or more in a week Daily
Other
Daily
79
61
1476
393
3.9
3.0
73.5
19.6
Using make up 1 Daily
1–2 times in the week
3 times or more in a week
Not using
60
100
45
1804
3.0
5.0
2.2
89.8
Purpose of using digital devices Work only
Social
Contact
Both
Other
23
485
0
1375
126
1.1
24.1
0.0
68.4
6.3
Duration of digital devices usage Less than 2 h
2–6 h
More than 6 h
140
644
1225
7.0
32.1
61.0
Two hundred and eighty-two (14%) participants were diagnosed with COVID-19, and 223 (11.1%) were quarantined. Three-fourths of participants did not use contact lens or spectacles, 393 (19.6%) used spectacles, 59 (2.9%) used contact lens and 55 (2.7%) used both spectacles and contact lens.
There were 1476 (73.5%) participants who had not undergone an optical checkup in the prior 2 years. Duration of optical aid usage differed between participants, ranging from 1–2 times a week (3.9%) to daily (19.6%). The purpose of using digital devices varied between participants as follows: work only (1.1%), social (24.1%) or both (68.4%). The number of hours spent on digital devices varied among participants, with the majority (61.0%) using them for more than 6 h.
The prevalence of knowledge of CVS was 9.4% (95% CI 8.1; 9.6), and the prevalence of knowledge of the ‘20-20-20 rule’ for using digital devices was 6.9% (95% CI 5.8; 8.0).
Most participants experienced headaches, burning, itching, tearing and redness of eyes related to eye strain from digital devices usage (Table 2).Table 2 Signs and symptoms of eye strain related to using digital devices as perceived by survey participants
Title Always Sometimes Never Score
Severe Average Severe Average Median (IQR)
1 Burning 35 176 58 1226 514 2.0 (0.0; 2.0)
2 Itching 69 168 96 1267 409 2.0 (0.0; 2.0)
3 Foreign body sensation 54 100 37 835 983 0.0 (0.0; 2.0)
4 Tears (watering) 144 263 58 1145 399 2.0 (0.0; 2.0)
5 Excessive blinking 50 108 34 711 1105 0.0 (0.0; 2.0)
6 Redness 92 123 74 986 734 2.0 (0.0; 2.0)
7 Eye pain 55 106 67 877 906 0.0 (0.0; 2.0)
8 Drooping eyelids 47 74 33 592 1263 0.0 (0.0; 2.0)
9 Dryness of eyes 74 101 36 685 1113 0.0 (0.0; 2.0)
10 Blurring of vision 98 87 60 740 1024 0.0 (0.0; 2.0)
11 Double vision 40 52 33 484 1400 0.0 (0.0; 2.0)
12 Difficulty in focusing near object 101 81 55 820 1052 0.0 (0.0; 2.0)
13 Intolerance to light 174 143 75 702 915 0.0 (0.0; 2.0)
14 Seeing colored halos 62 54 16 530 1347 0.0 (0.0; 2.0)
14 Feeling of worsening eyesight 99 80 50 759 1021 0.0 (0.0; 2.0)
15 Headache 250 195 170 992 402 2.0 (0.0; 4.0)
The median eye strain symptom score was 20 (IQR 10: 32). ‘No/ mild’ grade of eye strain was reported by 1,486 (74%), moderate eye strain by 468 (23.3%) and severe eye strain by 55 (2.7%) participants. Table 3 presents the determinants of eye strain. Longer than 6 h of digital device usage per day was statistically significantly positively associated to the grade of eye strain severity (P < 0.001).Table 3 Determinants of eye strain due to the digital devices usage during COVID-19 among adult Saudi surveyed participants
Eye strain of moderate to severe grade (N = 527) No/mild grade of eye strain (N = 1488) Validation
Number Percentage Number Percentage
Age group < 30 years 491 93.2 1379 92.7 OR = 1.3 (95% CI 0.8: 1.9) P = 0.26
31 and older 29 5.5 104 7
COVID status Yes 73 13.9 193 13 OR = 1.2 (95% CI 0.9: 1.7) P = 0.15
No 394 74.8 1290 86.7
Don’t know 60 11.4 5 0.3
Quarantined Yes 60 11.4 154 10.3 OR = 1.1 (95% CI 0.8: 1.6) P = 0.5
No 234 44.4 666 44.8
Missing 233 44.2 668 44.9
Digital devised used for Work only 9 1.7 13 0.9 χ2 = 1.6
Social 116 22 353 23.7 Df = 3
Both 315 59.8 1024 68.8 P = 0.2
Other 27 5.1 93 6.3
Missing 60 11.4 5 0.3
Type of visual aid usage Spectacles for Clear Vision 115 21.8 256 17.2 χ2 = 12
Contact lens cosmetic 12 2.3 45 3 Df = 3
Spectacles and contact lens 16 3 38 2.6 P < 0.001
No contact lens or spectacles 324 61.5 1144 76.9
Missing 60 11.4 5 0.3
Visual aid used for Spectacle for reading 17 3.2 51 3.4 χ2 = 2.3
Spectacle for distance 66 12.5 151 10.1 Df = 3
Spectacle for both 74 14 138 9.3 P = 0.12
Missing 370 70.2 1148 77.2
Visual aid checking done In last one year 124 23.5 316 21.2 χ2 = 0.36
1–2 years 45 8.5 93 6.3 Df = 3
More than 2 years 114 21.6 317 21.3 P = 0.54
Not applicable 244 46.3 762 51.2
Discussion/Conclusion
CVS is a rising public health issue related to continuous use of technology (computers, cell phones and tablets) and is a significant factor in reducing quality of life and workplace productivity [18]. Similar to previous two Saudi studies, which recruited elder participants during the period of COVID-19 lockdown, current study confirmed the excessive use of digital devices among most of the participants [11, 12]. Unlike previous two studies, we defined clearly how and what scoring system used to assess the severity of CVS [11, 12]. Another differences were the very poor use of optical aids (25.5%) by our younger participants when compared with those in the previous two studies [11, 12]. Additionally there was very poor regular checks of refractive status of our participants. Very few participants in the current study had COVID-19.
Alabdulkader reported a high incidence of digital eye strain (75%) during the period of COVID-19 lockdown among the Saudi participants 18 years or older [11]. The outcomes of the current study indicate that nearly one-fourth of Saudi participants 15 years or older had symptoms of moderate to severe eye strain. Almarzouki et al. reported higher rate (44%) of sever eye strain among the Saudi participants 20 years or older during the same period [12].
In this study, young participants had a very poor knowledge of CVS and the ‘20-20-20 rule’ for working with digital devices. Similar to a previous study, working with digital devices for more than 6 h was positively associated with the presence of signs and symptoms of eye strain (P < 0.001) [11].
The currents study enrolled a large sample of participants and represents a sample of convenience for assessing digital device usage among Saudis aged 15 years and older. Although this sample may not be representative of the entire adult Saudi population, the findings reflect the habits of the population facing lockdown and forced to overuse digital devices for their business and/or personal use including entertainment, communication and education. The vision/ eye health impact of digital device abuse requires healthcare providers to educate patients on incorporating healthy vision practices among the general population.
In the current study, only 9.4% of participants had adequate knowledge of CVS and only 7% knew about the ‘20-20-20 rule’ for using digital devices. These outcomes were much lower than the proportion of Saudi medical students (91.35%), and Indian students (34%) who knew about CVS [17, 18]. In addition, Alabdulkader found that 32% of the elder Saudi participants were aware of the 20-20-20 rule, only 13% of these participants practiced it, and 50% reported that they practiced it occasionally [11]. The higher level of knowledge in previous studies could be attributed to the high educational level of the participants with a medical education background [19, 20].
Nearly two thirds of participants in our study used digital devices for professional and social interactions. A previous study also noted increased digital devices usage in the era of COVID-19 for professional and other purposes [21].
We found that the compliance for using visual aids among participants was 3.6%, 11.1% and 11.5% for reading, distance viewing and both, respectively. This was much lower than the projected number of individuals with refractive error in this age group of Saudis. The prevalence of refractive error among 16 to 39-year-old Saudis was reported to be 45.8% as follows; 24.4% myopes,11.9% hyperopes and 9.5% astigmatism [22]. Another study reported refractive error as high as 55.5% among Saudi adolescents [23]. The prevalence of refractive error among 20–60-year-old Saudis was reported to be 75,2% as follows; 41.2% myopes,12.1% hyperopes and 20.9% astigmatism [12]. Thus, the risk of eye strain will be elevated in a population with a high prevalence of refractive error and low compliance for optical aids [11]. Additional determinant factors with the symptoms severity score reported in other Saudi studies included the number of devices used; the use of rewetting drops [11].
In our study, 73.5% participants did not undergo optical checkups for more than 2 years and used optical aids sparingly. This could also contribute to ocular strain symptoms. We concur with previous studies that urgent action is warranted to improve compliance with spectacle wear and contact lens usage to address eye stain [24, 25].
In the present study, all participants were using digital devices and majority of them reported eye strain related symptoms and signs. The most common symptoms associated with digital devices eye strain are headaches, blurred vision, dry eyes, pain in the neck, and shoulders [8]. Our outcomes concur with a previous study that reported 62.1% of Saudi medical students had similar signs and symptoms of eye strain [26]. Another study has also reported a high prevalence of eye strain in Pakistan (90.4%) [27]. Another study done in India reported a 82.4% prevalence of eye strain among medical and engineering students [26]. The high prevalence of eye strain reported in the present study can be explained by a shift towards excessive use of digital devices during the COVID-19 lockdown. Bahkir et al. also found that 93.6% of participants had an increase in their screen time since the lockdown and 56.5% reported increased frequency and intensity of symptoms since the lockdown [20].
Headache was the most commonly reported internal symptoms and the burning sensation with itching were the main external symptoms. However, the majority of reported symptoms were mild. Previous study have also reported headache as the main symptom of eye strain [20, 28]. Headache can be due to prolonged use of digital devices. External symptoms of CVS like burning, irritation, redness and tearing are related to dry eye and the internal symptoms of strain, and headache are linked to accommodative and/or binocular vision stress [7]. They can also be attributed to uncorrected refractive errors or exposure to a continuous bright light for extended periods.
Extended periods of digital device usage (> 6 h) seem to be a significant risk factor for eye strain in the current study. Other studies from Saudi Arabia reported defined extended duration of digital device usage as more than 4 h and still reported high rates of eye strain [12, 29–31]. This relationship between the duration of digital devices usage and eye strain has prompted some experts to suggest a reduction in the number of hours spent in front of computers and other devices to mitigate the risk of serious visual problems [20, 26]. Hence, they recommend public health initiatives directed at the general population on good practices for digital device usage. Taking breaks during electronic use, viewing computers at appropriate distance, and the use of screen protectors were significant practices to relive the eye symptoms severity score [11].
In the current study, very few participants had COVID-19. Hence, we could not test for an association of this disease and eye strain. The American Academy of Ophthalmology reports that 1–3% of people with confirmed COVID-19 may have conjunctivitis, either as an initial presenting sign or during advanced stage of the disease [32]. Some common ocular symptoms recorded in patients with conjunctivitis and confirmed COVID-19 infection include itching, redness, tearing, discharge, and foreign body sensation [32–34]. It will be interesting to study the additive impact of COVID-19 infection on eye strain due to excessive digital devices usage during the lockdown.
There are some limitations to the present study including the cross sectional survey design that precluded an establishment of eye strain to known risk factors. Therefore, we recommend judicious interpretation of a causal association of eye strain to risk factors in the current study. The sample size may not be representative of the entire adult Saudi population as the reported symptoms were subjective, self-reported should not be compared by studies based on objective measurements of eye strain.
During the COVID-19, pandemic outdoor activities were limited for children and they spent more time using digital devices for educational purposes and social interactions. Hence, they are vulnerable to a potential eye health effect. We recommend that future studies investigate school children for the magnitude and determinants of eye strain during lockdown. It will also be interesting to study the impact of public awareness campaigns for safe use of digital devices on vision.
Conclusion
The study provides evidence that a significant proportion of the Saudi population is affected by CVS during the COVID-19 lockdown due to abuse of digital devices usage. The digital devices usage varied for work or social interactions. Longer use of digital device usage seems to influence increased symptoms of CVS and severity. The majority of the surveyed population had poor knowledge regarding CVS, self-regulating skills regarding digital screen and media devices.
Health promotion initiatives are recommended that incorporate healthy practices for digital device usage in daily life. These initiatives should focus on periodic checkups of refractive status, regular usage of optical aids as prescribed, address dry eye and incorporated the ‘20-20-20 rule’ during digital device usage.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 16 KB)
Acknowledgements
The authors would like to express sincere thanks to the research coordinators and assistant at King Khaled Eye Specialist Hospital: Ms. Sara AlNuwaysir, Maria Elena Pabillano, Sultan AlSubaie, for their contribution in this project. Authors acknowledge all the participants for their cooperation during this study.
Author contributions
Dr. AMJA, contributed in writing the proposal, data collection, writing the discussion, methodology, conclusion and abstract. Mr. MA, contributed in writing data collection, writing the introduction. Dr. AA, contributed in collecting data, writing the results, and conclusion. Dr. RK, contributed in reviewing the proposal, doing the statistical analysis, writing methodology, and reviewing the manuscript. Dr. SA-S, contributed in reviewing the proposal, collecting data, and reviewing the manuscript.
Funding
This manuscript did not receive any funding. No funding of any research relevant to the study.
Data availability
All data generated or analyzed during this study are included in this published article.
Declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose. None of the authors received any support and they have no financial involvement (e.g. employment, consultancies, honoraria, stock ownership and options, expert testimony, grants or patents received or pending, royalties) over the previous 3 years. None of authors have nonfinancial relationships (personal, political, or professional) that may potentially influence the writing of the manuscript.
Ethical approval
The study was approved by the Institutional Research Board (19th July 2020, P 0436-20) at King Khaled Eye Specialist Hospital. This study adhered to tenets of the Declaration of Helsinki.
Informed consent
Informed consent was electronically obtained after explaining the aims of the study to all subjects who participated in the study. Participants are aware that all collected data will be published.
Consent to publish
This manuscript does not contain any individual’s data in any form (including any individual details, images or videos).
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36471221 | PMC9734945 | NO-CC CODE | 2022-12-14 23:28:31 | no | Int Ophthalmol. 2022 Dec 5;:1-9 | utf-8 | Int Ophthalmol | 2,022 | 10.1007/s10792-022-02593-y | oa_other |
==== Front
Int Ophthalmol
Int Ophthalmol
International Ophthalmology
0165-5701
1573-2630
Springer Netherlands Dordrecht
36471221
2593
10.1007/s10792-022-02593-y
Original Paper
Population perceived eye strain due to digital devices usage during COVID-19 pandemic
Almalki Ashwaq M. [email protected]
12
Alblowi Mohammed [email protected]
3
Aldosari Ayat M. [email protected]
12
http://orcid.org/0000-0002-3925-1005
Khandekar Rajiv [email protected]
14
http://orcid.org/0000-0002-1070-7232
Al-Swailem Samar A. [email protected]
[email protected]
1
1 grid.415329.8 0000 0004 0604 7897 Research Department, King Khaled Eye Specialist Hospital, 2775 AlUrubah Road, Umm AlHammam AlGharbi, Unit 2, P.O. Box 7191, 11462 Riyadh, Saudi Arabia
2 grid.415254.3 0000 0004 1790 7311 Department of Ophthalmology, King Abdulaziz Medical City, Jeddah, Saudi Arabia
3 Optometry Division, Medical Staff Department, King Khalid Eye Specialist Hospital, Riyadh, Saudi Arabia
4 grid.17091.3e 0000 0001 2288 9830 Department of Ophthalmology, Faculty of Medicine, University of British Columbia, Vancouver, Canada
5 12 2022
19
23 1 2022
12 11 2022
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Purpose
To assess the magnitude severity and determinants of eyestrain and the use of digital devices in a Saudi population during the COVID-19 pandemic lockdown.
Methods
This web-based survey was conducted in September 2020 and enrolled only Saudi nationals 15 years or older. Data were collected on demographics, eye strain related symptoms, severity, and the use of optical aids during the COVID-19 lockdown. The frequency and severity of eye strain were calculated. A Computer Vision Syndrome (CVS) score was graded as none/mild moderate and severe, based on the sum of 15-eye strain related signs and symptoms. Correlation analysis was performed for determinants of CVS.
Results
The study sample was comprised of 2009 individuals with median age of 20 years. Among those who used digital devices for more than 6 h daily, the main reasons for use were work and social purposes among 68.4%, and 61% of respondents, respectively. The prevalence of knowledge on CVS and the ’20-20 rule for using digital devices’ was 9.4% and 6.9, respectively. The most common symptoms of eye strain from digital device usage were headache, burning, itching, tearing, and redness of eyes. Six hours of daily usage of digital devices was positively associated to the grade of eye strain severity during the COVID-19 lockdown (P < 0.05)).
Conclusion
The Saudi population experienced eye strain during COVID-19 lockdown due to excessive digital devices usage. Longer duration of digital device usage was associated to eye strain. Health care providers should educate the general population on measures to mitigate eye strain due to digital devices.
Trial registration ID None applicable.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10792-022-02593-y.
Keywords
Computer vision syndrome
Visual problems
Digital devices
Digital eye strain
COVID-19
Eye strain
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pmcIntroduction
After nearly 100 years since the Influenza pandemic, the human population faced the COVID-19 pandemic in 2020 [1, 2]. To prevent high hospitalization rates and mortality, global health organizations recommended personal hygiene, social distancing and restricted mobility especially among high-risk groups [3]. Fortunately, there were alternatives to remain in contact with others by using digital devices such as computers, mobile phones and tablets. [4]. Prior to the pandemic, the estimated utilization of daily computer use was 75% [5, 6].
Factors that cause eye strain include, working with digital devices for a long time, poor illumination, usage at less than the recommended distances and not using the required visual aids for clear vision [7]. Eye strain from digital devices is called Computer Vision Syndrome (CVS) or digital eye strain (DES). CVS is defined as “a complex of eye and vision problems related to near work experienced during prolonged computer, tablet, e-reader and cell phone use” [8].
To combat the pandemic in Saudi Arabia, schools and colleges were initially closed and there was a subsequent transition to online education. This transition often resulted in an excessive use of internet platforms for schoolwork and homework. In the professional environment, many jobs transitioned to an online model mainly using videoconferencing. Thus, the risk of eye strain in the Saudi population increased during the lockdown and pandemic.
Prior to the pandemic, the prevalence of eye strain due to CVS among young Saudi students was 69.8%. [9]. More time spent on computers and digital devices was also found to be a risk factor for CVS. Thus, CVS in the Saudi population was likely to increase during the COVID-19 pandemic. During the period of COVID-19 lockdown, two studies were conducted to study the prevalence of CVS, it’s associated risk factors and common related symptoms associated with the prolonged use of electronic devices perceived signs and symptoms of CVS among the Saudi population aged 18–20 years or older [11, 12]. Known determinants of CVS include female gender, longer duration of work, type of work, refractive status and compliance to spectacle wear [10–13].
This study investigates the scoring for responses of the same CVS Questionnaire, the prevalence of knowledge of CVS and determinants of eyestrain among the Saudi population aged 15 years or older, during the same period.
Materials and methods
A cross-sectional survey was performed in September 2020. The study was approved by the Institutional Research Board (P 0436-20) and adhered to the tenets of the Declaration of Helsinki. Informed consent was electronically obtained from all participants after explaining the aims of the study. For children under 16 years of age, an electronic signature of the parent or legal guardian was obtained.
The study population was comprised of Saudi nationals 15 years or older who had access to digital devices during the study period. Sample size calculations, we assumed that there were 10 million Saudis (15 years or older) using digital devices. Previous literature indicated that the prevalence of eye strain during the COVID-19 pandemic and excessive use of digital devices would be 67.8% [14]. To achieve 95% confidence interval and 3% acceptable error margin with clustering factor of 2, at least 1,864 participants were required for the survey. To compensate for the incomplete data we increased the sample by 10%. Thus, the final sample for the proposed survey was 2,050 Saudi aged 15 years or older. Stat calculator to calculate the sample size for a cross-sectional study [15]. Subjects were excluded if they refused to participate in the study, were not able to complete survey data, had chronic ophthalmic diseases that resulted in vision that could not be fully corrected by spectacles or contact lenses (e.g. diabetic macular edema, macular scar, advanced glaucoma, etc.).
To quantify digital eye strain, the Computer Vision Syndrome Questionnaire (CVS) was used in this study [14]. The CVS has acceptable psychometric properties, making it a valid and reliable tool to control for the visual health of workers who use computer terminals and this survey is appropriate for clinical trials and outcomes research [16].
The survey tool was a web-based questionnaire, which was designed by a research coordinator using a Google form. Investigators and a research coordinator used “Research Survey Invitation e-mail account” to invite all researchers at King Khaled Eye Specialist Hospital (KKESH) to participate in this study. Investigators invited people to participate by posting a link in different social platforms. Both English and Arabic version links were distributed. The survey remained open for a period of 2 weeks. The survey collected data on the profile of participant’s COVID-19/quarantine status, refractive status from pre-existing ophthalmic reports, habitual optical aid usage and usage of digital devices. Data were also collected on the purpose of using digital devices, frequency of digital device usage, duration spent on a digital device, symptoms during digital device usage at least half of the time over the previous week [17]. The behavior and status of optical aid usage was assessed as was the knowledge about the ‘20-20-20 rule’ for using digital devices.
There were 15 questions on eye strain signs and symptoms. For each question, the response choices were never, sometimes and always. Those with signs and symptoms further graded their problem as mild, average and severe (Supplementary Material: 1). According to the American Academy of Ophthalmology, digital device-related eye strain could present as patient complaints of visual blur, achy and tired eyes, dry eyes, or tearing and stinging [12].
Scoring for responses was as follows: (A) frequency of signs/symptoms, never = 0, sometimes = 1, always = 2; (B) severity of sign and symptoms, mild = 1, average = 2 and severe = 3. For each sign and symptom, the total score was calculated using a formula score of A X B. The sum of 15 eye strain related signs and symptoms score was further graded as < 30 = no or mild CVS, 30 to 59 = moderate CVS and more than 60 = severe CVS. To associate the CVS severity to different determinants we grouped the score into no or mild eye strain and moderate to severe eye strain.
The data were transferred into an Excel spreadsheet (Microsoft Corp., Redmond, WA, USA). After consistency checks and coding, it was transferred to Statistical Package for Social Sciences (SPSS 26; IBM Corp., Armonk, NY, USA). Qualitative data are presented as number and percentage. The eye strain scores are presented as median and interquartile range (IQR). The grade of eye strain was associated to determinants and for two subgroups, a 2 × 2 table was used to estimate the Student T test and calculate the Odd’s ratio, the 95% confidence interval (CI) and a two-sided P value. For more than 3 subgroups, the chi-square value was calculated along with the degrees of freedom and two-sided P value. P values less than 0.05 were considered statistically significant.
Results
The study sample was comprised of 2,009 participants with median age 20 years (IQR: 18; 22). Table 1 presents the profile of the study sample.Table 1 Profile of refractive status and usage of digital devices among surveyed Saudi participants
Number Percentage
COVID-19 status Positive
Negative
Don’t know
282
1727
0
14.0
86.0
0
Quarantine status Quarantined
No
Missing
223
932
854
11.1
46.4
42.5
Use of spectacles Spectacles for Clear Vision
Contact lens cosmetic
Spectacles and contact lens
No contact lens or spectacles
393
59
55
1502
19.6
2.9
2.7
74.8
Purpose of visual aids Spectacle for reading
Spectacle for distance
Spectacle for both
Missing
72
222
231
1484
3.6
11.1
11.5
73.9
Last optical check up Within 1 year
1 to 2 year
More than 2 years
Not applicable
79
61
1476
393
3.9
3.0
73.5
19.6
Duration of using optical aids (hours in week) 1–2 times in the week
3 times or more in a week Daily
Other
Daily
79
61
1476
393
3.9
3.0
73.5
19.6
Using make up 1 Daily
1–2 times in the week
3 times or more in a week
Not using
60
100
45
1804
3.0
5.0
2.2
89.8
Purpose of using digital devices Work only
Social
Contact
Both
Other
23
485
0
1375
126
1.1
24.1
0.0
68.4
6.3
Duration of digital devices usage Less than 2 h
2–6 h
More than 6 h
140
644
1225
7.0
32.1
61.0
Two hundred and eighty-two (14%) participants were diagnosed with COVID-19, and 223 (11.1%) were quarantined. Three-fourths of participants did not use contact lens or spectacles, 393 (19.6%) used spectacles, 59 (2.9%) used contact lens and 55 (2.7%) used both spectacles and contact lens.
There were 1476 (73.5%) participants who had not undergone an optical checkup in the prior 2 years. Duration of optical aid usage differed between participants, ranging from 1–2 times a week (3.9%) to daily (19.6%). The purpose of using digital devices varied between participants as follows: work only (1.1%), social (24.1%) or both (68.4%). The number of hours spent on digital devices varied among participants, with the majority (61.0%) using them for more than 6 h.
The prevalence of knowledge of CVS was 9.4% (95% CI 8.1; 9.6), and the prevalence of knowledge of the ‘20-20-20 rule’ for using digital devices was 6.9% (95% CI 5.8; 8.0).
Most participants experienced headaches, burning, itching, tearing and redness of eyes related to eye strain from digital devices usage (Table 2).Table 2 Signs and symptoms of eye strain related to using digital devices as perceived by survey participants
Title Always Sometimes Never Score
Severe Average Severe Average Median (IQR)
1 Burning 35 176 58 1226 514 2.0 (0.0; 2.0)
2 Itching 69 168 96 1267 409 2.0 (0.0; 2.0)
3 Foreign body sensation 54 100 37 835 983 0.0 (0.0; 2.0)
4 Tears (watering) 144 263 58 1145 399 2.0 (0.0; 2.0)
5 Excessive blinking 50 108 34 711 1105 0.0 (0.0; 2.0)
6 Redness 92 123 74 986 734 2.0 (0.0; 2.0)
7 Eye pain 55 106 67 877 906 0.0 (0.0; 2.0)
8 Drooping eyelids 47 74 33 592 1263 0.0 (0.0; 2.0)
9 Dryness of eyes 74 101 36 685 1113 0.0 (0.0; 2.0)
10 Blurring of vision 98 87 60 740 1024 0.0 (0.0; 2.0)
11 Double vision 40 52 33 484 1400 0.0 (0.0; 2.0)
12 Difficulty in focusing near object 101 81 55 820 1052 0.0 (0.0; 2.0)
13 Intolerance to light 174 143 75 702 915 0.0 (0.0; 2.0)
14 Seeing colored halos 62 54 16 530 1347 0.0 (0.0; 2.0)
14 Feeling of worsening eyesight 99 80 50 759 1021 0.0 (0.0; 2.0)
15 Headache 250 195 170 992 402 2.0 (0.0; 4.0)
The median eye strain symptom score was 20 (IQR 10: 32). ‘No/ mild’ grade of eye strain was reported by 1,486 (74%), moderate eye strain by 468 (23.3%) and severe eye strain by 55 (2.7%) participants. Table 3 presents the determinants of eye strain. Longer than 6 h of digital device usage per day was statistically significantly positively associated to the grade of eye strain severity (P < 0.001).Table 3 Determinants of eye strain due to the digital devices usage during COVID-19 among adult Saudi surveyed participants
Eye strain of moderate to severe grade (N = 527) No/mild grade of eye strain (N = 1488) Validation
Number Percentage Number Percentage
Age group < 30 years 491 93.2 1379 92.7 OR = 1.3 (95% CI 0.8: 1.9) P = 0.26
31 and older 29 5.5 104 7
COVID status Yes 73 13.9 193 13 OR = 1.2 (95% CI 0.9: 1.7) P = 0.15
No 394 74.8 1290 86.7
Don’t know 60 11.4 5 0.3
Quarantined Yes 60 11.4 154 10.3 OR = 1.1 (95% CI 0.8: 1.6) P = 0.5
No 234 44.4 666 44.8
Missing 233 44.2 668 44.9
Digital devised used for Work only 9 1.7 13 0.9 χ2 = 1.6
Social 116 22 353 23.7 Df = 3
Both 315 59.8 1024 68.8 P = 0.2
Other 27 5.1 93 6.3
Missing 60 11.4 5 0.3
Type of visual aid usage Spectacles for Clear Vision 115 21.8 256 17.2 χ2 = 12
Contact lens cosmetic 12 2.3 45 3 Df = 3
Spectacles and contact lens 16 3 38 2.6 P < 0.001
No contact lens or spectacles 324 61.5 1144 76.9
Missing 60 11.4 5 0.3
Visual aid used for Spectacle for reading 17 3.2 51 3.4 χ2 = 2.3
Spectacle for distance 66 12.5 151 10.1 Df = 3
Spectacle for both 74 14 138 9.3 P = 0.12
Missing 370 70.2 1148 77.2
Visual aid checking done In last one year 124 23.5 316 21.2 χ2 = 0.36
1–2 years 45 8.5 93 6.3 Df = 3
More than 2 years 114 21.6 317 21.3 P = 0.54
Not applicable 244 46.3 762 51.2
Discussion/Conclusion
CVS is a rising public health issue related to continuous use of technology (computers, cell phones and tablets) and is a significant factor in reducing quality of life and workplace productivity [18]. Similar to previous two Saudi studies, which recruited elder participants during the period of COVID-19 lockdown, current study confirmed the excessive use of digital devices among most of the participants [11, 12]. Unlike previous two studies, we defined clearly how and what scoring system used to assess the severity of CVS [11, 12]. Another differences were the very poor use of optical aids (25.5%) by our younger participants when compared with those in the previous two studies [11, 12]. Additionally there was very poor regular checks of refractive status of our participants. Very few participants in the current study had COVID-19.
Alabdulkader reported a high incidence of digital eye strain (75%) during the period of COVID-19 lockdown among the Saudi participants 18 years or older [11]. The outcomes of the current study indicate that nearly one-fourth of Saudi participants 15 years or older had symptoms of moderate to severe eye strain. Almarzouki et al. reported higher rate (44%) of sever eye strain among the Saudi participants 20 years or older during the same period [12].
In this study, young participants had a very poor knowledge of CVS and the ‘20-20-20 rule’ for working with digital devices. Similar to a previous study, working with digital devices for more than 6 h was positively associated with the presence of signs and symptoms of eye strain (P < 0.001) [11].
The currents study enrolled a large sample of participants and represents a sample of convenience for assessing digital device usage among Saudis aged 15 years and older. Although this sample may not be representative of the entire adult Saudi population, the findings reflect the habits of the population facing lockdown and forced to overuse digital devices for their business and/or personal use including entertainment, communication and education. The vision/ eye health impact of digital device abuse requires healthcare providers to educate patients on incorporating healthy vision practices among the general population.
In the current study, only 9.4% of participants had adequate knowledge of CVS and only 7% knew about the ‘20-20-20 rule’ for using digital devices. These outcomes were much lower than the proportion of Saudi medical students (91.35%), and Indian students (34%) who knew about CVS [17, 18]. In addition, Alabdulkader found that 32% of the elder Saudi participants were aware of the 20-20-20 rule, only 13% of these participants practiced it, and 50% reported that they practiced it occasionally [11]. The higher level of knowledge in previous studies could be attributed to the high educational level of the participants with a medical education background [19, 20].
Nearly two thirds of participants in our study used digital devices for professional and social interactions. A previous study also noted increased digital devices usage in the era of COVID-19 for professional and other purposes [21].
We found that the compliance for using visual aids among participants was 3.6%, 11.1% and 11.5% for reading, distance viewing and both, respectively. This was much lower than the projected number of individuals with refractive error in this age group of Saudis. The prevalence of refractive error among 16 to 39-year-old Saudis was reported to be 45.8% as follows; 24.4% myopes,11.9% hyperopes and 9.5% astigmatism [22]. Another study reported refractive error as high as 55.5% among Saudi adolescents [23]. The prevalence of refractive error among 20–60-year-old Saudis was reported to be 75,2% as follows; 41.2% myopes,12.1% hyperopes and 20.9% astigmatism [12]. Thus, the risk of eye strain will be elevated in a population with a high prevalence of refractive error and low compliance for optical aids [11]. Additional determinant factors with the symptoms severity score reported in other Saudi studies included the number of devices used; the use of rewetting drops [11].
In our study, 73.5% participants did not undergo optical checkups for more than 2 years and used optical aids sparingly. This could also contribute to ocular strain symptoms. We concur with previous studies that urgent action is warranted to improve compliance with spectacle wear and contact lens usage to address eye stain [24, 25].
In the present study, all participants were using digital devices and majority of them reported eye strain related symptoms and signs. The most common symptoms associated with digital devices eye strain are headaches, blurred vision, dry eyes, pain in the neck, and shoulders [8]. Our outcomes concur with a previous study that reported 62.1% of Saudi medical students had similar signs and symptoms of eye strain [26]. Another study has also reported a high prevalence of eye strain in Pakistan (90.4%) [27]. Another study done in India reported a 82.4% prevalence of eye strain among medical and engineering students [26]. The high prevalence of eye strain reported in the present study can be explained by a shift towards excessive use of digital devices during the COVID-19 lockdown. Bahkir et al. also found that 93.6% of participants had an increase in their screen time since the lockdown and 56.5% reported increased frequency and intensity of symptoms since the lockdown [20].
Headache was the most commonly reported internal symptoms and the burning sensation with itching were the main external symptoms. However, the majority of reported symptoms were mild. Previous study have also reported headache as the main symptom of eye strain [20, 28]. Headache can be due to prolonged use of digital devices. External symptoms of CVS like burning, irritation, redness and tearing are related to dry eye and the internal symptoms of strain, and headache are linked to accommodative and/or binocular vision stress [7]. They can also be attributed to uncorrected refractive errors or exposure to a continuous bright light for extended periods.
Extended periods of digital device usage (> 6 h) seem to be a significant risk factor for eye strain in the current study. Other studies from Saudi Arabia reported defined extended duration of digital device usage as more than 4 h and still reported high rates of eye strain [12, 29–31]. This relationship between the duration of digital devices usage and eye strain has prompted some experts to suggest a reduction in the number of hours spent in front of computers and other devices to mitigate the risk of serious visual problems [20, 26]. Hence, they recommend public health initiatives directed at the general population on good practices for digital device usage. Taking breaks during electronic use, viewing computers at appropriate distance, and the use of screen protectors were significant practices to relive the eye symptoms severity score [11].
In the current study, very few participants had COVID-19. Hence, we could not test for an association of this disease and eye strain. The American Academy of Ophthalmology reports that 1–3% of people with confirmed COVID-19 may have conjunctivitis, either as an initial presenting sign or during advanced stage of the disease [32]. Some common ocular symptoms recorded in patients with conjunctivitis and confirmed COVID-19 infection include itching, redness, tearing, discharge, and foreign body sensation [32–34]. It will be interesting to study the additive impact of COVID-19 infection on eye strain due to excessive digital devices usage during the lockdown.
There are some limitations to the present study including the cross sectional survey design that precluded an establishment of eye strain to known risk factors. Therefore, we recommend judicious interpretation of a causal association of eye strain to risk factors in the current study. The sample size may not be representative of the entire adult Saudi population as the reported symptoms were subjective, self-reported should not be compared by studies based on objective measurements of eye strain.
During the COVID-19, pandemic outdoor activities were limited for children and they spent more time using digital devices for educational purposes and social interactions. Hence, they are vulnerable to a potential eye health effect. We recommend that future studies investigate school children for the magnitude and determinants of eye strain during lockdown. It will also be interesting to study the impact of public awareness campaigns for safe use of digital devices on vision.
Conclusion
The study provides evidence that a significant proportion of the Saudi population is affected by CVS during the COVID-19 lockdown due to abuse of digital devices usage. The digital devices usage varied for work or social interactions. Longer use of digital device usage seems to influence increased symptoms of CVS and severity. The majority of the surveyed population had poor knowledge regarding CVS, self-regulating skills regarding digital screen and media devices.
Health promotion initiatives are recommended that incorporate healthy practices for digital device usage in daily life. These initiatives should focus on periodic checkups of refractive status, regular usage of optical aids as prescribed, address dry eye and incorporated the ‘20-20-20 rule’ during digital device usage.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 16 KB)
Acknowledgements
The authors would like to express sincere thanks to the research coordinators and assistant at King Khaled Eye Specialist Hospital: Ms. Sara AlNuwaysir, Maria Elena Pabillano, Sultan AlSubaie, for their contribution in this project. Authors acknowledge all the participants for their cooperation during this study.
Author contributions
Dr. AMJA, contributed in writing the proposal, data collection, writing the discussion, methodology, conclusion and abstract. Mr. MA, contributed in writing data collection, writing the introduction. Dr. AA, contributed in collecting data, writing the results, and conclusion. Dr. RK, contributed in reviewing the proposal, doing the statistical analysis, writing methodology, and reviewing the manuscript. Dr. SA-S, contributed in reviewing the proposal, collecting data, and reviewing the manuscript.
Funding
This manuscript did not receive any funding. No funding of any research relevant to the study.
Data availability
All data generated or analyzed during this study are included in this published article.
Declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose. None of the authors received any support and they have no financial involvement (e.g. employment, consultancies, honoraria, stock ownership and options, expert testimony, grants or patents received or pending, royalties) over the previous 3 years. None of authors have nonfinancial relationships (personal, political, or professional) that may potentially influence the writing of the manuscript.
Ethical approval
The study was approved by the Institutional Research Board (19th July 2020, P 0436-20) at King Khaled Eye Specialist Hospital. This study adhered to tenets of the Declaration of Helsinki.
Informed consent
Informed consent was electronically obtained after explaining the aims of the study to all subjects who participated in the study. Participants are aware that all collected data will be published.
Consent to publish
This manuscript does not contain any individual’s data in any form (including any individual details, images or videos).
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734947 | NO-CC CODE | 2022-12-14 23:28:31 | no | Orth Unfallchir. 2022 Dec 6; 12(6):3 | latin-1 | null | null | null | oa_other |
==== Front
Arch Gynecol Obstet
Arch Gynecol Obstet
Archives of Gynecology and Obstetrics
0932-0067
1432-0711
Springer Berlin Heidelberg Berlin/Heidelberg
36480033
6877
10.1007/s00404-022-06877-7
Gynecologic Endocrinology and Reproductive Medicine
Sexual function in heterosexual couples undergoing assisted reproductive technology (ART) cycles with donor sperm
Le Goff Juliette 1
Reignier Arnaud 12
Mirallie Sophie 1
Dubourdieu Sophie 1
Barrière Paul 12
http://orcid.org/0000-0002-7243-7709
Fréour Thomas [email protected]
123
Lefebvre Tiphaine 1
1 grid.277151.7 0000 0004 0472 0371 Service de Médecine et Biologie de la Reproduction, Hôpital Mère et Enfant, CHU de Nantes, 38 Boulevard Jean Monnet, Nantes, France
2 grid.277151.7 0000 0004 0472 0371 Center for Research in Transplantation and Translational Immunology, UMR 1064, Nantes Université, CHU Nantes, INSERM, 44000 Nantes, France
3 grid.410458.c 0000 0000 9635 9413 Department of Obstetrics, Gynecology and Reproductive Medicine, Dexeus University Hospital, Barcelona, Spain
8 12 2022
18
9 8 2022
29 11 2022
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Purpose
Sexuality and the desire for children are closely linked, and infertility can increase the risk of sexual dysfunction (SD). Among heterosexual infertile couples undergoing assisted reproductive technology (ART) cycles, those referred for donor sperm cycles constitute a specific subgroup, potentially different than those undergoing ART with partner’s sperm, as giving up on biological parenthood can be difficult to overcome. However, the impact of donor sperm ART on infertile couples’ sexuality has been hardly explored in the literature. This study aimed to describe the sexual function in couples undergoing ART with donor sperm.
Methods
This monocentric prospective observational study was conducted in heterosexual couples undergoing ART cycle with sperm donor, using the FSFI and the IIEF15 questionnaires. Seventy-nine couples were solicited to participate in the study.
Results
In our sample, 39.3% (n = 24) of women had sexual dysfunction (SD). Among men, 26.5% (n = 13) had erectile dysfunction (ED). No statistically significant difference was found between both groups (with or without SD) in men and women in univariate analysis. Therefore, multivariate analysis was not performed and no specific predictor of SD could be identified.
Conclusion
Although this should be confirmed in a larger number of participants, our study demonstrates that a significant proportion of infertile patients undergoing ART with donor semen suffer from SD. No significant predictor could, however, be identified. Further research should focus on the evaluation of psychological interventions to treat or improve these disorders.
Keywords
Sexuality
Infertility
Erectile dysfunction
Sexual dysfunction
Sperm donor
==== Body
pmcWhat does this study add to the clinical work
"A significant proportion of infertile patients undergoing ART with donor semen suffer from Sexual Dysfunction, but no significant predictor could however be identified in this study".
Introduction
An increasing number of couples face infertility. Although many of them will achieve childbearing, the diagnosis of infertility, as well as subsequent infertility care, are very likely to affect their quality of life [1]. Infertility can indeed lead to a feeling of physical and/or psychological aggression due to the diagnosis, the therapies, but also the repeated failures [1], which can trigger feelings of injustice or anger. Infertility and its treatments may also lead to changes in self-esteem and are associated with anxiety and sadness [2]. Low self-esteem has been shown to increase stress levels during treatment [3].
“Healthy sexuality is essential for psychological well-being and quality of life” according to the World Health Organization [4]. As sexuality and the desire for children may be linked, infertility can lead to dissociating sexuality from sexual desire and pleasure [5] with an increased risk of sexual dysfunction (SD) diagnosed when the disturbances in sexual functioning described by the patient cause marked subjective suffering. A significant impact on sexual life was reported with 21% of patients reporting an absence of sexual intercourse for several weeks or even months [6]. It has been reported that as much as 32% of women and 23% of men show signs of depression with sexual desire disorders resulting from the discovery of infertility and its management [7]. Men often associate fertility with virility [8]. The prevalence of erectile dysfunction (ED) appears to be higher in men with infertility [7]. After diagnosis of impaired semen parameters, 11% of erectile or orgasmic problems were reported [9], and male sexual satisfaction scores were lower compared to men in couples with female factor infertility [10]. The prevalence of SD in women in infertile couples also appears to be higher than in the general population [7]. Women whose male partner suffers from severe infertility seem to have a decrease in satisfaction during sexual intercourse [11]. The announcement of azoospermia can be a devastating experience and men with infertility will feel stigmatized because they are perceived as being deficient in a specific component of their masculinity [12].
Surprisingly, the impact on the sexuality of couples resorting to donor conception has been hardly explored in the literature. In a small cohort of 16 couples, men reported a period of impotence and a decrease in the number of sexual encounters following the diagnosis, and women experienced anger for a short period of time, but without any decrease in the frequency of sexual encounters [13]. In contrast, Reder et al. [14] reported a higher frequency of sexual desire disorders in couples enrolled in autologous ART compared to those in intrauterine insemination with donor sperm (IUI-D). Among the numerous scientific questionnaires available in the literature to assess human sexuality, the Female Sexual Function Index (FSFI) and the International Index of Erectile Function (IIEF) appear to be the most relevant ones.
This preliminary study aimed to describe sexual function in couples undergoing ART with donor sperm and to determine which demographic characteristics or medical covariates were associated with SD.
Patients and methods
This monocentric prospective observational study was conducted in heterosexual couples undergoing ART cycle with sperm donation, either in vitro fertilization (IVF) or intra-uterine insemination (IUI) in our University-based ART center between October 2019 and October 2021. Of note, inclusions were suspended for several months due to the closure of the center in the context of the COVID-19 epidemic. All couples with women aged between 18 and 43 years who referred for donor sperm-assisted reproduction were solicited. Oral informed consent was obtained from all individual participants included in the study. Exclusion criteria were pre-existing sexual disorders unrelated to diagnosis or medical management or oral opposition by the patients when the study is offered to them. The study was approved by the local ethics committee GNEDS (Groupe Nantais d’Ethique dans le Domaine de la Santé).
Male and female demographic characteristics were first recorded. Of note, primary–secondary infertility refers to couples with a history of early pregnancy loss without live birth. An anonymous questionnaire was distributed to all eligible couples via the Sphinx software. It included the FSFI questionnaire for women and the IIEF15 questionnaire for men. We chose the Female Sexual Function Index (FSFI) and the International Index of Erectile Function (IIEF) because these questionnaires are often used in studies of sexuality and ART. In addition, they are short, adapted to our study, and easily interpretable. Both questionnaires are scientifically validated. The questionnaires are validated in French. [15–19].
The FSFI consists of 19 questions investigating 6 areas of female sexual function over the past 4 weeks: desire, lubrication, arousal, orgasm, satisfaction, and pain. Scores range from 0 or 1 to 5 for each question. Each domain is given its own coefficient. The scores for each area are then added together to give a total score between 2 and 36. SD is defined by a score below 26.55 with a specificity of 0.73 and a sensitivity of 0.88 [17]. The IIEF-15 explores male sexual function over the past 4 weeks through 15 questions with 5 or 6 answer choices and grouped into 5 domains: erectile function, orgasm, desire, satisfaction during sex, and overall satisfaction. There is a score per dimension but no overall score, unlike FSFI. The IIEF-15 scores increase with the improvement in the patient's sexuality components. Questions 1–5 and question 15 assess erectile function. According to Cappelleri et al. [19], an Erectile Function (EF) score ≤ 25 out of 30 for these six questions defines erectile dysfunction (ED) with good sensitivity and specificity (Se 0.97 and Sp 0.88). ED severity was then classified into five categories: no ED, mild, mild to moderate, moderate, and severe.
All analyses were performed using Excel version 2019 and/or BiostaTGV online. We first performed a descriptive analysis of the data. Qualitative variables (smoking status, infertility type and etiology, ART protocol, frequency of sexual intercourse) were described by counts and percentages. Quantitative variables were described with means and standard deviation (age, BMI, FFSI score, and IIEF15 domains). To search for independent predictive factors of SD, we divided the male and female populations into two groups (with or without SD) and performed univariate comparative analyses by Fischer's exact test, followed by multivariate analysis when appropriate. A p value < 0.05 was considered statistically significant.
Results
Characteristics of the population
Seventy-nine couples were initially solicited to participate in the study. Sixty-one female questionnaires were finally collected, representing a participation rate of 77.2%, and fifty male questionnaires representing a participation rate of 63.3%. The characteristics of the population are presented in Table 1. Among the respondents, the majority of women reported having sex 1–3 times per month, while men reported having sex 1–2 times per week.Table 1 Characteristics of the population
Variables MD Men MD Women
N = 50 N = 61
Age 0 0
≤ 30 years old 9 (18%) 21 (34.4%)
31–40 years old 39 (78%) 38 (62.3%)
> 40 years old 2 (4%) 2 (3.3%)
BMI (kg/m2) 0 24.8 ± 3.65 0 24.8 ± 5.40
Smoking 0 0
Active smoking 11 (22%) 6 (9.8%)
Smoking cessation 18 (63%) 17 (27.9%)
No smoking 21 (24%) 38 (2.36%)
Infertility duration 2 1
1–3 years 24 (48%) 28 (45.9%)
4–6 years 16 (32%) 21 (34.4%)
7–9 years 3 (6%) 8 (13.1%)
> 10 years 5 (10%) 3 (4.9%)
Infertility 0 0
Primary 44 (88%) 44 (72.1%)
Secondary 4 (8%) 11 (18%)
Primary–secondary** 2 (4%) 6 (9.8%)
Etiology 1 0
Azoospermia 34 (68%) 45 (73.8%)
Autologous ART failure 10 (20%) 12 (19.7%)
Genetic or incurable disease 5 (10%) 4 (6.6%)
ART protocol 0 0
IUI with sperm donation 47 (94%) 57 (93.4%)
IVF with sperm donation 3 (6%) 4 (6.6%)
Status of infertility care 2 1
Waiting for first cycle, not yet started 11 (22%) 18 (29.5%)
Currently undergoing ART 37 (74%) 42 (68.9%)
Number of previous ART cycles* 2 N = 37 0 N = 42
1 17 (45.9%) 15 (35.7%)
2–3 8 (21.6%) 9 (21.4%)
4–9 9 (24.3%) 15 (35.7%)
10 and more 1 (2.7%) 3 (7.1%)
Missing data 2 (5.4%) 0
Frequency of sexual intercourse 0 1
Never 0 (0%) 0 (0%)
< 1 per month 1 (2%) 3 (5%)
1–3 per month 24 (48%) 23 (38.3%)
1–2 per week 21 (24%) 29 (48.3%)
> 2 per week 4 (8%) 5 (8.3%)
Data are presented as mean ± standard deviation or as number (percentage)
MD missing data
*Among patients undergoing sperm donation treatment
**Primary–secondary infertility refers to couples with a history of early pregnancy loss without live birth
FSFI and IIEF scores
In our sample, 39.3% (n = 24) of women had SD, defined as a FSFI score < 26.55. The average score was 27.5 ± 5.6. Among men, 26.5% (n = 13) had ED according to the IIEF15 erectile function domain analysis. One participant did not answer three out of fifteen questions, so his total IIEF-15 score was not usable; the statistics are calculated on a total of forty-nine men. The average for each domain of FSFI and IIEF-15 scores analyzed is presented in Table 2.Table 2 Average score of FSFI domains and IIEF15 domains
Areas Average score
FSFI score Desire (/10) 6.3 ± 1.6
Excitement (/20) 14.3 ± 3.7
Lubrication (/20) 17.4 ± 3.7
Orgasm (/15) 11.1 ± 3.6
Satisfaction (/15) 11.9 ± 2.9
Pain (/15) 12.6 ± 3.1
Total (/36)* 27.5 ± 5.6
IIEF15 domains Erectile function** (score /30) 26.8 ± 5.3
No ED (26–30) 36 (73.5%)
Light ED (22–25) 7 (14%)
Mild to moderate ED (17–21) 3 (6.1%)
Moderate ED (11–16) 2 (4.1%)
Severe ED (1–10) 1 (2%)
Orgasm (/10) 8.8 ± 2.0
Desire (/10) 7.6 ± 1.3
Sexual satisfaction (/15) 10.8 ± 3.0
Overall satisfaction (/10) 8.2 ± 2.2
Total score (/75) 62.3 ± 10.9
Data are presented as mean ± standard deviation and n (%);
ED erectile dysfunction
*After multiplying each domain by its ratio
**Score according to Capparelli classification
Comparison of populations with and without sexual dysfunction
The comparison of general characteristics between the groups “with SD” and “without SD” is presented in Table 3. No statistically significant difference was found between both groups in men and women in univariate analysis. Therefore, multivariate analysis was not performed and no specific predictor of SD could be identified.Table 3 Comparison of men with or without erectile dysfunction (ED) and women with or without sexual dysfunction (SD)
Male score p value Male score
Variable MD EF ≤ 25
N=13 EF > 25
N = 36 MD FSFI < 26.55
N=24 FSFI > 26.55
N=37 p value
Age 0 0
≤ 30 years old 2 (15.4%) 7 (19.4%) 0.99 6 (25%) 15 (40.5%) 0.27
31–40 years old 10 (76.9%) 28 (77.8%) 0.99 17 (70.8%) 21 (56.8%) 0.29
> 40 years old 1 (7.7%) 1 (2.8%) 0.46 1 (4.2%) 1 (2.7%) 0.99
BMI (kg/m2) 0 25.0 ± 4.8 24.7 ± 3.3 0.81 0 24.4 ± 5.6 25.0 ± 5.35 0.68
Duration of infertility 1/1 4.4 ± 3.1 4.28 ± 2.7 0.90 0/1 3.7 ± 2.4 4.4 ± 2.69 0.25
1–3 years 6 (46.2%) 18 (50%) 0.99 10 (41.7%) 10 (27%) 0.28
> 3 years 6 (46.2%) 17 (47.2%) 0.99 14 (58.3%) 26 (70.3%) 0.28
Smoking 0 0
Active smoking 3 (23.1%) 8 (22.2%) 0.99 4 (16.7%) 2 (5.4%) 0.20
Smoking cessation 5 (38.5%) 13 (36.1%) 0.99 6 (25%) 11 (29.7%) 0.78
No smoking 5 (38.5%) 15 (41.7%) 0.99 14 (58.3%) 24 (64.9%) 0.79
Sexual intercourse 0 0/1
< 1 per month 1 (7.7%) 0 (0%) 0.27 2 (8.3%) 1 (2.7%) 0.56
1–3 per month 7 (53.8%) 16 (44.4%) 0.75 12 (50%) 11 (29.7%) 0.18
1–2 per week 5 (38.5%) 16 (44.4%) 0.76 7 (29.2%) 22 (59.5%) 0.02
> 2 per week 0 (0%) 4 (11.1%) 0.56 3 (12.5%) 2 (5.4%) 0.38
Infertility 0 0
Primary 13 (100%) 30 (83.3%) 0.17 17 (70.8%) 27 (73%) 0.99
Secondary 0 (0%) 4 (1.11%) 0.56 4 (16.7%) 7 (8.91%) 0.99
Primary–secondary 0 (0%) 2 (5.6%) 0.99 3 (12.5%) 3 (8.1%) 0.67
Etiology 0 0
Azoospermia 10 (76.9%) 24 (66.7%) 0.73 16 (66.7%) 29 (78.4%) 0.38
Autologous ART failure 3 (23.1%) 7 (19.4%) 0.99 4 (16.7%) 8 (21.6%) 0.75
Genetic disease 0 (0%) 5 (13.9%) 0.31 4 (16.7%) 0 0.02
Protocol 0 0
IUI-D 12 (92.3%) 34 (4.49%) 0.99 22 (91.7%) 35 (4.69%) 0.64
IVF-D 1 (7.7%) 2 (5.6%) 0.99 2 (8.3%) 2 (5.4%) 0.64
Status of infertility care 2 0/1
Not yet started 8 (61.5%) 28 (77.8%) 0.70 9 (37.5%) 9 (24.3%) 0.39
Currently undergoing ART 3 (23.1%) 8 (22.2%) 0.70 15 (62.5%) 27 (73%) 0.39
Results are presented as mean ± standard deviation or number (percentage)
MD missing data
Discussion
In this original study, we found a significant prevalence of ED (26.5%) and female SD (39.3%) among heterosexual couples undergoing ART cycles with sperm donation. Specifically, our study is the first to analyze the prevalence of ED in the context of sperm donation management.
Several studies evaluated sexology among infertile couples. The prevalence of SD detected by the FSFI questionnaire has been reported to range between 26 and 40% among women with infertility [20, 21]. The prevalence of ED observed in the literature ranges between 15 and 22% of men with infertility [7] and was 35% in azoospermic men [22]. A meta-analysis [23] reported a high prevalence of SD (43–90% in women and 48–58% in men). Many reasons are suggested to explain the observed association between SD and infertility: scheduled sexual intercourses, fear of involuntary childlessness, diagnosis of the infertility etiology.
Infertility could also be associated with premature ejaculation and occasional psychological anejaculation for 90% of men at some point in the management of infertility [7]. The prevalence of ED and premature ejaculation has been reported to be positively correlated with the severity of semen abnormalities in men with infertility [24]. According to the European Society of Sexual Medicine (ESSM), ED has been reported in 9–62% of male partners of infertile couples, with severe impairment observed in only 1–3% of ED cases [25]. Moreover, worse semen parameters have been associated with greater ED severity, and low sexual desire has been reported by one third of men of infertile couples [25]. However, in our study, the prevalence of SD was not significantly higher in the “azoospermia” group than in the “another cause” group.
Some studies found that fertile women had a higher FSFI score than women with infertility, the most common disorders being related to desire and lubrication [26]. In a study using the FSFI questionnaire [27], the proportion of females with SD was higher in the infertile versus control group (47% versus 30%, p value: < 0.001). Total orgasm, satisfaction, and pain scores were significantly lower in infertile versus control group [27]. The impact of the primary or secondary character seems contradictory with studies which find that the impact on sexuality was more severe when it came to primary infertility [28] and other studies which find a higher prevalence of SD in secondary women with infertility [29] with a decreased sexual desire, orgasm, and satisfaction compared with primary women with infertility.
Approximately a third of the survey respondents were not fully satisfied with their sexuality. This is in agreement with the literature [30]. We also observed that the frequency of sexual intercourse seemed lower in that population of infertile couples than that of the general population, which has been reported in France to 8.7 per month for both sexes or 1.5 per week on average [31].
Regarding the impact of ART treatment on sexual function, we found no significant difference between newly diagnosed couples awaiting treatment onset but not yet started, and those who already started ART cycles with sperm donation. Studies assessing the impact of the timing of treatment are discordant, probably due to small numbers and the heterogeneity scores used. According to Marci et al. [30], ED were more common in men with a recent diagnosis of infertility compared to the on-treatment group. Similarly, women in the newly diagnosed infertility group had poorer sexual function than those already included in the ART program. In contrast, Bayar et al. [32] reported a significant increase of SD in couples 3 months into treatment compared to the beginning of treatment. This needs further exploration in large-scale and long-term studies. In our study, we did not find a significant association between the duration of infertility and SD. According to a case–control study [33], a duration of infertility of 3 to 6 years was associated with a significant increase in marital conflict. In a recent study, as the number of years of infertility increased, the total score of FSFI was not significantly different but, using the multivariable logistic regression model, when the infertility duration was greater than 8 years, there was a significant increase in the incidence of female SD [34].
Sexuality disorders associated with infertility have, therefore, been widely studied. However, only one study focusing on oocyte recipient population explored sexual function and reported 47% of women with a FSFI score < 26.55 [35]. One study finds that, men using donor sperm expect more positive effects from parenthood on relationships and feelings of fulfillment, and report fewer negative effects of infertility on sexuality, compared with men using their own sperm, but a lower self-image and more guilt [36]. To our knowledge, no study explored sexual function of patients undergoing ART with sperm donation. However, the use of gamete donation seems to lead to a different impact on sexual function as compared to autologous ART (with partner’s sperm) [37]. Indeed, couples enrolled in autologous IUI and IVF had more sexual disorders than couples receiving sperm donation. They were more likely to admit to seeking pregnancy rather than sexual pleasure. In our study, many couples using sperm donation after failed intra-marital techniques had SD. It can be assumed that they already had a long history of infertility treatments before resorting to sperm donation. Moreover, some people wait for a long period of 9–12 months from registration to their first attempt.
We acknowledge that our study has some limitations. First of all, its monocentric design calls for caution when generalizing, and advocates for confirmation in other settings. The second limitation lies within the use of only one questionnaire per gender. Although the FSFI and the IIEF-15 appear to be the most relevant ones to help evaluating the prevalence of SD, especially using the IIEF-15, the psychological factors causing SD might be underestimated with these tools. Therefore, additional evaluation of mood and self-perception as well as anxiety and depressive symptoms should be considered for future studies. The fact that the study was completely anonymized made it impossible to relate the responses of the man and the woman from the same couple, preventing from performing dyadic analyses. In addition, the number of participants in this study was relatively low, and the numbers were actually insufficient to allow multivariate analysis and to have sufficient statistical power to identify predictive risk factors for SD. For instance, a larger number of participants would enable to evaluate the effect of age, of the type or duration of infertility, and the effect of the protocol (IUI-D versus IVF-D). It is unclear whether COVID-19 pandemic may have impacted results after March 2020 [38]. However, this is the first study to analyze SD in a population using sperm donation. Moreover, the participation rate was high, and therefore representative of our population and the scores used are scientifically validated [15–19]. Finally, the majority of couples underwent IUI-D, and too few couples underwent IVF-D to allow separate analysis.
Although this study was not designed to explain the psychological mechanisms involved in infertility-induced SD (as stated above), some hypotheses can be raised. Literature largely found that intimacy and sexuality appear impaired by intrusiveness of treatments. The discovery of infertility first causes a narcissistic wound in couples who have a desire for a child. The shift from a pleasant and spontaneous sexuality to a scheduled and procreative one contributes to SD. SD in infertile couples might be underdiagnosed and not enough taken into consideration, as doctors do not dare to discuss sexuality during consultations, either out of modesty or for fear of increasing suffering of patients by asking intrusive questions [14]. Additionally, the use of sperm donation triggers a psychological upheaval in patients, as giving up on biological parenthood can be a painful ordeal to overcome. Patients should be encouraged to express their feelings and share about the sexual problems they might encounter. In this context, a better collaboration between doctors and sexologists would help couples maintaining a better quality of sexual life and hopefully ultimately improve the quality of care and ART outcomes [39]. A couple-centered program for the integrated management of psychological and SD should be considered in the context of ART programs [40]. Doctors might be encouraged to propose self-questionnaires, such as the FertQol, designed to assess the quality of life of infertile patients during treatment with questions on sexuality. Further research should focus on the evaluation of psychological interventions (sex therapy, focus groups, etc.) to treat or improve these disorders.
Author contribution
JLG: study design, data collection, manuscript drafting. AR: study design, manuscript revision. SM: study design, manuscript revision. SD: study design, data collection. PB: study design, manuscript revision. TF: study design, data analysis, manuscript revision, study supervision, final validation of manuscript. TL: study design, data analysis, manuscript revision, study supervision.
Funding
No funding was received for conducting this study.
Data availability
The data that support this paper are available from the corresponding author, upon reasonable request.
Declarations
Conflict of interest
The authors report no conflict of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36480033 | PMC9734951 | NO-CC CODE | 2022-12-14 23:28:31 | no | Arch Gynecol Obstet. 2022 Dec 8;:1-8 | utf-8 | Arch Gynecol Obstet | 2,022 | 10.1007/s00404-022-06877-7 | oa_other |
==== Front
Environ Dev Sustain
Environ Dev Sustain
Environment, Development and Sustainability
1387-585X
1573-2975
Springer Netherlands Dordrecht
2819
10.1007/s10668-022-02819-0
Article
How does risk perception of the COVID-19 pandemic affect the consumption behavior of green food?
https://orcid.org/0000-0003-4852-8042
Li Houjian [email protected]
Cao Andi [email protected]
Chen Si [email protected]
https://orcid.org/0000-0002-7722-3793
Guo Lili [email protected]
grid.80510.3c 0000 0001 0185 3134 College of Economics, Sichuan Agricultural University, Wenjiang District, Chengdu, Sichuan China
6 12 2022
123
12 8 2022
30 11 2022
© The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Attention to health is on the rise with the global pandemic of COVID-19, especially in food security. Green food is viewed as a healthy, safe, and nutritious food, which plays a significant role in enhancing immunity. This study aimed to investigate how risk perception affects the consumption behavior of green food. Risk perception and health awareness were added to the original model based on the extended theory of planned behavior. And an online survey about the influence of COVID-19 on consumers' green food consumption behavior was conducted with 612 valid respondents recruited. The results indicate that risk perception has a positive effect on both consumption intention and behavior. The mediating effect analysis shows that risk perception influences green food consumption intention by improving people’s attitudes, subjective norms, and health awareness. These findings can not only help clarify the relationship between green food consumption behavior and the risk perception of COVID-19 but also provide some valuable implications for policymakers and marketers in promoting green food.
Keywords
Risk perception
Health awareness
COVID-19
Green food consumption behavior
Theory of planned behavior
http://dx.doi.org/10.13039/501100012456 National Social Science Fund of China 20CMZ037 Guo Lili
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pmcIntroduction
In the Green Food Mark Management Measures released by China in 2012, green food was defined as safe, high-quality edible agricultural products and related products produced in an excellent ecological environment, produced under the green food standard, with full quality control and the right to use the green food mark. Over the past ten years, green food in China has developed rapidly, and green food products have been marketed successively. Data provided by the Center for Quality and Safety of Agricultural Products of the Ministry of Agriculture and Rural Affairs showed that the number of certified products in the green food industry in China reached 21,638 in 2021, an increase of 28.32% from 2020. However, green food only accounts for approximately 8% of the total number of major food products, indicating a low market share for green food. Despite the awareness of the health benefits of green food, the higher price of green food compared to regular food led to a gap between green food consumption intention and behavior (Qi et al., 2020; Zhang et al., 2018; Zhu et al., 2013).
The coronavirus disease identified in 2019 (COVID-19) has been playing a huge negative impact on people's lives and production activities (WHO, 2020). During the COVID-19 spread, people perceive a strong risk of infection and the whole society has been full of tension, anxiety, and fear (Cori et al., 2020; Sun et al., 2021). Against this background, people began to choose their food more cautiously (Laguna et al., 2020). This paper focuses on whether and how the risk perception derived from the COVID-19 pandemic affects green food consumption. However, existing studies do not provide a definite answer to this question. To our knowledge, some studies have observed changes in people's green food consumption behavior during the COVID-19 pandemic, but the investigation of potential mechanisms is still limited. For example, Sun et al. (2021) found that fear, anxiety, and powerlessness induced by COVID-19 motivated people to pay more attention to their safety and health, thereby promoting green food consumption. Risk aversion, furthermore, played a mediating role between negative awe and green consumption behavior. Qi et al. (2020) found that health consciousness, environmental consciousness, social influence, perceived attributes, family structure, and shopping experiences were the main factors driving consumers' willingness to purchase green food. Still, green food consumption intention was also hindered by high price, unavailability, distrust, and lack of knowledge. Although COVID-19 increases consumers' willingness to purchase green food, there is still a gap between purchase intention and purchase behavior. And Qi et al. (2021) incorporated three factors such as moral attitude, health consciousness, and the impact of COVID-19 into the original theory of planned behavior and used the structural equation model (SEM) to explain consumers' intention to purchase green food in the post-COVID-19 pandemic period. They found that attitude, perceived behavioral control, moral attitude, health consciousness, and the impact of COVID-19 enhanced the consumption intention of green food.
In contrast to the above studies, this paper attempts to explore the relationship and underlying mechanisms between the risk perception of the COVID-19 pandemic and green food consumption behavior in the framework of the extended theory of planned behavior, which fills the research gap. The theory of planned behavior (TPB) is one of the best theoretical frameworks for studying consumption intention and behavior and has been widely used. In psychology, this theory links one’s beliefs and behavior (Ajzen, 1985) and improves the predictive power of the theory of reasoned action (TRA) by including perceived behavioral control (Ajzen, 1991). It covers people's non-volitional behavior, which cannot be explained by the TRA. The intention is not the only determinant of behavior where the individual does not have complete control over their behavior. Adding more factors, the TPB can better explain the relationship between intention and actual behavior. And the growing literature found that the TPB helps in predicting health-related behavioral intention better than the TRA, given that the TPB has improved the predictability of intention in various health-related fields and even nutrition intervention (Ajzen, 1989; Conner et al., 2003; Nguyen et al., 1997; Sweitzer et al., 2011). Currently, the outbreak of COVID-19 is viewed as an external health risk factor that affects consumers' decision-making when purchasing green food. To estimate the potential influence of COVID-19 on green food consumption in China, this study added risk perception and health awareness to the TPB. Our study aims to construct an integrated framework concerning the effect of consumers' risk perception of COVID-19 on green food consumption behavior. Specifically, this study is based on the extended TPB, using the structural equation model (SEM) to fit 612 valid samples collected online in 2020, and found that risk perception has a positive effect on both consumption intention and behavior. Furthermore, we also found that risk perception affects consumption intention by improving people's attitudes, subjective norms, and health awareness.
This study contributes to several aspects. First, this paper constructs an analytical framework for the risk perception of COVID-19 to influence green food consumption behavior. This paper adds risk perception and health awareness into the original TPB framework, which contributes to the relevant literature. Second, we collected a larger sample size than those involved in existing studies, and therefore the results would be more reliable when estimating the effect of COVID-19 on green food consumption intention and behavior using the SEM. Third, this paper also examines how the risk perception of COVID-19 influences green food consumption intention. Compared to existing studies, this paper is more in-depth in this aspect. Revealing the internal mechanism could help us deeply understand the interrelationship between them. Fourth, the findings of this paper could also provide some useful empirical evidence for green food policymakers and marketing promoters.
The remainder of this study is as follows: Sect. 2 describes the theoretical framework and poses hypotheses; Sect. 3 introduces the data collection and empirical methods; Sect. 4 provides a detailed discussion of findings; and Sects. 5–7 discuss and summarize the results, illustrate the limitations of this study, and suggest future research directions, respectively.
Theoretical framework and hypothesis development
Theory of planned behavior (TPB)
The TPB illustrates that three factors determine intention––attitude, subjective norms, and perceived behavior control, further substantially impacting behavior (Ajzen, 1985). The theory has been frequently applied in the research field of individual behavior. It has been used to explain people's behavior and their decision-making process in different disciplines, such as family recycling (Kaiser & Gutscher, 2003), family waste of dairy products (Toma et al., 2020), food quality, and preference (Sultan et al., 2020). Both personal and external factors can determine green food consumption (Tanner & Kast, 2003). Considering changes in individual psychology and behavior, COVID-19 can influence green food consumption. Moreover, it has been proved in the existing literature that it is appropriate to use the TPB to explain the consumption of green food (Wang & Wang, 2016; Zhu et al., 2013). Under the background of the COVID-19 pandemic, this paper uses the TPB to explore green food consumption, which could help us better understand green food consumption behavior.
Green food consumption intention and behavior
The intention is the probability that a person will take specific action for a certain intention and purpose, which is the primary factor in predicting behavior (Russell & Fielding, 2010). And behavior refers to an individual taking action. Consumption intention is determined by attitude, subjective norms, and perceived behavior control. Meanwhile, consumption intention has a positive effect on consumption behavior. These conclusions have been confirmed by numerous studies (Dunn et al., 2011; Luo et al., 2009; Michaelidou & Hassan, 2014; Paul et al., 2016; Yazdanpanah & Forouzani, 2015; Zhu et al., 2013). Thus, hypothesis 1 is presented as follows:
Hypothesis 1 (H1)
Consumption intention of green food has a positive effect on consumption behavior.
Risk perception and health awareness
In addition to the general applicability, many studies tried to improve the explanatory ability of the model by adding variables. For example, Paul et al. (2016) confirmed that the extended TPB model was more effective in predicting the consumption intention of green products by adding environmental awareness variables into the model. Qi and Ploeger (2019) added confidence and personal characteristics into the TPB framework to study green food consumption behavior. However, most of the literature variables are unique, but few studies included external risk factors. The intention might be affected by various external factors, thereby determining people's behavior. To identify the impact of COVID-19 on consumers, this paper introduced risk perception and health awareness to discuss the relationship between the risk brought by COVID-19 and green food consumption.
Risk perception refers to the perception of uncertainty or the possible negative consequences of a specific event (Jacobs & Worthley, 1999), namely the subjective judgment of the severity of the risk (Slovic et al., 1982). Risk perception is influenced by various factors, such as the severity of perceived outcomes, cautious behaviors, and concerns caused by risk (Champion & Skinner, 2008). During the COVID-19 spread, the perceived health risk was very high, increasing anxiety and quickly spilling throughout society (Cori et al., 2020). Since consumers are risk-averse, they make consumption decisions to minimize risk. In terms of food consumption, if consumers perceive a product as high-risk, they would consider choosing an alternative to reduce the risk (Ha et al., 2020; Lee, 2020). Green food is considered less risky than traditional food (Yu et al., 2014) and can reduce foodborne diseases (Sanders, 2006; Sirieix et al., 2011), which might prompt consumers to buy it. For instance, Sun et al. (2021) pointed out that more and more people chose to buy green food to protect their families during the COVID-19 pandemic. As alluded to above, hypotheses 2 and 3 are proposed as follows:
Hypothesis 2 (H2)
The risk perception of COVID-19 has a positive effect on green food consumption intention.
Hypothesis 3 (H3)
The risk perception of COVID-19 has a positive effect on green food consumption behavior.
When people recognize the risk of COVID-19, their health awareness is also awakened. The mortality following COVID-19 infection reaches up to 6%, and it is easier to lead to severe sequelae such as heart, brain, and lung diseases (Baud et al., 2020). Epidemic diseases can reshape the public’s awareness of life, especially the perception of health risks that can trigger individuals to think about health, body, and life in multiple dimensions (Commodari et al., 2020; Ferrer & Klein, 2015). For example, people subconsciously wash their hands frequently, maintain physical distance, avoid public places and wear masks to prevent infection (Dryhurst et al., 2020). Health awareness indicates an individual’s willingness to be healthier and take the necessary actions to achieve the goal (Sun & Liang, 2020). Furthermore, health awareness can strengthen people's intentions to respond to public health crisis events actively and encourage health-protective behaviors during the COVID-19 pandemic (Paakkari & Okan, 2020). People perceive green food as a healthy food with a higher consumption value, richer nutrition, and lower contamination risk (Sivapalan et al., 2021; Zhu et al., 2013). And results of Kriwy and Mecking (2012) and Qi et al. (2021) confirmed that consumers' health awareness could strengthen green food consumption intention. Given this, health awareness is added to the model, and hypotheses 4 and 4a are posed as:
Hypothesis 4 (H4)
Health awareness has a positive effect on green food consumption intention.
Hypothesis 4a (H4a)
Health awareness mediates the effect of risk perception of COVID-19 on green food consumption intention.
Attitude
Attitude refers to the positive or negative feelings of the individual toward behavior (Chen, 2016), which evaluates people's behavior (Ajzen, 1991). Consumers' attitude toward green food reflects consumers' recognition and trust in green food. Ajzen (1985) pointed out that consumers would have a positive attitude when believing that the product is beneficial. Attitude plays a significant role in encouraging consumers to buy healthy food (Voon et al., 2011). Consumers prefer to understand healthy products when optimistic about them (Golnaz et al., 2012; Kim and Chung, 2011; Paul et al., 2016). When consumers hold a positive attitude toward green food and think it is healthy, their consumption intention will be increased. Based on the relationship between attitude and intention, hypothesis 5 is proposed as follows:
Hypothesis 5 (H5)
Attitude toward green food has a positive effect on green food consumption intention.
Earlier studies found that attitude is negatively correlated with risk perception (Jarvenpaa et al., 2000; Shimp & Bearden, 1982; White & Truly, 1989). Using the structural equation model (SEM), Xu et al. (2020) analyzed the impact factors of consumers' risk perception of transgenic. They found that consumers' attitudes toward transgenic technology and risk perception of transgenic food are opposite. In this study, green food is a safe and healthy alternative to traditional food. Health concerns significantly impact consumers' attitudes toward purchasing healthy food (Husic-Mehmedovic et al., 2017). The increase in consumers' risk perception of COVID-19 may lead to a higher positive attitude toward green food consumption. For instance, Hsu et al. (2016) found that food safety problems had a positive impact on both consumers' attitudes toward healthy food and consumption intention. Consumers pay more attention to food health and have more positive attitudes toward healthy food. Therefore, we suppose that consumers would pay more attention to health and change their attitude toward green food due to infection concerns. Then hypothesis 5a is put forward as follows:
Hypothesis 5a (H5a)
Attitude toward green food mediates the effect of risk perception of COVID-19 on green food consumption intention.
Subjective norms
Subjective norms refer to the social pressure on individuals to behave and reflect the influence on other people’s opinions as well as personal decision-making. Scholars believe subjective norms can represent social influence (Malhotra & Galletta, 1999), including the effects of alternatives, people, and opinion leaders. In this paper, subjective norms are measured by the threat of substitutes for usual food and the attitude of the media and the public. If the public and organizations think highly of the importance of green food, consumers would be more likely to purchase green food (Park, 2000). Most studies supported that subjective norms can significantly affect consumption intention (Åstrøm & Masalu, 2001; Bianchi & Mortimer, 2015; Kim & Chung, 2011; Pomsanam et al., 2014). Because of the great influence of COVID-19 and the frequent media coverage, the pandemic would have a certain impact on subjective norms. Moreover, consumers mainly obtain information about COVID-19 through the government, media, and surrounding people. News reports, media communication, and the preventive measures adopted by surrounding people impact consumers' risk perception, then affect their subjective norms, and finally affect their consumption intention (Fuentes & Fuentes, 2015; Huynh, 2020) (Fig. 1). Therefore, hypotheses 6 and 6a are proposed as follows:Fig. 1 Conceptual framework of green food consumption behavior based on the original structure of TPB
Hypothesis 6 (H6)
Subjective norms have a positive effect on green food consumption intention.
Hypothesis 6a (H6a)
Subjective norms of green food mediate the effect of risk perception of COVID-19 on green food consumption intention.
Perceived behavior control
Perceived behavioral control (PBC) usually reflects the impediment of personal experience or second-hand information on consumption intention and behavior (Ajzen, 1991). In this paper, PBC contains the costs (including money, time, and energy), convenience, and purchasing experience. Cranfield (2020) found that consumers' purchasing habits, places, and ways changed during the COVID-19 pandemic. Ajzen (1991) held that the perceived behavioral control of a certain behavior positively affects a person's intention. For example, Kavaliauske and Ubartaite (2014) argued that consumers prefer fresh and easily accessible healthy food and are not sensitive to the price. Considering the factors of limited movement and reduced income during COVID-19, we assumed that consumers with rich green food knowledge and more convenient purchase conditions would have a stronger purchasing intention:
Hypothesis 7
Perceived behavior control has a positive effect on green food consumption intention.
Data and method
Questionnaire design
We designed the questionnaire concerning existing literature and well-established scales (Ajzen, 1991; Anvar & Venter, 2014; Gerhold, 2020; Prentice et al., 2019; Siegrist et al., 2021; Voon et al., 2011; Zhu et al., 2013), then distributed and collected the questionnaire through an online survey. The questionnaire consists of two parts: the demographic section (including gender, age, education level, salary, etc.) and the measurements of the extended TPB model (behavior, intention, risk perception, health awareness, attitude, subjective norms, and PBC). About 4 to 6 questions are set under each construct. All questions are formulated using the five-point Likert Scale and rated from strongly disagree to strongly agree. Each construct is modified according to its implication in this study and adapted from previous literature. A detailed design is given as follows:
(1) Consumption behavior of green food (CBGF) is used to measure the actual behavior of consumers to buy green food, including four questions: the preference and frequency of purchasing green food and whether consumers recommend it to others; (2) consumption intention of green food (CIGF) involves six questions: the possibility and purchasing motivation (for environmental protection, requirements for health and high-quality life, etc.); (3) risk perception (RP) is measured by five questions, which describe consumers' worry and fear of being infected; (4) health awareness (HA) is also measured by five questions about washing hands, cleaning rooms, wearing masks, and opening doors; (5) attitude (ATGF) contains six questions to measure how consumers think green food is environmentally friendly, healthy, and safe; (6) subjective norms (SN) include four questions, reflecting the influence of a vital person's advice, reliability, and the feeling when purchasing substitutes; (7) perceived behavior control (PBC) includes questions about the available conditions for purchasing green food (time, purchasing experience, and purchasing power, etc.). Table 5 in Appendix refers to the details of the questionnaire set.
Data collection
The survey data come from an internet questionnaire called The Impact of COVID-19 on Consumers' Green Food Consumption Behavior designed by us and distributed randomly on one of China's largest online questionnaire platforms. The sample contains consumers' ages, incomes, regions, and education levels. Most respondents were from Sichuan Province. Between February 20, 2020, and May 10, 2020, 738 samples were collected, and 126 invalid questionnaires were deleted, with a valid response rate of 82.9%. Respondents aged between 16 and 25, 26 and 35, and 36 and 45 accounted for 51.8, 24.5, and 14.2%, respectively. In addition, 76.1% of participants had a bachelor's or a higher education degree. Moreover, 46.2% of respondents were students, only 12 respondents were unemployed, and the rest had a job. And 94.1% of respondents thought they were healthy or above; only 4 thought they were not in good health. When asked about income, 54.8% of respondents declared their monthly income is less than 3000 yuan, and the income of 14.2% is between 3001 and 5000 yuan.
Method
Partial least squares-structural equation modeling (PLS-SEM) was used to test the correlation between the risk perception of the COVID-19 pandemic and green food consumption. The PLS-SEM is a causal modeling method that focuses on the relationship between the potential variables in the estimation and analysis model. The estimation of the structural model will be more robust when all path coefficients are valid simultaneously (Hoyle, 1995). The PLS-SEM proposed by Hair et al. (2012b) includes effect size, internal consistency reliability, average variance extraction (AVE), discrimination validity, convergence validity, and path coefficient estimation. It can simplify the complicated decision-making process. For example, PLS minimizes the deviation caused by the minimum sample size and would not lead to unreasonable estimates or model identification problems. Moreover, it can also maximize the ability to predict.
In the previous study, the conceptual framework of green food consumption behavior based on the original structure of TPB is established in Sect. 2. Based on this conceptual framework, we build a structural equation model in the Smart-PLS, which contains seven latent variables such as attitude, subjective norms, perceived behavior control, risk perception, health awareness, consumption intention, and consumption behavior. Latent variables above have been measured by several indicators shown in Table 5. Then we use the confirmatory factor analysis to optimize the scale. Confirmatory factor analysis (CFA) is a research method used to test whether the relationship between a factor and the corresponding measure term conforms to the theoretical relationship designed by the researcher. The main purpose of confirmatory factor analysis (CFA) is to verify the validity of CFA and to analyze the common method deviation CMV. The reliability of each index should be considered in the verification, and the absolute standardized load of each index should be higher than 0.7. The indicator demonstrating a load of 0.4 or less should be removed from the reflection scale. In the first CFA calculation result, the load value of HA5 (I am aware that one should wear a mask at home during the pandemic) is less than 0.7, so it should be deleted. In the second operation result, the load values of RP3 (I will wash the vegetables I bought outside many times during the pandemic) and RP5 (I often worry that I will infect with SARS-CoV-2 during the pandemic) are also less than 0.7. After deleting them, the confirmatory analysis is carried out again. Finally, the absolute standardization compliance of each index is higher than 0.7. The effective and reliable scale of each structure was established, and the influence relationships among every factor were confirmed.
Subsequent sections examine the reliability and validity of the latent variables contained in the structural equation model to ensure the accuracy and reliability of path coefficient estimation and mediating effect identification.
Survey results
Reliability and validity
In this study, Smart-PLS software was used to detect the mean value, standard deviation, and reliability of each variable. Table 1 presents the results of the descriptive statistics. It demonstrates that the mean values of overall indicators are below four except for health awareness. At the same time, health awareness had a relatively low standard deviation. The higher mean and lower standard deviation indicate that most consumers will take corresponding measures to deal with infectious diseases.Table 1 Reliability and validity
Variables No. items Means SD CA CR AVE
SN 4 3.288 1.088 0.898 0.930 0.768
HA 4 4.379 0.620 0.735 0.832 0.555
RP 3 3.805 1.164 0.733 0.843 0.641
PBC 4 3.240 1.106 0.888 0.897 0.922
ATGF 6 3.843 0.907 0.913 0.932 0.698
CIGF 6 3.788 0.848 0.956 0.961 0.806
CBGF 4 3.516 0.977 0.928 0.949 0.822
RP Risk perception, HA Health awareness, ATGF Attitude toward green food, SN Subjective norms, PBC Perceived behavioral control, CIGF Consumption intention of green food, CBGF Consumption behavior of green food, SD Standard deviation, CA Cronbach’s alpha, CR Composite reliability, AVE Average variance extracted
In contrast, PBC had a lower mean and a higher standard deviation, signifying that the overall level of PBC is low, and consumers' experience, time, and economic situation have large differences. In addition, the standard deviation of risk perception is 1.164, indicating that the scattered distribution of risk perception is high overall. To evaluate the internal consistency of each construct, Cronbach’s alpha is used to test internal consistency and reliability. When the CA value is greater than 0.7, the construct is reliable. According to Table 1, the CA values of all variables are above 0.7, implying good consistency and reliability.
Additionally, the CR method is used to test internal consistency. The threshold of composite reliability was 0.7 (Hair et al., 2012a). As shown in Table 1, all CR values are greater than 0.8, implying that all indicators are reliable. Convergence validity represents potential structures (Carmines & Zeller, 1979) and is measured by the AVE (Average Variance Extracted) value. The AVE represents the average variance of structure in its index variable relative to its total index variance. According to Table 1, the convergence validity of all indexes is over 0.5. The average value of more than 0.5 indicates sufficient convergence validity (Fornell & Larcker, 1981). It means that the potential variables account for more than half of the variances, so they all have a good convergence validity.
Discriminant validity can be used to test the non-correlation between constructs. Fornell–Larcker criterion, cross-loading analysis, and heterotrait–monotrait ratio (HTMT) approach are commonly used in the evaluation. Hair et al.’s (2012a) marketing study involved a certain type of discriminant validity assessment, using cross-loadings (7.79%) and the Fornell–Larcker criterion (72.08%). The AVE square should be greater than the correlation coefficient between other constructs and itself. According to Table 2, all indicators meet the conditions. The second method is more convenient for testing validity: The loadings of each indicator should be greater than that of cross-loadings. Table 6 in Appendix reports the load and cross load of all indexes in the model. The construct load of its structure was relatively higher than that of other structures, confirming the discrimination validity. Since PLS overestimates the factor loadings and underestimates the relationship between the constructs, the HTMT method can reduce this error. The HTMT is used to estimate the correlation between each variable, and the threshold of HTMT is 0.9. According to the results, all of them are below 0.9, implying no clear evidence of a lack of discriminant validity. Therefore, the above three methods all verified the validity of the discrimination.Table 2 Discriminant validity
Variables Fornell–Larcker criterion Heterotrait–monotrait ratio (HTMT)
AVE SN HA RP PBC ATGF IGF CGF SN HA RP PBC ATGF IGF
SN 0.768 0.876 SN
HA 0.555 0.336 0.745 HA 0.398
RP 0.641 0.401 0.397 0.801 RP 0.464 0.521
PBC 0.922 0.688 0.267 0.229 0.865 PBC 0.767 0.313 0.256
ATGF 0.698 0.606 0.354 0.461 0.553 0.835 ATGF 0.777 0.413 0.533 0.606
CIGF 0.806 0.654 0.383 0.406 0.587 0.845 0.898 CIGF 0.813 0.442 0.461 0.633 0.886
CBGF 0.822 0.617 0.377 0.403 0.688 0.570 0.634 0.907 CBGF 0.885 0.437 0.454 0.755 0.835 0.856
RP Risk perception, HA Health awareness, ATGF Attitude toward green food, SN Subjective norms, PBC Perceived behavioral control, IGF Consumption intention of green food, CGF Consumption behavior of green food. The square root of Average Variance Extracted (AVE) is marked in bold
Path analysis
We used SEM to construct the structural model and test the relationship between each variable (Table 3). The coefficient value of intention to behavior (H1) is 0.802 and significant at a 1% level, indicating that consumption intention has a positive impact on behavior. The f2 value of 1.789 implies that the effect of intention on behavior is great. The influence coefficient value (H2) of risk perception on green food consumption intention is 0.025 with a p value of 0.0348, indicating that risk perception has a positive impact on people's consumption intention significantly. The f2 value of 0.002 demonstrates that the effect is negligible. And the coefficient value of risk perception toward consumption behavior (H3) is 0.078 with a p value of 0.0173, indicating that risk perception of the COVID-19 pandemic has a positive impact on green food consumption behavior. The standardized regression coefficient illustrates that the effect of risk perception on behavior is smaller than that of intention. The f2 value of 0.017 shows that the impact of risk perception on behavior is weak. R2 value indicates that 70% of green food consumption changes are explained by risk perception and intention. Finally, the Q2 value is 0.539, suggesting that risk perception and intention have a robust predictive relevance toward green food consumption.Table 3 Path coefficient
Hypothesis Beta p R2 f2 Q2 Decision
H1 CIGF-CBGF 0.802 0.000 0.700 1.789 0.539 Accept
H2 RP-CIGF 0.025 0.035 0.002 Accept
H3 RP-CBGF 0.078 0.017 0.769 0.017 0.578 Accept
H4 HA-CIGF 0.071 0.039 0.017 Accept
H5 ATGF-CIGF 0.610 0.000 0.723 Accept
H6 SN-CIGF 0.278 0.000 0.121 Accept
H7 PBC-CIGF 0.046 0.632 0.005 Reject
RP Risk perception, HA Health awareness, ATGF Attitude toward green food, SN Subjective norms, PBC Perceived behavioral control, CIGF Consumption intention toward green food, CBGF Consumption behavior of green food
In addition, the coefficient of health awareness (H4) is 0.071 with a p value of 0.0386 (less than 5% significance level). The standardized regression coefficient indicates that health awareness has a positive impact on consumption intention, which is slightly higher than that of risk perception. Meanwhile, the coefficient of attitude on intention (H5) is 0.610 and significant at the 1% level, showing that attitude has a positive and significant effect on intention. Moreover, the coefficient value (H6) of the influence of subjective norms on green food consumption intention is 0.278 with a p value of 0.000, suggesting that subjective norms have a positive impact on green food consumption intention. The value of f2 is 0.121, indicating that the influence of subjective criteria on green food consumption intention is weak. Finally, the coefficient value (H7) of the influence of PBC on the intention of green food is 0.046, but not significant. The result shows that the PBC has no significant positive effect on green food consumption intention. In general, the R2 value demonstrates that 76.9% of the changes in green food consumption intention are jointly explained by risk perception, health awareness, attitude, subjective norms, and the PBC. Moreover, the Q2 value is 0.578, which indicates that risk perception and health awareness have a medium predictive relevance for green food consumption intention (Fig. 2).Fig. 2 Path coefficients followed by p-values. Note ***, **, and * indicate 1, 5, and 10% significance levels, respectively; The dotted line is not significant
Mediating effects
Three mediating analyses are performed: RP → HA → CIGF, RP → ATGF → CIGF, and RP → SN → CIGF. In this paper, bootstrap (5000 samples) is utilized to test whether the mediating effect is significant (Table 4). The confidence interval includes zero, meaning that it is not significant. Results show that the confidence interval from risk perception to health awareness (H4a) does not include zero, indicating that the impact is also significant (95% CI 0.320–0.474). While the confidence interval of risk perception (H5a) has a significant indirect effect on green food consumption intention (95% CI 0.386–0.537), confirming that attitude can mediate the relationship between risk perception and green food consumption intention. The effect of risk perception (H6a) on subjective norms is also statistically significant (95% CI 0.325–0.477). Therefore, health awareness, attitude, and subjective norms mediate the relationship between the risk perception of COVID-19 and green food consumption intention.Table 4 Mediating models
Hypothesis Beta LLCI ULCI Result
H4a: HA mediates the relationship between RP and CIGF 0.397 0.320 0.474 Mediation
H5a: ATGF mediates the relationship between RP and CIGF 0.461 0.386 0.537 Mediation
H6a: SN mediates the relationship between RP and CIGF 0.401 0.325 0.477 Mediation
RP Risk perception, HA Health awareness, ATGF Attitude toward green food, SN Subjective norms
Discussion
We proposed seven direct and three mediating hypotheses, all of which have been tested. Consistent with most current research results, consumption intention has a significant effect on consumption behavior (H1). If people buy green food with strong possibility, intention, and purpose, they will be more likely to have corresponding consumption behavior. Therefore, marketers can promote green food through in-store promotion, online marketing, media publicity, and other ways to improve their perceived value of green food and encourage them to buy it. By publicizing the characteristics of safety, social benefits, and environmental benefits, consumers would take action in consideration of personal health and a sense of social responsibility. Furthermore, adding risk perception into the framework improves explanatory power. H2 and H3 support that risk perception impacts both consumption intention and behavior. Risk perception plays a vital role in strengthening green food consumption behavior. On the one hand, risk perception can directly affect consumption behavior. On the other hand, it can conduct the effect of consumer behavior through intention. Additionally, H4 is also confirmed with the significant influence of health awareness on intention. Under the influence of COVID-19, there is a higher demand for high-quality and safe food. As a high-quality and nutritious food, green food is conducive to enhancing human immunity and reducing the diet risk to the human body (Arshad et al., 2020; Qin et al., 1998). Therefore, it is necessary to promote the benefits of green food and related knowledge.
These findings also show that attitude and subjective norms have strong and significant path coefficients on green food consumption intention. Among them, attitude is the key to understanding behavior and intention, contributing to predicting food consumption behavior (Yadav & Pathak, 2017). A positive attitude will encourage consumers to buy green food (H5 is accepted), which is consistent with other research (Kim & Chung, 2011; Paul et al., 2016). Besides, the results show that subjective norms are a significant determinant of consumption intention, and the H6 is proved. The influence of important people or organizations and people's feelings about using substitutes would affect their consumption intention. This is also in line with relevant research (Jackson et al., 1993; Paul et al., 2016). Therefore, society can increase the role of subjective norms by utilizing the influence of public figures and institutions. However, this study also demonstrated that the effect of PBC on intention was not significant, rejecting H7. The result is interpretable in common sense. Although the impact of PBC on consumption intention is not significant at the 10% level, the path coefficient is still positive. Our results suggest that during the COVID-19 pandemic, green food consumption intention is mainly affected by attitude and subjective norms, while consumers' purchasing power, energy, and purchasing experience of green food have little to do with their consumption intention. This could be attributed to the introduction of risk perception in the TPB framework. That is, there may be a substitution relationship between PBC and risk perception (Luo et al., 2009), but we cannot deny the effect of PBC on consumption intention.
Three mediating hypotheses are all confirmed in this study. H4a is accepted, which means health awareness mediated the impact of risk perception on consumption intention. In this paper, the potential risk of COVID-19 to human health may affect their health awareness, which is consistent with the results of Gullette et al. (2009), Kaba et al. (2017), and Tran et al. (2013). The frequency and intensity of preventive measures will increase when the pandemic becomes more serious. In H5a, consumers' high risk of COVID-19 magnifies their attitude toward green food and promotes their consumption intention. A strong sense of risk for COVID-19 will make a better attitude toward green food. Additionally, the public health event formed an external pressure, which impacted subjective norms. Immunity plays an important role in fighting SARS-CoV-2, and people can reduce the infection rate by advising others on a healthy diet. Finally, this paper found that attitude played a more critical role in regulating perception than subjective norms, which is consistent with the results of Chen (2016).
Conclusion
In the context of the COVID-19 pandemic, this study explored the influence of consumers' risk perception on green food consumption behavior. Based on the original TPB, external factors such as risk perception and health awareness were added for a comprehensive analysis. According to the results, COVID-19 was confirmed to affect green food consumption behavior in China. Furthermore, the stronger the risk perception is, the higher the intention to purchase green food.
This paper provides some new study aspects. On the one hand, consumer behavior is often affected by external factors. We considered the change in the external environment and added risk perception of COVID-19 as the key factor. On the other hand, the emergence of COVID-19 threatened people's health and their decision for food, so they have to take measures to prevent being infected. As a more healthy and safe food alternative, green food is a better choice with the increasing food quality requirements. Therefore, this study introduced risk perception and health awareness in the original model and proposed three mediating hypotheses. This study can enrich the research on green food consumption, and provide a valuable reference for marketers to comprehend consumers' psychology and make targeted strategies to expand the market.
Based on these findings, attention should be paid to improving consumers' knowledge about green food and enhancing its perceived value. Risk perception is a key factor affecting green food consumption intention. The government and marketers should attach importance to the benefits of green food as it can enhance human immunity and reduce the risk of illness. Attitude has the largest influence among seven direct effects and three mediating effects, and it also promotes the impact of risk perception on consumption intention. Some scholars found that consumers' knowledge positively impacts their risk perception (Liu, 2008; Martinez-Poveda et al., 2009). Therefore, strengthening the propaganda of epidemic prevention and improving people's knowledge of green food is the key to expanding the green food market. By emphasizing the importance of healthy food as well as the threat brought by external risks, green food consumption intention will be enhanced.
Limitations and future research
Although the hypotheses proposed in this study have been verified, there are still some limitations. First, the survey area is concentrated in southwest China, which is affected by the local green food industry, climate, customs, etc. The green food market is mainly concentrated in large and medium-sized cities, especially in the eastern coastal areas (Yin et al., 2010). Additionally, this study only focused on the impact of green food intention on behavior but neglected the gap between them. The results showed that the effect of risk perception on behavior is greater than that on intention. Although intention and behavior are significantly related, the gap between them may not be neglected.
Future studies can expand the sample size and distribute it to each population characteristic group and region, as well as conduct a detailed survey of the eastern coastal areas with the most active green food market. Second, the sample size can be narrowed to a certain income group and occupation type group, which is helpful in exploring the specific consumption behavior. Third, as an essential factor in predicting green consumption, risk perception affects consumption behavior differently. Future studies can consider the influence of external events and change the research object. Finally, since COVID-19 has a huge impact on the world, extensive research can be done on other countries worldwide.
Appendix
See Tables Table 5 Survey Instrument
Code Questions Sources
Risk Perception (1. Strongly Disagree to 5. Strongly Agree)
RP-1 I am afraid to contact other strangers during the pandemic Gerhold (2020); Siegrist et al. (2021)
RP-2 I am afraid to go out during the pandemic
RP-3 I will wash the vegetables I bought outside many times during the pandemic
RP-4 I am afraid that the food in my family was not well cooked during the pandemic
RP-5 I often worry that I will infect with SARS-CoV-2 during the pandemic
Health awareness (1. Strongly Disagree to 5. Strongly Agree)
HA-1 I am aware that my family should wash their hands frequently during the pandemic Qi et al. (2021); Naveed and Shaukat (2022)
HA-2 I am aware that my house should be often cleaned during the pandemic
HA-3 I am aware that the door should be often opened for ventilation during the pandemic
HA-4 I am aware that my hands should be washed frequently during the pandemic
HA-5 I am aware that one should wear a mask at home during the pandemic
Attitude toward Green Food (1. Strongly Disagree to 5. Strongly Agree)
ATGF-1 Compared with ordinary food, I prefer to buy similar green food Voon et al. (2011); Prentice et al. (2019); Ajzen (1991)
ATGF-2 Eating green food is very necessary to prevent foodborne diseases
ATGF-3 I think it is a good idea to buy green food
ATGF-4 I think buying green food is a good thing for family health
ATGF-5 I think green food is safe
ATGF-6 I think buying green food is a good thing for environmental protection
Subjective Norms (1. Strongly Disagree to 5. Strongly Agree)
SN-1 Those who are very important to me suggest I buy green food Anvar and Venter (2014); Ajzen (1991)
SN-2 Those who are important to me want me to buy green food
SN-3 Everyone has the responsibility to protect the environment by purchasing green food
SN-4 I feel terrible when I replace green food with common food of the same kind
Perceived Behavior Control (1. Strongly Disagree to 5. Strongly Agree)
PBC-1 It's convenient for me to buy green food Ajzen (1991)
PBC-2 I have enough time to choose and buy green food
PBC-3 I have enough economic strength to buy green food
PBC-4 I have enough experience to distinguish similar green food from common food
Consumption Intention of Greed Food (1. Strongly Disagree to 5. Strongly Agree)
CIGF-1 I have a good chance to buy green food Zhu et al. (2013); Grankvist and Biel (2001); Ajzen (1991)
CIGF-2 I want to reduce the damage to the environment by buying green food
CIGF-3 For the sake of health, I have a strong desire to buy green food
CIGF-4 As a responsible individual, I will buy green food
CIGF-5 To improve life quality, I will spend more money to buy green food
CIGF-6 I plan to continue to buy green food
Consumption Behavior of Green Food (1. Strongly Disagree to 5. Strongly Agree)
CBGF-1 When purchasing food, I try to buy food with a green food logo Zhu et al. (2013); Ajzen (1991)
CBGF-2 Even though the price is high, I still buy green food
CBGF-3 I will recommend relatives and friends buy green food
CBGF-4 I often buy green food
5 and Table 6 Loadings and cross-loadings
SN HA RP PBC ATGF IGF CGF
SN1 0.918 0.285 0.356 0.560 0.527 0.568 0.541
SN2 0.915 0.290 0.376 0.557 0.515 0.555 0.528
SN3 0.846 0.312 0.336 0.434 0.561 0.510 0.505
SN4 0.824 0.288 0.338 0.459 0.565 0.501 0.488
HA1 0.287 0.818 0.351 0.209 0.330 0.328 0.315
HA2 0.307 0.732 0.319 0.287 0.298 0.339 0.360
HA3 0.175 0.660 0.259 0.102 0.170 0.188 0.176
HA4 0.197 0.759 0.225 0.160 0.219 0.249 0.229
RP1 0.246 0.304 0.797 0.130 0.304 0.267 0.226
RP2 0.244 0.305 0.815 0.113 0.306 0.259 0.247
RP4 0.420 0.334 0.790 0.263 0.452 0.406 0.436
PBC1 0.494 0.240 0.206 0.897 0.528 0.543 0.519
PBC2 0.533 0.239 0.229 0.898 0.512 0.551 0.519
PBC3 0.513 0.214 0.153 0.834 0.374 0.419 0.528
PBC4 0.529 0.229 0.194 0.829 0.478 0.502 0.504
ATGF1 0.501 0.368 0.472 0.494 0.827 0.433 0.595
ATGF2 0.521 0.274 0.405 0.458 0.836 0.464 0.545
ATGF3 0.524 0.307 0.394 0.491 0.899 0.525 0.588
ATGF4 0.586 0.288 0.358 0.439 0.865 0.523 0.535
ATGF5 0.493 0.235 0.297 0.398 0.750 0.430 0.455
ATGF6 0.501 0.289 0.367 0.479 0.826 0.547 0.428
CIGF1 0.538 0.371 0.376 0.504 0.577 0.899 0.521
CIGF2 0.472 0.367 0.376 0.466 0.555 0.871 0.493
CIGF3 0.465 0.338 0.380 0.490 0.556 0.911 0.538
CIGF4 0.497 0.343 0.409 0.528 0.586 0.925 0.564
CIGF5 0.465 0.290 0.307 0.562 0.575 0.849 0.572
CIGF6 0.521 0.353 0.342 0.507 0.599 0.931 0.598
CBGF1 0.495 0.361 0.373 0.542 0.507 0.573 0.896
CBGF2 0.504 0.318 0.326 0.539 0.559 0.527 0.912
CBGF3 0.592 0.351 0.401 0.499 0.598 0.552 0.911
CBGF4 0.572 0.335 0.362 0.514 0.528 0.569 0.908
The bold values in the matrix above are the item loadings and others are cross-loadings
6.
Acknowledgements
Funding for this research from National Social Science Foundation of China with ratification number 20CMZ037 is gratefully acknowledged. We would like to thank the anonymous reviewers for their kind comments and valuable suggestions. We confirm that we have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The datasets generated for this study are available on request to the corresponding author.
Data availability
The datasets generated for this study are available on request to the corresponding author.
Declarations
Conflict of interest
We confirm that we have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Zhang B Fu Z Huang J Wang J Xu S Zhang L Consumers' perceptions, purchase intention, and willingness to pay a premium price for safe vegetables: A case study of Beijing, China Journal of Cleaner Production 2018 197 1498 1507 10.1016/j.jclepro.2018.06.273
Zhu Q Li Y Geng Y Qi Y Green food consumption intention, behaviors and influencing factors among Chinese consumers Food Quality and Preference 2013 28 1 279 286 10.1016/j.foodqual.2012.10.005
| 0 | PMC9734953 | NO-CC CODE | 2022-12-14 23:28:31 | no | Environ Dev Sustain. 2022 Dec 6;:1-23 | utf-8 | Environ Dev Sustain | 2,022 | 10.1007/s10668-022-02819-0 | oa_other |
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Geogr. Nat. Resour.
Geography and Natural Resources
1875-3728
1875-371X
Pleiades Publishing Moscow
1110
10.1134/S1875372822030064
Article
The Evolution of the Nature Management System and Modern Trends in Its Development
Kochurov B. I. [email protected]
1
Chernaya V. V. [email protected]
2
Voronin R. M. [email protected]
2
1 grid.424976.a 0000 0001 2348 4560 Institute of Geography, Russian Academy of Sciences, 119017 Moscow, Russia
2 Pavlov State Medical University, 390026 Ryazan, Russia
8 12 2022
2022
43 3 212217
5 11 2021
22 12 2021
29 3 2022
© Pleiades Publishing, Ltd. 2022, ISSN 1875-3728, Geography and Natural Resources, 2022, Vol. 43, No. 3, pp. 212–217. © Pleiades Publishing, Ltd., 2022.Russian Text © The Author(s), 2022, published in Geografiya i Prirodnye Resursy, 2022, Vol. 43, No. 3, pp. 20–27.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
We have examined the evolution of nature management systems in a historical context. An analysis has been made of the crisis of existing nature management models, an aggravation of contradictions, and an increase in threats and risks at the beginning of the 21st century. Modern trends in the development of effective nature management have been discussed, namely, low-waste technologies, technoecopolises, agroecopolises, and green clusterization. We have generalized and suggested conceptual prospects in the realm of effective nature management: the concept of a New Ecological Policy and a new “ecopolicy of containment.” We have explored the possibility of introducing the culture of nature management contributing to reinforcing the necessary rules and regulations—the binding force of the system of restrictions and prohibitions for humans in nature management, with due regard for the sustainability of natural systems. Emphasis is placed on a crucial need for changes in mass-scale consumer stereotypes and for an increase in the number of green technologies and production and the furthering of ecological education and medical–ecological tourism, as well as the importance of reorientation of the attitudes of the population from ecological–consumer to social–spiritual values in accordance with the Code of the Culture of Nature Management. We have substantiated the need for integrating the economic determinism of nature management and the ecological–economic imperative of sustainable development based on a noospheric approach.
Keywords:
sustainable nature management
green technologies
nature-compatible technologies
new ecological policy
culture of nature management
noosphere
issue-copyright-statement© Pleiades Publishing, Ltd. 2022
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pmcINTRODUCTION
The development of life, the maintenance of species diversity, and even the emergence of new organisms is possible only if there are favorable environmental conditions. In the history of the Earth, due to changes in the natural environment, many organisms have disappeared without a trace and others suddenly appeared, more developed and adapted, with a unique body structure and exceptional abilities [1–6]. During the appearance of Homo sapiens, on the one hand, all possible ecological niches had already been filled, but, on the other hand, there were favorable natural conditions for its existence. Today the most important global duty for a person is to maintain the environment of their habitat at the proper level. The unwillingness to fulfill this function threatens humanity with various dangers and, ultimately, extinction. The COVID-19 pandemic clearly demonstrates that it is impossible to eliminate global risks only by the development of medicine and the healthcare system [7, 8].
Man is an integral part of the single “living organism” of the Earth’s biosphere and must ensure the waste-free activity of all living things and maintain the most effective natural mechanism—the circulation of matter, energy, and information. According to the law of internal dynamic equilibrium, matter, energy, information and the dynamic qualities of individual natural systems in their hierarchy are interconnected so much that any change in one of these indicators causes concomitant functional–structural quantitative and qualitative changes that preserve the total amount of material–energetic, informational, and dynamic qualities of the system where these changes occur, or in their hierarchy.
Human economic activity has led to changes in biogeochemical cycles and the destruction of individual components of its “biological” link—many species of animals and plants—which makes this “living organism” sick and disturbs the human habitat, in some places completely destroying and degrading it.
Thus, in modern realities, the problem of effective nature management goes far beyond the scope of economic or social issues, but is directly related to the very existence of human civilization; that is, it refers to global, worldwide problems that require their solution in the foreseeable future.
EVOLUTION OF THE NATURE MANAGEMENT SYSTEM
One important question is, when did humans begin to engage in environmental management in the current sense of this term? From a modern point of view, environmental management is the science of the rational and balanced use of natural resources; it is the involvement of territorial complexes of the natural environment and their resources in the process of social production, culture, and recreation, as well as their rational and balanced use, protection, restoration, and transformation [9].
It is believed that the history of mankind began from 3400–3300 B.C. with the advent of writing [10]. However, this is not entirely accurate, since even before that time, human society actively interacted with the environment [1–3]. Thus, a number of researchers connect the beginning of the history of mankind with the appearance of behavioral signs similar to the characteristics of modern people. The time frame is quite difficult to establish and is the subject of a dispute between scientists, ranging from 200 000 to 40 000 B.C. [11, 12].
The most correct, in our opinion, is the neurobiological approach [13], according to which representatives of the genus Homo became behaviorally modern people with the acquisition of prefrontal synthesis (PFS), which is a conscious purposeful process of synthesizing new mental images. This date is defined as 42 000 B.C., i.e., coincides with the time of the appearance of works of art—images of figures of people and animals [14, 15] (see Fig. 1). This important event in the history of mankind provided the grounds for American researcher V.V. Torvich [1–3] to single out the first group of resources during this period of time (consisting of similar types of resources), “new mental images,” which are very important for the development of human society.
Fig. 1. Block diagram of a comprehensive assessment of the ecological and economic balance of the territory. NP, natural protection of the territory; NRP, natural resource potential; AL, anthropogenic load; EES, ecological and economic state of the territory; and EEB, ecological and economic balance of the territory.
According to V.V. Torvich, “resources are tools, things, qualities, and methods that can be used to achieve human goals” [2, p. 48]. In total, in the history of mankind, the author identified 26 groups of resources: from new mental images to artificial intelligence (AI).
The largest amount of new resources was mastered by humans during the Holocene period (11 700 B.C.) (see Fig. 1), when climatic conditions became most favorable for the development of human activity [1–3]. The cold climate on Earth has changed to a warmer one. The most dramatic warming occurred around 9700 B.C. Since this period, mankind has been able to successfully domesticate many plant and animal species (see Fig. 1), which has created unprecedented opportunities for various types of economic activities. A rapid increase in population began. In 2019 A.D., 7.6 billion people lived on Earth, which is 1 million times more than in 1000 B.C. [16, 17], primarily due to the high rate of technological breakthroughs. Traditional nature management is increasingly becoming a thing of the past. New types of nature management have appeared, on the basis of which the industrial period (stage) in the development of human society started several centuries ago, gradually giving way to the postindustrial one. These periods are characterized by the fact that the social systems created in them increasingly depend not on the effect of influences, but on the consequences of the development of the systems themselves [18–21].
In connection with the threat of an ecological catastrophe, to which human society as a result of its economic activity (especially over the past decades) has come close, there is a need to revise the old approach and develop new ones that can stop destruction and death and ensure the further development of mankind. How does one see the further development of human society? V.V. Torvich [1–3] believes that humanity is subject to the so-called directed process and is moving towards an increase in the number of “great” opportunities for its development. This is confirmed by the increase in the number of various resources for development, which cannot always contribute to it and often lead to the degradation and death of all living things. As for the statement about the controllability of the process of emergence of new resources, technologies, tools, methods, etc., there is no evidence for this. It is only obvious that new resources expand the possibilities of influencing the environment [1, 3, 18, 20].
Human society must adequately respond to various threats and challenges, and this is the main and only condition for its development and preservation. The creativity of people who make new resources is what determines the development of human society today. However, creativity must be controlled, humane, and not provide conditions for self-destruction and the death of mankind. The ever-increasing insatiability of the modern consumer society, which negatively affects the natural environment, is manifested in the uncontrolled development of the market for biotechnologies, genetic engineering, and nanotechnologies, which in the future can cause irreversible consequences—mutations and the emergence of new viruses and diseases, which can lead to the extinction of humans on Earth. In this case, we are talking about irresponsible scientific activity in modern civilization.
The alternative is the development of low-waste technologies, technoecopolises, agroecopolises, and green clusters, which can minimize the impact of by-products of technogenesis; technogenic accidents and disasters should be reduced by decreasing the energy intensity of the economy and creating autotrophic natural–anthropogenic ecosystems [19–23].
There are a number of prerequisites for the development of this direction, first and foremost, the growth of our knowledge and ideas about the structure and patterns of functioning of the biosphere, geo-eco-sociosystems, and the rapid development of green technological innovations that make the goal quite feasible. Today, a number of countries are developing low-waste industries and closed life support systems for outer-space, underground, underwater, and arctic purposes and sustainable green technologies and concepts. Cities of the future, from the point of view of the principle of autotrophy, are considered practically closed geosystems with a predominance of the eco-urban structure [24, 25].
According to experts [26], environmentally compatible technologies must correspond to the natural features and patterns of the Earth’s territory, cause no harm to nature, and be in harmony with it.
In recent years, as part of environmentally compatible technologies that are used on living organisms or in contact with them, nanotechnology products, hybrid and bionic devices, and biorobotic systems [26, 27] stand out; their environmental consequences are difficult to imagine or predict.
Environmentally compatible technologies include alternative energy—nontraditional ways of obtaining, transmitting, and using energy. Alternative energy sources are understood as renewable natural resources: water, sunlight, wind, biofuels, etc. However, the replacement of oil, gas, coal, and wood combustion technologies with alternative energy does not exclude its negative impact on the natural environment. This can be a serious reason for revising the prospects for its further development.
MODERN DIRECTIONS OF THE DEVELOPMENT OF EFFICIENT NATURE MANAGEMENT
Modern environmental management is determined by three main indicators [1, 2, 5]: (1) the balance between the production (profit-generating) and environmental (green) sectors of the economy, (2) the creative activity of the population in two directions: national (to work for the state) and individual (to ensure their livelihoods), and (3) the balance between real and monetary efficiency of production.
As was shown by our calculations [20], for the regions of Russia and the world, a balanced and harmonious ratio of the main indicators of nature management is created when their ratio is 1.0–1.5:
1 < (PGS/GES) < 1.5, where POS is a profit-generating sector and GES is a green economic sector;
1 < (NCAP/ICAP) < 1.5, where NCAP is the nationwide creative activity of the population and ICAP is the individual creative activity of the population;
1 < (REP/MEP) < 1.5, where REP is the real efficiency of production and MEP is the monetary efficiency of production.
For example, the profit received from production activities provides a balance between the sphere of production and services, as well as the quality of the natural environment with its constant improvement [5].
If the values in the considered ratios exceed 1.5, then this indicates economic and environmental problems (a decline in production, a rapid depreciation of assets, pollution and degradation of the natural environment, etc.), which manifests itself in the form of economic, financial, and other crises that are cyclical. Thus, an increase in environmental safety and sustainability of development is seen only in a balanced approach and harmony between competing interests.
Increasing the efficiency of nature management, both from an economic and environmental point of view, is likely an insufficient measure, but it postpones the onset of a global environmental catastrophe for a certain period [18–21]. Therefore, effective environmental management can be considered with full confidence as a new “resource package” for the development of mankind, when the value of the results of this social and production activity exceeds the value of the natural resources consumed in this case.
The current crisis in the models of nature management is also due to problems in the environmental policy of Russia and other countries. The concept of the New Environmental Policy (NEP) of environmental expert A.I. Kalachev [28] deserves close attention, placing the following emphasis:
(i) The state is the main beneficiary of solving the problems of environmental protection and nature management.
(ii) Human-centeredness: the state is a partner for business and citizens in solving problems, and the main customer of environmental services.
(iii) There is a guideline for solving environmental problems that reasonably depend on the existing shortcomings of nature management models.
Understanding the threats looming over society (environmental disasters, pandemics, and economic crises) is a global challenge for fundamental science—the need to develop a new containment methodology (noospheric convergence) and create modern production, management, social, educational and other technologies on its basis [19].
It is urgent to achieve an ecological and economic balance on Earth based on the noospheric concept, efficient nature management, and the principles of sustainable development (see Fig. 1). The world, according to the capitalist model of society and based on Adam Smith’s idea of economic growth, gradually ceases to be attractive and loses its relevance [18–21].
The noospheric approach is the basis of the modern development of human society. It is a global concept aimed at a gradual transition to autotrophy, strategic initiatives and planning, a new environmental policy, the development of local communities (civil society), and the maximum conservation of natural landscapes and ecosystems. It can be viewed as a kind of convergence at the intersection of technological innovations, as well as economics, ecology, education, which will bring human society to a fundamentally new level of development [19].
Undoubtedly, the creation of the noosphere as an area of interaction between nature and society is associated with the emergence and formation in the biosphere of the Earth of the bearer of consciousness (mind)—humanity. Hence, consciousness is the basis of the noosphere. Its state completely depends on the adequacy of the reflection by the consciousness of humanity of the relationship between it and nature [25–27].
In modern realities, consciousness and its manifestations are, to a large extent, spontaneous and destructive for the biosphere and the geographical sphere as a whole. Obviously, this situation will continue until our consciousness is freed from the idea of anthropocentrism and humanity learns to adhere to objective natural laws and subordinate its needs to them.
The level of responsible consumption of natural resources in the sphere of production, aimed at meeting human needs, is determined by the culture of nature management [18, 19]. As a scientific direction, it studies the principles of rational use of natural resources, including the factors of anthropogenic and technogenic impacts on nature and their consequences for the population. The culture of nature management not only contributes to the consolidation of the necessary rules and norms, but also acts as a binding force for a system of restrictions and prohibitions for humans in the processes of nature management and the regulation of economic activity taking into account the sustainability of natural systems.
The culture of nature management is a membrane through which human interaction with nature takes place. Its most important direction, as we noted above, is the development of the mental qualities of the individual, primarily spirituality and harmony.
To balance the processes of nature management, it is extremely necessary to change consumer stereotypes; increase the number of green technologies and industries; develop environmental education, medical and environmental tourism, i.e.; reorient people from environmental–consumerism to social–spiritual in accordance with the Code of the Culture of Nature Management [18, 19], which consists of two sections that have specific postulates.
The first section considers the limits of human adaptation to nature, namely the following postulates:
(i) Nature is the natural source of human vitality; we cannot be allowed to deplete it or needlessly waste it.
(ii) Man-made quasi-natural developments may conceal unknown, untested dangers; therefore, before offering innovations, constantly confirmed boundaries for their safe use should be indicated.
(iii) We cannot change natural conditions without taking into account even the smallest negative consequences, because they can cause unpredictable natural and man-made disasters.
(iv) Nature must be constantly taken care of by restoring its potential, and this restoration requires the same efforts and costs as are necessary for the extraction and consumption of natural resources.
(v) Humans are children of nature, and their increasing power should not be directed to its oppression, but to ensuring the creation of mutually beneficial and mutually enriching technologies for nature management.
The second section discusses the limits of nature’s adaptation to man, expressed in certain rules and prohibitions:
(i) One must not destroy nature; mankind has become powerful and capable of causing irreparable harm.
(ii) It is necessary to limit and control the level of scientific and technical progress in terms of possible damage to nature.
(iii) Natural resources cannot be used for excessive personal enrichment; they should be distributed in proportion to ability and labor.
(iv) One cannot build a relationship with nature built on half-truths: introducing even a small lie hidden underneath a grain of truth into the technologies of nature management will destroy nature over time and bring great misfortune.
(v) One cannot use natural wealth for excesses, praise, and out of envy for others, and the acquisition of the gifts of nature should be conditioned by the need for their consumption.
The culture of nature management, according to the Code of the Culture of Nature Management, is becoming the most important mechanism for achieving effective nature management, and we have to admit that other mechanisms are secondary and, without taking into account its requirements, lead to the destruction of the natural environment.
CONCLUSIONS
The development of human society and related nature management during the Holocene period (11 700 years) is characterized by an ever-expanding use of natural resources and the rapid emergence of new resources (genetic engineering and nanotechnologies), which has led to unprecedented pressure on the natural environment and put the world on the brink of ecological disaster.
It should be noted that the current environmental crisis is perhaps the deepest in the periods of modern and recent history, and it is global in nature. Today, there is no single scientifically based approach to overcoming the ecological crisis, and there is no universal trajectory for the development of human society. Existing standards, regulations, and calls for the formation of a green economy and green technologies and cities for the environmental protection of the economy and regulations only temporarily postpone the onset of regional crises and a global environmental catastrophe [27, 29–31].
Obviously, in the 2000s, ecology, the rational use of natural resources, and environmental protection are becoming the leading force in the development of society. Nondecreasing emissions of ecopollutants, pseudoscientific concepts of energy supply, and gray technologies lead to local and regional environmental and economic crises and regional and global drops in the GDP. The scenarios of A. Peccei and A. King [32], according to which the global economic growth was supposed to stop in 2020, was justified to some extent, given the coronavirus pandemic.
The existing system of global consumer nature management leads to the fact that the main goal of society is stagnation and survival, rather than development and coevolution with nature. Understanding the threat of the COVID-19 pandemic looming over human society, global climate change poses a challenge to science, primarily geoecology and nature management, environmental resource science, etc., of enormous socioeconomic significance, as well as the further development of new concepts and models: the Ecopolitics of Containment and the New Environmental Policy. It is necessary to integrate the economic determinism of nature management and the ecological and economic imperative of the sustainable development of countries and regions based on the noospheric approach in the territory–resources–population–economy–ecology system.
CONFLICT OF INTEREST
The authors declare that they have no conflicts of interest.
Translated by S. Avodkova
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China Int Strategy Rev.
China International Strategy Review
2524-5627
2524-5635
Springer Nature Singapore Singapore
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10.1007/s42533-022-00119-w
Original Paper
The evolution of the ‘QUAD’: driving forces, impacts, and prospects
Wei Zongyou [email protected]
grid.8547.e 0000 0001 0125 2443 Center for American Studies, Fudan University, No. 220, Handan Rd, Yangpu District, Shanghai, China
4 12 2022
117
8 9 2022
7 11 2022
© The Institute of International and Strategic Studies (IISS), Peking University 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The evolution of the Quadrilateral Security Dialogue, commonly known as “the Quad”, from a senior-level security dialogue involving the U.S., Japan, India, and Australia, to leader-level summit since 2017, speaks volumes about the rapidly changing strategic landscape in the Indo-Pacific. From the very beginning, there have been three driving forces behind the rebirth, development, and improvement of the Quad: balancing China’s power and influence; promoting practical cooperation; and shaping regional order. The evolution of the Quad, especially its overt anti-China rhetoric and activities, has negatively affected political, economic, and security order in the region. Looking ahead, although the Quad is not envisioned to become an Asian NATO, it is poised to strengthen practical cooperation, policy coordination, and strategic consultations in efforts to balance and compete with China. That said, its future direction hinges on how China–U.S. relations evolve and is thus shrouded in uncertainty.
Keywords
QUAD
Indo-Pacific
China–U.S. relations
The National Social Science Foundation of ChinaNo. 20AGJ009 Wei Zongyou
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pmcIntroduction
On May 24, 2022, the leaders of the Quad nations—the United States, Japan, India, and Australia—met in Tokyo for the fourth time (the second in-person meeting). Under U.S. President Joseph Biden’s watch, the Quad, which was revived in 2017 as a counterbalance against China’s growing power and influence in the Asia–Pacific, has been elevated from a minister-level meeting to a leader-level summit, and greatly expanded in its scope. The Biden administration and relevant parties aim to turn this informal dialogue into a premier platform for strategic consultation, policy coordination, and practical cooperation in the Indo-Pacific and a tool for shaping an emerging regional order favorable to the interests, values, and vision of the United States and its allies and partners (White House 2022a).
The evolution of QUAD
The Quad was first established in the wake of the 2004 Indian Ocean Tsunami to coordinate humanitarian assistance and disaster relief. “While the humanitarian relief mission ended in mid-January 2005, a new seeding of the Quad framework emerge in the leaders’ minds” (Pant 2022). In 2007, then-Japanese Prime Minister Shinzo Abe took steps to turn the four-nation response to the tsunami into a more formal, quadrilateral security dialogue, with the goals of enhancing maritime security along the “Confluence of the Two Seas” and facilitating cooperation among the four democratic nations in view of the growing influence of China (Prime Minister of Japan and His Cabinet 2007). The four countries held their first Quad meeting on the sidelines of the ASEAN Regional Forum in May 2007 and conducted their joint naval exercises in the Bay of Bengal, together with Singapore. However, the Quad fell apart soon afterward, due to China’s suspicion and displeasure over the intention and orientation of this new group (Buchan and Rimland 2020), and the differing interests and considerations among the four countries (Marlow 2022; Liu and Xu 2021; Yang and Ren 2022).
Ten years later, the Quad was revived when Donald J. Trump became the U.S. President in 2017. But before the Quad returned, it was again the Japanese Prime Minister Abe who took the initiative and pushed it forward. In 2012, when Abe became Prime Minister for the second time, he published an opinion piece titled, “Asia’s Democratic Security Diamond” on an American think tank website, in which he expressed his worries about China’s activities in the South and East China Seas, claiming that “peace, stability, and freedom of navigation in the Pacific Ocean are inseparable from peace, stability, and freedom of navigation in the Indian Ocean,” and argued for “a strategy whereby Australia, India, Japan, and the U.S. state of Hawaii form a diamond to safeguard the maritime commons stretching from the Indian Ocean region to the western Pacific” (Abe 2012).
In 2016, a year before Trump became President, Abe put forward Japan’s “free and open Indo-Pacific” strategy. In his 2016 address to the sixth Tokyo International Conference on African Development in Nairobi, Kenya, he declared that “Japan bears the responsibility of fostering the confluence of the Pacific and Indian Oceans and of Asia and Africa into a place that values freedom, the rule of law, and the market economy, free from force or coercion, and making it prosperous” (Ministry of Foreign Affairs of Japan 2016). According to Japanese scholar, Abe’s “free and open Indo-Pacific” strategy has three pillars: political, economic, and security. Politically, this strategy aims to strengthen democratic values in the region. Economically, Japan wants to promote infrastructure development and economic connectivity in the region together with the U.S., India, and Australia, to compete with China’s Belt and Road Initiative. On the security pillar, Japan will deepen security cooperation with the U.S. and other Quad members and build closer ties with Southeast Asian countries (Takenaka 2022). According to a Chinese scholar, Abe’s interest in and push for his Indo-Pacific strategy were mainly driven by two considerations: geostrategic competition and regional cooperation, with the former based on Japan’s realistic strategic interest, and the latter cultivating a more favorable regional environment (Lu 2021).
After Trump entered the White House, the Abe administration successfully persuaded the Trump administration to accept Japan’s “free and open Indo-Pacific” concept as an overarching strategic framework to unite like-minded partners, protect the U.S. values and interests, and guard against China (Hu and Meng 2020). In November 2017, officials from the United States, Japan, India, and Australia restarted the Quad after a decade’s hibernation at the sidelines of the 31st ASEAN Summit in Manila. The officials discussed a wide range of issues, including maritime security, North Korea, connectivity, support for the “Free and Open Indo-Pacific” concept, and the promotion of a rules-based system in the Indo-Pacific region (Buchan and Rimland 2020).
In November 2019, in response to the proposal by the Trump administration, the Quad was promoted from a senior official-level dialogue to a ministerial-level dialogue. The foreign ministers of the Quad met for the first time in New York to discuss cooperation on counterterrorism, humanitarian assistance and disaster relief, maritime security cooperation, development finance, and cybersecurity. They also looked forward to coordinating efforts to promote their shared vision for a “free and open Indo-Pacific” region (U.S. Department of State 2019).
During the 4-year Trump administration, the Quad not only came back to life, but also entered a new period of expansion and increased institutional consultations. The Quad members held a seven-round senior official-level dialogue, and a two-round ministerial-level dialogue, and their dialogue and consultation covered issues as wide-ranging as maritime security, counterterrorism and humanitarian and disaster relief, infrastructure and economic connectivity, and support for ASEAN centrality, among others.
When Biden came into power in 2021, he upgraded the Quad to a leader-level summit, holding a first-ever virtual leaders’ summit in March 2021 and an in-person summit in September 2021. During the virtual summit, the four countries established three expert working groups, namely, the vaccine working group, the critical- and emerging-technology working group, and the climate working group, to combine efforts to jointly deal with the challenges in the above-mentioned issue areas and to provide a positive vision in the Indo-Pacific (White House 2021a). The Quad leaders held two more summits in 2022, a virtual summit in March and an in-person one in May. During the May summit, the four leaders established three more expert working groups in cyber, space, and infrastructure, greatly expanding the Quad’s areas of cooperation. The Quad also launched a new initiative, the Indo-Pacific Partnership for Maritime Domain Awareness (IPMDA), to support enhanced and shared maritime domain awareness in the Indo-Pacific, in the name of responding to humanitarian and natural disasters and combating illegal fishing (White House 2022b).
By upgrading the Quad to a leader-level summit, regularly holding ministerial- and senior-level dialogue, and establishing six expert working groups to facilitate practical cooperation on issues of shared interest, the Biden administration is trying to turn the Quad into a premier informal strategic consultation platform, not only to pool resources among the members and like-minded partners as a way to better compete with China, but also to provide “public goods” to increase its attraction and shape the emerging regional order in its favor.
Driving forces behind
Among the forces driving the formation, rebirth, and elevation of the Quad since 2007, three are outstanding:
Balancing China
Since its first formation as a quadrilateral security dialogue in 2007, “balancing China” has been the implicit and even explicit objective and driving force behind the Quad. For Japan, China’s growing power and economic influence overshadows what was once Japan’s leading economic status in Asia. What’s more, the diplomatic and political relations between China and Japan cooled and worsened since the beginning of this century due to historical issues, such as Japanese leaders’ repeated visits to Yasukuni Shrine, where Japanese World War II war criminals were shrined and worshipped, and the rising territorial disputes concerning the Diaoyu Islands. Japan has increasingly viewed China as a rival to its economic influence in Asia and a security challenge, especially after Shinzo Abe came into power (Green 2022, 55–64). By formally establishing the Quad, the Abe administration hoped to forge a China-balancing group among the four democracies based on common values (Chen 2020).
As for India, China’s comprehensive strategic partnership with Pakistan and India–China border disputes has always been a thorn in the side for India. The commencement of the China–Pakistan Economic Corridor (CPEC) in 2014 only increased India’s sense of “encirclement” with India speaking openly against China’s Belt and Road Initiative in general, and CPEC in particular (Baruah 2018). Then, in June 2017, Indian and Chinese troops confronted each other at the Doklam plateau near the borders of China and Bhutan, after Indian troops crossed the border to prevent China’s road construction near Doka La pass. The 2-month-long military standoff is the most serious confrontation between the two countries in decades. Although China and India agreed to disengage troops to end the standoff, harm was done to bilateral relations, which prompted India to join the Quad dialogue in November 2017. Again, in June 2020, there was a deadly clash between Chinese and Indian soldiers at the border area of Galwan Valley, which left dozens of soldiers dead or wounded. After the incident, the Indian chief of defense, Staff General Bipin Rawat claimed China as “enemy number one” facing India (Times of India 2021, 2–21). Given China’s growing economic influence in South Asia and the border incidents, the Modi administration increasingly came to view China as a major security challenge for India and a strategic adversary. By joining the Quad, India hoped to enlist support from the U.S., Japan, and Australia in its competition with China (Liu 2021). Additionally, India needs the other parties’ help to make sure that Asia will not become dominated solely by China, as India’s famous strategist C. Raja Mohan points out (Mohan 2021).
Australia has been an economic beneficiary of China’s economic rise and rapid development for the past several decades. However, Australia is becoming increasingly worried about its economic dependence on China (Eisentraut and Gaens 2018) and China’s perceived or potential “malign influence” in Australia (Searight 2020, 3–40). According to a Chinese scholar, Australia, along with Japan, are the two countries pushing the hardest for the establishment of the Quad. “Their intention of keeping the United States in the region and bringing in India as a check on China has become the fundamental driving force for the resumption and accelerated cooperation of the Quad” (Zhang 2019). In 2017, the Malcolm Turnbull administration published its Foreign Policy White Paper, in which it argues that the international order is undergoing great changes as anti-globalization intensifies, global governance is becoming harder, and rules are being contested. In the Indo-Pacific, the paper claims, China’s power and influence are growing and, in some ways exceed, that of the United States. “Like all great powers, China will seek to influence the region to suit its own interests.” As a result, “we will face an increasingly complex and contested Indo-Pacific” (Australian Government 2017).
Since 2017, and especially after Scott John Morrison became Prime Minister in 2018, Australia–China relations deteriorated rapidly. The Morrison administration claimed China interfered in Australian domestic politics and passed laws limiting Chinese investment in Australia and banning the Chinese company Huawei from participating in Australia’s 5G telecommunication development. Furthermore, Australia also accuses China of changing the status quo of the South China Sea, and “asks” China to comply with the 2016 South China Sea Tribunal reward, which China sees as illegal and void. As Australian–China relations deteriorate and Australia’s concerns about China grow, Australia is more than happy to join the Quad to gang up against China.
After Donald J. Trump entered the White House in 2017, he not only put his “America First” foreign policy idea into practice, but also declared China the strategic competitor of the United States. The U.S. China policy transformed from a more balanced approach of “competition plus cooperation” to an unbalanced one of mainly focusing on containing China (Wang 2019). Under his watch, the U.S. initiated a trade war, a tariffs war, and a technology war against China, and published the first Indo-Pacific strategy aiming at balancing China’s increasing power and influence in the Indo-Pacific region. From the U.S. perspective, the traditional “hub and spoke” alliance system in the Asia–Pacific is not competent enough to deal with a rising and more “assertive” China, and needs to be complimented by adding more capable and “willing” partners (Chen 2020). By reviving the Quad, the United States can pool together the resources of the South Asia heavyweight India, the economic and technology powerhouse Japan, and the culturally similar and geographically important Australia to better compete with China and counterbalance China’s power and influence in the Indo-Pacific.
Promoting practical cooperation
By establishing the Quad, the four countries also want to strengthen practical cooperation and provide regional “public goods,” collectively, to compete with China. Since 2017, the Quad members have taken a series of steps to strengthen their cooperation in the following areas.
Maritime security
Ever since the first senior official-level Quad dialogue in 2017, maritime security has been a top issue. For one thing, the tsunami in 2004 and earthquake and tsunami in Japan in 2011 underscored the devastating effects of natural disasters and humanitarian risks lurking in the maritime Indo-Pacific. For another, the maritime disputes in the East and South China Seas concerning China and the relevant parties have ratcheted up in recent years, destabilizing relations in the region. Third, for the United States, China’s claims in the South China Sea run diametrically counter to the U.S. style “freedom of navigation and overflight” and if allowed to prevail, would negatively impact its Navy operations and power projection in the world in general and in the Indo-Pacific in particular. A report by the U.S. Congressional Research Service warned that, if China’s claims to the South China and its’ interpretation of freedom of navigation prevail, it “could potentially require changes (possibly very significant ones) in U.S. military strategy, U.S. foreign policy goals, or U.S. grand strategy” (U.S. Congress 2020).
As a result, the Quad members have coordinated their positions concerning the East and South China Seas disputes and freedom of navigation and overflight “right” in the South China Sea, conducted joint maritime exercises in the Indo-Pacific, provided maritime assistance to Southeast Asian countries to improve the latter’s maritime law enforcement and humanitarian aid and disaster relief capabilities, and launched the IPMDA to “support enhanced, shared maritime domain awareness to promote stability and prosperity” in the Indo-Pacific (White House 2022b). Through those measures, the Quad members hope to speak with “one voice” against China’s maritime claims and activities in the East and South China Seas, provide regional maritime “public goods”, and win the goodwill of the regional countries.
Infrastructure development
Infrastructure development is another area where the four countries cooperate to provide an alternative to China’s Belt and Road Initiative. During the Trump administration, the United States, Japan, and Australia established a Blue Dot Network in 2019 to assess and certify infrastructure development projects worldwide on measures of financial transparency, social, and environmental sustainability, and impact on economic development, with the goal of mobilizing private capital to invest (U.S. Department of State n.d.(a)). The Trump administration even revamped its overseas finance development agency and established the U.S. International Development Finance Corporation in place of the Overseas Private Finance Corporation. The underlying motivation of the Quad’s moves was to write the rules of infrastructure development, undermine the appeal of China’s BRI, and act as a counterbalance to China’s soft power in the region (Liu 2019).
Under Biden’s watch, the Quad held a first-ever Quad Leaders’ Summit in Washington in September 2021, where the four leaders announced new Quad infrastructure partnerships to “coordinate our efforts, map the region’s infrastructure needs, and coordinate on regional needs and opportunities,” and “will cooperate to provide technical assistance, empowering regional partners with evaluative tools, and will promote sustainable infrastructure development” (White House 2021b).
Through the years, the Quad’s cooperation on infrastructure evolved from naming and shaming China’s BRI to tentatively providing an alternative. They know from their interaction with regional partners that it will not work just to say “bad things” about China’s infrastructure development; they must provide something concrete and satisfy the region’s growing infrastructure needs (Lew and Roughead 2021). By acting together and leveraging their respective comparative advantages, the Quad members hope to not only discredit China’s BRI, but to provide an alternative and win “the struggle of heart” in the region (Zhai 2022; Liu 2019).
Technology and supply chains’ security
After the Trump administration initiated the trade war with China in 2018, it soon turned its eyes on China’s hi-tech companies and strategic emerging industries, including semiconductors, 5G, EV batteries, Artificial Intelligence, quantum technology, biotechnology, and autonomous robotics. The U.S. not only imposed sanctions on China’s hi-tech leaders, such as ZTE and Huawei, and banned their 5G services in the U.S., but also welcomed and coordinated with other Quad members to ban Huawei and ZTE 5G services (Hartcher 2021). The US even launched “the Clean Network” to pressure and dissuade other allies and partners from using Huawei or ZTE 5G services, among others (U.S. Department of State n.d.(b)). The motivation behind the Trump administration’s hi-tech war was colored and reinforced by growing negative attitudes toward China, the U.S. strategic establishment, and the impacts of China’s indigenous innovation rush on U.S. economic, technology, and security interests (Sun 2019). By those measures, the Trump administration aimed to kill three birds with one stone: strengthen policy coordination among the Quad and beyond, exclude Chinese hi-tech companies from the U.S.-launched “Clean Network” supply chains, and prevent China’s technology dominance.
The Biden administration largely inherited the Trump administration’s technology Cold War against China and sees technology and supply chain security cooperation with other Quad members as a high priority. At the first virtual Quad leaders meeting in March 2021, the four leaders agreed to establish a critical and emerging-technology working group to facilitate cooperation on international standards and innovative technologies of the future (White House 2021a). Six months later, the Quad announced that it would launch a semiconductor supply chain initiative “to map capacity, identify vulnerabilities, and bolster supply-chain security for semiconductors and their vital components”. In addition to technology supply chain security, the Quad also intends to cooperate on “secure supply chains” for vaccine production and clean energy (White House 2021c), and has deepened its collaborative efforts in climate change, public health, space, and cybersecurity. In doing so, the Quad hopes to increase the “stickiness” of the grouping, improve its image as a regional public goods provider, and enhance its collective ability to compete with China.
Enhancing voice and status in regional affairs
If serving as a counterbalance to China and promoting practical cooperation are the common denominators, for India, Japan, and Australia, the “junior partners” of the U.S., the Quad also serves as a vehicle to improve their voice and status in regional affairs. India has long aspired to be an influential power in regional and world affairs. In February 2015, less than a year after he took office, India’s Prime Minister Narendra Modi said, “the world is keen to embrace India, and India is moving forward with confidence.” He challenged India’s diplomats to “use this unique opportunity to help India position itself in a leading role, rather than just a balancing force, globally” (Indian Press Information Bureau 2015). With the Quad, as the Vice President of Studies and Foreign Policy at Observer Research Foundation at New Delhi said, “India can rise above its middle-power status” and even project its influence beyond the Indo-Pacific (Pant 2022). Indian External Affairs Minister S. Jaishankar viewed the growing Quad grouping as a reflection of the “rise of Asia” as well as “the repositioning of big powers”, and said: “From an Indian perspective, it is also a statement of its growing interests beyond the Indian Ocean.” He said that India’s place within the Quad made sense given its “growth, confidence, and worldview”, and emphasized that “the firm establishment of Quad” is one of the major diplomatic accomplishments of the Modi government (Krishnankutty 2022).
For Japan, the primary driver behind the rebirth of the Quad is “uniting its Quad partners around its own vision for the Indo-Pacific” as a “significant success for Japan’s reinvigorated diplomatic agenda,” and “indicative of the greater efforts that Japan is investing in its external relations as part of its vowed ‘proactive contribution to international peace’” (Wilkins 2022a). Given the U.S. unwillingness to bear responsibility and retreat from the world stage under the Trump administration’s America First banner, by establishing and joining the Quad, Japan hopes not only to “entrap” the U.S., but also acts as a leader by default in setting a regional agenda to better serve Japan’s national interests in an increasingly uncertain world. Japan can also use its technological prowess, military potential, and economic power to consolidate its “leading role” in the Quad’s practical cooperation (Koga 2022). “Tokyo’s sustained championship of mini-lateral cooperation through the Quad and other mechanisms is testament to the emerging leadership role the country has assumed in regional affairs” (Wilkins 2022a).
Australia, a middle power whose relations with China have soured in recent years, is more than happy to embrace the Quad. For Australia, the Quad not only binds the U.S. in an exclusive small group, but also provides an additional assurance by forging more close relations with other major Asian powers besides the U.S., in a time of growth in the “looking inward trend” in the U.S. By joining an exclusive “club”, together with the U.S., India, and Japan, to set the agenda in regional affairs, expand practical cooperation in infrastructure, maritime security, supply chains, among other areas, and help shape the regional order, Australia can elevate its voice and status in regional affairs. As one Australian scholar emphasized, “its interaction with these major powers, gains access to advanced defense technologies and acquires a more influential voice in shaping the regional security environment.” He adds: “In this respect they add another powerful instrument to Canberra’s diplomatic and strategic toolkit as Australia faces unprecedented challenges to its national security” (Wilkins 2022b).
In addition to the above-mentioned reasons, as an informal security dialogue mechanism, the Quad has its own “comparative advantage”. It is small with only four members sharing “democratic values”. It’s informal without the burden of formal treaty. This flexibility enables it to expand the issue areas on which it focuses as situations dictate.
Impacts on regional order
The rebirth and upgrading of the Quad coincided with the deterioration of China–U.S. relations and heightened the rhetoric of a new Cold War in the Asia–Pacific. Despite Biden’s repeated claims that he does not “seek a new cold war or a world divided into rigid blocs” (White House 2021d), many worry his actions and “bloc politics” did just that (Shidore 2022).
The Quad’s development and evolution in the past several years have negatively affected regional order in four ways.
Political fault line
When Abe proposed the establishment of Quadrilateral security dialogue, he viewed it as an “Asia’s Democratic Security Diamond” to guard against an “undemocratic” China’s influence and activities in the maritime Indo-Pacific. In other words, from the very beginning, the Quad has had a strong flavor of ideology competition between an “authoritarian” China and the “democratic” Quad. After Trump declared China a U.S. strategic competitor and long-term security challenge and revived the Quad, the U.S. increasingly saw its competition with China through an ideological lens. The Biden administration vows to unite democracies in Asia and around the world and make the Quad a premier group for providing regional public goods and safeguarding “democratic values” (White House 2022a).
The “democracy vs. authoritarianism” and “us against them” rhetoric and mindset not only increasingly raises China’s concerns and even hostility, but also puts great pressure on countries in the region that do not want to choose sides, threatening to create a political fault line in the Asia–Pacific. Chinese government has made its view on the Quad very clear: China is against establishing any exclusive, anti-China group or any Cold War-style camp, or any self-claimed group of democracies that preaches “democracy vs. authoritarianism” confrontation and conflict (Ministry of Foreign Affairs of the People’s Republic of China 2022a). China’s Foreign Minister Wang Yi emphasized that the Quad is the backbone of the U.S. Indo-Pacific strategy and seeks to establish an Asian NATO, to promote an outdated Cold War mindset, confrontation and geopolitical struggle, potentially endangering East Asia’s prospects for peace and development and spirit of win–win cooperation (Ministry of Foreign Affairs of the People’s Republic of China 2020). Singapore, an AESAN member, who has close relations with both the U.S. and China, has expressed its worries of increasing geopolitical competition between the U.S. and China and potentially being forced to choose sides. Singapore’s Prime Minister Lee Hsien Loong said that Singapore is worried about the growing geopolitical competition between the U.S. and China, and does not want to “pick sides”, similar to many other ASEAN countries (Tham 2021).
Economic fragmentation
As China’s economic rise accelerated after China’s entry into the World Trade Organization in 2001, China has gradually replaced the U.S. and Japan as the economic engine and driving force for economic integration in East Asia. In 2010, the China–ASEAN Free Trade Area came into force, which was the first agreement of its kind signed by ASEAN. In 2013, China initiated the BRI to facilitate the “Five Links” between China and the relevant parties. As BRI attracts more countries to join in, the U.S. and other Quad members became increasingly concerned. They viewed BRI not only as an economic initiative, but also a strategic master plan to squeeze the influence of the U.S., Japan, and other countries, and to create an economic and even political sphere of influence for China (Russel and Berger 2020). In other words, the Quad increasingly views China’s strategy as a zero-sum game requiring action by Quad members. Initially, the U.S., India, Japan, and Australia took a more negative strategy by “naming and shaming” in the hope of scaring away potential participants and sabotaging China’s BRI. When this proved ineffective, the Quad changed their strategy and coordinated to offer alternatives to BRI by launching Quad infrastructure partnerships to compete directly with China. In May 2022, under the Biden administration’s initiative, the Quad members, together with nine other countries (Fiji joined later as the 14th founding member), launched the Indo-Pacific Economic Framework for Prosperity (IPEF), to coordinate and cooperate in the area of trade, supply chains, clean economy, and fair economy, to compete economically with China.
Theoretically, more options are better for the region, and healthy competition will offer more good products and increase overall wellbeing. However, the Quad’s infrastructure and economic initiatives all exclude China and the four countries even established technology and supply chain mini-lateral groupings to de-couple from China’s technology and supply chains. If this trend continues, it will disrupt the momentum toward economic integration of the region and will likely lead to economic fragmentation. China’s Foreign Minister Wang Yi warned against this in a speech to the Asia Society in September 2022. He said, “Ideology driven, the U.S. has overstretched the concept of national security, built ‘small yard, high fence’, clamored for decoupling and cutting supply chains, pushed for ‘friend-shoring’, conceived the Indo-Pacific Economic Framework, and formed the Chip 4 Alliance. This is clearly not healthy competition. Such moves are not helpful to the U.S.’s own development. They will also disrupt global economic cooperation” (Wang 2022).
Maritime security
Under the joint efforts of China, the Philippines, and ASEAN, the situation in the South China Sea has improved considerably since 2016. China and the Philippines signed economic agreements to improve economic and diplomatic relations while shelving their maritime disputes (Baguisi 2021). China and ASEAN have also stepped up their dialogue and consultations on the Code of Conduct (COC) in the South China Sea with an eye to reach an agreement on COC before the end of 2022 (Ministry of Foreign Affairs of the People’s Republic of China 2022b).
However, despite China and ASEAN’s efforts, the Quad still puts the South China Sea disputes at the core of their maritime security cooperation and “concerns” and links it with the East China Sea disputes between China and Japan, the situation in the Taiwan Straits, and the issue of “freedom of navigation” in the South China Sea. Furthermore, the Quad members’ positions on the South China Sea, the constant freedom of navigation and military exercises in the South China Sea, and military assistance to the Southeast Asia, together with their launching of the Indo-Pacific Partnership for Maritime Domain Awareness, complicate maritime security in the Western Pacific at least in three ways. First, it may distract the joint efforts of China and ASEAN countries to reach a practical COC in the near future. Second, it will ratchet up maritime competition between China and the Quad, with each side sticking to its own interpretation of maritime interests, security, and rights. Third, it may encourage other parties of the South China Sea disputes to initiate bolder activities and thus reignite the maritime tension in the South China Sea.
ASEAN centrality
In the past several decades and especially since the beginning of this century, ASEAN and ASEAN-centered institutions have been the driving force behind East Asia (Southeast Asia included) economic integration and serve as bridges between the major players in the Asia–Pacific. This ASEAN centrality in setting the regional economic, and even security agendas has gradually been accepted by the major players in the region. Upgrading the Quad from a senior-level dialogue held at the sidelines of ASEAN and East Asia summits to leader-level summits to be held on a rotational basis, along with expanding the scope of the Quad’s areas of cooperation, greatly overshadows the role of ASEAN and threatens its centrality (Tang et al. 2020).
From the very beginning, it was clear that “most Southeast Asian states are not publicly and fully embracing the Quad, even though they are not energetically working to challenge or denounce the nascent dialogue.” Among the ASEAN countries, Indonesia, Malaysia, Laos, Thailand, and Cambodia are top skeptics of the Quad. Indonesia is especially worried about the sidelining of ASEAN, and Singapore is worried about the sharpening of the US–China competition (Laksmana 2020). According to the 2021 State of Southeast Asia Survey, less than half of the respondents thought that the Quad made a “positive” or “very positive” contribution to regional security. Just as Jonathan Stromseth said, “most ASEAN nations remain suspicious of the four-country grouping, seeing it as a challenge to ‘ASEAN centrality’” (Stromseth 2021).
Looking ahead
As an informal group, the Quad has developed from an obscure senior-level dialogue to a multilayer leaders’ summit. The dialogue has become more institutionalized with regular senior-, ministerial-, and leader-level meetings, and the cooperation among the members has expanded, especially in the areas of maritime security and economic development. Given the rapid development in the past several years, one cannot help but wonder how the current trajectory of the Quad will unfold in the future? Will it turn into, as many predict, an Asian NATO? What areas of cooperation might be added in the years ahead? What challenges might the Quad encounter in its future development?
An Asian NATO?
Since the revival of the Quad in 2017, there have been talks of forming an Asian NATO based on the Quad. In 2020, when China–U.S. relations hit a new low due to the COVID-19 pandemic, the Trump administration even floated the idea of turning the Quad into an Asian NATO. Then Deputy Secretary of State Stephen E. Biegun suggested that the Quad could be the beginning of a NATO-style alliance in Asia. “It’s something… that would be very much worthwhile to be explored,” he said at a U.S.–Indian strategic dialogue in August 2021 (Taylor 2020). However, the idea never bore fruit. India, which is not a treaty ally of the U.S. and has a long tradition of nonalignment, never agrees to join a U.S.-led alliance. Indian External Affairs Minister S. Jaishankar dismissed the notion that the Quad is an Asian NATO as “completely misleading” and warned “interested parties” who advance the idea “not to slip into that lazy analogy of an Asian-NATO” (Economic Times 2022).
ASEAN, the support of which the U.S. and the Quad both try to attract, also expresses its concerns about forming an Asian NATO and the potential to draw the region into a new cold war. As Singapore Prime Minister Lee Hsien Loong cautioned: “In Asia, the history is different. There was never a grouping in Asia which was the equivalent of NATO… So I think that that is a better configuration than one where countries are divided along a line and one bloc confronts another” (Prime Minister’s Office Singapore 2022). Given the inherent hurdles of forming an Asian NATO based on the Quad, the Biden administration makes its position very clear: The Quad will remain an informal grouping, and will not become an Asian NATO, even though it will become a premier grouping in the Indo-Pacific (White House 2021e).
In summary, the Quad will not turn into an Asian ANTO in the near future. As Gregory Poling, director of the Asia Maritime Transparency Initiative at the US-based Center for Strategic and International Studies said, “There is just not enough shared strategic interest or shared desire to accept risk on the military front” (Akhter 2021). Nevertheless, the Quad will continue its cooperation in the maritime security, cybersecurity, and other military-related cooperation and consultation, and supplement the US-centered “hub and spokes” bilateral alliances in Asia.
Areas of further cooperation
The Quad will remain informal for the foreseeable future. However, the practical cooperation, policy coordination, and strategic consultations will deepen. In the next several years, maritime domain awareness in the Indo-Pacific will be a top priority of the Quad, because, by providing a unified maritime picture, the Quad hopes to realize three objectives. First, it can keep close track of China’s maritime activities in the Indo-Pacific; not only of China’s navy activities, but also China’s large fishing fleet. Second, it can present itself as regional “public goods” provider. From the Quad’s perspective, a unified and real-time maritime picture will enable Southeast Asia countries and Pacific Islands countries to better “protect” their maritime rights, especially fish resources from being exploited by China (Pandlai and Singh 2022). Though unstated, the implicit target of the initiative is China, which the U.S. has accused of being the largest exploiter of global fishing (Zhang 2022). And third, it will likely assist the Quad in winning support from regional countries. Most Southeast Asian countries and Pacific Islands countries lack the necessary technology and means to have sufficient maritime domain awareness and therefore welcome the Quad’s offer. Representing itself as a regional public goods provider to help them will no doubt win their praise.
Supply chain and infrastructure cooperation will be the other two priority areas where the four countries hope to reduce their dependence on China’s technology and supply chains and provide an alternative to China’s infrastructure related to both “standard” and project financing. As Moody’s Vice President Nishad Majmudar said, “The economic realignment will benefit (the Quad) member countries’ technology and energy sectors as they seek to reduce reliance on Chinese-produced critical materials and technologies that are key inputs to tech and renewable energy products” (Anand 2022).
In terms of policy coordination, the Quad will further coordinate their positions on the East and South China Seas disputes, the situation in Taiwan Straits, and other hot-button issues in the Indo-Pacific region and beyond. The Quad will also enhance their cooperation in climate change, public health, space, and cybersecurity. In the area of strategic consultation, the Quad will focus on China’s foreign policy orientation and major diplomatic, economic, and security initiatives, and react in a coordinated way.
Potential challenges
As an informal grouping aiming at balancing China, promoting practical cooperation, and raising its voice and status in shaping an emerging regional order to its advantage in the context of growing US–China strategic competition, the Quad has made considerable progress in mechanism building and cooperation. Nevertheless, it may still face three potential challenges as it evolves. First, how to maintain its informality while its mechanisms become more institutionalized and areas of cooperation have multiplied. One of the virtues of the Quad is its informality and ability to offer more flexibility and comfort to its members. However, as its functions expand and mechanisms multiply, can the Quad still stay informal and resist the temptation to turn into a formal military alliance as the Trump administration once attempted? And if future US administrations again attempt to formalize the Quad, how will India, who is uncomfortable with a formal military alliance with the US, react? What impacts it will have on the cohesion of the Quad?
Second, how can it avoid mission creep? The Quad has evolved from an informal senior-level security dialogue into a multi-layered leaders’ summit covering a wide range of issues from maritime security, to infrastructure development, climate change, supply chain resilience, critical and emerging technology, and cybersecurity. As its mission expands, so its focus will dilute. Will the Quad morph into something that covers all issues of importance, while its members are not in a position to solve them and just become another cheap talk show? South Korea also expresses its interest in joining the Quad, though the Biden administration says it has no plan to invite South Korea to join for fear of further antagonizing China (Kang 2022). For how long can the Quad resist the temptation of inviting new members into its club?
Third, how can the Quad reconcile its intention of turning itself into a “premier grouping” in the Indo-Pacific and maintaining ASEAN centrality and unity? The rebirth of the Quad has already triggered concern and discord among ASEAN members. Even though ASEAN’s attitudes toward the Quad improved after the Biden administration and other members repeatedly assured ASEAN that they support ASEAN centrality and unity and intend to orient the Quad more in the direction of regional public goods provision, suspicion, and worries remain. In the context of China–US strategic competition and the Quad as a “premier grouping” in the Indo-Pacific to serve as a strategic dialogue mechanism, it will inevitably overshadow the role of ASEAN and its centrality in regional affairs.
Funding
This study was funded by The National Social Science Foundation of China (Grant No. 20AGJ009).
Declarations
Conflict of interest
The author declares that there is no competing interest regarding the publication of this paper.
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China Int Strategy Rev.
China International Strategy Review
2524-5627
2524-5635
Springer Nature Singapore Singapore
119
10.1007/s42533-022-00119-w
Original Paper
The evolution of the ‘QUAD’: driving forces, impacts, and prospects
Wei Zongyou [email protected]
grid.8547.e 0000 0001 0125 2443 Center for American Studies, Fudan University, No. 220, Handan Rd, Yangpu District, Shanghai, China
4 12 2022
117
8 9 2022
7 11 2022
© The Institute of International and Strategic Studies (IISS), Peking University 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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The evolution of the Quadrilateral Security Dialogue, commonly known as “the Quad”, from a senior-level security dialogue involving the U.S., Japan, India, and Australia, to leader-level summit since 2017, speaks volumes about the rapidly changing strategic landscape in the Indo-Pacific. From the very beginning, there have been three driving forces behind the rebirth, development, and improvement of the Quad: balancing China’s power and influence; promoting practical cooperation; and shaping regional order. The evolution of the Quad, especially its overt anti-China rhetoric and activities, has negatively affected political, economic, and security order in the region. Looking ahead, although the Quad is not envisioned to become an Asian NATO, it is poised to strengthen practical cooperation, policy coordination, and strategic consultations in efforts to balance and compete with China. That said, its future direction hinges on how China–U.S. relations evolve and is thus shrouded in uncertainty.
Keywords
QUAD
Indo-Pacific
China–U.S. relations
The National Social Science Foundation of ChinaNo. 20AGJ009 Wei Zongyou
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pmcIntroduction
On May 24, 2022, the leaders of the Quad nations—the United States, Japan, India, and Australia—met in Tokyo for the fourth time (the second in-person meeting). Under U.S. President Joseph Biden’s watch, the Quad, which was revived in 2017 as a counterbalance against China’s growing power and influence in the Asia–Pacific, has been elevated from a minister-level meeting to a leader-level summit, and greatly expanded in its scope. The Biden administration and relevant parties aim to turn this informal dialogue into a premier platform for strategic consultation, policy coordination, and practical cooperation in the Indo-Pacific and a tool for shaping an emerging regional order favorable to the interests, values, and vision of the United States and its allies and partners (White House 2022a).
The evolution of QUAD
The Quad was first established in the wake of the 2004 Indian Ocean Tsunami to coordinate humanitarian assistance and disaster relief. “While the humanitarian relief mission ended in mid-January 2005, a new seeding of the Quad framework emerge in the leaders’ minds” (Pant 2022). In 2007, then-Japanese Prime Minister Shinzo Abe took steps to turn the four-nation response to the tsunami into a more formal, quadrilateral security dialogue, with the goals of enhancing maritime security along the “Confluence of the Two Seas” and facilitating cooperation among the four democratic nations in view of the growing influence of China (Prime Minister of Japan and His Cabinet 2007). The four countries held their first Quad meeting on the sidelines of the ASEAN Regional Forum in May 2007 and conducted their joint naval exercises in the Bay of Bengal, together with Singapore. However, the Quad fell apart soon afterward, due to China’s suspicion and displeasure over the intention and orientation of this new group (Buchan and Rimland 2020), and the differing interests and considerations among the four countries (Marlow 2022; Liu and Xu 2021; Yang and Ren 2022).
Ten years later, the Quad was revived when Donald J. Trump became the U.S. President in 2017. But before the Quad returned, it was again the Japanese Prime Minister Abe who took the initiative and pushed it forward. In 2012, when Abe became Prime Minister for the second time, he published an opinion piece titled, “Asia’s Democratic Security Diamond” on an American think tank website, in which he expressed his worries about China’s activities in the South and East China Seas, claiming that “peace, stability, and freedom of navigation in the Pacific Ocean are inseparable from peace, stability, and freedom of navigation in the Indian Ocean,” and argued for “a strategy whereby Australia, India, Japan, and the U.S. state of Hawaii form a diamond to safeguard the maritime commons stretching from the Indian Ocean region to the western Pacific” (Abe 2012).
In 2016, a year before Trump became President, Abe put forward Japan’s “free and open Indo-Pacific” strategy. In his 2016 address to the sixth Tokyo International Conference on African Development in Nairobi, Kenya, he declared that “Japan bears the responsibility of fostering the confluence of the Pacific and Indian Oceans and of Asia and Africa into a place that values freedom, the rule of law, and the market economy, free from force or coercion, and making it prosperous” (Ministry of Foreign Affairs of Japan 2016). According to Japanese scholar, Abe’s “free and open Indo-Pacific” strategy has three pillars: political, economic, and security. Politically, this strategy aims to strengthen democratic values in the region. Economically, Japan wants to promote infrastructure development and economic connectivity in the region together with the U.S., India, and Australia, to compete with China’s Belt and Road Initiative. On the security pillar, Japan will deepen security cooperation with the U.S. and other Quad members and build closer ties with Southeast Asian countries (Takenaka 2022). According to a Chinese scholar, Abe’s interest in and push for his Indo-Pacific strategy were mainly driven by two considerations: geostrategic competition and regional cooperation, with the former based on Japan’s realistic strategic interest, and the latter cultivating a more favorable regional environment (Lu 2021).
After Trump entered the White House, the Abe administration successfully persuaded the Trump administration to accept Japan’s “free and open Indo-Pacific” concept as an overarching strategic framework to unite like-minded partners, protect the U.S. values and interests, and guard against China (Hu and Meng 2020). In November 2017, officials from the United States, Japan, India, and Australia restarted the Quad after a decade’s hibernation at the sidelines of the 31st ASEAN Summit in Manila. The officials discussed a wide range of issues, including maritime security, North Korea, connectivity, support for the “Free and Open Indo-Pacific” concept, and the promotion of a rules-based system in the Indo-Pacific region (Buchan and Rimland 2020).
In November 2019, in response to the proposal by the Trump administration, the Quad was promoted from a senior official-level dialogue to a ministerial-level dialogue. The foreign ministers of the Quad met for the first time in New York to discuss cooperation on counterterrorism, humanitarian assistance and disaster relief, maritime security cooperation, development finance, and cybersecurity. They also looked forward to coordinating efforts to promote their shared vision for a “free and open Indo-Pacific” region (U.S. Department of State 2019).
During the 4-year Trump administration, the Quad not only came back to life, but also entered a new period of expansion and increased institutional consultations. The Quad members held a seven-round senior official-level dialogue, and a two-round ministerial-level dialogue, and their dialogue and consultation covered issues as wide-ranging as maritime security, counterterrorism and humanitarian and disaster relief, infrastructure and economic connectivity, and support for ASEAN centrality, among others.
When Biden came into power in 2021, he upgraded the Quad to a leader-level summit, holding a first-ever virtual leaders’ summit in March 2021 and an in-person summit in September 2021. During the virtual summit, the four countries established three expert working groups, namely, the vaccine working group, the critical- and emerging-technology working group, and the climate working group, to combine efforts to jointly deal with the challenges in the above-mentioned issue areas and to provide a positive vision in the Indo-Pacific (White House 2021a). The Quad leaders held two more summits in 2022, a virtual summit in March and an in-person one in May. During the May summit, the four leaders established three more expert working groups in cyber, space, and infrastructure, greatly expanding the Quad’s areas of cooperation. The Quad also launched a new initiative, the Indo-Pacific Partnership for Maritime Domain Awareness (IPMDA), to support enhanced and shared maritime domain awareness in the Indo-Pacific, in the name of responding to humanitarian and natural disasters and combating illegal fishing (White House 2022b).
By upgrading the Quad to a leader-level summit, regularly holding ministerial- and senior-level dialogue, and establishing six expert working groups to facilitate practical cooperation on issues of shared interest, the Biden administration is trying to turn the Quad into a premier informal strategic consultation platform, not only to pool resources among the members and like-minded partners as a way to better compete with China, but also to provide “public goods” to increase its attraction and shape the emerging regional order in its favor.
Driving forces behind
Among the forces driving the formation, rebirth, and elevation of the Quad since 2007, three are outstanding:
Balancing China
Since its first formation as a quadrilateral security dialogue in 2007, “balancing China” has been the implicit and even explicit objective and driving force behind the Quad. For Japan, China’s growing power and economic influence overshadows what was once Japan’s leading economic status in Asia. What’s more, the diplomatic and political relations between China and Japan cooled and worsened since the beginning of this century due to historical issues, such as Japanese leaders’ repeated visits to Yasukuni Shrine, where Japanese World War II war criminals were shrined and worshipped, and the rising territorial disputes concerning the Diaoyu Islands. Japan has increasingly viewed China as a rival to its economic influence in Asia and a security challenge, especially after Shinzo Abe came into power (Green 2022, 55–64). By formally establishing the Quad, the Abe administration hoped to forge a China-balancing group among the four democracies based on common values (Chen 2020).
As for India, China’s comprehensive strategic partnership with Pakistan and India–China border disputes has always been a thorn in the side for India. The commencement of the China–Pakistan Economic Corridor (CPEC) in 2014 only increased India’s sense of “encirclement” with India speaking openly against China’s Belt and Road Initiative in general, and CPEC in particular (Baruah 2018). Then, in June 2017, Indian and Chinese troops confronted each other at the Doklam plateau near the borders of China and Bhutan, after Indian troops crossed the border to prevent China’s road construction near Doka La pass. The 2-month-long military standoff is the most serious confrontation between the two countries in decades. Although China and India agreed to disengage troops to end the standoff, harm was done to bilateral relations, which prompted India to join the Quad dialogue in November 2017. Again, in June 2020, there was a deadly clash between Chinese and Indian soldiers at the border area of Galwan Valley, which left dozens of soldiers dead or wounded. After the incident, the Indian chief of defense, Staff General Bipin Rawat claimed China as “enemy number one” facing India (Times of India 2021, 2–21). Given China’s growing economic influence in South Asia and the border incidents, the Modi administration increasingly came to view China as a major security challenge for India and a strategic adversary. By joining the Quad, India hoped to enlist support from the U.S., Japan, and Australia in its competition with China (Liu 2021). Additionally, India needs the other parties’ help to make sure that Asia will not become dominated solely by China, as India’s famous strategist C. Raja Mohan points out (Mohan 2021).
Australia has been an economic beneficiary of China’s economic rise and rapid development for the past several decades. However, Australia is becoming increasingly worried about its economic dependence on China (Eisentraut and Gaens 2018) and China’s perceived or potential “malign influence” in Australia (Searight 2020, 3–40). According to a Chinese scholar, Australia, along with Japan, are the two countries pushing the hardest for the establishment of the Quad. “Their intention of keeping the United States in the region and bringing in India as a check on China has become the fundamental driving force for the resumption and accelerated cooperation of the Quad” (Zhang 2019). In 2017, the Malcolm Turnbull administration published its Foreign Policy White Paper, in which it argues that the international order is undergoing great changes as anti-globalization intensifies, global governance is becoming harder, and rules are being contested. In the Indo-Pacific, the paper claims, China’s power and influence are growing and, in some ways exceed, that of the United States. “Like all great powers, China will seek to influence the region to suit its own interests.” As a result, “we will face an increasingly complex and contested Indo-Pacific” (Australian Government 2017).
Since 2017, and especially after Scott John Morrison became Prime Minister in 2018, Australia–China relations deteriorated rapidly. The Morrison administration claimed China interfered in Australian domestic politics and passed laws limiting Chinese investment in Australia and banning the Chinese company Huawei from participating in Australia’s 5G telecommunication development. Furthermore, Australia also accuses China of changing the status quo of the South China Sea, and “asks” China to comply with the 2016 South China Sea Tribunal reward, which China sees as illegal and void. As Australian–China relations deteriorate and Australia’s concerns about China grow, Australia is more than happy to join the Quad to gang up against China.
After Donald J. Trump entered the White House in 2017, he not only put his “America First” foreign policy idea into practice, but also declared China the strategic competitor of the United States. The U.S. China policy transformed from a more balanced approach of “competition plus cooperation” to an unbalanced one of mainly focusing on containing China (Wang 2019). Under his watch, the U.S. initiated a trade war, a tariffs war, and a technology war against China, and published the first Indo-Pacific strategy aiming at balancing China’s increasing power and influence in the Indo-Pacific region. From the U.S. perspective, the traditional “hub and spoke” alliance system in the Asia–Pacific is not competent enough to deal with a rising and more “assertive” China, and needs to be complimented by adding more capable and “willing” partners (Chen 2020). By reviving the Quad, the United States can pool together the resources of the South Asia heavyweight India, the economic and technology powerhouse Japan, and the culturally similar and geographically important Australia to better compete with China and counterbalance China’s power and influence in the Indo-Pacific.
Promoting practical cooperation
By establishing the Quad, the four countries also want to strengthen practical cooperation and provide regional “public goods,” collectively, to compete with China. Since 2017, the Quad members have taken a series of steps to strengthen their cooperation in the following areas.
Maritime security
Ever since the first senior official-level Quad dialogue in 2017, maritime security has been a top issue. For one thing, the tsunami in 2004 and earthquake and tsunami in Japan in 2011 underscored the devastating effects of natural disasters and humanitarian risks lurking in the maritime Indo-Pacific. For another, the maritime disputes in the East and South China Seas concerning China and the relevant parties have ratcheted up in recent years, destabilizing relations in the region. Third, for the United States, China’s claims in the South China Sea run diametrically counter to the U.S. style “freedom of navigation and overflight” and if allowed to prevail, would negatively impact its Navy operations and power projection in the world in general and in the Indo-Pacific in particular. A report by the U.S. Congressional Research Service warned that, if China’s claims to the South China and its’ interpretation of freedom of navigation prevail, it “could potentially require changes (possibly very significant ones) in U.S. military strategy, U.S. foreign policy goals, or U.S. grand strategy” (U.S. Congress 2020).
As a result, the Quad members have coordinated their positions concerning the East and South China Seas disputes and freedom of navigation and overflight “right” in the South China Sea, conducted joint maritime exercises in the Indo-Pacific, provided maritime assistance to Southeast Asian countries to improve the latter’s maritime law enforcement and humanitarian aid and disaster relief capabilities, and launched the IPMDA to “support enhanced, shared maritime domain awareness to promote stability and prosperity” in the Indo-Pacific (White House 2022b). Through those measures, the Quad members hope to speak with “one voice” against China’s maritime claims and activities in the East and South China Seas, provide regional maritime “public goods”, and win the goodwill of the regional countries.
Infrastructure development
Infrastructure development is another area where the four countries cooperate to provide an alternative to China’s Belt and Road Initiative. During the Trump administration, the United States, Japan, and Australia established a Blue Dot Network in 2019 to assess and certify infrastructure development projects worldwide on measures of financial transparency, social, and environmental sustainability, and impact on economic development, with the goal of mobilizing private capital to invest (U.S. Department of State n.d.(a)). The Trump administration even revamped its overseas finance development agency and established the U.S. International Development Finance Corporation in place of the Overseas Private Finance Corporation. The underlying motivation of the Quad’s moves was to write the rules of infrastructure development, undermine the appeal of China’s BRI, and act as a counterbalance to China’s soft power in the region (Liu 2019).
Under Biden’s watch, the Quad held a first-ever Quad Leaders’ Summit in Washington in September 2021, where the four leaders announced new Quad infrastructure partnerships to “coordinate our efforts, map the region’s infrastructure needs, and coordinate on regional needs and opportunities,” and “will cooperate to provide technical assistance, empowering regional partners with evaluative tools, and will promote sustainable infrastructure development” (White House 2021b).
Through the years, the Quad’s cooperation on infrastructure evolved from naming and shaming China’s BRI to tentatively providing an alternative. They know from their interaction with regional partners that it will not work just to say “bad things” about China’s infrastructure development; they must provide something concrete and satisfy the region’s growing infrastructure needs (Lew and Roughead 2021). By acting together and leveraging their respective comparative advantages, the Quad members hope to not only discredit China’s BRI, but to provide an alternative and win “the struggle of heart” in the region (Zhai 2022; Liu 2019).
Technology and supply chains’ security
After the Trump administration initiated the trade war with China in 2018, it soon turned its eyes on China’s hi-tech companies and strategic emerging industries, including semiconductors, 5G, EV batteries, Artificial Intelligence, quantum technology, biotechnology, and autonomous robotics. The U.S. not only imposed sanctions on China’s hi-tech leaders, such as ZTE and Huawei, and banned their 5G services in the U.S., but also welcomed and coordinated with other Quad members to ban Huawei and ZTE 5G services (Hartcher 2021). The US even launched “the Clean Network” to pressure and dissuade other allies and partners from using Huawei or ZTE 5G services, among others (U.S. Department of State n.d.(b)). The motivation behind the Trump administration’s hi-tech war was colored and reinforced by growing negative attitudes toward China, the U.S. strategic establishment, and the impacts of China’s indigenous innovation rush on U.S. economic, technology, and security interests (Sun 2019). By those measures, the Trump administration aimed to kill three birds with one stone: strengthen policy coordination among the Quad and beyond, exclude Chinese hi-tech companies from the U.S.-launched “Clean Network” supply chains, and prevent China’s technology dominance.
The Biden administration largely inherited the Trump administration’s technology Cold War against China and sees technology and supply chain security cooperation with other Quad members as a high priority. At the first virtual Quad leaders meeting in March 2021, the four leaders agreed to establish a critical and emerging-technology working group to facilitate cooperation on international standards and innovative technologies of the future (White House 2021a). Six months later, the Quad announced that it would launch a semiconductor supply chain initiative “to map capacity, identify vulnerabilities, and bolster supply-chain security for semiconductors and their vital components”. In addition to technology supply chain security, the Quad also intends to cooperate on “secure supply chains” for vaccine production and clean energy (White House 2021c), and has deepened its collaborative efforts in climate change, public health, space, and cybersecurity. In doing so, the Quad hopes to increase the “stickiness” of the grouping, improve its image as a regional public goods provider, and enhance its collective ability to compete with China.
Enhancing voice and status in regional affairs
If serving as a counterbalance to China and promoting practical cooperation are the common denominators, for India, Japan, and Australia, the “junior partners” of the U.S., the Quad also serves as a vehicle to improve their voice and status in regional affairs. India has long aspired to be an influential power in regional and world affairs. In February 2015, less than a year after he took office, India’s Prime Minister Narendra Modi said, “the world is keen to embrace India, and India is moving forward with confidence.” He challenged India’s diplomats to “use this unique opportunity to help India position itself in a leading role, rather than just a balancing force, globally” (Indian Press Information Bureau 2015). With the Quad, as the Vice President of Studies and Foreign Policy at Observer Research Foundation at New Delhi said, “India can rise above its middle-power status” and even project its influence beyond the Indo-Pacific (Pant 2022). Indian External Affairs Minister S. Jaishankar viewed the growing Quad grouping as a reflection of the “rise of Asia” as well as “the repositioning of big powers”, and said: “From an Indian perspective, it is also a statement of its growing interests beyond the Indian Ocean.” He said that India’s place within the Quad made sense given its “growth, confidence, and worldview”, and emphasized that “the firm establishment of Quad” is one of the major diplomatic accomplishments of the Modi government (Krishnankutty 2022).
For Japan, the primary driver behind the rebirth of the Quad is “uniting its Quad partners around its own vision for the Indo-Pacific” as a “significant success for Japan’s reinvigorated diplomatic agenda,” and “indicative of the greater efforts that Japan is investing in its external relations as part of its vowed ‘proactive contribution to international peace’” (Wilkins 2022a). Given the U.S. unwillingness to bear responsibility and retreat from the world stage under the Trump administration’s America First banner, by establishing and joining the Quad, Japan hopes not only to “entrap” the U.S., but also acts as a leader by default in setting a regional agenda to better serve Japan’s national interests in an increasingly uncertain world. Japan can also use its technological prowess, military potential, and economic power to consolidate its “leading role” in the Quad’s practical cooperation (Koga 2022). “Tokyo’s sustained championship of mini-lateral cooperation through the Quad and other mechanisms is testament to the emerging leadership role the country has assumed in regional affairs” (Wilkins 2022a).
Australia, a middle power whose relations with China have soured in recent years, is more than happy to embrace the Quad. For Australia, the Quad not only binds the U.S. in an exclusive small group, but also provides an additional assurance by forging more close relations with other major Asian powers besides the U.S., in a time of growth in the “looking inward trend” in the U.S. By joining an exclusive “club”, together with the U.S., India, and Japan, to set the agenda in regional affairs, expand practical cooperation in infrastructure, maritime security, supply chains, among other areas, and help shape the regional order, Australia can elevate its voice and status in regional affairs. As one Australian scholar emphasized, “its interaction with these major powers, gains access to advanced defense technologies and acquires a more influential voice in shaping the regional security environment.” He adds: “In this respect they add another powerful instrument to Canberra’s diplomatic and strategic toolkit as Australia faces unprecedented challenges to its national security” (Wilkins 2022b).
In addition to the above-mentioned reasons, as an informal security dialogue mechanism, the Quad has its own “comparative advantage”. It is small with only four members sharing “democratic values”. It’s informal without the burden of formal treaty. This flexibility enables it to expand the issue areas on which it focuses as situations dictate.
Impacts on regional order
The rebirth and upgrading of the Quad coincided with the deterioration of China–U.S. relations and heightened the rhetoric of a new Cold War in the Asia–Pacific. Despite Biden’s repeated claims that he does not “seek a new cold war or a world divided into rigid blocs” (White House 2021d), many worry his actions and “bloc politics” did just that (Shidore 2022).
The Quad’s development and evolution in the past several years have negatively affected regional order in four ways.
Political fault line
When Abe proposed the establishment of Quadrilateral security dialogue, he viewed it as an “Asia’s Democratic Security Diamond” to guard against an “undemocratic” China’s influence and activities in the maritime Indo-Pacific. In other words, from the very beginning, the Quad has had a strong flavor of ideology competition between an “authoritarian” China and the “democratic” Quad. After Trump declared China a U.S. strategic competitor and long-term security challenge and revived the Quad, the U.S. increasingly saw its competition with China through an ideological lens. The Biden administration vows to unite democracies in Asia and around the world and make the Quad a premier group for providing regional public goods and safeguarding “democratic values” (White House 2022a).
The “democracy vs. authoritarianism” and “us against them” rhetoric and mindset not only increasingly raises China’s concerns and even hostility, but also puts great pressure on countries in the region that do not want to choose sides, threatening to create a political fault line in the Asia–Pacific. Chinese government has made its view on the Quad very clear: China is against establishing any exclusive, anti-China group or any Cold War-style camp, or any self-claimed group of democracies that preaches “democracy vs. authoritarianism” confrontation and conflict (Ministry of Foreign Affairs of the People’s Republic of China 2022a). China’s Foreign Minister Wang Yi emphasized that the Quad is the backbone of the U.S. Indo-Pacific strategy and seeks to establish an Asian NATO, to promote an outdated Cold War mindset, confrontation and geopolitical struggle, potentially endangering East Asia’s prospects for peace and development and spirit of win–win cooperation (Ministry of Foreign Affairs of the People’s Republic of China 2020). Singapore, an AESAN member, who has close relations with both the U.S. and China, has expressed its worries of increasing geopolitical competition between the U.S. and China and potentially being forced to choose sides. Singapore’s Prime Minister Lee Hsien Loong said that Singapore is worried about the growing geopolitical competition between the U.S. and China, and does not want to “pick sides”, similar to many other ASEAN countries (Tham 2021).
Economic fragmentation
As China’s economic rise accelerated after China’s entry into the World Trade Organization in 2001, China has gradually replaced the U.S. and Japan as the economic engine and driving force for economic integration in East Asia. In 2010, the China–ASEAN Free Trade Area came into force, which was the first agreement of its kind signed by ASEAN. In 2013, China initiated the BRI to facilitate the “Five Links” between China and the relevant parties. As BRI attracts more countries to join in, the U.S. and other Quad members became increasingly concerned. They viewed BRI not only as an economic initiative, but also a strategic master plan to squeeze the influence of the U.S., Japan, and other countries, and to create an economic and even political sphere of influence for China (Russel and Berger 2020). In other words, the Quad increasingly views China’s strategy as a zero-sum game requiring action by Quad members. Initially, the U.S., India, Japan, and Australia took a more negative strategy by “naming and shaming” in the hope of scaring away potential participants and sabotaging China’s BRI. When this proved ineffective, the Quad changed their strategy and coordinated to offer alternatives to BRI by launching Quad infrastructure partnerships to compete directly with China. In May 2022, under the Biden administration’s initiative, the Quad members, together with nine other countries (Fiji joined later as the 14th founding member), launched the Indo-Pacific Economic Framework for Prosperity (IPEF), to coordinate and cooperate in the area of trade, supply chains, clean economy, and fair economy, to compete economically with China.
Theoretically, more options are better for the region, and healthy competition will offer more good products and increase overall wellbeing. However, the Quad’s infrastructure and economic initiatives all exclude China and the four countries even established technology and supply chain mini-lateral groupings to de-couple from China’s technology and supply chains. If this trend continues, it will disrupt the momentum toward economic integration of the region and will likely lead to economic fragmentation. China’s Foreign Minister Wang Yi warned against this in a speech to the Asia Society in September 2022. He said, “Ideology driven, the U.S. has overstretched the concept of national security, built ‘small yard, high fence’, clamored for decoupling and cutting supply chains, pushed for ‘friend-shoring’, conceived the Indo-Pacific Economic Framework, and formed the Chip 4 Alliance. This is clearly not healthy competition. Such moves are not helpful to the U.S.’s own development. They will also disrupt global economic cooperation” (Wang 2022).
Maritime security
Under the joint efforts of China, the Philippines, and ASEAN, the situation in the South China Sea has improved considerably since 2016. China and the Philippines signed economic agreements to improve economic and diplomatic relations while shelving their maritime disputes (Baguisi 2021). China and ASEAN have also stepped up their dialogue and consultations on the Code of Conduct (COC) in the South China Sea with an eye to reach an agreement on COC before the end of 2022 (Ministry of Foreign Affairs of the People’s Republic of China 2022b).
However, despite China and ASEAN’s efforts, the Quad still puts the South China Sea disputes at the core of their maritime security cooperation and “concerns” and links it with the East China Sea disputes between China and Japan, the situation in the Taiwan Straits, and the issue of “freedom of navigation” in the South China Sea. Furthermore, the Quad members’ positions on the South China Sea, the constant freedom of navigation and military exercises in the South China Sea, and military assistance to the Southeast Asia, together with their launching of the Indo-Pacific Partnership for Maritime Domain Awareness, complicate maritime security in the Western Pacific at least in three ways. First, it may distract the joint efforts of China and ASEAN countries to reach a practical COC in the near future. Second, it will ratchet up maritime competition between China and the Quad, with each side sticking to its own interpretation of maritime interests, security, and rights. Third, it may encourage other parties of the South China Sea disputes to initiate bolder activities and thus reignite the maritime tension in the South China Sea.
ASEAN centrality
In the past several decades and especially since the beginning of this century, ASEAN and ASEAN-centered institutions have been the driving force behind East Asia (Southeast Asia included) economic integration and serve as bridges between the major players in the Asia–Pacific. This ASEAN centrality in setting the regional economic, and even security agendas has gradually been accepted by the major players in the region. Upgrading the Quad from a senior-level dialogue held at the sidelines of ASEAN and East Asia summits to leader-level summits to be held on a rotational basis, along with expanding the scope of the Quad’s areas of cooperation, greatly overshadows the role of ASEAN and threatens its centrality (Tang et al. 2020).
From the very beginning, it was clear that “most Southeast Asian states are not publicly and fully embracing the Quad, even though they are not energetically working to challenge or denounce the nascent dialogue.” Among the ASEAN countries, Indonesia, Malaysia, Laos, Thailand, and Cambodia are top skeptics of the Quad. Indonesia is especially worried about the sidelining of ASEAN, and Singapore is worried about the sharpening of the US–China competition (Laksmana 2020). According to the 2021 State of Southeast Asia Survey, less than half of the respondents thought that the Quad made a “positive” or “very positive” contribution to regional security. Just as Jonathan Stromseth said, “most ASEAN nations remain suspicious of the four-country grouping, seeing it as a challenge to ‘ASEAN centrality’” (Stromseth 2021).
Looking ahead
As an informal group, the Quad has developed from an obscure senior-level dialogue to a multilayer leaders’ summit. The dialogue has become more institutionalized with regular senior-, ministerial-, and leader-level meetings, and the cooperation among the members has expanded, especially in the areas of maritime security and economic development. Given the rapid development in the past several years, one cannot help but wonder how the current trajectory of the Quad will unfold in the future? Will it turn into, as many predict, an Asian NATO? What areas of cooperation might be added in the years ahead? What challenges might the Quad encounter in its future development?
An Asian NATO?
Since the revival of the Quad in 2017, there have been talks of forming an Asian NATO based on the Quad. In 2020, when China–U.S. relations hit a new low due to the COVID-19 pandemic, the Trump administration even floated the idea of turning the Quad into an Asian NATO. Then Deputy Secretary of State Stephen E. Biegun suggested that the Quad could be the beginning of a NATO-style alliance in Asia. “It’s something… that would be very much worthwhile to be explored,” he said at a U.S.–Indian strategic dialogue in August 2021 (Taylor 2020). However, the idea never bore fruit. India, which is not a treaty ally of the U.S. and has a long tradition of nonalignment, never agrees to join a U.S.-led alliance. Indian External Affairs Minister S. Jaishankar dismissed the notion that the Quad is an Asian NATO as “completely misleading” and warned “interested parties” who advance the idea “not to slip into that lazy analogy of an Asian-NATO” (Economic Times 2022).
ASEAN, the support of which the U.S. and the Quad both try to attract, also expresses its concerns about forming an Asian NATO and the potential to draw the region into a new cold war. As Singapore Prime Minister Lee Hsien Loong cautioned: “In Asia, the history is different. There was never a grouping in Asia which was the equivalent of NATO… So I think that that is a better configuration than one where countries are divided along a line and one bloc confronts another” (Prime Minister’s Office Singapore 2022). Given the inherent hurdles of forming an Asian NATO based on the Quad, the Biden administration makes its position very clear: The Quad will remain an informal grouping, and will not become an Asian NATO, even though it will become a premier grouping in the Indo-Pacific (White House 2021e).
In summary, the Quad will not turn into an Asian ANTO in the near future. As Gregory Poling, director of the Asia Maritime Transparency Initiative at the US-based Center for Strategic and International Studies said, “There is just not enough shared strategic interest or shared desire to accept risk on the military front” (Akhter 2021). Nevertheless, the Quad will continue its cooperation in the maritime security, cybersecurity, and other military-related cooperation and consultation, and supplement the US-centered “hub and spokes” bilateral alliances in Asia.
Areas of further cooperation
The Quad will remain informal for the foreseeable future. However, the practical cooperation, policy coordination, and strategic consultations will deepen. In the next several years, maritime domain awareness in the Indo-Pacific will be a top priority of the Quad, because, by providing a unified maritime picture, the Quad hopes to realize three objectives. First, it can keep close track of China’s maritime activities in the Indo-Pacific; not only of China’s navy activities, but also China’s large fishing fleet. Second, it can present itself as regional “public goods” provider. From the Quad’s perspective, a unified and real-time maritime picture will enable Southeast Asia countries and Pacific Islands countries to better “protect” their maritime rights, especially fish resources from being exploited by China (Pandlai and Singh 2022). Though unstated, the implicit target of the initiative is China, which the U.S. has accused of being the largest exploiter of global fishing (Zhang 2022). And third, it will likely assist the Quad in winning support from regional countries. Most Southeast Asian countries and Pacific Islands countries lack the necessary technology and means to have sufficient maritime domain awareness and therefore welcome the Quad’s offer. Representing itself as a regional public goods provider to help them will no doubt win their praise.
Supply chain and infrastructure cooperation will be the other two priority areas where the four countries hope to reduce their dependence on China’s technology and supply chains and provide an alternative to China’s infrastructure related to both “standard” and project financing. As Moody’s Vice President Nishad Majmudar said, “The economic realignment will benefit (the Quad) member countries’ technology and energy sectors as they seek to reduce reliance on Chinese-produced critical materials and technologies that are key inputs to tech and renewable energy products” (Anand 2022).
In terms of policy coordination, the Quad will further coordinate their positions on the East and South China Seas disputes, the situation in Taiwan Straits, and other hot-button issues in the Indo-Pacific region and beyond. The Quad will also enhance their cooperation in climate change, public health, space, and cybersecurity. In the area of strategic consultation, the Quad will focus on China’s foreign policy orientation and major diplomatic, economic, and security initiatives, and react in a coordinated way.
Potential challenges
As an informal grouping aiming at balancing China, promoting practical cooperation, and raising its voice and status in shaping an emerging regional order to its advantage in the context of growing US–China strategic competition, the Quad has made considerable progress in mechanism building and cooperation. Nevertheless, it may still face three potential challenges as it evolves. First, how to maintain its informality while its mechanisms become more institutionalized and areas of cooperation have multiplied. One of the virtues of the Quad is its informality and ability to offer more flexibility and comfort to its members. However, as its functions expand and mechanisms multiply, can the Quad still stay informal and resist the temptation to turn into a formal military alliance as the Trump administration once attempted? And if future US administrations again attempt to formalize the Quad, how will India, who is uncomfortable with a formal military alliance with the US, react? What impacts it will have on the cohesion of the Quad?
Second, how can it avoid mission creep? The Quad has evolved from an informal senior-level security dialogue into a multi-layered leaders’ summit covering a wide range of issues from maritime security, to infrastructure development, climate change, supply chain resilience, critical and emerging technology, and cybersecurity. As its mission expands, so its focus will dilute. Will the Quad morph into something that covers all issues of importance, while its members are not in a position to solve them and just become another cheap talk show? South Korea also expresses its interest in joining the Quad, though the Biden administration says it has no plan to invite South Korea to join for fear of further antagonizing China (Kang 2022). For how long can the Quad resist the temptation of inviting new members into its club?
Third, how can the Quad reconcile its intention of turning itself into a “premier grouping” in the Indo-Pacific and maintaining ASEAN centrality and unity? The rebirth of the Quad has already triggered concern and discord among ASEAN members. Even though ASEAN’s attitudes toward the Quad improved after the Biden administration and other members repeatedly assured ASEAN that they support ASEAN centrality and unity and intend to orient the Quad more in the direction of regional public goods provision, suspicion, and worries remain. In the context of China–US strategic competition and the Quad as a “premier grouping” in the Indo-Pacific to serve as a strategic dialogue mechanism, it will inevitably overshadow the role of ASEAN and its centrality in regional affairs.
Funding
This study was funded by The National Social Science Foundation of China (Grant No. 20AGJ009).
Declarations
Conflict of interest
The author declares that there is no competing interest regarding the publication of this paper.
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| 0 | PMC9734956 | NO-CC CODE | 2022-12-14 23:28:31 | no | gynäkologie + geburtshilfe. 2022 Dec 7; 27(6):8-9 | latin-1 | null | null | null | oa_other |
==== Front
J Mater Cycles Waste Manag
J Mater Cycles Waste Manag
Journal of Material Cycles and Waste Management
1438-4957
1611-8227
Springer Japan Tokyo
1563
10.1007/s10163-022-01563-x
Original Article
Analysis of COVID-19 waste management in Vietnam and recommendations to adapt to the ‘new normal’ period
http://orcid.org/0000-0002-3374-5477
Nguyen Trang D. T. [email protected]
1
Nakakubo Toyohiko 1
Kawai Kosuke 2
1 grid.412314.1 0000 0001 2192 178X Ochanomizu University, 2-1-1 Otsuka, Bunkyo, Tokyo 112-8610 Japan
2 grid.140139.e 0000 0001 0746 5933 National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506 Japan
8 12 2022
116
15 7 2022
27 11 2022
© Springer Japan KK, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Amid the 4th wave of COVID-19, Vietnam reopened its economy, which placed extra burdens on the COVID-19 waste management system. This study analyzed existing issues and recommended adaptations to secure appropriate management of COVID-19 waste under the ‘new normal’ pandemic period. Results showed changes in COVID-19 waste characteristics (e.g., rapid rise in waste generation, lower percentage of plastic) and multiple other issues (e.g., presence of COVID-19 waste in municipal waste, lack of temporary storage sites and local treatment capacity), along with greater waste-handling responsibilities placed on authorities and higher infection risks. To adapt to the ‘new normal’, introduction of separate handling routes and collaboration in waste treatment were recommended. Employing the network of pharmacies used for vaccination would require COVID-19 waste collection from scattered, small-scale sources as part of the waste management solution. Also, following the 4R initiatives (reduce, reuse, recycle, recovery) could help ease the burden on the country’s waste system and provide additional opportunities to move towards a circular economy in the post-acute COVID-19 era. The findings should contribute to a safer co-existence with the virus through appropriate waste management in Vietnam and could be used to tackle waste problems in other developing countries.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10163-022-01563-x.
Keywords
COVID-19
Medical waste
Waste management
Adaptation
Developing country
==== Body
pmcIntroduction
The global pandemic of ‘Coronavirus disease 2019’ (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains an acute crisis in 2022 [1], with ongoing significant worldwide spikes of infections driven by the highly transmissible Omicron variant—the dominant variant since March 2022 [1, 2]. Several countries are, however, gradually lifting their social restrictions to reopen their economies [1, 3], and entering a so-called ‘new normal’ period under which a pathway of ‘co-existence with the virus’ is replacing previous zero-COVID policies [3–5]. Countermeasures and preparedness to adapt to such changes in overall crisis responses are required for waste management systems, which are, in addition to the healthcare system, essential in this era of COVID [1].
Waste management systems have struggled remarkably during the pandemic, mainly because of the increased generation of waste associated with COVID-19 [1, 3, 6–8]. The burden has been greater in developing countries where most of the waste management systems were not designed to operate under a crisis or are operating with limited resources or both [9–16]. Various issues emerged under pandemic time included unseparated COVID-19 waste in general waste [17–22], suspension of recycling [23, 24] and shortage of incineration capacity [15, 16, 25]. Furthermore, problems such as insufficient protective equipment for waste handlers [21, 26]; infections due to virus-laden waste to community [24], scavengers [19, 27] and waste handlers [20–22] added difficulties on the management of COVID-19 waste in those nations. Plastic pollution due to huge amount of discarded single-use personal protective equipment (PPE) was considered as the typical environmental consequence linking to the pandemic [1, 6], affecting air quality (from incineration), fresh water, oceans and threatening the marine life [28, 29]. The transition to ‘new normal’ pandemic conditions, which is viewed as necessary to help economies recover in several developing countries [4, 30, 31], likely presents additional waste management challenges, especially when all social restrictions have been lifted. A more environmentally sustainable model of waste management is thus required to gain the flexibility and adaptability of the current waste systems in the new situations of COVID crisis.
For future perspective, the move towards a circular economy was proposed for a probably more sustainable model of waste management in adaptation to post-COVID conditions [27, 32–35]. Incorporating 4R initiatives (reduce, reuse, recycling, recovery) into waste management strategy was likely a prerequisite approach [29, 33, 36] to mitigate the environmental consequences linked to pandemic and to shape a safer, more environmentally sustainable model for COVID-19 waste management in the pathway towards circular economy. Initiatives of 4Rs aimed at lessening the exploitation of resources (reduce), extending the lifespan of the products through possibly multiple usage (reuse), considering waste as resources for reprocessed products, materials, substances whether for the original or other purposes (recycling), or for usable energy, heat (recovery). Because of its infectiousness, reprocessing of COVID-19 waste is complex for disinfecting and converting the materials and thus, in most of the cases, is recognized under a category of both recycling and recovery. Opportunities and options for 4Rs have been identified for COVID-19 waste in recent literature [29, 36–40]. In addition, the World Health Organization (WHO) introduced options on reduction and reuse of COVID-19 waste to cope with plastic pollution that have been intensified due to the mass generation of discarded PPE and other COVID-19 related waste [6]. Appropriate recommendations to address the current issues and to adapt to new challenges in this new phase of the pandemic are therefore vital, particularly in developing nations, in the fight against COVID-19 through waste management.
Since the onset of the pandemic in late January 2020, Vietnam saw a steep surge in infections under the 4th wave of infections since April 2021, driven by the highly contagious Delta variant and additionally by Omicron since December 2021. Several strict antivirus measures were accordingly introduced to curb the outbreak, including complete social restrictions such as a nearly 3-month lockdown imposed at the epicenter of Ho Chi Minh City. Soon after the pandemic had first been brought under control nationwide, Vietnam adopted a new pandemic response policy of ‘safe adaptation, flexible and effective control of the COVID-19 pandemic’ (Resolution 128, Resolution 128/NQ-CP, 11 October 2021) to restore the economy while also introducing flexible responses against the highly transmissible Omicron variant without large-scale social restrictions [5, 41]. In terms of management of waste associated with COVID-19, the Ministry of Health (MOH) stressed the need for suitable countermeasures and preparedness in adaptation to a new pandemic period, which had a high probability of another surge in infections when all of the social restrictions had been lifted due to newly-found subvariants and other variants of concern [42]. Also, the newly-launched Pandemic prevention and control program for 2022–2023 (Resolution 38, 17 March 2022) confirmed the requirement of adaptive management of waste in the ‘new normal’ period.
Operating under crisis conditions which it had no prior experience, the waste management system in the country was burdened with a much larger than normal amount of waste generated. According to Law on prevention and control of infectious diseases (Law 03/2007/QH12), resources (e.g., medicines, chemicals) and equipment (e.g., medical equipment, PPE) needed for combating COVID-19, a declared national pandemic, were fully supplied by the authorities. In the absence of reported data, generation and composition of COVID-19 waste were estimated from the used amounts and typical compositions of the supplied resources, equipment [43]. Estimated amount of 1486 t of COVID-19 generated in the first year of the pandemic caused the annual rate of increase of hazardous medical waste generation to have nearly doubled [43], but infrastructure resources remained limited [44–46]. Other issues (e.g., overwhelmed local treatment capacity, shortage of waste handlers) also remained inadequately addressed [47]. In the absence of social restrictions under the ‘new normal’ period, these issues could be exacerbated. Understanding waste management under pandemic conditions in general as well as grasping specific issues in particular is critical to improving the performance of the existing waste treatment system and supporting preparedness for the ‘new normal’. However, little was found in a literature search on the management of waste associated with COVID-19 in Vietnam: Nguyen et al. estimated COVID-19 waste generation and composition in the country during the first year under complete restrictions [43] and assessed the treatment capacities of COVID-19 waste nationwide, in the epicenter of Ho Chi Minh City during the 4th (Delta) wave [48], the Asian Development Bank (ADB) projected the additional amount of COVID-19 waste for Hanoi using China’s experience [13], and Le et al. proposed a decentralized blockchain-based system for automating waste treatment processes for medical equipment and supplies after usage among relevant parties [49]. A comprehensive analysis of COVID-19 waste practices and issues considering the changes in pandemic response policy in the country was therefore essential to improve the performances of the country’s waste system and to adapt to the new phase of this unprecedented crisis.
This study analyzed the management practices related to waste associated with COVID-19 in Vietnam to address current issues and to prepare recommendations to adapt to the ‘new normal’ period, so as to secure the correct management of COVID-19 waste. The recommendations provide a timely contribution in accordance with the legal recognition of the need for a pandemic response strategy for a safe co-existence with the virus under the ongoing pandemic. The findings could also serve as a practical country-based reference for other developing nations to tackle their own waste problems because the end of the COVID-19 pandemic is not currently in sight.
Sources of COVID-19 waste generation in the ‘new normal’ period
Sources of COVID-19 waste generation, previously identified based on a monitoring and treatment scheme [43], were updated in association with the adjusted policy of pandemic response in ‘new normal’ (Fig. 1). Because movement was being made away from a target of ‘new case control’ under the former zero-COVID policy, mandatory quarantine was removed for a number of targeted persons and no lockdown would be imposed in ‘new normal’ period. As a result, 4 sources of COVID-19 waste generation included in the previous scheme were no longer included during the ‘new normal’ period. These were sources of waste from quarantine areas (medical facilities, QMED; centralized quarantine facilities, QC; households, QHH) and from 24/7 traffic checkpoints under lockdown (Checkpoint). Similarly, following the target of ‘severe case control’ currently in place, 5 more sources of COVID-19 waste were added according to the changed scheme of monitoring and treatment in ‘new normal’. Of the 5 added sources, 3 were treatment areas for F0 (i.e., COVID-19 patients: intensive care unit, TreatICU; centralized facility, TreatC; households, TreatHH) linking to the newly-adopted classification of F0 by severity that was put in practice to improve the treatment efficiency and to protect the medical system from being collapsed due to excessive hospitalizations. Other 2 additional sources of waste were places out of medical facilities for F1 persons (i.e., those with direct contact with F0 persons: centralized facility, QC-F1; households, QHH-F1) as a solution to secure hospital beds for F0 persons. Three sources were unchanged over the shifting to ‘new normal’ including COVID-19 specimen collection and testing, Testing; treatment areas in medical facilities, TreatMED; and COVID-19 vaccination, Vaccination. For convenience, we refer to these by their corresponding abbreviations; for example, Testing refers to ‘COVID-19 specimen collection and testing’ (Fig. 1).Fig. 1 Changes in sources of COVID-19 waste generation in the transition to ‘new normal’ period; name of source is under the symbol and its abbreviation is bordered, placed in the right of symbol
In this study, estimation of COVID-19 waste generation in April 2020–March 2022 covered all sources in Fig. 1 according to their specified availability during calculation period. QHH was excluded because it was not recognized as a source of COVID-19 waste (Decision 3455). The ‘new normal’ waste management scheme as of March 2022 included sources available at this time (5 additional, 3 unchanged sources; Fig. 1). However, the recommendations proposed in this study omit QC-F1 and QHH-F1 because F1 persons were no longer required to quarantine at centralized facilities or to self-isolate at households after April 2022 (Legal document 1909).
Materials and methods
Research framework
Based on the adopted regulations and estimation of COVID-19 waste characteristics (generation, composition), waste management practices were analyzed not only considering issues under complete restriction but also considering those that probably will occur under the ‘new normal’, as well as the influence of changes in regulations regarding the pandemic response. Conditions of pre-pandemic waste system was taken into account for a local-specified analysis results. Adaptive recommendations were accordingly proposed for a safer and more sustainable management of COVID-19 waste towards circular economy (Fig. 2). Analysis results were presented by stage in waste system (separation and collection, transportation, treatment), followed by proposed recommendations addressing the identified issues in ‘new normal’ in Results and discussion section.Fig. 2 Research framework
Estimations of COVID-19 waste generation, composition
Because of the absence of reported waste data, COVID-19 waste generation and composition were estimated from the state-supplied anti-pandemic resources (e.g., medicines, chemicals) and equipment (e.g., medical, personal protective), a method proposed for Vietnam [43], for the 2 years from April 2020 to March 2022 (i.e., since COVID-19 was declared a national pandemic). Employing the same method of estimation as the previous study enabled a comparison between the results in the present study that covered the transition into the ‘new normal’ period and those calculated only for the first year of the study period when the country was under complete social restrictions (April 2020–March 2021) [43].
COVID-19 waste generation was the total of all sources (i: Testing; TreatMED; TreatICU; TreatC; TreatHH; Vaccination; QMED; QC). COVID-19 waste generation by source i (Wi) was calculated from the number of generating units (Ni) and the waste generation rate (Ri) calculated from the state supply of pandemic resources and equipment, estimated here as:
Wi=Ni∗Ri/1000 [43]
Daily logged COVID-19 data were used as number of generating units (Ni) to estimate waste generation; they were acquired from the COVID-19 Information Portal of MOH (https://covid19.gov.vn/) and included the number of COVID-19 patients under treatment by place (ICU, medical facility, centralized facility, household), number of quarantined persons by place (medical facility, centralized facility), and number of real-time reverse-transcription polymerase chain reaction (qRT-PCR) tests performed and COVID-19 vaccination shots administered. Rates of waste generation (Ri) were additionally estimated for the 5 newly-identified sources of COVID-19 waste (TreatICU, TreatC, TreatHH, QC-F1, and QHH-F1) under ‘new normal’. Rates of sources identified under complete restriction (Testing, TreatMED, Vaccination, QMED, QC) were obtained from the previous study by Nguyen et al. [43]. Daily discharged amount of solid waste per medical bed and per habitant were referred to in reported data in the National Environment Reports of 2011 and 2019, respectively, and included as part of the estimate of the generation of COVID-19 waste for TreatICU and TreatHH. For estimating composition, the main materials of PPE components were acquired from a study by Purnomo et al. [40] and product specifications on www.amazon.co.jp, in addition to compositions of clinic waste by UNEP-IETC [50] and of municipal waste by the World Bank [51]. The quantities of state-supplied anti-pandemic resources and equipment used in the estimation of generation rates of COVID-19 waste are presented in Supplementary Table S1.
Sources of data and information
The volume of hazardous medical waste generated before the pandemic was acquired from official sources (Center for Environmental Information and Data, under the Vietnam Environment Administration (VEA)–MONRE, http://ceid.gov.vn/; Statistical Reporting System, http://thongke.monre.gov.vn/), as well as from environmental reports and other sources. Estimates of waste generation in the non-COVID scenario was based on the reported annual rate of increase in waste generation of 7.6% [46] and using the reported value of 21,810 t of waste in 2019 [52]. Descriptions of all types of waste mentioned in this study are presented in Supplementary Table S2.
Legal documents on pandemic responses and reports related to waste management by WHO, National Steering Committee (NSC), MOH, Ministry of Natural Resources and Environment (MONRE), and the WHO Representative Office in Vietnam were thoroughly reviewed to gain a comprehensive understanding of the hazardous medical waste management system before and during the pandemic. Approved waste management planning prior to the pandemic and relevant information following the Program on COVID-19 prevention and control for 2022–2023 (Resolution 38) provided necessary background on a prospective view of the ‘new normal’ under which handling of COVID-19 waste would be performed.
Conditions for calculation
The estimates are considered to be reliable in part because of the ready availability of COVID-19 data from official source (MOH), as well as the availability of actual quantities of resources and equipment supplied to combat the pandemic. Changes in regulations on pandemic control during the calculation period and on availability of reported COVID data (Table 1), however, influenced the estimation. Exceptions of estimation of COVID-19 waste generation from QC-F1 and QHH-F1 were considered to be acceptable owing to their small rates of daily waste generation (of 47.35 and 24.62 g per bed, respectively) and the lack of reported data on their generating units. Further exception was made for estimation of COVID-19 waste generation from Checkpoint because of its partial availability during lockdown. In the absence of waste collection rates, all waste generated was assumed to be eventually collected for treatment. Testing was considered to be a source of COVID-19 waste generation within medical facilities, given that 331 of the 334 qualified laboratories nationwide performing COVID-19 qPCR testing were located in MOH hospitals and provincial Centers for Disease Control and Prevention, and the remaining 3 were directed by other ministries [5]. Also, Vaccination was seen as a community source because almost all COVID-19 vaccines were administered in numerous temporary vaccine clinics in the community as part of the nationwide mass vaccination program [5] except for a relatively few delivered in medical facilities for staff members.Table 1 Availability of sources of COVID-19 waste generation according to reported COVID-19 data; months in italic indicate ‘new normal’ period (Data source: MOH)
Results and discussion
Waste identification and management regulations
Legally recognized under the term ‘potentially SARS-CoV-2 contaminated waste’, COVID-19 waste was classified as infectious waste, a subcategory of hazardous medical waste, and was co-administered by MOH and MONRE, according to Decision 3455/QD-BCDQG (Decision 3455, 5 August 2020) and Legal document 102/MT-YT (Legal document 102, 4 March 2021). All legal documents in relation to COVID-19 waste management mentioned in this study are presented in Supplementary Table S3. Management of COVID-19 waste was subjected to regulations on medical waste management within medical facilities and on hazardous waste management (Circular 20 and Circular 02), which replaced their previous versions (Joint Circular 58 and Circular 36) to become the basis for Decision 3455. Resources (e.g., medicines, chemicals) and equipment (e.g., medical equipment, PPE) for combating the pandemic were fully supplied by authorities following the Law 03/2007/QH12 (Law 03, 21 November 2007) as COVID-19 was declared a national pandemic (Decision 447, 1 April 2020).
Waste handling responsibility
Responsibility for COVID-19 waste handling varied by source. Medical facilities are required to manage the waste produced within their boundaries, including that from COVID-19 testing laboratories and from treatment and quarantine areas (Testing, TreatICU, TreatMED and QMED; Fig. 1) (Circular 20). Operating under the direction of the local authority, or the Provincial People’s Committee, the state-run Urban Environment Company (URENCO) was responsible for handling of COVID-19 waste from the remaining sources (TreatC, TreatHH, QC, QC-F1, QHH-F1, Checkpoint and Vaccination; Fig. 1) using its current system of management for hazardous medical waste (Circular 02). Because it was not officially recognized as COVID-19 waste, medical waste from households with a person or persons under quarantine (QHH) followed the current handling flow of municipal solid waste. The new flexible antivirus measures in the ‘new normal’ were reflected in changes in the sources of COVID-19 waste generation (Fig. 1); this required a reallocation of some of the F0 sources and all F1 sources from medical facilities to the community (Fig. 3) and careful consideration of proper management of COVID-19 waste in the community to prevent infections related to contaminated waste. As a result, greater responsibility was placed on local communities (i.e., the people’s committees) in the handling of COVID-19 waste. Private companies licensed to treat hazardous medical waste were encouraged to join URENCO in COVID-19 waste treatment (Decision 3455) in addition to their usual provision of treatment services to medical facilities lacking incinerators.Fig. 3 Transition of waste-handling responsibilities and community exposure following the reallocation of sources of COVID-19 waste generation in the ‘new normal’ period
Estimated generation and composition
An estimated 279,137 t of COVID-19 waste was produced over the 2 study years (Table 2), an average of approximately 11,630 t per month, or nearly 383 t per day. Households with COVID-19 patients under treatment (TreatHH) generated the largest amount (130,605 t; 47%), despite the fact that the category was only available for 4 of the 24 study months. The large amount of household waste was influenced by the great number of mild and asymptomatic COVID-19 patients who recuperated in their homes because the Omicron variant caused less severe symptoms than previous variants of SARS-CoV-2 [2, 5]. Moreover, COVID-19 waste production fluctuated largely during the study period (Fig. 4); the maximum monthly amount (101,042 t), far greater than the average value, apparently stretched the treatment capacity of the existing system. In general, growth of estimated generation of COVID-19 waste was found in correlation with pandemic progression during study period. The large and sudden growth of COVID-19 waste generation in March 2022 was probably a result of the surge associated with the Omicron variant, which became dominant nationwide in February 2022 [5, 53]. The increase in waste generation by community sources (Fig. 4) affirmed the heavier responsibility of local authorities in COVID-19 waste handling at this time.Table 2 Generation rates and volume of COVID-19 waste (April 2020–March 2022)
Source of waste Rate of waste generation Estimated generation of waste
t (2 years)−1 (%)
Testing 50 g test−1 2273.8 0.8
TreatMED 3.86 kg bed−1 day−1 130,275.5 46.7
TreatICU 4.64 kg bed−1 day−1 5008.7 1.8
TreatC 3.09 kg bed−1 day−1 2674.7 1.0
TreatHH 1.94 kg bed−1 day−1 130,605.0 46.8
Vaccination 29.89 g shot−1 6168.2 2.2
QMED 3.86 kg bed−1 day−1 1694.6 0.6
QC 46.43 g bed−1 day−1 436.1 0.2
Total 279,136.6 100.0
Fig. 4 Estimated monthly distribution of the amount of COVID-19 waste generated (April 2020–March 2022)
We compared the amount of waste generated during the study period with that projected for the same period in a non-COVID scenario. The pandemic clearly caused significant growth in hazardous medical waste generation (Fig. 5) and consequently placed remarkable burdens on the nation’s existing waste-handling infrastructure. Under these conditions, any system would most likely be overwhelmed as the demand for waste treatment in a timely manner as is required for infectious waste surpassed the available treatment capacity.Fig. 5 Generation of hazardous medical waste under COVID-19 and a non-COVID scenario
Plastic accounted for nearly 54% of the total COVID-19 waste composition (Fig. 6). The ‘other’ category of constituents expanded to 36.2% in the second year from its previous proportion of just 0.6%. The changes in waste composition were probably influenced by the addition of municipal solid waste by COVID-19 patients, identified as COVID-19 waste, in the connection with the steep surge in infections during December 2021–March 2022. The composition is important because the treatment efficiency of COVID-19 waste by incineration would be affected if a larger share of municipal solid waste containing a higher level of moisture and having a much lower energy value [50] was included in the feedstock. The monthly estimated compositions of COVID-19 waste are presented in Supplementary Fig. S1.Fig. 6 Changes in estimated composition of COVID-19 waste (April 2020–March 2022)
Management practices and issues
Separation and collection
Separation and collection of COVID-19 waste varied depending on the source (Fig. 7); the procedures were governed by regulations in Decision 3455 by NSC; Circular 02, Legal document 1336 by MONRE; Circular 20, Legal documents 1560, 922, 5599, and 5679 by MOH, and Legal document 102 by VIHEMA-MOH (Table S3). All of the discharged waste from sources with COVID-19 patients under treatment (in medical and centralized facilities and households) was collected as infectious waste (COVID-19 waste) and handled separately. In quarantine areas (in centralized facilities and households), only discharged medical waste was collected as COVID-19 waste, except for areas within a medical facility, where both medical and municipal waste were treated as COVID-19 waste. Medical waste from COVID-19 testing and vaccination was separated for handling as COVID-19 waste. Moreover, medical waste consisting of used PPE clothing, gloves, and masks from lockdown areas (e.g., from staff at checkpoints) was also identified as ‘potentially SARS-CoV-2 contaminated waste’ and handled as COVID-19 waste.Fig. 7 Management scheme of COVID-19 waste by March 2022
COVID-19 waste was regulated to be packed, sealed in yellow standard bags, and labeled as ‘potentially SARS-CoV-2 contaminated waste’ before transportation for final disposal. This requirement distinguished COVID-19 waste from other medical waste discharged within medical facilities, which is also packed in yellow bags, and from municipal waste (in green bags) for handling priority. Labeling was also required for waste bins that were placed by the front doors of F0 households (TreatHH); they were dedicated for PPE disposal by visiting medical staff. Provision of yellow standard bags dedicated for infectious waste from community sources was prioritized for centralized waste generators (e.g., TreatC, Vaccination) but not for the great number of scattered generation units such as TreatHH. Waste from laboratories performing qRT-PCR testing (Testing) was identified as highly infectious waste (Decision 3455) and had to be pre-treated in an autoclave before being mixed with other infectious waste in medical facilities for collection. Waste from vaccination was categorized as sharp waste (e.g., disposed auto-disable syringes) and medical waste (e.g., used PPE) and packed and labeled in safety boxes and yellow bags, respectively. Unused vials of vaccines were returned to manufacturers or disposed of following the established procedure for pharmaceutical goods (Legal document 5679). This waste was not part of the COVID-19 waste flow.
Although it was categorized as potentially SARS-CoV-2 contaminated waste, TreatHH waste was found mixed in with municipal solid waste [47]. This waste would have gone through the normal waste-handling steps before most likely ending up in a landfill, the destination of 71% of all municipal waste [54]; other forms of treatment include composting and incineration. In addition to at-source separation awareness, a shortage of waste handlers, transportation vehicles and funding were typical constraints to the introduction of additional collection and transportation for household COVID-19 waste, which operated independent of the current municipal waste system. COVID-19 households were numerous and scattered widely in the community. The additional time, labor, and suitable vehicles needed to collect this waste resulted in delays in collection and transportation and slowed the process of isolating potentially contaminated waste from the community, which is a prerequisite for infection control.
Transportation
Transportation of COVID-19 waste took place on a daily basis for infection prevention. It sometimes was more frequent in accordance with demand and the availability of vehicles specialized for use with infectious waste. In the face of a rapidly growing amount of waste, authorities allowed COVID-19 waste to be stored temporarily in hazardous waste storage sites in medical facilities. Because these were designed for non-crisis conditions, available storage space was most likely insufficient for COVID-19 waste storage. Moreover, there was a lack of temporary storage sites for COVID-19 waste discharged by community sources, which raised the risk of infection associated with contaminated waste. Furthermore, some infectious waste remained uncollected for timely disposal because of the previously noted shortage of waste handlers and the sometimes-heavy workloads, which also highlights the need for temporary sites for COVID-19 waste storage.
Waste handlers in the formal waste management sector (e.g., URENCO) and medical facilities were provided with adequate PPE (PPE level 3: medical mask, gloves, PPE clothing, shoe covers, face shields) for safety during collection, transportation, and treatment of COVID-19 waste (Decisions 4159, 1259). However, those working in the informal sector (e.g., waste collection service cooperatives) lacked such protective equipment because they were not responsible for COVID-19 waste handling and thus were not required to wear or provided with state-supplied PPE. Some informal workers wore their own protective equipment, however, usually medical or fabric masks, gloves, and a disposable raincoat. Given the presence of unsorted COVID-19 waste in municipal waste, the inadequate use of PPE could raise the potential risk of infection of informal waste handlers by contaminated waste, especially in the ‘new normal’ period.
Treatment
Incineration within a day of generation was required for safe, final disposal of COVID-19 waste, preferably in an onsite hazardous medical waste incinerator in medical facilities or in incinerators serving a cluster of medical facilities that did not have onsite incinerators. Incinerators used for industrial hazardous waste were also encouraged to accept COVID-19 waste in cases where the demand for treatment surpassed the available capacity of medical waste incinerators (Decision 3455, Legal document 1878). Flue gas must meet the emission standards in QCVN 02:2012/BTNMT. The pre-treatment of waste from COVID-19 testing laboratories was handled according to guidelines in QCVN 55:2013/BTNMT (Table S3).
Vietnam is likely able to handle COVID-19 waste (hazardous medical waste) treatment using its enormous hazardous waste treatment capacity (1.3 million t per year) [46]. However, deficits in local capacity for waste treatment probably occurred when demand for waste treatment surpassed the capacity of the existing disposal infrastructure; an example of this occurred in Ho Chi Minh City, the epicenter of the 4th (Delta) wave during August–October 2021 [48, 55]. Furthermore, limited disposal infrastructure in remote and underdeveloped provinces or localities [44, 56] also contributed to difficulties in properly treating COVID-19 waste.
Most of identified issues in Vietnam were found similar to those in other developing countries, including presence of COVID-19 waste in municipal waste, a lack of temporary storage sites, and deficits in local capacity for COVID-19 waste treatment. However, inadequate PPE for waste handlers during COVID was mainly recognized in informal waste sector. In ‘new normal’ period of pandemic, those issues were likely to exacerbated as social restrictions were lifted.
Recommendations for adapting to the ‘new normal’
To address current issues using existing resources for safer and more appropriate waste management practices in the transition to the ‘new normal’ period of the pandemic, we propose recommendations that cover all stages of solid waste management from at-source separation to final disposal (Fig. 7) and all sources of COVID-19 waste generation including testing, treatment, and vaccination during ‘new normal’ except for those of F1 (QC-F1 and QHH-F1; Fig. 1). They included separate handling route of COVID-19 waste for household COVID-19 waste, collaboration in waste treatment, adaptive collection of COVID-19 vaccination waste and enhancing COVID-19 waste characteristics.
Separate handling route of COVID-19 waste for household COVID-19 waste
Introduction of a separated handling route for COVID-19 waste discharged from TreatHH appeared to address multiple issues in COVID-19 waste management practices and also to serve as a longer-term response in waste management following the promotion of home-based treatment of COVID-19 patients (Resolution 128). Stickers could be used as an alternative to yellow standard bags to deal with the shortage of yellow standard bags for household COVID-19 waste because the waste would still be distinguishable from municipal waste. The informal sector is a promising alternative to perform COVID-19 waste collection using its network of collection routes and suitable vehicles, many of which are able to perform door-to-door waste collection, even in narrow roads. Collection fees for COVID-19 waste should be determined by referring to Law 03 and other relevant regulations, taking into account the extra cost needed for safety and infection prevention (e.g., PPE for waste handlers, added antivirus measures) in addition to the cost to operate the collection network, under the direction of the local authority. In compliance with current standards for storing hazardous medical waste, temporary storage sites for the COVID-19 waste community could be positioned within the boundaries of district-level or ward-level medical centers that would be quite distant from the nearest households and accessible by trucks. COVID-19 waste collected by the informal sector and moved to temporary storage sites could then be transported by the formal sector to final disposal sites using specialized vehicles. Furthermore, collection times and collection routes need to be rescheduled and reorganized in both the formal and informal sectors to optimize the collection of COVID-19 waste along with that of municipal solid waste, according to service areas and operational capabilities.
Collaboration in waste treatment
Collaboration in waste treatment, in principal authorized under Decision 3455, is likely an efficient way to tackle local deficiencies in treatment capacity for COVID-19 waste by employing the nation’s available capacity and is also consistent with previous suggestions for developing countries in securing treatment capacity of pandemic-related waste [9]. This type of collaboration would expand the treatment capacity for COVID-19 waste by having private treatment service providers join URENCO. Under Delta outbreak (April–October 2021), capacity for COVID-19 waste treatment in Ho Chi Minh City was practically enhanced from 42 to 69 t per day, reducing the treatment occupancy rate––the ratio of estimated demand to calculated capacity––from 395.7 to 290.3% through waste treatment collaboration between 3 private treatment companies (Viet Uc Environment Joint Stock Company, Moc An Chau Logistics Corporation and Green Sai Gon Company) and the state-run Ho Chi Minh City Urban Environment Company Limited [48]. Considering the treatment demand on average during the outbreak (133.4 t per day, [48]), a total of 159 t in capacity per day had been planned to be available from 2022 over such the collaboration in waste treatment to secure the COVID-19 waste treatment in the city [55]. Joint treatment providers must be licensed to treat hazardous medical waste by incineration and satisfy requirements for treating a larger-than-usual amount of infectious waste (e.g., operating incinerators in a waste treatment complex, adopting necessary measures for infection prevention). Collaboration could be introduced within a province or region, depending on specific conditions of treatment capacity and demand. Adequate antivirus measures are essential for the safe transportation of a large amount of infectious waste, especially if it crosses provincial boundaries. Additionally, Global Positioning System/Geographical Information System technology should be used for tracking and managing the transportation of hazardous waste with the agreement of the relevant entities regarding information sharing. A thorough assessment of capacity of COVID-19 waste treatment is needed at both the local and regional levels for a ready and effective response in the context of the unpredictable progression of the pandemic.
Adaptive collection of COVID-19 vaccination waste
Before the ‘new normal’ period, public establishments (e.g., schools, sport centers, indoor stadiums) were temporarily repurposed for use as vaccination clinics under the national mass vaccination campaign. As these sites were restored to their original functions when restrictions were lifted, the national network of pharmacies was likely to be employed as a possible alternative for administering additional booster shots of COVID-19 vaccines, as well as for supplying approved COVID-19 treatment drugs. These actions would be taken in association with the promotion of home-based treatment of COVID-19 patients as part of a strategy to flexibly and effectively control COVID (Resolution 128). Hazardous waste from pharmacies—categorized as small-scale sources of hazardous medical waste—includes discharged chemicals and medicines containing hazardous substances, is characterized as poisonous waste, and is currently regulated to be collected on an on-demand basis in a composite or stainless-steel container with a 30–50 kg storage capacity installed behind the driver’s seat of a motorcycle (Circular 20). Vaccination waste could also be collected using this convenient means of transportation with some added infection-prevention measures. The collection frequency and amount of temporary storage capacity should be increased accordingly to ensure the timely and safe handling of such infectious waste.
Enhancing COVID-19 waste characteristics
Since the beginning of the pandemic, to bring infections under control, Vietnam classified all waste that was potentially contaminated with SARS-CoV-2 as infectious waste (COVID-19 waste) based on the initial information available on the survival and possibility of transmission of the virus through solid waste. This determination resulted in a great increase in the amount of waste generated and subject to special handling. For example, for COVID-19 patients under treatment in medical facilities (TreatMED) under the formerly complete restrictions, all wastes discharged, including both municipal waste and pandemic-induced waste (used PPE for patients, medical staff, and waste handlers; disposable medical care equipment and sterilization), were identified as COVID-19 waste (Decision 3455). This classification introduced an estimated daily amount of 4.64 kg per bed of infectious-identified waste to the existing waste system [43], far larger than a previously reported amount of 0.86 kg bed−1 day−1 in the absence of the pandemic [45]. Similar phenomena have been observed worldwide [6], although the WHO has stated that no change is needed in the classification of waste discharged by COVID-19 patients in terms of infectious and non-infectious waste [6, 57].
As we learn more about the virus and its behaviors in the environment, better identification and classification of waste associated with COVID is needed with the goal of improving the 4Rs (reduce, reuse, recycle, recovery) in ‘new normal’, for example, using reusable, bio-based, or recyclable materials for PPE (e.g., face shields, goggles) and more sustainable and smaller amounts of packaging (e.g., for medical masks or vaccine shipments) [6]. This could help to reduce the volume of generated waste and improve the efficiency of incineration treatment, thereby easing the burden on the current waste system as well as moving towards the larger goal of a circular economy as it applies to waste in the post-acute COVID-19 period. Of options for 4Rs implementation (Table 3), 2 examples in Vietnam likely supported the application of 4Rs to enhance COVID-19 waste characteristics using ‘reduce’ initiative in particular. Further considerations were required to explore more potential applications, covering also other 4R initiatives.Table 3 Options for 4Rs implementation in COVID-19 waste [6, 29, 36–40, 58]; (*)indicates example of application in Vietnam
Option for 4Rs implementation Examples
Reduce Ensure the rational and appropriate use of PPE [6] (*) Vaccinator should wear a medical mask (3 g, [58] instead of PPE level 2 (medical mask, protective clothing, medical gloves, face shield; 252 g, Decision 4159)
Exclude municipal waste from infectious
medical waste (COVID-19 waste) [6, 37, 39]
(*) Excluding the municipal waste discharged by patient and caregiver (1.08 and 0.54 kg per day, respectively) could cut the daily amount of COVID-19 waste from household with patient under treatment (TreatHH) from 1.94 to 0.32 kg per bed
Smaller quantities for healthcare commodities and vaccine [6] Individually packaging for sterile healthcare items only [6]
Reuse Reuse of masks, gowns, or eye protectors with appropriate decontamination, sterilization processing [6, 29, 36] Reuse of masks, gowns, or eye protectors after decontamination processing using dry heat, vaporized hydrogen peroxide, ozone, or Ultraviolet light [36]
Recycle, recovery More sustainable packaging for vaccine [6, 38] Replacement of conventional polypropylene based plastics with bioplastics or paper for vaccine packaging [38]
Use of PPE made with greater proportion of renewable, bio-based or recyclable materials as an alternatives to single-use PPE items [29] Biodegradable gloves made by polysaccharide-based material-filled natural rubber latex (PFNRL) [36]
Cotton fabric face masks [36]
Safety processing COVID-19 medical waste for energy and material recovery Recycling of used medical masks for repurposing as construction materials [6]
Safely convert COVID-19 related medical waste to a usable fuel or heat available with disinfection stage added or integrated with the selected technology [40]
Conclusion
The waste management system in Vietnam struggled during the pandemic because of the large and sudden growth in waste generation, growth that far exceeded that projected for a non-COVID scenario as well as that approved during planning. In our analysis of current waste management practices, we found a number of issues that constrained the proper management of COVID-19 waste and posed a higher risk of infection in relation to contaminated waste. These included mixing of COVID-19 waste in municipal waste, a lack of temporary storage sites for infectious waste, local deficits in waste treatment, and inadequate provision of PPE for waste handlers in the informal sector. As the “new normal” period of the pandemic was implemented, these issues appeared to be exacerbated as social restrictions were lifted. Furthermore, reallocation of part of the recognized sources of COVID-19 waste placed more responsibility for waste handling on local communities and caused a higher level of exposure risk to potentially contaminated waste. In addition, the composition of COVID-19 waste changed such that the proportion of plastic (which is highly combustible in incinerators) was reduced in the second year (including the “new normal”), as compared to the first year (under complete social restriction).
To secure the correct management of COVID-19 waste, a set of recommendations were prepared to address the current issues and those that would probably occur in the new normal period. Separate handling of home treatment COVID-19 waste is highly recommended to ensure the adequate isolation of infectious waste (COVID-19 waste) from the community to prevent additional infection, particularly because home-based treatment of COVID-19 patients is being officially promoted in the ‘new normal’ period. To accomplish this task, the labor and infrastructure of the informal sector currently collecting household municipal waste are seen as suitable, but additional support will be needed for appropriate handling of household COVID-19 waste (e.g., PPE, stickers for COVID-19 waste bags). In addition, collaboration in waste treatment between URENCO and local private waste service providers is a promising route to secure additional capacity for treatment of COVID-19 waste. Pharmacies that administer booster shots of COVID-19 vaccines already have a collection system for hazardous waste, and this system could be modified with additional infection-prevention measures to also collect COVID-19 vaccination waste. Finally, better identification and classification of waste associated with COVID should be considered to enhance waste generation and composition to improve the 4Rs, with the aim of easing the burden on the current waste system and improving waste handling in the post-acute pandemic time.
The proposed recommendations should be considered in the context of regulations that are currently in place to combat the pandemic, as well as current management of solid waste in general and of COVID-19 waste in particular, and in consideration of longer-term strategies related to the pandemic response. Current measures should be maintained, but authorities should remain open to making any adjustments necessary to adapt to the complicated progression of the pandemic. These recommendations for COVID-19 waste management should be, along with those for the healthcare system, integrated into the overall planning of the COVID-19 response to enhance the efficiency of the responses and improve resilience against COVID. Other developing countries could use these findings and recommendations to tackle their waste management problems in the post-acute COVID period.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (PDF 224 kb)
Supplementary file2 (PDF 101 kb)
Supplementary file3 (PDF 49 kb)
Supplementary file4 (PDF 57 kb)
Acknowledgements
The authors thank the medical staff of the Immunology and Microbiology Department of the Pasteur Institute of Ho Chi Minh City for their valuable information on the Vietnamese system of the Centers for Disease Control and Prevention and on the roll-out planning of the 4th booster shot during the ‘new normal’ period of the national mass program on COVID-19 vaccination. We also thank the staff of Nguyen Dinh Chieu General Hospital in Ben Tre Province for information on the COVID-19 waste-handling system in a hospital dedicated to COVID-19 patients, and an official of the Department of Natural Resources and Environment of An Giang Province and staff of the Urban Infrastructure Construction Investment Projects Management Unit (under the People’s Committee of Ho Chi Minh City) for sharing their insights on the provincial administration of COVID-19 waste. Additional thanks go to the researchers of the Department of Administration and Planning–Institute for Environment and Resources at the Vietnam National University-Ho Chi Minh City (VNU-HCM) for their input on the challenges associated with securing correct management of COVID-19 waste in the absence of social restrictions and on the national strategies of waste management during the pandemic.
Data availability
The data that support the findings of this study are available from the corresponding author, Trang DT Nguyen, upon reasonable request.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734957 | NO-CC CODE | 2022-12-14 23:28:31 | no | J Mater Cycles Waste Manag. 2022 Dec 8;:1-16 | utf-8 | J Mater Cycles Waste Manag | 2,022 | 10.1007/s10163-022-01563-x | oa_other |
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J Med Syst
J Med Syst
Journal of Medical Systems
0148-5598
1573-689X
Springer US New York
36471095
1895
10.1007/s10916-022-01895-z
Review
Systematic Review of Telemedicine and eHealth Systems Applied to Vascular Surgery
http://orcid.org/0000-0003-0841-653X
Herrera Montano Isabel [email protected]
1
Presencio Lafuente Elena [email protected]
1
Breñosa Martínez Jose [email protected]
2
Ortega Mansilla Arturo [email protected]
23
Torre Díez Isabel de la [email protected]
1
Río-Solá María Lourdes Del [email protected]
4
1 grid.5239.d 0000 0001 2286 5329 Department of Signal Theory and Communications and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain
2 grid.512306.3 0000 0004 4681 9396 Universidad Europea del Atlántico, C / Isabel Torres, 21, 39011 Santander, Spain
3 grid.441061.6 0000 0004 1786 8906 Universidad Internacional Iberoamericana, Calle 15 Num. 36, between 10 and 12 IMI III, 24560 - Campeche, Mexico City, Mexico
4 grid.411057.6 0000 0000 9274 367X Vascular Surgery Department, Hospital Clínico Universitario de Valladolid, Ramón y Cajal Ave, nº 3, 47003 Valladolid, Spain
6 12 2022
2022
46 12 10417 5 2021
22 11 2022
25 11 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Objective: The objective of this paper is to review and analyze the current state of telemedicine and ehealth in the field of vascular surgery. Methods: This paper collects the relevant information obtained after reviewing the articles related to telemedicine in vascular surgery, published from 2012 to 2022 contained in scientific databases. In addition, the results obtained are statistically studied based on various factors, such as the year of publication or the search engine. In this way, we obtain a complete vision of the current state of telemedicine in the field of vascular surgery. Results: After performing this search and applying selection criteria, 29 articles were obtained for subsequent study and discussion, of which 20 were published in the second half of the decade, representing 70% of the results. In the analysis carried out according to the search criteria used, it can be seen that using the word telemedicine we obtained 69% of the articles while with the criteria mHealth and eHealth we only obtained 22% and 9% of the results, respectively. It can be seen that the filter with the most potential content articles was “vascular surgery AND telemedicine”. In the analysis performed according to the search engine, it was observed that the Google Scholar database contains 93% of the articles found in the massive search and the relevant articles contained therein represent 52% of the total. Conclusion: An upward trend has been observed in recent years, with a clear increase in the number of publications and much lower figures in the first years. One aspect to highlight is that 47.8% of the articles analyzed focus only on postoperative treatment, which may be due to the help provided by telemedicine in detecting surgical site infections by sending images and videos, this being one of the most common postoperative complications. The analyzed works show the importance of telemedicine in vascular surgery and identify possible future lines of research. In the analysis carried out on the origin of the selected relevant papers, an important interest of the US in this topic is demonstrated since more than 50% of the research contains authors from this country, it is also observed that there is no research from Spain, so this research would be an initial step to determine the weaknesses of telemedicine in this field of medicine and a good opportunity to open a research gap in this branch.
Keywords
Telemedicine
mHealth
eHealth
Vascular surgery
Monitoring
Diagnosis
issue-copyright-statement© Springer Science+Business Media, LLC, part of Springer Nature 2022
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pmcIntroduction
The concept of telemedicine emerged in the 1970s as a solution to geographical barriers, increasing accessibility to health care, especially in rural areas and developing countries [1, 2]. Over time, it has been shown that Communication Technologies (ICT) are also useful for improving the quality of healthcare delivery, support for continuity of care, efficiency of services, training of professionals, and communication between healthcare personnel and patients [1, 3, 4]. The World Health Organization (WHO) defines telemedicine as “the provision of health services (where distance is a determining factor) by health professionals through the use of ICT for the exchange of valid information for diagnosis, treatment, disease prevention, research and evaluation and for the continuing education of health professionals, all with the ultimate goal of improving the health of populations and communities” [5–7].
On the other hand, eHealth is a somewhat more complicated concept that is often confused with telemedicine. This concept, located at the intersection between medical informatics, public health and commercial interests, refers to the provision of health information and services on the Internet and has also been imbued with a philosophy implicit in these technologies: new ways of thinking, networking, global thinking, sharing as a value, etc., which has led to this new concept being increasingly developed [1, 8]. WHO defines it as: “the cost-effective and safe use of information and communication technologies in support of health and health-related fields, including health care, health surveillance and health education, knowledge and research” [9].
The number of people with access to smartphones is increasing every day. According to survey Figs. [10–12]., the two regions with the highest Internet penetration are Eastern Europe (92%) and Northern Europe (95%), closely followed by North America (88%). In contrast, the regions with the lowest Internet penetration are East Africa (23%) and West Africa (36%). In 2020, the ranking of countries with the highest Internet penetration was led by the United Arab Emirates, with 99% penetration, followed by Denmark (98%), South Korea (96%), Sweden (96%), Switzerland (96%), the United Kingdom (96%) and the Netherlands (95%). Spain ranked 14th, with an internet penetration of 91%, decreasing 2% points from the 2019 results. The countries with the lowest internet penetration were North Korea, Sudan (8.0%), Eritrea, with a penetration of 8.3% and Burundi with 9.9%.
Angiology and vascular surgery are a medical-surgical specialty dedicated to the study, prevention, clinical and instrumental diagnosis and treatment of vascular pathology. Its field of action covers organic and/or functional diseases of the arterial, venous (Phlebology) and lymphatic (Lymphology) systems [13]. After vaccination against covid-19, numerous studies have focused on the diagnosis and treatment of thrombotic events, due to the high number of thrombosis caused by the adverse effects of these vaccines [14–21]. The main objective of this work is to study the situation of telemedicine in vascular surgery in order to develop new tools and systems to aid in its detection, diagnosis and treatment. For this purpose, a systematic review of the existing articles related to the subject has been carried out, applying a PRISMA methodology. In addition, the results are analyzed statistically, clearly showing the increase in research in this field as the years go by and with them the interest of scientists. The most important ideas of the relevant articles are synthesized to group in a single work the contributions and conclusions of each one of them.
There are other publications related to this research work on telemedicine and vascular surgery that focus on the study of various mobile telemedicine systems [22]; the literature review on the effect of telemedicine on patient-physician communication [23] and telemedicine systems that have been evaluated for usability or ease of use [24]. The systematic review on the use of additive manufacturing in vascular surgery, specifically, the applications of 3D printing in endovascular surgery [25] and a summary of academic publications indexed in the MEDLINE database, concerning the use of telemedicine in vascular surgery in the pathologies of aortic disease, LEAD and carotid disease [26]. However, there is no study that performs a systematic review in the Science Direct, PubMed, Web of Science and Google Scholar databases of studies related to telemedicine in vascular surgery.
The methodology followed for this research work is described below. Subsequently, the results obtained are presented and discussed, which in turn give rise to the conclusions shown at the end of this paper.
Methods
This work is based on a systematic review of the literature in scientific databases following a prismatic methodology, the search is focused on scientific papers related to telemedicine in vascular surgery. First, the scientific databases in which the search was performed, and the terms used are presented. Then, the procedure used for the selection of the articles to be analyzed is described.
Scientific Databases
The systematic review was based on the scientific databases Science Direct, PubMed, Web of Science and Google Scholar, because these are the ones that bring together almost all the information and papers related to telemedicine in this field. Figure 1 shows the search criteria inserted in each of the search engines of these databases and the sections of the papers searched in each case. These sections are determined according to the characteristics of the advanced search engines in each of the databases. The search was carried out in the years 2012 to 2022, using papers in English and discarding books or conference abstracts.
Fig. 1 Search criteria in different databases
Papers Selection
After performing the search, the articles to be analyzed were selected by reading the titles of the results obtained, resulting in 110 papers of interest in this step. Once these were selected, we proceeded to eliminate those that were duplicated (33). Then the abstracts of the remaining 77 papers were analyzed, eliminating those that were not sufficiently significant or that belonged to other areas of study, resulting in a total of 45 papers for complete reading. In this phase, only those that are relevant to our study are selected, finally obtaining 29 papers for analysis and evaluation. This procedure is shown in the prism diagram in Fig. 2.
Fig. 2 Methodological Prisma for the selection of articles
The 29 resulting articles are subsequently evaluated, analyzing the results according to the year of publication and search criteria, according to the search engine where each article was found and its contribution. The results obtained are shown in the next section.
Results
Once the systematic review methodology explained above has been applied, the results of the selection of relevant papers from the databases are analyzed.
Analysis by Publication year
Figure 3 shows the results of the relevant papers obtained in the search, categorized according to the year of publication. As can be seen, most of the articles have been published in the last five years, which shows a growing interest in the subject.
Fig. 3 Number of relevant papers for each year
Analysis by Search Engine
Figure 4 a graph showing the percentage of relevant papers selected in each database. It can be clearly seen that the most complete database for the search of articles on telemedicine applied to vascular surgery is “Google Scholar”, since more than 50% of the relevant articles selected after applying the methodology were found. The PubMed database is the next with the highest number of articles selected, with 22% of the articles chosen from here. Slightly behind are the Web of Science and Science Direct databases with 18% and 8% of the selected articles, respectively.
Fig. 4 Graph with the percentage of results by search engine after the application of the methodology
Keyword Analysis
Fig. 5 Results graph by keywords after applying the methodology
If we focus on the results obtained according to the search criteria used, we can see in Fig. 5 that using the word telemedicine we have obtained 69% of the articles, while with the criteria mHealth and eHealth we have only obtained 22% and 9% of the results respectively. It can be seen that the filter with the most potential content articles “vascular surgery AND telemedicine”.
Analysis of Relevant Papers
Table 1 shows a comparison of the articles obtained in terms of publication date and contributions to obtain a clearer idea of the current state of research in telemedicine applied to vascular surgery.
Table 1 Articles on telemedicine and eHealth applied to vascular surgery
TITLE YEAR CONTRIBUTION
Cyber medicine enables remote neuromonitoring during aortic surgery [27]. 2012 Study of remote neuromonitoring of spinal cord function during open repair of descending thoracic aortic aneurysms and thoracoabdominal aortic aneurysms.
Multidisciplinary treatment for peripheral arterial occlusive disease and the role of eHealth and mHealth [28]. 2012 New treatment model for peripheral arterial occlusive disease (PAOS) using eHealth and mHealth solutions.
Robot-assisted fenestrated endovascular aneurysm repair (FEVAR) using the Magellan system [29]. 2013 Remote manipulated endovascular aneurysm repair robot.
Development, Implementation, and Evaluation of a Structured Reporting Web Tool for Abdominal Aortic Aneurysms [30]. 2013 New structured reporting system for abdominal aortic aneurysms (AAA), aimed at improving professional communication by providing clinical information in a pre-defined standard.
Teleconsultation in vascular surgery: a 13-year single center experience [31]. 2013 Analysis of the results of a medical consultation service via email carried out for 13 years in the field of vascular surgery.
Inter-rater agreement and checklist validation for postoperative wound assessment using smartphone images in vascular surgery [32]. 2016 Study of the validity of images taken with the mobile as a substitute for a medical review for the identification of postoperative infections (SSI).
Technology-Enabled Remote Monitoring and Self-Management - Vision for Patient Empowerment Following Cardiac and Vascular Surgery: User Testing and Randomized Controlled Trial Protocol [33]. 2016 Study of the efficacy of an eHealth-enabled service delivery intervention, technology-enabled remote monitoring and self-maintenance for patient treatment after cardiac and vascular surgery.
Evaluating Patient Usability of an Image-Based Mobile Health Platform for Postoperative Wound Monitoring [34]. 2016 Image-based mobile application for postoperative injury monitoring.
Diagnosing Surgical Site Infection Using Wound Photography: A Scenario-Based Study [35]. 2016 Study of the importance of providing images of postoperative lesions for the identification of surgical infections through telemedicine.
Feasibility of Implementing a Patient-Centered Postoperative Wound Monitoring Program Using Smartphone Images: A Pilot Protocol [36]. 2017 Development of a protocol for monitoring injuries in the postoperative period by means of images taken with the mobile phone and study of its viability for patients and healthcare personnel.
Early clinical experience using telemedicine for the management of patients with varicose vein disease [37]. 2017 Comparison of the results of the evaluation of patients with varicose veins in a virtual clinic by videoconference and in the traditional clinic with the same doctor.
Feasibility of an Image-Based Mobile Health Protocol for Postoperative Wound Monitoring [38]. 2018 Mobile application for sending images of surgical lesions in the postoperative period. Through this application, they are also asked a series of questions about their recovery.
Implementation of a virtual vascular clinic with point-of-care ultrasound in an integrated health care system [39]. 2018 Virtual vascular clinic for the diagnosis of arterial and venous diseases. Offers remote videoconference consultations with vascular surgeons.
Use of photograph-based telemedicine in postoperative wound assessment to diagnose or exclude surgical site infection [40]. 2018 Study of the feasibility of substituting a traditional medical check-up for postoperative image-based monitoring for the identification of surgical infections (SSI).
Telemonitoring of left-ventricular assist device patients-current status and future challenges [41]. 2018 Study of the potential of telemonitoring patients with a left ventricular assist device (LVAD) as well as the necessary requirements for its implementation.
Telehealth Electronic Monitoring for Post Discharge Complications and Surgical Site Infections following Arterial Revascularization with Groin Incision [42]. 2018 Study of the results of patients whose postoperative monitoring is carried out by telemedicine compared with those whose monitoring is carried out in a standard way.
Evaluation of Wound Photography for Remote Postoperative Assessment of Surgical Site Infections [43]. 2019 Remote medical care for the diagnosis of postoperative infections (SSI) by sending images of the lesions.
EHealth tool for patients with abdominal aortic aneurysm: development and initial evaluation [44]. 2019 EHealth tool for patients with abdominal aortic aneurysm (AAA) through a participatory design process.
Telemedicine in patients with peripheral arterial disease: is it worth the effort? [45]. 2019 Study of the current use of telemedicine for interventions in peripheral arterial disease (PAD).
Infrastructural needs and expected benefits of telemonitoring in left ventricular assist device therapy: Results of a qualitative study using expert interviews and focus group discussions with patients [46]. 2019 Study on the specific requirements of the left ventricular assist device for telemonitoring and infrastructure translation from the point of view of caregivers and patients.
Postoperative Remote Automated Monitoring and Virtual Hospital-to-Home Care System Following Cardiac and Major Vascular Surgery: User Testing Study [47]. 2020 Study of the response and acceptance of users to remote monitoring and virtual medical care from hospital to home using Philip’s Guardian and Electronic Transition to Ambulatory Care technologies.
Telemedicine platforms and their use in the coronavirus disease-19 era to deliver comprehensive vascular care [48]. 2020 Study on the use of technology and telemedicine to allow communication between doctors and health professionals and patients during the COVID-19 pandemic in the field of vascular surgery.
An international experience of electronic communication and implementation of eHealth solutions in a vascular surgery clinic [49]. 2020 Collection of international data through questionnaires given to vascular surgery patients in hospitals in Ireland and Canada.
Telemedicine in vascular surgery: simple and protected tools and procedures[50] 2020 Development of a telemedicine health care access system for vascular surgery patients for wound follow-up and postoperative consultations at home or at health care centers.
The Benefits of a Centralised Remote Surveillance Programme for Vascular Patients [51]. 2022 Study of clinical and financial benefits of a centralized remote monitoring program for vascular patients over traditional outpatient follow-up.
The Application of Digital Frailty Screening to Triage Nonhealing and Complex Wounds [52]. 2022 Study and proposal for the use of digital fragility biomarkers to predict the complexity of diabetic foot ulcer, classifying patients who require simple treatments from those who require more complex care, such as vascular surgery.
Utilizing Machine Learning Algorithms to Evaluate Sex-based Differences in Preoperative Hemoglobin Thresholds in Open Vascular Surgery [53]. 2022 Analysis of risk factors for the prediction of mortality in vascular surgery using machine learning.
Improved Outpatient Medical Visit Compliance with Sociodemographic Discrepancies in Vascular Telehealth Evaluations [54]. 2022 Demonstrates the impact of eHealth for vascular surgery patient visits, as well as, exploring the effect of sociodemographic factors on vascular surgery outpatient eHealth management during the COVID-19 pandemic.
Improving Access to Specialty Care Using Vascular Surgery E-consults [55] 2022 Evaluation of the impact, in vascular surgery patients, of electronic consultations to determine their essential components, use and impact on patients.
Discussion and Conclusion
Finally, if we look at the content and contributions of each of the articles, we see that 65.5% of the 29 articles selected study telemedicine applied to teleconsultation and postoperative follow-up. In this case, we have seen telemedicine in virtual medical care, using images and videos of the wound to check its evolution, e-mails for patient follow-up, among other platforms that allow virtual contact between the healthcare personnel and the patient. Figure 6 shows these and other applications of telemedicine applied to vascular surgery, such as Telemonitoring by ventricular assist devices in 6.9% of the articles, for the treatment of peripheral artery disease in 10.3%, as well as Biomarkers of digital fragility and in aortic surgery representing 6.8% of the total articles. In addition, the first signs of machine learning algorithms applied to vascular surgery in the analysis of mortality risk factors are shown in one of the articles found.
It is worth noting that 20.6% of the articles deal with the implementation of a virtual clinic focused on vascular surgery, which would not only treat postoperative problems, but would also perform periodic remote consultations throughout the diagnosis and recovery process and make a comparison with a totally face-to-face treatment.
It is worth noting that 20.6% of the articles deal with the implementation of a virtual clinic focused on vascular surgery, which would not only treat postoperative problems, but would perform periodic remote consultations throughout the diagnostic and recovery process and make a comparison with a fully face-to-face treatment.
In addition, 5 of the 29 final articles deal with telemedicine tools for active participation in patient treatment, as opposed to the remaining articles that focus on an application of telemedicine for diagnosis, monitoring and communication between patients and healthcare personnel. This represents 17.2% of the articles and these are useful applications:
- Remotely manipulated endovascular aneurysm repair robot.
- Remote neuromonitoring of spinal cord function during open repair of descending thoracic and thoracoabdominal aortic aneurysms.
- Mobile application called “WalkMate”, which has an ambient location radar to search for other patients or volunteers within the network, a pre-recorded audio coach to advise and encourage walking, a global positioning system tracking device to record walking distances and speed, live coaching by (schooled) peers, and support from the coach via audio/video call system.
-The use of digital frailty biomarkers for the prediction of diabetic foot ulcer complexity, which allows the classification of patients for simple treatments from those needing more complex care or vascular surgery.
- Telemedicine system for healthcare of vascular surgery patients for wound follow-up and postoperative consultations at home or in health centers.
Fig. 6 Percentage of results according to content after application of the methodology
The relevant studies found show that the applications of telemedicine in the field of vascular surgery are multiple, from patient follow-up and early detection of complications to the performance of remote aneurysm repairs. This is why this topic is of interest to many countries around the world, as shown in Fig. 7, which shows the number of relevant publications for each country, basing this analysis on the affiliation of the authors of each paper. Several of these papers are collaborations of authors from different countries, repeating the same article for different countries in these cases. A high number of publications from the USA is observed, which shows a high interest of researchers from this country in this regard. There is also evidence of interest from other countries such as The Netherlands, Germany, Switzerland and Canada, each of which has more than two studies indexed in the databases studied during the last ten years. However, it can be observed that no relevant work has been found from Spain, so this research would be a first step to determine the weaknesses of telemedicine in this field and a good opportunity to open a research gap in this branch.
Fig. 7 Number of relevant investigations by country of origin
In this research work, a systematic review of works related to telemedicine in vascular surgery in scientific databases has been carried out. An upward trend is observed in recent years, with a clear increase in the number of publications and much lower figures in the early years. This is not surprising given that technology is advancing by leaps and bounds, with increasing access to mobile devices with which to enjoy the benefits that telemedicine offers.
The search yielded a total of 29 relevant articles after applying the methodology. In the analysis carried out according to the search engine, it was shown that the Google Scholar database contains 93% of the articles found in the massive search and the relevant contents in it represent 52% of the total.
Another aspect to highlight is that 65.5% of the articles analyzed focus on teleconsultation and remote postoperative follow-up, which may be due to the help provided by telemedicine in the detection of surgical site infections by sending images and videos, this being one of the most common complications in the postoperative period. The studies found have shown the reduction of costs and waiting times for the patient, making it evident that telemedicine can be very interesting in cases in which traveling to the health center is a problem, as in the case of patients who live in isolated areas, with fewer resources, or even in cases of pandemic, in which traveling to a health center may pose a risk to the patient. In addition to the mobility factor, the time factor invested in these clinical visits must also be considered, as well as cost savings.
In addition to this, a possible future line of telemedicine may be the use of surgical telepresence in vascular patients. Surgical telepresence would allow more socially distant operations to be performed through telemedicine and could benefit patients who cannot risk longer trips for surgery. Although preliminary research has shown the efficacy of these types of operations in pigs, and robotic surgery is gaining acceptance in healthcare, more research would be needed to verify that the distances might be necessary for humans. As well as the development of Machine Learning and Deep Learning algorithms in order to early detect pathologies of interest within vascular surgery.
Acknowledgements
This research has been partially supported by European under the project Erasmus + named Digital Simulator for Entrepreneurial Finance.
Declarations
Conflict of Interest
The authors declare that they have no conflict of interest.
Ethical Approval
This article does not contain any studies with human participants or animals performed by any of the authors.
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| 36471095 | PMC9734958 | NO-CC CODE | 2022-12-14 23:28:31 | no | J Med Syst. 2022 Dec 6; 46(12):104 | utf-8 | J Med Syst | 2,022 | 10.1007/s10916-022-01895-z | oa_other |
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Erwerbs-Obstbau
Erwerbs-Obstbau
0014-0309
1439-0302
Springer Berlin Heidelberg Berlin/Heidelberg
784
10.1007/s10341-022-00784-6
Original Article / Originalbeitrag
Internal Factors Affecting Competitiveness in Agribusinesses: A Case Study in the Hazelnut Sector in Ordu and Giresun Provinces of Turkey
http://orcid.org/0000-0001-8427-5412
Aydoğan Mehmet [email protected]
grid.507331.3 0000 0004 7475 1800 Department of Agricultural Economics, Faculty of Agriculture, Malatya Turgut Özal University, Malatya, Turkey
5 12 2022
111
9 8 2022
31 10 2022
© The Author(s), under exclusive licence to Der/die Autor(en), exklusiv lizenziert an Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature 2022, Springer Nature oder sein Lizenzgeber (z.B. eine Gesellschaft oder ein*e andere*r Vertragspartner*in) hält die ausschließlichen Nutzungsrechte an diesem Artikel kraft eines Verlagsvertrags mit dem/den Autor*in(nen) oder anderen Rechteinhaber*in(nen); die Selbstarchivierung der akzeptierten Manuskriptversion dieses Artikels durch Autor*in(nen) unterliegt ausschließlich den Bedingungen dieses Verlagsvertrags und dem geltenden Recht.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The study’s primary purpose is to reveal the factors affecting the competitiveness of hazelnut agribusiness enterprises. The data used in the research were obtained from surveys with 51 enterprises in Ordu and Giresun provinces, Turkey. The enterprises were divided into competitive and non-competitive with a two-step cluster analysis. Indices were calculated to measure enterprises’ competitiveness, and the t‑test was used to compare enterprises’ characteristics and competitiveness values. The research results indicated that the size of the enterprises, implementation of corporate governance processes, support for personnel development, employment of qualified personnel, differentiated process management, robust information technologies infrastructure, and using e‑commerce applications increased the competitiveness. The research results confirmed that the competitiveness of enterprises was affected not only by financial indicators but also by internal factors within the enterprise. The non-competitive enterprises focused on low-cost production and overlooked other internal and external factors necessary for competitiveness. The hazelnut enterprises could increase their competitiveness by investing in e‑commerce and information technologies infrastructure by prioritizing personnel and corporate management processes.
Keywords
Competitiveness
Internal factors
Hazelnut agro-companies
COVID-19
Turkey
Eastern Black Sea Project Regional Development Administration
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pmcIntroduction
Hazelnut is a strategic product for Turkey, the largest hazelnut producer in the Mediterranean region and the world. Turkey is in the leading position by achieving an average of 66.4% hazelnut production and 70% hazelnut export worldwide. Hazelnut, which is among Turkey’s traditional export products, provides a foreign exchange inflow to the country of approximately 1.3 billion dollars annually. Approximately 9% of Turkey’s annual export of agricultural products and approximately 2% of total exports are obtained from hazelnuts and their products alone (FAOStat 2020). In addition, its cultivation in a specific region (the Black Sea region) has led to the formation of all value chain actors in the region. It is the primary source of livelihood for approximately 3 million people, especially those employed as farmers and other sub-sectors.
Although Turkey ranks first in the world in terms of hazelnut production and export, serious competitors have entered the market in recent years, and Turkey’s hazelnut production and export have decreased significantly. While Turkey had a share of 70% of the world’s total hazelnut production at the beginning of the 2000s, this rate has decreased gradually in recent years. Similarly, at the beginning of the 2000s, 81.9% of the world’s hazelnut exports were carried out by Turkey, while this rate decreased to 66.1% on average over the last 10 years (WTC 2020). Therefore, the decrease in Turkey’s hazelnut production and exports may cause many sectors worldwide to have problems in the supply of raw materials. On the other hand, Italy, Chile, Azerbaijan, and Georgia constantly increase their shares in the world hazelnut market in production and exports. In Italy, hazelnut production has accelerated in recent years due to the desire to guarantee the raw material requirement in the chocolate industry; hazelnut is one of the primary inputs in the chocolate industry. Besides, while some South American countries, such as Chile, have suitable climatic conditions for hazelnut production, Georgia, Azerbaijan, and Iran have the advantages of cheap labor for hazelnut farming. These countries are Turkey’s new competitors in the world hazelnut market (Aktaş et al. 2009). The fact that other countries have become competitive in the world hazelnut market may indirectly mean a loss of income for the producers in Turkey. When income losses are added to the Turkish hazelnut sector, which is currently struggling with many structural problems, the world hazelnut supply may be adversely affected in the short term.
Hazelnut cultivation in Turkey has been struggling with long-term infrastructure problems such as low yield, production with traditional methods, expensive inputs, small farm size, and various marketing problems (Özkan 2011; Öztürk and Kaşko Arıcı 2017; Cansev et al. 2018). When the infrastructural problems are combined with the relative superiority of other countries, Turkey’s role in the world hazelnut market is gradually decreasing. In other words, Turkey may no longer maintain its competitive advantage in hazelnuts with production alone. Therefore, for Turkey to maintain its competitive advantage, a competitive agriculture-based industry should support hazelnut cultivation.
It is difficult to say that the hazelnut processing industry in Turkey is sufficiently developed. However, considering that 37% of the hazelnuts exported by Turkey consist of processed hazelnuts and hazelnut products (Erköse et al. 2020), it can be said that the sector is open to development. Hazelnut enterprises in Turkey generally prepare and market hazelnuts as cracking, roasting, crushing, slicing, and oil. The previous studies on the hazelnut industry in Turkey revealed that there had been a severe decrease in the competitiveness of the Turkish hazelnut industry in recent years (Yenisu 2017), and product diversification and technology usage level is low due to insufficient research and development (R&D) investment works in the industrial enterprises in the sector (Şahinli 2014; Yılmaz 2017). As a result, the Turkish hazelnut industry competes worldwide only with the amount of production and exports but cannot provide good competition for value-added products. The development of the competitiveness of the Turkish hazelnut industry in the category of value-added products is crucial for the world hazelnut supply and the sustainability of the livelihoods of hazelnut producers.
Competitiveness is a multi-dimensional concept in the literature. The competitiveness concept has been examined at three, generally related levels: country, sector, and firm (Ajitabh and Momaya 2004; Windsperger 2006; Allen and Potiowsky 2008; Pigatto et al. 2020). National competitiveness is the comparison of macroeconomic indicators and social welfare parameters among countries (Murtha et al. 1998). Martin et al. (1991) explained sector competitiveness as a sector’s ability to survive and expand sustainably in existing or new markets. On the other hand, Buckley et al. (1988) paraphrased the firm competitiveness as the firm’s long-term profit performance, as well as its ability to satisfy its employees and provide high returns to its owners. Since the concept of competitiveness is multi-dimensional, measurement methods also differ. In the literature, the concept of firm competitiveness has often been measured in comparison with the adoption of innovations, capacity to respond to changing demands (Chodavarapu et al. 2016; Brito and Zapata 2017), private cost ratios, profits, inputs, costs, and operating incomes (Martin et al. 1991; de Freitas et al. 2015; Winarno and Harisudin 2018). On the other hand, in some studies, it was emphasized that in the measurement of competitiveness, it was not only possible to focus on the production factors and market conditions of the firms, but also the interactions and cooperation between the firms were important (Sarturi et al. 2016; Pigatto et al. 2020). Similarly, Man et al. (2002) asserted that competitiveness is affected by internal factors and external environmental factors, and competitiveness at the firm level can only be measured by internal factors. Internal factors affecting competitiveness are financial resources, human and technological resources, quality systems, product diversity, and organizational structure (Buckley et al. 1988; Man et al. 2002; Dlamini et al. 2014).
Firm-level competitiveness is one of the most studied topics in the literature. Siudek and Zawojska (2014) argued that a country’s improving competitiveness is directly related to firm-oriented competitiveness. Firm competitiveness, which was the subject of the study, was explained by the firm’s long-term economic performance, as well as its ability to satisfy its employees and provide sustainable high returns to its owners in literature (Hudori 2013; de Freitas et al. 2015; Winarno and Harisudin 2018; Pigatto et al. 2020). Considering the definition, the concept of competitiveness that is valid today does not only focus on firm profitability. In addition to profitability, two critical concepts, satisfying employees and sustainability of economic return, come to the fore. However, many studies measured competitiveness with traditional methods such as increased profitability, asset return, and equity (Chao-Hung and Li-Chang 2010; Sachitra 2016). In other words, traditional methods ignored factors other than financial indicators in measuring competitiveness. Babu and Shishodia (2018) criticized the methods that did not consider variables other than financial indicators in the measurement of competitiveness, claiming that financial indicators would only provide information about the financial management of companies. Latruffe (2010) suggested that current literature mainly focused on price or cost competitiveness, while non-price components of firms’ competitiveness were often overlooked.
Another issue as crucial as factor selection is the measurement method of competitiveness. Policy analysis matrix, private cost ratio (Winarno and Harisudin 2018), comparative advantages, Balassa index (Sachitra 2016), analytical hierarchy process, linear regression (Delfín-Ortega and Bonales-Valencia 2020), and descriptive statistics (Dlamini et al. 2014; Sarturi et al. 2016) can be indicated among the measurement methods frequently used in competitiveness measurement in previous studies. Although the variables used to measure competitiveness in these studies had different units, analyses were carried out without considering this difference. This problem encourages studies to use variables in different units in the same model. The study de-unitized the variables used in the model by converting them into indices to eliminate the differences stemming from the units and sought a solution to the problem of comparing different units.
The external factors affecting competitiveness usually have a national-level result, which similarly affects the sector and all companies. On the other hand, internal factors affecting competitiveness also affect external factors positively or negatively from bottom to top. So, the study focused on the fact that firms cannot directly control variables such as policies, supports, and market structure, which are external factors that affect competitiveness. However, the human capital, economic structure, cooperation, innovation, and infrastructure variables in their internal structures that directly affect competitiveness can be controlled by enterprises. The research aimed to reveal the internal factors affecting hazelnut enterprises’ competitiveness and the differences between competitive and non-competitive enterprises.
Materials and Methods
Research Area
In Turkey, an average of 580,000 t of shelled hazelnuts are produced annually. The total amount of in-shell hazelnuts produced in the Giresun and Ordu provinces is 39.5% of the hazelnuts produced in Turkey (Turkstat 2020). Therefore, hazelnut agribusinesses enterprises are concentrated in these provinces. Ordu and Giresun provinces were chosen purposefully because hazelnut agricultural enterprises were mainly located in these provinces (Fig. 1).Fig. 1 Research area and hazelnut producing provinces
Research Data and Sampling Size
The main material of the research consisted of primary data obtained through a survey from hazelnut agribusiness enterprises in Ordu and Giresun provinces. The list of enterprises was obtained from the Turkish Ministry of Agriculture and Forestry (MoAF) databases. The research used the whole count method to determine the number of enterprises to be surveyed, and a survey was conducted with 51 hazelnut agribusiness enterprises. The secondary research data included previous studies, databases, and related reports. The data used in the study belonged to the production period of 2019.
Classifying Enterprises and Calculation of Competitiveness Indices
Previous studies stated that the firm’s competitiveness is related to market share, profitability, and capacity (Martin et al. 1991; Chao-Hung and Li-Chang 2010; Bedek and Njavro 2016). Ajitabh and Momaya (2004) argued that a firm’s share in the competitive market was its competitiveness. Therefore, the enterprises were divided into competitive and non-competitive by two-step cluster analysis using market share and unit profitability variables. According to the cluster analysis results, 54.9% of the enterprises were competitive and 45.1% were non-competitive. The average Silhouette value indicating the clustering quality (Netshipale et al. 2022) was determined as 0.4 and was interpreted as a good clustering.
The variables affecting competitiveness were grouped into human capital, economic capital, corporate governance, cooperation, and innovativeness. In the study, the variables were converted into indices and de-unitized to eliminate the problem of comparing different units. A new method was tried in the study based on previous measurement methods. The procedures for creating and calculating the indices are explained in detail below.
In the first step, the indicators (Xi) used to measure competitiveness and given in Table 1 were converted into scores (SXi) using Eq. 1 to de-unitize them (Barrera-Roldán and Saldivar-Valdés 2002; Aydoğan et al. 2022). Five sub-competitiveness indexes (HCI, ECI, CGI, CI, and InovI) were created by summing the calculated score values (SXi) according to their relevance. The calculating methods were given in the first column of Table 1. In determining the best value and the worst value terms (Eq. 1), the lowest value among all observations of the relevant variable was accepted as the “worst value,” and the highest value was accepted as the “best value.”1 SXi=1-Xi's best value-Xi/[Xi's best value-Xi's worst value]
Table 1 Sub-competitiveness indices and indicators used in the calculation
Sub-competitiveness indices Indicators (Xi)
Human Capital Index (HCI)
HCI = SX1 + SX2 + SX3 + SX4 + SX5
Total number of employees score (X1)
Permanent employee score (X2)
Number of qualified personnel score (X3)
Personnel development support score (X4)
Personnel specialization score (X5)
Economic Capital Index (ECI)
ECI = SX6 + SX7 + SX8 + SX9 + SX10
Allocated R&D share score (X6)
Capacity utilization rate score (X7)
Equity utilization score (X8)
Market share score (X9)
Revenue growth score (X10)
Corporate Governance Index (CGI)
CGI = SX11 + SX12 + SX13 + SX14 + SX15
Size of the business area score (X11)
Legal status score (X12)
Corporate governance score (X13)
Quality management processes score (X14)
Operating capacity score (X15)
Cooperation Index (CI)
CI = SX16 + SX17 + SX18 + SX19 + SX20
Clustering score (X16)
Collaboration score (X17)
Sectoral developments follow-up score (X18)
Technical consulting score (X19)
Joint-production score (X20)
Innovativeness Index (InovI)
InovI = SX21 + SX22 + SX23 + SX24 + SX25
Brand creation score (X21)
Differentiated product score (X22)
Differentiated process management score (X23)
E‑commerce score (X24)
IT infrastructure score (X25)
In the next step, the Total Competitiveness Index (TCI) was calculated by taking the sum of the sub-competition indices (Eq. 2), and this value indicated the competitiveness of the enterprises compared to the others.2 TCI=HCI+ECI+CGI+CI+InovI
In the last step, the values of the Total Competitiveness Index (TCI), Human Capital Index (HCI), Economic Capital Index (ECI), Corporate Governance Index (CGI), Cooperation Index (CI), Innovativeness Index (InovI), and enterprise characteristics were compared according to competitive and non-competitive groups with the t‑test. The t‑test is a widely used hypothesis test that measures the difference between the means of two groups (Demiryürek et al. 2008; Aydoğan et al. 2016). Thus, it was aimed to reveal the factors that positively or negatively affect the competitiveness of the enterprises in the research area. Also, ratios and percentages were used in the analysis of enterprise characteristics. Analyses were performed with SPSS (ver. 25) package program.
Results
Comparison of Agribusiness Enterprise Characteristics
Hazelnut agribusiness enterprises purchase shelled hazelnuts (raw materials) from farmers or intermediaries and transform them into raw hazelnut kernels, roasted hazelnut kernels, sliced hazelnuts, hazelnut puree, hazelnut oil, and hazelnut flour. However, the variety of these products may vary according to the enterprises. Some enterprises produce all of these products, some only produce a few, depending on the operating capacity. Thus, the general characteristics of the enterprises were compared according to competitiveness groups (Table 2). A total of 58.8% of the enterprises in the research were located in Ordu province and 41.2% in Giresun province, Turkey. In all, 17.6% of the companies were sole proprietorships, 58.8% were limited liability companies, and 23.5% were joint stock companies.Table 2 Comparison of enterprise characteristics
Characteristics Enterprises Count Mean Std. Err t Value p-Value
Firm age (years) Competitive 28 14.9 1.6 1.753 0.086*
Non-competitive 23 20.2 2.7
The size of the open space area (m2) Competitive 28 5.985 1.910 1.763 0.084*
Non-competitive 23 2.096 708
The size of the closed area (m2) Competitive 28 3.876 1.093 0.623 0.536
Non-competitive 23 2.964 914
The hazelnut (raw material) cost
($/Kg)
Competitive 28 2.62 0.1 2.235 0.030**
Non-competitive 23 2.80 0.3
Hazelnut (product) sales price
($/Kg)
Competitive 28 6.25 0.9 1.838 0.072*
Non-competitive 23 5.62 1.2
Total gross income per employee
($/employee)
Competitive 28 760,316.6 239,111 1.841 0.053*
Non-competitive 23 266,095.9 52,260
*, **, *** Significant at 10%, 5%, and 1%, respectively
The average firm age was 17.3 years, and the average age of non-competitive enterprises (20.2) was higher than the competitive ones (14.9) (p < 0.10). In the research area, the enterprises’ average open area was 8139.3 m2, and the average indoor area was 3759.7 m2. The competitive enterprises’ open area (5985 m2 vs. 2096 m2) (p < 0.10) and indoor area (3876 m2 vs. 2964 m2) sizes were higher than non-competitive enterprises. In the study, the average hazelnut raw material cost was 2.70 $ kg−1, the average product sales price was 5.99 $ kg−1, and the gross profit per employee was 537,432.7 US dollars. The competitive enterprises’ raw materials cost (shelled hazelnuts) was lower than non-competitive (p < 0.05), and they sold products at higher prices (p < 0.10). Moreover, competitive enterprises’ gross income per employee was higher than non-competitive (p < 0.05).
The attitudes and vision of the enterprise managers are as crucial as the technical indicators in competitiveness. Attitudes of enterprise managers on concepts related to competitiveness are presented in Table 3.Table 3 Attitudes of enterprise managers towards some competitiveness indicators
Competitiveness indicators Competitive Non-competitive
Disagree (%) Undecided (%) Agree (%) Total (%) Disagree (%) Undecided (%) Agree (%) Total (%)
Product quality 0.0 0.0 100.0 100.0 0.0 4.3 95.7 100.0
Brand creation 3.60 0.00 96.40 100.0 8.70 4.30 87.00 100.0
Low-cost production 28.6 17.9 53.6 100.0 17.4 26.1 56.5 100.0
Taking quick action 0.0 3.6 96.4 100.0 4.3 21.7 73.9 100.0
Use of advanced technology 0.0 10.7 89.3 100.0 8.7 21.7 69.6 100.0
Cooperation with competitors 21.4 10.7 67.9 100.0 26.1 8.7 65.2 100.0
Cooperation with suppliers 0.0 3.6 96.4 100.0 0.0 4.3 95.7 100.0
In the study, the product quality variable expressed the products produced in a certain quality and standard. All managers of competitive enterprises and 95.7% of non-competitive enterprises believed that product quality would provide a competitive advantage. Brand creation variable refers to marketing products under a particular brand name. As 96.4% of the managers of competitive enterprises argued that it was essential to create a brand in competition, 87.0% of the managers of non-competitive considered it was essential to create a brand in competition. The number of those who argued that creating a brand would not provide a competitive advantage or had no idea was higher in non-competitive enterprises. One of the most crucial competitiveness indicators in the literature is low-cost production compared to competitors. Those who believed that low-cost production was influential in the competition were more in the non-competitive enterprises. The variable of taking quick action can be defined as adapting quickly to market conditions, innovations, and developments in the sector. Those who thought taking quick action would provide a competitive advantage were competitive enterprises. In other words, it could be concluded that competitive enterprises had a more remarkable ability to adapt to innovations. The rate of those who believed that using advanced technology in production would provide a competitive advantage was higher in competitive enterprises. While enterprises in both groups were aware of the importance of cooperation with suppliers in competitiveness, the indicator of cooperation with competitors was less important than other variables.
Comparison of Competitiveness Indices by Competitiveness Groups
The competitiveness of enterprises in the research area was compared to the calculated competitiveness indices (Table 4). The average values of competitive enterprises’ Corporate Governance Index (p < 0.10), Economic Capital Index (p < 0.05), Human Capital Index (p < 0.01), and Innovativeness Index (p < 0.05) were higher than non-competitive enterprises. Although the enterprises’ average Cooperation Index values differed, this difference was not statistically significant (p > 0.05).Table 4 Comparison of competitiveness indices by competitiveness groups
Competitiveness indices Enterprises Count Mean Std. Error t Value p-value
Total Competitiveness Index (TCI) Competitive 28 11.35 0.44 3.904 0.000***
Non-competitive 23 8.87 0.45
Corporate Governance Index (CGI) Competitive 28 1.83 0.17 1.880 0.066*
Non-competitive 23 1.39 0.15
Economic Capital Index (ECI) Competitive 28 2.73 0.14 2.152 0.036**
Non-competitive 23 2.35 0.10
Human Capital Index (HCI) Competitive 28 3.39 0.16 3.164 0.003***
Non-competitive 23 2.73 0.11
Innovativeness Index (InovI) Competitive 28 1.79 0.15 2.385 0.021**
Non-competitive 23 1.19 0.21
Cooperation Index (CI) Competitive 28 1.60 0.16 1.650 0.105
Non-competitive 23 1.21 0.17
*, **, *** Significant at 10%, 5%, and 1%, respectively
From the findings, it could be concluded that enterprises that were institutionally managed, had good economic indicators, had substantial human capital, and were open to innovations were more competitive. After determining that the leading indices analyzed affect competitiveness, it became necessary to investigate which sub-indicators caused these differences. For this reason, the sub-indicators that made up each leading index were also analyzed and presented below.
The corporate governance index value of competitive and non-competitive enterprises was statistically different (Table 4). In order to determine from which sub-indicators this difference arose, the sub-indicators that make up the corporate governance index, the scores of the business area size, legal status, corporate governance, quality management processes, and operating capacity were compared to the competitiveness groups and presented in Table 5.Table 5 Comparison of the sub-indicators of the corporate governance index
Sub-indicators Enterprises Count Mean Std. Error t Value p-Value
Size of the business area score Competitive 28 0.16 0.05 1.596 0.118
Non-competitive 23 0.08 0.03
Operating capacity score Competitive 28 0.30 0.05 1.702 0.095*
Non-competitive 23 0.19 0.04
Corporate governance score Competitive 28 0.36 0.06 2.126 0.039**
Non-competitive 23 0.21 0.04
Quality management processes score Competitive 28 0.45 0.06 0.213 0.646
Non-competitive 23 0.43 0.07
Legal status score Competitive 28 0.57 0.06 0.323 0.218
Non-competitive 23 0.48 0.07
*, **, *** Significant at 10%, 5%, and 1%, respectively
A comparison of the corporate governance index sub-indicators according to the competitiveness groups determined that the operating capacity (p < 0.10) and the corporate management (p < 0.05) increased the enterprises’ competitiveness. The values of enterprises’ legal status, the size of the business area, and quality processes strategies carried out in the company were similar according to the competitiveness groups. As a result, it can be concluded that large-size and corporate enterprises were more fortunate in competitiveness.
The Economic Capital Index, which indicated the economic competitiveness of the enterprises, consisted of the share allocated to R&D, the capacity utilization rate score, the equity utilization rate score, the increase in market share score, and the revenue growth score in the last 3 years. The analysis results of the sub-indices that made up the economic capital index are given in Table 6. In the last 3 years, the increase in market share and revenue growth rates of competitive enterprises were higher than non-competitive (p < 0.05). On the other hand, the capacity utilization rate, the share allocated to R&D, and the equity utilization rates were not statistically different according to the competitiveness groups. The equity utilization ratio expresses the ratio of equity to total capital. The similarity of this ratio in both groups could be explained by the enterprises that did not have sufficient access to financial resources and avoided borrowing. It could be said that the indifference in capacity utilization rates was due to the instability in the hazelnut supply. In addition, the budget allocated to R&D in food companies in Turkey is generally low (Bakkaloğlu and Güneş 2018). Thus, the R&D budgets of the hazelnut enterprises were similar.Table 6 Comparison of the sub-indicators of the economic capital index
Sub-indicators Enterprises Count Mean Std. Error t Value p-Value
Capacity utilization rate score Competitive 28 0.70 0.05 0.002 0.998
Non-competitive 23 0.70 0.06
Allocated R&D share score Competitive 28 0.05 0.04 0.601 0.551
Non-competitive 23 0.03 0.02
Market share increase score Competitive 28 0.67 0.04 3.033 0.004***
Non-competitive 23 0.49 0.04
Revenue growth score Competitive 28 0.65 0.04 2.565 0.013**
Non-competitive 23 0.50 0.04
Equity utilization score Competitive 28 0.66 0.07 0.282 0.779
Non-competitive 23 0.63 0.07
*, **, *** Significant at 10%, 5%, and 1%, respectively
The sub-indicators that made up the competitiveness of the enterprises according to their human capital and the analysis result are in Table 7. The differences in the human capital index were due to the total number of employees, the number of permanent employees, the number of qualified personnel, and the support the personnel development. From the research findings, it could be concluded that enterprises that employed qualified personnel and adopted policies that support the development of their employees stood out in competitiveness.Table 7 Comparison of the sub-indicators of the human capital index
Sub-indicators Enterprises Count Mean Std. Error t Value p-Value
Total number of employees score Competitive 28 0.24 0.05 2.347 0.026**
Non-competitive 23 0.10 0.01
Permanent employee score Competitive 28 0.21 0.05 2.146 0.037**
Non-competitive 23 0.09 0.01
Personnel specialization score Competitive 28 1.93 0.05 0.695 0.491
Non-competitive 23 1.87 0.07
Number of qualified personnel scores Competitive 28 0.14 0.04 2.389 0.040**
Non-competitive 23 0.04 0.02
Personnel development support score Competitive 28 0.88 0.05 2.893 0.006*
Non-competitive 23 0.63 0.07
*, **, *** Significant at 10%, 5%, and 1%, respectively
In the context of the innovation competition, the differences in brand creation, differentiated product creation, differentiated management processes, e‑commerce applications, and information technology infrastructure variables were compared with the competitiveness group. (Table 8).Table 8 Comparison of innovativeness index sub-indicators
Sub-indicators Enterprises Count Mean Std. Error t Value p-Value
Differentiated product score Competitive 28 0.14 0.07 0.607 0.273
Non-competitive 23 0.09 0.06
Brand creation score Competitive 28 0.36 0.04 0.659 0.257
Non-competitive 23 0.32 0.04
Differentiated process management score Competitive 28 0.19 0.05 2.785 0.004*
Non-competitive 23 0.02 0.02
IT infrastructure score Competitive 28 0.62 0.06 1.715 0.094*
Non-competitive 23 0.46 0.07
E‑commerce score Competitive 28 0.48 0.06 1.796 0.079*
Non-competitive 23 0.30 0.08
*, **, *** Significant at 10%, 5%, and 1%, respectively
Differences in the enterprises’ innovativeness index were due to differentiated process management (p < 0.05), information technologies infrastructure (p < 0.10), and e‑commerce applications (p < 0.10). It can be concluded that establishing a robust information technologies infrastructure and putting differentiated process management and e‑commerce applications in production and marketing makes enterprises more competitive.
The cooperation index values did not differ according to the competitiveness groups, but sub-indicators as the collaboration and following the sectoral developments differed (Table 9). Collaborating with other enterprises (p < 0.05) and following the sectoral developments (p < 0.001) led to increasing enterprises’ competitiveness.Table 9 Comparison of cooperation index sub-indicators
Sub-indicators Enterprises Count Mean Std. Error t Value p-Value
Collaboration score Competitive 28 0.36 0.05 2.019 0.049**
Non-competitive 23 0.24 0.03
Clustering score Competitive 28 0.25 0.08 0.425 0.673
Non-competitive 23 0.30 0.10
Sectoral developments follow-up score Competitive 28 0.30 0.05 3.718 0.001***
Non-competitive 23 0.10 0.01
Technical consulting score Competitive 28 0.50 0.10 0.456 0.650
Non-competitive 23 0.43 0.11
Joint-production score Competitive 28 0.20 0.06 0.845 0.402
Non-competitive 23 0.13 0.05
*, **, *** Significant at 10%, 5%, and 1%, respectively
Discussion
The research determined that corporate governance values, economic capital values, human capital values, and innovativeness values were higher in competitive enterprises. Although studies analyzing enterprise competitiveness based on indices are limited, the division of labor (Siudek and Zawojska 2014), growth of business scale (Armağan 2004), diversification of business income (Savcı 2009), brand management (Altenburg and Meyer-Stamer 1999), product standardization (Lopez-Garcia et al. 2008; Beuchelt and Zeller 2013) and innovative capacity (Chikán 2008; Delfin-Ortega and Valencia 2015; Miniussi et al. 2015; Díaz-Chao et al. 2016) variables were reported as factors positively affecting competitiveness. Also, the research results supported the results of previous studies, in which the factors affecting competitiveness were examined separately, and the cooperation variable differed. This difference stemmed from the focus on a broad definition of the cooperation concept used in the study. In the study, the cooperation concept considered variables such as participating in clusters, receiving technical production support, and joint production. The cooperation index was calculated with the data belonging to these variables. The cooperation index value did not differ according to the groups, but the collaboration indicator, one of the sub-indicators, differed according to the groups. This finding confirmed the results of previous studies (Siudek and Zawojska 2014; Sarturi et al. 2016). The differentiation of the other sub-indicators of the cooperation index can be explained by the research region’s low level of cooperation culture. In Turkey, cooperation between agricultural enterprises and producer organizations, especially companies, is generally low. According to Aydoğan et al. (2016), horizontal cooperation among agricultural producer organizations was low, and their social networks were low-density. Therefore, it can be concluded that the cooperation concept among enterprises may differ according to country and may be affected by the general tendency towards cooperation. As a result, the orientation of hazelnut agribusiness enterprises in Turkey to vertical cooperation would positively affect their competitiveness.
Many studies on competitiveness stated that low-cost production affects competitiveness (Powers and Hahn 2004; González-Benito 2010; Soltanizadeh et al. 2016). However, the degree of influence of this judgment may vary according to the sectors. Taçoğlu et al. (2019), in their study examining the factors affecting the competitiveness of small and medium-sized enterprises (SMEs) in Turkey, stated that the impact of production costs on competitiveness had a medium level of importance. Similarly, the previous studies stated that companies that implemented mixed competition strategies were more competitive than companies that implemented only low-cost strategies (Acquaah and Yasai-Ardekani 2008; Pertusa-Ortega et al. 2009; Martinez-Simarro et al. 2015). In the study, the ratio of those who thought low-cost production provides a competitive advantage was higher in the non-competitive group. It can be explained that the competitive enterprises gave relatively more minor importance to low-cost production due to the hazelnut market structure. On shelled-hazelnut purchasing (raw material), the government determines the hazelnut minimum sales prices, and processed hazelnuts (final product) are generally exported at world prices. Therefore, other than operational improvements, cost-reducing factors are limited. As a result, focusing only on cost advantage may overlook other competitiveness parameters such as quality, brand, use of advanced technology, and cooperation. It can be concluded that non-competitive enterprises should focus on mixed competition strategies rather than entirely low-cost production.
Conclusion
The study intended to determine the factors affecting the competitiveness of hazelnut agribusiness enterprises. Inferences were obtained by comparing the findings with the literature. The research results indicated that corporate governance, economic capital, human capital, and innovativeness increased competitiveness. The hypothesis of that the non-financial indicators affect enterprise competitiveness at least as much as financial indicators were confirmed in the study. The research results could be interpreted that enterprise competitiveness is positively affected by corporate management, a robust financial structure, the investments made in the employees, and the ability to adapt quickly to innovations. The fact that all rules in business management are transparent and open to everyone, and that employees’ job descriptions are clear, increases employee productivity and competitiveness. In addition, the employment of qualified personnel and quality-enhancing activities for personnel development increase competitiveness. Investing in personnel development and employing qualified personnel would increase the competitiveness of hazelnut agribusinesses in Turkey.
Another critical research result was that non-competitive enterprises thought low-cost production increased competitiveness. On the other hand, competitive enterprises emphasize that product quality and standardization are as crucial as low-cost production in competition. As a result, it can be commented that non-competitive enterprises focus on low-cost production and overlook other internal and external factors necessary for competitiveness. Concentrating on product quality and standardization besides low-cost production strategies by non-competitive hazelnut enterprises may elevate them to the forefront of competition.
Another notable result of the research was the relationship between information technologies and e‑commerce with competitiveness. It was determined that competitive enterprises had a robust information technology infrastructure and market their products with e‑commerce. Considering the disruptions in the global agricultural supply chain due to the COVID-19 epidemic, it is likely that hazelnut agricultural enterprises would lose customers and their competitiveness would ultimately be negatively affected. Hazelnut agribusinesses in Turkey may become more competitive globally by developing robust IT infrastructure and e‑commerce applications in order to not be affected by supply chain disruptions, acquiring new customers, and establishing new partnerships. In addition, a robust IT infrastructure and marketing products with e‑commerce can increase resource utilization efficiency.
Funding
This work was supported by the Eastern Black Sea Project Regional Development Administration in the period 2016–2019.
Conflict of interest
M. Aydoğan declares that he has no competing interests.
Data, associated metadata, and calculation tools are available from corresponding author Mehmet AYDOĞAN ([email protected]).
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World J Urol
World J Urol
World Journal of Urology
0724-4983
1433-8726
Springer Berlin Heidelberg Berlin/Heidelberg
36484819
4234
10.1007/s00345-022-04234-6
Letter to the Editor
Commentary RE: Balasubramanian S, Ronstrom C, Shiang A, Vetter JM, Sheets J, Palka J, Figenshau RS, Kim EH. Feasibility and safety of same-day discharge following single-port robotic-assisted laparoscopic prostatectomy. World J Urol. 2022 Nov 2:1–7. doi: 10.1007/s00345-022-04204-y. Epub ahead of print. PMID: 36322183; PMCID: PMC9629187
http://orcid.org/0000-0003-2609-5629
Shahait Mohammed [email protected]
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Lee David I. [email protected]
3
1 Surgery Department, Clemenceau Medical Center, Dubai Healthcare City Phase 2, P.O. Box: 112693, Dubai, UAE
2 grid.428291.4 Urology Department, Cook County Health and Hospital System, Chicago, IL USA
3 grid.266093.8 0000 0001 0668 7243 Urology Department, University of California Irvine, Irvine, CA USA
9 12 2022
12
18 11 2022
21 11 2022
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
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pmcCommentary:
Amid the COVID-19 global pandemic, several institutions have developed and adopted same-day discharge (SDD) pathways to maintain proper patient flow, avoid treatment postponement, and mitigate hospital revenue loss from canceling surgeries [1]. The feasibility and safety of SDD Robotic-assisted laparoscopic radical prostatectomy (RALP) using multiport platforms has been corroborated by several studies [2]. Recently, Balasubramanian et al. reported on the safety and feasibility of SDD post Single port-RALP (SP-RALP). Of the 51 patients eligible for SDD after SP-RALP, 15 underwent SDD, and 36 opted for standard discharge process due to various reasons such as pain, fatigue, other medical reasons, and nonmedical reasons related to distance from hospital and being a second start surgery. [3] Encouragingly, the study demonstrated comparable outcomes in regard to complications, 90-day readmission and 90-day emergency room visits between the SDD and standard discharge process.
Future efforts should focus on optimizing the multifaceted aspects of SDD. This can be achieved by investing in the peri-operative educational material for the patient and caregiver, Outpatient surgery pre-admission tours, transportation planning and securing access to immediate telemedicine follow-up during the early postoperative period. Additionally, mobile applications may be helpful to monitor vital signs, encourage utilization of incentive spirometer and promote ambulation [4].
More subjective criteria to best select patients for SDD include 5-items modified frailty score to screen for comorbidities, assessing patient’s health literacy, availability of transportation, and the presence of a caregiver [5, 6].
Prior to even beginning an operation, early communication with the anesthesia team about the planned SDD is crucial to ensure selection of proper anesthetics agents associated with rapid recovery and less incidence of postoperative nausea and vomiting. Also, adoption of opioid-free pathways with preemptive use of NSAIDs and administering regional anesthesia such as Transversus Abdominis Plane (TAP) block have been found to decrease postoperative opioid requirement and postoperative nausea and vomiting [7]. Furthermore, the use of the Valveless-Trocar System for maintaining low pneumoperitoneum has been linked to lower postoperative pain and nausea episodes [8].
Finally, the discharge process could be optimized by assessing the readiness for discharge using a standardized assessment tool for the quality of the recovery and ensuring clear discharge instructions and the availability of educational materials to both the patient and the caregiver [9, 10].
It is clear that our practice patterns have been irrevocably changed during recent years. Adopting a multimodal approach to SDD provides a safe and effective pathway for care that benefits patients, physicians and healthcare systems alike.
Author contributions
MS contributed to project development and manuscript writing. RD contributed to manuscript writing. DL contributed to supervision and manuscript editing.
Data availability statement
There is no data related to this commentary.
Declarations
Conflict of interest
The author declares that they have no conflict of interest.
Research involving human participants and/or animals
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References
1. Abaza R Kogan P Martinez O Impact of the COVID-19 crisis on same-day discharge after robotic urologic surgery Urology 2021 149 40 45 10.1016/j.urology.2021.01.012 33482129
2. Abaza R Martinez O Ferroni MC Bsatee A Gerhard RS Same day discharge after robotic radical prostatectomy J Urol 2019 202 5 959 963 10.1097/JU.0000000000000353 31112102
3. Balasubramanian S Ronstrom C Shiang A Vetter JM Sheets J Palka J Figenshau RS Kim EH Feasibility and safety of same-day discharge following single-port robotic-assisted laparoscopic prostatectomy World J Urol 2022 10.1007/s00345-022-04204-y
4. Belarmino A Walsh R Alshak M Patel N Wu R Hu JC Feasibility of a mobile health application to monitor recovery and patient-reported outcomes after robot-assisted radical prostatectomy Eur Urol Oncol 2019 2 4 425 428 10.1016/j.euo.2018.08.016 31277778
5. Shahait M Labban M Dobbs RW Cheaib JG Lee DI Tamim H El-Hajj A A 5-item frailty index for predicting morbidity and mortality after radical prostatectomy: an analysis of the American college of surgeons national surgical quality improvement program database J Endourol 2021 35 4 483 489 10.1089/end.2020.0597 32935596
6. Jaensson M Dahlberg K Nilsson U Factors influencing day surgery patients’ quality of postoperative recovery and satisfaction with recovery: a narrative review Perioper Med 2019 8 3 10.1186/s13741-019-0115-1
7. Shahait M Yezdani M Katz B Lee A Yu SJ Lee DI Robot-assisted transversus abdominis plane block: description of the technique and comparative analysis J Endourol 2019 33 3 207 210 10.1089/end.2018.0828 30652509
8. Shahait M Cockrell R Yezdani M Improved Outcomes Utilizing a Valveless-Trocar System during Robot-assisted Radical Prostatectomy (RARP) JSLS. 2019 23 1 e2018.00085 10.4293/JSLS.2018.00085
9. Stark PA Myles PS Burke JA Development and psychometric evaluation of a postoperative quality of recovery score: the QoR-15 Anesthesiology 2013 118 6 1332 1340 10.1097/ALN.0b013e318289b84b 23411725
10. Williams BA Kentor ML The WAKE© score: patient-centered ambulatory anesthesia and fast-tracking outcomes criteria Int Anesthesiol Clin 2011 49 33 43 10.1097/AIA.0b013e3182183d05 21697668
| 36484819 | PMC9734962 | NO-CC CODE | 2022-12-14 23:28:31 | no | World J Urol. 2022 Dec 9;:1-2 | utf-8 | World J Urol | 2,022 | 10.1007/s00345-022-04234-6 | oa_other |
==== Front
Res Math Sci
Res Math Sci
Research in the Mathematical Sciences
2522-0144
2197-9847
Springer International Publishing Cham
366
10.1007/s40687-022-00366-8
Research
Modular knots, automorphic forms, and the Rademacher symbols for triangle groups
Matsusaka Toshiki [email protected]
1
http://orcid.org/0000-0003-3799-1074
Ueki Jun [email protected]
2
1 grid.177174.3 0000 0001 2242 4849 Faculty of Mathematics, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka-shi, 819-0395 Fukuoka Japan
2 grid.412314.1 0000 0001 2192 178X Department of Mathematics, Faculty of Science, Ochanomizu University, 2-1-1 Otsuka, Bunkyo-ku, 112-8610 Tokyo Japan
9 12 2022
2023
10 1 417 8 2022
2 11 2022
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
É. Ghys proved that the linking numbers of modular knots and the “missing” trefoil K2,3 in S3 coincide with the values of a highly ubiquitous function called the Rademacher symbol for SL2Z. In this article, we replace SL2Z=Γ2,3 by the triangle group Γp,q for any coprime pair (p, q) of integers with 2≤p<q. We invoke the theory of harmonic Maass forms for Γp,q to introduce the notion of the Rademacher symbol ψp,q, and provide several characterizations. Among other things, we generalize Ghys’s theorem for modular knots around any “missing” torus knot Kp,q in S3 and in a lens space.
Keywords
Modular knot
Triangle group
Rademacher symbol
Harmonic Maass form
Bounded Euler cocycle
Mathematics Subject Classification
Primary 11F37
57M10
Secondary 11F20
57K10
http://dx.doi.org/10.13039/501100001691 Japan Society for the Promotion of Science JP19K14538 JP20K14292 JP21K19141 issue-copyright-statement© Springer Nature Switzerland AG 2023
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pmcIntroduction
In a celebrated paper “Knots and dynamics” [16], Étienne Ghys proved a highly interesting result connecting two objects, one coming from low-dimensional topology and the other coming from automorphic forms for SL2Z. Namely, he proved that the linking number of a modular knot with the “missing” trefoil K2,3 coincides with the value of the Rademacher symbol.
Now let (p, q) be any coprime pair of integers with 2≤p<q and put r=pq-p-q. In this article, we invoke the theory of harmonic Maass forms to introduce the notion of the Rademacher symbol ψp,q for the triangle group Γp,q=Γ(p,q,∞)<SL2R. Then we extend Ghys’s theorem to modular knots around the general torus knot Kp,q in S3 and its image in the lens space L(r,p-1). We also provide several characterizations of the symbol and discuss its several variants.
In order to make a concrete description, let us briefly recollect the case for Γ2,3=SL2Z. The exterior of the trefoil K2,3 in S3 is homeomorphic to the set {(z,w)∈C2∣z3-w2≠0,|z|2+|w|2=1}, the unit tangent bundle T1PSL2Z\H of the modular orbifold, and the homogeneous space SL2Z\SL2R. The so-called geodesic flow on S3-K2,3≅SL2Z\SL2R is defined by φt:M↦M(et00e-t), t∈R and its closed orbits are called modular knots. Each modular knot corresponds to the conjugacy class of primitive hyperbolic elements of SL2Z; Let γ=(abcd)∈SL2Z with a+d>2 and c>0 so that we have Mγ-1γMγ=(ξγ00ξγ-1) with ξγ>1 for some Mγ∈SL2R. Then the corresponding modular knot Cγ is explicitly defined by the curveCγ(t)=Mγet00e-t,0≤t≤logξγ.
Note in addition that the unique cusp orbit of the unit tangent bundle T1PSL2Z\H is the missing trefoil K2,3 in S3.
The discriminant function Δ2,3(z)=q∏n=1∞(1-qn)24 with q=e2πiz and z∈H is a well-known modular form of weight 12. The Rademacher symbol ψ2,3:SL2Z→Z is defined as the function satisfying the transformation lawlogΔ2,3(γz)-logΔ2,3(z)=12log(cz+d)+2πiψ2,3(γ)
for every γ=(abcd)∈SL2Z and z∈H. Here, we take branches of the logarithms so that we have Imlog(cz+d)∈[-π,π) and logΔ2,3(z)=2πiz-24∑n=1∞∑d∣nd-1qn.
In [16, Sections 3.2–3.3], Ghys precisely asserts the following; let γ=(abcd)∈SL2Z be a primitive element with trγ>2 and c>0. Then the linking number is given bylk(Cγ,K2,3)=ψ2,3(γ).
The original Rademacher symbol Ψ2,3:SL2Z→Z is a class-invariant function initially introduced by Rademacher in his study of Dedekind sums ([33], see also [35]). This function is highly ubiquitous, as Atiyah [3, Theorem 5.60] proved the (partial) equivalences of seven very distinct definitions and Ghys went further. Ghys indeed worked in his 1st proof with the slightly modified function ψ2,3:SL2Z→Z, which is not a class-invariant function but coincides with the original symbol Ψ2,3 at every γ∈SL2Z with trγ>0. In this paper, we proactively take advantage of Ghys’s first treatment and afterward discuss the original symbol.
Ghys’s theorem for (2, 3) generalizes to any (p, q) in two directions; let SL2~R denote the universal covering group of SL2R and Γ~p,q<SL2~R the inverse image of Γp,q. Let Gr denote the kernel of a surjective homomorphism Γ~p,q↠Z/rZ, which is unique up to multiplication by units in Z/rZ. Then we have the following:[41] The spaces Γp,q\SL2R≅Γ~p,q\SL2~R are homeomorphic to the exterior of a knot K¯p,q in the lens space L(r,p-1), where K¯p,q is the image of a (p, q)-torus knot Kp,q via the Z/rZ-cover h:S3↠L(r,p-1).
[37] The space Gr\SL2~R is homeomorphic to the exterior of the torus knot Kp,q in S3.
Modular knots in L(r,p-1)-K¯p,q≅Γp,q\SL2R are defined in a similar manner to the case for SL2Z, so that each of them corresponds to a conjugacy class of primitive hyperbolic elements of Γp,q. In order to define the Rademacher symbol ψp,q for the triangle group Γp,q, we invoke the theory of harmonic Maass forms for Fuchsian groups; we construct a harmonic Maass form E2(p,q),∗(z) and a mock modular form E2(p,q)(z) of weight 2 to define a suitable holomorphic cusp form Δp,q(z) of weight 2pq, that is, Δp,q(z) has no poles and zeros on H and has a unique zero of order r at the cusp i∞. The Rademacher symbol ψp,q:Γp,q→Z is then defined as a unique function satisfying the transformation lawlogΔp,q(γz)-logΔp,q(z)=2pqlog(cz+d)+2πiψp,q(γ)
for every γ=(abcd)∈Γp,q and z∈H under suitable choices of branches of the logarithms. Among other things, we prove the following assertion in Sect. 4.
Theorem A
(I) Let the notation be as above. Let γ=(abcd)∈Γp,q be a primitive element with trγ>2 and c>0. Then the linking number of the modular knot Cγ and the image of the missing torus knot K¯p,q in L(r,p-1) is given by the Rademacher symbol ψp,q(γ) as:lk(Cγ,K¯p,q)=1rψp,q(γ)∈1rZ.
(II) In addition, let Cγ′ be a connected component of the preimage h-1(Cγ) via the Z/rZ-cover h:S3-Kp,q↠L(r,p-1)-K¯p,q. Then the linking number is given bylk(Cγ′,Kp,q)=1gcd(r,ψp,q(γ))ψp,q(γ)∈Z.
In the course of the proof, we obtain the following as well.
Theorem B
The Rademacher symbol ψp,q:Γp,q→Z has the following five (partial) characterizations. Definition (Sect. 2.4): logΔp,q(γz)-logΔp,q(z)=2pqlog(cz+d)+2πiψp,q(γ).
Cycle integral (Sect. 3.1): Let γ∈Γp,q be as in Theorem A. Then, the harmonic Maass form E2(p,q),∗(z) satisfies ∫S¯γE2(p,q),∗(z)dz=1rψp,q(γ).
2-cocycle (Sect. 3.2): Define a bounded 2-cocycle W:SL2R×SL2R→{-1,0,1} by W(γ1,γ2)=12πi(logj(γ1,γ2z)+logj(γ2,z)-logj(γ1γ2,z)) as in Definition 3.3. Then, ψp,q is a unique function satisfying 2pqW=-δ1ψp,q.
Additive character (Sect. 3.3): Let χp,q:Γ~p,q→Z denote the additive character defined by χp,q(S~p)=-q and χp,q(U~q)=-p. Then, ψp,q(γ)=χp,q(γ~) holds for any γ∈Γp,q and its standard lift γ~.
Linking number (Sect. 4.2): Theorem A (I).
The first two properties are described by means of modular forms, while the third and fourth are related to the universal covering group. The final property is of low-dimensional topology.
Although ψp,q is not a class-invariant function, it seems to be rather a natural object in some aspects and easier to treat, as (1), (3), (4) explain. Besides, we may modify ψp,q to define several class-invariant functions, namely the original Rademacher symbol Ψp,q, the homogeneous Rademacher symbol Ψp,qh, and the modified Rademacher symbol Ψp,qe with distinct advantages.
Our results mainly concern Ghys’s first proof and briefly a half of his second proof. Those are comparable with the results of Dehornoy–Pinsky [11, 14] on templates and codings related to Ghys’s third proof (cf. Sect. 5.1).
We remark that (mock) modular forms for triangle groups are quite less studied than those for congruence subgroups of SL2Z, although they would also be of arithmetic interest; for instance, Wolfart [46] showed that Fourier coefficients of holomorphic modular forms for the triangle group are mostly transcendental numbers (see also [12]). Our study would hopefully give a new cliff in this direction.
The rest of the article is organized as follows. In Sect. 2, we recollect harmonic Maass forms for the triangle groups to construct the harmonic Maass form E2(p,q),∗(z) and the holomorphic cusp form Δp,q(z). In Sect. 3, we define the Rademacher symbol ψp,q for Γp,q and prove the equivalence of (1)–(4) in Theorem B. In addition, we discuss several variants of ψp,q. In Sect. 4, based on Tsanov’s group theoretic study, we establish Theorem A on the linking numbers of modular knots in L(r,p-1) and S3, completing a generalization of Ghys’s first proof. Furthermore, we define knots corresponding to elliptic and parabolic elements to extend the theorem and give a characterization of the modified symbol Ψp,qe via an Euler cocycle, to justify Ghys’s outlined second proof. Finally, in Sect. 5, we give remarks on templates and codings and on the Sarnak–Mozzochi distribution theorem for Γp,q, and attach further problems.
Harmonic Maass forms for triangle groups
In this section, we introduce harmonic Maass forms for a triangle group Γp,q. In particular, we construct two important functions E2(p,q),∗(z) and Δp,q(z). The function E2(p,q),∗(z) is a unique harmonic Maass form of weight 2 on Γp,q with polynomial growth at cusps, and the function Δp,q(z) is a unique holomorphic cusp form of weight 2pq with no poles and zeros on H.
Triangle groups
Let (p, q) be a coprime pair of integers with 2≤p<q and put r=pq-p-q as before. In this subsection, we define the triangle group Γp,q as a subset of SL2R and recall several properties.
Recall that PSL2R=SL2R/{±I} acts on the upper half-plane H={z∈C∣Im(z)>0} via the Möbius transformation γz=az+bcz+d for γ=(abcd) and z∈H, so that PSL2R=Isom+H holds. Triangle groups are often defined as a subgroup of PSL2R generated by reflections on the sides of a triangle in H. However, we here define them as subgroups of SL2R to make our argument simple. PutTp,q=12cosπp+cosπq01,Sp=0-112cosπp,Uq=2cosπq-110,
so that we have Spp=Uqq=-I and Tp,q=-UqSp.
Definition 2.1
The (p, q) -triangle group Γp,q=Γ(p,q,∞) is a subgroup of SL2R generated by elements Sp and Uq.
This group Γp,q is a Fuchsian group of the first kind. We especially have Γ2,3=SL2Z. There is an isomorphism to the amalgamated productΓp,q≅⟨Sp⟩∗⟨-I⟩⟨Uq⟩≅Z/2pZ∗Z/2ZZ/2qZ,
which is obtained by applying [39, Theorem 6] to a geodesic segment T={eπiθ∣1/q≤θ≤1-1/p}⊂H.
We can visualize the group Γp,q by its fundamental domain in H. Let Δ=Δ(p,q,∞) denote the triangle with interior angles π/p,π/q,0 defined byΔ(p,q,∞)={z∈H∣-cosπp≤Re(z)≤cosπq,|z|≥1}.
In addition, let Δ′=Δ′(p,q,∞) denote the reflection of Δ(p,q,∞) with respect to the geodesic {eiθ∣0<θ<π}, that is, we putΔ′(p,q,∞)={z∈H∣0110z¯=1z¯∈Δ(p,q,∞)}.
Then, the set Dp,q=Δ(p,q,∞)∪Δ′(p,q,∞) is a fundamental domain of Γp,q (Fig. 1). Fig. 1 Fundamental domain Dp,q=Δ∪Δ′
The vertices a=eπi1-1/p,b=eπi/q, and i∞ of Δ(p,q,∞) are fixed points of Sp,Uq, and Tp,q, respectively. The first two vertices a and b are called elliptic points of Γp,q, and i∞ is called a cusp of Γp,q. The stabilizer subgroups of these vertices are given by (Γp,q)a=⟨Sp⟩, (Γp,q)b=⟨Uq⟩, and (Γp,q)∞=±⟨Tp,q⟩, respectively. The two sides of the quadrangle Dp,q joined at each elliptic point are Γp,q-equivalent. Hence, the Riemann surface Γp,q\H has one cusp, two elliptic points, and genus 0. By the Gauss–Bonnet theorem, or by a direct calculation, one may verify thatvol(Γp,q\H)=∫Dp,qdxdyy2=2πrpq.
In general, an element γ∈Γp,q is said to be elliptic if |trγ|<2, parabolic if |trγ|=2, and hyperbolic if |trγ|>2. In each case, the conjugacy class of γ corresponds to elliptic points, the cusp, and closed geodesics on Γp,q\H, respectively (see also Sect. 3.1). An element γ∈Γp,q is said to be primitive if γ=±σn for σ∈Γp,q and n∈Z implies that n=±1.
We make use of the following lemma in later calculations.
Lemma 2.2
For each integer n∈Z, let Cn(x)∈Z[x] denote the Chebyshev polynomial of the second kind characterized by Cn(cost)=sinnt/sint, t∈R. Then, C0(x)=0, C1(x)=1, and Cn+1(x)=2xCn(x)-Cn-1(x) hold. The generators Sp and Uq satisfySpn=-Cn-1(cosπp)-Cn(cosπp)Cn(cosπp)Cn+1(cosπp),Uqn=Cn+1(cosπq)-Cn(cosπq)Cn(cosπq)-Cn-1(cosπq).
Modular forms for Γp,q
In this subsection, we recollect the notions of meromorphic modular forms and harmonic Maass forms for triangle groups together with some properties.
Meromorphic modular forms
For γ=(abcd)∈SL2R and a variable z∈H, the automorphic factor is defined by j(γ,z)=cz+d, so that the cocycle condition j(γ1γ2,z)=j(γ1,γ2z)j(γ2,z) for any γ1,γ2∈SL2R holds. For the pair of a function f:H→C and an element γ∈SL2R, the slash operator of weight k∈Z is defined by (f|kγ)(z)=j(γ,z)-kf(γz).
Definition 2.3
A meromorphic function f:H→C∪{∞} is called a meromorphic modular form of weight k∈Z for Γp,q if the following conditions hold. f|kγ=f for every γ∈Γp,q.
Put λ=2(cosπp+cosπq) and qλ=e2πiz/λ. Then, f(z) has a Fourier expansion of the form: f(z)=∑n=n′∞anqλn,an∈C
for some n′∈Z.
If in addition f is holomorphic on H and an=0 holds for all n<0 (resp. n≤0), then f is called a holomorphic modular form (resp. cusp form) of weight k for Γp,q. The space of all holomorphic modular forms of weight k for Γp,q is denoted by Mk(Γp,q).
Cauchy’s residue theorem yields the following valence formula in a similar manner to [20, Proposition 3.8]:
Proposition 2.4
(The valence formula) Let f be a nonzero meromorphic modular form of weight k for Γp,q. Let vP(f) denote the order of zero of f at each z=P on Γp,q\H and put v∞(f)=min{n∈Z∣an≠0}. Then,v∞(f)+1pva(f)+1qvb(f)+∑P∈Γp,q\HP≠a,bvP(f)=r2pqk
holds, where a=eπi(1-1/p) and b=eπi/q are the fixed points of Sp and Uq, respectively.
We use the following lemma later.
Lemma 2.5
M2(Γp,q)=0.
Proof
Suppose 0≠f∈M2(Γp,q) and put N=v∞(f)+∑PvP(f), A=va(f), B=vb(f). Then, we have N,A,B∈Z≥0. In addition, Proposition 2.4 yields N+Ap+Bq=rpq=pq-p-qpq. Since 0<pq-p-qpq<1, we have N=0, hence p(B+1)+q(A+1)-pq=0. Since p and q are coprime, we may write A+1=pl for some l∈Z>0. Now we have 0=p(B+1)+pq(l-1)>0, hence contradiction. Therefore, we have f=0. □
Harmonic Maass forms
The notion of harmonic Maass forms is a generalization of holomorphic modular forms. It was introduced by Bruinier–Funke [4] to study geometric theta lifts and played a crucial role in the study of Ramanujan’s mock theta functions. It is defined by using ξ-differential operators and the hyperbolic Laplace operators.
Definition 2.6
Let k∈Z. For a real analytic function f:H→C, the ξ-differential operator ξk of weight k is defined byξkf=2iyk∂∂z¯f¯,
where ∂/∂z¯ is the Wirtinger derivative defined by∂∂z¯=12(∂∂x+i∂∂y).
The hyperbolic Laplace operator Δk of weight k is defined byΔk=-ξ2-k∘ξk=-y2(∂2∂x2+∂2∂y2)+iky(∂∂x+i∂∂y).
A direct calculation yields thatξk(f|kγ)=(ξkf)|2-kγ
holds for any γ∈Γp,q. Hence, if f satisfies the modular transformation law f|kγ=f of weight k for every γ∈Γp,q, then so does ξkf of weight 2-k. We also note that if f is a holomorphic function, then ξkf=0 holds.
Definition 2.7
A real analytic function f:H→C is called a harmonic Maass form of weight k∈Z for Γp,q if the following conditions hold. f|kγ=f for every γ∈Γp,q.
Δkf(z)=0.
There exists α>0 such that f(x+iy)=O(yα) as y→∞ uniformly in x∈R.
The space of all harmonic Maass forms of weight k for Γp,q is denoted by Hk(Γp,q).
We remark that in a basic textbook of harmonic Maass forms [5, Definition 4.2], for instance, the condition (iii) is replaced by a slightly different condition, namely, (iii’) there exists a polynomial Pf(z)∈C[qλ-1] such that f(z)-Pf(z)=O(e-εy) as y→∞ for some ε>0. Whichever condition is chosen, we have Mk(Γp,q)⊂Hk(Γp,q) and the ξ-differential operator of weight k induces a linear map ξk:Hk(Γp,q)→M2-k(Γp,q). A virtue of our choice (iii) is that the function E2(p,q),∗(z) in Sect. 2.3 will be a harmonic Maass form.
Let f∈Hk(Γp,q) and suppose k≠1. Then, a standard argument yields a Fourier expansionf(x+iy)=∑n≥0c+(n)qλn+c-(0)y1-k+∑n<0c-(n)y-k/2W-k2,k-12(4π|n|yλ)e2πinx/λ,
where c+(n) with n≥0 and c-(n) with n≤0 are complex constants and Wμ,ν(y) denotes the so-called W-Whittakerfunction (cf. [30, Chapter VII]). If instead k=1, then y1-k is replaced by logy.
The holomorphic part f+(z)=∑n≥0c+(n)qλn of each f∈Hk(Γp,q) is called a mock modular form of weight k for Γp,q.
On the other hand, we remark that the Fourier coefficients c-(n) of the remaining non-holomorphic part are closely related to a function ξkf∈M2-k(Γp,q) called the shadow of the mock modular form f+. In fact, we haveξkf(z)=(1-k)c-(0)¯-∑n>0c-(-n)¯(4πnλ)2-k2qλn.
The harmonic Maass form E2(p,q),∗(z) of weight 2
In this subsection, we construct a harmonic Maass form E2(p,q),∗(z) and a mock modular form E2(p,q)(z) of weight 2 for Γp,q with explicit descriptions. For this purpose, we first recollect the notion of the Eisenstein series E2k(p,q)(z,s) of even weight for Γp,q, that yields most basic examples of harmonic Maass forms. We refer to Iwaniec’s book [19] and Goldstein’s paper [17] for some properties, but we rather follow a standard recipe of mock modular forms.
The Eisenstein series
Recall that the triangle group Γp,q<SL2R is a Fuchsian group with finite covolume vol(Γp,q\H)=2πr/pq and the stabilizer subgroup of the unique cusp i∞ is given by (Γp,q)i∞=±⟨Tp,q⟩.
Let λ=2(cosπp+cosπq) as before and put σ=(λ1/200λ-1/2)∈SL2R, so that σ is a scaling matrix of the cusp i∞, that is, σi∞=i∞ and σ-1Tp,qσ=(1101) hold.
Definition 2.8
Let k be an integer. For z∈H and s∈C with Re(s)>1, the real analytic Eisenstein series of weight 2k for Γp,q is defined byE2k(p,q)(z,s)=∑γ∈(Γp,q)∞\Γp,qIm(z)s-k|2k(σ-1γ)=1λs∑γ∈(Γp,q)∞\Γp,qIm(γz)s-kj(γ,z)2k.
For each s with Re(s)>1, as a function in z, this series converges absolutely and uniformly on compact subsets of H. By the definition, (E2k(p,q)|2kγ)(z,s)=j(γ,z)-2kE2k(p,q)(γz,s)=E2k(p,q)(z,s) holds for any γ∈Γp,q. By the commutativity ξk(f|kγ)=(ξkf)|2-kγ and the equation ξ2kys-k=(s¯-k)ys¯-(1-k), for each s with Re(s)>1, we haveξ2kE2k(p,q)(z,s)=(s¯-k)E2-2k(p,q)(z,s¯)
andΔ2kE2k(p,q)(z,s)=(s-k)(1-k-s)E2k(p,q)(z,s).
The limit formula
The following is classically known.
Proposition 2.9
([19, Proposition 6.13]) The Eisenstein series E0(p,q)(z,s) of weight 0 has a meromorphic continuation around s=1 with a simple pole there with residueRess=1E0(p,q)(z,s)=1vol(Γp,q\H)=pq2πr.
The classical Kronecker limit formula describes the constant term of the Eisenstein series E0(2,3)(z,s) at s=1. Goldstein established a generalization of the limit formula for general Fuchsian groups [17], which yields the following:
Proposition 2.10
([17, (21)]) The constant term of the Laurent expansion of E0(p,q)(z,s) in s at s=1, which is also called the limit function, is given byLp,q(z)=lims→1(E0(p,q)(z,s)-1vol(Γp,q\H)1s-1)=Cp,q-logyvol(Γp,q\H)+yλ+∑n=1∞cp,q(n)qλn+∑n=1∞cp,q(n)¯qλ¯n,
where Cp,q and cp,q(n) are the complex numbers described in terms of a certain Dirichlet series.
A harmonic Maass form of weight 2
Let us define a function by E2(p,q),∗(z)=ξ0Lp,q(z). Then, we have the following.
Proposition 2.11
The function E2(p,q),∗(z) is a harmonic Maass form of weight 2 for Γp,q. The space H2(Γp,q) is a 1-dimensional C-vector space spanned by E2(p,q),∗(z).
Proof
By a direct calculation, we haveE2(p,q),∗(z)=-1vol(Γp,q\H)1y+1λ+∑n=1∞dp,q(n)qλn,
where dp,q(n)=(-4πn/λ)cp,q(n). Since Lp,q(z) is a Γp,q-invariant function, E2(p,q),∗(z) satisfies the modular transformation law of weight 2. The conditions (ii) and (iii) in Definition 2.7 are easily verified. Hence, we have E2(p,q),∗(z)∈H2(Γp,q).
Let f∈H2(Γp,q). Since M0(Γp,q)=C by Proposition 2.4, the image ξ2f is a constant function. Hence, there exists a constant c∈C such that ξ2(f(z)-cE2(p,q),∗(z))=0, that is, f(z)-cE2(p,q),∗(z)∈M2(Γp,q). Since M2(Γp,q)=0 by Lemma 2.5, we obtain f(z)-cE2(p,q),∗(z)=0, completing the proof. □
A mock modular form of weight 2
Let E2(p,q)(z) denote the holomorphic part of the harmonic Maass form E2(p,q),∗(z), so that E2(p,q)(z) is a mock modular form of weight 2 and we haveE2(p,q)(z)=E2(p,q),∗(z)+1vol(Γp,q\H)1Im(z)=1λ+∑n=1∞dp,q(n)qλn.
The modular transformation law of weight 2 for E2(p,q),∗(z) yields the modular gap of the function E2(p,q)(z) described as follows:
Lemma 2.12
For any γ=(abcd)∈Γp,q, we have(cz+d)-2E2(p,q)(γz)-E2(p,q)(z)=1vol(Γp,q\H)(cz+d)-21Im(γz)-1Im(z)=pqrcπi(cz+d).
This gap will play a crucial role in defining a holomorphic cusp form Δp,q(z) in the next subsection.
The cusp form Δp,q(z) of weight 2pq
In this subsection, we construct a holomorphic cusp form Δp,q(z) of weight 2pq for Γp,q with no poles and zeros on H. In the course of the argument, we introduce a primitive function Fp,q(z), a 1-cocycle function Rp,q(γ,z), and the Rademacher symbol ψp,q:Γp,q→Z as well.
A 1-cocycle function
Let Fp,q(z) denote the primitive function of 2πirE2(p,q)(z) defined byFp,q(z)=2πirzλ+rλ∑n=1∞dp,q(n)nqλn=2πirzλ-4πr∑n=1∞cp,q(n)qλn,
where cp,q(n) are those in Proposition 2.10. This Fp,q is the regularized primitive function in the sense that the leading coefficient of the Fourier expansion of Δp,q(z)=expFp,q(z) is 1.
In addition, let Rp,q:Γp,q×H→C denote the weight 0 modular gap function of Fp,q(z) defined byRp,q(γ,z)=Fp,q(γz)-Fp,q(z),
Then, we have Rp,q(-γ,z)=Rp,q(γ,z) and the 1-cocycle relationRp,q(γ1γ2,z)=Rp,q(γ1,γ2z)+Rp,q(γ2,z).
The Rademacher symbol ψp,q(γ)
By Lemma 2.12, we have ddz(Rp,q(γ,z)-2pqlogj(γ,z))=0. Hence, there exists a function ψp,q:Γp,q→C satisfyingRp,q(γ,z)=2pqlogj(γ,z)+2πiψp,q(γ),
where we assume that Imlogj(γ,z)∈[-π,π). We call this ψp,q the Rademacher symbol for Γp,q. Let us verify that ψp,q(γ)∈Z.
Lemma 2.13
For the elements Tp,q,Sp,Uq of Γp,q (cf. Definition 2.1), we have ψp,q(Tp,q)=r, ψp,q(Sp)=-q, and ψp,q(Uq)=-p.
Proof
Let us first show that ψp,q(Uq)=-p. By the fact that Uqq=-I, for any z∈H, we have0=Rp,q(-I,z)=Rp,q(Uqq,z)=∑k=0q-1Rp,q(Uq,Uqkz)=2pq∑k=0q-1logj(Uq,Uqkz)+2πiqψp,q(Uq).
Since ∑k=0q-1log|j(Uq,Uqkz)|=log|j(-I,z)|=0, we see thatψp,q(Uq)=-pπ∑k=0q-1argj(Uq,Uqkz)=-pπ∑k=0q-1argUqkz,
where argz∈[-π,π). Here, the left-hand side is independent of the choice of z, and the right-hand side is continuous in z∈H. By taking the limit z→i∞ and applying Lemma 2.2, we obtain ψp,q(Uq)=-p. In a similar way, we may obtain ψp,q(Sp)=-q.
Finally, by2πiψp,q(Tp,q)=Rp,q(Tp,q,z)=Fp,q(z+λ)-Fp,q(z)=2πirλ((z+λ)-z)=2πir,
we obtain ψp,q(Tp,q)=r. □
Proposition 2.14
For any γ∈Γp,q, the value ψp,q(γ) is an integer.
Proof
We prove the assertion by induction on the word length of γ∈Γp,q with respect to the generators Sp and Uq. We proved in Lemma 2.13 that ψp,q(Sp),ψp,q(Uq)∈Z. Now suppose that ψp,q(γ)∈Z. If w∈{Sp,Uq}, then we see that2πiψp,q(wγ)=Rp,q(wγ,z)-2pqlogj(wγ,z)=Rp,q(w,γz)+Rp,q(γ,z)-2pqlogj(w,γz)j(γ,z).
By logj(w,γz)+logj(γ,z)-logj(w,γz)j(γ,z)∈2πiZ, we obtain ψp,q(wγ)∈Z. □
A cusp form of weight 2pq
Finally, we define a holomorphic function on H by Δp,q(z)=expFp,q(z). By Proposition 2.14, for any γ∈Γp,q, we haveΔp,q(γz)=Δp,q(z)expRp,q(γ,z)=j(γ,z)2pqΔp,q(z),
that is, Δp,q|2pqγ=Δp,q holds. By the definition, Δp,q(z) is holomorphic, and has no zeros and poles on the upper-half plane H. Moreover, by Proposition 2.4, the function vanishes at the cusp i∞. Therefore, by the construction, we have the following.
Proposition 2.15
The function Δp,q(z) is a cusp form of weight 2pq with a unique zero of order r at the cusp i∞, having a Fourier expansion of the form Δp,q(z)=qλr+O(qλr+1). In addition, we have
ddzlogΔp,q(z)=Fp,q′(z)=2πirE2(p,q)(z).
Remark 2.16
For the function logηΓp,q,i(z/λ) introduced in [17, Theorem 3.1], we have Fp,q(z)=4pqlogηΓp,q,i(z/λ) and Δp,q(z)=ηΓp,q,i(z/λ)4pq. However, our ψp,q(γ) and the generalized Dedekind sum SΓp,q,i(γ) in [17] are slightly different, due to their choices of branches of the logarithm.
In terms of our cusp form Δp,q(z), the Kronecker limit type formula in Proposition 2.10 is paraphrased as follows:Lp,q(z)=lims→1(E0(p,q)(z,s)-1vol(Γp,q\H)1s-1)=-1vol(Γp,q\H)log(y|Δp,q(z)|1/pq)+Cp,q.
Remark 2.17
The limit function Lp,q(z) is an example of polyharmonic Maass forms, which were recently introduced by Lagarias–Rhoades in [21] as a generalization of harmonic Maass forms. A real analytic function f:H→C is called a polyharmonic Maass form of weight k∈Z and depth r∈Z for Γp,q if it satisfies the conditions (i) and (iii) in Definition 2.7 and (ii)’ (Δk)rf(z)=0. In fact, the function Lp,q(z) satisfies the above three conditions with k=0 and r=2. For further studies on polyharmonic Maass forms, we refer to [22, 24] written by the first author.
The Rademacher symbols
In the previous section, we introduced the Rademacher symbol ψp,q:Γp,q→Z by using a certain 1-cocycle function Rp,q(γ,z). Let us briefly recall the definition. The harmonic Maass form E2(p,q),∗(z) yields the mock modular form E2(p,q)(z). We defined the regularized primitive function Fp,q(z) of 2πirE2(p,q)(z) and the cusp form Δp,q(z) so that Δp,q(z)=expFp,q(z)=qλr+O(qλr+1) hold for λ=2(cosπp+cosπq). We further put logΔp,q(z)=Fp,q(z). Our symbol ψp,q may be defined as follows, assuming that Imlogz∈[-π,π).
Definition 3.1
The Rademacher symbol ψp,q:Γp,q→Z is a unique function satisfyingRp,q(γ,z)=logΔp,q(γz)-logΔp,q(z)=2pqlogj(γ,z)+2πiψp,q(γ).
Since the classical case ψ2,3 admits many characterizations as Atiyah and Ghys proved, we may expect that ψp,q also has many. In this section, we establish characterization theorems of ψp,q from three aspects; cycle integrals of E2(p,q),∗(z), a 2-cocycle W generating the bounded cohomology group Hb2(SL2R;R), and an additive character χp,q:Γ~p,q→Z. In addition, we introduce several variants Φp,q, Ψp,q, and Ψp,qh in a view of the classical cases. We obtain several lemmas for our main theorem on the linking number through this section.
Cycle integrals
The group Γp,q acts on R∪{i∞}=∂H via the Möbius transformation. Let γ∈Γp,q be a hyperbolic element, that is, |trγ|>2 holds. Then, there are exactly two fixed points wγ,wγ′ on R⊂R∪{i∞}. Assume wγ>wγ′ and put Mγ=1wγ-wγ′(wγwγ′11)∈SL2R. Then, γ is diagonalized asMγ-1γMγ=j(γ,wγ)00j(γ,wγ′)=ξγ00ξγ-1.
Now suppose that γ=(abcd)∈Γp,q is an element with a+d>2 and c>0, so that ξγ>1 holds. Let Sγ denote the geodesic in H connecting two fixed points wγ and wγ′. Then, the action of γ preserves the set Sγ and sends every point on Sγ toward wγ. The image S¯γ of Sγ on the Riemann surface (orbifold) Γp,q\H is a closed geodesic. If in addition γ is primitive, then the arc on Sγ connecting any z0∈Sγ and γz0 is a lift of the simple closed geodesic S¯γ.
Theorem 3.2
Let γ=(abcd)∈Γp,q be a primitive element with a+d>2 and c>0. Then, the cycle integral is given by the Rademacher symbol as:∫S¯γE2(p,q),∗(z)dz=1rψp,q(γ).
Proof
For any z0∈Sγ, the cycle integral coincides with the path integral along Sγ on H as∫S¯γE2(p,q),∗(z)dz=∫z0γz0E2(p,q),∗(z)dz.
We let z0=Mγi. Recall that the harmonic Maass form E2(p,q),∗(z) may be written the sum of holomorphic and non-holomorphic parts as:E2(p,q),∗(z)=E2(p,q)(z)-1vol(Γp,q\H)1Im(z).
The integration of the holomorphic part is given by∫z0γz0E2(p,q)(z)dz=12πir[Fp,q(z)]z0γz0=12πirRp,q(γ,z0).
As for the integration of the non-holomorphic part, recall that vol(Γp,q\H)=2πrpq. In addition, by changing variables via z=Mγiy, we obtain∫z0γz0dzIm(z)=∫1ξγ21Im(Mγiy)idyj(Mγ,iy)2=∫1ξγ21-iy1+iyidyy=∫1ξγ2(iy+21+iy)dy=2ilogξγj(Mγ,i)j(Mγ,iξγ2)=2ilogj(Mγ,i)j(Mγξγ00ξγ-1,i)=2ilogj(Mγ,i)j(γMγ,i)=-2ilogj(γ,Mγi),
where we assume that Imlogz∈[-π,π) as before. By summation, we have∫z0γz0E2(p,q),∗(z)dz=12πir(Rp,q(γ,z0)-2pqlogj(γ,z0))=1rψp,q(γ),
which finishes the proof. □
The 2-cocycle W
In this subsection, we give an alternative definition of the Rademacher symbol ψp,q without using automorphic forms. We introduce a bounded 2-cocycle W following Asai [1] and prove that ψp,q is a unique function satisfying 2pqW=-δ1ψp,q.
A 2-cocycle and Asai’s sign function
Here, we introduce a 2-cocycle W corresponding to the universal covering group SL2~R together with an explicit description using Asai’s sign function.
Definition 3.3
We define a 2-cocycle W:SL2R×SL2R→Z byW(γ1,γ2)=12πi(logj(γ1,γ2z)+logj(γ2,z)-logj(γ1γ2,z)),
assuming argj(γ,z)=Imlogj(γ,z)∈[-π,π).
This is equivalent to say that we have j(γ1,γ2z)j(γ2,z)=j(γ1γ2,z)e2πiW(γ1,γ2) in the universal covering group C×~ of the multiplicative group C×=C-{0}. Since the right-hand side of the definition is continuous in z, the value of W is independent of z. We may easily verify the 2-cocycle conditionW(γ1γ2,γ3)+W(γ1,γ2)=W(γ1,γ2γ3)+W(γ2,γ3).
The universal cover SL2~R→SL2R as manifolds is a group homomorphism as well. The group SL2~R is called the universal covering group of SL2R. Note in addition that each central extension of SL2R by Z corresponds to a 2-cocycle SL2R×SL2R→Z and each isomorphism class of central extensions corresponds to a 2nd cohomology class in H2(SL2R;Z) (cf. [7, Chapter IV]). Now we have the following.
Proposition 3.4
As a group, the universal covering group SL2~R of SL2R is a central extension of SL2R by Z corresponding to the 2-cocycle W. In other words, when we identify SL2~R with SL2R×Z as sets, we have(γ1,n1)·(γ2,n2)=(γ1γ2,n1+n2+W(γ1,γ2))
for every (γ1,n1),(γ2,n2)∈SL2~R.
By virtue of the convention argj(γ,z)=Imlogj(γ,z)∈[-π,π), we have W(γ1,γ2)∈{-1,0,1}. Asai introduced the following sign function to explicitly express the values of W.
Definition 3.5
For any γ=(abcd)∈SL2R, we define its sign bysgn(γ)=sgncifc≠0,sgna=sgndifc=0=1if0≤argj(γ,z)<π,-1if-π≤argj(γ,z)<0.
Proposition 3.6
([1]) The values of W(γ1,γ2) are given by the following table. sgn(γ1) sgn(γ2) sgn(γ1γ2) W(γ1,γ2)
1 1 -1 1
-1 -1 1 -1
Otherwise 0
Remark 3.7
Asai showed that there is no function V:SL2R→R satisfyingW(γ1,γ2)=-(δ1V)(γ1,γ2)=V(γ1γ2)-V(γ1)-V(γ2),
that is, the cohomology class [W] in H2(SL2R;R) is non-trivial [1, Theorem 1].
Note that W is a bounded 2-cocycle by |W(γ1,γ2)|≤1. The bounded cohomology group Hb2(SL2R;R)≅R naturally injects into H2(SL2R;R); hence, the class of W in Hb2(SL2R;R) is a generator (cf. [6, 15, 28]).
A 2-coboundary of Γp,q
We next calculate the cohomology of Γp,q and establish the relationship between the 2-cocycle W on Γp,q and the Rademacher symbol ψp,q.
Lemma 3.8
We have H1(Γp,q;Z)=H1(Γp,q;C)={0} and H2(Γp,q;Z)≅Z/2pqZ.
Proof
Since the triangle group Γp,q is generated by torsion elements Sp and Uq, a group homomorphism f:Γp,q→C is trivial. Hence, H1(Γp,q;Z)=H1(Γp,q;C)={0}.
The second assertion follows from the factsHi(Z/nZ;Z)≅Zifi=0,Z/nZifiis even withi>0,0ifiis odd,
Γp,q≅Z/2pZ∗Z/2ZZ/2qZ, and the Mayer–Vietoris sequence for group cohomology.
□
Since H2(Γp,q;Z)≅Z/2pqZ, we have 2pq[W]=0 in H2(Γp,q;Z). Hence, there exists a function f:Γp,q→Z satisfying the coboundary condition2pqW(γ1,γ2)=-(δ1f)(γ1,γ2)=f(γ1γ2)-f(γ1)-f(γ2)
for every γ1,γ2∈Γp,q. Such f is unique. Indeed, if there are two functions f1,f2:Γp,q→C satisfying the same coboundary condition, then the difference f1-f2 is a homomorphism. Hence, by H1(Γp,q;C)={0}, we have f1-f2=0. We further have the following.
Theorem 3.9
The Rademacher symbol ψp,q:Γp,q→Z is a unique function satisfying2pqW|Γp,q=-δ1ψp,q.
Proof
It suffices to verify that the equalityψp,q(γ1γ2)-ψp,q(γ1)-ψp,q(γ2)=2pqW(γ1,γ2)
holds for every γ1,γ2∈Γp,q.
By the definition of ψp,q, the left-hand side equals12πi(Rp,q(γ1γ2,z)-2pqlogj(γ1γ2,z)-Rp,q(γ1,γ2z)+2pqlogj(γ1,γ2z)-Rp,q(γ2,z)+2pqlogj(γ2,z)).
The Rp,q-terms cancel out by the 1-cocycle relation and the remaining equals 2pqW(γ1,γ2). □
The additive character χp,q:Γ~p,q→Z
In this subsection, we provide another characterization of the Rademacher symbol ψp,q by using an additive character χp,q:Γ~p,q→Z.
As before, we assume that SL2~R=SL2R×Z as a set. Let P:SL2~R→SL2R;(γ,n)↦γ denote the universal covering map and put Γ~p,q=P-1(Γp,q), so that we haveΓ~p,q={(γ,n)∈SL2~R∣γ∈Γp,q,n∈Z}.
For each γ∈Γp,q, we define the standard lift by γ~=(γ,0)∈Γ~p,q.
Lemma 3.10
The lifts of Sp,Uq,Tp,q∈Γp,q satisfyS~pp=(-I,1)=U~qq,T~p,q=-I~U~qS~p.
The group Γ~p,q is generated by S~p and U~q.
Proof
The equalities immediately follow from the group operation of SL2~R with use of W and Lemma 2.2. Since we have (I,1)=S~p2p=U~q2q, the elements S~p and U~q generate Γ~p,q. □
Let χ:Γ~p,q→Z be an additive character, that is, a group homomorphism to the additive group Z. Such χ is determined by the values χ(S~p)=s and χ(U~q)=u. The relation S~pp=(-I,1)=U~qq imposes the condition χ(-I,1)=ps=qu on the pair (s, u). Since p and q are coprime, we have s=mq,u=mp for some m∈Z. In addition, since (-I,1)2=(I,1), we have χ(I,1)=2mpq.
Define a function V:Γp,q→Z by putting V(γ)=χ(γ~). Then, we have χ(γ,n)=χ(γ~·(I,1)n)=V(γ)+2mnpq for any (γ,n)∈Γ~p,q. In addition, for any γ1,γ2∈Γp,q, by the relation γ~1·γ~2=(γ1γ2,W(γ1,γ2)), we haveV(γ1γ2)=V(γ1)+V(γ2)-2mpqW(γ1,γ2).
If m=-1, then Theorem 3.9 yields V=ψp,q. Consequently, we obtain the following.
Theorem 3.11
The additive character χp,q:Γ~p,q→Z determined by χp,q(S~p)=-q and χp,q(U~q)=-p satisfiesψp,q(γ)=χp,q(γ,n)+2npq
for every γ∈Γp,q and n∈Z.
Remark 3.12
Theorem 3.11 is a generalization of Asai’s result in his unpublished lecture note [2]. His function Φ satisfies Φ(γ)=ψ2,3(γ)+3sgn(γ) for any γ∈SL2Z.
For the convenience of later use, let us calculate the values of the Rademacher symbol at several elements. By Theorem 3.11, we easily seeψp,q(-I)=χpq(-I,1)+2pq=-pq+2pq=pq,ψp,q(Tp,q)=χp,q(-I~U~qS~p)=pq-p-q=r.
The latter agrees with the previous result in Lemma 2.13. In addition, we have the following.
Lemma 3.13
For any γ=(abcd)∈Γp,q, we haveψp,q(-γ)=ψp,q(γ)+pqsgn(γ),ψp,q(γ-1)=-ψp,q(γ)+2pqifc=0,d<0,-ψp,q(γ)if otherwise.
Proof
By Theorem 3.9, we haveψp,q(-γ)=ψp,q(γ)+ψp,q(-I)+2pqW(-I,γ).
Recall ψp,q(-I)=pq. Since W(-I,γ)=0 if sgn(γ)=+1 and W(-I,γ)=-1 if sgn(γ)=-1, we have ψp,q(-I)+2pqW(-I,γ)=pqsgn(γ).
In general, the inverse of any (γ,n)∈SL2~R is given by(γ,n)-1=(γ-1,-n-W(γ,γ-1))=(γ-1,-n+1)ifc=0,d<0,(γ-1,-n)if otherwise.
Hence, we haveψp,q(γ-1)=χp,q(γ-1,0)=χp,q((γ,1)-1)=-χp,q(γ,1)=-ψp,q(γ)+2pq
if c=0,d<0, andψp,q(γ-1)=χp,q((γ,0)-1)=-ψp,q(γ)
if otherwise. □
We also use the following lemma later.
Lemma 3.14
Let (x,y)∈Z2 be a pair satisfying px+qy=1, |x|<q, |y|<p, xy<0 and put γ=Uq-xSp-y=(abcd)∈Γp,q. Then, we haveγ=T2,3=(1101) if (p,q)=(2,3),
trγ>2 and c>0 if (p,q)≠(2,3).
In both cases, we have ψp,q(γ)=1.
Proof
If (p,q)=(2,3), then we have γ=U3-2S2=U3S2-1=(1101).
If (p,q)≠(2,3), then by Lemma 2.2, we haveγ=1sinπp1sinπq-sinπ(x-1)qsinπxq-sinπxqsinπ(x+1)qsinπ(y+1)psinπyp-sinπyp-sinπ(y-1)p.
By the condition xy<0, we have c>0. In addition, we havetrγ=-2sinπp·sinπqsinπxqcosπqsinπypcosπp-sinπqcosπxqsinπpcosπyp+sinπxqsinπyp=2sinπxqsinπypsinπpsinπq×cosπpcosπq+1+cosπxqcosπyp>2.
For any m, n with 0<|m|<p and 0<|n|<q, we have sgn(Spm)=sgn(m) and sgn(Uqn)=sgn(n). Hence, we have ψp,q(Uq-x)=-xψp,q(Uq)=px and ψp,q(Sp-y)=-yψp,q(Sp)=qy. By xy<0, we obtainψp,q(γ)=ψp,q(Uq-x)+ψp,q(Sp-y)+2pqW(Uq-x,Sp-y)=px+qy=1.
□
Class-invariant functions
In this subsection, we recall several variants of the classical Rademacher symbol and generalize them for any Γp,q. We modify the Rademacher symbol ψp,q to obtain a class-invariant function, namely the original Rademacher symbol Ψp,q. In addition, we define the Dedekind symbol Φp,q and the homogeneous Rademacher symbol Ψp,qh and attach remarks.
The classical cases
Let us recollect two classical variant Φ2,3 and Ψ2,3 of the Rademacher symbol ψ2,3. The Dedekind symbol Φ2,3:SL2Z→Z introduced by Dedekind in 1892 [10] is defined as a unique function satisfyinglogΔ2,3γz-logΔ2,3(z)=12log(cz+disgnc)+2πiΦ2,3(γ)ifc≠0,2πiΦ2,3(γ)ifc=0,
for every γ=(abcd)∈SL2Z and z∈H, assuming Imlogz∈(-π,π). Here, sgnc∈{-1,0,1} denotes the usual sign function. For each a∈Z and c∈Z>0, the Dedekind sum is defined bys(a,c)=∑k=1c-1((kc))((kac)),
where we put ((x))=x-⌊x⌋-1/2 if x∉Z and ((x))=0 if x∈Z. The following formula is due to Dedekind:Φ2,3(abcd)=a+dc-12sgnc·s(a,|c|)ifc≠0,bdifc=0.
This symbol Φ2,3 is not a class-invariant function. In 1956 [33], Rademacher introduced a class-invariant function by modifying the Dedekind symbol, namely he defined the original Rademacher symbol Ψ2,3:SL2Z→Z by puttingΨ2,3(γ)=Φ2,3(γ)-3sgn(c(a+d)).
This symbol Ψ2,3 satisfiesΨ2,3(γ)=Ψ2,3(-γ)=-Ψ2,3(γ-1)=Ψ2,3(g-1γg)
for any γ,g∈SL2Z. In addition, if trγ>0, thenlogΔ2,3(γz)-logΔ2,3(z)=12logj(γ,z)+2πiΨ2,3(γ)
holds, that is, we have Ψ2,3(γ)=ψ2,3(γ).
We remark that there are many more variants in the literature with confusions. The clarification between Φ2,3 and Ψ2,3 is due to [13].
The original symbol Ψp,q
Let us generalize the original symbol for any Γp,q.
Definition 3.15
We define the original Rademacher symbol for Γp,q by
where sgn(γ)∈{±1} denotes Asai’s sign function and sgntrγ∈{-1,0,1} the usual sign function.
If we put (p,q)=(2,3), then we obtain the classical symbol Ψ2,3 due to Rademacher. If trγ>0, then holds. The following assertion is proved by Lemmas 3.17–3.20.
Proposition 3.16
For any γ,g∈Γp,q,Ψp,q(γ)=Ψp,q(-γ)=-Ψp,q(γ-1)=Ψp,q(g-1γg)
holds. In addition, if |trγ|≥2, then Ψp,q(γn)=nΨp,q(γ) holds for any n∈Z.
Lemma 3.17
For any γ∈Γp,q, we have Ψp,q(-γ)=Ψp,q(γ), that is, Ψp,q induces a function on Γp,q/{±I}.
Proof
By Lemma 3.13, we obtainΨp,q(-γ)=ψp,q(-γ)+pq2sgn(-γ)(1-sgntr(-γ))=ψp,q(γ)+pqsgn(γ)-pq2sgn(γ)(1+sgntrγ)=Ψp,q(γ).
□
Lemma 3.18
For any γ∈Γp,q, we have Ψp,q(γ-1)=-Ψp,q(γ).
Proof
If γ=(abcd)∈Γp,q satisfies c=0 and d<0, then by Lemma 3.13,Ψp,q(γ-1)=ψp,q(γ-1)-pq=-ψp,q(γ)+pq=-Ψp,q(γ).
Other cases are obtained in as similar manner. □
Lemma 3.19
For γ∈Γp,q with |trγ|≥2, we have Ψp,q(γn)=nΨp,q(γ).
Proof
Since -Ψp,q(γ-1)=Ψp,q(-γ)=Ψp,q(γ) holds by the above lemmas, we may assume sgn(γ)>0, trγ≥2, and n>0 without loss of generality. Put t=trγ≥2. Then, we have γn=an(t)γ-an-1(t)I, where a0(t)=0,a1(t)=1, and an(t)=tan-1(t)-an-2(t). This implies that sgn(γn)>0 and tr(γn)>0 for any n>0. Hence, we obtainΨp,q(γn)=ψp,q(γn)=χp,q(γn,0)=χp,q((γ,0)n)=nψp,q(γ)=nΨp,q(γ),
which conclude the proof. □
Lemma 3.20
The function Ψp,q(γ) is a class-invariant function, that is, for any g∈Γp,q, we have Ψp,q(g-1γg)=Ψp,q(γ).
Proof
We may assume sgn(γ)>0 and trγ≥0 without loss of generality. It suffices to show the equation for generators g=Tp,q,Sp. By the definitions, we haveΨp,q(g-1γg)=Ψp,q(g-1)+Ψp,q(γ)+Ψp,q(g)+2pq(W(g-1,γg)+W(γ,g))+pq2(sgn(g-1γg)(1-sgntr(g-1γg))-sgn(g-1)(1-sgntr(g-1))-1+sgntrγ-sgn(g)(1-sgntrg)).
By andW(γ1,γ2)=14(sgn(γ1)+sgn(γ2)-sgn(γ1γ2)-sgn(γ1)sgn(γ2)sgn(γ1γ2)),
we obtainΨp,q(g-1γg)=Ψp,q(γ)+pq2(-sgn(g-1)sgn(γg)sgn(g-1γg)-sgn(g)sgn(γg)-sgn(g-1γg)sgntrγ+sgn(g-1)sgntr(g-1)+sgntrγ+sgn(g)sgntrg).
If g=Tp,q, then we have sgn(γg)=sgn(g-1γg)=sgn(γ)=1, that is, Ψp,q(g-1γg)=Ψp,q(γ).
If g=Sp, then we haveΨp,q(g-1γg)=Ψp,q(γ)+pq2(sgn(γg)-sgntrγ)(sgn(g-1γg)-1).
Assume γ=(abcd) with a+d≥0 and sgn(γ)>0. Then, we see thatγSp=b-a+2bcosπpd-c+2dcosπp,Sp-1γSp=d+2bcosπp∗-ba-2bcosπp.
If a+d=0, then -bc=a2+1>0. Thus we have c>0 and -b>0, that is, sgn(g-1γg)=1.
If a+d>0, then it suffices to show that (sgn(γSp)-1)(sgn(Sp-1γSp)-1)=0. If d>0, then we have sgn(γSp)=1.
If d=0, then sgn(γSp)=sgn(-c)<0. In addition, by det(γ)=-bc=1, we have b<0. Hence, we obtain sgn(Sp-1γSp)=1.
If d<0, then sgn(γSp)=-1. In this case, we have a>0,c>0, and b<0. Hence, we have sgn(Sp-1γSp)=1.
In conclusion, we obtain Ψp,q(g-1γg)=Ψp,q(γ) for all cases. □
Other variants Φp,q and Ψp,qh
Here, we discuss two more variants Φp,q and Ψp,qh.
Definition 3.21
We define the Dedekind symbol Φp,q:Γp,q→12Z byΦp,q(γ)=Ψp,q(γ)+pq2sgn(c(a+d)).
This symbol Φp,q is a unique function satisfyingΦp,q(γ1γ2)-Φp,q(γ1)-Φp,q(γ2)=-pq2sgn(c1c2c12)
for every γi=(∗∗ci∗)∈Γp,q with γ1γ2=(∗∗c12∗), hence a generalization of [35, (62)]. The values at generators are given byΦp,q(Tp,q)=r=pq-p-q,Φp,q(Sp)=q(p-2)2,Φp,q(Uq)=p(q-2)2.
Definition 3.22
We define the homogeneous Rademacher symbol Ψp,qh:Γp,q→Z by the homogenization of ψp,q, that is, we putΨp,qh(γ)=limn→∞ψp,q(γn)n=limn→∞Φp,q(γn)n
for every γ∈Γp,q.
In comparison with Proposition 3.16, for any γ,g∈Γp,q and n∈Z, we haveΨp,qh(γ)=Ψp,qh(-γ)=-Ψp,qh(γ-1)=Ψp,qh(g-1γg)
and Ψp,qh(γn)=nΨp,qh(γ).
If |trγ|≥2, then Ψp,qh(γ)=Ψp,q(γ) holds. If instead |trγ|<2, then we have Ψp,qh(γ)=0, while the original symbol satisfiesΨp,q(Sp)=0ifp=2,-qifp>2,Ψp,q(Uq)=-p.
Note that we have trSp=2cosπp and trUq=2cosπq.
If trγ≥2, then Ψp,qh(γ)=ψp,q(γ) holds.
Remark 3.23
Recently, in a view of the Manin–Drinfeld theorem, Burrin [8] introduced certain functions for a general Fuchsian group Γ by using a recipe close to ours. Her functions may be seen as generalizations of our Φp,q and Ψp,q, for which our Theorem 3.2 persist. She also proved that if Γ is a non-cocompact Fuchsian group with genus zero, then the values of the functions are in Q. Our result further claims for Γp,q that the values are in Z.
Modular knots around the torus knot
In this section, we establish our main result, that is, the coincidence of the values of the Rademacher symbol and the linking number between modular knots and the (p, q)-torus knot.
The torus knot groups
Here, we prepare group theoretic lemmas, which enable us to clearly recognize the natural Z/rZ-cover h:S3-Kp,q↠L(r,p-1)-K¯p,q, as well as to make an explicit argument.
Recall that the universal covering group SL2~R is the central extension of SL2R by Z corresponding to the 2-cocycle W, that is, SL2~R is SL2R×Z as a set and endowed with the multiplication(γ1,n1)·(γ2,n2)=(γ1γ2,n1+n2+W(γ1,γ2)).
Let P:SL2~R→SL2R;(γ,n)↦γ denote the natural projection and put Γ~p,q=P-1(Γp,q), so that we have Γ~p,q={(γ,n)∣γ∈Γp,q}<SL2~R. For each γ∈SL2R, define the standard lift by γ~=(γ,0)∈SL2~R. Then Γ~p,q is generated by S~p and U~q, for which S~pp=U~qq=(-I,1) holds.
Recall r=pq-p-q. We here explicitly define a discrete subgroup Gr<SL2~R byGr=⟨S~pr,U~qr⟩=⟨S~pr,U~qr∣(S~pr)p=(U~qr)q=(-I,1)r⟩.
The following lemmas are due to Tsanov [41]. Since the original assertions are for PSL2R, we partially attach proofs for later use. For each group G, let Z(G) denote the center, [G, G] the commutator subgroup, and Gab the abelianization.
Lemma 4.1
Z(Gr) is generated by (-I,1)r=(-I,r+12).
P(Gr)=Γp,q.
Proof
(1) An isomorphism Γ~p,q→≅Gr is defined by S~p↦S~pr and U~q↦U~qr. Since Z(Γ~p,q) is generated by S~pp=U~qq=(-I,1), Z(Gr) is generated by (-I,1)r=(-I,r+12).
(2) Since r is an odd number coprime to both p and q, there exist some s,t∈Z satisfying rs≡1(mod2p) and rt≡1(mod2q), hence Sprs=Sp and Uqrt=Uq. Thus, we have Sp,Uq∈P(Gr). □
Lemma 4.2
[Γ~p,q,Γ~p,q]=[Gr,Gr].
Γ~p,qab≅Grab≅Z.
Γ~p,q/Gr≅Γ~p,qab/Grab≅Z/rZ.
As mentioned in Sect. 1, we have the following.
Proposition 4.3
([37, 41]) (1) The spaces Γp,q\SL2R≅Γ~p,q\SL2~R are homeomorphic to the exterior of a knot K¯p,q in the lens space L(r,p-1), where K¯p,q is the image of a (p, q)-torus knot via the Z/rZ-cover S3↠L(r,p-1).
(2) The space Gr\SL2~R is homeomorphic to the exterior of the torus knot Kp,q in S3.
The second assertion was established by Raymond–Vasquez by using the theory of Seifert fibrations in [37]. Tsanov gave explicit homeomorphisms for both cases in [41]. We remark that Tsanov discussed the lens space L(r,p(q1-p1+pp1)) for a pair (p1,q1)∈Z2 with pp1+qq1=1, which is homeomorphic to L(r,p-1) by Brody’s theorem.
Since the fundamental groups are given by π1(Γp,q\SL2R)≅π1(Γ~p,q\SL2~R)≅Γ~p,q, by the Hurewicz theorem and the lemmas above, we obtain the following.
Lemma 4.4
The groups Gr≅π1(S3-Kp,q) are the kernels of any surjective homomorphism Γ~p,q≅π1(L(r,p-1)-K¯p,q)↠Z/rZ. We may identify the corresponding Z/rZ-cover h:S3-Kp,q→L(r,p-1)-K¯p,q with the natural surjection Gr\SL2~R↠Γ~p,q\SL2~R.
The groups Grab≅H1(S3-Kp,q;Z)≅Z may be seen as the subgroups of Γ~p,qab≅H1(L(r,p-1)-K¯p,q;Z)≅1rZ of index r in a natural way.
The following diagram visualizes the situation. Here, for G=Γ~p,q and Gr, G′ denotes the commutator subgroup of G and Z′(G) denotes the subgroup of Z(G)≅Z with index 2. The Z-covers of L(r,p-1)-K¯p,q and S3-Kp,q are denoted by L∞=X∞.
Modular knots in the lens space
In this subsection, we introduce the notion of modular knots for Γp,q around the (p, q)-torus knot in the lens space L(r,p-1), recall the notions of the linking number and the winding number, and establish the former half of our main result on the linking number.
Modular knots
Let us first define a modular knot in the lens space.
Definition 4.5
(1) Let γ=(abcd)∈Γp,q be a primitive element with a+d>2 and c>0, so that γ is diagonalized by the scaling matrix Mγ and its larger eigenvalue satisfies ξγ>1. Define an oriented simple closed curve Cγ(t) in Γp,q\SL2R byCγ(t)=Mγet00e-t,(0≤t≤logξγ).
We call the image Cγ in Γp,q\SL2R≅L(r,p-1)-K¯p,q with the induced orientation the modular knot associated with γ.
(2) Let γ∈Γp,q be any hyperbolic element, so that we have γ=±γ0n for some primitive element γ0=(abcd)∈Γp,q with a+d>2 and c>0, and n∈Z. We define the modular knot associated with γ by Cγ=nCγ0 with multiplicity.
Linking numbers
A general theory of the linking number in a rational homology 3-sphere can be found in [40, Section 77]. Since H1(L(r,p-1);Z)≅Z/rZ, the linking number in L(r,p-1) takes value in 1rZ. Via a standard homeomorphism Γp,q\SL2R→≅T1(Γp,q\H) to the unit tangent bundle, the knot K¯p,q may be seen as the cusp orbit with a natural orientation. Let μ be a standard meridian of K¯p,q and consider the isomorphism H1(L(r,p-1)-K¯p,q;Z)→≅1rZ sending [μ] to 1. A standard meridian μ may be explicitly given by the curve c(t) in the proof of Proposition 4.9 with 0≤t≤λ.
Definition 4.6
The linking number lk(K,K¯p,q) of an oriented knot K in L(r,p-1)-K¯p,q and the knot K¯p,q is defined as the image of [K] via the isomorphism H1(L(r,p-1)-K¯p,q;Z)→≅1rZ.
This definition naturally extends to a knot with multiplicity, that is, a formal sum of knots with coefficients in Z.
Winding numbers
In order to compute the linking number, let us recall the notion of the winding number. Let the unit circle T={|z|=1}⊂C be endowed with the counter-clockwise orientation and let H1(C×;Z)→≅Z denote the isomorphism sending [T] to 1.
Definition 4.7
For an oriented closed curve C in C×, the winding number ind(C,0)∈Z is defined to be the image of [C] via the isomorphism H1(C×;Z)→≅Z. Equivalently, it is defined by the cycle integral asind(C,0)=12πi∫Cdzz.
The equivalence of these two definitions is verified by Cauchy’s integral theorem.
We define a lift Δ~p,q:SL2R→C× of the cusp form Δp,q(z) byΔ~p,q(g)=j(g,i)-2pqΔp,q(gi).
Since Δp,q(z) has no zeros on H and satisfies Δ~p,q(γg)=Δ~p,q(g) for any γ∈Γp,q, we obtain the induced continuous function Δ~p,q:Γp,q\SL2R→C×.
Proposition 4.8
For a modular knot Cγ defined in Definition 4.5 (1), we haveind(Δ~p,q(Cγ),0)=ψp,q(γ).
Proof
Recall ddzlogΔp,q(z)=2πirE2(p,q)(z) and put z0=Mγi. Then, by Theorem 3.2, we obtainind(Δ~p,q(Cγ),0)=12πi∫Δ~p,q(Cγ)dzz=12πi∫0logξγdΔ~p,q(Cγ(t))Δ~p,q(Cγ(t))=r∫z0γz0E2(p,q),∗(z)dz=ψp,q(γ).
□
Proposition 4.9
The function Δ~p,q induces an isomorphism H1(Γp,q\SL2R;Z)→≅H1(C×;Z).
Proof
The function Δ~p,q induces a group homomorphism (Δ~p,q)∗:H1(Γp,q\SL2R;Z)→H1(C×;Z). Since both homology groups are isomorphic to Z, it suffices to show the surjectivity.
If (p,q)=(2,3), take a sufficiently large y∈R>0. Define a closed curve in SL2Z\SL2R byCy(t)=1t01y1/200y-1/2,(0≤t≤1)
and that in C× byΔ~2,3(Cy(t))=y6Δ2,3(t+iy),(0≤t≤1).
Since Δ2,3(z)=q1+O(q12), we have ind(Δ~2,3(Cy(t)),0)=1. Thus, the map (Δ~2,3)∗ is surjective.
If (p,q)≠(2,3), take the hyperbolic element γ∈Γp,q defined in Lemma 3.14. By Proposition 4.8, we have ind(Δ~p,q(Cγ),0)=ψp,q(γ)=1, which concludes that (Δ~p,q)∗ is surjective. □
Theorem in L(r,p-1)
By Proposition 4.9, for any oriented knot K in L(r,p-1)-K¯p,q≅Γp,q\SL2R, we havelk(K,K¯p,q)=1rind(Δ~p,q(K),0).
Together with the results in Sect. 3.4, we conclude the following.
Theorem 4.10
(1) Let γ=(abcd)∈Γp,q be a primitive element with a+d>2 and c>0. Then, the linking number of the modular knot Cγ and the image K¯p,q of the (p, q)-torus knot in the lens space L(r,p-1) is given bylk(Cγ,K¯p,q)=1rψp,q(γ).
(2) Let γ∈Γp,q be any hyperbolic element. Then, the linking number is given bylk(Cγ,K¯p,q)=1rΨp,q(γ)=1rΨp,qh(γ).
Modular knots in the 3-sphere
In this subsection, we investigate modular knots around the (p, q)-torus knot Kp,q in S3 to establish the latter half of our main theorem on the linking number.
Linking numbers in Z/rZ-cover
Definition 4.11
For an oriented knot K in S3-Kp,q, the linking number lk(K,Kp,q)∈Z is defined by the image of [K] via the isomorphism H1(S3-Kp,q;Z)→≅Z sending a standard meridian μ of Kp,q to 1. This definition naturally extends to knots with multiplicity.
Recall that the restriction of the Z/rZ-cover h:S3↠L(r,p-1) to the exterior of Kp,q may be identified with the natural surjection Gr\SL2~R↠Γ~p,q\SL2~R. Let K be an oriented knot in L(r,p-1)-K¯p,q and K′ a connected component of h-1(K). The following two lemmas are consequences of a standard argument of the covering theory (e.g., the lifting property of continuous maps, [18, Propositions 1.33, 1.34]).
Lemma 4.12
The covering degree of the restriction h:K′→K coincides with the order of [K] in H1(L(r,p-1);Z)≅Z/rZ. The covering degree of h:Kp,q→K¯p,q is equal to r.
Proof
Note that the decomposition group of K′ is a subgroup of the Deck transformation group Deck(h)≅H1(L(r,p-1);Z)≅Z/rZ generated by [K]. The assertion follows from the Hilbert ramification theory for Z/rZ-cover [42, Section 2]. □
Lemma 4.13
If [K] in H1(L(r,p-1);Z)≅Z/rZ is of order m, then we havelk(K′,Kp,q)=mlk(K,K¯p,q).
Proof
We have a connected surface Σ in L(r,p-1) with ∂Σ=mK and a connected component Σ′ of the preimage h-1(Σ) with ∂Σ′=K′. Let ι denote the intersection number. Then, by Lemma 4.12, we have lk(K′,Kp,q)=ι(Σ′,Kp,q)=ι(Σ,K¯p,q)=lk(mK,K¯p,q)=mlk(K,K¯p,q). □
Modular knots in Z/rZ-cover
We define a modular knot in S3 as a connected component of the inverse image of that in L(r,p-1).
Definition 4.14
(1) Let γ=(abcd)∈Γp,q be a primitive element with a+d>2 and c>0. Consider the modular knot Cγ in L(r,p-1)-K¯p,q associated to γ and let mγ denote the order of [Cγ] in H1(L(r,p-1);Z)≅Z/rZ, so that the inverse image h-1(Cγ) consists of exactly r/mγ-connected components. We call each connected component Cγ′ of h-1(Cγ) a modular knot associated with γ∈Γp,q in S3-Kp,q.
(2) Let γ∈Γp,q be any hyperbolic element, so that we have γ=±γ0ν for some primitive γ0=(abcd)∈Γp,q with a+d>2 and c>0 and ν∈Z. Let Cγ0′ be a modular knot in S3-Kp,q associated to γ0. We call the knot Cγ′=νCγ0′ with multiplicity a modular knot associated with γ∈Γp,q in S3-Kp,q.
The following lemma plays a key role in explicitly finding the integer mγ.
Lemma 4.15
For each γ∈Γp,q, we have (γ,n)∈Gr if and only if2pqn≡ψp,q(γ)modr
holds. Such n’s define an element in Z/rZ.
If nγ∈Z with (γ,nγ)∈Gr, then gcd(r,nγ)=gcd(r,ψp,q(γ)) holds.
Proof
By Lemma 4.1 (2), there exists some n∈Z satisfying (γ,n)∈Gr. In addition, by Lemma 4.1 (1), we have Z′(Gr)=P-1(I)∩Gr=⟨(I,r)⟩=⟨(-I,1)2r⟩, which is the subgroup of Z(Gr)≅Z with index 2. Now suppose (γ,n),(γ,n′)∈Gr. Then, we have (γ,n)(γ,n′)-1∈Gr, which implies n-n′≡0modr. Thus, the set of n∈Z with (γ,n)∈Gr defines a class nγ∈Z/rZ.
Now take nγ∈Z with (γ,nγ)∈Gr for each γ∈Γp,q, so that we have a map n∙:Γp,q→Z. Note that gcd(2pq,r)=1. Since Γp,q is generated by Sp and Uq of orders 2p and 2q, a group homomorphism Γp,q→Z/rZ is trivial, that is, we have H1(Γp,q;Z/rZ)=0. Since (γ1,nγ1)·(γ2,nγ2)=(γ1γ2,nγ1+nγ2+W(γ1,γ2)) in Gr, we havenγ1γ2≡nγ1+nγ2+W(γ1,γ2)modr.
On the other hand, by Theorem 3.9, we haveψp,q(γ1γ2)=ψp,q(γ1)+ψp,q(γ2)+2pqW(γ1,γ2).
Hence, we have a group homomorphism ψp,q(γ)-2pqnγmodr:Γp,q→Z/rZ, which must be zero by H1(Γp,q;Z/rZ)=0. Thus, we obtain 2pqnγ≡ψp,q(γ)modr.
Again by gcd(2pq,r)=1, we obtain gcd(r,nγ)=gcd(r,ψp,q(γ)). □
Now let γ=(abcd)∈Γp,q be a primitive element with a+d>2 and c>0 and take nγ∈Z with (γ,nγ)∈Gr.
Lemma 4.16
For each l∈Z/rZ, we may define a simple closed curve in Gr\SL2~R byCγ,l(t)=(Mγet00e-t,l),(0≤t≤rgcd(r,ψp,q(γ))logξγ).
Proof
Note that we havesgn(γ)>0,sgn(Mγet00e-t)>0,sgn(Mγet+logξγ00e-t-logξγ)>0.
Then, a direct calculation yieldsCγ,l(t+logξγ)=(Mγξγ00ξγ-1et00e-t,l)=(γ,0)(Mγet00e-t,l)=(γ,nγ)(I,-nγ)(Mγet00e-t,l)=(I,-nγ)Cγ,l(t).
Hence, for any k∈Z, we haveCγ,l(t+klogξγ)=(I,-knγ)Cγ,l(t).
Since Z′(Gr)=P-1(I)∩Gr=⟨(I,r)⟩, we have (I,-knγ)∈Gr if and only if -knγ=0 in Z/rZ holds. The least positive k with -knγ=0 is given by k=r/gcd(r,nγ)=r/gcd(r,ψp,q(γ)). Hence, we obtain the assertion. □
The image Cγ,l in Gr\SL2~R≅S3-Kp,q with the induced orientation is a modular knot associated with γ.
Proposition 4.17
For l,l′∈Z/rZ, we have Cγ,l=Cγ,l′ if and only if l≡l′modgcd(r,ψp,q(γ)) holds. The set of modular knots in S3-Kp,q associated with γ coincides with {Cγ,l∣l∈Z/rZ}={Cγ,l∣l=0,1,⋯,gcd(r,ψp,q(γ))-1}.
Proof
Suppose Cγ,l=Cγ,l′. Then, there exists some t∈R>0 satisfying Cγ,l(0)=Cγ,l′(t) in Gr\SL2~R, that is, there exists some (σ,s)∈Gr satisfying(σ,s)(Mγ,l)=(Mγet00e-t,l′).
Since σMγ=Mγ(et00e-t), there exists some k∈Z>0 satisfying σ=γk, t=klogξγ, and s≡knγ mod r. Since(γkMγ,knγ+l)=(Mγξγk00ξγ-k,l′),
we have knγ+l≡l′ mod r. Hence, we have l≡l′ mod gcd(r,nγ)=gcd(r,ψp,q(γ)).
Suppose instead that l≡l′ mod gcd(r,nγ). Then, we have l′=l+kgcd(r,nγ) and gcd(r,nγ)=ar+bnγ for some k,a,b∈Z. ByCγ,l′(t)=(Mγet00e-t,l+akr+bknγ)=(I,bknγ)(Mγet00e-t,l)=Cγ,l(t-bklogξγ),
we obtain Cγ,l=Cγ,l′.
Comparing the covering degree, we obtain the second assertion. □
Proposition 4.18
The element [Cγ]∈H1(L(r,p-1);Z)≅Z/rZ is of ordermγ=rgcd(r,nγ)=rgcd(r,ψp,q(γ)).
Proof
Since the period of Cγ(t) is logξγ, Lemma 4.16 yields that the covering degree of the restriction h:Cγ,l→Cγ is r/gcd(r,ψp,q(γ)). By Lemma 4.12, we obtain the assertion. □
Theorem in S3
By Lemma 4.13, Theorem 4.10, and by Proposition 4.18, we obtainlk(Cγ′,Kp,q)=mγlk(Cγ,K¯p,q)=mγrψp,q(γ)=1gcd(r,ψp,q(γ))ψp,q(γ).
Together with the results in Sect. 3.4, we conclude the following.
Theorem 4.19
(1) Let γ=(abcd)∈Γp,q be a primitive hyperbolic element with trγ>2 and c>0. Then, the linking number of each modular knot Cγ′ in S3-Kp,q associated with γ and the (p, q)-torus knot Kp,q is given bylk(Cγ′,Kp,q)=1gcd(r,ψp,q(γ))ψp,q(γ).
(2) Let γ∈Γp,q be any hyperbolic element and γ0∈Γp,q a primitive element with γ=±γ0ν for some ν∈Z. Then, the linking number is given bylk(Cγ′,Kp,q)=1gcd(r,Ψp,q(γ0))Ψp,q(γ)=1gcd(r,Ψp,qh(γ0))Ψp,qh(γ).
Remark 4.20
In the above, we proved the theorem in S3 via the case in the lens space. We may also directly discuss the case in S3 by using automorphic differential forms of degree 1/r studied by Milnor [27, Section 5]. Indeed, we can construct a lift Δ~p,q1/r:Gr\SL2~R→C× satisfying (Δ~p,q1/r(γ,n))r=Δ~p,q(γ) for every (γ,n)∈SL2~R. By a similar argument, we may obtainlk(Cγ′,Kp,q)=ind(Δ~p,q1/r(Cγ′),0)=1gcd(r,ψp,q(γ))ψp,q(γ)
for γ with the condition of Theorem 4.19 (1). The lift Δ~p,q1/r equals Tsanov’s function ω∞(z,dz) in [41, Lemma 4.16] up to a constant multiple, yielding a homeomorphism Gr\SL2~R≅S3-Kp,q [41, Section 5].
Euler cocycles
In this subsection, we further introduce another variant Ψp,qe of the Rademacher symbol as well as define knots corresponding to elliptic and parabolic elements, so that the theorems on linking numbers extend to whole Γp,q. This symbol is characterized by using an Euler cocycle, which arises as an obstruction to the existence of sections of cycles in the S1-bundle T1Γp,q\H≅Γp,q\SL2R≅L(r,p-1)-K¯p,q. Our argument partially justifies Ghys’s outlined second proof [16, Section 3.4] of his theorem.
The linking numbers of fibers
The singular fibers of the S1-bundle corresponding to the elliptic points a=eπi(1-1/p) and b=eπi/q are parametrized as:fa(t)=1-cosπp01(sinπp)1/200(sinπp)-1/2cost-sintsintcost,(0≤t≤πp),fb(t)=1cosπq01(sinπq)1/200(sinπq)-1/2cost-sintsintcost,(0≤t≤πq).
Indeed, they define closed curves byfa(πp)=0-112cosπpfa(0)=Spfa(0),fb(πq)=2cosπq-110fb(0)=Uqfb(0).
In addition, for any t∈R, we have fa(t)i=a, fb(t)i=b. ByΔ~p,q(fa(t))=j(fa(t),i)-2pqΔp,q(a)=(sinπp)pqe-2pqitΔp,q(a),
the winding number of Δ~p,q(fa(t)) (0≤t≤πp) around the origin is -q. In a similar way, the winding number of Δ~p,q(fb(t)) (0≤t≤πq) is -p. Thus, by Lemma 2.13, we see thatlk(fa,K¯p,q)=-qr=ψp,q(Sp)r,lk(fb,K¯p,q)=-pr=ψp,q(Uq)r,
and Theorem 4.10 (1) for the Rademacher symbol ψp,q may (literally) extends to these curves.
On the other hand, for any non-elliptic point z=x+iy∈H, the corresponding fiber (a generic fiber) in L(r,p-1)-K¯p,q≅Γp,q\SL2R is parametrized as:fz(t)=1x01y1/200y-1/2cost-sintsintcost,(0≤t≤π).
Indeed, we have fz(π)=-fz(0)=fz(0) and fz(t)i=z. ByΔ~p,q(fz(t))=j(fz(t),i)-2pqΔp,q(z)=e-2pqitypqΔp,q(z),
the winding number of Δ~p,q(fz(t)) (0≤t≤π) around the origin is ind(Δ~p,q(fz),0)=-pq. Hence the linking number of a generic fiber is given bylk(fz,K¯p,q)=-pqr.
Knots for Sp, Uq, and Tp,q
In order to extend the theorems on linking numbers to whole Γp,q, we define knots corresponding to elliptic and parabolic elements. Take a sufficiently small ε∈R>0. For the elliptic point a=eπi(1-1/p), we consider a circlec~a={z∈H∣dhyp(a,z)=ε}
with a clockwise orientation, where dhyp denotes the hyperbolic distance on H. The elliptic element Sp acts on c~a as a rotation of angle -2π/p. Take any point z0∈c~a and let s¯a denotes the circle segment connecting z0 to Spz0. Then, the image ca of s¯a in Γp,q\H is a simple closed curve. In addition, take any point Z0∈SL2R with Z0i=z0 and let sa denote the section of s¯a connecting Z0 to SpZ0. Then, the image Ca of sa in Γp,q\SL2R≅L(r,p-1)-K¯p,q is a simple closed curve satisfying Cai=ca. Since Ca→fa as ε→0, we havelk(Ca,K¯p,q)=lk(fa,K¯p,q)=-qr.
Similarly, for b=eπi/q, we define simple closed curves cb and Cb satisfying Cbi=cb andlk(Cb,K¯p,q)=lk(fb,K¯p,q)=-pr.
For the parabolic element Tp,q, as in the proof of Proposition 4.9 for (p,q)=(2,3), we take a lift Cy(t) (0≤t≤λ=2(cosπp+cosπq)) of a holocycle so that we havelk(Cy,K¯p,q)=1=rr=1rψp,q(Tp,q).
Theorem on whole Γp,q
Note that the fundamental group of the orbifold Γp,q\H is described by both the languages of loops and covering spaces (cf. [34, Chapter 13]). For each γ∈Γp,q, let w be a fixed point on H∪R∪{i∞} and consider the stabilizer (Γp,q)w. If γ is hyperbolic or parabolic, then (Γp,q)w≅Z×Z/2Z. If instead γ is elliptic, then (Γp,q)w is a finite cyclic group. Let c~ be a curve in H which is stable under the action of (Γp,q)w and let c denote the image of c~ in Γp,q\H. If γ is elliptic, then c is a cycle around a cone point. If γ is parabolic, then c is the image of a holocycle. If γ is hyperbolic, then we further assume that c~ is a geodesic. Such c is freely homotopic to a generator of γ in the sense of the orbifold fundamental group.
We define the knot Cγ as a section of such c. More precisely, in addition to Definition 4.5, we define knots corresponding to elliptic and parabolic elements as follows:
Definition 4.21
We put CSp=Ca, CUq=Cb, and CTp,q=Cy discussed in above. In addition, for any g∈Γp,q, we put C±g-1Spng=nCSp for n=1,2,⋯,p-1 and C±g-1Uqng=nCUq for n=1,2,⋯,q-1. For any g∈Γp,q and n∈Z, we put C±g-1Tp,qng=nCTp,q.
Definition 4.22
We define the modified Rademacher symbol Ψp,qe:Γp,q→Z byΨp,qe(γ)=-nqifγ∼±Spn(1≤n≤p-1),-npifγ∼±Uqn(1≤n≤q-1),Ψp,q(γ)=Ψp,qh(γ)if otherwise.
where ∼ denotes the group conjugate in Γp,q.
We remark that Ψp,qe(γ)=ψp,q(γ) holds if trγ≥2 or γ=Spn (1≤n≤p-1) or γ=Uqn (1≤n≤q-1). By combining all above, we may conclude the following.
Theorem 4.23
For any γ∈Γp,q, the linking number in L(r,p-1) is given bylk(Cγ,K¯p,q)=1rΨp,qe(γ).
In addition, suppose that γ=±γ0ν for a primitive non-elliptic element γ0∈Γp,q and ν∈Z or γ∼±Spn (1≤n≤p-1) or γ∼±Uqn (1≤n≤q-1). If Cγ′ is a connected component of h-1(Cγ) in the sense of Definition 4.14 (2), then the linking number in S3 is given bylk(Cγ′,Kp,q)=1gcd(r,Ψp,qe(γ0))Ψp,qe(γ).
An Euler cocycle for Ψp,qe
Let f=fz be a generic fiber given in Sect. 4.4.1. An Euler cocycleeu:Γp,q2→Z
of the S1-bundle T1Γp,q\H≅L(r,p-1)-K¯p,q is defined by the equality-[Cγ1]-[Cγ2]=-eu(γ1,γ2)[f]
in H1(L(r,p-1)-K¯p,q;Z) for every γ1,γ2∈Γp,q. Taking the linking numbers with K¯p,q, we obtainlk(Cγ1γ2,K¯p,q)-lk(Cγ1,K¯p,q)-lk(Cγ2,K¯p,q)=-eu(γ1,γ2)lk(f,K¯p,q)=eu(γ1,γ2)pqr.
Note that we have H2(Γp,q/{±I};Z)≅Z/pqZ and Cγ=C-γ for any γ∈Γp,q. Let ϕ:Γp,q→Z be a unique function satisfying -δϕ=pqeu and ϕ(γ)=ϕ(-γ) for any γ∈Γp,q. Then, for any γ∈Γp,q, we have lk(Cγ,K¯p,q)=ϕ(γ)/r. Together with the equality lk(Cγ,K¯p,q)=Ψp,qe(γ)/r in Theorem 4.23, we obtain the following.
Theorem 4.24
Let eu:Γp,q2→Z denote the Euler cocycle function defined as above. Then, the modified Rademacher symbol Ψp,qe is a unique function satisfying -δΨp,qe=pqeu and Ψp,qe(γ)=Ψp,qe(-γ) for any γ∈Γp,q.
Remark 4.25
We may replace Ψp,qe and eu in Theorem 4.24 by ψp,q and W by modifying the definition of modular knots for γ’s which do not satisfy the condition of Theorem 4.10 (1). In this case, the equalities Cγ=C-γ and Cγn=nCγ will be modified according to the formula ψp,q(-γ)=ψp,q(γ)+pqsgn(γ).
Remark 4.26
Ghys claims in [16, Section 3.4] that if we adapt the definition of modular knots to parabolic and elliptic elements, then his theorem follows from results of Atiyah [3] and Barge–Ghys [6], which explicitly investigate Euler cocycles in a view of Homeo+S1. If we directly extend the results of Atiyah and Barge–Ghys for Γp,q, then we may obtain alternative proofs of our theorems on the linking numbers.
Miscellaneous
Finally, we give some remarks and further problems.
Templates and codings
Ghys gave three proofs for his theorem on the Rademacher symbol for SL2Z and the linking number around the trefoil. In this article, through Sects. 2–4, we generalized his first proof in [16, Section 3.3] by introducing the cusp form Δp,q(z), as well as discussed an Euler cocycle in a view of his second outlined proof in [16, Section 3.4].
Ghys’s third proof in [16, Section 3.5] is a dynamical approach. A Lorenz knot is a periodic orbit appearing in the Lorenz attractor. Ghys proved for SL2Z that isotopy classes of Lorenz knots and modular knots coincide. In addition, he gave an explicit formula for lk(Cγ,K2,3) by using the Lorenz template. A hyperbolic element γ∈SL2Z is conjugate to a matrix of the formγ∼±S2U3ε1S2U3ε2⋯S2U3εn
with εi∈{+1,-1}. Then, the linking number counts the number of left and right codes on the Lorenz template, that is,lk(Cγ,K2,3)=∑i=1nεi.
On the other hand, Rademacher showed in [35, (70)] that ∑i=1nεi=Ψ2,3(γ). Thus, we obtain lk(Cγ,K2,3)=Ψ2,3(γ).
The templates for geodesic flows for triangle groups are studied by Dehornoy and Pinsky [11, 14, 32]. In particular, Dehornoy [11, Proposition 5.7] gave an explicit formula for the linking number between a periodic orbit of the geodesic flow ΦΓp,q\H and the (p, q)-torus knot K¯p,q. By combining their result and Theorem 4.10, we may obtain an explicit formula of the Rademacher symbol Ψp,q(γ). On the other hand, if one can show the explicit formula of Ψp,q(γ) directly from the definition, then we obtain a generalization of Ghys’s third proof.
Distributions
It is a natural question to ask the relation between the linking number lk(Cγ,Kp,q) of a modular knot and the length ℓ(Cγ) of the corresponding closed geodesic on the modular orbifold. Based on Sarnak’s idea in his letter [38], Mozzochi [31] proved variants of prime geodesic theorems to establish the following distribution formula, invoking the Selberg trace formula for SL2Z;
Proposition 5.1
Suppose that γ runs through conjugacy classes of primitive hyperbolic elements in SL2Z with trγ>2 and let ℓ(γ)=2logξγ denote the length of the image of each modular knot Cγ in SL2Z\H. Then, for each -∞≤a≤b≤∞, we havelimy→∞#{γ∣ℓ(γ)≤y,a≤lk(Cγ,K2,3)ℓ(γ)≤b}#{γ∣ℓ(γ)≤y}=arctanπb3-arctanπa3π.
Von Essen generalized their results in his Ph.D. thesis [45] (see also [9]) for any cofinite Fuchsian group with a multiplier system; let Γ<SL2R be a cofinite Fuchsian group, let f:H→C be a holomorphic modular form of weight 1 for Γ with no zero on H, and let ν:Γ→C be a multiplier system, namely we havef(γz)=ν(γ)j(γ,z)f(z)
for every γ∈Γ. For its holomorphic logarithm F(z)=logf(z), define Φ:Γ→C byF(γz)-F(z)=logj(γ,z)+2πiΦ(γ).
Assume in addition that the image of Φ is contained in Q. By invoking the Selberg trace formula for Fuchsian groups, von Essen gave generalizations of the Sarnak–Mozzochi results. For instance, his Theorem H implies the following:
Proposition 5.2
If we replace SL2Z by Γ in Proposition 5.1, then we havelimy→∞#{γ∣ℓ(γ)≤y,a≤Φ(γ)ℓ(γ)≤b}#{γ∣ℓ(γ)≤y}=arctan4πb-arctan4πaπ.
We remark that von Essen also showed for the Hecke triangle group Hn=Γ2,n a formula which is essentially the same as in our Theorem 4.10 (1). His construction of the cusp form Δ2,n(z) differs from ours but is closely related to Tsanov’s construction of ω∞(z,dz) explained in Remark 4.20.
His results and Proposition 5.2 are applicable to our setting with a more general triangle group Γp,q. In fact, let f(z)=Δp,q(z)1/2pq=exp12pqFp,q(z) and F(z)=12pqFp,q(z). By Definition 3.1, we havef(γz)=ν(γ)j(γ,z)f(z),ν(γ)=e2πiψp,q(γ)2pq,
and Φ(γ)=12pqψp,q(γ). Thus, we obtain the following.
Corollary 5.3
If we replace SL2Z by Γp,q in Proposition 5.1, then we havelimy→∞#{γ∣ℓ(γ)≤y,a≤ψp,q(γ)ℓ(γ)≤b}#{γ∣ℓ(γ)≤y}=arctan2πbpq-arctan2πapqπ.
By our Theorem 4.10, we may replace ψp,q(γ) by rlk(Cγ,K¯p,q) to obtain the Sarnak–Mozzochi formula for Γp,q.
Remark 5.4
The set of modular knots around the trefoil satisfies another distribution formula called the Chebotarev law in the sense of Mazur [25] and McMullen [26], so that it may be seen as an analogue of the set of all prime numbers in SpecZ [43, 44], in a sense of arithmetic topology [29]. An exploration of a unified viewpoint for these formulas would be of further interest.
Further problems
Hyperbolic analogue
Duke–Imamoḡlu–Tóth [13] investigated the linking number of two modular knots for SL2Z. More precisely, they introduced a hyperbolic analogue of the Rademacher symbol Ψγ(σ) for two hyperbolic elements γ,σ∈SL2Z by using rational period functions, and established the equation Ψγ(σ)=lk(Cγ++Cγ-,Cσ++Cσ-). Here Cγ+ is the modular knot as before, and Cγ- is another knot such that Cγ++Cγ- is null-homologous in S3-K2,3. Furthermore, the first author [23] gave an explicit formula for the hyperbolic Rademacher symbol Ψγ(σ) in terms of the coefficients of the continued fraction expansion of the fixed points of γ and σ. An open question for SL2Z is to find a modular object yielding the linking number lk(Cγ,Cσ) (see also [36]). We may expect similar results for general triangle groups Γ(p,q,r).
Other characterizations
In [3, Theorem 5.60], Atiyah gave seven different definitions of the Rademacher symbol for hyperbolic elements of SL2Z (see also [6]). It would be interesting to extend any of them for Γp,q.
Galois actions
Since torus knots are algebraic knots, we have a natural action of the absolute Galois group on the profinite completions of the knot groups. We wonder if we may, in a sense, parametrize the Galois action via modular knots.
Acknowledgements
The authors would like to express their sincere gratitude to Masanobu Kaneko for his introduction to Asai’s work in a private seminar and to Masanori Morishita for posing an interesting question related to Ghys’s work. The authors are also grateful to Pierre Dehornoy, Kazuhiro Ichihara, Özlem Imamoḡlu, Atsushi Katsuda, Morimichi Kawasaki, Ulf Kühn, Shuhei Maruyama, Makoto Sakuma, Yuji Terashima, and Masahito Yamazaki for useful information and fruitful conversations. Furthermore, the authors would like to thank all the participants who joined the online seminar FTTZS throughout the COVID-19 situation for cheerful communication. The first author has been partially supported by JSPS KAKENHI Grant Numbers JP20K14292 and JP21K19141. The second author has been partially supported by JSPS KAKENHI Grant Number JP19K14538.
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| 0 | PMC9734963 | NO-CC CODE | 2022-12-14 23:28:31 | no | Res Math Sci. 2023 Dec 9; 10(1):4 | utf-8 | Res Math Sci | 2,022 | 10.1007/s40687-022-00366-8 | oa_other |
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J Bus Psychol
J Bus Psychol
Journal of Business and Psychology
0889-3268
1573-353X
Springer US New York
9851
10.1007/s10869-022-09851-x
Original Paper
Difficult Times, Difficult Decisions: Examining the Impact of Perceived Crisis Response Strategies During COVID-19
http://orcid.org/0000-0002-9910-5341
Bricka Traci M. [email protected]
1
http://orcid.org/0000-0001-9925-6783
He Yimin [email protected]
2
http://orcid.org/0000-0002-6955-4322
Schroeder Amber N. [email protected]
1
1 grid.267315.4 0000 0001 2181 9515 Department of Psychology, The University of Texas at Arlington, 313 Life Science, Box 19528, Arlington, TX 76019 USA
2 grid.266815.e 0000 0001 0775 5412 Department of Psychology, The University of Nebraska Omaha, ASH 347 F, 222 University Dr. E, Omaha, NE 68182 USA
6 12 2022
121
11 10 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Crises, such as the COVID-19 pandemic, require rapid action to be taken by leaders, despite minimal understanding of the impact of implemented crisis management policies and procedures in organizations. This study’s purpose was to establish a greater understanding of which perceived crisis response strategies were the most beneficial or detrimental to relevant perceptions and outcomes during the recent COVID-19 crisis. Using a time-lagged study design and a sample of 454 healthcare employees, latent profile analysis was used to identify strategy profiles used by organizations based on several policy/procedure categories (i.e., human-resource supportive, human-resource disadvantaging, behavioral/interactional human safety and protection-focused, and environmental and structural safety supports-focused policies and procedures). Results indicated that four perceived crisis response strategies were employed: (1) human resource-disadvantaging, (2) maximizing, (3) safety and human resource-supportive, and (4) inactive. Perceived crisis response strategy was linked to several employee well-being (e.g., work stress) and behavioral (e.g., safety behavior) outcomes via proximal perceptions (i.e., perceived organizational support, ethical leadership, and safety climate). Proximal perceptions were the most positive for employees within organizations that enacted safety and human resource-supportive policies and procedures or that utilized a maximizing approach by implementing a wide array of crisis response policies and procedures. This paper contributes to the literature by providing crucial information needed to reduce organizational decision-making time in the event of future crises.
Keywords
Crisis response strategies
Work attitudes
Workplace health and well-being
Safety
==== Body
pmcThe onset of the COVID-19 pandemic was a crisis situation characterized by significant loss of life, pressure to rapidly enact strategic responses, and a lack of available resources and information (WHO, 2020). As tremendous progress has been made since that time, it may be enticing to move past the devastation and focus on a more hopeful future. However, we argue that it is important to take a lessons-learned approach by evaluating the effects of implemented policies during the onset of the crisis in order to determine which may be most appropriate to deploy in the future.
Crises have widespread impacts for many entities (e.g., governments, communities), but can be particularly disruptive to organizations, rendering negative effects on employee attitudes and behaviors (Ayoko et al., 2017). However, due to an absence of resources on pandemic strategy approaches (Boin & Lodge, 2021), little is known about the impact that specific policies or strategic human resource responses have on employee perceptions and outcomes during crises. As such, identifying effective perceived crisis response strategies, particularly those not studied in previous research, is crucial in order to take a prescriptive approach for navigating future large-scale disasters which present similar crisis scenarios. Therefore, this study used a novel configural approach (i.e., latent profile analysis; LPA; a technique in which patterns across variables are examined to configure profiles; Spurk et al., 2020) to establish a greater understanding of which strategies enacted in response to the COVID-19 pandemic were the most impactful on relevant perceptions and outcomes in order to inform organizational actions in future crises.
Crisis Management Responses
A crisis is an ambiguous situation that poses an immediate threat to a group’s essential operations or values (Boin & Hart, 2007), arising from a disaster event, such as a pandemic (Shaluf et al., 2003). The crisis management process (i.e., an organized effort to avoid or respond to crises) has been argued to impact relevant outcomes, and scholars have emphasized the importance of observing lessons learned during a crisis to apply to future events (Pearson & Clair, 1998). As such, this study aims to further the crisis management literature by examining actions taken in response to a recent crisis (i.e., the COVID-19 pandemic) to better equip organizations for future health-related crises.
More specifically, by providing evidence of the beneficial or detrimental nature of strategic crisis responses on employee outcomes, the results of this effort can be used to significantly reduce organizational decision-making time in determining which strategies to enact. As crisis management consists of three phases (i.e., pre-crisis, crisis, and post-crisis; Coombs & Laufer, 2018), this study contributes to the post-crisis phase (i.e., a time in which crisis responses are evaluated for learning purposes) of the COVID-19 pandemic to serve as a valuable resource in the pre-crisis (i.e., preparation) phase for future crises and provide a roadmap for subsequent crisis phases. In particular, we present specific, actionable policies that have been empirically demonstrated to be beneficial to employee outcomes and can be immediately implemented by organizations, which is particularly vital as the crisis management literature lacks research investigating the post-crisis phase (Coombs & Laufer, 2018) and detailed, practical crisis management plans (Coombs, 2015) focused on internal stakeholders (Frandsen & Johansen, 2011).
Several conceptual models have been introduced that offer insight into existing conceptualizations of crisis management strategies. Crises impacting the healthcare system require concentrated efforts, as their severe impact on everyday life extends beyond the scope of traditional crisis management (Burkle, 2019). Work has been done to revise general crisis management frameworks (e.g., a three-stage model consisting of prevention and preparedness, response, and recovery and rehabilitation) to be tailored to health crises by considering what each phase would specifically entail in this context (Burkle, 2019). Similarly, Olu (2017) provided a framework highlighting how specific strategies (e.g., acquiring surplus equipment) align with crisis management stages and Heath et al. (2020) highlighted strategies likely to increase worker resilience during the pandemic (e.g., providing organizational justice). Further, reviews of crisis management conceptual models have highlighted the varying foci of crisis management strategies (Wang & Belardo, 2005) and tactics for determining which strategy is most appropriate for a given crisis situation (Harwati, 2013). In addition, research has identified specific competencies of effective leaders in healthcare organizations during crises, such as communication and influencing others (Sriharan et al., 2021). Taken together, the crisis management literature offers useful information regarding the selection of crisis management strategies.
However, the crisis management literature is lacking research examining how organizational internal crisis responses impact employee outcomes (Guzzo et al., 2021; Witala & Mistry, 2022), particularly in the healthcare sector. Therefore, the present effort addresses this gap by empirically examining which relevant outcomes are impacted by perceived enactment of specific strategies. More specifically, we recognize that leadership teams are forced to make rapid decisions in times of crisis and may inadvertently make crucial missteps in the crisis management process (Pearson & Clair, 1998). As such, we rely on theoretical tenets to investigate the relations between crisis response strategies and employee perceptions of their organization, the organization’s leaders, and the work environment, as well as their attitudinal and behavioral outcomes to determine which strategy approaches were associated with positive outcomes.
Perceived Crisis Responses During COVID-19
Although nearly all organizations were affected by the pandemic, healthcare organizations battled the crisis on multiple fronts (Grimm, 2020), including financial loss (The Associated Press, 2020) and increased employee safety risks (Cohen & Nigam, 2020). This is particularly concerning, as healthcare workers were on the frontlines in combating the COVID-19 crisis, and their efforts likely had wide-reaching impacts (Bapuji et al., 2020). Because of the prevalence of crises in this field, healthcare organizations have been deemed a “living laboratory” for the development of crisis management approaches (Nemeth et al., 2011). Thus, the identification of effective perceived crisis management strategies enacted within the healthcare sector is particularly imperative.
There has been widespread variability in enacted policies during COVID-19, with healthcare organization responses ranging from implementing employee furloughs (Frankel & Romm, 2020) to introducing telemedicine services to better serve patients (Centers for Disease Control and Prevention, 2020a). Due to this variability, there is a need to identify which policy implementation approaches were taken in order to determine the differential impacts. Notably, recent efforts have made strides in identifying COVID-19-related human resource management responses in various fields (i.e., hospitality, education), focusing on tactics such as communication and leader behaviors (e.g., Agarwal, 2021; Matthews et al., 2022; Witala & Mistry, 2022). Such efforts provide tremendous value to the literature by extending knowledge on policy-based crisis responses; however, the present effort is distinct in that it provides a specific list of policies that healthcare organizations can rapidly enact, using a latent profile approach to highlight which strategies were most effective to improve decision-making response time in future events. As better understanding the impact of such strategies on workplace outcomes can serve a prescriptive purpose, the first objective of this project was to identify unique profiles of perceived crisis response strategies.
As scholars have endorsed using a profile approach for examining organizational policies (Schulte et al., 2009), the method used to identify unique profiles is LPA, an exploratory analysis that groups participants with similar responses into categorical configural profiles (Spurk et al., 2020). As the profiles that emerge are dependent on which strategies respondents perceive to have been implemented, precise expectations of profiles and expected differences cannot be stated. However, as previous research has established that policymakers can delay or altogether fail to enact crisis response strategies (Bristow & Healy, 2015) and as crisis responses often involve implementing numerous policies in a limited time frame (Huang, 2008), we anticipate the emergence of both an inactive response profile in which no policies were enacted and a maximizing profile in which a multitude of actions were taken simultaneously. Further, as suggested by the diversity of policies compiled by subject matter experts (i.e., SMEs) for the purpose of this study (e.g., some organizations providing bonus pay and others decreasing pay; see Appendix 1), we expected a misalignment between profiles, such that some organizations primarily implemented strategies that were supportive to employees, whereas others implemented those that disadvantaged employees. Taken together, the following research question is proposed on an exploratory basis:Research Question 1 (RQ1): What perceived crisis response strategies were employed by healthcare organizations during COVID-19?
Perceived Crisis Response Strategy Impact
Employee perceptions of their organization’s crisis response strategy are likely to directly impact perceptions of the organization, the organization’s leaders, and the work environment. Although a number of theories have put forth explanatory mechanisms for this proposition, we focus specifically on social exchange and organizational support theories as guiding frameworks. Namely, social exchange theory (Blau, 1964; Homans, 1958) suggests that the quality of relationships between two parties is determined by their mutual exchanges (Cropanzano & Mitchell, 2005), which can be applied to employee relationships with both organizational leaders and the employing organization (Brown et al., 2005). Thus, when employees perceive that their organization has enacted favorable policies or procedures, employee attitudes and behaviors are also likely to be positive (Masterson et al., 2000).
Similarly, organizational support theory (Eisenberger et al., 1986) proposes that in the social exchange relationship between employees and an organization, employees develop attributions based on the favorability of the treatment they receive, resulting in reciprocating responses (Kurtessis et al., 2017). For instance, research has suggested that unsupportive organizational practices can result in feelings of exploitation, which can negatively impact employee attitudes and well-being (Caesens et al., 2017). Organizational support theory is rooted in the tenets of social exchange theory, as perceived support from an employee’s organization is the foundation for evaluating social exchange (Wayne et al., 1997).
Research has established that employees form perceptions about leadership through inferential processes, such that employees examine leader actions or processes in which they are involved, then make conclusions about leadership based on the outcome of those events (Jantzi & Leithwood, 1996). As such, perceived policy implementation may serve as a basis for employees to form perceptions about the organization and its leaders. Thus, our second objective was to examine how employee perceptions of the crisis responses employed by their organization were related to employee perceptions of the organization, leadership, and the work environment.
Proximal Employee Perceptions
We define proximal employee perceptions as perceptions that are formed as a direct result of perceived efforts undertaken by the organization in response to the crisis. Just as policies can be wide-ranging, so can the targets of employee attributions and perceptions. Namely, individual attributions of responsibility during organizational crises can vary (Zemba et al., 2006), as blame assignment during an organizational crisis is based on a complex sensemaking process (Gephart, 1993). Thus, whereas social exchange theory would suggest that perceived crisis response policies are likely to impact perceptions of employee treatment, an examination of the specific target(s) of those attributions (e.g., leaders) would provide greater insight into employee perceptions of responsibility.
Thus, in the current study, we focus on employee perceptions of three diverse workplace targets—leaders, the organization, and the work environment. Although a variety of perceptions would likely be impacted by organizational crisis management approaches, we selected three factors that align with the lenses set forth by the aforementioned theories and capture a wide range of phenomena while balancing survey length considerations. Namely, perceptions of ethical leadership, organizational support, and safety climate were included to assess employee perceptions of their leaders, organizations, and work environments, respectively.
Ethical leadership was selected to assess employee perceptions of leadership, as many of the policies enacted by healthcare organizations were innately ethical issues. Namely, healthcare organizations were required to make ethically complex decisions such as allocating scarce life-sustaining resources (e.g., ventilators; Springs, 2022) or evaluating the necessity of employee pay cuts. As severe ethical challenges in regard to healthcare policy and decision-making were raised by the pandemic (WHO, n.d.), examining perceptions of ethical leadership (i.e., a leader’s exhibition and promotion of normative workplace behavior via interpersonal communication, enforcement of consequences, and decision-making; Brown et al., 2005) can provide insight into how judgments of leader attributes are affected by perceived crisis response strategies, thereby providing organizations with a roadmap for effective crisis management.
Ethical leadership has often been identified as an important variable to consider within the context of social exchange theory (e.g., Brown et al., 2005; Mayer et al., 2009) as the theory suggests that leader actions toward employees are the basis of employee perceptions of leadership, such that interactions consisting of reciprocal equity and trust are likely to result in strong perceptions of ethical leadership (Mayer et al., 2009). Previous work investigating perceived ethical leadership in a healthcare context has established that organizational policies are often perceived to be ethical issues, and as leaders enact policies that set expectations for ethical standards (Mayer et al., 2009), organizational policies may impact employee perceptions of ethical leadership (Makaroff et al., 2014). Further, policies pertaining to ethical issues (e.g., pay) can impact employee perceptions of organizational ethics, which is reflective of the leaders implementing such policies (Weeks et al., 2004). Research has not only identified the overlap between policy-making and ethical leadership (Hudson, 1997) but also linked crisis scenarios to ethical leadership, as crises often result in leader decision-making errors (Pearson & Clair, 1998) and have been argued to impair leader abilities to make ethical decisions (Harwati, 2013).
In turn, POS was selected to assess perceptions of organizations, as human resource-focused responses more advantageous to employees (e.g., increased mental health benefits) are likely to impact employee perceptions of organizational support. Perceived organizational support (POS; i.e., an employee’s belief that the organization values their well-being and cares about their welfare) has frequently been examined in the context of social exchange theory due to the reciprocity of support perceptions that occur between an employee and their organization and the importance of those perceptions in determining relevant outcomes (Cropanzano & Mitchell, 2005).
Social exchange theory posits that the favorability of organizational actions are likely to strongly influence POS, particularly when the actions are perceived to be voluntarily implemented (Eisenberger et al., 1986), which is a proposition that has been supported by empirical evidence (Eisenberger et al., 1997). As organizations enacted a wide array of policies during the pandemic in a condensed period of time (Burrill et al., 2020), it is possible that employees perceived these policy implementations to be within the organization’s realm of control, therefore impacting POS as suggested by social exchange theory. Further, employees often view actions by agents of the organization (e.g., human resources) as indicators of the organization’s intentions (Eisenberger et al., 1986), and meta-analyses have demonstrated that favorable human resource practices are positively linked to POS (Kurtessis et al., 2017; Rhoades & Eisenberger, 2002).
Lastly, as a large number of safety-focused policies are frequently enacted during health-related crises, safety climate was selected to assess employee perceptions of their work environment. Safety climate is particularly relevant to employee health in health-related crisis situations (Sinclair et al., 2020) and has been identified to be a critical component in shaping healthcare work environments during active disease outbreaks (Wang et al., 2021). As both theoretical (see, e.g., Zohar, 2014) and meta-analytic work (He et al., 2019) have identified organizational policies as crucial to the development of safety climate perceptions, safety climate was identified as a particularly important factor to measure to assess work environment perceptions in response to crisis-enacted policies.
Notably, Zohar (2014) conceptualized safety climate differently based on the level of theory and analysis. At the individual level, safety climate is defined as an individuals’ perceptions of safety policies, procedures, and practices at work. At the unit level (e.g., organizations), safety climate refers to employees’ shared perceptions of safety policies, procedures, and practices within a unit (Zohar, 2014), calculated by aggregating employees’ perceptions of safety climate across meaningful clusters (Zohar, 2014). Collectively, safety climate emerges from individuals’ sense-making processes about organizational events. Specific to our study, the crisis response policies directly influence individuals’ sense-making processes regarding safety environments, which ultimately form the safety climate. We aimed to focus on this proximal, or direct, influence in the current study; therefore, the current study focuses on perceived safety climate at the individual level.
Safety climate perceptions have been investigated through the lens of social exchange theory. For example, it has been argued that organizational support of safety will result in greater employee safety climate perceptions (Cheung & Zhang, 2020). To this point, several efforts have reported a positive relationship between organizational support and safety climate perceptions (Cheung & Zhang, 2020; DeJoy et al., 2004). Similarly, scholars have theorized that organizational efforts to create a protected work environment will increase employee reciprocation of those values and safety climate perceptions (Cheung & Zhang, 2020). As such, an investigation of perceived ethical leadership, organizational support, and safety climate is warranted within the theoretical framework of social exchange theory and can provide insight into the diverse targets and nature of perceptions that can result from perceived organizational crisis responses.
Taken together, perceived crisis response strategies are likely to impact employee proximal perceptions such that strategies that are perceived by employees to be favorable may be positively related to ethical leadership, organizational support, and safety climate perceptions. As research has not yet identified the common strategic approaches employed by organizations during health-related crises, we broadly expect that the favorability of employee proximal perceptions will reflect the extent to which perceived crisis response strategies included supportive (e.g., increased pay) and maximizing (i.e., enacting a wide array of changes) human resource policies and procedures and avoided disadvantaging (e.g., decreased pay) policies or being inactive (i.e., minimal actions taken).Hypothesis 1 (H1): Perceived crisis response strategies that put greater emphasis on supportive and maximizing human resource policies and procedures will be linked to more favorable employee proximal perceptions (i.e., perceptions of ethical leadership, organizational support, and safety climate) than those that enacted primarily disadvantaging policies or were inactive.
Distal Employee Effects
Social exchange theory (Blau, 1964; Homans, 1958) suggests that subjective assessments play a key role in determining future attitudes and behaviors. Kurtessis et al. (2017) provided meta-analytic evidence for the impact of social exchange relationships, such that organizational policies and practices were linked to employee POS, which were related to employee well-being, work behavior, and orientation toward the organization. As this pattern of relationships has been demonstrated, it is likely that a similar trend will occur in the present effort via mediation effects. Although work orientation factors are certainly important outcomes that can have long-term implications, because of the toll the COVID-19 pandemic has taken on healthcare workers (Pappa et al., 2020), the current study focuses on the arguably more pressing concerns of employee well-being and behavior. More specifically, we examine two facets of employee well-being (i.e., job satisfaction and work stress) and two work behavior outcomes (i.e., turnover intentions and safety behavior).
Much support has been garnered for organizational support theory’s proposition that an employee’s perceptions about the extent to which they are valued by their organization are predictive of their subsequent attitudes and behaviors. For instance, in regard to employee well-being, perceptions of ethical leadership, organizational support, and safety climate have been positively linked to employee satisfaction (Church, 1995; Harris et al., 2007; Huang et al., 2016; Nixon et al., 2015) and inversely related to psychological stress or job strain (Chen et al., 2017; Elçi et al., 2012; Harris et al., 2007; Yu & Li, 2020). Further corroborating organizational support theory’s proposition regarding work behaviors, perceptions of ethical leadership, organizational support, and safety climate have been inversely linked to turnover intentions (Elçi et al., 2012; Harris et al., 2007; Nixon et al., 2015) and positively linked to safety behaviors (i.e., individual actions aimed at improving the health and safety; Christian et al., 2009; Chughtai, 2015; Hofmann & Morgeson, 1999). Thus, using both theoretical and empirical work as a foundation, we expect that proximal perceptions formed during COVID-19 will be an intermediary in the link between perceived crisis response strategies and distal employee outcomes (see Fig. 1).Hypothesis 2 (H2): Perceived crisis response strategy will impact distal employee outcomes via proximal employee perceptions such that individuals in organizations that are perceived to employ supportive or maximizing response strategies will perceive more favorable proximal perceptions (i.e., perceptions of ethical leadership, organizational support, and safety climate) than those that are perceived to employ disadvantaging or inactive response strategies, leading to more positive employee distal outcomes (i.e., job satisfaction, work stress, turnover intentions, and safety behavior).
Fig. 1 Hypothesized model in which perceived crisis response profiles are expected to predict distal effects via proximal perceptions
Specific Perceived Crisis Response Policies and Procedures
Due to the unprecedented nature of the COVID-19 crisis, entities worldwide had to tackle numerous challenges with limited decision-making time (Burrill et al., 2020). This sense of urgency resulted in the rapid implementation of wide-ranging policies and procedures likely to have varying impacts (Burrill et al., 2020). In order to provide prescriptive information on which specific perceived crisis response policies and practices were the most impactful, we will conduct an exploratory examination of the links between specific perceived policies and practices implemented during COVID-19 and employee proximal perceptions and distal outcomes.Research Question 2 (RQ2): Which perceived crisis response policies and practices have the strongest links to employee proximal perceptions and distal outcomes?
Method
Participants
Individuals employed at healthcare facilities were recruited via the ResearchMatch platform, online healthcare forums and social media pages, researcher personal networks, and direct solicitations to hospitals. Participants who completed both surveys included 454 individuals who were at least 18 years of age and employed at a healthcare facility within the USA. In the sample, 66.5% worked in medical roles within their healthcare facilities, and 81.9% reported having direct interaction with patients in their roles.
Procedure
This study consisted of two data collection phases between May and August 2020, as time-lagged study designs are necessary to infer directionality in a mediation model (Cole & Maxwell, 2003). Phase one assessed policies enacted by organizations during COVID-19 and proximal employee perceptions, in addition to demographics, covariate measures, and distal outcomes to collect initial outcome scores. Approximately 30 days later, participants provided additional data on the distal effect variables, which were used in analyses as outcome variables. Participants were entered into a raffle for one of three $100 gift cards each time they completed the survey.
Measures
For each measure discussed below, five-point agreement scales were used, unless otherwise stated. Reliability coefficients are reported in Table 1.Table 1 Descriptive statistics and scale reliabilities for all study variables
Variable M SD 1 2 3 4 5 6 7 8 9
1. Age 41.29 13.51
2. Gender 0.85 0.36 − .07
3. Education 0.82 0.39 − .10* − .07
4. Race 0.14 0.34 − .07 − .05 − .05
5. Career tenure 13.43 11.74 .74** .04 − .03 − .07
6. Job tenure 7.10 8.05 .56** .01 .03 − .12* .66**
7. Patient interaction 0.82 0.39 − .10* .00 − .06 .10* − .12* − .16**
8. Work location 0.45 0.50 − .01 − .06 − .13** .05 − .06 − .11* .05
9. Hours worked 40.71 19.24 − .03 − .05 .04 .01 .02 − .04 − .07 .04
10. # of children 0.40 0.80 − .10* − .04 − .02 − .01 − .04 − .01 .01 .03 .05
11. Work intensity 3.32 1.01 − .05 .02 − .02 − .07 .03 .00 − .06 .04 .20**
12. Job title 0.33 0.47 .04 − .05 − .10* − .01 − .06 .08 − .26** .13** .05
13. Human resource-supportive 7.86 3.84 .03 .06 .10* − .07 .02 .15* − .12** − .30** .01
14. Human resource-disadvantaging 2.57 1.55 .02 − .01 .01 − .06 .07 .13* − .13** − .10* .00
15. Behavioral/interactional human safety and protection-focused 6.41 2.14 .00 .05 .06 − .01 − .02 .12* − .04 − .24** .05
16. Environmental and structural safety supports-focused 12.58 4.38 .00 .03 .12* − .06 − .02 .17* − .08 − .28** .06
17. Perceived ethical leadership 3.62 0.97 .06 .00 .10* − .01 .01 .06 − .12* − .06 − .01
18. Perceived organizational support 3.43 1.04 .03 − .01 .09* .05 − .02 .06 − .08 − .03 − .05
19. Perceived safety climate 3.85 0.93 − .06 .03 .09 − .01 − .10* .05 − .03 − .09* .02
20. Job satisfaction 3.86 0.91 .17** − .02 .04 .04 .11* .08 .03 − .06 − .01
21. Work stress 3.28 0.79 − .11** .06 − .01 − .03 − .03 − .01 .02 .03 .20**
22. Turnover intentions 2.31 1.25 − .13** .00 − .02 .03 − .08 − .12* .01 .09* .10*
23. Safety behavior 4.26 0.58 .24** − .04 − .06 − .01 .15** .13** .03 .07 .09
Variable 10 11 12 13 14 15 16 17 18 19 20
11. Work intensity − .06 (.86)
12. Job title − .06 .03
13. Human resource-supportive .04 − .07 .00 (.81)
14. Human resource-disadvantaging .05 .14** .05 .19** (.47)
15. Behavioral/interactional human safety and protection-focused .02 − .10* .07 .62** .24** (.72)
16. Environmental and structural safety supports-focused .09 − .07 .06 .67** .27** .83** (.86)
17. Perceived ethical leadership .10* − .25** .13** .46** .02 .44** .47** (.95)
18. Perceived organizational support .10* − .30** .11* .42** − .04 .36** .38** .86** (.95)
19. Perceived safety climate .11* − .19** .13** .42** .06 .44** .47** .73** .76** (.93)
20. Job satisfaction .11* − .31** − .04 .24** − .01 .20** .18** .48** .56** .51** (.90)
21. Work stress − .03 .58** .00 − .07 .13** − .03 − .01 − .30** − .38** − .29** − .53**
22. Turnover intentions − .05 .26** .03 − .17** − .01 − .11* − .14** − .37** − .44** − .45** − .70**
23. Safety behavior .08 − .06 .06 .11* − .01 .11* .10* .28** .22** .25** .33**
Variable 21 22 23
21. Work stress (.94)
22. Turnover intentions .44** (.89)
23. Safety behavior − .15* − .26** (.85)
M and SD are used to represent mean and standard deviation, respectively. Items 12–15 represent the average number of policies enacted in each response category per participant. Gender was coded: 0 = male, 1 = female. Education was coded: 0 = less than a bachelor’s degree, 1 = bachelor’s degree and above. Race was coded: white = 0, non-white = 1. Work location was coded: 0 = hospital, 1 = non-hospital facility. Patient interaction was coded: 0 = no, 1 = yes. Job title was coded: 0 = medical staff, 1 = non-medical staff. Scale reliabilities are reported in the diagonal. *p < .05; **p < .01. The four organizational crisis response policy categories consisted of 17 items (human-resource supportive), 7 items (human-resource disadvantaging), 9 items (behavioral/interactional human safety and protection-focused), and 19 items (environmental and structural safety supports-focused)
Perceived Organizational Crisis Policies and Procedures
A list of 52 COVID-19-specific perceived organizational crisis response policies and procedures was compiled using publicly available information and data provided by SMEs. More specifically, we reviewed the literature on organizational crisis response policies and publicly available taxonomies (i.e., Centers for Disease Control and Prevention, 2020b; OHSU, 2020) and consulted 15 healthcare workers in the researchers’ personal networks with a variety of expertise across healthcare facilities and departments to qualitatively generate a comprehensive set of crisis response policies. In this process, the SMEs indicated in an open-response format which policies had been implemented or should have been enacted by healthcare organizations in response to COVID-19. Lists of policies were then independently generated by two members of the research team using the gathered information, who then calibrated their lists to reach full agreement on the initial set of items. Notably, the list of generated policies was directed toward primarily employees but also patients, as policies relevant to patients have a substantial impact on employees.
After identifying distinct policies and procedures, the research team used affinity mapping methodology (see, e.g., Murphy et al., 2018) to generate categories to represent the broad types of policies and procedures encompassed by the measure. More specifically, a qualitative sorting process was used to group perceived organizational policies and procedures into four categories: (a) human resource-supportive (i.e., focused on personnel compensation, benefits, job specifications, and work arrangements likely to be viewed as neutral or beneficial for employees; 17 items; e.g., introduced a temporary pay increase), (b) human resource-disadvantaging (i.e., focused on personnel compensation, benefits, job specifications, and work arrangements likely to be viewed as detrimental to employees; 7 items; e.g., introduced a temporary pay decrease), (c) behavioral/interactional human safety and protection-focused (i.e., focused on managing safety behaviors and/or providing protections in interactions among staff, patients, and/or visitors; 9 items; e.g., introduced visitor restrictions), and (d) environmental and structural safety supports-focused (i.e., focused on regulations related to the medical facility, safety equipment, and/or organization-level strategies for COVID-19 management; 19 items; e.g., imposed limits on PPE use). See Appendix 1 for the comprehensive list of policies comprising each category. The research team reached full agreement on the categorization of each item into the established categories. After these categories were identified, 12 student researchers with knowledge of organizational behavior independently sorted the 52 items into the categories to verify the placement of each item after undergoing rater training. The category that received the majority placement for each item was retained, with the study authors serving as tiebreakers.
We then solicited face and content validity evaluations of the generated policies (e.g., content relevance of the policies, the representativeness of the domain being assessed) from SMEs with various expertise (i.e., occupational health and safety researchers, healthcare practitioners in academia and medical facilities). We also asked for input on whether additional policies were overlooked in the initial version. Their feedback was independently incorporated by the authors through revising, deleting, and adding policy items to ensure the comprehensiveness, representativeness, and clarity of the crisis policy items. The authors then convened to discuss the discrepancies until reaching full agreement. The final list rendered a Cronbach’s alpha reliability coefficient of 0.91, consisting of 52 organizational crisis policy and procedure items which were then distributed to participants, asking them to indicate on a yes/no scale if each item was perceived to be implemented by their organization during the pandemic. This methodology follows that of Ramus and Steger (2000), who asked participants to agree or disagree that each policy had been enacted in their organization.
Proximal Perceptions
Perceptions of ethical leadership were assessed using Brown et al.’s (2005) 10-item scale, POS was measured with Eisenberger et al.’s (1986) nine-item scale, and perceived safety climate was evaluated with Huang et al.’s (2017) eight-item measure. Each scale was modified to include the stem, “during the COVID-19 crisis” and was phrased in past tense.
Distal Effects
Job satisfaction and turnover intentions were measured using three-item scales from the Michigan Organizational Assessment Questionnaire (Camman et al., 1979; Seashore et al., 1982). Stress was evaluated using Stanton et al.’s (2001) 15-item Stress in General scale, and safety behavior was measured with Griffin and Neal’s (2000) eight-item measure. Each of the distal effect scale items (with the exception of the following turnover intentions item: “I will probably look for a new job during the next year”) asked participants to respond in reference to the past 30 days and used past tense phrasing.
Demographic Variables and Covariates
Participants reported basic demographic information (i.e., age, gender, education level, and race), completed Boekhorst et al.’s (2017) five-item measure of work intensity, and reported average hours worked per week over the past 30 days, number of children in their household, job title, healthcare facility type, career and job tenure, and whether they directly interact with patients. Including a large number of variables in analyses is a common, recommended tactic when using an exploratory approach (Spector, 2017). As such, these measures were included as covariates either because employee work experiences were likely to be biased on the basis of the variable (i.e., job title) or because it had been shown to impact at least one outcome variable.
More specifically, job title was included as a covariate as non-medical staff are likely to have differential relationships with certain outcome variables (e.g., perceived safety climate), as their jobs do not entail interacting with infected patients unlike the medical staff. Further, research has demonstrated that all remaining explored covariates (i.e., age, gender, education level, race, work intensity, work hours, number of children, healthcare facility type, career and job tenure, direct interaction with patients) explain considerable variance in at least one outcome variable of interest (Besen et al., 2013; Carless & Arnup, 2011; Duffy et al., 1998; Grunfeld et al., 2005; Hersch & Xiao, 2016; Iranmanesh et al., 2017; Ozyurt et al., 2006). For instance, age has been shown to positively impact job satisfaction (Besen et al., 2013; Carless & Arnup, 2011), whereas job satisfaction has been shown to be negatively impacted by important considerations such as work intensity (Iranmanesh et al., 2017). As such, a failure to account for a wide array of influential factors may impact the ability to detect meaningful relationships between the variables of interest in this study.
Results
Confirmatory Factor Analysis
As strong correlations between proximal perceptions were demonstrated (see Table 1 for variable descriptive statistics and intercorrelations), we tested a series of confirmatory factor analyses to demonstrate the distinctiveness of our measured variables following previous recommendations (Brown, 2006). We used the lavaan package (Rosseel, 2012) in R (R Core Team, 2020) and implemented maximum-likelihood estimation with robust standard errors. Model fit was assessed with the χ2 statistic, the comparative fit index (CFI), the Tucker-Lewis index (TLI), the standardized root mean square residual (SRMR), and the root mean square error of approximation (RMSEA). Hu and Bentler’s (1999) recommended cut-offs were used to evaluate model fit, with CFI and TLI exceeding 0.90, and SRMR and RMSEA below 0.08. The seven-factor model including the mediators and outcomes was compared with several alternative models by setting correlations between different combinations of latent factors equal to one; identified and alternative models were nested. We found that the seven-factor model demonstrated the best fit to the data compared to alternative models (Δχ2(1506) = 3222.35, p < 0.001, CFI = 0.92, TLI = 0.92, RMSEA = 0.05 [90% CI [0.05, 0.05]], SRMR = 0.06; see Appendix 2), therefore demonstrating that our constructs were distinct.
Latent Profile Analysis Results
A three-step approach (Asparouhov & Muthén, 2013) was used to examine the effects of perceived crisis response strategy on employee perceptions and distal outcomes. In the first step, we conducted LPA to identify unique strategy profiles. Next, profile assignments were made for each participant based on the posterior distribution of profile membership. In the third step, we used a regression-based approach to examine whether perceived strategy profiles predicted distal outcomes via proximal perceptions. Additionally, the impact of individual policies and procedures was assessed using relative weights analysis.
LPA was conducted using Mplus version 8.4 (Muthén & Muthén, 2019-2020). We considered the types of policies and procedures enacted, the number of individuals within each profile, and model fit to determine the number of meaningful perceived strategy profiles. Fit was assessed using the six indices recommended by Morin et al. (2017), and the Lo-Mendell-Rubin likelihood ratio test (LMR-LRT) and the bootstrapped likelihood ratio test (BLRT) statistics were used to compare adjacent models. In general, lower values of AIC, BIC, and SSA-BIC and higher Entropy values indicating greater profile separation are better (Lubke & Muthén, 2007). In comparing adjacent models, we used the LMR-LRT and BLRT statistics (Morin et al., 2017). Generally, a significant p value means that the examined model has a better fit than an adjacent model with one less profile. As SSA–BIC has been identified as the most accurate of these indices for LPA (Nylund et al., 2007), we prioritized SSA-BIC when interpreting model fit. Model fit indices were best for the five-profile model as it produced the lower SSA–BIC and BIC and as well as a significant BLRT and LMR-LRT (see Table 2). Although the five-profile model produced lower AIC values, one profile in this model was only a slight variation of one profile in the five-profile model and it had higher SSA–BIC and BIC. Thereby, based on those fit indices as well as parsimony and interpretability, we selected the four-profile model.Table 2 Fit statistics for profile structures
# of profiles LL AIC BIC SSA–BIC Entropy BLRT LMR_LR
2 − 2242 4518 4588.01 4534.05 0.83 665.58* 621.26*
3 − 2127.19 4306.39 4413.46 4330.94 0.82 229.61* 214.32*
4 − 2077.27 4224.53 4368.66 4257.59 0.83 99.86* 93.21*
5 − 2065.17 4218.33 4399.53 4259.89 0.85 24.2 22.59*
LL log-likelihood, AIC Akaike information criteria, BIC Bayesian information criteria, SSA–BIC sample-size-adjusted BIC, BLRT bootstrapped log-likelihood ratio tests, LMR_LR Lo-Mendell-Rubin likelihood ratio test. *p < .05
Average values for each of the policy and procedure categories across the four strategy profiles in this model appear in Table 3 and Fig. 2, which reveal the pattern of results across categories, therefore aiding in the interpretation and naming of each profile. For example, we labeled the first profile (reflecting 12% of the data) as an inactive response, as average values for all four dimensions of policies and procedures were low. We labeled the second profile (reflecting 39% of the data) as a human resource-disadvantaging response due to its highest score being for human resource-disadvantaging policies and procedures and its low scores for the other three categories. Some specific policies that characterize the human-disadvantaging response likely include introducing temporary pay decreases and expanding required work duties.Table 3 Descriptive information per latent profile
Profiles % of sample Human resource-supportive Human resource-disadvantaging Behavioral/interactional human safety and protection-focused Environmental and structural safety supports-focused
M SE M SE M SE M SE
Inactive response 12 − 1.66 0.06 − 1.03 0.09 − 1.39 0.22 − 1.46 0.23
Human resource-disadvantaging response 39 − 0.39 0.09 0.18 0.1 -0.38 0.1 -0.36 0.08
Safety and human resource-supportive response 15 0.43 0.16 − 0.54 0.14 0.24 0.1 0.62 0.11
Maximizing response 34 0.83 0.1 0.34 0.13 0.81 0.07 0.64 0.08
Mean scores on each of the four dimensions have been standardized to demonstrate the relative relationships among these dimensions
Fig. 2 Perceived crisis response profile average latent profile values across policy/procedure categories. The four perceived crisis response policy categories consisted of 17 items (human-resource supportive), 7 items (human-resource disadvantaging), 9 items (behavioral/interactional human safety and protection-focused), and 19 items (environmental and structural safety supports-focused). The inactive response was implemented by 12% of the sample, the human resource-disadvantaging response was implemented by 39%, the safety and human resource-supportive response was implemented by 15%, and the maximizing response was implemented by 34%. The standardized values provided on the vertical axis represent the level of each policy category within each profile. Given that four types of policy responses have different ranges of values, we standardized them before performing LPA for ease of interpretation and presentation. The use of standardized versus unstandardized values results in no differences in profile identification
We labeled the third profile (reflecting 15% of the data) as a safety and human resource-supportive response, as this strategy focused on more positive policies and procedures with less reliance on human resource-disadvantaging actions, such as introducing additional mental health benefits for employees and providing bonus pay. The fourth profile (reflecting 34% of the data) was termed a maximizing response, as these organizations employed policies and procedures from all four categories. Taken together, in answering RQ1, the data indicated that there are four distinguishable strategy profiles that typify the perceived crisis response styles enacted by healthcare organizations during COVID-19, which aligned with the aforementioned profile expectations.
Regression Results on Proximal Perceptions
To investigate H1, which expected that perceived crisis response strategies would predict proximal perceptions, PROCESS model 4 (Hayes, 2018) was used with 5000 bias-corrected bootstrapping estimates and a custom seed to ensure estimate stability across models. More specifically, four models were run, each testing a different dependent variable but including the same three mediators, perceived strategy profile as a multicategorical independent variable, and covariates. Relationships between proximal factors were accounted for, as all predictors, including the three mediators, were simultaneously regressed on the distal outcomes. All continuous variables were standardized, and the inactive response strategy profile was set as the referent class in response strategy comparisons. Following Lum et al.’s (1998) methodology, only significant demographic variables and covariates were retained in the final models. Each of these retained factors was correlated with at least one mediator or dependent variable, following Becker’s (2005) recommendation, thereby removing impotent control variables (i.e., unrelated to any outcome variable), which diminish power; Becker, 2005).1
First examining relations between perceived crisis response strategy and proximal perceptions, as demonstrated in Table 4, employees within organizations that were perceived to employ human resource-disadvantaging, safety and human resource-supportive, or maximizing responses reported higher perceptions of ethical leadership and safety climate compared to organizations that were perceived to be inactive. Likewise, organizational support perceptions were higher within organizations that were perceived to employ safety and human resource-supportive or maximizing responses than within organizations with perceived inactive responses.Table 4 Regression results for proximal perceptions
Variable Perceived ethical leadership Perceived organizational support Perceived safety climate
B SE B SE B SE
Covariates
Age .04 .04 .00 .04 − .07 .04
Work hours .03 .04 .00 .04 .04 .04
Work intensity − .23** .04 − .29** .04 − .19** .04
Job title .28* .09 .25** .09 .30** .09
Crisis response strategies
Human resource-disadvantaging response .36** .14 .26 .14 .68** .14
Safety and human resource-supportive response 1.05** .16 .85** .16 1.13** .17
Maximizing response 1.12** .14 .93** .14 1.21** .14
R2 = .26** R2 = .24** R2 = .21**
F = 22.24 F = 19.46 F = 16.82
Crisis responses strategy variables were dummy coded with the inactive crisis response profile serving as the reference group. Job title was coded: 0 = medical staff, 1 = non-medical staff. Non-significant control variables such as career tenure, patient interaction, and work facility type were removed from analyses to follow Lum et al.’s (1998) methodology of only retaining significant covariates. *p < .05; **p < .01
To examine whether other effects differed across active strategy profiles, a series of ANOVAs with Bonferroni-adjusted pairwise comparisons were conducted. Results indicated that effects in each of the three models differed (p < 0.01) across the human resource-disadvantaging and safety and human resource-supportive responses, but not between the safety and human resource-supportive and maximizing responses. Notably, although the safety and human resource-supportive and maximizing response strategy profiles demonstrated similar patterns of results, differences between these profiles were deemed non-negligible based on the BLRT results that suggested meaningful differences were present, as well as the fact that human resource-disadvantaging policy and procedure reliance differed across strategies (i.e., one profile had above-average and one below-average reliance on such policies and procedures).
These findings provide full support for H1, as the utilization of a safety and human resource-supportive response strategy and enacting a wide array of crisis response policies and procedures was positively related to perceptions of ethical leadership, organizational support, and safety climate. The regression results for distal effects are provided in Appendix 3.
Mediation Effects
To test H2, which expected that perceived crisis response strategy would impact distal outcomes via proximal perceptions, all three mediators were included simultaneously in each of the four models run to test each dependent variable. Results indicated that perceived ethical leadership mediated all three effects of perceived crisis response strategy variables on safety behavior (see Table 5). Likewise, POS served as a mediator in relations between both the safety and human resource-supportive and maximizing perceived crisis response strategies on all dependent variables. Perceived safety climate mediated each of the effects between perceived crisis response strategies and the four distal outcomes. All other effects were non-significant, thereby providing partial support for H2. As limited direct effects between perceived response strategies and distal outcome variables emerged (i.e., the only direct effects were between perceived crisis response strategies and work stress), the indirect effects highlight the critical role that proximal perceptions played in linking perceived response strategies and distal outcomes.Table 5 Indirect effects of perceived crisis response strategy on distal employee outcomes
Outcome Mediator Strategy Indirect effect Boot SE LL95%CI UL95%CI
Job satisfaction Perceived ethical leadership HR-disadvantaging − .03 .04 − .11 .03
Safety and HR-supportive − .10 .09 − .28 .07
Maximizing − .10 .09 − .29 .08
Perceived organizational support HR-disadvantaging .10 .06 − .01 .23
Safety and HR-supportive .32* .10 .15 .53
Maximizing .35* .11 .17 .57
Perceived safety climate HR-disadvantaging .21* .07 .09 .36
Safety and HR-supportive .35* .09 .18 .54
Maximizing .37* .10 .20 .57
Work stress Perceived ethical leadership HR-disadvantaging .03 .03 − .02 .10
Safety and HR-supportive .09 .08 − .07 .24
Maximizing .09 .09 − .08 .25
Perceived organizational support HR-disadvantaging − .06 .04 − .16 .01
Safety and HR-supportive − .20* .08 − .37 − .05
Maximizing − .21* .09 − .40 − .06
Perceived safety climate HR-disadvantaging − .09* .05 − .20 − .01
Safety and HR-supportive − .15* .07 − .31 − .02
Maximizing − .16* .08 − .32 − .02
Turnover intentions Perceived ethical leadership HR-disadvantaging .04 .04 − .02 .14
Safety and HR-supportive .11 .10 − .07 .31
Maximizing .12 .10 − .08 .33
Perceived organizational support HR-disadvantaging − .07 .05 − .19 .01
Safety and HR-supportive − .22* .10 − .42 − .05
Maximizing − .24* .10 − .46 − .05
Perceived safety climate HR-disadvantaging − .24* .08 − .40 − .11
Safety and HR-supportive − .40* .10 − .61 − .23
Maximizing -.43* .10 − .64 − .25
Safety behavior Perceived ethical leadership HR-disadvantaging .10* .05 .01 .23
Safety and HR-supportive .30* .10 .12 .51
Maximizing .32* .11 .13 .55
Perceived organizational support HR-disadvantaging − .05 .04 − .15 .01
Safety and HR-supportive − .17* .09 − .36 − .01
Maximizing − .18* .10 − .38 − .01
Perceived safety climate HR-disadvantaging .16* .07 .05 .30
Safety and HR-supportive .27* .09 .10 .46
Maximizing .29* .10 .10 .49
Crisis responses strategy variables were dummy coded with the inactive crisis response profile serving as the reference group. The three mediators were included simultaneously in each of the four models run, each testing a separate dependent variable. *p < .05
Relative Weights Analysis Results
To address RQ2, which questioned how specific perceived crisis response policies and procedures are linked to employee proximal perceptions and distal outcomes, multivariate relative weights analyses were conducted using the procedures recommended by Tonidandel and LeBreton (2011; see Appendix 1). Findings suggested that providing remote work options and implementing programs focused on employee morale may be particularly impactful human resource-supportive responses, whereas implementing employee travel restrictions and expanding required work duties were the most detrimental human resource-disadvantaging policies and procedures. Among behavioral/interactional human safety and protection-focused policies and procedures, implementing a COVID-19 prevention training program and utilizing remote communication between patients and staff were the most beneficial, and implementing a PPE and hygiene auditing process for personnel and frequently sanitizing equipment and clinical areas were the most beneficial environmental and structural safety supports-focused responses.
Discussion
This study investigated perceived strategic responses employed during the COVID-19 pandemic, as well as the impact of these responses on employee perceptions and work outcomes in order to provide information needed for rapid organizational action in future crises. Four distinct profiles of perceived crisis response strategies were identified, with the most prevalent profile being a human resource-disadvantaging response. These findings align with reports of actions taken by healthcare organizations during this study’s data collection period, such as widespread reductions of work hours and instituting furloughs (Paavola, 2020). As such, it is not surprising that employees perceived a disadvantaging response to be the most frequently implemented strategy, particularly when considering the severe financial pressure burdening organizations which required actions that were perceived as disadvantageous.
Notably, 35 of the 52 policies examined were enacted in over 50% of organizations, with those in the environmental and structural safety supports-focused category being implemented most frequently (see Appendix 1). However, some of the responses most likely to impact employee well-being and behavior were not as common as other less impactful policies and procedures. For instance, only 51.3% of respondents indicated that their employer implemented employee and patient COVID-19 prevention and control training, despite it being the most beneficial environmental and structural safety supports-focused procedure. Yet, 86.3% of respondents reported that their employer instituted visitor restrictions in patient areas, which was an important safety measure, but also one of the least impactful behavioral/interactional human safety and protection-focused responses. Such mismatches suggest that the prevalence of perceived policy implementation may not always translate directly into impacts on employee attitudes and behaviors.
In comparing the three active perceived crisis response strategies, results indicated that both the safety and human resource-supportive response and maximizing response profiles were linked to favorable proximal employee perceptions, with no meaningful differences between the two profiles. This suggests that perceived crisis response strategies are likely to have the greatest positive impact on employees when they include safety and positive human resource policies and procedures. These strategies resulted in more favorable outcomes than the human resource-disadvantaging approach, demonstrating that utilization of these positively perceived actions may offset the negative ramifications of enacting disadvantageous policies.
Notably, a few unexpected findings emerged, such as the positive link between the human resource-disadvantaging response and both ethical leadership and safety climate perceptions. As the data collection period was characterized by reports of hospital overcrowding and shortages (Bellware et al., 2020), participants were likely aware of their organization’s financial challenges, therefore perhaps perceived policies such as pay cuts and required overtime hours to be ethical and safe actions. Further, a negative relationship was found between POS and safety behavior, which may be similarly explained by the environment at the time in which organizations were perceived to provide support but were hindered by external factors such as PPE shortages, therefore POS may not have positively impacted safety behavior due to a lack of resources. Ethical leadership emerged as a mediator in the links between perceived crisis response strategies and safety behavior, but unexpectedly did not mediate relations with the other three distal outcomes, perhaps due to multicollinearity among the proximal variables.
Theoretical Implications
Several indirect effects demonstrated that greater perceived implementation of policies and procedures related to safety and human resource considerations was generally linked to more positive POS and perceived safety climate, which in turn had advantageous links to both employee well-being (i.e., job satisfaction and work stress) and behavioral outcomes (i.e., turnover intentions and safety behavior). These findings are consistent with the tenets of social exchange theory, as well as empirical work demonstrating that receiving support and beneficial treatment from organizations is likely to produce favorable organizational perceptions, improved well-being, and positive job behaviors (Caesens et al., 2017; Eisenberger et al., 1986, 1997; Kurtessis et al., 2017; Rhoades & Eisenberger, 2002).
Likewise, indirect effects in which perceived safety climate served as an intermediary are in line with extant workplace safety models (see, e.g., Beus et al., 2016) and empirical work (DeJoy et al., 2004), demonstrating the importance of safety policies and perceived safety climate in increasing safety behavior. Taken together, in line with theoretical expectations, the indirect effects demonstrated in this study extend these theories by highlighting how perceived crisis response strategies play a key role in the social exchanges between employees and organizations by providing cues that employees use to evaluate leader characteristics, organizational priorities, and work environment attributes.
Practical Implications
This study has several practical implications. Namely, developing a clearer understanding of approaches taken by organizations is beneficial, as policy perceptions were shown to be predictive of crucial employee judgments of their organization (e.g., POS), which, in turn, were found to predict worker attitudes and behaviors (e.g., turnover intent, safety behavior). This finding is paramount during this pivotal time in which healthcare worker safety is at risk and 22% of nurses have reported planning to leave their jobs in the next year (Berlin et al., 2021). As such, organizations could use such findings to implement policies that have been linked to key outcomes in an attempt to avoid negative worker attitudes and behaviors.
Further, as the perceptions employees form about the organization based on enacted policies play a crucial role in determining outcomes, organizations should clearly communicate new policies and the rationale behind them to employees in an attempt to encourage positive perceptions, thus potentially decreasing the likelihood of adverse outcomes. In addition, employees may be particularly averse to crisis management policies and procedures in which they perceive a loss, particularly within their personal lives (e.g., employee travel restrictions). Research demonstrating that negative phenomena can have a stronger impact than positive stimuli is robust (Baumeister et al., 2001). Yet, our findings indicate that negative salience effects in a crisis scenario may be softened by simultaneously implementing positively perceived policies and procedures.
Thus, in instances where policies that have been demonstrated to be detrimental to employee perceptions of social exchange with the organization are deemed necessary, implementation of a variety of resource-gain or safety-focused efforts may be particularly warranted to promote more balanced perceptions of the employee-organization social exchange relationships. Taken together, as organizational decision-making is often a complex process in which multiple considerations must be weighed (e.g., employee well-being, available resources), our findings can serve a prescriptive purpose by serving as a resource to help organizations make better decisions regarding the impact of perceived crisis response policies on employee well-being and behavior.
Limitations and Future Research Directions
Although this study has a number of strengths, we also acknowledge limitations. First, all data were collected from the same source, which increases the possibility of common method bias (Podsakoff et al., 2012). To mitigate this effect, we conducted time-lagged assessments of employee outcomes, which also allowed for a better understanding of effect directionality (Cole & Maxwell, 2003). However, given that policies and proximal perceptions were collected at the same time, temporal precedence is not established in the present effort; thus, causality cannot be inferred from our results. Future research could collect longitudinal data and examine the causal relationships among variables.
Further, given that our data consists of only two time points, future research could collect multi-wave longitudinal outcome data and examine how the profiles established in this effort may change or influence changes in various outcomes over an extended period of time. Relatedly, as our two waves of data collection were conducted only 30 days apart, more elapsed time may be necessary for enacted policies to impact employee outcomes. However, as there is evidence of healthcare organizations enacting policies as early as March 2020 (Grimm, 2020), it is possible that policies had been enacted for some time before we collected data on distal outcomes.
Additionally, it is possible that our policy measure may not have encapsulated all possible actions, especially uncommon approaches, thereby warranting more research on this topic. Further, to maintain participant confidentiality, respondents did not identify their employing organization, which precluded the examination of the collective perceptions and intraorganizational variability in reports of crisis response strategies at the organization level. Future work could collect multilevel data to investigate how shared perceptions (e.g., team safety climate perceptions) and perception variability of crisis response strategies influence organizational outcomes and exert trickle-down effects on individual outcomes.
This study focused on a single industry (i.e., healthcare), which could limit generalizability. However, as crises are especially common in healthcare organizations (Nemeth et al., 2011) and given the nature of the COVID-19 crisis, our focus on healthcare organizations seemed particularly necessary. As the policies examined in this effort were implemented in a variety of work sectors, such as introducing furloughs and pay cuts, we believe these results are likely to generalize to a number of work contexts outside of healthcare organizations.
As previous research has demonstrated that human resource practices also have the potential to impact customer satisfaction via their impact on the work climate (Rogg et al., 2001), future research should also examine the impact of perceived crisis response strategies on outcomes relevant to both patients/customers (e.g., satisfaction, trust) and potential employees (e.g., organizational attraction). In addition, examination of other relevant proximal perceptions (e.g., ethical climate perceptions) and distal outcomes (e.g., organizational commitment), as well as parallel effects (e.g., ethicality perceptions at both the leader and organizational level) would provide additional insight into who employees perceive as responsible for crisis responses.
Additional avenues include investigating potential moderators on the demonstrated relationships. For instance, culture may moderate the effects of crisis strategies on outcomes, with strategies employed in tight cultures (i.e., those with strict norms and a resistance to deviance) demonstrating stronger effects than loose cultures (i.e., those with flexible norms and receptive to deviance; Gelfand et al., 2011). In turn, team-member exchange or team trust could serve as moderators, with crisis strategies rendering stronger effects on outcomes when those factors are high. Thus, cultural context and team dynamics may influence crisis management strategy effectiveness.
In sum, this study sheds light on how organizations responded to the COVID-19 crisis, as well as how perceived response strategies during a large-scale crisis can impact employee outcomes. Thus, this paper not only contributes to the limited research on organizational crisis management impacts by highlighting the process by which employee attitudes and behaviors may be affected by perceived crisis response strategies, but it also provides prescriptive information that can aid organizational decision-makers.
Appendix 1
Table 6 Multivariate relative weights analyses and prevalence of each organizational crisis policy/procedure
Category Organizational crisis response R 2 %R 2 Rank Prevalence
Human resource-supportive Promoted programs focused on employee morale (e.g., providing free meals) 0.010 11.6 2 53.1%
Established a COVID-19 hotline for staff questions 0.007 8.7 3 59.3%
Offered free COVID-19 testing for employees and/or employee family members 0.007 7.9 4 50.1%
Provided PTO “loans” 0.006 7.5 5 26.7%
Provided additional employee mental health benefits (e.g., counseling, stress prevention programs) 0.006 7.4 6 61.7%
Implemented special policies for “high risk” employees (e.g., transfer to non-COVID unit, additional PTO) 0.005 6.3 7 47.2%
Increased telemedicine benefits* 0.005 6.2 8 61.9%
Implemented non-punitive sick leave policies that allow sick personnel to stay home 0.005 5.8 9 71.1%
Provided additional childcare support/financial assistance 0.004 4.8 10 38.1%
Implemented PTO for infected/symptomatic employees 0.004 4.2 11 65.4%
Provided non-critical employees an option to perform roles/tasks outside of normal duties (e.g., job rotation) 0.003 4.1 12 63.1%
Implemented full or partial PTO for unworked/missed/canceled hours 0.003 3.6 13 47.8%
Reactivated retired or separated employees 0.003 3.3 14 20.4%
Covered hotel costs for quarantining 0.002 2.6 15 21.7%
Introduced a temporary pay increase 0.002 2.1 16 11.0%
Provided bonus pay (excludes temporary wage increases) 0.002 2.0 17 17.6%
Total R2 0.09
Human resource-disadvantaging Implemented employee travel restrictions 0.015 40.1 1 62.1%
Expanded required work duties 0.005 13.7 2 51.1%
Implemented required furloughs/unpaid leave 0.005 13.1 3 39.2%
Eliminated overtime hours 0.004 11.3 4 32.2%
Introduced a temporary pay decrease 0.003 9.3 5 16.3%
Implemented required overtime hours 0.002 6.6 6 12.1%
Reduced work hours 0.002 6.0 7 44.6%
Total R2 0.04
Behavioral/interactional human safety and protection-focused Implemented a training program for personnel, patients, and their families concerning COVID-19 prevention and control measures* 0.019 25.8 1 51.3%
Implemented a process to allow for remote communications between the patients and staff (e.g., video call applications on phone or tablets)* 0.013 18.2 2 74.8%
Developed a written protocol for identifying, monitoring, and reporting COVID-19 among hospitalized patients, volunteers, and staff* 0.008 10.3 3 74.1%
Implemented regular employee COVID symptom/temperature screening* 0.007 10.1 4 82.2%
Designated a care team to take care of COVID-19 symptomatic patients 0.007 9.8 5 62.5%
Provided regular COVID-19 related updates (e.g., potential employee COVID-19 exposure) 0.007 9.3 6 83.3%
Posted signs instructing visitors to leave if they have a fever or are showing symptoms of respiratory infection* 0.005 6.6 7 84.3%
Implemented policies restricting all visitors in patient areas* 0.004 5.6 8 86.3%
Implemented policies allowing visitors to enter COVID-19 patient areas when safety precautions have been taken (e.g., wearing PPE, no touching, log of entry and exit)* 0.003 4.4 9 43.8%
Total R2 0.08
Environmental and structural safety supports-focused Implemented an auditing process for ensuring that personnel adhere to PPE and hygiene guidelines* 0.013 12.2 1 50.2%
Sanitized/cleaned equipment and clinical areas more frequently* 0.011 10.3 2 89.8%
Developed a process for adhering to recommended infection prevention and control practices (e.g., providing hand sanitizer in every patient room)* 0.009 7.9 3 86.1%
Reduced patient ratios in COVID-19 units* 0.008 7.5 4 58.4%
Created a multidisciplinary team or committee to address COVID-19 issues (e.g., preparedness, ethical issues) 0.007 6.7 5 81.3%
Provided training on ethical issues concerning how decisions will be made in the event that services require prioritization and allocation (e.g., decisions based on probability of survival) 0.006 5.4 6 41.6%
Provided training on donning and doffing PPE 0.006 5.2 7 78.0%
Developed a process for triage during the COVID-19 outbreak (e.g., supply PPE to patients showing respiratory symptoms, instructions on prioritization of patients) 0.005 5.0 8 82.3%
Introduced a requirement to change clothes/shoes at work arrival and/or departure 0.005 4.4 9 20.0%
Increased the frequency of air exchange* 0.005 4.4 10 37.3%
Imposed strict limits on PPE use 0.005 4.3 11 67.5%
Introduced a strategy for continuing to provide required non-COVID-19 care (e.g., chronic illnesses, emergency services)* 0.005 4.2 12 82.6%
Established criteria for employee COVID-19 testing 0.004 4.0 13 76.7%
Developed plans for shifting healthcare services away from the hospital (e.g., home care)* 0.004 3.9 14 54.5%
Established a process for tracking and allocating PPE and equipment 0.004 3.8 15 71.4%
Quarantined symptomatic patients to specific locations in the facility* 0.003 3.0 16 81.7%
Re-used/re-sterilized PPE 0.003 2.8 17 76.4%
Used methods of communication (e.g., signs) to notify incoming people about the presence of COVID-19 in the facility* 0.003 2.5 18 63.0%
Made determinations of critical (e.g., intensive care unit) vs. non-critical (e.g., dental unit) employees 0.003 2.4 19 65.6%
Total R2 0.11
R2, or the raw relative weight, refers to raw variance explained. %R2, or the rescaled relative weight, refers to the estimates of relative weight using the metric of percentage of predicted variance accounted by each policy. Rank refers to the relative importance of each item in predicting all proximal and distal outcomes simultaneously. Prevalence refers to the percentage of respondents who indicated that the stated policy was enacted in their organization. *denotes policies oriented towards both employees and patients
Appendix 2
Table 7 Confirmatory factor analyses
Model χ 2 df χ2 diff CFI TLI RMSEA[90%CI] SRMR
Model 1: Seven factors 3222.35*** 1506 - 0.92 0.92 0.05[0.05, 0.05] 0.06
Model 2: Six factor (perceived ethical leadership + perceived safety climate) 3903.32*** 1507 680.98*** 0.89 0.88 0.06[0.06, 0.06] 0.07
Model 3: Six factor (perceived organizational support + perceived safety climate) 3792.30*** 1507 569.96*** 0.89 0.89 0.06[0.06, 0.06] 0.07
Model 4: Six factor (perceived ethical leadership + perceived organizational support) 3596.49*** 1507 374.15*** 0.90 0.90 0.06[0.05, 0.06] 0.07
Model 5: Six factor (job satisfaction + safety behavior) 3932.87*** 1507 710.52*** 0.89 0.88 0.06[0.06, 0.06] 0.10
Model 6: Six factor (turnover intentions + safety behavior) 3575.12*** 1507 352.78*** 0.90 0.90 0.06[0.05, 0.06] 0.08
N = 454. ***p < 0.001; POS = perceived organizational support; χ2 = Chi-square statistic; df = degrees of freedom; CFI = the comparative fit index; TLI = the Tucker-Lewis index; AIC = Akaike information criterion; BIC = Bayesian information criterion; RMSEA = the root mean square error of approximation; SRMR = the standardized root mean square residual. The seven factor model includes ethical leadership, organizational support, safety climate, job satisfaction, turnover intentions, work stress, and safety behavior as seven distinct factors, with the subsequent models testing the fit of a reduced number of factors by combining any two out of those seven variables
Appendix 3
Table 8 Regression results for distal outcomes
Variable Job satisfaction Work stress Turnover intentions Safety behavior
B SE B SE B SE B SE
Covariates
Age 0.17** 0.04 -0.08* 0.04 -0.15** 0.04 0.24** 0.04
Work hours 0.05 0.04 0.09* 0.04 0.06 0.04 0.09 0.05
Work intensity -0.15** 0.04 0.47** 0.04 0.12** 0.04 -0.01 0.05
Job title -0.23* 0.08 0.04 0.08 0.16 0.09 0.00 0.09
Crisis response strategies
Human resource-disadvantaging response -0.21 0.13 0.30* 0.13 0.12 0.14 -0.36* 0.15
Safety and human resource supportive-response -0.21 0.15 0.34* 0.15 0.12 0.17 -0.30 0.18
Maximizing response -0.19 0.14 0.38** 0.14 0.22 0.15 -0.31 0.16
Proximal perceptions
Ethical leadership -0.09 0.08 0.08 0.08 0.11 0.08 0.28** 0.09
POS 0.38** 0.08 -0.23** 0.08 -0.25** 0.09 -0.20* 0.09
Safety climate 0.31** 0.06 -0.14* 0.06 -0.35** 0.07 0.24** 0.07
R2 = 0.40** R2 = 0.41** R2 = 0.29** R2 = 0.17**
F = 29.34 F = 30.25 F = 17.63 F = 8.91
Crisis responses strategy variables were dummy coded with the inactive crisis response profile serving as the reference group. Job title was coded: 0 = medical staff, 1 = non-medical staff. * p < 0.05. ** p < 0.01
Data Availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author upon request.
Declarations
Ethics Approval
The questionnaire and methodology for this study was approved by the Human Research Ethics Committee of The University of Texas at Arlington (Protocol #2020–0644).
Consent to Participate and Publish
Informed consent was obtained from all individual participants included in the study, indicating that participants consented to both participation in the study and publication of results without naming them as participants.
Conflict of Interest
The authors declare no conflict of interest.
1 On an exploratory basis, these analyses were conducted without the covariates to confirm the results. The results were virtually identical, therefore the analyses including the covariates are reported here, following previous recommendations in such instances (Atinc et al., 2012; Becker, 2005; Carlson & Wu, 2012).
Amber Schroeder is now affiliated with Amazon. All activities relating to this article were completed prior to the changes in affiliation.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Bangal Kedar 1
PVS Prakash 4
Patangi Sanjay Orathi 5
1 grid.416504.2 0000 0004 1796 819X Dept of Cardiac Anaesthesiology, Narayana Institute of Cardiac Sciences, Narayana Hrudayalaya, Narayana Health City, Bangalore, 560099 Karnataka India
2 grid.17635.36 0000000419368657 University of Minnesota, Minneapolis, USA
3 Narayana Hrudayalaya Institute of Allied Health Sciences, #258/A, Bommasandra Industrial Area, Anekal Taluk, Bangalore, 560099 Karnataka India
4 grid.416504.2 0000 0004 1796 819X Perfusion Department, Narayana Institute of Cardiac Sciences, Narayana Hrudayalaya, Narayana Health City, Bangalore, 560099 Karnataka India
5 grid.416504.2 0000 0004 1796 819X Cardiac Critical Care Services, Narayana Institute of Cardiac Sciences, Narayana Hrudayalaya, Narayana Health City, Bangalore, 560099 Karnataka India
7 12 2022
110
16 11 2021
12 11 2022
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Extracorporeal membrane oxygenation (ECMO) is a modality utilized for partially or completely supporting the cardiac and/or pulmonary function. There are multiple vascular access techniques depending upon the necessity and the mode of ECMO used. ECMO has evolved over the years as an integral part of the cardiac care discipline. Historically, this lifesaving modality began as an extension of cardiopulmonary bypass and was associated with adverse outcomes. Currently, ECMO has evolved as an accepted and viable solution to patients with severe cardiac/respiratory/cardiorespiratory failure that is refractory to conservative management. The outcomes of patients on ECMO are dependent on multiple factors originating from demographic and pathophysiological status of patients as well as the control of homeostasis during ECMO within the acceptable range. Various studies have been published by many practitioners over past decades since the dawn of ECMO era. A brief review of such experience is summated, and a conclusion is derived about the clinical course of the patients on ECMO, while adding the author’s experience about the same in a tertiary care large-volume center.
Keywords
ECMO
Lifesaving
Cardiac
Pulmonary
Vascular
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pmcIntroduction
Extracorporeal membrane oxygenation (ECMO) is an advanced modality used to support the failing heart, lungs, or both. The support may be partial or full depending on the status of the cardiorespiratory function. Vascular access may be achieved centrally, peripherally, or as a hybrid technique. Over time, ECMO has evolved as an offshoot of cardiac surgery and has become an integral part of cardiac care where advanced and high-risk cardiac surgeries and interventional cardiology procedures are performed. Additionally, ECMO is an essential component of intensive care units where its use is indicated in severe respiratory failure that does not respond to conventional therapy. ECMO may be used as a bridging therapy (bridge to decision, bridge to recovery, and bridge to transplantation). Finally, ECMO may be used to facilitate resuscitation of the patients who are in refractory cardiac arrest; this is called extracorporeal cardiopulmonary resuscitation (ECPR).
History
Gibbon in 1953 had successfully utilized cardiopulmonary bypass (CPB) for the first time for the correction of atrial septal defect (ASD) using a screen oxygenator [1]. The first documented use of ECMO, a membrane oxygenator in a patient with severe respiratory failure following trauma, was performed by Hill and associates in 1972 [2]. In 1975, Dr Robert Bartlett successfully used ECMO to treat a new-born patient following respiratory failure secondary to meconium aspiration [3]. In 1989, the Extracorporeal Life Support Organization (ELSO) was founded in Michigan by Robert Bartlett and his associates. ECMO in India was first reported by K. V. Surendranath, D. P. Shetty, and team from BM Birla Heart Research Centre in Calcutta in December 1991 in a paper entitled “Long Term Cardiopulmonary Support in Children.”[4] The ELSO Society of India (ESOI) was established in India in 2010 for improving the awareness of ECMO in India. In 2013, the South and West Asia Chapter (SWAC) was incorporated by ELSO, and in 2015 Africa was added to SWAC making it the South and West Asia, Africa Chapter of ELSO (SWAAC) [5].
Landmark Trials
Zapol and associates published a trial in 1979 performed in 90 patients with acute respiratory failure (ARF) that demonstrated lack of long-term survival with the use of ECMO in patients with severe ARF. However, there were many limitations like the usage of the standard ventilation technique (high tidal volume and low PEEP), lack of guidelines on anticoagulation, patient selection, along with the use of veno-arterial (VA)-ECMO instead of veno-venous (VV)-ECMO [5]. The concept of extracorporeal removal of CO2 was put forth by Gattinoni and colleagues during 1980s in a series of publications. This technique was used with a combination of low-frequency, intermittent positive-pressure ventilation with a view to permit lung rest in patients with severe respiratory failure in conjunction [6, 7].
There has been a remarkable increase in the use of ECMO globally in the recent past: this is attributable to two important publications. Firstly, the Conventional Ventilatory Support Versus Extracorporeal Membrane Oxygenation for Severe Adult Respiratory Failure (CESAR) trial in 2009 supported the use of ECMO in specialized centers for patients with potentially reversible severe respiratory failure. The severity of respiratory failure was based on the derivation of the Murray Score that used four criteria, namely PaO2/FiO2 ratio, positive end-expiratory pressure (PEEP), dynamic lung compliance, and the number of quadrants infiltrated on the chest radiograph. A Murray Score greater than 3.0 was the main criterion institution of ECMO in addition to respiratory acidosis with a pH lower than 7.20. The CESAR trial showed an improvement in survival: 63% versus 43% by conventional treatment [8]. Its limitations were that there was no standard protocol for ventilatory management in the control group, whereas the ECMO group was managed with lung protective ventilation. Zapol and associates published a trial in 1979 performed in 90 patients with acute respiratory failure (ARF) that demonstrated lack of long-term survival with the use of ECMO in patients with severe ARF. However, there were many limitations like the usage of standard ventilation technique (high tidal volume and low PEEP), lack of guidelines on anticoagulation, patient selection, along with the use of veno-arterial (VA)-ECMO instead of veno-venous (VV)-ECMO [9]. The second publication that endorsed the use of ECMO in respiratory failure was the 2009 influenza A (H1N1) pandemic; the “ANZ-ECMO” was a case series published from Australia and New Zealand about the use of VV-ECMO in patients with ARDS, which showed a survival of 79% at 30 days [10]. This resulted in a dramatic increase in this use of VV-ECMO all over the world as a rescue therapy for patients with severe respiratory failure unresponsive to conventional therapy that included mechanical ventilation. However, the “ECMO to Rescue Lung Injury in severe ARDS” (the EOLIA) study demonstrated that in patients with very severe ARDS, 60-day mortality was not significantly lower with ECMO than with a strategy of conventional mechanical ventilation that included ECMO as rescue therapy [11]. In the EOLIA trial, indications for the use of VV-ECMO were patients with very severe ARDS, with by one of three criteria: (i) a ratio of partial pressure of arterial oxygen (PaO2) to the fraction of inspired oxygen (FiO2) of less than 50 mmHg for more than 3 h; (ii) a PaO2:FiO2 of less than 80 mmHg for more than 6 h; or (iii) an arterial blood pH of less than 7.25 with a partial pressure of arterial carbon dioxide of equal to or greater than 60 mmHg for more than 6 h. VV-ECMO has been used for many years in treating ARDS and is now the widely used therapy for supporting patients awaiting lung transplantation for interstitial lung disease, cystic fibrosis, aspiration pneumonitis, and most recently for COVID-19 ARDS. Raleigh and associates have demonstrated from 10 studies that the use of ECMO in the pre-transplant period does not affect the post-transplant outcome compared to those who did not require ECMO [12]. However, Brodie et al. have highlighted that the role of extracorporeal life support in the management of adults with acute respiratory failure is being redefined by advances in technology and increasing evidence of its effectiveness. Future developments in the field will result from technological advances, an increased understanding of the physiology and biology of extracorporeal support, and increased knowledge of how it might benefit the treatment of a variety of clinical conditions [13].
Indications of VA-ECMO and VV-ECMO
VV-ECMO
VV-ECMO should be taken into consideration in patients with potentially reversible severe acute respiratory failure that is refractory to optimal conventional management. The indications for VV-ECMO may be conveniently categorized into (i) pathophysiologic criteria, (ii) criteria based on scoring systems, and (iii) specific clinical conditions. The pathophysiological criteria for initiation of ECMO are (i) hypoxemic respiratory failure (PaO2/FiO2 ratio < 80 mmHg despite optimal management including a trial of prone position (ii) hypercapnic respiratory failure with PaCO2 > 60 mmHg and pH < 7.25 despite optimal ventilatory management.
Specific indications for VV-ECMO other than respiratory failure in ARDS alluded above include severe air leak syndromes, for CO2 retention in mechanically ventilated patients despite a high (> 30 cm H2O) plateau pressure (Pplat), and for miscellaneous patient conditions such as airway support in a patient listed for lung transplantation and a patient with acute respiratory failure unresponsive to optimal care. The indications and contraindications of VV-ECMO and VA-ECMO are detailed in Tables 1 and 2.Table 1 Indications for ECMO
VA-ECMO VV-ECMO
1. Refractory cardiogenic shock* 1. Severe ARDS
2. Combined cardiorespiratory failure 2. Severe pneumonia/acute eosinophilic pneumonia
3. Failure to wean from CPB 3. Severe asthma
4. Bridge to ventricular assist device and/or transplantation 4. Thoracic trauma
5. Unstable/refractory arrhythmias 5. Aspiration pneumonitis
6. Cardiac arrest without return of spontaneous circulation (ECPR) 6. Inhalational injury
7. Massive pulmonary embolism 7. Air-leak syndromes
8. Before and/or after lung transplant
(peri-lung transplant)
9. Bridge to recovery or transplantation
10. Diffuse alveolar/pulmonary hemorrhage
* (based on SHOCK trial, 1999): (i) SBP < 90 mmHg or vasopressor support to maintain SBP > 90 mmHg; (ii) evidence of end-organ damage (urine output < 30 mL/h, cool extremities); (iii) hemodynamic criteria: CI < 2.2 L/min/m2, PCWP > 15 mmHg; VA veno-arterial, VV veno-venous, ARDS adult respiratory distress syndrome, CPB cardiopulmonary bypass, ECPR extracorporeal cardiopulmonary
Table 2 Contraindications to ECMO
Absolute Relative
Acute intracranial hemorrhage Advanced age
Massive stroke Contraindications to anticoagulation
Active bleeding Morbid obesity
Malignancy End-stage liver disease
Severe aortic insufficiency/aortic dissection (for VA-ECMO)
immunosuppression
Mechanical ventilation for more than 7 days with Pplat > 30 cm H2O and FiO2 > 90%
Types and Techniques of ECMO
ECMO consists of two major types—veno-arterial (VA) ECMO and veno-venous (VV) ECMO (Fig. 1). There are further two subtypes in VA-ECMO—central and peripheral.Fig. 1 Types of extracorporeal membrane oxygenation (ECMO) techniques
VA-ECMO provides rest to the heart by taking over the function of the heart perfusing the body. VV-ECMO provides rest to the lung by providing oxygenation and carbon dioxide removal. In VA-ECMO, the machine draws deoxygenated blood from the systemic venous circulation, oxygenates the blood, and supplies oxygenated blood to the systemic arterial circulation for perfusion to the whole body. This is achieved by placing cannula in the right atrium (RA) for the purpose of drawing the blood and placing another cannula in the ascending aorta for returning the blood. This is called central VA-ECMO. In peripheral VA-ECMO, one drainage cannula is inserted in the right femoral vein, the tip of which is positioned at the level of the right atrium, whereas the return cannula is inserted in the right femoral artery with the tip residing in the common iliac artery (please see Fig. 2).Fig. 2 Veno-arterial (VA) ECMO: (A) The venous drainage cannula inserted via the internal jugular vein into the right atrium; the arterial return cannula inserted via the carotid artery. (B) The venous drainage cannula inserted via the femoral vein into the mid RA and the arterial return cannula is inserted via the femoral artery. (C) Central VA ECMO: the venous drainage cannula inserted in the RA and the arterial return cannula inserted in the aorta
In VV-ECMO, three different configurations of cannulation are possible (please see Fig. 3): (i) femoro-jugular: the drainage cannula is inserted in the right femoral vein and advanced until the inferior vena cava-right atrium (IJV-RA) junction, and the return cannula is inserted in the right internal jugular vein (IJV) and advanced until the mid-RA; (ii) femoro-femoral: the drainage and return cannulae are inserted in femoral veins on either of the sides. The drainage cannula is advanced until the proximal IVC, while the tip of the other one, the return cannula, is advanced until the mid-RA. The return cannula may be in the same femoral vein as the drainage cannula, or it may be in the contralateral femoral vein. (iii) Dual lumen cannula: VV-ECMO may also be configured using a dual lumen cannula with one lumen draining blood from the inferior vena cava (IVC) and the superior vena cava (SVC). The oxygenated blood is returned to the RA through the other lumen with the opening of the return cannula facing towards the tricuspid valve. Transesophageal echocardiography (TEE) is useful in identifying the jet of blood directed towards the tricuspid valve. Hypoxemia during VV-ECMO may be due to one of the following reasons: (i) when patient’s cardiac output is greater than the ECMO flow, ECMO run may be associated with inadequate tissue oxygen delivery; in this instance, the ECMO flows can be increased in an attempt to increase/normalize oxygen delivery: consumption ratio of up to 5:1 but certainly above the critical threshold of 2:1; (ii) increased metabolic demand due to sepsis, fever, agitation, shivering, etc.; (iii) recirculation which refers to oxygenated blood from return cannula reaching the drainage cannula without entering the right ventricle due to the proximity of the cannulae in the RA. This leads to poor gas exchange. This may be identified by oxygenated bright red blood issuing out of the drainage cannula. This may be avoided by ensuring that the tips of the drainage and return cannula are at least 10 cm apart.Fig. 3 (A) Peripheral venous (VV) ECMO: The venous drainage cannula is inserted via the femoral vein into the IVC, tip positioned at the IVC-RA junction. The oxygenated blood is returned via the cannula inserted into the contralateral femoral vein and positioned in the mid RA. (B) Peripheral VV-ECMO: The venous drainage cannula inserted via the femoral vein and positioned at the IVC-RA junction and the oxygenated blood is returned through the cannula inserted via the internal jugular vein and positioned in the mid RA. (C) VV-ECMO by dual lumen cannula: The dual lumen cannula with multiple orifices is inserted via the internal jugular vein and positioned such that the orifices in the SVC and IVC. The oxygenated blood is returned through the same cannula via another lumen that opens and faces the tricuspid valve. The oxygenated blood is thus directed towards the tricuspid valve into the RV
In cases of femoral VA-ECMO, two major problems relating to circuit/ECMO run may be encountered. (i) When the native heart recovers function with lungs yet to recover, the upper body may be perfused with deoxygenated blood emanating from the heart due to cardiac contraction. This leads to upper body being perfused with relatively deoxygenated blood whereas the lower parts of the body receive oxygenated blood. This is termed north/south or Harlequin syndrome. In such a case, an additional cannula is inserted in the right IJV that is connected to the arterial return cannula though a Y-connector. The oxygenated blood passes through the pulmonary circulation and returns to the left atrium and then to the left ventricle (LV), thus passing to the aorta; thus, the upper body gets perfused with adequately oxygenated blood. This configuration is called VAV-ECMO (Fig. 4). (ii) Left ventricular distension occurs in patients on VA-ECMO as a result of inability of the aortic valve to open in the setting of an increase in the afterload and decreased cardiac contractility, additionally myocardial blood flow from the Thebesian veins and bronchial blood return, and most importantly systemic venous return that is not captured by the ECMO venous cannula. This calls for strategies to unload the LV such as placement of LA vent, LV apical venting, atrial septostomy, or use of an intra-aortic balloon pump or Impella.Fig. 4 (A) VAV ECMO: The venous drainage cannula is inserted via the femoral vein and positioned at the IVC-RA junction and the arterial cannula inserted in the femoral artery. Additionally, a cannula supplying oxygenated blood is inserted using a Y-connector in the internal jugular vein to the RA; this is a treatment strategy for Harlequin syndrome. (B) V-PA ECMO: The venous drainage is via the internal jugular vein and the oxygenated blood is returned to the pulmonary artery; this strategy is used for patients with isolated right ventricular failure
In V-PA ECMO, the return cannula is placed in the main pulmonary artery using a graft, and a venous drainage cannula is either placed in right IJV or any one of the femoral veins. Alternatively, a dual lumen inflow cannula can be placed that drains simultaneously from the IVC and SVC. Yet another technique is where a cannula is placed via the right IJV with its inflow (venous drainage) ports in the RA and its tip with the outflow port resides in the main pulmonary artery.
The Seldinger technique is used for percutaneous cannulation using a guidewire and serial dilatations or a surgical cutdown is done followed by insertion of the cannulae. In the author’s institute, surgical cutdown is the preferred method and in non-emergency situations, a graft is placed over the femoral artery to attach the outflow cannula to avoid limb ischemia.
Outcomes of ECMO
Survival
ECMO is an invasive therapeutic modality for resuscitation of patients with severe cardiac, respiratory, or cardiorespiratory failure. Despite its increased utilization, ECMO may be associated with many adverse effects and complications. The ELSO registry showed decreased survival as the treatment duration increases [14]. Duration of VA-ECMO therapy amongst survivors and non-survivors was quoted to be similar in one study [15]. Smith et al. concluded that survival was poor in patients who were weaned early, and survival was also poor in patients with a long ECMO run. This suggests timing of weaning is crucial to have good outcome [16]. Survival decreases after ECMO therapy crosses 14 days due to the disease process and treatment complications adding a cumulative effect [17]. There is no effect on mortality with increased duration of VV-ECMO per se [18, 19].
Scoring
Survival after VA-ECMO can be predicted by means of survival after VA-ECMO (SAVE) score developed by ELSO in conjunction with the intensive care department of Alfred Hospital, Melbourne, in 2015 [20]. This score takes into consideration age, diagnosis, cardiac and respiratory vital parameters, renal function, and other organ functions like the central nervous system and liver function. It has a good predictive capability with area under the receiver operating characteristic curve of 0.68 (95% confidence interval: 0.64–0.71).
Complications of ECMO
Complications during ECMO can be broadly categorized into (i) circuit-related (technical) and (ii) patient-related.
Circuit-Related Complications
Circuit-related complications are (i) thrombosis: this is the most common complication that can have devastating effects: precise anticoagulation and constant vigilance are needed to avoid clotting in the ECMO circuits; (ii) circuit fracture may occur due to excessive pressure generation in the circuit; this will lead to sudden exsanguination of the patient and immediate replacement of the affected portion of the circuit or the entire apparatus may be necessary; (iii) gas embolism is an abrupt entrainment of air leading organ ischemia or a devastating air-lock leading to stoppage of circulation and is usually due to the creation of a significant negative pressure and air entrainment in the circuit. (iv) Cavitation, in which gas is forced out of the liquid medium by a circuit obstruction, can also lead to gas embolism.
Patient-Related Complications
Neurologic Derangements
The literature has cited a vast myriad of neurological issues with the use of ECMO [21]. The causative factors for neurological derangements are microemboli, hypocapnia, cerebral hypoperfusion, and loss of cerebral autoregulation. In the neonatal age group, with VV-ECMO, the incidence of clinical seizures is 9% while that of intracranial hemorrhage is 7.4%. In the pediatric VV-ECMO group, the incidence of clinical seizures is 5.2% while that of intracranial hemorrhage is 6.2%. In adult patients, the data show a lower incidence of neurologic complications with VV-ECMO compared with VA ECMO. According to cumulative ELSO data, adult VV-ECMO patients have a 1.0% incidence of clinical seizures and a 3.8% incidence of intracranial hemorrhage. Adults on VA ECMO have a 1.7% incidence of seizures and a 2.4% incidence of intracranial hemorrhage.
Hemorrhage
Bleeding is the most common complication of ECMO particularly from cannulation sites due to systemic anticoagulation [22]. Bleeding is known to occur in the gastrointestinal tract, brain, and intrapulmonary and retroperitoneal space [23, 24]. It is thus, important to closely monitor the heparin dosage, activated clotting time (ACT), and activated partial thromboplastin time (aPTT) of patients on ECMO. Risk factors for hemorrhage in patients on ECMO are pre-ECMO cardiac arrest, sepsis, renal replacement therapy, influenza, hemolysis, and thrombocytopenia [25]. Arterial cannulation in VA-ECMO presents a higher bleeding risk compared with venous cannulations used in VV-ECMO.
Infection
The prevalence of hospital acquired infections in patients on ECMO is 10–12% with coagulase-negative Staphylococcus being the major culprit, followed by Candida, Pseudomonas aeruginosa, and Enterobacteriaceae [26]. The infection risk increases with duration of ECMO utilisation. Other factors like translocation of gut bacteria, ECMO-related impairment of immune system, colonisation of oxygenator, catheters, and cannulae are also other aetiologies [26]. Bizzaro et al. and Schmidt et al. have found that the rate of infection is directly related to the duration of ECMO therapy [27, 28].
Renal Dysfunction
Makdisi et al. have demarcated phases of renal performance of patients receiving ECMO support. They have stated that the first 24 to 48 h is the oliguric phase which occurs due to inflammatory response of the body. This is followed by a diuretic phase [29]. Continuous renal replacement therapy (CRRT) is utilized to maintain fluid balance on ECMO. Kielstein et al. have demonstrated that survival is reduced in patients requiring CRRT when on ECMO [30].
Extracorporeal Cardiopulmonary Resuscitation (ECPR)
ECPR, the adjunctive use of ECMO in routine CPR, is recognized by the American Heart Association (AHA) and the European Resuscitation Council (ERC) [31–33]. Zakhary et al. have found in their study on 75 patients with in-hospital and out-of-hospital cardiac arrest (OHCA) that 39% patients were successfully weaned from ECMO and 31% survived until hospital discharge amongst them [34]. Holmberg et al. in their review on ECPR included 25 observational studies including OHCA and in-hospital cardiac arrests. They found that, in spite of the increasing use of ECMO support over the past decade, the availability of ECPR is still lacking for OHCA. OHCA patients need to rely on rapid transportation to ECPR capable hospitals. According to them, there were no guidelines for the initiation of ECPR, confounders have not been adjusted, and vague accounting of past medical history of comorbidities like renal function or cardiac function of the patients exist [35]. With increasing utilisation of ECMO, for various indications there must exist clear guidelines about the initiation and termination of ECMO. It is required to define the inclusion and exclusion criteria for pediatric and adult patients who may need ECMO due to pulmonary or cardiac problems. The author has also commented that, there is a necessity of establishing a timing of the commencement of ECMO to avoid any doubt about occurrence of a delay in treating the patients and affecting their outcomes [36]. Table 3 shows the current criteria for ECPR.Table 3 Criteria for ECPR
Witnessed arrest
Arrest to first CPR (“no-flow interval”) < 5 min
Initial cardiac rhythm of VF/pVT/PEA
Arrest to ECMO flow < 60 min “low flow interval*
Good-quality CPR with ETCO2 > 10 mmHg before cannulation for ECMO
Intermittent ROSC or recurrent VF
“Signs of life” during conventional CPR
The absence of severe comorbidities/malignancy
No known aortic valve regurgitation
ECPR, ECMO cardiopulmonary resuscitation; CPR, cardiopulmonary resuscitation; VF, ventricular fibrillation; pVT, pulseless ventricular tachycardia; PEA pulseless electrical activity; ETCO2, end-tidal carbon dioxide; ROSC, return of spontaneous circulation
Maintenance on ECMO
Care of patients on ECMO need a multitude of health care professionals who understand the physiology of this form of therapy. At the bedside, a nurse and a perfusionist are available 24/7 to monitor the patients. In the author’s institute, lung protective ventilation is preferred for intubated patients on VV-ECMO. Those patients who are suspected to require prolonged ventilation may be tracheostomized. Patients are extubated if and when suitable. Arterial blood gas, flows, rotations per minute, sweep gas flow, and pre and post oxygenator membrane pressure are monitored periodically. The pre and post oxygenator partial pressure of oxygen is monitored to keep a track of oxygenator performance. Feeding is recommended that is monitored by a dietician. Renal replacement therapy is instituted as required.
Monitoring
Monitoring during ECMO is crucial. Monitoring will encompass technical aspects of ECMO (pre and post pump pressures and deltaP) and patients’ physiological status. This entails invasive monitoring such as arterial blood pressure (BP), central venous pressure (CVP), pulmonary artery pressure (PAP) and pulmonary capillary wedge pressure (PCWP). The arterial pressure waveform provides information about mean arterial pressure and pulsatility. Invasive BP monitoring also provides an access for sampling for arterial blood gas analysis. Anticoagulation on ECMO is achieved by unfractionated heparin (UFH) and the options for monitoring are by means of activated clotting time (ACT), activated partial thromboplastin time (aPTT), and factor Xa assay. It is very important to monitor anticoagulation on ECMO, to prevent thrombotic complications, circuit clotting, and hemorrhage. The adverse effects of UFH are heparin-induced thrombocytopenia (HIT) of which there are 2 types—HIT 1 and HIT 2. It needs to be detected early, and the patient should be switched to other anticoagulants like argatroban or bivalirudin [37]. It is very important to monitor for infection when the patient is on ECMO using a protocolized approach on the basis of culture/sensitivity reports.
Weaning
Weaning from ECMO is a very complex task that requires multidisciplinary involvement. The approach to weaning will be dictated by echocardiographic parameters, lowering serum lactate levels, and adequate mixed venous oxygen saturation levels in VA-ECMO. In VV-ECMO, reduction of sweep gas to maintain acceptable gas exchange with radiological clearance will be a necessary prerequisite. Ventilation is set to provide adequate gas exchange along with escalation of inotropes. Once it is confirmed that the cardiorespiratory function is adequate, the ECMO is weaned off in OR/ICU followed by decannulation. Inability of the heart to exhibit adequate function warrants continuation of ECMO. This is considered as a failure to wean off ECMO. Alternatively, a technique termed as “AV-bridge” is utilized in ICU. Patients on VV-ECMO are weaned when the pulmonary physiology of the patient allows adequate oxygenation and carbon dioxide removal with minimal lung protective ventilation by reducing the sweep gas flow. Arterial blood gas monitoring is done hourly or half hourly during this process. Importance has been given to the presence of a cardiac anesthesiologist in an ECMO team for initiating and managing an ECMO inside and outside the hospital and transferring the patient on ECMO support [38]. European consensus is also in favor of a strong role of a cardiac anesthesiologist in an ECMO team [39]. Transesophageal echocardiography (TEE) helps in correct positioning of the ECMO cannulae and assessing the cardiac function [40].
Cost of ECMO
The cost of receiving ECMO support varies from region to region. In the USA, the mean charges range from USD 154,215 to USD 868,979 [41]. Tseng and associates, from Taiwan, have provided a breakdown of total hospital costs where 41% were spent on personnel, 26% on disposable items, 13% on medications, 10% on laboratory and radiological tests, 8% on blood products, and 2% on renal replacement therapy [41]. Dennis et al. have mean hospital costs in Australia for OHCA that were USD 42,658 and for IHCA they were USD 62,700 [42]. Jӓӓmaa-Holmberg et al. have stated in their study that the costs vary according to diagnoses for which the patients received ECMO therapy and they have provided the charges encountered according to the diagnosis [43]. The charges ranged from USD 63,271 to USD 126,605.
ECMO Experience at Narayana Institute of Cardiac Sciences
The details of experience from the author’s institution for the last 1000 cases of ECMO over the last 15 years are detailed in Table 4. Patients above the age of 18 were grouped under adult and there were 741 adult patients. There were 306 adult males: 337 male pediatric patients. The most frequent type of ECMO used was VA followed by VV. Commonest indication was failure to wean cardiopulmonary bypass in adults and cardiac arrest in pediatric population. Survival rate is 59.1% in adults and pediatric survival was 46.9%.Table 4 Demography and clinical details of the patients
Demography and clinical details Adult Pediatric
Age (years); mean (SD) 46.8 (15.3) 8.5 (3.6)
Height (cm); mean (SD) 158 (11.2) 77.9 (32.2)
Weight (kg); mean (SD) 62.5 (16.9) 12.6 (9.8)
Male (n) 306 337
Female (n) 435 209
Mode of ECMO
VA 331 531
VV 406 12
VAV 3 2
VVA 1 1
Survival (%) 59.1 46.8
Indications
Hypoxemia 93 41
LV failure 132 47
Failure to wean 193 54
ARDS 13 10
RV failure 97 25
Supra-systemic PA pressure 9 10
Hypotension 78 88
Cardiac arrest 58 200
Bridge to transplant 9 0
Cardiogenic shock 41 42
Refractory arrhythmia 0 9
Cardiac tamponade 0 2
Pneumonia (COVID and others) 4 0
Meconium aspiration 0 4
Hyperkalemia 0 2
Hypoxic arrest 0 9
Chloroaniline inhalation 1 0
Bridge to recovery 2 1
ECPR 11 2
Future
In the near future, there will be further advances in the technology of ECMO. Spherical chambers may replace the square-shaped membrane oxygenators to avoid formation of thrombi. Other advances may include paracorporeal membrane lung, automatic adjustment of sweep gas, and nitric oxide eluting plastic combined with anti-fibrin chemical of ECMO circuit to avoid anticoagulation [32].
ECMO is a modality which can transform patient outcomes when used judiciously. Timing all aspects of the ECMO run is crucial. Stringent monitoring, appropriate and timely trouble shooting strategies, and attention to detail along with teamwork are keys to a successful outcome. ECMO entails considerable investment in infrastructure, highly skilled and dedicated personnel, and substantial costs. The economics of ECMO vary from continent to continent. A center’s core team mix and experience are directly linked to outcomes.
Declarations
Conflict of Interest
The authors declare no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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7. Gattinoni L Pesenti A Mascheroni D Marcolin R Fumagalli R Rossi F Low-frequency positive-pressure ventilation with extracorporeal CO2 removal in severe acute respiratory failure JAMA 1986 256 881 886 10.1001/jama.1986.03380070087025 3090285
8. Peek GJ Mugford M Tiruvoipati R Wilson A Allen E Thalanany MM Efficacy and economic assessment of Conventional Ventilatory Support versus Extracorporeal Membrane Oxygenation for Severe Adult Respiratory Failure (CESAR): a multicentre randomised controlled trial Lancet 2009 374 9698 1351 1363 10.1016/S0140-6736(09)61069-2 19762075
9. Zapol WM Snider MT Hill JD Extracorporeal membrane oxygenation in severe acute respiratory failure: a randomized prospective study JAMA 1979 242 20 2193 2196 10.1001/jama.1979.03300200023016 490805
10 Davies A Jones D Beca J Blackwell N Forrest P Gattas D The Australia and New Zealand Extracorporeal Membrane Oxygenation (ANZ ECMO) Influenza Investigators*. Extracorporeal membrane oxygenation for 2009 influenza A(H1N1) acute respiratory distress syndrome JAMA 2009 302 17 1888 1895 10.1001/jama.2009.1535 19822628
11. Combes A Extracorporeal membrane oxygenation (ECMO) for severe acute respiratory distress syndrome (ARDS). The EOLIA (ECMO to rescue Lung Injury in severe ARDS) trial: a multicenter, international, randomized, controlled open trial [in French] Reanimation 2011 20 49 61 10.1007/s13546-010-0002-8
12. Raleigh L Ha R Hill C Extracorporeal membrane oxygenation applications in cardiac critical care Semin Cardiothorac Vasc Anesth 2015 19 4 342 352 10.1177/1089253215607065 26403786
13 Brodie D Slutsky AS Combes A Extracorporeal life support for adults with respiratory failure and related indications: a review JAMA 2019 13;322 6 557 568 10.1001/jama.2019.9302
14. Merrill ED Schoeneberg L Sandesara P Molitor-Kirsch E O’Brien J Dai H Outcomes after prolonged extracorporeal membrane oxygenation support in children with cardiac disease–Extracorporeal Life Support Organization registry study J Thorac Cardiovasc Surg 2014 148 582 588 10.1016/j.jtcvs.2013.09.038 24189317
15. Aubron C Cheng AC Pilcher D Leong T Magrin G Cooper DJ Factors associated with outcomes of patients on extracorporeal membrane oxygenation support: a 5-year cohort study Crit Care 2013 17 R73 10.1186/cc12681 23594433
16 Smith M Vukomanovic A Brodie D Thiagarajan R Rycus P Buscher H Duration of veno-arterial extracorporeal life support (VA ECMO) and outcome: an analysis of the Extracorporeal Life Support Organization (ELSO) registry. Smith et al. Critical Care 2017 21 45 10.1186/s13054-017-1633-1 28264702
17. Gupta P Robertson MJ Beam B Gossett JM Schmitz ML Carroll CL Relationship of ECMO duration with outcomes after pediatric cardiac surgery: a multi-institutional analysis Minerva Anestesiol 2015 81 619 627 25280142
18. Camboni D Philipp A Lubnow M Bein T Haneya A Diez C Support time-dependent outcome analysis for veno-venous extracorporeal membrane oxygenation Eur J Cardiothorac Surg 2011 40 1341 1347 21700473
19. Staudacher DL Bode C Wengenmayer T Duration of extracorporeal membrane oxygenation is a poor predictor of hospital survival J Crit Care 2016 32 207 208 10.1016/j.jcrc.2016.01.001 26852395
20. Schmidt M Burrell A Roberts L Bailey M Sheldrake J Rycus PT Hodgson C Scheinkestel C Cooper DJ Thiagarajan RR Brodie D Pellegrino V Pilcher D Predicting survival after ECMO for refractory cardiogenic shock: the survival after veno-arterial-ECMO (SAVE)-score Eur Heart J 2015 36 33 2246 2256 10.1093/eurheartj/ehv194 26033984
21. Xie A Phan K Tsai Y-C Yan TD Forrest P Venoarterial extracorporeal membrane oxygenation for cardiogenic shock and cardiac arrest: a metaanalysis J Cardiothorac Vasc Anesth 2015 29 637 645 10.1053/j.jvca.2014.09.005 25543217
22. Akihiko Inoue MD Toru Hifumi MD Tetsuya Sakamoto MD Yasuhiro Kuroda MD Extracorporeal cardiopulmonary resuscitation for out- of- hospital cardiac arrest in adult patients J Am Heart Assoc 2020 9 7 e015291 10.1161/JAHA.119.015291 32204668
23. Swol J Belohlavek J Brodie D Bellezzo J Weingart SD Shinar Z Schober A Bachetta M Haft JW Ichiba S Extracorporeal life support in the emergency department: a narrative review for the emergency physician Resuscitation 2018 133 108 117 10.1016/j.resuscitation.2018.10.014 30336233
24. Otani T Sawano H Natsukawa T Matsuoka R Nakashima T Takahagi M Hayashi Y D- Dimer predicts bleeding complication in out- of- hospital cardiac arrest resuscitated with ECMO Am J Emerg Med 2018 36 1003 1008 10.1016/j.ajem.2017.11.016 29129499
25. Alexandros Cavayas Y Intracranial hemorrhage in adults on ECMO Perfusion 2018 33 42 10.1177/0267659118766435 29788836
26. Biffi S Di Bella S Scaravilli V Peri AM Grasselli G Alagna L Pesenti A Gori A Infections during extracorporeal membrane oxygenation: epidemiology, risk factors, pathogenesis and prevention Int J Antimicrob Agents 2017 50 1 9 16 10.1016/j.ijantimicag.2017.02.025 28528989
27. Bizzarro MJ Conrad SA Kaufman DA Rycus P Extracorporeal Life Support Organization Task Force on InfectionsExtracorporeal Membrane Oxygenation Infections acquired during extracorporeal membrane oxygenation in neonates, children, and adults Pediatr Crit Care Med 2011 112 277 10.1097/PCC.0b013e3181e28894
28. Schmidt M Bréchot N Hariri S Guiguet M Luyt CE Makri R Nosocomial infections in adult cardiogenic shock patients supported by venoarterial extracorporeal membrane oxygenation Clin Infect Dis 2012 55 1633 1641 10.1093/cid/cis783 22990851
29. Makdisi G Wang IW Extra corporeal membrane oxygenation (ECMO) review of a lifesaving technology J Thorac Dis 2015 7 7 E166 E176 26380745
30. Kielstein JT Heiden AM Beutel G Renal function and survival in 200 patients undergoing ECMO therapy Nephrol Dial Transplant 2013 28 86 90 10.1093/ndt/gfs398 23136216
31. Link MS Berkow LC Kudenchuk PJ Halperin HR Hess EP Moitra VK Part 7: Adult advanced cardiovascular life support: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Circulation 2015 132 18 Suppl 2 S444 S464 26472995
32. de Caen AR Berg MD Chameides L Gooden CK Hickey RW Scott HF Part 12: Pediatric advanced life support: 2015 American Heart Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Circulation 2015 132 18 Suppl 2 S526 S542 26473000
33. Soar J Nolan JP Böttiger BW Perkins GD Lott C Carli P European Resuscitation Council Guidelines for Resuscitation 2015: Section 3 Adult advanced life support Resuscitation 2015 95 10047 10.1016/j.resuscitation.2015.07.016
34. Zakhary B Nanjayya VB Sheldrake J Collins K Ihle JF Pellegrino V Predictors of mortality after extracorporeal cardiopulmonary resuscitation Crit Care Resusc 2018 20 3 223 230 30153785
35. Holmberg MJ Geri G Wiberg S Guerguerian A-M Donnino MW Nolan JP Deakin CD Andersen LW International Liaison Committee on Resuscitation’s (ILCOR) Advanced Life Support and Pediatric Task Forces Extracorporeal cardiopulmonary resuscitation for cardiac arrest: A systematic review Resuscitation 2018 131 91 100 10.1016/j.resuscitation.2018.07.029 30063963
36. Chakravarthy M ECMO - the way to go Ann Card Anaesth. 2011 14 1 2 21196666
37. Barlett RH ECMO: the next 10 years Egyp J Critical Care Med 2016 4 7 10 10.1016/j.ejccm.2016.01.003
38. Dalia AA Extracorporeal membrane oxygenation is a team sport: institutional survival benefits of a formalized ECMO team J Cardiothoracic Vasc Anesth 2018 85 902
39. Nwozuzu A Fontes ML Schonberger RB Mobile extracorporeal membrane oxygenation teams: the North American versus the European experience J Cardiothoracic Vasc Anesth 2016 30 6 1441 1448.86 10.1053/j.jvca.2016.06.005
40. Combes A Position paper for the organization of extracorporeal membrane oxygenation programs for acute respiratory failure in adult patients Am J Respir Crit Care Med 2014 190 5 488 496 10.1164/rccm.201404-0630CP 25062496
41. Tseng YH Wu MY Tsai FC Chen HJ Lin PJ Costs associated with extracorporeal life support used in adults: a single-center study Acta Cardiol Sin 2011 27 4 221 228
42. Dennis M Zmudzki F Burns B Scott S Gattas D Reynolds C Sydney ECMO Research Interest Group Cost effectiveness and quality of life analysis of extracorporeal cardiopulmonary resuscitation (ECPR) for refractory cardiac arrest Resuscitation 2019 139 49 56 10.1016/j.resuscitation.2019.03.021 30922936
43. Jäämaa-Holmberg S Salmela B Suojaranta R Lemstrom KB Lommi J Cost-utility of venoarterial extracorporeal membrane oxygenation in cardiogenic shock and cardiac arrest Eur Heart J Acute Cardiovasc Care 2020 9 4 333 341 10.1177/2048872619900090 32004079
| 0 | PMC9734967 | NO-CC CODE | 2022-12-14 23:28:31 | no | Indian J Surg. 2022 Dec 7;:1-10 | utf-8 | Indian J Surg | 2,022 | 10.1007/s12262-022-03620-z | oa_other |
==== Front
BDJ In Pract
Bdj in Practice
2057-3308
2520-8675
Nature Publishing Group UK London
1817
10.1038/s41404-022-1817-5
Feature
Flexible Commissioning - a new approach
Hearnshaw Simon [email protected]
Health Education England, Yorkshire, United Kingdom
5 12 2022
2022
35 12 1821
© British Dental Association 2022
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
issue-copyright-statement© British Dental Association 2022
==== Body
pmcDental contract reform has been on-going for over a decade. Recently Flexible Commissioning (FC) has been implemented by some areas to meet oral health needs and commissioning challenges. This approach uses the existing contractual framework, substituting a percentage of a practice's contract value to deliver additional services instead of units of dental activity (UDAs)1 or alternatively funding programmes with additional financial resource.
This has always been possible within the existing NHS General Dental Services (GDS) and Personal Dental Services (PDS) contracts via the two main components: mandatory services (UDAs) and additional services (which may include dental public health, orthodontic, sedation or other services).2,3 An interesting outcome of the substitution method of flexible commissioning is that where UDA values are lower the UDA target reduction is greater. This has the effect of reducing UDA value inequality. The March 2021 dental contract reform and arrangements letter (NHS England) describes a flexible commissioning toolkit that is intended to make it easier to target local oral health priorities, using the flexibility that exists in the current contractual arrangements.4
The NHS England Yorkshire and the Humber Dental Commissioning Team are at the forefront in developing and implementing flexible commissioning. The Yorkshire and Humber Flexible Commissioning programme has been supported by the Local Dental Networks, dental public health colleagues, Health Education England (HEE), Local Dental Committees, NHS Business Service Authority (NHS BSA) and by local authorities in the region. This paper is a continuation of the article published in 2020.1© pbombaert/Getty Images Plus
Programme model
The key elements of the Yorkshire and the Humber Flexible Commissioning Programme are set out in Figure 1.Figure 1 Elements of the Flexible Commissioning Programme
The programme was co-produced with a range of stakeholders as described in a previous paper.1
The objectives of the programme were to Improve access to dental care
Develop skill mix care delivery
Improve evidence-based prevention and
Facilitate Making Every Contact Count (MECC) delivery.5
The programme framework incentivised the delivery of a number of programme access and prevention components as shown in Table 1.Table 1 Components of the Flexible Commissioning Programme
Prevention Evidence informed pathways based on Delivering Better Oral Health (DBOH)6 and informed by learning from In Practice Prevention (Y&H) and Starting Well (Hull & Wakefield)
Whole population All children - DBOH recommended prevention
All adults - DBOH lifestyle advice and signposting to local Health & Wellbeing Services
Making Every Contact Count (MECC)
Target groups Children 0-18
Caries
Referred for extractions under general anesthetic
Older Adults
Dementia
Dry Mouth
Osteonecrosis of the Jaw Risk
Diabetes
High needs / Phased treatment approach
Access Open to new patients (all ages) on NHS webpages (formerly NHS Choices)
Acceptance of referrals from CDS and 0-19 workforce
Was Not Brought Policies / Safeguarding
Implementation of Dental Check by One (DCby1)
Skill mix Appointment of a practice Oral Health Champion
Training for DCPs & whole dental team in association with HEE Y&H
DCP led pathways - skill mix
Audit and evaluation Completion of NHS BSA bespoke audit and reporting tool (Snap Tool)
Dental nurses were trained by HEE to deliver targeted one-to-one prevention sessions for children and adults with disease or disease risk embedding skill mix within dental teams. To date HEE have trained over 170 dental nurses through the delivery of a bespoke course including dental health education, fluoride varnish application and implementation of MECC.5
Practices who joined the programme were asked to be open for new patients through their NHS webpages and to work with health visitor and social care teams to facilitate access for vulnerable children and adults. Practices within the programme were also asked to work with local community dental services to accept the safe discharge of healthy level 1 patients and to engage in MECC delivery contributing to local health improvement and health inequality strategies.
' The NHS England Yorkshire and the Humber Dental Commissioning Team are at the forefront in developing and implementing flexible commissioning.'
All practices were required to appoint and train an Oral Health Champion (usually an enhanced trained dental nurse) to lead the programme internally. The Champions were given the opportunity to join a region-wide Champion peer review group on a virtual platform to provide support for implementation. Currently the membership of this informal peer review and support group is 109. An initial training event was held to provide information to the 147 practices involved in the programme.
The inclusion criterion to join the programme was the delivery of at least 90% of annual contract value.
The programme was supported by work with NHS BSA developing outcomes data collection tools including quarterly data submission surveys and a programme dashboard. A bespoke programme clinical delivery data report was provided by dental insight at the BSA.
Outcomes
The Yorkshire and the Humber Flexible Commissioning Programme started in late 2019. Of the 149 practices who initially joined the programme, 146 have remained enrolled. Although sites were not targeted, 48% of participating practices were located in deprived areas (IMD 1 to 3). Over the first 12 months the programme delivered the following outcomes
Access
The 146 Flexible Commissioning practices in the region have delivered approximately 39,500 new adult patient appointments and 18,500 new child patient appointments. The total number of new adult and child patient appointments seen through the programme represents 24% of the total new appointments in the region.
In terms of Dental Check by One (DCby1) in some localities the flexible commissioning sites delivered 12% more access for children under one year old.
The facilitated access for 3,500 children referred by health visitor and social care teams reflected the development of simple and effective patient pathways for vulnerable children. Of the 1,100 referrals from social care teams a significant proportion were looked after children a group with established health inequality.6
At the end of quarter four (Dec 2021) most practices (65%) reporting a waiting time in excess of 26 weeks for a first appointment for a non-urgent new patient via the online reporting tool.
Prevention
Oral Health Champions within each flexible commissioning practice delivered most of the evidence based targeted prevention pathways based on DBOH.7 The champion training commissioned by HEE and delivered locally by the Leeds Dental Institute included modules on behaviour change and fluoride varnish application. The prevention pathways were developed with the paediatric and special care dentistry Managed Clinical Networks.
Around 50,000 targeted prevention sessions were provided for children and over 15,000 for adults with disease or disease risk shown in Table 3.Table 2 Rates of fluoride varnish for children April - October 2021
Fluoride Varnish Rate
0-3-year olds (%) Fluoride Varnish Rate
3-16-year olds (%)
FC practices 27.1 69.8
Non-FC practices 23.2 62.3
Over 5,000 referrals were made by flexible commissioning practices into wider health and wellbeing services, integrating general health improvement into oral health services. 4,000 of these were referrals to smoking cessation services. The small number of weight management interventions reflect the requirement for greater training.8
Despite the restrictions imposed on delivery of care by the ongoing pandemic, evidence from FP17 data show that there was an increased rate of application of fluoride varnish by FC practices for children compared to non-FC practices in Table 2.Table 3 Programme delivery for 2021/22 - including Q4 2020/21
Delivery outcomes Numbers delivered
Referrals from wider health and social care services
Referrals from CDS 919
Health Visitor Referrals 2,336
Social Care Referrals 1195
Total 4450
Referrals into health and wellbeing services
Smoking cessation 4118
Alcohol reduction 497
Weight management 48
Other 550
Total 5,213
Targeted prevention sessions for children
Caries 46,774
General anaesthesia 3,973
Total child sessions 50,747
Targeted prevention sessions for adults
Dry mouth 1,177
Dementia 441
Osteonecrosis of the jaw 616
Diabetes 2,380
High needs 10,545
Total adult sessions 15,159
' The 146 Flexible Commissioning practices in the region have delivered approximately 39,500 new adult patient appointments and 18,500 new child patient appointments.'
Impact of COVID-19
The pandemic had a significant impact on the delivery of the programme. The suspension of all routine dental care in England started soon after the third wave of practices enrolled in the programme.
An online survey was conducted with the practices enrolled in Flexible Commissioning to evaluate the impact of the COVID-19 pandemic on the delivery of the programme in late 2021.
From the online survey to practices:95% of practices thought that delivery of the flexible commissioning programme was affected by COVID-19
Around two fifths of these practices estimated that under normal circumstances, if not affected by COVID-19, delivery of the flexible commissioning programme could have been improved by between 25% and 50%
Almost a third felt that this improvement would have been greater than 50%.
Cost effectiveness of the programme
Most practices (93%) opted to take the maximum 10% contract variation, which equates to a potential spend of £7.7million annually, with a range between practices around £250,000 to £10,000. It would be expected that such a range would lead to wide variation in the activity that a practice would have the capacity to deliver, however performance of delivery did not correlate with contract value.
Contract values and programme data have been used to assess value for money and cost-effectiveness. This has permitted modelling of values for the elements of the programme enabling benchmarking of delivery performance and analysis of return on investment. More data are required to inform service design ideally with the programme delivered under 'normal' 100% contract delivery expectations.
This evaluation has however shown that Flexible Commissioning practices fall broadly into three groups:Group 1: Engaged with delivering all elements of the programme and some evidence of delivering value for the investment.
Group 2: Engaged with some but not all elements of the programme.
Group 3: Poor/no compliance and delivery of the programme. Little or no return on investment.
Group 2 with support (training, targeted peer support etc) could potentially increase their delivery and cost effectiveness.
Summary of findings
The FC programme was launched in early 2020 just before the coronavirus pandemic forced healthcare services to shift their focus to a pandemic response. In many respects the positive engagement across the programme during a very challenging period underlines the commitment of dental teams and stakeholders to embrace the process of incremental reform of the existing dental contract and the fact that we need to capture the 'innovations in health driven by the COVID-19 response'.9 Some of the systems connectivity and consequent development of patient pathways for more vulnerable groups have developed at speed because of the general access challenges.10 The development of safe discharge arrangements between community dental services and flexible commissioning sites has been largely successful in terms of developing closer links and improved communication across care boundaries.
As the contractual requirements and targets return to the pre-pandemic levels, it is critical that programme development and improvement does not lose momentum.
Despite the limitations on delivery of primary dental care services imposed by the pandemic there is evidence that the FC practices are having an impact on delivery of prevention and to a lesser extent access. There is a considerable variation in volume of programme components delivered between practices. Some of this can be explained by size of the practice, but it is probable that practice readiness and understanding of the programme will have had an impact.
The provision of evidence informed pathways, local public health support for the development of referral pathways and the establishment of peer support forums have undoubtedly helped those practices who have engaged with training and support. Expansion of the programme may be supported by the requirement of practices to have a minimum level of staff trained and competent in place before programme commencement. Continued work with HEE to support training and associated workforce development is essential. Development of a dedicated NHS resource hub would also support sharing of best practice.
' Oral Health Champions within each flexible commissioning practice delivered most of the evidence based targeted prevention pathways based on DBOH'
The FC programme has supported the introduction and development of skill mix in practices. To an extent this supports the recent contract changes around skill-mix development announced this year.11 It remains to be seen if dental nurses will be included as members of the wider dental team who will be able to open courses of preventive care.
Overall, the Yorkshire and Humber Flexible Commissioning initiative has demonstrated that it is possible to commission outcomes-based programmes that can impact on the delivery of preventive care, reduction of inequalities, improved access to new patients and contribute to improvement of general health through MECC. Change management required was supported by clear communication with practices, appropriate training, specific data collection, embedding of skill-mix, programme support and critically buy-in from stakeholders.
Acknowledgements
The regional teams of NHS England, Health Education England, Local Dental Networks, Local Dental Committees, local authorities, Community Dental Services and especially the practices delivering the programme and the champions leading it. Partnership work with the NHS Business Service Authority and Health Education England was critical to evidencing and evaluating outcomes and training and developing the workforce. Special thanks to Mr Colin Sullivan, Clinical Photographer, Medical & Dental Illustration Department, Leeds Teaching Hospital Trust for his help designing Fig. 1. ◆
==== Refs
References
1. Mustufvi Z, Barraclough O, Hearnshaw S, et al. Flexible Commissioning: A prevention and access focused approach in Yorkshire and the Humber. BDJ In Pract 2020; 33: 20-22.
2. NHS England. Standard General Dental Services Contract. 2018. Available online at: www.england.nhs.uk/wp-content/uploads/2018/08/general-dental-services-contract-2018.pdf (accessed July 2022).
3. NHS England. Standard Clauses for a Personal Dental Services Agreement. 2018. Available online at: www.england.nhs.uk/wp-content/uploads/2018/08/standard-clauses-for-a-personal-dental-services-agreement-2018.pdf (accessed July 2022).
4. NHS England. NHS dental contract reform and arrangements letter. 2021. Available online at: www.england.nhs.uk/coronavirus/documents/nhs-dental-contract-reform-and-arrangements-letter/ (accessed July 2022).
5. Health Education England. Making Every Contact Count (MECC). Available online at: www.makingeverycontactcount.co.uk/ (accessed July 2022).
6. Public Health England. Inequalities in oral health in England. 2021. Available online at: www.gov.uk/government/publications/inequalities-in-oral-health-in-england (accessed July 2022).
7. Office for Health Improvement and Disparities. Delivering better oral health: an evidence-based toolkit for prevention. 2021. Available online at: www.gov.uk/government/publications/delivering-better-oral-health-an-evidence-based-toolkit-for-prevention (accessed July 2022).
8. Daley A J. Time to get our teeth into reducing obesity: should dentists screen and deliver interventions to reduce obesity in the population? Br Dent J 2022; 232: 78-79.
9. Hurley S. Why re-invent the wheel if you've run out of road? Br Dent J 2020; 228: 755-756.
10. Westgarth D. Improving dental care and access for this group is essential. BDJ In Pract 2022; 35: 10-11.
11. NHS England. Outcome of 2022/23 Dental Contract Negotiations letter. 2022. Available online at: www.england.nhs.uk/wp-content/uploads/2022/07/B1802_First-stage-of-dental-reform-letter_190722.pdf (accessed November 2022).
| 0 | PMC9734969 | NO-CC CODE | 2022-12-14 23:28:31 | no | BDJ In Pract. 2022 Dec 5; 35(12):18-21 | utf-8 | null | null | null | oa_other |
==== Front
Spat. Inf. Res.
Spatial Information Research
2366-3286
2366-3294
Springer Nature Singapore Singapore
488
10.1007/s41324-022-00488-9
Article
Spatio-temporal analysis of the COVID-19 pandemic in Iran
Isaza Vahid [email protected]
http://orcid.org/0000-0001-8303-1723
Parizadi Taher [email protected]
Isazade Esmail [email protected]
grid.412265.6 0000 0004 0406 5813 Department of Geographical Sciences, Kharazmi University, Tehran, Iran
3 12 2022
114
18 2 2022
21 9 2022
21 9 2022
© The Author(s), under exclusive licence to Korean Spatial Information Society 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Globally, the COVID-19 pandemic is a top-level public health concern. This paper is an attempt to identify and COVID-19 pandemic in Iran using spatial analysis approaches. This study was based on secondary data of confirmed cases, deaths, recoveries, number of hospitals, hospital beds and population from March 2, 2019 to the end of November 2021 in 31 provinces of Iran from hospitals and the website of the National Institute of Health. In this paper, three geographical models in ArcGIS10.3 were utilized to analyze and evaluate COVID-19, including Geographic Weight Regression (GWR), Getis-OrdGi* (G-i-star) statistics (hot and cold spot), and Moran autocorrelation spatial analysis. Moran statistics, based on the GWR model, demonstrated that deaths and recoveries followed a clustering pattern for the confirmed cases index during the study period. The Moran Z-score for all three indicators confirmed cases, deaths, and recoveries, which was greater than 2.5 (95% confidence level). The Getis-OrdGi* (G-I-Star) (hot and cold spot) data revealed a wide range of levels for six variables (confirmed cases, deaths, recoveries, population, hospital beds, and hospital) across Iran's provinces. The overall number of deaths exceeded the population and the number of hospitals in the central and southern regions, including the provinces of Qom, Alborz, Tehran, Markazi, Isfahan, Razavi Khorasan, East Azerbaijan, Fars, and Yazd, which had the largest number and The Z-score for the deaths Index is greater than 14.314. The results of this research can pave the way for future studies.
Keywords
COVID-19 pandemic
Geographic weight regression
Moran I
Getis-Ord I*
Iran
==== Body
pmcIntroduction
In late December 2019, viral pneumonia with an unknown agent was reported, in Wuhan, China. The virus, named COVID-19 (SARS-COV-2), quickly crossed the borders and dispersed worldwide on March 25, 2020, affecting 196 countries [1]. In February 2020, the world health organization)WHO( named the new disease COVID-19 [2]. The United Nations have considered COVID-19 as the central public, human, and economic event with many unfavorable effects on various countries [3].
Although, countries have adopted different strategies such as house quarantine, mask use, and social distancing [4], the desease can still have potential devious effects on general health [5].
Notwithstanding considerable advances in all countries of the world for disease control, infectious diseases are important in epidemiology and social health [6]. Thus, all required information should be instantly accessed and utilized to assess the risk of COVID-19 and identify the locations that are currently at high risk. Affecting more than 185 countries indicates that the fast pandemic of COVID-19 requires modern technology to assess the risk of specified locations [7]. Hence, GIS can play a significant role in the spatial analysis of this pandemic virus [8]. One of the major applications of epidemiology is to facilitate the identification of geographical locations and teams of people in danger, providing the most appropriate health and social choices to mitigate risk factors [9]. Health experts have been utilizing maps for spatial analysis of diseases for 150 years [10]. Geographical epidemiology is part of anatomical epidemiology that analyzes the geographical spread of infection and mortality [11].
The first stage in analyzing geographical data is visualization and representing data in the form of geographical maps [12]. geographic information system (GIS) has been widely used in agriculture, business, environment, natural resources, urban design, and various disease modeling for years [13]. Due to the vastness of the geographical distribution and activeness of health care service centers, familiarity with GIS skills is essential for the managers of this sector [14]. Geospatial analysis capability in GIS has a direct application in modeling the spatial pandemic of diseases and their connection with environmental features and the health care system. Currently, GIS technology is considered a significant tool in the health investigation and management of infectious diseases [15, 16]. Iran is one of the countries in the world in Asia, where the first of outbreak COVID-19 was reported on March 2, 2020, in Qom province [17]. According to the Ministry of Health of Iran, the rate of the virus has increased strongly from early July to late June; approximately 23,475 to 64,695 have been confirmed, during this period with an increase in a pandemic in most provinces and terms of the population of Iran with about 5,954,962 million people [18]. It is currently one of the top countries in terms of confirmation compared to the entire population of the country [19].
The most important limitations of this study were the downward trend and the small number of confirmed cases in the first weeks of COVID-19 onset and the start of two doses of Sinofarm and Astrazenka vaccines in Iran. With the pandemic of COVID-19 in January 2020, the investigation has focused heavily on understanding the space–time dynamics of the prime wave of the disease and examining the outcomes of inhibition measures.
Hui et al. [20] examined the pandemic of COVID-19 and its trends as well as why the virus poses a long-term threat to public health. Zhonghua and Xue [21] evaluated the Spatial–temporal profile of COVID-19 in Guangdong Province and if the virus transmission chain-breaking strategies were effective. Liu et al. [22] used a statistical analysis to determine the spatial pandemic of the virus.
Xie et al. [23] examined Wuhan population density and potent economic link as the main reasons for the pandemic of the virus. They also recounted other factors, such as population pandemic, average temperature, access to transportation, and medical facilities. Guliyev [24], in a perusal of the association between COVID-19, mortality, and improved use of spacecraft models, developed a map of the virus pandemic in China. The results showed that spatial influences, directly and accidentally, affect the pandemic of the virus. Rahnama and Bazargan [25] evaluated the analysis of Spatial–temporal patterns of the COVID-19 pandemic in Iran using descriptive-analytical methods and spatial distribution modeling. They discovered that the most significant geographical factor for the pandemic of COVID-19 is the distance and vicinity of the provinces affected by COVID-19 in the Iran, which follows the pattern of the spatial distribution of adaptation. Abolfazl et al. [26] modeled the pandemic of COVID-19 geographically and its variability across the United States. They utilized GWR and multi-geographic weighted regression (MGWR) to study the pandemic of the virus. The results indicated that GWR has reasonable performance in spatial analysis of COVID-19 pandemic as compared to the MGWR model. Pourghasemi et al. [27] analyzed the risk factors for COVID-19 pandemic to identify the locations at extreme danger of infection and assess infection behavior in Fars province in Iran. For this purpose, a GIS-Based machine learning algorithm was employed to measure the risk of COVID-19 pandemic.
Jia et al. [28] presented a dynamic model to diagnose the transmission of COVID-19 considering the relationship between virus pandemic and air quality conditions. The results showed that the air index is the most important climatic factor in virus diffusion.
Aral et al. [29] find the Spatio-temporal pattern of the COVID-19 pandemic in Turkey. They also employ spatial regression to uncover the related factors affecting the COVID-19 cases. In the COVID-19 model, they discovered that population density and the elderly dependency ratio are necessary. Aldana et al. [30] investigated the spatial distribution of COVID-19 cases in Iran. They identified important spatial clusters of cases and the effect of socio-economic features of Iranian provinces on the number of cases. They found a spatial correlation within Iranian provinces in terms of COVID-19.
GIS due to having different types of spatial statistical analysis can be very important in the production of time and space maps of COVID-19 pandemic in Iran. In particular, the development of GIS methods, especially in space spatial and general image of the primary centers of the pandemic of the virus in different areas, is possible [31].
The main purpose of this paper is (1) Evaluation of Spatio-temporal patterns of COVID-19 pandemic using confirmed data, deaths, recoveries and population information from March 2, 2019 to November 31, 2021. (2) Quantification of changes in COVID-19 and (3) Comparison of annual changes of COVID-19 in the provinces of Iran. This activity will stop the pandemic of the virus at different times and regions of its transmission chain, which in itself can help managers and policymakers to be able to adopt new strategies to mitigate this crisis in Iran.
Spatial statistics have emerged as a useful tool for the analysis of spatial pandemic, concerning mapping and statistical analyses of spatial and Spatio-temporal incidences of different pathogens. The value of this paper is to perform spatial analyses which allow us to better understand the COVID-19 pandemic in Iran. Therefore, the result is expected to help the Iran government create more appropriate policies and strategies to reduce the virus pandemic.
Methods
The present paper examines Iran as the second-largest country in the Middle East (Fig. 1), the area of this country is 1873959 Km2 and it has an arid and semi-arid climate [32]. Iran has 31 provinces due to its political characteristics according to several studies, Iran has suffered the most harm from the virus in the world and ranks fifth in terms of vulnerability [33]. Iran, with a collection of 5,973,457, confirmed cases and 127,053 deaths, is the eighth location in the world in terms of the number of confirmed cases of COVID-19 in this paper.Fig. 1 Location of study area. a The global location of Iran, b Provinces of Iran
This paper is based on secondary data, the data related to confirmed, deaths, recovered, hospital beds and hospitals from the website of the Ministry of Health of Iran, and the data related to population statistics received from the website of the Statistical Center of Iran from March 2, 2019, until the end of November 2021. the data were classified in the software Excel in six indicators for 31 selected provinces of Iran (Table 1).Table 1 Data was used for spatial analysis in terms of provinces of Iran to model the COVID-19 pandemic [34]
No Province Confirmed cases Deaths Recovered Population Hospital Bed Hospitals
1 Ardabil 2025 2533 220,935 1,270,420 2600 14
2 East Azerbaijan 488,125 8561 479,564 3,909,652 10,000 64
3 West Azerbaijan 304,170 6847 297,323 3,265,219 5500 40
4 Kurdistan 83,454 1787 81,667 2,453,677 1850 18
5 Kermanshah 25,436 2774 22,662 1,952,434 2200 31
6 Ilam 63,711 1125 61,407 557,599 780 15
7 Khuzestan 28,659 3452 250,207 4,710,509 2280 62
8 Bushehr 87,848 1998 85,850 1,163,400 1700 20
9 Hormozgan 148,252 2430 136,832 1,776,415 2573 22
10 Sistan and Baluchestan 125,747 2604 123,143 2,775,014 2385 24
11 South Khorasan 147,252 1197 146,055 768,898 1208 16
12 Razavi Khorasan 423,067 9625 413,442 6,434,501 6453 82
13 North Khorasan 128,725 1234 116,591 863,092 1313 14
14 Golestan 7690 869 6821 1,868,819 2430 34
15 Mazandaran 128,121 1825 126,296 3,283,582 3250 49
16 Gilan 128,121 1825 126,296 2,530,696 2050 36
17 Zanjan 35,184 1766 33,418 1,057,461 2300 13
18 Lorestan 192,012 2596 189,416 1,760,649 2150 35
19 Hamadan 95,877 3030 92,847 1,758,268 2454 27
20 Chaharmahal and Bakhtiari 83,650 1663 81,987 947,763 1479 14
21 Kohgiluyeh andBoyer-Ahmad 77,609 993 76,616 713,052 1400 24
22 Fars 478,094 6990 4,640,366 4,851,274 3250 57
23 Kerman 291,061 3579 255,072 3,164,718 2943 47
24 Yazd 96,283 10,052 86,231 1,138,533 2664 31
25 Semnan 46,210 1765 37,194 702,360 1876 19
26 Tehran 582,723 19,672 563,051 13,267,637 55,132 178
27 Alborz 76,651 6338 70,313 2,712,400 3130 17
28 Qazvin 42,591 2566 40,025 1,501,565 2000 9
29 Markazi 103,075 2905 100,170 1,429,000 2100 26
30 Isfahan 418,092 16,607 1,190,233 5,120,850 9156 79
31 Qom 178,251 2672 165,579 1,292,283 1404 14
Then, analysis of the Spatio-temporal distribution of four confirmed indices, deaths and recovered and population from the GWR model and Getis-OrdGi * (G-I-star) statistical model ArcGIS10.3 environments in the form of two different models were used. To implement the GWR model, three indicators of confirmed, deaths, and recovered and population, number of hospital beds and hospitals in Excel environment were added to the shapefile of the study area. From the modeling spatial relationships section of ArcGIS10.3 software, the GWR statistical model was called for.
The input of this model was selected as the shapefile of the study area, to which 6 data were added, then three indicators of confirmed, deaths, and recovered as dependent variables and 3 indicators of the number of hospital beds, hospitals, and population as independent variables, were introduced to the model. Hot and Cold spots were determined using the Getis-OrdGi * (G-I-Star) statistical model in the GIS environment to quantify the Z-score and P-values. Finally, the inverse distance weighting (IDW) method was implemented to produce a spatial layer that depicts hot spots and cold regions using the Z-score as the input data. In this paper, Getis-OrdGi * geostatistical model was used for spatial clustering, and Spatial Autocorrelation Morans I analysis for spatial autocorrelation between COVID-19 indices in the provinces of Iran.
Geographically weighted regression (GWR model)
Regression analysis is generally used to examine the relationship between parameters. When it is more focused on the relationship between an affiliate parameter and one or more independent parameters, it is used for modeling [35]. There are two types of regression models: global multivariate regression and local multivariate regression models. Global multivariate regression model (OLS, spatial error and spatial delay). These models can clarify the importance of statistical relationships between the independent and affiliate variables by an equation. The GWR model reveals the location of the regression parameters. This model examines the parameters that are points one by one by the local weight ordinary least squares (OLS) [36]. The relationship of the model in question is analogous to the global regression models; however, the variables are different in different places [36]:1 yi=β0+β1ix1i+β2ix2i+⋯+βknXkn+δi
I where β is the estimated parameter vector, x is the independent variables, and y is the observed values' vectors.
Hot and cold spots model (Getis-OrdGi *)
In this model, the regions with the highest rates of incidence were identified as hot spot areas [37]. The hot spot analysis could be beneficial in studying the evidence of identifiable spatial patterns. This technique, implemented in ArcGIS software, pinpoints statistically meaningful spatial bunches of higher value (hot spots) and lower value (cold spots). In Getis-Ord Gi*, the significance and intensity of clustering are assessed based on an assurance surface and Z-scores. For positive Z-scores, higher Z-scores reveal many intense clusters (hot spots). However, for minus Z-scores, low Z-score values show more severity of bunches of lower values (cold spots) [38]. The Getis-Ord-J. K statistic is calculated by Eqs. 2, 3, and 4.2 Gi∗=∑j=1nwijxj-X¯wij[n∑j=1nwij2-∑j=1nwij]n-1S
In this formula Xj, the value of the attribute for complication j, Wij represents the spatial weight between the complication and i, j and n the collected number of complications.3 X¯=∑j=1nxjn
4 S=∑j=1nxj2n-(X¯)2
Since Gi itself is a type of Z-score, it does not need to be recalculated.
Spatial autocorrelation (Global Moran’s I)
Spatial autocorrelation (Global Moran’s I) analysis reveals the correlation between the same values and variables in different locations, strong spatial autocorrelation occurs when the values are randomly distributed in space with no relationship between them [39]. Spatial correlation analysis is calculated as spatial autocorrelation (Global Moran’s I) by Eq. (5).5 I=NW∑i∑jwij(xi-x¯)(xj-x¯)∑i(xi-x¯)2
where Xi is the coefficient of the distance or relative variable in location unit i, n is the number of location units, and w (i, j) is the connectivity spatial weight between j and I.
Results and discussion
Analysis of the Spatio-temporal of COVID-19 pandemic with the GWR model
Figure 2 shows the COVID-19 pandemic in Iran in the period from March 2, 2019, to the end of November 2021. Using the GWR model, each indicator separately on an annual basis indicates that on March 24, 2019, patients with COVID-19 are observed only in Gilan and Golestan provinces. However, in the provinces of Tehran and Khorasan Razavi, the rate of this index in 2020 had the highest pandemic. Again Gilan province was reported as the most critical province with the highest pandemic of the virus in 2021. The reason for the higher pandemic of this virus in urban and suburban traffic had been the non-compliance with health protocols in neighboring provinces such as Tehran, Qom, and central Ardabil to this province. The number of confirmed cases of this virus in Iran was 28 cases, 86.67% of which were reported in Qom province.Fig. 2 Spatial distribution of COVID-19 pandemic. a confirmed 2019, b confirmed 2020 c confirmed 2021, d death 2019, e death 2020, f death 2021, g recovered 2019, h recovered 2020, i recovered 2021
Since March 1, 2019, of the COVID-19 pandemic in the country has been rising sharply, reaching over 1000 infected people in the country. Studies show that COVID-19 from the provinces of Tehran, Qom, Gilan, Markazi, Mazandaran, and Isfahan in the surrounding areas is expanding quickly. From March 2, 2019, until the end of November 2021, the number of confirmed infected people with COVID-19 in Iran reached 5,117,766 people showing an increase in the number of infected people in the country. traveling to pilgrimage and tourist cities such as Mashhad, Qom, Mazandaran, Golestan, and Gilan, without following the health instructions required by the headquarters in fighting the COVID-19 caused the rapid pandemic of the virus to most parts of the country.
From March 2, 2019, to the end of November 2021, the number of deaths in the country reached 133,880, and the most deaths in 2019 were reported in Lorestan and Markazi provinces. However, in 2020, due to weddings and the lack of hygiene items and crowds, and the lack of virus detection kits caused the transmission of the COVID-19 chain to the provinces of West Azerbaijan and Yazd and a major number of people died. In addition to the high number of patients, Gilan province had many deaths in 2021, the most important reason for the high number of patients and deaths in this province was the excessive travel of people to this province on weekends (Fig. 2). With the observance of health protocols, home quarantine, and closure of pilgrimage and recreation centers by the COVID-19 headquarters, the number of recovered people in the whole country reached 10,317,609 people.
Of these, Markazi province in 2019 with 26.7% has the highest approval in the country compared to other provinces of Iran. Meanwhile, in 2020, West Azerbaijan province with 17.18% and Isfahan province in 2021 with 7.9% have recovered the incidence of COVID-19. The results of the COVID-19 pandemic for the three confirmed case, deaths and recovery are presented in (Tables 2, 3 and 4). Using geographic weighted regression as a visual technique can reveal interesting patterns in geographic data. Spatial distribution of confirmed, deaths and recovered patients in relation to the number of hospitals (dependent variable), the number of beds in each hospital and the population of each province (explanatory variable) shows that there is a strong relationship in some provinces between the variable There is a relationship and explanation, and in some provinces this relationship is negative. One of the important parameters is the coefficient of determination (R2) which expresses the goodness and accuracy of the model, and the closer this parameter is to 1, it means that the explanatory variable used has been able to explain the changes in the dependent variable well, in This research on the spatial distribution of COVID-19 is very well estimated and shows that the model with the dependent variable was able to explain the pandemic of COVID-19 spatial distribution in 31 provinces of Iran for confirmed 81%, deaths 58% and recovered 67% (Tables 2, 3 and 4).Table 2 Results of the confirmed cases of the COVID-19 pandemic relative to population, hospital bed and hospitals
No Parameter Variable Dissection
1 Bandwidth 209.47
2 Residual squares 4.83
3 Effective number 4.00
4 R2 0.77
5 R2Adjusted 0.74
6 Dependent field 0 Confirmed (2019)
7 Expository field 1 Hospitals
8 Expository field 2 Hospital Bed
9 Expository field 3 Population
1 Bandwidth 210.21 209.47
2 Residual squares 3.42
3 Effective number 4.00
4 R2 0.78
5 R2Adjusted 0.75
6 Dependent field 0 Confirmed (2020)
7 Explanatory field 1 Hospitals
8 Explanatory field 2 Hospital Bed
9 Explanatory field 3 Population
1 Bandwidth 209.47
2 Residual squares 17.00
3 Effective number 4.00
4 R2 0.90
5 R2Adjusted 0.78
6 Dependent field 0 Confirmed (2021)
7 Expository field 1 Hospitals
8 Expository field 2 Hospital Bed
9 Expository field 4 Population
Table 3 Results of the deaths of the COVID-19 pandemic in relative to the population
No Parameter Variable Dissection
1 Bandwidth 209.47
2 Residual squares 3.11
3 Effective number 4.00
4 R2 0.68
5 R2Adjusted 0.43
6 Dependent field 0 Deaths (2019)
7 Expository field 1 Population
1 Bandwidth 19.59
2 Residual squares 21.80
3 Effective number 4.63
4 R2 0.61
5 R2Adjusted 0.56
6 Dependent field 0 Deaths (2020)
7 Expository field 1 Population
1 Bandwidth 14.52
2 Residual squares 14.09
3 Effective number 5.14
4 R2 0.45
5 R2Adjusted 0.36
6 Dependent field 0 Deaths (2021)
7 Expository field 1 Population
Table 4 Results of the recovered of the COVID-19 pandemic in relative to the population, hospital bed and hospitals
No Parameter Variable Dissection
1 Bandwidth 209.47
2 Residual squares 24.02
3 Effective number 4.00
4 R2 0.72
5 R2Adjusted 0.65
6 Dependent field 0 Recovered (2019)
7 Expository field 1 Hospitals
8 Expository field 2 Hospital Bed
9 Expository field 3 Population
1 Bandwidth 9.56
2 Residual squares 17.24
3 Effective number 6.55
4 R2 0.66
5 R2Adjusted 0.59
6 Dependent field 0 Recovered (2020)
7 Expository field 1 Hospitals
8 Expository field 2 Hospital Bed
9 Expository field 3 Population
1 Bandwidth 209.47
2 Residual squares 14.22
3 Effective number 4.00
4 R2 0.71
5 R2Adjusted 0.63
6 Dependent field 0 Recovered (2021)
7 Expository field 1 Hospitals
8 Expository field 2 Hospital Bed
9 Expository field 3 Population
Past research has shown that a large number of socio-economic and environmental parameters are used to analyze the of COVID-19 and the number of deaths by means of using GIS tools [40]. Also at the provincial level in Italy, Giuliani et al. [41] modeled the Spatio-temporal dynamics of contagion and mortality due to COVID-19. As in Italy, the local pandemic is many heterogeneous. Its major focus is in the north, but it is gradually penetrating the southern provinces.
There is strong proof that hard control measures implemented in some provinces effectively break the cycle of infection and limit the pandemic to adjacent regions. Spatial autocorrelation analysis based on distance shows that at a distance of 383.8 km from the provinces of Qom, Tehran, Razavi and Gilan, the spatial distribution of infected and deceased is positive; However, at a distance of 762.6 km from the provinces of Qom, Tehran, Khorasan Razavi and Gilan, the spatial distribution of recoveries is positive, indicating that from this distance, the number of confirmed and deaths due to COVID-19 has decreased and the number of recoveries has increased.
Spatial distribution pattern of three indicators of confirmed, the deaths and the recovery in Iran
Table 5 shows the provinces of Ilam, Golestan, Gilan Isfahan, Tehran, and West Azerbaijan in terms of spatial distribution results of Moran correlation from March 2, 2019, to the end of November 2021. The Z-score is 3.357. However, this is 0.478 and 4.938 deaths rate due to the COVID-19 pandemic in Yazd, West Azerbaijan, Tehran, Isfahan, and Qazvin provinces, respectively.Table 5 Estimating the geographic pattern of the COVID-19 pandemic in Iran using spatial autocorrelation Morans I
Morans index Confirmed
Morans I Variance Z-score P-value Pattern
0.469 0.004 3.357 0.0007 Clustered
Morans index Deaths
Morans I Variance Z-score P-value Pattern
0.478 0.005 4.938 0.0001 Clustered
Morans index Recovery
Morans I Variance Z-score P-value Pattern
0.550 0.006 3.309 0.0009 High-Clusters
While the Moran value for the recovery index was 0.550 and the Z-score was 3.309 in the central provinces of West Azerbaijan and Isfahan. The results of Moran's spatial correlation showed that the Z-score for these provinces was positive in terms of both confirmed and deceased indicators and was statistically significant because in these provinces the number of confirmed cases and deaths of COVID-19 has been too much.
The spatial pandemic of COVID-19 using the hot and cold spot model
Figure 3 show the COVID-19 pandemic in the country using the hot and cold spot model for March 2, 2019 to the end of November 2021 for the indicators of infection, deaths, recovered relative to hospital, hospital beds and population. As it can be seen in 2019, COVID-19 patients are found only in the provinces of Tehran, the northern parts of Mazandaran and Qom.Fig. 3 Spatial distribution of COVID-19 pandemic with Getis-Ord Gi model a confirmed 2019, b confirmed 2020, c confirmed 2021, d death 2019, e deaths 2020, f deaths 2021, g recovered 2019, h recovered 2020, i recovered 2021
However, in 2020, there is a fast COVID-19 pandemic in the provinces of Tehran, East Azerbaijan and West Azerbaijan. The non-observance of health protocols caused many people in these provinces to become infected with COVID-19.
The announced conditions showed their results with a 99% confidence level in 2021 in the provinces of Tehran and Khorasan Razavi. Studies have shown that the spatial spread of COVID-19 pandemic from the provinces of Tehran, Qom, West Azerbaijan, East Azerbaijan, Isfahan and Mazandaran to the surrounding areas was growing rapidly.
With the rapid of COVID-19 in the provinces from March 2, 2019 to the end of November 2021, a major number of people died due to a lack of medical kits, hospital facilities and disregard for health protocols the provinces of Tehran and Isfahan, Khuzestan and Ilam had hot spots compared to other provinces in terms of deaths, with a 95% confidence level (Fig. 3).
The provinces of East Azerbaijan, Khorasan Razavi, Tehran and Fars had 95% of the recovery areas with internal points. However, the provinces of North Khorasan, Golestan, Kurdistan, Yazd, Isfahan, Qazvin and Zanjan as cold provinces with a 90% confidence level, in terms of cold and hot spots, didn’t show significant results in terms of recovery index (Fig. 3).
Assessment I anselin local moran
Anselin Local Moran I analysis was used to obtain stronger results in terms of hot spots and cold spots. Due to a series of weight characteristics, this method determines statistically considerable hot spots, cold spots, and spatial outlets. As shown in (Table 6), from March 2, 2019, to November 31, 2021, the confirmed index, deaths and recovered of the COVID-19 were found only in one high cluster in central Iran, including Tehran, Isfahan, Fars, and East Azerbaijan.Table 6 Estimation of geographical pattern of COVID-19 pandemic in Iran using Getis-Ord Gi *
Getis-Ord Gi * Confirmed
Morans I Variance Z-score P-value Pattern
0.081 0.002 0.689 0.4906 Random
Getis-Ord Gi * Deaths
Morans I Variance Z-score P-value Pattern
0.215 0.003 14.314 0.0000 Clustered
Getis-Ord Gi * Recovery
Morans I Variance Z-score P-value Pattern
0.299 0.004 4.662 0.0003 Clustered
This very high cluster shows that the risk of COVID-19 infection in these four provinces is much higher compared to other provinces of Iran, and the deaths and recovery rates are high compared to other provinces of Iran. Brasil [42], analyzed the spread and spatial pandemic of COVID-19 and identified the occurrence of clusters of COVID-19 in northeastern Brazilian cities, the results of his research show that COVID-19 is a dangerous crisis for health [43, 44]. Many studies have examined the spatial dynamics of the virus, however they have used a combination of spatial and spatial–temporal time-cycle methods on a small number of cases to analyze the COVID-19 pandemic.
Overall, the result of our research shows the exponential growth of mortality in the central regions of Iran, and the quick dispersion of this virus compared to other regions. Other studies have also been performed about two widespread diseases and COVID-19, and the bulk showed an affirmative relationship between patients with COVID-19 and other diseases for example, blood pressure, diabetes and cardiovascular diseases [45, 46]. Tabarej and Minz [47] spatial–temporal variation pattern in the epicenter footprint: a case study of confirmed, recovered and deceased cases of COVID-19 in India. The study found a sudden change in the hotspot region and a similar shift in the footprint from August. The changing pattern of the hotspot’s footprint will show that October is the riskier month for the first wave of COVID-19. Monte Carlo simulation with 999 simulations is taken to find the statistical significance. So, for the 99% significance level, the p-value is taken as 0.001.
Effect of population density on the COVID-19 pandemic
The geographical analysis of the COVID-19 pandemic in Iran shows that the spread of COVID-19 in the country is in the surrounding areas of Tehran province, north, west, and northwest of the country, and the highest spatial COVID-19 pandemic in Tehran provinces. Alborz, Ardabil, Bushehr, Ilam, and Khorasan Razavi due to high population density. Spatial and geographical studies show that the most significant factor in the COVID-19 pandemic in Iran is population density and spatial location, which has accelerated the COVID-19. In other words, up to a radius of 382 km from Tehran provinces, the COVID-19 due to provincial travel, non-compliance with health protocols, overcrowding in sales centers and population displacement due to capital accumulation and development of service and industrial sectors caused the dispersion. The virus increased, but from 763 km due to increasing focal length and decreasing population density, the pandemic of the virus gradually in 2021 showed a somewhat decreasing trend (Fig. 4). The results show that most of the confirmed cases are from provinces with high population density such as Tehran as the capital of Iran and Khorasan Razavi as a pilgrimage city though with medical facilities, many hospital beds. At the end of November 2021, the COVID-19 headquarters in these provinces were able to decrease the pandemic of COVID-19 as much as possible (Fig. 5). In the meantime, studies have been done on the origin, transmission and epidemiological characteristics of COVID-19 due to high population density [48, 49].Fig. 4 Population density in the provinces of Iran
Fig. 5 Relationship between population density and the COVID-19 pandemic at the level of the provinces of Iran
Isazadeh and Argany [50] showed that the intensity of the desease became more in the monthly COVID-19 pandemic in Qom province in an 8-month perusal era. In particular, from February to April for a two-month reduction, the number of cases increased anew in the next months. It seems that observance of health protocols including social distancing, regular hand washing, use of masks and gloves, lazing at home by people and closing of pilgrimage and tourist centers could reduce the disease in May and June. In China's Hubei province, a study was conducted, the results of this study showed that space clusters follow an upward pattern and undergo a sudden change, and due to high population density, the rapid pandemic of the COVID-19 was observed in this province [51].
Conclusion
The pandemic of COVID-19 has become a clinical threat to communities around the world. Today, the study of the geographical distribution of infectious viruses in the world is very important in discovering the cause and conditions of the pandemic of viruses in each region, so the WHO began using geographic information technology in the spatial analysis of viruses in 1993. In this paper, we modeled the spatial of COVID-19 pandemic during the period March 2, 2019, to the end of November 2021 using GWR, Getis Ord Gi * models (hot and cold spot analysis) and Moran's spatial self-solidarity in Iran we also used Moran's spatial correlation to deduce the 6 indicators of confirmed cases, deaths, recoveries, population, hospital beds, and hospital. Using Getis Ord Gi * (hot and cold spot) and GWR, we were able to identify which provinces were most likely to show confirmed, deaths and recovered events. Therefore, the link between COVID-19 hot and cold spots and population may be useful in future studies to investigate spatial insulin Moran correlation. The highest annual space distribution using the GWR model for approvals was seen from March 2, 2019, to the end of November 2020 in Ilam and Golestan provinces reaching over 5,973,457 confirmed in the country. With the continuation of this upward trend in the country, the spatial COVID-19 in its surrounding areas in densely populated provinces such as Tehran, Isfahan, Gilan, West and East, and Central Azerbaijan has been rapidly increasing by over 60%. of the population becoming infected with the virus. Not following the health protocols, pilgrimage trips and tourism to the neighboring provinces caused many citizens to lose their lives. Moran's spatial correlation in these provinces has been positive and statistically significant, and follows the cluster pattern. Following the health protocols of the COVID-19 headquarters and observing social distance and advertised warnings on social media, and tightening traffic caused the number of deaths to decrease by the end of November 2021. The spatial analysis models (hot and cold spot) show results different from the geographically weighted regression model for 31 provinces of Iran, in terms of the confirmed index of deaths and recoveries relative to the population, hospital, and hospital bed. In the central and southern parts of the provinces of Iran, including the provinces of Alborz, Tehran, Isfahan, Tabriz, Yazd and Fars, 99% confidence levels are hot spots. Nevertheless, the central provinces showed to be very hot spots with a 95% confidence level in terms of the index of deaths relative to the population compared to other places. In terms of index of deaths and recoveries as the safest provinces, the provinces of North Khorasan, Golestan, Kurdistan, Qazvin, and Zanjan showed cold spots with a level of 90% confidence, and were scheduled the least dangerous areas among the 31 provinces of Iran on March 2, 2019, to November 31, 2021. The results of Moran's spatial autocorrelation analysis of hot spots of COVID-19 for patients in 2019 showed that the Z-score was negative, indicating that the number of patients across the country has been declining on a random pattern. The Spatio-temporal hazard presented in this paper shows that the Spatio-temporal hazard model, based on the annual release of COVID-19, offers a good grasp of the changes caused by the virus throughout the country.
Acknowledgements
We the authors thank the referees for reviewing the paper
Funding
Not applicable.
Data availability
The data in this article is available through the following links: Monthly and annual counts of cases, deaths and recurrences of COVID-19 based on the provinces of Iran are available from the website of the Ministry of Health of Iran at the following address. https://behdasht.gov.ir/. Statistics and Information Department of Hospitals of Iran Province. Iran National Statistics Portal. https://www.amar.org.ir/.
Declarations
Conflict of interests
The authors declare no conflicts of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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==== Front
Multimed Tools Appl
Multimed Tools Appl
Multimedia Tools and Applications
1380-7501
1573-7721
Springer US New York
14247
10.1007/s11042-022-14247-3
Track 2: Medical Applications of Multimedia
LWSNet - a novel deep-learning architecture to segregate Covid-19 and pneumonia from x-ray imagery
Lasker Asifuzzaman [email protected]
1
http://orcid.org/0000-0002-4777-2492
Ghosh Mridul [email protected]
2
Obaidullah Sk Md [email protected]
1
Chakraborty Chandan [email protected]
3
Roy Kaushik [email protected]
4
1 grid.440546.7 0000 0004 1779 9509 Department of Computer Science & Engineering, Aliah University, Kolkata, India
2 Department of Computer Science, Shyampur Siddheswari Mahavidyalaya, Howrah, India
3 Department of Computer Science & Engineering, NITTTR, Kolkata, India
4 grid.419478.7 0000 0004 1768 519X Department of Computer Science, West Bengal State University, Barasat, India
3 12 2022
123
6 6 2022
18 8 2022
4 11 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Automatic detection of lung diseases using AI-based tools became very much necessary to handle the huge number of cases occurring across the globe and support the doctors. This paper proposed a novel deep learning architecture named LWSNet (Light Weight Stacking Network) to separate Covid-19, cold pneumonia, and normal chest x-ray images. This framework is based on single, double, triple, and quadruple stack mechanisms to address the above-mentioned tri-class problem. In this framework, a truncated version of standard deep learning models and a lightweight CNN model was considered to conviniently deploy in resource-constraint devices. An evaluation was conducted on three publicly available datasets alongwith their combination. We received 97.28%, 96.50%, 97.41%, and 98.54% highest classification accuracies using quadruple stack. On further investigation, we found, using LWSNet, the average accuracy got improved from individual model to quadruple model by 2.31%, 2.55%, 2.88%, and 2.26% on four respective datasets.
Keywords
Stack ensemble technique
Deep neural network
Chest radiography
Lung diseases
Pneumonia
Covid-19
==== Body
pmcIntroduction
Coronavirus disease often referred to as Covid-19, is a submicroscopic pathogen resulting from worldwide pandemics. Coronavirus causes rapid bronchial distress disorder, a severe type of asthma. It is a kind of atypical, human-to-human transmissible pneumonia. Due to its enormous adverse influence on the healthcare of the general community, the Covid-19 pandemic is currently the most serious issue affecting our entire world. To fight Covid-19, governments and rulers imposed a variety of different strategies, policies, and lifestyles [38]. Science and technology had significantly impacted the implementation of these new ideas and techniques.
Reverse transcriptase-polymerase chain reaction (RT-PCR) [21] and enzyme-linked immunosorbent assay (ELISA) [63] are two of the most commonly used methods for detecting Covid-19 viruses. The most effective screening tool for finding Covid-19 patients is RT-PCR, which can locate the virus’s RNA from lower respiratory tract samples. The whole testing method for identifying pathogens using RT-PCR is manual and time-consuming, with a high risk of false negatives of 39–61%. In any event, significant clinical development leading to pneumonia, chest imaging studies are regularly conducted in suspected or confirmed Covid-19 patients, by the recommendation of WHO [43]. Antibodies, antigens, proteins, and glycoproteins are routinely measured in biological samples using an immunological test known as ELISA.
According to preliminary research, people with Covid-19 or pneumonia infection show anomalies in their chest radiographs. It was suggested that radiography examination might be used as a critical means of pneumonia-based disease screening in epidemic areas [4]. Radiography analysis is an excellent complement to the RT-PCR test and, in some instances, even provides a positive index. Accommodations for chest imaging are easily accessible in modern medical systems, even though radiographic images cannot simply and rapidly solve our purposes. There was a high demand for expert radiologists in this epidemic. The healthcare industry needs a solution to this problem. The field of computer vision and image processing could manage this problem with the aid of advanced tools and techniques [17]. Machine learning and deep learning were extremely promising solutions for managing these issues.
Artificial intelligence is widely being applied in medical imaging identification, and analysis [39]. The advantage of deep learning-based techniques such as CNN, RNN, LSTM-RNN, etc., in the field of computer-vision, outperformed the work of professional radiologists [29]. Those CNNs-based framework extract feature and classification prediction capabilities are quite a height, but due to a tremendous amount of data required for the training purpose, authors [6] used pre-trained models to save CPU power and calculation time.
The chest X-ray image is readily available due to its low-cost compared to other tests; the correct diagnosis from only these images is an immediate need for mankind. Since it is difficult to diagnose COVID-19 and pneumonia from X-ray images manually by medical practitioners, an automated system is required to correctly diagnose these diseases from the pool of normal, pneumonia, and COVID-19 x-ray images.
In this research, we experimented with one of the largest datasets for COVID-19 identification, comprised of 20738 images in three classes. Here, a hybrid deep learning architecture is designed by the stack-ensemble method and tuned lightweight version of the three standard deep learning frameworks and a custom CNN framework. The proposed architecture is developed to consider the issue of deploying the system in low-configuration devices to make the diagnosis faster with high performance.
The key contributions of the present work are as follows: A novel stack ensemble deep learning framework namely LWSNet is proposed to segregate Covid-19, Pneumonia and Normal from x-ray imagery.
During stack ensemble process, truncated versions of MobileNetV2, VGG19 and InceptionResNetV2 were considered, making the final model lightweight for running at resource-constrained environments.
Three distinct public datasets were used to evaluate the performance of the proposed system.
Review of state-of-the-arts
It is essential to quarantine patients as soon as possible in order to control this infectious disease. Available resources are fast running out due to a constantly rising number of patients and lengthy treatment time [21]. Researchers from many disciplines and policymakers urgently need to develop a strategy to control the unwanted situation. We are attempting to concentrate on numerous computer vision areas to speed up the entire procedure. We explored some previously mentioned research areas on computer vision intelligent systems for automatic diagnosis. Researchers are using radiographic images to apply machine learning, and deep learning algorithms as the main categories to classify Covid-19 automatically and pneumonia disease [19, 20, 28, 55]. Other subcategories, such as multi-layer perceptron [62], ensemble [57], LSTM [22], fusion [53], and fuzzy [62], were applied for categorization. Those categories can implement different imaging modalities like X-ray, CT, etc.
Stack ensemble classification
The method of increasing the performance of the classifier by aggregating the already learned sub-models to tackle the same classification task is known as ensemble learning [36]. Each base learner takes a vote, and the meta-learner, a model that learns to improve the base learners’ predictions, receives the final prediction. Tang et al. [57] suggested ensemble learning can solve deep learning’s drawbacks by making predictions with several models rather than as a single model. Their experiment showed the results with good accuracy of 95%. Saha et al. [50] proposed a model that extracted deep features from X-ray images, then used an ensemble classifier. They obtained individual scores before implementing an ensemble classifier, which provides better accuracy from 1320 images. The highest accuracy, precision, recall, and F1-score were 98.91%, 100%, 97.28%, and 98.89%. Li et al. [31] combined ensemble with VGG16 as a base model, and they used cascade classifier from multiple training sets.
Annavarapu et al. [5] introduced a new ensemble technique for reducing the computationally learning cost. They named this approach the snapshot ensemble technique. Snapshot Ensembling’s adaptability with a wide range of network models and learning tasks was verified by its cyclic learning rate scheduling. This snapshot ensemble approach saved the local minima parameter and changed the model during runtime. They used ResNet50 as a base architecture. Chowdhury et al. [9] used the snapshot ensemble model, which is based on EfficientNet model. To identify and predict a critical section, they used the Grad-CAM model to visualize a CAP. They published their overall accuracy of 96.07% for Covid-19 detection.
Upadhyay et al. [60] implemented a fusion-based model to categorize three distinct classes. They used the handcrafted color-space method to collect specific features from X-ray images and then applied a stacked ensemble. Abdar et al. [1] proposed novel model named Uncertainty FuseNet. It is based on the fusion method using ensemble dropout currently. This model produced good results in noisy data.
Gifani et al. [52] implemented a pre-trained model using a total of 15 pre-trained architectures and fine-tuned the target classes. Among the 15 pre-trained architectures, the majority of voting was applied only on 5 architectures.
Deep transfer learning
Deep Transfer Learning is a method of deep learning where knowledge is transmitted from one model to the other. Zhu et al. [64] used traditional CNN and VGG16 net models. They optimized both the models and evaluated the predictions. But a weakness of their work was the selection of fewer chest images. Gupta et al. [18] worked with a five pre-trained integrated stack model called InstaCovNet-19. For boosting classification, various training and pre-processing techniques were applied. They benchmarked their model on other state-of-the-art approaches. Fan et al. [12] experimented with five pre-trained models and applied three optimizers using different learning rates. In addition, they used a 10-fold cross-validation approach. They achieved an average accuracy of 97%. Mohammadi et al. [35] discussed four popular pre-trained models with binary classification and obtained 99.1% accuracy using MobileNet for identifying Covid-19 disease from a chest X-ray. Niu et al. [42] proposed a new technique named distant domain transfer learning (DDTL). They used two models, namely reduced-size U-net Segmentation and Distant Feature Fusion. Their models worked on unstructured data and efficiently handled the variation in distribution during the training and testing data. Rezaee et al. [48] introduced a pre-trained deep learning architecture-based hybrid deep transfer learning technique. They utilized feature extraction, feature selection, and a support vector machine to classify. Other researchers presented their approach in aiming for pneumonia-based disease as an exception to these limited categories of deep learning and machine learning model. Saha et al. [49] used a pre-processing method to transform image data into an undirected graph such that simply the edges of the image are considered rather than the entire image. These networks showed impressive accuracy of 99% for the limited dataset. Another effective approach utilized by researchers for classification is the segmentation method. Munusamy et al. [41] proposed an architecture using segmentation of CT images and segregation on X-ray images. They used the U-net model for segmentation purposes and combined the location information. They compared their classification model with different pre-trained standard architecture, and overall accuracy of 99% was reported.
Lightweight CNN
In lightweight CNN, layers of the network are made reduced considering the system’s complexity, and accuracy trade-off [40]. Karakanis et al. [26] implemented a lightweight model in addition to a conditional generative adversarial network to develop synthetic images to replace the minimal data set. They began with a two-class dataset but later switched to a three-class dataset, which performed better. Paluru et al. [44] proposed 7.8 times fewer lightweight parameters using U-net architecture. They showed that their model performed well compared to the other six standard models. They claimed that their model could also run on a low configuration system. Ter-Sarkisov et al. [58] discussed lightweight segmentation models based on R-CNN masks with different standard architecture. The lightweight model isn’t limited to working with fixed images or structural data. Trivedi et al. [59] proposed a lightweight architecture based on MobileNet that can identify pneumonia from chest x-ray images. A benchmark dataset containing 5856 images in two classes was used. Additionally, they discussed the total training time for preparing the lightweight model and represented the accuracy at 97.09%.
The state-of-the-art research dealt with available datasets ignoring the performance over the conglomeration effects of these datasets. The system deployment issue on the resource-constraint devices is also a significant research gap to the best of our knowledge.
Proposed method
In this work, we considered deep learning-based models. Medical fields were significantly benefited from deep learning, including the detection of lung infection. In recent years, due to their impressive classification capabilities, deep learning methods were gained popularity on COVID-19. It was also observed that deep learning models outperform handcrafted feature-based models [14]. To train a deep learning model, a huge amount of data and a good amount of training time are required. So to abstain from these issues, here, transfer learning-based models were considered.
Transfer learning [15] is a machine training strategy where a system is built utilizing many training samples for a specific assignment and then used as the starting solution in another study. Rather than constructing the whole architecture initially, a pre-trained framework was used since this learning technique assures how an architecture trained for one problem may perform on another issue. As a result, the learning process is more resilient and adaptable. In addition, building a deep neural framework from scratch necessitates a high volume of samples and a significant quantity of cost time. Transfer learning allows one to focus on the beginning efforts rather than developing an entire deep architecture. Through the use of the transfer learning technique, three well-established deep learning architectures are transformed into lightweight models that are fine-tuned, as discussed in Section 3.1.
Amongst different deep learning frameworks [32], CNN is a very useful technique for processing spatial data. It is generally made up of three tiers: convolution, pooling, and dense. The design of such networks allows us to learn a wide range of complicated patterns that a basic neural network often fails to perform. CNN-based frameworks are a wide variety of uses, including self-driving cars, robots, surgical operations, etc. The convolutional layer transfers the presence of features observed in individual portions of the input images into a feature map. The process of creating a feature map from this layer is as follows: 1 νm,n=∑m=1m∑n=1nρ(m−j,n−k)∗xj,kr
Where, xj,kr represents the kernal for the jth,kth pixel in cth layer over the instance ρm,n and * represent the convolution operator. 2 νm,n=λ∑m=1m∑n=1nρ(m−j,n−k)∗xj,kr
Here, λ denotes ReLU (rectified linear unit) activation function, which can be expressed as 3 λ(z)=max(0;z)
if(z < 0);Re(z) = 0otherwise,Re(z) = z,where,zdenotestheneuroninput.
The softmax activation function is utilized in the network’s last dense layer, can be represented as 4 χ(n)=en∑1men
Here, n signifies the source vector, which has a length of m.
Proposed lightweight models
In this work, we proposed lightweight versions of existing deep CNN models: MobileNetV2, VGG19, and InceptionResNetV2, and designed a custom lightweight CNN (CLCNN) architecture. Developing lightweight stack ensemble models aims to deploy the system into resource-constraint devices. The number of parameters generated in the lightweight models is significantly less than the original counterpart.
Lightweight MobileNetV2
MobileNet-V2 is built on the principles of MobileNet-V1, which uses depth-wise separable convolution as a robust building component. They introduced an inverted residual block and a linear bottleneck framework in this version [51]. The original MovibleNetV2 architecture has fifty-three levels and 3.4 million parameters in its final version. In contrast, the proposed lightweight version consists of only the top twenty-five layers and utilizes 0.139331 M parameters. The structure and parameter details of this architecture are shown in Table 1. Table 1 Layer-wise parameter details for the lightweight models
Layers Network Input Dimension (# Parameter)
MobileNetV2 InceptionResNetV2 VGG19 Proposed
Conv1 (Conv2D) 112×112×32 (864) 111×111×32 (864) 224×224×64 (1792) 222×222×64 (1792)
BatchNormalization_Conv1 112×112×32 (128) 111×111×32 (96) 224×224×64 (36928) 220×220×32 (18464)
Activation – 111×111×32 (0) – –
Conv1_relu (ReLu) 112×112×32 (0) – – 108×108×16 (2320)
Expanded_conv_depthwise 112×112×32 (288) 112×112×64 (0) 112×112×64 (0) –
BatchNormalization_3 112×112×32 (128) – 112×112×128 (73856) –
Expanded_conv_depthwise_relu 112×112×32 (0) – – –
Expanded_conv_project 112×112×16 (512) – 112×112×128 (147584) –
Expanded_conv_project_BN 112×112×16 (64) – – –
Block_1_expand (Conv2D) 112×112×96 (1536) – – –
Block_1_expand_BN 112×112×96 (384) – – –
Block_1_expand_relu (ReLu) 112×112×96 (0) – – –
Block_1_pad (ZeroPadding2D) 113×113×96 (0) – – –
BatchNormalization_3 – 109×109×32 (96) – –
Activation_1 – 109×109×32 (0) – –
Conv2d_4 (Conv2D) – 109×109×64 (18432) – 106x106x8 (1160)
BatchNormalization_4 – 109×109×64 (192) – –
Expanded_conv_depthwise 56×56×96 (864) – – –
Expanded_conv_depthwise_BN 56×56×96(384) – –
Expanded_conv_depthwise_relu 56×56×96 (0) – – –
Block_1_expand (Conv2D) 56×56×24 (2304) – – –
Block_1_expand_BN 56×56×24 (96) – – –
Block_2_expand (Conv2D) 56×56×144 (3456) – – –
Block_2_expand_BN 56×56×144 (576) – – –
Block_2_expand_relu (ReLu) 56×56×114 (0) – – –
Block_2_depthwise 56×56×144 (1296) – – –
Block_2_expand_BN 56×56×144(576) – – –
Activation_2 (Conv2D) – 109×109×64 (0) – –
Max_pooling2d_2 – 54×54×80 (0) – –
Conv2d_5 (Conv2D) – 54×54×80 (5120) – 106×106×16 (2320)
BatchNormalization_5 – 54×54×80 (240) – –
Activation_3 (Conv2D) – 54×54×80 (0) – –
Conv2d_6 (Conv2D) – 52×52×192 (138240) – –
BatchNormalization_6 – 52×52×192 (576) – –
Activation_4 (Conv2D) – 52×52×192 (0) – –
Max_pooling2d_1 – 25×25×192 (0) 56×56×128 (0) –
Conv2d_10 (Conv2D) – 25×25×64 (12288) 27×27×32 (36896) 51×51×8 (1160)
BatchNormalization_10 – 25×25×64 (192) – –
Block_2_expand_relu (ReLu) 56×56×144 (0) – - –
Block_2_project (Conv2D) 56×56×24 (3456) – – –
Conv2d_1 (Conv2D) 27×27×32 (6944) 12×12×32 (18464) – 49×498 (584)
Droupout_1 (Dropout) 23328 (0) 4608 (0) 23328 (0) –
Flatten_1 (Flatten) 23328 (0) 4608 (0) 23328 (0) –
Droupout_2 (Dropout) – 4608 (0) – –
Batch_normalization 23328 (93312) 4608 (18432) 23328 (93312) –
Dense 3 (69987) 3 (9218) 3 (69987) 3 (13827)
Trainable parameters 139,331 226,131 413,699 42,835
Lightweight VGG19
Simonyan and Zisserman [54] at the University of Oxford, UK, in early 2014, designed a CNN model named VGG network. VGG (Visual Geometry Group) was trained using the ImageNet ILSVRC dataset, consisting of more than 1 million pictures. According to these picture patterns, pictures are divided into 1000 categories and utilize more than 100 thousand images for training and 50 thousand images for validation. VGG-19 is a VGG variation with 19 densely linked layers that routinely outperform other state-of-the-art models. The model is made up of convolutional and fully connected layers that allow for enhanced feature extraction and the use of maxpooling instead of average pooling for downsampling, and modifying the linear unit (ReLU) as the activation function, selecting the largest value in the image area as the pooled value.
Lightweight InceptionResNetV2
The Inception-ResNet architecture [56] combines Inception block with residual module. In each Inception component, there is a filter expansion layer, which is used to scale up the depth of the filter bank to match the depth of the input. We made a lightweight version of this architecture by considering only the top twenty layers out of one hundred sixty-four. There are 0.2261 M parameters generated in this pre-trained lightweight architecture, whereas 55 M parameters are in the original architecture. In Table 1 the structure and parameter details of the lightweight InceptionResNetV2 architecture model are presented.
Custom lightweight CNN (CLCNN)
In this CLCNN framework (shown in Fig. 1), six convolution layers with 64, 32, 16, 16, 8, and 8 filters accompanied by two max-pool layers having a pooling size of 2 × 2 were considered. One max-pool layer is placed after the first two convolutions layers, and the second one is employed at the end of the fourth convolution layer. A dense/output layer of size 3 was used. In ablation study, we obtained the accuracies of 96.25%, 96.45%, 96.42%, and 96.35%, using 0.3, 0.4, 0.5, and 0.6 dropout values, respectively. Since a dropout of 0.4 yielded the best accuracy, we considered this value throughout the rest of the experiments. The layer-wise number of trainable parameters generated is shown in Table 1. The number of trainable parameters in original and lightweight versions is tabulated in Table 2. Fig. 1 CLCNN architecture for Covid-19 and pneumonia classification
Table 2 The comparison of number of trainable parameters (Million) between original and lightweight versions
Architecture Name Trainable Parameter Less parameter (%) of lightweight model
Original Model Lightweight Model
MobileNetV2 3.4 M 0.139331 M 96.03
InceptionResNetV2 55 M 0.226131 M 99.59
VGG19 144 M 0.413699 M 99.71
Customize CNN – 0.042835 M –
Lightweight stack ensemble learning
The prediction outcome suffers from high variance, and generalization problems [24] occur due to noise in the training data and the unpredictability of the deep learning models. We considered a stack ensemble approach to boost efficiency. It uses deep learning architecture for non-linear integration of predictors to increase prediction accuracy while reducing training errors. Specifically, several ensemble techniques are available, but among all the technique stacking generalization, [61] method is most effective in terms of accuracy. Before obtaining the final prediction, passing information through one group of classifiers to other sets of classifiers is known as stacking generalization. The information in the classifier network originates from several subgroups of the training set. The original training set is split into numerous subgroups of training sets, a distinguishing property of stacking generalization. Each sub-training group is utilized to gather biased information on the dataset’s generalization behavior, which is then used to populate the classifier network. This study developed an ensemble-based stacked framework for improving classification by combining predictions of different models and obtaining the highest positive true predictive values.
Figure 2 depicts the architecture of the proposed lightweight stack ensemble learning framework. In this architecture, we considered lightweight CNN models as single models. Then the stacked ensemble was designed considering double stack, triple stack, and quadruple stack. The performance of the single models was evaluated after classification from the final predictor. The double stack consists of, MobileNetV2 & VGG19, MobileNetV2 & InceptionResNetV2, MobileNetV2 & CLCNN, VGG19 & InceptionResNetV2, VGG19 & CLCNN, and InceptionResNetV2 & CLCNN. Similarly, a triple stack consists of three base architecture such as InceptionResNetV2 & VGG19 & MobileNetV2, InceptionResNetV2 & VGG19 & CLCNN, and MobileNetV2 & VGG19 & CLCNN. This quadruple stack comprises MobileNetV2, VGG19, InceptionResNetV2, and CLCNN. This multi-stack prediction is fed to the meta-learner. In the meta-learner, three dense layers having sizes 512, 256, and 128 were deployed. The meta-learner predictions are fed to the final prediction block, which comprises a dense layer of dimension 3. Fig. 2 Four-step experiments of the proposed lightweight stack ensemble learning architecture
Experiment
The LWSNet is a classification problem to detect Covid-19 from chest X-ray images. Since the infection is unusual and has pneumonia-like characteristics, we included pneumonia images along with Covid-19 and normal images in our experiment.
Setup
We performed training and evaluation of our proposed system on a GPU machine consists of two core Intel(R) Core(TM) i5-10400 H CPU @ 2.60 GHz 2.59 GHz, 32 GB of RAM, and two NVIDIA Quadro RTX 5000. It runs on Windows 10 Pro OS version 20H2 with TensorFlow 2.0.0 installed for deep learning model training and inference, where cuDNN is enabled to speed up the training computation on a GPU device. Table 3 Details of the databses used in the current experiment
Datasets Covid-19 Normal Pneumonia Total
Dataset 1 [45] 576 1583 4273 6432
Dataset 2 [10] 1808 5096 672 7576
Dataset 3 [47] 874 1583 4273 6730
Dataset 4 (combined) 3258 8262 9218 20738
Datasets
The datasets used in this study were obtained from three different public sources and contained three classes. As a result, since Covid-19 is a novel disease, only a limited number of benchmark datasets are available for studies. The first datasets were collected from Kaggle repositories, which contained 6432 samples divided into three classes. The second dataset was constructed using 50% of chest X-ray images from Kaggle repositories with three classes. This dataset contains 21165 chest X-ray images from four classes. The third dataset is mixed with two public repositories; one is the GitHub repository with Covid-19 images, which is constantly updated by a researcher named Cohen et al. [11] at the Montreal University, and the other datasets are taken from the Kaggle repository [37] with two classes: Normal and Pneumonia. These mixed datasets are also available in the Kaggle repository. In order to conduct further experiments, we prepared a combined dataset. Merge three datasets with their respective classes to create a combined dataset. Table 3 represents the number of images containing three categories: Covid-19, Pneumonia, and Normal, from four different datasets. In Fig. 4 the sample sizes using an 8:2 train-set of three datasets are shown. The sample images of three classes corresponding to the three datasets are presented in Fig. 3. Fig. 3 Organize the three datasets Dataset 1, Dataset 2, and Dataset 3 with their corresponding classes of images in three columns: (a) Covid-19, (b) normal, and (c) pneumonia
Evaluation protocol
To evaluate the performance of our LWSNet, we used different evaluation metrics since accuracy is not sufficient [13] to justify the performance of the proposed framework, especially in disease detection cases. The classification of diseases is based directly on the number of True Positives, False Negatives, True Negatives, and False Positives. Using these values, the following matrices are used to evaluate model performance from different perspectives:
Sensitivity
Sensitivity is a measure that evaluates the number of patients who was detected as positive in a scenario when the patient is genuinely effected.
Specificity
Specificity is a measure that evaluates the number of patients who was not been detected as negative in a scenario when the patient is genuinely not effected.
F1-Score
Statistics use F1 scores to determine how accurate a test is when analyzing classification data. During the computation of the F1 score, the precision and recall of the test are both considered. The F1 score is the harmonic average of precision and recall, where 1 is the best and 0 is the worst score.
Precision
Precision is the positive prediction value for the corresponding diseases. A predicted value of this disease is calculated based on true and false positives.
Negative predictive value
The negative predicted value is calculated based on the true, and false negative values.
Miss rate
Miss rate refers to the result of a test which suggests that a person does not have a specific disease when, in reality, that person does in fact, have that disease.
Fall-out
One of the most significant risks of receiving a false positive result is when the person is cohorted with other patients who are suffering with Covid-19 and is thus exposed to the virus.
False discovery rate
When making multiple comparisons, the false discovery rate is a means of conceptualizing the rate of type I error in the null hypothesis testing that is often used. Statistical approaches for regulating false discovery rates are intended to keep the predicted percentage of rejected null hypotheses) from exceeding a certain threshold.
False omission rate
It is The statistical technique, which is the complement of negative predictive value, is employed in multiple hypothesis testing to account for numerous comparisons. It calculates the percentage of false negatives that are wrongfully rejected.
Training regime
The datasets are of different sizes, so the images were resized into dimensions of 224 × 224 as a pre-processing step. The datasets were split into 8:2 train-test sets. The reason for the 8:2 division is that it was observed that the 8:2 train-test set gave better results compared to other ratios [64]. By this split, there are 5144 trains and 1288 tests for dataset 1. For dataset 2, 6061 images were considered in training, while 1515 images were for testing. Similarly, 5384 images were used in training, and the rest, 1346, were kept for testing dataset 3. To show the robustness of LWSNet, we combined all three datasets with their respective classes. In this combination, there are 16592 trained images and 4146 test images. At the beginning of the experiment, the learning rate was set to 0.001. The performance was evaluated at the interval of 0.001 learning rate. A dropout value was set at 0.5 throughout our experiment. Accordingly, the initial and secondary momentum exponential decay rates were fixed to 0.9 and 0.999. The epsilon level was set to 0.0000001. The value of the AMSGrad Boolean optimization parameter variable was set to false.
Results & analysis
Several levels of experiments were conducted to build the LWSNet model. The experiment was performed on single as well as double, triple, and quadruple stacking experiments. A total of 60 experiments were conducted during the experimentation period. To demonstrate the performance of LWSNet, we used different statistical approaches. Table 4 Accuracy and loss values for the three datasets and the combination of three datasets in the quadruple stack model for diverse learning rates
Learning Rate Dataset 1 Dataset 2 Dataset 3 Combined
Accuracy Loss Accuracy Loss Accuracy Loss Accuracy Loss
0.001 0.9805 0.0912 0.9658 0.2430 0.9651 0.3751 0.9786 0.1283
0.0001 0.9719 0.1785 0.9643 0.2186 0.9641 0.3660 0.9786 0.1085
1.00E-05 0.9727 0.1829 0.9741 0.2196 0.9638 0.3613 0.9854 0.1101
1.00E-06 0.9728 0.1852 0.9658 0.2241 0.9634 0.3630 0.9779 0.1136
1.00E-07 0.9719 0.1826 0.9643 0.2216 0.9638 0.3623 0.9767 0.1126
1.00E-08 0.9727 0.1833 0.9658 0.2245 0.9634 0.3616 0.9774 0.1131
1.00E-09 0.9727 0.1848 0.9658 0.2235 0.9634 0.3615 0.9777 0.1116
1.00E-10 0.9727 0.1848 0.9643 0.2234 0.9638 0.3601 0.9779 0.1128
To test the underfit and overfit of single architectures, the accuracies and corresponding losses were presented in Fig. 4. It is seen that using mobileNetV2 training and validation loss were almost null, whereas, in InceptionResNetV2, there is a validation loss of 0.17%. Similarly, VGG19 and Custom CNN loss were generated at 0.08 and 0.27. In Table 4 the accuracies and losses corresponding to the learning rates are presented for the quadruple stack model on four datasets. Changing the learning rate is very significant in building a better DL model. We observed that accuracy gradually increased and loss decreased when learning rates were decreased. Fig. 4 Training accuracy and training loss, validation accuracy and validation loss for individual lightweight models on dataset 1
The results of individual lightweight architecture: MobileNetV2 (Mbl), VGG-19 (Vgg), InceptionResNetV2 (Incp) and Custom lightweight CNN (CLCNN) are depicted in Fig. 5, also represent other three stacking experiment results. In the four different individual lightweight models, the average accuracy of the datasets 1, 2, 3, and combined is 96.22%, 93.95%, 94.52%, and 95.84%, respectively. The average values of MobileNetV2, VGG-19, InceptionResNetV2, and CLCNN for those four datasets are 94.00%, 94.48%, 95.74%, and 95.39%, respectively. Fig. 5 Consolidated accuracy graph to single architecture to quad stack architecture. The individual model’s abbreviation within brakets is MobileNetV2(Mbl), VGG19(Vgg), InceptionResNetV2(Incp), and custom lightweight CNN (CLCNN) and ‘+’ sign indicate that models are concatenated for ensemble stacking
In this experiment, the batch size of 32, initial learning rate 0.001, optimizer RMSprop, activation function ReLu, and epoch size 100 were considered. We utilized these parameters for training four individual architectures. The results of four datasets showed that our CLCNN architecture performed well as compared to the pre-trained lightweight architecture. In the CLCNN architecture, only 42,899 trainable parameters were used, which were 2.24, 4.27, and 8.64 times less than mobileNetV2, InceptionResNetV2, and VGG19, respectively. The parameters are tabulated in Table 2. Stacking approaches were divided into three phases according to the proposed lightweight stack ensemble architecture. The stacking process in the first phase was done by selecting two lightweight models among the 4 variants. Using these selection criteria, a total of six combinations are there in a dataset. As a result, using the double-stack ensemble technique, a total of 24 experiments were carried out on four datasets. Compared to individual models, in the double-stack ensemble model, the accuracies improved by 0.32%, 1.54%, 1.14%, and 1.22% for dataset 1, dataset 2, dataset 3, combined, respectively. For dataset 2, the double-stacked architecture performed better than the single-lightweight architecture in terms of average accuracy. In the second step, we took three distinct models and combined them into a single stack. Three lightweight models were selected from four types of the triple stack model. The average accuracy gained by the triple stack model compared with the double stack was 0.88%, 0.68%, 0.36%, and 0.51% for datasets 1, 2, 3, and combined, respectively.
Testing was conducted further by changing the number of epochs from 50 to 300 with 50 epoch intervals considering the batch size of 32. But, the system’s performance didn’t increase for the increasing number of an epoch. Considering 100 epochs, we experimented again by changing the batch size by 64, 128, and 256. For 128 batch size, the quadruple stack block returns the highest accuracies of 98.54%, 96.50%, 97.41%, and 98.10%, on dataset 1, 2, 3 and combined, respectively.
The accuracy value of a system cannot be the only measure of its performance. We further calculated other statistical measures to check the architecture performance. We used nine statistical metrics to evaluate the LWSNet architecture’s efficiency in terms of correctly and incorrectly identified X-ray images with their respective diseases. From the Table 5 we observed that false positive rate is 0.0009, 0.0181, 0.0026 and 0.0010 for Covid-19 classes in Dataset 1, 2, 3, and Combined, respectively. Table 5 Quad stack performance evaluation for different datasets
Rate Dataset 1 Dataset 2 Dataset 3 Combined
C N P C N P C N P C N P
Sensitivity 0.9661 0.9650 0.9848 0.9632 0.9708 0.9148 0.9716 0.9678 0.9847 0.9652 0.9739 0.9839
Specificity 0.9991 0.9866 0.9676 0.9819 0.9539 0.9920 0.9854 0.9795 0.9886 0.9820 0.9956
F1-score 0.9785 0.9619 0.9842 0.9524 0.9743 0.9165 0.9771 0.9601 0.9864 0.9517 0.9733 0.9892
Precision 0.9913 0.9589 0.9836 0.9419 0.9779 0.9182 0.9828 0.9525 0.9882 0.9386 0.9728 0.9946
Negative predictive 0.9966 0.9886 0.9698 0.9887 0.9395 0.9917 0.9957 0.9902 0.9735 0.9937 0.9828 0.9870
Miss rate 0.0339 0.0339 0.0152 0.0368 0.0368 0.0852 0.0284 0.0284 0.0153 0.0348 0.0348 0.0161
Fall-out 0.0009 0.0134 0.0324 0.0181 0.0461 0.0080 0.0026 0.0146 0.0205 0.0114 0.0180 0.0044
False discovery 0.0087 0.0411 0.0164 0.0581 0.0221 0.0818 0.0172 0.0475 0.0118 0.0614 0.0272 0.0054
False omission 0.0034 0.0114 0.0302 0.0113 0.0605 0.0083 0.0043 0.0098 0.0265 0.0063 0.0172 0.0130
Error analysis
It was observed from Table 4 that changing the learning rates 0.001, 1.00e-06, and 1.00e-05, the lowest error rate of 1.46%, 2.59%, 3.49%, and 1.90% were generated for a quadruple stack using dataset 1, 2, 3, and combined, respectively. The correctly and incorrectly classified samples for each respective dataset can be understood easily from the confusion matrices as shown in Fig. 6. It is observed that for dataset 1 in Fig. 6(a) the lowest error was generated, i.e., 26 samples out of 1285 sample size were misclassified. As a result of this sample size, one instance of Covid-19 was misclassified as pneumonia, and one instance of normal was misinterpreted as Covid-19, while three instances of pneumonia were wrongly classified as Covid-19. Similarly, in the combined dataset, 22 samples were misclassified to detect Covid-19, while 30 samples were misclassified to detect pneumonia (Fig. 6(d)). Fig. 6 Confusion matrix of quad stack architecture of (a) Dataset 1, (b) Dataset 2, (c) Dataset 3, and (d) Combined dataset
In Fig. 7, the misclassified instances of images are shown. The possible reasons of misclassification are noisy, blur, and opaque images. Fig. 7 The first column represents the target class, and misclassified samples of the target class are represented by the second and third columns. Here, the first row and the first column represent the target class of Covid-19. In the same row, the second and third columns represent misclassified samples that are normal and pneumonia, similarly in the second and third rows
Comparative study
We compared LWSNet with the standard lightweight deep learning models for dataset 1, 2, 3, and combined dataset. The results indicate that the proposed LWSNet model is most effective in four datasets, particularly in the combined dataset. The accuracy of LSWNet was improved by 3.77%, 2.07%, 2.88%, and 2.09% when compared with lightweight MobileNet, InceptionResNetV2, and CLCNN in the combined dataset, respectively. In Table 6, along with accuracy, precision, sensitivity, and f1-score, the inference time for a batch size of 128 is also presented for single models and LSWNet. Table 6 Evaluation metrics of lightweight deep learning models with LWSNet on given X-ray images datasets
Datasets Models Name Precision Sensitivity f1-score Accuracy(%) Time/step
Dataset 1 MobileNet 0.9520 0.9563 0.9540 96.34 694 ms
InceptionResNetV2 0.9508 0.9529 0.9512 96.19 695 ms
VGG19 0.9498 0.9588 0.9541 96.58 693 ms
Custom CNN 0.9550 0.9447 0.9498 95.80 692 ms
LWSNet 0.9632 0.9765 0.9697 97.28 690 ms
Dataset 2 MobileNet 0.8979 0.8992 0.8982 92.51 85 ms
InceptionResNetV2 0.9350 0.9350 0.9350 95.05 86 ms
VGG19 0.8870 0.9101 0.8978 93.04 84 ms
Custom CNN 0.9349 0.9310 0.9334 95.21 84 ms
LWSNet 0.9512 0.9489 0.9500 96.50 80 ms
Dataset 3 MobileNet 0.9142 0.9205 0.9178 93.15 421 ms
InceptionResNetV2 0.9494 0.9572 0.9512 95.98 419 ms
VGG19 0.9165 0.9318 0.9236 93.82 420 ms
Custom CNN 0.9412 0.9438 0.9425 95.16 419 ms
LWSNet 0.9745 0.9747 9746 97.41 417 ms
Combined Dataset MobileNet 0.9440 0.9294 0.9362 94.77 383 ms
InceptionResNetV2 0.9633 0.9565 0.9598 96.48 384 ms
VGG19 0.9515 0.9522 0.9517 95.66 386 ms
Custom CNN 0.961 0.9477 0.9540 96.45 385 ms
LWSNet 0.9779 0.9719 0.9748 98.54 384 ms
The proposed architecture was compared with other state-of-the-art architecture. In Table 7, it is seen that the accuracies were improved by 4.54%, 0.93%, and 0.28% and the F1-score on dataset 1 were improved by 4.48%, 1.12%, and 1.48% in comparison with the article of Gour et al. [16], Abdar et al. [1], and Jain et al. [23], respectively. Also, comparing the techniques [3, 27, 33, 46], with this proposed method for dataset 2, the accuracies got improved by 0.73%, 5.86%, 1.39%, and 0.50%. But, compared with the work of Aggarwal et al. [2] a loss of 0.50% of accuracy was also observed. Using the same dataset, the f1-scores of our method comparing with Rahman [46] and Lafraxocite [33] were improved by 1.11% and 1.97%, respectively. For dataset 3, the f1-scores in our technique were improved by 0.48%, 5.49%, 0.66%, and 4.46%, and the accuracies were gained by 0.40%, 6.91%, 8.41%, and 0.98% comparing the results of the articles of [7, 8, 30, 34], respectively. Table 7 Comparison with same public X-ray images dataset by using different evaluation metrics
Datasets Author’s Precision Sensitivity f1-score Accuracy(%)
Dataset 1 Gour et al. [16] 0.9581 0.9333 0.9300 92.74
Abdar et al. [1] 0.9635 0.9637 0.9636 96.35
Jain et al. [23] 0.9800 0.9466 0.9600 97.00
Proposed LWSNet 0.9632 0.9765 0.9697 97.28
Dataset 2 Lafraxo et al. [27] 0.9369 0.9366 0.9367 95.77
Ahmed et al. [3] 0.9200 0.8900 0.8980 90.64
Rahman et al. [46] 0.9455 0.9456 0.9453 95.11
Loey et al. [33] 0.9608 0.9604 0.9605 96.00
Aggarwal et al. [2] 0.9766 0.9733 0.9733 97.00
Proposed LWSNet 0.9512 0.9489 0.9500 96.50
Dataset 3 Li et al. [30] 0.9700 0.9709 0.9698 97.01
Mangal et al. [34] 0.9128 0.9414 0.9198 90.50
Chatterjee et al. [8] 0.8500 0.9350 0.9680 89.00
Kanwal et al. [25] 0.1000 0.1000 0.1000 93.00
Chakraborty et al. [7] 0.9900 0.9368 0.9300 96.43
Proposed LWSNet 0.9745 0.9747 0.9746 97.41
Conclusion
In this work, we presented LWSNet, a lightweight stack ensemble architecture to segregate Covid and non-Covid pneumonia. We explored truncated versions of three state-of-the-art networks, namely MobileNetV2, VGG19, InceptionResNetV2, and CLCNN architecture for the said problem. Further, the stack ensemble technique was employed on these four tailors-made models. Three different stacking techniques, namely double, triple and quadruple stacking, were experimented. Among all, the quadruple stack ensemble produced the highest accuracy of 97.28%, 96.50%, 97.41%, and 98.54%, using datasets 1, 2, 3, and combined, respectively, which outperform the state-of-the-art.
Our plan for the future is threefold: (i) the experiments will be carried out on other radiological images such as CT and MRI, (ii) different advanced deep learning architectures such as generative adversarial network, attention-based encoder-decoder, zero-shot learning, etc., will also be explored, and (iii) fusion of deep and handcrafted features, and clinical information (upon availability) will also be evaluated.
Acknowledgement
The fourth author would like to acknowledge Indian Council of Medical Research, Govt of India [Ref. No. BMI/12(81)/2021] for the research work.
Data Availability
This study used a secondary dataset as described by Rahman et al. in [10, 37, 45, 47]. The dataset can be obtained from the https://www.kaggle.com repository using this direct links: https://www.kaggle.com/datasets/tawsifurrahman/covid19-radiography-database, https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumoniahttps://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia, https://www.kaggle.com/datasets/prashant268/chest-xray-covid19-pneumoniahttps://www.kaggle.com/datasets/prashant268/chest-xray-covid19-pneumonia.
Declarations
Conflict of Interests
The authors declare that they have no conflict of interest.
Asifuzzaman Lasker and Mridul Ghosh contributed equally to this work.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734972 | NO-CC CODE | 2022-12-14 23:28:31 | no | Multimed Tools Appl. 2022 Dec 3;:1-23 | utf-8 | Multimed Tools Appl | 2,022 | 10.1007/s11042-022-14247-3 | oa_other |
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Can J Public Health
Can J Public Health
Canadian Journal of Public Health = Revue Canadienne de Santé Publique
0008-4263
1920-7476
Springer International Publishing Cham
36482144
715
10.17269/s41997-022-00715-8
Special Section on COVID-19: Quantitative Research
Pathways of association between disordered eating in adolescence and mental health outcomes in young adulthood during the COVID-19 pandemic
http://orcid.org/0000-0002-2656-2760
Loose Tianna [email protected]
12
Geoffroy Marie Claude 34
Orri Massimiliano 5
Chadi Nicholas 26
Scardera Sara 3
Booij Linda 278
Breton Edith 29
Tremblay Richard 10
Boivin Michel 11
Coté Sylvana [email protected]
12
1 grid.14848.31 0000 0001 2292 3357 Department of Social and Preventive Medicine, Université de Montréal School of Public Health, Montreal, QC Canada
2 grid.411418.9 0000 0001 2173 6322 Sainte-Justine University Hospital Research Centre, Montreal, QC Canada
3 grid.14709.3b 0000 0004 1936 8649 Department of Educational and Counselling Psychology, McGill University, Montreal, QC Canada
4 grid.14709.3b 0000 0004 1936 8649 Douglas Research Centre and Department of Psychiatry, McGill University, Montreal, QC Canada
5 grid.14709.3b 0000 0004 1936 8649 McGill Group for Suicide Studies, Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC Canada
6 grid.14848.31 0000 0001 2292 3357 Department of Pediatrics, University of Montreal, Montreal, QC Canada
7 grid.410319.e 0000 0004 1936 8630 Department of Psychology, Concordia University, Montreal, QC Canada
8 grid.14709.3b 0000 0004 1936 8649 Department of Psychiatry, McGill University, Montreal, QC Canada
9 grid.14848.31 0000 0001 2292 3357 Department of Psychiatry and Addictology, University of Montreal, Montreal, QC Canada
10 grid.14848.31 0000 0001 2292 3357 Department of Pediatrics and School of Psychology, Université de Montréal, Montreal, QC Canada
11 grid.23856.3a 0000 0004 1936 8390 School of Psychology, Université Laval, Québec City, QC Canada
8 12 2022
111
4 7 2022
21 10 2022
© The Author(s) under exclusive license to The Canadian Public Health Association 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Objectives
The COVID-19 pandemic has been associated with increased mental health problems. We investigated (1) associations between disordered eating in adolescence and mental health problems after one year of the pandemic and (2) the mechanisms explaining associations.
Method
We analyzed data from a population-based birth cohort in Quebec, Canada (557 males and 759 females). High and low levels of disordered eating symptom trajectories were previously estimated (age 12, 15, 17, and 20 years). Anxiety, depression, non-suicidal self-injury, and suicidal ideation were assessed at 23 years (March–June 2021). Putative mediators included loneliness and social media use (age 22 years, July–August 2020). Analyses controlled for mental health and socio-economic status at age 10–12 years and were conducted for males and females separately.
Results
Females in the high-level disordered eating symptom trajectory were at increased risk for non-suicidal self-injury (OR 1.60; 95% CI 1.02–2.52) and suicidal ideation (2.16; 1.31–3.57), whereas males were at increased risk for severe anxiety (2.49; CI 1.11–5.58). Males and females in the high-level trajectory were more likely to report severe depression (2.26; 1.14–5.92 and 2.15, 1.36–3.38 respectively). Among females, associations were partially explained (17–35%) by loneliness during the first 4 months of the pandemic.
Conclusion
Young adults who experienced disordered eating as adolescents were at increased risk of mental health problems during the pandemic. Loneliness partially mediated the effect, suggesting that pandemic mitigation resulting in increased social isolation may have exacerbated mental health problems among women with a history of disordered eating.
Supplementary Information
The online version contains supplementary material available at 10.17269/s41997-022-00715-8.
Résumé
Objectifs
La pandémie de COVID-19 a été associée à une augmentation des problèmes de santé mentale. Nous avons investigué 1) les associations entre les problèmes de comportement alimentaire à l’adolescence et les problèmes de santé mentale après un an de pandémie et 2) les mécanismes expliquant les associations.
Méthode
Nous avons analysé les données d’une cohorte de naissance basée sur la population au Québec, Canada (557 hommes et 759 femmes). Nous avons utilisé des trajectoires précédemment estimées indicatives d’un haut et bas niveau de problèmes alimentaires (à l’âge de 12, 15, 17 et 20 ans). L’anxiété, la dépression, l’automutilation et les idées suicidaires ont été évaluées à 23 ans (mars à juin 2021). Les médiateurs putatifs incluaient la solitude et l’utilisation des réseaux sociaux (à l’âge de 22 ans, juillet à août 2020). Les analyses contrôlaient la santé mentale et le statut socio-économique à l’âge de 10 à 12 ans et ont été menées séparément pour les hommes et les femmes.
Résultats
Les femmes dans la trajectoire des problèmes alimentaires élevés présentaient un risque accru d’automutilation non-suicidaire (OR 1,60; IC à 95 % 1,02-2,52) et d’idées suicidaires (2,16; 1,31-3,57), tandis que les hommes présentaient un risque accru d’anxiété sévère (2,49; IC 1,11-5,58). Les hommes et les femmes de la trajectoire élevée étaient plus susceptibles de déclarer une dépression grave (2,26; 1,14-5,92 et 2,15; 1,36-3,38, respectivement). Chez les femmes, les associations s’expliquaient en partie (17-35 %) par la solitude durant les 4 premiers mois de la pandémie.
Conclusion
Les jeunes adultes ayant connu des problèmes de comportement alimentaire à l’adolescence couraient un risque accru de problèmes de santé mentale pendant la pandémie. La solitude a partiellement atténué l’effet, suggérant que l’isolation accrue entrainée par la pandémie peut avoir exacerbé les problèmes de santé mentale chez les femmes ayant des antécédents de problèmes de comportement alimentaire.
Keywords
COVID-19
Longitudinal cohort
Disordered eating
Mental health
Suicide
Loneliness
Mots-clés
COVID-19
cohorte longitudinale
troubles alimentaires
santé mentale
suicide
solitude
Observatory for Children's Education and HealthRQC00384
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pmcIntroduction
The COVID-19 pandemic has been associated with millions of deaths, drastic mitigation measures, and major concerns for its impact on mental health (Campion et al., 2020). According to the conclusions of the World Health Organization (WHO) 2022 scientific brief on the plethora of research conducted on the impact of COVID-19 on mental health, symptoms of anxiety and depression increased from before to during the pandemic in the general population (Prati & Mancini, 2021). Pooled effects of mostly cross-sectional studies suggested that suicidal ideation and behaviours among youth increased during the pandemic (Dubé et al., 2021). Moreover, evidence shows that females and young people are at greater risk for mental health problems during the pandemic (Patel et al., 2022). Yet, high-quality longitudinal research investigating mental health outcomes of potentially vulnerable populations is still lacking (WHO, 2022).
The COVID-19 context exacerbated risk factors for disordered eating, such as isolation and dysfunctional disordered eating thoughts (Vitagliano et al., 2021). Although both males and females would be affected, there are substantial differences between sexes in the disordered eating literature that should be noted suggesting that it would be beneficial to study disordered eating and its correlates among males and females separately. Further, males are under-represented in the disordered eating literature and empirical findings related to men specifically are flagrantly needed (Weltzin et al., 2005). It is well known that the prevalence of eating disorders is higher among females than among males with, for example, 56% of 14-year-old girls and 28% of 14-year-old boys reporting at least one disordered eating behaviour (Croll et al., 2002). Body image concerns are as prevalent among males as among females, but the preferred body type often differs (i.e., muscular versus thin). The prevalence of specific eating disorder symptoms also differs, e.g., males are more likely than females to instate rigid excessive exercise routines but are less likely to present purging behaviours such as vomiting or excessive laxative use (Womble et al., 2001). The psychological correlates of eating disorders such as eating expectancies also differ across sex (Hayaki & Free, 2016). Researchers found that associations between disordered eating and COVID-19-related stress and anxiety were stronger among women than among men (Swami et al., 2021). Also, research shows that the mechanisms underlying disordered eating behaviours would differ across sex (Weltzin et al., 2005; Womble et al., 2001). Taken together, empirical studies with gender-specific results would be beneficial.
Cross-sectional research found that disordered eating problems during the COVID-19 pandemic were associated with increased mental health problems, including symptoms of anxiety (Bayram Deger, 2021; Czepczor-Bernat et al., 2021) and depression (Chan & Chiu, 2021; Giel et al., 2021), but the direction of the association is difficult to establish using cross-sectional data. There are a few longitudinal studies on disordered eating prior to the pandemic and mental health outcomes during COVID-19. For instance, researchers in the United Kingdom showed that young adults (N = 2657) with disordered eating problems prior to the pandemic (age 25 years) were at increased risk of anxiety, depression, and lower levels of well-being during the pandemic (age 28 years) independently of pre-pandemic mental health and well-being (age 22–24 years) (Warne et al., 2021). Kwong et al. (2021) found significant associations between disordered eating traits prior to the pandemic and anxiety and depression during the pandemic among young adults but not among older adults. Weight stigma prior to the pandemic was related to negative outcomes such as increased depression, COVID-19-related stress, and binge eating (Puhl et al., 2020). In comparison to healthy controls, patients with eating disorders prior to the pandemic experienced increased post-traumatic responses, compensatory exercise habits, and binge eating during COVID-19 (Castellini et al., 2020). Yet, the mechanisms behind these associations remain unclear. Understanding these mechanisms could allow for the identification of targets for prevention of mental health problems among adolescents and young adults.
Many studies suggest that mitigation measures during the COVID-19 pandemic (e.g., distancing, lockdowns) increased youths’ feelings of loneliness, which were more pronounced among young adults (Killgore et al., 2020) and have been associated with a wide range of physical and mental health problems (Park et al., 2020), including depression and suicidal ideation (Killgore et al., 2020). Those with disordered eating vulnerabilities would tend to be more secretive and alienate themselves from others which would increase their feelings of loneliness (Levine, 2012). Loneliness would then in turn contribute to increases in mental health problems such as depression, anxiety, and suicidal behaviours (Killgore et al., 2020; Park et al., 2020). Further, there is mounting evidence that social media use increased during the lockdown (Drouin et al., 2020). Prior studies have shown that heavy social media use can be associated with adverse mental health outcomes (e.g., anxiety, depression) because it often provokes comparisons, jealousy, and low self-esteem (Drouin et al., 2020; Verduyn et al., 2017). Content frequently includes body-centric messaging (e.g., thin/fit body ideals, sexualizing content, glorification of diets and exercise), which is particularly detrimental for people with disordered eating vulnerabilities (Cooper et al., 2020). Many studies have shown that exposure to these types of messages can provoke body image concerns, negative affect, and disordered eating behaviours among men and women (Agliata & Tantleff-Dunn, 2004; Hawkins et al., 2004; Sabik et al., 2020). Taken together, this evidence supports the hypothesis that increased loneliness and social media use during lockdowns may partially explain increases in mental health challenges during the pandemic among those with prior disordered eating symptoms.
Using a large population-based cohort from the Canadian province of Québec, our first aim was to investigate the association between disordered eating problems from age 12 to 20 years (2010–2018) and mental health problems (namely, anxiety, depression, non-suicidal self-injuries, and suicidal ideation) at age 23 years, one year after the onset of the COVID-19 pandemic (winter and spring 2021). Our second aim was to estimate to what extent perceived loneliness and social media use during the first 4 months of the pandemic mediated these associations. Given the importance of sex-based differences related to disordered eating, associations were investigated in males and females separately.
Methods
Sample
Participants were drawn from the Québec Longitudinal Study of Child Development (QLSCD), which is conducted by the Institut de la Statistique du Québec: a population-based birth cohort of children born in the province of Québec in Canada in 1997 and 1998, and followed up annually or biannually until now (Orri et al., 2021). Of the 2120 participants (N female = 1040; 49.1%) initially included in the cohort, we retained participants with information on disordered eating symptoms with data from at least one time point (12–20 years) and mental health assessment at age 23 years. Analyzed data included 759 females and 557 males. As in other studies conducted with this cohort, participants who were more likely to be excluded from our study sample were males, came from families with lower socio-economic status, and had mothers who experienced higher rates of depression at childbirth and who were younger at the time of birth of their first child (see Table S1, available online). The QLSCD protocol was approved by the Institut de la statistique du Québec ethics committee. The 2021 Special Round data collection (23 years) was also approved by the Douglas Research Centre Ethics Committee and by the CHU Ste-Justine research ethics committee. Informed consent was obtained from participants and/or their parents at each data collection.
Measures
Exposure: disordered eating trajectories from 12 (2010) to 20 (2018) years
Disordered eating problems were measured at age 12, 15, 17, and 20 years using the 5-item self-report questionnaire Sick, Control, One stone, Fat, Food (SCOFF) (Morgan et al., 2000), which has been psychometrically validated in French (Garcia et al., 2011). The SCOFF assesses the presence of disordered eating behaviours (yes vs no) during the past year, including purging, loss of control, weight loss, feeling overweight, and attributing importance to food. Behaviours were summed up to create a total score ranging from 0 to 5. We used group-based trajectories previously calculated (Breton et al., 2022). Some females (N = 188) and males (N = 284) had missing data on all time points and were therefore excluded. Two trajectories best fit the data indicative of high- and low-level trajectories. Twelve percent of males (N = 67) and 37% of females (N = 278) were assigned to the high-level trajectory. The mean a posteriori probability of being assigned to high- and low-risk groups was above the recommended .7 threshold (females: high risk M = .86, low risk M = .85; males: high risk M = .80, low risk M = .91), suggesting that hard classification into high and low groups can be confidently used as an exposure variable (Nagin, 2005). Note that the average number of disordered eating symptoms was higher among females than among males (Breton et al., 2022).
Mental health outcomes at 23 years old
Mental health outcomes were measured between March and June 2021 when participants were 23 years old and in a province-wide lockdown, which included closures of all non-essential services (e.g., restaurants, gyms, theatres) and schools, with learning moved to virtual platforms.
Anxiety symptoms
Participants reported their symptoms over the past 2 weeks using the Generalized Anxiety Disorder 7 (GAD-7) scale. The GAD-7 is a widely used efficient screening questionnaire with excellent psychometric properties, including internal consistency (α = .91) and criterion, construct, and factorial and procedural validity. Scores > 14 indicate severe symptoms (Micoulaud-Franchi et al., 2016; Spitzer et al., 2006).
Depressive symptoms
Participants reported their symptoms over the past week using the short form of the Center for Epidemiological Studies-Depression Scale (CES-D), a widely used screening tool for depression symptoms. The CES-D has good internal consistency (α = .87) and test-retest reliability as well as construct and factorial validity. Scores > 20 indicate severe symptoms (Radloff, 1977).
Non-suicidal self-injury
Non-suicidal self-injury was measured with the item: “In the past 12 months, did you ever deliberately harm yourself but not mean to take your life?” (1 = yes, 0 = no), which has been successfully used in previous cohort studies (Georgiades et al., 2019).
Suicidal ideation
Suicidal ideation was measured with the item: In the past 12 months, did you ever seriously consider taking your own life or killing yourself? (1 = yes, 0 = no), which has been successfully used in previous cohort studies (Georgiades et al., 2019).
Mediators during the COVID-19 pandemic (22 years old)
Mediators were measured from July to August 2020 during the first wave of the COVID-19 pandemic at age 22 years.
Loneliness
Loneliness was measured with the UCLA Loneliness Scale, which is a valid and reliable (α = .84) self-report measure with three items (feeling left out; feeling isolated from others; lack of companionship). Participants are prompted to rate the frequency of their feelings over the last 2 weeks (1 = almost never; 3 = often). Total scores were converted into a standardized scale ranging from 0 to 10 (de Grâce et al., 1993).
Social media use
Participants reported how much time per day between mid-March and mid-June 2020 they estimated using social media (e.g., Facebook, Instagram, TikTok) (1 = no use; 5 = over 6 h per day).
COVID-19 news on social media
Participants reported the average time per day they estimated consulting COVID-19-related news on social media between mid-March and mid-June 2020 (e.g., Facebook, Twitter, Reddit) (1 = never; 7 = more than 4 h).
Confounders
Confounders were measured at 10 and 12 years of age and averaged. Family socio-economic status (SES) was measured with an aggregate of five items regarding parental education, parental occupation, and annual gross income (range: 3 [low] to 3 [high], 0 centered) (Willms & Shields, 1996). Externalizing (3 items) and internalizing (2 items) symptoms were self-reported using the Social Behavior Questionnaire, which is a valid and reliable measure of symptoms among children (Murray et al., 2019).
Data analyses
All statistical analyses were conducted using SPSS, version 26. As recommended by guidelines such as those of the Canadian Institutes of Health Research (Coen & Banister, 2012; Rich-Edwards et al., 2018), we investigated sex differences by stratifying analyses by sex. First, we present descriptive statistics for all key variables. Second, prospective associations (i.e., total association) between disordered eating trajectories and mental health outcomes were estimated using logistic regressions. To conduct mediation analyses, we used the macro PROCESS v4 (model 4) (Hayes, 2017). This model allowed us to partition the total association into an indirect association (i.e., the part of the total association explained by the hypothesized mediator) and a direct association (i.e., the remaining part of the total association not explained by the hypothesized mediator). Effect size of the indirect association was calculated using the ratio between indirect and total associations (indicating the % of association mediated). We tested mediation models if disordered eating trajectories were associated with the mediator, and if the mediator was associated with the outcome (Fig. 1) (MacKinnon, 2008). The amount of missing data in mediators and confounders is detailed in Supplementary Table S2. We used the expectation maximization (EM) algorithm to handle missing data in the mediators and confounding variables. EM is a maximum likelihood–based approach that consists in iterating the expected log-likelihood function and a maximization estimate based on available data (Dong & Peng, 2013). To minimize bias due to the fact that more vulnerable participants were excluded from analyses, we applied inverse probability weighting. First, a variable “missing at follow-up” was created, with values of 1 if participants are missing and 0 if otherwise. Second, we used a binary logistic regression model to predict missing at follow-up from a large number of potential variables (socio-demographic, parental, and behavioural characteristics). The predicted probabilities (p) estimated from this model represent the likelihood of being missing at follow-up based on participants’ characteristics. Third, the inverse of these probabilities (1 − p) was used as a weight to account for the fact that certain participants may be under-represented because they are more likely to leave the cohort. All regression analyses are presented with and without adjusting for confounding factors. Statistical tests were two-tailed and considered significant for p < 0.05. As recommended (Hayes, 2017), 95% confidence intervals for the direct and indirect associations were calculated with 10,000 bootstrapped samples. Fig. 1 Conceptual model of mediation analyses. Note: X = exposure (high- or low-level disordered eating trajectories). M = mediator (loneliness). Y = internalizing symptoms (anxiety, depression, non-suicidal self-injury, or suicidal thoughts). ab = indirect effect of X on Y. c = total effect of X on Y. c’ = direct effect of X on Y
Results
Descriptive statistics are presented in Table 1. For males, 6.5% reported severe anxiety problems, 6.8% severe depression, 8.1% non-suicidal self-injury, and 7.2% suicidal ideation. For females, 11.1% reported severe anxiety problems, 11.5% severe depression, 11.7% non-suicidal self-injury, and 9.2% suicidal ideation. Table 1 Descriptive statistics for key variables in high- and low-level disordered eating trajectories for males and females separately
All Low risk High risk p Effect sizea
Males (N = 557) N = 490 N = 67
Mediators
Loneliness (M, SD) 2.48 (2.52) 2.39 (2.41) 3.12 (3.20) 0.025 .26
Social media (M, SD) 3.05 (.81) 3.05 (.81) 2.99 (.75) 0.567 .08
COVID news (M, SD) 2.62 (1.16) 2.58 (1.15) 2.87 (1.24) 0.053 .24
Outcomes
Severe anxiety (N, %) 36 (6.5%) 26 (5.3%) 10 (14.9%) 0.003 .13
Severe depression (N, %) 38 (6.8%) 28 (5.7%) 10 (14.9%) 0.005 .12
Self-harm (N, %) 45 (8.1%) 36 (7.3%) 9 (13.4%) 0.086 .07
Suicidal ideation (N, %) 40 (7.2%) 32 (6.5%) 8 (12.1%) 0.099 .07
Females (N = 759) N = 481 N = 278
Mediators
Loneliness (M, SD) 3.33 (3.12) 3.00 (2.95) 3.91 (3.32) < 0.001 .29
Social media (M, SD) 3.46 (.81) 3.42 (.80) 3.53 (.83) 0.074 .13
COVID news (M, SD) 2.66 (1.35) 2.61 (1.33) 2.74 (1.39) 0.215 .10
Outcomes
Severe anxiety (N, %) 84 (11.1%) 45 (9.4%) 39 (14.1%) < 0.001 .08
Severe depression (N, %) 87 (11.5%) 40 (8.3%) 47 (17.0%) < 0.001 .14
Self-harm (N, %) 89 (11.7%) 47 (9.8%) 42 (15.1%) < 0.001 .10
Suicidal ideation (N, %) 70 (9.2%) 32 (6.6%) 38 (13.7%) < 0.001 .12
Data were compiled from the final master file of the Québec Longitudinal Study of Child Development (1998–2022). Significant results in bold. ©Gouvernement du Québec, Institut de la statistique du Québec. p < 0.05 in bold
aCohen’s d is calculated for continuous variables; Phi coefficient is calculated for categorical variables
Prospective associations between disordered eating trajectories and mental health problems (total association)
Males or females in the high-level disordered eating trajectory reported higher levels of non-suicidal self-injury, anxiety, and depression than males or females in the low-level trajectory. Females in the high-level trajectory reported higher levels of suicidal ideation than females in the low-level trajectory, whereas these differences did not reach statistical significance among males.
In adjusted models, females in the high-level disordered eating trajectory were more likely to engage in non-suicidal self-injury (OR 1.60; 95% CI 1.02–2.52) and to think about suicide during the COVID-19 pandemic (OR 2.16; 95% CI 1.31–3.57), whereas males in the high-level trajectory were more likely to report severe anxiety (OR 2.49; 95% CI 1.11–5.58). Both males and females in the high-level-trajectory groups were more likely to report severe depression (OR 2.26; 95% CI 1.14–5.92 and OR 2.15; 95% CI 1.36–3.38 respectively) (Table 2). Table 2 Prospective associations between high- and low-level disordered eating trajectories and mental health problems at age 23
High-risk trajectory (reference = 0) Severe anxiety Severe depression Non-suicidal self-injury Suicidal ideation
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Males
Unadjusted 3.06 (1.40–6.67) 2.80 (1.29–6.09) 1.96 (0.90–4.28) 1.98 (0.88–4.47)
Adjusteda 2.49 (1.11–5.58) 2.26 (1.14–5.92) 1.69 (0.761–3.77) 1.62 (0.70–3.76)
Females
Unadjusted 1.59 (1.01–2.51) 2.24 (1.43–3.52) 1.64 (1.05–2.56) 2.26 (1.37–3.71)
Adjusteda 1.52 (0.96–2.41) 2.15 (1.36–3.38) 1.60 (1.02–2.52) 2.16 (1.31–3.57)
Data were compiled from the final master file of the Québec Longitudinal Study of Child Development (1998–2022), ©Gouvernement du Québec, Institut de la statistique du Québec. Significant results in bold (95% CI)
OR odds ratio, CI confidence interval
aAdjusted for socio-economic status and prior mental health at 10–12 years old. Weighted results reported
Association of disordered eating trajectories with loneliness and social media use
We used Student’s t test to compare mean levels of loneliness and social media use among males and females in the high- versus low-level trajectories. Males in the high-level trajectory scored significantly higher than males in the low-level trajectory on loneliness. The same significant differences were observed among females. There were no significant differences in social media use in the high and low trajectories (Table 1).
Loneliness as a mediator between trajectories and mental health problems
Mediation models were tested based on previously stated requirements (MacKinnon, 2008). Among females, we found significant indirect effects of loneliness in the association between disordered eating trajectory and all our outcomes (Table 3). The proportion of the association explained by loneliness was 35.2% for severe anxiety, 23.1% for severe depression, 16.8% for non-suicidal self-injury, and 18.1% for suicidal ideation. After accounting for the mediators, significant direct effects for all outcomes except anxiety were still observed. However, no significant indirect effect of loneliness was found for males on any of the mental health problems (Table 3). Table 3 Direct and indirect effects of trajectories on mental health problems via loneliness among males and females
Direct effect Indirect effect % mediation
OR (95% CI) OR (95% CI)
Females
Severe anxiety 1.32 (0.83–2.10) 1.16 (1.06–1.31) 35.2%
Severe depression 1.93 (1.21–3.09) 1.22 (1.09–1.41) 23.1%
Non-suicidal self-injury 1.56 (1.02–2.55) 1.10 (1.02–1.20) 16.8%
Suicidal ideation 1.82 (1.09–3.03) 1.14 (1.05–1.28) 18.1%
Males
Severe anxiety 2.10 (0.90–4.91) 1.19 (0.98–1.52)
Severe depression 1.53 (0.63–3.73) 1.20 (0.98–1.58)
Non-suicidal self-injury 1.39 (0.61–3.18) 1.15 (0.93–1.41)
Suicidal ideation 1.23 (0.50–3.02) 1.19 (0.98–1.53)
Data were compiled from the final master file of the Québec Longitudinal Study of Child Development (1998–2021), ©Gouvernement du Québec, Institut de la statistique du Québec. Significant results in bold (95% CI). Results adjusted for prior mental health and socio-economic status at 10–12 years old
OR odds ratio, CI confidence interval
Discussion
Drawing on a large population-based cohort born in the Canadian province of Québec, we found that males and females with high levels of disordered eating symptoms from age 12 to 20 years were more likely to experience severe levels of anxiety and depression symptoms during the COVID-19 pandemic. This converges with longitudinal findings (Warne et al., 2021) and cross-sectional research on associations between disordered eating and symptoms of depression (Chan & Chiu, 2021; Giel et al., 2021) and anxiety (Chan & Chiu, 2021; Czepczor-Bernat et al., 2021). We also found that females with prior disordered eating problems were at increased risk of suicidal ideation and non-suicidal self-injury during the pandemic. The same pattern in prevalence was observed among males, but differences were not statistically significant. One possible explanation is that the number of males with suicidal behaviours was low, which could lead to a lack of statistical power to detect a true effect. Another possibility is that males in the high-level disordered symptom trajectory group had a lower intensity of symptoms than females in the high-risk group. This lower level of intensity could explain in part why there were no significant associations with suicidal ideation and self-harming behaviours among men. Collectively, these associations show that youth with prior disordered eating are at greater risk for experiencing mental health problems during stressful contexts such as the COVID-19 pandemic.
Loneliness during lockdown explained a part of the association between prior disordered eating and mental health problems among women, but not among men. Feelings of loneliness are a well-established risk factor for physical and mental health problems (Park et al., 2020). Experts highlight that research on individuals with disordered eating vulnerabilities, whether within or apart from the pandemic context, should focus on loneliness and related concepts such as social support that contribute to the development and maintenance of disordered eating symptoms (Cooper et al., 2020). Those with disordered eating patterns tend to alienate themselves from others, which would be associated with the often secretive nature of problem eating behaviours (e.g., food restriction, binging, purging), low self-esteem, and negative perceptions of others (Levine, 2012). In the context of COVID-19, increased feelings of loneliness have been well documented in general populations and associated with mental health problems especially among young women (Killgore et al., 2020; Park et al., 2020). Though young women with prior disordered eating may have been at greater risk for experiencing loneliness and mental health problems in young adulthood regardless of the pandemic, our study highlighted that COVID-19 mitigation measures may have impacted a highly relevant risk factor among those with a disordered eating history which would exacerbate the problem.
Loneliness did not appear to play a mediating role in the association between prior disordered eating and mental health problems among males. We can advance several possible explanations for our findings. First, associations between feelings of loneliness or lack of social support and anxiety, depression, suicidal ideation, and self-harming behaviours tend to be stronger among young females than among males (Beutel et al., 2017; Elbogen et al., 2021). The weaker associations observed among males could explain in part why our study did not evidence loneliness as a mediator. Second, a few studies evidenced that factors implicated in disordered eating behaviours would be similar across both sexes, but that the underlying mechanisms would differ (Weltzin et al., 2005). For instance, males would be more likely than females to binge eat because of body image concerns and less likely to restrict eating to cope with negative affect (Womble et al., 2001). Our results might suggest that loneliness is an important mechanism underlying associations between disordered eating symptoms and other mental health problems that would be pertinent to females specifically. Alternatively, the finding could be a false-negative result due to the lower statistical power in our male sample.
Contrary to our hypotheses, we did not find that social media use during lockdown explained the associations between disordered eating symptoms and mental health problems. This hypothesis was mostly grounded in research conducted outside of the pandemic context and theoretical arguments supporting its relevance during COVID-19 (Cooper et al., 2020). Though empirical research is scarce, one longitudinal study conducted during the pandemic evidenced that time spent on Facebook was associated with increased body image and weight concerns, which was explained by passive but not active use (Mannino et al., 2021). Outside of the pandemic context, multiple studies revealed both positive and negative effects of social media use on well-being. For instance, passive use could increase envy and negative affect whereas active use (e.g., private chats with friends) could enhance social ties and decrease loneliness (Verduyn et al., 2017). Our measure of social media use relied on a single item which did not allow us to distinguish between different types of use nor indicate the specific platforms used (e.g., Instagram versus Reddit), which may contribute to why we did not observe an association. Longitudinal event–level studies could be an interesting design to better ascertain the phenomenon. For instance, using a smartphone application, researchers could additionally take daily measures of multiple facets of social media use daily and monitor participants’ subsequent feelings.
Our study should be interpreted in light of several limitations. First, as in all longitudinal studies, participants with certain characteristics were more likely to drop out, which could lead to an under-representation of these individuals. In order to minimize this bias, we applied inverse probability weighting on key variables. Second, despite the use of a longitudinal design, definitive conclusions about causality between disordered eating and mental health problems and the underlying processes cannot be ascertained as non-included confounding factors could influence results. However, as we adjusted analyses for important confounding factors, namely socio-economic status and prior mental health problems, that source of bias is thought to be minimal. We did not statistically adjust for the uncertainty of individuals being assigned to their respective trajectories, but the posterior probabilities were high and we believe bias is minimal. Similar studies with larger sample sizes may consider adjusting for this potential source of bias in the future. Though the SCOFF is a well-known screening assessment, the self-report format can cause bias and it did not allow us to account for specific types of eating disorders nor the intensity of each symptom. Our measures of social media use relied on single items created for the purpose of this study rather than validated psychometric scales. Our study did not have enough statistical power to test for sex interactions, but our stratified analyses suggested important sex differences and lay the grounds for larger-scale studies investigating moderation. As the majority of our cohort was of Caucasian decent (Orri et al., 2021), generalization of our results to gender (vs sex), minority groups such as the LGBTQ+ community, or diverse socio-cultural environments is unclear and it would be important to conduct research on the topic.
Main strengths of our study include reliance on representative longitudinal cohort data with several assessment time points spanning from infancy to young adulthood. We were able to adjust for confounding variables in childhood including socio-economic status and mental health problems, which allows us to better establish causal inferences. By making use of disordered eating trajectories that were calculated in another study, we were able to capture the phenomenon over the course of adolescence rather than relying on a sole time point, which reduces measurement error. We used validated tools to measure mental health problems with excellent psychometric properties and evaluated clinically relevant outcomes. Further, we measured mental health outcomes in 2021, a year after the outbreak of the COVID-19 pandemic. Males are often neglected and under-represented in the eating disorder literature, but we were able to include over 500 men in analyses and highlight sex-based differences. We were among the few to conduct a longitudinal study on prior disordered eating as a vulnerability factor leading to anxiety and depression during the pandemic and the first to include measures of self-harm and suicidal ideation as outcomes. We were also the first to pinpoint loneliness as an explanatory factor which can allow us to implement evidence-based strategies to mitigate mental health problems during the pandemic among women with prior disordered eating.
Conclusion
Males and females with a history of disordered eating during their adolescence were at higher risk for experiencing mental health problems during the stressful period of the COVID-19 pandemic. Researchers and policy makers should be attentive to this group and implement evidence-based strategies to help support at-risk individuals. According to the WHO (2022), effective interventions in the COVID-19 context include programs focused on self-help, cognitive behavioural training, psycho-education, and relaxation which can be delivered in person or via online platforms. Our findings evidenced that loneliness could be a potential target for the prevention of anxiety, depression, non-suicidal self-injury, and suicidal ideation among females with prior disordered eating symptoms. Effective cognitive behavioural techniques to decrease loneliness include addressing maladaptive cognitive beliefs (e.g., negative evaluations of others, lack of interpersonal trust), training in social skills, encouraging socialization and community involvement (e.g., volunteering), and increasing opportunities for socialization (Mann et al., 2017). Though we found that loneliness explained 17–35% of the associations among females, more research would be needed in order to identify explanatory mechanisms among males and better understand sex-related differences. Further research would also be needed to better ascertain the longer-lasting effects of the pandemic on the individuals in our cohort and how the effects may carry over to their offspring.
Contributions to knowledge
What does this study add to existing knowledge? Young adults in Québec with a history of problematic eating behaviours in adolescence were at greater risk for severe anxiety and depression and suicidal behaviours during the COVID-19 pandemic.
Our study was the first to pinpoint that loneliness during lockdown could explain associations between prior disordered eating symptoms and mental health problems among women.
We included a large sample of males, who are most often neglected in the disordered eating literature, and highlighted differences across sex.
What are the key implications for public health interventions, practice, or policy? Public policies should focus on those with prior disordered eating antecedents as they would be at greater risk for developing mental health problems later in life and under stressful conditions such as the current pandemic context.
As loneliness partially explained these associations with mental health problems among women, intervention and prevention efforts could focus on promoting social ties.
Supplementary Information
ESM 1 (DOCX 18 kb)
Acknowledgements
This work was supported by the Observatory for Children’s Education and Health (RQC00384). The Québec Longitudinal Study of Child Development was supported by funding from the ministère de la Santé et des Services sociaux, le ministère de la Famille, le ministère de l’Éducation et de l’Enseignement supérieur, the Lucie and André Chagnon Foundation, the Institut de recherche Robert-Sauvé en santé et en sécurité du travail, the Research Centre of the Sainte-Justine University Hospital, the ministère du Travail, de l’Emploi et de la Solidarité sociale, and the Institut de la statistique du Québec. Additional funding was received by the Fonds de Recherche du Québec - Santé (FRQS), the Fonds de Recherche du Québec - Société et Culture (FRQSC), the Social Sciences and Humanities Research Council of Canada (SSHRC), and the Canadian Institutes of Health Research (CIHR; including a recent grant (166126)) partly supporting the 23-year data collection.
Author contributions
TL, NC, MC, SC, and MO conceptualized the study and analyses. RT, MB, MC, and SC collected the data. EB provided the calculations for the trajectories. TL drafted the paper and performed the analyses. SC provided supervision. All of the authors revised the paper and approved the final version of the manuscript.
Availability of data and material
Not applicable
Code availability
Not applicable
Declarations
Ethics approval
The QLSCD protocol was approved by the Institut de la statistique du Québec ethics committee. The 2021 Special Round data collection (23 years) was also approved by the Douglas Research Centre Ethics Committee and by the CHU Ste-Justine research ethics committee. Informed consent was obtained from participants and/or their parents at each data collection.
Consent to participate
Informed consent was obtained from participants and/or their parents at each data collection.
Consent for publication
Not applicable
Conflict of interest
The authors declare no competing interests.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36482144 | PMC9734974 | NO-CC CODE | 2022-12-14 23:28:31 | no | Can J Public Health. 2022 Dec 8;:1-11 | utf-8 | Can J Public Health | 2,022 | 10.17269/s41997-022-00715-8 | oa_other |
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Appl Phys A Mater Sci Process
Appl Phys A Mater Sci Process
Applied Physics. A, Materials Science & Processing
0947-8396
1432-0630
Springer Berlin Heidelberg Berlin/Heidelberg
6279
10.1007/s00339-022-06279-1
Article
Bambusa arundinacea leaves extract-derived Ag NPs: evaluation of the photocatalytic, antioxidant, antibacterial, and anticancer activities
Jayarambabu N. 1
Velupla Suresh 2
Akshaykranth A. 1
Anitha N. 1
http://orcid.org/0000-0003-4978-7011
Rao T. Venkatappa [email protected]
1
1 grid.419655.a 0000 0001 0008 3668 Department of Physics, National Institute of Technology, Warangal, 506004 India
2 grid.412419.b 0000 0001 1456 3750 Department of Biochemistry, Osmania University, Hyderabad, 500007 India
7 12 2022
2023
129 1 1311 8 2022
25 11 2022
© The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Bio-fabrication has become a safe approach for silver nanoparticles (Ag NPs). The plant-mediated biosynthesized Ag NPs have emerged as a potential substitute for conventional chemical formation. The biosynthesized Ag NPs were analyzed in terms of crystalline nature, morphology, chemical composition, particle size, stability, size, and shape of the particles. The XRD, FTIR, and TEM analysis indicate the presence of the bioactive secondary metabolites compounds. The bamboo-mediated Ag NPs demonstrated a notable antibacterial efficacy against Gram-positive and Gram-negative pathogenic microorganisms and showed significant antioxidant activity against DPPH free radicals. The degradation of methylene blue at various intervals under solar light irradiation was used to evaluate the photocatalytic performance of Ag NPs. Further, Ag NPs conveyed potent anticancer activity against MCF-7 cell lines with a significant value IC50. The bamboo leaves-mediated Ag NPs synthesized Ag NPs signified strong antibacterial, antioxidant, and anticancer activity; hence, it can be used in various biomedical applications and face mask coating to prevent the coronavirus after successful clinical trials in research laboratories.
Keywords
Antioxidant
Antibacterial
Anticancer activity
Ag nanoparticles
Bambusa arundinacea
Photocatalytic activity
Maharashtra Bamboo Development Board (MBDB), NagpurGrant No: MD/MBDB/CR-86/18-19/589 Rao T. Venkatappa issue-copyright-statement© The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2023
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pmcIntroduction
Nanotechnology is a rapidly evolving multidiscipline that contains designing, synthesizing, assembling, and modifying molecules/ bulk matter/ particles to nanostructured dimensions (1–100 nm in size) [1]. Nanoparticles have a large surface-to-volume ratio, giving them unique features and improving their mechanical, catalytic, optical, and magnetic properties, allowing them to be used in biomedical applications. They have been widely employed in medical, food, agriculture, optics, the environment, mechanics, chemical, photochemical, catalysis, cosmetics, electronics, sensing technologies, energy research, and other fields [2]. There are two types of nanoparticles: inorganic and organic. Metallic (Au, Ag), semiconductor (CdS, ZnO), and magnetic (Ni, Co) nanoparticles are the most common inorganic nanoparticles, whereas organic nanoparticles are carbon-based nanoparticles (carbon nanotubes, quantum dots) [3]. Metallic nanoparticles, in particular, have been widely exploited for various applications due to their unique features. Metallic nanoparticles’ therapeutic efficacy is owing to their optical property, which is proved by localized surface plasmon resonance [4]. Silver nanoparticles (Ag Nps) are particularly common among metal nanoparticles. They have many applications in biomedicine and industry due to nanoparticles’ physical, thermal, optical, chemical, catalytic activity, electrical conductivity, and antibacterial activity. These unique qualities have allowed Ag NPs to be used in various sectors such as antifungal, antiviral, anticancer, anti-inflammatory, drug administration, sensing, diagnostics, orthopedics, and so on [5].
The efficiency of Ag NPs inside biological systems is influenced by the size, surface chemistry, shape, size distribution, particle morphology, coating agglomeration, dissolving rate, and particle composition [6]. Silver is a non-toxic, harmless inorganic antibacterial agent that can kill over 650 different species of disease-causing bacteria [7, 8]. Various methods have been devised for the preparation of nanoparticles, each with its own set of benefits and drawbacks [9]. Metallic nanoparticles can be made using both chemical and physical processes. Although these technologies create particles with the desired properties, they are frequently expensive, time consuming, and undesirably harmful to living creatures and the environment. The biological technique has been utilized to generate nanoparticles to overcome the limitations of these physical and chemical technologies. Several biological resources have been employed to produce metal nanoparticles, including plant extracts, milk, microbes, and panchagavya [10, 11]. Among the different green sources investigated, microalgae offer essential advantages in terms of ease of development and living in harsh settings (such as temperature and pH) [12]. Recently, numerous advantages of biological Ag NPs production have been recognized. Several plant materials and microorganisms have been identified as possible Ag NPs production candidates. Specific proteins in plants and microorganisms have been postulated as a possible source of Ag+ ion reduction. It has been postulated that NADH-dependent nitrate reductase may reduce Ag+ ions to Ag0 ions [13]. However, the synthesis of Ag NPs using plant extracts has the potential to be more advantageous than microbes due to its simplicity in scaling up. [14]. Using microorganisms has some drawbacks, including high costs, aseptic environment upkeep, mass microbe cultivation, output quantity, and purification [13]. On the other hand, the green method involves using plant extracts, is environmentally friendly, cost-effective, and efficient [15]. Several researchers employing plant extracts such as Carica papaya [16], Azadirachta indica [17], Alternanthera dentata [18], Olea europaea [19], and Coffea Arabica [20] have been conducted in recent years to synthesize nanoparticles. Furthermore, plant extracts from various species are regarded as a beneficial approach for nanoparticle synthesis due to their extraordinary ability to synthesize a wide range of phytochemicals with a high reduction potential [19]. Sugars, polyphenols, terpenoids, alkaloids, proteins, and phenolic acids reduce metal ions into nanoparticles. These phytochemicals are also responsible for stabilizing the nanoparticles produced [21]. All parts of the bamboo plant, including the rhizome, bark, culm, leaves, shoots, roots, and seeds, have been used in clinical and therapeutic. Bamboo is the fastest-growing multipurpose woody plant. The natural substances abundant in bamboo leaves, including phenols, flavonoids, saponins, vitamins, glycosides, antioxidants, and some other compounds, have a role in reducing silver nitrate to Ag NPs (Table 1). At the same time, these compounds bound on the surface of the Ag NPs and enhanced the biological activities due to the presence of biological compounds.Table 1 Bioactive compounds of Bambusa arundinacea
Phytochemical compound Reference
Alkaloids [22]
Carbohydrates [23]
Glycosides [24]
Saponins [25]
Phytosterol [26]
Resins
Phenols
Fixed oil
Tannins
Diterpenes
Protein and amino acid
Flavonoids
Alkaloids
Carbohydrates
Glycosides
Saponins
In this present study, Ag NPs were green synthesized by the reduction of silver precursor in the presence of plant extract sources. The benefits of green synthesis techniques, ease of nanoparticle creation, eco-friendly, cost effectiveness, quick crystallization, and reduced waste generation are all demonstrated by the plant extract sources employed for the bio-reduction of silver nitrate to Ag NPs. The synthesized Ag NPs were analyzed by X-ray diffraction (XRD), FTIR spectroscopy, scanning electron microscopy (SEM), UV–Visible spectroscopy, dynamic light scattering (DLS), and TEM to investigates the antibacterial, antioxidant, anticancer, and photocatalytic activities of Ag NPs’.
Materials and methods
Materials
Bambusa arundinacea leaves’ extract solution, silver nitrate (Sigma Aldrich) 2, 2-diphenyl-1-picrylhydrazyle (DPPH) were purchased from Sigma-Aldrich, St. Louis, MO, USA.
Preparation of the plant extract
An extract of the Bambusa arundinacea leaves was used for the biogenic synthesis of Ag NPs. The leaves have been used as medicine for various inflammatory conditions. The leaves were washed with double distilled water to remove the dust and mud particles on the leaves' surface, and these were finely cut into small pieces before going to dry in the presence of sunlight. 20 gm of the leaves was immersed into 100 ml double distilled water and placed on the magnetic stirrer for 70 min at 80 °C to prepare for extractions of the solution. A Whatman filter paper used for filtration of the extract solution was kept at room temperature for cooling and finally used for the biogenic synthesis of Ag NPs.
Biogenic synthesis of Ag NPs
For the biogenic synthesis of Ag NPs, 0.5 mM silver nitrate was prepared in 100 mL double distilled water. The aqueous solution of the leaves’ extract was added to the above solution and stirred for 4 h at a temperature of up to 60 °C. Under these circumstances, the solution's color changed from a colorless solution to dark color due to the Ag+ conversion into Ago ions. Bamboo leaves extract as a reduction agent for the synthesis of Ag nanoparticles. Bamboo leaves contain phytoconstituents which help to stabilize the Ag nanoparticles as shown in Fig. 1. The biogenic synthesized Ag NPs were characterized with different analytic techniques for their morphology, stability, chemical compositions, crystallinity, and particle size.Fig. 1 Biogenic synthesis of Ag NPs
Antibacterial activity
The antibacterial activity of Ag NPs was investigated using the suitable disc diffusion method. The bacteria were isolated from an initial single colony and were grown overnight in nutrient broth. The items, including the glassware, reagents, and medium, were sterilized in an autoclave at 121 °C for 20 min under 15 kg/cm2 pressure. The bacterial inoculum was incubated in lysogeny broth for 24 h at 28 °C and 200 rpm, then re-suspended in a lysogeny broth medium until the optical density was adjusted to 0.1 at 600 nm, which corresponds to 108 colony-forming units (CFU)/mL. The spread plate method was performed in this bacterial suspension (each 100 µl) spread on the nutrient agar. Subsequently, wells were made on agar plates, and various concentrations of Ag were loaded. The entire agar plates were placed in the bacteriological incubator for 24 h at 37 °C, and the zone of inhibition was calculated with a measuring scale (mm).
DPPH scavenging assay
Ag NPs were investigated by DPPH (1, 1-diphenyl-2-picrylhydrazyle) scavenging assay. To the DPPH (50 µM) solution prepared in absolute ethanol (in the dark), various concentrations were added to 96-well microtitre plates. After adding NPs, the plate was placed in the dark, and the reaction samples were incubated for 30–60 min at room temperature. The DPPH solution incubated with reference standard ascorbic acid (25 µg/mL) and bamboo leaves extract served as positive and negative controls, respectively. The AgNPs sample was evaluated in triplicates, and the absorbance was recorded at 520 nm using a microplate reader (Micro Scan, MS5608A, ECIL, and India). A decrease in absorbance was recorded for calculating DPPH scavenging (%) using the following equation [27].DPPH scavenging activity%=DPPH absorbance-sample absorbanceDPPH absorbance×100
MTT assay
To test the cell viability (MTT) assay, the breast cancer cell line (MCF-7) was collected from the National Centre for Cell Sciences India. The cells were grown in Dulbecco’s modified Eagles medium (DMEM) containing 10% fetal bovine serum (FBS), 100 units/mL penicillin G and 1 μg/streptomycin, 5 μg/mL amphotericin B (Sigma-Aldrich Chemicals, St. Louis, United States) (2 mM) l-glutamine and non-essential amino acids (1X), (Himedia, Mumbai, India) at 37 °C in a humidified 5% CO2 incubator Nectarnova, Symbiogen, Chennai, India). Cytotoxicity of the nanoparticles was studied under the conditions after 80% confluence. Cells were trypsinized with 0.1% trypsin–EDTA and were harvested by centrifugation at 500 × g. Serial dilutions of cells were made from 1 × 106 to 1 × 103 cells per mL.
The cells were seeded in triplicates in a 96-well plate. The suspended cells were treated with 20, 40, 60, 80, and 100 µL concentrations of AgNPs, in a dose-dependent way for 24 h. Tamoxifen drug was used as a positive control, and tumor cells without nanoparticles were added to serve as a control. After incubation, MTT (20 µl, 5 mg/mL) solution was added to each well, and the cell viability was calculated by measuring the ability of cells to transform MTT to a purple-colored formazan dye. At 570 nm, the absorbance was observed using an ELISA instrument (MS5608A from ECIL, Hyderabad, India). The percent cell viability was measured using the following equation [28]Percent cell viability=A570sampleA570controlX100
where A 570 (sample) corresponds to absorbance obtained from the wells treated with nanoparticles, and A 570 (control) represents the absorbance from the wells in which no nanoparticle construct was added.
Characterization of Ag nanoparticles
The following analytical techniques carried out the characterizations of biogenic synthesized Ag NPs. First, the purity and crystallinity of Ag NPs were observed by powder XRD (Bruker advanced D8). The functional groups of biogenic nanoparticles were identified by FTIR, ranging from 500 to 4000 cm-1 (Bruker Alpha-II). The particle size and stability of the nanoparticles were measured by dynamic light scattering (DLS) (Horiba-SZ100). UV–Vis analysis was performed by spectrophotometer between 200 to 800 nm (Analytical Jena, Specord 210 Plus). The morphology of the biogenic synthesized sample was analyzed by field emission scanning microscope (FESEM, Carl Zeiss, Ultra Plus) size and shape of the nanoparticles were analyzed by TEM. Finally, X-ray photoelectron spectroscopy XPS (PHI 5600 Versa Probe III) was used to analyze the synthesized samples' surface components.
Results and discussion
Biosynthesized Ag NPs indicated the five diffraction peaks at 2θ position 32.20°, 38.16°, 46.15°, 67.40°, and 76.10°. These peaks correspond to the (122), (111), (200), (220), and (311) planes, respectively, and showed the face-centered cubic structure as shown in Fig. 2a. The unwanted peaks in the spectrum indicated the presence of various bioactive reducing agents and capping compounds accumulated on the surface of Ag NPs. The reducing agents of plant extract compounds were responsible for the synthesis of Ag NPs [29].Fig. 2 a X-ray diffraction pattern b UV–Visible spectra c FTIR spectra of biogenic synthesized Ag NPs
UV–Visible spectroscopy is the primary tool to confirm that as-synthesized materials are nanoparticles. Figure 2b shows UV analysis of as-synthesized Ag NPs mediated by Bambusa arundinacea leaves extract. The range of absorption spectra was between 200 to 800 nm, and the peak position appeared at 452 nm, indicating the formation of Ag NPs. The plasmon resonances of Ag were observed near 452 nm [30]. The metal contains the free electrons that go through plasmon resonance transitions in the visible spectrum, which gives rise to such strong colors. This type of property mostly appeared in Ag NPs due to the occurrence of free conduction electrons. The electric field of the inward radiation induces the creation of a dipole in the nanoparticles. The number of factors depends on the wavelength of oscillation. The nature of medium particles' size, as well as shape, were the most important ones.
FTIR analysis of the Ag NPs prepared from Bambusa arundinacea leaves extract is shown in Fig. 2c. The characteristic peaks around 3434 cm−1 were ascribed to the OH stretching vibration of the OH structure. The peaks around 2937 and 2368 cm−1were ascribed to C–H stretching vibrations. The peak position at 1611 cm-1 was ascribed to the C = C stretching vibration of aromatic rings. The peak at 1380 cm−1 was assigned to polyphenols group compounds [31–33].
Additionally, the peak around 1016 was attributed to alkynes C–H bending vibration. The peak position at 573 and 450 cm−1indicated the Ag NPs. The FTIR results verified that the bioactive compounds in the aqueous were distributed on the surface of Ag NPs and also responsible for the reduction and capping agent of silver ions, which is consistence with the previous reports.
The FESEM analysis was determined to evaluate the morphology, shape, size, and uniformity of the distribution of the Ag NPs. Figure 3a, b shows the FESEM images of biosynthesized Ag NPsat scales of 100 and 200 nm. Based on the FESEM images, the spherical nature of the Ag NPs was found [34]. The FESEM images showed that the average particle diameter of the synthesized Ag NPs varied in the range of 20–50 nm. The TEM analysis was determined to accurately investigate the shape and size of the synthesized Ag NPs. In the TEM images, the sizes of the nanoparticles were in the range of 30–40 nm with spherical structure particles [35]. In addition, the TEM analysis revealed the bioactive compounds' presence on the surface of the Ag NPs in Fig. 3d, e.Fig. 3 a, b FESEM images c zeta potential d, e TEM images f DLS particles size of biogenic synthesized Ag NPs
The average particle size of the biosynthesized Ag NPs was measured by dynamic light scattering (DLS) measurement. The DLS analysis showed that Ag NPs had an average particle size of 23.6 nm in Fig. 3f. In addition, the zeta potentials analyzer was observed to identify the stability of the Ag NPs and found to be − 19.3 mV as shown in Fig. 3c. The negative value of the zeta potential indicates that the components such as phenolic, flavonoids, glycosides, saponins, tennis, antioxidants, etc., present in the leaves extract solutions act as capping agents and stabilize the Ag NPs. Hence, the sufficient charge on the surface of NPs which is compatible with the repulsive force will stop the NPs agglomeration.
XPS analysis
The chemical state and near-surface composition of Ag NPs derived from bamboo leaves extract were confirmed by X-ray photoelectron spectroscopy. An XPS spectrum of the Ag NPs in the range of 0–800 eV is depicted in the Fig. 4a. The presence of such elements as carbon (C 1 s), silver (Ag3d), and oxygen (O 1 s) was observed. Figure 4b shows the binding energy (BE) associated with the Ag3d region of the sample utilizing high-resolution XPS (HR-XPS). Two peaks at 372 and 366 eV, produced by the orbital spin interplanetary splitting corresponding to the Ag 3d3/2 and Ag 3d5/2 core levels, are critical characteristics of the Ag3d region. The other peaks at 531 and 282 eV correspond to O1s and C1s. The O1s appearing in the region between 529–535 eV due to oxygen–carbon or water incorporated on the surface of the Ag NPs are shown in Fig. 4c. The C–C binding energy contribution at 282 eV corresponds to SP2 (C = C) [36, 37].Fig. 4 XPS spectra of a Ag NPs XPS survey spectrum b binding energy for Ag3d c binding energy for O1s d binding energy for C1s
Photocatalytic activity of biosynthesized Ag NPs
The degradation of azo dyes, such as methylene blue, was investigated in reactions utilizing the UV-irradiation approach to evaluate the photocatalytic activity of green synthesized Ag nanoparticles. Initial color changes caused by the catalytic breakdown of organic dyes in the presence of Ag NPs were visible. Methylene blue color intensity gradually turned from dark blue to white in UV irradiation, demonstrating the effective catalytic degrading activity of Ag NPs. This work used the radioactive dye methylene blue to test the potential nanomaterial as Ag NPs photocatalytic activity. Figure 5 shows the results; as the irradiation time increased, the efficiency of methylene blue decolorization gradually increased (up to 30 min). UV–Vis absorption spectra of MB dyes at different times showed decreasing peaks with the color shift into light color. When exposed to light, the MB absorption peak at 660 nm initially showed a rapid drop every 2 min. Ag NPs percentage of decolorization activity under UV irradiation may have reduced the amount of methylene blue (80 percent). However, as the exposure time lengthened, it persisted. The surface plasmon resonance (SPR) effect causes conduction electrons to be stimulated on the surface of silver nanoparticles when light photons interact with the Ag NPs. The surface hydroxyl groups can scavenge electron holes produced by the ultraviolet light system, which leads to the production of reactive oxygen species (ROS) and the start of the organic oxidation reaction. The size and shape of the metal nanoparticles, as well as the kind and structure of the dispersion medium, all impacted the interaction [38, 39]. As Ag NPs, a putative-reducing agent destroyed the azo dyes effectively. The results unequivocally show that Ag NPs effectively degrade hazardous pollutants in a photocatalytic manner from the textile sector.Fig. 5 Photocatalytic activity of biosynthesized Ag NPs as a nanocatalyst in the presence of NaBH4
Ag NPs showed potent DPPH scavenging activities at various concentrations. Among the concentrations tested, 25, 50, 75, 100, 150, and 200 showed the percent scavenging activities depicted in Fig. 6 as follows 26.8, 37.3, 45.0, 61.5, 65.5, and 74.4, respectively. The test of positive control ascorbic acid (AA) showed a maximum of 75.2% DPPH scavenging activity at 25 µg/mL. The bamboo plant has been used in traditional medicine in India (Ayurveda). It also has potential applications, especially in anti-stress and anti-aging [40]. In this work, we have elaborated on the effect of bamboo-based Ag NPs because of the antioxidant property of both the plant extract and Ag NPs. Surprisingly, bamboo-based Ag NPs showed higher antioxidant activity than a plant extract independently. Our results showed that the antioxidant DPPH scavenging properties of Ag NPs are maximum at 200 µg/mL with 74.4% compared with ascorbic acid (25 µg/mL), which showed 75.2% Fig. 6.[41] Similarly also reported the photochemical synthesis of Ag NPs using Pistacia khinjuk leaves extract (PKL@AgNPs). Overall, the bamboo-based Ag NPs showed much higher DPPH scavenging activity when compared with the only extract. This may lead to medicinal applications for Ag NPs concerning major oxidation-related diseases.Fig. 6 Depiction of percent scavenging activity of bamboo-mediated Ag NPs with various concentrations along with positive control ascorbic acid (AA)
The in vitro results revealed that the Ag NPs exhibited enhanced inhibition of cancer cell proliferation. The MTT assay was carried out to evaluate the cytotoxic effects of plant-derived Ag NPs against MCF-7 (breast cancer cell lines) and calculated their percent cell viability. However, a significant decrease in the percent cell viability after 60 μL concentration tested is observed in Fig. 7. A complete change in the percent viability was observed in control (no nanoparticles added) and treated (with Ag NPs). Hence, IC50 (inhibitory concentration at 50%) was observed at 80µL of Ag NPs added to cancer cells Fig. 7.Fig. 7 MCF-7 cell lines a control b treated c cytotoxicity evaluation of bamboo-mediated Ag NPs at various concentrations against (MCF-7) cell lines
Antibacterial activity
The antibacterial activity of Ag NPs was evaluated against five food-borne disease bacteria, i.e., two Gram-positive (S. epidermis and B. subtilis) and three Gram-negative (P. aeruginosa, E.coli, and S. Shigella boydii). The zones of inhibition (ZOI) of Ag NPs were determined at volumes of control, extract, 50 and 100 µl, individually. In treating two Gram-positive bacteria with AgNPs, the inhibition zones were observed to be 0, 4, 9, and 10 mm for S. Epidermis and 0, 4, 8, and 9 mm for B. Subtilis, and three Gram-negative bacteria (P. aeruginosa, E.coli, and S. Shigella boydii) at concentration 100 µl showed excellent activity, respectively. These results indicate Ag NPs in a concentration-dependent manner which was in concordance with the results obtained. In the present study, the maximum inhibition was seen at 100 µl of Ag NPs against B. Subtilis and, S. Epidermis and three Gram-negative at 100 µl showed excellent activity against (P. aeruginosa, E.coli, and S. Shigella boydii) as shown in Fig. 8. Some physical and chemical properties of Ag NPs were considered to elucidate their mechanism of antibacterial activity. The synthesized nanoparticles' size and shapes are critical in exerting antibacterial action. [42–44] showed that smaller-sized, spherical-shaped AgNPs displayed better germ-killing activity owing to their larger surface-to-volume ratio enabling better interaction with the bacterial cell membrane, thus destroying the respiratory system of bacteria, ultimately leading to death. This mechanism of antibacterial activity was accredited to Ag0 ions released from metal nanoparticles which were absorbed by the bacterial cell membrane resulting in subsequent alteration in permeability of the membrane, solidification of protein structure, inhibition of respiration, and altered enzyme function, finally leading to cell membrane damage. Especially, Ag NPs, due to their elevated tendency to react with sulfur and phosphorous of biomolecules in the bacterial cell, interact and inhibit DNA replication and also destabilize and degrade the outer membrane of the plasma membrane, thus reducing the intracellular ATP. In addition, due to the presence of a single peptidoglycan layer, Gram-positive bacteria are more susceptible to the treatment of AgNPs compared to Gram-negative bacteria [45]. All this aforementioned evidence suggests the potential antibacterial activity of Ag NPs against Gram-positive and Gram-negative bacteria, with a great emphasis on Gram-positive bacteria. These results possibly open new avenues for therapeutic potential against antibiotic-resistant bacteria. Ag NPs could frequently release silver ions (Ag+), which might be considered one of the mechanisms behind the bactericidal activity of Ag NPs. The positively charged Ag+ plays a vital role to exhibit the silver's antibacterial or toxicity activities of the silver (Ag), and to maintain its antibacterial or toxicity activities, the Ag should be in its ionized state. Due to the electrostatic attraction and affinity toward the sulfur proteins, the Ag+ ions adheres to the cytoplasm and cell wall, significantly enhancing the permeability, leading to the disruptions of bacterial casings.Fig. 8 Antibacterial activity of biosynthesized Ag NPs
Conclusion
The present research work on the basis of bamboo leaves extract secondary metabolites biosynthesis of Ag NPs was carried out. The secondary metabolites responsible for the reduction and capping agent of Ag NPs are present in the bamboo leaves extract. XRD analysis confirmed the formation of Ag NPs and was well matched with the standard card number. The UV–Vis spectroscopy determined the absorption peak at 425 nm; FTIR analysis indicated the presence of the various functional groups in the Ag NPs. The morphology of particle stability, average particle size, shape of the particles were analyzed by FESEM, DLS, and TEM. The bamboo-mediated Ag NPs showed potent antibacterial activity against microbial pathogens. The synthesized Ag NPs suggested significant scavenging activity by reducing DPPH free radicals. The bamboo-mediated Ag NPs resulted in dose-dependent anticancer against MCF-7 breast cancer cell lines showing good cell viability at various concentrations. This complete study concludes that bamboo leaves extract-mediated Ag NPs have excellent antibacterial, antioxidant, and anticancer activity. This approach of synthesized Ag NPs can be a used potential application in biomedical, and it may also be used in face mask coatings to prevent the coronavirus in the future due to being eco-friendly, cheap, non-toxic, and strong effective against pathogens. Finally, synthesized Ag NPs have been employed successfully to degrade the organic contaminant methylene blue.
Acknowledgements
Authors acknowledge the financial support from Maharashtra Bamboo Development Board (MBDB), Nagpur (Grant No: MD/MBDB/CR-86/18-19/589). The authors also sincerely acknowledge the encouragement given by Sri T. Sai Kumar Reddy, MD, MBDB, Nagpur, to carry out this work.
Author contributions
NJ investigation, data curation, writing—original draft, methodology, analysis, AA investigation, data curation, NA: formal analysis, TVR conceptualization, supervision, formal analysis, writing—review and editing, SV resources, formal analysis.
Data availability
All data that support the findings of this study are included in the article.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734976 | NO-CC CODE | 2022-12-14 23:28:31 | no | Appl Phys A Mater Sci Process. 2023 Dec 7; 129(1):13 | utf-8 | Appl Phys A Mater Sci Process | 2,022 | 10.1007/s00339-022-06279-1 | oa_other |
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Appl Phys A Mater Sci Process
Appl Phys A Mater Sci Process
Applied Physics. A, Materials Science & Processing
0947-8396
1432-0630
Springer Berlin Heidelberg Berlin/Heidelberg
6279
10.1007/s00339-022-06279-1
Article
Bambusa arundinacea leaves extract-derived Ag NPs: evaluation of the photocatalytic, antioxidant, antibacterial, and anticancer activities
Jayarambabu N. 1
Velupla Suresh 2
Akshaykranth A. 1
Anitha N. 1
http://orcid.org/0000-0003-4978-7011
Rao T. Venkatappa [email protected]
1
1 grid.419655.a 0000 0001 0008 3668 Department of Physics, National Institute of Technology, Warangal, 506004 India
2 grid.412419.b 0000 0001 1456 3750 Department of Biochemistry, Osmania University, Hyderabad, 500007 India
7 12 2022
2023
129 1 1311 8 2022
25 11 2022
© The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Bio-fabrication has become a safe approach for silver nanoparticles (Ag NPs). The plant-mediated biosynthesized Ag NPs have emerged as a potential substitute for conventional chemical formation. The biosynthesized Ag NPs were analyzed in terms of crystalline nature, morphology, chemical composition, particle size, stability, size, and shape of the particles. The XRD, FTIR, and TEM analysis indicate the presence of the bioactive secondary metabolites compounds. The bamboo-mediated Ag NPs demonstrated a notable antibacterial efficacy against Gram-positive and Gram-negative pathogenic microorganisms and showed significant antioxidant activity against DPPH free radicals. The degradation of methylene blue at various intervals under solar light irradiation was used to evaluate the photocatalytic performance of Ag NPs. Further, Ag NPs conveyed potent anticancer activity against MCF-7 cell lines with a significant value IC50. The bamboo leaves-mediated Ag NPs synthesized Ag NPs signified strong antibacterial, antioxidant, and anticancer activity; hence, it can be used in various biomedical applications and face mask coating to prevent the coronavirus after successful clinical trials in research laboratories.
Keywords
Antioxidant
Antibacterial
Anticancer activity
Ag nanoparticles
Bambusa arundinacea
Photocatalytic activity
Maharashtra Bamboo Development Board (MBDB), NagpurGrant No: MD/MBDB/CR-86/18-19/589 Rao T. Venkatappa issue-copyright-statement© The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2023
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pmcIntroduction
Nanotechnology is a rapidly evolving multidiscipline that contains designing, synthesizing, assembling, and modifying molecules/ bulk matter/ particles to nanostructured dimensions (1–100 nm in size) [1]. Nanoparticles have a large surface-to-volume ratio, giving them unique features and improving their mechanical, catalytic, optical, and magnetic properties, allowing them to be used in biomedical applications. They have been widely employed in medical, food, agriculture, optics, the environment, mechanics, chemical, photochemical, catalysis, cosmetics, electronics, sensing technologies, energy research, and other fields [2]. There are two types of nanoparticles: inorganic and organic. Metallic (Au, Ag), semiconductor (CdS, ZnO), and magnetic (Ni, Co) nanoparticles are the most common inorganic nanoparticles, whereas organic nanoparticles are carbon-based nanoparticles (carbon nanotubes, quantum dots) [3]. Metallic nanoparticles, in particular, have been widely exploited for various applications due to their unique features. Metallic nanoparticles’ therapeutic efficacy is owing to their optical property, which is proved by localized surface plasmon resonance [4]. Silver nanoparticles (Ag Nps) are particularly common among metal nanoparticles. They have many applications in biomedicine and industry due to nanoparticles’ physical, thermal, optical, chemical, catalytic activity, electrical conductivity, and antibacterial activity. These unique qualities have allowed Ag NPs to be used in various sectors such as antifungal, antiviral, anticancer, anti-inflammatory, drug administration, sensing, diagnostics, orthopedics, and so on [5].
The efficiency of Ag NPs inside biological systems is influenced by the size, surface chemistry, shape, size distribution, particle morphology, coating agglomeration, dissolving rate, and particle composition [6]. Silver is a non-toxic, harmless inorganic antibacterial agent that can kill over 650 different species of disease-causing bacteria [7, 8]. Various methods have been devised for the preparation of nanoparticles, each with its own set of benefits and drawbacks [9]. Metallic nanoparticles can be made using both chemical and physical processes. Although these technologies create particles with the desired properties, they are frequently expensive, time consuming, and undesirably harmful to living creatures and the environment. The biological technique has been utilized to generate nanoparticles to overcome the limitations of these physical and chemical technologies. Several biological resources have been employed to produce metal nanoparticles, including plant extracts, milk, microbes, and panchagavya [10, 11]. Among the different green sources investigated, microalgae offer essential advantages in terms of ease of development and living in harsh settings (such as temperature and pH) [12]. Recently, numerous advantages of biological Ag NPs production have been recognized. Several plant materials and microorganisms have been identified as possible Ag NPs production candidates. Specific proteins in plants and microorganisms have been postulated as a possible source of Ag+ ion reduction. It has been postulated that NADH-dependent nitrate reductase may reduce Ag+ ions to Ag0 ions [13]. However, the synthesis of Ag NPs using plant extracts has the potential to be more advantageous than microbes due to its simplicity in scaling up. [14]. Using microorganisms has some drawbacks, including high costs, aseptic environment upkeep, mass microbe cultivation, output quantity, and purification [13]. On the other hand, the green method involves using plant extracts, is environmentally friendly, cost-effective, and efficient [15]. Several researchers employing plant extracts such as Carica papaya [16], Azadirachta indica [17], Alternanthera dentata [18], Olea europaea [19], and Coffea Arabica [20] have been conducted in recent years to synthesize nanoparticles. Furthermore, plant extracts from various species are regarded as a beneficial approach for nanoparticle synthesis due to their extraordinary ability to synthesize a wide range of phytochemicals with a high reduction potential [19]. Sugars, polyphenols, terpenoids, alkaloids, proteins, and phenolic acids reduce metal ions into nanoparticles. These phytochemicals are also responsible for stabilizing the nanoparticles produced [21]. All parts of the bamboo plant, including the rhizome, bark, culm, leaves, shoots, roots, and seeds, have been used in clinical and therapeutic. Bamboo is the fastest-growing multipurpose woody plant. The natural substances abundant in bamboo leaves, including phenols, flavonoids, saponins, vitamins, glycosides, antioxidants, and some other compounds, have a role in reducing silver nitrate to Ag NPs (Table 1). At the same time, these compounds bound on the surface of the Ag NPs and enhanced the biological activities due to the presence of biological compounds.Table 1 Bioactive compounds of Bambusa arundinacea
Phytochemical compound Reference
Alkaloids [22]
Carbohydrates [23]
Glycosides [24]
Saponins [25]
Phytosterol [26]
Resins
Phenols
Fixed oil
Tannins
Diterpenes
Protein and amino acid
Flavonoids
Alkaloids
Carbohydrates
Glycosides
Saponins
In this present study, Ag NPs were green synthesized by the reduction of silver precursor in the presence of plant extract sources. The benefits of green synthesis techniques, ease of nanoparticle creation, eco-friendly, cost effectiveness, quick crystallization, and reduced waste generation are all demonstrated by the plant extract sources employed for the bio-reduction of silver nitrate to Ag NPs. The synthesized Ag NPs were analyzed by X-ray diffraction (XRD), FTIR spectroscopy, scanning electron microscopy (SEM), UV–Visible spectroscopy, dynamic light scattering (DLS), and TEM to investigates the antibacterial, antioxidant, anticancer, and photocatalytic activities of Ag NPs’.
Materials and methods
Materials
Bambusa arundinacea leaves’ extract solution, silver nitrate (Sigma Aldrich) 2, 2-diphenyl-1-picrylhydrazyle (DPPH) were purchased from Sigma-Aldrich, St. Louis, MO, USA.
Preparation of the plant extract
An extract of the Bambusa arundinacea leaves was used for the biogenic synthesis of Ag NPs. The leaves have been used as medicine for various inflammatory conditions. The leaves were washed with double distilled water to remove the dust and mud particles on the leaves' surface, and these were finely cut into small pieces before going to dry in the presence of sunlight. 20 gm of the leaves was immersed into 100 ml double distilled water and placed on the magnetic stirrer for 70 min at 80 °C to prepare for extractions of the solution. A Whatman filter paper used for filtration of the extract solution was kept at room temperature for cooling and finally used for the biogenic synthesis of Ag NPs.
Biogenic synthesis of Ag NPs
For the biogenic synthesis of Ag NPs, 0.5 mM silver nitrate was prepared in 100 mL double distilled water. The aqueous solution of the leaves’ extract was added to the above solution and stirred for 4 h at a temperature of up to 60 °C. Under these circumstances, the solution's color changed from a colorless solution to dark color due to the Ag+ conversion into Ago ions. Bamboo leaves extract as a reduction agent for the synthesis of Ag nanoparticles. Bamboo leaves contain phytoconstituents which help to stabilize the Ag nanoparticles as shown in Fig. 1. The biogenic synthesized Ag NPs were characterized with different analytic techniques for their morphology, stability, chemical compositions, crystallinity, and particle size.Fig. 1 Biogenic synthesis of Ag NPs
Antibacterial activity
The antibacterial activity of Ag NPs was investigated using the suitable disc diffusion method. The bacteria were isolated from an initial single colony and were grown overnight in nutrient broth. The items, including the glassware, reagents, and medium, were sterilized in an autoclave at 121 °C for 20 min under 15 kg/cm2 pressure. The bacterial inoculum was incubated in lysogeny broth for 24 h at 28 °C and 200 rpm, then re-suspended in a lysogeny broth medium until the optical density was adjusted to 0.1 at 600 nm, which corresponds to 108 colony-forming units (CFU)/mL. The spread plate method was performed in this bacterial suspension (each 100 µl) spread on the nutrient agar. Subsequently, wells were made on agar plates, and various concentrations of Ag were loaded. The entire agar plates were placed in the bacteriological incubator for 24 h at 37 °C, and the zone of inhibition was calculated with a measuring scale (mm).
DPPH scavenging assay
Ag NPs were investigated by DPPH (1, 1-diphenyl-2-picrylhydrazyle) scavenging assay. To the DPPH (50 µM) solution prepared in absolute ethanol (in the dark), various concentrations were added to 96-well microtitre plates. After adding NPs, the plate was placed in the dark, and the reaction samples were incubated for 30–60 min at room temperature. The DPPH solution incubated with reference standard ascorbic acid (25 µg/mL) and bamboo leaves extract served as positive and negative controls, respectively. The AgNPs sample was evaluated in triplicates, and the absorbance was recorded at 520 nm using a microplate reader (Micro Scan, MS5608A, ECIL, and India). A decrease in absorbance was recorded for calculating DPPH scavenging (%) using the following equation [27].DPPH scavenging activity%=DPPH absorbance-sample absorbanceDPPH absorbance×100
MTT assay
To test the cell viability (MTT) assay, the breast cancer cell line (MCF-7) was collected from the National Centre for Cell Sciences India. The cells were grown in Dulbecco’s modified Eagles medium (DMEM) containing 10% fetal bovine serum (FBS), 100 units/mL penicillin G and 1 μg/streptomycin, 5 μg/mL amphotericin B (Sigma-Aldrich Chemicals, St. Louis, United States) (2 mM) l-glutamine and non-essential amino acids (1X), (Himedia, Mumbai, India) at 37 °C in a humidified 5% CO2 incubator Nectarnova, Symbiogen, Chennai, India). Cytotoxicity of the nanoparticles was studied under the conditions after 80% confluence. Cells were trypsinized with 0.1% trypsin–EDTA and were harvested by centrifugation at 500 × g. Serial dilutions of cells were made from 1 × 106 to 1 × 103 cells per mL.
The cells were seeded in triplicates in a 96-well plate. The suspended cells were treated with 20, 40, 60, 80, and 100 µL concentrations of AgNPs, in a dose-dependent way for 24 h. Tamoxifen drug was used as a positive control, and tumor cells without nanoparticles were added to serve as a control. After incubation, MTT (20 µl, 5 mg/mL) solution was added to each well, and the cell viability was calculated by measuring the ability of cells to transform MTT to a purple-colored formazan dye. At 570 nm, the absorbance was observed using an ELISA instrument (MS5608A from ECIL, Hyderabad, India). The percent cell viability was measured using the following equation [28]Percent cell viability=A570sampleA570controlX100
where A 570 (sample) corresponds to absorbance obtained from the wells treated with nanoparticles, and A 570 (control) represents the absorbance from the wells in which no nanoparticle construct was added.
Characterization of Ag nanoparticles
The following analytical techniques carried out the characterizations of biogenic synthesized Ag NPs. First, the purity and crystallinity of Ag NPs were observed by powder XRD (Bruker advanced D8). The functional groups of biogenic nanoparticles were identified by FTIR, ranging from 500 to 4000 cm-1 (Bruker Alpha-II). The particle size and stability of the nanoparticles were measured by dynamic light scattering (DLS) (Horiba-SZ100). UV–Vis analysis was performed by spectrophotometer between 200 to 800 nm (Analytical Jena, Specord 210 Plus). The morphology of the biogenic synthesized sample was analyzed by field emission scanning microscope (FESEM, Carl Zeiss, Ultra Plus) size and shape of the nanoparticles were analyzed by TEM. Finally, X-ray photoelectron spectroscopy XPS (PHI 5600 Versa Probe III) was used to analyze the synthesized samples' surface components.
Results and discussion
Biosynthesized Ag NPs indicated the five diffraction peaks at 2θ position 32.20°, 38.16°, 46.15°, 67.40°, and 76.10°. These peaks correspond to the (122), (111), (200), (220), and (311) planes, respectively, and showed the face-centered cubic structure as shown in Fig. 2a. The unwanted peaks in the spectrum indicated the presence of various bioactive reducing agents and capping compounds accumulated on the surface of Ag NPs. The reducing agents of plant extract compounds were responsible for the synthesis of Ag NPs [29].Fig. 2 a X-ray diffraction pattern b UV–Visible spectra c FTIR spectra of biogenic synthesized Ag NPs
UV–Visible spectroscopy is the primary tool to confirm that as-synthesized materials are nanoparticles. Figure 2b shows UV analysis of as-synthesized Ag NPs mediated by Bambusa arundinacea leaves extract. The range of absorption spectra was between 200 to 800 nm, and the peak position appeared at 452 nm, indicating the formation of Ag NPs. The plasmon resonances of Ag were observed near 452 nm [30]. The metal contains the free electrons that go through plasmon resonance transitions in the visible spectrum, which gives rise to such strong colors. This type of property mostly appeared in Ag NPs due to the occurrence of free conduction electrons. The electric field of the inward radiation induces the creation of a dipole in the nanoparticles. The number of factors depends on the wavelength of oscillation. The nature of medium particles' size, as well as shape, were the most important ones.
FTIR analysis of the Ag NPs prepared from Bambusa arundinacea leaves extract is shown in Fig. 2c. The characteristic peaks around 3434 cm−1 were ascribed to the OH stretching vibration of the OH structure. The peaks around 2937 and 2368 cm−1were ascribed to C–H stretching vibrations. The peak position at 1611 cm-1 was ascribed to the C = C stretching vibration of aromatic rings. The peak at 1380 cm−1 was assigned to polyphenols group compounds [31–33].
Additionally, the peak around 1016 was attributed to alkynes C–H bending vibration. The peak position at 573 and 450 cm−1indicated the Ag NPs. The FTIR results verified that the bioactive compounds in the aqueous were distributed on the surface of Ag NPs and also responsible for the reduction and capping agent of silver ions, which is consistence with the previous reports.
The FESEM analysis was determined to evaluate the morphology, shape, size, and uniformity of the distribution of the Ag NPs. Figure 3a, b shows the FESEM images of biosynthesized Ag NPsat scales of 100 and 200 nm. Based on the FESEM images, the spherical nature of the Ag NPs was found [34]. The FESEM images showed that the average particle diameter of the synthesized Ag NPs varied in the range of 20–50 nm. The TEM analysis was determined to accurately investigate the shape and size of the synthesized Ag NPs. In the TEM images, the sizes of the nanoparticles were in the range of 30–40 nm with spherical structure particles [35]. In addition, the TEM analysis revealed the bioactive compounds' presence on the surface of the Ag NPs in Fig. 3d, e.Fig. 3 a, b FESEM images c zeta potential d, e TEM images f DLS particles size of biogenic synthesized Ag NPs
The average particle size of the biosynthesized Ag NPs was measured by dynamic light scattering (DLS) measurement. The DLS analysis showed that Ag NPs had an average particle size of 23.6 nm in Fig. 3f. In addition, the zeta potentials analyzer was observed to identify the stability of the Ag NPs and found to be − 19.3 mV as shown in Fig. 3c. The negative value of the zeta potential indicates that the components such as phenolic, flavonoids, glycosides, saponins, tennis, antioxidants, etc., present in the leaves extract solutions act as capping agents and stabilize the Ag NPs. Hence, the sufficient charge on the surface of NPs which is compatible with the repulsive force will stop the NPs agglomeration.
XPS analysis
The chemical state and near-surface composition of Ag NPs derived from bamboo leaves extract were confirmed by X-ray photoelectron spectroscopy. An XPS spectrum of the Ag NPs in the range of 0–800 eV is depicted in the Fig. 4a. The presence of such elements as carbon (C 1 s), silver (Ag3d), and oxygen (O 1 s) was observed. Figure 4b shows the binding energy (BE) associated with the Ag3d region of the sample utilizing high-resolution XPS (HR-XPS). Two peaks at 372 and 366 eV, produced by the orbital spin interplanetary splitting corresponding to the Ag 3d3/2 and Ag 3d5/2 core levels, are critical characteristics of the Ag3d region. The other peaks at 531 and 282 eV correspond to O1s and C1s. The O1s appearing in the region between 529–535 eV due to oxygen–carbon or water incorporated on the surface of the Ag NPs are shown in Fig. 4c. The C–C binding energy contribution at 282 eV corresponds to SP2 (C = C) [36, 37].Fig. 4 XPS spectra of a Ag NPs XPS survey spectrum b binding energy for Ag3d c binding energy for O1s d binding energy for C1s
Photocatalytic activity of biosynthesized Ag NPs
The degradation of azo dyes, such as methylene blue, was investigated in reactions utilizing the UV-irradiation approach to evaluate the photocatalytic activity of green synthesized Ag nanoparticles. Initial color changes caused by the catalytic breakdown of organic dyes in the presence of Ag NPs were visible. Methylene blue color intensity gradually turned from dark blue to white in UV irradiation, demonstrating the effective catalytic degrading activity of Ag NPs. This work used the radioactive dye methylene blue to test the potential nanomaterial as Ag NPs photocatalytic activity. Figure 5 shows the results; as the irradiation time increased, the efficiency of methylene blue decolorization gradually increased (up to 30 min). UV–Vis absorption spectra of MB dyes at different times showed decreasing peaks with the color shift into light color. When exposed to light, the MB absorption peak at 660 nm initially showed a rapid drop every 2 min. Ag NPs percentage of decolorization activity under UV irradiation may have reduced the amount of methylene blue (80 percent). However, as the exposure time lengthened, it persisted. The surface plasmon resonance (SPR) effect causes conduction electrons to be stimulated on the surface of silver nanoparticles when light photons interact with the Ag NPs. The surface hydroxyl groups can scavenge electron holes produced by the ultraviolet light system, which leads to the production of reactive oxygen species (ROS) and the start of the organic oxidation reaction. The size and shape of the metal nanoparticles, as well as the kind and structure of the dispersion medium, all impacted the interaction [38, 39]. As Ag NPs, a putative-reducing agent destroyed the azo dyes effectively. The results unequivocally show that Ag NPs effectively degrade hazardous pollutants in a photocatalytic manner from the textile sector.Fig. 5 Photocatalytic activity of biosynthesized Ag NPs as a nanocatalyst in the presence of NaBH4
Ag NPs showed potent DPPH scavenging activities at various concentrations. Among the concentrations tested, 25, 50, 75, 100, 150, and 200 showed the percent scavenging activities depicted in Fig. 6 as follows 26.8, 37.3, 45.0, 61.5, 65.5, and 74.4, respectively. The test of positive control ascorbic acid (AA) showed a maximum of 75.2% DPPH scavenging activity at 25 µg/mL. The bamboo plant has been used in traditional medicine in India (Ayurveda). It also has potential applications, especially in anti-stress and anti-aging [40]. In this work, we have elaborated on the effect of bamboo-based Ag NPs because of the antioxidant property of both the plant extract and Ag NPs. Surprisingly, bamboo-based Ag NPs showed higher antioxidant activity than a plant extract independently. Our results showed that the antioxidant DPPH scavenging properties of Ag NPs are maximum at 200 µg/mL with 74.4% compared with ascorbic acid (25 µg/mL), which showed 75.2% Fig. 6.[41] Similarly also reported the photochemical synthesis of Ag NPs using Pistacia khinjuk leaves extract (PKL@AgNPs). Overall, the bamboo-based Ag NPs showed much higher DPPH scavenging activity when compared with the only extract. This may lead to medicinal applications for Ag NPs concerning major oxidation-related diseases.Fig. 6 Depiction of percent scavenging activity of bamboo-mediated Ag NPs with various concentrations along with positive control ascorbic acid (AA)
The in vitro results revealed that the Ag NPs exhibited enhanced inhibition of cancer cell proliferation. The MTT assay was carried out to evaluate the cytotoxic effects of plant-derived Ag NPs against MCF-7 (breast cancer cell lines) and calculated their percent cell viability. However, a significant decrease in the percent cell viability after 60 μL concentration tested is observed in Fig. 7. A complete change in the percent viability was observed in control (no nanoparticles added) and treated (with Ag NPs). Hence, IC50 (inhibitory concentration at 50%) was observed at 80µL of Ag NPs added to cancer cells Fig. 7.Fig. 7 MCF-7 cell lines a control b treated c cytotoxicity evaluation of bamboo-mediated Ag NPs at various concentrations against (MCF-7) cell lines
Antibacterial activity
The antibacterial activity of Ag NPs was evaluated against five food-borne disease bacteria, i.e., two Gram-positive (S. epidermis and B. subtilis) and three Gram-negative (P. aeruginosa, E.coli, and S. Shigella boydii). The zones of inhibition (ZOI) of Ag NPs were determined at volumes of control, extract, 50 and 100 µl, individually. In treating two Gram-positive bacteria with AgNPs, the inhibition zones were observed to be 0, 4, 9, and 10 mm for S. Epidermis and 0, 4, 8, and 9 mm for B. Subtilis, and three Gram-negative bacteria (P. aeruginosa, E.coli, and S. Shigella boydii) at concentration 100 µl showed excellent activity, respectively. These results indicate Ag NPs in a concentration-dependent manner which was in concordance with the results obtained. In the present study, the maximum inhibition was seen at 100 µl of Ag NPs against B. Subtilis and, S. Epidermis and three Gram-negative at 100 µl showed excellent activity against (P. aeruginosa, E.coli, and S. Shigella boydii) as shown in Fig. 8. Some physical and chemical properties of Ag NPs were considered to elucidate their mechanism of antibacterial activity. The synthesized nanoparticles' size and shapes are critical in exerting antibacterial action. [42–44] showed that smaller-sized, spherical-shaped AgNPs displayed better germ-killing activity owing to their larger surface-to-volume ratio enabling better interaction with the bacterial cell membrane, thus destroying the respiratory system of bacteria, ultimately leading to death. This mechanism of antibacterial activity was accredited to Ag0 ions released from metal nanoparticles which were absorbed by the bacterial cell membrane resulting in subsequent alteration in permeability of the membrane, solidification of protein structure, inhibition of respiration, and altered enzyme function, finally leading to cell membrane damage. Especially, Ag NPs, due to their elevated tendency to react with sulfur and phosphorous of biomolecules in the bacterial cell, interact and inhibit DNA replication and also destabilize and degrade the outer membrane of the plasma membrane, thus reducing the intracellular ATP. In addition, due to the presence of a single peptidoglycan layer, Gram-positive bacteria are more susceptible to the treatment of AgNPs compared to Gram-negative bacteria [45]. All this aforementioned evidence suggests the potential antibacterial activity of Ag NPs against Gram-positive and Gram-negative bacteria, with a great emphasis on Gram-positive bacteria. These results possibly open new avenues for therapeutic potential against antibiotic-resistant bacteria. Ag NPs could frequently release silver ions (Ag+), which might be considered one of the mechanisms behind the bactericidal activity of Ag NPs. The positively charged Ag+ plays a vital role to exhibit the silver's antibacterial or toxicity activities of the silver (Ag), and to maintain its antibacterial or toxicity activities, the Ag should be in its ionized state. Due to the electrostatic attraction and affinity toward the sulfur proteins, the Ag+ ions adheres to the cytoplasm and cell wall, significantly enhancing the permeability, leading to the disruptions of bacterial casings.Fig. 8 Antibacterial activity of biosynthesized Ag NPs
Conclusion
The present research work on the basis of bamboo leaves extract secondary metabolites biosynthesis of Ag NPs was carried out. The secondary metabolites responsible for the reduction and capping agent of Ag NPs are present in the bamboo leaves extract. XRD analysis confirmed the formation of Ag NPs and was well matched with the standard card number. The UV–Vis spectroscopy determined the absorption peak at 425 nm; FTIR analysis indicated the presence of the various functional groups in the Ag NPs. The morphology of particle stability, average particle size, shape of the particles were analyzed by FESEM, DLS, and TEM. The bamboo-mediated Ag NPs showed potent antibacterial activity against microbial pathogens. The synthesized Ag NPs suggested significant scavenging activity by reducing DPPH free radicals. The bamboo-mediated Ag NPs resulted in dose-dependent anticancer against MCF-7 breast cancer cell lines showing good cell viability at various concentrations. This complete study concludes that bamboo leaves extract-mediated Ag NPs have excellent antibacterial, antioxidant, and anticancer activity. This approach of synthesized Ag NPs can be a used potential application in biomedical, and it may also be used in face mask coatings to prevent the coronavirus in the future due to being eco-friendly, cheap, non-toxic, and strong effective against pathogens. Finally, synthesized Ag NPs have been employed successfully to degrade the organic contaminant methylene blue.
Acknowledgements
Authors acknowledge the financial support from Maharashtra Bamboo Development Board (MBDB), Nagpur (Grant No: MD/MBDB/CR-86/18-19/589). The authors also sincerely acknowledge the encouragement given by Sri T. Sai Kumar Reddy, MD, MBDB, Nagpur, to carry out this work.
Author contributions
NJ investigation, data curation, writing—original draft, methodology, analysis, AA investigation, data curation, NA: formal analysis, TVR conceptualization, supervision, formal analysis, writing—review and editing, SV resources, formal analysis.
Data availability
All data that support the findings of this study are included in the article.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Int J Appl Posit Psychol
Int J Appl Posit Psychol
International Journal of Applied Positive Psychology
2364-5040
2364-5059
Springer International Publishing Cham
83
10.1007/s41042-022-00083-1
Research Paper
Virtuous Hope: Moral Exemplars, Hope Theory, and the Centrality of Adversity and Support
http://orcid.org/0000-0002-2102-2909
Thomas Kendra [email protected]
1
Namntu Musawenkosi 2
Ebert Stephanie 2
1 grid.257108.9 0000 0001 2222 680X Hope College, Holland, MI USA
2 iThemba Projects, KwaZulu-Natal, Sweetwaters, South Africa
7 12 2022
126
1 12 2022
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Psychology has primarily studied hope as a value-neutral trait even though it has a history of being counted among the virtues. The current study seeks to conceptualize hope as a virtue while building on the dominant empirical paradigm (Hope Theory; Snyder, 2002). Ithemba is the isiZulu word for hope, and this qualitative study investigated the lived experiences and meaning construction of ithemba/hope among 13 nominated moral exemplars in a South African township. Participants ranged from 20 to 75+, including farmers, educators, caregivers, entrepreneurs, and construction workers. Independent coders conducted thematic analysis from a theoretical top-down process (within Hope Theory and virtue science frameworks) and an inductive bottom-up approach (open coding). Data reflected much of the existing Hope Theory model; however, many pathways were relational and spiritual, and goals were inherently beneficial to others. A virtue science framework was used to construct the cognitive, motivational, and behavioral dimensions of virtuous hope. This study constructed the operational definition of virtuous hope as the ardent pursuit of realizing a particular vision of the common good with intention and action, often growing out of adversity and shaped in relation to other people and the transcendent.
Supplementary Information
The online version contains supplementary material available at 10.1007/s41042-022-00083-1.
Keywords
Hope Theory
Virtue Science
Moral exemplars
Social support
Adversity
University of IndianapolisUniversity of Indianapolis
==== Body
pmcIntroduction
The purpose of this study is to conceptualize hope as a virtue of communal value within a high-adversity context, expanding the current dominant psychological framework of hope theory (Snyder, 2002). Ithemba is the isiZulu word for hope. This qualitative study investigated the lived experiences and meaning construction of ithemba among exemplars of ithemba/hope in a South African township. This study conceptualized ithemba/hope through qualitative participant-driven data while comparing it to the prominent research paradigm.
Hope has historically been studied as a virtue in philosophical and theological writings for millennia (Snow, 2018; Tanesini, 2021). However, the current scientific conceptualization of hope (hope theory) assumes a cognitive-motivational process based on personal experiences. Thus, it does not adequately address hope that transcends circumstances or is communal in nature or benefits the surrounding community. A virtuous definition of hope would align with how humanity has historically conceptualized it. For example, Aquinas organized virtues hierarchically and placed hope as one of three transcendent virtues.
Character is understood to be context-specific (Lerner, 2018) and communal (Narvaez, 2008). Thus, virtuous hope cannot be studied in a vacuum, nor can it be divorced from the human drive for the betterment of one’s community. Just as courage exemplars might be salient in war times, it is especially relevant to study ithemba/hope in a context of high adversity. Thus, a qualitative study on moral exemplars in a community scarred by apartheid, economic inequality, and multiple pandemics is especially relevant to conceptualizing hope. This paper uses “ithemba” and “hope” interchangeably to reflect the multicultural iterative methodological process. This qualitative study operates from the framework that psychological science in African and non-Western nations must not produce knowledge from point zero (Makhubela, 2016). It is valuable to acknowledge the interconnection of all human knowledge and that even the current Western knowledge has African roots (Makhubela, 2016). Therefore, the multicultural research team utilized existing scientific frameworks while gleaning insights from exemplars of ithemba in a South African Zulu township.
Current Science of Hope
Hope theory has generated the most empirical research on hope in modern-day psychology. Pioneered by Snyder (1991), hope has been studied empirically as a cognitive-motivational process. This theory explains that hopeful thinking comprises two goal-directed processes (a) agency and (b) pathways (i.e., the will to change and the ways to get there). According to this theory, hopeful thinking requires both a goal-directed will (agency) and the generation of multiple routes forward (pathways; Snyder et al., 2002). In this model, emotions follow cognitions and provide feedback for future goal pursuits (Rand & Touza, 2021; Snyder et al., 2002). For example, devising a plan for success and engaging in each step forward fosters positive motivating emotions that propel the individual forward. The theory posits that actions and emotions create an iterative feedback process influencing hope. Progress and success increase hope. In contrast, repeated failures can result in a loss of hope (Rand & Cheavens, 2009). Data on Hope Theory in South Africa found that levels of hope were significantly related to power status, with rural participants having significantly lower levels than urban participants, females scoring lower than males, and ethnicities of privilege having higher hope (Boyce & Harris, 2013). An operational definition of hope that overlaps with social status might inadvertently be measuring success and opportunity.
Hope theory has generated much research, particularly seeing hope as a precursor to positive outcomes. Higher levels of hope predict better psychological adjustment, better physical well-being, and more robust academic and work performance (Rand & Touza, 2021). For example, studies among students found hope predictive of academic success in cross-sectional (Dixon et al., 2017) and longitudinal studies (Fraser et al., 2021). Based on hope theory’s current operational definition, a person with malevolent intentions could have high hope even if their goals were to harm others and pursue self-promotion as long as they have a well-developed sense of agency and can demonstrate persistence in developing paths towards their (selfish or anti-social) goal (see Shorey et al., 2002). Some research has correlated hope with prosocial and relational variables (Fraser, 2021; Rand & Touza, 2021), but its framework inadequately explains how hope emerges from adverse circumstances, or how it could function as a moral virtue (i.e., something inherently good and beneficial to others/the community; Jubilee Centre, 2017). Peterson & Seligman (2004) included hope as one of their 24 VIA character strengths and had detailed criteria for including each strengths, such as “morally valued” and “does not harm others”. However, its measurement operational definition centers positive expectations of the future and could still presumably apply to self-centered goals. Additionally, not all of the 24 VIA strengths are classified as moral virtues. Peterson & Seligman (2004) intentionally conflate hope with optimism and future-mindedness and openly suggest that their definition masks internal heterogeneity.
Positive youth development (PYD) research has found hopeful future expectations to be positively related to supportive parent-child relationships (Callina et al., 2014) and well-being (Kadir & Mohd, 2021). A meta-analysis of predictors of hope among youth found that the highest predictors were positive affect, life satisfaction, optimism, self-esteem, and social support (Yarcheski & Mahon, 2016). Except for social support, the meta-analysis is consistent with the individualistic benefits of hope. A follow-up meta-analysis found that peer support was better at predicting adolescent hope than parental support (Mahon & Yarcheski, 2017).
A review of the empirical literature on hope (including but not limited to hope theory; Scioli 2020) summarized that hope has been studied empirically as a mindset and a buffer to stress. However, philosophers and theologians (e.g. Aquinas) have long studied hope as rooted in relationships and faith. Sciloi critiques the current understanding of hope as over-representing a worldview of the “self-made man” that emphasizes a personal mastery-directed approach (Scioli, 2020). Positive psychology in particular has been criticized for imposing western individualism on the majority world (Kristjásson, 2013). A recent qualitative study with South African children noted the central role of community flourishing and the role of hope as a character virtue that is both stimulated by the community and for the common good (Cherrington, 2018). That study emphasized the importance of both existing frameworks and indigenous conceptualizations of hope, particularly those adopting an Africentric lens acknowledging the sociopolitical context and the organic interdependence of communities (Cherrington, 2018).
It would also be mistaken to believe that there is a “pure Zulu” ithemba/hope definition. Through the influence of the internet, TV, and smartphones, most people have access to many perspectives outside their immediate cultural setting (e.g., Nigerian televangelists and American social media influencers). This qualitative research aims at understanding an indigenous definition of hope, but linguistic constructs are always alive and embedded within broader globalized contexts. The current study seeks to operationally define hope through the eyes of moral exemplars so that the emerging definition might more closely resemble virtuous hope/ithemba.
Hope as a Virtue for Social Change
Brazilian educational theorist Paulo Freire explains that people hope not because they have succeeded in the past but because it is a moral imperative that drives social change (Freire, 2014). Philosophers have long written about hope as a virtue, and more recent writings have specifically categorized it as a civic virtue because of how it sustains collective identities and actions (Snow, 2018; Tanesini, 2021). Nancy Snow’s conceptualization of hope is embedded in shared cultural narratives, such as immigrants’ dreams of democracy and opportunity. According to philosopher Alessandra Tanesini (2021), when we hope, we pre-experience what we desire, which provides emotional scaffolding to persevere. Tanesini argues that a community’s shared memories and collective hopes are similar because they are both exercises of the imagination, one in the past (memories) and one in the future (hope). Thus, hope is a fundamental part of developing strong, caring communities. The PYD framework has suggested that hope is composed of self-regulation skills, connectedness, and positive future expectations, and these have strong theoretical ties to Contribution, a civic virtue (Callina, et al., 2015).
Tanesini (2021), Freire (2014), and Snow (2013) discuss hope as part of human creativity that provides people with the energy to persevere. Humans’ creative imperative is part of the virtue of ithemba/hope because it empowers people toward positive social action. The current science of hope helps explain individual success but does not adequately explain communal goal pursuits or relational sources of hope. For example, the dominant theory does not adequately explain a teacher or parent sacrificing for the hope of a child’s future or how hope can be strengthened through adversity or benefiting others. Virtue and moral science, in contrast, continuously emphasize the importance of social interactions and behaviors that benefit the broader community (Lerner, 2018; Narvaez, 2008; Thomas et al., 2022).
It is empirically relevant to study positive outliers who can elucidate a path forward and guide future operational definitions. According to Damon & Colby (2013), moral exemplars can portray moral creativity and contextually confront unjust and immoral narratives in a reflective and ongoing intellectual process. Exemplars reveal the range of morality and set an inspirational direction for future pursuits of moral science. In line with virtue researchers (Fowers, 2021), the current study assumes individual differences and internal person-level coherency (i.e. some people do have higher levels of moral virtues than others). Thus, it is possible (and appropriate) to utilize moral exemplars to conceptualize the virtue of ithemba/hope. Studying virtues or moral exemplars requires the disclosure and awareness of personal values. Researchers should openly reveal value commitments so these can be questioned and challenged (Fowers, 2022). The authors of this study posit that ithemba/hope is a virtue that is inherently good and necessary for social change, and irrelevant without adversity. Thus, ithemba/hope exemplars intentionally foster this virtue, center it around personal values, and have a record of habitually hoping. The current study of ithemba/hope exemplars in a socioeconomic context of adversity aims to deepen the psychological construct of hope.
Socio-historical Context & Current Study
This study takes place in a peri-urban community outside of Pietermaritzburg, South Africa. This township was historically reserved for non-whites, a long-lasting effect of apartheid. Due to pervasive unemployment, racial segregation, and lack of opportunities, many people must move to the city for jobs, leaving family or children. This location (Vulindlela, Kwa-Zulu Natal) has the highest HIV infection rate in the world (Dwyer-Lindgren, 2019; Kharsany et al., 2018) and has left many children orphaned.
The study of hope in a context of high inequality and systemic injustices is of particular conceptual interest because this context tests the optimistic limits of the goals and pathways of people with high adversity (Boyce & Harris, 2013). South Africa has the highest GINI score of all included countries (World Bank, 2014), and record levels of income inequality (IMF, 2020) which undermines social cohesion (Khambule & Siswana, 2017). In this setting, people with little financial resources live adjacent to affluence. The lasting structural legacy of apartheid makes it difficult for those in poverty to see the fruits of their labor. Thus, it is relevant to study hope when success is so much more complex than an individual desire to persevere. Lastly, these interviews were conducted in the context of the COVID-19 pandemic, which increased health and economic hardship nationally. This area was also affected by political unrest and looting in July 2021, which are symptomatic of low social trust and a grim outlook on the future (Patel, 2021).
Methods
Research Philosophy and Approach
This study is designed with an asset-based approach, assuming that this community has strengths and resources of wisdom to share (Keikelame & Swartz, 2019; Whiting et al., 2012). Existing research has left a gap in understanding the depth of hope in the context of adversity and its utility in helping others. The current empirical definition of hope is predominantly self-focused and studied in wealthy countries (Snyder, 2002) and has limited evidence for how it can emerge from suffering, persist in adversity, or be used toward the common good (i.e., as a moral virtue). Thus, to construct a deeper understanding of the virtue of ithemba/hope, qualitative research will be used to probe and interpret lived experiences instead of hypothesis testing. For this, researchers must be self-conscious about their role in co-creating and interpreting the phenomenon at hand (Braun & Clarke, 2006). Qualitative interviews are based on the assumption that the interviewer is there to listen and represent reality as the participants see it. The perspective of this study is that all views have an origin and embedded values. Thus, the researchers were careful to ascribe a conscious subjectivity to the process, and actively question their values and assumptions.
Participants
Ithemba exemplars were nominated by the leadership and staff of a large local community development non-profit. This organization has worked in the community for 20 years on a wide range of initiatives such as early child development centers, home visitation programs, youth mentoring initiatives, and community gardens, among others. The exemplars were community members, such as successful homestead farmers who endure many environmental challenges, creative entrepreneurs who have built opportunities for others in a difficult financial environment, mothers or grandmothers who have raised children that contribute to their community, and youth mentors who invest their time in upcoming generations. The non-profit nominated individuals embodied the concept of ithemba and demonstrated virtuous qualities despite conditions of repeated hardship. Fourteen participants were invited by the interviewer and 13 were interviewed. One person declined the interview because they were too busy. Participants ranged from 20 to over 75 (exact age uncertain) and various occupations such as farmers, educators, caregivers, and those actively seeking employment. See Table 1.
Table 1 Participant Description
Participant Interv. Length Sex Age Marital Status Family roles Household composition Occupation/Employment status
1 12 min Male 48 Married Father/ Husband Lives at his home with wife and kids Unemployed/self employed-Garden
2 29 min Female 60 Widow Mother/ Grandmother Lives with her son and grandchild Creche caregiver/teacher
3 33 min Female 75+ Married Grandmother Lives with husband at mission house, creche is on the same yard Creche caregiver/teacher
4 27 min Male 37 Married Father/ Husband Lives with wife and his 3 kids Construction site manager
5 34 min Male 34 Engaged Father/Son/ Brother Lives alone but his fiance and their child live in the community Programme coordinator
6 58 min Male 31 Single parent Father Lives alone, kids visit construction worker
7 48 min Female 38 Single parent Mother Lives with her mother and her 2 kids Community care giver
8 43 min Male 26 Engaged Father/Son/ Brother Lives with her grandmother and siblings Youth Mentor
9 41 min Female 20 Single Daughter/ Sister Live with baby brother and grandmother, mom works out of town and comes back on some weekends Student/ Unemployed
10 33 min Male 27 Single Brother/Father Lives with grandmother, uncle, aunt and baby brother Community gardener
11 41 min Female 65 Widow Mother/ Grandmother Lives with her 2 children and 6 grandchildren Early child development teacher
12 39 min Female 26 Single Daughter/ Parent Lives with her mother, child and cousin Unemployed
13 64 min Male 32 Single Father/Son/ Brother Lives with mother and sibling and visits his child Farmer
Data Collection, Transcription, Translation
The interviewer was a trusted community figure who shares the same cultural background and language as the interviewees. The interviewer was trusted largely because of their affiliation with a local non-profit, which has been engaged in community organizing and regularly works with the traditional leadership. The interviewer conducted standardized interviews in isiZulu and was trained by a local qualitative researcher to conduct high-quality interviews and qualitative principles such as fidelity and reflexivity. In general, the interviews followed the same format and order, but the interviewee had the freedom to ask follow-up questions as needed. Interviews took between 12 and 64 min, with the average being 39.4 min long. The first one was the shortest and this was perhaps related to the interviewer warming up, but could also be attributed to individual participant differences of succinctness and openness. The same person interviewed all participants and all interviews were included.
All interviews took place within the home/yard of the participant. Interviews were conducted in February of 2022 near the participants’ homes. Safety precautions were taken due to the Covid-19 pandemic. This study was approved by the Institutional Review Board prior to data collection. Participants were told this research is voluntary and confidential and there were no incentives. At the start of the visit, they were reminded the study was voluntary and they could opt-out at any point. Participants provided verbal consent for the interview to be recorded and transcribed without any personal names. Some of the interviews raised emotionally charged events such as stories of high adversity and loss. In those cases, the researcher reminded the participants they did not have to share and could opt-out at any time or not respond to a question. All participants wanted to remain in the study.
The interview started by inviting participants, “Tell me your story.” In the cultural context, this demonstrates a respectful start to a deep conversation and allows the interviewee to introduce themselves and their story in their own words. Other questions include: What does hope mean to you? Do you have any stories, from your life or your family that come into your mind when you think of hope? Describe a time when hope was strongest in your life. The full script and questions are in Supplementary Materials.
The questions were reviewed and translated by a native speaker of isiZulu in Kwazulu-Natal, South Africa, and verified by another researcher fluent in English and isiZulu. A professional South African translator transcribed and translated the interviews to maintain construct integrity. The interviewer reviewed all the transcripts for accuracy and verified their authenticity. An independent person compared the English and isiZulu transcripts for accuracy. The coding was primarily conducted in English, but isiZulu speakers specifically searched the transcripts to verify that ithemba was always translated as hope and vice-versa.
Data Analysis Process
After the interviewer had reviewed the translated documents for accuracy and authenticity, English transcriptions were analyzed by a team of undergraduate and graduate students alongside the authors. The isiZulu and English transcripts were also read side-by-side by another bilingual researcher who verified the process.
All names were omitted in the transcription process and analyzed blindly (the coders did not know the interviewees and had no access to names before or after the analysis). Coders only saw the basic demographic information provided in Table 1. Transcripts were analyzed using thematic analysis under a constructionist theoretical framework, which explores how participants construct their meaning of the world (Braun & Clark, 2006). The goal is not to produce an objective analysis of the event but instead focus on the individual’s account. The current study also takes the sympathetic stance of interpretation, where the researchers take the participant’s point of view of the participant instead of trying to question their perspective (critical stance).
To best understand how participants defined and embodied the concept of ithemba/hope, we utilized an iterative process using both a theoretical “top-down” process (to draw the wisdom and structure of existing scientific theories), as well as an inductive “bottom-up” process. Both are permitted in a thematic analysis as outlined by Braun and Clark (2006). The multicultural team is vital in de-colonizing the research process (Duden, 2021; Keikelame & Swartz, 2019). The translation and analysis plan establishes authenticity and trustworthiness in the cross-cultural interpretive process and detailed procedural descriptions are in the section below to be transparent about the decision-making process and conform to best practices in the field (Demuth, 2013; Duden, 2021).
Analysis and Trustworthiness
Each interview was processed at least twice independently and the analysts got together to discuss each code and any discrepancies until there was consensus and was brought to the larger group to further consensus.The interviewer audited the analysis at the end to verify accuracy and provide another layer of cultural insight and accountability into the authenticity of the themes extracted.
The first round of coding was completed in a theory-driven perspective, looking for areas in which the data aligned with Hope Theory (Snyder, 2002). All coders were well-versed with Hope Theory, having all recently engaged in a systematic literature review on this topic. At least two coders worked on every data item and consistently coded the same parts of the interviews as relevant to Hope Theory. All coders found evidence supporting Hope Theory in all interviews. The initial plan was to sub-code into agency and pathways, consistent with the quantitative measure. However, when attempting to sub-code data items the analysts found low inter-rater consistency. For example, in one story, the interviewee talked about their active role in establishing a community garden. One coder interpreted the story as an example of agency, because the participant expressed a clear focus on an end goal and their initiative to obtain that success. The other coder perceived that story as pathways example because, in context of the story, the garden was a means to the end goal of feeding the community. Hope Theory suggests that agency and pathways are iterative and additive and arranged hierarchically, in a sequence of goal-directed cognitions (Snyder et al., 2002). Thus, some lower goals (e.g. cultivating a garden) turn into pathways to higher-ranking goals (e.g. caring for others). Thus, in the coding process it became more important to look for broader Hope Theory themes instead of differentiating between goals and pathways. Once this was done, the interrater reliability came up to 97%. Researchers also conducted a coding analysis in line with a virtue science framework, looking at the cognitive, emotion/motivation, and behavioral dimensions of virtues (in line with Fowers et al., 2021). In that round, inter-rater reliability started at 80% (based on simple percentage agreement of both raters), but upon further conversations and honed operational definitions, independent re-coding reliability rose to 98%.
In the final open-coding analysis, the researchers inductively searched for themes and patterns by re-reading all the transcripts and jotting down topics and ideas that resurfaced. A group of four researchers (two authors, two research assistants) got together after repeatedly reading all interviews and they determined together a final list of codes and subcodes to be applied. In the meeting, they established operational definitions and talked through examples. Interviews were scanned for frequency and stories/quotes that exemplified each area. See Table 2 for a frequency table of the codes used. The inter-rater reliability was 99%. Both the interviewer and all analysts reported a sense of data saturation, with repeated themes and stories. This felt saturation provides some confidence that these insights have valuable information about the virtue of ithemba/hope in this socio-cultural context.
Results
The following results are subdivided into the Hope Theory framework (top-down) results and then the open coding (bottom-up) results.
Identifying Hope Theory: both Agency and Pathways
Ithemba/hope exemplars had a personal narrative of perseverance and plenty of stories of behaviors and thought patterns that demonstrated an inner sense of agency over the future and multiple pathways to pursue such goals as consistent with Hope Theory. Participant 7 said “Hope for me is believing that you have control of your life.” Participants demonstrated a mindset that is flexible to pursue multiple routes forward in the face of adversity which aligned with the pathways subdomain of Hope Theory. For example, Participant 4 said:A person with hope motivates themselves by avoiding looking at a situation from a single viewpoint. They try to look at situations from different angles. For example, If something happens to me. I don’t look at it as something that is coming to hurt me but as something that is teaching me a lesson. I really see it as my growth. I always tell people around me that you need to get God’s perspective.
The quote above demonstrates the cognitive flexibility needed to find multiple pathways in adversity and aligns with Hope Theory’s cognitive-behavioral approach. In response to the question about the disposition of ithemba/hope, Participant 2 said: “You motivate yourself by working hard. If you live with people, you have to always ask for forgiveness when you’ve done something wrong. You are always pursuing peace.”
The above quotes align Hope Theory in that work is a source of hope, but it also connects hope to a broader pursuit of an upright moral life that considers others.
Agency and Pathways as Relational and Transcendent
Though there was a clear alignment with the pathways and agency operational definition of Hope Theory, nuances became salient. Ithemba exemplars consistently connected their actions back to a common good. The Hope Theory coded items also had an explicitly relational component to this perspective (e.g. ‘pursuing peace’ in the quote above). While the main consistency with Hope Theory was the cognitive and action-oriented approach, the main divergence was the relational and transcendent nature of these strategies and goals, with a strong focus on the interdependent nature of success and the other-oriented approach to the main goals. For example, in response to “how does your community foster hope?”, Participant 9 said:Churches are helping foster hope and also the different programs in the community brought by organizations. These programs keep the young people busy because these programs stop them from doing bad things like crime. And these programs also help them see their potential so these programs bring hope to the communities.
Hope Theory’s model posits that personal successes stimulate hope. But it was also evident in the data that other people’s success stimulated hope. Participant 5 said “People in our community nurture hope by looking up to those who have succeeded within the community.” Vicarious success can produce hope. These themes of faith and social support will be expanded through the open coding iteration of the process.
Virtue Science Coding Analysis
If hope is to be defined as a moral virtue, it should have the dimensions other virtues have. According to Fower and colleagues (2021), virtues have the dimensions of knowledge/cognition, emotion/motivation, and behavior. These dimensions also align with philosophical writings about virtue measurement, which require knowledge (appropriate virtue schemes), behaviors (action scripts and consistent patterns), upright motivation, and habituated dispositions (Snow et al., 2020).
Knowledge/Cognition
Ignorance is not a source of virtue (Fowers et al., 2021). The data analysis identified four specific sub-categories for knowledge/cognition as virtuous forms of cognitive ithemba/hope.
Knowledge of Adversity and Strategies is Central to Virtuous Hope. Many data items coded as “knowledge/cognition” had some connection to knowledge of adversity. For example, Participant 2 “Hope opens my mind. If you have hope you need to stand and be watchful the same way as somebody crossing the road. You need to ensure that you have looked at all sides.” Virtuous hope must be distinguished from naive optimism. For example, someone can think things will get better but can be ignorant of adversity or the strategies and sacrifices necessary. That person is not demonstrating virtuous hope because they lack the cognition/knowledge dimension. Hope is not positive thinking and does not imply short-term gains or an easy life. Ithemba exemplars spoke of their prioritizing and planning processes. For example, Participant 13 characterized hope as engaging in prudent spending and planning for long-term financial goals. They specifically mentioned adversity and their plans for the future. Similarly, Participant 4 said “[hopeful people] don’t take rushed decisions. They put much thought into it and thoroughly investigate before deciding”. These quotes stand in stark contrast to naïve optimism. Exemplars described their hope shrewd toward the challenges ahead.
Exemplars Nurture a Cognitive Focus. All interviews reflected on the importance of focusing on the goals. Participant 2 leads an early child development (creche) center and said, “I had a vision of a big garden at the creche that was going to supply food for the parents and the community at large”, and also said, “A person with hope does not have discouraging thoughts.” Her vision and focus on that goal demonstrate the cognitive habit of hope and aims at the benefit of the broader community. Multiple participants explicitly mentioned not paying attention to gossip or others’ opinions but instead focused on stories of hope from their family narratives or past experiences. Not entertaining negative thoughts (a cognitive dimension of the virtue of hope) is not the same as one-dimensional positive thinking. This study suggests that virtuous hope is informed of the adversity ahead, has a clear goal, and is supported by intellectual virtues such as perseverance and critical thinking. Cognitive hope is a slowly built habitual process. Participant 3 said that “[people who are full of hope] take time to nurture the hope they have.” This is consistent with the neo-Aristotelian perspective of virtue as a trait honed through habits (Snow, 2020).
Hope is Specific and Grounded. The interviews specifically named sources of hope and their goals ahead. Most mentioned specifically God and theological beliefs as their source of hope (see Table 2). Participant 3 said, “You need to understand that your hope comes from God. He will get you through it all.” Participant 5 said “It was the support of people in my life that contributed to my hope. My colleagues, friends and family … Another thing that encouraged me was the verse from the Bible.” Interviewees specifically named their sources (typically spiritual or relational) and their goals (typically service-oriented).
Emotion/Motivation
People can engage in prosocial behaviors (e.g. gratitude) for the wrong reason (e.g. to gain favor), which is one of the differentiators between prosocial and virtuous actions. Thus, a hopeful feeling or motivation based on social desirability would not qualify as virtuous hope.
Ithemba Exemplars are Motivated to Help Others. The ithemba/hope exemplars were motivated to contribute to their community, such as planting a community garden, wanting to be an example of perseverance to others, working to keep families together, and caring for children in the neighborhood. Participant 8 said “I always ask myself before I do something if it is good for other people.” These exemplars consistently took the perspective of others and used that as a way to motivate personal actions. Participant 10 said a newspaper recognized him for his work in the community garden. When describing the spotlight, he hoped the publicity would give others hope and benefit the community. He did not disregard his benefit but centered the motivation to help others.
Adversity and Role Models. Similar to the cognitive dimension, relationships and adversity are central to the emotion/motivation dimension. Participant 12 said, “It is also important to look at people who have gone before you for motivation. When I see people succeed, especially those who have been through worse struggles than I have been, I get inspired.” These exemplars flipped the narrative about adversity and saw their struggles (not just successes) as a source of hope. This dimension might be a key source of differentiation between virtuous hope (ithemba hope herein defined) and hope theory (as defined by Snyder, 2002).
Behavior
For virtues to be meaningful, they must have a behavioral manifestation (Fowers et al., 2021). For example, unless gratitude is expressed or generosity is enacted, the virtue lacks substance. The behavioral dimension of hope aligns well with the operational definition of Hope Theory, which emphasizes a problem-solving plan and an agency behind it. Hope Theory differentiates self-efficacy from hope because the former does not require any intentionality or action toward the goal (Rand, 2018). Thus, from both a Hope Theory and a virtue science framework, hope must do something.
Of the three virtue dimensions, the behavioral code was the most frequent, with all interviews mentioning specific actions participants engaged in, which exemplified their hope. At first glance, the behaviors seemed varied but centered around helping behaviors, such as working with youth, caring for children, and supporting others. When asked specifically about behaviors related to hope, participants pointed out the importance of encouraging others and sharing their struggles. Exemplars talked about how hopeful people are reliable and disciplined, including spiritual disciplines such as daily prayer or scripture reading. While most of the behaviors mentioned seemed like broadly good moral behaviors, a closer look revealed some common attributes. Hopeful people invest and give and encourage.
Hopeful people invest. Exemplars invested in the future in a disciplined manner that exceeded direct personal benefit. Participant 12 talked about reading to her child as an act of hope, and Participant 4 spoke of teaching his child to pray for the things they want. Participant 8 described taking his child to a good school so his child would have a better future and helping youth with their applications to jobs and universities. Most participants spoke of their work and labor as a manifestation of their hope. While this may seem broad given the variety of professions and life stages, working to improve something implies a belief that a better future is available and within their power to influence. The act of parenting is an investment into someone else’s future. If they did not have the hope that the future was affected by their labor, they would not engage in long-term strategies such as reading to young child. Participant 7, a single parent with a painful chronic illness said, “the little I have I am able to give them everything they need”.
Hopeful people give. Participants described how they were motivated to provide for their families and help others even when things were not guaranteed. Participant 7 spoke of caring for her teenage daughter’s baby so her daughter could complete her education. Participant 13 described his challenges in school, especially in learning to speak English, but his constant pursuit of excellence. As a farmer, he is reliant upon grant funding, and he said, “Currently, I am able to help people get different types of funding, but when it comes to me, I always have a hard time getting funding for myself, but I am hopeful that I will eventually get the funding I need.” He helps others even though his own needs are unmet. Without hope, there would be a scarcity mindset that would promote a fear-based hoarding of resources.
Hopeful people encourage others. Most of the behaviors recorded were helping-oriented behaviors. While most of these were tangible such as caregiving and action-oriented, many people also expressed the desire to listen and talk to others as an active part of living hope. For example, Participant 8 described taking time to help youth and talking to them. Participant 6 said, “it is good to testify about what you know. Even in my preaching, I like to talk about the things that people experience. This helps us to even prepare for things that are still going to happen.” While the behaviors for hope might seem broad, they center on the belief that the future can be better, at least for others, and that actions today matter.
Open Coding
The section below reflects the open-coding process. Table 2 provides the breakdown of each code and they are ordered by frequency.
Table 2 Open coding frequency by interview
Interview Number
Level 1 Level 2 1 2 3 4 5 6 7 8 9 10 11 12 13 Sum
Hardship/Adversity 1 1 1 1 1 1 1 1 1 1 1 1 1 13
Family (broken relationships, deaths) 1 1 1 1 1 1 1 1 1 1 1 11
Job-related 1 1 1 1 1 1 1 7
Community (violence, sickness, malnutrition) 1 1 1 1 1 1 6
Faith/God/Prayer 1 1 1 1 1 1 1 1 1 1 1 1 1 13
Personal faith disciplines 1 1 1 1 1 1 1 7
Faith community/church 1 1 1 1 1 1 1 7
Personal relationship with God 1 1 1 1 1 1 1 1 1 1 10
Theological convictions/beliefs 1 1 1 1 1 1 1 1 1 9
Social support 1 1 1 1 1 1 1 1 1 1 1 1 1 13
Supportive (giving support) 1 1 1 1 1 1 1 1 1 1 1 1 1 13
Supported by others (receiving) 1 1 1 1 1 1 1 1 1 1 1 1 1 13
Insufficient of support 1 1 1 1 1 1 1 7
Difficult relationships 1 1 1 1 1 5
Morality/virtues related to hope 1 1 1 1 1 1 1 1 1 1 1 1 1 13
Treating others well 1 1 1 1 1 1 1 1 1 9
Antithesis: Self-centered behavior 1 1 1 1 1 1 1 7
Source of hope 1 1 1 1 1 1 1 1 1 1 1 1 1 13
Self 1 1 1 1 1 1 6
Beyond self 1 1 1 1 1 1 1 1 1 1 1 1 12
Faith/God 1 1 1 1 1 1 1 1 8
Mental discipline (always hoping) 1 1 1 1 1 1 1 1 1 1 1 1 1 13
Unwavering attitude 1 1 1 1 1 1 1 1 1 1 1 1 12
Hope unglued from success 1 1 1 1 1 1 1 7
“but” stories 1 1 1 1 1 1 1 7
“one day” stories/dreams 1 1 1 1 1 1 1 7
Vision/Seeing ahead 1 1 1 1 1 1 6
Progressive (Push forward) 1 1 1 1 1 5
Family Narratives of Hope 1 1 1 1 1 1 1 1 1 1 1 11
Ancestors/parents 1 1 1 1 4
Supporting/leading children/offspring 1 1 1 1 1 1 1 1 1 1 1 11
Community Problems 1 1 1 1 1 1 1 1 8
Breaking social contract 1 1 1 1 1 5
Violence and youth disengagement 1 1 1 1 1 1 1 1 8
Transcendence 1 1 1 1 1 1 1 7
SUM 15 30 26 23 19 23 22 27 24 26 27 23 21
Hardship: Hope Refined Through fire
The most resounding theme in the data was the saturation of stories of adversity and hardship. When people were asked about their perceived status as someone of hope, they told their stories of deep tragedy and loss, and sorrow. The authors’ experiences of interviewing/reading the transcripts made it apparent that the commonality of hope exemplars is adversity, not success. Of these, most (n = 11) mentioned family tragedies such as broken relationships and loss. For example, Participant 6 said, “Both my parents passed in front of my eyes.” Many people mentioned unemployment and underemployment challenges (n = 7) and personal hardships due to community such as break-ins, robbery, and violence (n = 6). Participants told stories of homelessness, chronic pain, family deaths. Participant 8 said, “[my mother] died in the first month of my job and I had to use my first salary to bury her.”
Hope Theory places stressors as a central part of the model (Snyder, 2002); however, repeated failures would eventually lead to a loss of hope according to the model (Rand & Cheavens, 2009). The sheer depth and breadth of suffering represented by these ithemba/hope exemplars leads us to believe that the current Hope Theory model is inadequate to explain the juxtaposition of these high levels of hope and sorrow, especially from a virtuous perspective.
The stories of adversity were embedded within larger narratives where the participant gave meaning to their suffering and described how it contributed to their high levels of hope. Participant 4 said, “I don’t look at it as something that is coming to hurt me but as something that is teaching me a lesson. I really see it as my growth. I always tell people around me that you need to get God’s perspective.” Faith and social support were just as pervasive (n = 13) as adversity and likely key variables that differentiate how repeated adversity can lead to exemplar-status instead of hopelessness.
Faith: Spiritual Source and Support
All participants mentioned faith/God even though there was no faith-related interview question. Faith played a central role in their ability to sustain high levels of ithemba/hope. Within this theme, four subcodes were identified. Most people spoke of their faith as a personal relationship with God that sustained them (n = 10). Personal faith disciplines (n = 7) were items such as regular Bible reading and prayer habits such as Participant 2 who said “I would sit by the swings in the morning and pray.” or Participant 10 who said ‘the only way to stay motivated is reading the Bible.” These were in response to the questions about what contributed to high ithemba/hope and how hopeful people are motivated, respectively.
Most interviewees (n = 9) elaborated on specific theological beliefs they hold that sustains their hope, such as Participant 10 who said “Believing that God is real is part of hope because we are not sure if it is true but we have hope that God is real.” Lastly, many participants (n = 7) mentioned their churchs in the context of providing either support or structure to their lives or community.
Social Support: Catalyst or Dilutant
The interview questions specifically asked about social support, so it is not surprising that all participants were included in this theme. However, it showed up many times outside of that question response and, all told, was a pervasive theme. Support is a source of hope. This is exemplified in Participant 9 who said “hope, when you are alone, will not take you far” and Participant 10 said “[my neighbor] gives me compost and I give him vegetables. We help each other.” That participant also described feeling supported by those who buy his produce and support his business. Being supported can act as a catalyst to transform hardship into hope. All participants mentioned people whom they support, emphasizing the network and interconnected nature of hope. Participant 2 said, “Hope does not mean that you must be on the receiving end at all times. It encourages you to give back to others.“
It would be remiss to only provide a one-dimensional approach to the effects that relationships and communities have on hope. Participant 6 said that people who do not have the same (hopeful) mindset could “dilute your hope.” He told a story about how many people doubted him and how he was rejected by his family. He said, “because I have hope, I do not move with the crowd.” Thus, negative relationships can be a dilutant to someone’s individual level of hope, dissolving the spark.
Morality: Virtues Related to hope
Although the interview questions never asked about virtues or moral motivations, all participants made connections between ithemba/hope and other virtues. Of those, nine people specifically mentioned how it was positively connected to kindness. Seven participants talked about the antithesis of hope as being self-centered or selfish. We created a list of all of the virtues mentioned that participants explicitly connected to ithemba/hope: gratitude, reliability, love, generosity, joy, kindness, prudence, patience, perseverance, wisdom, humility, and self-discipline. While the translation process did ensure that the word ithemba was always translated as hope and vice-versa, this overlap emphasizes the importance of creating a virtuous definition for hope/ithemba. Two participants made explicit reference to the Southern African moral framework of Ubuntu which scholars summarize as respect for human life and passion for community related to virtues such as helpfulness, conviviality, sharing, mutual trust and unselfishness (Mawere & Marongwe, 2016; Zimunye et al., 2015). Anti-apartheid activist Archbishop Desmond Tutu, described Ubuntu through the proverb “umuntu ngumuntu ngabantu”, or, “I am because we are” (Battle & Tutu, 2009).
Participant 8 shared,I think the purpose of hope is to defeat giving up because when people lose hope they give up. There is a Zulu saying that says ‘I am because we are’. That also means you can see hope in other people and hope can bring about unity… I believe that hope can fight things like inequality in the community.
In this description, hope’s purpose is situated clearly in a dynamic relationship to the community – it is for the benefit of the community (“it can bring about unity”, it can “fight inequality”), as well as the community bringing hope to individuals.
Source: Internal, External, Transcendent
All of the participants referenced a source of their hope, with most having a combination of various sources (see Table 2). We coded sources as coming from within the person (e.g., individual differences of perseverance and agency), from outside the person (e.g., social support, a job) or as having a divine or faith-based source (e.g., God). All but one (n = 12) mentioned a source outside themselves, even if not including God/faith. While all participants mentioned God/faith/spirituality as related to hope (see sections above), eight participants explicitly mentioned God/faith as a source of hope.
Mental Discipline: Deep Anchor & Pessimistic hope
One of the most salient commonalities of these ithemba exemplars is the apparent resilience of their hope, where they repeatedly described that they would hope “no matter what.” Participant 7 said, “Hope is something you can never lose regardless of the situation you are facing. And when you have hope, things happen.“ The subcode of unwavering attitude (n = 12) was created with coding requirements that participants must mention hardships and a positive attitude simultaneously. Participant 3 repeatedly said, “no matter what” and “Even when things come, you will not be shaken.” Participant 2 said, “At times, I did not get a salary, but I always had hope,”
Seven participants had at least one story that we categorized as a “one-day” story. Such as Participant 10 who said, “I have hope that one day I will be a farmer with twenty hectares of land… hope gives you encouragement and that one day you will succeed.” Seven participants also told at least one story coded as a “but” story. Participant 7 said, “I am always sick, but with God’s grace I always recover.“ Participant 11 said, “there was no electricity, but we stayed hopeful.”
Six people specifically talked about holding on to a vision for the future as part of their hope. Participant 2 leads an early child development (creche) center. She said, “I had a vision of a big garden at the creche that was going to supply food for the parents and the community at large.” Participant 6 said, “The fact that I want to build a home is not a dream but a vision. It is something that won’t change.“
It is one thing to look back on adversity and retell the story from a hopeful vantage point once the troubles have passed or the success is earned. To differentiate these stories from a narrative bias, an additional subcode was developed for stories where people expressed hope at the time of the interview even though it was clear that their situation was far from success. While all participants had an objective level of ongoing hardship due to the inequality and challenges of their community, a few situations stood out. For example, Participant 5 told the story of how drugs have negatively affected her family. At the time of the interview, there was no indication that things would improve yet, she said, “My nephew has started using drugs. We have hope for him also.” Similarly, Participant 13 described still waiting for funding for his farm, and Participant 12 said, “I have been without employment since 2018. I have a strong hope that I will get a job. I still submit my CV when there is a vacancy available.“ She had been applying for jobs for four years and is hopeful and continuing to apply. Her story is an example of what we conceptualize as a “deep anchor” to hope. She is not exemplifying a “new” or “naïve” hope. Perhaps the first few applications could have easily sustained a positive perspective. However, at this point, another rejection will likely not change her hope. The anchor of her hope is much deeper than the next piece of bad news. These stories made us (authors) contemplate the “pessimistic hope,” a hope that might even anticipate bad news to inoculate against hopelessness/cynicism, strengthening resolve towards paced, action-oriented, disciplined hope.
Hopeful people hold fast and push through. There were five instances where the English word “progressive” was used in the transcript. For example, Participant 1 said: “[ithemba exemplars] are progressive. You would not progress in life without hope.”, Participant 5 said “a person with hope is progressive.” Here, the word translated as “progressive” refers to the isiZulu phrase “qhubekela phambili” (n = 5). Qhubekela is to “go on,“ and phambili means forward. While this project did not aim to conduct specific discourse analysis, the open coding process allowed researchers to investigate the cultural undertones of this specific concept because its English translation seemed insufficient. Qhubekela phambili has connotations of strenuously pushing forward. Rather than the word for perseverance, which had a connotation of holding on but being stationary, qhubekela phambili was the idea of “holding fast while pushing forward”. The phrase implies challenges and implies hardships. An old hymn commonly sung in churches in the area that says, “You people of faith, qhuba phambili!“ It is a rousing gospel song, where everyone sings out “Qhuba phambili!“ repeatedly in the chorus, encouraging people to continue in their efforts. Despite whatever, people with this quality push forward and push through in an active strenuous process. This theme demonstrates the habitual discipline of hope that is honed through hardships and narratives of resilience.
Family Narratives of hope: Speaking into Their Future
Most participants (n = 11) connected ithemba/hope to their family narrative either in the generation above them (n = 4), or in raising their children (n = 11). Participants described hope as a generational pursuit. Participants talked about how they related hope to raising children and caring for the younger generations of families. Participant 10 told the story about how his grandfather used to have a community garden, and this young man started a garden like his grandfather used to have. He saidI teach my child a lot about hope. When he visits me, I bring him to the garden and I tell him stories and I tell him that one day we will have a bigger garden and I can see that he also has hope now.
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He said that “without hope as a parent nothing can happen.” Similarly, Participant 5 said, “Being a parent is all about hoping. We start hoping before the baby arrives… before they can dream for themselves we are already speaking things into their future.” It is as if a parent’s hope provides a “starter dream” for the child to connect to and build upon.
Community Problems: Contexts can Discourage
Several people (n = 8) mentioned community-level problems that discouraged hope. This was coded separately from the hardship theme and from the social support theme because those were at the individual level, and this one was at a neighborhood level, not their personal lives. Most participants (n = 8) mentioned how youth disengagement/violence (e.g., unemployment and delinquency) discouraged hope. This theme accentuates the contextual role of hope and how it is spread through networks and the social fabric of a community.
Discussion
The current study brings together ithemba/hope exemplars who helped construct a definition of virtuous hope. This study sought both a top-down and bottom-up analytic process because psychology is a universal undertaking that must embrace existing wisdom while continuing to explore. Rejecting existing knowledge can still lead to euro-centric results and “otherizing” implications (Makhubela, 2016). Based on the results, the following operational definition is put forth:
Virtuous hope involves the ardent pursuit of realizing a particular vision of the common good with intention and action, often growing out of adversity and shaped in relation to other people and the transcendent.
Additionally, this study posits that virtuous hope is necessary for positive social change and is irrelevant without adversity, thus is more other-oriented and less tied to personal success than hope defined by hope theory. Virtuous hope is grounded in specific beliefs and actions, thus is distinct from naive optimism. This definition is further elaborated in the discussion below where it is integrated with existing literature.
Ardent Pursuit of the Common Good
The dominant overlap between the Hope Theory analysis and the open-coding process was the portrayal of hope as a habitual discipline that requires persistence and action with a strong sense of agency and mental flexibility to pursue multiple paths toward a goal (aligning with Snyder, 2002). Most studies on Hope Theory are related to positive personal outcomes (e.g., education, employment success, health recovery) and very few Hope Theory studies correlate it with pro-social or other-benefitting outcomes (see Schornick et al., under review). Hope Theory scholars suggested that cultures could vary in what they consider moral and virtuous goals, thus the definition itself would be value-neutral (Shorey et al., 2002). However, the self-oriented definition of hope is also culturally-based. This small qualitative study suggests a revisiting of this value-neutral part of Hope Theory or at least separately construct a virtuous definition of hope, one that is socially oriented and guided by moral values for the common good.
Ancient Greek philosophers agreed that virtues are fostered through habits and enable individuals and communities to flourish (eudaimonia; Aristotle, 1999). Thus, if hope is to follow an Aristotelian model of virtue (see Snow et al., 2020), it should be motivated for the right reasons and hopeful behaviors must be enacted because it is ‘the right thing to do’. The current science of hope helps explain individual success, but does not adequately explain communal goal pursuits or relational sources of hope. The dominant theory does not adequately explain a teacher or parent sacrificing for the hope of a child’s future or how hope can be strengthened through adversity or benefit others. Virtue and moral science, in contrast, continuously emphasizes the importance of social interactions and behaviors that benefit the broader community (Lerner, 2018; Narvaez, 2008; Thomas et al., 2022). Moral virtues are distinct from intellectual/epistemic virtues (e.g. attentiveness; perspective-taking) or performance virtues (e.g. confidence) (Fowers et al., 2021; Jubilee Centre, 2017). Moral virtues are habitual behaviors that are inherently good and beneficial to others (Jubilee Centre, 2017) and the science of moral virtues is specifically focused on people’s choices and agency that are habitually cultivated (Fowers et al., 2021). Lastly, under Aquinas’ hierarchy of virtues, hope is a transcendent virtue. The data presented here aligns with this view as the hope exemplars displayed many other supporting virtues.
Honed Through Adversity
This study supports the definition of hope as an active trait that both holds fast and pushes forward. Ithemba/hope also aligns with how Hope Theory distinguishes itself from optimism. Optimism is more general and less agentic than hope and can be derived from external and even superstitious sources (Rand, 2018). The definition of hope constructed by these exemplars portrayed it as an active strenuous process grounded in specific beliefs and actions, different from simply a positive outlook. The construct of “pessimistic hope” is helpful to differentiate hope as a virtue when used for the common good. While optimism might be more of a stylistic individual difference (e.g., it is useful to have both optimists and pessimists on a team), hope is a virtue that all can practice. Optimism might not be inherently good because it could lead to miscalculations and can be unglued from reality. However, hope defined herein is inherently good because by definition, it is matured through adversity and has proven itself through habitual practice.
Adversity played a central role in the development, description, and flourishing of ithemba/hope. When asked about stories of hope, people told stories of tragedy. Hope Theory encompasses some setbacks/stressors, but adversity does not take center stage in this model. In that theory, repeated failures can result in a loss of hope (Rand & Cheavens, 2009) and success is more central to propelling future goal pursuits and positive emotional responses (Rand & Touza, 2021; Boyce & Harris, 2013) conducted research in a representative South African sample looking at Hope levels using Hope Theory and found that those in higher privilege groups had higher hope levels. Yet, we find evidence of hope exemplars with such high levels of adversity and sociological challenges. Unless hope is researched in situations of high inequality, its operational definition may be skewed to a socioeconomic profile of greater success. The ithemba/hope exemplars herein described deep anchors of hope that are likely only honed through adversity.
Virtuous Hope is Relational and Spiritual
Relationships are a central factor that enables the study of hope as a virtue. Relationships are a key component of character development (Lerner, 2018; Narvaez, 2008). Children who have stronger relationships at school develop higher levels of virtues such as bravery, prosocial leadership, and fairness (Thomas et al., 2022). Furthermore, in that study, improvements in relationships were predictive of steeper gains in virtues. Relationships seem to be germane in the development of virtues, and virtuous hope is no exception. The ithemba/hope that the exemplars described was multi-sourced, and participants named people who constructed/sustained their hope. Participants tied their own stories of ithemba/hope to bigger family storylines, seeing the broad narrative arch. The family narrative piece is not currently well explained by Hope Theory’s theoretical or empirical base because most research is on personal hope and personal benefits. Perhaps this is because of how hope is currently defined, over-centering personal success in its measurement, or perhaps it is a lack of research interest thus far in identifying and studying hope as beneficial and connected to a broader communal purpose. Although there is less research on this in hope theory, there is some work that highlights the importance of shared goals for communal hope (Snyder et al., 1997).
Hope exemplars know the source of their hope. They were not vague or blind, but explicitly mentioned their support system, their specific theological beliefs, and their agency over the future (only one of these is encompassed in the current Hope Theory). The participants’ spiritual perspective of the world allowed them to transcend their adversities and provided an anchor and purpose to their lives.
Limitations
Participants were invited and told that they were considered by others to be ithemba exemplars. For this reason, they may have been susceptible to amplifying their hope in the interview and be affected by a social desirability bias. However, since this study seeks to define hope as a virtue that is good for others, there must be communal acknowledgment of this virtue.
It is worth noting that 95% of this community would self-identify as Christian, and nearly 80% of the national population self-identifying as Christian (South African Government, 2016). In attempting to generalize the wisdom of these exemplars to a broader study of hope, it is important to highlight their conviction and specificity of beliefs so as to not overgeneralize to all spiritual or theological beliefs. Religions differ in their approach to hope thus this study does not wish to over-generalized into a common spiritual influence on hope. These interviewees were selected based on their “exemplar” status, thus this project does not insinuate that this manifestation of hope is representative of their community or any other group. By nature of selection, this is an exemplary sample that can provide insight into the range and ideals of human development (Damon & Colby, 2013).
The interview questions asked about social support and community and thus may have led interviewees to speaking about these issues. However, the majority of the coding came from stories and examples which emerged from the earlier questions in the interview. The later questions that singled out the community and the social support ended up providing an outlet for participants to talk about some of the negative influences of the community (e.g. “Community problems” code). Regardless, the quotes and operational definition provide depth to the construct that the questions could not anticipate.
Adversity may have emerged as central in this study because it is a central part of the community which has suffered from pandemics, apartheid, and high unemployment. However, we posit that the current definition of hope is too centered around success because its research base is predominantly in wealthy Western contexts. Thus, the limitations of this study provide a helpful juxtaposition of the limitations of the current study of hope.
Conclusion
In a context of high injustice and inequality and many financial and health challenges, adversity surfaced as a more central component of hope than success. This study aligned well with the current model of Hope Theory in its agentic and flexible pathways perspective but the goals mentioned and sources of hope were transcendent and relational in nature. A virtue science framework highlighted the knowledge of adversity and disciplined hopeful thoughts, which stems from a motivation for the common good, and intentionally invests, gives, and encourages others. Open coding constructed the definition of hope as an ardent pursuit of a common good and shaped by relationships and the transcendent. Future research should seek to create quantitative measurements of virtuous ithemba/hope so it can be further measured and studied across contexts.
Electronic Supplementary Material
Below is the link to the electronic supplementary material.
Supplementary Material 1
Acknowledgements
The authors would like to thank all the moral exemplars who were interviewed, the non-profit iThemba Projects, and research assistants Zachary Schornick and Nolan Ellis.
Statements and Declarations
Conflict of interest
The authors report there are no competing interests to declare and no financial information to report. Partial funding for interview costs (transportation, transcription, translation) was provided from an internal research grant from the University of Indianapolis InQuery Grant.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734978 | NO-CC CODE | 2022-12-14 23:28:31 | no | Int J Appl Posit Psychol. 2022 Dec 7;:1-26 | utf-8 | Int J Appl Posit Psychol | 2,022 | 10.1007/s41042-022-00083-1 | oa_other |
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Med Oncol
Med Oncol
Medical Oncology (Northwood, London, England)
1357-0560
1559-131X
Springer US New York
36472716
1900
10.1007/s12032-022-01900-y
Review Article
Implications of reactive oxygen species in lung cancer and exploiting it for therapeutic interventions
ArulJothi K. N. [email protected]
1
Kumaran K. 1
Senthil Sowmya 1
Nidhu A. B. 1
Munaff Nashita 2
Janitri V. B. 3
Kirubakaran Rangasamy 4
Singh Sachin Kumar 67
Gupt Gaurav 8910
Dua Kamal 711
http://orcid.org/0000-0002-8886-8482
Krishnan Anand [email protected]
5
1 grid.412742.6 0000 0004 0635 5080 Department of Genetic Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, SRM Nagar, Chennai, 603203 India
2 grid.412742.6 0000 0004 0635 5080 Department of Biotechnology, Faculty of Engineering and Technology, SRM Institute of Science and Technology, SRM Nagar, Chennai, 603203 India
3 grid.262613.2 0000 0001 2323 3518 Rochester Institute of Technology, Rochester, NY USA
4 grid.444708.b 0000 0004 1799 6895 Department of Biotechnology, Vinayaka Mission’s Kirupananda Variyar Engineering College, Vinayaka Missions Research Foundation, Salem, Tamil Nadu India
5 grid.412219.d 0000 0001 2284 638X Department of Chemical Pathology, School of Pathology, Faculty of Health Sciences, University of the Free State, Bloemfontein, 9300 South Africa
6 grid.449005.c School of Pharmaceutical Sciences, Lovely Professional University, Jalandhar-Delhi G.T Road, Phagwara, Punjab India
7 grid.117476.2 0000 0004 1936 7611 Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007 Australia
8 grid.448952.6 0000 0004 1767 7579 School of Pharmacy, Suresh Gyan Vihar University, Jagatpura, Mahal Road, Jaipur, 302017 India
9 grid.412431.1 0000 0004 0444 045X Department of Pharmacology, Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India
10 grid.449906.6 0000 0004 4659 5193 Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun, India
11 grid.117476.2 0000 0004 1936 7611 Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Sydney, NSW 2007 Australia
6 12 2022
2023
40 1 4317 10 2022
15 11 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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Lung cancer is the second (11.4%) most commonly diagnosed cancer and the first (18%) to cause cancer-related deaths worldwide. The incidence of lung cancer varies significantly among men, women, and high and low-middle-income countries. Air pollution, inhalable agents, and tobacco smoking are a few of the critical factors that determine lung cancer incidence and mortality worldwide. Reactive oxygen species are known factors of lung carcinogenesis resulting from the xenobiotics and their mechanistic paths are under critical investigation. Reactive oxygen species exhibit dual roles in cells, as a tumorigenic and anti-proliferative factor, depending on spatiotemporal context. During the precancerous state, ROS promotes cancer origination through oxidative stress and base-pair substitution mutations in pro-oncogenes and tumor suppressor genes. At later stages of tumor progression, they help the cancer cells in invasion, and metastases by activating the NF-kB and MAPK pathways. However, at advanced stages, when ROS exceeds the threshold, it promotes cell cycle arrest and induces apoptosis in cancer cells. ROS activates extrinsic apoptosis through death receptors and intrinsic apoptosis through mitochondrial pathways. Moreover, ROS upregulates the expression of beclin-1 which is a critical component to initiate autophagy, another form of programmed cell death. ROS is additionally involved in an intermediatory step in necroptosis, which catalyzes and accelerates this form of cell death. Various therapeutic interventions have been attempted to exploit this cytotoxic potential of ROS to treat different cancers. Growing body of evidence suggests that ROS is also associated with chemoresistance and cancer cell immunity. Considering the multiple roles of ROS, this review highlights the exploitation of ROS for various therapeutic interventions. However, there are still gaps in the literature on the dual roles of ROS and the involvement of ROS in cancer cell immunity and therapy resistance.
Keywords
Reactive oxygen species
Oxidative stress
Cancer therapy
Lung cancer
Programmed cell death
issue-copyright-statement© Springer Science+Business Media, LLC, part of Springer Nature 2023
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pmcIntroduction
The inability of the cells to abide by contact inhibition paving its way toward uncontrolled proliferation causes cancer. Cancer cells can bypass all the checkpoints that are otherwise present in a normal mitotic division and thereby disrupt the functioning of the body. The cancer is named based on the site of origin; thus, lung cancer originates in the cells of the respiratory system. Lung cancer is among the most common ones with an estimation of 2.20 million new cases per year. About 27% of all cancer-related deaths are attributed to lung cancer making it responsible for being the leading cause of cancer-related deaths worldwide. The prognosis for lung cancer remains the poorest of all tumor types owing to the 5-year survival rate of an average of 10–20%. However, survival is particularly determined by the stage at which the diagnosis is made, the earliest stages have a 5-year survival of 92%, whereas the last stages have nil. There are two broad classifications in lung cancer namely—Non-Small Cell Lung Cancer (NSCLC) and Small Cell Lung Cancer (SCLC); the former accounts for 85% and the latter for about 15% of the total diagnoses [1, 2]. Lungs are also a primary metastatic site for cancer of other origins like the breast, skin, pancreas, and liver. 75% of lung cancer is endemic to smoking and the remaining is due to occupational exposure and air pollution [3].
Reactive oxygen species (ROS) are a regular ramification of cellular metabolism and the altered redox state of the cell due to these results in cancer. These are molecules with an extra unpaired electron, superoxide (O2·−) and hydroxyl (OH·), and as the name suggests it is unstable and highly reactive. Superoxides are processed by superoxide dismutase (SODs) to hydrogen peroxide (H2O2) and they further produce hydroxyls either via the Fenton reaction or the Haber–Weiss reaction. Hydrogen peroxide also gets converted to other damaging oxidants like hypochlorous acid and hypobromous acid. ROS can be generated exogenously and endogenously. The exogenous trigger is via exposure to environmental gases like NO2, SO2, CO, and particulate matter in the air like from cigarette smoke, while mitochondria and membrane-bound NADPH oxidases are the main intracellular sources of ROS involved in the signaling cascade. Cancer cells fine-tune the ROS signaling and its scavenging to their comfort. The expected scenario in the cell upon increased ROS production would be to induce oxidative stress and eventual cell death; however, in the cancer niche detoxification of ROS via scavengers like NRF2 (nuclear factor-erythroid 2-related factor 2), PRXs (peroxiredoxins), GPXs (glutathione peroxidases), SODs (superoxide dismutases), and CAT (catalase) help maintain the required ROS for pro-tumorigenic signaling.
Mitochondrial ROS (mROS) predominantly contributes to the cellular ROS with 1% of the total oxygen consumption being utilized in superoxide release. The cancer cells have an increased ROS production which elevates multiple signaling pathways ultimately leading to the transcription of cellular proliferation genes. The prime target of mROS is the inhibition of PTEN (phosphatase and tensin homolog), which leads to incessant activation of the PI3K/AKT pathway, finally resulting in enhanced proliferation and survival. The AKT activation further increases ROS levels promoting cancer cell proliferation and survival. ROS is also known to oxidize and inhibit other phosphatases like the MAPK phosphatases that result in growth factor receptor activation, inducing MAPK/ERK signaling, an established pro-proliferative signaling. MAPK/ERK pathway is specifically made conducive to lung cancer by mROS regulation of Kras-induced anchorage-independent growth of the cells [4]. ROS manipulates tumor cell survival by activating transcription factors like NF-κB and nuclear factor-erythroid 2-related factor (NRF2), which stimulate the expression of antioxidants to avoid ROS-mediated cell death. NRF-2 is negatively regulated by KEAP1 which is inhibited by ROS-mediated oxidation of cysteine residues on KEAP1 protein, thus stabilizing the former transcription factor to increase the transcription of GPXs to maintain the desired ROS balance in cancer cells. It is apparent that the annihilation of the mitochondrial respiratory chain reduces ROS production diminishing tumorigenesis and the knockout of NRF-2 promotes oxidative stress, thus killing the tumor. The cells in the cancer microenvironment thrive on hypoxia, hypoxia-induced angiogenesis, and glycolysis, wherein the role of mROS pitches in by activating and stabilizing HIF-1α an oxygen-sensitive subunit of HIF-1 protein via inhibition of PHD2 activity. In normoxia condition, PHD-2 degrades the HIF-1α, but under hypoxia, HIF-1α dimerizes with HIF-1β and localize to the nucleus to transcribe pro-angiogenic genes like VEGF1, and genes implicated in glycolysis, cell survival, and mobility. Hypoxia upregulates the Serine hydroxy methyltransferase 2 (SHMT2) enzyme, which increases the catabolism of mitochondrial serine to compensate for NADPH. Matrix metalloproteases that degrade the extracellular matrix are upregulated by mROS, and additionally, it also inhibits the activity of TIMP (tissue inhibitor of metalloproteinase). It is also known that mROS specifically targets Src Homology region 2 (SH2)-containing protein tyrosine Phosphatase 2 (SHP-2) and Focal adhesion kinase (FAK), enabling the cell to migrate and prevent cell death by anoikis, matrix detachment-induced apoptosis. Mitochondrial DNA is 5 times more susceptible to mutations via oxidative damage than nuclear DNA owing to its locality in the vicinity of Electron transport chain (ETC) and lack of histone proteins and DNA repair mechanisms. A cytochrome b mutation in mitochondrial complex II of ETC induces metastasis in cancer cells and mROS is comprehensive to all factors required for tumorigenesis from fabricating a tumor favorable microenvironment to metastasis [5, 6].
External factors regulating ROS in the lungs
Lungs are the main organ for gaseous exchange in the body, which makes them more vulnerable to ROS exposures. Factors like lifestyle, disease conditions, and medications are known to influence the ROS levels in the lungs. Lifestyle factors regulate ROS levels in different ways, for example, cigarette smoking and occupational hazards introduce exogenous ROS into the body, while healthy eating habits and supplements help scavenge ROS. Cigarette smoke enters the lungs in two phases: gaseous and tar, containing over 4000 chemical substances, including free radicals and other oxidants. The gaseous phase contains nitric oxide, an oxidant that readily reacts with superoxide (O2·−) to form peroxynitrite (ONOO−). The tar consists of more steady free radicals like the semiquinone radical, which readily reacts with oxygen to form O2·− and·H2O2. Individuals exposed to occupational and environmental hazards, including xenobiotics (pesticides and metals), physical factors (radiation, heat, noise), and biological agents, resulting in the production or exposure of ROS leading to formation of tumors, are depicted in Fig. 1. The occupational situations that are reported to be involved in oxidative stress-related toxicity are textile, metal, cement, pesticide industries, and radiology centers. The prolonged exposure to pollutants and allergens stimulates ROS generation and result in inflammation in the windpipe and asthma [6]. During infection, excessive amounts of ROS are generated in the respiratory tract to fight the invasion of virus and bacteria, but the downside of this defense mechanism is that these ROS needs to be scavenged adequately to avoid tissue damage. Indeed, recent reports suggest that COVID-19 infection and lung cancer are regulated through the ROS/NRF2-mediated mechanism. Medications used for various diseases may also result in ROS generation during the course of their metabolism, which may adversely affect the host cell physiology (Fig. 1). For example, the long-acting beta agonists asthma drug, indacaterol, enhances H2O2-induced ROS generation in THP1 cells. Doxorubicin (Dox) is an example of a drug generating ROS as an intermediate metabolite in the host system. Dox can be readily reduced to semiquinone by the mitochondrial enzymes, which in turn generate superoxide anion and H2O2. It is noteworthy that the ability of the drugs to induce ROS in host cells was exploited for anticancer and other treatment strategies. Another important lifestyle factor in modern-day life is physical exercise. Reports suggest that heavy physical workouts augment free radical (ROS) generation through the mitochondrial metabolism of skeletal muscles and other tissues, causing oxidative injury in the corresponding tissues. Certain diets and supplements can also operate the ROS levels in the human system. Vitamins E, C, and beta-carotene are considered major choices of antioxidants that are supplemented via diet in addition to the endogenous antioxidants. Antioxidants, in general, tend to diminish ROS and protect the host cells from oxidative injury and other adverse conditions [7].Fig. 1 An overview of various sources and ill effects of ROS: Exogenous sources of ROS include radiation, environmental smoke, industrial toxins, alcohol, ozone, heavy metals, and cigarette smoke, as well as endogenous sources such as mitochondria, phagocytotic cells, lipids, protein, -oxidation of fatty acids in peroxisomes, cancer cells, and enzymes such as cytochrome p-450 and thiol oxidase in the endoplasmic reticulum [8]
ROS/oxidative stress leads to cancer, metastasis, and invasion
ROS can readily react with DNA bases to form DNA adducts, which leads to miscoding during replication. This may lead to several irreversible mutations in the genome, especially when they occur in oncogenes or tumor suppressor genes; it leads to cancerous state [9]. The oncogenes, K-Ras, Jun, and Myc and the tumor suppressor genes TP53, CDKN2A, and STK11 are the most commonly reported moieties to carry mutations in cancer patients. Moreover, lipid and protein peroxidation by the oxidants can also induce more free radicals and enhance the chances of carcinogenesis through DNA mutations. Chronic pulmonary obstructive disease is an inflammatory disease caused by free radicals released from tobacco smoking and has more possibilities for genotoxic changes and adds a 4.5-fold risk of developing lung cancer [1, 10]. When the cells have sufficient irreversible damage in their crucial genes, they attain a survival advantage state, which helps them to proliferate continuously, evading programmed cell death. These specific events are collectively known as cancer initiation and promotion [9, 11, 12]. ROS has been implicated in the regulation of integrins and other extracellular matrix proteins, which in turn regulate cellular migration and adhesion. This property of ROS has been investigated by several researchers with an interest in cancer cell migration and invasion. Although the exact mechanism of regulation remains to be elucidated, there is a growing body of evidence to suggest that integrin, an important cell anchoring protein, when interacting with antibodies or extracellular matrix proteins, produces cellular ROS through mitochondrial metabolism. Furthermore, it activates several oxidases, including NOX, 5-LOX, and COX-2; and Rac-1, a rho GTPase protein, which is involved in ROS-mediated actin cytoskeleton rearrangement required for cell migration. Moreover, ROS regulates stabilization and destabilization of VE-cadherin junctions, which in turn regulate cell–cell adhesion, leading to permeability change, migration, and proliferation. Breaking of extracellular matrix (ECM) by the cancer cells is termed as invasion, which is crucial for metastasis [13–15]. There are several proteases involved in degradation of ECM, of which matrix metalloproteinases, cathepsins, and urokinase plasminogen activator are relevant in cancer context. ROS has been associated with abnormal upregulation of these inhibitors through NF-kB and MAPK pathways. ROS can trigger SNAIL and promote epithelial-to-mesenchymal transition (EMT), and SNAIL has also been shown to increase ROS levels in prostate cancer cells [18, 20]. Interestingly, ROS and TGF-β signaling are interconnected during EMT. When TGF-β is stimulated, ROS increases the phosphorylation of Smad2 and p38, which upregulates α-SMA and fibronectin, respectively, and ERK1/2 activation leads to E-cadherin repression [16, 17]. Together, it is apparent that ROS regulates cancer cell metastasis and invasion through various signaling molecules.
Effect of ROS on cancer stem cells
Cancer stem cells (CSCs) can self-renew and differentiate into many lineages, like normal stem cells. This helps in accelerating tumor growth and heterogeneity. It is also possible for CSC to develop from differentiated cancer cells as a result of adaptation to the microenvironment and therapeutic pressures; such factors are responsible for their heterogeneity. Because of their high resistance, CSCs are resistant to conventional cancer treatments, which lead to metastasis and recurrence of cancer as well as the possibility of carcinogenesis due to EMT malfunction. This epithelial–mesenchymal transition (EMT) is important for embryonic development and the formation of various tissues or organs [18]. Based on their respective biological functions, EMTs can be divided into three distinct classes. Type 1 refers to Epithelial–Mesenchymal transition associated with embryo implantation, formation and development of the organ; type 2 corresponds to tissue regeneration, organ fibrosis and wound healing and type 3 tell how EMTs occur within tumor cells that have already undergone genetic and epigenetic changes. These types of EMT are essential for the progression of cancer and cancer stem cells.
The tumor microenvironment is typically rich in proteins like the growth factor TGF- β and cytokines that activate the pathway that affects the longevity of CSCs [19]. Based on this analysis, the researchers concluded that cytokines and growth factors increased cancer stem cells' flexibility and EMT properties. Apart from the role of the tumor niche, the researchers have also observed lower levels of ROS in cancer stem cells, this made the CSCs more sensitive to radiotherapy and minimized their ability to clone themselves. The excess level of ROS has increased oxidative stress that triggers cancer cell death and also damages protein, lipids, and DNA, which are regarded as oncogenic since they result in instability of the genome [20]. Regulation of ROS can be understood through the following example: in gastric cancer, a variant of CD44 (adhesion molecule) can protect CSCs in the membrane-proximal region by using insertion in alternative splicing; in the human liver, CD13 negatively regulates ROS that increases the ability of stem cells in it. And it has been observed that ROS has a specific effect on Cav-1 expression, motility of cells and also it helps in the migratory process with the help of Akt signaling in the non-small-cell lung cancer cell line [21].
Reports suggest that low concentration of ROS is necessary for CSCs, whereas a higher concentration of ROS promotes tumor growth. Research has shown that when transplanting CD24 and CD49 in mouse mammary CSCs, ROS levels were low and also, the CSCs were able to adhere and develop a novel tumor and it was demonstrated in head and neck tumors as well [22]. Together, for maintaining the prominent features of CSCs, ROS has a crucial role in redox control, cell signaling, also in therapeutic targets.
In human lung cancer A549 cells, Tan-IIA induces the ROS and decreases the mitochondrial membrane potential. Hence, it is mitochondrial dependent to increase apoptosis in Tan-IIA pathways in human A549. As TanIIA increases the production of ROS, it results in generation of cytochrome c that triggers apoptosis [22, 23]. In cancer cells, to increase the expression of CSCs and EMT, activation of the PI3K/AKT/mTOR pathway is needed as it triggers glycolysis to increase ROS levels. Since mTOR is needed for tumorigenic properties in ovarian CSCs. AKT also regulates ROS levels, Cellular longevity, and metastasis through signaling via the FOXO family of transcription factors. The production of manganese superoxide dismutase/superoxide dismutase-2 (Mn SOD/SOD2) also plays an important role for this process. Metastatic progression and invasion of markers are thought to catalase SOD2 in cancer such as colon, lung squamous, and prostate carcinoma. In addition, over expression of SOD2 induced mitochondrial ROS and HIF2 activity, as well as CSC formation, resulting in increased tumor invasiveness and poor prognosis for lung cancer patients. Activation and expression of Notch pathway components are related to insufficient outcomes and resistance to radiation or chemotherapy. The signaling cascade improves CSC’s drug resistance and proliferation by stimulating angiogenesis and EMT. Notch signaling also regulates CSCs by interfering with signaling protein as demonstrated by HER2 that promotes CSCs multiplication and proliferation in lung cancer. By upregulating AKT, Notch activates AKT in a manner that is independent of transcriptional regulation. Notch also increases ROS scavenging enzyme expression, resulting in low ROS levels [22, 24].
ROS in cancer tumor microenvironment
It is generally known that the tumor microenvironment (TME), which is made up of a wide variety of cell types, including numerous immune cells, cancer cells, and fibroblasts linked with cancer, produces a significant amount of ROS [11]. In lung tissues, benzo(a)pyrene (BaP), which is widely regarded as the substance that causes cancer at a higher rate than any other substance, triggers a cascade of chronic oxidative stress and inflammation and also increases the likelihood of mutation in certain genes, which may eventually result in the development of cancer. NF-κB, a transcriptional factor that is activated by oxidative stress, is implicated in triggering lung cancer through stimulation of the inflammatory cascade. It is reported that the inflammasome NOD-like receptor protein 3 (NLRP3), a type of intracellular multiprotein complex found in the microenvironment of a tumor, has been linked to the development of chronic inflammation in patients with lung cancer induced by benzo(a)pyrene (BaP) [25]. The formation of NLPR3 is responsible for the maturation and release of inflammatory cytokines in the microenvironment of a tumor. These cytokines, which promote cancer progression and are also responsible for immunological tolerance, are accountable for both of these processes [26]. One of the main factors contributing to the TME's resistance to immunotherapy, particularly immune checkpoint blockades, is the high levels of ROS [27, 28]. The CD4 + Foxp3 + regulatory T (Treg) cells are enrolled into the tumor microenvironment and act as potent immune suppressors, according to recent findings [29, 30]. Treg cells that have migrated into tumors experience apoptosis due to the elevated ROS levels in the TME. Notably, tumor-infiltrating apoptotic Treg cells reduce the ATP to adenosine, to suppress the immunity of programmed death ligand 1-blockade-mediated antitumor T-cells. These cells are extremely sensitive to ROS because of their weak NRF2 linked with the antioxidant defense system. It is significant to observe that dead Treg cells have a stronger immunosuppressive effect than living Treg cells [28]. This suppression of ROS can result in improved cancer immunotherapies. In fact, a new nano-scavenger that was anchored to the extracellular matrix prevented the apoptosis of suppressive immune cells by removing ROS [31].
Dual roles of ROS
ROS levels in noncancerous cells are closely regulated by balance between ROS production and scavenging, which is mainly caused by cellular respiration, and antioxidant levels, which are predominantly maintained by intracellular pools of glutathione and NADPH [32].
ROS act as signaling molecules/secondary messengers at low levels, regulating cellular and differentiation proliferation, inflammation associated with tissue maintenance, adaptive and innate immunity and aging, among other biological processes crucial for sustaining physiologic function (15) (Fig. 2). ROS have high reactivity and so play an essential function in a cell's redox balance. Increased amounts of ROS, on the other hand, can cause oxidative stress, resulting in damage to particular biomolecules like lipids, nucleic acids, and proteins and eventually death [33]. Apart from inducing cancer, ROS is also held responsible for the inhibition of cancer. This occurs due to extremely high levels of ROS accumulation above a cytotoxic threshold, which triggers the apoptotic pathways, ultimately leading to cancer cell senescence.Fig. 2 Increased ROS causes NF-κB transcription to be upregulated, resulting in increased tissue mass. As a result, tissues become hypoxic, triggering angiogenesis and the release of VEGF. However, excessive levels of VEGF lead to T-cell activation and tumor development [9, 13, 15]
As reported, overexpression of ROS causes normal cells to turn into cancerous cells, which activates oncogenes to promote tumorigenesis. ROS oxidizes various entities of the biomolecules, in this case, the bases of the nucleotide. This leads to the formation of various kinds of oxidation products which facilitate damage of the biomolecules via mutation and bond breaking. The ROS oxidizes guanine to form 7,8-dihydro-8-oxo-2-deoxyguanosine, causing G to mispair with T instead of C, while deoxyguanosine triphosphate is also oxidized to form 8-oxo-deoxyguanosine as a substrate, which causes A to mispair with C instead of T. When ROS oxidizes with adenine, there are two possible substrates: (i) 2-hydroxy-2-deoxyadenosine, which mispairs A with C, A with G, and A with T, and (ii) 7,8-dihydro-8-oxo-2-deoxyadenosine, which mispairs A with G, and A with C [34]. Exposure of purines and pyrimidines caused by hydrogen bond breakage, unfolding, double-, and single-strand breakage of DNA, facilitates ROS oxidation, thus resulting in DNA mutation and mispairing. Another way through which ROS damages DNA is by directly attacking and repressing the DNA repair system. This occurs when ROS attacks human 8-Oxoguanine DNA N-Glycosylase 1 (hOGG1) by oxidizing it. The hOGG1 is responsible for the elimination of 8-oxo-guanosine. So, in this case, the oxidation of hOGG1 makes 8-oxo-guanosine sticks around, which makes the turnover of epithelial cells faster. Colorectal carcinogenesis follows the very same mechanism [35].
T-cell death is induced due to high levels of ROS. This causes repression of T-cell differentiation, maturation, and activation. When ROS is increased, NF-κB is upregulated, causing T-cell development, maturation, and proliferation, resulting in more tissue mass. These new regions are in hypoxia conditions. This triggers HIF-1α induction to stimulate the release of vascular endothelial growth factor, hence resulting in angiogenesis [36]. When VEGF is overproduced, it blocks and represses T-cell development and migration, in turn causing immunodeficiency. An increase in the ROS downregulates the CD3 expression, thereby inactivating T-cells by suppressing immune responses. The immunosuppressive cells present in the tumor regions over express ROS to inhibit T-cell activation, thus promoting tumor metastasis. The myeloid-derived suppressor cells in the tumor region increase the count of CD8 + and CD4 + as a response to the defense mechanism of the above. This is again taken care of by ROS by releasing an apoptosis-inducing factor, ultimately leading to T-cell death.
Increased levels of ROS downregulate NK cell function by repressing CD16ζ expression, thereby abating the cytotoxicity of NK cells. The mechanism is similar, but with a slight difference, in various forms of carcinomas. In breast cancer, high amounts of ROS reduce the release of cytotoxic factors by NK cells by downregulating the expression of NK group 2 and its ligands, hence promoting cancer cell growth and metastasis. NK cells facilitate the elimination of malignant cells [37]. In melanoma, ROS spike causes decrease in the production of IFN-γ in the NK cells, which results in melanoma metastasis. ROS elevation also induces apoptosis leading to the death of NK cells. In chronic myelomonocytic leukemia, the cells themselves release ROS, which causes the death of NK cells, leading to the metastasis of chronic myelomonocytic leukemia. Apoptosis of NK cells in the liver occurs due to the high production of ROS in the mitochondria. This results in tumor growth leading to colorectal carcinoma.
Higher levels of ROS cause an increase in the production of NF-κB. This downregulates E-cadherins causing dissociation of the cell–cell junctions. This initiates endothelial–mesenchymal transition (EMT), which facilitates cancer cell invasion and metastasis (Fig. 3). Apart from NF-κB, ROS can also interact with TGF-β, PI3K/Akt, NRF2, HIF-1α signaling pathways to cause cell–cell disruption resulting in EMT [10].Fig. 3 Epithelial–mesenchymal transition (EMT) in cancer metastasis: Down-regulation of E-cadherin results in loss of adherence. This results in a loss of apical-basal polarity and mesenchymal transition; thus, motility is increased and cancer metastasis is facilitated [18, 20, 22]
ROS inhibits the proliferation signaling pathway. An increase in the ROS production downregulates epithelial growth factor and its expression. This inhibits the phosphorylation of extracellular signal-regulated kinase, which leads to the decreased production of EGF and EGFR, ultimately inhibiting cancer cell growth. Ascorbic acid (sourced from vitamin C) and koumine are known to promote ROS production. They are also known to inhibit ERK phosphorylation, suppressing cancer cell carcinoma [38, 39]. Non-small cell lung cancer cells proliferation is inhibited when ROS blocks the PI3K/Akt/NF-κB signaling pathway [10, 40]. ROS buildup downregulates the production of cyclins and cyclin-dependent kinases and stops cancer cell proliferation, since CDKs and cyclins are responsible for the promotion of mitotic cell cycle of somatic cells. In multiple myeloma, ROS downregulates JK1 and JK2 to block cyclin D, B1, E, CDK2, and CDK4 to stop the cancer cell cycle and growth [9, 18]. If ROS is overexpressed in human non-small cancer cells, CDK1 is phosphorylated and cyclin B1 and CDK1 expression is suppressed. This causes arresting of G2/M phase in cell cycle [41]. Researchers found that Physalin A (PA) inhibits G2/M cell cycle progression in A549 cells by causing ROS to accumulate excessively in their cells. This effect was attributed to Physalin A's inhibition of the p38 MAPK/ROS pathway [25].
ROS induces tumor cell apoptosis. ROS promotes the release of Ca2 + ions from the lumen of the endoplasmic reticulum, which causes defects such as protein misfolding and/or unfolding. Overproduction of ROS causes phosphorylation of eIF2α. This activates transcription factor IV, inducing C/EBP homologous protein which leads to apoptosis. High levels of ROS accumulation cause it to oxidize cardiolipin (phospholipid), which causes cytochrome c (Cyt c) to detach from the outer surface of the mitochondrial membrane. The freely suspended Cyt c will now interact with the apoptotic protease activating factor 1 and forms an apoptosome. This in turn activates caspase-3 and caspase-9 to initiate apoptosis. In gastric cancer cells, α-heredin is known to trigger overproduction of ROS. In the A549 cell line, Atractylodin (ATR) which is known for its antitumor activities-induced apoptosis by upregulating ROS production by regulating STAT, MAPK, and NF-κB pathways and inhibits the G2/M phase of the cell cycle by mediating the AKT signaling pathway [42].
ROS enhances the transcription effects of P53 and then translocate it to the mitochondria. ROS accumulation can also damage cancer cell DNA leading to apoptosis. Mutations of P53 cause cancer. ROS accumulation can reverse and restore the normal functions of the mutated P53 in cancer cells. Occurrence of lung cancer is associated with various kinds of cell death, one of which is ferroptosis [43]. In ferroptosis, cell death occurs with the help of iron where the ROS is of lipid type. Ferroptosis significantly targets only cancerous cells due to its iron dependency. High amounts of ROS are accumulated due to faulty metabolism of iron along with the lack of natural antioxidants in the cells. This leads to lipid peroxidation followed by ferroptosis [44]. In a recent study, it was discovered that hemin promotes the growth of noncancerous lung cells while increasing the production of reactive oxygen species (ROS) that cause lipid peroxidation and ferroptosis in lung cancer cells [45].
ROS balance and homeostasis in cancer cells
Cancer cells have developed a reliable ROS detoxification system. As a result, cancer cells' reliance on antioxidant systems provides a unique vulnerability which must be targeted to cause targeted cell death. This is achieved by elevating oxidative stress level above the toxicity threshold, sparing the normal cells, which are distinguished by lower intracellular ROS levels. ROS serve as both 'good' and 'bad' molecules, regulating cellular physiology or causing cytotoxicity, relying on the duration, quantity, and location of their formation. The methods of ROS detoxification can be directly supported by malignant cells [46]. High doses of vitamin C (antioxidant) cause colon cancer cell death by increasing ROS levels [39]. Lung cancer progresses swifter when antioxidants like N-acetylcysteine are consumed and increasing Nrf2 gene expression causes accelerated lung tumor growth [47]. The methods of ROS detoxification can be directly supported by malignant cells.
In glycolysis, the pro-glycolytic shift caused by the activation of oncogenes and the loss of tumor suppressors gives tumors a selective advantage by giving them the building blocks they need to make the macromolecules that keep them growing and spreading. Since glycolytic intermediates can be transported into the metabolic pathways that directly or indirectly produce reducing equivalents, primarily PPP-derived NADPH or glutaminolysis-derived GSH, glucose metabolism is crucial in the regulation of redox homeostasis in malignancies. In order to reduce the load of ROS and avoid cell death by hydroperoxide, cancer cells enhance their glucose metabolism. By lowering ATP at intracellular levels and inhibiting the lactate dehydrogenase-A by the small drug FX11 prevents the growth of cancer cells.
In cancer cells, activation of pentose phosphate pathway constitutes a major feature, as this pathway synthesizes nucleotides, which is required during cell reproduction. PPP-dependent production of NADPH is enhanced by the regulation of glucose-6-phosphate dehydrogenase (G6PD). The availability of glucose may influence G6PD regulation: glucose funneling into the oxidative branch of PPP directly regulates the redox balance of human renal cell carcinoma cells (Fig. 4). The serine–glycine one-carbon metabolism (SGOC) is a network of biochemical reactions in which amino acids and their derivatives are converted into multiple outputs as carbon units that serve various cellular functions. These carbon units from glycine and serine depend on three different pathways: the folate cycle, the methionine cycle, and the trans-sulfuration pathway [20]. Recent evidence indicates that this pathway also plays a crucial role for redox balance [48].Fig. 4 ROS Balance and Homeostasis. Metabolic pathways such as PPP, glycolysis, and serine-glycine one carbon involved in ROS balance and homeostasis in cancer cells [27, 48]
ROS-mediated cancer therapy
Roles of ROS in cancer chemotherapy
To treat cancer patients in a clinical context, chemotherapy has been widely employed. A majority of chemotherapy drugs generate ROS, and several of them can change the redox balance in cancer cells [12]. The main medications that enhance ROS in cancer cells are alkylating agents, camptothecins (irinotecan and topotecan), anthracyclines (daunorubicin, epirubicin, and doxorubicin), and platinum coordination complexes (cisplatin, oxaliplatin, and carboplatin) [49]. The two main causes of the increase in ROS in response to chemotherapeutic drugs are the production of ROS by mitochondria and the suppression of the cellular antioxidant system. For instance, cisplatin, one of the most popular and successful chemotherapy drugs for treating lung cancer, causes mitochondria-dependent ROS that cause nuclear DNA damage and ultimately lead to cell death. Because of the direct impact of cisplatin on mitochondrial DNA, there is an increase in ROS production that impairs the production of proteins for the electron transport chain.
ROS are crucial in the development of multidrug resistance. One of the main causes of chemotherapy's failure in the treatment of cancer is such resistance [50]. The plasma has P-glycoprotein (P-gp) and other transporter-based efflux pumps and these pumps are closely linked to drug resistance [15]. P-gp, a member of the large ATP-binding cassette protein family, is encoded by the MDR1/ABCB1 gene. P-gp plays a defensive role for the uptake of chemotherapeutic drugs [51]. NRF2 is turned on and overexpressed in cancer cells as a defense against too much ROS, as was previously mentioned. A NRF2 target gene called MDR1/ABCB1 is involved in the upregulation of P-gp and drug resistance in cancer cells [52]. In conclusion, elevated production of ROS in response to therapy is essential for destroying the cancer cells and this also plays an important role in drug resistance.
ROS-mediated programmed cell deaths pathways
As previously mentioned, cancer cells have higher ROS levels compared to non-malignant cells. Therefore, antioxidant enzyme activity increases in malignant cells to negate the detrimental effects of excess ROS production. Indeed, the disruption of this delicate balance has been of interest as potential anticancer interventions because either increasing ROS generation and/or decreasing antioxidant activity may result in activating of cell death pathways. Some of the key cell death pathways induced through the manipulation of ROS levels will be discussed below. Table 1 explains the anticancer compounds/drugs widely used for eliminating the cancer cell via modulating ROS generation.Table 1 Various compounds exhibiting anticancer potential through ROS-mediated programmed cell death pathways
Cell death pathway induced Stimulus ROS type Model system References
Apoptosis 3,3′-OH curcumin H2O2 HepG2 [67]
Apoptosis 6-gingerol ROS U937 & K562 [68]
Apoptosis Arctigenin H2O2 & O2· − MDA-MB-231 [69]
Apoptosis Arsenic trioxide O2· − HPF [70]
Apoptosis Artesunate ROS TE671 & RD18 [5]
Apoptosis Butein ROS HeLa
Apoptosis H2O2 & O2· − HepG2 & Hep3B [71]
Apoptosis Cannabidiol ROS Molt-4 &Jurkat [72]
Apoptosis Capsaicin H2O2 NB4 & Kasumi-1 [73]
Apoptosis ROS HepG2
Apoptosis H2O2 & O2· − BxPC-3 & AsPC-1
Apoptosis ROS Jurkat
Apoptosis Carnosic acid ROS IMR-32 [74]
Apoptosis ROS Caski
Apoptosis ROS HCT116
Apoptosis Carnosol ROS HCT116 [75]
Apoptosis CAY10598 ROS HCT116 [76]
Apoptosis Celastrol ROS B16 [77]
Apoptosis Cepharanthine ROS H1299 & A549 [1]
Apoptosis Curcumin H2O2 & O2· − HuT-78 [8]
Apoptosis Curcumin O2· − HCT-116
Apoptosis Curcumin ROS L929
Apoptosis FTY720 ROS Jeko& Mino [4]
Apoptosis Gambogic acid ROS MDA-MB-231 [78]
Apoptosis Glucocorticoid H2O2 WEHI7.2
Apoptosis Gossypol ROS COLO205 [79]
Apoptosis Isoliensinine ROS MDA-MB-231 [80]
Apoptosis LZ-106 O2· − H460 & A549 [81]
Apoptosis Methylglyoxal O2· − Jurkat [82]
Apoptosis Nimbolide H2O2 MG63 [83]
Apoptosis Patulin O2· − HCT116 & HEK293 [28]
Apoptosis Piperlongumine H2O2 EJ & U2OS [84]
Apoptosis Plumbagin H2O2 & O2· − A375.S2 [85]
Apoptosis Plumbagin ROS EL4
Apoptosis Resveratrol ROS SGC7901 [86]
Apoptosis ROS SUDHL4 & HBL-1
Apoptosis O2· − U937
Apoptosis Rotenone H2O2 PC12 [87]
Apoptosis Salinomycin ROS PC3 [88]
Apoptosis Salvicine H2O2 HeLa
Apoptosis Sanguinarine H2O2 Jurkat& Molt-4
Apoptosis Shikonin O2· − HL60 [89]
Apoptosis Sodium selenite ROS HepG2 [16]
Apoptosis Sodium selenite ROS HCT116 & SW480
Apoptosis TRAIL O2· − Jurkat
Apoptosis Thymoquinone ROS MCF-7 [90]
Apoptosis H2O2 & O2· − BC1
Apoptosis Wogonin H2O2 Jurkat
Apoptosis H2O2 HepG2 [91]
Apoptosis Zebularine O2· − Calu-6 [3]
Apoptosis Zerumbone ROS K562 [92]
Autophagy/Apoptosis Calyxin Y H2O2 NCI-H460 [2]
Apoptosis/Autophagy Cannabidiol ROS MDA-MB-231 [93]
Autophagy/Apoptosis Carnosol ROS MDA-MB-231 [94]
Apoptosis/Autophagy Celastrol ROS HOS & MG-63 [95]
Apoptosis/Autophagy Colistin ROS N2a [96]
Autophagy/Apoptosis Compound K ROS HCT-116 [97]
Apoptosis/Autophagy FTY720 ROS U266 [98]
Apoptosis/Autophagy Gambogic acid ROS T24 [99]
Apoptosis/Autophagy Isoorientin ROS HepG2 [100]
Autophagy/Apoptosis KIOM-C ROS HT1080 [101]
Apoptosis/Autophagy MomordinIc H2O2 HepG2 [102]
Apoptosis/Autophagy Plumbagin ROS PC-3 & DU145 [103]
Apoptosis/Autophagy Resveratrol ROS OVCAR-3 & Caov-3
Apoptosis/Autophagy Sanguinarine H2O2 U87MG & U118MG
Apoptosis/Autophagy Sodium selenite ROS A549 [17]
Autophagy 2-methoxyestradiol O2· − U87MG & HEK293 [60]
Autophagy Bufalin ROS HT-29 & Caco-2 [104]
Autophagy Ciclopirox ROS Rh30 & RD [105]
Autophagy Cucurbitacin B O2· − HeLa [106]
Autophagy ROS MCF-7
Autophagy Curcumin ROS
Autophagy Dichloroacetate ROS HT29 & HCT116 [107]
Autophagy Dihydroartemisinin ROS BxPC-3 & PANC-1
Autophagy Rotenone O2· − U87MG & HEK293
Autophagy Salinomycin H2O2 SW620 & RKO [108]
Autophagy Sodium selenite O2· − U87MG & T98G [109]
Autophagy Ursolic acid ROS U87MG [110]
Apoptosis/Necrosis Auranofin O2· − HeLa
Necrosis Salinomycin ROS U251MG [111]
Necrosis Sodium selenite H2O2 & O2· − Jurkat& J774.2
Necroptosis Dimethylfumarate ROS CT26
Necroptosis Lycorine ROS ARH-77
ROS and apoptosis
The most common and well characterized form of cell death is apoptosis, which is also known as type I programmed cell death. Caspases, a distinct family of aspartate-directed cysteine-dependent proteases, are responsible for both starting and finishing this process (Fig. 2). There are two major pathways for apoptosis, the extrinsic (death receptor-dependent) and the intrinsic (mitochondrial) mechanisms and ROS have been found to play a major role in both mechanisms [13].
Through the binding of death-inducing ligands like tumor necrosis factor-related apoptosis-inducing ligand (TRAIL-R1/2), Fas (FasL) and tumor necrosis factor receptor 1 to their corresponding receptors like TNF (TNFR), Fas (FasR) and death receptors (DR4 and DR5), ROS has been shown to initiate the extrinsic pathway of apoptosis. Adaptor proteins such as procaspases 8 and 10 and Fas-associated protein with death domain (FADD) are recruited to the cytoplasmic surface to form death-inducing signaling complexes when transmembrane death receptors are activated (DISCs). Following, caspases 8 and 10 are activated and this causes apoptosis by directly activating effector caspases [53] Cellular FLICE-inhibitory protein (c-FLIP) is one of the proteins that helps ROS initiates the extrinsic apoptosis. Pro-caspases and this protein compete with each other to attach to the adaptor protein, which prevents the creation of DISCs and induces apoptosis as a result. It has been demonstrated that ROS adversely control c-FLIP through two different ways, (i) the nitric oxide is negatively regulated by oxygen (O2), which stops S-nitrosation and subsequently enables ubiquitin-proteasomal destruction of c-FLIP [54], (ii) ROS sets c-FLIP up for ubiquitination and phosphorylation and this leads to the destruction of subsequent proteasomes.
The intrinsic pathway of apoptosis is also referred to as the mitochondrial pathway. Indeed, the [54] mitochondria are a major source of ROS generation and mitochondria contribute a major function in initiating apoptosis. Due to this, mitochondria also often considered as a target of ROS. During apoptosis, the mitochondrial membrane becomes more permeable and release pro-apoptotic factors through the mitochondrial permeability transition pore (MPTP). Apoptosis-inducing factor (AIF), second mitochondria-derived activator of caspase/direct inhibitor of apoptosis-binding protein with low pI (Smac/DIABLO), and cytochrome c (Cyt-c) are few of the substances released from the cytoplasm [9]. When cytochrome-c enters the cytosol, it forms a complex with apoptotic protease activating factor 1 (APAF1), which creates an apoptosome and activates caspase-9 [55]. A crucial component of intrinsic pathway, caspase-9 triggers the caspases 3, 6, and 7, which causes the breakdown of cellular proteins and induces apoptosis [56]. Additionally, in the mitochondria, Cardiolipin and Cyt-c form a combination that prevents Cardiolipin from being released into the cytosol. H2O2 inhibits this complex by oxidizing cardiolipin, which lowers its affinity for Cyt-c and permits its release into the cytosol [57]. Also, the ratio of pro-apoptotic Bcl-2 proteins (such as Bax, Bid, and Bad) to anti-apoptotic Bcl-2 proteins (such as Bcl-2 itself, Mcl-1 and Bcl-xL) controls intrinsic apoptosis [55]. (Fig. 5) Once again, ROS controls this equilibrium by directly oxidizing Bcl-2 at Cys229 and Cys158 by H2O2, which eliminates its anti-apoptotic activity, decreases the Bax and Bad ubiquitination and increases the Bcl-2 ubiquitination by O2 [12, 24].Fig. 5 An overview of apoptosis: The mitochondrial-mediated apoptosis can be permeability transition pore dependent or permeability transition pore independent [1, 56]
ROS and autophagy
Autophagy, also referred to as type II programmed cell death, is a process of self‐digestion which occurs in the lysosome and aims to recycle cytoplasmic components and damaged organelles when cells are exposed to stress [58]. In cancer cells, more recent literature has found that autophagy acts in a context-dependent manner and may function in tumor promotion and suppression [59]. Autophagy's redox regulation is, in reality, influenced by a number of variables, including the expression of ROS, time frame, and cell type. For instance, ROS affects cancer cells but does not cause autophagic cell death in untransformed cells [60]. Both the induction of autophagy by ROS generation and the decrease of ROS by autophagy show the close relationship between ROS and autophagy [61]. A key negative regulator of autophagy is mammalian target of rapamycin (mTOR), a serine/threonine kinase, and H2O2 inhibits mTOR activity resulting in autophagy [6, 62]. Autophagy is a multi-step process and is strategically controlled by autophagy-related genes (ATGs). ROS upregulates the expression of beclin-1 an important component for initiation of autophagy. Furthermore, nutrient starvation-induced H2O2 oxidizes ATG4 which promotes lipidation of LC-3 and increasing autophagosomes formation [63].
ROS and necroptosis
Necrosis was once thought to be an uncontrolled kind of cell death, but studies now suggest that there is another form of necrosis that is available and is controlled by a protein-mediated platform. This alternative form of necrosis is known as necroptosis. Necroptosis is started by death-inducing receptors like FasR and TNFR, once they have been stimulated by their corresponding ligands, just like the extrinsic apoptotic pathway. There are two critical regulators involved in necroptosis execution such as receptor-interacting protein kinases RIP1 and RIP3 [64]. In fact, RIP3 enhances the mitochondrial catalytic activity and increases the amount of ROS production in the mitochondria, interacting directly with metabolic enzymes [14, 65]. Furthermore, RIP3 phosphorylates PGAM5, which is a subunit of mitochondrial protein phosphatase. This role results in the activation and de-phosphorylation of the dynamin-related protein 1 (Drp1), which fragments the mitochondria, increases ROS production, and induces necroptosis as a result [66].
Future perspectives
The levels of reactive oxygen species (ROS) within cells are the target of many different chemotherapeutic approaches. The non-steroidal and anti-inflammatory drug sulindac is undergoing clinical trials for the treatment of tumors at the moment. It causes lung cancer cells to undergo induced apoptosis by increasing intracellular ROS. The propensity of mtDNA to mutate as a consequence of being subjected to reactive oxygen species (ROS) is something that could potentially be utilized in the treatment of various cancer treatments. Reactive oxygen species (ROS)-based nanoparticles such as gold nanoparticles and cerium-based nanoparticles induce cancer cell death by increasing the intracellular ROS.
Using 2-deoxyglucose as a glucose analog increases oxidative stress in the cell. This leads to cancer cell death due to the inhibition of glucose metabolism as cancerous cells are more vulnerable to glucose toxicity than non-cancerous cells. One way to activate ROS-based nanoparticles is through photodynamic therapy [44], also known as PDT. In this case, light energy is used to increase ROS activity inside the cell. With its photostability and low toxicity to non-cancerous cells, graphene has recently been used in PDT for cancer treatment purposes. Thus, activating intracellular ROS by suitable targeted therapy in cancer cells holds a great potential in anticancer treatment strategies.
Acknowledgements
The authors are grateful to the SRM Institute of Science and Technology for providing support for this work. KK is supported by the SRM IST scholarship.
Funding
The authors have not disclosed any funding.
Declarations
Conflict of interest
The authors declare that there are no conflicts of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
K. N. ArulJothi and K. Kumaran have contributed equally to this work.
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| 36472716 | PMC9734980 | NO-CC CODE | 2022-12-14 23:28:32 | no | Med Oncol. 2023 Dec 6; 40(1):43 | utf-8 | Med Oncol | 2,022 | 10.1007/s12032-022-01900-y | oa_other |
==== Front
World J Pediatr
World J Pediatr
World Journal of Pediatrics
1708-8569
1867-0687
Springer Nature Singapore Singapore
36484872
664
10.1007/s12519-022-00664-9
Original Article
Effects of synbiotic supplementation on anthropometric indices and body composition in overweight or obese children and adolescents: a randomized, double-blind, placebo-controlled clinical trial
Atazadegan Mohammad Amin 1
Heidari-Beni Motahar [email protected]
2
Entezari Mohammad Hassan 3
Sharifianjazi Fariborz 4
Kelishadi Roya 5
1 grid.411036.1 0000 0001 1498 685X Department of Clinical Nutrition, School of Nutrition and Food Sciences, Isfahan University of Medical Sciences, Isfahan, Iran
2 grid.411036.1 0000 0001 1498 685X Department of Nutrition, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
3 grid.411036.1 0000 0001 1498 685X Department of Clinical Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran
4 grid.264978.6 0000 0000 9564 9822 School of Science and Technology, The University of Georgia, Tbilisi, Georgia
5 grid.411036.1 0000 0001 1498 685X Department of Pediatrics, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
9 12 2022
110
14 5 2022
17 11 2022
© Children's Hospital, Zhejiang University School of Medicine 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Background
Recently, beneficial effects of probiotics and/or prebiotics on cardio-metabolic risk factors in adults have been shown. However, existing evidence has not been fully established for pediatric age groups. This study aimed to assess the effect of synbiotic on anthropometric indices and body composition in overweight or obese children and adolescents.
Methods
This randomized double-blind, placebo-controlled trial was conducted among 60 participants aged 8–18 years with a body mass index (BMI) equal to or higher than the 85th percentile. Participants were randomly divided into two groups that received either a synbiotic capsule containing 6 × 109 colony forming units (CFU) Lactobacillus coagulans SC-208, 6 × 109 CFU Lactobacillus indicus HU36 and fructooligosaccharide as a prebiotic (n = 30) or a placebo (n = 30) twice a day for eight weeks. Anthropometric indices and body composition were measured at baseline and after the intervention.
Results
The mean (standard deviation, SD) age was 11.07 (2.00) years and 11.23 (2.37) years for the placebo and synbiotic groups, respectively (P = 0.770). The waist-height ratio (WHtR) decreased significantly at the end of the intervention in comparison with baseline in the synbiotic group (0.54 ± 0.05 vs. 0.55 ± 0.05, P = 0.05). No significant changes were demonstrated in other anthropometric indices or body composition between groups.
Conclusions
Synbiotic supplementation might be associated with a reduction in WHtR. There were no significant changes in other anthropometric indices or body composition.
Keywords
Anthropometry
Body composition
Pediatrics
Synbiotics
http://dx.doi.org/10.13039/501100003970 Isfahan University of Medical Sciences 298113 Heidari-Beni Motahar
==== Body
pmcBackground
Childhood obesity is a global health concern. It is estimated that the prevalence of overweight in preschool children will increase to 11% worldwide by 2025 [1]. Pediatric obesity is associated with cardiovascular and metabolic diseases [2]. It increases the risk of adult-onset obesity. Obesity or overweight can reduce life expectancy or quality of life [3]. Treatment of obesity is more challenging than its prevention [4].
Several factors, including genetic susceptibility and environmental factors, are associated with obesity. Some modifiable factors, such as lifestyle and diet, are important for national prevention policies. The gut microbiota is a new point of interest that plays a role in the pathophysiology of obesity. It is associated with body weight control, energy homoeostasis, host energy storage and inflammation [5]. Some lifestyle factors, including lack of exercise, smoking habits and stress, can alter gut microbiota composition. Dietary habits and the composition of nutrients have been suggested as the main geographical factors associated with gut microbiota composition. Some nutrients and bioactive compounds, including probiotics (including yogurts) and prebiotics (fibers and polyphenols), influence the microbiome. Unhealthy dietary patterns, such as Western diets, have been associated with the development of obesity and induce gut dysbiosis [6]. The amount and type of energy source can impact the composition of gut microbiota [7, 8]. Studies have shown reduced levels of Clostridium perfringens and Bacteroidetes in obese subjects compared to lean subjects. Bacteroides thetaiotamicron in association with Methanobrevibacter smithii increases adipose tissue accumulation. An imbalanced Firmicutes/Bacteroidetes ratio, associated with an increase in the Actinobacteria phylum and a decrease in Verrucomicrobia in obesity, was confirmed [9]. The findings suggested a dose-dependent association between certain species of bacteria and obesity. In particular, there is a clear relationship between the number of Lactobacillus reuteri cells and obesity. Excess weight is associated with a higher number of L. reuteri [10].
Human and animal studies have shown that the composition of gut microbiota varies in obese and lean subjects. The major types of bacteria in the body are Firmicutes and Bacteroidetes. Firmicutes is more abundant than Bacteroidetes in obese people [7]. Thus, decreasing Firmicutes and increasing Bacteroidetes will be helpful for obese people.
Nutritional interventions such as probiotics, prebiotics and synbiotics (a mixture of probiotics and prebiotics) can improve the gut microbiota [11]. Synbiotics have the simultaneous properties of probiotics and prebiotics and may influence the survival of probiotics in the gastrointestinal tract [12]. Therefore, a suitable combination of both probiotics and prebiotics in a single product might have a better impact on host health in comparison with the separate activity of probiotics or prebiotics [13]. However, some studies did not show any significant effects of synbiotics on weight and body mass index (BMI) [14, 15].
Different strains of the probiotic family have shown various impacts on cardio-metabolic risk factors, including obesity [16]. A combination of several strains is likely to be more effective than one strain. The present study aimed to determine the potential effects of synbiotic supplementation on anthropometric indices and body composition in overweight or obese children and adolescents.
Methods
Study design
This project was a randomized double-blind placebo-controlled study. It was conducted on 60 overweight or obese children aged between 8 and 18 years with a body mass index (BMI) equal to or higher than the age- and sex-specific 85th percentile according to the World Health Organization percentiles [17]. Use of antibiotics during the previous three months, having any chronic disease, including diabetes, thyroid disorders, cardiovascular diseases, digestive problems, pancreatic and liver diseases, and non-compliance with the intervention regularly were exclusion criteria. Individuals’ compliance with the intervention was assessed by counting the number of capsules remaining in each package (compliance = consuming at least 90% of the capsules delivered during the study) and by weekly phone interview. Additionally, those with a daily diet above 4200 Kcal and below 800 Kcal were excluded from the study [18]. Participants were randomly allocated into two groups, synbiotic and placebo. Participants were randomly assigned based on the permutated block randomization method. The random allocation was carried out using a table of random numbers.
The sample size in the current study was determined using a formula for a parallel design randomized controlled trial in which type I and II error rates were considered 5 and 20% (statistical power of 80%), respectively, and the minimum detectable standardized effect size was considered 0.75 [19]. We considered a 33% additional sample size to cover the potential dropout rates. Finally, 40 individuals were included in each group.
Ethical considerations
The study protocol was in accordance with the Declaration of Helsinki and was approved by the research and ethics committee of Isfahan University of Medical Sciences. The trial was registered, and the number of registrations is IRCT20170501033747N2. A written informed consent form was obtained from parents, and oral assent was obtained from their children after the aims and procedures were explained.
Supplement administration
The synbiotic group received two daily capsules containing 12 × 109 colony forming units (CFU) of probiotics (6 × 109 CFU: Lactobacillus coagulans SC-208, 6 × 109 CFU Lactobacillus indicus HU36). The prebiotic was short-chain fructooligosaccharide (FOS), and each capsule included 38.5 g FOS (7.7% of each capsule).
Those in the placebo group received two 0.5 g capsules containing maltodextrin. Participants consumed two capsules daily with enough water before lunch and dinner. Synbiotic supplements and the placebo were provided by Shiraz Mehregan Campus Growth Bio products Company, Shiraz, Iran. The manufacturer assigned synbiotic supplement and placebo into A and B codes and packed them in the same boxes in terms of color, shape and size.
They were also advised to store the supplements in a refrigerator to preserve the bacterial load. Additionally, they refrain from consuming fermented products and foods containing probiotics.
Dietary and physical activity assessment
Dietary intake was evaluated by three-day dietary records at the beginning and the end of the study. Dietary data were analyzed by Nutritionist IV software (First Databank, San Bruno, CA, USA). Data entry was performed by a trained dietitian.
Physical activity was assessed by International Physical Activity Questionnaires (IPAQ) [20]. The questions ask about the time of physical activity during the last seven days. Intensity of activity (i.e., vigorous or moderate) and sedentary behaviors such as watching TV were questioned.
Additionally, participants were advised not to change their usual diet and physical activity during the study period.
Anthropometric measurement assessments
Height was measured by a trained nutritionist to the nearest 0.1 cm with a portable stadiometer (SECA, Hamburg, Germany) without shoes. Weight was measured to the nearest 0.1 kg with a balanced portable digital weight scale (SECA, Hamburg, Germany) with light indoor clothing and no shoes. Body mass index (BMI) was calculated as weight (kg)/height2 (m). Waist circumference (WC) was measured over the unclothed abdomen at the narrowest point between the rib cage and the superior border of the iliac crest using a nonelastic flexible tape to the nearest 0.1 cm.
Hip circumference (HC) was measured at the widest part of the hip at the level of the greater trochanter to the nearest 0.1 cm. Wrist circumference (WrC) was measured to the nearest 0.1 cm on the dominant arm using a tape meter. Neck circumference (NC) was measured with the most prominent portion of the thyroid cartilage taken as a landmark to the nearest 0.1 cm. The waist-height ratio (WHtR), waist-hip ratio (WHR), abdominal volume index (AVI), conicity index (CI), and a body shape index (ABSI) were calculated using the following formulas:WHR:WCcm/HCcm
WHtR:WCcm/heightcm
AVI:2×WC2cm2+0.7×WCcm-HCcm2/1000
CI:WCm/0.109×WeightkgHeightm
ABSI:Waistcircumference(cm)BMI2/3×height12(m)
Body composition analysis
Bioelectrical impedance analysis was performed using an InBody 720 Body Composition Analyzer (BioSpace Co., Ltd., Seoul, Korea). Sex, age, and height were entered directly into the instrument prior to the impedance measurement. Bare feet were placed on the metal plates of the scale, and the participant firmly grasped the hand grips while placing the thumb and fingers in the standard location as indicated in the operation manual. The InBody uses eight points of tactile electrodes (contact at the hands and feet), and it detects the amount of segmental body water. The technique uses multiple frequencies to measure intracellular and extracellular water separately. Thirty impedances are measured in five parts (right arm, left arm, right leg, left leg and trunk) using six frequency bands (1, 5, 50, 250, 500 and 1000 kHz). Frequencies below 50 kHz measure extracellular water, whereas frequencies above 50 kHz measure total body water. The impedances obtained at each frequency are combined to measure intracellular water and extracellular water. After calculating the body water content by the impedance method, the protein mass (muscle) and the mineral mass (bone) are derived from the body water, and the body fat mass is obtained by subtracting these three components from the body weight. It also calculates skeletal muscle mass.
Statistical analysis
Descriptive data were expressed as the mean ± standard deviation (SD) for quantitative variables and number (percentage) for qualitative variables. After assessment of the normal distribution by the Kolmogorov–Smirnov test, within-group changes were compared by the paired t test. For comparison of data between the two groups, we used an independent t test for data with a normal distribution. The interaction effect of gender and intervention was assessed by analysis of covariance adjusted for baseline values. A P value of less than 0.05 was considered statistically significant. We used SPSS for Windows software (version 20; SPSS, Chicago, IL) for statistical analysis.
Results
Among 80 subjects, 7 subjects in the placebo group and 13 in the synbiotic group dropped out. Twelve participants had to take antibiotics due to viral diseases. Five participants did not want to continue taking the drug for personal reasons, and digestive problems occurred in three participants. A total of 60 subjects (32 girls and 28 boys) completed the study and were included in the final analysis (Fig. 1). The mean (SD) age was 11.07 (2.00) years and 11.23 (2.37) years for the placebo and synbiotic groups, respectively (P = 0.770). Baseline characteristics at the beginning of the study did not differ significantly between the two groups (Table 1). Baseline carbohydrate intake was significantly different between the two groups. However, there were no significant differences in energy and other nutrient intake within and between groups (Table 2).Fig. 1 Study flow diagram
Table 1 Baseline characteristics of participants in the two groups
Variables Placebo (n = 30) Synbiotic (n = 30) P value
Age (y) 11.07 ± 2.00 11.23 ± 2.37 0.770
Gender (female) 19 (59.4) 13 (40.6) 0.121
Height (m) 1.46 ± 0.12 1.48 ± 0.14 0.522
Weight (kg) 54.77 ± 16.11 55.02 ± 15.37 0.950
BMI (kg/m2) 25.30 ± 4.23 24.70 ± 3.27 0.541
Sleep duration (h) 8.00 ± 0.62 7.85 ± 0.56 0.339
Screen time (h) 4.63 ± 0.93 4.51 ± 0.84 0.598
Physical activity (h) 1.65 ± 0.53 1.48 ± 0.66 0.286
Data are shown as mean ± standard deviation or number (percent). BMI body mass index
Table 2 Daily dietary intake of participants throughout the study
Variables Stage Placebo group (n = 30) Synbiotic group (n = 30) Pa
Energy (Kcal) Before 2166.46 ± 444.87 2001.24 ± 289.16 0.093
After 2125.25 ± 402.08 2018.50 ± 326.64 0.264
Change −41.21 ± 193.64 17.26 ± 189.93 0.243
Pb 0.253 0.622
Protein (g) Before 73.86 ± 18.17 68.89 ± 19.15 0.307
After 71.65 ± 13.34 66.62 ± 15.79 0.188
Change −2.21 ± 12.63 −2.26 ± 17.76 0.990
Pb 0.345 0.491
Carbohydrate (g) Before 330.72 ± 79.33 295.75 ± 46.11 0.041
After 319.76 ± 60.20 295.88 ± 52.87 0.108
Change −10.96 ± 48.34 0.13 ± 48.84 0.380
Pb 0.224 0.988
Total fat (g) Before 64.00 ± 15.99 63.13 ± 15.67 0.832
After 67.66 ± 20.94 66.15 ± 16.72 0.758
Change 3.66 ± 15.30 3.02 ± 16.00 0.874
Pb 0.200 0.310
Saturated fat (g) Before 16.98 ± 4.76 16.72 ± 5.08 0.837
After 18.47 ± 6.34 17.36 ± 6.33 0.504
Change 1.48 ± 6.19 0.65 ± 5.91 0.594
Pb 0.200 0.555
Mono unsaturated fat (g) Before 19.08 ± 7.34 22.33 ± 9.63 0.148
After 21.41 ± 9.68 22.55 ± 9.73 0.652
Change 2.33 ± 6.18 0.22 ± 6.23 0.193
Pb 0.050 0.845
Poly unsaturated fat (g) Before 20.85 ± 7.73 17.87 ± 9.43 0.186
After 21.28 ± 11.32 19.00 ± 9.64 0.403
Change 0.43 ± 8.14 1.13 ± 7.79 0.736
Pb 0.773 0.434
Cholesterol (mg) Before 223.27 ± 144.73 188.35 ± 121.23 0.315
After 192.17 ± 84.24 173.62 ± 140.87 0.538
Change −31.10 ± 175.48 −14.73 ± 154.99 0.703
Pb 0.340 0.607
Linoleic fat (g) Before 19.77 ± 7.55 16.74 ± 9.37 0.173
After 20.25 ± 11.12 17.85 ± 9.42 0.372
Change 0.48 ± 7.95 1.12 ± 7.88 0.756
Pb 0.744 0.443
Linolenic fat (g) Before 0.38 ± 0.34 0.39 ± 0.34 0.925
After 0.42 ± 0.56 0.43 ± 0.47 0.929
Change 0.04 ± 0.56 0.05 ± 0.37 0.976
Pb 0.691 0.516
Total fiber (g) Before 18.79 ± 6.90 15.96 ± 5.23 0.079
After 17.07 ± 4.61 15.62 ± 5.12 0.253
Change −1.72 ± 6.48 −0.34 ± 3.89 0.324
Pb 0.158 0.633
Data are presented as means ± standard deviations. aP value resulted from independent t test for difference between probiotic and placebo groups based on after intervention and mean changes. bP value resulted from paired t test for difference within groups throughout the study
There were no significant differences between anthropometric values in the placebo and synbiotic groups at baseline (P > 0.05, Table 3). The mean WHtR was significantly different before and after the intervention in the synbiotic group (P = 0.05). There were no significant differences between the mean changes in anthropometric indices between the two groups (P > 0.05, Table 3).Table 3 The effect of synbiotic on anthropometric measurements in comparison with placebo
Variables Placebo (n = 30) Synbiotic (n = 30) Pa
Weight (kg)
Before 54.77 ± 16.11 55.02 ± 15.37 0.950
After 54.89 ± 16.52 54.90 ± 15.15 0.998
Change 0.12 ± 2.15 −0.12 ± 1.87 0.644
Pb 0.763 0.723
Height (m)
Before 1.46 ± 0.12 1.48 ± 0.14 0.522
After 1.46 ± 0.12 1.48 ± 0.14 0.517
Change 0.0025 ± 0.004 0.002 ± 0.0051 0.784
Pb 0.2 0.6
BMI (kg/m2)
Before 25.30 ± 4.23 24.70 ± 3.27 0.541
After 25.24 ± 4.35 24.58 ± 3.33 0.509
Change −0.05 ± 0.78 −0.12 ± 0.75 0.747
Pb 0.717 0.400
Waist circumference (m)
Before 0.80 ± 0.10 0.80 ± 0.08 0.983
After 0.80 ± 0.10 0.80 ± 0.08 0.922
Change −0.0003 ± 0.02 −0.0022 ± 0.01 0.599
Pb 0.913 0.214
Waist-to-hip ratio
Before 0.87 ± 0.05 0.86 ± 0.06 0.693
After 0.87 ± 0.05 0.84 ± 0.15 0.333
Change 0.0002 ± 0.02 −0.02 ± 0.13 0.315
Pb 0.952 0.319
WHtR
Before 0.55 ± 0.06 0.55 ± 0.05 0.580
After 0.55 ± 0.06 0.54 ± 0.05 0.536
Change −0.0014 ± 0.01 −0.0024 ± 0.01 0.657
Pb 0.446 0.05
Hip circumference (m)
Before 0.93 ± 0.11 0.94 ± 0.09 0.811
After 0.93 ± 0.11 0.93 ± 0.09 0.850
Change −0.0007 ± 0.02 −0.0020 ± 0.01 0.722
Pb 0.827 0.363
Neck circumference (m)
Before 0.33 ± 0.03 0.33 ± 0.03 0.903
After 0.33 ± 0.02 0.45 ± 0.65 0.315
Change −0.0027 ± 0.01 0.12 ± 0.64 0.308
Pb 0.129 0.323
Wrist circumference (m)
Before 0.16 ± 0.01 0.16 ± 0.01 1.000
After 0.16 ± 0.01 0.16 ± 0.01 0.620
Change −0.0008 ± 0.0030 0.0007 ± 0.0022 0.3
Pb 0.134 0.103
ABSI
Before 0.08 ± 0.01 0.08 ± 0.01 0.676
After 0.08 ± 0.01 0.08 ± 0.01 0.681
Change −0.0000 ± 0.0010 −0.0000 ± 0.0011 0.963
Pb 0.985 0.935
AVI
Before 2330.61 ± 1842.48 2632.04 ± 2120.18 0.559
After 2331.86 ± 1913.49 2625.16 ± 2158.52 0.580
Change 1.25 ± 584.62 −6.87 ± 289.06 0.946
Pb 0.991 0.897
CI (g)
Before 45.20 ± 10.36 44.84 ± 8.62 0.885
After 45.21 ± 10.68 44.64 ± 8.56 0.822
Change 0.01 ± 1.70 −0.20 ± 1.17 0.586
Pb 0.985 0.356
AVI abdominal volume index, CI conicity index, ABSI a body shape index, BMI body mass index, WHtR waist-height ratio. aComparison between group. bComparison within group
Body composition was measured at baseline and at the end of the intervention. No significant differences were observed between the other anthropometric indices between the two groups. Body composition was assessed at baseline and after the intervention. However, there were no significant changes between and within groups (Table 4). Sex-stratified analysis revealed no significant changes in anthropometric indices or body composition after the intervention in either sex (Table 5).Table 4 The effect of synbiotic on body composition in comparison with placebo
Variables Placebo (n = 30) Synbiotic (n = 30) Pa
Body fat mass (kg)
Before 20.98 ± 8.69 21.30 ± 5.99 0.867
After 21.25 ± 9.03 21.31 ± 6.02 0.973
Change 0.27 ± 1.30 0.01 ± 1.43 0.469
Pb 0.264 0.960
Mineral content (kg)
Before 2.33 ± 0.78 2.45 ± 0.87 0.596
After 2.36 ± 0.79 2.44 ± 0.87 0.715
Change 0.03 ± 0.08 −0.01 ± 0.07 0.075
Pb 0.045 0.687
Protein content (kg)
Before 6.56 ± 2.15 6.81 ± 2.23 0.669
After 6.54 ± 2.12 6.75 ± 2.12 0.702
Change −0.02 ± 0.25 −0.06 ± 0.32 0.658
Pb 0.617 0.344
Skeletal muscle mass (kg)
Before 17.68 ± 6.44 18.50 ± 6.63 0.628
After 17.34 ± 6.96 18.35 ± 6.47 0.559
Change −0.35 ± 1.75 −0.15 ± 0.67 0.572
Pb 0.290 0.231
Total body water (L)
Before 24.40 ± 7.87 24.96 ± 8.38 0.791
After 24.30 ± 7.80 24.83 ± 8.23 0.799
Change −0.10 ± 0.79 −0.13 ± 0.88 0.890
Pb 0.494 0.427
aComparison between group. bComparison within group
Table 5 Subgroup analysis based on gender on the effects of synbiotic and placebo consumption on anthropometric measurements and body composition
Variables Stage Female (n = 32) Male (n = 28) P for interaction
Placebo (n = 19) Synbiotic (n = 13) Placebo (n = 11) Synbiotic (n = 17)
Weight Before 51.56 ± 14.41 57.65 ± 13.82 60.30 ± 18.05 53.01 ± 16.59 0.652
After 51.69 ± 14.97 57.79 ± 14.28 60.42 ± 18.31 52.69 ± 15.85
Change 0.12 ± 1.64 0.14 ± 2.04 0.11 ± 2.93 −0.32 ± 1.76
Height Before 1.42 ± 0.10 1.48 ± 0.10 1.52 ± 0.14 1.47 ± 0.16 0.968
After 1.42 ± 0.10 1.49 ± 0.10 1.52 ± 0.14 1.48 ± 0.16
Change 0.0026 ± 0.0042 0.0031 ± 0.01 0.0023 ± 0.0041 0.0026 ± 0.0044
BMI Before 25.08 ± 4.51 25.80 ± 3.25 25.67 ± 3.89 23.85 ± 3.11 0.816
After 25.03 ± 4.63 25.75 ± 3.36 25.61 ± 3.99 23.69 ± 3.12
Change −0.05 ± 0.64 −0.05 ± 0.79 −0.06 ± 1.02 −0.16 ± 0.73
WC Before 0.79 ± 0.11 0.83 ± 0.08 0.82 ± 0.08 0.79 ± 0.08 0.855
After 0.79 ± 0.11 0.83 ± 0.08 0.82 ± 0.09 0.78 ± 0.08
Change −0.0000 ± 0.01 −0.0008 ± 0.01 −0.0009 ± 0.02 −0.0032 ± 0.01
WHR Before 0.86 ± 0.06 0.86 ± 0.05 0.87 ± 0.02 0.86 ± 0.06 0.141
After 0.87 ± 0.06 0.81 ± 0.22 0.87 ± 0.04 0.86 ± 0.06
Change 0.0010 ± 0.01 −0.06 ± 0.19 −0.0012 ± 0.03 0.0014 ± 0.01
WHtR Before 0.56 ± 0.07 0.56 ± 0.04 0.54 ± 0.04 0.54 ± 0.05 0.882
After 0.56 ± 0.07 0.56 ± 0.04 0.54 ± 0.03 0.53 ± 0.05
Change −0.0011 ± 0.01 −0.0016 ± 0.01 −0.0020 ± 0.01 −0.0030 ± 0.01
HC Before 0.92 ± 0.11 0.96 ± 0.10 0.95 ± 0.10 0.92 ± 0.09 0.194
After 0.92 ± 0.12 0.96 ± 0.10 0.95 ± 0.10 0.91 ± 0.09
Change −0.0011 ± 0.01 0.0023 ± 0.01 −0.0000 ± 0.03 −0.01 ± 0.01
NC Before 0.32 ± 0.02 0.34 ± 0.03 0.34 ± 0.03 0.32 ± 0.02 0.592
After 0.32 ± 0.02 0.61 ± 0.99 0.33 ± 0.03 0.32 ± 0.02
Change −0.00 ± 0.01 0.27 ± 0.97 −0.01 ± 0.01 −0.00 ± 0.00
Wrist Before 0.16 ± 0.01 0.16 ± 0.01 0.17 ± 0.01 0.16 ± 0.01 0.300
After 0.16 ± 0.01 0.16 ± 0.01 0.17 ± 0.01 0.16 ± 0.01
Change −0.00 ± 0.00 0.0012 ± 0.0030 −0.0023 ± 0.0047 0.0003 ± 0.0012
ABSI Before 0.08 ± 0.01 0.08 ± 0.0042 0.08 ± 0.0042 0.08 ± 0.01 0.931
After 0.08 ± 0.01 0.08 ± 0.0044 0.08 ± 0.0044 0.08 ± 0.01
Change 0.00002 ± 0.0010 0.000004 ± 0.0009 −0.00004 ± 0.0011 −0.00003 ± 0.0012
AVI Before 2281.51 ± 1885.42 2878.60 ± 2313.75 2415.42 ± 1853.00 2443.49 ± 2011.27 0.211
After 2250.46 ± 1840.96 2988.49 ± 2373.68 2472.45 ± 2117.39 2347.32 ± 2007.43
Change −31.05 ± 227.97 109.89 ± 282.45 57.03 ± 944.56 −96.17 ± 268.44
CI Before 43.87 ± 10.74 47.33 ± 8.28 47.49 ± 9.72 42.94 ± 8.62 0.809
After 43.90 ± 11.08 47.28 ± 8.33 47.46 ± 10.05 42.63 ± 8.42
Change 0.03 ± 1.15 −0.05 ± 1.35 −0.03 ± 2.44 −0.31 ± 1.04
Fat mass Before 21.42 ± 8.22 23.95 ± 6.78 21.56 ± 8.08 18.40 ± 6.00 0.928
After 21.55 ± 8.79 23.98 ± 6.99 21.91 ± 7.89 18.50 ± 6.04
Change 0.14 ± 1.33 0.03 ± 1.36 0.35 ± 1.96 0.10 ± 0.99
Mineral body mass Before 2.11 ± 0.55 2.39 ± 0.74 2.71 ± 0.98 2.49 ± 0.98 0.543
After 2.14 ± 0.54 2.39 ± 0.76 2.75 ± 1.01 2.48 ± 0.96
Change 0.02 ± 0.08 −0.0015 ± 0.08 0.04 ± 0.07 −0.01 ± 0.07
Protein content (kg) Before 5.91 ± 1.44 6.64 ± 1.69 7.70 ± 2.72 6.94 ± 2.62 0.736
After 5.94 ± 1.42 6.62 ± 1.75 7.57 ± 2.74 6.85 ± 2.41
Change 0.04 ± 0.18 −0.02 ± 0.27 −0.13 ± 0.33 −0.08 ± 0.36
Skeletal muscle mass (kg) Before 15.78 ± 4.43 17.98 ± 4.75 20.95 ± 8.14 18.91 ± 7.90 0.518
After 15.36 ± 5.29 17.98 ± 4.94 20.74 ± 8.36 18.64 ± 7.57
Change −0.42 ± 2.12 −0.00 ± 0.69 −0.21 ± 0.92 −0.26 ± 0.66
Total body water Before 22.13 ± 5.52 24.67 ± 5.68 28.33 ± 9.90 25.19 ± 10.14 0.248
After 22.06 ± 5.34 24.80 ± 5.86 28.18 ± 9.96 24.86 ± 9.85
Change −0.07 ± 0.74 0.13 ± 0.75 −0.15 ± 0.91 −0.33 ± 0.95
P was resulted from analysis of covariance model including baseline values, group, gender and interaction effect of gender group. BMI body mass index, WC Waist circumference, WHR waist-hip ratio, WHtR waist-height ratio, HC Hip circumference, NC neck circumference, ABSI a body shape index, AVI abdominal volume index, CI conicity index
Discussion
The present study aimed to assess whether a synbiotic combination of L. coagulans SC-208 and L. indicus HU36 with FOS was effective on anthropometric indices and body composition in overweight or obese children and adolescents. Our results showed that WHtR significantly decreased at the end of the intervention in the synbiotic group in comparison with baseline. No significant changes were demonstrated in other anthropometric indices or body composition between groups.
The results of a recent meta-analysis showed no effect of pro/synbiotic supplementation on BMI, weight, body fat percent and WC among adults with metabolic syndrome [21]. However, another meta-analysis of 23 randomized trials showed that supplementation with a synbiotic can decrease body weight and WC [22]. The reason for the difference in the results may be that the difference in the selected population and the type of intervention.
There are limited human studies that have assessed the effects of probiotics on obesity and anthropometric indices, particularly among pediatric age groups. One month of intervention with synbiotic significantly decreased weight and BMI in obese children and adolescents [23]. Eight weeks of intervention with synbiotic without any lifestyle manipulation reduced BMI z score, WC and waist-to-hip ratio [24]. Eight weeks of intervention with Lactobacillus rhamnosus in obese children with liver disease showed that L. rhamnosus strain GG altered the bacterial composition without any remarkable effect on BMI z score or visceral fat [25]. However, 12 weeks of intervention with Lactobacillus salivarius (Ls-33) did not show any significant influence on BMI z score, WC or body fat in adolescents [26]. Three months of intervention with probiotics [Bifidobacterium animalis subsp. lactis CECT 8145 (Ba8145)] improved WC, WC/height ratio, conicity index, BMI and visceral fat among adults [27]. Another 12 weeks of intervention with probiotics (Lactobacillus gasseri BNR17) showed a slight weight reduction and significant waist and hip circumference changes among obese adults [28], and 12 weeks of intervention with L. gasseri SBT2055 showed a beneficial impact on abdominal adiposity and body weight among adults [29]. The differences between our results and other studies could be due to diversity in probiotic strain, composition and dose of supplement, subjects’ characteristics, geographical differences, and duration of the intervention.
Animal studies showed that probiotic supplementation with L. gasseri, Lactobacillus curvatus HY7601 and Lactobacillus plantarum KY1032 could decrease abdominal obesity and white adipose tissue size. It may be correlated with a reduction in leptin and adiponectin levels and an increase in the expression of fatty acid oxidation-related genes [30–32]. These findings reveal the effects of probiotics on the modulation of the natural gut microbiota [33]. Evidence has suggested that an imbalance in gut microbiota could contribute to overweight and obesity [22]. Weight loss with a calorie-restricted diet accompanied by increased physical activity has favorable effects on gut microbiota composition [34]. Although the pathogenesis and mechanisms underlying excess adiposity are complex, manipulation of the bacteria in the gastrointestinal system can be considered a potential therapy for overweight and obesity [22].
Initial diversity in the gut microbiota composition in children could be associated with overweight development in adulthood. The impact of probiotics on gut microbiota composition during the first year of life was shown to be a preventive factor for childhood obesity [35]. Intake of L. rhamnosus for four weeks before delivery and six months postnatally prevented severe weight gain during the first years of life [36].
The intestinal microbiota increases short-chain fatty acids (SCFAs), including acetate, butyrate and propionate. G-protein coupled receptors 43 and 41 (GPR43 and GPR41) are considered key receptors for SCFA. These two receptors impact the secretion of pancreatic peptide YY (PYY) hormone and leptin and ultimately influence appetite and weight gain [37].
Acetate directly influences the hypothalamus and reduces appetite. Some gut microbiota compounds can suppress the expression of fasting-induced adipose factor (FIAF) protein. This glycoprotein inhibits the production of lipoprotein lipase (LPL) in adipose tissue and the oxidation of fatty acids in both muscle and skeletal muscle [38].
However, the findings are still contradictory, and some mechanisms are controversial. Therefore, further investigation is necessary. The effects of dietary changes and supplements on the human gut microbiota are highly individualized. Findings of the interaction between diet–microbiota and host genetics and epigenetics help us plan new personalized diet approaches and implement new personalized strategies to prevent and decrease the incidence of obesity and other non-communicable diseases [39]. The advantages of the present study are the difference in probiotic strain and pediatric age groups. We assessed several anthropometric indices and body composition.
Intervention during the global pandemic of coronavirus disease 2019 (COVID-19) along with home quarantine and the inability to study enough molecular parameters to reveal molecular mechanisms are limitations of the present study. Our study included children and adolescents, and this age range has a differential impact on gut microbiota. Synbiotic supplements in our study were a combination of two different species, so we could not determine the singular effect and the possible synergistic or antagonistic effects of them. In addition, some studies [24, 28] used the fecal count of gut microbiota to confirm probiotic intake-related changes in intestine flora, but fecal samples were not taken in our study because of financial problems.
In conclusion, synbiotic supplementation might be associated with a reduction in WHtR. Further large-scale studies are required to highlight the importance of the synbiotic on cardio-metabolic risk factors in pediatric age groups.
Author contributions
HBM, KR and SJF: conceptualization, writing–review and editing. HBM: formal analysis. AMA: writing–original draft. EMH: review and editing. All authors read and approved the final manuscript.
Funding
This study was conducted as the project number 298113 supported by Isfahan University of Medical Sciences.
Data availability
The data that support the findings of this study are available from the corresponding author, upon reasonable request.
Declarations
Conflict of interest
No financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subject of this article.
Ethical approval
This study was approved by Ethics Committee of Isfahan University of Medical Sciences (Research ethics code: IR.MUI.RESEARCH.REC.1398.449).
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36484872 | PMC9734986 | NO-CC CODE | 2022-12-14 23:28:32 | no | World J Pediatr. 2022 Dec 9;:1-10 | utf-8 | World J Pediatr | 2,022 | 10.1007/s12519-022-00664-9 | oa_other |
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Appl Intell (Dordr)
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Applied Intelligence (Dordrecht, Netherlands)
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Springer US New York
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Article
FIRE: knowledge-enhanced recommendation with feature interaction and intent-aware attention networks
http://orcid.org/0000-0002-7941-2969
Zhang Ruoyi 1Ruoyi Zhang
is currently working toward the M.E. degree in the College of Computer Science and Engineering at Northwest Normal University, PR China. He received the B.E. degree from Yanan University, PR China., in 2020. His general area of research is KGbased recommendation and Graph Neural Networks.
http://orcid.org/0000-0002-5104-8982
Ma Huifang [email protected]
12Huifang Ma
is currently a professor in the College of Computer Science and Engineering at Northwest Normal University, PR China. She received the B.E. degree from Northwest Normal University, PR China., in 2003, and the M.S. degree from Beijing Normal University, PR China., in 2006. She received the Ph.D. degree from Institute of Computing Technology, Chinese Academy of Sciences, in 2010. Her general area of research is data mining and machine learning.
Li Qingfeng 1Qingfeng Li
is currently a postgraduate student in the College of Computer Science and Engineering at Northwest Normal University, PR China. His general area of research is intelligent recommendation.
Wang Yike 1Yike Wang
is currently a postgraduate student in the College of Computer Science and Engineering at Northwest Normal University, PR China. She received the B.E. degree from Qingdao University of Technology, PR China., in 2021. Her general area of research is Bioinformatics and recommendation.
Li Zhixin 2Zhixin Li
is currently a professor in the College of Computer Science and Information Engineering at Guangxi Normal University, PR China. His general area of research is natural language processing and machine learning.
1 grid.412260.3 0000 0004 1760 1427 College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070 China
2 grid.459584.1 0000 0001 2196 0260 Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, 541004 China
7 12 2022
121
27 10 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
To solve the information overload issue and enhance the user experience of various web applications, recommender systems aim to better model user interests and preferences. Knowledge Graphs (KGs), consisting of real-world objective facts and fruitful entities, play a vital role in recommender systems. Recently, a technological trend has been to develop end-to-end Graph Neural Networks (GNNs)-based knowledge-aware recommendation (a.k.a., Knowledge Graph Recommendation, KGR) models. Unfortunately, current GNNs-based KGR approaches focus on how to capture high-order feature information on KGs while neglecting the following two crucial limitations: 1) The explicitly high-order feature interaction and fusion mechanism and 2) The valid user intent modelling mechanism. As such, these issues lead to insufficient user/item representation learning capability and unsatisfactory KGR performance. In this work, we present a novel Knowledge-enhanced Re commendation with F eature I nteraction and Intent-aware Attention Networks (FIRE) to address the latent intent modelling and high-order feature interaction deficiencies ignored by existing KGR methods. Based on the prototype user/item representation learning leveraging the GNNs-based approach, our model offers the following major improvements: One is the innovative use of Convolutional Neural Networks (CNNs) that perform vertical convolutional (a.k.a., bit-level convolutional) and horizontal convolutional (a.k.a., vector-level convolutional) processes to model multi-granular high-order feature interactions to enhance item-side representation learning. Another is to model users’ latent intent factors by utilizing a two-level attention mechanism (i.e., node- and intent-level attention mechanism) to enhance user-side representation learning. Extensive experiments on three KGs domain public datasets demonstrate that our method outperforms the existing state-of-the-art baseline. Last but not least, numerous ablation- and model studies demystify the working mechanism and elucidate the plausibility of the proposed model.
Keywords
Recommendation
Knowledge Graph
Feature Interaction
Convolutional Neural Network
Attention Mechanism
Disentangled Representation Learning
https://doi.org/10.13039/501100001809 National Natural Science Foundation of China 61762078 61363058,U1811264,61966004 Ma Huifang Gansu Natural Science Foundation Project21JR7RA114 Ma Huifang Northwest Normal University Young Teachers Research Capacity Promotion PlanNWNU-LKQN2019-2 Ma Huifang NWNU Graduate Research Project Funding Program2021KYZZ02103 Zhang Ruoyi Industrial Support Project of Gansu CollegesNo.2022CYZC-11 Ma Huifang
==== Body
pmcIntroduction
The last decades have witnessed the flourishing of the World Wide Web, facilitating the development of online recommender systems (a.k.a., recommendation). Recommender systems have become essential components for internet applications (i.e., micro-video [1], E-commerce [2], and P2P lending [3]) to discover latent user interests and select items of interest for users accurately and in a timely manner based on a user-item historical interaction network. To alleviate the inherent sparsity and cold-start problems of recommender systems, an increasing amount of cutting-edge research has focused on recommendation methods that incorporate auxiliary information to capture deeper features and improve recommendation performance, including social networks [4–6], tags [7], and multi-modal information [8]. Knowledge Graph (KGs) are beneficial for enhancing item features with a large amount of structured attribute information. Unlike classic user-item bipartite graphs and user-user social networks, KGs are composed of a set of triplets, i.e., <head entity, relation, tail entity>. Figure 1 illustrates an example of KGs, which can describe not only node attributes, such as <Music1, Style, Popular>, but also include node relationships, such as <Singer, Friend, Arranger>. Recently, several large-scale KGs have been proposed, such as Satori, Freebase, and Google’s Knowledge Graph. These KGs can benefit recommender systems by introducing relatedness among entities, which makes it convenient to build KGs for recommendation, enrich entity information, and produce explainability. The above-mentioned enriched information in KGs can also supplement the relational modelling between users and items. Therefore, recommendation methods incorporating KGs are of interest to researchers and can effectively improve recommendation performance. Fig. 1 A schematic diagram of the music KGs recommendation system
Indeed, the research work dedicated to knowledge graph recommendation (a.k.a., KGR) has been ongoing. The previous KGs-based recommendation studies aim to obtain high-quality items and KGs entity embeddings leveraging pre-trained models, such as classical K nowledge G raph E mbedding (KGE) approaches are remarkable, including TransR [9], TransE [10], and RotatE [11]. Unfortunately, KGE-based KGR approaches neglect high-order connectivity and collaborative signals, leading to poor performance.
Consecutively, to resolve the natural shortcomings of the KGE approach, researchers attempt to probe the sophisticated high-order connectivity between items and entities. Primarily, there are two endeavours: 1) Meta-path-based methods. These methods mainly focus on leveraging the meta-path to capture item-entity long-distance connections and entity affiliations to augment the item/user representation. Nevertheless, these methods heavily rely on hand-designed meta-paths with expert knowledge. As a result, they are difficult to optimize during a practical training process. 2) Graph Neural Networks (GNNs)-based methods. These approaches focus iteratively over the whole KGs to find side information for recommendations. GNNs are a widespread neighbour aggregation strategy used to integrate multi-hop KGs entity nodes’ features into the target user/item representation. We must acknowledge that the existing GNNs-based KGR methods achieve excellent performance. However, can the current GNNs-based KGR methods achieve adequate awareness of high-order feature interaction signals and users’ latent intent information?
Based on the above doubts, we rethink the shortcomings and improvement goals of existing GNNs-based KGR methods. We believe that an effective approach for GNNs-based KGR methods is to couple both high-order feature interaction and user intent modelling as a whole based on which knowledge-enhanced method can be fully investigated. Nevertheless, fully exploiting high-order feature interaction signals and modelling latent intent information is by no means an easy task. To build an end-to-end KGR framework via high-order feature interaction and latent intent modelling, two issues inevitably need to be tackled: How can an effective high-order feature interaction paradigm be designed? In existing studies, high-order features from GNNs aggregation are generally combined with concatenation, pooling, or summation to receive high-order information without explicitly modelling their interactions. Such high-order aggregation mechanisms easily lead to over-smoothing issue. Besides, no further valuable feature information can be encoded, which significantly limits the performance of the model. Intuitively, adequately modelling the fine-grained feature interaction signals among high-order features has profound implications for enriching node representation learning.
How can a user’s latent intent signal be fully captured? In the real world, users’ intents are sophisticated and diversified, driving the user to consume different items. The intent behind user-item interaction offers a deep understanding of the user preferences. Existing KGR recommendation studies rarely consider the underlying user intent modelling, which makes the trained models uninterpretable and leads to unsatisfactory model performance.
Consequently, to solve the above two issues, we propose a novel Knowledge-enhanced Recommendation with Feature Interaction and Intent-aware Attention Networks (FIRE) to address the latent intent modelling and high-order feature interaction deficiencies ignored by existing KGR methods. Initially, we adopt a GNNs-based knowledge-aware backbone network to generate the user/item prototype representation. Next, to combat the first issue raised above, we innovatively use of Convolutional Neural Networks (CNNs) that perform vertical convolutional (a.k.a., bit-level convolutional) and horizontal convolutional (a.k.a., vector-level convolutional) approaches to model multi-granular high-order feature interactions to enhance item-side representation learning. For the second issue, we use a two-level attention mechanism (i.e., node-level attention mechanism and intent-level attention mechanism) to model the latent intent embedding to enhance user-side representation learning. Finally, all user-side/item-side representations are integrated, and inner product operations are performed to output prediction scores.
Overall, the contributions of our FIRE framework are three-fold: A novel high-order feature interaction paradigm: To the best of our knowledge, our work is the first attempt to incorporate high-order feature interaction techniques into the knowledge-aware recommendation task. Concretely, to enhance item-side representations, we highlight the critical importance of explicitly exploiting the feature interaction method in KGs-based GNNs recommendation methods. We propose a novel CNNs-based high-order feature interaction strategy to extract fine-grained interaction information features, which enrichs the item-side node representation learning capability.
Comprehensive modelling of users’ latent intent signals: For enhancing user-side representations, we propose a new approach to model a user’s latent intent by leveraging a two-level attention mechanism to enrich the node representation learning capability on the user-side.
Extensive experiments: We prepare three real-world datasets to evaluate our model. The empirical results demonstrate the effectiveness of our FIRE framework for KGs-based recommendation and show superiority to the current state-of-the-art baseline. Besides, numerous ablation- and model studies demystify the working mechanism and elucidate the plausibility of our FIRE model.
The rest of our paper is organized as follows. We summarize the related work in Section 2. Then, we briefly outline our task in Section 3. Based on this, we give a detailed description of our method in Section 4. In addition, the proposed model is analyzed and discussed in depth. In Section 5, a series of experiments on real-world KGs-based recommendation data are conducted, and the results are discussed in detail. Finally, a brief conclusion and future work are given in Section 6.
Related work
In this section, we review the current related work that is most relevant to the proposed approach. We present the relevant technical points in order from each of the following three technical perspectives: 1) KGs-based recommendation, 2) Feature interaction methods in recommendations, and 3) Disentangled representation learning (intent modelling) methods in recommendations. Next, we conclude and state these approaches after each subsection and briefly explain the differences from our proposed method.
KGs-based recommendation methods
In the early stages of KGR research, related work focused on embedding-based techniques. Entities and relations in KGs are used as supplementary information for users and items in recommendation tasks. In order to fully utilize the KGs information, the Knowledge Graph Embedding (KGE) technique is used to encode the entities and relations of the KGs as low-rank embeddings. Mainstream KGE algorithms are based on translation models (e.g., TransE, TransR, and RotatE). Based on the above method, a global graph representation of the user/item can be obtained. For instance, CKE [12] utilizes multimodal information as item-side supplemental information and learns item representation via TransR. DKN [13] treats contextual and word embedding information in news as side information and employs a multi-channel approch to generate news representations via TransD. However, embedding-based KGs recommendation approaches neglect the consideration of high-order connectivity and fails to adequately capture item-side high-order attribute embeddings.
Next, to pay more attention to the high-order connectivity problem in KGR, researchers are committed to advancing the path-based recommendation method. The path-based approach aims at path representation utilizing high-order entity connectivity patterns in heterogeneous information networks. The Meta-path is a relation sequence (i.e., P=A0→R1A1→R2…→RkAk ) connecting object pairs in a Heterogeneous Information Network (HIN), which can be used to extract connectivity features in the graph, which accounts for long-range connectivity by extracting paths that connect the target user and item nodes via KGs entities, such as PER [14], McRec [15], and HERec [16]. However, mainstream path-based methods suffer from some inherent limitations: 1) Brute force searches tend to lead to labour-intensive and time-consuming feature engineering when large-scale graphs are involved; 2) Experts are needed to define domain knowledge. The path-based method often results in difficult-to-train models and poor performance.
Furthermore, the rise of GNNs-based technology offers the possibility of exploring long-range connectivity in recommendations. It can iteratively execute the propagation mechanism to capture the high-order semantic information of target nodes on KGs, thus updating the high-order embeddings of the target node on the KGs. For instance, KGAT [17] proposes a Collaborative Knowledge Graph (CKG) to combine user-item-entity and recursively performs propagation over CKG by G raph A ttention NeT works (GATs [18]) to enrich entity embeddings, KGCN [19] recursively performs propagation over KGs via GNNs to enhance item-side entity embeddings. CKAN [20] utilizes a heterogeneous propagation strategy, which enables simultaneous augmentation of user- and item-side representations via GATs. KGIN [21] utilizes intent- and relation-aware mechanisms to model user/item representations in KGR. Nevertheless, mainstream GNNs-based methods suffer from two inherent limitations: 1) Neglecting fine-grained feature interactions and user intent modelling; 2) Unavoidable over-smoothing phenomenon.
Summary
As we mentioned in the introduction, the existing GNNs-based KGR model shows a strong dominance. Yet, the lack of fine-grained feature interactions and the absence of an explicit intent modelling mechanism limits the performance of recommendations to some extent. Our work adopts a GNNs-based model as a backbone network to explore the issue of high-order feature interactions in KGR models as well as intent-aware modelling, which is the primary focus of our model.
Feature interaction technique in recommendations
Feature interaction (a.k.a., feature combination) techniques have been successful in the field of click-through prediction (CTR), which can fully extract explicit as well as implicit interactions between high-order features. Converging feature interactions with deep neural networks for end-to-end models has become a mainstream approach for CTR, which can enhance the nonlinear capability of models and is significant for increasing model prediction accuracy. DeepFM [22] is a feature interaction model based on deep neural networks and factorization machines, which can effectively model the interactions of low-order and high-order features. xDeepFM [23] proposes a Compressed Interaction Network (CIN), which aims to learn arbitrary low-order and high-order feature interactions. FINT [24] proposes a feature interaction model that aims to perform high-order feature interaction while preserving the semantic information at the field level. CAN [25] proposes a method for modelling feature interactions utilizing a co-action network.
Afterwards, with the rise of GNNs technology, researchers attempt to utilize GNNs technology to deal with feature interactions. Fi-GNN [26] proposes a graph-based feature interaction method that models high-order features as nodes on a graph for simulating complex high-order feature interactions. L0-SIGN [27] is a graph-based feature interaction model that proposes a method based on L0 regularization to preserve useful feature interactions and filter irrelevant feature interactions in the feature graph.
Summary
In this paper, inspired by the great progress made in the feature interaction paradigm in the CTR task as well as in the sequence model [28], we introduce high-order feature interaction techniques into the KGR task to model fine-grained feature interactions. To the best of our knowledge, our work is the first attempt to incorporate high-order feature interaction techniques into the KGR task. This is one of the contributions and novelties of our work.
Disentangled representation learning (intent modelling) technique in recommendations
In the real world, there are often highly complex factors behind the construction of graphs(e.g., social networks, and user-item bipartite graphs). With the boom in graph machine learning techniques, deep learning techniques often ignore the latent factors behind these interactions. Indirectly, this leads to poor model robustness, neglect of interpretability, and unsatisfactory performance. The idea of disentangled representation learning originated in Capsules Network, and the core algorithm is the neighbour routing mechanism. DGCF [29] combines disentangled representation learning with collaborative filtering. IPREC [30] adopts a novel package recommendation framework that considers user latent intent modelling via an attention mechanism. GNUD [31] is a framework for news recommendation that combines disentangled representation learning with news recommendation, where a neighbour routing mechanism algorithm is applied. MIDGN [32] proposes a multi-view intent disentangled GNNs-based bundle recommendation model. IDS4NR [33] proposes a novel intent disentangled recommendation model based on item popularity and user preference perspectives. DisenHAN [34] proposes a recommendation method for disentangling user intent in heterogeneous information networks. However, little research has been done on the great potential of intent modelling for KGR.
Summary
In this paper, benefiting from the success of disentangled representation learning and intent modelling, we consider the introduction of an intent-aware technique based on a two-level attention mechanism for modelling fine-grained user intents in KGR tasks. This is another of the contributions and novelties of our work.
Problem formulation
We have the following definition and description of the KGs-based recommendation task.
User-Item interaction data
In a classic recommendation scenario, we have a set of M users U=u1,u2,…,uM and a set of N items V=v1,v2,…,vN. The user-item interaction matrix Y is defined according to user-item (u, v) implicit feedback as follows: 1 yuv=1if interaction(u,v)is observed0otherwise.
Knowledge graph
We have a knowledge graph G=(E,R), which is an undirected graph composed of entity-relation-entity triples (h,r,t). Where h,t∈E and r∈R, denote the head entity, tail entity, and KGs-relation of a knowledge triple, E and R are the set of entities and relations in the KGs, respectively. In addition, we define an item-entity alignment set A={(v,e)∣v∈V,e∈E} that is designed to uncover the alignment operations of items in both the user-item interaction matrix and KGs.1 Ultimately, we aim to learn a match function y~uv=F(u,v∣Θ,Y,G), where y~uv denotes the probability that user u will match with item v, and Θ is the set of model parameters(a.k.a., configuration).
Task description
We detail the recommendation of this paper for the task. Input: User-Item interaction matrix Y, knowledge graph G, and the model parameter set Θ.
Output: The probability that a user interacts with the item y~uv.
In addition, the important symbols involved in this paper are listed in Table 1. Table 1 The important symbols and definitions in this paper
Symbol Definition
U, V The set of users and items
Y, G User-Item interaction matrix and KGs
A, e Entities alignment set and KGs entity
Θ The set of model parameter
π Attention score of knowledge propagation
evinit The initial embedding of v
Rul l-order receptive field via KGs propagation
d Embedding dimension
Tul l-order triple set via KGs propagation
Mv 2-D high-order embeddings matrix
c convolutional value
Ht,Vt Horizontal and Vertical convolutional kernels
zv Final convolutional embedding
f Intent embedding
α,β Node-level and intent-level intent attention scores
Γ(⋅) Cross-entropy loss function
||⋅||22 L2-regularizer
y~uv The matching score of (u, v)
Method
In this section, we introduce the proposed FIRE. The framework is shown in Fig. 2. Precisely, FIRE consists of three modules: 1) Attentive Propagation Layer, which generates high-order propagation embeddings of target users and target items; 2) Feature Interaction (Bi-CNNs) module. The high-order representation computed by the target item is integrated into a 2-D matrix. Features are fused and interacted with two granularity convolutional kernels, thus obtaining a feature-enhanced item embedding; 3) Intent Disentangled Module. It utilizes two-level attention mechanisms to model the latent intent behind user-item interactions and obtain user intent-enhanced embeddings. Fig. 2 The framework of the proposed FIRE. The framework is composed of three crucial components: 1) Knowledge-aware attention network (backbone network), which yields the user/item embedding eu/v via the GNNs-based attentive propagation layer. 2) Feature interaction module (Bi-CNNs), which extracts local and global feature interaction signals from high-order feature matrix (See Fig. 3 for Bi-CNNs details). 3) Intent Disentangled module, which extracts fine-grained latent intent factors via node- and intent-level attention mechanisms. Best viewed in color
Backbone network
FIRE relies on GATs to capture high-order neighbour information following CKAN [20] and RippleNet [35]. The receptive field R is defined as follows: 2 Ru0=e∣v∈v∣yuv=1∧(v,e)∈A
3 Rul=t∣(h,r,t)∈G∧h∈Rul−1
4 Rv0=e∣v∗∈v∗∣∃u∈U,yuv∗=1∧yuv=1∧v∗,e∈A
Here, l={1,2,…,L}. We elaborately describe the user representation learning process here. Because item representation learning is a dual process, we omit it for brevity. In addition, we need to define the triple set of l-th knowledge affiliation triples, taking the user as an example.The size of the triplet set T directly determines the number of associated high-order entities. 5 Tul=(h,r,t)∣(h,r,t)∈Gandh∈Rul−1
Next, first-order propagation on the KGs is used as a case to demonstrate in detail the calculation of high-order embeddings via the knowledge propagation attention mechanism as follows: 6 π=softmaxfneuraleih⊕eir
Here i=1,2,…,Tul and fneural(⋅) is a 3-layer feedforward neural network. ⊕ is the vector concatenation operation. Then, we can obtain the user embedding after first-layer propagation as follows: 7 eu1=∑i=1Tu1π⋅eit
In addition, we introduce the initial propagation embeddings eu0,ev0 and the item initial embedding evinit as follows: 8 eu0=1Ru0∑e∈Ru0e,ev0=1Rv0∑e∈Rv0e
9 evinit=1|{e∣(v,e)∈A}|∑{e∣(v,e)∈A}e
By analogy, we can obtain both user and item high-order embeddings: 10 eu0,eu1,…,euL,evinit,ev0,ev1,…,evL
To aggregate high-order embeddings, we implement three aggregators: sum, concat, and maxpooling aggregators. Thus, we obtain the user and item integration representations: eu,ev. For convenience, we replace the user/item with the uniform symbol o. 11 aggsum=eo0+eo1+…+eoL
12 aggconcat=eo0⊕eo1⊕…⊕eoL
13 aggmaxpooling=maxpoolingeo0,eo1,…,eoL
where + is the vector summation operator, ⊕ is the vector concatenation operator and maxpooling{⋅} is the vector maxpooling function.
Feature interaction
Classic GNNs-based KGs recommendation frameworks merely choose to aggregate high-order embeddings by concat, mean, sum, or maxpooling while fine-grained feature interactions are neglected, e.g. KGCN, RippleNet, and KGIN. Nevertheless, we believe that these methods do not consider high-order feature interactions, which are crucial for recommendations. Convolutional Neural Networks (CNNs) and related variants are known to have recently witnessed breakthroughs in the areas of computer vision and natural language processing. This technique has been successful in extracting both local- and global features. We innovatively attempt CNNs as feature aggregators to process the 2-D high-order embedding matrix Mv∈ℝ(L+2)×d. Specific to the item-side, we adopt two convolutional kernels (Horizontal convolutional kernel and Vertical convolutional kernel) for extracting feature interaction signals, and the module is named Bi-CNNs.
More precisely, the vertical convolutional kernel Vt∈ℝ(L+2)×1 slides column-wise over matrix Mv to extract interactions of fixed dimension for high-order features, called the bit-level feature interaction mode. Similarly, a horizontal convolutional kernel Ht∈ℝh×d slides over matrix Mv in rows to extract interaction signals between neighbouring high-order features, called the vector-level feature interaction mode. In addition, to extract richer feature interaction information, we follow concept of multi-head mechanism [18] in GATs and stack several convolutional kernels for two types of convolutional modes.
Initially, the high-order embedding is concatenated into a 2-D matrix, with the following formalization. 14 Mv=evinitev0⋯evLℝ(L+2)×d
Vector-level feature interaction mode
As shown in Fig. 3, the upper part of the Bi-CNNs module depicts the working mechanism of the horizontal convolutional kernel, denoteed as Ht∈ℝh×d, for extracting neighbouring order feature interaction signals. As mentioned previously, following the multi-head mechanism requires several convolutional kernels to extract more feature interaction signals. Hence, t∈[1,ñ] and h ∈{1,2,…,(L + 2)} is shown as the height of the horizontal convolutional kernel. The i-th convolutional value c~it is illustrated as follows: 15 c~it=ReLUMv[i:i+h−1,:]⊙Ht
Where ⊙ denotes the inner product operator. Thus, the horizontal convolutional result c~t∈ℝ(L+2)−h+1 is : 16 c~t=c~1t,c~2t,…,c~it,…,c~((L+2)−h+1)t
Since vector-level feature interactions resulting from horizontal convolutional kernel interactions cannot avoid overlap and redundancy of interaction information. Hence, we apply the maxpooling operation and the output vector oh∈ℝñ×1 for the ñ kernels is denoted as: 17 oh=maxc~1,maxc~2,…,maxc~ñ
Fig. 3 Bi-CNNs employ two kinds of convolutional kernels to process high-order feature interactions (Horizontal convolutional kernel and Vertical convolutional kernel) for local- and global feature interactions. Specifically, the order L= 2, the size of horizontal convolution kernels ñ= 2, the size of vertical convolutional kernels n= 2, and the size of embedding dimension d= 3. Best viewed in color
Bit-level feature interaction mode
To extract significant feature interactions from a fixed dimensional viewpoint, we employ a vertical convolutional kernel Vt∈ℝ(L+2)×1 to extract bit-level feature interactions. As shown in Fig. 3, the lower part of the Bi-CNNs layer depicts the working mechanism of the vertical convolutional kernel. The vertical convolutional kernel Vt covers the 2-D high-order feature matrix Mv and slides along the embedding dimension.
Similar to the Horizontal convolutional kernel, the i-th convolutional value cit is denoted as: 18 cit=ReLUMv[:,i]⊙Vt
Where Vt∈ℝ(L+2)×1,t∈[1,n]. Thus, the vertical convolutional result ct∈ℝd is: 19 ct=c1t,c2t,…,cit,…,cdt
where d denotes the embedding dimension.
In particular, the vertical convolutional interaction results are equal to the weighted sum over the l rows of Mv weighted via vertical convolutional kernel Vt. 20 ct=∑l=1L+2Vt[l,:]⋅Mv[l,:]
Here l ∈ [1,(L + 2)], i ∈ [1,d], and ⋅ denotes multiplication operation.
We stack n vertical convolutional kernels. In contrast to the horizontal convolutional kernel processing, we expect to maximize the retention of bit-level feature interaction information in each dimension. Hence, we join the n vertical convolutional kernels in sequence. The output vector ov∈ℝdn is denoted as: 21 ov=c1⊕c2⊕…⊕cn
where ⊕ is shown as the connection operator.
Dense layer
We concatenate the above two convolutional vectors, fed into the dense layer to extract global interactive features, and output the item feature-enhanced convolutional embedding zv as such: 22 zv=φW⋅ovoh
Where W∈ℝd×(ñ+dn) is the transformation matrix and the convolutional embedding zv∈ℝd×1, φ(⋅) is the Sigmoid function. Then the final representation e~v is: 23 e~v=ev+zv
In summary, we innovatively employ CNNs and dense networks (layers) for extracting feature interaction signals, with the following advantages: 1) The horizontal convolutional mode primarily extracts feature interaction signals between adjacent high-order features, i.e., overall feature interactions between vectors. 2) The vertical convolutional mode extracts fine-grained feature interaction signals in each dimension of all features. 3) Similar to the multi-head mechanism, several types of convolutional kernels are used to extract more feature interaction signals. 4) The local feature interaction signals generated by the two convolutional modes are recombined and fed into a dense network to learn advanced global feature interaction signals.
Intent disentangled module
The construction of a real-world user-item interaction graph often results from a highly complex interaction of many latent factors. Existing deep learning techniques consider graph interactions holistically and rarely consider the entanglement of latent factors, causing the learned embeddings to be flawed for downstream tasks and uninterpretable. Figure 4 reveals the details of intent modelling driving user decisions and motivations. Thus, we first disentangle the user and item representations to different spaces and then make the user interact with the item in the same space to model the complex intent behind the user-item interaction: 24 eus=Wuseu,eixs=Wseix
where eus and eixs represent the corresponding embeddings under the s-th disentangled space, and s ∈ [1,S]. Ws is denoted as the disentangled matrix. ohistory=i1,i2,…,ix is defined as the set of items with which the target user has interacted. Immediately afterwards, we integrate the embeddings for each intent via the node-level attention mechanism as such: 25 fs=∑ix∈Ohistoryαxseixs
26 αxs=expqT⋅tanhweus⊕eixs∑ix∈OhistoryexpqT⋅tanhweus⊕eix′s
Where q∈ℝd and W∈ℝd×2d are trainable parameters for the attention mechanism. In essence, the attention weight αxs captures the target user preference for an item in a particular intent disentangled space. Intuitively, user preferences vary for each intent, motivating us to further combine the influence from s-th disentangled spaces with intent-level attention mechanism: 27 f=∑s=1Sβsfs
28 βs=expqT⋅tanhweu⊕fs∑s=1SexpqT⋅tanhweu⊕fs
Where f∈ℝd is the final embedding for encoding the complex intent influence for the user. Then the final representation e~u is: 29 e~u=eu+f
Fig. 4 There are complex and diverse intents behind user-item interactions, and specific users display different intent and interests when confronted with a particular item. Best viewed in color
Model prediction and optimization
On the premise that user/item prototype representations eu,ev are obtained via the knowledge-aware attention networks (c.f., Equations 11-13), we assign the ability to high-order feature interactions (c.f., Equation 23) and intent-aware (c.f., Equation 29) to the model.
Next, the interaction probability (matching score) y~uv between the target user u and the target item v is calculated by the inner product as follows: 30 y~uv=σe~uT⋅e~v
Here, σ(⋅) is the sigmoid function.
To ensure the effectiveness of model training and to improve training efficiency, we adopt the negative sampling strategy, sampling the same number of negative samples for each user. Ultimately, the loss function of FIRE is defined as follows. 31 L=∑u∈U∑v∈v|(u,v)∈γ+Γyuv,y~uv−∑v∈v|(u,v)∈γ−Γyuv,y~uv+λ∥Θ∥22
Where Γ(⋅) is the cross-entropy loss function, and γ+ denotes the user-item positive pair set. Conversely, γ− denotes the user-item negative pair set. λ is the L2-regularization coefficient for reducing overfitting. Θ denotes the model parameter set (model configuration). Finally, we compute the loss and adopt Adam optimization [36] to optimize our model parameters.
To make the overall framework of FIRE readable, we present the pseudo-code for the overall prediction method in Algorithm 1. Algorithm 1 The overall prediction algorithm of FIRE (u,v,Θ).
Model analysis and discussion
In this subsection, we conduct an in-depth analysis and discussion of the relation between FIRE and existing GNNs-based KGR models [17, 19, 20, 39]. Two main aspects are developed: 1) Novelty and differences, and 2) Relation with the state-of-the-art approach (KGIN [21]). Novelty and differences. For the knowledge graph recommendation task, previous work [17, 19, 20, 39] has focused on extracting long-range attribute (knowledge) information using GNNs techniques, leading to better representation learning of the user/item. Due to the inherent sparsity of recommender systems, we believe high-order feature interactions are crucial for recommendations to achieve feature enhancement. To the best of our knowledge, this is the first attempt to utilize CNNs for feature interaction on high-order attributes generated by knowledge-aware networks. In addition, previous KGR models rarely considered the user intent modelling process. We strongly believe that the knowledge-aware backbone network, empowering item-side feature interaction, and user-side intent modelling could jointly make FIRE more efficient than previous work.
Relation with KGIN. KGIN [21] is the state-of-the-art model for KGs-based recommendations. The main highlights are 1) setting multiple latent intent factors to describe the intent associations behind user-item interactions, and 2) proposing a relation-aware mechanism to extract relational dependency signals in long-range connections. Although this has a plausible intent-aware design similar to FIRE, there are major distinctions: 1) KGIN’s intent modelling process is naive, setting the latent intent factor as a trainable parameter, inevitably leading to insufficient extraction of latent intent signals, and resulting in unsatisfactory results. In FIRE, we couple the user’s historical interaction behaviour with the intent-aware process and design a more sophisticated two-level attention mechanism to capture the latent intent-aware signals. 2) Despite the significant progress in KGIN’s path-aware mechanism, it still cannot consider the crucial feature interaction module in the KGR task. In summary, we believe that a great KGR model should fully extract the feature interaction signals and the latent intent information so that the model performance is satisfying.
Experiment
In this section, we perform experiments on three real-world scenario datasets to evaluate our method and answer the following four research questions: RQ1: What is the performance of the proposed FIRE framework compared to the state-of-the-art KGs-based recommendation model?
RQ2: How do the key hyperparameters influence the performance of the proposed FIRE?
RQ3: How do different components affect FIRE?
RQ4: What is the time efficiency of the FIRE in model training?
Experimental setting
Dataset description
To evaluate the effectiveness of our method, we conduct a series of experiments on three different recommendation scenario datasets: 1) Last.FM, 2) Dianping-Food, and 3) MovieLens-1M, which are all openly accessible. Last.FM2 is a widely utilized benchmark in music KGs-based recommendations, which includes approximately 2000 users’ listening information from the Last.FM website.
Dianping-Food3 is a restaurant recommendation (POI recommendation) dataset, provided by Meituan Dianping, which contains more than 10 million interactions between approximately 2 million users and 1000 restaurants.
MovieLens-1M4 is a widely utilized benchmark in movie KGs-based recommendations, which contains 1 million ratings (ranging from 1 to 5) on a total of 2445 items from 6036 users.
For the construction of the dataset, we follow the treatment of previous work [20, 35, 39]. First, since the interactions in MovieLens-1M and Last.FM are both explicit feedback, they are converted to implicit feedback, where 1 indicates a positive sample (for MovieLens-1M, the threshold for a rating to be considered positive is 4, but no threshold is set due to the sparsity of Last.FM). We randomly sample negative samples per user with a negative sampling rate of 1. Second, in addition to the construction of the U-I interaction data, it was necessary to construct item-side sub-KGs for each dataset. sub-KGs for MovieLens-1M and Last.FM are constructed using Microsoft Satori.5 as for the Dianping-food dataset, we use the KGs provided by Meituan to construct Dianping-food sub-KGs. For all items in the dataset (music, movies, restaurants), the IDs can be matched in the corresponding sub-KGs. In addition, to filter out noise, we have filtered items that matched multiple entities and items that did not match any entity. Table 2 summarizes the detailed statistics for the three datasets; Last.FM (music), MovieLens-1M (movies) and Dianping-Food (restaurant). Table 2 Statistics and hyper-parameter settings for the three datasets (d: embedding dimension, s: intent number, λ: L2 regularization coefficient, L: depth of GNNs layer)
Dataset Last.FM Dianping-Food MovieLens-1M
#users 1872 2298698 6036
#items 3846 1362 2445
#interactions 42346 23416418 753772
#entites 9366 28115 182011
#relations 60 7 12
#triples 15518 160519 1241995
#data split 6:2:2 6:2:2 6:2:2
#dropout ratio 0.5 0.5 0.5
#learn rate 0.005 0.005 0.005
#d 128 64 64
#s 6 4 6
#λ 1e-5 1e-5 1e-6
#L 2 1 2
Experimental settings
We utilize PyTorch6 to implement our method and deploy it on a server with Quadro RTX 6000 GPU with 24 G of video memory.7 For each dataset, the ratio of the training, validation, and test sets is 6:2:2. For BCE loss, we construct the training set by randomly sampling 1 negative item for each positive item (i.e., negative sampling rate: 1).
Evaluation metrics
We perform experiments in two prototypical recommendation scenarios. For the top-K recommendation task, we adopt a widely-used evaluation protocol to evaluate the effectiveness of our proposed method: Recall@K, and we set K={50, 100}. For the CTR prediction task, we utilize Area Under the ROC Curve (AUC) and F1-score for the evaluation protocol [40]. 32 Recall@K(u)=R1:K(u)∩T(u)|T(u)|
33 Precision=TPTP+FP
34 Fl-score=2×Precision×RecallPrecision+Recall
35 AUC(u)=∑i∈T(u)∑j∈I∖T(u)Py~ui≥y~uj|T(u)||I∖|T(u)|∣
Where P(⋅) is the indicator function, T(u) denotes the ground truth item set, and R1:K(u) denotes the top-K recommended item list.
Implement details
We train the model by optimizing the BCE loss with Adam [36] optimizer and Xavier [37] initializer. We train the model for 50 epochs, and an early stopping strategy is performed to prevent overfitting. We perform a grid search for hyperparameters: The embedding dimension size in the range of {8, 16, 32, 64, 128, 256}, the L2 regularization factor tuned amongst {0, 1e-6, 1e-5, …, 1e-3} and the learning rate is tuned amongst {5e-2, 1e-2, 5e-3, 1e-3, 5e-4, 1e-4}. During KGs propagation, the depth of GNNs layer is adjusted among {1, 2, 3, 4}. We select the user- and item triple set size in {8, 16, 32, 64}. For user intent modelling, the number of intents is searched within {2, 4, 6, 8, 10}. For Bi-CNNs, we search for the number of two convolutional kernels in the range {2,4,8,16}. Three aggregators (sum, concat, and maxpooling) are employed for aggregating high-order representations, and the default Dropout [38] rate (Dr) is set to Dr= 0.5 in the Bi-CNNs and Dr= 0.5 in the all attention networks.
Baselines
To illustrate the effectiveness of our model, we choose eight baselines, as follows: CKE [12]: It incorporates multi-modal knowledge to enhance item embeddings for collaborative filtering.
PER [14]: It’s treating the KGs as a heterogeneous information network (HIN) and explores high-order path information based on a meta-path way.
RippleNet [35]: It’s a propagation-based KGs recommendation method, that models user representation as plenty of entities related to users’ historical interacting items. And treats users’ preferences as Ripple that captures high-order attributes on the KGs.
KGCN [19]: It’s a GNNs-based KGR method, which effectively captures user-specific preferences for items in the KGs.
KGNN-LS [39]: It’s a GNNs-based KGR method, that considers label-smoothing in the information aggregation phase to generate user-specific item representations.
KGAT [17]: It’s a GNNs-based KGR method, that adopts attention mechanism and relies on GATs to capture the high-order neighbour information and node-level feature interaction.
CKAN [20]: It’s a GNNs-based KGR method, that utilizes attention mechanism and relies on GATs to capture the high-order neighbour information.
KGIN [21]: It’s a state-of-the-art GNNs-based KGR method, that disentangles the intent factor behind the user-item interaction and utilizes a relation-aware mechanism to obtain user/item representations.
Performance comparison (RQ1)
To answer the first research question, we compare the performance of all the baselines in Tables 3 and 4. From the results, we make the following observations: PER has the worst performance on the three datasets over all baselines. This indicates that the path-based method requires domain knowledge to define meta-paths and it is hard to optimize path selection in training, which limits the performance of PER.
CKE achieves performance improvement over PER because of the introduction embedding-method. This indicates that it is helpful to improve recommendation performance with knowledge graph embedding technology. Nevertheless, CKE cannot effectively capture the high-order features on the KGs, which results in insufficient performance. In addition, CKE does not perform well, which might also be caused by a lack of multimodal information.
RippleNet has a significant performance improvement in comparison to path-based and embedding-based methods. This demonstrates the importance of exploring information about high-order attributes on the KGs. However, RippleNet constructs user and item representations asymmetrically and ignores high-order connectivity, which can lead to unsatisfactory performance.
Compared with the shallow model, the performance of KGCN, KGNN-LS, KGAT, and CKAN confirm that incorporating the high-order connectivity and attention mechanisms can improve the recommendation effect. However, the above KGs-based GNNs model neglects fine-grained feature interaction and intent disentangled, and struggles to avoid over-smoothing of high-order features, which leads to unsatisfactory performance.
KGIN is currently the strongest baseline model for KGR and is highly correlated to our model. Its strengths lie in fine-grained intent modelling and path-aware techniques. Whereas it still fails to deal with the lack of high-order feature interactions compared to our model, resulting in unsatisfactory model performance. This reflects the progressive nature of our model’s fine-grained feature interactions.
FIRE outperforms all the baseline methods, which demonstrates that FIRE can effectively explore user latent intent and item fine-grained high-order feature interactions via a two-level attention mechanism and Bi-CNNs module.
Table 3 Overall performance comparison of AUC and F1
Method Last.FM Dianping-Food MovieLens-1M
AUC F1 AUC F1 AUC F1
CKE 0.747 0.674 0.812 0.741 0.906 0.802
PER 0.641 0.603 0.766 0.697 0.712 0.667
RippleNet 0.776 0.702 0.863 0.783 0.919 0.842
KGCN 0.802 0.708 0.845 0.774 0.909 0.836
KGNN-LS 0.805 0.722 0.852 0.778 0.914 0.841
KGAT 0.829 0.742 0.846 0.785 0.914 0.844
CKAN 0.842 0.769 0.878 0.802 0.915 0.842
KGIN 0.848 0.760 0.879 0.799 0.919 0.844
FIRE 0.860* 0.772* 0.882* 0.805* 0.925* 0.851*
%Imp. 1.41% 0.39% 0.34% 0.37% 0.65% 0.82%
*Note that all results have the statistical significance for p< 0.05 compared with the best baseline result
Table 4 Overall performance comparison of Recall@K
Method Last.FM Dianping-Food MovieLens-1M
R@50 R@100 R@50 R@100 R@50 R@100
CKE 0.181 0.297 0.305 0.439 0.375 0.522
PER 0.117 0.177 0.256 0.355 0.171 0.251
RippleNet 0.235 0.356 0.392 0.545 0.317 0.460
KGCN 0.298 0.345 0.331 0.441 0.358 0.512
KGNN-LS 0.271 0.349 0.342 0.488 0.359 0.513
KGAT 0.365 0.451 0.389 0.561 0.385 0.533
CKAN 0.342 0.432 0.413 0.574 0.395 0.540
KGIN 0.367 0.462 0.415 0.577 0.402 0.544
FIRE 0.371* 0.469* 0.423* 0.581* 0.412* 0.556*
%Imp. 1.08% 1.51% 1.92% 0.69% 2.48% 2.20%
*Note that all results have the statistical significance for p< 0.05 compared with the best baseline result
Study of FIRE (RQ2)
To answer the second research question, we perform a crucial hyperparameter analysis of FIRE. From the results, we have the following conclusions.
Impact of embedding size
Figure 5 reports the effect of embedding size on the AUC performance in three recommendation scenarios. The best performance is achieved when the embedding size are set to 128, 64, and 64 for the three datasets. We can observe that with the increase in embedding size from 8 to 256, the recommendation performance improves due to the stronger representation feature space. However, a larger embedding size does not always result in stronger model representation ability for recommendations. This is caused by model overfitting as well as encoding irrelevant feature information. Fig. 5 AUC results of FIRE with different dimension of embedding
Impact of different user intent numbers
To analyze the effect of the number of intents, we adjust in the range {2, 4, 6, 8, 10} and illustrate the performance change for the three datasets in Fig. 6. We find that the best performance is achieved when the number of intents is set to 6, 4, and 6 for each of the three datasets. Specifically, performance is poorer when the number of intents is set small, i.e. in the case of coarse-grained intent modelling. This justifies the encouragement of multiple user intents. However, when the number of intents is set larger, the model performance decreases instead. A reasonable explanation is that when intent modelling is too fine-grained, it encodes some irrelevant information and noise, which is detrimental to the accurate representation of the model. Fig. 6 AUC results of FIRE with different user intent numbers
Impact of different L2 regularization coefficients
Figure 7 summarizes the effect of different L2 regularization coefficients on AUC performance, and we have consistent conclusions that the model has different tolerances for different regularization coefficients. We find that the best performance is achieved when the L2 regularization coefficients are set to 1e-5, 1e-5, and 1e-6 for each of the three datasets. Specifically, when the regularization coefficient is small, it can lead to model over-fitting. Conversely, L2 regularization is like a double-edged sword. When the L2 regularization coefficient is too large, it can cause a shift in the correct optimization direction of the model and lead to the severe consequence of underfitting the model. Therefore, choosing an appropriate regularization coefficient allows the model to best performance. Fig. 7 AUC results of FIRE with different L2 regularization coefficients
Impact of different aggregators
We explore the impact of the three aggregators on the AUC performance in Table 5 and find that the sum aggregator consistently outperforms the other aggregators. In contrast, the maxpooling aggregator causes the model performance to collapse. One possible reason is that the concat aggregator may encode some irrelevant features, while the maxpooling aggregator undoubtedly loses important attribute information, which leads to poor performance. Table 5 AUC results of FIRE with different aggregators
Aggregator FIRE_sum FIRE_concat FIRE_maxpooling
Last.FM 0.860 0.857 0.832
Dianping-Food 0.882 0.880 0.876
MovieLens-1M 0.925 0.924 0.921
The best performance is bolded, and the runner-up is underlined
Impact of different GNNs layers
We verified how GNNs depth affects model performance by varying the number of GNNs layers from 1 to 4. Table 6 shows that FIRE achieves the best performance when L is taken to be 2, 1, and 2 for the three datasets, respectively. In addition to the well-known problem of oversmoothing due to deep GNNs, two other reasons that are very significant are 1) The difficulty of avoiding the introduction of irrelevant information when high-order propagation introduces remote knowledge, especially when facing large-scale datasets. 2) The problem of leading to representation degradation. All these problems can lead to overfitting of the model and thus to poor model performance. Therefore, keeping an appropriate depth of layers in high-order information propagation can maximize the performance of recommendations. Table 6 AUC results of FIRE with depth of GNNs layer
Depth of GNNs layer 1 2 3 4
Last.FM 0.848 0.860 0.856 0.854
Dianping-Food 0.882 0.880 0.879 0.876
MovieLens-1M 0.920 0.925 0.917 0.919
The best performance is bolded, and the runner-up is underlined
Impact of the size of the triple set
We fine-tune the size of the user and item triple sets to explore their impact on FIRE within the range of {8, 16, 32, 64}. Here we choose Last.FM and Movielens-1M for our experiments. Tables 7 and 8 show the results of the experiments. We find that the best results are obtained when the user triple size is set to a uniform 16. The best performance is achieved when the item triple set size is chosen to be 32 and 64. One possible reason for this is that there is a difference in the initial number of user/item entities for different datasets, which directly determines the number of triples that can be associated. This results in performance differences. In addition, when the user triple size is set too large, the model’s performance is weakened, which is the cause of a degree of overfitting in the analysis. Table 7 AUC results for Last.FM w.r.t. different sizes of the triple set
8 16 32 64
8 0.857 0.856 0.858 0.859
16 0.854 0.857 0.860 0.860
32 0.855 0.859 0.858 0.858
64 0.856 0.855 0.854 0.857
The best performance is bolded, and the runner-up is underlined
Table 8 AUC results for MovieLens-1M w.r.t. different sizes of the triple set
8 16 32 64
8 0.917 0.919 0.922 0.923
16 0.919 0.923 0.924 0.925
32 0.922 0.924 0.924 0.922
64 0.923 0.922 0.923 0.924
The best performance is bolded, and the runner-up is underlined
Impact of convolutional kernels
We fine-tune the sizes of the vertical- and horizontal convolutional kernels to explore their impact on FIRE within the range of {2, 4, 8, 16}. Here we choose Last.FM and Movielens-1M for our experiments. Tables 9 and 10 show the results of the experiments. We find that the best results were obtained when the horizontal convolutional kernel size is set to a uniform 4, and the size of the vertical convolution kernels is set to 2 and 4 respectively. A consistent conclusion is that when the size of convolutional kernels is too small, it is not possible to encode feature interaction information adequately. Conversely, when the size of convolutional kernels is too high, it encodes some of the noise and leads to the overfitting of the model. Therefore, choosing the suitable size of convolutional kernels is crucial for model performance improvement. Table 9 AUC results for Last.FM w.r.t. different sizes of the two convolutional kernels (n: size of vertical convolutional kernel, ñ: size of horizontal convolutional kernel)
2 4 8 16
2 0.858 0.860 0.859 0.854
4 0.858 0.857 0.857 0.856
8 0.857 0.856 0.858 0.857
16 0.829 0.831 0.839 0.829
The best performance is bolded, and the runner-up is underlined
Table 10 AUC results for MovieLens-1M w.r.t. different sizes of the two convolutional kernels (n: size of vertical convolutional kernel, ñ: size of horizontal convolutional kernel)
2 4 8 16
2 0.923 0.924 0.922 0.918
4 0.922 0.925 0.923 0.921
8 0.922 0.924 0.923 0.920
16 0.919 0.922 0.921 0.917
The best performance is bolded, and the runner-up is underlined
Network visualization
To explore the effects produced by the two core modules in the FIRE model (i.e., the feature interaction module (Bi-CNNs) and the intent modelling module), we observe some details of the trained network. Figure 8(a) reveals the convolutional values of the five vertical convolutional kernels after training FIRE on the Last. FM dataset at L= 3. We find that the five convolutional kernels are trained to be diverse. After analysis, we believe that the vertical convolution kernels produce a similar effect to the attention mechanism by assigning a corresponding weighted sum to each dimension of high-order features (c.f., Equation (20)), which is sufficient to capture fine-grained bit-level feature interactions. Fig. 8 Network visualization w.r.t. vertical convolutional kernel and intent-level attention weight
Next, we explore the practical effects produced by the intent-level attention mechanism in Fig. 8(b). We are again conducting experiments on Last.FM (with the number of intents set to 5), and we randomly select five users (U204, U32, U1324, U305, U472) to reveal the effect of intent-level attentive weight visualization (c.f., Equations 27-28). We can find that, after network training, the five attentive weights produce a significant divergence. This indirectly coincides with our vision to encourage modelling the complex and diverse intent perception factors of users to pinpoint their intents and interests.
Ablation analysis (RQ3)
To answer RQ3, as shown in Figs. 9 and 10, a comprehensive ablation analysis is conducted from two views (i.e., macro- and micro views) to assess the effectiveness and performance of all key components of the model. The specific variants are shown below. FIREW/OIntent: Remove the user intent component totally.
FIRE Dual-Bi-CNNs: Add Bi-CNNs modules to the user-side.
FIRE-light: Remove both Bi-CNNs and intent component.
FIREW/OH-kernel: Remove the horizontal convolution module.
FIREW/OV-kernel: Remove the vertical convolution module.
FIREW/OGNNs-att: Remove the knowledge-aware attention mechanism module.
FIREW/OIntent-att: Remove the Intent-Aware Attention Mechanism module.
Fig. 9 AUC results of FIRE w.r.t. macro-ablation analysis
Fig. 10 AUC results of FIRE w.r.t. micro-ablation analysis
Impact of the intent-aware attention mechanism
To investigate the impact of the intent-aware attention module in FIRE, we disable the whole intent module, and FIREW/O Intent is represented as the variant model. Based on the results reported in Fig. 9, the AUC performance decreases significantly after removing the whole intent component, which demonstrates that the intent-aware modelling is essential for performance improvement. In addition, we conduct an additional experiment to verify the effectiveness of a two-level intent-aware attention mechanism. We construct a variant model FIREW/OIntent-att that shows the use of average aggregation instead of attention mechanism aggregation. The results are shown in Fig. 10 which indicates a significant drop in performance. This demonstrates the importance of a two-level intent-aware attention mechanism for distinguishing intents.
Impact of the feature interaction mechanism
Similarly, to investigate the need for the feature interaction module, we set up a variant named FIRE-light with the removal both Bi-CNNs and intent-aware component. As shown in Fig. 9, a significant performance degradation occurs when the feature interaction module is removed, indicating that the feature interaction module is critical to knowledge-aware recommendation models and contributes significantly to performance improvement. Next, to investigate the effect of two convolutional kernels on the performance of the model, two additional variants were set up: FIREW/OH-kernel and FIREW/OV-kernel. As shown in Fig. 10, we found that using only one type of convolutional kernel for feature fusion significantly degrades the model accuracy. Furthermore, the performance degradation is more pronounced when only the horizontal convolutional kernels are retained. Therefore, we conclude that 1) the best performance can be achieved by using both types of convolutional kernels and 2) bit-level feature interactions (i.e. vertical convolutional kernels) can make a sufficient contribution to the model.
Impact of the knowledge-aware attention mechanism
To explore the position of the knowledge-aware attention mechanism in the overall model, we set up variant FIREW/OGNNs-att. As shown in Fig. 10, the model performance collapses when the average aggregation mechanism is utilized instead of the knowledge-aware attention mechanism. This demonstrates that knowledge-aware attention mechanisms play a crucial role in user/item representation. It allows for adaptive aggregation of entity information and provides assurance that the model is accurately represented.
Other aspects
To further explore the efficiency of the feature interaction module in Fig. 9, we construct a variant FIRE Dual-Bi-CNNs, i.e., one that also gives feature interaction functionality for the user side. We have an interesting finding that the performance collapses when the Bi-CNNs module is added together with the user/item side. One possible reason is that the model underwent severe overfitting, rendering the feature interaction module useless. We leave the exploration of a more fine-grained and balanced approach to feature interaction to future work.
Training cost and efficiency analysis (RQ4)
To answer RQ4, in this section, we examine the time efficiency of the FIRE model and the two macro-variants and select four baseline methods for the CTR task as our control. All methods are performed in the same hardware environment, and the corresponding results are reported in Fig. 11. Specifically, the upper part of Fig. 11 reveals the specific training time of the model, and the lower half reports the overall performance of the model in terms of training time versus accuracy (AUC) (scatter plot). In this case, the top right corner implies the best performance. Fig. 11 Model comparison of the efficiency and accuracy (AUC)
We have the following observations: 1) Compared to the GNNs-based KGR model, FIRE is justified by the introduction of the feature interaction module and the intent-aware attention module, which makes the model more robust and thus introduces some additional overhead. 2) Compared to RippleNet, the temporal performance is relatively superior on large-scale datasets, demonstrating the effectiveness and efficiency of the adaptive knowledge-aware attention mechanism.
Unfortunately, while the performance is sufficiently good compared to traditional GNNs-based KGR methods, the stacking of additional neural modelling mechanisms makes the time consumption not advantageous. We will design a lightweight neural recommendation model in future work to achieve a double win between efficiency and time costs.
Conclusion and future work
In this paper, we propose a novel end-to-end KGs-based GNNs recommendation method. Specifically, the method leverages an attention mechanism to capture the high-order attribute information of users and items on the KGs. Next, a multi-granular convolutional neural network is adopted to capture the high-order feature interactions of the item-side. Last but not least, a two-level attention mechanism is utilized to model the latent intent of the user, thus achieving enhanced user embeddings. Empirical results on three large-scale benchmark datasets demonstrate the superiority and efficiency of our FIRE method.
In future work, we will consider how to distill and refine the sub-KGs in KGs-based recommendations, and attempt to integrate self-supervised learning techniques into the KGs-based GNNs recommendation. Besides, in view of the shortcomings of our work, which consumes more time than existing methods, we will aim to design more efficient and light-weight neural recommendation [41, 42] models in the future.
On the other hand, we will pay more attention to negative sampling techniques on KGs-based GNNs recommendation methods to generate better quality negative samples. We also leave these works in the future.
Acknowledgements
This work is supported by the Industrial Support Project of Gansu Colleges (No.2022CYZC-11), the Gansu Natural Science Foundation Project (21JR7RA114), the National Natural Science Foundation of China (61762078, 61363058, U1811264, 61966004) and Northwest Normal University Young Teachers Research Capacity Promotion Plan (NWNU-LKQN2019-2). NWNU Graduate Research Project Funding Program (2021KYZZ02103).
In addition, we also appreciate the professional and constructive suggestions and revisions from the anonymous reviewers and editor. And we are very appreciative of the doctors, nurses, and volunteers working on the front lines of the fight against COVID-19.
1 Special note: When a bold e appears in the context, it is uniformly signified as an embedding. Conversely, e is signified as an entity symbol in KGs.
2 grouplens.org/datasets/hetrec-2011/
3 https://www.dianping.com/
4 https://grouplens.org/datasets/movielens/1m/
5 https://searchengineland.com/library/bing/bing-satori
6 pytorch.org
7 https://www.nvidia.cn/
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9734987 | NO-CC CODE | 2022-12-14 23:28:32 | no | Appl Intell (Dordr). 2022 Dec 7;:1-21 | utf-8 | Appl Intell (Dordr) | 2,022 | 10.1007/s10489-022-04300-x | oa_other |
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Univers Access Inf Soc
Univers Access Inf Soc
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1615-5289
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Springer Berlin Heidelberg Berlin/Heidelberg
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10.1007/s10209-022-00953-0
Long Paper
A bibliometric analysis and visualization of e-learning adoption using VOSviewer
http://orcid.org/0000-0002-7787-6305
Martins José [email protected]
12
Gonçalves Ramiro [email protected]
13
Branco Frederico [email protected]
3
1 AquaValor – Centro de Valorização e Transferência de Tecnologia da Água, Chaves, Portugal
2 grid.20384.3d 0000 0004 0500 6380 INESC TEC, Porto, Portugal
3 grid.12341.35 0000000121821287 INESC TEC and University of Trás-Os-Montes E Alto Douro, Vila Real, Portugal
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14 11 2022
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Even though being perceived as a novel approach, multiple authors claim that the digital transition of all sectors in society started when information and communication technologies (ICT) started to be an integral part of our daily lives. The education sector currently represents one of the contexts where the use of ICT is more promising and allows to reach greater benefits, mostly due to the wide range of tools, applications, and management and methodological approaches that are associated with e-learning. With the above in mind, a bibliometric analysis of the e-learning adoption topic has been performed, aiming on delivering a detailed analysis of the status of the topic. This analysis was carried out by analyzing the scientific literature indexed in the Scopus database that addressed the multiple stages of the e-learning adoption process (i.e., acceptance, adoption, and use). Our study analyzed 896 documents published between 1989 and 2021, of which 98.3% represented papers published in journals and conference proceedings.
Keywords
e-Learning
e-Learning acceptance
e-Learning adoption
e-Learning use
Bibliometric analysis
VOSviewer
http://dx.doi.org/10.13039/501100008530 European Regional Development Fund NORTE-01-0246-FEDER-000053
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pmcIntroduction
As digital transition began to encompass educational institutions, from basic education schools to universities and polytechnique institutes, it was possible to perceive the establishment of strategic approaches that not only focused on the adoption of innovative technologies, but also on the adoption of innovative educational and management strategies that are perceived as compliant with the continuously emerging challenges in the “education world” [33]. By merging these innovative technologies, such as ICT—information and communication technologies, a plethora of opportunities has emerged for students, who were given a new set of knowledge repositories and approaches to improve their learning process, and for teachers, that could improve the efficiency and overall efficacy of the teaching methods and initiatives they were applying and trying to develop [15].
Despite the increasing adoption of ICT for educational purposes and the prominent role that the “internet” has had in this phenomenon, there is still a set of issues concerning not only this adoption process but also the actual use of these technologies [46]. As argued by authors such as Hamid [16] and Aparicio et al. [3], when focusing on e-learning (the concept typically applied to characterize the use of ICT for educational purposes), one should address all elements that encompass it, namely the pedagogical dimension, the content strategy, the user interface (UI), and also the inherent information architecture.
According to existing literature [19, 25, 27, 43], these issues have been the focus of attention by both researchers and practitioners during the past decade, but there are still multiple perspectives that have not been addressed and that are considered to have a serious impact to the full adoption and use of e-learning.
Thus, with the abovementioned in mind and considering the need to concentrate, in a focused manner, on the multiple perspectives present in the existing literature on the topic of e-learning adoption and use, and consequently stimulate further developments of this knowledge and the arise of innovative approaches and perspectives, a decision was made to undergo a wide-range exploration and bibliometric analysis to the existing literature on the topic. After acknowledging the large volume of scientific data associated with the terms and concepts we were aiming, and considering Donthi et al. [11] and Sandnes [41] arguments, the research team opted to perform a bibliometric analysis of the referred data and have chosen VOSviewer as the tool that would support this task [7].
The remainder of the paper is structured as follows. The paper begins by presenting the methodological approach that supported all the performed identification and analysis of existing literature, followed by an in-depth overview of the achieved results. Next, the referred results are discussed according to the perspectives of other authors on the topic. The paper concludes with its final remarks and a brief highlight of the detected limitations and research topics that should be focused on the future.
Methodology (data and methods)
Sources of information
Drawing on the arguments by Sweileh [44] and Yas et al. [53], the scientific data used as the basis for this study were selected from the Elsevier Scopus database. This database, created in 2004 by Elsevier, currently holds more than 77.8 million records (post-1969) from which over 23,000 are peer-reviewed journals, 294 trade publications, over 852 book series, and over 120,000 worldwide scientific events [13]. Hence, it is possible to perceive that Scopus represents one of the most comprehensive views of the current state of research at a global level. According to Agarwal et al. [1], besides the global context of Scopus, it also permits its users to benefit from a series of features that accelerate bibliometric analysis, such as multicriteria filters that allow for segmentation of the global sample (for example, journal name, type of document, year of publication, authors’ names, authors’ affiliations, number of citations, etc.).
Study design
As one can perceive by analyzing the existing studies on the technology adoption topic (acceptance, adoption, and use), the most relevant contributions that have arisen are the theoretical models that not only identify the determinants of the adoption of a given technology but also characterize the hypothetical relations between them [20, 35, 40]. As argued by authors such as Taherdoost [45], the most relevant technology adoption theories and models are: (a) theory of reasoned action, (b) theory of planned behavior; (c) theory of interpersonal behavior; (d) technology acceptance model—TAM; (e) extension of TAM; (f) Igbaria’s model; (g) social cognitive theory; (h) diffusion of innovation theory; (i) perceived characteristics of innovating theory; (j) motivational model; (k) uses and gratification theory; (l) the model of personal computers utilization; (m) unified theory of acceptance and use of technology—UTAUT; and (n) compatibility UTAUT.
Considering “e-learning” as the use of ICT for educational purposes, it has been perceived by different authors as a technology on its own. Hence, drawing on the abovementioned, it is possible to infer that the understanding of the e-learning adoption process might be achieved by analyzing the literature that focused not only on the concept of e-learning but also on the most popular technology adoption models and theories. To identify the set of literature records that compose our study sample, we combined the technology adoption theories and models highlighted by Taherdoost [45] with the term “e-learning.”
To ensure that the used sample was of the utmost scientific relevance and validity, the “type of document” has been also used as a filter criterion applied to Scopus search tools. Considering this, our study only focused on journal articles, conference papers, reviews, and book chapters (Table 1).Table 1 Type of retrieved documents
Type of document Frequency Proportion (%)
Conference paper 476 53.1
Article 405 45.2
Review 11 1.2
Book chapter 4 0.4
Total 896 100.0
Although the study sample was defined during the final trimester of 2021, and despite the existence of some studies on the e-learning adoption topic in pre-publication for 2022, a decision has been made to define the top limit of publication date to 2021.
Considering all the imposed criteria to the definition of the study sample, in its final state it was composed of 896 documents, where the majority were conference papers (476) and journal articles (405).
Results
This section holds a detailed presentation of the performed bibliometric analysis outcomes. The results’ presentation starts by characterizing the status of e-learning adoption (3.1) and is followed by the keywords analysis of research hot spots on e-learning adoption. The analysis of the co-authorships and the co-citation are presented in the final two subsections, respectively.
Considered by existing literature as a statistical method through which one can perform quantitative analysis on voluminous sets of scientific data (i.e., research papers), bibliometric analysis aims at delivering insights into the key areas of research surrounding a given concept and predict future research topics [55]. As argued by Van Eck and Waltman [48], despite the consensual value of bibliometric analysis, a significant part of its value is undoubtedly related to the visual perception one can make of the achieved results. For this reason, VOSviewer has been chosen as the software tool that supported this study.
As explained by Meng et al. [26], VOSviewer is a software tool originally developed in 2010 by Nees Jan van Eck and Ludo Waltman at Leiden University's Centre for Science and Technology Studies (CWTS), which allows for the creation of maps based on network data and for the visualization and exploration of those maps. In fact, VOSviewer can extrapolate and create networks of scientific publications and journals, researchers and research organizations, countries, keywords, and/or terms. The items in these networks can be related by co-authorship, co-occurrence, citation, bibliographic coupling, or co-citation links. According to Van Eck and Waltman [48], the added value of this tool is not only its ability to create the abovementioned networks, but also its ability to collect data from multiple scientific databases, such as web of science, Scopus, dimensions, and PubMed files, and reference managers files, such as RIS, EndNote and RefWorks files.
Current status of e-learning adoption
Annual trends in publications
From the analysis of the annual trends of publication (Fig. 1), one can perceive that 2003 was the year in which the first paper on the “e-learning adoption” topic was published in Scopus, and from then on to 2017 the growth rate has been constant but not significant. An example of this is the fact that during the 7 years between 2010 and 2017, the number of e-learning adoption papers that were published in Scopus was averaging the high forties/lower fifties. After 2018, the referred research topic has been targeted by a significant number of researchers and this has translated into exponential growth in the number of papers published in the Scopus database, to the point of reaching almost 140 in 2021.Fig. 1 Annual trends of publications
According to Palvia et al. [38], 2017 was the year in which governments, companies, students, and teachers started to converge on the potential opportunities associated with e-learning. This aggregation of perceptions was the result of a series of education and technical training-related challenges that have arisen as a consequence of the global digital transition movement [8], 47. Also, the 2017–2019 period has been the period in which disruptive technologies such as virtual and augmented reality have witnessed the most significant developments and have started to be perceived as potential (optimal) technologies to use as the basis for novel learning and training initiatives [14], 54.
Distribution of organizations
By analyzing the authors’ affiliations, it is possible to observe that the top 10 organizations whose affiliates published on the e-learning adoption topic hold a total of 95 papers (Fig. 2), thus ensuring 10.6% of the total papers on the referred topic. The Universiti Kebangsaan from Malaysia has the greatest number of publications with a total of 14 papers, representing 1.78% of the used scientific data sample. Indeed, Malaysia is the country of origin of 5 of the top 10 organizations with the biggest number of publications, with an aggregate of 50 papers (5.58% of the study sample), followed by Indonesia (20 papers), Hong Kong (9 papers), and Saudi Arabia (8 papers).Fig. 2 Top 10 institutes according to the number of publications
Muaadh Mukred and Zawiyah Yusof have been the authors from the Universiti Kebangsaan Malaysia with the biggest number of publications, and they collaborated on 5 papers, 3 of them published in peer-reviewed journals [28, 28, 29, 29–31, 31] and 2 of them in conference proceedings [31]. In the referred publications, the authors have focused on the managerial challenges that are posed to education organizations when implementing a combined approach of traditional learning and e-learning and the opportunities that might arise from transposing their data to an electronic record management system (ERMS). Despite having been published in the last 3 years, these publications have recorded 49 citations in Scopus and 82 in Google Scholar.
Distribution of published journals
From the initial 896 publications that composed the study sample, 41% of the global sample (405) are papers published in 146 peer-reviewed journals. At the same time, 146 of these articles were published in the top 10 journals, “Computers in Education” being the journal with the most articles published, with a total of 27 articles (2.74% of the global sample). Nevertheless, 6 of the referred top journals have published more than 10 papers each. Furthermore, six of the top 10 journal are first quartile, two are second quartile, and the other two are third quartile (Fig. 3). Fig. 3 Top 10 journals according to the number of publications
Distribution of published conference papers
By observing the study sample, it is easily perceived that the majority (476) of the inherent publications refer to papers published in conference proceedings. It is also observable that 150 of the conference papers (31.5%) are published in the top 10 conference proceedings (Fig. 4). Lecture Notes in Computer Science, the Proceedings of the International Conference on e-Learning, and the ACM International Conference Proceedings Series are the most relevant proceedings to focus on the e-learning acceptance, adoption, and use topic, by ensuring almost 10% of the overall amount of conference papers.Fig. 4 Top 10 conferences according to the number of publications
Citation and H-index analysis
As argued by Bai et al. [5], the number of citations of a given paper tends to not only ensure the overall value of its (scientific and/or practical) contribution, but also to impact other aspects more related to the research team, such as funding allocations and even hypothetical rewards. From the analysis of Scopus data on e-learning acceptance, adoption, and use, all the inherent publications reached an aggregate of 18,281 citations. Drawing on the data presented in Fig. 5, the number of citations in the top 10 of the countries that most cited these articles was 13,245 citations (72% of the total number of citations), with Taiwan (5253), Spain (1862), and the UK (1650) being the countries that most cited these same publications.Fig. 5 Top 10 countries according to the number of citations
As perceived by the existing literature, H-index is the term used to describe the relationship between the most H papers that were cited, at least, H times, conceptually demonstrating the impact a given author has on his peers [6]. When Hirsch [17] proposed to use the H-index to evaluate the scientific relevance of each researcher, there were multiple arguments against it. However, to this day, H-index is considered a reliable measurement of the researcher’s work and has been adopted worldwide by both education organizations and governing and funding institutions [4].
Taiwan holds the number 1 ranking in terms of H-index (26), followed by Malaysia (19), the UK (18), Spain (17), and the USA, which ranks fifth with an H-index of 16 (Fig. 6). However, when considering the countries with the utmost number of publications on the e-learning acceptance, adoption and use topic, Malaysia ranks first, closely followed by Taiwan. China, which has an H-index of 10, published more than 60 papers and ranks third in the top 10 countries with the biggest publication number (please refer to Fig. 7 for more details), thus allowing us to perceive the possibility that despite producing a considerable volume of publications, China might need to improve their overall quality to the scientific community perceive them as valuable contributes to the development of the abovementioned research topic.Fig. 6 Top 10 countries according to the H-index
Fig. 7 Top 10 countries according to the number of publications
Keywords analysis of research hotspots
After a careful analysis of the context of each record of the study sample, we moved forward and started assessing the content of each of the selected publications, and we did so by analyzing their keywords. Through the analysis of the co-occurrence of keywords, we assess the critical points of research in the scientific investigation of e-learning acceptance, adoption, and use. In the 896 publications that composed the study sample, 4420 keywords are used, of which 3191 are used only once. For VOSviewer to deliver a keywords co-occurrence network capable of being visually analyzed and perceptible, the minimum number of occurrences of a keyword used was adjusted to 10 in VOSviewer, thus thresholding keywords with less than 10 occurrences [55].
The analysis of the keywords co-occurrence network (Fig. 8), in which the keywords are labeled with colored circles and their size is correlated with the appearance of the words in the titles and abstracts of the publications (i.e., the greater the occurrence of the keyword, the greater the size of the text and circle) [48], allows to perceive that the keywords with the biggest frequency are: (a) “e-learning” (896); (b) “students” (355); (c) “technology acceptance model” (305); (d) “learning systems” (252); (e) “education computing” (235); (f) “engineering education” (186); (g) “education” (172); (h) “teaching” (148); (i) “surveys” (135); (j) “TAM” (130); (k) “computer aided instruction” (122); (l) “perceived usefulness” (121); and (m) “perceived ease of use” (112). Furthermore, it was also possible to identify 7 keyword clusters.Fig. 8 The keywords co-occurrence network of e-learning adoption models-related publications
The distance between the nodes represents the strength of the two-node relationship (i.e., a smaller distance reveals a greater strength). The two words’ correlation is represented by the lines, the greater the thickness of the line, the greater the co-occurrence they have [48]. The nodes with link strength greater than 100 are: (a) “e-learning” with “students” (355); (b) “e-learning” with “technology acceptance model” (305),«; (c) “e-learning” with “learning systems” (252); (d) “e-learning” with “education computing” (235); (e) “e-learning” with “engineering education” (186); (f) “education computing” with “students” (185); (g) “e-learning” with “education” (172); (h) “e-learning” with “teaching” (148); (i) “technology acceptance model” with “students” (143); (j) “e-learning” with “surveys” (135); (k) “learning systems” with “students” (133); (l) “e-learning” with “TAM” (130); (m) “computer aided instruction” with “e-learning” (122); (n) “e-learning” with “perceived usefulness” (121); (o) “e-learning” with “perceived ease of use” (112); and (p) “technology acceptance model” with “education computing” (102). A deeper assessment of these relations might be considered as a demonstration that, although practitioners may perceive e-learning as an acquired reality, the truth is that researchers are still more concerned with the acceptance of the technology itself and with the existence of behavioral intentions toward its use, rather than with its actual application and incorporation in all moments of the educational process.
Co-authorship analysis on e-learning adoption
The execution of a research project is a complex task that in order to produce solid and accurate outputs, tends to involve multidisciplinary collaborations between various researchers [18]. Drawing on Liao et al. [22], analyzing the co-authorship networks is a very focused manner to assess the novelty level of a given research topic, for the establishment of a straightforward analysis of the co-authors’ countries of origin, but also the organizations to which the co-authors are affiliated.
Country co-authorship analysis
The country co-authorship analysis demands analyzing which countries have the greatest influence in the field of investigation, as well as the degree of communication between them. The country co-authorship network on e-Learning Adoption models related publications is shown in Fig. 9. The countries with the greatest influence are represented by the size of the nodes. The links, on the other hand, show the cooperative relationship between institutions in the various countries, and their thickness and distance between nodes show the cooperation that exists between countries. The diversification of research directions can be seen by the variety in the number of colors on the map. The countries with the highest number of publications are Malaysia (98) and Taiwan (95), the countries with the uppermost number of citations are Taiwan (5253) and Spain (1862), and the countries with the highest total link strength value are the UK (40) and Malaysia (42). The strongest link strength relationships are between the UK and Saudi Arabia, and Malaysia and Saudi Arabia both with 6.Fig. 9 The country co-authorship network of e-learning adoption models-related publications
Highly cited publications
The scientific community holds a perception that the number of citations of a given paper is directly related to its overall quality, and hence the more the citations, the higher the paper quality. To assess the potential impact that the papers on e-learning acceptance, adoption, and use, which composed our study sample, might have on the development of science, we analyzed the 10 papers with the biggest number of citations. Table 2 displays the title, journal, authors, year, and citation of the most-cited papers. The average number of citations per article is 2.4. The top 10 most-cited papers were published between 2004 and 2010, which might indicate that these are considered the theoretical foundations on the topic. Despite the number of publications on the referred topic having significantly raised after 2011, up to this point there is no reflection of this growth on the overall number of citations. “Computers and Education,” “British Journal of Educational Technology,” “Computers in Human Behavior,” and “Information and Management” are the journals whose papers hold the most citations.Table 2 Top 10 papers citations
Title Journal Authors Year Citation
Explaining and predicting users' continuance intention toward e-learning: an extension of the expectation-confirmation model Computers and Education [21] 2010 667
Investigating the determinants and age and gender differences in the acceptance of mobile learning British Journal of Educational Technology [52] 2009 633
Investigating students' perceived satisfaction, behavioral intention, and effectiveness of e-learning: a case study of the blackboard system Computers and Education [23] 2008 590
The acceptance and use of a virtual learning environment in China Computers and Education [49] 2008 520
Empirical examination of the adoption of WebCT using TAM Computers and Education [34] 2007 474
Gender differences in perceptions and relationships among dominants of e-learning acceptance Computers in Human Behavior [36] 2006 444
Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies Information and Management [37] 2004 411
Understanding e-learning continuance intention in the workplace: a self-determination theory perspective Computers in Human Behavior [39] 2008 401
Extending the TAM model to explore the factors that affect intention to use an online learning community Computers and Education [24] 2010 394
Learning presence: toward a theory of self-efficacy, self-regulation, and the development of a communities of inquiry in online and blended learning environments Computers and Education [42] 2010 349
In his research, Lee [21] aimed to study the determinants of e-learning continuous use by combining three different theoretical models, namely the expectation–confirmation theory, the technology acceptance model, and the theory of planned behavior. The author proposed a novel research model, validated using a sample of over 360 learners, that argued that satisfaction is a very strong determinant of the existence of behavioral intention to continue using e-learning. At the same time, the author was also able to highlight that students’ satisfaction is significantly dependent on their perception of the usefulness of e-learning and the tools that support it. This paper holds the highest citation ranking, with 667 citations.
Drawing on the evolution of mobile technologies and the extreme increase in their global adoption, Wang et al. [52] focused on the application of these technologies in the education context. The use of mobile technologies for education is conceptually perceived as m-learning, and its overall acceptance and use, in 2009, was still something that required further study. By supporting their research hypothesis on an extended version of the unified theory of acceptance and use of technology (that added perceived playfulness and self-management of learning as extra determinants), and on the impact that gender and age might have on the model’s ability to accurately characterize the acceptance and use of m-learning, the authors performed an empirical study involving 330 respondents in Taiwan. The study concluded that performance expectancy and perceived playfulness are triggers to the rise of behavioral intentions toward using m-learning that as learners become older they tend to value more the effort expectancy, social influence has a part in the rise of behavioral intention (particularly for older men) and that despite being considered significant in what concerns its impact on behavioral intention to use m-learning, self-management of learning is considered to be more relevant to women. With over 630 citations, this paper ranks second in the top 10 ranking of most-cited papers on the e-learning acceptance, adoption, and use topic.
Co-citation analysis
According to Liao et al. [22], when in a given citing item references list two items (e.g., articles, journals, authors) are cited at the same, we are in the presence of a co-citation relationship, which can be used—as argued by Donthu et al. [12]—to examine the relationship and structure of research topics. With this in mind, in our research, a focused co-citations analysis has been performed to highlight the possible relations that exist between authors, articles, and journals on the e-learning adoption topic.
Reference co-citation analysis
Transposing the abovementioned to the specific context of research papers, when a given paper simultaneously cites two other papers, then one must consider those two cited papers have a co-citation relationship. The analysis of the co-citations allows researchers to perceive the structure and the development of a given research topic. By dividing the identified papers into clusters, using the network analysis method, it is possible to achieve the full set of characteristics of a research topic. Contrary to what one might think, in the reference co-citation network, the importance of the node—visually represented by its size and color depth—concerns the papers that are more closely related to the e-learning adoption topic (Fig. 10).Fig. 10 The reference co-citation network of e-learning adoption models-related publications
From the interpretation of Fig. 11, it is perceivable that the biggest nodes are Davis et al. [10], Davis [9], Ajzen [2], Venkatesh and Davis [50], and Venkatesh et al. [51]. A straightforward analysis of the highlighted papers shows that these are the original publications of the most relevant technology acceptance, adoption, and use theoretical models.Fig. 11 The journal co-citation network of e-learning adoption models-related publications
Journal co-citation analysis
The analysis of the journal co-citation network is important to understand the general structure of the subject and the characteristics of a journal. In Fig. 11, the network of co-citations of the journals, composed of 91 nodes, is shown. The node size represents the journal's activity, that is, the number of published papers on the topic. The proximity of the nodes allows us to observe the frequency of citation between journals, greater proximity, greater frequency. The journals “Computers and Education,” “Computers in Human Behavior,” “MIS Quarterly,” “Information Systems Research,” and “Information and Management” are the ones with the highest number of papers. Simultaneously, the existence of three clusters is noticeable, one in green that encompasses journals from the education area, one in red that represents the journals from the information systems area, and a third cluster—in blue—that includes the multidisciplinary journals that also cover the education topic. By observing the network, it is also possible to conclude that the proximity of the nodes between the “Computers and Education” and the “Computers in Human Behavior” journals, as well as between “MIS Quarterly,” “Information and Management,” and “Information Systems Research,” represents the increased number of citations between them.
Table 3 lists the top 10 journals with the highest number of citations, as well as the subject area and category. It is noteworthy that “Computers and Education,” “MIS Quarterly,” and “Computers in Human Behavior” are the most-cited journals.Table 3 Top 10 core journals
Journal Subject Citations
Computers and Education Computer science | Computer science (miscellaneous)
Social sciences | Education, e-learning
1372
MIS Quarterly Business, management, and accounting | Management information systems
Computer Science | Computer science applications, information systems
Decision sciences | Information systems and management
918
Computers in Human Behavior Arts and humanities | Arts and humanities (miscellaneous)
Computer science | Human–computer interaction
Psychology | Psychology (miscellaneous)
833
Information and Management Business, management, and accounting | Management information systems
Computer science | Information systems
Decision sciences | Information systems and management
483
Information Systems Research Business, management, and accounting | Management information systems
Computer science | Computer networks and communications, information systems
Decision sciences | Information systems and management
Social sciences | Library and information sciences
325
Management Science Business, management and accounting | Strategy and management
Decision sciences | Management science and operations research
286
British Journal of Educational Technology Social sciences | Education, e-learning 253
Decision Sciences Business, management, and accounting | Business, management and accounting (miscellaneous), Management of technology and innovation, Strategy and Management
decision sciences | Information systems and management
150
Journal of Management Information Systems Business, management, and accounting | Management information systems
Computer science | Computer science applications
Decision sciences | Information systems and management, management science, and operations research
139
Journal of Marketing Research Business, management, and accounting | Business and international management, marketing
Economics, econometrics and finance | Economics and econometrics
122
Discussion of the results
The aim of this research was the execution of a bibliometric analysis of e-learning adoption-related publications. Although the publications on the “e-learning” topic started to appear back in 1989, it is easily perceivable that until 2006 the growth in the number of papers being published on the adoption of this novel learning approach based on digital technologies is not significant. From 2006 to 2016, there was a significant increase in the number of publications; however, it was only after 2017 that the “e-learning adoption” topic started to be at the center of attention for the scientific community and the government bodies across the world, which led to exponential growth in the annual number of published papers.
Malaysia, Indonesia, and Hong Kong are the top 3 countries with the highest number of papers published on the e-learning adoption topic. “Computers and Education,” “Computers in Human Behavior,” and “Computer Applications in Engineering Education” are the top 3 journals with the most published papers, and, in what concerns papers published in conference proceedings, the most important proceedings on the topic (according to the number of published papers) are “Lecture Notes in Computer Science,” “Proceedings of the International Conference on e-Learning,” and “ACM International Conference Proceedings Series.”
The analysis of the number of citations and inherent H-index allows us to perceive that Taiwan, Spain, and the UK are the top 10 most-cited countries and that the 3 countries with the biggest H-index (due to their e-learning adoption-related papers) are Taiwan, Malaysia, and the UK. The countries that cite the most are Malaysia, Taiwan, and China, respectively.
One of the most relevant components of a research paper is the set of keywords that classify it. Therefore, by analyzing the set of papers that composed the sample for this study, it was possible to realize that “e-learning,” “students,” and “technology acceptance model” are the top three keywords, with an aggregate of over 1500 occurrences. Considering that papers tend to have multiple keywords, it is relevant to analyze the strength of the relationship between those same keywords. Hence, the keywords relationships with the greatest strength are “e-learning” with “students,” “e-learning” with “technology acceptance model,” and “e-learning” with “learning systems.”
Concerning the number of citations, the average number of citations for the study sample is 2.4, which indicates that each paper on the e-learning adoption topic is cited more than two times, on average. It is also interesting to state that the most-cited papers on the topic, by far, are documents published between 2004 and 2010 and that despite the number of publications has increased in the last decade this has yet to be reflected in the number of citations in the most recent papers. “Computers and Education,” “British Journal of Educational Technology,” and “Computers in Human Behavior” are the journals that published the e-learning adoption-related papers with the biggest number of citations.
By analyzing the study sample, we were also able to acknowledge that the journals that have published e-learning adoption-related papers might be divided into three clusters, one where “Education” is the focus, one that is more directed at publications from the information systems area, and a third one composed of multidisciplinary journals that encompass “Education” as one the topics on the journal’s scope.
Conclusions
The present paper represents an additional demonstration that a bibliometric analysis might be considered a scientific method that produces valid results, namely a retrospective analysis of rich and vast research areas. As argued through the initial sections of the paper, the bibliometric methodology is establishing itself as a robust research methodology that can be of assistance to both senior and junior researchers.
The achieved results show that the e-learning adoption topic (that includes the acceptance, adoption, and use stages) is indeed relevant, and its overall importance has grown exponentially since 2017, to the point of reaching a sum of over 350 papers published during the last 3 years and collecting over 18,000 citations since the first paper on the topic was published back in 1989.
From a practical perspective, Malaysia and Indonesia were the countries that dedicated the most attention to the abovementioned topic. This has also been reflected in the institutions whose affiliates published the most, and where Malaysian and Indonesian universities are in a clear lead. It is also noticeable that the countries that most-cited papers on the e-learning adoption topic were Taiwan, Spain, the UK, the USA, and Malaysia, respectively. On the other hand, the countries with the biggest H-index (resulting from publications on the referred topic) were Taiwan, Malaysia, the UK, Spain, and the USA, respectively.
The journal with the largest number of publications on the topic is “Computers and Education,” a first-quartile journal published by Elsevier focused on showcasing the existing knowledge and overall understanding of the impact digital technologies might have on education. The top 10 journals with the most publications are responsible for publishing 146 papers on the e-learning adoption topic, thus ensuring 36% of the total amount of journal articles composing the study sample. Through the analysis of papers published in conference proceedings, it was possible to conclude that “Lecture Notes in Computer Science” had the most publications. The top 10 conference proceedings with the most publications have published 31.5% (150) of the global amount of conference papers.
From a theoretical perspective, even though the e-learning adoption has been the focus of attention of multiple researchers worldwide for more than 20 years and practitioners already consider e-learning as something that is completely embedded in current education programs and organizations’ activities, the analysis of the published papers demonstrates that this assumption has yet to be fully proven, as the acceptance and early-stage adoption are the issues that are most commonly addressed, including by the most recent literature.
Limitations and future research
Despite delivering, from our perspective, a bibliometric analysis of the existing literature on the e-learning adoption that represents a valuable insight into the current status of the topic, a deeper analysis of the used approach allows us to identify some limitations. The limitations can be justified by the fact that we only used the Scopus database as the source of information, not including other relevant sources such as WoS, and the fact that we only addressed scientific papers, thus ignoring the existing gray literature on the topic that could bring some interesting insights on the actual adoption and use of e-learning tools and applications. Therefore, future research will aim to broaden the scope of the bibliometric analysis carried out either through the inclusion of new sources of information not only, through the use of articles other than journal articles (conference articles, book chapters, and books), but also by extending the research to, for example, dissertations and theses. Considering the COVID-19 pandemic, which started in early-2020 and still forces students and professors are around the World to use e-learning, we would also believe it would be very interesting to include papers published in 2022 on the topic and, particularly, on the impact that it had to learn (e.g., efficiency, efficacy, universal access, etc.).
Despite its inequivalent value to both e-learning (adoption) researchers and practitioners, we recognize the performed analysis could be improved by including scientific records from other scientific repositories other than Scopus.
Also, after carefully considering the achieved results and highlighted implications, it is possible to perceive the added value of including an entirely novel section with a qualitative analysis (e.g., a Focus Group) on those results. From our perspective, this would allow for highly qualified experts to be able to deliver their own considerations on both the achieved results and on future developments on the e-learning adoption field of study.
Acknowledgements
The authors wish to acknowledge financial support from the project “AquaValor—Centro de Valorização e Transferência de Tecnologia da Água” (NORTE-01-0246-FEDER-000053), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF).
Declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Geoheritage
Geoheritage
1867-2477
1867-2485
Springer Berlin Heidelberg Berlin/Heidelberg
766
10.1007/s12371-022-00766-w
Original Article
A Whale in a Vineyard: Palaeontological Preparation and Education During the ‘Brunella’ Project, a Large-Scale Conservation Effort Focused on a Pliocene Whale in Southern Tuscany, Italy
http://orcid.org/0000-0002-0281-4863
Bisconti Michelangelo [email protected]
12
Scotton Roberta 3
Santagati Pierluigi 4
Foresi Luca Maria 5
Ragaini Luca 6
Tartarelli Giandonato 7
Carnevale Giorgio 1
Buckeridge John 89
Koenig Elizabeth 10
Tabolli Jacopo 11
Nannini Paolo 11
Tarantini Massimo 12
1 grid.7605.4 0000 0001 2336 6580 Dipartimento di Scienze della Terra, Università degli Studi di Torino, Via Valperga Caluso 35, 10125 Turin, Italy
2 grid.410409.8 0000 0000 9905 3022 Paleobiology Department, San Diego Natural History Museum, 1788 El Prado, San Diego, CA 92101 USA
3 Istituto di Studi Archeo-Antropologici, Via delle Cascine 46, 50018 Scandicci (Florence), Italy
4 grid.7778.f 0000 0004 1937 0319 Dipartimento di Biologia, Ecologia e Scienze della Terra, Università della Calabria, Via P. Bucci Cubo 15B, 87036 Rende (Cosenza), Italy
5 grid.9024.f 0000 0004 1757 4641 Dipartimento di Scienze Fisiche, della Terra e dell’Ambiente, Università degli Studi di Siena, Via Laterina 8, 53100 Siena, Italy
6 grid.5395.a 0000 0004 1757 3729 Dipartimento di Scienze della Terra, Università di Pisa, Via Santa Maria 53, 56126 Pisa, Italy
7 grid.6093.c Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy
8 grid.1017.7 0000 0001 2163 3550 RMIT University, 376 Swanston St, Melbourne, VIC 3001 Australia
9 Museums Victoria, 11 Nicholson St, Carlton, Melbourne, VIC 3053 Australia
10 Banfi S.R.L, Castello di Poggio alle Mura, Montalcino, 53024 Siena, Italy
11 Soprintendenza Archeologia, Belle Arti e Paesaggio per le Province di Siena, Via di Città 138/140, 53100 Grosseto, ArezzoSiena, Italy
12 Soprintendenza Archeologia, Belle Arti e Paesaggio per la Città Metropolitana di Firenze e le Province di Pistoia e Prato, Piazza de’ Pitti 1, 50125 Florence, Italy
8 12 2022
2023
15 1 120 6 2022
15 11 2022
© The Author(s), under exclusive licence to International Association for the Conservation of Geological Heritage 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Abstract
In 2007, a whale skeleton was found and excavated in Lower Pliocene sediments at Poggio alle Mura (southern Tuscany, central Italy). This partially complete skeleton is known by the nickname ‘Brunella’. The extracted blocks containing the fossil whale were deposited in a warehouse where they remained for nine years. A new project started in 2016 with the goal of (a) preparing and stabilising the whale bones, (b) studying its anatomy and relationships, and (c) developing educational activities to disseminate scientific information to local communities and tourists. In the years 2016–2019, the ‘Brunella’ Project gave rise to an unprecedented number of activities in terms of scientific and educational efforts. The skeleton was micro-excavated, stabilised and prepared for exhibition; primary and secondary schools as well as university students were involved in educational activities both at the preparation laboratory and in their classrooms. University students were involved in a field school on palaeontological preparation that was active for three years (1 week per year); local populations were invited to visit the laboratory during special Open days where they were able to see palaeontologists working on the project, the whale and the palaeoecosystem in which it ended its life cycle; foreign tourists visited the laboratory and were involved in guided tours; social media were extensively used to disseminate results and advertise opportunities to visit the laboratory; a national TV channel screened a documentary on the whale and the project, disseminating a wealth of scientific results to hundreds of thousands of people. This project represents a unicum in Italy and can be seen as a prototype standard of an ideal process directed at preserving an important palaeontological specimen and, at the same time, enhancing the awareness and enthusiasm of local citizens for their local geoheritage.
Keywords
Cetacea
Education
Field school
Mysticeti
Palaeontology
Pliocene
Preparation methods
Tourism
Banfi s.r.l.Art Bonus Bisconti Michelangelo issue-copyright-statement© The Author(s), under exclusive licence to International Association for the Conservation of Geological Heritage 2023
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pmcIntroduction
Palaeontology plays an important role in our collective imagination and, because of that, fossils may be used as a ‘Trojan horse’ to deliver scientific concepts related to both the evolution of life and the history of territories where charismatic fossils are found.
Dinosaurs gather the attention of almost everyone, even in Italy where dinosaur finds are rare (e.g. Dal Sasso 2003, 2005). This is testified by the unprecedented success of exhibitions focused on dinosaur palaeontology in Modena, Florence, Padova and Naples. However, exhibitions on alternative palaeontological subjects have had success too, suggesting that palaeontology per se is a relevant topic as a cultural attraction. In particular, three exhibitions of fossil cetaceans (primarily involving baleen whales) at Reggio Emilia, Florence and Asti have attracted surprisingly high numbers of visitors recently. The first of these exhibitions focused on a Pliocene right whale nicknamed ‘Valentina’ (Bisconti et al. 2021a; Chicchi and Bisconti 2014; Chicchi and Scacchetti 2003); it was opened between 31 March and 30 June 2009 during which time it was attended by 9000 + visitors. The Natural History Museum of the Florence University opened a new Hall dedicated to the Pliocene Mediterranean Sea in 2016; there, a c. 10-m-long mysticete skeleton was displayed together with a sample of the molluscs that lived associated with the whale’s remains (Cioppi 2014; Cioppi et al. 2011). This exhibition included a documentary and an explanation of the ecosystem that developed in association with the dead whale. This in turn was linked to concepts related to climate change. The Asti exhibition is titled Balene preistoriche (Prehistoric whales in English) and will be open from 30 September 2021 to 30 September 2022. In the first 9 months, c. 13,000 visitors attended to this exhibition.1 These data underline the importance that fossil whales play in people’s imagination and their capacity to attract visitors and school classes. Scientists and museum specialists have been able to deliver concepts related to the history of the relevant territories through these exhibitions thus enhancing local awareness of the geological and biological history of a region.
Based on the above observations, we anticipate that new finds of almost complete whale skeletons will be of interest to the general public, especially in the region where the fossils are found, and this is exactly the case with the skeleton of a Pliocene baleen whale discovered 15 years ago in southern Tuscany that is now known as the #whaleinavineyard and #brunellawhale on Twitter (Scotton et al. 2020).
In February 2007, a fossil skeleton of a baleen whale was discovered in the Pliocene of Poggio alle Mura (southern Tuscany), a locality in the territory of the Montalcino municipality (Siena province). This skeleton was found and excavated by a group of amateur palaeontologists (Gruppo AVIS Mineralogia e Paleontologia Scandicci) under the scientific direction of a technician from the University of Florence (M. Mazzini) (see Batini 2009 for the chronicle of the events). The specimen was discovered in a field close to the famous Brunello vineyards on land belonging to the Banfi S.r.l. company. During field operations, it was clear that a wide array of fossils was in close association with the skeleton, including shark teeth, mollusc shells, fossil wood and a diverse microfossil assemblage. Many international journals reported news about this fossil whale discovery to a global audience because of the location of the site in a field of an internationally renowned wine-maker company and because the timing of the discovery occurred when the new Brunello wine was to be presented to the public (e.g. Anonymous 2007; De Pretis 2007). The fossils were removed from the field after several months of excavation and were deposited within a warehouse close to the castle of Poggio alle Mura (Fig. 1) in the Banfi’s property. The whale bears the number ICCD (Istituto Centrale per il Catalogo e la Documentazione) 09 00000001–18 and was nicknamed (e.g., ‘Brunella’) (Scotton et al. 2020).Fig. 1 The locality of the discovery of ‘Brunella’. A Italian peninsula with Tuscany in orange. B Tuscany outlined showing the location of Poggio alle Mura. C Close-up of Poggio alle Mura and near localities (scale bar equals 5 km). D Aerial view of the locality of the discovery (arrow and whale icon) and, on the background, the Poggio alle Mura castle. E A view of the vineyard castle at Poggio alle Mura
This specimen remained in the warehouse for about nine years. In 2016, a renewed interest in this whale occurred as, under the co-ordination of Massimo Tarantini, the Tuscan Archaeological Superintendency (whose Italian name, at that time, was Soprintendenza Archeologica Toscana) launched a new exploratory project with the following goals: (i) to understand the physical conditions of the whale skeleton; (ii) to begin its preparation and consolidation; (iii) to develop a field school on fossil preparation and restoration in which university students could contribute to the preparation of the whale; (iv) to undertake a preliminary study of the specimen. The Istituto di Studi Archeo-antropologici (ISA), the company Banfi S.r.l., and Montalcino Municipality provided logistic and/or financial support and the project started with local news coverage. 23
In 2018, a new dedicated action (the ‘Brunella’ Project), promoted and coordinated by new State heritage office in Siena (in the person of Massimo Tarantini and, later, Jacopo Tabolli), undertook actions to complete the preparation of the specimen, to continue its scientific evaluation and to present this to the general public. The project was entirely funded by Banfi S.r.l. company4 and represents a unique joint project of this kind between public and private entities in Italy.5 Most of this story was published (see footnote 5) by Scotton et al. (2018, 2020) and part of the work carried out during this project was diffused, in popular terms, as a monthly online diary by the Tuscan Archaeological Superintendency,67 as well as on the website of the Banfi Foundation.8
In the last few years, a strong, multidisciplinary effort was devoted to the scientific study of the whale, its associated biota and the discovery site. The earliest attempts to determine the age of this specimen revealed that the whale-bearing horizon was deposited in the middle Zanclean, c. 4.5–3.8 Ma (Avanzati 2018; Dominici et al. 2019). The age of the specimen is important as it documents that this whale is one of only a handful of Zanclean mysticetes from the Mediterranean.
Based on the morphology of the posterior end of the mandibular rami (including mandibular condyle faced posteriorly and reduced angular process), the ear bones (triangular anterior process of the periotic, transversely elongated pars cochlearis, ventral keel present in the tympanic bulla), the whale was preliminarily assigned to the Balaenopteridae family. Some morphological characters (especially the shape of the periotic) suggest that it may represent a new, basal species of balaenopterid, but the anatomical study is still in progress.
The age of ICCD 09 00000001–18, together with the extraordinary fossilisation of the associated biota, supports the hypothesis that this locality will be of high importance in the determination of (a) taxonomic placement, (b) trophic web, (c) environmental characters of the early Pliocene of the central Mediterranean area. In turn, this may provide crucial information about the recovery of the marine fauna and flora after the end of the Messinian Salinity Crisis and the re-establishment of fully marine conditions at the beginning of the Pliocene in the Mediterranean basin (Carnevale et al. 2019; Vai 2016; Roveri et al. 2014; Riforgiato et al. 2011). Wide-range taxonomic analyses were undertaken on the associated barnacles, nannoplankton, shark’s teeth, trace fossils, fish otoliths, foraminifers, molluscs and the whale skeleton in order to better understand the characteristics of the palaeoecosystem that existed when they accumulated.
Three courses of the field school on fossil preparation and restoration were carried out involving students from many Italian and German universities. Workshops with local primary and secondary schools were undertaken to broadly disseminate the scientific results of the ‘Brunella’ Project. Social media were extensively used to increase the visibility of the actions (Scotton et al. 2020). New hashtags (i.e. #brunellawhale, #pliocenerenaissance, #whaleinavineyard) were created, and others were used to disseminate the information about the activities at the warehouse during the project and to inform tourists and other people about possibilities to visit the preparation laboratory, and to talk to palaeontologists about the fossil whale and its palaeoecosystem (Scotton et al. 2020).
After 3 years of preparation work at the warehouse, ‘Brunella’ become a well-known mysticete nickname in Italy and elsewhere, judging from the thousands visualisations of our posts in the social media (Scotton et al. 2020; see Education and tourism at the fossil excavation lab section in this paper) and is now part of the collective imagination of those living in southern Tuscany. The ‘Brunella’ Project was described upon invitation to the first meeting of the Italian Palaeontological Society that focused on palaeontological preparation and preservation. This presentation was given at Florence in September 2019 as a case study that highlighted the positive interaction between governmental offices and private companies in conserving the remains, whilst ensuring the educational potential of this important fossil and its associated palaeoecosystem (see footnote 5).
Over the last five years, it became clear that ‘Brunella’ acted as the focal point of an unprecedented number of activities in Italy as far as palaeontological heritage is concerned, and formed the basis for a multidisciplinary approach to reach wide-range scientific and educational results. The starting point of this process was, however, the preparation and stabilisation of the whale skeleton that suffered from remaining in a warehouse without climatic control for nine years. The bad effects of this stay were described in detail by Scotton et al. (2020); to cope with them represented one of the major methodological challenges of the entire project.
In this paper, we discuss (1) the methods that were used to prepare the whale skeleton and the associated fossils (in light of very little field information and after a long period in a warehouse without climatic controls), (2) the impact of the ‘Brunella’ Project on tourism in the area and on the population of the relevant territory in southern Tuscany and (3) how an integrated use of social media, public conferences and open days allowed this whale to become part of the collective imagination of the populations in whose territory it was discovered. We conclude that this project is a useful prototype for geoheritage conservation in Italy and beyond.
Institutional Abbreviations
EGPPA, Ente di Gestione del Parco Paleontologico Astigiano, Asti; MSNUP, Museo di Storia Naturale dell’Università di Pisa, Calci; MGGC, Museo Geopaleontologico Giovanni Capellini, Bologna; MGPT, Museo Geopaleontologico dell’Università di Torino, Torino.
Geological and Palaeontological Context
Mediterranean Geodynamics in the Latest Neogene and Its Biotic Impact
In the Mediterranean region, the geological history of the last few million years was punctuated by three main extinction events at c. 5.96, 3.2–3.0 and 2.6–2.4 Ma (Carnevale et al. 2019; Landini and Sorbini 2005; Monegatti and Raffi 2001). The first event is related to the massive ecological changes that occurred at the end of the Miocene; it is known as Messinian Salinity Crisis (hereinafter, MSC) (Vai 2016; Roveri et al. 2014). The MSC has been recognised for many years (Hsü and Cita 1973) and is actively investigated by many research groups (Carnevale et al. 2019 and literature therein). The principal trigger of the biotic extinctions during the MSC is thought to be a tectonic-driven partial or total desiccation of the Mediterranean that led to a massive species loss in c. 600 ky (Krijgsman et al. 1999). Even though the exact sequence of the tectonic and ecological steps that led to this large-scale impoverishment of the marine fauna is not completely known, it is clear that a crisis took place, and that the post-crisis cetacean fauna was taxonomically different from the pre-crisis, Late Miocene assemblage (e.g. Mas et al. 2018a, b; Bisconti 2010, Bisconti 2006; Bianucci and Landini 2002).
Dominici et al. (2019) documented that most of the Pliocene cetaceans from the Mediterranean are from the Piacenzian of Italy, and thus evidencing a gap in our knowledge about the earliest phases of cetacean colonisation of the basin after the end of the MSC. Only a few mysticete specimens are known from sediments with age constrained between 5.3 and 3.8 Ma: the holotype of Balaena montalionis Capellini, 1904 (MSNUP I-12357; Bisconti 2000, 2003), the Gorgognano balaenopterid (MGGC 21,813–21,833; Sarti and Lanzetti 2014), the Ca’ Lunga (MGPT PU 13,810; Ormezzano and Lanzetti 2014) and Chiusano (EGPPA 217.13308; Bisconti et al. 2021b; Damarco 2014) specimens from Piedmont, and the whale from Poggio alle Mura that is the subject of the present work. This observation underlines the importance of ICCD 09 00000001–18 in the reconstruction of the recovery phases subsequent to the end of the MSC event.
Stratigraphy of Poggio alle Mura and Age of the Whale
The site of the discovery (Poggio alle Mura) is part of the Middle Ombrone Basin (hereinafter, MOB; Menacci et al. 2010; Bossio et al. 1991, 1994) that includes several places where numerous finds of shark’s teeth, Pliocene whales, dolphins and sirenians have occurred over the years (e.g. Scotton et al. 2018; Bianucci et al. 2019; Sorbi et al. 2012; Danise 2010; Benvenuti et al. 2007; Sorbi and Vaiani 2007; see also footnote 5) (Fig. 1).
The stratigraphic section at Poggio alle Mura includes the uppermost Miocene sediments and a complete sequence encompassing almost the entire Lower Pliocene (Scotton et al. 2020; Avanzati 2018; Dominici et al. 2019). The Upper Miocene outcrops, represented by several lithologies, indicate a fluvial-lacustrine depositional environment. The earliest basal Pliocene deposition is not represented here because this area was submerged by the sea subsequently and marine Pliocene rests unconformably overlying the fluvio-lacustrine Miocene. Early-to-mid-Zanclean sediments include: (1) sands with large-sized molluscs (e.g. Panopaea sp. and Pelecyora gigas Lamarck, 1818) and lithodome-bearing rocks (Fig. 2A); (2) finer sands with a diversified mollusc assemblage (Fig. 2B); (3) clayey-sands with a shell bed dominated by Helminthia vermicularis Brocchi, 1814 and including the whale-bearing horizon (Fig. 2C); (4) clays with a poor fossil content (Scotton et al. 2020; Avanzati 2018; Dominici and Forli 2021; Dominici et al. 2019). This stratigraphic sequence shows a gradual increase of the depth throughout the Pliocene with parallel changes in the macro- and microfossil assemblages.Fig. 2 Geological and palaeontological evidence from the site of the discovery. A Rock perforated by lithodomes. B A diverse mollusc assemblage (arrowheads indicate some of the numerous specimens in the field). C The Haustator shell bed corresponding to the whale-bearing horizon (white arrowhead indicate Haustator spp. specimens; black arrowheads indicate wood-bearing nodules; orange arrowheads and white lines indicate whale bones). Scale bars equal 25 cm in A and B, and 6 cm in C
Following Bossio et al. (1994), two geological formations are recognised in the Poggio alle Mura area: (a) Conglomerati di Poggio ai Fichi and (b) Argille e argille sabbiose di Pod. Cavallini III, which were deposited in the Zanclean. Following the allostratigraphical concept, the Poggio alle Mura Zanclean is composed of SAS1s and SAS1a sub-synthema (Foglio 320,010—Regione Toscana—SITA Cartoteca). To better constrain the stratigraphic age of the whale-bearing horizon, molluscs, foraminifers, calcareous nannoplankton and magnetostratigraphy have been analysed. The mollusc fauna includes several well-preserved specimens of Tethystrombus coronatus Defrances, 1827 that become locally extinct c. 3 Ma in the Mediterranean basin (Monegatti and Raffi 2001), thus suggesting that the whale-bearing horizon was older than c. 3 Ma. Dominici et al. (2019) found that the Helminthia shell bed (i.e., the whale-bearing horizon) was deposited within the MPL2 zone of Cita (1975) which corresponds to an age interval of c. 5.1–4.45 Ma based on planktonic foraminifers. Avanzati (2018) provided a slightly different assessment based on preliminary analysis of calcareous nannofossils as he found that the whale-bearing, Helminthia shell bed was possibly deposited in the MNN13-MNN14/15 biozones as defined by Rio et al. (1990), corresponding to an age interval of c. 4.6–3.85 Ma. As a whole, the micropalaeontological content of the Pliocene outcrops at Poggio alle Mura supports the attribution of the whale-bearing, Helminthia shell bed to the Lower Pliocene and, more precisely, to the early-to-middle Zanclean. Quantitative calcareous plankton and magnetostratigraphic analysis, which are still in progress, are expected to tighten the relevant age interval.
Field Excavation
Field operations ceased in 2007 following removal of blocks of sediments that included the whale bones (Scotton et al. 2020). Paper and plaster jackets were used to protect the borders of the blocks and the surfaces in which the bones had been partially exposed (Fig. 3). The mandibular rami were removed from the field together with sediment blocks that were protected by plaster jackets and strengthened by steel tubes and wooden posts. The skull-bearing block and a large block including most of the cervical and thoracic vertebrae, two scapulae, a single humerus and many ribs were protected using dedicated wooden boxes strengthened by steel tubes and covered by expanded polyurethane; in these blocks, the surface with the emerging bones was protected with paper and plaster jackets. The two large wooden boxes containing the skull and most of the postcranial skeleton were deposited upside-down in the warehouse. A number of shark’s teeth found in close association to the whale bones, several mollusc shells, and a c. 30-cm-long fossilised fragment of wood were removed from the field and deposited in the warehouse together with the whale skeleton. Unfortunately, the relationships between these fossils and the whale bones were not recorded by the group that performed the excavation. Several pictures were taken during the field excavation and these were made available to the operators working in the ‘Brunella’ Project. Only a few pictures represented the bones in an orthogonal way as most were taken from oblique points of view. Neither a map of bone dispersal, nor any information about the chemicals used in the field to pre-consolidate the specimen were made formally available to the operators of the ‘Brunella’ Project. One of the present authors (M.B.) was present in the field for 2 days during which he took a few orthogonal pictures, sampled the sediment for micropalaeontological analyses, and described and measured the stratigraphic column at the excavation site (Scotton et al. 2020).Fig. 3 Field photographs of the whale skeleton during the 2007 excavation. A Series of partially articulated cervical vertebrae including axis (2nd cervical vertebra: C2), 3rd (C3), 4th (C4) and 5th (C5). B Partial excavation of the ribcage including one scapula, one thoracic vertebra and several ribs. C Right mandibular ramus. D First cervical vertebra (atlas: C1). E Group of lumbar vertebrae in a partially isolated block. F Group of caudal vertebrae surfacing from a completely isolated block whose lateral and inferior surfaces are protected by a plaster jacket. Scale bars equal 10 cm. Pictures by Michelangelo Bisconti
Micro-excavation and Preparation
Overview of the Fossil Preservation Before Preparation
Twenty-five blocks of sedimentary rock, containing whale bones and associated biota were recovered from the field and deposited in the warehouse at the Banfi S.r.l. facility in Poggio alle Mura (Scotton et al. 2020). Some of the blocks were covered by plaster jackets and paper; other blocks were not protected and the bones were visible. The covered blocks were opened by the operators of the ‘Brunella’ Project immediately prior to the preparation process.
Once uncovered, the bones appeared dark brown, their surface details were hard to differentiate as a surface cuticle had developed on them. The bones were partly covered by the sediment, and mollusc shells were very abundant. The block including one of the mandibular rami showed a big fracture approximately at its mid-length (Fig. 4A–C). A natural fault occurred in the largest block (Fig. 4D) and in another block (Fig. 4E).Fig. 4 Examples of preservation of the blocks. A The block including the left mandibular ramus was protected by a plaster jacket and paper interposed between the jacket and the bones; the whole block was reinforced by steel tubes (scale bar equals 50 cm). B The same block after the removal of the plaster jacket and the paper: note the fracture (white arrowheads) vertically crossing the whole block (scale bar equals 50 cm). C Close-up view of the same block showing that the fracture (big white arrowhead) affected the sediment and the whale bone (scale bar equals 10 cm). D View of the big block including most of the ribcage showing a fault (big white arrowheads) crossing the whole block (scale bar equals 50 cm). E Lateral view of a block including lumbar vertebrae and showing a fault (big white arrowheads; scale bar equals 50 cm)
The initial state of each block was recorded through pictures and by filling a standard printed form.
Preparation of the Whale Skeleton
Preparation operations began in 2016 and lasted until 2019. In 2007, most of the blocks had been deposited with the fossil-bearing surface up but the two largest blocks were deposited with the fossil-bearing surfaces down. These blocks included the skull and most of the ribcage. During the ‘Brunella’ Project, both were re-oriented with the fossil-bearing surface up. In the case of the ribcage-bearing block, as the weight of the block was c. 4 t, specialised equipment and personnel was provided by the APICE company, Florence,9 that was able to overturn the whole block without damaging the fossils still covered by paper, plaster jackets and polyurethane (Fig. 5A–C).Fig. 5 Details of preparation of the whale skeleton and the associated biota. A The large box including the ribcage (c. 3.5 t in weight) in the original location in the warehouse as it was deposited after the 2007 excavation (note the polyurethane protecting the bones that is surfacing from the lower part of the box as indicated by the arrowheads). B The large box during rotation (arrowheads indicate the polyurethane covering the whale bones). C The large box after the rotation was almost completed. D One thoracic vertebra in the large box before preparation (arrowhead: note that the bone surface is barely observable; the black colour is due to the oxidisation of the 2007 stabiliser); the ellipses shows a surface apparently free of bones (scale bar equals 10 cm). E The same thoracic vertebra completely polished; the old stabiliser was removed and new stabiliser was distributed; note that the details of the bone surface are now perfectly visible; the ellipses shows that another vertebra was brought to light during the preparation of the previous one at a location where it was not previously noticed (scale bar equals 23 cm). F A group of mollusc shells including Haustator specimens with similar orientation broadly suggested by the arrow (scale bar equals 10 cm). G The same group was enclosed within canvas and stabiliser before being removed as a whole ensemble. H The same group deposited and protected within a dedicate box. I Exceptional preservation of a barnacle (probably Concavus concavus) on the transverse process of a whale vertebra (scale bar in cm). J Barnacle scars observed on a whale mandibular ramus (scale bar in cm)
Once the blocks were ready, the plaster jackets were opened and the polyurethane was removed, the wooden boxes were opened and the operators micro-excavated the blocks to expose bone surfaces, to remove the old and oxidised stabiliser and to better consolidate the bones (Fig. 5D, E). Careful removal of sediment exposed a significant amount of skeletal remains that were previously obscured by the matrix. Almost all the thoracic vertebrae and most of the ribs were discovered through this process.
The oxidised stabiliser was mechanically removed as it had formed a cuticle over the bones. Different experiments with a new stabiliser were carried out to which dilution was the best solution for the whale and the associated molluscs. Stabilisers of various dilution were distributed over sampled bones for different periods of time in order to determine the best strategy to be adopted for stabilisation of the whole skeleton. The new stabiliser was made up by 50% acrylic microemulsion and 50% water and was applied by soft brushes.
The mandibular rami were carefully removed from the blocks and cleaned and stabilised. One of the blocks that originally included the mandibular rami was saved and prepared in order to preserve the original distribution of the mollusc shells under the mandible and in the stratigraphic column. Molluscs filled all the spaces within and between the bones probably also due to post mortem transport operated by bottom currents rather than growing attached to the bones. The shells closely associated to the bones were photographed and mapped before removal and careful storage.
The sediment removed during the preparation process was saved in its entirety for both micropalaeontological and palynological analysis. Thirty-one shark teeth were found in close association with the whale bones; these teeth are currently under study. All teeth but one were removed and carefully stored. The operators of the ‘Brunella’ Project decided to leave a single shark tooth in the same position as it was found to show the close association between the teeth and the whale bones (Fig. 6). We tentatively suggest that the presence of these teeth is related to the shark feeding upon the whale carcass because shark bite marks were found in a number of bones. These bite marks suggest that many, if not all of the teeth, are in situ.Fig. 6 Close-up view of a shark tooth in place at close distance to a skeletal element of ‘Brunella’. Note that several shells are present in the same area. A Photographic plate. B Interpretation. Scale bar in A equals 5 cm
Preparation of the Invertebrate Fossils
The whale skeleton lies on a shell bed in such a way that hundreds of mollusc shells are visible in the blocks that were removed from the site. As the molluscs represent a prominent part of the fossil assemblage, their shells were prepared for study and exhibition following established scientific procedures. A number of mollusc shells were collected to test different chemical and mechanical properties of the fossils. All the specimens were prepared, curated and stored in dedicated boxes. During the preliminary analysis, the enveloping matrix in which the shells were embedded was weakened by a water + acetone mixture that was applied by a soft brush. Occasionally, the mixture was re-applied over a 24-h period to disaggregate the matrix and free the fossils.
As the shells were well-preserved, it was possible to clean these fossils revealing details of the surface ornamentation and permitting taxonomic identification. The preparation process was carried out with soft brushes and probes; any fractures generated during this process were repaired, maintaining the original shape of the shells and their original position in relation to the whale skeleton.
The block in which the left mandibular bone of the whale was preserved was carefully excavated after the removal of the ramus, exposing as many molluscs as possible and permitting analysis of their orientation along both horizontal and vertical axes. A number of nodules including plant remains were also discovered in association with the whale bones and were treated with specific methods (see next section). Both the whale mandibular rami were completely removed from the matrix and prepared; mollusc shells closely associated with the mandibular rami or directly adhering to the surface of bone were cleaned, photographed, and removed. Where possible, these shells were consolidated and stored in dedicated boxes with indication of their provenances.
On several occasions, we realised that groups of shells showed a preferential orientation of their long axes. This preferential orientation is interpreted as being caused by sea bottom or near bottom palaeocurrents. In most of these cases, we prepared, consolidated and left the molluscs in their original position to show this preferential orientation. For those mollusc shells that were removed, we isolated the specimens by excavating a trench of c. 1 cm all around the specimens and then the shells were enveloped under three strata of soft canvas after impregnation with a mixture of 50% acrylic microemulsion and 50% water. The microemulsion consolidated the molluscs and warranted a safe removal of whole groups of shells in their original position after that they were photographed in situ (Fig. 5F–H). The shells were then stored in dedicated boxes.
Approximately 400 individual shells were labeled and photographed in the fossil-bearing blocks in addition to more than 200 specimens removed from the blocks. The taxonomic study of these shells is in progress, and we hope that most of them will be identified at species level in order to provide a high-resolution reconstruction of the malacological community represented in the biota associated to the whale skeleton.
Thirty-six barnacles and barnacle scars were recovered over or among the whale bones (Fig. 5I, J).
All of them were removed from matrix and stabilised with the same procedure adopted for the molluscs. In some cases, a cuticle formed by an old stabiliser was detected that could be dissolved in water (Fig. 7); this suggests that a vinyl stabiliser was used in the field in 2007 to preserve these specimens. The old stabiliser was dissolved and a new stabiliser was added to maintain the integrity of the specimens. A few specimens showed 3D preservation (Figs. 5I and 7). All specimens were studied and their taxonomy and ecological characters were assessed. Unfortunately, no opercular valves were found with these barnacles. They are nonetheless tentatively identified as Concavus concavus Bronn, 1831, which is known from rocks of this age in the Mediterranean. The barnacle scars are important as they show settlement of barnacle cyprids (larvae) after the whale had died, had settled to the bottom and had been stripped of soft tissue. This means that the barnacles did not accumulate around the whale bones in the same manner as most of the mollusc shells, the latter being introduced as mostly disarticulated shells by bottom currents and trapped around the skeleton.Fig. 7 Close-up view of a barnacle on a whale rib showing the cuticle formed by the 2007 stabiliser (white arrowhead) over the barnacle wall (black arrowhead). Scale bar equals 5 cm
Preparation of Palaeobotanical Specimens
During the preparation, several palaeobotanical specimens were found in the block sections and on the surface; these consist of nodules enveloping wood fragments and partial branches of trees (Fig. 8A–D). All the sampled specimens were mapped and their relationships with the whale bones were recorded. Micro-excavation of the nodules was performed by excavating around each specimen at a distance of 5 mm from the external surface of each nodule. The excavation was then expanded and deepened mechanically excavation to detach the nodule. Wood fragments were prepared under a magnification lens using soft brushes. In the case in which the wood fragment appeared particularly fragile and fragmented, we applied several highly diluted doses of the stabilising chemical, allowing full penetration of the preservative within the wood. Three layers of a soft canvas were then applied over the pre-consolidated fragments to maintain integrity during the removal. The removal occurred on specimens following visual and tactile inspections that confirmed that the specimen was fully consolidated. After the detachment, the canvas was carefully removed, and the wood was additionally consolidated by application of the stabiliser by using a soft brush. The specimens were then stored in dedicated boxes. Matrix from the blocks originally removed from the field are stored in dedicated boxes to allow future analyses of pollens and dinoflagellate cysts.Fig. 8 Plant fossils found in close association with the whale bones. A Nodule including a wood fragment (white ellipses) found close to the axis and the other cervical vertebrae (scale bar equals 25 cm). B Close-up view of the same nodule (scale bar equals 10 cm). C A wood fragment (white arrowheads) found close to the right mandibular ramus (scale bar equals 10 cm). D A wood fragment (white arrowheads) found close to an indeterminate bone fragment (scale bar equals 10 cm). E Large wood fragment including a Teredolites trace fossil (scale bar equals 25 cm)
A single, 30-cm-long fragment of Pliocene wood was deposited in the warehouse from the whale excavation of 2007 (Fig. 8E). This specimen bears a Teredolites trace fossil. During the 9 years of its storage within the warehouse, cracks appeared in the wood fragment, breaking it into several parts. The specimen was cleaned, wrapped in aluminium foil, closed within a plaster jacket to preserve it from further degeneration. This kept all the fragments together and saved the sample from variations in temperature and humidity. This conservative approach was the only procedure followed to stop the natural degradation of the specimen. Additional actions are now urgently required to stabilise this Pliocene wood fragment and to stop further degradation.
Sampling
Apart from the vertebrate, mollusc and barnacle specimens described above, we removed c. 225 kg of matrix during the preparation of remains from the site. All the matrix removed during the preparation of the skeleton was stored; sediment samples from areas adjacent to the discovery site and from higher and lower levels in the stratigraphic column were taken in 2007 by one of the present authors (M.B.). The matrix was subdivided into 84 bags and underwent analysis for fish otoliths and microfossils. This work is in progress with 1930 Pliocene fish otoliths currently recovered. All the barnacles, barnacle scars and shark teeth were photographed, labeled, and reported in the map of distribution of the whale bones and photographed. Then, all the specimens were submitted for taxonomic and palaeoecological analyses. One large (c. 25 mm in maximum length) sea urchin spine was detected in the matrix close to the whale bones. It was mapped, prepared, removed and deposited in a dedicated box. Thousands of sea urchin spines are present in the matrix but their preservation is generally poor.
Reconstruction of the Original Deposition of the Whale Bones
Several pictures from the field excavation were provided by the volunteers and a limited number were taken by one of us when in the field (M.B.). Almost all the pictures represent the exposed bones in oblique ways. Only a very general map was produced (by M.B.) during the field work in 2007 outlining the external perimeter of the bone distribution and relationship of the skull and mandibular rami with respect to the ribcage and the disarticulated lumbar and caudal vertebrae and forelimb elements. A few pictures were taken in the field once the blocks had been partly excavated so that it was possible to determine the original disposition of the blocks now in the warehouse. Once the blocks in the pictures were identified, the photographs were treated with the perspective correction instrument of Adobe Lightroom Classic that allowed changing the point of view and transformed oblique pictures into orthogonal ones. In doing that, the programme generates deformations in the objects represented in the picture in the following way: horizontal pictures are deformed with the distances along the vertical axis being changed by the transformation algorithm although the distances along the horizontal axis are not. In this way, and after treating a number of pictures with this method, we obtained several reasonably correct distances between the blocks and, therefore, it was possible to place most of the blocks in the correct position within a map of bone dispersal. To our knowledge, this is the first time that this method is used to the present scope.
Analyses of the Chemicals Used in 2007
The Old Stabiliser
The stabiliser used in 2007 was the Paraloid B72. This information was provided to the operators of the ‘Brunella’ Project by the volunteers of the 2007 excavation. No information about the dilution was provided by the volunteers therefore we did not know the exact concentration of the stabiliser used during the field work. What we observed was that the dilution was insufficient to penetrate the bones, rather it formed a sort of an external cuticle that could be removed using a scalpel during preparation. It is thus very likely that the concentration of the stabiliser used during the field work was too high to penetrate the bones. Soon, the operators became aware that the internal structures of the whale bones were not stabilised and were prone to disintegrate if handled without a new and more efficient stabilisation procedure.
Fragments of the old stabiliser were removed during the preparation of the skeleton (Fig. 9A) and were observed by a RoHS wi-fi digital microscope able to provide HD images (1980 × 1080 pixel). The stabiliser layer was easily identified as it had a distinct colour and density compared to the sediment, fossil bone and fossil wood; if observed from above, the stabiliser layer showed sharp edges at its lateral terminations (Fig. 9B). In cases, it could be easily removed like a piece of adhesive paper tape (Fig. 9C).Fig. 9 Analysis of the old stabiliser by microscopy. A Fragments of cuticle formed by the old stabiliser (scale bar equals 5 cm) as seen from above. B A specimen observed from above showing the sharp edge of the stabiliser layer (indicated by the arrowheads) that allows that lies along the border between the stabiliser and fossil bone (scale bar equals 5 mm). C Three-quarters view of a specimen showing the stabiliser layer looking like paper indicated by the arrowheads (scale bar equals 5 mm). D Sequence through of a specimen showing the thick layer of the old stabiliser, the top of which is separated from the sediment surface by a gap (scale bar equals 5 mm). E Three-quarters view of a specimen in which sediment and old stabiliser are tightly joined but the stabiliser layer is still evident (scale bar equals 5 mm). F A specimen showing the thin layer of the old stabiliser tightly bonded with the sediment (yellow) covering the bone fragments (scale bar equals 5 mm). G Specimen, as observed from above, showing inconsistent distribution of the old stabiliser demonstrated by the presence of an uncovered wooden nodule emerging from the stabiliser layer (scale bar equals 5 mm). H The same specimen as in G as seen from below (scale bar equals 5 mm)
The stabiliser was non-homogeneously distributed during the field operations forming anything from a thin cuticle to a thick layer at different locations. In the cases in which the stabiliser formed a thick layer, a gap developed between the stabiliser and the sediment underneath (Fig. 9D), so that the stabiliser formed a raised layer that was not in contact with the sediment (including mollusc, bone, and wood fragments) thereby not providing its preservation capacity to the fossils. Likely, humidity was trapped between the raised stabiliser layer and the sediment surface and this probably decreased the chemical stability of the fossil bones leading to the damage to the internal structures described above.
In the cases in which the stabiliser formed a thin cuticle, it remained tightly joined with the sediment (including mollusc, bone and wood fragments) (Fig. 9E, F) but it can still be observed as a separate layer from the sediment. It is unclear whether in these cases it was able or not to preserve the internal structures of the bones. Certainly, the stabiliser distributed during the field operations prevented the dispersion of fragments generated by the natural disintegration of the fossil specimens but it was unable to prevent the destruction of at least part of the internal structures of the skeleton. In cases, the stabiliser had not completely covered the specimens (Fig. 9G, H).
The Polyurethane
The original polyurethane was chemically analysed by a private company (Geochim S.a.S., Loc. Sigillo, Perugia province) who provided a report (Rapporto di Prova 64,736, Rif. Interno R.I. 16,605, 2 July 2019) including all the methodologies used. The analyses found presence of antimony, arsenic, mercury, lead, aromatic chemicals in quantities that were tolerated by the Italian law but that were sufficiently high to impose the adoption of protection masks, glasses and body suites for the operators of the ‘Brunella’ Project. Moreover, the results of the analyses strongly suggested that we ask a specialised company to remove the polyurethane from the big box including the ribcage and to clean the whole warehouse. The work made by this company was supervised by the operators of the ‘Brunella’ Project to prevent accidental damage to the fossils.
Conservation Results of the ‘Brunella’ Project
Our subsequent preparation and stabilisation of the whale skeleton found in Poggio alle Mura was successful. The whole skeleton was micro-excavated, prepared and stabilised. All the removed sediment was stored for future analyses. In the process, further portions of the skeleton were exposed that previously had been hidden by the sediment. Tens of shark teeth, barnacles, barnacle scars, trace fossils, wood fragments, and hundreds of mollusc shells were discovered, prepared and stabilised. The sediment was then filtered and treated in search for fish otoliths, sea urchin fragments and other fish remains. Part of the sediment was preserved for further palaeobotanical analyses. The map of the original distribution of the whale bones was digitally reconstructed and is now shown in Fig. 10. This map is a key instrument to understand aspects of the taphonomy of the specimen and will provide students and visitors with useful information about the destiny of this whale after death.Fig. 10 The skeleton of ‘Brunella’ as reconstructed from the present work. The largest blocks in their inferred position at fossilisation with many whale bones exposed. Black spots represent wood fragments. Yellow spots represent barnacles. Scale bar equals 1 m. Note that the skeleton is largely disarticulated and crushed; the peculiar arrangement of the bone distribution is the key for a narrative about the history of this whale from death to burial
The old and oxidised stabiliser was removed and new stabiliser was distributed that maintained the original colours of the fossil bones and allowed the detailed analysis of the bone surface—this being fundamental in the search for trace fossils potentially revealing the existence of a whale fall palaeocommunity. Aspects of the taphonomy of ‘Brunella’ have been provided by Santagati et al. (2021) but additional work is needed to better decipher the wealth of the trace fossils assemblage found in the whale bones that are still under study.
Additional documentation was gathered during the project. Two 3D renderings of the skull and the ribcage of the whale (Fig. 11) were undertaken and a wide-range, aerial photographic documentation of the fossil site and the surrounding areas was performed (Fig. 1D). Moreover, a cast of the skull, as exposed on the surface of the corresponding block, was undertaken, opening the possibility of a new project on the complete extraction and preparation of the skull without losing information on its original disposition.Fig. 11 A photogrammetric representation of the skull of ‘Brunella’ in anterodorsal view
Education and Tourism at the Whale Preparation Laboratory
All the operations directed at the preparation of ‘Brunella’ were planned to incorporate educational activities for a wide spectrum of potential public. The scientific work at the site provided a constant flow of information that was used to assemble a narrative of the history of the whale from death to burial in the context of the palaeoecological reconstruction.
Formal Education
The operators of the ‘Brunella’ Project developed a portfolio of educational laboratories that were shown to the schools of the southern Tuscany during a conference in the historical theatre of Montalcino and by sending brochures via mail. The conference was attended by c. 10 school classes from the elementary schools of the territory with c. 200 students very active in asking numerous questions to the scientific director of the ‘Brunella’ Project who was at their disposal for more than two hours (Scotton et al. 2020). Conferences in the elementary schools were then performed together with combined lessons-and-laboratory experiences at the warehouse in Poggio alle Mura where the ‘Brunella’ Project was being carried out. Lessons included aspects of the geological and palaeoecological history of southern Tuscany, the information that fossils can reveal about the history of the territory, the mollusc shells associated to the whale skeleton, the characteristics of the mysticete whales and the taphonomic history of ‘Brunella’. The participation of young students was enthusiastic. Boys and girls were very active within their classrooms and when visiting the laboratory where ‘Brunella’ was being prepared. They used the microscope to explore the sediment at their disposal and were excited when observing small-sized shark teeth or exquisitely preserved, tiny mollusc shells.
Two high school classes were involved in a project funded by the Italian Government (PON, Candidatura N. 1183 4427, 2 May 201710) on the development of communicative skills concerning the scientific concepts (whale anatomy and evolution, palaeoecology at the discovery site in Poggio alle Mura, preparation methodology) related to the ‘Brunella’ Project and jointly carried out by the operators of the ‘Brunella’ Project and the teachers of the involved high school (Fig. 12A). The students were guided through field activities (surface exploration at the discovery site, sampling of Pliocene molluscs from different stratigraphic settings, conservation works related to the molluscs) in order to give them the possibility to perform first-hand palaeontological experiences. Subsequently, they were asked to write down a short essay and a blog on the ‘Brunella’ Project with data that they were able to collect. The data included pictures and videos made during the preparation process, interviews with the operators and general information on geology and palaeontology at the site. The students worked in small groups under a peer-to-peer approach; they used their own devices (smartphones and tablets) and were allowed to organise their work as they preferred by using digital applications of their choice; the operators of the ‘Brunella’ Project and the teachers involved in the project supervised the work and provided help whenever necessary. The participation of the students was variable revealing that Palaeontology is not interesting for all the young people per se. Many students were interested in (a) learning new communicative techniques, (b) practical activities related to the project, and (c) realisation of the blog by using technological instruments. Some students were very interested in the field work directed at collecting, cleaning and cataloguing fossil shells. Additional pictures of this project can be viewed on the website of the Tuscan Archaeological Superintendency.11Fig. 12 Formal and non-formal education at the laboratory. A Students from a high school working on a project about scientific communication based upon their field experiences on the taxonomy of fossil molluscs. B A typical lesson during the field school in palaeontological preparation; here the head preparator (R.S.) teaches preparation techniques. C Students of the field school working on the preparation of part of the skeleton of the Pliocene whale. D Visitors during a guided tour by an operator (M.B.) during an Open lab event. E Children visiting the laboratory with their families during the Open lab events and asking questions to an operator (M.B.)
University students from Geology and Palaeontology courses at the University of Florence and students from the Università per Stranieri (International Athenaeum) of Siena came to the warehouse and observed the work of the operators during the preparation of the whale and the other associated fossils. They were taught the history of the project and relevant activities, along with the geological and palaeontological importance of the find and its bearing in the international debate about the evolution of baleen whales and the Messinian Salinity Crisis.
A field school on preparation and conservation of palaeontological specimens was active from 2016 to 2019. University, doctoral and postdoctoral students attended this school from many different universities in Italy and Germany. The students received lessons from numerous professors from the Universities of Siena, Pisa, Florence, the Scuola Normale Superiore (Pisa), the Museo di Storia Naturale di Milano, and the Istituto di Studi Archeo-antropologici. A wide range of subjects were covered: geology and stratigraphy of southern Tuscany, whale anatomy and evolution, mollusc evolution, whale taphonomy and whale fall ecology, museum studies, geopalaeontological educational strategies and preparation techniques (Fig. 12B). The students were also able to directly participate into the preparation of ‘Brunella’ by joining the operators in the laboratory (Fig. 12C). They were supervised and taught by the preparator head of the ‘Brunella’ Project and by all the other operators and had constant feedback with professionals. They were also trained in working in the field at the location of the discovery where they studied the stratigraphic section at the site, the different stratigraphic levels observed in the field and the fossil record of the territory. Pictures of the field school were published by Scotton et al. (2020) and can be viewed in the website of the Banfi Foundation.12
Social Palaeontology: a Key Component of Citizen Science Activities
The definition of Social Palaeontology comes from Spanish experiences directed at disclosing the educational potential of Palaeontology at all levels (Torices et al. 2004; Castilla Cañamero et al. 2006). The ‘Brunella’ Project aimed to accomplish this goal by developing different activities involving a broad spectrum of the community. Apart from the formal educational projects dedicated to schools and universities, additional activities were developed that attracted a diverse audience at the laboratory. In particular, considerable success was attained by the Open Lab (Cantiere aperto in Italian) at the warehouse where the ‘Brunella’ Project was being carried out. The laboratory was opened on two occasions and more than 700 visitors came to the warehouse, visited the laboratory and observed ‘Brunella’ and its palaeoecosystem in guided tours provided by the project operators (Fig. 12D, E). Visitors came from the whole of southern Tuscany (Grosseto and Siena provinces) and made tours in small groups in which they could easily and informally interact with the operators by making questions and freely moving through the laboratory. Some teachers brought their students to the laboratory during these days too.
Part of the advertisement for the Open Lab was successfully made through social media (such as Facebook and Twitter). The 29 tweets published by the scientific director of the project (M.B.) received 39,371 views, a result that was well beyond the expectations. Twitter was a useful way to inform tourists from all over the world about the existence of the laboratory and the fossil whale. Poggio alle Mura includes a beautiful castle, a museum of historical and archaeological wine bottles, a restaurant and a wine shop hold by Banfi S.r.l. company and is thus already an attractive centre for international tourists. The operators received many tourists at the laboratory that came there by chance their primary objective being a visit to the Banfi facilities and wine shop. In those cases, the operators stimulated tourists’ attention by placement of blackboards just outside the laboratory with nice sketches and statements about ‘Brunella’ (Scotton et al. 2020). These blackboards attracted many visitors to the laboratory.
After two years, the ‘Brunella’ Project came to an end. The laboratory was visited by more than 2000 visitors and, in many cases, these people (especially non-Italian ones) said that they had received information about ‘Brunella’ from Twitter. Tourists, in small groups, visited the laboratory in guided tours with the project operators providing a commentary in Italian and English. No fee was required for the visits of the Open Lab days and for the visits of occasional tourists.
After the formal end of the ‘Brunella’ Project, a public conference was given at the Accademia dei Fisiocritici in Siena. This is a historical and prestigious institution in which scientists, humanists and non-specialised people are welcome to attend educational programmes and conferences of cultural interest. Many people attended the conference in which the project was explained.
In the end, a documentary on ‘Brunella’ was produced by the Italian National Television (RAI 1) by one of the most celebrated scientific journalists in Italy (Alberto Angela). The documentary was shown on an important TV programme devoted to science popularisation and can be freely watched online.13 The programme was watched by 726,000 people representing a share of 8.23%.14
Future Perspectives
The SARS-CoV-2 pandemic halted further development of the ‘Brunella’ Project for more than 2 years. In retrospect, the work that has been done at the laboratory in the warehouse of Poggio alle Mura was unique for several respects. Its special characteristics included: (a) a joint co-operative effort between a governmental agency and a private company; (b) funding almost completely sourced privately; (c) wide range scientific investigations involving conservation science, geology, stratigraphy, vertebrate and invertebrate palaeontology, micropalaeontology, palaeobotany, and palaeoichnology; (d) broad-scale dissemination of preliminary results and work in progress to a wide audience including school classes and university students, tourists and non-specialised, local public. The educational activities carried out at the laboratory worked well and represented an exploration of the educational potential of the site. The fossil whale represents an exceptional “Trojan horse” enabling operators to deliver a wealth of scientific concepts related to the geological history and the palaeontological content of the territory where the whale was found.
Now that the ‘Brunella’ Project is formally closed, it is to be hoped that an exhibition will be established to permanently illustrate the scientific outputs resulting from the anatomical and phylogenetic analysis of this Pliocene whale, and the study of the palaeoecosystem where it ended its life cycle. A museum concept for ‘Brunella’ is under study for the development of a permanent exhibition at Poggio alle Mura. Hopefully, when the current pandemic ends, ‘Brunella’ and its palaeoecosystem will be once again a centre of geoheritage interest for the whole central Mediterranean basin.
Acknowledgements
The authors wish to warmly thank Renzo Bigazzi, Giuseppe D’Amore and Sylvia Di Marco for their intense work at the warehouse during the preparation of ‘Brunella’: any results would be prevented without their participation. We would like to thank all the students that participated in the field school in the years 2016–2018. Umberto Lamioni and Laura Gherardi provided great help during the preparation operations. Enrico Viglierchio (Banfi S.r.l.), Andrea Pessina (Tuscan Archaeological Superintendency), Giuseppe Venturini (Tuscan Archaeological Superintendency), Luca Pellegrino (Università degli Studi di Torino), Mattia Marini (Università degli Studi di Milano), Claudia Caruso, Cristiano Dal Sasso (Museo di Storia Naturale di Milano), Stefano Dominici (Museo di Storia Naturale, Università degli Studi di Firenze) provided help in several ways and we want to thank them very much.
Author Contribution
In this work, MB and RS designed and performed the experimental work; GC, LR, PS, JB, LMF, PN and GT performed specific experimental works in the framework of the ‘Brunella’ Project; MT, JT and EK contributed to the formal organisation of the ‘Brunella’ Project from the side of the Tuscan Superintendency and Banfi S.r.l. company; MB wrote the paper and provided the images; MB, RS, GC, LR, PS, JB, LMF, PN, GT, MT, JT and EK participated to the discussion and checked the manuscript and the images.
Funding
The project was funded by Banfi S.r.l. through the Art Bonus scheme of the Italian Ministry of Culture and University in the years 2017–2019 (https://artbonus.gov.it/1261-cetaceo-fossile.html, last access: 4 May 2022) and by the Tuscan Archaeological Superintendency in 2016.
Declarations
Conflict of Interest
The authors declare no competing interests.
1 https://www.torinofan.it/eventi/un-viaggio-nel-tempo-con-le-balene-preistoriche/; last access: 22 April 2022.
2 http://www.montalcinonews.com/2016/11/progetto-brunella%E2%80%9C-la-balena-fossile-di-montalcino-scoperta-e-recuperata/, last access: 4 May 2022.
3 http://www.montalcinonews.com/2017/02/con-%E2%80%9Cbrunella%E2%80%9D-torna-alla-luce-un-pezzo-di-storia-di-montalcino/, last access: 4 May 2022.
4 https://artbonus.gov.it/1261-cetaceo-fossile.html, last access: 29 April 2022.
5 http://paleoitalia.org/media/attachments/news_news/221/la_conservazione_dei_beni_paleontologici_SPI.pdf, last access: 4 May 2022.
6 http://www.sabap-siena.beniculturali.it/index.php?it/259/brunella-la-balena-di-montalcino, last access: 22 April 2022.
7 http://www.sabap-siena.beniculturali.it/index.php?it/277/diari; last access: 22 april 2022.
8 https://fondazionebanfi.it/it/progetto-brunella/; last access: 22 april 2022).
9 https://www.apicescrl.it/it/, last access: 22 April 2022.
10 https://www.istruzione.it/pon/avviso_patrimonio-artistico.html, last access: 27 April 2022.
11 http://www.sabap-siena.beniculturali.it/index.php?it/277/diari, last accessed: 28 April 2022.
12 https://fondazionebanfi.it/en/brunella-project/archeobioschool.php, last accessed: 28 April 2022.
13 https://www.youtube.com/watch?v=viOxXpEG0lA; last access: 4 May 2022.
14 https://it.wikipedia.org/wiki/Superquark_natura#Stagione_2020; last access: 4 May 2022.
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==== Front
J Biol Inorg Chem
J Biol Inorg Chem
Journal of Biological Inorganic Chemistry
0949-8257
1432-1327
Springer International Publishing Cham
36484825
1977
10.1007/s00775-022-01977-w
Original Paper
Tryptone-stabilized silver nanoparticles’ potential to mitigate planktonic and biofilm growth forms of Serratia marcescens
Pandey Pooja [email protected]
Meher Kimaya [email protected]
Falcao Berness [email protected]
Lopus Manu [email protected]
http://orcid.org/0000-0001-5001-0272
Sirisha V. L. [email protected]
grid.452882.1 0000 0004 1761 3305 School of Biological Sciences, UM-DAE Centre for Excellence in Basic Sciences, University of Mumbai, Kalina Campus, Santacruz East, Mumbai, India
9 12 2022
114
14 6 2022
19 10 2022
© The Author(s), under exclusive licence to Society for Biological Inorganic Chemistry (SBIC) 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Several microbial pathogens are capable of forming biofilms. These microbial communities pose a serious challenge to the healthcare sector as they are quite difficult to combat. Given the challenges associated with the antibiotic-based management of biofilms, the research focus has now been shifted towards finding alternate treatment strategies that can replace or complement the antibacterial properties of antibiotics. The field of nanotechnology offers several novel and revolutionary approaches to eradicate biofilm-forming microbes. In this study, we evaluated the antibacterial and antibiofilm efficacy of in-house synthesized, tryptone-stabilized silver nanoparticles (Ts-AgNPs) against the superbug Serratia marcescens. The nanoparticles were of spherical morphology with an average hydrodynamic diameter of 170 nm and considerable colloidal stability with a Zeta potential of − 24 ± 6.15 mV. Ts-AgNPs showed strong antibacterial activities with a minimum inhibitory concentration (MIC50) of 2.5 µg/mL and minimum bactericidal concentration (MBC) of 12.5 µg/mL against S. marcescens. The nanoparticles altered the cell surface hydrophobicity and inhibited biofilm formation. The Ts-AgNPs were also effective in distorting pre-existing biofilms by degrading the extracellular DNA (eDNA) component of the extracellular polymeric substance (EPS) layer. Furthermore, reduction in quorum-sensing (QS)-induced virulence factors produced by S. marcescens indicated that Ts-AgNPs attenuated the QS pathway. Together, these findings suggest that Ts-AgNPs are an important anti-planktonic and antibiofilm agent that can be explored for both the prevention and treatment of infections caused by S. marcescens.
Graphical abstract
Supplementary Information
The online version contains supplementary material available at 10.1007/s00775-022-01977-w.
Keywords
Silver nanoparticles
Antibacterial
Antibiofilm
Anti-quorum sensing
Tryptone
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pmcIntroduction
Infections caused by antibiotic-resistant bacterial strains are a leading cause of mortality and have an overall detrimental effect on public health and the health economy worldwide [1]. One of the potential mechanisms of bacteria to attain antibiotic resistance is through biofilm formation. By definition, a biofilm is formed by bacterial colonies with the potential to collectively grow and adhere to biotic or abiotic surfaces into a 3-dimensional network [2]. This complex 3D multi-layered network holds resting bacteria, which have the potential to move on another surface, leading to the formation of a new biofilm on maturing. The extracellular protective layer of biofilms is composed of various proteins, nucleic acids, and other biomolecules. These biomolecules’ network with entrenched cells in the biofilm helps in adherence and protection from harsh environments and bactericides. They also play a key role in the manufacturing of metabolites and nutrition for the bacteria [3, 4]. Biofilms play an important role in shielding bacterial strains against antibiotics. This is achieved by slowing down the process of antibiotic penetration, enzymatically degrading the antibiotics, and supporting bacterial cells to develop resistance at the gene level. Targeting these biofilms can render bacterial cells vulnerable to antibiotics and are a great target for antimicrobial therapy [4, 5]. Laboratories across the world have been exploring different therapeutic strategies including bacteriophage therapy, antimicrobial peptides, surface modulators, natural compounds, and metallic nanoparticles for controlling these bacterial biofilms [6–9].
Among these, the definitive advantage of using metallic nanoparticles is that they display a wide range of physicochemical properties, compared to their bulk analogues and are easily tuneable. Nanoparticles of the size between 1 nm to 200 nm exert unique and novel properties in biological systems [10–14]. These properties are attributed to their high surface energy, minimal imperfections, large proportion of surface atoms, and spatial confinement. Silver has been known to possess strong antimicrobial properties since ancient times [15, 16]. It has been in use for preventing and treating microbial infections for more than 5 millennia. In recent times, silver is also known to prevent viral infections [17]. It is also used in the form of silver-impregnated polymer on medical devices and implants used for surgery. With the advent of nanotechnology, silver nanoparticles (AgNPs) have been investigated extensively in several biomedical applications. Several ‘green synthesis’ approaches utilizing the reducing power of plant polyphenols, peptides, microbes, etc. have been explored with varying degrees and definitions of success [18]. Specifically, proteins and other chemicals present in these biomaterials act as reducing-capping or stabilizing agents during the synthesis process [19, 20]. These biological methods for metallic nanoparticle synthesis have gained credence and momentum over the past decade [21].
For the current study, we made use of tryptone (trypsinized casein) as the stabilizing agent for the silver nanoparticles. Tryptone, by itself, has no toxicity to bacteria. On the contrary, it is a vital component in several nutrient media used to grow bacteria [22, 23]. Nevertheless, it is an excellent stabilizing agent. As we have reported earlier, both gold and silver nanoparticles that are stabilized with tryptone have considerable anticancer potential [11–14]. Given that tryptone by itself has no considerable antibacterial effect, it can be used for surface functionalization of silver. This method would enable pinpointing of the stand-alone mechanism of action of nanosilver in bacterial cells, without the considerable contribution from the stabilizing agents.
In the current study, silver nanoparticles stabilized with tryptone (Ts-AgNPs) were tested for their antibacterial and antibiofilm potential against respiratory tract infection-causing bacteria S. marcescens.
Materials and methods
Synthesis and characterization of silver nanoparticles
Ts-AgNPs were synthesized and characterized as we have reported earlier [14]. Briefly, 1 mg/mL tryptone (pH 12) (SRL, Bangalore, India) was mixed with 1 mM of silver nitrate (SD fine chemicals, Mumbai, India) and the solution was kept for heating for 20 min in the dark till the colour changed to dark brown. The following day, the nanoparticles were collected by centrifugation (26,200×g) for 30 min and the pellets were dried using a Labconco FreeZone 2.5 lyophilizer. The formation of Ts-AgNPs was confirmed by observing the UV–Vis spectrum (Infinite® 200 PRO, Tecan, Switzerland). The core size and shape of the Ts-AgNPs were visualized using a transmission electron microscope. The hydrodynamic diameter and the stability of the synthesized Ts-AgNPs were checked using a Zetasizer Nano-ZS90 size analyser (Malvern Instruments Ltd, Worcestershire, UK). The Fourier-transform infrared (FTIR) spectral analysis was employed to detect the presence of different functional groups on the nanoparticles [14].
Minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) determination assay
To check the antibacterial potential of Ts-AgNPs against S. marcescens, minimum inhibitory concentration was assessed using the microdilution method as mentioned in Clinical and Laboratory Standards Institute [23] guidelines followed by MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide) assay. Briefly, 106 CFU/mL bacterial cells were suspended in microtiter plates containing serially diluted Ts-AgNPs (1−10 µg/mL). The plates were incubated at 37 °C for 24 h and bacterial cell viability was determined using MTT as mentioned in Vishwakarma and Vavilala 2020. To check if Ts-AgNPs have a bactericidal effect on S. marcescens, minimum bactericidal activity was then determined. For this 24 h, Ts-AgNPs treated bacterial cells were taken, Ts-AgNPs were removed, and the bacterial cells were supplied with fresh medium and allowed to grow for another 24 h. After incubation, viable cells were determined by staining with MTT assay as mentioned above [24].
Time–kill curves and colony-forming unit (CFU) assay
To check the potential of Ts-AgNPs to inhibit bacterial growth over time, a time–kill curve was performed. For this experiment, 106 CFU/mL cells were treated with different concentrations of Ts-AgNPs (0–10 MIC) and bacterial growth was monitored from 0 h till 48 h by taking the optical density @595 nm using a spectrometer. Then, growth–kill curves were plotted by plotting the optical density vs time [25].
Colony forming unit assay was performed, by taking 106 CFU/mL culture treated with different concentrations of Ts-AgNPs and incubated for 37 °C for 24 h. Post-incubation, 100 µL of this culture was spread on fresh GM3 medium and incubated further 24 h at 37 °C. Post-incubation, the number of colonies formed were counted manually and compared with untreated control [25].
Intracellular reactive oxygen species (ROS) determination
To check if Ts-AgNPs induce endogenous reactive oxygen species production, this assay was performed. For this experiment, overnight grown culture was further inoculated in fresh GM3 medium and incubated at 37 °C for 3–4 h until the O.D. of the culture reaches to 0.5. Then, 100 µL of this culture was suspended in 96-well microtiter plates, and then, 100 µM 2′,7′-dichlorodihydrofluorescein diacetate (DCFDA) was added. Further, different concentrations of Ts-AgNPs (0–5 MIC) were added into these wells, mixed well, and kept in dark for 3 h and 5 h. The amount of ROS produced was monitored by measuring the fluorescence of highly fluorescent dichlorofluorescein (DCF) formation in presence of ROS by exciting at 485 nm and emission at 535 nm using Tecan UV–Vis spectrophotometer [26, 27].
Hydrogen peroxide sensitivity assay
To validate the antibacterial ability of Ts-AgNPs by inducing ROS, this assay was performed. Briefly, 106 CFU/mL overnight culture was further inoculated in fresh medium and different concentrations of Ts-AgNPs (0-5MIC) were added and incubated further 24 h at 37 °C. Post-incubation, 100 µL of this culture was spread on GM3 agar plate. A sterile 6 mm Whatman paper disk was placed in the middle of the plate and 10 µL of 3% hydrogen peroxide was added to the paper disc placed at the centre. These plates were incubated at 37 °C for 24 h. After incubation, the zone of inhibition was measured. The experiment was repeated thrice for each concentration of the Ts-AgNPs and untreated controls [28].
Biofilm Inhibition studies
The property of silver nanoparticles to inhibit the formation of biofilms was assessed using biofilm inhibition assay. Bacterial culture (overnight grown) was sub-cultured in fresh GM3 media and allowed to grow until an O.D. reaches to 0.5. This culture was further treated with different concentrations of Ts-AgNPs (0–100 µg/mL) and incubated for 24 h, 37 °C, 120 rpm. The planktonic cells and unadhered cells were removed, washed three times using distilled water, and dried for 10 min at room temperature. After drying, 200 µL of 1% crystal violet stain was added to each well and placed at room temperature for 30 min. The excess stain was washed off and 200 µL of ethanol (100%) was added to all wells. The O.D. was measured using a spectrophotometer at 595 nm [29].
Cell-surface-hydrophobicity assay
The effect of Ts-AgNPs on the hydrophobicity of bacterial cells to inhibit biofilm formation was evaluated using the Bacterial Adherence to Hydrocarbon (BATH) Assay. A 106 CFU/mL cells were incubated with different concentrations of Ts-AgNPs (0–100 µg/mL) for 24 h at 37 °C, 120 rpm. After incubation, absorbance values were obtained at 600 nm. The reaction mixture was then transferred to glass tubes with equal volumes of absolute toluene in each tube. After vigorous shaking for 30 sec, the tubes were incubated for 5 min at room temperature for phase separation. After separation, the aqueous layer was collected into a 96-well plate and the optical density was measured at 600 nm [25].
Biofilm eradication assay
This assay is carried out to examine the ability of Ts-AgNPs to eradicate or disintegrate preformed biofilms. Approximately 106 CFU/mL of cells were treated with 15 mM hydrogen peroxide and incubated for 24 h at 37 °C to form a biofilm. After 24 h of incubation, planktonic cells were removed slowly and fresh medium with varying concentrations of Ts-AgNPs was added to the wells and incubated for 24 h at 37 °C, 120 rpm. Further, unadhered cells were washed using distilled water and biofilms in the wells were quantified using the crystal violet assay as mentioned above. The assay was performed thrice, and percentage eradication was graphically represented against Ts-AgNPs’ concentration [30, 31].
Quantification of extracellular polymeric substance (EPS)
Extracellular polysaccharide is the matrix that helps in the protection as well as maintains the structural and functional integrity of the biofilm. To examine the ability of Ts-AgNPs in distorting the EPS layer, this assay was performed. In this assay, preformed biofilms were treated with different concentrations of Ts-AgNPs and incubated at 37 °C for 24 h. After 24 h, equal volumes of absolute acetone and 10% trichloroacetic acid (TCA) were added to the EPS extract and incubated at 4 °C overnight. After incubation, the tubes were centrifuged at 8000 rpm for 5 min at 25 °C. The supernatant was gently discarded and the pellet was air dried. The weights of the pellets of both untreated and Ts-AgNPs-treated samples were measured and the results were represented as a graph of the total weight of EPS against the concentration of Ts-AgNPs [32].
eDNA quantification
Extracellular DNA (eDNA) isolation was performed using a modified protocol by Wang et al. [33]. Preformed biofilms in microtiter plates were treated with different concentrations of Ts-AgNPs and eDNA was extracted from the EPS layer by incubating the biofilms at 4 °C for 1 h, after which 1 µL of 0.5 M of EDTA was added to each well. The contents of wells were carefully transferred into the microfuge tubes and centrifuged. The pellet was resuspended into 50 mM Tris HCL (pH 8). eDNA was then isolated by adding an equal volume of phenol:chloroform:isoamyl alcohol (25:24:21 and centrifuged for 5 min at 10,000 rpm. To the aqueous layer, three equal volumes of ice-cold ethanol along with 1/10th amount of sodium acetate (pH 5.2) were added and stored overnight at − 20 °C. After incubation, tubes were centrifuged at 18,000g, 4 °C for 20 min. The pellet was allowed to dry and resuspended in Tris:EDTA buffer. The concentration and purity of the eDNA extracted were calculated spectrophotometrically by measuring the absorbance ratio A260/A280 using nanoquant200©.
Fluorescent microscopy analysis
To validate the biofilm eradicating potential of Ts-AgNPs, fluorescence microscopy analysis was carried out. Biofilms were preformed on the coverslips and these pre-existing biofilms were then treated with ½ MIC and MIC of Ts-AgNPs for 24 h at 37 °C. Post-incubation, the biofilms were washed with phosphate buffer saline (PBS) twice. Then, the biofilms were stained with 10 µ/mL of propidium iodide and kept in the dark for 20 min. After staining, the coverslips were washed with Milli Q water and mounted on the slides. Slides were observed under fluorescent microscopy in TRITC filters at 100 X with oil immersion [34].
Analysis of quorum-sensing pathway-induced virulence factors
Quorum sensing pathway is known to induce various virulence factors in S. marcescens and contribute to its pathogenicity. To check the effect of Ts-AgNPs in inhibiting these virulence factors production, quantification of urease, protease, lipase, hemolysin, and prodigiosin pigment production was carried out.
Urease assay
For urease assay, overnight grown culture of Ts-AgNPs treated/untreated cells was centrifuged at 8499 × g at 25 °C for 5 min and 0.1 mL of supernatant was treated with 0.5 mL of 2% urea, incubated at 37 °C for 3 h. Post-incubation, the amount of ammonia released was quantified by adding 0.1 mL of Nessler’s reagent and incubated for another 5 min at room temperature. Urease activity was quantified by measuring the O.D. at 530 nm using a UV–Visible spectrophotometer [35].
Protease assay
Azocasein assay was performed to determine the proteolytic action of S. marcescens in the presence/absence of Ts-AgNPs. For this experiment, 75 µL of Ts-AgNPs treated/untreated cell-free supernatant was reacted with 125 µL of azocasein substrate (0.3% azocasein in 0.05 M Tris–HCl + 0.5 mM CaCl2). The mixture was then incubated for 15 min at 37 °C. The reaction was then stopped by adding 600 µL 10% trichloroacetic acid and incubated at − 20 °C for 20 min. The mixture was then centrifuged at 8000 rpm for 5 min. Then, 700 µL of NaOH was added to the supernatant and the protease activity was measured at 534 nm [36].
Hemolysin assay
Ts-AgNPs treated and untreated bacterial cultures were centrifuged at 11,000 rpm for 20 min at 4 °C. Then, 900 µL of fresh sheep blood suspension (2% sheep blood erythrocytes in PBS; pH 7.4) was added to 100 µL of supernatant. The mixture was incubated at 37 °C for 1 h. Then, the suspension was centrifuged at 3000 rpm for 10 min and the amount of hemoglobin released in the supernatant was measured at 530 nm. Erythrocytes suspended in distilled water served as positive control and erythrocytes suspended in PBS served as a negative control for this experiment [37]. Hemolysin activity was determined using the formula below:Percentage lysis=A530of sample-A530of background/A530of total-A530of background∗100.
Lipase assay
Overnight grown Ts-AgNPs treated and untreated bacterial cultures were centrifuged at 10,000 × g for 10 min at 4 °C. Pellet was dissolved in 0.5 mL of Tris–EDTA buffer (pH 8.0), and the resultant suspension was sonicated to release lipase from the cells. After sonication, the suspension was centrifuged, and the supernatant was collected to check lipase activity. To 0.1 mL of cell-free supernatant, 0.9 mL of p-nitrophenyl palmitate (pNPP) substrate mixture (solution A- 3 mg of pNPP in 1 mL isopropanol and solution B- 10 mg of gum arabic and 40 mg of Triton-X in 9 mL of 50 mM Tris–HCl buffer pH 8) was added, and incubated for 20 min at 60 °C in a shaking water bath. The lipase activity was measured spectrophotometrically at 400 nm [38].
Prodigiosin pigment production
Overnight grown culture was further inoculated in fresh GM3 medium, treated with different concentrations of Ts-AgNPs, and incubated for 24 h at 37 °C. The cells were then harvested at 10,000 rpm for 10 min. Prodigiosin pigment from S. marcescens cell pellet was extracted using 1 mL of acidified ethanol. The extracted pigment was quantified at 535 nm using UV–visible spectrophotometer [36].
Effect of Ts-AgNPs on swimming and swarming motilities of S. marcescens
The effects of Ts-AgNPs on S. marcescens swimming and swarming motilities were assayed. For this experiment, GM3 media with 0.3% and 0.5% agar plates without and with Ts-AgNPs (1/8 MIC, ¼ MIC, and ½ MIC) were prepared and 5 µL of S. marcescens culture was placed at the centre of the plate and incubated at 37 °C for 24 h in a plate incubator. After 24 h, the swimming and swarming motility of S. marcescens was measured in millimetres (mm) and reported in comparison to untreated controls [39].
Results
Synthesis and characterization of Ts-AgNPs
As we have reported [14], UV–Vis spectral analysis showed the maximum peak at 408 nm confirming the formation of the Ts-AgNPs. Transmission electron microscopy revealed ~ 18 nm core size and spherical morphology of the particles. The hydrodynamic diameter of the Ts-AgNPs was found to be ~ 170 nm and the zeta potential of − 24 ± 6.15 mV confirmed the stability of the nanoparticles. The presence of different functional groups like amines, amides, aldehydes, and aromatic compounds indicated that tryptone played a crucial role in capping and stabilization of the Ts-AgNPs [14].
Antibacterial studies
The minimum inhibitory concentration (IC50) of Ts-AgNPs against S. marcescens was found to be 2.5 µg/mL. Ts-AgNPs showed a bactericidal effect on S. marcescens, indicating that Ts-AgNPs were very effective in killing the bacteria and can help treat S. marcescens-associated infections.
Growth kill assay was performed to monitor the bacterial growth with respect to varying time points and concentrations of Ts-AgNPs. The graph obtained showed that there was a significant decrease in the number of viable cells of S. marcescens as the concentration of Ts-AgNPs increases (Fig. 1A). Ts-AgNPs significantly affected the log phase growth of this bacteria showing its bactericidal effect. Initially, the growth pattern was similar for all concentrations, but as the time increases, there was a gradual decrease in the number of viable cells. After 24 h, a steady growth pattern was seen in the untreated sample, whereas for treated samples, the number of viable cells decreased significantly with the increased concentration of Ts-AgNPs in a dose-dependent manner. A stark decrease in growth was observed from MIC till 10 MIC of Ts-AgNPs for S. marcescens (1A).Fig. 1 Antibacterial potential of Ts-AgNPs against S. marcescens. A Time–kill curves. B CFU assay (C1–C6). Representative images of S. marcescens's ability to form colonies in the presence/absence of Ts-AgNPs. Data are the means of three independent experiments ± SE. (p < 0.05)
Moreover, it was observed that Ts-AgNPs significantly affected the colony-forming ability of S. marcescens cells. It was observed that when the cells were incubated with different concentrations of Ts-AgNPs, there was a significant decrease in the CFU in this bacterium (Fig. 1B). At 1/4th and ½ MIC of Ts-AgNPs, there was a significant decrease in the number of bacterial colonies formed by S. marcescens as compared to the untreated control sample, whereas at MIC till 5 MIC of Ts-AgNPs treated bacteria showed no colonies (Fig. 1C). This indicates that Ts-AgNPs has a significant effect on colony-forming ability of S. marcescens in a concentration-dependent manner.
Intracellular ROS quantification
To explore the probable mechanism of Ts-AgNPs-induced bacterial death, intracellular ROS was quantified. It was observed that Ts-AgNPs inhibited bacterial growth by inducing ROS. Ts-AgNPs-treated bacteria showed a significant increase in ROS accumulation in a dose-dependent manner over time as compared to control. There was a maximum of ~ 2.5-fold increase in ROS production after 1 h Ts-AgNPs treatment. While at 3 h and 5 h, there was a maximum of 1.57- and 1.76-fold increase in ROS was observed in Ts-AgNPs-treated cells as compared to untreated control (Fig. 2A), indicating that Ts-AgNPs changing the redox environment in S. marcescens that led to bacterial cell death.Fig. 2 Ts-AgNPs potential to induce reactive oxygen species in S. marcescens. A Quantification of intracellular ROS and B H2O2 sensitivity assay (C1–C4). Data are the means of three independent experiments ± SE. (p < 0.05)
To substantiate the ability of Ts-AgNPs to induce ROS and kill bacteria, H2O2 sensitivity assay was performed. The results obtained clearly showed that with increased concentration of Ts-AgNPs, there was a gradual increase in the bacterial growth inhibition as indicated by increased diameter of the zone of inhibition (Fig. 2B). As compared to plain H2O2 disk, there was a 1.5-fold increase in the diameter of bacterial growth inhibition at MIC of Ts-AgNPs indicating the potential of Ts-AgNPs in inducing ROS and oxidative damage to S. marcescens (Fig. 2C1–C4).Fig. 3 Inhibition of biofilm formation by Ts-AgNPs in S. marcescens. A Biofilm-inhibition assay. B Cell-surface-hydrophobicity assay. Data are the means of three independent experiments ± SE. (p < 0.05)
Biofilm-inhibition assay
Ts-AgNPs-treated cells showed decreased biofilm formation as compared to control in a dose-dependent manner. It was observed that Ts-AgNPs showed 29–90% of inhibition of biofilm formation in S. marcescens at 1–100 µg/mL concentrations (Fig. 3A). This result indicates the potential of Ts-AgNPs to efficiently prevent the bacteria from adhering to the surface and initiate biofilm formation.
To determine the mechanism by which Ts-AgNPs inhibit biofilm formation, the cell surface hydrophobicity assay was performed. The graph obtained showed that with increased concentration of Ts-AgNPs, there was a gradual decrease in the hydrophobicity of the S. marcescens cells. Treated cells showed 15–70% reduced cell surface hydrophobicity at 1–100 µg/mL of Ts-AgNPs as compared to control (Fig. 3B). This indicates that Ts-AgNPs effectively altered the hydrophobic nature in this bacterium, which is a crucial determinant in the initial attachment of the cells to the substrate in the course of forming a biofilm. Therefore, Ts-AgNPs can be developed into a promising antibiofilm agent to prevent bacterial biofilms.
Biofilm eradication assay
Eradication of preformed biofilm by Ts-AgNPs was determined by performing this assay. The results showed that S. marcescens preformed biofilms were effectively distorted with increased concentration of Ts-AgNPs. Bacteria treated with 5–25 µg/mL of Ts-AgNPs showed 14%, 17%, and 53% distortion of biofilms, respectively. While, 53%, 55%, and 63% distortion were observed at 50 µg/mL, 100 µg/mL, and 250 µg/mL of Ts-AgNPs-treated cells as compared to control (Fig. 4A).Fig. 4 Eradication of preformed biofilms of S. marcescens by Ts-AgNPs. A Biofilm eradication assay. B EPS quantification. C eDNA quantification. Data are the means of three independent experiments ± SE. (p < 0.05)
To determine the ability of Ts-AgNPs in distorting this outer protective covering, quantification of EPS content was performed. It was observed that after centrifugation, the pellet of Ts-AgNPs-treated samples gradually decreased in a dose-dependent manner in comparison to the untreated sample. There was approximately 78% and 82% decrease in the weight of pellets at 50 µg/mL and 250 µg/mL of Ts-AgNPs, respectively, as compared to the control samples (Fig. 4B). This confirms the ability of Ts-AgNPs in disrupting the EPS layer of preformed biofilms in S. marcescens.
In the aim to determine the mechanism by which Ts-AgNPs distort the EPS covering in S. marcescens, quantification of eDNA of the EPS layer was carried out in both Ts-AgNPs treated and untreated samples. It was observed that the amount of eDNA isolated from the cell-free supernatants of Ts-AgNPs-treated samples of S. marcescens gradually decreased as compared to the untreated sample. Ts-AgNPs-treated cells showed a 4.3-fold decrease in the eDNA content of the EPS layer at 25 µg/mL. A maximum of 6.6-fold decrease in eDNA was observed at 250 µg/mL concentration of Ts-AgNPs, indicating their potential in degrading the eDNA component of the EPS layer and dissolving the biofilms (Fig. 4C).
Microscopy analysis
The ability of Ts-AgNPs in distorting preformed biofilms is further validated by fluorescence microscopy analysis. Preformed biofilms were stained with propidium iodide, showed densely packed aggregates of bacterial cells with intense fluorescence (Suppl Fig. 1A). While, the ½MIC, MIC, and 2 MIC Ts-AgNPs-treated preformed biofilms showed distorted biofilms with loosely packed small clusters of bacteria (Suppl Fig. 1B–D) validating the effect of Ts-AgNPs in eradicating matured biofilms.
Anti-quorum-sensing studies: quantification of virulence factors
It was observed that Ts-AgNPs significantly reduced QS-induced virulence factor production in S. marcescens. Urease activity was reduced to 48%, 82%, and 90% at 10 µg/mL, 25 µg/mL, and 100 µg/mL of Ts-AgNPs (Fig. 5A). ExoProtease activity was reduced to a maximum of 70–81% at 2.5–50 µg/mL concentration of Ts-AgNPs (Fig. 5B). Similarly, lipase activity was significantly reduced with increased concentrations of Ts-AgNPs. It was observed that about 56% reduced lipase activity was observed from 2.5 to 50 µg/mL of Ts-AgNPs as compared to untreated control (Fig. 5C). Prodigiosin, an important pigment produced by S. marcescens, was significantly decreased to about 30–77% in 25–100 µg/mL of Ts-AgNPs-treated bacterial cells (Fig. 5D). Another important virulence factor produced by S. marcescens in hemolysin. Ts-AgNPs-treated cells showed ~ 20–60% reduced hemolysin production (Fig. 5E). These results indicate the promising potential of silver nanoparticles in attenuating the quorum-sensing pathway and its associated pathogenicity.Fig. 5 Anti-quorum-sensing potential of Ts-AgNPs. A Urease assay, B protease assay, C lipase assay, D prodigiosin pigment production, and E hemolysin assay. Data are the means of three independent experiments ± SE. (p < 0.05)
Swimming and swarming motility
Ts-AgNPs significantly reduced the motility in S. marcescens. Swimming motility in S. marcescens was tested using sub-lethal concentrations of Ts-AgNPs. It was observed that 1/8 MIC Ts-AgNPs reduced the swimming motility of S. marcescens, while ¼ MIC- and ½ MIC-treated cells showed complete inhibition of swimming motility as compared to control (Fig. 6a2, a3, a4) and as compared to untreated control (Fig. 6a1). Ts-AgNPs showed reduced diameter of motility with increased Ts-AgNPs concentration. The diameter of swimming motility was 30 mm in 1/8th MIC, 10 mm in 1/4th MIC, and 0 mm in ½ MIC as compared to 38 mm in control cells (Fig. 6a5).Fig. 6 a Swimming motility of S. marcescens in the absence/presence of Ts-AgNPs. a1 Control, a2 1/8th MIC Ts-AgNPs, a3 1/4th MIC Ts-AgNPs, a4 ½ MIC Ts-AgNPs, and a5 diameter of swimming motility in presence of Ts-AgNPs. Data are the means of three independent experiments ± SE. (p < 0.05). b Swarming motility of S. marcescens in the absence/presence of Ts-AgNPs. b1 Control, b2 1/8th MIC Ts-AgNPs, b3 1/4th MIC Ts-AgNPs, b4 ½ MIC Ts-AgNPs, and b5 diameter of swimming motility in presence of Ts-AgNPs. Data are the means of three independent experiments ± SE. (p < 0.05)
Similarly, even swarming motility of S. marcescens was also decreased drastically with Ts-AgNPs treatment in a dose-dependent manner (Fig. 6b1–b4). Control cells showed a diameter of 40 mm of swarming motility, while 1/8 MIC Ts-AgNPs-treated cells showed a diameter of 25 mm. Both ¼ MIC and ½ MIC Ts-AgNPs-treated cells showed complete inhibition of swarming motility in S. marcescens (Fig. 6b5).
Discussion
Multidrug-resistant bacteria have been causing severe infections that claim 13 lakh lives a year; of this, over 3.9 lakhs are just in South Asia alone. The ongoing COVID-19 pandemic has also led to an increase in the usage of antibiotics [40]. One of the major factors driving antibiotic resistance is the formation of biofilms by these bacteria [41–45]. The ability of bacteria to form biofilms is one of the main virulence factors that interfere with antibiotic activity and immune defence response mechanisms [43, 46, 47]. Among the biofilm-forming bacteria, S. marcescens showcases many virulence factors that are responsible for severe life-threatening infections [48]. It is a causative agent of wound infection, pneumonia, and urinary tract infection (UTI). The ability to form biofilms along with virulence factors plays a key role in providing this bacterium with resistance to antimicrobial drugs [49, 50]. As of now, no known drugs can mitigate S. marcescens biofilms, and it has attained a superbug status [51].
Antimicrobial treatment strategies have been bolstered by recently developed techniques, such as antibiotic cocktails, bacteriophage therapy, nanoparticles-based methods, natural compounds, and antimicrobial peptides [29, 52–56]. There has been significant research on the antibacterial properties of silver ions. In particular, some silver ions are highly efficient against both Gram-positive and Gram-negative bacteria. Such silver ions come from silver sulfadiazine and dissolved silver nitrate (AgNO3). On the other hand, the highly reactive nature of silver ions drives down its antibacterial efficacy. With the rapid growth of nanotechnology in recent years, it is now possible to fabricate a variety of silver nanoparticles with increased antimicrobial efficacy due to their small size [57]. In the current study, Ts-AgNPs have been shown to be a potent antimicrobial agent for topical administration against multidrug-resistant bacteria in preclinical settings [58]. However, lack of colloidal stability, time-consuming synthesis procedures, cost, etc. pose major challenges in developing them for industrial and commercial applications [59]. Here, using tryptone as a stabilizing agent, we sought to mitigate the problems associated with colloidal stability, undesired toxicity, cost, time of their synthesis, and adverse effects on the ecosystem. Moreover, tryptone is known as a vital component in the nutrient media used for bacterial growth, and as such, it has no antibacterial effect. In the current study, using a combination of biochemical, microscopical, and cellular assays, highly efficacious antibacterial and antibiofilm activity of Ts-AgNPs in S. marcescens was demonstrated. As mentioned earlier, we took a facile synthetic approach for the synthesis of Ts-AgNPs and characterized them using an assortment of spectroscopic analyses and transmission electron microscopy [14]. First, the effect of these Ts-AgNPs on the planktonic growth of S. marcescens was carried out. Antibacterial activity of Ts-AgNPs was evidenced by lower MIC values and delay in the bacterial growth after the treatment with the nanoparticles (Fig. 1). Compared to most of the previous reports using different stabilizing/capping agents, the MIC values of Ts-AgNPs are substantially lower, indicating their superior efficacy [60–62]. It is documented earlier that the inhibitory effect of AgNPs on Gram-negative bacteria is more pronounced as compared to Gram-positive bacteria. One of the potential mechanisms that lead to this enhanced antibacterial activity in Gram-negative bacteria is the adsorption of the ionic form of silver (Ag +) by cytoplasmic membranes which ultimately leads to the destruction of the cell membrane, causing bacterial content leakage, and death [63]. Substantiating previous findings, the elevated levels of ROS by Ts-AgNPs observed in the current study, probably due to their interaction with the sulfur groups of some crucial proteins, facilitated bacterial death [64].
These results prompted us to investigate the impact of the Ts-AgNPs on the biofilm-forming ability of S. marcescens. It was observed that Ts-AgNPs efficiently inhibited biofilm formation in a concentration-dependent manner (Fig. 3A). Further, as demonstrated by a cell surface hydrophobicity assay, the Ts-AgNPs altered the hydrophobic properties of the bacterial cell wall, contributing, at least in part, to the inhibition of biofilm formation, demonstrating its prophylactic potential (Fig. 3B). On a therapeutic perspective, Ts-AgNPs effectively distorted preformed biofilms as evidenced via the interruption of EPS production (Fig. 4). These finding supports previous findings about the ability of AgNPs in inhibiting bacterial biofilms but with a considerably higher efficacy [65–73]. Concerning its mechanism of action, Ts-AgNPs likely diffuse through the EPS layer of the biofilm, and induced ROS production, prompting bacterial death, and thereby reducing EPS layer formation and dissolution of the biofilms. The antibiofilm ability of Ts-AgNPs to diffuse through the EPS layer has been reported earlier [74].
It is known that an important contributor to bacterial biofilm formation is their intercellular communication mechanism which is the quorum-sensing pathway. The quorum-sensing (QS) pathway, operated via chemical signals production, controls the bacterial response to extracellular signalling molecules and induces microbial virulence factors [75]. Ts-AgNPs demonstrated their ability to inhibit the production of QS-induced virulence factors. Specifically, as we observed, sub-MIC of the Ts-AgNPs efficiently inhibited the production of these virulence factors (such as urease, protease, lipase, prodigiosin pigment, and hemolysin) (Fig. 5) as reported earlier in other bacterial species [76]. Furthermore, Ts-AgNPs also significantly reduced the swimming and swarming motility in this bacterium indicating their potential to inhibit both adhesion and dispersal stages of bacterial biofilms (Fig. 6), thereby attenuating the QS pathway and reducing bacterial biofilms [77].
Conclusion
The current study shows the effectiveness of tryptone-stabilized silver nanoparticles in interrupting bacterial growth and multiplication by altering the redox environment of the bacteria. Furthermore, Ts-AgNPs because of their small size diffused into the bacterial cells and inhibited biofilm formation by altering the cell surface hydrophobicity of this bacteria. It also effectively distorted pre-existing biofilms by inducing ROS production, and degrading eDNA, thereby distorting the EPS layer of biofilms, indicating their potential for both prevention and treatment of S. marcescens-associated diseases. Notably, Ts-AgNPs reduced various QS-induced virulence factors and their pathogenicity. Our study helps to understand the mechanistic details through which Ts-AgNPs interfere with bacterial persistence and antibiotic resistance, and might pave the way for developing Ts-AgNPs-based antibiofilm therapeutics.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file 1 (JPG 317 KB) Fluorescence microscopy images showing distortion of S. marcescens biofilms by Ts-AgNPs. (A) Control (B) ½ MIC Ts-AgNPs treated cells (C) MIC Ts-AgNPs treated cells (D) 2 MIC Ts-AgNPs treated cells.
Acknowledgements
This work is supported by UM-DAE Centre for Excellence in Basic Sciences, Mumbai, India.
Data availability
Data is available with the corresponding author and will be provided upon request.
Declarations
Conflict of interest
The authors of this manuscript do not have any conflict of interest in publishing this work.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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http://orcid.org/0000-0002-0972-6540
Ishikawa Jota [email protected]
345
Okoshi Hirofumi [email protected]
6
1 grid.17088.36 0000 0001 2150 1785 Department of Economics, Michigan State University, East Lansing, MI 48824 USA
2 grid.15444.30 0000 0004 0470 5454 School of Economics, Yonsei University, Seoul, Korea
3 grid.256169.f 0000 0001 2326 2298 Faculty of International Social Sciences, Gakushuin University, Toshima-ku, Tokyo, 171-8588 Japan
4 grid.472046.3 0000 0001 1230 0180 Research Institute of Economy, Trade and Industry, Chiyoda-ku, Tokyo 100-8901 Japan
5 grid.412160.0 0000 0001 2347 9884 Hitotsubashi Institute for Advanced Study, Hitotsubashi University, Kunitachi, Tokyo 186-8601 Japan
6 grid.261356.5 0000 0001 1302 4472 Faculty of Economics, Okayama University, Okayama, 700-8530 Japan
6 12 2022
134
4 11 2022
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Multinational enterprises (MNEs) have incentive to reduce tax payment through transfer pricing. The incentive is stronger when MNEs own intangibles, because it is easy to transfer them across countries. To mitigate such strategic tax planning, the OECD proposes the arm’s length principle (ALP). This paper deals with technology patents as an example of intangibles and investigates how the ALP affects MNEs’ licensing strategies and welfare in a model with a tax haven. The ALP may distort MNEs’ licensing decisions, because providing a license to unrelated firms restricts MNEs’ profit-shifting opportunities due to the emergence of comparable transaction. Interestingly, the termination of licensing in the presence of the ALP may worsen domestic welfare if the (potential) licensee and the MNE’s subsidiary do not compete in the domestic market but may improve welfare if they compete. The results under ad valorem royalty are in distinct contrast with those under per-unit royalty.
Keywords
Multinational enterprises
Intangibles
Licensing
Transfer pricing
Arm’s length principle
JEL Classification
D45
F23
H26
L12
Japan Society of the Promotion of Science17H00986 Ishikawa Jota German Science FoundationGRK1928 Okoshi Hirofumi National research foundation of koreaNRF-2020S1A5A2A01040865 Choi Jay Pil
==== Body
pmcIntroduction
It is well known that multinational enterprises (MNEs) take advantage of differences in corporate tax rates and preferential tax measures provided by various countries. In particular, it has been reported that MNEs often artificially shift their profits across countries to avoid taxation (Huizinga & Laeven, 2008; Egger et al., 2010; Zucman, 2014; Davies et al., 2018; Tørsløv et al., 2020). For example, according to the estimation of Tørsløv et al. (2020), more than $600 billion, which was close to 40% of multinational profits, was shifted to tax havens in 2015.1 Such huge profit-shifting is basically conducted via “transfer pricing” of intra-firm transactions across countries which account for more than 60% of world trade. With respect to the prices of goods and services within a firm (i.e., transfer prices), there is no market mechanism. Thus, MNEs can manipulate transfer prices for tax planning.
The member countries of Organisation for Economic Co-operation and Development (OECD) have cooperated in efforts to tackle this problem by setting guidelines for transfer pricing and carrying out the Base Erosion and Profit Shifting (BEPS) project.2 OECD (2017) stipulatesWhen independent enterprises transact with each other, the conditions of their commercial and financial relations (e.g., the price of goods transferred or services provided and the conditions of the transfer or provision) ordinarily are determined by market forces. (Chapter I, p. 33)
These market-driven conditions are codified into the “arm’s length principle (ALP),” which is found in Article 9 of the OECD Model Tax Convention. The ALP is the framework for bilateral treaties between not only OECD member countries but also many non-OECD countries. The application of ALP has received substantial attention in the context of international taxation.3 In fact, three out of fifteen actions of the BEPS projects deal with issues on transfer pricing and action 8 particularly targets transfer pricing on intangible transactions based on ALP.4
As a method of exercising the ALP, the comparable uncontrolled price (CUP) method is considered ideal. It suggests that tax authorities audit tax avoidance behaviors by comparing the prices used in intra-firm transactions with those of similarly uncontrolled transactions between independent parties, i.e., arm’s length prices (OECD, 2017).
Reality, unfortunately, is not as simple. In particular, it is very difficult to audit intra-firm transfers of intangibles because of the following ambiguous nature of intangibles.5 First, it is easy to shift intangibles across countries without having a substantial physical presence in transfer destinations. Thus, MNEs tend to locate their intangibles in tax havens to minimize their tax payments.6 For instance, profits shifted to Ireland via royalties accounted for approximately 23% of Ireland’s annual GDP between 2010 and 2015.7 Second and more importantly, finding appropriate fees or royalties for intangibles is difficult. As pointed out by the OECD (2017), “Tax administrations should not automatically assume that associated enterprises have sought to manipulate their profits. There may be a genuine difficulty in accurately determining a market price in the absence of market forces or when adopting a particular commercial strategy.”
In the case of transactions of intangibles, therefore, it is difficult to apply the CUP method.8 In practice, practitioners heavily rely on a different method called the transactional net margin (TNM) method because of its ease of use.9 According to the US Internal Revenue Service, the most frequently used transfer pricing method for both the sales of tangibles and intangibles in advance pricing agreements (APAs) is the comparable profits method or the TNM method, which accounted for 89% in 2016.10 The Agency, Japan also reports that the share of the TNM method in mutual agreement procedures closed during the 2019 operation year was 59%.11 Despite the fact that different methods of the ALP are used, the extant literature ignores how MNEs determine their transfer pricing via intangible assets under different methods of the ALP.
Against this background, we theoretically explore the relationship between the ALP and MNEs’ technology transfers through patent licensing. Specifically, we investigate how the ALP affects MNE’s licensing strategy and welfare in the presence of a tax haven. On one hand, if the MNE decides to license its technology to unrelated firms, then a comparable transaction appears, and the CUP method becomes applicable. Thus, the MNE needs to set the same royalty for both related and unrelated parties. On the other hand, if the MNE transfers its technology only internally, then there is no comparable transaction and the tax authority relies on the TNM method. When making a licensing decision, the MNE faces a trade-off between the license revenues from the unrelated parties and the greater opportunity for profit-shifting to a tax haven via transfer pricing. Although the MNE always licenses its technology to the local firm without the ALP, the MNE may terminate technology patent with the ALP when tax avoidance opportunity under TNM method is huge or licensing revenues from the local firm are small. Thus, the very presence of the ALP may affect the MNE’s licensing decisions and welfare.
We contribute to transfer pricing literature by capturing this aspect of profit-shifting using intangibles. We explicitly model the determination of transfer prices according to the ALP and show that the ALP increases tax revenues while potentially harming consumers. As a result, the ALP can worsen economic welfare.12 Specifically, we demonstrate that the mechanisms of the negative impacts depend on the market structure. If the MNE and the local firm do not compete in the final-good market, the ALP can deteriorate domestic welfare when the MNE does not license its technology because the local firm’s production improvement is not realized. If the MNE and the local firm compete in the market, however, the ALP can decrease domestic welfare when the MNE licenses its patent to the local firm.13 This is because the MNE produces less to increase the local firm’s revenues and consequently larger MNE’s revenues in a tax haven via licensing revenues from the local firm. These results indicate market competition plays a critical role in determining welfare impacts.
Many studies about patent licensing have assumed licensing either by means of a per-unit royalty or a fixed fee alone. However, as documented by San Martin and Saracho (2010), most license contracts have adopted the ad valorem scheme for royalty payments instead of a per-unit royalty or a fixed fee. In our analysis, therefore, we focus on ad valorem royalties as licensing payments. Moreover, despite the fact that licensing improves production costs, the interaction between patent licensing and the market has been largely overlooked, because extant literature has often considered only perfectly competitive markets. Our model of imperfect competition can capture this interaction.
Furthermore, we examine the case of per-unit royalty to emphasize transfer pricing under different modes of royalty. We show that the results in the case of an ad valorem royalty contrast strikingly with those in the case of a per-unit royalty. Without market competition between the MNE and the local firm, the ALP resulting in no licensing can worsen domestic welfare because of smaller consumer surplus in the case of an ad valorem royalty. However, such ALP benefits the domestic country in the case of a per-unit royalty because the effective marginal cost for the local firm remains the same and there is no impact on consumer surplus. Moreover, with market interaction between firms, the ALP leading to no licensing benefits consumers in the case of an ad valorem royalty whereas it harms consumers in the case of a per-unit royalty. The reason of consumer-hurting ALP under a per-unit royalty is that the ALP ending up with TNM method removes the MNE’s strategic use of royalty setting which induces the MNE to produce more. These results also imply that welfare effect of the ALP depends on the type of royalty choice as well.
Currently, the ALP is the international transfer pricing regulation to which both OECD and non-OECD member countries have agreed. However, theoretical studies which basically focus on transfer pricing regulation itself are rather limited (Samuelson, 1982; Raimondos-Møller & Scharf, 2002; Bauer & Langenmayr, 2013; Choe & Matsushima, 2013; Keuschnigg & Devereux, 2013; Behrens et al., 2014; Choi et al., 2018, 2020) and the most of them are concerned with only the CUP method.14 Additionally, the theoretical analysis of profit-shifting via intangibles has to date been limited only a few studies, including those of Juranek et al. (2018), Juranek et al. (2018), and Hopland et al. (2019). They incorporated royalty payments in their analysis but they did not consider licensing to external firms. Hence, the choice between the CUP and the TNM method, which is the focus of our analysis, was not investigated. To our knowledge, the TNM method has never been dealt with in the theoretical literature on transfer pricing.
The rest of the paper is organized as follows. Section 2 presents a basic setup with licensing by means of ad valorem royalties and analyzes how the ALP (i.e., the CUP and TNM methods) affects MNEs’ incentives to licensing in the presence of a tax haven. In the basic model, the good produced by the licensee is not substitutable with the good produced by the MNE. Section 3 explores the effects of the ALP on domestic welfare with a tax haven. Section 4 extends the basic model to examine substitutability of the goods. Section 5 considers the case of per-unit royalty and makes a comparison. Section 6 concludes the paper.
Basic model
Consider the world composed of a domestic country, a foreign country, and another foreign country, labeled D, F, and H, respectively. Country H is a tax haven. Its corporate tax rate is lower than that of country D and is normalized to zero. We assume for simplicity that there is no source tax on royalty payments.15 There is a single MNE, the headquarters of which is located in country F . There is a single local firm (called firm Y) in country D. Firm X, a subsidiary of the MNE located in country D, and firm Y, respectively, produce goods X and Y. The two goods are independent and not substitutable.16 Each firm is a monopolist in country D. Because we are primarily interested in the MNE’s profit-shifting from the domestic country to the tax haven and the domestic welfare consequences of introducing the ALP, we assume that both goods are consumed only in country D. MNE’s decision making on both the transfer price and production is centralized.17
On production costs, there is no fixed cost (FC) and the original marginal cost (MC) of producing good i (i=X,Y) is ci. The MNE owns a technology patent which can reduce MCs. Although the two goods are not substitutes, the patented technology is assumed to be applied to the production of both goods. With the patent, each firm can reduce its MC from ci to zero. Thus, firm X’s MC is always zero, whereas firm Y’s MC is zero only when the patent is granted to the local firm. We assume that the licensing contract is by means of ad valorem royalties on revenue basis. The MNE offers ad valorem royalties rx for internal licensing (i.e., licensing to firm X) and ry for external licensing (i.e., licensing to firm Y), respectively.
Let πic denote the monopoly profits when MC of good i (i=X,Y ) with its MC ci. Since the internal licensing always occurs, firm X ’s profits are always πx0. Firm Y’s profits depend on whether licensing takes place or not. The profits are πyc without licensing and πy0 with licensing, respectively.
We solve the following three-stage game. In the first stage, the MNE determines its internal and external royalty rates. The MNE specifically makes a take-it-or-leave-it offer to firm Y.18 After observing the royalty rates, firm Y decides whether to accept the license contract. Finally, firms X and Y produce and supply their products in country D.
The benchmark case: without a tax haven
To clarify the effects of a tax haven and the ALP, this subsection analyzes the case without the tax haven. We assume that the domestic corporate tax rate, t, and the foreign corporate tax rate are the same.19
The MNE has a patent which reduces MC from ci to 0. Therefore, the subsidiary’s MC is always 0, whereas the local firm’s MC is either cy or 0. If the MNE grants a license to the local firm, the local firm pays a license fee to the MNE. The royalty rate of the license is ry∈[0,1]. Formally, the post-tax profits can be written as1 ΠM=(1-t)(πx0+λryπy0),
2 Πy=(1-t){λ(1-ry)πy0+(1-λ)πyc},
where λ is a binary variable which takes one if the external licensing arises and zero otherwise.20 It should be noted that a change in t does not affect output levels.
Given Eq. (2), the local firm accepts the licensing offer if and only if3 Πyλ=1≥Πyλ=0⟺ry≤1-πycπy0=Ωπy0,
where Ω≡πy0-πyc>0. Since the two firms do not interact in the markets, the MNE is always willing to license its technology to the local firm. From Eq. (1), it is always optimal for the MNE to obtain license revenues by setting the highest royalty subject to Eq. (3), ry=Ω/πy0≡ry∗(<1). In other words, the MNE will set the royalty rate such that license revenues equal Ω.
In equilibrium, the post-tax profits become4 ΠM∗=(1-t)πx0+ΩandΠy∗=(1-t)(1-ry∗)πy0=(1-t)πyc.
As seen in the above equation, the optimal license contract makes the local firm indifferent between with and without licensing.
A tax haven without the ALP
We now introduce a tax haven into the analysis. We assume that the MNE establishes a shell company, firm S, in country H without any cost. Obviously, transferring the patent to the shell company is the optimal strategy for the MNE, because it can make more profits in the tax haven not only by profit-shifting from firm X but also by license revenues from firm Y. We assume for simplicity that the headquarters transfers the patent to the shell company free of charge.21 The profits of the MNE and firm Y are, respectively, given byΠMTH=(1-t)(1-rxTH)πx0+rxTHπx0+ryTHπy0,ΠyTH=(1-t)(1-ryTH)πy0,
where the first term of ΠMTH is the post-tax profits of firm X and the second and third terms are the license revenues from firms X and Y recorded in country H.
We first consider the case without the ALP. In this case, the MNE can set ad valorem royalties without any constraint. The optimal royalty rate is one with which all profits of firm X are shifted to firm S. Thus, rx∗TH=1, whereas the arm’s length royalty rate is the same as the benchmark case (i.e., ry∗TH=ry∗).
As a result, we obtain the same licensing strategy as the benchmark case in equilibrium. This is because the country where the MNE reports the tax base simply changes from country D to country H. Because the corporate tax is proportionally imposed on the profits, the tax rates never affect the licensing strategy. Therefore, the post-tax profits are computed as5 ΠM∗TH=πx0+Ω,andΠy∗TH=(1-t)πyc=Πy∗.
A tax haven with the ALP
Finally, we investigate the effect of the ALP in the presence of a tax haven. The ALP restricts the MNE’s profit-shifting strategy through one of two methods, the CUP method and the TNM method. The TNM method examines the profit-level indicator (PLI), defined as net profits relative to an appropriate base (e.g., sales) that a taxpayer realizes from a controlled transaction. With the TNM method, the PLI of the taxpayer from the controlled transaction should be equal to the PLI obtained in a comparable transaction by an independent enterprise (i.e., a reference firm).
First, if the MNE licenses the technology to the local firm, the CUP method applies. The MNE is unable to price-discriminate because of the emergence of a comparable transaction and arm’s length royalty. Put differently, the MNE must set a uniform royalty rate, rCUP. The MNE’s problem can be stated as follows:MaxrCUPΠMCUP=(1-t)(1-rCUP)πx0+rCUP(πx0+πy0)=(1-t)1+t1-trCUPπx0+rCUPπy0
subject toΠyCUPλ=1≥ΠyCUPλ=0⟺r≤1-πycπy0=ry∗(<1).
Because ΠMCUP is strictly increasing in rCUP, the optimal royalty rate is given by r∗CUP=ry∗. This strategy generates the following post-tax profits:6 ΠM∗CUP=(1-t)1+t1-t1-πycπy0πx0+Ω
7 =(1-t)1+t1-tΩπy0πx0+Ω,Πy∗CUP=(1-t)πyc=Πy∗=Πy∗TH.
Note that the imposition of the ALP does not lead to the elimination of profit-shifting.22 As seen in Eq. (6), the MNE shifts only a part of its profits to the tax haven. As discussed in Sect. 2.1, r∗CUP is determined only by the market condition of good Y. This means that the MNE’s global post-tax profits under the CUP method increase as Ω increases.
Alternatively, if the MNE does not license its technology, no comparable transaction appears. Hence, the royalty rate is regulated by the TNM method. Under TNM method, the tax authority compares MNEs’ PLI with a reference firm’s PLI.23 The selection criteria of the reference firm are based upon an evaluation of the functional risks of the taxpayer and the reference firm (e.g., R&D risk and credit risk). This implies that they may not operate in the same industry. Moreover, a particular taxpayer can propose a reference firm for the TNM method in an APA.24 However, the tax authorities still reserve the right to reject the APA application and can choose the reference firm to some extent.
Given the above features, with the TNM method, the royalty rate rxTNM is set such that the PLI of firm X equals the PLI of the reference firm which is exogenously given by 1-η in this subsection.25 That is, (pxx-rxTNMpxx)/pxx=1-η where px and x are the price and the output level of good X. Then, rx∗TNM=η holds. Thus, we have the following post-tax profits under the TNM method:8 ΠM∗TNM=(1-t)(1-η)πx0+ηπx0=(1-t)πx0+tηπx0,
9 Πy∗TNM=(1-t)πyc=Πy∗=Πy∗TH=Πy∗CUP.
A comparison of the two post-tax profits reveals the condition used to determine whether to license the technology. Formally, the MNE grants the license to the local firm if and only if10 ΔΠM≡ΠM∗CUP-ΠM∗TNM
11 =(1-t)1+t1-tΩπy0πx0+Ω-(1-t)πx0+tηπx0
12 =Ω-tη-Ωπy0⏟=r∗CUP=ry∗πx0>0.
We can easily confirm that∂ΔΠM∂η<0,∂ΔΠM∂Ω>0.
Thus, given the other parameters, we can define a threshold of η, ηL, such that the MNE is indifferent to licensing and non-licensing. Licensing arises if and only if η≤ηL(≡Ω(πy0+tπx0)/(tπx0πy0)). It is obvious that ηL>Ω/πy0=ry∗.
Thus, the following proposition is established.
Proposition 1
The introduction of the ALP in the presence of the tax haven results in non-licensing if η is sufficiently large or if Ω is sufficiently small.
The proposition is intuitive. The MNE faces a trade-off between license revenues from the local firm and the profit-shifting from its subsidiary to the tax haven. The latter is likely to dominate the former as η becomes larger and Ω (or cy) becomes smaller.
Welfare analysis
In this section, we consider the effects of the ALP on domestic welfare. Following the previous literature (e.g., Kind et al., 2005), we assume that the MNE is owned by residents in the foreign country. Thus, domestic welfare comprises consumer surplus, firm Y’s profits, and domestic tax revenues.26 Note that the sum of firm Y’s post-tax profits and tax revenues from firm Y is always constant and equal to πyc. Consumer surplus in the market of good X also remains constant. Thus, a change in domestic welfare is simply the sum of a change in consumer surplus in the market of good Y, CSy, and a change in tax revenues from the MNE, TRx. Obviously, CSy is larger with licensing than without it.
In the absence of the ALP, domestic welfare with the tax haven is always less than that of the benchmark case, because the presence of the tax haven does not affect the licensing strategy. Instead, it leads to leakage of tax revenues from the domestic country to the tax haven. Thus, the presence of the tax haven is always harmful for the domestic country.
We now investigate the welfare effects of the ALP in the presence of the tax haven. To this end, we compare domestic welfare between the two regimes with and without the ALP. If the introduction of the ALP does not affect the licensing strategy of the MNE, that is, if the MNE is still engaged in licensing with the ALP (which is the CUP method in this case), the impact of the ALP is straightforward. Obviously, CSy is not affected. Under the CUP method, MNE’s profit-shifting is restricted, which means that TRx increases. Thus, the ALP increases domestic welfare by t(1-r∗CUP)πx0, implying W∗CUP>W∗TH holds. However, if the ALP changes the licensing strategies, that is, if the MNE is not engaged in licensing under the ALP, a trade-off arises. On one hand, the ALP decreases MNE’s profit-shifting to the tax haven and hence TRx increases. On the other hand, non-licensing lowers productivity of the local firm and hence CSy decreases. Thus, W∗TNM>W∗TH may or may not hold. We then obtain the following lemma.
Lemma 1
While W∗CUP>W∗TH holds, the comparison between W∗TNM and W∗TH is ambiguous.
W∗TNM is decreasing in η while both W∗CUP and W∗TH are independent of η. Thus, W∗TNM>W∗CUP and W∗TNM>W∗TH are likely if η is close to 0 and vice versa if η is close to 1. Recall that whether licensing occurs or not depends on ΔΠM(≡ΠM∗CUP-ΠM∗TNM) and hence licensing occurs if and only if η≤ηL.
The following computation reflecting linear demands clarifies lemma 1. Assume that the inverse demands are given by13 px=A-axandpy=B-by.
Then, we obtainx∗TH=A2a,y∗TH=B2b,x∗TNM=A2a,y∗TNM=B-cy2b.
First, domestic welfare without the ALP, W∗TH, is compared to that with the TNM method, W∗TNM:14 W∗TNM-W∗TH=CSy∗TNM-CSy∗TH+t(1-η)A24a
15 =-cy(2B-cy)8b+t(1-η)A24a≥0⟺η≤1-acy(2B-cy)2tbA2≡ηW.
W∗TNM<W∗TH holds if and only if η>ηW, because greater η results in more opportunity of profit-shifting for the MNE. The increase in tax revenues caused by the ALP (which is the TNM method in this case) is not large enough to cover the decrease in consumer surplus in the market of good Y.
Thus, we have two cases. With ηL<ηW, the ALP may enhance domestic welfare even if licensing does not occur in the presence of the ALP. More specifically, if ηL<η<ηW, domestic welfare increases even without licensing. With ηL>ηW, however, the ALP improves domestic welfare if and only if licensing arises (recall Lemma 1).
We can thus derive the condition under which ηL<ηW holds:ηL<ηW⟺t>aB2(2B2+2Bcy-cy2)2bA2(B-cy)2≡t_.
This is illustrated in Fig. 1. Therefore, if licensing does not occur in the presence of the ALP, the ALP is necessarily harmful to the domestic country with t<t_ but may be beneficial with t>t_. When t is high, the tax revenues may be large enough to offset the consumer loss.Fig. 1 Licensing decision and welfare in equilibrium
The results are illustrated in Figs. 2 and 3.27 The figures show how η affects the MNE’s licensing strategy and domestic welfare. Figure 2 is drawn with t=0.3< t_, meaning ηL>ηW. If η<ηL, the MNE has an incentive for licensing and domestic welfare is larger with the ALP (i.e., the CUP method) than without. If η>ηL, on the other hand, licensing does not occur and domestic welfare is smaller with the ALP (i.e., the TNM method) than without. Thus, if the MNE terminates licensing because of the ALP, the domestic country loses. Figure 3 is drawn with t=0.5> t_, meaning ηL<ηW. In this case, even if the ALP leads the MNE to stop licensing, the domestic country gains with η<ηW.Fig. 2 Welfare effects of the ALP with t=0.3
Fig. 3 Welfare effects of the ALP with t=0.5
These results are summarized in the following proposition.
Proposition 2
Suppose that the ALP is introduced in the presence of a tax haven. The ALP improves domestic welfare if licensing occurs. More specifically, domestic welfare improves if and only if η<max{ηL,ηW}.
We next take the choice of η into account. As described in Sect. 2, APAs are often made. In its scheme, a tax payer can pre-consult the tax authority about the reference firm. Although the government cannot freely choose the reference firm or η, it still has freedom of choice to some extent. Given the fact, we specifically assume that the government can choose η∈[η_,η¯] where 0<η_<η¯<1.
We consider an extended game where in Stage 0, prior to the MNE’s decision on royalty rates, the domestic government chooses η from a certain range to maximize domestic welfare. If η_<ηL, the government sets η to induce licensing. As long as licensing is induced, the size of η does not matter. This is because domestic welfare with licensing is independent of η. If η_≥ηL on the other hand, the government chooses η=η_. Note that the ALP harms the domestic country if η_>max{ηW,ηL}.
Thus, we have the following proposition.
Proposition 3
Suppose that the government chooses η from the domain [η_,η¯] where 0<η_<η¯<1. The optimal royalty rate η∗ is given by η∗=η_ if ηL≤η_ and η_≤η∗≤min{ηL,η¯} if η_<ηL.
This proposition says that the domestic government should choose a reference firm which leads to licensing. However, if licensing cannot be induced with a possible choice set of reference firms, the domestic government should choose a reference firm with the lowest η. Note that licensing is more likely to occur with a lower η. Thus, whether or not licensing is induced, the domestic government should choose a reference firm with the lowest η, i.e., the most stringent regulation.
Substitutable goods
In the basic model, to clarify our point, we have assumed that both goods X and Y are not at all substitutable. In this section, we consider the case in which the two goods are substitutable. We show that the results with substitutable goods contrast clearly with those in the basic model.
We assume that the MNE and the local firm produce a homogeneous good and are engaged in Cournot competition. We also assume the following linear demand:16 p~=A-a(x~+y~).
One may think that the MNE’s subsidiary exits the market after providing the license, enabling the local firm to earn the monopoly profits and extracting possibly a higher rent through a license fee. As Mukherjee (2007) points out, however, the commitment by the MNE for not entering the market may not be credible. In our analysis, therefore, we focus on the Cournot duopoly.
A tax haven with the ALP
In the case of non-licensing with the ALP, the MNE has to set the internal royalty rate equal to the comparable value η. The profits are17 Π~MTNM=(1-t)(1-η)p~x~+ηp~x~=(1-t+ηt)p~x~,Π~yTNM=(1-t)p~-cyy~.
Noting that the outputs are independent of the internal royalty rate, we obtain18 x~∗TNM=A+cy3a,y~∗TNM=A-2cy3a.
Thus, the MNE’s profits with the TNM method becomeΠ~M∗TNM=(1-t+tη)(A+cy)29a,Π~y∗TNM=(1-t)(A-2cy)29a≡Π~y∗.
In the case of licensing with the ALP, the MNE cannot price-discriminate between its subsidiary and the local firm.19 Π~MCUP=(1-t)(1-r~CUP)p~x~+r~CUPp~x~+r~CUPp~y~=(1-t+tr~CUP)p~x~+r~CUPp~y~,Π~yCUP=(1-t)(1-r~CUP)p~y~.
Then, the outputs and profits are given byx~CUP={(1-t+tr~CUP)-r~CUP}A{3(1-t+tr~CUP)-r~CUP}a,y~CUP=(1-t+tr~CUP)A{3(1-t+tr~CUP)-r~CUP}a,Π~MCUP=(1-t+tr~CUP)3A2{3(1-t+tr~CUP)-r~CUP}2a,Π~yCUP=(1-t)(1-r~CUP)(1-t+tr~CUP)2A2{3(1-t+tr~CUP)-r~CUP}2a.
We can verify Π~MCUP is increasing in r~CUP but Π~yCUP is decreasing in r~CUP. Thus, the optimal royalty rate, r~∗CUP, satisfies the following condition:Π~y∗CUP=(1-t)(1-r~∗CUP)(1-t+tr~∗CUP)2A2{3(1-t+tr~∗CUP)-r~∗CUP}2a=(1-t)(A-2cy)29a=Π~y∗.
Substituting r~∗CUP, the MNE’s profits with the CUP method becomeΠ~M∗CUP=(1-t+tr~∗CUP)3A2{3(1-t+tr~∗CUP)-r~∗CUP}2a.
The relative magnitude of Π~M∗CUP and Π~M∗TNM is ambiguous. We can confirm that ΔΠ~M(≡Π~M∗CUP-Π~M∗TNM)<0 is possible only if cy is small. Small cy implies that licensing is not very attractive to the MNE, because the smaller the cy , the smaller the license revenues.
Welfare comparison
We examine how domestic welfare changes when the ALP is introduced in the presence of a tax haven. Since the presence of the ALP does not affect the profits of the local firm, a change in domestic welfare is measured by the sum of changes in tax revenues from the MNE, TRx, and in consumer surplus, CS. The ALP necessarily makes the tax revenues from the MNE positive. Thus, we check how CS changes as a result of the ALP.
We can prove the following lemma.28
Lemma 2
(i) x~∗CUP+y~∗CUP<x~∗TNM+y~∗TNM, (ii) x~∗CUP+y~∗CUP<x~∗TH+y~∗TH if t≤13, and (iii) x~∗TH+y~∗TH<x~∗TNM+y~∗TNM.
In the presence of the ALP, the total supply of the good is greater without licensing than with licensing (see Lemma 2 (i)). This seems surprising because the total output is less with licensing despite the fact that licensing leads both firms to produce the good with zero MC. The intuition is as follows. When the goods are substitutes, the MNE decreases the output of its subsidiary to increase the output of the local firm and the price and hence the license revenues from the local firm. The negative effect on the total output caused by the MNE’s centralized decision with licensing by means of ad valorem royalties dominates the positive effect of the cost reduction of the local firm.
Lemma 2 (ii) and (iii) say that CS without the ALP may be larger than CS with the CUP method but is smaller than CS with the TNM method. Thus, as a result of the introduction of the ALP, consumers may lose if licensing occurs but gain if it does not.
The above strategic channel of ad valorem royalty on production is analyzed by San Martin and Saracho (2010), but our model newly shows the impact of the ALP on licensing behavior. Without the ALP, external royalty has a collusive effect. However, with the ALP, such collusive effect may no longer exist when the MNE decides not to license to the local firm.
Given the importance of tax avoidance via intangible asset, the welfare effect of licensing under the ALP is interesting to investigate. Noting that the ALP increases tax revenues, we can establish the following proposition.
Proposition 4
Suppose that the MNE’s subsidiary and the local firm compete in the market. The ALP may harm consumers and worsen domestic welfare if the MNE continues licensing to the local firm, but benefits consumers and improves domestic welfare if the MNE terminates licensing to the local firm.
Figures 4, 5, and 6 illustrate whether the introduction of the ALP improves domestic welfare.29 Each figure is drawn with a different tax rate. Π~M∗TNM is more likely to exceed Π~M∗CUP if η is relatively large and t is relatively small. In the presence of the ALP, licensing occurs if and only if η<ηL. The ALP always improves domestic welfare in Figs. 4 and 5. If licensing is present under the ALP, the increase in the tax revenues dominates the loss of consumers. However, in Fig. 6, the ALP worsens domestic welfare in the presence of licensing because the loss of consumers actually exceeds the increase in the tax revenues.Fig. 4 Perfect substitutability and welfare effects of the ALP with t=0.3
Fig. 5 Perfect substitutability and welfare effects of the ALP with t=0.4
Fig. 6 Perfect substitutability and welfare effects of the ALP with t=0.5
Proposition 4 provides us with a new implication on the optimal enforcement of the ALP. As the main purpose of the ALP is to prevent MNEs’ tax avoidance, extant literature regards stricter enforcement of the ALP as a desirable policy, which is captured by a lower η¯ in our model. While this is also true in our basic model, it is not necessarily true with goods substitutability because consumers may lose. Thus, even though choosing a reference firm with a lower η¯ becomes possible thanks to stricter enforcement of the ALP, such a choice does not necessarily imply a welfare improvement in non-tax haven countries.
Per-unit royalty
We have investigated transfer pricing with patent licensing by means of ad valorem royalties. In this section, to further emphasize transfer pricing with ad valorem royalties, we consider transfer pricing with patent licensing by means of a per-unit royalty and make a comparison.
The profits with a tax haven are given byΠM=(1-t)(px-υx)x+υxx+λυyy=(1-t)px+tυx1-tx+λυyy,Πy=(1-t){λ(py-υy)y+(1-λ)(py-cy)y},
where υx and υy are the per-unit royalty charged by the MNE. With the CUP method, we have υx= υy.
No substitutability
We begin with the case without substitutability between the MNE’s final good and the local firm’s final good.30 As we will see immediately, the introduction of the ALP always improves domestic welfare.
First, suppose that the ALP is absent. Then, the MNE has an incentive to grant the patent to the local firm, because the MNE can price-discriminate between its subsidiary and the local firm. On the one hand, the per-unit royalty for the local firm is equal to its MC, cy to extract all the increased revenues.31 On the other hand, as shown in Choi et al. (2020), the per-unit royalty for the subsidiary is equal to the monopoly price of good X which would be charged if the effective MC equals zero. That is, the subsidiary produces the monopoly output level with the effective MC equal to zero and all the profits of the subsidiary are shifted to the tax haven.
Now suppose that the ALP is introduced. In the presence of licensing to the local firm, the CUP method applies, implying that the same per-unit royalty must be set between the subsidiary and the local firm. Appendix B shows that the per-unit royalty equals cy with the CUP method. Thus, the output of the local firm remains the same, which indicates that consumer surplus in the market of good Y, the revenues of firm Y, and the tax revenues from firm Y do not change. However, as shown in Choi et al. (2020), the output of the subsidiary increases because the MNE cannot shift all the profits of subsidiary to the tax haven and tries to shift more profits by increasing the volume of the MNE’s production. This means two positive effect of the ALP resulting in CUP method. First, likewise in the previous analyses, domestic tax revenues from the MNE, TRx, become positive. In addition, consumer surplus in the market of good X, CSx, increases due to the tax-induced supplies by the MNE. Thus, domestic welfare improves under CUP method.
If the MNE’s licensing to the local firm is terminated as a result of the ALP, the TNM method applies. With the TNM method, the per-unit royalty for the subsidiary, υx, becomes pxη because we have (pxx-υxx)/pxx=1-η. The local firm produces its final good with its original MC to produce good Y, cy. As a result, Eqs. (8) and (9) hold, and we can readily verify that the outputs of goods X and Y do not change. Additionally, since the ALP makes TRx positive, domestic welfare improves. Thus, we obtain the following proposition.
Proposition 5
(Per-unit royalty) Suppose that the MNE’s subsidiary and the local firm do not compete in the market and licensing contract is based on per-unit basis. The introduction of the ALP in the presence of the tax haven improves domestic welfare whether or not the MNE license its patent to the local firm.
This proposition is in contrast with Proposition 2 which shows the possibility of negative welfare effect of the ALP under TNM method. The difference stems from the nature of supplies by the local firm. In the case of a per-unit royalty, the supplies by the local firm remain constant as per-unit royalty is equal to its MC, and hence the introduction of the ALP necessarily improves domestic welfare by the appearance of tax revenues from the MNE. However, in the case of ad valorem royalty, the local firm’s supplies increase by licensing as ad valorem royalty is proportional to revenues, and the ALP may worsen domestic welfare if the patent is not licensed to the local firm. Overall, patent licensing by means of a per-unit royalty results more likely in welfare improvement.
Perfect substitutability
Next we consider the case with substitutability to see positive effects of the ALP on consumer and the local firm.
Without the ALP, the MNE always grants patent to the local firm at the per-unit royalty equal to the MC, cy. Unlike no substitutability case, the equilibrium supplies are functions of the tax rate because the MNE’s output decision depends on tax-adjusted MC including the efficiency of tax-savings.32 As higher transfer prices induce more profit-shifting and enhance efficiency of tax-savings, the MNE’s outputs increase, and the local firm’s outputs decrease compared to the standard Cournot duopoly.33
With the ALP which drops efficiency of the MNE’s tax avoidance, the MNE supplies less and subsequently the local firm supplies more compared to the case without the ALP. With the CUP method, the MNE sets the same per-unit royalty resulting in inefficient tax-savings and an increase in the tax-adjusted MC. With the TNM method, again, we have υx=pxη and such transfer pricing proportional to good price results in the standard Cournot duopoly outcome shown in Eq. (18). Moreover, by the nature of the take-it-or-leave-it offer, the local firm’s supplies do not change between CUP and TNM methods, but increases because of the ALP.
In addition to the above discussion on supplies by each firm, Appendix C shows the following lemma.34
Lemma 3
(i) x~∗TH>x~∗CUP>x~∗TNM, (ii) y~∗CUP=y~∗TNM>y~∗TH, (iii) x~∗TNM+y~∗TNM<x~∗TH+y~∗TH and (iv) x~∗CUP+y~∗CUP>x~∗TH+y~∗TH if A(2-t)7-5t<cy<A(1-t)2-t, while x~∗CUP+y~∗CUP<x~∗TH+y~∗TH if A(1-t)2-t<A(2-t)7-5t.
The lemma provides three notable results. First, as the profits of the local firm increase as its output increases, the ALP benefits the local firm (see Lemma 3 (ii)). In the previous analyses, no effects of the ALP on the local firm are confirmed. Hence, this positive effect of the ALP on local firm is observed only in the case with a per-unit royalty and perfect substitutability. Moreover, since the profits of the local firm increase, the ALP increases tax revenues not only from the MNE but also from the local firm.
Second, the effects of the ALP under TNM method on consumer are opposite to those in the case of ad valorem royalty. In the case of ad valorem royalty, Lemma 2 (iii) shows that the ALP necessarily benefits consumers if licensing to the local firm is terminated. However, in the case of per-unit royalty, consumers necessarily lose if licensing does not occur with the ALP (see Lemma 3 (iii)). The difference stems from different channels of strategic use of royalty settings without the ALP. With ad valorem royalty, royalties are set such that the MNE’s supplies become less to increase the local firm’s revenues and to extract the increased revenues of the local firm. With per-unit royalty, the royalties are determined such that the MNE produces more to increase intra-firm trade and to shift profits into the tax haven. Hence, termination of the licensing due to the ALP impacts on total supplies in opposite directions.
Finally, although the effect of the ALP on consumers is ambiguous with both licensing by means of ad valorem royalties and licensing by means of a per-unit royalty (see Lemma 2 (ii) and (iii), and Lemma 3 (iii) and (iv)), the magnitude of consumer surplus in the presence of the ALP is also opposite between the two licensing cases as a result of the above pattern of firms’ production. With a per-unit royalty, consumers prefer licensing to non-licensing (see Lemma 3 (i) and (ii)) whereas ad valorem royalties make consumer surplus higher when non-licensing takes place.
Hence, given the positive and negative impacts of the ALP, the ALP may or may not improve domestic welfare. To sum, the following proposition is established.
Proposition 6
(Per-unit royalty) Suppose that the MNE’s subsidiary and the local firm compete in the goods market and licensing contract is based on per-unit basis. The introduction of the ALP in the presence of the tax haven benefits the local firm and increases the tax revenues but may harm consumers. Consumers gain only if the MNE sells the input to the local firm with the ALP.
Concluding remarks
This paper has dealt with the MNE’s transfer pricing of intangibles licensed by means of ad valorem royalties. Our focus was on the effects of the ALP on MNE’s licensing strategies and economic welfare in the presence of a tax haven. Specifically, we have explored the CUP and TNM methods as the ALP.
Our findings in the basic model, in which a potential licensee is unrelated to the MNE’s subsidiary, provide two insights. First, the ALP may distort the MNE’s licensing strategy. In the absence of the ALP, the MNE is willing to offer a licensing contract to an unrelated firm regardless of the existence of a tax haven. In the presence of the ALP, however, the MNE may refrain from the offering the contract to eliminate the comparable transaction of licensing, which may enable the MNE to avoid the imposition of the CUP method and enjoy further profit-shifting opportunities from its subsidiary.
Second and more importantly, the disincentivization of licensing may worsen the welfare of high-tax countries. One may expect that anti-tax avoidance policies such as BEPS actions prevent MNEs from profit-shifting and contribute to welfare improvement through an increase in the tax revenue. Our model, however, has shown that such a positive aspect may appear at the expense of consumers, because the MNEs may terminate licensing to remove comparable transactions.
We then investigated the case in which the goods are substitutes as an extension to our basic model. In this case, interestingly enough, consumers may lose even if the licensing still occurs with the ALP. This is because the MNE decreases the output of its subsidiary to take more advantage of the license revenues from the unrelated firm. The point is a strategic effect which is absent in the basic model comes in. As a result, the ALP harms consumers. Thus, the welfare effects of ALP depend on whether or not goods are substitutable.
We have focused on two extreme cases (i.e., non-substitution and perfect substitution) and obtained the distinct results between these cases. In our model, the MNE adjusts a trade-off between the license revenues from the unrelated firm and the greater opportunity for profit-shifting to a tax haven via transfer pricing when offering licensing contracts. The adjustment is most contrasting between the non-substitution case and the perfect substitution case. As shown in Appendix D which examines imperfect substitution, we confirm that the results are robust.
Furthermore, we have examined the case of a per-unit royalty. The results are shown to be in contrast with those in the case of ad valorem royalties. This implies whether the type of licensing contract on royalty payments in question is ad valorem or per-unit royalty could be crucial in evaluating the ALP. Note that we can regard the case of per-unit royalty as the case of tangible inputs. Moreover, we can readily confirm that the results of technology licensing by means of a fixed payment are basically the same as those by means of ad valorem royalties without any substitutability, because there are no strategic interactions via royalty payments in both cases. Thus, licensing scheme also matters in evaluating the ALP.
We use the Cournot model to analyze competition with substitutable products. As demonstrated by Kreps and Scheinkman (1983), we can interpret the Cournot model as a static representation of a two-stage game in which firms first build capacity followed by price competition. For instance, it can be applied to the semi-conductor industry in which firms first build capacity prior to engaging in price competition. However, the Cournot model may be less appropriate for R&D intensive tech firms for which capacity constraint is less relevant. Nonetheless, our main results are robust to Bertrand competition with differentiated products. The reason is that regardless of the mode of competition, the MNE will have incentives to relax competition as its licensing revenues depend on the licensee’s revenues, which induces a semi-collusive outcome. This incentive has the effects of impairing consumer welfare in both Cournot and Bertrand models (see Fauli-Oller and Sandonis, 2002). Note also that the MNE may not have incentives to drive the rival firm out with differentiated products because industry revenue maximization requires both products in the market.
Our Cournot framework can also be applied to platform firms with ad-funded business models in two-sided markets. These firms provide services free to consumers but derive revenues from advertising. They choose the amount of advertising (ad load) which determines the advertising price. As the marginal cost of serving consumers is close to zero in digital markets, we can also interpret cost-reducing innovations as quality-enhancing.
Although our model has shed new light on the link between licensing and profit-shifting, further analysis on this topic is essential. A potential extension would be policy analyses focusing more on patents (e.g., the patent box).35 Although several empirical studies have focused on these kinds of policies rapidly prevailing in Europe, theoretical studies have not been very satisfactory.
Appendix A: Proof of Lemma 2
This appendix proves Lemma 2.
Proof
First, we prove (i) x~∗CUP+y~∗CUP<x~∗TNM+y~∗TNM. The total supply of the good isx~∗TNM+y~∗TNM=2A-cy3a,with the TNM method,x~∗CUP+y~∗CUP=A{2(1-t+r~∗CUPt)-r~∗CUP}a{3(1-t+r~∗CUPt)-r~∗CUP},with the CUP method.
We can then derive the condition that the total supply is greater under the TNM method than under the CUP method:20 x~∗TNM+y~∗TNM-x~∗CUP+y~∗CUP=(A+cy)r~∗CUP-3(1-t+r~∗CUPt)cy3a{3(1-t+r~∗CUPt)-r~∗CUP}≥0⟺r~∗CUP≥3(1-t)cyA+cy-3tcy≡rCS.
Then, we can verify that the local firm accepts the license offer if the MNE sets rCS because the following holds:21 Π~y∗CUPr=rCS-Π~y∗TNM=(1-t)(1-rCS)A2(1-t+trCS)2a{3(1-t+trCS)-rCS}2-(1-t)(A-2cy)29a=(1-t)(A-2cy)9a(A+cy-3tcy)(A+cy)2-(A-2cy)(A+cy-3tcy)=(1-t)(A-2cy)cy3a(A+cy-3tcy)A+cy+t(A-2cy)>0
Note that the MNE has an incentive to set the royalty rate as high as possible, because ∂Π~MCUP/∂r~CUP=(1-t+r~CUPt)p~x~+p~y~>0 holds. Eq. (21) suggests that rCS is acceptable for the local firm but is not optimal for the MNE, because Π~y∗CUP=Π~y∗TNM is not satisfied. Thus, the optimal royalty is greater than rCS. In view of Eq. (20), the optimal royalty results in more total supply under the TNM method than under the CUP method.
Second, we prove (ii) x~∗CUP+y~∗CUP<x~∗TH+y~∗TH if t≤13. We haveΠ~yCUP=1-taΨ,Π~yTNM=1-ta(A-2cy)29,whereΨ≡(1-r~CUP)A2(1-t+r~CUPt)2{3(1-t+tr~CUP)-r~CUP}2.
The optimal r~CUP is determined by22 ΔΠ~y≡Π~yCUP-Π~yTNM=1-taΨ-(A-2cy)29=0.
Suppose that the domestic tax rate is zero under the CUP method. Then, the optimal royalty rate is the same as the one in the benchmark case r~∗CUPt=0=r~y∗. This is because there is no tax avoidance motive. Thus, x~∗CUP+y~∗CUP=x~∗TH+y~∗TH holds at t=0. We next examine how x~∗CUP+y~∗CUP changes as t increases. We have∂Ψ∂t=2(1-r~CUP)2A2(1-t+r~CUPt)r~CUP{3(1-t+tr~CUP)-r~CUP}3>0.
We can also show23 ∂Ψ∂r~CUP=A2(1-t+r~CUPt){3(1-t+tr~CUP)-r~CUP}3×-(1-t)(1-r~CUP)(1-t+r~CUPt)-2(1-t)r~CUP-(1-r~CUP)2t-2tr~CUP2<0if0<t≤13.
To show Eq. (23), we examine the inside of the second square brackets.F(r~CUP;t)≡-(1-t)(1-r~CUP)(1-t+r~CUPt)-2(1-t)r~CUP-(1-r~CUP)2t-2tr~CUP2=-t3t-1r~CUP2+6t+1t-1r~CUP-3t-1t-1.
F(0;t)=-3t-1t-1 and F(1;t)=-2. Thus, if t<13, F(r~CUP;t)<0 holds for r~CUP∈[0,1]. If t=13, F(r~CUP;13)=-2r~CUP<0 holds for r~CUP∈(0,1]. Noting that the inside of the first square brackets is positive, we can confirm Eq. (23). Therefore, as t increases in the range of (0,13], the MNE increases r~CUP to achieve Eq. (22). That is, the optimal royalty rate is increasing in t in the range of (0,13]. In addition, we can confirm∂(x~∗CUP+y~∗CUP)∂t=-(1-r~∗CUP)r~∗CUPAa{3(1-t+tr~∗CUP)-r~∗CUP}2<0,∂(x~∗CUP+y~∗CUP)∂r~∗CUP=-(1-t)Aa{3(1-t+tr~∗CUP)-r~∗CUP}2<0.
Eqs.(21) and (22) imply that an increase in t in the range of (0,13] increases the total supply under the CUP method directly and indirectly. The indirect increase is through an increase in r~CUP caused by the increase in t. Thus, we obtain x~∗CUP+y~∗CUP<x~∗TH+y~∗TH if 0<t≤13.
Lastly, with respect to (iii) x~∗TH+y~∗TH<x~∗TNM+y~∗TNM, Proposition 2 (ii) of San Martin and Saracho (2010) proves that consumer surplus with licensing is lower than without licensing. Thus, the TNM method increases the total supply, i.e., x~∗TH+y~∗TH<x~∗TNM+y~∗TNM. □
Appendix B: Derivation of υ∗CUP=cy
This appendix shows that the per-unit royalty equals cy with the CUP method in the case of licensing by means of a per-unit royalty.
Proof
With Eq. (13), the MNE’s post-tax profits under CUP are given byΠMCUP=(1-t)(p-υCUP)x+υCUP(x+y)=1-t4aA+tυCUP1-t2+υCUPB-υCUP2b,
where υ is the per-unit royalty. Then, we obtain∂ΠMCUP∂υCUP=t2aA+tυCUP1-t+B-2υCUP2b,
which is positive if υCUP<B/2. The local firm accepts the licensing contract offered by the MNE only if υCUP≤cy holds. Therefore, if B-2cy>0 holds, the optimal CUP per-unit royalty is υ∗CUP=cy. □
Appendix C: Proof of Lemma 3
This appendix proves Lemma 3 with the demand function (16).
Proof
Under the TNM method, Eq. (18) holds. Under the CUP method, we obtain24 x~CUP=A3a+(1+t)υ~CUP3a(1-t),y~CUP=A3a-(2-t)υ~CUP3a(1-t).Π~MCUP=1-t9aA+(1+t)υ~CUP1-t2+υ~CUP3aA-(2-t)υ~CUP1-t.
Then, we have∂Π~MCUP∂υ~CUP=(5+2t)A9a-2(5-5t-t2)υ~CUP9a(1-t).
Assume that the second order condition (5-5t-t2>0) holds. This assumption implies t<(35-5)/2≈0.8541. If an interior solution exists, it isυ~ICUP=(1-t)(5+2t)A2(5-5t-t2).
We need to check if firm Y has an incentive to accept the MNE’s licensing offer with the above per-unit royalty. Since the revenues of firm Y are increasing in its output, the upper bound of υ~CUP which firm Y is willing to take the offer is determined byy~|λ=1=A3a-(2-t)υ~CUP3a(1-t)≥A-2cy3a=y~|λ=0⟺υ~CUP≤2(1-t)cy2-t≡υ~UCUP.
We can readily verify υ~ICUP>υ~UCUP. Thus, substituting υ~∗CUP=υ~UCUP into Eq. (24), we obtainx~∗CUP=A3a+2(1+t)cy3a(2-t),y~∗CUP=A-2cy3a=y~∗TNM.
We can also easily verify x~∗CUP>x~∗TNM .
We next derive x~∗TH and y~∗TH. Without the ALP, the post-tax profits are given byΠ~MTH=(1-t)(p~-υ~x)x~+υ~xx~+λυ~yy~=(1-t)p~+tυ~x(1-t)x~+λυ~yy~,Π~yTH=(1-t)λ(p~-υ~y)y~+(1-λ)(p~-cy)y~.
Note p~-υ~x≥0 holds, because the MNE has no incentive to report negative revenues in the domestic country. If both firms produce, the equilibrium outputs arex~TH=A+υ~y+2tυ~x1-t3a,andy~TH=A-2υ~y-tυ~x1-t3a,ifλ=1,x~TH=A+cy+2tυ~x1-t3a,andy~TH=A-2cy-tυ~x1-t3a,ifλ=0.
With λ=1, the MNE’s post-tax profits areΠ~MTHλ=1=(1-t)9aA+2tυ~x1-t+υ~y2+υ~y3aA-tυ~x1-t-2υ~y,
which is increasing in both υ~x and υ~y. Thus, noting p~=υ~x, we obtain υ~x∗=1-t3-2t(A+cy) and υ~y∗=cy and the outputs are given byx~∗TH=(A+cy)a(3-2t),y~∗TH=A(1-t)-(2-t)cya(3-2t).
Note that these are the equilibrium outputs whether or not the local firm accepts the MNE’s licensing offer, because υ~y∗=cy holds. y~∗TH>0 if and only if cy<A(1-t)2-t. With cy<A(1-t)2-t, we have x~∗CUP-x~∗TH=-t3(3-2t)a2A-5-4t2-tcy<0. Moreover, it is also straightforward to show y~∗CUP=y~∗TNM>y~∗TH; x~∗TNM+y~∗TNM<x~∗TH+y~∗TH; and x~∗CUP+y~∗CUP<x~∗TH+y~∗TH if cy<A(1-t)2-t<A(2-t)7-5t. With cy≥A(1-t)2-t, the monopoly equilibrium arises. When the MNE’s subsidiary becomes a monopolist, the MNE’s post-tax profits areΠ~MTH=p~+tυ~x(1-t)x~=1aA2-tυ~x2(1-t)+tυ~x(1-t)A2-tυ~x2(1-t)=A-At+tυ~x24a1-t2,
which is increasing in υ~x. Noting p~-υ~x≥0, we obtain p~∗TH=υ~x∗TH=cy. This implies that x~∗TNM+y~∗TNM<x~∗CUP+y~∗CUP<x~∗TH+y~∗TH if cy≥A(1-t)2-t. □
Appendix D: Imperfect substitution
We have seen the contrasting effects of the ALP by considering two extreme cases: no substitutability and perfect substitutability. This appendix shows that results are similar with imperfect substitutability.
Let us consider the Cournot competition with the following linear demand px=A-ax-γay and py=A-ay-γax, where γ∈[0,1] represents degree of substitutability of the goods. The two goods are independent if γ=0 holds and are homogeneous if γ=1.Fig. 7 Imperfect substitutability and welfare effects of the ALP with t=0.3
Figure 7 shows how an increase in γ affects the threshold ηL and the welfare effects of the ALP with two different MCs of the local firm with t=0.3.36 In the upper figure in Fig. 7, the threshold ηL under a larger (smaller) MC of the local firm is drawn with the dashed (solid) curve. The thresholds increase in the degree of substitutability γ because higher substitutability makes the gains from the strategic use of royalty setting larger and thus licensing to the local firm is more beneficial for the MNE.
To see the opposite effects of the ALP as in Figs. 2 and 4, let’s consider the case where η is sufficiently high. With η=0.95, the equilibrium licensing strategy is non-licensing except for the case with small MC (c=1/40) and sufficiently large γ. At γ=0, ΔW=WTNM-WTH<0 because consumers’ loss due to non-licensing dominates tax revenue from the MNE. As a larger γ generates stronger incentive for strategic use of royalty setting under the case without the ALP. Hence, consumers’ gains from the ALP become the dominant effect when γ is high. Therefore, we can confirm a threshold of γ at which ΔW=0 holds, which is drawn with the vertical lines in the bottom figure.Fig. 8 Imperfect substitutability and welfare effects of the ALP with t=0.5
In addition, Fig. 8 shows the contrast effects of the ALP with t=0.5 as in Figs. 3 and 6. Likewise in the upper figure of Fig. 7, the threshold of ηL is upward sloping. With η=0.1, the MNE always licenses the technology to the local firm and the welfare effect is illustrated in the bottom figure of Fig. 8. At γ=0, the effect of the ALP is always positive due to tax revenue from the MNE without any consumers’ losses. A larger γ, however, generates strategic motive for royalty manipulation and total supply by the firms declines. As γ is higher, this consumer’s losses tend to dominate tax revenue from the MNE and harmful ALP realizes. Thus again, we can see a thresholds of γ at which ΔW=WCUP-WTH=0 holds.
Appendix E: Product innovation
One may think that the results in the main analysis change with a patent for a new product, because the MNE seems to have no incentive for technology licensing which creates competitors. However, if such a monopoly situation induces a local potential firm to enter the market by developing its own technology through R&D or imitation, the MNE is likely to license its own technology to the local firm to obtain licensing revenues.
Suppose that the MNE develops a new technology to produce a brand new good at constant MC which is normalized to zero. On the other hand, the local firm is a potential entrant by developing their technology by incurring fixed R&D cost F. R&D successfully develops a new technology to produce the good at zero MC with the probability ρ∈(0,1) and fails with probability 1-ρ. The firms face the linear inverse demand function p~=A-a(x~+y~) as shown in Eq. (16). Again, we assume the Cournot duopoly after licensing as in Sect. 4.
As the outcome of R&D investment is probabilistic, the MNE and local firm determine their decision based on expected revenues. That is, the followings are, respectively, the condition that the local firm accepts the take-it-or-leave-it offer and the condition that MNE grants its technology patent to the local firm:E(Δπy)≡(1-t)(1-ry)p~y~-ρ(1-t)A29a-F≥0,E(ΔΠM)≡{(1-t)(1-rx)p~x~+rxp~x~+ryp~y~}-(1-ρ)A24a+ρA29a≥0.
The conditions tell two features of the modified model. First, as R&D becomes less successful, the entry of the local firm is less likely and the MNE can set higher royalty rate to the local firm. Hence, with small ρ , the optimal royalty is unity and the monopoly outcome can arise. Second, the effect of higher ρ has two opposite impacts on MNE’s revenues. On the one hand, higher probability of successful R&D increases the MNE’s expected gains from licensing due to reduction in the expected revenue under non-licensing, captured by the second bracket of E(ΔΠM). On the other hand, the higher probability of successful R&D decreases royalty rate for the local firm and subsequently reduces the MNE’s post-tax profits under licensing. Hence, the total impact is ambiguous depending on the size of ρFig. 9 Probability of successful product innovation and licensing decision
The above discussion is illustrated in Fig. 9.37 All the four curves in the figure show the MNE’s expected gains from licensing E(ΔΠM) over probability of successful R&D ρ. The solid curve represents the case without the ALP while the dashed curves depict those with the ALP at different levels of η.
Without the ALP, when probability of successful R&D is sufficiently low, the monopoly outcome due to ry=1 occurs, which is steep part of the solid curve in the area under lower ρ. However, a higher ρ makes the royalty lower than unity. In the middle size of ρ, a higher probability increases the expected gains from licensing due to the reduction in the MNE’s expected revenue under non-licensing. However, a further higher likelihood of successful R&D magnify the effect of lower royalty to the local firm and thus E(ΔΠM) is lower. In short, due to the above counteracting impacts of an increase in probability of successful R&D, the curves are hump-shaped. Even with the negative effect on the MNE’s gains from licensing, the figure shows E(ΔΠM)≥0 implying that the MNE always licenses its technology to the local firm without the ALP as in Sect. 4.
With the ALP, similar shapes of the MNE’s expected gains from licensing are depicted where the thinnest one shows the MNE’s expected profits of licensing under η=1 and the thickest shows that under η=0.5. Intuitively, the MNE’s expected revenue under non-licensing becomes smaller under lower η because such stricter TNM method does not allow the MNE to save tax. Therefore, The MNE’s expected gains from licensing are greater as η is smaller.
Moreover, under the ALP, it is impossible for the MNE to discriminate royalty rate and thus the strategic use of royalty setting is also weakened, which implies the gains from licensing are likely to be smaller under the ALP than those without the ALP. This negative aspect has greater impacts when the likelihood of successful R&D is more likely because the strategic royalty is further downwardly distorted because of the local firm’s smaller gains from taking the licensing offer. In Fig. 9, this point is captured by the steeper dashed curve than the solid curve under higher ρ. As a result, the figure shows the existence of the case where the MNE’s expected gains from licensing are negative in the presence of the ALP and the MNE stops licensing only after the ALP is introduced when both sufficiently high η and ρ hold. Hence, our results obtained in Sect. 4 are robust even with product innovation as long as R&D for a new technology is highly successful.
Acknowledgements
The authors wish to thank Nadine Riedel (editor) and two anonymous referees for helpful comments and suggestions. We also thank Andreas Haufler, Hiro Kasahara, Hiroaki Kobayashi, and the participants of the conferences and workshops at Hitotsubashi University, Kobe University, RIETI, Ryukoku University, University of Glasgow, University of Hawaii, University of Munich, and University of Tokyo for helpful comments. Choi acknowledges financial support from the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2020S1A5A2A01040865). Ishikawa acknowledges financial support from the Japan Society of the Promotion of Science through the Grant-in-Aid for Scientific Research (A): Grant Number 17H00986 and 19H00594. Okoshi acknowledges financial support from Deutsche Forschungsgemeinschaft (German Science Foundation, GRK1928). The usual disclaimer applies. The authors declare no conflict of interest. No data was generated or analyzed in this study
1 Tax havens include Ireland, the Netherlands, Luxembourg, Switzerland, Singapore, the Bahamas, Barbados, Bermuda, and the Cayman Islands, among others.
2 The BEPS project was proposed by OECD in 2012 to limit the risk of tax avoidance by MNEs. In particular, 15 action plans were stipulated as international taxation rules. Currently over 135 countries and jurisdictions are collaborating on the implementation of the BEPS actions. For more detailed information, see the following web page: https://www.oecd.org/tax/beps/
3 Many countries have taken the OECD’s transfer pricing guidelines very seriously. In fact, some countries have renewed their law based on actions of the BEPS project. For example, Australia incorporated the OECD’s transfer pricing guidelines in its transfer pricing law. Section 1 Foreign Tax Code in Germany defines the main aspects of the German interpretation of the ALP. The UK also has enacted the OECD guidelines in its law. For more details, see the following web site: https://www2.deloitte.com/global/en/pages/tax/articles/beps-action-implementation-matrices.html
4 See https://www.oecd.org/tax/beps/beps-actions/action8-10/
5 One of the most famous examples of profit-shifting through intangible assets is the “Double Irish with a Dutch Sandwich” conducted by Apple, Google, and Facebook, among others. It was reported that Google saved at least $3.7 billion in taxes in 2016 using this method (https://www.irishtimes.com/business/economy/double-irish-and-dutch-sandwich-saved-google-3-7bn-in-tax-in-2016-1.3343205).
6 For empirical evidence of location choices for intangible assets, see Dischinger and Riedel (2011), Karkinsky and Riedel (2012), and Griffith et al. (2014), among others.
7 See the Financial Times (https://www.ft.com/content/d6a75b56-215b-11e8-a895-1ba1f72c2c11).
8 In the case of intangibles, the CUP method is often called the comparable uncontrolled transaction method.
9 The TNM method is explained in Sect. 2.3. The OECD proposes three different additional methods of exercising the ALP: the cost plus method, the resale price method, and the transactional profit split method.
10 An APA is a prior agreement between a tax payer and tax authorities on the method of calculating arm’s length prices for transactions between the taxpayer and its related parties. For details, see https://www.irs.gov/irb/2017-15_IRB. The comparable profits method is mainly used in the U.S. to calculate appropriate transfer prices. Basically, these two methods are the same, with the only difference being that the TNM method deals with investigations based on transaction units, whereas the comparable profits method investigates firm-level transactions.
11 See https://www.nta.go.jp/english/MAP-Report/2020.pdf.
12 Behrens et al. (2014) and Choi et al. (2020) also show that transfer pricing regulations may harm consumers and worsen welfare in different contexts.
13 We observe a number of cross-border licensing within an industry. For example, Fujifilm Corporation licensed its technology to produce antiviral drug called Avigan to an Indian and a UAE’s pharmaceutical company, Dr. Reddy’s Laboratories Ltd. and Global Response Aid in 2020. In addition, in 2021, Novavax Inc and Takeda Pharmaceutical Company Ltd. concluded their contract on the use of intellectual property rights for the production of vaccination of COVID-19. Ishikawa & Okubo (2013) also list many other examples of cross-border licensing to rival firms. For example, Samsung Electronics Co. Ltd. used to enter a lot of licensing contracts with Japanese and European firms.
14 Transfer pricing of tangibles has also been explored from different aspects. See Schjelderup and Sørgard (1997), Auerbach and Devereux (2018), Mukunoki and Okoshi (2021), and Kato and Okoshi (2022), for example. Studies that explore actions of the BEPS project other than transfer pricing include Gresik et al. (2017), Haufler et al. (2018), and Agrawal (2021), among others.
15 For example, royalty payments within the EU are exempted from the source tax.
16 In Sect. 4, we consider the case in which the goods are substitutes.
17 According to practitioners, decision making on transfer pricing is centralized in almost all the MNEs in Western countries. See (Mori (2014), p.410).
18 Our qualitative results do not depend on the MNE’s full bargaining power assumption. If the licensee has some bargaining power, the royalty rate would be lower and the MNE will have less incentives to license its technology. Nonetheless, the overall qualitative effects would be intact. In addition, if the licensing contract is a two-part tariff, the bargaining power by the licensee will only affect the lump-sum component and the royalty rate would be the same independent of the relative bargaining power of the MNE and the local firm.
19 Even if the foreign tax rate is higher than the domestic one, the analysis in this subsection would not change with the assumption that the MNE establishes a shell company in the domestic country and transfers its patent to the shell company.
20 In the presence of the external licensing, πy0 equals firm Y ’s revenues because there is no FC for production.
21 In reality, it is often observed that intellectual property rights (IPRs) are transferred within a firm free of charge or at low prices. For example, when Google used a tax avoidance scheme, the Double Irish with a Dutch Sandwich, the headquarters transferred its IPRs to its Irish subsidiary at an extremely low price (see Saez and Zucman, 2019).
22 Some existing literature such as Peralta et al. (2006) and Yao (2013) considers cases in which the ALP completely eliminates the opportunity of profit-shifting. In our model, however, the MNE still enjoys some profit-shifting because the ALP makes the royalties equal between related and unrelated firms and a part of profits are shifted to the shell company. This is based on the assumption that the MNE can relocate the patent without any costs. Although such reallocation of technologies into tax havens is restricted and costly by current anti-tax avoidance measures such as the European exit tax and the modified nexus approach, the MNE can avoid such measures by relocating the intellectual property rights ex ante. The incentive of relocation ex ante is theoretically analyzed and supported by Sharma et al. (2021). See also footnote 21.
23 According to the Internal Revenue Service, the most frequently used PLI is operating margin (i.e., the ratio of operating profits to sales) which accounts for 67%. There are several other measures of the PLI, such as belly ratio and return on assets or capital employed, which accounted for 33%. On service transactions, the comparable profits method or the TNM method was used in 76% of the cases. The most commonly used PLI was the operating margin (43%).
24 Once an APA is made, the tax authorities neither adjust nor audit the pricing of specified transactions under the agreed to transfer pricing method for 3 to 5 years. In Japan, 133 APA applications were submitted in 2019. See https://www.nta.go.jp/english/Report_pdf/2021e.pdf
25 As explained in above, this reference firm is not necessarily in the same industry or the potential licensee. For example, in March 1999, the Japanese national tax tribunal made a decision on arm’s length royalty based on 23 transactions as comparable transactions which included different countries and products. See Fujieda and Tsunoda (2020).
26 The domestic country may benefit from knowledge spillovers caused by licensing, which are beyond the scope of this paper.
27 We set A=B=a=b=1 and cy=110 in Figs. 2 and 3.
28 See Appendix A for the proof.
29 Figures 4, 5, 6 are drawn with cy=11000 and A=a=1.
30 This case is somewhat similar to the case explored in Choi et al. (2020). In fact, some of their results are applicable here.
31 Strictly speaking, the optimal price is less than cy if cy is sufficiently high. With Eq. (13), this is the case if cy>B/2. We assume away this case.
32 This tax-adjusted MC for the MNE is -tυx1-t<0(=cx) and is known as the perceived marginal costs in the literature. See Choi et al. (2018) for example.
33 Note that in the absence of the ALP, the Cournot duopoly equilibrium in the domestic market arises if and only if cy<A(1-t)2-t.
34 A(1-t)2-t>A(2-t)7-5t if and only if t<12.
35 Regarding the patent box, see Haufler and Schindler (2020), for example.
36 The following parameter values are set: A=1, a=1.
37 The following parameters are set: A=1, a=1, t=310, and F=1500.
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Fujieda, J., & Tsunoda, N. (2020). Itenkakaku Zeisei no Jitsumu Shoukai (Practical Explanation on Transfer Pricing Regulation) (pp. 471–473). Tokyo: Chuo-Keizaisha.
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Gresik TA Schindler D Schjelderup G Immobilizing corporate income shifting: Should it be safe to strip in the harbor? Journal of Public Economics 2017 152 68 78 10.1016/j.jpubeco.2017.06.001
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Haufler, A., & Schindler, D. (2020). Attracting profit shifting or fostering innovation? On patent boxes and R&D. CESifo Working Paper No. 8640.
Hopland, A. O., Lisowsky, P., Mardan, M., & Schindler, D. (2019). Implications of flexibility in income shifting under losses. Available at SSRN: https://ssrn.com/abstract=3327666
Huizinga H Laeven L International profit shifting within multinationals: A multi-country perspective Journal of Public Economics 2008 92 1164 1182 10.1016/j.jpubeco.2007.11.002
Ishikawa, J., & Okubo, T. (2013). Trade and industrial policy subtleties with international licensing. RIETI Discussion Paper Series 13-E-050
Juranek S Schindler D Schjelderup G Transfer pricing regulation and taxation of royalty payments Journal of Public Economic Theory 2018 20 67 84 10.1111/jpet.12260
Juranek, S., Schindler, D., & Schneider, A. (2018). Royalty taxation under tax competition and profit shifting. CESifo working paper No. 7227.
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Kato H Okoshi H Economic integration and agglomeration of multinational production with transfer pricing International Economic Review 2022 63 3 1325 1355 10.1111/iere.12569
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| 0 | PMC9734996 | NO-CC CODE | 2022-12-14 23:28:32 | no | Int Tax Public Financ. 2022 Dec 6;:1-34 | utf-8 | Int Tax Public Financ | 2,022 | 10.1007/s10797-022-09770-w | oa_other |
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Environ Dev Sustain
Environ Dev Sustain
Environment, Development and Sustainability
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Article
Blood plasma supply chain planning to respond COVID-19 pandemic: a case study
Fallahi Ali 1
Mousavian Anaraki Seyed Alireza 2
http://orcid.org/0000-0002-5297-5841
Mokhtari Hadi [email protected]
https://scholar.google.com/citations?user=btXeO3oAAAAJ&hl=en&oi=ao
3
https://orcid.org/0000-0001-6281-055X
Niaki Seyed Taghi Akhavan https://scholar.google.com/citations?user=wn5ljLEAAAAJ&hl=en&oi=ao
1
1 grid.412553.4 0000 0001 0740 9747 Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran
2 grid.411748.f 0000 0001 0387 0587 School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
3 grid.412057.5 0000 0004 0612 7328 Department of Industrial Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran
8 12 2022
152
30 1 2022
24 11 2022
© The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The COVID-19 pandemic causes a severe threat to human lives worldwide. Convalescent plasma as supportive care for COVID-19 is critical in reducing the death rate and staying in hospitals. Designing an efficient supply chain network capable of managing convalescent plasma in this situation seems necessary. Although many researchers investigated supply chains of blood products, no research was conducted on the planning of convalescent plasma in the supply chain framework with specific features of COVID-19. This gap is covered in the current work by simultaneous regular and convalescent plasma flow in a supply chain network. Besides, due to the growing importance of environmental problems, the resulting carbon emission from transportation activities is viewed to provide a green network. In other words, this study aims to plan the integrated green supply chain network of regular and convalescent plasma in the pandemic outbreak of COVID-19 for the first time. The presented mixed-integer multi-objective optimization model determines optimal network decisions while minimizing the total cost and total carbon emission. The Epsilon constraint method is used to handle the considered objectives. The model is applied to a real case study from the capital of Iran. Sensitivity analyses are carried out, and managerial insights are drawn. Based on the obtained results, product demand impacts the objective functions significantly. Moreover, the systems' total carbon emission is highly dependent on the flow of regular plasma. The results also reveal that changing transportation emission unit causes significant variation in the total emission while the total cost remains fixed.
Keywords
Logistics
COVID-19 pandemic
Blood supply chain network
Sustainable location-allocation analysis
==== Body
pmcIntroduction
Severe respiratory syndrome coronavirus 2 (SARS-CoV-2), known as COVID-19, is an acute respiratory disease in which, regarding the physiological characteristics of people, the mortality rate is estimated at 1 to 5 percent (Ibarra-Vega, 2020). On March 11, 2020, World Health Organization recognized COVID-19 as a pandemic (Tison et al., 2020). About 549 million people have been diagnosed with the disease worldwide by June 2022.1 The high mortality rate of this disease and the pandemic’s resulting human and economic impact prompted the expert to investigate efficient cures for COVID-19. Before the approval of vaccines, various drugs and substances such as convalescent plasma, RamedSivir, and Favipiravir were used to reduce to control the virus (Abolghasemi et al., 2020; Lauer et al., 2020). Although the invention of some vaccines by lead developer companies such as Pfizer, Moderna, and AstraZeneca was a significant step toward controlling COVID-19, the accessibility and availability of these vaccines are not guaranteed according to limited production capacity and some other reasons. As an example, Africa had delivered almost 34 doses of vaccine per 100 persons as of April 2022. This vaccination rate is significantly lower than the global average, with 145 vaccinations per 100 people.2
Due to that, and in the current situation, convalescent plasma still has a significant role as supportive care for the control and treatment of Covid-19. Convalescent plasma is collected from the recovered patient with a prespecified antibody level that can be used for other patients (Abolghasemi et al., 2020). The history of successful convalescent plasma therapy backs up more than 100 years ago for infectious diseases, including SARS, MERS, Ebola, etc. (Cheraghali et al., 2020; Zhang et al., 2020). Researchers confirmed the efficiency of convalescent plasma for COVID-19 treatment and stated that using recovered patients' plasma could reduce the death rate and stay time in hospitals (Chen et al., 2020).
Although various research works were published on the medical aspects of convalescent plasma, there is a lack of attention to how convalescent plasma should be managed. There is a limited supply of convalescent plasma as the recovered patients from Covid-19 are the only source of the donation. On another side, the high virus transmission rate causes more people to become infected. Hence, there is a need to design and develop a system for the efficient management of convalescent plasma (Asadpour et al., 2021; Wendel et al., 2021).
A research line is related to the blood supply chain to manage regular blood products. Pirabán et al. (2019) defined the blood supply chain as a network that operates blood products' flow from donors to patients through some echelons. Previous authors investigated various blood supply chains for different blood products such as red blood cells, platelet, and regular plasma under different real-world assumptions (Beliën & Forcé, 2012; Osorio et al., 2015; Pirabán et al., 2019). Despite the publication of many papers in this field, no work analyzed a blood supply chain in pandemic situations while considering the flow of convalescent plasma. The critical importance of convalescent plasma and the blood supply chain's capability in managing blood products motivated the current research to present a plasma supply chain network in the condition of the COVID-19 pandemic.
On the other hand, there is a lack of attention to the plasma supply chain in the literature (Dehghani Ashkezari & Yaghoubi, 2020; Hosseini-Motlagh et al., 2020a). Regular plasma flow is also considered in the presented network to bring the problem closer to reality. In other words, the goal is to cover the gaps simultaneously by offering a model for the multi-product plasma supply chain during COVID-19.
From an environmental viewpoint, there is a growing concern about carbon emissions in the industrial and service sectors (Fallahi et al., 2022a). There is a strictly increasing trend in greenhouse gas emissions where the global carbon emission has risen from 25 to 36 billion in recent two decades.3 The global direction of carbon emission from 1940 to 2021 is shown in Fig. 1.Fig. 1 The annual carbon emission from 1940 to 2021 (www.statista.com)
This issue also impacted the supply chains and caused academics and practitioners' attention to design environmentally friendly supply chains. The concerns about carbon emission in health care supply chains and pollution reduction are reminded for health care managers during the COVID-19 pandemic (Goodarzian et al., 2021b). Recent studies in the medical field prove the significant role of carbon emission and environmental pollution on the severity of COVID-19 (Chen et al., 2022; Fattorini & Regoli, 2020; Frontera et al., 2020; Wu et al., 2020). The results of these studies, which are performed in different countries, show that air pollution increases the infection and mortality rate of COVID-19. Therefore, it can be concluded that the importance of carbon emission not only is not reduced during this pandemic but also is intensified and may impact the prevalence of the disease. The importance of carbon emission in the COVID-19 pandemic is so high that several recent research on health care supply chain planning investigated and addressed it (Goodarzian et al., 2021a, 2021b; Govindan et al., 2021).
In the current work, the resulting emission from the proposed plasma supply chain's activities is taken into account to address the mentioned concerns. Besides, our work is the first research investigating carbon emission in a plasma supply chain. We attempt to reduce carbon emission as much as possible by considering the total carbon emission as one of the objective functions of the proposed model. In summary, this work aims to address five research questions (RQ) as follows:RQ 1: What is the optimal design of a green plasma supply chain during the outbreak of the COVID-19 pandemic?
To answer RQ 1, we develop a mixed-integer linear programming model to determine the location, allocation, motivational programs, and inventory decisions of the considered plasma supply chain network during the COVID-19 pandemic. The operational limitations of the studied network are formulated as the problem constraints. This model is presented by considering certainty for the parameters.
RQ 2: How to deal with the arising carbon emission concerns during the COVID-19 pandemic?
To answer RQ 2, we consider the total carbon emission from the transportation activities of the systems as an objective function of the problem along with the total cost. We formulate the problem as a bi-objective mathematical model.
RQ 3: How to deal with the total cost and total carbon emission as the conflicting objective of the problem simultaneously?
We utilize the epsilon constraint method as an efficient approach to deal with the considered economic and environmental objectives. This method can be easily applied and converts the problem to a single-objective problem by considering the more important goal as the objective function. This way, the less important objective is bounded as a problem constraint. After, the set of Pareto solutions is obtained using different upper bounds for the constrained objective function. This method enables the decision-makers to obtain a set of non-dominated solutions and selects the desired solution from this set.
RQ 4: What is the approach to solving the developed bi-objective mixed-integer linear mathematical model?
To answer RQ 4, we propose the GAMS programming environment and CPLEX commercial solver, one of the most powerful tools in solving the mixed-integer linear programming models.
RQ 5: How is the performance and applicability of the model?
To answer RQ 5, we apply the model to a case study and solve the model for the collected data of this supply chain network. In this regard, first, the Pareto front is calculated using the epsilon constraint method. After that one of the Pareto solutions is selected, and further analyses are performed on that solution.
The rest of the paper is organized as follows: Sect. 2 provides a literature review of the various aspects of this work. Section 3 defines the problem, and a multi-objective mathematical model is developed for the considered plasma supply chain network during the outbreak of the COVID-19 pandemic. Section 4 describes the epsilon constraint method as a solution methodology for handling the multi-objective model. In Sect. 5, a real-world case study from the plasma supply chain of the capital of Iran during COVID-19 is solved to evaluate the model. Section 6 provides the paper's conclusion with some suggestions for the extension of this work.
Literature review
This section reviews the literature of the present work's central aspects to highlight the gaps and specify current work contributions. We divide the literature review into three subsections: supply chain planning of blood products, supply chain planning during the COVID-19 pandemic, and green supply chain planning.
Blood-product supply chain planning
In the field of supply chain planning for blood products, Nagurney et al. (2012) presented the first mathematical programming model for a comprehensive supply chain network focusing on the general aspect of whole blood. Nagurney and Masoumi (2012) extended the previous work by formulating the capacity of network arcs as decision variables. Although this work's extension was significant progress in this research direction, the network was elementary and did not consider other important features.
Pierskalla (2005) investigated a simulation optimization problem for various decisions such as scheduling, location, allocation, and distribution in decentralized and centralized blood bank systems. A combination of stochastic dynamic programming and simulation approaches was proposed by Van Dijk et al. (2009) for a platelet production planning problem. Duan and Liao (2014) studied a red blood cells inventory system with ABO group compatibility and shelf-life features. Jabbarzadeh et al. (2014) formulated a supply chain network optimization problem under the pre-disaster and post-disaster assumptions, where a robust optimization method for this location-allocation problem was proposed. Zahiri and Pishvaee (2017) suggested a blood supply chain model considering different blood groups' compatibility. The goal was to minimize the total cost and the maximum unsatisfied demand under uncertainty.
Gunpinar and Centeno (2016) focused on routing aspects of the blood supply chain network by presenting an integer programming model for optimal routing of mobile collection centers. The objectives were minimizing the number of collection centers and total traveled distance. Hosseinifard and Abbasi (2018) investigated the hospital inventory centralization and transshipment impact on the performance of a two-echelon blood supply chain network. They found positive results from inventory centralization, where the performance would enhance from 21 to 40%. Khalilpourazari and Khamseh (2019) discussed disruption in blood supply chain networks in a bi-objective model with different transportation modes. The goal was to minimize the systems' total cost and delivery time. Yousefi Nejad Attari et al. (2019) proposed an integrated method considering stochastic programming, robust optimization, and epsilon constraint to deal with some combination of uncertainty in blood supply chain networks. The donation uncertainty was formulated by stochastic scenarios, while the polyhedral uncertainty sets were considered for patients' uncertainty demand. Khalilpourazari et al. (2020) worked on blood supply chain planning in disaster conditions. They proposed using a helicopter to transform blood to disaster points and return injured people from this point to safe medical centers. Using neural learning for decision-making was also discussed. The paper of Hosseini-Motlagh et al. (2020b) was the first research in the supply chain of blood products that investigated a stimulation program to motivate volunteer donors of the blood supply chain. Fallahi et al. (2021b) presented a mathematical model to formulate a closed-loop blood supply chain network considering the quality of the transportation equipment.
As one of the few works exploring carbon emission in blood supply chains, Heidari-Fathian and Pasandideh (2018) proposed a multi-objective sustainable model to minimize the total cost and carbon emission in the blood supply chain. In addition, Mousavi et al. (2021) investigated a sustainable blood supply chain in which both the environmental and social criteria were considered. This problem was formulated as a stochastic green split pick-up VRP model with uncertainty in donation capacity and the decomposition ratio of blood.
Beliën and Forcé (2012) shed light on the blood-product supply chain literature by providing a comprehensive review paper for the first time. Various approaches and methods for blood supply chain planning, including mathematical programming, simulation, and queuing models, were discussed in this work. In addition to this article, some other works tried to investigate the features of past works and presented some review papers, e.g., Osorio et al. (2015), Pirabán et al. (2019), and Meneses et al. (2022).
Despite the appearance of significant research in this field, the supply chain of plasma products is rarely investigated in recent years, and the focus of previous works in the literature was on other blood products.
Dehghani Ashkezari and Yaghoubi (2020) presented a single-period plasma supply chain network model among the published work in this area. The whole blood and apheresis donation methods were possible, and they considered plasma demand from pharmaceutical companies and hospitals. Hosseini-Motlagh et al. (2020a) proposed another location-allocation model for the plasma supply chain. They seek to enhance the quality of delivered plasma to hospitals and pharmaceutical companies, focusing on frozen time, where data envelopment analysis (DEA) evaluates the candidate locations for plasma donation. More details on the state of the art of the problem are available in the related papers in the literature (Amiri et al., 2020).
As mentioned earlier, many researchers investigated the supply chain of blood products. However, this product's supply chain is rarely studied despite plasma's significant importance. Moreover, some features of blood supply chains, such as pandemic situations and the sustainability criteria, remain unaddressed, or there is a lack of attention.
Supply chain planning during the COVID-19 pandemic
The occurrence of the COVID-19 pandemic influenced all nodes (members) of various supply chains worldwide (Gunessee & Subramanian, 2020). This issue attracted scholars' and researchers' attention to study the traditional supply chain networks under the assumptions of the COVID-19 pandemic.
Tsao et al. (2021) discussed the impact of COVID-19 on the supply chains in the energy sector, where the challenge was many disruptions in the supply of renewable energies in the network. This problem was investigated by presenting a resilient network. Majumdar et al. (2020) provided explanatory research to find the reasons for the lack of social responsibility in India's clothing supply chain, where the motivation was the unemployment of many laborers during the COVID-19 pandemic. Chowdhury et al. (2021) provided the first systematic review paper focusing on the emerging studies about the impact of the COVID-19 pandemic on supply chains. Paul and Chowdhury (2020) developed a recovery model for manufacturing supply chains under high-demand products like toilet papers. This problem arises from the disruption caused by increasing the demand for products and decreasing the supply of raw materials from suppliers.
A portion of current works in supply chain planning during COVID-19 relates to the supply chain in the medical sector. Goodarzian et al. (2021b) presented the first integrated multi-objective sustainable medical supply chain that considers the features of medicines such as RamedSivir and Favipiravir for COVID-19 patients. They viewed both the social and environmental dimensions of sustainability in their model. Mehrotra et al. (2020) utilized a stochastic programming approach for managing ventilator inventory under the US's pandemic limitations. They proposed resource sharing as an effective strategy to mitigate the risk of disruption. Lozano Díez et al. (2020) formulated the risk of resulting disruption from the pandemic and its effect on the shortage quantity in a general drug supply chain. Zahedi et al. (2021b) applied an IoT system to a relief logistic network in the COVID-19 pandemic. The network focused on the suspectable cases of COVID-19, a prioritizing, and an allocating approach were discussed. The goal of the first approach was minimizing the maximum response time of ambulances, and the second approach aimed to minimize the critical response time.
Mosallanezhad et al. (2021a) addressed a bi-objective logistic network for personal protection equipment of medical centers in the COVID-19 pandemic. They suggested the total cost and the maximum unsatisfied demand as the objectives.
Kargar et al. (2020) pointed out that the prevalence of the COVID-19 pandemic caused more generations of medical waste and presented a reverse supply chain network for better waste management. Regarding the shortage of personal protective equipment, Rowan and Laffey (2020) analyzed this problem from the supply chain standpoint and provided some solutions for this problem.
Despite these studies' great contribution, none considered the supply chain of plasma products in COVID-19, which has a significant role in controlling this pandemic.
Green supply chain planning
The environmental concerns about global warming resulting from carbon emissions caused the concentration of research on green supply chain planning and created an exciting research area.
Sheu et al. (2005) attempted to deal with logistic problems in a green supply chain by presenting a linear programming model. In Garg et al. (2015) work, the closed-loop supply chain's environmental concerns were addressed, where they used a bi-objective mixed-integer nonlinear programming model for this problem. They considered different transportation modes in the distribution layer. Nia et al. (2015) extended a sustainable multi-item EOQ model for a two-echelon supply chain under various operational constraints. To enhance the performance, they utilized Vendor Managed Inventory (VMI) contract as the coordination mechanism of the supply chain. Centobelli et al. (2017) presented a recent systematic review of the green supply chains problem. Mirzapour Al-e-hashem et al. (2013) proposed a stochastic mathematical model for aggregate production planning in an environmentally responsible supply chain network. Another extension was proposed by Entezaminia et al. (2016), where they developed the formulation of aggregate production planning in a green reverse supply chain network.
Resat and Unsal (2019) investigated multi-objective sustainable supply chain networks in packaging industries. They utilized a two-stage method based on the Analytic Hierarchy Process (AHP) and mathematical programming to minimize the total time and cost of the sustainability factors. Abdi et al. (2020) applied a new approach to design a green supply chain network by considering simultaneous pick-up and split delivery. The network's environmental features were also addressed by using a green VRP model for the network. Mokhtari and Rezvan (2020) investigated a multi-product single vendor-multibuyer supply chain under a VMI contract with a limitation on the system's total carbon emission. A bi-objective sustainable supply chain for palm date was presented by Hamdi-Asl et al. (2021). The total cost and total carbon emission were considered the problem's objective functions. Hasani et al. (2021) developed a sustainable and resilient supply chain for a company in the medical industry. The goal was to make a trade-off between the network's carbon emission, resiliency, and profitability. Salehi-Amiri et al. (2022a) studied the application of IoT in a sustainable waste management system. This problem was formulated as two VRP sub-models. As some research on the green supply chain models for agricultural products, Salehi-Amiri et al. (2021) studied a closed-loop agriculture supply chain network focusing on the walnut product. Chouhan et al. (2021) presented a closed-loop structure for a sugarcane supply chain network. The environmental features of the sugarcane supply chain were also studied by Chouhan et al. (2022). They formulated the supply chain network under carbon tax regulation. Another agricultural closed-loop supply chain was studied by Salehi-Amiri et al. (2022b). In addition to the economic and environmental pillars, they considered the social responsibility of the network by formulating the number of job opportunities as one of the objective functions. The closed-loop supply chain network design is also investigated for marine products. For example, Mosallanezhad et al. (2021b) developed a mathematical model for shrimp closed-loop supply chain planning. A closed-loop fish supply chain network was investigated by Fasihi et al. (2021a). In this regard, the computational complexity of the fish closed-loop supply chain was addressed in Fasihi et al. (2021b) research. They used three efficient metaheuristics, MOKA, NSGA-II, and MOSA, as the solution approaches. Qiao et al. (2021) used the Stackelberg game approach for a supply chain coordination problem under emission-dependent demand and investment options to curb environmental impacts. The interested reader can refer to the relevant papers in the literature for more information on green supply chain planning problems (Fallahi et al., 2021a; Boronoos et al., 2021; Daneshdoost et al., 2022; Khan et al., 2021; Rajak et al., 2022; Zahedi et al., 2021a). The summary of reviewed literature is provided in Table 1. Table 2 contains the abbreviations used in Table 1.Table 1 The features of the relevant studies in the field of blood supply chain planning
Research Special
features Decision-making
level Product
INT COL PRO INV DIS WHB RBC PLT PLS CPL
Van Dijk et al. (2009) Platelet production policy ✗ ✗ ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗
Nagurney et al. (2012) A network design for blood supply chain ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Duan and Liao (2014) Red blood cell inventory control with ABO possible substitution ✗ ✗ ✗ ✓ ✗ ✗ ✓ ✗ ✗ ✗
Jabbarzadeh et al. (2014) Robust model for blood supply chain in disaster ✗ ✓ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Nagurney and Masoumi (2012) Variable arc capacity and blood waste disposal ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Gunpinar and Centeno (2016) A VRP model for mobile blood collection center ✗ ✓ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Zahiri and Pishvaee (2017) Blood supply chain with ABO possible substitution ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Heidari-Fathian and Pasandideh (2018) Green blood supply chain ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Hosseinifard and Abbasi (2018) Inventory centralization policy for hospital blood banks ✗ ✗ ✗ ✓ ✗ ✓ ✗ ✗ ✗ ✗
Yousefi Nejad Attari et al. (2019) The total cost and the and the remaining time objectives under uncertainty ✗ ✓ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Khalilpourazari and Khamseh (2019) Disruption in the relief blood supply chain ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Hosseini-Motlagh et al. (2020b) Motivational programs in blood supply chain ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Dehghani Ashkezari and Yaghoubi (2020) Plasma supply chain ✓ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✓ ✗
Mousavi et al. (2021) Sustainable VRP for blood collection ✗ ✓ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Fallahi et al. (2021b) Closed-loop blood supply chain ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✗ ✗
Current research Green Plasma supply chain in COVID-19 pandemic ✓ ✗ ✗ ✗ ✗ ✗ ✗ ✗ ✓ ✓
Research Special
features Collection method Supply
side Demand
side Objective
numbers
WBC APC RGD RCD HOS MCC PHC SO MO
Van Dijk et al. (2009) Platelet production policy ✓ ✗ ✓ ✗ ✓ ✗ ✗ ✓ ✗
Nagurney et al. (2012) A network design for blood supply chain ✓ ✗ ✓ ✗ ✓ ✗ ✗ ✗ ✓
Duan and Liao (2014) Red blood cell inventory control with ABO possible substitution ✓ ✗ ✓ ✗ ✓ ✗ ✗ ✓ ✗
Jabbarzadeh et al. (2014) Robust model for blood supply chain in disaster ✓ ✗ ✓ ✗ ✓ ✗ ✗ ✓ ✗
Nagurney and Masoumi (2012) Variable arc capacity and blood waste disposal ✓ ✗ ✓ ✗ ✓ ✗ ✗ ✗ ✓
Gunpinar and Centeno (2016) A VRP model for mobile blood collection center ✓ ✗ ✓ ✗ ✗ ✗ ✗ ✓ ✗
Zahiri and Pishvaee (2017) Blood supply chain with ABO possible substitution ✓ ✗ ✓ ✗ ✓ ✗ ✗ ✗ ✓
Heidari-Fathian and Pasandideh (2018) Green blood supply chain ✓ ✗ ✓ ✗ ✓ ✗ ✗ ✗ ✓
Hosseinifard and Abbasi (2018) Inventory centralization policy for hospital blood banks ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✓ ✗
Yousefi Nejad Attari et al. (2019) The total cost and the and the remaining time objectives under uncertainty ✓ ✗ ✓ ✗ ✓ ✗ ✗ ✗ ✓
Khalilpourazari and Khamseh (2019) Disruption in the relief blood supply chain ✓ ✗ ✓ ✗ ✓ ✗ ✗ ✗ ✓
Hosseini-Motlagh et al. (2020b) Motivational programs in blood supply chain ✓ ✓ ✓ ✗ ✓ ✗ ✗ ✗ ✓
Dehghani Ashkezari and Yaghoubi (2020) Plasma supply chain ✓ ✓ ✓ ✗ ✓ ✗ ✓ ✓ ✗
Mousavi et al. (2021) Sustainable VRP for blood collection ✓ ✗ ✓ ✗ ✗ ✗ ✗ ✗ ✓
Fallahi et al. (2021b) Closed-loop blood supply chain ✓ ✗ ✓ ✗ ✓ ✗ ✗ ✓ ✗
Current research Green Plasma supply chain in COVID-19 pandemic ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✗ ✓
Research Special
features Sustainability
pillar Other features Solution
approach Time
period Case study
ECO ENV SOC TRS MOP EX Me SP MP
Van Dijk et al. (2009) Platelet production policy ✓ ✗ ✗ ✗ ✗ ✗ ✓ ✓ ✗ ✓
Nagurney et al. (2012) A network design for blood supply chain ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✓ ✗ ✗
Duan and Liao (2014) Red blood cell inventory control with ABO possible substitution ✓ ✗ ✗ ✗ ✗ ✗ ✓ ✗ ✓ ✗
Jabbarzadeh et al. (2014) Robust model for blood supply chain in disaster ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✓ ✓
Nagurney and Masoumi (2012) Variable arc capacity and blood waste disposal ✓ ✓ ✗ ✗ ✗ ✓ ✗ ✓ ✗ ✗
Gunpinar and Centeno (2016) A VRP model for mobile blood collection center ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✓ ✗ ✓
Zahiri and Pishvaee (2017) Blood supply chain with ABO possible substitution ✓ ✗ ✗ ✓ ✗ ✓ ✗ ✓ ✗ ✓
Heidari-Fathian and Pasandideh (2018) Green blood supply chain ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✓ ✗
Hosseinifard and Abbasi (2018) Inventory centralization policy for hospital blood banks ✓ ✗ ✗ ✓ ✗ ✓ ✗ ✗ ✓ ✗
Yousefi Nejad Attari et al. (2019) The total cost and the and the remaining time objectives under uncertainty ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✓ ✓
Khalilpourazari and Khamseh (2019) Disruption in the relief blood supply chain ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✗ ✓ ✓
Hosseini-Motlagh et al. (2020b) Motivational programs in blood supply chain ✓ ✗ ✗ ✗ ✓ ✓ ✗ ✗ ✓ ✓
Dehghani Ashkezari and Yaghoubi (2020) Plasma supply chain ✓ ✗ ✗ ✗ ✗ ✓ ✗ ✓ ✗ ✓
Mousavi et al. (2021) Sustainable VRP for blood collection ✓ ✓ ✓ ✗ ✗ ✗ ✓ ✓ ✗ ✗
Fallahi et al. (2021b) Closed-loop blood supply chain ✓ ✗ ✗ ✗ ✗ ✗ ✓ ✓ ✗ ✗
Current research Green Plasma supply chain in COVID-19 pandemic ✓ ✓ ✗ ✓ ✓ ✓ ✗ ✗ ✓ ✓
Table 2 The abbreviation used in Table 1
Decision-making level Objective numbers
Integrated INT Single-objective SO
Collection COL Multi-objective MO
Production PRO Sustainability pillar
Inventory INV Economic ECO
Distribution DIS Environmental ENV
Product Social SOC
Whole blood WHB Other features
Red blood cell RBC Transshipment TRS
Platelet PLT Motivational programs MOP
Plasma PLS Solution approach
Convalescent plasma CPL Exact EX
Collection method Metaheuristic ME
Whole blood collection WBC Time period
Apheresis collection APC Single-period SP
Supply side Multi-period MP
Regular donors RGD
Recovered donors RCD
Demand side
Hospitals HOS
Medical centers for COVID-19 patients MCC
Pharmaceutical companies PHC
Research gap
Regarding the reviewed literature, despite the publication of a wide range of research in the blood supply chain, there is a lack of attention to managing convalescent plasma in pandemic situations like COVID-19. The convalescent plasma shows great efficiency in treating infected people in the epidemic and pandemic outbreak of several diseases. Therefore, it seems necessary to investigate the presence of this product in a supply chain framework. Besides, the regular plasma supply chain is rarely addressed and discussed. Finally, despite many carbons emission-related problems, the green blood products supply chain design, especially the plasma, is rarely addressed. The importance of carbon emission and environmental pollution not only reduced in COVID-19 but also intensified regarding the impact of this phenomenon on the disease severity of infected people.
Our current work tries to cover the above gaps. It is the first research that addresses the flow of convalescent plasma as a critical substance for treating COVID-19 disease alongside the flow of plasma in a multi-product plasma supply chain. We try to present a closer problem to real-world assumptions by considering various features of regular and convalescent plasma, the COVID-19 pandemic, and carbon emissions from the supply chain's activity. The main contributions of the present work can be listed as follows:We develop a mixed-integer linear programming model to design a plasma supply chain network during the COVID-19 pandemic. In this model, we try to consider several specific assumptions about the pandemic, which have not been considered so far in the literature. The presence of convalescent plasma recovered patients, and the medical centers for COVID-19 patients as the special supply and demand point, the motivational programs for the recovered patients, and the transshipment of convalescent plasma are some of these assumptions which have not been addressed in the literature. Therefore, the newly developed model is a generalized framework of the previous works for plasma supply chain network design.
We consider the plasma supply chain network's carbon emission and the total cost and present the problem as a bi-objective model. Carbon emission is rarely addressed in the blood supply chain, and no work in the literature considers the presence of carbon emission in the plasma supply chain. Due to the intensified emission concern and the impact of pollution on the state of COVID-19 patients, we address the carbon emission from transportation activities. We aim to help the decision-makers to select the desired solution.
We investigate the applicability and efficiency of the mathematical model by applying it to the plasma supply chain network of the capital of Iran during the COVID-19 pandemic, as one of the largest cities in the Middle East. In this way, several analyses are performed, and insights are drawn that can help the decision-makers manage the studied network.
Problem description and formulation
This section first defines the proposed supply chain network for managing plasma and convalescent plasma under COVID-19 limits. After that a mixed-integer linear mathematical programming model is proposed for the desired network.
Problem definition
A four-echelon multi-product multi-period network is developed to determine the optimal location, allocation, production, motivational programs, and inventory control decisions of the considered plasma supply chain during the COVID-19 pandemic.
In this network, there are two groups of donors at the first layer: the first group is regular donors (Hosseini-Motlagh et al., 2020a). In contrast, the second is the recovered patients from the COVID-19 disease with a predefined virus antibody level (Chen et al., 2020). Motivational programs are efficient methods used to motivate people to blood donation and boost the supply side of blood supply chains (Hosseini-Motlagh et al., 2020b). These programs have received much attention during COVID-19 to motivate recovered patients to donate their convalescent plasma in different countries (Bloch et al., 2021) (behdasht.gov.ir). We consider three categories of motivational programs: medical credits, advertisement, and educational courses for the recovered donors in the presented network. These programs positively correlate with each recovered group's convalescent plasma donation capacity, and there is a limited available budget for them.
Both groups of donors should refer to collection centers for blood donation. The state of the COVID-19 pandemic is not stable and may change in different areas. Hence, we consider mobile collection centers as facilities for collecting convalescent plasma from recovered donors. The location of these mobile centers can be changed in each period (Bloch et al., 2021). Besides, fixed collection centers are assumed for plasma collection. Logically, the location decision of these fixed centers is strategic and remains fixed prior, during, and past the pandemic. The location of mobile collection centers in each period and the overall location of fixed collection centers should be determined from a prespecified set of candidate locations.
There are two donation modes: apheresis donation and whole blood donation to collect blood from donors (Dehghani Ashkezari & Yaghoubi, 2020). The collection of convalescent plasma is similar to other products and is performed by these methods (Bloch et al., 2021). In apheresis donation, the plasma is extracted directly from the donor's body. In contrast, in whole blood donation, the whole blood is withdrawn, and the plasma is separated through some process operations (Dehghani Ashkezari & Yaghoubi, 2020). More plasma is attainable by the apheresis donation method, while whole blood donation is cheaper (Osorio et al., 2018). Both whole blood and apheresis donation modes are considered for mobile and fixed collection centers. The collected (convalescent) whole blood/plasma is assumed to be transferred to processing facilities within less than 6 h (Dehghani Ashkezari & Yaghoubi, 2020; Mobasher et al., 2015).
There is a limited set of candidate locations for processing facilities, and the location of these facilities should be specified, similar to fixed collection centers (Samani et al., 2018). The received (convalescent) whole blood/plasma is processed in processing facilities to become usable for final consumption. The shelf life and perishability of both products are regarded from this layer. Convalescent plasma production and shelf life are similar to regular plasma (Bloch et al., 2021).
Pharmaceutical companies and hospitals are the two main demand points for regular plasma (Dehghani Ashkezari & Yaghoubi, 2020). Regular plasma is used in pharmaceutical companies to produce various plasma-based medicines such as human albumin. In hospital demand points, regular plasma is used to treat patients with burn, shock, hemophilia, etc. (Rytilä & Spens, 2006). Another special feature of the plasma supply chain during the COVID-19 pandemic is some medical centers that admit patients with COVID-19. These centers need convalescent plasma to treat their COVID-19 patients, and the produced convalescent plasma is transformed to these centers based on their needs. All three demand points are taken into account in the proposed model, and the flow of regular plasma and convalescent plasma is established based on their demand.
The high mortality rate of COVID-19 boosted the demand for convalescent plasma, and various inventory challenges appeared (Wendel et al., 2021). In our model, the possibility of convalescent plasma transshipment between processing facilities is regarded to restrict the shortage of this critical substance during the pandemic as much as possible. Regarding the related inventory challenges of convalescent plasma, a minimum safety-stock level is considered for this product in processing facilities.
Finally, the movement of mobile collection centers and product transportation is the primary source of carbon emissions in blood supply chains (Heidari-Fathian & Pasandideh, 2018; Mousavi et al., 2021). We try to incorporate sustainability in the supply chain of plasma and blood during the COVID-19 pandemic for the first time by taking into account these primary sources of pollution in the network and attempting to minimize the total carbon emission of the system as much as possible. Figure 2 presents the framework of the studied plasma supply chain network under the assumptions of the COVID-19 pandemic.Fig. 2 The structure of the presented plasma supply chain network to manage regular and convalescent plasma during the COVID-19 pandemic
The main assumptions and decisions of the proposed plasma supply chain network for the COVID-19 pandemic are specified as follows:
Assumptions
The following assumptions are considered for the presented plasma supply chain:The supply chain is a multi-echelon, multi-product, and multi-period network.
There are two groups of volunteers for donation in the network: The first group is the regular people who donate regular plasma. The second group comprises the recovered patients from COVID-19 disease that donate convalescent plasma.
There are two types of donation methods for donors and recovered donors, including apheresis and whole blood donation.
Two collection centers are fixed collection centers for regular volunteers and mobile collection centers for recovered volunteers.
Three motivational programs for recovered patients from COVID-19 motivate them to donate their convalescent plasma: Medical credits, advertisement, and educational courses.
There is a limited budget for the motivational programs of recovered donors from COVID-19.
There is a limited set of candidate locations for the location of mobile collection centers in each period.
There are limited sets of candidates, fixed collection centers, and processing facilities.
The perishability of plasma and convalescent plasma is considered due to the shelf-life parameter.
The transshipment of convalescent plasma between processing facilities is allowed to prevent shortage as much as possible.
The carbon emission causes by the movement of collection facilities and transportation of products in the network.
Decisions
The following decisions are made by solving the presented mathematical model:
Optimal motivational programs decisions
Assigned medical credit units to each recovered donor group in each period
Assigned advertisement units to each recovered donor group in each period
Assigned educational course units to each recovered donor group in each period
Optimal location decisions
Location of mobile collection centers in each period
Location of fixed collection centers
Location of processing facilities
Optimal allocation decisions
Allocation pattern of donors to fixed collection centers and received quantity of regular whole blood/plasma in each period
Allocation pattern of recovered donors to mobile collection centers and received quantity of convalescent whole blood/plasma in each period
Allocation pattern of fixed collection centers to processing facilities and transformed quantity of regular whole blood/plasma in each period
Allocation pattern of mobile collection centers to processing facilities and transformed quantity of convalescent whole blood/plasma in each period
Allocation pattern of processing facilities to pharmaceutical companies and transformed quantity of regular plasma in each period
Allocation pattern of processing facilities to hospitals and transformed quantity of regular plasma in each period
Allocation pattern of processing facilities to medical centers for COVID-19 patients and transformed quantity of convalescent plasma in each period
Allocation pattern between processing facilities and transshipment quantity of convalescent plasma in each period
Optimal production decisions
Production quantity of regular plasma in each processing facility in each period
Production quantity of convalescent plasma in each processing facility in each period
Optimal inventory decisions
Inventory level of regular plasma in each processing facility in each period
Inventory level of convalescent plasma in each processing facility in each period
Shortage quantity of regular plasma in each pharmaceutical company in each period
Shortage quantity of regular plasma in each hospital in each period
Shortage quantity of convalescent plasma in each medical center for COVID-19 patients in each period
Expired quantity of regular plasma in each pharmaceutical company in each period
Expired quantity of regular plasma in each hospital in each period
Expired quantity of convalescent plasma in each medical center for COVID-19 patients in each period
Mathematical modeling
A mixed-integer multi-objective model is developed in this section to formulate the considered plasma supply chain network. The model contains the following notations, parameters, and decision variables.
Notations
The indices, parameters, and decision variables are defined as follows:Sets and indices
I Set of regular donors; indexed by i(i∈I)
J Set of recovered donors from COVID-19 disease; indexed by j(j∈J)
R Set of donation methods; indexed by r(r∈R)
M Set of candidate locations for mobile collection centers; indexed by m,m1,m2(m,m1,m2∈M)
F Set of candidate locations for fixed collection centers; indexed by f(f∈F)
P Set of candidate locations for processing facilities; indexed by p,p′(p,p′∈P)
E Set of pharmaceutical companies; indexed by e(e∈E)
H Set of hospitals; indexed by h(h∈H)
C Set of medical centers for COVID-19 patients; indexed by c(c∈C)
T Set of periods; indexed by t,t′(t,t′∈T)
Parameters
crcst The unit cost of a medical credit for motivation of convalescent plasma donors in period t
adcst The unit cost of an advertisement for motivation of convalescent plasma donors in period t
edcst The unit cost of an educational course for motivation of convalescent plasma donors in period t
crcft Correlation factor of convalescent plasma donation capacity of a recovered group and a medical credit unit in period t
adcft Correlation factor of convalescent plasma donation capacity of a recovered group and an advertisement unit in period t
edcft Correlation factor of convalescent plasma donation capacity of a recovered group and an educational course unit in period t
BMOT The maximum available budget for motivational programs
dcnmirt Maximum possible donation of regular donors group i through donation method r (regular whole blood/plasma) in period t
dccmjrt Maximum possible donation of recovered donors j through donation method r (convalescent whole blood/ plasma) in period t
lcfcf The location cost of fixed collection center f
lcmmm1m2t Moving cost of each mobile collection center from node m1 to node m2 in period t
cnfmifrt Unit collection cost of a regular whole blood/plasma through donation method r from donor group i at fixed collection center f in period t
ccmmjmrt Unit collection cost of a convalescent whole blood/plasma through donation method r from recovered donor group j at mobile collection center m in period t
fcnmfr The capacity of fixed collection center f for collecting regular whole blood/plasma through donation method r
mccmmr The capacity of mobile collection center m for collecting convalescent whole blood/plasma through donation method r
lcpcp The location cost of processing facility p
pctpp Collection capacity of processing facility p
mnfpfpt Unit transportation cost of a regular whole blood/plasma from fixed collection center f to processing facility p in period t
mcmpmpt Unit transportation cost of a convalescent whole blood/plasma from mobile collection center m to processing facility p in period t
pnmprpt The unit production cost of a regular whole blood/plasma collected through donation method r in production facility p in period t
pcmprpt The unit production cost of a convalescent whole blood/plasma collected through donation method r in production facility p in period t
cppmrp The unit production rate for a convalescent/regular whole blood/plasma collected through donation method r in processing facility p
hcnppt Unit holding cost of a regular plasma in processing facility p in period t
hccppt Unit holding cost of convalescent plasma in processing facility p in period t
innpp Total available space of processing facility p for storing regular plasma
incpp Total available space of processing facility p for storing convalescent plasma
pshl Shelf life of a convalescent/regular plasma
mnpepet Unit transportation cost of a regular plasma from processing facility p to pharmaceutical company e in period t
mnphpht Unit transportation cost of a regular plasma from processing facility p to hospital h in period t
mcpcpct Unit transportation cost of convalescent plasma from processing facility p to medical center for COVID-19 patients c in period t
shneet Unit shortage cost of a regular plasma in pharmaceutical company e period t
shnhht Unit shortage cost of a regular plasma in hospital h period t
shccct Unit shortage cost of convalescent plasma in medical center for COVID-19 patients c in period t
exneet Unit expiration cost of a regular plasma in pharmaceutical company e in period t
exnhht Unit expiration cost of a regular plasma in hospital h in period t
exccct Unit expiration cost of convalescent plasma in medical center for COVID-19 patients c in period t
dmneet The demand of pharmaceutical company e for regular plasma in period t
dmnhht The demand of hospital h for regular plasma in period t
dmccct The demand of medical center for COVID-19 patients c for convalescent plasma in period t
sscppt Safety-stock level of convalescent plasma in processing facility p in period t
mccppp′t Unit transshipment cost of convalescent plasma from processing facility p to processing facility p′ in period t
cemmm1m2 Unit carbon emission to move a mobile collection center from node m1 to node m2
cefpfp Unit carbon emission to transport a regular whole blood/plasma from fixed collection center f to processing facility p
cempmp Unit carbon emission to transport a convalescent whole blood/ plasma from mobile collection center m to processing facility p
cepepe Unit carbon emission to transport a regular plasma from processing facility p to pharmaceutical company e
cephph Unit carbon emission to transport a regular plasma from processing facility p to hospital h
cepcpc Unit carbon emission to transport a convalescent plasma from processing facility p to a medical center for COVID-19 patients c
cecppp′ Unit carbon emission to transport a convalescent plasma from processing facility p to processing facility p′ in period t
M A big number
Decision variables
lcff Equals one if fixed collection center f is located; 0 otherwise
lcmm1m2t Equals one if mobile collection center located in the node m1 in period t-1 move to the location m2 in period t; 0 otherwise
adfifrt Equals one if regular donor group i is allocated to fixed collection center f for donation through donation method r in period t; 0 otherwise
admjmrt Equals one if recovered donor group j is allocated to mobile collection center m for donation through donation method r in period t; 0 otherwise
lcpp Equals one if processing facility p is located; 0 otherwise
afpfprt Equals one if fixed collection center f is allocated to production facility p for transport collected regular whole blood/plasma through donation method r in period t; 0 otherwise
ampmprt Equals one if mobile collection center m is allocated to production facility p for transport collected convalescent whole blood/plasma through donation method r in period t; 0 otherwise
apepet Equals one1 if production facility p is allocated to pharmaceutical company e for transporting regular plasma in period t; 0 otherwise
aphpht Equals one1 if production facility p is allocated to hospital h for transporting regular plasma in period t; 0 otherwise
apcpct Equals one if production facility p is allocated to a medical center for COVID-19 patients c for transport convalescent plasma in period t; 0 otherwise
mcrjt Assigned medical credit units to motivate recovered donor group j in period t
madjt Assigned advertisement units to motivate recovered donor group j in period t
medjt Assigned educational course units to motivate recovered donor group j in period t
cdfifrt Quantity of collected regular whole blood/plasma through donation method r from donor group i at fixed collection center f in period t
cdmjmrt Quantity of collected convalescent whole blood/plasma through donation method r from recovered donor group j at mobile collection center m in period t
tfpfprt Quantity transformed regular whole blood/plasma from fixed collection center f to processing facility p, collected through donation method r in period t
tmpmprt Quantity transformed convalescent whole blood/plasma from mobile collection center m to processing facility p, collected through donation method r in period t
ppnrpt Production quantity of regular plasma from received regular whole blood/plasma that collected through donation method r in processing facility p in period t
ppcrpt Production quantity of convalescent plasma from received convalescent whole blood/plasma that collected through donation method r in processing facility p in period t
inppt Inventory level of regular plasma in processing facility p in period t
icppt Inventory level of convalescent plasma in processing facility p in period t
qnepett′ Quantity of transported regular plasma from processing facility p in period t to pharmaceutical company e that consumed in the period t′
sneet Shortage quantity of regular plasma in pharmaceutical company e in period t
eneet Expired quantity of regular plasma in pharmaceutical company e in period t
qnhphtt′ Quantity of transported regular plasma from processing facility p in period t to hospital h that consumed in the period t′
snhht Shortage quantity of regular plasma in hospital h in period t
enhht Expired quantity of regular plasma in hospital h in period t
qccpctt′ Quantity of transported convalescent plasma from processing facility p in period t to a medical center for COVID-19 patient c that consumed in the period t′
sccct Shortage quantity of convalescent plasma in medical center for COVID-19 patients c in period t
eccct Expired quantity of convalescent plasma in medical center for COVID-19 patients c in period t
tcppp′t Transshipment quantity of convalescent plasma between processing facility p and COVID-19 medical center p′ in period t
The model
The first objective function of the model to minimize is:1 MinTC=∑m1∑m2∑tlcmmm1m2t∗lcmm1m2t+∑i∑f∑r∑tcnfmifrt∗cdfifrt+∑j∑m∑r∑tccmmjmrt∗cdmjmrt+∑plcpcp∗lcpp+∑flcfcf∗lcff+∑r∑p∑tpnmprpt∗ppnrpt+∑r∑p∑tpcmprpt∗ppcrpt+∑p∑thcnppt∗inppt+∑p∑thccppt∗icppt+∑f∑p∑r∑tmnfpfpt∗tfpfprt+∑m∑p∑r∑tmcmpmpt∗tmpmprt+∑p∑e∑t∑t′mnpepet∗qnepett′++∑p∑h∑t∑t′mnphpht∗qnhphtt′+∑p∑c∑t∑t′mcpcpct∗qccpctt′+∑p∑p′∑t∑t′mccppp′t∗tcppp′tt′+∑e∑texneet∗eneet+∑h∑texnhht∗enhht+∑c∑texccct∗eccct+∑e∑tshneet∗sneet+∑h∑tshnhht∗snhht+∑c∑tshccct∗sccct+∑j∑tcrcst∗mcrjt+adcst∗madjt+edcst∗medjt
Objective function (1) minimizes the total cost of integrated network including movement cost of mobile collection centers, collection cost of regular plasma from regular donors, collection cost of convalescent plasma from recovered donors, location cost of processing facilities, location cost of fixed collection centers, production cost of regular plasma, production cost of convalescent plasma, inventory holding cost of regular plasma in processing facilities, inventory holding cost of convalescent plasma in processing facilities, transportation cost between fixed collection centers and processing facilities, transportation cost between mobile collection centers and processing facilities, transportation cost between processing facilities and pharmaceutical companies, transportation cost between processing facilities and hospitals, transportation cost between processing facilities and medical centers for COVID-19 patients, convalescent plasma transshipment cost between processing facilities, regular plasma expiration cost in pharmaceutical companies, regular plasma expiration cost in hospitals, convalescent plasma expiration cost in medical centers for COVID-19 patients, regular plasma shortage cost in pharmaceutical companies, regular plasma shortage cost in hospitals, convalescent plasma shortage cost in medical centers for COVID-19 patients, and the cost of motivational programs for recovered donors.
The second objective function to minimize is the total carbon emission:2 MinTE=∑m1∑m2∑tlcmm1m2t∗cemmm1m2+∑f∑p∑r∑tcefpfp∗tfpfprt+∑m∑p∑r∑tcempmp∗tmpmprt+∑p∑p′∑tcecppp′∗tcppp′t+∑p∑e∑t∑t′cepepe∗qnepett′+∑p∑h∑t∑t′cephph∗qnhphtt′+∑p∑c∑t∑t′cepcpc∗qccpctt′
The second objective (2) goal is to minimize the total carbon emission in the plasma supply chain network. This consists of the resulted carbon emission from the movement of mobile collection centers, the transformation of flow from fixed collection centers to processing facilities, the transformation of flow from mobile collection centers to processing facilities, transshipment between processing facilities, the transformation of flow from processing facilities to pharmaceutical companies and hospitals, and transformation from processing facilities to medical centers for COVID-19 patients.
The constraints of the mathematical formulation are:3 ∑m1lcmm1m2t≤1;∀m2,t
There should not be more than one mobile collection center in a candidate location. Constraint (3) puts an upper bound on the number of mobile collection centers in a location. It ensures that only one mobile collection center is located in a specific node in each period.4 ∑radfifrt≤1;∀i,f,t
5 ∑radmjmrt≤1;∀j,m,t
Constraints (4) and (5) provide that one donation method (apheresis or whole blood) is used for each group of regular donors and recovered donors in the considered fixed and mobile collection centers in a period.6 ∑m2lcmm1m2t≤∑mlcmmm1t-1;∀m1,t≥2
Constraint (6) implies that the relocation of a mobile collection center in a period is possible for the facilities located in the previous period.7 cdfifrt≤M∗adfifrt;∀i,r,f,t
8 cdmjmrt≤M∗admjmrt;∀j,r,m,t
9 tfpfprt≤M∗afpfprt;∀f,r,p,t
10 tmpmprt≤M∗ampmprt;∀m,r,p,t
11 qnepett′≤M∗apepet;∀p,e,t,t′
12 qnhphtt′≤M∗aphpht;∀p,h,t,t′
13 qccpctt′≤M∗apcpct;∀p,c,t,t′
The flow of regular plasma and convalescent plasma between two facilities in the supply chain is possible when the considered facilities are allocated in a period. Constraints (7) and (8) are the allocation constraints of regular donors and recovered donors to the fixed and mobile collection centers. The possibility of flow to the allocated collection centers and processing facilities is limited via constraints (9) and (10). Constraints (11)–(13) are the allocation constraints between the processing facilities and the demand points.14 ∑icdfifrt≤fcnmfr;∀f,r,t
15 ∑jcdmjmrt≤mccmmr;∀m,r,t
Constraints (14) and (15) limit the collection capacity of each fixed collection center and mobile collection center for collecting the donated regular/convalescent whole blood/plasma through each donation method in each period.16 ∑fcdfifrt≤dcnmirt;∀i,r,t
17 ∑mcdmjmrt≤dccmjrt+crcft∗mcrjt+adcft∗madjt+edcft∗medjt;∀j,r,t
Constraint (16) shows the maximum donation capacity of each group for regular plasma donation in a period, where the donation capacity of recovered groups considering the impact of motivational programs in each period is expressed via constraint (17).18 adfifrt≤lcff;∀i,r,f,t
19 admjmrt≤∑m1lcmm1mt;∀j,r,m,t
20 afpfprt≤lcff;∀f,r,p,t
21 afpfprt≤lcpp;∀f,r,p,t
22 ampmprt≤∑m1lcmm1mt∀m,r,p,t
23 ampmprt≤lcpp∀m,r,p,t
24 apepet≤lcpp∀p,e,t
25 aphpht≤lcpp∀p,h,t
26 apcpct≤lcpp∀p,c,t
Constraints (18)–(26) enforce that the flow of convalescent and regular plasma is possible only for the established facilities in each period. Constraints (18) and (19) ensure that the regular donor and recovered donors only refer to the established fixed collection centers and located mobile collection centers. Constraints (20) and (21) limit the flow of regular plasma between the established fixed collection centers and process facilities. Similarly, constraints (22) and (23) are the flow restriction constraints of convalescent plasma between the located mobile collection centers and the established processing centers. Constraints (24)–(26) state that the transformation of regular and convalescent plasma is possible only from the established processing centers to the demand points.27 ∑icdfifrt=∑ptfpfprt∀f,r,t
28 ∑iadfifrt=∑pafpfprt∀f,r,t
All the received regular whole blood/plasma from the regular donors in the fixed collection centers should be transformed to the processing centers. Constraints (27) and (28) control the inflow and outflow of received regular whole blood/plasma in fixed collection centers in each period.29 ∑jcdmjmrt=∑ptmpmprt∀m,r,t
30 ∑jadmjmrt=∑pampmprt∀m,r,t
The flow constraint of received convalescent whole blood/plasma in mobile collection centers in each period is formulated by Eqs. (29) and (30). Regarding these equations, the total convalescent whole blood/plasma delivered to the processing centers should equal the received quantity from the recovered donors in each period.31 ∑f∑rtfpfprt+∑m∑rtmpmprt≤lcpp∗pctpp∀p,t
The total received and convalescent plasma from the collection centers (fixed and mobile) should be equal to or less than the processing centers' storage capacity. Constraint (31) limits the capacity of each processing facility in each period.32 ∑fcppmrp∗tfpfprt=ppnrpt∀r,p,t
33 ∑mcppmrp∗tmpmprt=ppcrpt∀r,p,t
The production and transformation of received regular plasma and convalescent plasma in each processing facility in each period are shown by constraints (32) and (33). The total production is obtained by multiplying the received regular and convalescent plasma by the production rate of each item.34 ∑rppcrpt+icppt-1=icppt+∑c∑t′≥tqccpctt′-∑p′≠ptcpp′pt+∑p′≠ptcppp′t∀p,t
In the processing centers, the inflow of convalescent plasma should equal this product's outflow for each period. Constraints (34) is the inventory balance equation of convalescent plasma in the processing facilities in each period.35 ∑rppnrpt+inppt-1=inppt+∑e∑t′≥tqnepett′+∑h∑t′≥tqnhphtt′∀p,t
The balance of regular plasma inventory in processing facilities in each period is limited by constraints (35). These constraints specify the inflow and outflow of regular plasma in processing centers in each period.36 sscppt≤icppt∗lcpp∀p,t
Constraint (36) ensures that the minimum safety stock of convalescent plasma in an established process center is provided in each period. In other words, the convalescent plasma inventory level should be equal to or more than the specified safety stock.37 icppt≤innpp∗lcpp∀p,t
38 inppt≤incpp∗lcpp∀p,t
The storage capacity of processing centers is limited for regular and convalescent plasma in each period. Constraints (37) and (38) demonstrate that each processing facility's stored inventory of plasma and convalescent plasma should be less than the storage capacity for each product in each period.39 sneet=dmneet+sneet-1-∑t-pshl≤t′≤t∑pqnepet′t∀e,t
40 snhht=dmnhht+snhht-1-∑t-pshl≤t′≤t∑pqnhpht′t∀h,t
41 sccct=dmccct+sccct-1-∑t-pshl≤t′≤t∑pqccpct′t∀c,t
If the product delivery be less than the demand rate, a shortage occurs. Constraints (39) and (40) calculate the shortage quantity of regular plasma in each pharmaceutical company and hospital in each period, respectively. The shortage of convalescent plasma in each medical center for COVID-19 patients in each period is formulated by Eq. (41).42 eneet≤∑t-t′>pshl∑pqnepet′t∀e,t
43 enhht≤∑t-t′>pshl∑pqnhpht′t∀h,t
44 eccct≤∑t-t′>pshl∑pqccpct′t∀c,t
If the time interval between the production and delivery of plasma or convalescent plasma unit is more than the shelf life that unit would be expired. Constraints (42)–(44) reveal the expiration of plasma and convalescent plasm in pharmaceutical companies, hospitals, and medical centers for COVID-19 patients in each period, based on the shelf life of plasma products.45 ∑j∑tcrcst∗mcrjt+adcst∗madjt+edcst∗medjt≤BMOT
Constraint (45) considers the limits on the maximum available budget for motivational programs for recovered donors in the planning horizon.46 lcff,lcmm1m2t,adfifrt,admjmrt,lcpp,afpfprt,ampmprt,apepet,aphpht,apcpct∈0,1∀i,j,f,m,m1,m2,r,p,e,h,c,t
47 mcrjt,madjt,medjt,cdfifrt,cdmjmrt,tfpfprt,tmpmprt,ppnrpt,ppcrpt,inppt,icppt,qnepett′sneet,eneet,qnhphtt′,snhht,enhht,qccpctt′,sccct,eccct,tcppp′t≥0∀i,j,f,m,r,p,p′,e,c,t,t′
Constraints (46) and (47) present the types of decision variables.
The solution approach
In many real-world situations, the decision-makers usually deal with different goals and intend to trade-off multi-objectives in their problem (Mokhtari & Hasani, 2017). In this condition, the classic optimization approaches are not practical. Therefore, various approaches and methods are discussed for optimizing multi-objective optimization problems.
One of the main approaches for handling different objective functions in an optimization problem is the epsilon constraint method which tries to construct a single-objective model by converting other objectives to model constraints with predefined bounds (Haimes, 1971). By changing the bounds of the constraints, Pareto solutions are obtained, and the decision-maker can select the preferred solution based on their preference.
Consider the following model as a general multi-objective problem:48 MinZ=[f1x,f2x,⋯,fRx]
Subject to:49 gjx≥0;∀j=1,2,⋯,J
50 x∈RD
The epsilon constraint method transforms the objective functions of this problem into a single objective as:51 MinZ=fhx
Subject to:52 gjx≥0;∀j=1,2,⋯,J
53 frx≤εr;∀r=1,2,h-1,h+1,⋯,R
54 x∈RD,
where fhx is the hth objective function preferred to others, R is the total number of objective functions of the problem, and εr is considered the upper bound on the rth objective function. For solving the proposed plasma supply chain network during the COVID-19 pandemic, the solving procedure of the epsilon constraint method can be summarized in 4 steps:
Step 1 Obtain a payoff table by solving the model with each objective function separately to find each objective function's best and worst value.
Step 2 Select TC (total cost of the supply chain) or TE (total emission of the supply chain) as the objective function of the model and let the other be the model constraint.
Step 3 Calculate the range between the best and worst value of the bounded objective function, and divide the range to ε1,ε2,⋯,εk
Using the obtained information from the above steps, establish the single-objective model as:55 MinZ=TC(TE)
Subject to:
Eqs. (3)–(47)56 TETC≤ε
57 Wo≤ε≤BE
where BE and Wo are the best and worst obtained values from the payoff table for the constrained objective function.
Step 4 Solve the resulted problem in the previous section with different epsilon values to find the Pareto solutions.
Case description
In this section, a real-world case study from Tehran, the capital of Iran, is solved, to illustrate the efficiency and performance of the proposed multi-objective model in plasma supply chain planning during the COVID-19 pandemic.
Tehran is selected due to its high importance in three main dimensions of current research:Regarding the official reports, 2,739,875 cases were identified in Iran until May 15, 2021, and Iran is among the top 15 countries with high identified COVID-19 patients. The high population and various socioeconomic and cultural activities in Tehran have caused many people to be infected at any peak of the disease, which caused growing concerns about managing COVID-19.
Tehran accounts for about 24% of Iran's supply and 27% of its total blood demand. There is high demand in Tehran, considering particular regular plasma products. For example, a recent global survey confirmed that Iran is one of the countries with a high rate of hemophilia, about 12,000 per year. In this respect, Tehran is among the top three cities that need regular plasma to treat patients (Hosseini-Motlagh et al., 2020a).
Tehran is facing various environmental and air pollution problem which is caused by carbon emissions. Official statistics from the Tehran Municipal Air Quality Control company state that there were 123 days in the previous year that the air in Tehran was unhealthy due to greenhouse gas emissions (airnow.tehran.ir).
Tehran metropolis is the most populated city in Iran, with an 8,693,706 population according to a census in 2016 (Samani & Hosseini-Motlagh, 2019; Samani et al., 2019). Tehran has 22 municipal districts, and the disparity between these districts and their population is shown in Fig. 3.Fig. 3 Geographical location and population of Tehran's municipal districts
Iranian Blood Transfusion Organization (IBTO) manages the supply chain of regular and convalescent plasma in Tehran. The data of our case study are gathered from three primary sources as (1) the opinion of experts in the field, (2) IBTO and Tehran municipality documents, and (3) relevant published studies (Dehghani Ashkezari & Yaghoubi, 2020; Hosseini-Motlagh et al., 2020a; Nikpouraghdam et al., 2020; Samani et al., 2019; Yousefi Nejad Attari et al., 2017). Noteworthy, the dimension of the parameters of the model is presented in Table 3.Table 3 Dimension of the main parameters in the case study
Parameter Unit
Plasma Liter
Cost Million Rials (Iran currency)
Distance Kilometer
Carbon emission Gram
As mentioned, Tehran metropolitan has 22 municipal districts. Each city district is considered one group that can donate regular and convalescent plasma donors. The donation capacities of the districts are estimated based on their population. The geographical coordination of the districts and the estimated donation in a month are provided in Table 4.Table 4 Properties of Tehran municipal districts
District Population Geographical coordinates Regular plasma supply Convalescent plasma supply
Latitude Longitude Whole Apheresis Whole Apheresis
1 420,409 35.8025 51.45972 36,292.12 18,146.06 10.19 4.37
2 649,260 35.7575 51.36222 56,047.86 28,023.93 15.73 6.74
3 331,173 35.75444 51.44806 28,588.76 14,294.38 8.02 3.44
4 836,026 35.74194 51.49194 72,170.57 36,085.29 20.26 8.68
5 719,555 35.74889 51.30028 62,116.13 31,058.06 17.44 7.47
6 277,738 35.73722 51.30028 23,975.94 11,987.97 6.73 2.88
7 350,631 35.72194 51.40583 30,268.48 15,134.24 8.50 3.64
8 419,171 35.72444 51.44611 36,185.25 18,092.63 10.16 4.35
9 206,350 35.68361 51.49833 17,813.32 8906.66 5.00 2.14
10 356,065 35.68361 51.31722 30,737.58 15,368.79 8.63 3.70
11 315,688 35.67944 51.36667 27,252.00 13,626.00 7.65 3.28
12 288,494 35.68000 51.39583 24,904.46 12,452.23 6.99 3.00
13 286,171 35.70778 51.42639 24,703.93 12,351.96 6.93 2.97
14 523,878 35.67444 51.51417 45,224.16 22,612.08 12.69 5.44
15 684,706 35.63083 51.47028 59,107.76 29,553.88 16.59 7.11
16 331,615 35.63944 51.47361 28,626.91 14,313.46 8.04 3.44
17 296,469 35.65389 51.40917 25,592.91 12,796.45 7.18 3.08
18 357,634 35.65167 51.36306 30,873.02 15,436.51 8.67 3.71
19 290,233 35.62056 51.29278 25,054.58 12,527.29 7.03 3.01
20 376,080 35.59028 51.36694 32,465.39 16,232.69 9.11 3.91
21 200,240 35.69056 51.25778 17,285.87 8642.93 4.85 2.08
22 149,120 35.74722 51.20417 12,872.90 6436.45 3.61 1.55
There are two fixed collection centers in districts 5 and 6 to donate regular plasma in Tehran. To increase the collection capacity of the network, three more fixed centers in areas 1, 2, and 4 have been considered candidate points for donation. Since the beginning of the pandemic, the IBTO has been deemed the Vesal center and a center in district two as temporary centers for receiving recovery plasma. Two new candidate locations for locating new mobile centers exist in districts 1 and 3. Tehran's current plasma supply chain works with one processing facility, i.e., the Vesal center. Establishing more processing facilities is necessary due to the high demand rate in Tehran. Three other points in districts 14, 19, and 22 are assumed as the candidate locations for establishing new processing facilities. There are ten medical centers for COVID-19 patients in Tehran. The features of these medical centers are provided in Table 5.Table 5 Properties of medical centers for COVID-19 patients
Center Num Name Geographical coordinates Demand for convalescent plasma Center Num Name Geographical coordinates Demand for convalescent plasma
Latitude Longitude Latitude Longitude
1 Razi Hospital 35.67198 51.40806 38.85 6 Torfeh Hospital 35.69579 51.43483 33.78
2 Yaftabad Hospital 35.64386 51.31149 66.43 7 Imam Hussein Hospital 35.70661 51.45102 56.86
3 Sina Hospital 35.68632 51.41236 258.41 8 Imam Khomeini Hospital 35.70844 51.38067 619.27
4 Lolagar Hospital 35.69462 51.37284 51.23 9 Ziaeian Hospital 35.65769 51.35909 81.07
5 Madaen Hospital 35.69932 51.40346 75.44 10 Baqiyatallah Hospital 35.75654 51.39685 371
Currently, there is a demand for regular plasma from eight hospitals in Tehran. The detailed properties of these hospitals are shown in Table 6.Table 6 Hospitals' properties
Center Num Name Geographical coordinates Demand for regular plasma Center Num Name Geographical coordinates Demand for regular plasma
Latitude Longitude Latitude Longitude
1 Atieh Hospital 35.76549 51.36176 152.00 5 Lolagar Hospital 35.69462 51.37284 51.23
2 Ansari Hospital 35.72115 51.48862 56.30 6 Madaen Hospital 35.69932 51.40346 75.44
3 Yas Hospital 35.71859 51.41460 30.40 7 Torfeh Hospital 35.69579 51.43483 33.78
4 Sina Hospital 35.68632 51.41236 258.41 8 Imam Hussein Hospital 35.70661 51.45102 56.86
Finally, one pharmaceutical company in Tehran utilized regular plasma to produce some plasma-based drugs. The properties of this single-center are presented in Table 7.Table 7 Properties of pharmaceutical company
Center Num Name Geographical coordinates Demand for regular plasma
Latitude Longitude
1 Delta pharmacy center 35.76244 51.33486 16,200
The geographical location of the established and candidate facilities and the demand points in Tehran's current plasma supply chain is schematically provided in Fig. 4. The transportation cost between facilities is estimated at 0.22 Million Rials per kilometer. The distance between each pair of nodes is calculated using the following distance formula (Jabbarzadeh et al., 2014):58 Δij=6371.1×cos-1sinLati×sinLatj+cosLati×cosLatj×cosLongj-Longi
where Lat and Long are the geographical latitude and longitude, respectively, and should be converted to radian by multiplying π180. The carbon emission coefficients of transportation between nodes are calculated regarding the travel distance and the vehicle's load as 0.062 g/kilogram/ton. The location cost for the established facilities is set to zero, and the total available budget for motivational programs for recovered donors is assumed to be about 500 Million Rials. This case study is analyzed for three months planning horizon.Fig. 4 Geographical location of concerned facilities and demand points
Implementation
Tehran's green plasma supply chain case study is coded in the GAMS programming environment on a laptop with a Core i7 CPU 2.6 GHz and 8 GB RAM, where the solver is CPLEX. The corresponding payoff Table 8 shows the obtained results where the value in this table is calculated by optimization of each objective function separately.Table 8 Payoff table of the case study
Total cost Total carbon emission
TC∗ 46,879,718.74 67,623.66
TE∗ 829,270,873.00 0
As seen, the minimum value for the total emission function is zero, which is the case where there is no flow of plasma and convalescent plasma in the network. In contrast, the maximum amount of carbon emission has happened when there is no attention to the environmental concerns, and the total cost is considered the network's objective.
The total cost function is considered the objective function, and the total emission function is bounded in model constraints with different upper bounds, implementing the epsilon constraint method. The obtained Pareto solutions are reported in Table 9.Table 9 Optimal Pareto solutions
Pareto solution
1 2 3 4 5 6 7 8
ε(TE∗) 0 11295.28 22590.55 33885.83 45181.11 56476.39 67771.66 79066.94
TC∗ 87022392.87 66752904.77 61453749.21 57686864.78 55112589.9 53481439.96 53145827.24 53014784.77
CPUtime 00:01:12 00:01:05 00:00:47 00:00:55 00:00:48 00:00:52 00:00:51 00:01:03
%Gap 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Regarding the provided results in Table 9, the dimension of the problem is not increased by changing the bound for the total carbon emission, and the computational time is similar. Moreover, the gap between the obtained solutions is zero, which confirms that the CPLEX solver is able to reach the global optimum solutions for this case study.
The Pareto frontier is also drawn in Fig. 5, representing the total cost against the total carbon emission. As evident, the total cost behaves against the total carbon emission. The rationale for this behavior is that while increasing the flow of regular and convalescent plasma reduces the shortage quantity and the system's overall cost; it hurts the system's total carbon emission by increasing transportation activities.Fig. 5 The Pareto frontier of the case study
For further analysis of the results, the 8th Pareto solution (ε=79066.94,TC∗=53014784.77) is selected. For this solution, established mobile collection centers, fixed collection centers, and processing facilities are shown in Tables 10, 11 and 12. As seen, the current network states require locating all candidate mobile and fixed collection centers. In addition, there is a need to build a new processing facility in district 4.Table 10 Optimal locations of mobile collection centers in each period
Period Mobile collection center
District 1 District 2 District 3 Vesal
t=1 1 1 1 1
t=2 1 1 1 1
t=3 1 1 1 1
Table 11 Optimal establishment decision of fixed collection centers
Candidate fixed collection center District 1 Destrict2 District 4 District 5 District 6
Establishment state Established Established Established Established Established
Table 12 Optimal establishment decision of processing facilities
Candidate processing facility Vesal District 4 District 19 District 22
Establishment state Established Established Non established Non established
Such a need for establishing new facilities shows the pandemic's imposed load and proves the necessity of proper planning by considering the special features of COVID-19.
The assignment pattern of supply chain facilities, including regular donors and recovered donors, to the related collection centers, collection centers to processing facilities, and processing facilities to demand points, is presented in Tables 13, 14, 15, 16, 17, 18 and 19. Note that the donation method r=1 shows the whole blood donation method, and r=2 is the apheresis method. Besides, m = 1 to m = 4 offers the mobile collection centers 1, 2, 3, and Vesal, and f=1 to f=5 are the indices of the fixed collection centers in districts 1, 2, 4,5, and 6. The processing facilities Vesal, district 4, district 19, and district 22 are indexed by p=1 to 4. The indices of the demand points are according to the mentioned number in Tables 5, 6 and 7.Table 13 Optimal allocation of regular donors groups to fixed collection centers
Period Optimal allocation pattern (i,f,r)
t=1 (5,1,1), (5,4,1), (7,5,2), (8,2,1), (8,3,2), (9,2,2), (13,4,2), (14,1,2), (14,5,1)
t=2 (5,2,2), (6,4,2), (7,3,2), (13,5,2), (21,1,2)
t=3 (1,3,2), (1,5,2), (4,4,2), (9,1,2), (18,2,2)
Table 14 Optimal allocation of recovered donors groups to mobile collection centers
Period Optimal allocation pattern (j,m,r)
t=1 (1,1,1), (1,3,2), (2,2,2), (2,4,1), (3,3,1), (4,2,1), (4,4,2), (5,2,1), (5,4,2), (8,1,2), (8,3,1), (14,1,1), (14,3,2), (15,2,2), (15,4,1), (20,1,2)
t=2 (1,1,2), (1,3,1), (2,1,1), (2,2,2), (3,2,1), (3,3,2), (4,1,1), (4,4,2), (5,3,2), (5,4,1), (8,2,2), (8,3,1), (14,1,2), (14,4,1), (15,2,1), (15,4,2)
t=3 (1,4,2), (2,2,1), (2,3,2), (3,3,1), (4,3,2), (4,4,1), (5,1,1), (5,2,2), (8,1,2), (8,2,1), (10,1,2), (14,1,1), (14,2,2), (15,3,1), (15,4,2), (20,4,1)
Table 15 Optimal allocation of mobile collection centers to processing facilities
Period Optimal allocation pattern (m,p,r)
t=1 (1,1,1), (1,1,2), (2,1,1), (2,1,2), (3,1,1), (3,1,2), (4,1,1), (4,1,2)
t=2 (1,1,1), (1,1,2), (2,1,1), (2,2,2), (3,1,1), (3,1,2), (3,2,2), (4,1,1), (4,2,2)
t=3 (1,1,1), (1,1,2), (2,1,1), (2,1,2), (3,1,1), (3,1,2), (4,1,1), (4,1,2), (4,2,2)
Table 16 Optimal allocation of fixed collection centers to processing facilities
Period Optimal allocation pattern (f,p,r)
t=1 (1,1,1), (1,1,2), (2,1,1), (2,2,1), (2,2,2), (3,1,2), (4,2,1), (4,2,2), (5,1,1), (5,1,2)
t=2 (1,1,2), (2,2,2), (3,1,2), (4,2,2), (5,1,2)
t=3 (1,2,2), (2,2,2), (3,1,2), (4,2,2), (5,1,2)
Table 17 Optimal allocation of processing facilities to medical centers for COVID-19 patients
Period Optimal allocation pattern (p, c, t″)
t′=1 (1,1,1), (2,1,1)
t′=2 (1,1,2), (2,1,2)
t′=3 (1,1,3), (2,1,3)
Table 18 Optimal allocation of processing facilities to hospitals
Period Optimal allocation pattern (p, h, t″)
t′=1 (1,1,1), (1,2,1), (1,3,1), (1,4,1), (1,6,1), (1,7,1), (1,8,1), (2,5,1)
t′=2 (1,1,2), (1,2,2), (1,3,2), (1,4,2), (1,5,2), (1,6,2), (1,7,2), (1,8,2)
t′=3 (1,1,3), (1,2,3), (1,3,3), (1,4,3), (1,5,3), (1,6,3), (1,7,3), (1,8,3)
Table 19 Optimal allocation of processing facilities to pharmaceutical company
Period Optimal allocation pattern (p, h, t″)
t′=1 (1,3,1)
t′=2 (1,3,2), (2,9,2)
t′=3 (1,8,3)
The total cost is divided into its main parts to provide more insights into the cost performance of the network. The results are shown in Table 20. As seen in this table, the limited supply of convalescent plasma, high demand in the COVID-19 pandemic, and the high unit shortage cost of these products have led to a large part of the chain's total cost.Table 20 The components of the total cost function
Plasma supply chain cost components
Donation cost Location cost Production cost Inventory cost Allocation cost Motivational Programs cost Transshipment cost Shortage cost
Related cost 21144753.36 440200.00 2010453.48 311.78 278596.77 500.00 7.67 29139961.72
The percentage of each component is also graphically shown on a pie chart in Fig. 6. The shortage cost of products encompasses approximately 55% of the network cost. The donation cost accounts for about 40% of the total cost and ranks second. As can be seen, a small portion of the total cost is caused by transshipment cost, and this is because only a small portion of the convalescent plasma flow is transshipped in the case study’s network.Fig. 6 Percentage of the total cost function components
The total carbon emission of the supply plasma chain is divided into sub-elements, and the results are provided in Table 21. We can conclude that the volume flow of the regular plasma causes a significant portion of the emitted carbon. As all the mobile collection centers remain fixed during the planning horizon, there is no carbon emission from the movement of these facilities.Table 21 The components of the total carbon emission function
Plasma supply chain carbon emission components
Movement of mobile facilities Fixed collection center
s-processing facilities Mobile collection centers
and
processing facilities Processing facilities
and
pharmaceutical companies Processing facilities
and
hospitals Processing facilities
and
medical centers for COVID-19 patients Transshipment between processing facilities
Related carbon emission 0 43441.37 971.97 29199.12 5352.01 100.29 2.16
The schematic representation of the total carbon emission components and the relevant percentage is shown in Fig. 7.Fig. 7 Percentage of the total carbon emission function components
The role of each donation method is analyzed by comparing the collected quantity of each product through these methods in Fig. 8. Interestingly, most of the convalescent plasma volume is received through the whole blood method. In contrast, the total amount of received regular plasma through the apheresis method is higher than in the whole blood method. From this, it can concluded that none of these methods are superior to each other, and each may be selected regarding the features of the network.Fig. 8 Comparing the donation quantity of regular plasma and convalescent plasma by the considered donation methods
The role of each fixed and mobile center in the collection of products is investigated to see which center is more active in the collection process from the donors. The results in Fig. 9 show that the established fixed collection center in district 5 and the mobile collection center in district 2 receive a higher amount of plasma and convalescent plasma, respectively.Fig. 9 Comparing the collected quantity of regular plasma and convalescent plasma in the collection centers
The production portion of each product in the processing facilities is different, as demonstrated in Fig. 10. The Vesal center is more active in the production of convalescent plasma. Furthermore, more regular plasma should be produced in the production facility in district 2, compared to the Vesal center.Fig. 10 Comparing the production quantity of regular plasma and convalescent plasma by the established processing facilities
The state of demand satisfaction in the medical centers for COVID-19 patients is shown in Fig. 11, where the total shortage and the service level are presented. The limited donation of convalescent plasma made a huge impact on these demand points, and many of them are incapable of meeting the demand of their patients. As can be seen, there is a high volume of convalescent plasma shortages in most of these centers. Seven out of ten available medical centers for COVID-19 patients are unable to meet their demand, which shows the reason for the high shortage cost of the network.Fig. 11 Level of demand satisfaction in Medical centers for COVID-19 patients
The demand points for regular plasma can meet more demand than medical centers for COVID-19 patients. Due to the importance of the hospitals, more plasma is delivered to them in these conditions, and pharmaceutical companies consume the remaining plasma. As presented in Fig. 12, all hospitals can meet their demand, and there is a shortage only for a single pharmaceutical company in the network. The average service level of the demand points for regular plasma is about 95.8 percent. Here, all hospitals are capable of meeting their demand for regular plasma. The reason for such a high service level is the sufficient flow of regular plasma in the network.Fig. 12 Level of demand satisfaction in demand points for regular plasma
Sensitivity analyses
Sensitivity analyses are performed on some basic input parameters of the model, including the supply and demand of plasma and convalescent plasma, to obtain more insights into the performances of the presented model. The impact of parameter variation in the −30% to + 30% interval is investigated on the system's total cost and total carbon emission in the implemented analysis.
The demand for convalescent plasma may change during the pandemic. Some reasons, such as national social distancing or shutdowns, may reduce the rate of disease. In contrast, ignoring the alerts, making trips, and normalizing the activities may increase the infection rate. Each increase in the rate of infected people increases the demand for convalescent plasma. The impact of changing the demand for convalescent plasma is illustrated in Fig. 13. A slight increase trend can be observed in the total emission of the network. However, the system's total cost is much dependent on this parameter. Causing more demand in a limited supply situation results in more shortage and overall cost of the system.Fig. 13 Sensitivity of plasma supply chain objectives with respect to variation in demand of convalescent plasma
The changing trends of the total cost and total carbon emission, when the demand for regular plasma change is the same as the demand for convalescent plasma, are demonstrated in Fig. 14. Demand increasing in the condition of limited supply imposes more shortage on the system, and the overall cost will be increased. In this figure, the positive relation of the parameter with the objective functions can be seen. However, the primary difference is that the demand for regular plasma significantly impacts the supply chain's total cost and total carbon emission.Fig. 14 Sensitivity of plasma supply chain objectives with respect to variation in demand for regular plasma
According to Fig. 15, increasing the donation of the convalescent plasma reduces the total cost of the network to a reasonable level. When the donation rate rises, more infected patients can be treated, and as a result, the shortage cost and total cost of the system are decreased. Moreover, the more convalescent plasma flow positively correlates with the total carbon emission. This can be rationalized by the fact that the more flow of convalescent plasma in the network, the more carbon emission results from the transportation activities.Fig. 15 Sensitivity of plasma supply chain objectives with respect to variation in the supply of convalescent plasma
Contrary to the supply of convalescent plasma, variation in the supply of regular plasma in the considered interval has no meaningful effect on the objective functions of the system. This is illustrated in Fig. 16. This can be the result of several factors, such as the low shortage cost of regular plasma in the pharmaceutical company and the overall lower demand rate for the regular plasma product. In other words, when there is an adequate flow in the network, there is no need to receive more plasma from the donors.Fig. 16 Sensitivity of plasma supply chain objectives with respect to variation in the supply of regular plasma
Finally, we analyze the impact of changing the unit carbon emission multiplier of nodes on the objective functions of the network. The sensitivity analysis result of this parameter is graphically shown in Fig. 17.Fig. 17 Sensitivity of plasma supply chain objectives with respect to variation in the unit carbon emission parameters
As can be seen, reducing the unit carbon emission can significantly reduce the total carbon emission of the systems. In contrast, the parameters do not have any impact on the total cost of the system. The unit carbon emission parameters can be controlled by the type of vehicles used or investment in the other infrastructures of the network.
In the end, the summary of computational results is presented in Table 22 to provide better insights into the performance of Tehran's plasma supply chain network for managing this network during the COVID-19 pandemic.Table 22 Insights for managing the plasma supply chain of Tehran during the COVID-19 pandemic
Network component Managerial insights
Total cost A high cost of the network has resulted from the shortage of products in the network
Total carbon emission High carbon emission of the network has resulted from the flow of regular plasma between fixed collection centers and processing facilities
The total carbon emission of the systems is highly sensitive to the emission units between the network nodes
Collection centers The mobile facility in district 2 and fixed facility in district 5 have a more active role in the collection of donors
Donation method A higher proportion of regular plasma is collected through the whole blood method, while most recovered donors donate convalescent plasma through the apheresis method
Management must pay due attention to the provision of the desired equipment at the right time
Mobile collection centers The collection center should be placed in all four collection centers on the planning horizon, and there should be no movement or removal of facilities
Fixed collection centers The current collection capacity is not sufficient to meet the demand, and three new fixed collection centers should be established
Processing facilities To adequately meet the demand of patients, there is a need to establish a new processing facility in district 2, in addition to the Vesal center
A higher proportion of convalescent plasma production takes place in the Vesal center, while the new center in district 2 accounts for more blood production
Supply and demand The system has a high sensitivity to the demand for regular plasma and less sensitivity to the supply of regular plasma
Increasing the donation rate of convalescent plasma by assignment of more budget can reduce the overall cost meaningfully
Conclusions
This research presented a four-echelon multi-objective multi-product multi-period model to design a plasma supply chain network under the COVID-19 pandemic. The aim was simultaneous incorporation of convalescent plasma as a critical subsistence for treatment of infected patients and regular plasma, which is required by therapy and pharmacy sectors, as well as some other features of the COVID-19 pandemic in a plasma supply chain network for the first time. The arising environmental concerns from carbon emissions attracted attention in recent years. Hence, the resulted carbon emission of network activities was also considered to design a green supply chain. The objectives of the mixed-integer linear model were to minimize both the total cost and total carbon emission. A wide range of decisions, including location, allocation, production, inventory, and motivational programs, can be made by solving this model. The epsilon constraint method is adapted to make a trade-off between the objectives and handle the multi-objective nature of the problem. A real-world case study was investigated to examine the applicability and efficiency of the model. The exact Pareto solutions were obtained through solving the model by the CPLEX solver in the GAMS programming environment. A sensitivity analysis was carried out to get insights into the impact of some crucial parameters. The results showed that the shortage of plasma and convalescent plasma imposes a considerable cost on the network. In addition, a significant portion of carbon emission is imposed by the flow of regular plasma from the collection centers to the processing facilities. The sensitivity analysis results demonstrated that both objective functions are affected negatively by the increasing demand for products. The total cost increase is mainly due to the limited supply sources and the shortage cost. Here, the total carbon emission is increased because of increasing the transportation flow in the network.
This is not the endpoint, and various enhancement and development options exist. Researchers can investigate the following recommendations to extend the current work:I. Considering uncertainty in some model parameters such as the donation and demand (Samani et al., 2018). This research assumed a high degree of certainty for the donation and demand of the network. The pandemic status may not remain fixed, and the number of infected and recovered people can violate. Moreover, the donation and demand for regular plasma may not have a regular pattern. The extension of the proposed model under uncertainty can efficiently address these concerns.
II. Discussing the impact of investment on carbon emission reduction (Lou et al., 2015). Investment in the network’s infrastructures, such as transportation modes, can significantly reduce carbon emissions. Therefore, an investigation of the problem with emission investment seems interesting.
III. Developing the model under different carbon emission regulations, including cap-and-trade and carbon tax (Huang et al., 2020). Several countries use these regulations to curb carbon emissions. These policies can affect the optimal decision of the network. Reformulating the problem under these environmental policies is another suggestion for future works.
IV. Presenting solution methods such as benders decomposition, Lagrangian relaxation, and metaheuristics for solving the problem for large-size networks (Fallahi et al., 2022b). The presented model is solved for Tehran’s case study via a commercial solver. However, there may be more extensive supply chain networks that the commercial solver is not efficient in solving the problem. More advanced solution approaches can assist the managers in decision-making for such networks.
Author contributions
All authors conceived of the presented idea. Ali Fallahi and Seyed Alireza Mousavian Anaraki developed the theory and performed the computations. Hadi Mokhtari and Seyed Taghi Akhavan Niaki verified the analytical methods. All authors discussed the results and contributed to the final manuscript.
Funding
Not applicable.
Data availability and materials
Not applicable.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Consent to participate
Not applicable.
Consent to publish
Not applicable.
Ethical approval
This study has not been duplicate publication or submission elsewhere. The Local Ethics Committee approval was obtained.
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| 0 | PMC9734997 | NO-CC CODE | 2022-12-14 23:28:32 | no | Environ Dev Sustain. 2022 Dec 8;:1-52 | utf-8 | Environ Dev Sustain | 2,022 | 10.1007/s10668-022-02793-7 | oa_other |
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Stat Inference Stoch Process
Statistical Inference for Stochastic Processes
1387-0874
1572-9311
Springer Netherlands Dordrecht
9282
10.1007/s11203-022-09282-8
Article
High-dimensional estimation of quadratic variation based on penalized realized variance
Christensen Kim [email protected]
1
Nielsen Mikkel Slot [email protected]
2
Podolskij Mark [email protected]
3
1 grid.7048.b 0000 0001 1956 2722 Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
2 grid.7048.b 0000 0001 1956 2722 Department of Mathematics, Aarhus University, Aarhus, Denmark
3 grid.16008.3f 0000 0001 2295 9843 Department of Mathematics and Department of Finance, University of Luxembourg, Esch-sur-Alzette, Luxembourg
5 12 2022
129
25 3 2022
27 10 2022
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This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
In this paper, we develop a penalized realized variance (PRV) estimator of the quadratic variation (QV) of a high-dimensional continuous Itô semimartingale. We adapt the principle idea of regularization from linear regression to covariance estimation in a continuous-time high-frequency setting. We show that under a nuclear norm penalization, the PRV is computed by soft-thresholding the eigenvalues of realized variance (RV). It therefore encourages sparsity of singular values or, equivalently, low rank of the solution. We prove our estimator is minimax optimal up to a logarithmic factor. We derive a concentration inequality, which reveals that the rank of PRV is—with a high probability—the number of non-negligible eigenvalues of the QV. Moreover, we also provide the associated non-asymptotic analysis for the spot variance. We suggest an intuitive data-driven subsampling procedure to select the shrinkage parameter. Our theory is supplemented by a simulation study and an empirical application. The PRV detects about three–five factors in the equity market, with a notable rank decrease during times of distress in financial markets. This is consistent with most standard asset pricing models, where a limited amount of systematic factors driving the cross-section of stock returns are perturbed by idiosyncratic errors, rendering the QV—and also RV—of full rank.
Keywords
Bernstein’s inequality
LASSO estimation
Low rank estimation
Quadratic variation
Rank recovery
Realized variance
Shrinkage estimator
http://dx.doi.org/10.13039/100011199 FP7 Ideas: European Research Council 815703 Podolskij Mark http://dx.doi.org/10.13039/501100011958 Danmarks Frie Forskningsfond 1028-00030B 9056-00011B Christensen Kim Nielsen Mikkel Slot
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pmcIntroduction
The covariance matrix of asset returns is a central component, which is required in several contexts in financial economics, such as portfolio composition, pricing of financial instruments, or risk management (e.g., Andersen et al. (2003)). In the past few decades, estimation of quadratic variation (QV) from high-frequency data has been intensively studied in the field of econometrics. The standard estimator of QV, Σ, say over a window [0, 1], is the realized variance (RV) (e.g., Andersen and Bollerslev (1998); Barndorff-Nielsen and Shephard (2002, 2004); Jacod (1994)). Given a decreasing sequence (Δn)n≥1 with Δn→0 and equidistant observations (YiΔn)i=0⌊Δn-1⌋ of a d-dimensional semimartingale (Yt)t∈[0,1], the RV is defined as1.1 Σ^n=∑k=1⌊Δn-1⌋(ΔknY)(ΔknY)⊤,
where ΔknY=YkΔn-Y(k-1)Δn is the increment, and ⊤ denotes the transpose operator. The asymptotic properties of Σ^n are generally known, when the dimension d is fixed (e.g., Barndorff-Nielsen et al. (2006); Diop et al. (2013); Heiny and Podolskij (2020); Jacod (1994, 2008)). In particular, for any semimartingale Σ^n is by definition a consistent estimator of Σ.
When modeling the dynamics of a large financial market over a relatively short time horizon, one is often faced with an ill-posed inference problem, where the number of assets d is comparable to (or even exceeding) the number of high-frequency data ⌊Δn-1⌋ available to compute Σ^n. This renders RV inherently inaccurate, and it also implies that d cannot be treated as fixed in the asymptotic analysis. To recover an estimate of Σ in such a high-dimensional setting, the covariance matrix has to display a more parsimonious structure.
Currently, the literature on high-dimensional high-frequency data, mostly based on a continuous semimartingale model for the security price process, is rather scarce. Wang and Zou (2010) investigate optimal convergence rates for estimation of QV under sparsity constraints on its entries. Zheng and Li (2011) apply random matrix theory to estimate the spectral eigenvalue distribution of QV in a one-factor diffusion setting. Related work based on random matrix theory and eigenvalue cleaning, or on approximating the high-dimensional system by a low-dimensional factor model, can be found in, e.g., Cai et al. (2020); Hautsch et al. (2012); Lunde et al. (2016). Aït-Sahalia and Xiu (2017) study a high-dimensional factor model, where the eigenvalues of QV are assumed to be dominated by common components (spiked eigenvalue setting), and estimate the number of common factors under sparsity constraints on the idiosyncratic components.
In the context of joint modeling of the cross-section of asset returns, if a factor model is adopted, one should expect a small number of eigenvalues of Σ to be dominant (see also Sect. 4). In other settings, such as when the market is complete and some entries of Yt reflect prices on derivative contracts (spanned by the existing assets and therefore redundant), one should even expect the rank of the volatility to be strictly smaller than the dimension. In such an instance, the rank of the covariance matrix is smaller than d, meaning that the intrinsic dimension of the system can be represented in terms of a driving Brownian motion of lower dimension. In general, identifying a low rank can, for instance, help with the economic interpretation of the model, or it may lighten the computational load related to its estimation or simulation. We refer to several recent studies on identification and estimation of the intrinsic dimension of the driving Brownian motion and eigenvalue analysis of QV in Aït-Sahalia and Xiu (2017, 2019); Fissler and Podolskij (2017); Jacod et al. (2008); Jacod and Podolskij (2013, 2018), see also Kong (2017, 2020) in the high-dimensional setting. A related contribution of Pelger (2019) incorporates a finite-activity jump process in the model.
In this paper, we develop a regularized estimator of Σ called the penalized realized variance (PRV). We draw from the literature of shrinkage estimation in linear regression (e.g., Hoerl and Kennard (1970); Tibshirani (1996)). In particular, we propose the following LASSO-type estimator of Σ based on the RV in (1.1):1.2 Σ^nλ=argminA∈Rd×d‖Σ^n-A‖22+λ‖A‖1.
Here, λ≥0 is a tuning parameter that controls the degree of penalization, while ‖·‖1 and ‖·‖2 denote the nuclear and Frobenius matrix norm. It has been shown in various contexts that estimators based on nuclear norm regularization possess good statistical properties, such as having optimal rates of convergence and being of low rank. For instance, Koltchinskii et al. (2011) study such properties in the trace regression model and, in particular, in the matrix completion problem, where one attempts to fill out missing entries of a partially observed matrix. Negahban and Wainwright (2011) adopt a rather general observation model and, among other things, cover estimation in near low rank multivariate regression models and vector autoregressive processes. Further references in this direction include Argyriou et al. (2008); Bach (2008); Candès and Recht (2009); Recht et al. (2010). While previous papers on nuclear norm penalization are solely dedicated to discrete-time models, the current work is—to the best of our knowledge—the first to study this problem in a continuous-time Itô setting. This implies a number of subtle technical challenges, since the associated high-frequency data are dependent and potentially non-stationary.
We provide a complete non-asymptotic theory for the PRV estimator in (1.2) by deriving bounds for the Frobenius norm of its error. We show that it is minimax optimal up to a logarithmic factor. The derivation relies on advanced results from stochastic analysis combined with a Bernstein-type inequalities presented in Theorems 2.3 and 2.4, which constitute some of the major theoretical contributions of the paper. The latter builds upon recent literature on concentration inequalities for matrix-valued random variables, but it is more general as the variables are allowed to be both dependent and unbounded. We discuss the necessary conditions on d and Δn to ensure consistency results. We further show that in a “local-to-deficient” rank setting, where some eigenvalues are possibly decreasing as the dimension of the system increases, the penalized estimator in (1.2) identifies the number of non-negligible eigenvalues of Σ with high probability.
The estimator depends on a tuning parameter λ. We exploit the subsampling approach of Christensen et al. (2017) to choose a data-driven amount of shrinkage in the implementation. We also provide a related theoretical analysis for the local volatility, which is more likely to exhibit a lower rank than QV (the latter is only expected to have a near low rank in many settings).
In the empirical analysis, we look at the 30 members of the Dow Jones Industrial Average index to demonstrate that our results are consistent with a standard Fama–French three-factor structure, and one may expect a lower number of factors during crisis.
The paper proceeds as follows. In Sect. 2, we establish concentration inequalities for the estimation error ‖Σ^nλ-Σ‖2 and show minimax optimality up to a logarithmic factor. In Sect. 2.3, we present sufficient conditions to ensure that the rank of Σ^nλ coincides with the number of non-negligible eigenvalues of Σ with high probability. In Sect. 2.4, we show how the tuning parameter λ can be selected with a data-driven approach. In Sect. 3, the associated non-asymptotic theory for estimation of the instantaneous variance is developed. In Sect. 4, we design a simulation study to demonstrate the ability of our estimator to identify a low-dimensional factor model through rank(Σ^nλ). In Sect. 5, we implement the estimator on empirical high-frequency data from the 30 members of the Dow Jones Industrial Average index. The proofs are included in the appendix.
Notation
This paragraph introduces some notation used throughout the paper. For a vector or a matrix A the transpose of A is denoted by A⊤. We heavily employ the fact that any real matrix A∈Rm×q admits a singular value decomposition (SVD) of the form:1.3 A=∑k=1m∧qskukvk⊤
where s1≥⋯≥sm∧q are the singular values of A, and {u1,⋯,um∧q} and {v1,⋯,vm∧q} are orthonormal vectors. If m=q and A is symmetric and positive semidefinite, its singular values coincide with its eigenvalues and the SVD is the orthogonal decomposition (meaning that one can take vk=uk). Sometimes we write sk(A), vk(A) and uk(A) to explicitly indicate the dependence on the matrix A. The rank of A is denoted by rank(A), whereas1.4 rank(A;ε)=∑k=1m∧q1[ε,∞)(sk)
is the number of singular values of A exceeding a certain threshold ε∈[0,∞). Note that ε↦rank(A;ε) is non-increasing on [0,∞), and càdlàg and piecewise constant on (0,∞). Furthermore, rank(A;0)=m∧q and limε↓0rank(A;ε)=rank(A). We denote by ‖A‖p the Schatten p-norm of A∈Rm×q, i.e.,1.5 ‖A‖p=∑k=1m∧qskp1/p
for p∈(0,∞). Moreover, ‖A‖∞ denotes the maximal singular value of A, i.e., ‖A‖∞=s1. In particular, in this paper we work with p=1, p=2, and p=∞ corresponding to the nuclear, Frobenius, and spectral norm. The Frobenius norm is also induced by the inner product ⟨A,B⟩=tr(A⊤B) and we have the trace duality1.6 ⟨A,B⟩≤‖A‖1‖B‖∞.
For a linear subspace S⊆Rm, S⊥ denotes the linear space orthogonal to S and PS stands for the projection onto S.
Given two sequences (an)n≥1 and (bn)n≥1 in (0,∞), we write an=o(bn) if limn→∞an/bn=0 and an=O(bn) if lim supn→∞an/bn is bounded. Furthermore, if both an=O(bn) and bn=O(an), we write an≍bn. Finally, to avoid trivial cases we assume throughout the paper that the dimension d of the process (Yt)t∈[0,1] is at least two.
Theoretical framework
We suppose a d-dimensional stochastic process Yt=(Y1,t,⋯,Yd,t)⊤ is defined on a filtered probability space (Ω,F,(Ft)t∈[0,1],P). In our context, Yt is a time t random vector of log-prices of financial assets, which are traded in an arbitrage-free, frictionless market and therefore semimartingale (e.g., Delbaen and Schachermayer (1994)). In particular, we assume (Yt)t∈[0,1] is a continuous Itô semimartingale, which can be represented by the stochastic differential equation:2.1 dYt=μtdt+σtdWt,t∈[0,1],
where (Wt)t∈[0,1] is an adapted d-dimensional standard Brownian motion, (μt)t∈[0,1] is a progressively measurable and locally bounded drift with values in Rd, and (σt)t∈[0,1] is a predictable and locally bounded stochastic volatility with values in Rd×d. In the above setting the QV (or integrated variance) is Σ=∫01ctdt, where ct≡σtσt⊤. We remark that the length T=1 of the estimation window [0, T] is fixed for expositional convenience and is completely without loss of generality, since a general T can always be reduced to the unit interval via a suitable time change.
Note that we exclude a jump component from (2.1). It should be possible to extend our analysis and allow for at least finite-activity jump processes. To do so, we can replace the RV with its truncated version, following the ideas of Mancini (2009). We leave the detailed analysis of more general jump processes for future work. Apart from these restrictions, our model is essentially nonparametric, as it allows for almost arbitrary forms of random drift, volatility, and leverage.
Upper bounds for the PRV
The goal of this section is to derive a sharp upper bound on the estimation error ‖Σ^nλ-Σ‖2 that apply with high probability, where the PRV estimator Σ^nλ has been defined in (1.2). We first show that the PRV can alternatively be found by soft-thresholding of the eigenvalues in the orthogonal decomposition of Σ^n.
Proposition 2.1
Let Σ^n=∑k=1dskukuk⊤ be the orthogonal decomposition of Σ^n. Then, the unique solution Σ^nλ to (1.2) is given by2.2 Σ^nλ=∑k=1dmaxsk-λ2,0ukuk⊤.
Proposition 2.1 is standard (see Koltchinskii et al. (2011)), but we state it explicitly for completeness. The interpretation of the PRV representation in (2.2) is that all “significant” eigenvalues of Σ^n are shrunk by λ/2, while the smallest ones are set to 0. Hence, we only retain the principal eigenvalues in the orthogonal decomposition of Σ^n. The PRV can therefore account for a (near) low rank constraint. In the next proposition, we present a general non-probabilistic oracle inequality for the performance of Σ^nλ.
Proposition 2.2
Assume that 2‖Σ^n-Σ‖∞≤λ. Then, it holds that2.3 ‖Σ^nλ-Σ‖22≤infA∈Rd×d‖A-Σ‖22+min2λ‖A‖1,3λ2rank(A).
In particular, ‖Σ^nλ-Σ‖22≤min2λ‖Σ‖1,3λ2rank(Σ).
The statement of Proposition 2.2 is also a general algebraic result that is standard for optimization problems under nuclear penalization (e.g., Koltchinskii et al. (2011)). It says that an oracle inequality for Σ^nλ is available if we can control the stochastic error ‖Σ^n-Σ‖∞. The latter is absolute key to our investigation.
In order to assess this error, we need to impose the following assumption on the norms of the drift and volatility processes.
Assumption (A): supt∈[0,1]‖μt‖22≤νμ, supt∈[0,1]tr(ct)≤νc,2, and supt∈[0,1]‖ct‖∞≤νc,∞ for some constants νμ, νc,2, and νc,∞ with νc,∞≤νc,2.
Mathematically speaking, Assumption (A) appears a bit strong, since it imposes an almost sure bound on the drift and volatility. We can weaken the requirement on the drift to a suitable moment condition without affecting the rate of ‖Σ^n-Σ‖∞ in Theorem 2.4 below, but as usual the cost of this is more involved expressions. If the volatility does not meet the boundedness condition, which it does not for most stochastic volatility models, one can resort to the localization technique from Sect. 4.4.1 in Jacod and Protter (2012). In most financial applications, however, Assumption (A) is not too stringent if the drift and volatility do not vary strongly over short time intervals, such as a day.
The constants νμ, νc,2, and νc,∞ may depend on d, but they should generally be as small as possible to get the best rate (see, e.g., (2.13)). For example, if the components of μ and c are uniformly bounded, we readily deduce that2.4 νμ=O(d)andνc,2=O(d).
To study the concentration of ‖Σ^n-Σ‖∞, we present an exponential Bernstein-type inequality, which applies to matrix-valued martingale differences as long as the conditional moments are sufficiently well-behaved. While there are several related concentration inequalities (see, e.g., Minsker (2017); Tropp (2011, 2012, 2015) and references therein), existing results require that summands are either independent or bounded. Thus, to be applicable in our setting we needed to modify these.
Theorem 2.3
Suppose that (Xk)k=1n is a martingale difference sequence with respect to a filtration (Gk)k=0n and with values in the space of symmetric d×d matrices. Assume that, for some predictable sequence (Ck)k=1n of random variables and constant R∈(0,∞),2.5 ‖EXkp∣Gk-1‖∞≤p!2RpCk,fork=1,⋯,nandp=2,3,⋯
Then, for all x,ν∈(0,∞), it holds that2.6 P‖∑k=1nXk‖∞>x,∑k=1nCk≤ν≤2dexp-x22(xR+νR2).
Assume that Theorem 2.3 applies and that C1,⋯,Cn in (2.5) can also be chosen to be deterministic. Then, with ν=∑k=1nCk,2.7 P‖∑k=1nXk‖∞>x≤2dexp-x4νR2min{x,νR},
so ‖∑k=1nXk‖∞ has a sub-exponential tail. The next theorem derives a concentration inequality for ‖Σ^n-Σ‖∞. We remark that, although we have Theorem 2.3 at our disposal, the derivation of Theorem 2.4 requires a number of non-standard inequalities in order to prove that R in (2.5) can be chosen sufficiently small. For further details, see the discussion in relation to its proof in the supplementary file.
Theorem 2.4
Suppose that Assumption (A) holds. Then, there exists an absolute constant γ such that2.8 P‖Σ^n-Σ‖∞>x≤6dexp-xγνc,2νc,∞Δnmin{x,νc,∞},
for all x≥γmaxνc,2νμΔnνc,∞,νc,2νμΔn,νc,∞Δn.
We now combine Proposition 2.2 and Theorem 2.4 to deliver a result on the concentration of ‖Σ^n-Σ‖2, which is the main statement of this section.
Theorem 2.5
Suppose that Assumption (A) holds. For a given τ∈(0,∞) consider a regularization parameter λ such that2.9 λ≥γmaxνc,2νc,∞Δn(log(d)+τ),νc,2Δn(log(d)+τ),νc,2νμΔnνc,∞,
where γ is a large absolute constant. Then, with probability at least 1-e-τ,2.10 ‖Σ^nλ-Σ‖22≤‖Σ-A‖22+min{2λ‖A‖1,3λ2rank(A)},
for all A∈Rd×d.
If the drift term is non-dominant, in the sense that νμ≤νc,∞, it follows that the regularization parameter λ should meet2.11 λ≥γmaxνc,2νc,∞Δnlog(d)+τ,νc,2Δnlog(d)+τ,
for an absolute constant γ. To get a concentration probability as large as possible without impairing the rate implied by (2.10), we should choose τ≍log(d). Moreover, the first term of the maximum in (2.11) is largest for 1/Δn≥(log(d)+τ)νc,2/νc,∞. In light of these observations, the following corollary is an immediate consequence of Theorem 2.5, so we exclude the proof.
Corollary 2.6
Suppose that Assumption (A) holds with νμ≤νc,∞≤νc,2. Assume further that Δn-1≥2νc,2νc,∞log(d) and choose the regularization parameter2.12 λ=γνc,2νc,∞Δnlog(d),
where γ is a sufficiently large absolute constant. Then, it holds that2.13 ‖Σ^nλ-Σ‖22≤3γ2νc,2νc,∞rank(Σ)Δnlog(d)
with probability at least 1-d-1.
It follows from (2.13) that the estimation error of Σ^nλ is closely related to the size of νc,2 and νc,∞, which are both determined from the properties of the volatility process. If c is uniformly bounded, νc,2=O(d). As emphasized by Tropp (2015, Section 1.6.3), we can also often assume that ‖cs‖∞ and, hence, νc,∞ can be chosen independently of d. When this is the case, the rate implied by (2.13) is rank(Σ)Δndlog(d), and since rank(Σ)≤d, Corollary 2.6 implies consistency of Σ^nλ when both Δn→0 and d→∞ so long as d2log(d)=o(Δn-1). If rank(Σ) can be further bounded by a constant (that does not depend on d), the growth condition on d improves to dlog(d)=o(Δn-1). In contrast, for the estimation error ‖Σ^n-Σ‖22→0, one cannot expect a better condition than d2=o(Δn-1), since this estimation error corresponds to a sum of d2 squared error terms, each of the order Δn.
Minimax optimality
We denote by Cr, for a given non-zero integer r≤d, the subclass of d×d symmetric positive semidefinite matrices S+d whose effective rank is bounded by r:2.14 Cr=A∈S+d:re(A)≤r,
where2.15 re(A)≡tr(A)‖A‖∞.
Compared to the rank, the effective rank is a more stable measure for the intrinsic dimension of a covariance matrix (see, e.g., (Vershynin 2010, Remark 5.53)). In the following we argue that Σ^nλ, with λ of the form (2.12), is a minimax optimal estimator of Σ in the parameters νc,2, νc,∞, and rank(Σ) over the parametric class of continuous Itô processes generated by (2.1) with no drift μs≡0 and a constant volatility σs≡A for A∈Cr. To this end, denote by PA a probability measure for which (Yt)t∈[0,1] is defined as in (2.1) with no drift and constant volatility cs≡A. In this setting, we can choose νc,2=tr(A) and νc,∞=‖A‖∞, which by Corollary 2.6 means that2.16 supA∈CrPA‖Σ^nλ-Σ‖22>γ¯‖A‖∞2re(A)rank(A)Δnlog(d)≤1d,
for an absolute constant γ¯ and Δn-1≥2rlog(d).
Now, since the log-price increments Δ1nY,⋯,Δ⌊Δn-1⌋nY are i.i.d. Gaussian random vectors under PA, we can exploit existing results from the literature to assess the performance of Σ^nλ. Hence, the following is effectively an immediate consequence of Theorem 2 in Lounici (2014). It shows that, up to a logarithmic factor, no estimator can do better than (2.16).
Theorem 2.7
Let Cr be given as in (2.14) and suppose that ⌊Δn-1⌋≥r2. Then, there exist absolute constants β∈(0,1) and γ_∈(0,∞) such that2.17 infΣ^supA∈CrPA‖Σ^-Σ‖22>γ_‖A‖∞2re(A)rank(A)⌊Δn-1⌋≥β,
where the infimum runs over all estimators Σ^ of Σ based on (Δ1nY,⋯,Δ⌊Δn-1⌋nY).
Bound on the rank of PRV
In this section, we study the rank of Σ^nλ relative to the number of non-negligible eigenvalues and, in particular, the true rank of Σ. In line with Sect. 2.1, we begin by stating a general non-probabilistic inequality in Theorem 2.8. In the formulation of this result, we recall that rank(A;ε) is the number of singular values of A exceeding ε∈[0,∞).
Theorem 2.8
Suppose that 2‖Σ^n-Σ‖∞≤λ¯ for some λ¯∈(0,∞). Then2.18 rank(Σ;λ)≤rank(Σ^nλ)≤rankΣ;12(λ-λ¯),
for any λ∈(λ¯,∞). In particular, if λ∈(λ¯,s], where s is the smallest non-zero eigenvalue of Σ, then rank(Σ^nλ)=rank(Σ).
With this result in hand we can rely on the exponential inequality for the quantity ‖Σ^n-Σ‖∞ established in Theorem 2.4 to show that, with high probability and in addition to converging to Σ at a fast rate, Σ^nλ automatically has the rank of Σ when we neglect eigenvalues of sufficiently small order. In particular, if Σ has full rank, but many of its eigenvalues are close to zero, Σ^nλ is of low rank and reflects the number of important components (or factors) in Σ.
Corollary 2.9
Suppose that Assumption (A) holds with νμ≤νc,∞≤νc,2 and fix δ∈(0,1/2). Assume further that Δn-1≥2νc,2νc,∞log(d) and, for a sufficiently large constant γ depending only on δ, choose the regularization parameter λ as follows:2.19 λ=γνc,2νc,∞Δnlog(d).
Then, with probability at least 1-d-1, it holds that2.20 ‖Σ^nλ-Σ‖22≤3γ2νc,2νc,∞rank(Σ)Δnlog(d),
and2.21 rank(Σ;λ)≤rank(Σ^nλ)≤rank(Σ;δλ).
If, in addition, λ≤s, where s is the smallest non-zero eigenvalue of Σ, then both rank(Σ^nλ)=rank(Σ) and (2.20) hold with probability at least 1-d-1.
In the setting of Corollary 2.9, it follows that with high probability an eigenvalue s of Σ affects rank(Σ^nλ) for large n if λ=o(s), while it does not if s=o(λ). The first condition says that, relative to the level of shrinkage, an eigenvalue is significant (or non-negligible), whereas the second says the opposite. Hence, the notion of negligibility depends on λ, which in turn depends on the model through the constants νc,2 and νc,∞. However, we know that for Σ^nλ to be a consistent estimator of Σ, a necessary condition is that λ→0 as n→∞, which implies that for an eigenvalue of Σ to be negligible, it must tend to zero as n increases. In particular, if d is fixed, rank(Σ^nλ)=rank(Σ) with a probability tending to one as n→∞.
The following example illustrates a stylized setting, where many eigenvalues of Σ are negligible.
Example 2.10
Let r∈N be an absolute constant (i.e., independent of d and n). In line with the factor model studied in Aït-Sahalia and Xiu (2017), suppose that ct is of the form2.22 ct=βetβ⊤+gt,
where et∈Rr×r and gt∈Rd×d are predictable, symmetric, and positive definite processes, which are uniformly bounded such that ‖et‖∞≤Ce and ‖gt‖∞≤Cg for some constants Ce,Cg=O(1). The matrix β∈Rd×r of factor loadings is deterministic and constant in time; a common assumption in the literature, which is also supported by Reiss et al. (2015). The form (2.22) of ct can be motivated by a standard multi-factor model, where the total risk associated with any of the d assets can be decomposed into a systematic and an idiosyncratic component. The systematic component βetβ⊤ is composed of loadings on the r underlying priced common factors in the economy, β, and the risk of those factors, et. The idiosyncratic component gt is asset-specific and can therefore be reduced by diversification.
Suppose that, given an initial set of d individual securities, we start forming a new set of (orthogonalized) portfolios by taking linear combinations of the original assets, as prescribed by the APT model of Ross (1976), and a standard way to implement factor models in practice when constructing sorting portfolios. Then, these new assets are generally diversified enough to assume that Cg=O(d-1). To identify the number of driving factors, r, we assume that ‖d-γβ⊤β-Ir‖∞=o(1) (as d→∞) and sr(et)≥ε for some absolute constants γ∈[0,1] and ε∈(0,∞). This corresponds to Assumption 4 in Aït-Sahalia and Xiu (2017), but it is slightly more general as the assets are assumed to be diversified portfolios.
Now, given a suitable drift process (μt)t∈[0,1], Corollary 2.9 applies with regularization parameter λ=OdγΔnlog(d). In particular, due to the fact 0≤sk(Σ)-sk(βEβ⊤)≤‖Γ‖∞ with E=∫01etdt and Γ=∫01gtdt, it follows from (2.21) that2.23 rank(βEβ⊤;λ)≤rank(Σ^nλ)≤rank(βEβ⊤;δλ-‖Γ‖∞)
with probability at least 1-d-1. By assumption |sr(βEβ⊤)-dγsr(E)|=o(dγ) and sr(E)≥ε (the former follows from arguments as in the proof of Theorem 1 in Aït-Sahalia and Xiu (2017)), and hence dγ=O(sr(βEβ⊤)). Combining this with (2.23), we conclude that rank(Σ^nλ)=r with probability at least 1-d-1 if both log(d)=o(Δn-1) and Δn-1=o(d2+2γlog(d)), and n is large. Or to put it differently, rank(Σ^nλ) is, with a probability tending to one, exactly the number of underlying factors in the model.
We remark that the restrictions imposed above are too weak to ensure that the Frobenius estimation error ‖Σ^nλ-Σ‖2 tends to zero, meaning that our estimator can be used to detect the underlying factor structure even in very high-dimensional settings. To ensure the estimation error is small, we need d1+2γlog(d)=o(Δn-1) rather than log(d)=o(Δn-1).
Selection of tuning parameter
In view of Theorem 2.7 and Corollary 2.9, it follows that Σ^nλ can be of low rank and accurate, given optimal tuning of λ. However, as evident from (2.19), λ depends on the latent spot variance process (ct)t∈[0,1] through νc,2 and νc,∞ as well as the unknown absolute constant γ, whose value can be important in finite samples.
We remark that Σ^n-Σ provides an estimate of the null matrix, but it is perturbed by randomness in the data. Hence, a good choice of shrinkage parameter exactly shrinks the eigenvalues of Σ^n-Σ to zero (in view of problem (1.2) with Σ^n replaced by Σ^n-Σ). By Proposition 2.1, this means λ=2‖Σ^n-Σ‖∞.
The above is unobservable. To circumvent this problem and facilitate the calculation of our estimator in Sect. 4 and 5, we adopt a data-driven shrinkage selection by exploiting the subsampling technique of Christensen et al. (2017), see also Politis et al. (1999) and Kalnina (2011). To explain the procedure in short, suppose for notational convenience that n=Δn-1. We select an integer L—the number of subsamples—that divides n and assign log-returns successively to each subsample. Hence, the lth subsample consists of the increments Δ(k-1)L+lnYk=1,…,n/L for l=1,⋯,L. We denote the associated subsampled RV by2.24 Σ^n,l=1n/L∑k=1n/L(nΔ(k-1)L+lnY)(nΔ(k-1)L+lnY)⊤,
Note that the random matrices in the sequence (Σ^n,l)l=1L are asymptotically conditionally independent, as n→∞. Moreover, it follows from Christensen et al. (2017) that as n→∞, L→∞ and n/L→∞, the half-vectorization of n/L(Σ^n,l-Σ^n) and n(Σ^n-Σ) converge in law to a common mixed normal distribution, derived in Barndorff-Nielsen and Shephard (2004, Theorem 1).
Hence, in each subsample λ=2‖Σ^n-Σ‖∞ can be approximated by2.25 λl=2L‖Σ^n,l-Σ^n‖∞
As an estimator of λ, we therefore take the sample average:2.26 λ∗=1L∑l=1Lλl.
Estimation of the local variance
As noted in Sect. 1, the rank of the local variance ct is often much smaller than the rank of Σ. In fact, although Σ may be well-approximated by a matrix of low rank, we should expect that rank(Σ)=d. On the other hand, there are many situations where it is reasonable to expect that rank(ct) is small, in which case it provides valuable insight about the complexity of the underlying model. This motivates developing a theory for the spot version of our penalized estimator with particular attention on its ability to identify rank(ct).
To estimate ct, we follow Jacod and Protter (2012) and apply a localized realized variance, which is defined over a block of ⌊hn/Δn⌋≥2 log-price increments with hn∈(0,1). The RV computed over the time window [t,t+hn], for t∈(0,1-hn], is then defined as follows:3.1 Σ^n(t;t+hn)=∑k=⌊t/Δn⌋+1⌊(t+hn)/Δn⌋(ΔknY)(ΔknY)⊤.
The corresponding penalized version Σ^nλ(t;t+hn) is computed as3.2 Σ^nλ(t;t+hn)=argminA∈Rd×d‖Σ^n(t;t+hn)-A‖22+λ‖A‖1,
or by using Proposition 2.1 with Σ^n replaced by Σ^n(t;t+hn). Then, the penalized estimator c^nλ(t) of ct is given by3.3 c^nλ(t)=Σ^nλ(t;t+hn)hn.
Also, we write3.4 Σ(t1;t2)=∫t1t2csds,
for the QV over (t1,t2] for arbitrary time points t1,t2∈[0,1] with t1<t2.
Recall that for a convex and increasing function ψ:[0,∞)→[0,∞) with ψ(0)=0, the Orlicz norm of a random variable Z with values in the Hilbert space (Rd×d,‖·‖2) is defined as:3.5 ‖Z‖ψ≡infc>0:E[ψ(‖Z‖2/c)]≤1.
This setting includes, in particular, the Lp(P) norms (with ψ(s)=sp), but also the ψ1 and ψ2 norms for sub-exponential (ψ(s)=es-1) and sub-Gaussian (ψ(s)=es2-1) random variables. For convenience, we further impose the mild restriction that the range of ψ is [0,∞), so it admits an inverse ψ-1 on [0,∞).
Theorem 3.1
Suppose that Assumption (A) holds with νμ≤νc,∞≤νc,2. Furthermore, let t∈[hn2,1-3hn2] and assume sup0≤u<s≤1‖cs-cu‖ψ/s-u≤νc,ψ and hn≥2Δnνc,2νc,∞log(d). Take the regularization parameter λ as3.6 λ=γhnΔnνc,2νc,∞log(d)
for a sufficiently large absolute constant γ. Then,3.7 ‖c^nλ(t)-ct‖22≤κγ2νc,2νc,∞ΔnrankΣ(t-hn2;t+3hn2)hn+hnνc,ψ2log(d),
with probability at least 1-d-1-ψ(log(d))-1 for some absolute constant κ.
The bound on the estimation error of c^nλ(t) builds on Corollary 2.6, but Theorem 3.1 further enforces a smoothness condition on (ct)t∈[0,1]. It entails a trade-off between the smoothness of spot variance and the concentration probability associated with (3.7). For example, if (ct)t∈[0,1] is 1/2-Hölder continuous in L2(P), which corresponds to setting ψ(s)=s2, then we end up with a concentration probability converging to one at rate log(d)-1, which is slower than for the PRV. On the other hand, if (ct)t∈[0,1] is 1/2-Hölder continuous in the sub-Gaussian norm ψ(s)=es2-1, the concentration probability converges to one at the rate d-1, which is equivalent to the PRV.
Note that with d fixed, (3.7) reveals how to select the length of the estimation window hn optimally. The upper bound depends on Δn/hn and hn, and for these terms to converge to zero equally fast, we should take hn≍Δn. This is consistent with the literature on spot variance estimation; see, e.g., Jacod and Protter (2012).
The next result, which relies on Corollary 2.9, shows that the rank and performance of c^nλ(t) can be controlled simultaneously.
Theorem 3.2
Suppose that Assumption (A) holds with νμ≤νc,∞≤νc,2 and fix δ∈(0,1/4). Furthermore, let t∈[hn2,1-3hn2] and assume that sup0≤u<s≤1‖cs-cu‖ψ/s-u≤νc,ψ. Suppose further that hn≥2Δnνc,2νc,∞log(d) and consider a regularization parameter λ such that3.8 λ=γhnΔnνc,2νc,∞log(d),
for a sufficiently large constant γ depending only on δ. Then, with probability at least 1-d-1-ψ(log(d))-1, it holds that3.9 ‖c^nλ(t)-ct‖22≤κγ2νc,2νc,∞ΔnrankΣ(t-hn2;t+3hn2)hn+hnνc,ψ2log(d),
and3.10 rank(ct;ε¯)≤rank(c^nλ(t))≤rank(ct;ε_),
where3.11 ε_≡δγmax{νc,2νc,∞Δnhn-νc,ψhn,0}log(d),ε¯≡γνc,2νc,∞Δnhn+νc,ψhnlog(d),
and κ is an absolute constant. If, in addition, ε_>0 and ε¯≤srank(ct)(ct), then both (3.9) and rank(c^nλ(t))=rank(ct) hold with probability at least 1-d-1-ψ(log(d))-1.
Consider the setting of Theorem 3.2. For the upper bound in (3.10) to be useful, we must have that ε_>0 or, equivalently,3.12 νc,ψ2hn2<νc,2νc,∞Δn.
Suppose that νc,2, νc,∞, and νc,ψ do not depend on n. The inequality (3.12) can then be achieved in large samples by choosing hn=o(Δn). However, as pointed out above one should take hn≍Δn in order to achieve an optimal rate for the estimation error ‖c^nλ(t)-ct‖22. In that case, (3.12) translates directly into an upper bound on νc,ψ, which concerns the smoothness of (ct)t∈[0,1].
When can the term rank(Σ(t-hn2;t+3hn2)) in the upper bound of (3.9) be replaced by rank(ct)? This question appears difficult to answer in general, but it is not too difficult to show that the replacement is valid if the volatility process is locally constant.
Simulation study
In this section, we do a Monte Carlo analysis to inspect the finite sample properties of the PRV, Σ^nλ. The aim here is to demonstrate the ability of our estimator to detect the presence of near deficient rank in a large-dimensional setting. In view of Theorem 3.2, this can be achieved by a proper selection of λ. We simulate a d=30-dimensional log-price process Yt. The size of the vector corresponds to the number of assets in our empirical investigation. We assume Yt follows a slightly modified version of the r=3-factor model proposed in Aït-Sahalia and Xiu (2019):4.1 dYt=βdFt+dZt,t∈[0,1],
where Ft∈Rr is a vector of systematic risk factors, which has the dynamic:4.2 dFt=αdt+σtLdWt,
and Wt∈Rr is a standard Brownian motion. The drift term α∈Rr is constant α=(0.05,0.03,0.02)⊤. The random volatility matrix σt=diag(σ1,t,σ2,t,σ3,t)∈Rr×r, where diag(·) is a diagonal matrix with coordinates ·, is simulated as a Heston (1993) square-root process:4.3 dσj,t2=κj(θj-σj,t2)dt+ηjσj,tρjdWj,t+1-ρj2dW~j,t,
for j=1,⋯,r, where W~t∈Rr is an r-dimensional standard Brownian motion independent of Wt. As in Aït-Sahalia and Xiu (2019), the parameters are κ=(3,4,5)⊤, θ=(0.05,0.04,0.03)⊤, η=(0.3,0.4,0.3)⊤, and ρ=(-0.60,-0.40,-0.25)⊤. The factor correlation is captured by the Cholesky component L:4.4 ρ=LL⊤=1.000.050.100.051.000.150.100.151.00.
The idiosyncratic component Zt∈Rd is given by4.5 dZt=gtdBt,
where gt=diag(γ1,t2,⋯,γd,t2) with4.6 dγj,t2=κZ(θZ-γj,t2)dt+ηZγj,tdB~j,t,
for j=1,⋯,d, and Bt∈Rd and B~t∈Rd are independent d-dimensional standard Brownian motions. Thus, gt is the instantaneous variance of the unsystematic component. We set κZ=4, θZ=0.25, and ηZ=0.06. Hence, the idiosyncratic error varies independent in the cross-section of assets, but the parameters controlling the dynamics are common.Fig. 1 Relative importance of eigenvalues in simulated model. Note. In Panel A, we plot for daily RV the relative size of the three largest eigenvalues, and also the average of the remaining 27 eigenvalues. In Panel B, we plot a histogram of the sample average of the relative size of each of the eigenvalues across simulations
The above setup implies4.7 ct=βσtρσtβ⊤+gt,
so the spot covariance matrix has full rank at every time point t. However, it has only r=3 large eigenvalues associated with the systematic factors, while the remaining d-r associated with the idiosyncratic variance are relatively small. Note that in contrast to Aït-Sahalia and Xiu (2019), we allow for time-varying idiosyncratic variance.
We set Δn=1/n with n=78. This corresponds to 5-minute sampling frequency within a 6.5 hour window. Hence, d is relatively large compared to n. We construct 10,000 independent replications of this model. At the beginning of each simulation, we draw the associated factor loadings β∈Rd×r at random such that the first column (interpreted as the loading on the market factor) are from a uniform distribution on (0.25, 1.75), i.e. βi1∼U(0.25,1.75), i=1,⋯,d. The range of the support is consistent with the realized beta values reported in Table 1 in Sect. 5. The remaining columns are generated as βij∼N(0,0.52), i=1,⋯,d and j=2 and 3.
In Panel A of Fig. 1, we plot the relative size of the three largest eigenvalues, extracted from the corresponding RV, together with the average of the remaining 27 eigenvalues. In Panel B, we include a histogram of the relative size of the eigenvalues across simulations. We observe that it is generally challenging to distinguish important factors from idiosyncratic variation, since the relative size of the eigenvalues decays smoothly with the exception of the largest (and perhaps the second largest) eigenvalue.
In each simulation, we employ the subsampling procedure described in Sect. 2.4 with L=6 to choose λ∗.1Fig. 2 Properties of the PRV. Note. In Panel A, we report a kernel density estimate of the shrinkage parameter λ, expressed in percent of the maximal eigenvalue of the RV matrix. In Panel B, we show the relative frequency histogram of the associated rank of the PRV
In Panel A of Fig. 2, we report the distribution of the λ∗ parameter across simulations, which is here expressed in percent of the maximal eigenvalue of RV. Overall, the penalization is relatively stable with a tendency to shrink around one-fourth to one-third of the largest eigenvalue most of the times.
In Panel B, we plot a histogram of the relative frequency of the rank of the PRV. In general, the PRV does a good job at identifying the number of driving factors, given the challenging environment. Although there are variations in the rank across simulations, caused by the various sources of randomness incorporated in our model, the picture is close to the truth. This means we tend to identify about one-to-three driving factors. The average rank estimate is 1.79, so as expected there is a slight tendency to overshrink leading to a small downward bias. Based on these findings, we can confidently apply the PRV in the empirical application.
Empirical application
In this section, we apply the PRV to an empirical dataset. The sample period is from January 3, 2007 through May 29, 2020 (3,375 trading days in total) and includes both the financial crisis around 2007 – 2009 and partly the recent events related to Covid-19.Table 1 Descriptive statistics of high-frequency data
Realized beta
Code N σRV σϵ Median [q0.05,q0.95]
AAPL 171,438 0.227 0.165 0.990 [0.539, 1.784]
AXP 42,379 0.279 0.207 1.016 [0.532, 1.730]
BA 41,579 0.249 0.192 0.918 [0.427, 1.489]
CAT 41,943 0.256 0.187 1.154 [0.570, 1.747]
CSCO 111,876 0.223 0.163 0.997 [0.498, 1.470]
CVX 54,037 0.223 0.163 0.887 [0.370, 1.407]
DIS 56,563 0.213 0.157 0.863 [0.411, 1.303]
DOW 35,108 0.240 0.179 1.002 [0.467, 1.567]
GS 42,098 0.287 0.216 1.091 [0.572, 1.812]
HD 50,777 0.222 0.163 0.878 [0.422, 1.343]
IBM 35,955 0.182 0.131 0.769 [0.402, 1.136]
INTC 126,855 0.233 0.174 1.026 [0.531, 1.586]
JNJ 54,527 0.151 0.120 0.534 [0.168, 0.982]
JPM 127,497 0.296 0.216 1.135 [0.680, 1.911]
KO 55,932 0.156 0.126 0.496 [0.116, 0.891]
MCD 36,777 0.168 0.134 0.523 [0.137, 0.902]
MMM 24,253 0.183 0.131 0.825 [0.426, 1.201]
MRK 60,637 0.197 0.161 0.695 [0.241, 1.166]
MSFT 162,004 0.211 0.154 0.957 [0.501, 1.543]
NKE 32,390 0.216 0.171 0.806 [0.360, 1.260]
PFE 97,351 0.196 0.159 0.726 [0.281, 1.184]
PG 53,787 0.157 0.128 0.490 [0.117, 0.918]
RTX 31,372 0.203 0.149 0.861 [0.445, 1.248]
TRV 18,855 0.219 0.175 0.688 [0.220, 1.190]
UNH 37,540 0.251 0.212 0.771 [0.247, 1.307]
V 44,085 0.228 0.188 0.835 [0.322, 1.336]
VZ 69,710 0.185 0.146 0.560 [0.139, 1.033]
WBA 37,302 0.218 0.181 0.786 [0.261, 1.308]
WMT 59,091 0.165 0.135 0.525 [0.154, 0.906]
XOM 90,346 0.203 0.146 0.809 [0.332, 1.261]
Note. “Code” is the ticker symbol, “N” is the number of transactions, “σRV” is the annualized square-root realized variance, “σϵ” is the standard deviation of the idiosyncratic component. The latter is computed as σϵ2=σRV2-β2σSPY2, where β is the realized beta between the asset and SPY (acting as market portfolio)
We look at high-frequency data from the 30 members of the Dow Jones Industrial Average (DJIA) index as of April 6, 2020.2 The ticker codes of the various firms are listed in Table 1, along with selected descriptive statistics. As readily seen from Table 1, most of these companies are very liquid. In order to compute a daily RV matrix estimate we collect the individual 5-minute log-return series spanning the 6.5 hours of trading on U.S. stock exchanges from 9:30am to 4:00pm EST.3 Hence, our analysis is based on a relatively large cross-section (i.e., d=30) compared to the sampling frequency (i.e., n=78). The realized beta in Table 1 is calculated with SPY acting as market portfolio. The latter is an exchange-traded fund that tracks the S &P500 and its evolution is representative of the overall performance of the U.S. stock market. The dispersion of realized beta is broadly consistent with the simulated values generated in Sect. 4.Fig. 3 Proportion of variance explained by each eigenvalue. Note. In Panel A, we plot for each day in the sample the relative size of the three largest eigenvalues of RV, as well as the average of the remaining 27. In Panel B, we plot a histogram of the time series average of the relative size of each eigenvalues
In Fig. 3, we depict the factor structure in the time series of RV. In Panel A, we compute on a daily basis the proportion of the total variance (i.e., trace) explained by each eigenvalue, whereas Panel B reports the sample average of this statistic. As consistent with Aït-Sahalia and Xiu (2019), we observe a pronounced dynamic evolution in the contribution of each eigenvalue to RV with notably changes corresponding to times of severe distress in financial markets. The first factor captures the vast majority of aggregate return variation (about 35% on average). It is followed by a few smaller—but still important—factors accountable for an incremental 25% – 30% of the total variance, whereas the last 25 or so eigenvalues are relatively small.Fig. 4 Rank of PRV. Note. In Panel A, we report the relative frequency of the rank of the PRV. In Panel B, we compare the estimated rank to the effective rank, where both are smoothed over a three-month moving average window
Next, we turn our attention to the PRV estimator. To select the shrinkage parameter λ, we follow the subsampling implementation from the simulation section. The relative frequency histogram of the rank of the PRV is reported in Panel A of Fig. 4, whereas Panel B reports a three-month (90-day) moving average of the rank. The vast majority (around 95%) of the daily rank estimates are between one and three, which is consistent with a standard Fama–French three-factor interpretation of the data. There are relatively few rank estimates at four, and it never exceeds five (with about a dozen of the latter). In Panel B, we observe the rank varies over time in an intuitive fashion, often dropping close to a single-factor representation during times of crisis, where correlations tend to rise. As a comparison, we compute the effective rank of the RV (cf. (2.15)), which does not depend on a shrinkage parameter. There is a high association between the series, which is consistent with a soft-thresholding that eliminates smaller eigenvalues of the RV.
Conclusion
In this paper, we develop a novel and powerful penalized realized variance estimator, which is applicable to estimate the quadratic variation of high-dimensional continuous-time semimartingales under a low rank constraint. Our estimator relies on regularization and adapts the principle ideas of the LASSO from regression analysis to the field of high-frequency volatility estimation in a high-dimensional setting. We derive a non-asymptotic analysis of our estimator, including bounds on its estimation error and rank. The estimator is found to be minimax optimal up to a logaritmic factor. We design a completely data-driven procedure for selecting the shrinkage parameter based on a subsampling approach. In a simulation study, the estimator is found to possess good properties. In our empirical application, we confirm a low rank environment that is consistent with a three-factor structure in the cross-section of log-returns from the large-cap segment of the U.S. stock market.
A Appendix of proofs
This appendix presents the proofs of the results from the main text.
Proof of Proposition 2.1
Since the map A↦Ln(A)≡‖Σ^n-A‖22+λ‖A‖1 is strictly convex, the minimizer A of Ln is uniquely determined by the property that 0∈Rd×d belongs to the setA.1 ∂Ln(A)={2(A-Σ^n)+λ∑k=1duk(A)vk(A)⊤+PS1(A)⊥WPS2(A)⊥:‖W‖∞≤1}.
Here, ∂Ln(A) denotes the subdifferential of Ln at A, and we employ Watson (1992) to get the explicit expression of this set in (A.1). Moreover, {u1(A),⋯,ud(A)} and {v1(A),⋯,vd(A)} are the vectors introduced in the notation paragraph associated with the SVD of A, whereas S1(A) and S2(A) are the corresponding linear spans, and PS is the projection matrix onto the subspace S. With Σ^nλ given as in (2.2), we find that ∂Ln(Σ^nλ) coincides with the set of matrices V of the form:A.2 V=-2∑k:sk≤λ/2skukuk⊤+λPUWPU,
where W∈Rd×d is such that ‖W‖∞≤1, and U is the linear span of {uk:sk≤λ/2}. With W=2λ∑k:sk≤λ/2skukuk⊤, it follows that ‖W‖∞≤1 by submultiplicativity of the norm and PUWPU=W. Hence, (A.2) shows that 0∈∂Ln(Σ^nλ), so Σ^nλ is the unique minimizer of Ln. □
Proof of Proposition 2.2
The structure of the proof is based similar to the one of Theorem 1 in Koltchinskii et al. (2011), but is modified to fit our setting. Starting from the definition of Σ^nλ, and since Ln(A)=‖Σ^n-A‖22+λ‖A‖1, it follows thatA.3 Ln(Σ^nλ)≤Ln(A)
for any A∈Rd×d. Note also that‖Σ^n-A‖22-‖A-Σ‖22-‖Σ^n-Σ^nλ‖22+‖Σ^nλ-Σ‖22=2⟨Σ^nλ-A,Σ^n-Σ⟩.
By using the above identity and (A.3),‖Σ^nλ-Σ‖22≤‖A-Σ‖22+2⟨Σ^nλ-A,Σ^n-Σ⟩+λ‖A‖1-‖Σ^nλ‖1.
The first term in the minimum follows by observing that2⟨Σ^nλ-A,Σ^n-Σ⟩+λ(‖A‖1-‖Σ^nλ‖1)≤2‖Σ^nλ-A‖1‖Σ^n-Σ‖∞+λ(‖A‖1-‖Σ^nλ‖1)≤2λ‖A‖1,
where we employ the trace duality ⟨A1,A2⟩≤‖A1‖1‖A2‖∞, the triangle inequality, and the assumption that 2‖Σ^n-Σ‖∞≤λ. To show the second part of the proposition, we observe that if B is a subgradient of Ln at Σ^nλ, then by definitionLn(A)-Ln(Σ^nλ)≥⟨B,A-Σ^nλ⟩
or, equivalently,‖A‖22+λ‖A‖1-‖Σ^nλ‖22-λ‖Σ^nλ‖1≥⟨B+2Σ^n,A-Σ^nλ⟩
for all matrices A. This shows that B+2Σ^n is a subgradient of the function A↦‖A‖22+λ‖A‖1 at Σ^nλ and, thus, B=2Σ^nλ-2Σ^n+λV^ for an appropriate V^∈∂‖Σ^nλ‖1. Moreover, because Σ^nλ is a minimizer of Ln, there must exist B∈∂Ln(Σ^nλ) such that ⟨B,Σ^nλ-A⟩≤0 for all A∈Rd×d (see, e.g., (Clarke 1990), Section 2.4). Combining these facts, we establish thatA.4 2⟨Σ^nλ,Σ^nλ-A⟩+λ⟨V^,Σ^nλ-A⟩≤2⟨Σ^n,Σ^nλ-A⟩
for some V^∈∂‖Σ^nλ‖1 and any A∈Rd×d. Note the identityA.5 2⟨Σ^nλ-Σ,Σ^nλ-A⟩=‖Σ^nλ-Σ‖22+‖Σ^nλ-A‖22-‖A-Σ‖22.
Now, fix A∈Rd×d and consider a generic matrix V∈∂‖A‖1. Then, if we subtract ⟨2Σ+λV,Σ^nλ-A⟩ on both sides of (A.4), exploit (A.5), and note that ⟨V^-V,Σ^nλ-A⟩≥0 by the monotonicity of subdifferentials (see (Clarke 1990, Proposition 2.2.9)), we deduce thatA.6 ‖Σ^nλ-Σ‖22+‖Σ^nλ-A‖22≤‖A-Σ‖22+λ⟨V,A-Σ^nλ⟩+2⟨Σ^n-Σ,Σ^nλ-A⟩.
We shall bound each of the last two terms on the right-hand side of (A.6), starting with ⟨V,A-Σ^nλ⟩. According to Watson (1992), with r=rank(A) and A=∑k=1rskukvk⊤ being the SVD of A, the subdifferential ∂‖A‖1 has the characterization:∂‖A‖1=∑k=1rukvk⊤+PS1⊥WPS2⊥:‖W‖∞≤1.
Here, S1 and S2 denote the span of {u1,⋯,ur} and {v1,⋯,vr}, respectively. By the polar decomposition, one finds that W∈Rd×d with ‖W‖∞=1 and ⟨W,PS1⊥Σ^nλPS2⊥⟩=‖PS1⊥Σ^nλPS2⊥‖1. Fixing V to be the subgradient associated with this choice of W,A.7 ⟨V,A-Σ^nλ⟩=〈∑k=1rukvk⊤,A-Σ^nλ〉-⟨W,PS1⊥Σ^nλPS2⊥⟩=〈∑k=1rukvk⊤,PS1(A-Σ^nλ)PS2〉-‖PS1⊥Σ^nλPS2⊥‖1≤‖PS1(Σ^nλ-A)PS2‖1-‖PS1⊥Σ^nλPS2⊥‖1≤r‖Σ^nλ-A‖2-‖PS1⊥Σ^nλPS2⊥‖1.
The last term on the right-hand side of (A.6) can be handled by setting B=Σ^n-Σ-PS1⊥(Σ^n-Σ)PS2⊥. The Cauchy–Schwarz inequality and trace duality then delivers the estimate:A.8 ⟨Σ^n-Σ,Σ^nλ-A⟩≤|⟨B,Σ^nλ-A⟩|+|⟨Σ^n-Σ,PS1⊥Σ^nλPS2⊥⟩|≤‖B‖2‖Σ^nλ-A‖2+λ2‖PS1⊥Σ^nλPS2⊥‖1.
For any given matrix M∈Rd×d:M-PS1⊥MPS2⊥=PS1M+PS1⊥MId-PS2⊥=PS1M+PS1⊥MPS2.
Thus,‖M-PS1⊥MPS2⊥‖2≤r‖PS1M‖∞+‖PS1⊥MPS2⊥‖∞≤2r‖M‖∞.
This shows that ‖B‖2≤λr. Hence, by combining (A.6) – (A.8) we get‖Σ^nλ-Σ‖22+‖Σ^nλ-A‖22≤‖A-Σ‖22+3λr‖Σ^nλ-A‖2.
By subtracting ‖Σ^nλ-A‖22 on both sides and using the inequality α2/4≥αβ-β2 with α=3λr and β=‖Σ^nλ-A‖2, we arrive at the second term in the minimum (with A=Σ):‖Σ^nλ-Σ‖22≤‖A-Σ‖22+3λ2r.
□
Proof of Theorem 2.3
We set Sn=∑k=1nXk and νn=∑k=1nCk. The subadditivity of the maximal eigenvalue function λmax(·) implies thatA.9 λmaxθSn-θ22(1-θ)νnId≥θx-θ22(1-θ)ν,
whenever λmax(Sn)≥x, νn≤ν and θ∈(0,1). By exponentiating both sides of (A.9), applying the spectral mapping theorem and that λmax(A)≤tr(A) for any positive semidefinite matrix A,A.10 Pλmax(Sn)≥x,νn≤ν≤PYn≥expθx-θ22(1-θ)ν≤E[Yn]exp-θx+θ22(1-θ)ν,
where Yn=tr[expθSn-θ22(1-θ)νnId]. Suppose for the moment that R=1, so that ‖E[Xkp∣Gk-1]‖∞≤p!2Ck for all k and integers p≥2. Since E[Xk∣Gk-1]=0, it then follows that‖E[exp(θXk)∣Gk-1]‖∞≤1+∑p=2∞θp‖E[Xkp∣Gk-1]‖∞p!≤1+θ22(1-θ)Ck≤expθ22(1-θ)Ck.
Thus, the matrixexpθ22(1-θ)CkId-E[exp(θXk)∣Gk-1]
is positive semidefinite, and hence it follows by Tropp (2011, Lemma 2.1) that (Yk)k=1n is a positive supermartingale with Y0=d. By combining this observation with (A.10) and choosing θ=x/(x+ν), we conclude thatPλmax(Sn)≥x,νn≤ν≤dexp-x22(x+ν).
The general result can now be deduced by taking X~k=Xk/R. □
A key ingredient to verify the conditions of Theorem 2.3 and prove Theorem 2.4 below is a suitable version of the Burkholder–Davis–Gundy inequality. We shall employ the one given in (Seidler and Sobukawa 2003, Lemma 2.2), which is restated here for convenience. Note that, although their result applies to martingales with values in a general Hilbert space, we specialize the formulation here to the finite-dimensional setting.
Lemma A.1
(Seidler and Sobukawa (2003)) Let m∈N and T∈(0,∞). For any constant p∈[2,∞) there exists γp∈(0,∞) such thatE[supt∈[0,T]‖∫0tφsdWs‖2p]≤γppE[∫0T‖φt‖22dtp/2]
for all predictable processes φ:Ω×[0,T]→Rm×d with ∫0TE[‖φt‖2p]dt<∞. Moreover, one can always takeA.11 γp=4pp-1p+12.
With the choice in (A.11), γp is of smaller asymptotic order (as p→∞) than the constant associated with the usual Burkholder–Davis–Gundy inequalities available by application of Itô’s formula (cf. the proof of Proposition 2.1 in Marinelli and Röckner (2016)).
Proof of Theorem 2.4
We decompose the log-price into the drift and volatility component Yt=Ytμ+Ytσ, where Ytμ=∫0tμsds and Ytσ=∫0tσsdWs. By the triangle inequality,A.12 P‖Σ^n-Σ‖∞>x≤P‖∑k=1⌊Δn-1⌋(ΔknYμ)(ΔknYμ)⊤‖∞>x5+2P‖∑k=1⌊Δn-1⌋(ΔknYμ)(ΔknYσ)⊤‖∞>x5+P‖∑k=1⌊Δn-1⌋(ΔknYσ)(ΔknYσ)⊤-∫0⌊Δn-1⌋Δnctdt‖∞>x5+P‖∫⌊Δn-1⌋Δn1ctdt‖∞>x5≡a1+2a2+a3+a4.
Jensen’s inequality implies that for the first term in (A.12),A.13 a1≤P∑k=1⌊Δn-1⌋‖ΔknYμ‖22>x5≤1{x<5νμΔn}.
The fourth term can be bounded as:A.14 a4≤1{x<5νc,∞Δn}.
To handle the third term in (A.12), we note it has the form a3=∑k=1⌊Δn-1⌋(Ak-Bk), whereAk=(ΔknYσ)(ΔknYσ)⊤,Bk=∫(k-1)ΔnkΔnctdt,
and that (Ak-Bk)k=1⌊Δn-1⌋ is a martingale difference sequence with respect to the filtration (FkΔn)k=0⌊Δn-1⌋. Thus, we can apply Theorem 2.3 if we can controlMp,k≡‖E[(Ak-Bk)p∣F(k-1)Δn]‖∞,
for integer p≥2. First note that, since ‖Bk‖∞≤νc,∞Δn, the sub-multiplicativity of ‖·‖∞ and the binomial theorem imply thatA.15 Mp,k≤‖E[Akp∣F(k-1)Δn]‖∞+∑i=1ppiE[‖Ak‖∞p-i∣F(k-1)Δn](νc,∞Δn)i.
We start by analyzing the second term on the right-hand side of (A.15). For an arbitrary integer m≥1 and any F(k-1)Δn-measurable set A, it follows from Lemma A.1 thatE[‖Ak‖∞m1A]=E[‖∫(k-1)ΔnkΔnσt1AdWt‖22m]≤γ2m2mE[∫(k-1)ΔnkΔntr(ct)dtm1A]
and, thus,A.16 E[‖Ak‖∞m∣F(k-1)Δn]1/m≤αmνc,2Δn
for a suitable absolute constant α≥1. In particular, (A.16) shows that E[‖Ak‖∞p-i∣F(k-1)Δn]≤(αpνc,2Δn)p-i for i=1,⋯,p. Together with the mean value theorem and Stirling’s formula, we can therefore establish thatA.17 ∑i=1ppiE[‖Ak‖∞p-i∣F(k-1)Δn](νc,∞Δn)i≤(αpνc,2Δn)p∑i=1ppiνc,∞αpνc,2i≤p!2(eανc,2Δn)p[1+νc,∞αpνc,2p-1]≤p!2(2eανc,2Δn)pνc,∞νc,2.
Now, look at the first term on the right-hand side of (A.15). For a fixed u∈Rd with ‖u‖2=1, it follows from the Cauchy–Schwarz inequality thatA.18 u⊤E[Akp∣F(k-1)Δn]u=E[‖Ak‖∞p-1(u⊤(ΔknY))2∣F(k-1)Δn]≤E[‖Ak‖∞2(p-1)∣F(k-1)Δn]1/2E[(u⊤ΔknY)4∣F(k-1)Δn]1/2.
The first term in (A.18) is handled by (A.16) with m=2(p-1):A.19 E[‖Ak‖∞2(p-1)∣F(k-1)Δn]1/2≤(2α(p-1)νc,2Δn)p-1≤p!2(2eανc,2Δn)pνc,2Δn.
The second term is treated as:A.20 E[(u⊤ΔknY)4∣F(k-1)Δn]1/2≤γ42E[∫(k-1)ΔnkΔnu⊤ctud2∣F(k-1)Δn]1/2≤γ42νc,∞Δn,
where Lemma A.1 is used here for the conditional expectation. Consequently, by combining (A.18) – (A.20), we get the estimateA.21 u⊤E[Akp∣F(k-1)Δn]u≤γ42p!2(2eανc,2Δn)pνc,∞νc,2.
Since this analysis holds for an arbitrary unit vector u, the right-hand side of (A.21) is an upper bound for ‖E[Akp∣F(k-1)Δn]‖∞. This fact, together with (A.15) and (A.17), shows thatA.22 Mp,k≤p!2(α~νc,2Δn)pνc,∞νc,2
for a suitable absolute constant α~≥2. Now, it follows that Theorem 2.3 is applicable with R=α~νc,2Δn and Ck=C1=νc,∞/νc,2. SinceνR=α~νc,∞⌊Δn-1⌋Δn≥α~νc,∞(1-Δn)≥νc,∞
and 4νR2≤4α~2νc,2νc,∞Δn, the inequality (2.7) implies thatA.23 P‖∑k=1⌊Δn-1⌋(Ak-Bk)‖∞>y≤τ(y)≡2dexp-y4α~2νc,2νc,∞Δnmin{y,νc,∞}.
In particular, (A.23) shows thatA.24 a3≤τx5.
Finally, for the second term in (A.12) we invoke the Cauchy–Schwarz inequality and consider an x for which x225νμΔn-νc,2≥νc,25νc,∞x to deduce the following initial bound:A.25 a2≤P∑k=1⌊Δn-1⌋‖ΔknYμ‖22∑k=1⌊Δn-1⌋‖ΔknYσ‖22>x52≤P∑k=1⌊Δn-1⌋‖ΔknYσ‖22>x225νμΔn≤P∑k=1⌊Δn-1⌋‖ΔknYσ‖22-∫(k-1)ΔnkΔntr(ct)dt>x225νμΔn-νc,2≤P∑k=1⌊Δn-1⌋‖ΔknYσ‖22-∫(k-1)ΔnkΔntr(ct)dt>νc,25νc,∞x.
Next, observe thatXk=‖ΔknYσ‖22-∫(k-1)ΔnkΔntr(ct)dt,k=1,⋯,⌊Δn-1⌋,
is a martingale difference sequence. By (A.16), we see thatE[|Xk|p∣F(k-1)Δn]≤p!2(ανc,2Δn)p,
for a suitable absolute constant α≥2, and thus (2.7) ensures thatP|∑k=1nXk|>y≤τνc,∞νc,2y,
where we assume α~ in τ is larger than α. This estimate together with (A.25) means thatA.26 a2≤τx5.
By combining (A.13), (A.14), (A.24), and (A.26) we conclude thatA.27 P‖Σ^n-Σ‖∞>x≤3τx5≤6dexp{-x100α~2νc,2νc,∞Δnmin{x,νc,∞}}
if x≥5Δnmax{νμ,νc,∞} and x225νμΔn-νc,2≥νc,25νc,∞x. In particular, (A.27) holds whenever x≥γmax{νc,2νμΔnνc,∞,νc,2νμΔn,νc,∞Δn}, where γ is a sufficiently large absolute constant. □
Note that, in the above calculations, one has to be careful in order to achieve optimal rates. Indeed, instead of the estimate (A.22), it might have been more natural to rely on the following (seemingly harmless) sequence of inequalities using (A.16) and Stirling’s formula:6.28 Mp,k≤2pE[‖Ak‖∞p∣F(k-1)Δn]+E[‖Bk‖∞p∣F(k-1)Δn]≤p!(2eανc,2Δn)p.
However, with notation as in Theorem 2.3, this would result in νR≍νc,2, while (A.22) satisfies νR≍νc,∞. Since νR determines the rate and νc,∞ can be of strictly smaller order than νc,2 (see the discussion in the end of Sect. 2.1), this implies that a concentration inequality based on (6.28) cannot be optimal.
Proof of Theorem 2.5
Consider a fixed τ∈(0,∞). Theorem 2.4 implies the existence of an absolute constant α such thatP(2‖Σ^n-Σ‖∞>λ)≤6dexp-λανc,2νc,∞Δnmin{λ,νc,∞}
as long as λ≥αmax{νc,2νμΔnνc,∞,νc,2νμΔn,νc,∞Δn}. Thus, under this restriction on λ it follows that 2‖Σ^n-Σ‖∞≤λ with probability at least 1-e-τ if6dexp-λανc,2νc,∞Δnmin{λ,νc,∞}≤exp(-τ)
or, in particular, ifA.29 λ≥γmax{νc,2νc,∞Δn(log(d)+τ),νc,2Δn(log(d)+τ),νc,2νμΔnνc,∞}
for a suitably chosen absolute constant γ. In view of Proposition 2.2, the proof is complete. □
Proof of Theorem 2.7
Under PA, we have that Zk=ΔknY/Δn, k=1,⋯,⌊Δn-1⌋, are i.i.d. Gaussian random vectors with covariance matrix A. Consequently, since ⌊Δn-1⌋≥r2, (Lounici 2014, Theorem 2) implies thatA.30 infΣ~supA∈CrPA‖Σ~-A‖22>γ_‖A‖∞2re(A)rank(A)⌊Δn-1⌋≥β
for suitable absolute constants β∈(0,1) and γ_∈(0,∞), and this proves the result. □
Proof of Theorem 2.8
Set r^=rank(Σ^nλ). To show the upper bound in (2.18) it suffices to argue that Σ has at least r^ singular values which are larger than (λ-λ¯)/2 or, equivalently, sr^(Σ)≥(λ-λ¯)/2. Observe first that the representation (2.2) implies sr^(Σ^n)>λ/2 (recall that sk(A) refers to the kth largest singular value of A). By using this inequality together with the fact that A↦sk(A) is Lipschitz continuous with constant 1 with respect to the spectral norm, we establish thatsr^(Σ)≥sr^(Σ^n)-|sr^(Σ^n)-sr^(Σ)|≥λ-λ¯2.
In order to prove the lower bound of (2.18), we need to show that srλ(Σ^nλ)>0 with rλ=rank(Σ;λ). However, this follows immediately from the following sequence of inequalities:srλ(Σ^nλ)≥srλ(Σ^n)-λ2≥srλ(Σ)-‖Σ^n-Σ‖∞-λ2≥λ-λ¯2>0.
The last part of the result is a direct consequence of the inequality (2.18), since rank(Σ;x)=rank(Σ) for x∈(0,s]. This finishes the proof. □
Proof of Corollary 2.9
For an arbitrary number λ¯∈(0,∞), Proposition 2.2 and Theorem 2.8 imply that bothA.31 ‖Σ^nλ-Σ‖22≤3λ2rank(Σ)
andA.32 rank(Σ;λ)≤rank(Σ^nλ)≤rank(Σ;12(λ-λ¯))
on the set A(λ¯)≡{2‖Σ^n-Σ‖∞≤λ¯} whenever λ>λ¯. By the proof of Theorem 2.5, in particular (A.29) together with the fact that νμ≤νc,∞, it follows that for any τ∈(0,∞), the set A(λ¯) has probability at least 1-exp(-τ) ifA.33 λ¯=γ¯max{νc,2νc,∞Δn(log(d)+τ),νc,2Δn(log(d)+τ)}
for a sufficiently large absolute constant γ¯. By considering τ=log(d) and using that Δn-1≥2νc,2νc,∞log(d), the maximum in (A.33) equals its first term. With this choice of τ, the set A(λ¯) has probability at least 1-d-1, and (λ-λ¯)/2≥δλ when λ is given by (2.19) as long as we choose γ≥γ¯2/(1-2δ). Consequently, by plugging the specific values of λ and λ¯ into (A.31) and (A.32), we have established the first part of the result. The last part of the result follows immediately from Theorem 2.8. □
Proof of Theorem 3.1
First, let δn∈{0,1} be defined such thatA.34 ⌊(t+hn)Δn-1⌋-⌊tΔn-1⌋=⌊(hn+δnΔn)Δn-1⌋,
and set τ(s)=εs+⌊tΔn-1⌋Δn with ε=hn+δnΔn. Clearly, Y¯s=Yτ(s), s∈[0,1], is a diffusion with drift μ¯s=εμτ(s), volatility σ¯s=εστ(s), and driving (standard) Brownian motion W¯s=(Wτ(s)-Wτ(0))/ε. Moreover, its RV at time 1 based on a sampling frequency of Δ¯n=Δn/ε coincides with Σ^n(t;t+hn):Σ^n(t;t+hn)=∑k=1⌊Δ¯n-1⌋(Δ¯knY¯)(Δ¯knY¯)⊤,Δ¯knY¯=Y¯kΔ¯n-Y¯(k-1)Δ¯n.
Hence, the first step is to apply Corollary 2.6 to the process (Y¯s)s∈[0,1] with sampling frequency Δ¯n. To this end, note thatsups≤1‖μ¯s‖22≤ενμ,sups≤1tr(σ¯sσ¯s⊤)≤ενc,2,andsups≤1‖σ¯sσ¯s⊤‖∞≤ενc,∞.
Since we also have ε∈[hn,2hn] and hn/Δ≥2νc,2νc,∞log(d), it follows that the assumptions of Corollary 2.6 are satisfied and we deduce thatA.35 ‖Σ^nλ(t;t+hn)-Σ¯‖22≤3γ2νc,2νc,∞hnΔnrank(Σ¯)log(d)
with probability at least 1-d-1 when λ meets (3.6) and γ is a sufficiently large absolute constant. Here Σ¯ denotes the QV of (Y¯s)s∈[0,1] at time 1. By dividing both sides of the inequality (A.35) by hn2,A.36 ‖c^nλ(t)-Σ¯hn‖22≤3γ2νc,2νc,∞Δnrank(Σ¯)log(d)hn.
The error ‖hn-1Σ¯-ε-1Σ¯‖2 can be bounded in the following way using that hn/Δn≥νc,22νc,∞:A.37 ‖Σ¯hn-Σ¯ε‖22≤νc,2Δnhn2≤2νc,2νc,∞Δnhn.
Now, for any given β∈(1,∞), we want to argue that ‖ε-1Σ¯-ct‖2 is small with probability 1-β-1. To do so, note initially that t∈An≡[⌊tΔn-1⌋Δn,⌊tΔn-1⌋Δn+ε] and that, for any s,u∈An, we have νc,ψ≥‖cs-cu‖ψ/2hn. Using these two facts, and by relying on Jensen’s and Markov’s inequality, we do the following computations for an arbitrary x>0:P‖Σ¯ε-ct‖2>x≤P1ε∫An‖cs-ct‖2ds>x≤P1ε∫Anψ‖cs-ct‖2‖cs-ct‖ψds>ψxνc,ψ2hn.≤ψxνc,ψ2hn-1.
It follows that, with probability at least 1-β-1,A.38 ‖Σ¯ε-ct‖22≤2hnνc,ψ2ψ-1(β)2.
By choosing β=ψ(log(d)) and combining (A.36) – (A.38) we conclude that, with probability at least 1-d-1-ψ(log(d))-1,‖c^nλ(t)-ct‖22≤κγ2νc,2νc,∞Δnrank(Σ¯)hn+hnνc,ψ2log(d)
for a suitably chosen absolute constant κ. Since An⊆[t-Δn,t+hn+Δn] and hn≥2Δn, it follows that rank(Σ¯)≤rank(Σ(t-hn2;t+3hn2)), and the proof is complete. □
Proof of Theorem 3.2
Similarly to the proof of Theorem 3.1, we consider the time-changed process Y¯s=Yτ(s), s∈[0,1], and apply Corollary 2.9 to deduce that, with probability at least 1-d-1,‖c^nλ(t)-Σ¯hn‖22≤3γ2νc,2νc,∞Δnrank(Σ¯)log(d)hn
andA.39 rank(Σ¯;λ)≤rank(c^nλ(t))≤rank(Σ¯;2δλ).
Here we recall that τ(s)=εs+⌊tΔn-1⌋Δn and ε=hn+δnΔn, where δn∈{0,1} is chosen such that (A.34) holds. By following the exact same arguments as in the proof of Theorem 3.1 we obtain the estimate‖c^nλ(t)-ct‖22≤κγ2νc,2νc,∞Δnrank(Σ¯)hn+hnνc,ψ2log(d),
which applies with probability at least 1-d-1-ψ(log(d))-1 for a suitably chosen absolute constant κ. The inequality (3.9) follows immediately from the fact that rank(Σ¯)≤rank(Σ(t-hn2;t+3hn2)). To establish the bounds (3.10) on rank(c^nλ(t)) note initially that, from the proof of Theorem 3.1 (particularly, (A.38)), we may in fact assume that‖Σ¯ε-ct‖22≤2hnνc,ψ2log(d)
on the event that we are considering. Consequently, since singular values are Lipschitz continuous with constant 1 with respect to ‖·‖2,|skΣ¯ε-sk(ct)|≤νc,ψ2hnlog(d)
for k=1,⋯,d. By using this observation, the fact that ε∈[hn,2hn], and the explicit expression for λ the following two implications can be deduced:sk(Σ¯)≥2δλ⟹sk(ct)≥δγνc,2νc,∞Δnhn-νc,ψhnlog(d),sk(Σ¯)<λ⟹sk(ct)<γνc,2νc,∞Δnhn+νc,ψhnlog(d).
We have also imposed the innocent assumption that γ is chosen such that δγ≥2.
From these two implications we conclude that rank(Σ¯;2δλ)≤rank(ct;ε_) and rank(Σ¯;λ)≥rank(ct;ε¯), which (in view of (A.39)) establishes (3.10). The last statement in the result is a direct consequence of (3.10), and thus the proof is complete. □
1 We also employed L=13 subsamples, but there were no discernible change in the results.
2 On April 6, 2020, Raytheon Technologies (RTX) replaced United Technologies (UTX) in the DJIA index following a merger of United Technologies and Raytheon Company. Moreover, on April 2, 2019, Dow replaced DowDuPont following a spin-off from the parent company, which itself was a fusion between Dow Chemical Company and DuPont in 2017. We employ high-frequency data for the preceding member prior to each index update.
3 We truncate 5-minute log-returns that exceed three local standard deviations, as gauged by the daily bipower variation estimator, in order to get shelter from potential jumps.
Christensen and Nielsen were supported by the Independent Research Fund Denmark under grant 1028–00030B and 9056–00011B. Podolskij acknowledges funding from the ERC Consolidator Grant 815703 “STAMFORD: Statistical Methods for High Dimensional Diffusions”.
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| 0 | PMC9734998 | NO-CC CODE | 2022-12-14 23:28:32 | no | Stat Inference Stoch Process. 2022 Dec 5;:1-29 | utf-8 | null | null | null | oa_other |
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Research Highlight
Mild Respiratory COVID-Induced Neuroinflammation Causes Neurological Deficits
http://orcid.org/0000-0002-3421-7166
Yang Junlin
Qiu Mengsheng [email protected]
grid.410595.c 0000 0001 2230 9154 College of Life and Environmental Sciences, Key Laboratory of Organ Development and Regeneration of Zhejiang Province, Hangzhou Normal University, Hangzhou, 311121 China
5 12 2022
13
10 8 2022
8 9 2022
© Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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pmcTo date, more than 580 million people worldwide have been diagnosed with infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 (coronavirus disease 2019) not only affects lung function but also unexpectedly causes brain dysfunction as about a quarter of the survivors of this pandemic to have persistent cognitive impairment. While this sequela is more common in severely ill patients with COVID, those with mild symptoms also frequently experience cognitive impairment [1], and the pathogenic mechanism has not yet been elucidated.
Neuroinflammation is a defense mechanism that initially protects the brain by eliminating pathogens and removing cellular debris. However, persistent inflammatory responses generate neurotoxicity mediated by pro-inflammatory cytokines and microglia [2]. In the case of chronic inflammation caused by neurodegenerative diseases, activated microglia exert further detrimental effects by secreting interleukin-1β (IL-1β), tumor necrosis factor α (TNF-α), IL-6, and proteases [3]. In addition to endogenous factors (e.g., gene mutation and protein aggregation), environmental factors (e.g., infections and drugs) can also induce persistent inflammatory stimulation. A persistent inflammatory response has been reported in the brains of mice treated with chemotherapeutic drugs, and histological studies have shown that these drugs disrupt oligodendroglial lineage dynamics and myelin microstructure by activating microglia, leading to impaired performance in cognitive behavioral tests [4], similar to the cancer-chemotherapy-related cognitive impairment found in cancer survivors [5]. It was recently further demonstrated that inflammatory microglia in mouse models of chemotherapy induce neurotoxic A1 astrocytes by secreting IL-1α, TNF, and complement component 1q [6], which in turn secrete saturated lipids to mediate neurotoxicity [7]. Infection-induced neuroinflammation has been reported in both neurotropic [8] and non-neurotropic [9] virus-infected mice. The non-neurotropic H1N1 strain of influenza induces elevation of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α, and interferon-α) in cerebrospinal fluid (CSF) and hippocampal microglial reactivity, altering the morphology of hippocampal neurons and impairing cognitive function [9].
Recently, Fernández-Castañeda and colleagues found that mild respiratory COVID induces dysregulations associated with cognitive impairment such as impaired hippocampal neurogenesis, decreased subcortical oligodendrocytes, and loss of myelin due to CCL11 (C-C motif chemokine 11) elevation and microglial activation [10]. The authors first verified that mild respiratory COVID can indeed cause prominent neuroinflammation. Although no overt disease symptoms were observed in post-COVID mice, the cytokine profiles in serum and CSF were significantly elevated for at least 7 weeks (Fig. 1). In particular, the levels of CCL11, a chemokine associated with cognitive dysfunction in aging [11], were substantially increased. At the same time, white-matter-specific microglial reactivity was detected (IBA1+CD68+). This regionally-restricted microglial activation was also validated in humans with mild respiratory SARS-CoV-2 infection.Fig. 1 Schematic of inflammation-elicited dysregulation of myelinogenesis and neurogenesis in brain tissue during mild COVID infection. Mild respiratory SARS-CoV-2 infection triggers the immune response, resulting in increased levels of serum inflammatory cytokines, which, in turn, stimulate the elevation of CSF cytokines levels by increasing the abundance of chemokine-enriched microglia in the central nervous system. Mild respiratory COVID-induced CCL11 elevates white-matter-specific microglial reactivity which impedes hippocampal neurogenesis. Microglia in the subcortical white matter are activated by an unknown factor and induce the persistent loss of oligodendrocytes leading to demyelination.
Next, the researchers further analyzed the state of white matter microglia following mild respiratory COVID using single-cell RNA sequencing. Consistent with inflammation, the abundance of chemokine-enriched microglia, a subset of cells expressing chemokines and cytokines, was significantly increased in post-COVID mice. Even in the homeostatic microglia cluster, genes related to antigen processing and presentation, such as B2m, H2-D1, and H2-K1, were also up-regulated following mild respiratory COVID. More importantly, the microglial transcriptome profiling of post-COVID mice displayed high similarity to that of Alzheimer-associated microglia and aging-associated white-matter microglia. These data suggest that mild respiratory COVID indeed induces typical neuroinflammation.
Considering the previous reports that reactive microglia and cytokines/chemokines (e.g. IL6 and CCL11) induced by systemic illness or aging inhibit the generation of new neurons in the hippocampus [11, 12], the authors examined hippocampal neurogenesis following mild respiratory COVID. They found that microglial reactivity in the hippocampal white matter of post-COVID mice robustly increased, coinciding with the marked reduction of doublecortin-positive (DCX+) new neurons in the same period (Fig. 1).
To investigate whether CCL11 is responsible for cognitive impairment in post-COVID patients, the authors measured the CCL11 levels in the plasma of people suffering from COVID with and without cognitive symptoms. Unsurprisingly, the plasma levels of CCL11 were significantly higher in COVID patients exhibiting cognitive deficits than in COVID patients without cognitive symptoms. The CCL11 levels in the plasma were significantly elevated in both mild respiratory COVID mice and COVID patients with cognitive symptoms, which is reminiscent of the finding that CCL11 mediates cognitive impairment by inhibiting hippocampal neurogenesis, an ongoing mechanism of neural plasticity thought to support healthy memory function. Indeed, when CCL11 was administered intraperitoneally, a systemic microglial activation was induced specifically in hippocampal white matter, and impaired hippocampal neurogenesis was confirmed.
To investigate whether mild respiratory SARS-CoV-2 infection damages myelinating oligodendrocytes like chemotherapy [4], the researchers examined oligodendroglial lineage cells in subcortical white matter. The number of oligodendrocyte precursor cells did not change significantly at first, but a mild decrease (~10%) was detected later. Mature oligodendrocytes were significantly reduced initially and this continued for a long time. In keeping with the loss of oligodendrocytes, the density of myelinated axons in subcortical white matter was significantly reduced (Fig. 1) for at least 6 months following mild respiratory SARS-CoV-2 infection.
In the end, the comparison of cytokine profiles between H1N1 influenza and SARS-CoV-2 infection revealed overlapping but not identical neuroinflammatory profiles, with the notable shared feature of persistently elevated CCL11. In mild respiratory infection with H1N1 influenza, the same pattern of white matter-selective microglial reactivity was observed initially in the subcortical and hippocampal white matter. However, subcortical microglial reactivity became normal soon after. Concordant with the pattern of microglial reactivity in mice with H1N1 influenza, oligodendrocytes were initially decreased in the subcortical white matter but recovered rapidly as microglial reactivity resolved. However, hippocampal neurogenesis was deficient for a long time. These data further demonstrate the neurotoxicity of microglial reactivity.
In summary, this study provides strong evidence that mild respiratory COVID can induce CSF cytokine elevation and white matter-specific microglial reactivity in mice and humans, and the sustained inflammatory responses further impair hippocampal neurogenesis, reduce mature oligodendrocytes, and increase demyelination (Fig. 1). More importantly, the authors identified the key cytokine CCL11 that induced hippocampal microglial reactivity and impaired neurogenesis, suggesting CCL11 as a potential therapeutic target for mild respiratory COVID.
The findings of this study provide a scientific explanation for the impairment of cognition by mild respiratory COVID, but several important issues remain to be resolved. First of all, the authors attribute the reduction of hippocampal DCX+ neuroblasts caused by SARS-CoV-2 infection and CCL11 administration to impaired neurogenesis, but they cannot rule out the possibility that neuroblast apoptosis may also contribute to this defect. Therefore, detecting the apoptosis of hippocampal neurons is necessary. In addition, intraperitoneal injection of CCL11 only caused microglial reactivity in the hippocampus, but not in subcortical white matter, indicating that the subcortical microglia are not sensitive to CCL11. A similar phenomenon was reported in mice with respiratory H1N1 influenza, that is, the CSF CCL11 levels were consistently higher at least 7 weeks post-infection, but microglial reactivity in the subcortical white matter was only detected at 7 days post-infection. The finding that mild respiratory COVID can continue to activate microglia in the subcortical white matter for at least 7 weeks implies that other inflammatory factors may be responsible for the pro-inflammatory effects during this period. Identification of the related cytokines/chemokines will help to further understand the mechanism of respiratory COVID-induced myelin dysregulation (Fig. 1). It is also noted that reactive microglia contribute to a decrease in myelinated axons and adult hippocampal neurogenesis, but the exact underlying mechanism remains unclear. Liddelow et al. demonstrated that reactive microglia activate neurotoxic A1 astrocytes by secreting cytokines [6], which in turn secrete saturated lipids to kill oligodendrocytes and neurons [7]. Are the impaired hippocampal neurogenesis, decreased oligodendrocytes, and myelin loss caused by mild respiratory COVID mediated through the same mechanism? Hopefully, future discoveries will help to unravel these mysteries.
Acknowledgements
This highlight was supported by the National Natural Science Foundation of China (32170969) and the Zhejiang Provincial Natural Science Foundation of China (LY22H090002).
Conflict of interest
The authors declare no competing financial interests.
==== Refs
References
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10. Fernández-Castañeda A Lu P Geraghty AC Song E Lee MH Wood J Mild respiratory COVID can cause multi-lineage neural cell and myelin dysregulation Cell 2022 185 2452 2468.e16 10.1016/j.cell.2022.06.008 35768006
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12. Monje ML Toda H Palmer TD Inflammatory blockade restores adult hippocampal neurogenesis Science 2003 302 1760 1765 10.1126/science.1088417 14615545
| 36471132 | PMC9734999 | NO-CC CODE | 2022-12-14 23:28:32 | no | Neurosci Bull. 2022 Dec 5;:1-3 | utf-8 | Neurosci Bull | 2,022 | 10.1007/s12264-022-00990-y | oa_other |
==== Front
Aging Clin Exp Res
Aging Clin Exp Res
Aging Clinical and Experimental Research
1594-0667
1720-8319
Springer International Publishing Cham
36484946
2314
10.1007/s40520-022-02314-6
Original Article
“I know that my role is going to change”: a mixed-methods study of the relationship between amyloid-β PET scan results and caregiver burden
http://orcid.org/0000-0003-4692-5837
Couch Elyse [email protected]
1
Belanger Emmanuelle 12
Gadbois Emily A. 1
DePasquale Nicole 3
Zhang Wenhan 4
Wetle Terrie 1
1 grid.40263.33 0000 0004 1936 9094 Center for Gerontology and Healthcare Research, Brown University School of Public Health, Center for Gerontology and Healthcare Research, Providence, RI USA
2 grid.40263.33 0000 0004 1936 9094 Department of Health Services, Brown University School of Public Health, Policy & Practice, Providence, RI USA
3 grid.26009.3d 0000 0004 1936 7961 Division of General Internal Medicine, Duke University School of Medicine, Durham, NC USA
4 grid.26009.3d 0000 0004 1936 7961 Department of Population Health Sciences, Duke University School of Medicine, Durham, NC USA
9 12 2022
111
20 9 2022
27 11 2022
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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Background
Caregiver burden consists of disease specific and perceived stressors, respectively referred to as objective and subjective indicators of burden, and is associated with negative outcomes. Previous research has found that care partners to persons living with cognitive impairment and elevated levels of amyloid-β, as measured by a positron emission tomography (PET) scan, may experience caregiver burden.
Aims
To elucidate the relationship between amyloid scan results and subjective and objective indicators of burden.
Methods
A parallel mixed-methods design using survey data from 1338 care partners to persons with mild cognitive impairment (MCI) and dementia who received an amyloid scan from the CARE-IDEAS study; and semi-structured interviews with a subsample of 62 care partners. Logistic regression models were used to investigate objective factors associated with caregiver burden. A thematic analysis of semi-structured interviews was used to investigate subjective indicators by exploring care partners' perceptions of their role following an amyloid scan.
Results
Elevated amyloid was not associated with burden. However, the scan result influenced participants perceptions of their caregiving role and coping strategies. Care partners to persons with elevated amyloid expected increasing responsibility, whereas partners to persons without elevated amyloid and mild cognitive impairment did not anticipate changes to their role. Care partners to persons with elevated amyloid reported using knowledge gained from the scan to develop coping strategies. All care partners described needing practical and emotional support.
Conclusions
Amyloid scans can influence subjective indicators of burden and present the opportunity to identify and address care partners' support needs.
Supplementary Information
The online version contains supplementary material available at 10.1007/s40520-022-02314-6.
Keywords
Caregiver burden
Dementia
MCI
Amyloid scans
Disclosure
http://dx.doi.org/10.13039/100000049 National Institute on Aging R01AG053934 K01AG070284 P30AG028716 DePasquale Nicole http://dx.doi.org/10.13039/100000133 Agency for Healthcare Research and Quality 5T32 HS000011-37 Couch Elyse
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pmcIntroduction
Nine million Americans provide informal care to people living with dementia [1]. Compared to cognitively healthy older adults, people with dementia are more likely to need assistance with multiple self-care and medical tasks [2]. Care partners to people living with dementia are at increased risk of burden, which is associated with depression, anxiety and poorer physical health [3]. Existing models of caregiver burden, or caregiver stress, have outlined a complex relationship among multifactorial stressors. Levels of burden can be affected by primary stressors such as daily caregiving tasks and the care recipient's symptoms, referred to as objective indicators, or by how the care partner perceives the burden of care, referred to as subjective indicators [4]. Caregiver burden can further be moderated by coping strategies and social support.
Care partners play an important role in initiating the process of seeking a diagnosis for dementia [5]. In seeking a diagnosis, care partners expect to receive objective, personalized information and practical advice about the person living with cognitive impairment’s (PLwCI’s) condition [5]. Neuroimaging techniques, such as amyloid-β positron emission tomography (PET) scans, can detect the neuropathology associated with Alzheimer’s disease and increase diagnostic confidence [6]. The scan results are disclosed as a binary outcome, where a positive result indicates elevated levels of amyloid plaques, and a negative result indicates that levels of amyloid plaques are not elevated. In the US, coverage for amyloid scans is limited to those enrolled in a research study. Appropriate use criteria (which informed the inclusion criteria for this study) have recommended amyloid scans for those who are experiencing memory problems, with an uncertain etiology and where the scan is expected to influence the clinical management of the patient [7]. There is evidence that receiving a scan can alter the medical management of the patient [8]; however, its impact on patients and their care partners is less clear. More research is needed to understand how amyloid scan results can be used to better support PLwCI and their care partners before they can be made available in clinical practice.
Previous research has reported that care partners would like to learn the PLwCI’s amyloid status [9, 10]. However, it is not understood how scan results may shape care partners’ expectations of the disease process and experiences of caregiver burden. On the one hand, receiving amyloid scan results may help care partners to better understand the PLwCI’s condition and feel more confident in their future plans [11]. On the other hand, receiving an amyloid scan result may have a negative impact on care partners. A cross-sectional study of scan recipients in the US found that care partners to people diagnosed with dementia without elevated amyloid had significantly more caregiver burden than those with elevated amyloid [12]. However, this study reported baseline findings and the long-term relationship between scan results and caregiver burden has yet to be investigated. Furthermore, care partners to people with elevated amyloid have increased odds of reporting symptoms of anxiety compared to those with a negative scan [13, 14], and this was especially marked in care partners to people living with mild cognitive impairment (MCI). These findings are supported by a qualitative study reporting feelings of despair among care partners to PLwCI with elevated amyloid [15].
Care partners are at increased risk of burden, which is associated with poorer health outcomes. As care partners to persons with elevated amyloid may experience higher rates of caregiver burden, it is important to understand the relationship between caregiver burden and amyloid scans. It is unclear whether the symptoms of burden experienced by some care partners following an amyloid scan are a result of disease-specific factors (objective indicators), how they perceive their caregiving role in light of the scan result (subjective indicators), or a combination of both. Therefore, the aim of this study is to elucidate the relationship between amyloid scan and objective and subjective indicators of caregiver burden. The specific research questions were (1) Which factors are associated with caregiver burden 18 months after receiving a PET scan? and (2) How do caregivers perceive their caregiving role in light of the PLwCI’s scan result and diagnostic category? This knowledge could be used to inform clinical practice and develop interventions to better support care partners following an amyloid scan.
Methods
Mixed-methods design
This study uses an exploratory parallel mixed-methods design. Quantitative and qualitative data were collected and analyzed separately. Quantitative methods were used to address the first research question and investigate which factors put care partners at greater risk of burden as defined with objective indicators. Qualitative methods were used to address the second research question and examine the influence of the scan result on subjective indicators of burden by exploring the participants' interpretation of the scan and how this affected perceptions of their caregiving role. Findings from the quantitative and qualitative analyses were integrated during interpretation.
Data sources
Data for this study were derived from the Caregivers Reactions and Experience (CARE) supplemental study of the Imaging Dementia Evidence for Amyloid Scanning Study (IDEAS), a cohort study examining the impact of amyloid-β PET scans on clinical outcomes among Medicare beneficiaries with MCI or dementia. The CARE-IDEAS study expands on the IDEAS study by quantitatively and qualitatively investigating the perspectives of patients and care partners who have received an amyloid scan. The CARE-IDEAS study comprises a subsample of 2228 patients and 1872 care partners from 415 dementia care practices across 40 states who participated in the IDEAS study; the method of recruitment and inclusion and exclusion criteria have previously been reported [16]. The CARE-IDEAS study was approved by the Institutional Review Board at Brown University (#1606001534).
Quantitative analysis
Data collection procedures and measures
Quantitative data were collected at two time points through a structured telephone survey questionnaire. Time point 1 was completed on average 4.5 months after the scan (between 2017 and 2018) and the time point 2 was completed approximately 18 months later (between 2018 and 2019). Care partners who had completed the questionnaire at both time points were included in this analysis (N = 1338). Sociodemographic information for care partners was obtained at time point 1. PLwCI’s diagnostic category at enrollment (MCI vs dementia) and scan result (elevated vs non-elevated levels of amyloid) were taken from the IDEAS study.
We used a four-item screening version of the Zarit Burden Interview (ZBI) to measure caregiver burden at time point 2. Scores range between 0 to 16, where a higher score indicates greater burden. Participants scoring in the 75th percentile, a score of 7 or above (range = 0–16), were classified as experiencing high caregiver burden. The screening version of the ZBI was found to be reliable among community dwelling care partners to PLwCI for detecting caregiver burden in longitudinal studies [17].
Care partners rated the number of hours per week they spent caring for the PLwCI due to memory problems on a categorical scale (< 5, 5–19, 20–39, and 40 +) at both time points. We cross-tabulated the responses from care partners at both time points to determine whether there had been a change in the number of hours they spent caregiving, this was categorized as “fewer,” “the same” and “more”.
We used two items (help with dressing and help with keeping track of medications) from the National Health and Aging Trends Study (NHATS) to measure the degree to which memory problems affected the PLwCI’s daily activities in the last month. This measure was completed by care partners at time point 2.
Statistical analysis
First, participant characteristics were summarized, stratified by diagnostic category and level of impairment. Chi-squared tests were used to check for significant differences between the groups. Second, unadjusted and adjusted logistic regression models were estimated to determine which variables were associated with high caregiver burden at follow-up. All analyses were completed using the gtsummary package in RStudio [18].
Quantitative sample
Table 1 presents participant characteristics in the quantitative sample retained at time point 2. Most participants were caring for someone with MCI (72.4%) and over half were caring for someone with elevated amyloid (64.6%). The majority of care partners were younger than 75 (60.0%), female (67.6%), non-Hispanic White (93.8%), had a Bachelor’s or graduate degree (28.7 and 32.1%, respectively) and were caring for their spouse (89.3%). Half (50.7%) spent 5 hours or fewer per week caring for the PLwCI at follow-up, with 13.4% reporting the PLwCI required help with dressing and 44.9% required help with medications due to memory problems.Table 1 Quantitative sample characteristics by diagnostic category and level of amyloid
All participants Dementia (N = 369) MCI (N = 969)
N = 1338 Not Elevated, N = 96 Elevated, N = 273 p1 Not Elevated, N = 377 Elevated, N = 592 p1
Care partner Characteristics
Age, n (%) 0.43 0.35
< 65 209 (15.7) 15 (15.8) 40 (14.9) 64 (17.0) 90 (15.3)
65–74 589 (44.3) 49 (51.6) 116 (43.1) 175 (46.4) 249 (42.3)
75 + 532 (40.0) 31 (32.6) 113 (42.0) 138 (36.6) 250 (42.4)
Gender, n (%) 0.96 0.33
Male 433 (32.4) 34 (35.4) 96 (35.2) 111 (29.4) 192 (32.4)
Female 905 (67.6) 62 (64.6) 177 (64.8) 266 (70.6) 400 (67.6)
Non-Hispanic, White, n (%) 1251 (93.8) 87 (90.6) 254 (93.4) 0.13 349 (93.3) 561 (94.9) 0.16
Level of Education, n (%) 0.52 0.033
High school or less 160 (12.0) 11 (11.5) 38 (14.0) 38 (10.1) 73 (12.4)
Vocational/Some college 361 (27.2) 32 (33.3) 70 (25.8) 117 (31.2) 142 (24.2)
Bachelor’s degree 381 (28.7) 31 (32.3) 90 (33.2) 87 (23.2) 173 (29.5)
Graduate degree 427 (32.1) 22 (22.9) 73 (26.9) 133 (35.5) 199 (33.9)
Relationship to PLwCI, n (%) 0.66 0.54
Spouse 1,194 (89.3) 85 (88.5) 246 (90.1) 339 (89.9) 524 (88.7)
Other 143 (10.7) 11 (11.5) 27 (9.9) 38 (10.1) 67 (11.3)
Caregiver Burden, n (%) 0.031 0.33
Low 927 (70.5) 69 (74.2) 165 (61.8) 276 (74.4) 417 (71.5)
High 387 (29.5) 24 (25.8) 102 (38.2) 95 (25.6) 166 (28.5)
Hours Spent Caregiving (per week), n (%) 0.61 0.013
< 5 667 (50.7) 29 (30.9) 85 (31.5) 235 (63.3) 318 (54.7)
6–19 354 (26.9) 34 (36.2) 84 (31.1) 71 (19.1) 165 (28.4)
20–39 145 (11.0) 16 (17.0) 42 (15.6) 34 (9.2) 53 (9.1)
40 + 150 (11.4) 15 (16.0) 59 (21.9) 31 (8.4) 45 (7.7)
Change in hours spent caregiving per week, n (%) 0.45 0.46
Fewer 84 (12.0) 10 (20.0) 23 (14.7) 20 (10.2) 31 (10.4)
The same 431 (61.4) 27 (54.0) 79 (50.6) 135 (68.5) 190 (63.5)
More 187 (26.6) 13 (26.0) 54 (34.6) 42 (21.3) 78 (26.1)
PLwCI needs help with medication, n (%) 581 (44.9) 61 (65.6) 190 (73.4) 0.16 95 (26.1) 235 (40.7) < 0.001
PLwCI needs help with dressing, n (%) 178 (13.4) 27 (28.7) 72 (26.6) 0.69 23 (6.1) 56 (9.6) 0.060
PLwCI Characteristics
Age, n (%) 0.97 0.17
65–74 443 (43.3) 27 (40.3) 71 (41.8) 152 (47.8) 193 (41.2)
75 + 581 (53.7) 40 (59.7) 99 (58.2) 166 (52.2) 276 (58.8)
MCI mild cognitive impairment, PLwCI persons living with cognitive impairment
1Pearson’s Chi-squared test; Fisher’s exact test
Among care partners for people living with dementia, a greater proportion of those caring for a patient with elevated amyloid reported high caregiver burden (38.2%) compared to those caring for people without elevated amyloid (25.8%). Among participants caring for someone with MCI, the number of hours participants spent providing care varied significantly by the amyloid scan result; 63.5% of participants caring for a person with MCI and elevated amyloid spent 5 h or fewer per week providing care, compared to 54.7% without elevated amyloid. Furthermore, significantly more care partners to people with MCI and elevated amyloid (40.7 vs. 26.1%) reported the person they care for needed help with keeping track of medications due to memory problems.
Quantitative results
Factors associated with caregiver burden
Logistic regression models were used to explore which variables were associated with higher odds of caregiver burden (Table 2). Unadjusted logistic regression models show that being younger, female (OR = 2.26, CI = 1.72–3.01) and spending more hours caregiving per week was associated with increased odds of caregiver burden. Additionally, providing care to a PLwCI with an elevated scan result (OR = 1.34, CI = 1.04–1.72), a diagnosis of dementia (OR = 1.43, CI = 1.10–1.85) or who needs help with keeping track of medications (OR = 2.67, CI = 2.09–3.43) or dressing (OR = 3.37, CI = 2.42–4.71) was associated with an increased odds of burden.Table 2 Unadjusted and adjusted logistic regression models showing factors associated with high caregiver burden
Unadjusted Adjusted
Characteristic OR (95% CI)1 p OR (95% CI)1 p
Care partner age
< 65 – –
65–74 0.69 (0.50–0.97) 0.029 0.77 (0.48–1.25) 0.29
75–84 0.59 (0.42–0.84) 0.003 0.66 (0.40–1.08) 0.10
85 + 0.27 (0.11–0.56) 0.001 0.25 (0.09–0.66) 0.008
Care partner gender
Male – –
Female 2.26 (1.72–3.01) < 0.001 2.39 (1.74–3.32) < 0.001
Care partner race/ethnicity
Non-Hispanic, White – –
Hispanic, White 1.21 (0.49–2.77) 0.67 1.02 (0.36–2.75) 0.97
Non-Hispanic, Black or African American 1.61 (0.63–3.93) 0.30 1.31 (0.36–4.21) 0.66
Other 0.93 (0.42–1.89) 0.85 0.99 (0.39–2.40) 0.99
Relationship to PLwCI
Spouse – –
Other 1.25 (0.86–1.81) 0.24 0.96 (0.55–1.66) 0.88
Level of education
High school or less – –
Vocational/some college 1.13 (0.74–1.75) 0.59 0.96 (0.58–1.58) 0.86
Bachelor’s degree 1.46 (0.96–2.24) 0.079 1.36 (0.84–2.23) 0.21
Graduate degree 1.31 (0.87–2.01) 0.20 1.30 (0.81–2.12) 0.29
Hours spent caregiving (per week)
< 5 – –
6–19 4.65 (3.40–6.40) < 0.001 4.92 (3.46–7.06) < 0.001
20–39 7.96 (5.34–11.9) < 0.001 7.23 (4.59–11.5) < 0.001
40 + 10.1 (6.78–15.3) < 0.001 9.25 (5.76–15.0) < 0.001
PLwCI needs help with medication
No – –
Yes 2.67 (2.09–3.43) < 0.001 1.13 (0.81–1.57) 0.47
PLwCI needs help with dressing
No – –
Yes 3.37 (2.42–4.71) < 0.001 1.59 (1.06–2.40) 0.027
PLwCI scan result
Not Elevated – –
Elevated 1.34 (1.04–1.72) 0.026 1.15 (0.85–1.55) 0.36
Diagnostic category
MCI – –
Dementia 1.43 (1.10–1.85) 0.007 0.78 (0.56–1.08) 0.14
MCI mild cognitive impairment, PLwCI persons living with cognitive impairment
1OR Odds ratio, CI Confidence interval
When adjusting for all other variables, the effect of age as a protective factor against caregiver burden was attenuated but only significant for the 85 + group (OR = 0.25, CI = 0.09–0.66). Women still had much higher odds of burden compared to men (OR = 2.39, CI = 1.74–3.32). Spending more hours a week caregiving and providing care to a PLwCI who needs help dressing remained associated with increased odds of burden (OR = 1.59, CI = 1.06–2.40). In the adjusted models the diagnostic category (OR = 1.15, CI = 0.85–1.55) and scan result (OR = 0.78, CI = 0.56–1.08) were no longer significantly associated with caregiver burden.
Qualitative analysis
Data collection procedures
A subset of care partners who completed both survey time points and consented to be contacted for future research opportunities were invited to participate in an additional in-depth telephone interview. Care partners were eligible to participate if they scored 21 or above on the Modified Telephone Interview for Cognitive Status [19]; this cut-off was recommended by an expert in cognitive assessment. To increase diversity of experiences and perspectives in the qualitative sample, we over-sampled participants who did not identify as non-Hispanic White. Potential participants were mailed a consent form prior to being contacted by the research team for an interview.
Qualitative data were collected through semi-structured interviews. The interviews were conducted with 62 care partners via telephone between May 2020 and January 2021 by two research assistants and one research coordinator, under the supervision of senior researchers. Before starting the interviews, the consent form was reviewed with the participant and they were asked to explain the purpose of the study in their own words as an additional check of capacity. The interviews followed a topic guide which started with questions about the decision to get the scan followed by questions about what the scan meant for both the care partner and the PLwCI, how they felt about the results, and what the scan results meant for the PLwCI’s future care (see Supplementary File 1).
Thematic analysis
The interviews were recorded, with permission, and transcribed verbatim. Initially, the data were organized using exploratory content analysis. Codes determined to be relevant to this research question were selected for the thematic analysis presented in this paper. We followed the six steps of reflexive thematic analysis as outlined by Braun and Clarke [20]. All members of the research team familiarized themselves with the data and made an initial list of codes. The team met to share their codes, and discuss the different interpretations of the data. During this meeting the codes were compiled into a list of categories (see Supplementary File 2). The first author applied the categories developed by the team to the data in NVivo. We used the queries function to stratify the qualitative data by scan result and diagnostic category at the time of the scan to explore the subjective indicators of burden. The first author then developed themes, along with a thematic diagram, which was reviewed by the rest of the team.
Qualitative results
Qualitative sample
Most participants in the qualitative sample were under the age of 75 (72.6%), female (75.8%), non-Hispanic White (54.8%) and spent 20 hours per week providing care (74.2%), see Table 3. One third reported high caregiver burden (29.5). 35.5% reported the PLwCI needed help keeping track of medications due to memory problems. The majority of participants were caring for a person with elevated amyloid (58.1%) and/or MCI (79.0%).Table 3 Characteristics of qualitative sample
Characteristic N = 62
Care partner age, n (%)
< 65 13 (21.0)
65–74 32 (51.6)
75 + 17 (27.4)
Gender, n (%)
Male 15 (24.2)
Female 47 (75.8)
Non-Hispanic, White, n (%) 34 (54.8)
Caregiver burden, n (%)
Low 43 (70.5)
High 18 (29.5)
Hours spent caregiving (per week), n (%)
< 20 46 (74.2)
20 + 16 (25.8)
PLwCI needs help with medication, n (%) 22 (35.5)
Scan result, n (%)
Elevated 36 (58.1)
Not Elevated 26 (41.9)
Diagnostic category, n (%)
MCI 49 (79.0)
Dementia 13 (21.0)
MCI mild cognitive impairment, PLwCI persons living with cognitive impairment
Results
We identified three themes: (1) current and anticipated role as a care partner, (2) emotional impact of caregiving and (3) support and practical resources (Fig. 1). The scan result influenced care partners perceptions of their caregiving role and the emotional impact of caregiving. All participants described a need for support and practical resources to help them manage their current and future caregiving role and its emotional impact.Fig. 1 Thematic diagram of qualitative results
Current and anticipated role as a care partner
Most care partners described taking on caregiving tasks as a result of the PLwCI’s symptoms. Many, especially those caring for someone with elevated amyloid, expressed an expectation that this would gradually increase until formal care would be needed. However, some care partners to people with MCI without elevated amyloid reported they did not expect the PLwCI’s cognitive impairment to decline and therefore their caregiving role would not change.
Participants detailed gradually taking on more responsibility, including managing the PLwCI’s medications, medical appointments, finances and household chores as a result of the PLwCI’s memory problems. When taking on new tasks or roles, some participants noted concerns about the impact this change may have on the PLwCI’s sense of autonomy and identity.
“I’m a medical person, and he was the finance person. I allowed him to do everything in those early years. Like I said, we’ve been married 39 years, and I honestly did not take an active interest. Now, I find that when I really need to, he is extremely reluctant to give any of that up. Like, as I said, what he does with finances, that’s what defines him.” (MCI without elevated amyloid)
Participants acknowledged an awareness that the PLwCI’s care needs could increase to the point where they would no longer be able to manage their care alone. Some participants described increasing informal care arrangements by moving closer to family members, for example. Whereas others reported considering home care, nursing homes or assisted living. In general, participants expressed a preference to delay introducing formal care for as long as possible.
“I would like to have someone to help around here, but at the same time, I just rather do it myself. I don’t know how to explain. I think if [it] just gets really worse in the future, yeah, I will like somebody to help. Right now, I think I can handle it with the help of my kids.” (Dementia with elevated amyloid)
Conversely, some participants who were caring for a person with MCI without elevated amyloid did not describe a future where increasing care would be needed, and reported returning to their normal routines. “Well, hopefully we won’t need that, with the negative test results from that. We were hoping that you won't need any of that. If it had been positive, we would have already started making alternative, alternative plans.” (MCI without elevated amyloid).
Emotional impact of role
Participants outlined the emotional impact of their caregiving role. Participants who were caring for someone with elevated amyloid detailed using the knowledge derived from the scan to develop coping strategies. Whereas a participant caring for some with MCI without elevated amyloid said they struggled to cope with cognitive decline which could not be attributed to Alzheimer’s disease.
Participants noted that witnessing the progression of memory problems was upsetting. Spouses, in particular, expressed feeling sad and anticipatory grief from watching the cognitive and functional decline of the PLwCI. Many care partners were living alone with the PLwCI with minimal support, and noted that being the sole witness to changes in the PLwCI was an isolating experience.
“It's very eye opening, especially when you live with someone to watch their daily movements. People who do not live with their loved ones or people who just visit, don’t understand exactly what happens to people like that and that as the brain deteriorates, you could see changes.” (MCI with elevated amyloid)
Managing the everyday symptoms associated with dementia or MCI could be emotionally challenging. Participants noted that receiving a scan result indicating elevated amyloid helped to reinforce the knowledge that the symptoms they observed were likely to be caused by Alzheimer’s disease. This, in turn, helped them to develop coping strategies.
“I know that my role is going to change because I have to be even more patient and more supportive when he can’t find something that’s right in front of his face. So I just know that I just have to be more patient, and then him being anxious about it makes it more difficult for him.” (MCI with elevated amyloid)
“When that hits me and I’m just kind of freaking out, I go and open the picture of the PET scan on my desktop and say, ‘Oh yeah,’ and it helps me remind myself of what we’re dealing with. It's not him. It's the Alzheimer’s. I have this mantra, ‘It's not him. It’s the Alzheimer’s,’ and the PET scan helps me remember that. So I guess that's kind of, for me, it’s just a reminder that this is a real thing, not just he’s not just being weird.” (MCI with elevated amyloid)
However, a participant caring for a person without elevated amyloid, was increasingly frustrated by memory problems which could not be attributed to dementia: “At times, it’s very frustrating because of the memory loss. I keep hearing, he doesn't have Alzheimer’s. He doesn’t have dementia. It’s ADHD. That’s something not as serious. It’s something that we just have to deal with day-by-day.” (MCI without elevated amyloid).
Support and practical resources
Participants said they needed both practical and emotional support to manage their caregiving role and its emotional impact irrespective of scan result. Many care partners described family and friends as a source of both practical and emotional support. Some care partners in this study said they moved closer to family, or family members moved in to share caregiving tasks. Without such support, care partners could feel even more burdened by their role: “I think the biggest problem for me at this point is the fact that there’s really nobody else for me to share this. It’s a responsibility on me. I’m going to use the word ‘burden’ on me.” (Dementia without elevated amyloid). Furthermore, some participants said they felt uncomfortable with sharing their difficulties with family members: “It’s not fair to them for me to unload daily, with everything that’s going wrong. It is, in my opinion, important for me to keep them in the loop enough but I don’t call them every single time he does something screwy.” (MCI without elevated amyloid). Participants also listed specialist dementia services, rather than family members, as a source of support.
Participants reported attending classes run by specialist services and talking to health and social care professionals could help them to understand what to expect in the future, make plans and set realistic expectations for their anticipated caregiving role.
“What’s helped me a lot, again, is the support group that we go to where the social worker there is the one that has advised us what to do along the path of this illness or disease, whatever they want to call it. But she’s been very informative, telling us what steps we should take next.” (Dementia without elevated amyloid)
Attending caregiver meetings was also described as a valuable opportunity to meet others in similar situations: “[care partners should] go to the caregiver meetings. Sometimes that’s your only outlet to be able to talk to people.” (Dementia with elevated amyloid).
Integration of quantitative and qualitative findings.
To elucidate the relationship between amyloid scan and the objective and subjective indicators of burden, we grounded the integration of the quantitative results in the caregiver stress model (Fig. 2). Both the quantitative and qualitative results indicate the caregiver’s background and context can affect caregiver burden. The quantitative results show women have a greater risk of burden and care partners over the age of 85 have a reduced risk of burden. Furthermore, the qualitative results show distance to and degree of support from family members and friends can help care partners manage their caregiving role.Fig. 2 Integration of results and the caregiver stress model
Primary stressors contributing to caregiver burden can be broken down into objective and subjective indicators. The quantitative results show caring for someone with elevated amyloid was not associated with increased burden. Instead, the objective indicators of burden were spending more hours caregiving per week and providing care to someone who needs help with personal care tasks due to memory problems. The qualitative results indicate that amyloid scan results affected subjective indicators, including how care partners perceive their caregiving role. More specifically, care partners to people with elevated amyloid scans results describe a future of increasing care responsibilities, whereas partners to people with MCI without elevated amyloid did not describe anticipating such a future. Other subjective indicators of burden that did not vary by scan result were a concern that taking on new caregiving responsibilities would diminish the PLwCI’s sense of identity and anticipatory grief from the perceived loss of the PLwCI.
Coping strategies, support and resources can affect the degree to which care partners experience burden. The findings from the qualitative study demonstrated that the knowledge derived from an elevated amyloid scan result could help participants to understand the PLwCI better and develop coping strategies. However, there was also some evidence that care partners to someone with MCI without elevated amyloid could experience an inverse of this effect. All participants had a need for practical and emotional support to manage the objective and subjective indicators of burden.
Discussion
Previous research has found that care partners value the opportunity to learn the PLwCI’s amyloid status [10, 15]. In this study, we found elevated amyloid was not associated with caregiver burden when controlling for other factors. We found the number of hours spent caregiving and the degree of care required by the care recipient were associated with higher odds of burden. However, the scan result affected how care partners perceived their caregiving role and their coping strategies. These findings indicate elevated amyloid is not associated with objectively measured burden. This is perhaps unsurprising as objective indicators of burden encompass disease-specific determinants, such as severity and rate of decline, and amyloid scans are not recommended for determining the severity of the disease or prognosis [7].
The findings of this study show that the scan result can influence the care partner’s subjective experience of their caregiving role and their coping strategies. Previous research shows that the desire to find out if the PLwCI’s symptoms were caused by Alzheimer’s disease was a key motivator for patients and their care partners to undergo an amyloid scan [15] and that care partners report better understanding of the PLwCI after receiving an amyloid scan [11, 15]. The findings from our study suggest a more nuanced experience based on the level of impairment at the time of diagnosis and scan result. Firstly, participants with scans indicating elevated amyloid expressed confidence that the PLwCI’s memory problems were caused by Alzheimer’s disease. Therefore, they described anticipating a future where the PLwCI would require an increasing amount of care. Furthermore, a scan result for elevated amyloid could provide comfort to care partners by clarifying the diagnosis and help them to develop coping strategies. Conversely, a care partner to a person with MCI reported the care recipient did not have Alzheimer’s disease and did not anticipate increasing care needs in the future. However, those with a negative scan and MCI may still experience symptoms of memory loss, and their care partners may struggle with managing symptoms which could not be explained by a diagnosis of Alzheimer’s disease. While elevated amyloid increases the risk of converting from MCI to dementia, this relationship is not definitive [7]. As the scan result influences the care partner’s expectations of their role and how they cope with it, it is important they correctly interpret the meaning of the scan results. This is supported by research by our group, which found care partners to people with MCI had difficulty accurately reporting their scan results [21]. Still, it is not clear if this is due to the nuanced implications of the scan result or if this is due to how the results are communicated to patients and their care partners [9]. Furthermore, it is not clear how the diagnosis of alternative conditions to explain the PLwCI’s memory problem affects the care partner’s understanding of the scan result. Future research should examine how amyloid scan results are disclosed to care partners, including cases where PLwCI receive alternative diagnoses to explain their cognitive impairment, and how this affects their understanding of the scan result.
All participants in the qualitative analysis reported a need for emotional support and practical resources for managing their caregiving role, irrespective of the scan result or diagnostic category. This is supported by a survey of care partners in the US, where participants rated information on how to keep the care recipient safe at home and how to cope emotionally as their top two priorities [22]. Previous research has shown that care partners to persons with MCI and dementia have similar needs for support but differ in their specific support needs [23]. MCI care partners needed support with managing neuropsychiatric symptoms and dementia care partners needed support managing functional disability. Therefore, interventions to support care partners should be tailored depending on the diagnostic category of the patient.
Strengths and limitations
This study used a mixed-methods design to explore the relationship between caregiver burden and amyloid scan result. The use of both quantitative and qualitative data allowed us to examine the role of objective and subjective indicators and present a nuanced understanding of caregiver burden. The findings of this study should be considered in light of a few limitations. Firstly, when stratifying analyses by scan result and level of impairment, some cells contained a small number of participants, limiting the power to detect differences between groups. Furthermore, our quantitative sample was constrained by a lack of diversity in terms of race, ethnicity and socioeconomic status, although we did oversample diverse participants for the in-depth qualitative interviews. Similarly, we used a screening version of the ZBI, which may lack the sensitivity of longer versions. We detected similar levels of burden to Robinson and colleagues [12], who used the full version of this measure, however these similarities may be due to the distributional cut-off used to define high caregiver burden. More research is needed on this topic with a greater range of objective indicators of burden including the behavioral and psychological symptoms of dementia. Finally, qualitative interviews were completed a few years after the results of the amyloid scan and during the COVID-19 pandemic, which may have influenced how care partners perceived their caregiving role and willingness to introduce formal care.
Conclusions
In conclusion, the findings of this study indicate that amyloid scan results influence subjective indicators of burden, rather than the objective indicators. As the scan result affects the care partner’s subjective understanding of their current and future caregiving role, it is important they are correctly interpreting the meaning of the scan. This is an important area for future work. Participants reported a need for emotional and practical support, which should inform care and interventions. The disclosure of amyloid status is an opportunity for clinicians to identify and address the support needs of care partners.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 14 KB)
Supplementary file2 (DOCX 12 KB)
Author contributions
EC and EB: initially designed the aims and analyses reported in this manuscript, all authors gave critical feedback on the research aims and qualitative and quantitative analyses. EC: conducted the quantitative analysis. All authors contributed to the qualitative analysis. EC: integrated the results and drafted the manuscript. All authors contributed to the revising of the manuscript and approved the final draft.
Funding
Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Number R01AG053934 and by the American College of Radiology Imaging Network and the Alzheimer's Association. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, the American College of Radiology Imaging, or the Alzheimer's Association. EC was supported by an AHRQ National Research Service Award T32 (Grant 5T32 HS000011-37). ND was supported by the National Institute on Aging of the National Institutes of Health under Award Numbers K01AG070284 and P30AG028716 (Dr. Schmader).
Data availability
The datasets used and analyzed during the current study are available in the Brown Digital Repository (https://doi.org/10.26300/dqt0-vq57) which includes a CARE-IDEAS codebook, and a PDF file with a description of the software used and syntax used for data cleaning and the final analytical models.
Declarations
Conflicts of interest
The authors have no conflicts of interest to declare.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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16. Jutkowitz E Van Houtven CH Plassman BL Mor V Willingness to undergo a risky treatment to improve cognition among persons with cognitive impairment who received an amyloid PET scan Alzheimer Dis Assoc Disord 2020 34 1 9 10.1097/WAD.0000000000000338 31414990
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| 36484946 | PMC9735001 | NO-CC CODE | 2022-12-14 23:45:33 | no | Aging Clin Exp Res. 2022 Dec 9;:1-11 | utf-8 | Aging Clin Exp Res | 2,022 | 10.1007/s40520-022-02314-6 | oa_other |
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J Racial Ethn Health Disparities
J Racial Ethn Health Disparities
Journal of Racial and Ethnic Health Disparities
2197-3792
2196-8837
Springer International Publishing Cham
36478268
1478
10.1007/s40615-022-01478-1
Article
ICU Admission Risk Factors for Latinx COVID-19 Patients at a U.S.-Mexico Border Hospital
http://orcid.org/0000-0001-9228-5469
Quenzer Faith C. [email protected]
12
Coyne Christopher J. 3
Ferran Karen 1
Williams Ashley 1
Lafree Andrew T. 34
Kajitani Sten 34
Mathen George 34
Villegas Vanessa 4
Kajitani Kari M. 34
Tomaszewski Christian 34
Brodine Stephanie 1
1 grid.263081.e 0000 0001 0790 1491 Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA USA
2 Department of Emergency Medicine, Temecula Valley Hospital, Temecula, CA USA
3 grid.266100.3 0000 0001 2107 4242 Department of Emergency Medicine, University of California San Diego Health, San Diego, CA USA
4 Department of Emergency Medicine, El Centro Regional Medical Center, El Centro, CA USA
7 12 2022
112
9 4 2022
22 11 2022
23 11 2022
© W. Montague Cobb-NMA Health Institute 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Objective
Few studies have examined the impact of coronavirus disease 2019 (COVID-19) on the primarily Latinx community along the U.S.-Mexico border. This study explores the socioeconomic impacts which contribute to strong predictors of severe COVID-19 complications such as intensive care unit (ICU) hospitalization in a primarily Latinx/Hispanic U.S.-Mexico border hospital.
Methods
A retrospective, observational study of 156 patients (≥ 18 years) Latinx/Hispanic patients who were admitted for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection at a U.S.-Mexico border hospital from April 10, 2020, to May 30, 2020. Descriptive statistics of sex, age, body mass index (BMI), and comorbidities (coronary artery disease, hypertension, diabetes, cancer/lymphoma, current use of immunosuppressive drug therapy, chronic kidney disease/dialysis, or chronic respiratory disease). Multivariate regression models were produced from the most significant variables and factors for ICU admission.
Results
Of the 156 hospitalized Latinx patients, 63.5% were male, 84.6% had respiratory failure, and 45% were admitted to the ICU. The average age was 67.2 (± 12.2). Those with body mass index (BMI) ≥ 25 had a higher frequency of ICU admission. Males had a 4.4 (95% CI 1.58, 12.308) odds of ICU admission (p = 0.0047). Those who developed acute kidney injury (AKI) and BMI 25–29.9 were strong predictors of ICU admission (p < 0.001 and p = 0.0020, respectively). Those with at least one reported comorbidity had 1.98 increased odds (95% CI 1.313, 2.99) of an ICU admission.
Conclusion
Findings show that age, AKI, and male sex were the strongest predictors of COVID-19 ICU admissions in the primarily Latinx population at the U.S.-Mexico border. These predictors are also likely driven by socioeconomic inequalities which are most apparent in border hospitals.
Supplementary Information
The online version contains supplementary material available at 10.1007/s40615-022-01478-1.
Keywords
Intensive care unit (ICU)
COVID-19
SARS-CoV2
U.S.-Mexico border
Latinx
Hispanic population
Hospitalizations
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pmcIntroduction
The coronavirus disease 2019 (COVID-19) pandemic has revealed sweeping health care inequalities across the United States (U.S.). Latinx, the largest ethnic minority population in the country, has been particularly affected by severe COVID-19 complications and high mortality rates [1, 2]. Latinx patients accounted for almost 1.9 times the case rate, 2.8 times the hospitalization rate, and 2.3 times the death rate compared with their White, non-Latinx counterparts in the U.S. [1]. California is also home to the largest proportion of the U.S. Latinx population [3, 4]. In June 2020, during the second surge of COVID-19, the Latinx population accounted for 45% of the total number of deaths due to COVID-19 in California [3].
The Latinx population across the U.S.-Mexico border experiences significant health disparities relative to the rest of the U.S. due to higher poverty rates, higher rates of chronic comorbidities, decreased health insurance coverage, lack of health care infrastructure, and inadequate health care access [4–6]. Additionally, Latinx patients are overrepresented in essential service industries, such as food services, health care, waste management, agriculture, and construction which increases their exposure risk to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the causative agent of COVID-19 [7, 8]. Studies of Latinx patients who were hospitalized for COVID-19 found that 25% worked in essential occupations [6, 7]. These industries, in particular, lack the infrastructure for employees to work from home and are often set in crowded areas with poor hygiene, which thus increases the risk of transmission, disease, and subsequent complications [7–9].
Our objective is to describe the significant risk factors that may have contributed to the disparate COVID-19 outcomes of the Latinx patients at a U.S.-Mexico border hospital. Our study was set at El Centro Regional Medical Center (ECRMC) which is the largest hospital in Imperial County and is located 12 miles north of the U.S.-Mexico border. During the time of the study, the Latinx community had the highest overall COVID-19 cases per 100,000 across all age groups when compared to their White, non-Hispanic, Black, non-Hispanic, Asian, and Native Hawaiian/Pacific Islander counterparts in California [10].
In 2020, Imperial County had the second-highest rate of COVID-19 cases and the highest COVID-19 death rate per population (304 people per 100,000) in the entire state of California [10]. At the peak of the 2020 COVID-19 pandemic, ECRMC’s patient census rose to nearly two times the normal total patient census and ten times the normal ICU census (El Centro Regional Medical Center Internal Hospital Data, 2020). At ECRMC, preliminary data demonstrated that in 2020 from March through July during the first COVID-19 surge in Imperial County, 18.7% of the 497 COVID-19 patients who were admitted died (El Centro Regional Medical Center, Internal Hospital Data, 2020).
Previous studies have demonstrated that Latinx patients are disproportionately affected by COVID-19, but there is still a paucity of research on the outcomes of Latinx patients with COVID-19 who reside along the U.S.-Mexico border [7, 8]. Our study describes the unique characteristics of the Latinx population at a border hospital which have contributed to the complications during hospitalization such as ICU admission and death among Latinx COVID-19 patients in a U.S.-Mexico border hospital.
Methods
Study Design
This was a retrospective, observational study of 156 adults who were hospitalized for severe COVID-19 and their associated outcomes at a U.S.-Mexico border hospital while operating at surge capacity serving a primarily Latinx community from April 10, 2020, to May 30, 2020. The primary outcome of interest was admission to the ICU, while the secondary outcome of interest was mortality. This retrospective study was considered exempt by our institutional review board (IRB #200,558).
Inclusion Criteria
Included within this study were patients who identified as primarily as Latinx adult patients (≥ 18 years of age) with COVID-19 diagnosed by the SARS-CoV-2 nasal pharyngeal swab polymerase chain reaction test by Abbot© who were admitted to the hospital. The patients were admitted due to their requirement for treatment and a high risk of clinical deterioration as judged by the emergency medicine clinician at the time of assessment. Admission criteria included hypoxia (O2 saturation levels < 90% on room air), tachypnea (respiratory rate > 30), visible increased work of breathing, any complication due to a coagulopathy (stroke, cardiac ischemia, pulmonary embolism), and other indicators of end-organ damage (e.g., acute renal failure).
Exclusion Criteria
Excluded from the study were those who primarily identified as not-Latinx/Hispanic, pediatric patients (< 18 years of age), pregnant women, patients who did not consent for further treatment or admission, and patients who were dead on arrival to the ED.
Materials
Study participants were identified by searching the electronic health record (EHR) (MedHost©) for chief complaints and emergency department (ED) International Classification of Disease, 9th Revision (ICD-9) and 10th revision (ICD-10), associated with COVID-19. Admitted patients were then followed throughout their hospital course through another EHR (Cerner©) while matching the patients’ unique medical record numbers to obtain treatment, laboratory, death, discharge, and length-of-stay data (in unit days). Each admitted patient’s chart was scanned for information on vital signs and the ventilation strategies including the following: nasal cannula, high-flow nasal cannula, bi-level non-invasive positive pressure (BiPAP), and endotracheal intubation.
Data Collection
A team of trained data abstractors performed a retrospective chart review of patients diagnosed with SARS-CoV-2 infection who presented to ECRMC ED from April 1, 2020, to May 30, 2020. The data abstractors were unblinded to study hypothesis and uniformly received on-site training in data extraction, identifying cases through selection criteria, and identifying specific study variables. Documentation by the treating emergency department physician and the pharmacy infusion records were reviewed by study investigators.
Variables collected included receipt of intervention, patient demographics (age, sex, body mass index (BMI), and ethnicity), and comorbidities including cardiovascular disease/hyperlipidemia, hypertension, chronic obstructive pulmonary disease, or other chronic respiratory diseases such as asthma, chronic kidney disease, diabetes mellitus, and immunosuppression (current disease state of immunosuppression or currently taking immunosuppressive medication such as immunotherapy, and anticancer drugs). These data were recorded in a password-protected, patient deidentified Microsoft Excel© sheet. Delivering oxygenation through nasal cannula, non-rebreathing masks, bi-level positive pressure ventilation, intubation, and high-flow nasal cannula were recorded as were the associated outcomes of ICU admission and mortality. Additional outcomes data were recorded including repeat ED visits, hospitalization, and transfer to outside hospitals. Follow-up on discharged/transferred patients using a regional tracking website was performed to assess whether patients were seen or admitted at a different hospital. The data were reviewed for quality and consistency throughout the abstraction process.
Statistical Analysis
Descriptive statistics were employed to describe categorical data such as sex, age groups of 18–49 and 50–64, BMI ≥ 35, and presence of at least one comorbidity (coronary artery disease, hypertension, diabetes, cancer/lymphoma, current use of immunosuppressive drug therapy, chronic kidney disease/dialysis, or chronic respiratory disease). Means and standard deviations were used to express continuous data such as age, BMI, and time since the onset of COVID-19 symptoms. T-tests were used to examine if there was a statistically significant difference between continuous variables in ICU patients versus non-ICU patients. Associations between categorical variables and the following outcomes: ICU admission and mortality were examined using chi-square tests.
Bivariate analyses were used to assess potential associations between patients’ characteristics/demographics and the outcome variables: ICU admission and mortality. Due to missing mortality data, multivariate regression models were produced for only the ICU admission outcome. Using the bivariate analyses, the most significant variables and factors for ICU admission were used to produce both the full and the final regression models. For the full multivariate regression models, an α level of 0.10 was used initially to test for significance. For the final, reduced regression model, a p-value < 0.05 was considered statistically significant and confidence intervals were reported at a level of 95%. All analyses were performed using SAS© Studio Version 3.1.0 (Cary, North Carolina, USA).
Results
A total of 169 patient records were examined and 13 patient records were excluded from the study (Fig. 1). There were 5 patient encounters that were duplicate records of visits to the ED, 2 patients with unknown outcome data, 1 pregnant patient requiring transfer to a tertiary center, 2 patients who were hospitalized for another medical diagnosis but had asymptomatic COVID-19, and 3 non-Latinx patients.Fig. 1 Admissions with confirmed SARS-CoV-2 at El Centro Regional Medical Center (ECRMC). Note: *5 patients with duplicate visits to the ED, 2 unknown ICU status, 1 pregnant patient requiring transfer to a tertiary center, 2 patients who were hospitalized for another medical diagnosis but had asymptomatic COVID-19, 3 non-Latinx patients
Descriptive Statistics
Of the 156 hospitalized patients, 71 (45.5%) required intensive care unit (ICU) level of care. Most patients were male (63.5%) with a mean body mass index (BMI) of 29.9 (± 6.7) and 50.6% were ≥ 65 years old. Tabulated frequencies of patient comorbidities are found in Table 1. A majority of the hospitalized patients were overweight (body mass index (BMI) 25–30) or obese (BMI > 30). The average age of ECRMC hospitalized COVID-19 patients overall was 64.3 years (± 14.1). There was a significant difference in the mean age of ICU admitted patients compared with non-ICU patients ages which was 67.2 (± 12.2) versus 62.3 (± 14.9), respectively (p = 0.0359). As patients were categorized into 18–49 years old, 50–64 years old, and ≥ 65 years old, there was an observed increased frequency of ICU admissions with advancing age. Seventy-one percent (44) of the 62 ICU admissions were inpatients who were ≥ 65 years old.Table 1 Characteristics, demographics, and comorbidities of ECRMC COVID-19 ICU hospitalizations versus non-ICU hospitalizations
Characteristics* Total
n (%) No ICU
n (%) ICU admission
n (%) p-value
Sex N = 156 n = 94 n = 62
Male 99 (63.5) 54 (57.5) 45 (72.6) 0.0547
Female 57 (36.5) 40 (42.5) 17 (27.4)
Body mass index**
Mean (± std) 29.9 (6.8) 30.3 (7.12) 29.3 (6.3) 0.3278
Underweight or normal 37 (23.7) 24 (25.5) 13 (21.0) 0.0940
Overweight 57 (36.5) 28 (29.8) 29 (46.8)
Obese 62 (39.7) 42 (44.7) 20 (32.3)
Age (years)
Mean age (± std) 64.3 (14.1) 62.3 (14.9) 67.2 (12.2) 0.0359
18–49 years 20 (12.8) 14 (14.9) 6 (9.7) 0.0002
50–64 years 57 (36.5) 45 (47.9) 12 (19.3)
> 65 years 79 (50.6) 35 (37.2) 44 (71.0)
No. comorbidities
None 18 (11.5) 12 (12.8) 6 (9.7) 0.574
1 33 (21.1) 15 (16.0) 18 (29.0)
2 49 (31.4) 27 (28.7) 22 (35.5)
3 37 (23.7) 24 (25.5) 13 (21.0)
> 4 19 (12.2) 16 (17.0) 3 (4.8)
Chronic comorbidities*
Diabetes mellitus type 2 81 (51.9) 49 (52.1) 32 (51.6) 0.9498
Hypertension 104 (66.7) 63 (67.0) 41 (66.1) 0.9079
Coronary artery disease/hyperlipidemia 71 (45.5) 48 (51.1) 23 (37.1) 0.0865
Metabolic syndrome‡ 131 (84.0) 78 (83.0) 53 (85.5) 0.6764
Chronic kidney disease‡‡ 26 (16.7) 20 (21.3) 6 (3.9) 0.0571
Chronic renal comorbidities‡‡‡ 35 (23.2) 20 (21.5) 15 (25.9) 0.5370
Current smoker 13 (8.33) 7 (7.4) 6 (9.7) 0.6218
*Column percents are reported
**Underweight < 18.5, normal 18.5–24.9, overweight 25–29.9, obese > 30
***Most prevalent comorbidities in Imperial County include hypertension, diabetes, and hyperlipidemia/coronary artery disease
‡Metabolic syndrome includes those with hypertension, diabetes mellitus type 2, hyperlipidemia, and/or coronary artery disease
‡‡CKD is a documented history of chronic kidney disease
‡‡‡Chronic renal comorbidities category includes patients with a history of CKD and CKD with dialysis
Patient comorbidities in association with ICU admission were analyzed. Overall, the most common comorbidities in the hospitalized patients were hypertension (66.7%), diabetes mellitus (51.9%), coronary artery disease, or hyperlipidemia (CAD/HLD) (45.5%) (Table 1). There was no significant difference in the number of comorbidities in the non-ICU admitted patients versus the ICU admitted patients (p = 0.574).
The admission complications of COVID-19 patients are shown in Table 2. Of the 156 patients who initially presented to the ED, 132 (84.6%) required respiratory support for respiratory failure in the ED. Those who were admitted to the ICU required more intensive oxygenation and ventilation. Those admitted to the ICU frequently required BiPAP, high-flow nasal cannula, or were intubated immediately in the ED (Table 2).Table 2 Complications during hospitalization and association with ICU admission in ECRMC COVID-19 patients
Admission complications* Total
n (%) No ICU
n (%) ICU admission
n (%) p-value
N = 156 n = 94 n = 62
Respiratory failure in the emergency department** 132 (84.6) 77 (81.9) 55 (88.7) 0.2497
Acute kidney injury‡‡ 46 (30.5) 12 (12.9) 34 (73.9) < 0.0001
Dialysis‡‡ 21 (13.9) 9 (42.9) 12 (57.1) 0.0572
Cardiovascular and coagulopathy complications‡‡‡ 37 (100) 13 (13.8) 24 (38.7) 0.0004
Outcome
Mortality
Survived 126 (85.1) 87 (93.6) 39 (70.9) 0.0002
Died 22 (14.9) 6 (6.4) 16 (29.1)
Missing 8 1 7
*Column percents are reported
**Any signs or symptoms of the respiratory failure which was addressed in the ED. These include nasal cannula, non-breather mask, bi-level positive pressure ventilation, hi-flow, or intubation
***Unable to perform reliable chi-square analysis due > 25% cells with missing data when analyzed with the individual oxygen
‡Patient was considered a hospice patient
‡‡AKI and dialysis data missing a total of 5 patients, 1 non-ICU, 4 ICU patients
‡‡‡Cardiovascular and coagulopathic complications including those requiring anticoagulants for specific treatment of CVA, cardiac ischemia (elevated troponin), atrial fibrillation/arrhythmias, DVT/PE, or other coagulopathies during admission
The development of acute kidney injury (AKI) during any time during a patient’s hospitalization appeared to be significantly associated with ICU admission (p < 0.0001). If dialysis was also utilized at any time during hospitalization, this was also associated with ICU admission (p = 0.0572). In addition, cardiovascular and coagulopathic complications, including thromboembolic disorders (deep venous thrombosis, arterial thrombosis, pulmonary embolism), ischemic stroke (CVA), and troponin elevation were found to be associated with ICU admission (p = 0.0004) (Table 2).
Mortality Outcome
The unstratified mortality outcome data were available from 148 of the 156 COVID-19 patients. Of those who were admitted to the ECRMC ICU, a total of 22 patients died, 16 patients were admitted in the ICU, and 6 were not admitted to the ICU. There were 8 patients who initially received care at ECRMC and were subsequently transferred out to a tertiary facility and mortality data were not obtained from these patients (Appendix B). There were 19 (86.4%) deaths in the ≥ 65-year-old age group. Of all the characteristics between the survivors and those who died, older age was found to be statistically significant (p < 0.0001). Additionally, patients who required dialysis (p < 0.0001) or developed AKI (p = 0.0002) during their hospitalization were less likely to survive. Among other complications, those who had developed a coagulopathic complication were associated with non-survival (p = 0.0230). As far as interventions, there was no difference in mortality for those patients who required ventilatory support in the ED versus those who did not require ventilatory support (p = 0.3655). Due to the small sample size, a chi-square analysis and subsequently a regression model could not be performed.
Multivariate Logistic Regression Models
There were 151 observations due to 5 missing data that could not be included in the models. There were 58 ICU admissions and 93 non-ICU admissions. From the bivariate analysis in the previous tables, variables used for the full multivariate logistic regression model included sex (male versus female), age categories (18–49, 50–64, and ≥ 65 years old), BMI categories (underweight, or normal, overweight, and obese), history of CAD/HLD, history of CKD, and AKI complications, cardiovascular and coagulopathic complications, and history of dialysis (Table 1 and Table 2). These variables were found to be significant at an α level of 0.10.
The full multivariate logistic regression model included sex (male versus female), age categories (18–49 years old, 50–64 years old, and ≥ 65 years old), BMI categories (underweight, or normal, overweight, and obese), CAD/HLD alone, history of chronic kidney disease, history of dialysis, complications of coagulopathy during admission, and complications of AKI (Table 3). Of these, sex, overweight BMI, age ≥ 65 years old, comorbidities, history of CAD/HLD, cardiovascular and coagulopathic complications, and AKI were found to be the most significant. The clinically relevant variables such as coronary artery disease and/or hyperlipidemia were clinically significant risk factors for both ICU admission and mortality in previous observational literature. However, cardiovascular and coagulopathic complications were not included in the final model because they were not found to be statistically significant when entered in the final model at an α level of 0.05. Therefore, in creating the final multivariate logistic regression model, age was included, along with the variables of sex, BMI, history of coronary artery disease and/or hyperlipidemia, and AKI which were significant with an α level of 0.05 (Table 3).Table 3 Patient risk factors in ECRMC ICU admissions final regression model
Variable Odds ratio (OR) 95% CL Standard error Wald chi-square p-value
Sex
Male 3.76 (1.36, 10.4) 0.520 6.48 0.0109
Female 1.00 (reference) – – -
Age
18–49 years old 2.09 (0.519, 8.42) 0.711 1.08 0.299
50–64 years old 1.00 (reference) – – –
≥ 65 years old 5.84 (2.03, 16.8) 0.540 10.7 0.0011
Body mass index (BMI)
Underweight and normal 1.00 (reference) – – –
Overweight 7.14 (1.97, 25.8) 0.655 9.00 0.0027
Obese 2.61 (0.786, 8.71) 0.614 2.45 0.117
Coronary artery disease or hyperlipidemia 0.186 (0.067, 0.518) 0.523 10.3 0.0013
No coronary artery disease or hyperlipidemia 1.00 (reference) – – –
Acute kidney injury 19.7 (6.36, 61.1) 0.578 26.6 < 0.0001
No acute kidney injury 1.00 (reference) – – –
N = 151
In the final regression model, risk factors such as male sex, age, comorbidities, and complication of AKI during hospitalization were found to be significant predictors of ICU admission. Male patients have 3.76 odds (95% CI 1.36, 10.4) of being admitted to the ICU when compared with female patients (p = 0.0053). Those in the ≥ 65-year-old age group had 5.84 (95% CI 2.03, 16.8) odds of ICU admission compared with the 50–64-year-old age category (p = 0.0011). Of the ICU admitted patients, there was a higher proportion of overweight patients than obese patients (46.8% versus 32.3%, respectively) (Table 1). Obese patients were found to have 2.61(95% CI 0.79, 8.71) odds of admission to the ICU, but limited sample size may have contributed to the insignificant p-value (p = 0.117). Out of the chronic comorbidities in our hospitalized patients, those with a documented history of coronary artery disease/hyperlipidemia had 0.19 (95% CI 0.067, 0.518) odds of ICU admission compared with those without a history of coronary artery disease/hyperlipidemia (p = 0.0013). Additionally, those who developed AKI during their hospitalization had 19.7 (95% CI 6.36, 61.1) odds of ICU admission compared with those who do not develop AKI (p < 0001). Our multivariate logistic regression analysis found that the best predictors of ICU admission at ECRMC were male sex, those ≥ 65 years of age, those who developed acute kidney injury during their hospitalization, and those who had a BMI higher than 25. Additionally, patients with a history of coronary artery disease and/or hyperlipidemia were found to have a “protective factor” against ICU admission.
Discussion
Our study has a unique focus on the COVID-19 outcomes of a Latinx population specifically at a California border hospital. As with areas with predominantly Latinx populations, Imperial County has experienced some of the worst COVID-19 outcomes compared to the rest of the state. In our study of the initial COVID-19 surge, 45% of all the Latinx ECRMC hospitalized COVID-19 patients required intensive care compared with larger observational studies that had 14.2 to 36.1% of their patients requiring ICU level of care [12, 13]. These poor outcomes are indicators of overall health inequalities that have longed plagued Latinx border population prior to COVID-19.
Multiple factors likely contribute to the disparate COVID-19 hospitalizations at the U.S.-Mexico border. First, there is an increased risk of communicable respiratory disease spread due to transborder movement of essential workers [6, 7]. Second, poor health care infrastructure increases the risk of complications and death due to delayed medical care [7–9]. Third, there is a high prevalence multiple medical comorbid conditions such as diabetes, hypertension, and coronary artery disease [4–6]. Additionally, there is an influx of the aging population with multiple medical comorbidities that are known to substantially increase the risk of hospitalization, invasive ventilation or intubation, and death associated with COVID-19 [12–16].
The Imperial County Border Population
An estimated total of 15 million inhabitants resides at U.S.-Mexico Border with a large proportion who are of Mexican in origin [17]. Eight-five percent of Imperial County residents identify themselves as Hispanic/Latinx with a substantial percentage of Mexican heritage [17]. There is increased U.S.-Mexico transborder movement because of U.S. economic dependency of essential workers and because of the proximity to the border (12 miles). The U.S.-Mexico border is the busiest border crossing in the world with well over 275 million border crossings and comprise of essential workers, agricultural transit in trade and commerce, and U.S. citizens visiting family or seeking health care [17, 18]. Because of the essential nature of the border crossings, these crossings were not prevented by Department of Homeland Security (DHS) COVID-19 restrictions [19]. Studies from the most recent influenza pandemic demonstrated that cross-border travel can pose an increased risk of infectious disease transmission across both sides of the U.S.-Mexico border [20].
Like other areas with large Latinx population, Imperial County also has a large proportion of their population who are overrepresented in essential service industries, such as food services, health care, waste management, agriculture, and construction which increases their exposure risk to SARS-CoV-2 [7, 8]. Studies of Latinx patients who were hospitalized for COVID-19 found that 25% worked in essential occupations [6, 7]. These industries lack the infrastructure for employees to work from home and are often set in crowded areas with poor hygiene, which thus increases the risk of transmission, disease, and subsequent complications [7–9].
Socioeconomic Healthcare Disparities
Imperial County has high poverty rates with approximately 20% inhabitants of living below the poverty line [21]. Poverty is associated with decreased access to health insurance coverage and health care literacy [4–6]. Low insurance coverage leads to diagnostics delays of preventable diseases like diabetes and hypertension because of the limited access to preventative health screenings [22]. Decreased health literacy can contribute associated with obesity and other preventable diseases. Lack of health literacy is associated with for poorer health outcomes due to increased barriers to obtain disease prevention information. This, in turn, decreases success in disease management [22].
Imperial County has an overall shortage of health care providers and hospitals. The population is being served by two hospitals: ECRMC and Pioneers Memorial Hospital and Healthcare District in Brawley, California. In 2016, Imperial County has had one of the highest ratios of population to physician in California (4890 residents to one doctor), compared to 1090:1 in California overall [23]. This uneven distribution of physicians creates a health care delivery gap across all specialties. For example, emergency physicians practice overwhelmingly in urban areas (92%), whereas 2730 (6%) were in large rural areas and 1197 (2%) in small rural areas [24]. The disparate health care distribution has created a hole through the safety net of timely treatment of preventable disease overall which then became a significant contributor to the poor COVID-19 outcomes observed in Imperial County hospitals.
Emergency Department and Healthcare Disparities
The primary and preventative health care resource vacuum is absorbed by increased utilization of the emergency departments in already under-resourced hospitals. A large international survey study has shown that patients who see a regular physician had a decreased likelihood of going to the emergency department for care [25]. In the U.S., there is an increasing number of patients who utilize the ED because of significant delays in obtaining primary care appointments in a timely manner and are often waiting up to 2 months [25–28]. A California survey examined ED utilization found that patients with chronic illnesses compared to those without chronic illnesses were as follows: (1) likely to utilize the ED over an entire lifetime, (2) have had three of more visits to the ED per year, (3) likely to have “avoidable” ED visits [28]. Because of the 24/7/365 days a year availability of an ED, patients have more immediate access to laboratory results and specialists [28]. One report demonstrated that Imperial County has a low ratio of primary care physicians to population with 21.1 primary care physicians (PCPs) per 100,000 population compared to the adjacent border county of San Diego with 51.4 PCPs per 100,000 [29]. The delay and lack of primary care coverage then increases the demand for both chronic and acute health care needs which often overwhelms the resources at local emergency departments.
Prior to COVID-19 pandemic, reportedly 90% of U.S. emergency departments suffer from overcrowding where the need for emergency services often exceeds the resources for patient care [30]. The growth in ED visits over the last few decades has exceedingly outpaced the population demand. Additionally, there is a substantial increase of complex, comorbid patients with increased acuity who require medical attention in the EDs [31, 32]. The two lone EDs in Imperial County act a safety net for basic, primary medical care in a community where there is a high prevalence of chronic medical conditions. This dependency on the EDs for primary care can contribute to the constant overcrowding [30]. Emergency departments are often under resourced and understaffed which also contributes to the overcrowding and push rural and critical access hospitals like the hospitals in Imperial County to their breaking point even prior to the COVID-19 pandemic [30–32]. The COVID-19 pandemic in hospitals like ECRMC are often overwhelmed with shear volumes of patients where it is often ineffective in treating patients in a timely manner [30, 31]. Resources for a crisis or a continuous mass casualty event are non-existent because of the lack of resources at baseline [30]. The overcrowding that is already in most EDs make these departments most vulnerable to poor outcomes in highly contagious respiratory infectious disease like COVID-19.
Aging Population
Older hospitalized COVID-19 patients tend to have more comorbidities which are associated with an increased risk of severe COVID-19 complications and death [12–14, 33, 34]. Our study observations at ECRMC support these large studies where age was a significant risk factor for ICU admission and mortality, especially in the ≥ 65-year-old age category. Because there is a strong association of morbidity and mortality secondary to COVID-19 in older individuals, there has been a concerted effort to prioritize of both treatments and vaccines for 65-year-old and older age population [12–14, 33–35]. The aging population has increased precipitously over the last few decades in the U.S. with over a third (13,787,044) of the U.S. population which is now 65 years old and over, and this has been increasingly more evident in California overall [21]. Imperial County, like much of the rest of California, has had a 198% population increase over the last decade of those aged 65 years and older [21, 36]. Thus, the elderly population in Imperial County were the most vulnerable to severe COVID-19 complications in the often-overwhelmed emergency departments.
Male Sex
Males hospitalized for COVID-19 are at increased risk of becoming admitted to the ICU and dying when compared with females [12, 13, 23–25]. Our study supported this observation of male sex increased risk of COVID-19 ICU admission. Additionally, male patients had a higher prevalence of chronic conditions such as hypertension, diabetes, coronary heart disease, obstructive pulmonary disease, nicotine dependence, and heart failure compared with females which directly contribute to increased risk of COVID-19 ICU hospitalization and mortality [37, 39].
Social and behavioral factors can increase the risk for COVID-19 exposure and subsequent complications. Additionally, Latinx population is more likely to be disproportionately represented in essential industries that often increase exposure to SARS-CoV-2 infection. Males, in general, are often employed in food processing, transportation, construction, and manufacturing jobs—all of which are considered essential work during the pandemic [8, 38]. Many of those who reside in Imperial County work in the agricultural industry which accounts for approximately half of all employment [40, 41].
BMI
Obesity has become increasingly prevalent over the past few decades in the US. Compared to their non-Hispanic/White counterparts, Latinx populations also have higher rates elevated BMI (BMI > 25) [42]. Obesity is known to increase chronic comorbidities such as diabetes, hypertension, and hyperlipidemia, which in turn increases the risk for severe COVID-19 complications [1, 42–44]. According to California Health Interview Survey in 2009, 62% of Imperial County adults reported being overweight or obese, compared to 51% statewide. In Imperial County, 31% of the adult residents were obese (BMI > 30), compared to the rest of California overall (23%) [45]. It is with urbanization and increased exposure to Western style diets and lifestyle which has largely affected the health [46]. Often it is the children of subsequent generations of immigrants where increased exposure to Western diet and lifestyle will increase the risk of higher BMI and body fat percentage at baseline. In Imperial County, most of the residents are largely native residents of the US [45, 46].
Several prior observational studies have demonstrated that elevated BMI in patients increases the risk of respiratory failure and thus ICU admission and endotracheal intubation in COVID-19 patients [12–14, 42–44]. In our study, of the 62 patients who had an ICU admission, 79% (49) were classified as overweight or obese (Table 1). Although ICU admission was more frequently observed in the ≥ 65-year-old age group, the younger population of hospitalized 18–49-year-old patients was also likely to be obese or overweight (Appendix B, Table 3). Mechanical ventilation was frequently required due to respiratory failure in ICU patients with COVID-19 (Appendix B). Our regression model shows that even a BMI 24.5–29.9 was significantly associated with ICU admissions compared to those with normal BMI. Obesity also had an increased odds of ICU admission, but this was not statistically significant (p = 0.249). This discrepancy could be partially explained by the small sample size and may highlight the non-linear relationship between increasing BMI with the odds of ICU admission.
Acute Kidney Injury
While hospitalized, comorbidities have been shown to increase the risk of acute kidney injury (AKI) in patients. Diabetes, hypertension, and cardiovascular disease are very prevalent in the Imperial Valley [23]. These comorbidities increase the risk of AKI development [47, 48]. Multiple studies have demonstrated that AKI is a common complication for hospitalized COVID-19 patients and is associated with both ICU admission and mortality [49–53]. Our ECRMC patients who developed AKI at any time during hospitalization had increased odds of ICU level of care compared with those who did not have AKI. Patients who have been diagnosed with diabetes and hypertension may already have an upregulation of ACE2 receptors, which may contribute to an increased risk of severe COVID-19 secondary to direct renal damage due to SARS-CoV-2 [53, 54].
Limitations
This was a single-center, retrospective analysis of hospitalized COVID-19 patients at one hospital near the U.S.-Mexico border. While not representative of the general population, the emergent response at an under-resourced hospital may be reflective of many U.S-Mexico border hospitals that serve a large proportion of Latinx patients. Although few studies primarily investigated the impacts of Latinx populations, there have not been many studies on the Latinx patients at the U.S.-Mexico border.
Our number of observations is small. Comorbidities and obesity are both known to increase COVID-19 complications and disease severity such as ICU admission and death [11–14, 43]. But some well-established correlations could not be completely reflected because of the likely bias of a small sample size. Additionally, the overrepresentation of the 50–64-year-old age group also had more comorbidities which may have led to an increased risk of ICU admission. The reported history of coronary artery disease and/or hyperlipidemia was found to be protective against ICU admissions which could be partially explained by the chronic use of statin medications in this group of hospitalized COVID-19 patients [55]. Some observational studies on patients who have been admitted for COVID-19 have also demonstrated that taking lipid-lowering medications such as statins could potentially decrease the risk of developing severe COVID-19 and decrease the recovery time among patients with severe disease [55–57]. Perhaps a larger sample size may demonstrate that there is little association between the use of statins and protection against severe COVID-19. Statins have shown some theoretical anti-inflammatory, anti-thrombotic, and immunomodulatory functions which could be potentially decrease the risk of severe COVID-19 development [56].
Additionally, the data from this study was performed during a surge and therefore some data was incomplete and was inevitably excluded. This led to sample sizes that were insufficient in eliminating sampling bias. Despite the lack of complete data for some common complications due to COVID-19, our study supports prior findings and highlights the poor outcomes in this Latinx border population.
Future Studies
At the time of writing this study, there have been several variants of concern (VOCs) including delta, gamma, lambda, and omicron [26, 58, 59]. These VOCs have been contributing to an increased number of cases across the U.S. Most recently, Imperial County has one of the highest vaccination rates per population with 94% completely vaccinated and 44% with boosters against SARS-CoV-2 [45].
We hope that this observational study will call attention to the need to study the true impacts of infectious diseases like COVID-19 on the Latinx border population. Future research efforts can be potentially focused on addressing the underlying the health care disparities that make the health care system and the population at U.S.-Mexico border more vulnerable to poor outcomes from catastrophic events. Other research should also focus on the lessons learned from the COVID-19 pandemic that can be used to prepare for future catastrophic events that will overwhelm the emergency departments in under-resourced border hospitals.
Conclusion
More research is starting to develop on the impacts COVID-19 on the Latinx community; however, there is still little known in regard to the Latinx U.S. border population and COVID-19. Our study highlights the underlying socioeconomic and health care disparities which likely contribute to the significant disparity of COVID-19 outcomes in the Latinx/Hispanic U.S.-Mexico border population.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 32 KB)
Author Contribution
All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Faith C. Quenzer, Ashley Williams, Andrew T. Lafree, Sten Kajitani, George Mathen, Vanessa Villegas, Kari M. Kajitani, and Christian Tomaszewski. The first draft of the manuscript was written by Faith C. Quenzer, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Data Availability
The data obtained for this study can be found under restricted access at https://doi.org/10.5281/zenodo.6430637.
Code Availability
The SAS © Code used to analyze the data obtained for this study can be found under restricted access at https://doi.org/10.5281/zenodo.6430637.
Declarations
Ethics Approval
This is a retrospective, observational study which was conducted on already available data, for which formal consent was not needed. The UC San Diego Research Ethics Committee has confirmed that our study is IRB exempt and not requiring approval per their board.
Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Competing Interests
The authors declare no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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47. Farooqi S Dickhout JG Major comorbid disease processes associated with increased incidence of acute kidney injury World journal of nephrology 2016 5 2 139 146 10.5527/wjn.v5.i2.139 26981437
48. Loutradis C Pickup L Law JP Dasgupta I Townend JN Cockwell P Sharif A Sarafidis P Ferro CJ Acute kidney injury is more common in men than women after accounting for socioeconomic status, ethnicity, alcohol intake and smoking history Biol Sex Differ 2021 12 1 30 10.1186/s13293-021-00373-4 33832522
49. Ali H Daoud A Mohamed MM Salim SA Yessayan L Baharani J Murtaza A Rao V Soliman KM Survival rate in acute kidney injury superimposed COVID-19 patients: a systematic review and meta-analysis Renal Failure 2020 42 1 393 397 10.1080/0886022X.2020.1756323 32340507
50. Chan L Chaudhary K Saha A Chauhan K Vaid A Zhao S Paranjpe I Somani S Richter F Miotto R Lala A Kia A Timsina P Li L Freeman R Chen R Narula J Just AC Horowitz C Fayad Z Mount Sinai COVID Informatics. Center AKI in Hospitalized Patients with COVID-19 J American Soc Nephrol 2021 32 1 151 160 10.1681/ASN.2020050615
51 Hardenberg JB Luft FC Covid-19, ACE2 and the kidney Acta Physiolog 2020 230 1 e13539 10.1111/apha.13539
52. Hirsch JS Ng JH Ross DW Sharma P Shah HH Barnett RL Hazzan AD Fishbane S Jhaveri KD Northwell, COVID-19 Research Consortium, & Northwell Nephrology COVID-19 Research Consortium Acute kidney injury in patients hospitalized with COVID-19 Kidney Int 2020 98 1 209 218 10.1016/j.kint.2020.05.006 32416116
53. Ng JH Bijol V Sparks MA Sise ME Izzedine H JhaveriKD, Pathophysiology and pathology of cute kidney injury in patients with COVID-19 Adv Chron Kidney Dis 2020 27 5 365 376 10.1053/j.ackd.2020.09.003
54. Sharma P Uppal NN Wanchoo R Shah HH Yang Y Parikh R Khanin Y Madireddy V Larsen CP Jhaveri KD Bijol V Northwell Nephrology COVID-19 Research Consortium. COVID-19-associated kidney injury A case series of kidney biopsy findings Journal of the American Society of Nephrology 2020 31 9 1948 1958 10.1681/ASN.2020050699 32660970
55. Daniels LB Ren J Kumar K Bui QM Zhang J Zhang X Sawan MA Eisen H Longhurst CA Messer K Relation of prior statin and anti-hypertensive use to severity of disease among patients hospitalized with COVID-19: findings from the American Heart Association's COVID-19 Cardiovascular Disease Registry PLoS ONE 2021 16 7 e0254635 10.1371/journal.pone.0254635 34264974
56. Reiner Ž Hatamipour M Banach M Pirro M Al-Rasadi K Jamialahmadi T Radenkovic D Montecucco F Sahebkar A Statins and the COVID-19 main protease: in silico evidence on direct interaction Arch Med Sci 2020 16 3 490 496 10.5114/aoms.2020.94655 32399094
57. Castiglione V Chiriacò M Emdin M Taddei S Vergaro G Statin therapy in COVID-19 infection Eur Heart J Cardiovas Pharmacoth. 2020 6 4 258 259 10.1093/ehjcvp/pvaa042
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| 36478268 | PMC9735002 | NO-CC CODE | 2022-12-14 23:28:32 | no | J Racial Ethn Health Disparities. 2022 Dec 7;:1-12 | utf-8 | J Racial Ethn Health Disparities | 2,022 | 10.1007/s40615-022-01478-1 | oa_other |
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Global Surg Educ
Global Surgical Education - Journal of the Association for Surgical Education
2731-4588
Springer US New York
82
10.1007/s44186-022-00082-5
Original Article
Impact of faculty well-being on medical student education
http://orcid.org/0000-0002-0419-4741
Bynum Ryan C. [email protected]
1
Richman Joshua S. 23
Corey Britney 23
Fazendin Jessica M. 2
1 grid.266902.9 0000 0001 2179 3618 University of Oklahoma Health Sciences Center, Oklahoma City, USA
2 The UAB Heersink School of Medicine, Birmingham, USA
3 Birmingham Veteran’s Affairs Health Care System, Birmingham, USA
8 12 2022
2023
2 1 719 5 2022
3 10 2022
16 11 2022
© The Author(s), under exclusive licence to Association for Surgical Education 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Purpose
The prevalence of physician burnout has risen and negatively impacts patient care, healthcare costs, and physician health. Medical students are heavily influenced by the medical teams they rotate with on the wards. We postulate that faculty well-being influences student perception of clerkships.
Methods
Medical student evaluations core clerkships at one academic institution were compared with results of faculty well-being scores over 2 years (2018–2020). Linear mixed models were used to model each outcome adjusting for year, mean faculty distress score, and the standard deviation (SD) of WBI mean distress scores. Clerkships and students were treated as random effects.
Results
Two hundred and eighty Well-Being Index evaluations by faculty in 7 departments (5 with reportable means and standard deviations), and clerkship evaluations by 223 students were completed. Higher faculty distress scores were associated with lower student evaluation scores of the clerkship (− 0.18 per unit increase in distress, std. err = 0.05, p < 0.01). Increased SD (variability) of faculty distress was associated with higher student overall ratings (0.49 points per unit increase in variability, std. err = 0.11, p < 0.01), as was year with 2019–2020 having lower overall ratings (− 0.17, std. err = 0.06, p < 0.01). Findings were similar for ratings of faculty teaching: mean faculty distress (− 0.15, std. err = 0.25), SD faculty distress (0.33, std. err = 0.12), 2019–2020 vs. 2018–2019 (− 0.19, std. err = 0.06) (all p < 0.01).
Conclusions
Physician well-being is not only associated with quality of patient care and physician health, but also with medical student perceptions of clinical education. These findings provide yet another indirect benefit to improved physician well-being: enhanced undergraduate medical educational experience.
Keywords
Medical education
Well-being
Burnout
Teaching
issue-copyright-statement© The Author(s), under exclusive licence to Association for Surgical Education 2023
==== Body
pmcIntroduction
Over the recent year, the topics of burnout, fatigue and well-being have become significant areas of research. As the research interest surrounding physician wellness continues to expand, new tools are being developed to assess physician well-being [1]. The increasing prevalence of provider burnout negatively impacts patient care, healthcare costs and physician and provider health [2]. In one cross-sectional study, physicians who reported errors were found to have higher levels of burnout, and work-unit safety grades were found to be independently associated with burnout, well-being, and self-reported medical errors [3]. However, academic physicians not only affect the patients they encounter, but also shape the learners with whom they interact. Regarding medical student education, it has been shown that higher burnout rates in medical students may be related to lower professional climate scores [4]. While studies regarding physician well-being and its effects on patient care, healthcare cost, safety, and provider health are numerous, few studies have been conducted evaluating the relationship between physician wellness and learner education. We aim to evaluate if any association exists between faculty wellness scores and student perceptions of their clerkships and the quality of faculty teaching.
Methods
Student evaluations
Students complete evaluations of the core clerkships after each rotation. These evaluations include various questions, on a 5-point Likert scale, regarding organization of the clerkship, usefulness of the clerkship as preparation for residency, professionalism observed on the clerkship, as well as other questions regarding the learning environment. In particular, the questions regarding “Overall Evaluation of the Clerkship” and “Evaluation of Faculty Teaching” were of interest in this study. These survey results were obtained with de-identified student information.
Well-Being Index
The Physician Well-Being Index (WBI) is a screening tool developed to stratify mental quality of life (including depression and recent suicidal ideation), burnout, fatigue, stress, and career satisfaction in medical professionals. It has been validated in residents, medical students, and physicians [1, 5]. The WBI was distributed and voluntarily completed by faculty with the maximum frequency allowed for completion approximately monthly. Data from this 7-item screening tool were made available at the department level with mean distress score, standard deviation of mean distress score, and number of completed WBI’s reported for each department representing core clerkships. A minimum number of 5 unique individuals, set by the developers of the WBI, needed to complete the WBI for the mean distress scores to be generated.
Data analysis
Existing medical student evaluations of each of the 7 core clerkships (Psychiatry, Ob-Gyn, Neurology, Surgery, Family Medicine, Pediatrics, and Internal Medicine) were compared with Physician Well-Being Index scores of faculty over a 2 year period (2018–2020) at a single large academic medical center. The WBI was first implemented at the study institution at the beginning of the 2018–2019 academic year. Student evaluation data was modeled by academic year and both mean and standard deviation (SD) for both overall evaluations of the clerkship and for evaluation of faculty teaching. The primary outcomes were the student ratings of faculty teaching and their overall clerkship rating. Linear mixed models were used to model each outcome adjusting for year, mean distress score (where higher score indicates greater level of distress), and the standard deviation of WBI mean distress scores. The departments and students were treated as random effects to account for the multiple ratings per clerkship (department) and multiple ratings per student throughout the years. Of note, the second year over which this study was conducted (2019–2020) does include the time period where 3rd year medical students began virtual clerkships in place of in-person rotations during the beginning of the COVID-19 pandemic. However, this study was not specifically designed to evaluate the effects of changes in the learning environment due to the pandemic.
The study was submitted to, reviewed, and approved by the Institutional Review Board at the study institution.
Results
In total, 280 individual WBI evaluations were completed by faculty from the departments of the core clerkships over the 2-year period. As the WBI results were available only at the department level, this number indicates the number of unique instances the WBI was completed, and not necessarily the number of 5 unique individuals who completed the WBI. 1240 total student evaluations of the core clerkships were completed over the same time period by a total of 223 students with multiple ratings per student, as each 3rd year medical student rotates through and can evaluate each core clerkship.
Mean distress
Mean distress scores with associated student evaluations of the clerkship overall and evaluations of faculty teaching are shown in Tables 1 and 2, respectively. Of note, mean and SD of distress scores were not reported for Family Medicine and Ob-Gyn departments due to the restrictions placed by the developers of the WBI for a minimum threshold of unique individuals. Higher mean distress scores of faculty were observed to be associated with both lower evaluations by students of the clerkship overall, with a − 0.18 per unit increase in mean distress (std. err = 0.05, p < 0.01) as well as lower evaluations of faculty teaching on the clerkship, with a − 0.15 per unit increase in mean distress (std. err = 0.25, p < 0.01), as shown in Table 3.Table 1 Faculty distress vs overall clerkship evaluations
Department Mean distress score (n) Mean student evaluations of clerkship (n)
Family Medicine (13)* 4.19 (157)
Internal Medicine 0.77 (30) 4.38 (188)
Neurology 1.59 (22) 3.92 (182)
OBGYN (27)* 4.15 (172)
Pediatrics 2 (102) 4.41 (181)
Psychiatry 1 (23) 3.82 (179)
Surgery 1.34 (53) 3.71 (181)
Mean faculty distress scores (higher value indicates greater distress) from the WBI with number of completed WBI’s (n) shown with associated mean student evaluations (5-point scale) and number of evaluations of the clerkship overall(n) for each core clerkship (department)
*Denotes value not reported due to not meeting minimum number of unique individuals set by the Well-Being Index
Table 2 Faculty distress vs faculty teaching evaluations
Department Mean distress score (n) Mean student evaluations of teaching (n)
Family Medicine (13)* 4.22 (157)
Internal Medicine 0.77 (30) 4.41 (188)
Neurology 1.59 (22) 4.15 (182)
OBGYN (27)* 4.14 (172)
Pediatrics 2 (102) 4.25 (181)
Psychiatry 1 (23) 3.92 (179)
Surgery 1.34 (53) 3.75 (181)
Mean faculty distress scores (higher value indicates greater distress) from the WBI with number of completed WBI’s (n) shown with associated mean student evaluations of faculty teaching (5-point scale) and number of evaluations (n) for each core clerkship (department)
*Denotes value not reported due to not meeting minimum number of unique individuals set by the Well-Being Index
Table 3 Summary table depicting coefficients for the associations observed
Coefficient Std. Error p value
Mean distress vs. evaluations of clerkship − 0.18 0.05 < 0.01
Mean distress vs. evaluations of teaching − 0.15 0.05 < 0.01
Variance vs. evaluations of clerkship 0.49 0.11 < 0.01
Variance vs. evaluations of teaching 0.33 0.12 < 0.01
Y1 vs Y2 clerkship overall − 0.17 0.06 < 0.01
Y1 vs Y2 faculty teaching − 0.19 0.06 < 0.01
Variability
Additionally, the association between variability in faculty distress scores, quantified by the standard deviation within each department by year, and student evaluations of the clerkship overall and faculty teaching was assessed. Variance and associated student evaluation scores are shown in Table 4 and Table 5. Increased variability of faculty distress was found to be associated with higher evaluations of both clerkship (0.49 points per unit increase in sd, std. err = 0.11, p < 0.01) and of faculty teaching (0.33 points per unit increase in sd, std. err = 0.12) as shown in Table 3.Table 4 Faculty distress variability vs overall clerkship evaluations
Department SD distress score (n) Mean student evaluations of clerkship (n)
Family Medicine (13)* 4.19 (157)
Internal Medicine 1.65 (30) 4.38 (188)
Neurology 1.50 (22) 3.92 (182)
OBGYN (27)* 4.15 (172)
Pediatrics 2.87 (102) 4.41 (181)
Psychiatry 2.69 (23) 3.82 (179)
Surgery 2.53 (53) 3.71 (181)
Mean SD (variability) of faculty distress scores from the WBI with number of completed WBI’s (n) shown with associated mean student evaluations of the clerkship overall (5-point scale) and number of evaluations (n) for each core clerkship (department)
*Denotes value not reported due to not meeting minimum number of unique individuals (5) set by the Well-Being Index
Table 5 Faculty distress variability vs faculty teaching evaluations
Department SD distress score (n) Mean student evaluations of teaching (n)
Family Medicine (13)* 4.22 (157)
Internal Medicine 1.65 (30) 4.41 (188)
Neurology 1.50 (22) 4.15 (182)
OBGYN (27)* 4.14 (172)
Pediatrics 2.87 (102) 4.25 (181)
Psychiatry 2.69 (23) 3.92 (179)
Surgery 2.53 (53) 3.75 (181)
Mean SD (variability) of faculty distress scores from the WBI with number of completed WBI’s (n) shown with associated mean student evaluations of faculty teaching (5-point scale) and number of evaluations (n) for each core clerkship (department)
*Denotes value not reported due to not meeting minimum number of unique individuals (5) set by the Well-Being Index
Year 1 (2018–2019) versus Year 2 (2019–2020)
Finally, associations between mean distress scores by year and evaluations of clerkships and of faculty teaching were evaluated. Mean distress scores and corresponding clerkship and faculty teaching evaluations are shown in Tables 6 and 7, respectively. Again, the minimum threshold of 5 unique individuals completing the WBI for mean distress scores to be reported was not met for year 2 (2019–2020) for Family Medicine and Ob-Gyn. When year 1 and year 2 were compared, year 2 was found to be associated with lower evaluations of both the clerkships and of faculty teaching (− 0.19, std. err = 0.06, p < 0.01), as shown Table 3.Table 6 Faculty distress by year vs overall clerkship evaluations by year
Department Mean distress score Y1 (n) Mean student evaluations of clerkship Y1 (n) Mean distress score Y2 (n) Mean student evaluations of clerkship Y2 (n)
Family Medicine 2 (12) 4.25 (93) (1)* 4.1 (64)
Internal Medicine 0.41 (22) 4.41 (99) 1.75 (8) 4.33 (89)
Neurology 2.12 (17) 3.94 (103) − 0.2 (5) 3.90 (79)
OBGYN 1.96 (23) 4.27 (99) (4)* 3.97 (73)
Pediatrics 2.06 (80) 4.42 (99) 1.77 (22) 4.41 (82)
Psychiatry 0.47 (15) 4 (103) 2 (8) 3.58 (76)
Surgery 1.64 (42) 3.92 (100) 0.18 (11) 3.45 (81)
Y1 = 2018–2019, Y2 = 2019–2020
Mean faculty distress scores from the WBI with number of completed WBI’s (n) shown, with associated mean student evaluations of the clerkship overall (5-point scale) and number of evaluations (n) for each core clerkship (department), both by year
*Denotes value not reported due to not meeting minimum number of unique individuals (5) set by the Well-Being Index
Table 7 Faculty distress by year vs faculty teaching evaluations by year
Department Mean distress score Y1 (n) Mean student evaluations of teaching Y1 (n) Mean distress score Y2 (n) Mean student evaluations of teaching Y2 (n)
Family Medicine 2 (12) 4.33 (93) * (1) 4.08 (64)
Internal Medicine 0.41 (22) 4.47 (99) 1.75 (8) 4.35 (89)
Neurology 2.12 (17) 4.16 (103) − 0.2 (5) 4.14 (79)
OBGYN 1.96 (23) 4.3 (99) * (4) 3.92 (73)
Pediatrics 2.06 (80) 4.28 (99) 1.77 (22) 4.21 (82)
Psychiatry 0.47 (15) 4.09 (103) 2 (8) 3.68 (76)
Surgery 1.64 (42) 3.93 (100) 0.18 (11) 3.53 (810)
Y1 = 2018–2019, Y2 = 2019–2020
Mean faculty distress scores from the WBI with number of completed WBI’s (n) shown, with associated mean student evaluations of faculty teaching (5-point scale) and number of evaluations (n) for each core clerkship (department), both by year
*Denotes value not reported due to not meeting minimum number of unique individuals (5) set by the Well-Being Index
Discussion
This study, performed at a single large academic medical center, shows that lower faculty well-being is associated with lower student perceptions of both the clerkships on which they rotate and of faculty teaching. Faculty in academic medicine are in a unique position with many roles to fulfill which can conflict with teaching and their role as an educator [6]. As workloads increase and faculty wellness declines so may their level of work engagement, which can also include their commitment to undergraduate medical education. A sense of low job control has been observed to be associated with greater emotional exhaustion in one meta-analysis [7]. This may possibly place faculty in a position to become less engaged as educators, which may affect students and learners, as long-term outcomes of learner neglect have been discussed to negatively impact student learning and ultimately lead to learner burnout [8]. Additionally, while this study particularly focused on the association between faculty wellness and student perceptions of their education, burnout in residents has been seen to be related to not only self-reported sub-optimal care but has also been discussed as affecting the medical students whom they encounter via the hidden curriculum [9]. Positive associations have also been observed between medical student burnout rates and medical students reporting having a cynical resident on their team [10], findings the authors of this study would expect be a similar occurrence in the faculty-student relationship.
Additionally, greater variability in the well-being of faculty encountered by students on clerkships is associated with higher student perceptions of clerkships and faculty teaching. As individual wellness fluctuates over time, this finding may be explained in that with greater variability of faculty mean distress students may have had the opportunity to encounter faculty with higher well-being or healthier outlooks and approaches to improving their well-being. However, this study is limited in its ability to evaluate this as it is unable to assess changes and trends in individual faculty wellness over time due to faculty mean distress scores only available to be reported at departmental levels.
In addition, several other important limitations of this study exist. This study was completed at a single academic medical center, which may limit its generalizability to other institutions, as work environments differ between academic medical centers. Faculty distress scores were also only available to be reported by department and year, limiting the ability to incorporate changes in individual faculty well-being through the study period. This also means that we were unable to pair faculty who completed the WBI with students who rotated on the clerkship while these faculty were on service, limiting the ability to evaluate for direct associations between faculty wellness on student education within specific rotations. Further larger and multi-institutional and multivariate studies would be beneficial in the future. Of note, year 2 (academic year 2019–2020) includes the time period when clinical students were withdrawn from the wards during the beginning of the COVID-19 pandemic and began virtual clerkships. While this study attempts to provide some insight into longitudinal association of faculty wellness and student perceptions of education, the associations of lower faculty teaching and clerkships may be largely explained by the transition to virtual clerkships as well as the greater psychosocial effects of the pandemic.
Further studies to evaluate for correlations and causal relationships between wellness of academic medical educators and the education of learners is warranted. Studies investigating the impact of interventions improving educator wellness on education would also be beneficial, as this study did not evaluate if interventions to improve faculty well-being are associated with the perception of education by medical students. Examples of further directions include investigating resident wellness and its relation to student education, as residents also greatly influence medical students’ learning environment. Studies investigating levels of resident autonomy, competence, and social relatedness, which have been found to be associated with greater resident wellness [11], may be insightful, as would improvements in the learning climate, which is associated with higher work engagement and job satisfaction among residents [12].
As more studies regarding well-being in the medical field are carried out over the coming years, attention should be paid to how this area relates to the learning environment. Learner education may benefit from efforts to impact the wellness of educators and learners not only at the individual level, but all levels of education. Buery-Joyner et al. have proposed several questions which clinical educators, educational program directors, and health care systems may reflect on to improve the learning environment [8]. Intentional and systematic action has been proposed to ensure the development of vitality within departments of academic medicine and faculty as this unified drive has been argued to be crucial in combating declining wellness [13]. This process of training not only clinically and academically strong physicians, but those with high levels of work engagement is an important focus, which may be beneficial to begin as early as in undergraduate medical education [14].
Conclusion
Physician well-being is not only associated with quality of patient care and physician health, but also the perceptions medical students hold regarding their clinical education. While further studies identifying correlation are needed, improving physician wellness may enhance the undergraduate medical educational experience.
Funding
No funding was received for conducting this study.
Declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
==== Refs
References
1. Dyrbye LN Satele D Sloan J Shanafelt TD Utility of a brief screening tool to identify physicians in distress J Gen Intern Med 2013 28 3 421 427 10.1007/s11606-012-2252-9 23129161
2. Wallace JE Lemaire JB Ghali WA Physician wellness: a missing quality indicator Lancet 2009 374 9702 1714 1721 10.1016/S0140-6736(09)61424-0 19914516
3. Tawfik DS Profit J Morgenthaler TI Physician Burnout, well-being, and work unit safety grades in relationship to reported medical errors Mayo Clin Proc 2018 93 11 1571 1580 10.1016/j.mayocp.2018.05.014 30001832
4. Brazeau CM Schroeder R Rovi S Boyd L Relationships between medical student burnout, empathy, and professionalism climate Acad Med 2010 85 10 Suppl S33 S36 10.1097/ACM.0b013e3181ed4c47 20881699
5. Dyrbye LN Satele D Sloan J Shanafelt TD Ability of the physician Well-Being Index to identify residents in distress J Grad Med Educ 2014 6 1 78 84 10.4300/JGME-D-13-00117.1 24701315
6. van den Berg JW Verberg CP Berkhout JJ Lombarts MJ Scherpbier AJ Jaarsma AD A qualitative interview study on the positive well-being of medical school faculty in their teaching role: job demands, job resources and role interaction BMC Res Notes 2015 8 401 10.1186/s13104-015-1393-4 26329102
7. Aronsson G Theorell T Grape T A systematic review including meta-analysis of work environment and burnout symptoms BMC Public Health 2017 17 1 264 10.1186/s12889-017-4153-7 28302088
8. Buery-Joyner SD Ryan MS Santen SA Borda A Webb T Cheifetz C Beyond mistreatment: learner neglect in the clinical teaching environment Med Teach 2019 41 8 949 955 10.1080/0142159X.2019.1602254 31017502
9. Shanafelt TD Bradley KA Wipf JE Back AL Burnout and self-reported patient care in an internal medicine residency program Ann Intern Med 2002 136 5 358 367 10.7326/0003-4819-136-5-200203050-00008 11874308
10. Dyrbye LN Thomas MR Harper W The learning environment and medical student burnout: a multicentre study Med Educ 2009 43 3 274 282 10.1111/j.1365-2923.2008.03282.x 19250355
11. Raj KS Well-being in residency: a systematic review J Grad Med Educ 2016 8 5 674 684 10.4300/JGME-D-15-00764.1 28018531
12. Lases LSS Arah OA Busch ORC Heineman MJ Lombarts KMJMH Learning climate positively influences residents' work-related well-being Adv Health Sci Educ Theory Pract 2019 24 2 317 330 10.1007/s10459-018-9868-4 30519786
13. Shah DT Williams VN Thorndyke LE Restoring faculty vitality in academic medicine when burnout threatens Acad Med 2018 93 7 979 984 10.1097/ACM.0000000000002013 29166355
14. van den Berg JW Mastenbroek NJJM Scheepers RA Jaarsma ADC Work engagement in health professions education Med Teach 2017 39 11 1110 1118 10.1080/0142159X.2017.1359522 28830279
| 0 | PMC9735005 | NO-CC CODE | 2022-12-14 23:28:32 | no | Global Surg Educ. 2023 Dec 8; 2(1):7 | utf-8 | null | null | null | oa_other |
==== Front
Cerebellum
Cerebellum
Cerebellum (London, England)
1473-4222
1473-4230
Springer US New York
36482027
1504
10.1007/s12311-022-01504-2
Research
The Effects of N-Acetyl-L-Leucine on the Improvement of Symptoms in a Patient with Multiple Sulfatase Deficiency
Saberi-Karimian Maryam 12
Houra Mahsa 3
Jamialahmadi Tannaz 45
Sarvghadi Pooria 6
Nikbaf Mahlagha 7
Akhlaghi Saeed 8
Sahebkar Amirhosein [email protected]
[email protected]
491011
1 grid.411583.a 0000 0001 2198 6209 International UNESCO Center for Health Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, Iran
2 grid.411583.a 0000 0001 2198 6209 Endoscopic and Minimally Invasive Surgery Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
3 grid.411583.a 0000 0001 2198 6209 Department of Midwifery, School of Nursing and Midwifery, Mashhad University of Medical Sciences, Mashhad, Iran
4 grid.411583.a 0000 0001 2198 6209 Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
5 grid.411583.a 0000 0001 2198 6209 Surgical Oncology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
6 Atiyeh Rehabilitation Center, Mashhad, Iran
7 grid.412888.f 0000 0001 2174 8913 Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran
8 grid.411583.a 0000 0001 2198 6209 Psychiatry and Behavioral Sciences Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
9 grid.411583.a 0000 0001 2198 6209 Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
10 grid.1012.2 0000 0004 1936 7910 School of Medicine, The University of Western Australia, Perth, WA Australia
11 grid.411583.a 0000 0001 2198 6209 Department of Biotechnology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
9 12 2022
17
1 12 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Multiple Sulfatase Deficiency (MSD) is a rare autosomal recessive disease with specific clinical findings such as psychomotor retardation and neurological deterioration. No therapy is available for this genetic disorder. Previous studies have shown that N-acetyl-L-leucine (NALL) can improve the neurological inflammation in the cerebellum.
In the current study, the effects of NALL on ataxia symptoms and quality of life were explored in a patient with MSD.
This study was a crossover case study. The subject, a girl aged 12 years old, received NALL at a dose of 3 g/day (1 g in the morning, 1 g in the afternoon, and 1 g in the evening). A fasting blood sample was taken from the subject to evaluate side effects before the intervention and 4 weeks after taking supplement/placebo in every study stage. The ataxia moving symptoms were evaluated using the Scale for the Assessment and Rating of Ataxia (SARA) score in every study stage. Dietary intake was measured using 24-h dietary recall before and after the intervention. The diet compositions were assessed by Nutritionist IV software. Serum IL-6 level was measured using an ELISA kit.
There was no significant change in complete blood count (CBC) and serum biochemical factors in the patient with MSD after receiving NALL (3 g/day) over 4 weeks. The SARA score was reduced by 25%. The gait whose maximum score accounts for approximately one-fifth of the maximum total SARA score (8/40) was decreased. The heel-to-shin slide, the only SARA item performed without visual control, was also improved after therapy. Furthermore, there was a downward trend in the 8MWT (8.71 to 7.93 s). Regarding quality of life assessments, the parent and child reported improved quality of life index, physical health, and emotional function after taking NALL. Moreover, total energy intake was increased with NALL treatment through the study period.
Supplementation with NALL at a dose of 3 g/day over 4 weeks was well tolerated and improved ataxia symptoms, quality of life measure, and serum IL-6 levels in the patient with MSD. Further proof-of-concept trials are warranted to confirm the present findings.
Keywords
Multiple Sulfatase Deficiency
N-acetyl-leucine
Lysosomal Storage Disease
Clinical Study
http://dx.doi.org/10.13039/501100004748 Mashhad University of Medical Sciences 4001662 Sahebkar Amirhosein
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pmcIntroduction
Multiple sulfatase deficiency (MSD) is a lysosomal storage disease (LSD), which is a rare genetic disorder with autosomal recessive inheritance [1, 2]. Sulfatases can catalyze the hydrolysis of sulfate ester bonds in numerous substrates including glycosaminoglycans (GAGs), sulfolipids, and steroid sulfates [3]. Seventeen sulfatase genes have been found in the human genome [4]. In MSD, a severe reduction or complete absence of all sulfatase functions occurs due to a mutation in the gene encoding the formylglycine (FGly)-generating enzyme (FGE) that generates FGly [5, 6]. The mutations in the SUMF1 gene, encoding FGE, affect the posttranslational modification of sulfatases, thereby causing the replacement of a cysteine situated in the catalytic site of sulfatase by α-FGly [5, 6].
Specific clinical manifestations of MSD are psychomotor retardation and neurological deterioration, as well as vision and hearing loss, organomegaly, corneal clouding, cardiac valve disease, dystosis multiplex, stiff joints and ichthyosis, and ultimately premature death [5–7]. A total of 18 missense mutations over 17 different residues of mature FGE have been found to date [5, 6, 8].
No therapy is yet available for this genetic disorder. Previous studies have shown that N-acetyl-L-leucine (NALL) can improve the neurological inflammation in the cerebellum. An in vivo study in a rat model with traumatic brain injury (TBI) has shown that treatment with NALL improves lysosome-associated autophagy and can restore neuroprotective function in the ipsilateral cortex after TBI [9]. To date, no clinical study has been performed with NALL in patients with MSD. Moreover, due to the fact that this progressive genetic disorder can affect patients’ quality of life, administration of NALL as a low-cost supplement might be effective in improving patients’ symptoms and quality of life. Therefore, in the current study, we evaluated the effects of NALL intervention on ataxia symptoms and quality of life in a patient with MSD.
Methods
Ethics
The study protocol has been approved by the Ethics Committee at the Mashhad University of Medical Sciences (MUMS), (ID: IR.MUMS.MEDICAL.REC.1401.127) and registered in the Iranian Registry of Clinical Trials (registration number: IRCT20210413050958N5). A written consent form has been signed by her parents.
Subject
The subject was a girl with MSD aged 12 years old (weight 33.60 kg and height 136.00 cm). The MSD diagnosis had been confirmed by genetic testing at the age of 9 years {Variant: Homozygous NM: 182,760:exon4:c.G529C:p.A177P; SUMF1 class 2-Likely pathogenic}.
Drug Preparation
NALL powder was purchased from Shenzhen Ipure Biological Import and Export Co., Ltd (China). The caplets of NALL and placebo (500 mg) were prepared in the Industrial Laboratory of the Faculty of Pharmacy (MUMS, Mashhad, Iran).
Study Design
This study was a case crossover study. The subject received the NALL at a dose of 3 g/day (1 g in the morning, 1 g in the afternoon, and 1 g in the evening). A fasting blood sample was taken from the subject to evaluate side effects before the intervention and 4 weeks after taking supplement/placebo in every study stage. Serum IL-6 level was measured by the Karmania Pars gene ELISA kit (Kerman, Iran). The ataxia moving symptoms were evaluated using the Scale for the Assessment and Rating of Ataxia (SARA) score in every study stage. The quality of life has been assessed using the PedsQL questionnaire, in which the answers are in the form of Likert and five options {always (0), often: 1, sometimes: 2, very little: 3, never: 4}. The score obtained for each subscale will be from 0 to 100. Each phrase is scored as below: always: 0, often: 25, sometimes: 50, very low: 75, Never: 100. So that, a score < 25 shows a low quality of life. A score from 25 to 75 displays an average quality of life and a score > 75 indicates a high quality of life. It should be mentioned that the current study was conducted during the Coronavirus (COVID-19) pandemic, which significantly affected the schedule of events.
Dietary Intake Assessment
Dietary intake was measured using 24-h dietary recall before and after the intervention. The amount of dietary energy and nutritional intake of patients were then calculated using Nutritionist IV software (version 7.0; N‐Squared Computing, Salem, OR, USA) based on US Department of Agriculture (USDA) food composition table revised for Iranian foods [10]. The software computed the amount of calories consumed, macronutrients, micronutrients, fibers, and the percentage of macronutrients in the daily energy intake based on the meals ingested.
Results
Biochemical Markers
The main biochemical markers of the patient are summarized in Table 1. There was not any significant change in biochemical factors in our patient during study. The serum IL-6 level showed a downward trend.Table 1 The effect of N-acetyl-L-Leucine on clinical characteristics and serum biochemical factors in a girl with multiple sulfatase deficiency
Variables Phase I (Placebo) Phase II (treatment)
Pre treatment Post treatment Pre treatment Post treatment
Weight (kg) 33.60 34.35 34.55 35.10
Constipation (per week) 5 5 5 0
Serum biochemical factors
Urea (mg/dl) 36.00 31.0 34.00 30.00
Creatinine (mg/dl) 1.00 0.80 0.80 0.80
GOT(AST); (U/L) 26.00 31.00 22.00 22.00
GPT(ALT); (U/L) 20.00 31.00 14.00 15.00
Alkaline phosphatase; (U/L) 635.00 498.00 609.00 666.000
Bilirubin Total (mg/dl) 0.30 0.80 0.60 0.70
Bilirubin Direct (mg/dl) 0.10 0.10 0.30 0.10
LDH (U/L) 450.00 438.00 363.00 368.00
Na(mEq/L) 139.00 140.00 139.00 138.00
K(mEq/L) 4.10 4.10 4.30 4.30
IL-6(ng/ml) 14.32 15.02 14.22 13.12
Complete blood count (CBC)
WBC (109/L) 8.40 4.50 7.70 7.90
RBC (1012/L) 4.47 4.26 4.30 4.55
Hemoglobin (mmol/L) 12.90 12.20 12.70 13.60
Hematocrit (%) 37.80 37.30 38.60 40.20
Platelets (109/L) 333.00 300.00 386.00 341.00
RDW (%) 12.30 12.30 12.30 12.50
Neutrophils (%) 55.70 30.40 46.00 48.70
Lymphocytes (%) 36.50 62.90 48.70 43.60
SARA and SCAFI Score
The SARA score reduced dramatically (by 25% overall) following NALL intervention. The gait whose maximum score accounts for approximately one-fifth of the maximum total SARA score (8/40) was decreased significantly. The heel-to-shin slide, the only SARA item performed without visual control, was also marginally improved after therapy. Furthermore, there was a downward tendency on the 8MWT (8.71 to 7.93 s). Moreover, 9HPT revealed no improvement in fine motor dexterity (Table 2).Table 2 The effect of N-acetyl-L-leucine on ataxia moving symptoms in a girl with multiple sulfatase deficiency
Variable/Score Phase I (Placebo) Phase II (treatment)
Pre treatment Post treatment Pre treatment Post treatment
Scale for the assessment and rating of ataxia (SARA)
Gait 2 3 3 1
Stance 3 3 3 3
Sitting 2 1 2 2
Speech disturbance 2 2 3 2
Finger chase 2 1 1 1
Nose-finger test 3 2 2 2
Fast alternating hand movements 3 2 3 2
Heel-shin slide 3 3 3 2
Total SARA score 20 17 20 15
SCAFI
8MWT (Second) 8.50 9.11 8.71 7.93
9HPT Unable to do due to tremor Unable to do due to tremor Unable to do due to tremor Unable to do due to tremor
Child Self-report and Parent Proxy Report of Quality of Life
Our patient’s Physical Health score in Child self-report was significantly higher than before treatment. The administration of NALL boosted both emotional and social functioning modestly. During the trial, there were no discernible changes in school functioning or psychosocial health. Besides, after therapy, the quality of life index improved (Table 3).Table 3 The effects of N-acetyl-L-Leucine on quality of life according to Child self-report in a girl with multiple sulfatase deficiency
Phase I (Placebo) Phase II (treatment)
Child self-report Pre treatment Post treatment Pre treatment Post treatment
Physical Health 71.87 87.50 71.87 90.62
Emotional Functioning 85.00 90.00 80.00 90.00
Social Functioning 45.00 45.00 45.00 50.00
School Functioning 100.00 100.00 100.00 100.00
Total Psychosocial Health 68.33 78.33 75.00 80.00
Quality of life index 75.47 80.62 74.21 82.65
In Parent proxy report, the Physical Health score and emotional functioning of our patient were significantly higher than before treatment. Moreover, the quality of life index was improved after therapy (Table 4).Table 4 The effects of N-acetyl-L-Leucine on quality of life according to Parent proxy-report in a girl with multiple sulfatase deficiency
Phase I (Placebo) Phase II (treatment)
Parent proxy-report Pre treatment Post treatment Pre treatment Post treatment
Physical Health 75.00 87.50 71.87 93.75
Emotional Functioning 80.00 85.00 80.00 95.00
Social Functioning 90.000 90.00 90.00 90.00
School Functioning 100.00 100.00 100.00 100.00
Total Psychosocial Health 83.33 85.00 90.00 95.00
Quality of life index 86.25 90.62 85.47 94.68
Dietary Intake Status
The results for energy and macronutrient intake are displayed in Table 5. Total energy intake with NALL treatment was increased through the period. In the beginning phase, the total energy intake was 784.7 kcal/d, at the end of phase 2, the total energy intake increased by 1471 kcal/d.Table 5 The energy and macronutrient intake in a patient with multiple sulfatase deficiency
Variables Phase I (Placebo) Phase II (treatment)
Pre treatment Post treatment Pre treatment Post treatment
Macronutrients
Carbohydrate (g) 49.22 378.2 209 230.8
Dietary Fiber (g) 6.79 22.53 37.36 12.55
Total sugar (g) 11.06 44.93 79.87 84.37
Protein (g) 33.79 46.76 82.26 57.71
Fat (g) 54.11 15.38 101.6 38.35
SFA (g) 5.98 3.48 16.29 7.73
MUFA (g) 11.65 6.50 50.97 20.77
PUFA (g) 33.68 1.92 28.53 3.86
Trans (g) 0.00 0.00 0.00 0.00
Cholesterol (mg) 37.10 253 52.82 94.68
Energy (kcal) 784.7 1811 1984 1471
Micronutrients
Ca (mg) 102.2 283.9 351.4 282.3
Mg (mg) 150.4 307.6 763.8 133.7
P (mg) 1343 760.7 1899 459.6
Fe (mg) 5.53 8.91 23.38 8.54
Copper (mg) 1.97 2.49 3.02 0.70
Zinc (mg) 5.93 5.45 10.31 3.13
Manganese (mg) 4.59 4.28 7.57 5.75
Se (mg) 0.07 0.026 0.023 0.03
Iodine (µg) - - - 0.00
Carotene (µg) 0 9.11 62.09 0.00
Vit D (µg) 0 0 0 0.00
Vit E (mg) 0 0.90 1.72 2.47
Vit C (mg) 1.64 217.9 321.2 190.5
B1 (mg) 0.40 1.86 1.64 1.46
B2 (mg) 0.46 0.84 0.96 0.66
B3 (mg) 7.95 23.9 15.11 22.06
B5 (mg) 8.36 8.16 3.68 3.36
B6 (mg) 0.82 4.02 0.90 1.19
B9 (µg) 247.2 183.4 381.3 48.22
B12 (µg) 3.742 0.854 0.146 0.92
Discussion
To the best of our knowledge, the present study is the first to investigate the effects of NALL on MSD. Our results showed that taking NALL over 4 weeks did not have any side effect in a subject with MSD. In response to treatment with NALL, the cerebellar function, as assessed by SARA and SCAFI improved, especially in gait domain that was correlated with the reduction of the inflammatory parameter IL-6. However, at baseline there were no significant differences between the two groups (placebo/ treatment) with respect to IL-6. Besides, the quality of life was improved by taking NALL and total energy intake through the study period.
NALL is the L-enantiomer of N-acetyl-DL-leucine (NADLL), a modified amino acid available in France since 1957 as a racemate under the trade name of Tanganil®, indicated for the treatment of acute vertigo [11]. The mechanism of action of NADLL for dizziness has not been fully determined. It may directly affect the neurons in the vestibular nuclei [11]. Previous studies have reported that the L-enantiomer is the pharmacologically active enantiomer of NADLL [12, 13]. NALL has not yet been approved for any indication in any jurisdiction.
Another type of neurodegenerative LSD is GM2 gangliosidosis, which is a rare autosomal recessive genetic disorder that includes two disorders (Tay–Sachs and Sandhoff disease). These disorders result in the progressive deterioration of nerve cells as well as an inherited deficiency in the production of hexosaminidases A, B, and AB [14].
In 2020, Kaya et al. explored the efficacy of NADLL at a dose of 0.1 g/kg/day in a mouse model of Sandhoff disease. It was reported that NADLL significantly extended the lifespan, improved motor function, and decreased glycosphingolipid (GSL) storage in the forebrain and cerebellum. Furthermore, NADLL normalized glucose and glutamate metabolism, increased autophagy, reactive oxygen species (ROS) scavenging, and superoxide dismutase-1 (SOD1) expression (15).
In 2021, Martakis et al. evaluated the effects of NALL on 30 subjects aged > 6 years old with a confirmed genetic diagnosis of GM2 gangliosidosis. The patients were recruited from 4 countries including Germany, the UK, Spain and the USA. Their results showed that NALL intervention over 42 days was safe and well tolerated and could improve the symptoms, functioning, and quality of life in patients with GM2 gangliosidosis [16].
Bremova-Ertl et al. have investigated the safety and efficacy of NALL in 33 subjects with Niemann–Pick disease type C (NPC) aged 7–64 years in an open-label, rater-blinded Phase II study. NALL was safe and well tolerated without any serious adverse events. NALL improved neurological symptoms, functioning, and quality of life over 6 weeks [17]. Moreover, there is a Phase III crossover placebo-controlled clinical trial running right now in 53 patients (aged ≥ 4 years) with a confirmed genetic diagnosis of Niemann-Pick Disease Type C (NPC) in the USA (NCT number NCT05163288) (https://clinicaltrials.gov/ct2/show/NCT05163288?cond=Niemann-Pick+Disease%2C+Type+C&draw=2&rank=9).
In an in vitro study, Vibert et al. showed in guinea-pig whole brain that NADLL can specifically decrease vestibular-related neural asymmetries that cause acute vertigo crises. NADLL inhibits the abnormal depolarization of neurons on the hyperactive side without changing other normally functioning brain structures. However, its underlying molecular mechanism of action is still unknown and needs to be identified [11]. Previous studies have shown that aminopyridines can increase gait variability mostly during fast walking [18, 19]. On the other hand, NADLL is effective in decreasing the gait variability during slow walking. Schniepp et al. assessed the effects of NADLL (5 g/day) over at least 4 weeks on walking stability in patients with cerebellar ataxia. Treatment with NADLL significantly improved the SARA scores and coefficient of variation of stride time in the patients [19].
The effects of NADLL (dose of 3–5 g/day) in 6 patients with AT least over 4 weeks have been reported by Brueggemann et al. in 2022. They showed that NADLL can improve ataxia and ocular stability in these patients [20]. Likewise, a recent case study suggested the beneficial effects of NADLL supplementation (4 g/day for 16 weeks) in improving ataxia and quality of life in a 9.7-year-old girl with AT [21].
The findings from our study are consistent with those of previous investigations that reported the safety of NALL. The strength of the current study is its crossover design, although it was conducted only in one patient. Another strength is that this study is a placebo-controlled trial. Hence, it is necessary to conduct future proof-of-concept randomized controlled trials based on the results of this case study.
Conclusion
NALL intervention at a dose of 3 g/day over 4 weeks was safe and well tolerated in a young girl with MSD. The results showed that the ataxia symptoms and quality of life measures can be improved. Moreover, the serum IL-6 concentration showed a downward trend that may be improved by increasing the study period.
Author contribution
Conceptualization: MS, AS Investigation: MS, MH, TJ, PS, MN Methodology: MS, AS Analysis: SA, TJ Writing-original draft: MS Writing-review and editing: MH, TJ, PS, MN, SA, AS.
Data availability
Data are available upon request.
Declarations
Ethics approval
The study protocol has been approved by the Ethics Committee of Mashhad University of Medical Sciences (ID: IR.MUMS.MEDICAL.REC.1401.127), Mashhad, Iran.
Competing interests
None.
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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References
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2. Thomas D, Lars S, Andre FM, et al. Molecular basis of multiple sulfatase deficiency, mucolipidosis II/III and Niemann-Pick C1 disease-Lysosomal storage disorders caused by defects of non-lysosomal proteins. Biochim Biophys Acta Mol Cell Res. 2009;1793(4):710–25.
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6. Dierks T Schmidt B Borissenko LV Peng J Preusser A Mariappan M von Figura K Multiple sulfatase deficiency is caused by mutations in the gene encoding the human Cα-formylglycine generating enzyme Cell 2003 113 435 444 10.1016/S0092-8674(03)00347-7 12757705
7. Parini R, Andria G. Lysosomal storage diseases. John Libbey Eurotext; 2010 Jun 1.
8. Cosma MP Pepe S Parenti G Settembre C Annunziata I Wade-Martins R Di Domenico C Di Natale P Mankad A Cox B Molecular and functional analysis of SUMF1 mutations in multiple sulfatase deficiency Hum Mutat 2004 23 576 581 10.1002/humu.20040 15146462
9. Sarkar C, Hegdekar N, Lipinski MM. N-acetyl-L-leucine treatment attenuates neuronal cell death and suppresses neuroinflammation after traumatic brain injury in mice. bioRxiv. 2019. p. 759894. 10.1101/759894.
10. Azar M, Sarkisian E. Food composition table of Iran. Tehran: National Nutrition and Food Research Institute, Shaheed Beheshti University Press. 1980. p. 65.
11. Vibert N Vidal PP In vitro effects of acetyl-DL-leucine (tanganil) on central vestibular neurons and vestibulo-ocular networks of the guinea-pig Eur J Neurosci 2001 13 735 48 10.1046/j.0953-816x.2000.01447.x 11207808
12. Neuzil E Ravaine S Cousse H La N-ace ´tyl-DL-leucine, me ´dicament symptomatique de vertigineux. Bull Soc Pharm Bordx Bull Soc Pharm Bordx 2002 141 15 38
13. Churchill GC Strupp M Galione A Platt FM Unexpected differences in the pharmacokinetics of N-acetyl-DL-leucine enantiomers after oral dosing and their clinical relevance PLoS ONE 2020 15 2 e0229585 10.1371/journal.pone.0229585 32108176
14. Karimzadeh P Jafari N Nejad Biglari H GM2-Gangliosidosis (Sandhoff and Tay Sachs disease): diagnosis and neuroimaging findings (an Iranian pediatric case series) Iran J Child Neurol 2014 3 55 60
15. Kaya E Smith DA Smith C Boland B Strupp M Platt FM Beneficial effects of acetyl-DL-leucine (ADLL) in a mouse model of Sandhoff disease J Clin Med 2020 9 4 1050 10.3390/jcm9041050 32276303
16. Martakis K, Claassen J, Gascon-Bayarri J, Goldschagg N, Hahn A, Hassan A, Hennig A, Jones SA, Lau H, Perlman S, Sharma R. N-acetyl-L-leucine improves symptoms and functioning in GM2 Gangliosidosis (Tay-Sachs & Sandhoff). medRxiv. 2021. 10.1101/2021.09.24.21264020.
17. Bremova-Ertl T Claassen J Foltan T Gascon-Bayarri J Gissen P Hahn A Hassan A Hennig A Jones SA Kolnikova M Martakis K Efficacy and safety of N-acetyl-l-leucine in Niemann-Pick disease type C J Neurol 2022 269 3 1651 1662 10.1007/s00415-021-10717-0 34387740
18. Laumen A, Schneider S, Bremova-Ertl T, Kraus L, Feil K, Strupp M. Rates of responsiveness of acetyl-DL-leucine treatment for ataxia symptoms. Eur J Neurol. 2019. p. 26.
19. Schniepp R Strupp M Wuehr M Jahn K Dieterich M Brandt T Feil K Acetyl-DL-leucine improves gait variability in patients with cerebellar ataxia-a case series Cerebellum & ataxias 2016 3 1 1 4 10.1186/s40673-016-0046-2 26770813
20. Brueggemann A Bicvic A Goeldlin M Kalla R Kerkeni H Mantokoudis G Abegg M Kolníková M Mohaupt M Bremova-Ertl T Effects of acetyl-DL-leucine on ataxia and downbeat-nystagmus in six patients with ataxia telangiectasia J Child Neurol 2022 37 1 20 27 10.1177/08830738211028394 34620022
21. Saberi-Karimian M, Beyraghi-Tousi M, Mirzadeh M, Gumpricht E, Sahebkar A. The Effect of N-Acetyl-DL-Leucine on Neurological Symptoms in a Patient with Ataxia-Telangiectasia: a Case Study. Cerebellum. 2022. 10.1007/s12311-022-01371-x.
| 36482027 | PMC9735006 | NO-CC CODE | 2022-12-14 23:28:32 | no | Cerebellum. 2022 Dec 9;:1-7 | utf-8 | Cerebellum | 2,022 | 10.1007/s12311-022-01504-2 | oa_other |
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Nat Biotechnol
Nat Biotechnol
Nature Biotechnology
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Feature
Biopharmaceutical benchmarks 2022
Walsh Gary [email protected]
1
Walsh Eithne [email protected]
2
1 grid.10049.3c 0000 0004 1936 9692 The Industrial Biochemistry Program at the Department of Chemical Sciences and Bernal Institute University of Limerick, Limerick, Ireland
2 County Clare, Ireland
5 12 2022
2022
40 12 17221760
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This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Monoclonal antibodies as a group continue to lead biopharmaceuticals in numbers of approvals and sales, although COVID-19 vaccines shot to the top of the list of highest-grossing individual products.
issue-copyright-statement© The Author(s), under exclusive licence to Springer Nature America, Inc. 2022
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pmcThe past few years will forever be remembered as the years of a pandemic, the likes of which had not been seen for a century. And biopharmaceuticals took a starring role, with both COVID-19 vaccines and therapeutics dominating the news for the speed with which they were developed and their impact on global health. Nonetheless, regulatory agencies in both the United States and EU maintained the fast pace of prior years in moving products through their pipelines. This article is the latest survey of biopharmaceutical approvals, which we conduct every four years. The current survey period (January 2018–June 2022) witnessed the approval of 197 biopharmaceutical products (see Box 1 for definition) in the United States and/or EU, when counted by product trade name. Some products contain identical active ingredients or are sold under different trade names in the two regions; taking this into account, 180 distinct biopharmaceutical active ingredients entered the market.
Box 1 Biopharmaceuticals defined
Biopharmaceuticals (Table 1) are defined here as recombinant proteins, including recombinant antibodies, and nucleic acid- and genetically engineered cell-based products. They are listed in Table 1 consecutively from the most recent approval in each class, with registrations since 2018 indicated with boldface and withdrawals and discontinuations with italics. Eight categories are shown: recombinant clotting factors; recombinant thrombolytics, anticoagulants and other blood-related products; recombinant hormones; recombinant growth factors; recombinant interferons, interleukins and tumor necrosis factor; vaccines; monoclonal-antibody-based products; and other recombinant products. Where more than one drug in the same category was approved in a single year, they are listed alphabetically by trade name. In the case of several products that have been approved for multiple indications, only the first indication is listed here. Some product entries describe the product as being the same as another listed product. In such instances differences exist in terms of the approved indication range or the company holding the marketing authorizations, usually as a result of commercial agreements. Included are (COVID-19) therapeutics authorized under emergency procedures (Emergency Use Authorization in the United States and Conditional Marketing Authorisation in EU).
These new approvals bring the cumulative number of individual biopharmaceutical products (by trade name) licensed in these regions to 541, containing 435 distinct active biopharmaceutical ingredients. However, over the years, 98 products have been withdrawn from the market subsequent to approval in one or both regions, almost always for commercial reasons. Taking withdrawals into account, the number of individual biopharmaceutical products with current active licenses is estimated to be 443 (Table 1).Table 1 Biopharmaceuticals approved in the United States and European Union through end of June 2022
Product Company (location) Therapeutic indication Date approved
Recombinant clotting factors
Factor VIII
Esperoct (turoctocog alfa pegol), rh coagulation factor VIII, produced in a CHO cell line. PEGylated form of NovoEight (see later entry). Novo Nordisk (Bagsvaerd, Denmark)
Novo Nordisk (Plainsboro, NJ, USA)
Hemophilia A 2019 (EU & US)
Adynovi (rurioctocog alfa pegol), extended-half-life PEGylated form of full-length r factor VIII product Advate (see below). Same product as Adynovate (see below). Baxalta Innovations (Vienna) Hemophilia A 2018 (EU)
Jivi (damoctocog alfa pegol (EU), antihemophilic factor (recombinant), PEGylated-aucl (US)), PEGylated B-domain-deleted rh coagulation factor VIII, produced in BHK cells. Bayer (Leverkusen, Germany)
Bayer HealthCare (Whippany, NJ, USA)
Hemophilia A 2018 (EU & US)
Afstyla (lonoctocog alfa), B-domain-truncated rh coagulation factor VIII, produced in CHO cells. CSL Behring (Marburg, Germany, & Kankakee, IL, USA) Hemophilia A 2017 (EU) 2016 (US)
Vihuma (simoctocog alfa), rh B-domain-deleted factor VIII, produced in HEK cells. Same product as Nuwiq (see below). Octapharma (Stockholm) Hemophilia A 2017 (EU)
Iblias (octocog alfa), rh coagulation factor VIII, produced in BHK cells using the same expression construct as Bayer’s Kogenate and Helixate. Same product as Kovaltry (see below). Bayer Pharma (Berlin) Hemophilia A 2016 (EU)
Withdrawn 2020
Kovaltry (octocog alfa), rh coagulation factor VIII, produced in BHK cells using the same expression construct as Bayer’s Kogenate and Helixate. Same product as Iblias (see above). Bayer Pharma (Leverkusen, Germany)
Bayer HealthCare (Whippany, NJ, USA)
Hemophilia A 2016 (EU & US)
Vonvendi (von Willebrand factor (recombinant)), produced in CHO cells. Baxalta (Westlake Village, CA, USA) von Willebrand disease 2015 (US)
Nuwiq (simoctocog alfa), B-domain-deleted rh factor VIII, produced in HEK cells. Same product as Vihuma (see above). Octapharma USA (Hoboken, NJ, USA)
Octapharma (Stockholm)
Hemophilia A 2015 (US)
2014 (EU)
Obizur (susoctocog alfa), r B-domain-deleted porcine factor VIII, produced in BHK cells. Baxalta Innovations (Vienna)
Baxter Healthcare (Westlake Village, CA, USA)
Acquired hemophilia due to development of autoantibodies against factor VIII 2015 (EU)
2014 (US)
Adynovate (recombinant, PEGylated antihemophilic factor), extended-half-life PEGylated form of full-length r factor VIII product Advate (see below). Same product as Adynovi (see above). Baxalta Hemophilia A 2015 (US)
Elocta (efmoroctocog alfa; EU), Eloctate (antihemophilic factor recombinant, Fc fusion protein; US), rh coagulation factor VIII–Fc fusion protein comprising B-domain-deleted human factor VIII covalently linked to the Fc domain of a human IgG, produced in HEK cells. Swedish Orphan Biovitrum (Stockholm)
Biogen Idec (Cambridge, MA, USA)
Hemophilia A 2015 (EU)
2014 (US)
NovoEight (turoctocog alfa), rh factor VIII analog that, when activated, is structurally comparable to endogenous human factor VIIIa, produced in CHO cells. Novo Nordisk (Bagsvaerd, Denmark, & Plainsboro, NJ, USA) Hemophilia A 2013 (EU & US)
Xyntha (antihemophilic factor), rh coagulation factor VIII, produced in CHO cells. Pfizer/Wyeth (Philadelphia) Hemophilia A 2008 (US)
Advate (octocog alfa), rh factor VIII, produced in CHO cells. Takeda (Vienna)
Baxter Healthcare
(Westlake Village, CA, USA)
Hemophilia A 2004 (EU)
2003 (US)
Helixate NexGen (octocog alfa), rh factor VIII, produced in BHK cells. Bayer (Berlin) Hemophilia A 2000 (EU)
Withdrawn 2019
ReFacto (moroctocog alfa), B-domain-deleted rh factor VIII, produced in CHO cells. Pfizer (Brussels)
Genetics Institute (Cambridge, MA, USA)
Hemophilia A 2000 (US)
1999 (EU)
Kogenate, Helixate (antihemophilic factor), rh factor VIII, produced in BHK cells. Sold as Helixate by Aventis Behring through a license agreement. Bayer (Leverkusen, Germany, & Berkeley, CA, USA) Hemophilia A 2000 (EU)
1993 (US)
Bioclate (antihemophilic factor), rh factor VIII, produced in CHO cells. Aventis Behring (King of Prussia, PA, USA) Hemophilia A 1993 (US)
Recombinate (antihemophilic factor), rh factor VIII, produced in CHO cells. Baxter Healthcare (Westlake Village, CA, USA) Hemophilia A 1992 (US)
Other blood factors
Sevenfact (coagulation factor VIIa (recombinant)-jncw; rh activated factor VII, produced in milk of transgenic rabbits. HEMA Biologics (Louisville, KY, USA) Hemophilia A or B 2020 (US)
Ondexxya (andexanet alfa (EU), Andexxa (US)), engineered rh factor Xa lacking the coagulation activity of native FXa but retaining binding ability to FXa inhibitors, produced in CHO cells. AstraZeneca (Sodertalje, Sweden)
Portola Pharmaceuticals (South San Francisco, CA, USA)
Alexion Pharmaceuticals (Boston)
Stopping life-threatening or uncontrolled bleeding in adults taking the anticoagulant medicines apixaban or rivaroxaban 2019 (EU)
2018 (US)
Veyvondi (vonicog alfa), rh von Willebrand factor, produced in CHO cells. Baxalta Innovations (Vienna) von Willebrand disease 2018 (EU)
Rebinyn (rh coagulation factor IX; US), Refixia (nonacog beta pegol; EU), rh coagulation factor IX, produced in CHO cells and PEGylated. Novo Nordisk (Plainsboro, NJ, USA & Bagsvaerd, Denmark) Hemophilia B 2017 (EU & US)
Alprolix (eftrenonacog alfa), rh coagulation factor IX fused to a human IgG1 Fc domain, produced in HEK cells. Swedish Orphan Biovitrum (Stockholm)
Bioverativ Therapeutics (Waltham, MA, USA)
Hemophilia B 2016 (EU)
2014 (US)
Idelvion (albutrepenonacog alfa), rh factor IX–albumin fusion protein, produced in CHO cells. CSL Behring Hemophilia B 2016 (EU & US)
Ixinity (coagulation factor IX, recombinant)), rh coagulation factor IX, produced in CHO cells. Aptevo BioTherapeutics (Berwyn, PA, USA) Hemophilia B 2015 (US)
Rixubis (nonacog gamma), rh factor IX, produced in CHO cells. Baxalta Innovations (Vienna)
Baxter Healthcare (Lexington, MA, USA)
Hemophilia B 2014 (EU)
2013 (US)
Tretten (US), Novothirteen (EU) (catridecog), rh factor XIII A-subunit, produced in S. cerevisiae. Novo Nordisk Congenital factor XIII A-subunit deficiency 2013 (US)
2012 (EU)
Recothrom (thrombin), rh factor Iia, produced in CHO cells. Baxter Healthcare (Deerfield, IL, USA) Control of minor bleeding during surgery 2008 (US)
NovoSeven (eptacog alfa, activated), rh factor VIIa, produced in BHK cells. Novo Nordisk Some forms of hemophilia 1996 (EU)
1999 (US)
Benefix (nonacog alfa), rh factor IX, produced in CHO cells. Pfizer/Wyeth Hemophilia B 1997 (EU & US)
Recombinant thrombolytics, anticoagulants and other blood-related products
Tissue plasminogen activator (tPA)
Metalyse (tenecteplase), modified rh tPA, produced in CHO cells. Boehringer Ingelheim (Ingelheim, Germany) Myocardial infarction 2001 (EU)
Withdrawn 2005
TNKase (tenecteplase), modified rh tPA, produced in CHO cells. Roche/Genentech (South San Francisco, CA, USA) Myocardial infarction 2000 (US)
Ecokinase (reteplase), r tPA, produced in E. coli; differs from human tPA in the deletion of 3 of its 5 domains. Roche (Welwyn Garden City, UK) Acute myocardial infarction 1996 (EU)
Withdrawn 2000
Rapilysin (reteplase), r tPA (see Ecokinase, above). Actavis Group PTC (Hafnarfjordur, Iceland), Roche Acute myocardial infarction 1996 (EU)
Retavase (reteplase), r tPA (see Ecokinase, above). Chiesi USA (Cary, NC, USA) Acute myocardial infarction 1996 (US)
Activase (alteplase), rh tPA, produced in CHO cells. Roche/Genentech Acute myocardial infarction 1987 (US)
Hirudin
Refludan (lepirudin), r hirudin, produced in S. cerevisiae. Bayer HealthCare (Leverkusen, Germany) Anticoagulation therapy for heparin-associated thrombocytopenia 1997 (EU)
1998 (US)
Withdrawn 2012
Revasc (desirudin), r hirudin, produced in S. cerevisiae. Canyon Pharmaceuticals (London) Prevention of venous thrombosis 1997 (EU)
Withdrawn 2014
Other
Ruconest (conestat alfa), rh C1 esterase inhibitor, produced in the milk of transgenic rabbits. Pharming Healthcare (Warren, NJ, USA)
Pharming Group (Leiden, the Netherlands)
Acute angioedema 2014 (US)
2010 (EU)
Jetrea (ocriplasmin), r truncated form of human plasmin, produced in Pichia pastoris. Inceptua (Bromma, Sweden)
ThromboGenics (Iselin, NJ, USA)
Symptomatic vitreomacular adhesion, vitreomacular traction 2013 (EU)
2012 (US)
Atryn (rh antithrombin), produced in milk of transgenic goats. Laboratoire français du fractionnement et des biotechnologies (Les Ulis, France)
rEVO Biologics (Framingham, MA, USA)
Hereditary antithrombin deficiency 2009 (US)
2006 (EU)
Withdrawn 2018 (EU)
Kalbitor (ecallantide), plasma kallikrein inhibitor, produced in P. pastoris. Dyax (Cambridge, MA, USA) Hereditary angioedema 2009 (US
Xigris (drotrecogin alfa), rh activated protein C, produced in a human cell line. Eli Lilly (Houten, the Netherlands) Severe sepsis 2001 (US)
2002 (EU)
Withdrawn 2012
Recombinant hormones
Insulins
Inpremzia (rh insulin), produced in P. pastoris. Biosimilar to Actrapid. Baxter Holding (Utrecht, the Netherlands) Diabetes mellitus 2022 (EU)
Truvelog Mix 30 (insulin aspart, produced in E. coli. Biosimilar to NovoMix. Sanofi-Aventis (Paris) Diabetes mellitus 2022 (EU)
Kirsty (previously Kixelle) insulin aspart; fast-acting insulin analog, produced in P. pastoris. Biosimilar to NovoRapid. Mylan Ireland (Dublin, Ireland) Diabetes mellitus 2021 (EU)
Rezvoglar (insulin glargine-aglr, long-acting human insulin analog, biosimilar to Lantus, produced in E. coli. Eli Lilly Diabetes mellitus 2021 (US)
Semglee (insulin glargine (EU), insulin glargine-yfgn (US)); r insulin glargine, produced in P. pastoris. Biosimilar to Lantus. Mylan (Saint-Priest, France)
Mylan Pharmaceuticals (Morgantown, WV, USA)
Diabetes mellitus 2021 (US)
2018 (EU)
Insulin aspart Sanofi (insulin aspart, r fast-acting insulin analog, produced in E. coli. Biosimilar to NovoRapid. Sanofi-Aventis (Paris) Diabetes mellitus 2020 (EU)
Lyumjev (previously Liumjev; insulin lispro (EU), insulin lispro-aabc (US)); rh rapid-acting insulin analog, produced in E. coli. Same active ingredient as in Humalog, but new formulation. Eli Lilly Nederland (Utrecht, the Netherlands) Diabetes mellitus 2020 (EU & US)
Myxredlin (rh insulin, produced in P. pastoris). Baxter Healthcare (Deerfield, IL, USA) Diabetes mellitus 2019 (US)
Admelog (insulin lispro injection), rapid-acting human insulin analog, produced in E. coli. Sanofi (Bridgewater, NJ, USA) Diabetes mellitus 2017 (US)
Fiasp (insulin aspart injection), rapid-acting insulin analog, produced in S. cerevisiae. Novo Nordisk Diabetes mellitus 2017 (US & EU)
Insulin lispro Sanofi, produced in E. coli. Biosimilar to Humalog. Sanofi-Aventis (Paris) Diabetes mellitus 2017 (EU)
Lusduna (insulin glargine), engineered insulin, produced in E. coli. Biosimilar to Lantus. Merck Sharp & Dohme (Hoddesdon, UK) Diabetes mellitus 2017 (EU)
Withdrawn 2018 (EU)
2017 (US, tentative)
Withdrawn 2018 (US)
Suliqua (EU), Soliqua (US) (insulin glargine/lixisenatide), combination of long-acting insulin glargine, produced in E. coli, and a synthetically produced human GLP-1 analog. Sanofi-Aventis (Paris)
Sanofi (Bridgewater, NJ, USA)
Diabetes mellitus type 2 2017 (EU)
2016 (US)
Xultophy (insulin degludec/liraglutide), a combination of 2 previously approved products, Victoza and Tresiba. Novo Nordisk Diabetes mellitus type 2 2016 (US)
2014 (EU)
Abasaglar (previously Abasria; EU), Basaglar (US) (insulin glargine), produced in E. coli. Biosimilar (in EU) to Lantus. Eli Lilly (Utrecht, the Netherlands)
Eli Lilly (Indianapolis, IN USA)
Diabetes mellitus 2015 (US)
2014 (EU)
Ryzodeg 70/30 (US), Ryzodeg (EU) (insulin degludec/insulin aspart), combination of two engineered insulins, produced in S. cerevisiae. Novo Nordisk Diabetes mellitus type 1 and 2 2015 (US)
2013 (EU)
Toujeo (insulin glargine, long-acting rh insulin analog), produced in E. coli (see also Lantus, below). Previously Optisulin in EU. Sanofi-Aventis Deutschland (Frankfurt)
Sanofi (Bridgewater, NJ, USA)
Diabetes mellitus 2000 (EU)
2015 (US)
Tresiba (insulin degludec), engineered long-acting human insulin analog, produced in S. cerevisiae (see also Ryzodeg, above). Novo Nordisk Diabetes mellitus type 1 and 2 2015 (US)
2013 (EU)
Afrezza (rh insulin), produced in E. coli). MannKind (Danbury, CT, USA) Diabetes mellitus 2014 (US)
Novolog mix (insulin aspart mix), 50:50 mixture of engineered rh insulins, produced in S. cerevisiae in soluble and protamine suspension forms. Novo Nordisk Diabetes mellitus 2008 (US)
Insulin Human Winthrop (rh insulin), produced in E. coli. Sanofi (Frankfurt) Diabetes mellitus 2007 (EU)
Withdrawn 2018
Exubera (inhalable rh insulin), produced in E. coli. Pfizer (Sandwich, UK) Diabetes mellitus 2006 (EU & US)
Withdrawn 2008
Levemir (insulin detemir), long-acting rh insulin, produced in S. cerevisiae. Novo Nordisk Diabetes mellitus 2005 (US)
2004 (EU)
Apidra (insulin glulisine), rapid-acting insulin analog, produced in E. coli. Sanofi (Frankfurt) Diabetes mellitus 2004 (EU & US)
Actrapid, Velosulin, Monotard, Insulatard, Protaphane, Mixtard, Actraphane, Ultratard, rh insulin formulated as short-, intermediate- or long-acting products. Novo Nordisk Diabetes mellitus 2002 (EU)
Monotard and Ultratard withdrawn 2006
Velosulin withdrawn 2009
Novolog (insulin aspart), short-acting rh insulin analog, produced in S. cerevisiae. Novo Nordisk Diabetes mellitus 2001 (US)
Novolog mix 70/30 (contains insulin aspart, a short-acting rh insulin analog, as one ingredient). Novo Nordisk Diabetes mellitus 2001 (US)
Novomix 30 (contains a mixture of insulin aspart, a short-acting rh insulin analog, produced in S. cerevisiae, in both soluble and crystalline forms). Novo Nordisk Diabetes mellitus 2000 (EU)
Lantus (insulin glargine), long-acting rh insulin analog, produced in E. coli. Sanofi (Frankfurt) Diabetes mellitus 2000 (EU & US)
NovoRapid (insulin aspart), rh insulin analog), produced in S. cerevisiae. Novo Nordisk Diabetes mellitus 1999 (EU)
Liprolog (insulin lispro), insulin analog, produced in E. coli. Eli Lilly (Houten, the Netherlands) Diabetes mellitus 1997 (EU)
Withdrawn 2001
Insuman (rh insulin), produced in E. coli. Sanofi (Frankfurt) Diabetes mellitus 1997 (EU)
Humalog (insulin lispro), insulin analog, produced in E. coli. Eli Lilly (Houten, the Netherlands) Diabetes mellitus 1996 (EU & US)
Novolin (rh insulin), produced in S. cerevisiae. Novo Nordisk Diabetes mellitus 1991 (US)
Withdrawn 2010
Humulin (rh insulin), produced in E. coli. Eli Lilly (Indianapolis, IN, USA) Diabetes mellitus 1982 (US)
Human growth hormone
Lonapegsomatropin Ascendis Pharma (lonapegsomatropin), rhGH, produced in E. coli and PEGylated. Ascendis Pharma (Hellerup, Denmark) Growth hormone deficiency 2022 (EU)
Skytrofa (lonapegsomatropin-tcgd; r hGH, produced in E. coli and PEGylated. Same API as Lonapegsomatropin Ascendis Pharma. Ascendis Pharma Endocrinology Division Growth hormone deficiency 2021 (US)
Sogroya (somapacitan (EU, somapacitan-beco (US)), long acting r hGH with L101C substitution and an albumin-binding C-16 fatty acid derivative attached, produced in E. coli. Novo Nordisk Growth hormone deficiency 2021 (EU)
2020 (US)
Somatropin Biopartners (somatropin), r hGH, produced in S. cerevisiae. Biopartners (Reutlingen, Germany) Growth failure, growth hormone deficiency 2013 (EU)
Withdrawn 2017
Accretropin (somatropin), r hGH, produced in E. coli. Emergent Biosolutions (Rockville, MD, USA)
Cangene (Winnipeg, Canada)
Growth failure or short stature associated with Turner syndrome in children 2008 (US)
Valtropin (somatropin), r hGH, produced in S. cerevisiae. Biosimilar to Humatrope. Biopartners, LG Life Sciences (Republic of Korea & Reutlingen, Germany) Certain forms of growth disturbance in children and adults 2007 (US)
2006 (EU)
Withdrawn 2012 (EU), 2019 (US)
Omnitrope (somatropin), biosimilar to Genotropin (in EU) r hGH, produced in E. coli. Sandoz (Kundl, Austria)
Sandoz (Princeton, NJ, USA)
Certain forms of growth disturbance in children and adults 2006 (EU & US)
Somavert (pegvisomant), r hGH analog (antagonist), produced in E. coli and PEGylated. Pfizer Acromegaly 2003 (US)
2002 (EU)
Nutropin AQ (somatropin), r hGH, produced in E. coli. Different formulation of Nutropin (see below). Ipsen Pharma (Boulogne-Billancourt, France) Growth failure, Turner syndrome 2001 (EU)
1994 (US)
Withdrawn 2008 (EU)
Serostim (somatropin), r hGH, produced in mouse C127 cells. EMD Serono (Rockland, MA, USA) AIDS-associated catabolism and wasting 1996 (US)
Saizen (somatropin), r hGH, produced in mouse C127 cells. EMD Serono (Rockland, MA, USA) hGH deficiency in children 1996 (US)
Genotropin (somatropin), r hGH, produced in E. coli. Pfizer (New York) hGH deficiency in children 1995 (US)
Norditropin (somatropin), r hGH, produced in E. coli. Novo Nordisk Growth failure in children due to inadequate growth hormone secretion 1995 (US)
Tev-Tropin, Bio-tropin (somatropin), r hGH, produced in E. coli. Teva Pharmaceuticals (North Wales, PA, USA) hGH deficiency in children 1995 (US)
Nutropin (somatropin), r hGH, produced in E. coli. Roche/Genentech hGH deficiency in children 1994 (US)
Humatrope (somatropin), r hGH, produced in E. coli. Eli Lilly (Indianapolis) hGH deficiency in children 1987 (US)
Protropin (somatrem), r hGH differing from hGH by an extra N-terminal methionine, produced in E. coli. Genentech (South San Francisco, CA, USA) hGH deficiency in children 1985 (US)
Withdrawn 2004
Follicle-stimulating hormone
Rekovelle (follitropin delta), rh FSH, produced in PER.C6 cells Ferring Pharmaceuticals (Copenhagen) Anovulation 2016 (EU)
Bemfola (follitropin alfa), rh FSH, produced in CHO cells. Biosimilar to Gonal F. Gedeon Richter (Budapest) Anovulation (women), failure of spermatogenesis (men) 2014 (EU)
Ovaleap (follitropin alfa), rh FSH, produced in CHO cells. Biosimilar to Gonal F. Theramex Ireland (Dublin) Infertility, subfertility 2013 (EU)
Elonva (corifollitropin alfa), modified rh FSH with the C-terminal peptide of the β-subunit of hCG fused to the FSH β-chain, produced in CHO cells. N.V. Organon (Oss, the Netherlands) Controlled ovarian stimulation 2010 (EU)
Fertavid (follitropin beta), rh FSH, produced in CHO cells. Active substance same as in Puregon (see below). Merck Sharp & Dohme Infertility 2009 (EU)
Withdrawn 2020
Pergoveris (follitropin alfa/lutropin alfa) combination product containing rh FSH and rh luteinizing hormone, both produced in CHO cells. Merck (Amsterdam) Stimulation of follicular development in women with severe luteinizing hormone and FSH deficiency 2007 (EU)
Follistim (follitropin beta), rh FSH, produced in CHO cells. Merck (Whitehouse Station, NJ, USA) Infertility 1997 (US)
Puregon (follitropin beta), rh FSH, produced in CHO cells. N.V. Organon Anovulation and superovulation 1996 (EU)
Gonal F (follitropin alfa), rh FSH, produced in CHO cells. Merck Serono, EMD Serono (Rockland, MD, USA) Anovulation and superovulation 1997 (US)
1995 (EU)
Other hormones
Sondelbay (teriparatide), the active N-terminal fragment of human PTH, produced in E. coli. Biosimilar to Forsteo. Accord Healthcare (Barcelona, Spain) Osteoporosis 2022 (EU)
Wegovy (semaglutide), r glucagon-like peptide-1 (GLP-1) analog with a linker and a fatty acid side chain, produced in Saccharomyces cerevisiae and then chemically modified. Same active substance as in Ozempic. Novo Nordisk (Bagsvaerd, Denmark) Weight loss and weight control 2022 (EU)
Voxzogo (vosoritide), truncated (39-amino-acid) modified analog of the native human C-type natriuretic peptide, expressed in E. coli. BioMarin International (Cork, Ireland)
BioMarin Pharmaceutical (Novato, CA, USA)
Achondroplasia 2021 (EU & US)
Livogiva (teriparatide; r 1-34 N-terminal fragment of endogenous human PTH, produced in Pseudomonas fluorescens. Biosimilar to Forsteo. Theramex Ireland (Dublin) Osteoporosis 2020 (EU)
Qutavina (teriparatide; r 1-34 N-terminal fragment of endogenous human PTH, produced in P. fluorescens. Biosimilar to Forsteo. EuroGenerics (Amsterdam, the Netherlands) Osteoporosis 2020 (EU)
Withdrawn 2020
Rybelsus (semaglutide; long-acting hGLP 1 analog (receptor agonist), produced in S. cerevisiae and chemically modified via fatty acid attachment (acylation). Same active substance as Ozempic, but developed for oral use. Oral bioavailability improved via inclusion of a novel absorption-enhancer excipient (salcaprozate sodium (SNAC), a fatty acid derivative). Novo Nordisk Type 2 diabetes 2020 (EU)
2017 (US)
Myalepta (EU), Myalept (US) (metreleptin), rh leptin analog, produced in E. coli. Amryt Pharmaceuticals (Dublin)
Aegerion Pharmaceuticals (Cambridge, MA, USA)
Some forms of lipodystrophy 2018 (EU)
2014 (US)
Ozempic (semaglutide), human GLP-1 receptor agonist, produced in S. cerevisiae and covalently modified by attachment of a C18 fatty acid. Novo Nordisk Diabetes mellitus type 2 2018 (EU)
2017 (US)
Movymia (teriparatide), rh PTH fragment, produced in E. coli. Biosimilar to Fortseo. Same product as Terrosa (see below). Stada Arzneimittel (Bad Vilbel, Germany) Osteoporosis 2017 (EU)
Natpar (parathyroid hormone), rh PTH, full length, produced in E. coli. Same product as Preotact (see below). Takeda Pharmaceuticals (Dublin) Hypoparathyroidism 2017 (EU)
Terrosa (teriparatide), rh PTH fragment, produced in E. coli. Biosimilar to Fortseo. Same product as Movymia (see above). Gedeon Richter (Budapest) Osteoporosis 2017 (EU)
Natpara (parathyroid hormone), rh PTH, produced in E. coli. Shire-NPS Pharmaceuticals (Lexington, MA, USA) Hypocalcemia 2015 (US)
Saxenda (liraglutide), human GLP-1 analog, produced in S. cerevisiae and covalently modified by palmitic acid. Active substance same as in Victoza (see below). Novo Nordisk Obesity 2015 (EU)
Eperzan (EU), Tanzeum (US) (albiglutide), GLP-1 receptor agonist: two tandem copies of modified human GLP-1 fused to human albumin, produced in S. cerevisiae. GSK (Carrigaline, Ireland)
GSK (Research Triangle Park, NC, USA)
Diabetes mellitus type 2 2014 (EU & US)
Withdrawn 2018
Trulicity (dulaglutide), fusion protein consisting of a GLP-1 analog linked to a human IgG Fc domain, produced in a mammalian cell line. Eli Lilly (Utrecht, the Netherlands, & Indianapolis) Diabetes mellitus type 2 2014 (EU & US)
Gattex (US), Revestive (EU) (teduglutide), rh GLP-2 analog, produced in E. coli. Takeda (Dublin)
Shire (Lexington, MA, USA)
Short bowel syndrome 2012 (EU & US)
Victoza (liraglutide), GLP-1 analog with attached fatty acid, produced in S. cerevisiae. Novo Nordisk Diabetes mellitus type 2 2010 (US)
2009 (EU)
Preotact, rh PTH, produced in E. coli. NPS Pharma Osteoporosis 2006 (EU)
Withdrawn 2014
Fortical, r salmon calcitonin, produced in E. coli. Upsher-Smith Laboratories (Minneapolis, MN, USA)
Unigene Laboratories (Fairfield, NJ, USA)
Postmenopausal osteoporosis 2005 (US)
Luveris (lutropin alfa), rh luteinizing hormone, produced in CHO cells. Merck (Amsterdam) Some forms of infertility 2004 (US)
2000 (EU)
Withdrawn 2007 (US)
Forsteo (EU), Forteo (US) (teriparatide), r shortened human PTH, produced in E. coli. Eli Lilly (Utrecht, the Netherlands)
Lilly (Indianapolis)
Established osteoporosis in some postmenopausal women 2003 (EU)
1987 (US)
Natrecor (nesiritide), rh natriuretic peptide, produced in E. coli. Johnson & Johnson/Scios (Titusville, NJ, USA) Acutely decompensated congestive heart failure 2001 (US)
Ovitrelle (EU), Ovidrel (US) (choriogonadotropin alfa) rh chorionic gonadotropin, produced in CHO cells. Merck (Amsterdam)
EMD Serono (Rockville, MD, USA)
Selected assisted reproductive techniques 2001 (EU)
2000 (US)
Thyrogen (thyrotropin alfa), rh thyroid-stimulating hormone, produced in CHO cells. Genzyme (Amsterdam & Cambridge, MA, USA) Thyroid cancer (detection and treatment) 1998 (US)
2000 (EU)
Forcaltonin, r salmon calcitonin, produced in E. coli. Unigene UK (Bushey Heath, UK) Paget disease 1999 (EU)
Withdrawn 2008
Glucagen, rh glucagon, produced in S. cerevisiae. Novo Nordisk Hypoglycemia 1998 (US)
Glucagon (glucagon, recombinant), rh glucagon, produced in E. coli. Eli Lilly (Indianapolis) Hypoglycemia 1998 (US)
Bonsity. r PTH analog, expressed in P. fluorescens. Pfenex (San Diego, CA, USA) Osteoporosis 1987 (US)
Recombinant growth factors
Erythropoietin
Retacrit (epoetin zeta (EU), epoetin alfa-epbx (US)), rh EPO, produced in CHO cells. Biosimilar to Eprex and Erypo. Pfizer (Brussles, Belgium & Lake Forest, IL, USA) Anemia 2018 (US)
2007 (EU)
Biopoin (epoetin theta), rh EPO, produced in CHO cells. Teva (Ulm, Germany) Anemia 2009 (EU)
Eporatio (epoetin theta), rh EPO, produced in CHO cells. Ratiopharm (Ulm, Germany) Anemia 2009 (EU)
Abseamed (epoietin alfa), biosimilar to Eprex/Erypo, produced in CHO cells. Biosimilar to rh EPO. Medice Arzneimittel Pütter (Iserlon, Germany) Anemia associated with chronic renal failure 2007 (EU)
Binocrit (epoetin alfa), biosimilar to Eprex/Erypo, produced in CHO cells. Biosimilar to rh EPO. Sandoz (Kundl, Austria) Anemia associated with chronic renal failure 2007 (EU)
Epoetin alfa Hexal (epoietin alfa), biosimilar to Eprex/Erypo produced in CHO cells. Biosimilar to rh EPO. Hexal (Holzkirchen, Germany) Anemia associated with chronic renal failure 2007 (EU)
Mircera (methoxy polyethylene glycol-epoetin beta), rh EPO, produced in CHO cells and PEGylated. Roche (Grenzach-Wyhlen, Germany) Anemia associated with chronic kidney disease 2007 (EU & US)
Silapo (epoetin zeta), biosimilar toEprex/Erypo, produced in CHO cells. Biosimilar to rh EPO. Stada (Bad Vilbel, Germany) Anemia associated with chronic renal failure 2007 (EU)
Dynepo (epoetin delta), rh EPO, produced in a human cell line. Shire Pharmaceuticals (Hampshire, UK) Anemia 2002 (EU)
Withdrawn 2009
Aranesp (darbepoetin alfa), long-acting r EPO analog, produced in CHO cells (see Nespo, below) Amgen (Breda, the Netherlands)
Amgen (Thousand Oaks, CA, USA)
Anemia 2001 (EU & US)
Nespo (darbepoetin alfa), long-acting r EPO analog, produced in CHO cells (see Aranesp above) Dompé Biotec (Milan) Anemia 2001 (EU)
Withdrawn 2008
Neorecormon (epoietin beta), rh EPO, produced in CHO cells. Roche Anemia 1997 (EU)
Procrit (epoietin alfa), rh EPO, produced in a mammalian cell line. Janssen Biotech (Horsham, PA, USA) Anemia 1990 (US)
Epogen (epoietin alfa), rh EPO, produced in CHO cells. Amgen Anemia 1989 (US)
Colony-stimulating factors
Fylnetra (pegfilgrastim-pbbk; rh G-CSF, produced in E. coli and PEGylated. Biosimilar to Neulasta. Amneal Pharmaceuticals (Bridgewater, NJ, USA) Neutropenia 2022 (US)
Releuko (filgrastim-ayow; rh G-CSF, produced in E. coli. Biosimilar to Neupogen. Kashiv BioSciences (Piscataway, NJ, USA) Neutropenia 2022 (US)
Stimufend (pegfilgrastim), rh G-CSFr produced in E. coli. Biosimilar to Neulasta. Fresenius Kabi Deutschland (Höhe, Germany) Neutropenia 2022 (EU)
Nyvepria (pegfilgrastim (EU), pegfilgrastim-apgf (US)), rh G-CSF, expressed in E. coli and PEGylated. Biosimilar to Neulasta. Pfizer Europe MA EEIG (Brussels, Belgium)
Pfizer (New York).
Neutropenia 2020 (EU & US)
Cegfila (previously Pegfilgrastim Mundipharma; pegfilgrastim), rh G-CSF, produced in E. coli and PEGylated Biosimilar to Neulasta. Mundipharma (Dublin) Neutropenia 2019 (EU)
Grasustek (pegfilgrastim), rh-G-CSF, produced in E. coli and PEGylated. Biosimilar to Neulasta. Juta Pharma (Flensburg, Germany, USA) Neutropenia 2019 (EU)
Ziextenzo (pegfilgrastim (EU), pegfilgrastim-bmez (US)), rh G-CSF, produced in E. coli and PEGylated. Biosimilar to Neulasta. Sandoz (Kundl, Austria) Neutropenia 2019 (US)
2018 (EU)
Fulphila (pegfilgrastim-jmdb), rh G-CSF, produced in E. coli and PEGylated. Biosimilar to Neulasta. Mylan (Rockford, IL USA)
Mylan (Saint-Priest, France)
Neutropenia 2018 (US and EU)
Nivestym (filgrastim-aafi; US), Nivestim (filgrastim; EU), rh G-CSF, produced in E. coli. Biosimilar to Neupogen. Pfizer Neutropenia 2018 (US)
2010 (EU)
Pelgraz (pegfilgrastim), rh G-CSF, produced in E. coli and pEGylated. Biosimilar to Neulasta. Accord Healthcare (Barcelona, Spain) Neutropenia 2018 (EU)
Pelmeg (pegfilgrastim), rh G-CSF, produced in E. coli and PEGylated. Biosimilar to Neulasta. Cinfa Biotech (Olloki, Spain) Neutropenia 2018 (EU)
Udenyca (pegfilgrastim (EU), pegfilgrastim-cbqv (US)), rh G-CSF, produced in E. coli and PEGylated Biosimilar to Neulasta. ERA Consulting (Walsrode, Germany)
Coherus BioSciences (Redwood City, CA, USA)
Neutropenia 2018 (EU & US)
Withdrawn (EU)
Ristempa (pegfilgrastim), covalent conjugate of rh G-CSF, produced in E. coli and conjugated to 20-kDa PEG. Amgen (Breda, the Netherlands) Neutropenia 2015 (EU)
Withdrawn 2017
Zarxio (US), Zarzio (EU) (filgrastim-sndz), rh G-CSF, produced in E. coli. Sandoz (Princeton, NJ, USA, & Kundl, Austria) Neutropenia 2015 (US)
2009 (EU)
Accofil (filgrastim), G-CSF, produced in E. coli. Biosimilar to Neupogen. Same product as Grastofil (see below). Accord Healthcare (Barcelona, Spain) Neutropenia 2014 (EU)
Grastofil (filgrastim), rh G-CSF, produced in E. coli. Biosimilar to Neupogen. Same product as Accofil (see above). Accord Healthcare (Barcelona, Spain) Neutropenia 2013 (EU)
Lonquex (lipegfilgrastim), rh G-CSF, produced in E. coli and PEGylated. Teva Pharmaceuticals (Utrecht, the Netherlands) Neutropenia 2013 (EU)
Granix (tbo-filgrastim), rh G-CSF, produced in E. coli. Same product as Tevagrastim (see below). Teva Pharmaceuticals (North Wales, PA, USA) Neutropenia 2012 (US)
Filgrastim Hexal (filgrastim), biosimilar to Neupogen, produced in E. coli. Biosimilar rh G-CSF. Hexal Neutropenia 2009 (EU)
Biograstim (filgrastim), biosimilar to Neupogen produced in E. coli. Biosimilar rh G-CSF. ABZ-Pharma (Ulm, Germany) Neutropenia 2008 (EU)
Withdrawn 2015
Ratiograstim (filgrastim), biosimilar to Neupogen, produced in E. coli. Biosimilar rh G-CSF. Ratiopharm (Ulm, Germany) Neutropenia 2008 (EU)
Tevagrastim (filgrastim), rh G-CS, produced in E. coli. Biosimilar to Neupogen. Same product as Granix (see above). Teva (Radebeul, Germany) Neutropenia 2008 (EU)
Filgrastim Ratiopharm (filgrastim), produced in E. coli. Biosimilar to Filgrastim. Ratiopharm Neutropenia 2008 (EU)
Withdrawn 2011
Neulasta (EU and US), Neupopeg (EU) (pegfilgrastim), PEGylated rh G-CSF. Amgen (Breda, the Netherlands) Chemotherapy-induced neutropenia 2002 (EU & US)
Neupopeg withdrawn 2008 (EU)
Leukine (sargramostim), rh GM-CSF differing from the native protein by an R23L substitution, produced in E. coli. Partner Therapeutics (Lexington, MA, USA) Autologous bone marrow transplantation 1991 (US)
Withdrawn 2008 and reformulated without EDTA 2008
Neupogen (filgrastim), rh G-CSF differing from native protein by an extra N-terminal methionine, produced in E. coli. Amgen (Thousand Oaks, CA, USA) Chemotherapy-induced neutropenia 1991 (US)
Other growth factors
Oxervate (cenegermin (EU), cenegermin-bkbj (US)), ophthalmic solution, rh nerve growth factor, produced in E. coli. Dompé Farmaceutici (Milan)
Dompé U.S. (Boston)
Neurotophic keratitis 2018 (US)
2017 (EU)
Increlex (mecaserim), rh IGF-1, produced in E. coli. Ipsen Pharma Growth failure in children with IGF-1 deficiency or hGH gene deletion (long-term treatment) 2007 (EU)
2005 (US)
iPlex (mecasermin rinfabate), a complex of rh IGF-1 and rh IGF binding protein-3, produced separately in E. coli. Insmed (Glen Allen, VA, USA) Growth failure in children with severe primary IGF-1 deficiency or hGH gene deletion (long-term treatment) 2005 (US)
Withdrawn 2007 for IGF-1 deficiency
Kepivance (palifermin), rh keratinocyte growth factor, produced in E. coli. Swedish Orphan Biovitrum Severe oral mucositis in selected patients with hematologic cancers 2005 (EU)
2004 (US)
Withdrawn 2016 (EU)
GEM 21S: Regranex (see below) and tricalcium phosphate; growth-factor-enhanced matrix. BioMimetic Pharmaceuticals (Franklin, TN, USA) Periodontally related defects 2005 (US)
Regranex (becaplermin), rh platelet-derived growth factor receptor-BB, produced in S. cerevisiae. Janssen-Cilag International (Beerse, Belgium)
Johnson & Johnson (Raritan, NJ, USA)
Lower-extremity diabetic neuropathic ulcers 1997 (US)
1999 (EU)
Withdrawn 2012 (EU)
Recombinant interferons, interleukins and tumor necrosis factor
Interferon-α
Besremi (ropeginterferon alfa-2b (EU), ropeginterferon alfa-2b-njft (US); rh-interferon alfa-2b with an additional N-terminal proline conjugated to a 40-kDa two-arm PEG moiety, produced in E . coli. AOP Orphan Pharmaceuticals (Vienna)
PharmaEssentia (Burlington, MA, USA)
Polycythemia vera 2021 (US)
2019 (EU)
PEG-Intron/Rebetol combo pack (peginterferon alfa-2b/ribavirin), rh IFN-α-2b, produced in E. coli and PEGylated, and ribavirin. Schering Plough (Kenilworth, NJ, USA) Chronic hepatitis C 2008 (US)
Pegasys (peginterferon alfa-2a), IFN-α-2b, produced in E. coli and PEGylated. zr pharma (Vienna)
Roche/Genentech
Hepatitis C 2002 (EU & US)
PEG-Intron (peginterferon alfa-2b), IFN-α-2b, produced in E. coli and PEGylated. Merck Sharp & Dohme Chronic hepatitis C 2001 (US)
2000 (EU)
Withdrawn 2021 (EU)
Viraferon (interferon alfa-2b), produced in E. coli. Schering Plough (Brussels) Chronic hepatitis B, C 2000 (EU)
Withdrawn 2008
ViraferonPeg (peginterferon alfa-2b), IFN-α-2b, produced in E. coli and PEGylated. Merck Sharp & Dohme Chronic hepatitis C 2000 (EU)
Withdrawn 2021
Intron A, Alfatronol (interferon alfa-2b), produced in E. coli. Merck Sharp & Dohme Cancer, genital warts, hepatitis B and C, HPV 2000 (EU)
1986 (US)
Rebetron (ribavirin/interferon alfa-2b), produced in E. coli. Schering Plough Chronic hepatitis C 1999 (US)
Infergen (interferon alficon-1), r IFN-α, synthetic type I, produced in E. coli. Astellas Pharma Europe (Leiderdorp, the Netherlands)
Kadmon Pharmaceuticals (Warrendale, PA, USA)
Chronic hepatitis C 1999 (EU)
1997 (US)
Withdrawn 2006 (EU), 2013 (US)
Roferon A (interferon alfa-2a), produced in E. coli. Roche Hairy cell leukemia 1986 (US)
Withdrawn 2007
Interferon-β and interferon-γ
Plegridy (peginterferon beta-1a), rh IFN-β-1a, produced in CHO cells and PEGylated. Biogen (Badhoevedorp, the Netherlands) Multiple sclerosis 2014 (EU & US)
Extavia (interferon beta-1b), rh IFN-β-1b, produced in E. coli. Novartis (Dublin)
Novartis Pharmaceuticals (East Hanover, NJ USA)
Multiple sclerosis 2009 (US)
2008 (EU)
Rebif (interferon beta-1a), rh IFN-β-1a, produced in CHO cells. Merck (Amsterdam)
EMD Serono (Rockland, MA, USA)
Relapsing/remitting multiple sclerosis 2002 (US)
1998 (EU)
Avonex (interferon beta-1a), rh IFN-β-1a, produced in CHO cells. Biogen (Badhoevedorp, the Netherlands) Relapsing multiple sclerosis 1997 (EU)
1996 (US)
Betaferon (interferon beta-1b), r IFN-β-1b differing from native protein by C17S, produced in E. coli. Bayer Pharma Multiple sclerosis 1995 (EU)
Betaseron (interferon β-1b), differing from human protein by C17S, produced in E. coli. Berlex Laboratories (Richmond, CA, USA)
Chiron (Emeryville, CA, USA)
Relapsing/remitting multiple sclerosis 1993 (US)
Actimmune (interferon gamma-1b), produced in E. coli. Vidara Therapeutics (Dublin) Chronic granulomatous disease 1990 (US)
Others
Kineret (anakinra), rh IL-1 receptor antagonist, produced in E. coli. Swedish Orphan Biovitrum (Stockholm) Rheumatoid arthritis 2001 (US)
Beromun (tasonermin), rh TNF-α, produced in E. coli. Belpharma (Luxembourg) Adjunct to surgery for subsequent tumor removal, to prevent or delay amputation 1999 (EU)
Neumega (oprelvekin), r IL-11 lacking N-terminal proline of native molecule, produced in E. coli. Pfizer (Philadelphia), Genetics Institute Prevention of chemotherapy-induced thrombocytopenia 1997 (US)
Proleukin (aldesleukin) r IL-2, differs from native molecule in absence of N-terminal alanine and presence of C125S substitution, produced in E. coli. Prometheus Laboratories (San Diego) Renal cell carcinoma 1992 (US)
Vaccines
Hepatitis B
PreHevbri (EU), Prehevbrio (US), r hepatitis B surface antigen produced in CHO cells genetically modified to produce the hepatitis B virus envelope proteins, which include the small (S), middle (pre-S2) and large (pre-S1) hepatitis B surface antigens (HBsAg), representing the active substance. VBI Vaccines (Amsterdam)
VBI Vaccines (Cambridge, MA, USA)
Hepatitis B vaccine 2022 (EU)
2021 (US)
Heplisav B, r-hepatitis B surface antigen, produced in Hansenula polymorpha Dynavax (Dusseldorf, Germany)
Dynavax Technologies (Berkeley, CA, USA)
Hepatitis B vaccine 2021 (EU)
2017 (US)
Vaxelis, multi-component vaccine containing r HBsAg, produced in S. cerevisiae as one component. MCM Vaccine (Swiftwater PA, USA)
Merck (Whitehouse Station, NJ, USA)
Sanofi Pasteur (Swiftwater PA, USA)
Immunization against diphtheria, tetanus, pertussis, poliomyelitis, hepatitis B and invasive disease due to Haemophilus influenzae type b 2018 (US)
Hexacima (also sold as Hexyon), multi-component vaccine containing r HBsAg, produced in H. polymorpha as one component. Sanofi Pasteur (Lyon, France) Immunization against several pathogens and toxins 2013 (EU)
Ambirix, combination vaccine containing r HBsAg, produced in S. cerevisiae as one component. GSK (Rixensart, Belgium) Immunization against hepatitis A and B 2002 (EU)
Pediarix, combination vaccine containing r HBsAg, produced in S. cerevisiae as one component. GSK Immunization of children against various conditions inducing hepatitis B 2002 (US)
HBVAXPRO (r HBsAg), produced in S. cerevisiae. Merck Sharp & Dohme (Haarlem, the Netherlands) Immunization of children and adolescents against hepatitis B 2001 (EU)
Twinrix, combination vaccine containing r HBsAg, produced in S. cerevisiae as one component. GSK Immunization against hepatitis A and B 2001 (US)
1997 (EU pediatric form)
1996 (EU adult form)
Infanrix-hexa, combination vaccine containing r HbsAg, produced in S. cerevisiae as one component. GSK Immunization against diphtheria, tetanus, pertussis, Haemophilus influenzae b, hepatitis B and polio 2000 (EU)
Infanrix-penta, combination vaccine, containing r HbsAg, produced in S. cerevisiae as one component. GSK Immunization against diphtheria, tetanus, pertussis, polio, and hepatitis B 2000 (EU)
Withdrawn 2013
Hepacare (r S, pre-S & pre-S2 HBsAg), produced in a murine cell line. Evans Vaccines (Liverpool, UK) Immunization against hepatitis B 2000 (EU)
Withdrawn 2002
Hexavac, combination vaccine containing r HBsAg, produced in S. cerevisiae as one component. Sanofi Pasteur Immunization against diphtheria, tetanus, pertussis, hepatitis B, polio and H. influenzae b 2000 (EU)
Withdrawn 2012
Procomvax, combination vaccine containing r HBsAg as one component. Sanofi Pasteur Immunization against H. influenzae b and hepatitis B 1999 (EU)
Withdrawn 2009
Primavax, combination vaccine containing r HBsAg, produced in S. cerevisiae as one component. Sanofi Pasteur Immunization against diphtheria, tetanus and hepatitis B 1998 (EU)
Withdrawn 2000
Engerix B, r HbsAg, produced in S. cerevisiae. GSK Immunization against hepatitis B 1998 (US)
Infanrix Hep B, combination vaccine containing r HbsAg, produced in S. cerevisiae as one component. GSK Immunization against diphtheria, tetanus, pertussis and hepatitis B 1997 (EU)
Withdrawn 2005
Comvax, combination vaccine containing HBsAg, produced in S. cerevisiae as one component. Merck (Whitehouse Station, NJ, USA) Immunization of infants against H. influenzae b and hepatitis B 1996 (US)
Tritanrix-Hep B, combination vaccine containing r HBsAg, produced in S. cerevisiae as one component. GSK Immunization against hepatitis B, diphtheria, tetanus and pertussis 1996 (EU)
Withdrawn 2014
Recombivax, r HBsAg, produced in S. cerevisiae. Merck (Whitehouse Station, NJ, USA) Immunization against hepatitis B 1986 (US)
COVID-19
Nuvaxovid/Novavax COVID-19, vaccine directed at SARS-CoV-2 r (full-length) spike protein, produced in Spodoptera frugiperda (Sf9) insect cells using r baculovirus system. Novavax CZ (Jevany, Czechia) Vaccine (COVID-19) 2022 (US; Emergency Use Authorization)
2021 (EU; Conditional Marketing Authorisation)
Spikevax (previously COVID-19 Vaccine Moderna; elasomeran), ss mRNA produced by cell-free in vitro transcription from DNA templates encoding (full-length) viral spike (S) protein of SARS-CoV-2. Moderna Biotech Spain (Madrid)
ModernaTX (Cambridge, MA, USA)
Vaccine (COVID-19) 2021 (EU; Conditional Marketing Authorization)
2020 (US; Emergency Use Authorisation)
Jcovden (COVID-19 vaccine Janssen), r replication-deficient (E1- and partially E3-gene-deleted) adenovirus type 26 encoding SARS-CoV-2 spike glycoprotein, propagated in a PER.C6 cell line (derived from human embryonal retina cells). Janssen-Cilag International (Beerse, Belgium) Vaccine (COVID-19) 2021 (EU; Conditional Marketing Authorization)
2021 (US; Emergency Use Authorisation)
Vaxzevria, r replication-deficient (E1- and E3-deleted) chimpanzee adenovirus encoding SARS-CoV-2 spike protein combined with a tPA leader sequence, propagated in T-REx-293 cells (derivative of HEK293). AstraZeneca (Sodertalje, Sweden) Vaccine (COVID-19) 2021 (EU; Conditional Marketing Authorisation)
Comirnaty (Pfizer BioNTech COVID-19 vaccine; tozinameran; COVID-19 mRNA vaccine, nucleoside modified), ss, 5′-capped mRNA produced by cell-free in vitro transcription from DNA templates, encoding SARS-CoV-2 spike (S) protein. BioNTech Manufacturing (Mainz, Germany)
Pfizer (New York)
Vaccine (COVID-19) 2020 (US; Emergency Use Authorization)
2020 (EU; Conditional Marketing Authorisation)
Other
Vaxneuvance (Pneumococcal 15-valent Conjugate Vaccine), containing one r element, expressed in P. fluorescens. Merck Vaccine against Streptococcus pneumonia 2021 (US)
Mvabea (ebolavirus vaccine MVA-BN-Filo), engineered vaccinia strain encoding proteins from different viral strains. Janssen-Cilag International (Beerse, Belgium) Ebolavirus vaccine 2020 (EU)
Supemtek (Quadrivalent influenza vaccine), consisting of 4 r hemagglutinin (rHA) proteins, each expressed separately in Sf9 insect cells using a baculovirus protein expression vector. Sanofi Pasteur (Lyon, France) Influenza vaccine 2020 (EU)
Vaxchora, live, attenuated Vibrio cholerae O1 strain Classical biotype genetically engineered via deletion of part of the enterotoxin catalytic subunit A gene and inclusion of a mercury resistance marker (allowing it to be distinguished from wild-type V. cholerae). Emergent Netherlands (Amsterdam) Cholera vaccine 2020 (EU)
Zabdeno (Ebola vaccine; Ad26.ZEBOV-GP), r replication-incompetent, adenovirus type 26 (Ad26) encoding full-length glycoprotein (GP) of Ebola virus Zaire (ZEBOV) Mayinga strain. Janssen-Cilag International (Beerse, Belgium) Ebolavirus vaccine 2020 (EU)
Dengvaxia, dengue tetravalent vaccine (live, attenuated) based upon r engineered yellow fever virus–dengue virus. Sanofi Pasteur (Lyon, France)
Sanofi Pasteur (Swiftwater PA, USA)
Dengue vaccine 2019 (US)
2018 (EU)
Ervebo (Ebola Zaire Vaccine), live, r vesicular stomatitis virus with its envelope glycoprotein, replaced with ebolavirus Zaire surface glycoprotein, cultured in Vero cells. Merck Sharp & Dohme (Haarlem, the Netherlands)
Merck (Whitehouse Station, NJ, USA)
Ebolavirus vaccine 2019 (EU & US)
Shingrix (zoster vaccine recombinant, adjuvanted), r Varicella zoster virus surface glycoprotein E antigen component, produced in CHO cells. GlaxoSmithKline Biologicals (Rixensart, Belgium)
GlaxoSmithKline (Research Triangle Park, NC, USA)
Herpes zoster (shingles) prevention 2018 (EU)
2017 (US)
Trumenba (meningococcal group B vaccine), two r Neisseria meningitides serogroup B proteins independently expressed in E. coli. Pfizer (Brussels)
Pfizer (Philadelphia)
Vaccine against N. meningitides serogroup B 2017 (EU)
2014 (US)
Pandemic influenza vaccine H5N1, vaccine derived from engineered viral strain containing gene segments from appropriate influenzavirus strains, produced in embryonated eggs. MedImmune (Nijmegen, the Netherlands) Influenza vaccine 2016 (EU)
Bexsero (meningococcal group B vaccine), mixture of 3 N. meningitidis serogroup B proteins, produced in E. coli. GSK (Siena, Italy)
GlaxoSmithKline (Research Triangle Park, NC, USA)
Active immunization against N. meningitidis serogroup B 2015 (US)
2013 (EU)
Gardasil 9, mixture of the major capsid protein (L1) of 9 strains of HPV, each produced in S. cerevisiae. MSD (Haarlem, the Netherlands)
Merck (Whitehouse Station, NJ, USA)
Active immunization for those above 9 years of age against HPV-caused cancers and genital warts 2015 (EU)
2014 (US)
Flublok, r hemagglutinin proteins from 3 influenza viruses, produced in an insect cell line. Protein Sciences (Meriden, CT, USA) Immunization against influenza 2013 (US)
Provenge (sipuleucel-T), autologous peripheral blood mononuclear cells in combination with r prostatic acid phosphatase linked to GM-CSF, produced in an insect cell line. Dendreon (Seal Beach, CA, USA) Prostate cancer 2013 (EU)
2010 (US)
Withdrawn 2015 (EU)
Cervarix, r C-terminally truncated major capsid L1 proteins from HPV types 16 and 18, produced in a baculovirus-based expression system GSK Prevention of cervical cancer 2009 (US)
2007 (EU)
Gardasil (EU & US), Silgard (EU), r vaccine containing major capsid proteins from four HPV types, produced in S. cerevisiae. Merck Sharp & Dohme (Haarlem, the Netherlands)
Merck (Whitehouse Station, NJ, USA)
Vaccination against diseases caused by HPX 2006 (EU & US)
Dukoral, Vibrio cholerae and r cholera toxin B subunit. Valneva Sweden (Stockholm) Immunization against disease caused by V. cholerae subunit O1 2004 (EU)
Lymerix (r OspA), Borrelia burgdorferi surface lipoprotein, produced in E. coli. GSK Immunization against Lyme disease 1998 (US)
Withdrawn 2002
Triacelluvax, combination vaccine with r modified pertussis toxin as one component. Chiron (Siena, Italy) Immunization against diphtheria, tetanus and pertussis 1999 (EU)
Withdrawn 2002
Monoclonal-antibody-based products
Alymsys (bevacizumab-maly (US), bevacizumab (EU)), humanized IgG1 targeting VEGF, produced in a CHO cell line. Biosimilar to avastin. Same product as Oyavas. Amneal Pharmaceuticals (Bridgewater, NJ, USA)
Mabxience Research (Madrid)
Colorectal & various other cancers 2022 (US)
2021 (EU)
Bebtelovimab, rh IgG1 that binds an epitope of the SARS-CoV-2 spike protein RBD, expressed in CHO cell line. Eli Lilly (Indianapolis) COVID-19 2022 (US; Emergency Use Authorization)
Enjaym (sutimlimab-jome), humanized IgG4 targeting complement protein component 1s, produced in a CHO cell line. Bioverativ USA (Waltham, MA, USA) Cold agglutinin disease 2022 (US)
Evusheld (tixagevimab & cilgavimab), combination of 2 human IgG1κ mAbs directed against 2 (non-overlapping) epitopes on the SARS-CoV-2 spike protein RBD, produced in CHO cell lines. AstraZeneca (Sodertalje, Sweden) COVID -19 prevention. 2022 (EU)
2021 (US; Emergency Use Authorization)
Lunsumio (mosunetuzumab), humanized full-length anti-CD20/CD3 T-cell-engaging bispecific IgG1, produced in a CHO cell line. Roche (Grenzach-Wyhlen, Germany) Relapsed or refractory follicular lymphoma 2022 (EU)
Opdualag (nivolumab and relatlimab-rmbw), combination of two IgG4κ mAbs targeting PD-1 and lymphocyte activation gene-3, both produced in CHO cells. Bristol-Myers Squibb (Princeton, NJ, USA) Unresectable or metastatic melanoma 2022 (US)
Padcev (enfortumab vedotin (EU), enfortumab vedotin-ejfv (US)), antibody–drug conjugate (ADC) targeting nectin-4 (an adhesion protein highly expressed in urothelial cancer). Fully human IG1κ (produced in a CHO cell line) conjugated to monomethyl auristatin E (MMAE). Astellas Pharma Europe (Leiden, the Netherlands)
Astellas Pharma US (Northbrook, Illinois, USA)
Urothelial cancer 2022 (EU)
2019 (US)
Saphnelo (anifrolumab (EU), anifrolumab-fnia (US)), human IgG1κ directed against type I IFN subunit 1 receptor, produced in mouse myeloma cells (NS0). AstraZeneca (Sodertalje, Sweden)
AstraZeneca (Wilmington, DE, USA)
Systemic lupus erythematosus 2022 (EU)
2021 (US)
Uplizna (inebilizumab (EU), inebilizumab-cdon (US)), humanized, affinity-optimized, afucosylated (IgG1κ specific for the B-cell-specific surface antigen CD19, produced in fucosyltransferase-deficient CHO cells. Viela Bio (Schiphol, the Netherlands)
Viela Bio (Gaithersburg, MD, USA)
Neuromyelitis optica spectrum disorders 2022 (EU)
2020 (US)
Vabysmo (faricimab-svoa), humanized bispecific IgG1, targeting VEGF-A and angiopoietin-2, produced in a CHO cell line. Genentech Neovascular (wet) age-related macular degeneration and diabetic macular edema 2022 (US)
Vyepti (eptinezumab (EU), eptinezumab-jjmr (US)), humanized anti-CGRP IgG1 mAb, produced in P. pastoris. H. Lundbeck (Valby, Denmark)
Lundbeck Seattle BioPharmaceuticals
Migraine prevention 2022 (EU)
2020 (US)
Abevmy (bevacizumab), r humanized, anti-VEGF-A IgG1κ, produced in a CHO cell line. Biosimilar to Avastin. Mylan (Dublin) Cancer (various) 2021 (EU)
Adbry (tralokinumab-ldrm; US), Adtralza (tralokinumab; EU), anti-IL-13 human IgG4λ, manufactured in an NS0 murine cell line. LEO Pharma (Madison, NJ, USA)
LEO Pharma (Ballerup, Denmark)
Atopic dermatitis (eczema) 2021 (US & EU)
Aduhelm (aducanumab-avwa), human IgG1 directed against aggregated soluble and insoluble forms of amyloid-β, produced in a CHO cell line. Biogen (Cambridge, MA, USA) Alzheimer’s disease 2021 (US)
Bamlanivimab & eteseviman, rh IgG1 mAbs that bind distinct but overlapping epitopes in the SARS-CoV-2 spike protein RBD. Eli Lilly (Indianapolis) COVID 19 2021 (US; Emergency Use Authorization; Authorization paused in 2022 as product not sufficiently effective against Omicron variant)
Bimzelx (bimekizumab), humanized IgG1κ mAb targeting human IL-17A and 17F, produced in a CHO cell line. UCB Pharma (Brussels) Psoriasis 2021 (EU)
Byooviz (ranibizumab-nuna (US), ranibizumab (EU)), r humanized IgG1κ Fab fragment targeting VEGF-A, produced in E. coli. Biosimilar to Lucentis. Samsung Bioepis NL (Delft, the Netherlands)
Biogen (Cambridge, MA, USA)
Age-related macular degeneration (wet) and some additional retinal conditions 2021 (EU & US)
Enhertu (trastuzumab deruxtecan), ADC comprising humanized anti-HER2 IgG1κ (trastuzumab sequence), produced in CHO cells, conjugated to a topoisomerase I inhibitor derivative of exatecan. Daiichi Sankyo Europe (Munich, Germany)
Daiichi Sankyo (Basking Ridge, NJ, USA)
Metastatic breast cancer 2021 (EU)
2019 (US)
Enspryng (satralizumab (EU), satralizumab-mwge (US)), r humanized IgG2 targeting soluble and membrane-bound IL-6 receptor, produced in a CHO cell line. Roche (Grenzach-Wyhlen, Germany)
Genentech
Neuromyelitis optica spectrum disorders 2021(EU)
2020 (US)
Evkeeza (evinacumab-dgnb (US), evinacumab (EU)), rh-IgG4 mAb targeting angiopoietin-like 3, produced in a CHO cell line. Regeneron (Dublin)
Regeneron (Tarrytown, NY, USA)
Homozygous familial hypercholesterolemia 2021 (EU & US)
Hukyndra (adalimumab), human IgG1κ targeting TNF, produced in a CHO cell line. Biosimilar to Humira. Same as Libmyris. Stada Arzneimittel (Bad Vilbel, Germany) Various inflammatory conditions 2021 (EU)
Jemperli (dostarlimab-gxly (US), dostarlimab (EU)), humanized IgG4 mAb against programmed cell death protein 1 (PD-1), produced in CHO cells. GlaxoSmithKline (Dublin)
GlaxoSmithKline (Research Triangle Park, NC, USA)
Endometrial cancer 2021 (EU & US)
Kesimpta (ofatumumab), rh IgG1 targeting B cell surface CD20, expressed in a mouse NS0 cell line. Novartis (Dublin) Multiple sclerosis 2021 (EU)
Lextemy (bevacizumab), r humanized anti-VEGF-A IgG1κ, produced in a CHO cell line. Biosimilar to Avastin. Same product as Abevmy. Mylan (Dublin) Cancer (various) 2021 (EU)
Withdrawn 2021
Libmyris (adalimumab), human IgG1κ targeting TNF, produced in a CHO cell line. Biosimilar to Humira. Stada Arzneimittel (Bad Vilbel, Germany) Various inflammatory conditions 2021 (EU)
Minjuvi (EU), Monjivi (US) (tafasitamab (EU), tafasitamab-cxix (US)), humanized, Fc-engineered CD19-specific mAb, produced in a CHO cell line. Incyte Biosciences Distribution (Amsterdam)
Morphosys US (Boston)
Diffuse large B cell lymphoma 2021(EU)
2020 (US)
Onbevzi (bevacizumab), humanized, anti-VEGF mAb, produced in CHO cells. Biosimilar to Avastin. Samsung Bioepis (Delft, the Netherlands) Cancers (various) 2021 (EU)
Oyavas (bevacizumab), r humanized, anti-VEGF-A IgG1κ, produced in a CHO cell line. Biosimilar to Avastin. Stada Arzneimittel (Hessen, Germany) Cancer (various) 2021 (EU)
Regkirona (regdanvimab), human IgG1 targeting the SARS-CoV-2 spike protein, produced in a CHO cell line. Celltrion (Budapest) COVID 19 (treatment) 2021 (EU)
Ronapreve (EU), Regen-cov (US)) (casirivimab & imdevimab), combination of two human IgGs (IgG1κ and IgG1λ) targeting distinct epitopes of SARS-CoV-2 spike protein, both produced in CHO cell lines. Roche (Grenzach-Wyhlen, Germany)
Regeneron (US)
COVID-19 (prevention & treatment) 2021 (EU)
2020 (US; Emergency Use Authorization; Authorization paused in 2022 as product not sufficiently effective against Omicron variant)
Rybrevant (amivantamab-vmjw (US), amivantamab (EU)), human low-fucose IgG1 bispecific antibody that binds the extracellular domains of EGF and MET receptors, produced in CHO cell lines. Janssen-Cilag (Beerse, Belgium)
Janssen Biotech (Horsham, PA, USA)
Advanced non-small-cell lung cancer 2021 (EU & US)
Susvimo (ranibizumab), humanized IgG1κ antibody fragment specific for VEGF-A, produced in E. coli. Genentech Neovascular (wet) age-related macular degeneration 2021 (US)
Tezspire (tezepelumab-ekko), human IgG2λ specific for thymic stromal lymphopoietin (TSLP), produced in a CHO cell line. Amgen & AstraZeneca Severe asthma 2021 (US)
Tivdak (tisotumab vedotin-tftv), tissue factor (TF)-directed ADC comprising a human anti-TF IgG1κ antibody conjugated to monomethyl auristatin E (MMAE), produced in a CHO cell line. Seagen (Bothell, WA, USA) Cervical cancer 2021 (US)
Trodelvy (sacituzumab govitecan (EU), sacituzumab govitecan-hziy (US)), ADC comprising an anti-Trop-2 humanized IgG1κ, produced in Sp2/0 cells, conjugated to camptothecin-derived topoisomerase I inhibitor SN-38. Gilead Sciences (Cork, Ireland)
Immunomedics (Morris Plains, NJ, USA)
Breast cancer (triple-negative) 2021 (EU)
2020 (US)
Vyvgart (efgartigimod alfa-fcab), human IgG1-derived Fc fragment that binds the neonatal Fc receptor (FcRn), leading to reduced circulating IgG, produced in a CHO cell line. Argenx (Boston) Myasthenia gravis 2021 (US)
Xevudy (sotrovimab in US), human IgG1 targeting the COVID-19 spike protein RBD, produced in a CHO cell line. GlaxoSmithKline (Dublin)
GSK (Durham, NC, USA)
Treating COVID-19 2021 (EU)
2021 (US; Emergency Use Authorization; Authorization paused in 2022 as product not sufficiently effective against Omicron variant)
Yuflyma (adalimumab), anti-TNF human IgG1, produced in a CHO cell line. Biosimilar to Humira. Celltrion (Budapest) Various inflammatory conditions 2021 (EU)
Yusimry (adalimumab-aqvh), anti-TNF human IgG1, produced in a CHO cell line. Biosimilar to Humira. Coherus BioSciences (Redwood City, CA, USA) Various inflammatory conditions 2021 (US)
Zynlonta (loncastuximab tesirine-lpyl), CD19-directed humanized IgG1κ produced in a CHO cell line, conjugated to SG3199 (alkylating agent). ADC Therapeutics (Murray Hill, NJ, USA) Lymphoma 2021 (US)
Adakveo (crizanlizumab (EU), crizanlizumab-tmca (US)), r humanized IgG2aκ mAb targeting human P-selectin, produced in a CHO cell line. Novartis (Dublin)
Novartis (East Hanover, NJ, USA)
Prevention of recurrent vaso-occlusive crises (VOCs) in sickle cell anemia 2020 (EU)
2019 (US)
Amsparity (adalimumab), human IgG1 targeting TNF-α, produced in a CHO cell line. Biosimilar to Humira. Pfizer (Brussels) Various inflammatory conditions 2020 (EU)
Aybintio (bevacizumab), humanized anti-VEGF mAb, produced in a CHO cell line. Biosimilar to Avastin. Samsung Bioepis (Delft, the Netherlands) Various cancers 2020 (EU)
Beovu (brolucizumab (EU), brolucizumab-dbll (US)), humanized single-chain Fv (scFv) antibody fragment targeting vascular endothelial growth factor-A (VEGF-A), produced in E . coli. Novartis (Dublin)
Novartis (East Hanover, NJ, USA)
Wet age-related macular degeneration, macular oedema 2020 (EU)
2019 (US)
Blenrep (belantamab mafodotin (EU), belantamab mafodotin-blmf (US)), ADC comprising monomethyl auristatin F conjugated to an afucosylated humanized IgG1κ, produced in a CHO cell line, targeting B cell maturation antigen (BCMA). GlaxoSmithKline (Dublin)
GlaxoSmithKline (Research Triangle Park, NC, USA)
Multiple myeloma 2020 (EU & US)
Danyelza (naxitamab-gqgk), humanized IgG1 specific for glycolipid disialoganglioside (GD2), produced in a CHO cell line. Y-mABs Therapeutics (New York, NY, USA) Neuroblastoma 2020 (US)
Darzalex Faspro (daratumumab and hyaluronidase-fihj), IgG1κ specific for the CD38 antigen in combination with rh hyaluronidase (which increases drug dispersion and absorption upon SC administration), both produced in CHO cell lines. Janssen Biotech (Horsham, PA, USA) Multiple myeloma 2020 (US)
Ebanga (ansuvimab-zykl), Zaire ebolavirus glycoprotein (EBOV GP)-directed human IgG1, produced in a CHO cell line. Ridgeback Biotherapeutics (Miami, FL, USA) Infection by Zaire ebolavirus 2020 (US)
Equidacent (bevacizumab), humanized IgG1 targeting VEGF, produced in a CHO cell line. Biosimilar to Avastin. Centus Biotherapeutics (Dublin) Cancers, various 2020 (EU)
Withdrawn 2020
Hulio (adalimumab (EU), adalimumab-fkjp (US)), human IgG1 targeting TNF-α, expressed in CHO cells. Biosimilar to Humira. Mylan (Saint-Priest, France)
Mylan Pharmaceuticals (Morgantown, WV, USA)
Various inflammatory conditions mediated by TNF 2020 (US)
2018 (EU)
Inmazeb (atoltivimab, maftivimab and odesivimab-ebgn), combination of Zaire ebolavirus glycoprotein-directed human IgG1s, produced in CHO cell lines. Regeneron (Tarrytown, NY, USA) Infection by Zaire ebolavirus 2020 (US)
Margenza (margetuximab-cmkb), chimeric Fc-engineered IgG1κ specific for the extracellular domain of the human epidermal growth factor receptor 2 protein (HER2), produced in a CHO cell line. MacroGenics (Rockville, MD, USA) HER2positive breast cancer 2020 (US)
Obiltoxaximab SFL (EU), Anthim (US) (obiltoxaximab), chimeric IgG1 targeting the B. anthracis protective antigen (PA), the cell-binding component of anthrax toxin. Produced in an NS0 cell line. SFL Pharmaceuticals Deutschland (Lörrach, Germany)
Elusys Therapeutics (Pine Brook, NJ, USA)
Inhalational anthrax 2020 (EU)
2016 (US)
Phesgo (pertuzumab, trastuzumab), combination of 2 r humanized IgG1 mAbs targeting the human epidermal growth factor receptor 2 (HER2), both produced in CHO cells, along with rh hyaluronidase (vorhyaluronidase alfa) as an excipient. Roche (Grenzach-Wyhlen, Germany; EU)
Genentech (South San Francisco, CA, USA; US)
HER2-positive breast cancer 2020 (EU & US)
Polivy (polatuzumab vedotin), ADC comprising a humanized IgG1, produced in CHO cells, targeting a component of the B cell receptor (CD79b) conjugated to monomethyl auristatin E (MMAE). Roche (Grenzach-Wyhlen, Germany)
Genentech (South San Francisco, CA, USA)
Diffuse large B cell lymphoma 2020 (EU)
2019 (US)
Riabni (rituximab-arrx), chimeric IgG1κ directed against the CD20 antigen, produced in a CHO cell line. Biosimilar to Rituxan. Amgen (Thousand Oaks, CA, USA) Non-Hodgkin’s lymphoma, chronic lymphocytic leukemia, Wegener’s granulomatosis and microscopic polyangiitis 2020 (US)
Ruxience (rituximab (EU), rituximab-pvvr (US)), chimeric mouse/human IgG1 targeting B lymphocyte CD20, produced in a CHO cell line. Biosimilar to MabThera/Rituxan. Pfizer (Brussels)
Pfizer (New York)
Various cancers and inflammatory conditions 2020 (EU)
2019 (US)
Sarclisa (isatuximab (EU), isatuximab-irfc (US)), chimeric anti-CD 38 IgG1, produced in a CHO cell line. Sanofi-Aventis (Paris)
Sanofi-Aventis (Bridgewater, NJ, USA)
Multiple myeloma 2020 (EU & US)
Tepezza (teprotumumab-trbw), human IgG1 that binds IGF-1 receptor, produced in a CHO cell line. Horizon Therapeutics (Lake Forest, IL, USA) Thyroid eye disease 2020 (US)
Zercepac (trastuzumab), humanized anti-HER2 mAb, produced in a CHO cell line. Biosimilar to Herceptin. Accord Healthcare (Barcelona) Breast and stomach cancers 2020 (EU)
Abrilada (adalimumab-afzb), human IgG1 specific for TNF, produced in a CHO cell line. Biosimilar to Humira. Pfizer (New York) Various inflammatory conditions 2019 (US)
Ajovy (fremanezumab (EU), fremanezumab-vfrm (US)), humanized IgG2 targeting both isoforms of CGRP, produced in a CHO cell line. Teva (Ulm, Germany)
Teva Pharmaceuticals USA (North Wales, PA, USA)
Migraine 2019 (EU)
2018 (US)
Avsola (infliximab-axxq), anti-TNF chimeric IgG1κ, produced in a CHO cell line. Biosimilar to Remicade. Amgen (Thousand Oaks, CA, USA) Various inflammatory conditions 2019 (US)
Cablivi (Caplacizumab (EU), caplacizumab-yhdp (US)), humanized bivalent nanobody comprising two identical building blocks joined by a tri-alanine linker and targeting the A1 domain of von Willebrand factor, produced in E. coli. Ablynx (Zwijnaarde, Belgium)
Genzyme (Cambridge, MA, USA)
Acquired thrombotic thrombocytopenic purpura 2019 (US)
2018 (EU)
Evenity (romosozumab (EU), romosozumab-aqqg (US)), humanized IgG2 targeting sclerostin, produced in a CHO cell line. UCB Pharma (Brussels)
Amgen (Thousand Oaks, CA, USA)
Osteoporosis 2019 (EU & US)
Hadlima (adalimumab-bwwd), anti-TNF human IgG1 produced in a CHO cell line. Biosimilar to Humira. Same product as Imraldi. Merck (Whitehouse Station, NJ, USA) Various inflammatory conditions 2019 (US)
Herceptin Hylecta (trastuzumab and hyaluronidase-oysk). Genentech Breast cancer 2019 (US)
Idacio (adalimumab), rh-IgG1 targeting TNF, produced in a CHO cell line. Biosimilar to Humira. Same as Kromeya (see below). Fresenius Kabi Deutschland (Bad Homburg v.d. Höhe, Germany) Various inflammatory conditions 2019 (EU)
Kanjinti (trastuzumab (EU), trastuzumab-anns (US)), r humanized IgG1 against HER2, produced in CHO cells. Biosimilar to Herceptin. Amgen Europe (Breda, the Netherlands) Breast and gastric cancers 2019 (US)
2018 (EU)
Kromeya (adalimumab, rh-IgG1 targeting TNF, produced in a CHO cell line. Biosimilar to Humira. Same as Idacio (see above). Fresenius Kabi Deutschland (Bad Homburg v.d. Höhe, Germany) Various inflammatory conditions 2019 (EU)
Withdrawn 2019
Libtayo (cemiplimab-rwlc (US), cemiplimab (EU), human IgG4 specific for PD-1, produced in CHO cells. Regeneron Pharmaceuticals (Tarrytown, NY, USA)
Regeneron Ireland (Dublin)
Cutaneous squamous cell carcinoma 2019 (EU)
2018 (US)
Ontruzant (trastuzumab (EU), trastuzminjmab-dttb USA), produced in CHO cells. Biosimilar to Herceptin. Samsung Bioepis (Delft, the Netherlands)
Organon (Jersey City, NJ, USA)
Breast and gastric cancers 2019 (EU)
2017 (EU)
Skyrizi (risankizumab (EU), risankizumab-rzaa (US)), humanized IgG1 targeting IL-23, produced in a CHO cell line. AbbVie Deutschland (Rhein, Germany)
AbbVie (North Chicago, IL, USA)
Plaque psoriasis and psoriatic arthritis 2019 (US & EU)
Trazimera (trastuzumab (EU), trastuzumab-qyyp, US)), humanized IgG, produced in a CHO cells. Biosimilar to Herceptin. Pfizer (Brussels)
Pfizer (New York)
Breast cancer, gastric or gastroesophageal junction adenocarcinoma 2019 (US)
2018 (EU)
Trogarzo (ibalizumab (EU), ibalizumab-uiyk (US)), humanized IgG-4, targeting T-helper cells CD4 receptor, produced in an NS0 cell line. Theratechnologies Europe (Dublin)
TaiMed Biologics (Irvine, CA, USA) & Theratechnologies (Montreal)
Treatment of human immunodeficiency virus type 1 infection 2019 (EU)
2018 (US)
Ultomiris (ravulizumab (EU), ravulizumab-cwvz (US)), r humanized IgG2/4 targeting complement component 5, produced in a CHO cell line. Alexion Europe (LevallPerret, France)
Alexion Pharmaceuticals (Boston)
Paroxysmal nocturnal hemoglobinuria and atypical hemolytic uremic syndrome 2019 (EU)
2018 (US)
Zirabev (bevacizumab (EU), bevacizumab-bvzr (US)), humanized IgG1κ targeting VEGF, produced in CHO cell line. Biosimilar to Avastin. Pfizer Europe (Brussels)
Pfizer (New York)
Cancer (various) 2019 (EU & US)
Aimovig (erenumab-aooe (US), erenumab (EU)), human IgG2 targeting the CGRP receptor, produced in CHO cells. Amgen (Thousand Oaks, CA, USA)
Novartis (East Hanover, NJ, USA)
Novartis Europharm (Dublin)
Migraine 2018 (EU & US)
Crysvita (burosumab (EU), burosumab-twza (US)), human IgG1 antibody to soluble fibroblast growth factor-23, produced in CHO cells. Kyowa Kirin (Hoofddorp, the Netherlands)
Ultragenyx Pharmaceutical (Novato, CA, USA)
X-linked hypophosphatemia 2018 (EU & US)
Emgality (galcanezumab (EU), galcanezumab-gnlm (US)), humanized IgG4 that binds CGRP, produced in CHO cells. Eli Lilly Nederland (Utrecht, the Netherlands)
Eli Lilly (Indianapolis)
Migraine 2018 (EU & US)
Fasenra (benralizumab), humanized, afucosylated IgG1 targeting the α subunit of the human IL-5 receptor, produced in CHO cells. AstraZeneca (Södartälje, Sweden, & Wilmington, DE, USA) Asthma 2018 (EU)
2017 (US)
Gamifant (emapalumab-lzsg), r IgG1 targeting IFN-γ, produced in CHO cells. Sobi (Waltham, MA, USA) Primary hemophagocytic lymphohistiocytosis (HLH) 2018 (US)
Halimatoz (adalimumab), anti-TNF IgG, produced in CHO cells. Biosimilar to Humira. Same product as Hefiya and Hyrimoz (see below). Sandoz Various inflammatory conditions mediated by TNF, including rheumatoid arthritis and plaque psoriasis 2018 (EU)
Withdrawn 2020
Hefiya (adalimumab), anti-TNF IgG, produced in CHO cells. Biosimilar to Humira. Same product as Halimatoz and Hyrimoz (see above and below). Sandoz Various inflammatory conditions mediated by TNF, including polyarticular juvenile idiopathic arthritis and plaque psoriasis 2018 (EU)
Hemlibra (emicizumab (EU), emicizumab-kxwh (US)), humanized, bispecific IgG4 capable of binding factors IXa and X, produced in CHO cells. Roche Registration (Welwyn Garden City, UK)
Roche/Genentech (South San Francisco, CA, USA)
Hemophilia A 2018 (EU)
2017 (US)
Herzuma (trastuzumab (EU), trastuzumab-pkrb (US)), r humanized IgG1 against HER2, produced in CHO cells. Biosimilar to Herceptin. Celltrion Healthcare (Budapest), Celltrion (Incheon, Republic of Korea)
Teva Pharmaceuticals USA (North Wales, PA, USA)
Breast and gastric cancers (EU)
Breast cancer (US)
2018 (EU & US)
Hyrimoz (adalimumab (EU), adalimumab-adaz (US)), anti-TNF IgG, produced in CHO cells. Biosimilar to Humira. Same product as Halimatoz and Hefiya (see above). Sandoz Various inflammatory conditions mediated by TNF, including rheumatoid arthritis and plaque psoriasis 2018 (EU & US)
Ilumya (tildrakizumab-asmn; US), Ilumetri (tildrakizumab; EU), humanized IgG1 that binds the p19 subunit of IL-23, produced in CHO cells. Merck (Whitehouse Station, NJ, USA)
Almirall (Barcelona)
Psoriasis 2018 (US & EU)
Imfinzi (durvalumab), human IgG1 blocking the interaction of programmed cell death ligand-1 (PD-L1) with its receptor PD-1 and CD80, produced in CHO cells. AstraZeneca (Sodertalje, Sweden)
AstraZeneca (Wilmington, DE, USA)
Non-small-cell lung cancer
Urothelial carcinoma
2018 (EU)
2017 (US)
Mvasi (bevacizumab (EU), bevacizumab-awwb (US)), humanized IgG antibody to human VEGF-A1, produced in CHO cells. Biosimilar to Avastin. Amgen Europe Amgen (Thousand Oaks, CA, USA) Various cancers 2018 (EU)
2017 (US)
Mylotarg (gemtuzumab ozogamicin), ADC targeting the CD33 surface antigen, consisting of a humanized IgG4 chemically conjugated to N-acetyl-γ-calicheamicin, produced in NS0 mouse myeloma cells. Pfizer (Brussels)
Pfizer/Wyeth (Philadelphia)
Acute myeloid leukemia 2018 (EU)
2000 (US)
Withdrawn 2010 (US)
Reapproved 2017 (US) using modified dosage and regimen
Ocrevus (ocrelizumab), r humanized IgG1 targeting the CD20 surface antigen, produced in CHO cells. Roche/Genentech (South San Francisco, CA, USA) Multiple sclerosis 2018 (EU)
2017 (US)
Ogivri (trastuzumab-dkst (US), trastuzumab (EU)), IgG produced in CHO cells. Biosimilar to Herceptin. Viatris (Dublin)
Mylan (Morgantown, WV, USA)
Breast and gastric cancers 2018 (EU)
2017 (US)
Poteligeo (mogamulizumab (EU), mogamulizumab-kpkc (US)), defucosylated, humanized IgG1 that binds C-C chemokine receptor type 4 (CCR4), produced in CHO cells. Kyowa Kirin (Hoofddorp, the Netherlands)
Kyowa Kirin (Bedminster, NJ, USA)
Sezary syndrome, mycosis fungoides 2018 (EU & US)
Takhzyro (lanadelumab (EU), lanadelumab-flyo (US)), human IgG1 targeting active plasma kallikrein, produced in CHO cells. Shire (Dublin)
Dyax (Lexington, MA, USA)
Hereditary angioedemas 2018 (EU & US)
Truxima (rituximab (EU), rituximab-abbs (US)), chimeric IgG1 against cell surface antigen CD20, produced in CHO cells. Biosimilar to MabThera. Same product as Blitzima, Ritemvia (see above). Celltrion (Torony, Hungary)
Teva Pharmaceuticals USA (North Wales, PA, USA)
Selected cancers and autoimmune disorders (EU), non-Hodgkin’s lymphoma (US) 2018 (US)
2017 (EU)
Zessly (infliximab), chimeric anti-TNF IgG1 produced in CHO cells. Biosimilar to Remicade. Sandoz Rheumatoid arthritis and selected additional inflammatory diseases 2018 (EU)
Amgevita (adalimumab), anti-TNF human IgG1, produced in CHO cells. Biosimilar to Humira. Same product as Solymbic (see below). Amgen Europe Rheumatoid arthritis and selected additional inflammatory diseases 2017 (EU)
Withdrawn 2019
Bavencio (avelumab), human IgG1 specific for programmed death ligand-1 (PD-L1), produced in CHO cells. Merck Europe (Amsterdam)
Pfizer (New York)
Metastatic Merkel cell carcinoma, urothelial carcinoma 2017 (EU & US)
Besponsa (inotuzumab ozogamicin), ADC comprising a humanized IgG4 specific for human CD22, produced in CHO cells, covalently linked to the cytotoxic agent N-acetyl-γ-calicheamicin dimethylhydrazide. Pfizer (Brussels)
Pfizer/Wyeth (Philadelphia)
Acute lymphoblastic leukemia 2017 (EU & US)
Blitzima (rituximab), chimeric IgG1 against cell surface antigen CD20, produced in CHO cells. Biosimilar to MabThera. Same product as Ritemvia, Truxima and Rituzena (see below). Celltrion Healthcare (Budapest) Non-Hodgkin’s lymphoma, CLL, granulomatosis 2017 (EU)
Rixiamgelusd zarz ezo (adalimumab (EU), adalimumab-adbm (US)), rh IgG1 against human TNF, produced in CHO cells. Biosimilar to Humira. Boehringer Ingelheim (Rhein, Germany)
Boehringer Ingelheim (Ridgefield, CT, USA)
Range of inflammatory conditions, including psoriasis, rheumatoid arthritis and Crohn’s disease 2017 (EU & US)
Withdrawn 2019 (EU)
Dupixent (dupilumab), human IgG4 that binds the IL-4α receptor subunit, produced in CHO cells Sanofi-Aventis (Paris & Bridgewater, NJ, USA)
Regeneron Pharmaceuticals (Tarrytown, NY, USA)
Atopic dermatitis 2017 (EU & US)
Imraldi (adalimumab), produced in CHO cells. Biosimilar to Humira. Samsung Bioepis (Delft, the Netherlands) Rheumatoid arthritis, selected additional inflammatory diseases 2017 (EU)
Ixifi (infliximab-qbtx), produced in mammalian cells. Biosimilar to Remicade. Pfizer (New York) Various inflammatory conditions, including rheumatoid arthritis, Crohn’s disease, and psoriasis 2017 (US)
Kevzara (sarilumab), human IgG1 that binds IL-6 receptors, produced in CHO cells. Sanofi-Aventis (Paris & Bridgewater, NJ, USA)
Regeneron Pharmaceuticals (Tarrytown, NY, USA)
Rheumatoid arthritis 2017 (EU)
2017 (US)
Kyntheum (EU), Siliq (US) (brodalumab), human IgG2 against human IL-17 receptor A, produced in CHO cells. LEO Pharma (Ballerup, Denmark)
Valeant Pharmaceuticals (Bridgewater, NJ, USA)
Psoriasis 2017 (EU)
2017 (US)
Qarziba (dinutuximab beta; previously dinutuximab beta EUSA and dinutuximab beta Apeiron), chimeric IgG1 against carbohydrate disialoganglioside GD2 that is overexpressed by cells of neuroectodermal origin such as neuroblastoma cells, produced in a CHO cell line. EUSA Pharma (Schiphol-Rijk, the Netherlands) Neuroblastoma 2017 (EU)
Renflexis (infliximab-abda), chimeric IgG1 that binds TNF-α, produced in CHO cells. Biosimilar to Remicade. Same product as Flixabi (see below). Merck (Kenilworth, NJ, USA) Crohn’s disease and various other inflammatory conditions 2017 (US)
Ritemvia (rituximab), produced in CHO cells. Biosimilar to MabThera. Same product as Blitzima, Rituzena and Truxima (see above and below). Celltrion Healthcare (Budapest) Non-Hodgkin’s lymphoma, granulomatosis with polyangiitis, microscopic polyangiitis 2017 (EU)
Withdrawn 2021
Rituxan Hycela, rituximab and hyaluronidase human, both produced in CHO cells. Biogen (Cambridge, MA, USA), Genentech Follicular lymphoma, diffuse large B cell lymphoma, CLL 2017 (US)
Rituzena (previously Tuxella) (rituximab), produced in CHO cells. Biosimilar to MabThera. Same product as Blitzima, Ritemvia and Truxima (see above and below). Celltrion Healthcare (Budapest) Non-Hodgkin’s lymphoma, CLL, granulomatosis with polyangiitis 2017 (EU)
Withdrawn 2019
Rixathon (rituximab), chimeric IgG1 against cell surface antigen CD20, produced in CHO cells. Biosimilar to MabThera. Same product as Riximyo (see below). Sandoz Various conditions including non-Hodgkin’s lymphoma, CLL, rheumatoid arthritis 2017 (EU)
Riximyo (rituximab), chimeric IgG1 against cell surface antigen CD20, produced in CHO cells. Biosimilar to MabThera. Same product as Rixathon (see above). Sandoz Various conditions including non-Hodgkin’s lymphoma and rheumatoid arthritis, but excluding CLL 2017 (EU)
Solymbic (adalimumab), anti-TNF human IgG1 produced in CHO cells. Biosimilar to Humira. Same product as Amgevita and Amjevita (see above and below). Amgen Europe Rheumatoid arthritis and selected additional inflammatory diseases 2017 (EU)
Withdrawn 2018
Tecentriq (atezolizumab), humanized IgG1 specific for programmed death ligand 1 (PD-L1), engineered to lack Fc glycosylation, produced in CHO cells. Roche Registration (Grenzach-Wyhlen, Germany)
Genentech (South San Francisco, CA, USA)
Urothelial carcinoma, non-small-cell lung cancer 2017 (EU)
2016 (US)
Tremfya (guselkumab), human IgG1 that selectively binds the p19 subunit of IL-23, produced in CHO cells. Janssen-Cilag (Beerse, Belgium)
Janssen Biotech (Horsham, PA, USA)
Psoriasis 2017 (EU & US)
Zinplava (bezlotoxumab), human IgG directed against Clostridium difficile toxin B, produced in CHO cells. Merck Sharp & Dohme
Merck (Whitehouse Station, NJ, USA)
C. difficile infection 2017 (EU)
2016 (US)
Amjevita (adalimumab-atto), rh IgG1 specific for TNF, produced in CHO cells. Biosimilar to Humira. Same product as Solymbic and Amgevita (see above). Amgen (Thousand Oaks, CA, USA) Rheumatoid arthritis and selected additional inflammatory diseases 2016 (US)
Cinqair (US), Cinqaero (EU) (reslizumab), humanized IgG4 against IL-5, produced in NS0 cells. Teva Respiratory (Frazer, PA USA)
Teva (Haarlem, the Netherlands)
Asthma 2016 (US)
2016 (EU)
Darzalex (daratumumab), human IgG1 against CD-38, produced in CHO cells. Janssen-Cilag
Janssen Biotech
Multiple myeloma 2016 (EU)
2015 (US)
Empliciti (elotuzumab) humanized IgG1 against the cell surface receptor SLAMF7, produced in NS0 cells. Bristol-Myers Squibb (Dublin & Princeton, NJ, USA) Multiple myeloma (in combination with lenalidomide and dexamethasone) 2016 (EU)
2015 (US)
Flixabi (infliximab), chimeric IgG1 against TNF-α, produced in CHO cells. Biosimilar to Remicade. Same product as Renflexis (see above). Samsung Bioepis (Delft, the Netherlands) Various forms of arthritis, psoriasis, colitis, Crohn’s disease, ankylosing spondylitis 2016 (EU)
Inflectra (EU & US), Remsima (EU) (infliximab (EU), infliximab-dyyb (US)), chimeric IgG1 specific for TNF-α, produced in murine Sp2/0 cells. Biosimilar to Remicade. Inflectra: Hospira (Lake Forest, IL, USA)
Pfizer (Brussels)
Remsima: Celltrion (Budapest)
Certain forms of arthritis and psoriasis, Crohn’s disease, ulcerative colitis, ankylosing spondylitis 2016 (US)
2013 (EU)
Lartruvo (olaratumab), rh IgG1 specific for human platelet-derived growth factor receptor-α, produced in NS0 cells. Eli Lilly (Utrecht, the Netherlands, & Indianapolis) Sarcoma 2016 (EU & US)
Withdrawn 2019
Portrazza (necitumumab), human IgG1 against the ligand-binding site of human EGF receptor, produced in NS0 cells. Eli Lilly (Utrecht, the Netherlands, & Indianapolis) Non-small-cell lung cancer (in combination with gemcitabine and cisplatin) 2016 (EU)
2015 (US)
Withdrawn 2021 (EU)
Taltz (ixekizumab), humanized IgG4 against hIL-17A, produced in CHO cells. Eli Lilly (Utrecht, the Netherlands, & Indianapolis) Psoriasis 2016 (EU & US)
Zinbryta (daclizumab), humanized IgG1 against IL-2Rα, produced in NS0 cells. Biogen (Cambridge, MA, US)
Biogen Idec (Maidenhead, UK)
Multiple sclerosis 2016 (EU & US)
Withdrawn 2018
Blincyto (blinatumomab), bispecific T cell engager antibody construct (BiTE), produced in CHO cells. Amgen Europe
Amgen (Thousand Oaks, CA, USA)
Acute lymphoblastic leukemia 2015 (EU)
2014 (US)
Cosentyx (secukinumab), human IgG1 selectively binding human IL-17a, produced in CHO cells. Novartis (Dublin)
Novartis (East Hanover, NJ, USA)
Moderate to severe plaque psoriasis in adults 2015 (EU & US)
Keytruda (pembrolizumab), humanized IgG4 capable of binding to the receptor PD-1, produced in CHO cells. Merck Sharp & Dohme
Merck (Whitehouse Station, NJ, USA)
Advanced (unresectable or metastatic) melanoma in adults 2015 (EU)
2014 (US)
Nivolumab BMS (nivolumab), human IgG4 against the receptor PD-1, produced in CHO cells. Same product as Opdivo (see below). Bristol-Myers Squibb (Uxbridge, UK) Locally advanced or metastatic squamous non-small-cell lung cancer after prior chemotherapy in adults July 2015 (EU)
Withdrawn November 2015
Nucala (mepolizumab), humanized IgG1 capable of binding human IL-5, produced in CHO cells. GlaxoSmithKline (Cork, Ireland)
GSK (Research Triangle Park, NC, USA)
Add-on treatment for severe refractory eosinophilic asthma in adult patients 2015 (EU & US)
Opdivo (nivolumab), human IgG4 against the receptor PD-1, produced in CHO cells. Same product as nivolumab BMS (see above). Bristol-Myers Squibb (Dublin, & Princeton, NJ, USA) Melanoma (as monotherapy or in combination with ipilimumab), non-small-cell lung cancer, renal cell carcinoma 2015 (EU)
2014 (US)
Praluent (alirocumab), human IgG1 targeting PCSK9, produced in CHO cells Sanofi-Aventis (Paris & Bridgewater, NJ, USA)
Regeneron Pharmaceuticals (Tarrytown, NY, USA)
Primary hypercholesterolemia or mixed dyslipidemia, as an adjunct to diet 2015 (EU & US)
Praxbind (idarucizumab), humanized IgG1 Fab fragment capable of binding the anticoagulant drug dabigatran, produced in CHO cells. Boehringer Ingelheim (Rhein, Germany, & Ridgefield, CT, USA) Rapid reversal agent for the anticoagulant drug dabigatran 2015 (EU & US)
Repatha (evolocumab), human IgG2 capable of binding human PCSK-9, produced in CHO cells. Amgen Europe
Amgen (Thousand Oaks, CA, USA)
Hypercholesterolemia and mixed dyslipidemia 2015 (EU & US)
Unituxin (dinutuximab), chimeric IgG1 targeting human disialoganglioside (GD2), produced in Sp2/0 cells United Therapeutics Chertsey (Surrey, UK, & Silver Spring, MD, USA) Neuroblastoma (administered in combination with GM-CSF, IL-2 and isotretinoin) 2015 (EU & US)
Withdrawn 2017 (EU)
Cyramza (ramucirumab), human mAb that binds the VEGF-2 receptor, produced in NS0 cells. Eli Lilly Nederland (Utrecht, the Netherlands)
Eli Lilly (Indianapolis)
Gastric cancer 2014 (EU & US)
Entyvio (vedolizumab), humanized IgG targeting the human α4β7 integrin, produced in CHO cells. Takeda Pharmaceuticals (Deerfield, IL, USA)
Takeda Pharma (Taastrup, Denmark)
Ulcerative colitis, Crohn’s disease 2014 (EU & US)
Gazyva (US), Gazyvaro (EU) (obinutuzumab), humanized, glycoengineered mAb specific for B cell antigen CD20, produced in CHO cells. Roche/Genentech CLL 2014 (EU)
2013 (US)
Sylvant (siltuximab), chimeric mAb that binds human IL-6, produced in CHO cells. Janssen Biotech Multicentric Castleman disease 2014 (EU & US)
Kadcyla (trastuzumab emtansine), humanized mAb specific for HER2 antigen, produced in CHO cells and conjugated to the small-molecule cytotoxin DM1. Roche Breast cancer 2013 (EU & US)
Simponi Aria (golimumab). Active substance same as that in Simponi (see below); different strength and mode of administration. Janssen Biotech Rheumatoid arthritis 2013 (US)
Perjeta (pertuzumab), human mAb specific for HER2, produced in CHO cells. Roche/Genentech Breast cancer 2013 (EU)
2012 (US)
Abthrax (raxibacumab), human IgG mAb against the protective antigen (PA) of B. anthracis, produced in NS0 cells. GSK/Human Genome Sciences (Rockville, MD, USA) Inhalational anthrax 2012 (US)
Adcetris (brentuximab vedotin), chimeric mAb conjugate specific for human CD30 (expressed on the surface of lymphoma cells), produced in CHO cells. Takeda Pharma (Roskilde, Denmark)
Seattle Genetics
Lymphoma 2012 (EU)
2011 (US)
Benlysta (belimumab), human mAb that targets human B-lymphocyte stimulator (BLyS), a B cell survival factor. Produced in NS0 cells. Human Genome Sciences, GSK (Dublin) Lupus 2011 (EU & US)
Xgeva (denosumab) (see Prolia). Amgen Europe Bone loss associated with cancer 2011 (EU)
2010 (US)
Yervoy (ipilimumab), human mAb binding to CTLA-4 (a negative regulator of T cell activation), thereby enhancing T cell activation and proliferation, produced in CHO cells. Bristol-Myers Squibb (Dublin)
Bristol-Myers Squibb (Princeton, NJ, USA)
Melanoma 2011 (EU & US)
Actemra (US), RoActemra (EU) (tocilizumab), humanized mAb specific for IL-6, produced in a mammalian cell line. Roche (Grenzach-Wyhlen Germany)
Genentech (South San Francisco, CA, USA)
Rheumatoid arthritis 2010 (US)
2009 (EU)
Arzerra (ofatumumab), human mAb specific for CD20, produced in NS0 hybridoma cells. Novartis, Genmab (Greenford, UK) CLL 2010 (EU)
2009 (US)
Withdrawn 2019 (EU)
Prolia (denosumab), human mAb specific for receptor activator of nuclear factor-κB ligand (RANKL), produced in CHO cells. Amgen Osteoporosis in postmenopausal women 2010 (EU & US)
Scintimun (besilesomab), murine mAb against nonspecific cross-reacting antigen-95 (found on surface of granulocytes), produced in hybridoma cells. CIS Bio International (Gif-sur-Yvette, France) In vivo diagnosis or investigation of sites of inflammation or infection via scintigraphic imaging 2010 (EU)
Cimzia (certolizumab pegol), anti-TNF-α humanized antibody Fab′ fragment, produced in E. coli and PEGylated. UCB Pharma (Brussels)
UCB (Smyrna, GA, USA)
Crohn’s disease, rheumatoid arthritis 2009 (EU)
2008 (US)
Ilaris (canakinumab), human mAb specific for IL-1β, produced in Sp2/0 cells. Novartis Pharmaceuticals (East Hanover, New Jersey, USA)
Novartis Europharm (Dublin)
Cryopyrin-associated periodic syndromes (CAPS) 2009 (EU & US)
Removab (catumaxomab), bispecific engineered antibody targeting the human epithelial cell adhesion molecule (EpCAM) and human CD3 expressed on T lymphocytes, respectively, produced in hybridoma cells. Neovii Biotech (Gräfelfing, Germany) Malignant ascites in patients with carcinomas expressing epithelial cell adhesion molecule 2009 (EU)
Withdrawn 2017
Simponi (golimumab), human mAb specific for TNF-α, produced in Sp2/0 cells. Janssen Biologics (Leiden, the Netherlands)
Janssen Biotech (Horsham, PA, USA)
Rheumatoid arthritis, psoriatic arthritis, ankylosing spondylitis 2009 (EU & US)
Stelara (ustekinumab), human MAb specific for the p40 subunit of IL-12 and IL-23, produced in Sp2/0 cells. Janssen-Cilag Moderate to severe plaque psoriasis 2009 (EU & US)
Lucentis (ranibizumab), humanized IgG fragment that binds and inactivates VEGF-A, produced in E. coli. Novartis (Dublin)
Genentech
Neovascular (wet) age-related macular degeneration 2007 (EU)
2006 (US)
Soliris (eculizumab), humanized IgG that binds human C5 complement protein, produced in a murine myeloma cell line. Alexion Pharmaceuticals (Cheshire, CT, USA, & Paris) Paroxysmal nocturnal hemoglobinuria 2007 (EU & US)
Vectibix (panitumumab), human mAb that binds human EGF receptor, produced in CHO cells. Amgen EGF-receptor-expressing colorectal carcinoma 2007 (EU)
2006 (US)
Tysabri (natalizumab), humanized mAb against selected leukocyte integrins, produced in murine myeloma cells. Biogen (Cambridge, MA, USA)
Biogen Netherlands (Badhoevedorp, the Netherlands)
Relapsing forms of multiple sclerosis 2006 (EU) 2004 (US)
Suspended 2005 (US)
Resumed 2006 (US)
Xolair (omalizumab), humanized mAb that binds IgE at the site of high-affinity IgE receptor binding, produced in CHO cells. Roche/Genentech Moderate to severe persistent asthma in adults and adolescents 2005 (EU)
2003 (US)
Zevalin (ibritumomab tiuxetan), murine mAb against the CD20 antigen, produced in CHO cells. Ceft Biopharma (Prague)
Spectrum Pharmaceuticals (Irvine, CA, USA)
Non-Hodgkin’s lymphoma 2004 (EU)
2002 (US)
Erbitux (cetuximab), chimeric mAb against human EGF receptor, produced in Sp2/0 cells. Merck (Amsterdam)
Eli Lilly (Indianapolis)
EGF-receptor-expressing metastatic colorectal cancer 2004 (EU & US)
Raptiva (efalizumab), humanized mAb that binds LFA-1, which is expressed on all leukocytes; produced in CHO cells. Serono (London, UK)
Genentech
Chronic moderate to severe plaque psoriasis in adults 2004 (EU)
2003 (US)
Withdrawn 2009
Avastin (bevacizumab), humanized mAb against VEGF, produced in CHO cells. Roche/Genentech Metastatic colorectal cancer, glioblastoma, metastatic renal carcinoma 2005 (EU)
2004 (US)
NeutroSpec (fanolesomab), murine mAb against CD15, a surface antigen of selected leukocytes, produced in hybridoma cells. Palatin Technologies (Cranbury, NJ, USA), Mallinckrodt Pharmaceuticals (Hazelwood, MO, USA) Imaging of equivocal appendicitis 2004 (US)
Withdrawn 2005
Humira (EU & US), Trudexa (EU) (adalimumab), anti-TNF human mAb, produced in CHO cells. AbbVie (Maidenhead, UK) Rheumatoid arthritis 2003 (EU)
2002 (US)
Trudexa withdrawn 2007 (EU)
Bexxar (tositumomab), radiolabeled mAb against CD20, produced in murine hybridoma cells. GSK CD20-positive follicular non-Hodgkin’s lymphoma 2003 (US)
Withdrawn 2014
Mabcampath (EU), Campath (US) (alemtuzumab), humanized mAb against CD52, a surface antigen of B lymphocytes, produced in CHO cells. Genzyme (Naarden, the Netherlands)
Millennium (Cambridge, MA, USA)
CLL 2001 (EU & US)
Withdrawn 2012 (EU)
Mylotarg (gemtuzumab zogamicin), a humanized antibody–toxic antibiotic conjugate targeted against the CD33 antigen found on leukemic blast cells, produced in NS0 cells. Wyeth (Madison, NJ, USA) Acute myeloid leukemia 2000 (US)
Withdrawn 2010
Reintroduced in 2017
Herceptin (trastuzumab), humanized mAb against HER2, produced in a murine cell line. Roche (Grenzach-Wyhlen, Germany) Treatment of metastatic breast cancer overexpressing HER2 protein 2000 (EU)
1998 (US)
Remicade (infliximab), chimeric mAb against TNF-α, produced in Sp2/0 cells. Janssen (Leiden, the Netherlands) Crohn’s disease 1999 (EU)
1998 (US)
Synagis (palivizumab) humanized mAb directed against an epitope on the surface of respiratory syncytial virus, produced in a murine myeloma cell line AstraZeneca (Sodertalje, Sweden) Prophylaxis of lower respiratory tract disease caused by syncytial virus in children 1999 (EU)
1998 (US)
Zenapax (daclizumab), humanized mAb against the IL-2 receptor α-chain, produced in NS0 cells. Roche (Welwyn Garden City, UK)
Biogen (Cambridge, MA, USA)
Prevention of acute kidney transplant rejection 1999 (EU)
1997 (US)
Withdrawn 2009 (EU)
Humaspect (votumumab), human mAb against cytokeratin tumor-associated antigen, produced in a human lymphoblastoid cell line. KS Biomedix (Farnham, UK) Detection of carcinoma of the colon or rectum 1998 (EU)
Withdrawn 2004
MabThera (EU), Rituxan (US) (rituximab), chimeric mAb against CD20 surface antigen of B lymphocytes, produced in CHO cells. Genentech/Roche Non-Hodgkin’s lymphoma 1998 (EU)
1997 (US)
Simulect (basiliximab), chimeric mAb directed against the α-chain of the IL-2 receptor, produced in a murine myeloma cell line. Novartis (Dublin) Prophylaxis of acute organ rejection in allogeneic renal transplantation 1998 (EU)
LeukoScan (sulesomab), murine mAb Fab fragment against granulocyte surface nonspecific cross-reacting antigen-90, produced in Sp2/0 cells. Immunomedics (Darmstadt, Germany) Diagnostic imaging for infection and inflammation in bone of patients with osteomyelitis 1997 (EU)
Withdrawn 2018
Verluma (nofetumomab), murine mAb Fab fragment directed against carcinoma-associated antigen, produced in a murine cell line. Boehringer Ingelheim, NeoRx (Seattle) Detection of small-cell lung cancer 1996 (US)
Withdrawn 1999
Tecnemab KI (anti-melanoma mAb fragments), murine mAb fragments (Fab/Fab2 mix) against HMW-MAA, produced in murine ascites culture. Amersham Sorin (Milan) Diagnosis of cutaneous melanoma lesions 1996 (EU)
Withdrawn 2000
ProstaScint (capromab pentetate), murine mAb against the tumor surface antigen PSMA, produced in a murine cell line. EUSA Pharma (Langhorne, PA, USA) Detection, staging and follow-up of prostate adenocarcinoma 1996 (US)
Discontinued 2018
MyoScint (imiciromab pentetate), murine mAb fragment directed against human cardiac myosin, produced in a murine cell line. Centocor Myocardial infarction imaging 1996 (US)
Withdrawn 1999
CEA-scan (arcitumomab), murine mAb Fab fragment against human carcinoembryonic antigen (CEA), produced in mouse ascites. Immunomedics Detection of recurrent or metastatic colorectal cancer 1996 (EU & US)
Withdrawn 2005 (EU & US)
Indimacis 125 (igovomab), murine mAb Fab2 fragment against the tumor-associated antigen CA125, produced in a murine cell line. CIS Bio (Gif-sur-Yvette, France) Diagnosis of ovarian adenocarcinoma 1996 (EU)
Withdrawn 2009
ReoPro (abciximab), Fab fragments derived from a chimeric mAb against the platelet surface receptor GPIIb/III, produced in a mammalian cell line. Janssen Biologics (Leiden, the Netherlands)
Centocor
Prevention of blood clots 1994 (US)
Withdrawn 2019
OncoScint CR/OV (satumomab pendetide), murine mAb against the tumor-associated glycoprotein TAG-72, produced in a murine cell line. Cytogen (Princeton, NJ, USA) Detection, staging and follow-up of colorectal and ovarian cancers 1992 (US)
Withdrawn 2002
Orthoclone OKT3 (muromomab CD3), murine mAb against the T-lymphocyte surface antigen CD3, produced in a murine cell line. Centocor Ortho Biotech Products (Raritan, NJ, USA) Reversal of acute kidney transplant rejection 1986 (US)
Withdrawn 2010
Other recombinant products
Bone morphogenetic proteins
Opgenra (eptotermin alfa), rh BMP-7, produced in CHO cells Olympus Biotech (Limerick, Ireland) Posterolateral lumbar spinal fusion 2009 (EU)
Withdrawn 2016
Infuse bone graft, containing dibotermin alfa, a rh BMP-2 produced in CHO cells, placed on an absorbable collagen sponge. Active substance same as that in Infuse (see below). Wyeth (Madison, NJ, USA) Acute open tibial shaft fracture 2004 (US)
Inductos (dibotermin alfa), rh BMP-2, produced in CHO cells. Medtronic BioPharma (Heerlen, the Netherlands) Acute tibia fractures 2002 (EU)
Infuse (rh BMP2), produced in CHO cells. Medtronic Sofamor Danek (Memphis, TN, USA) Promotes fusion of lower spine vertebrae 2002 (US)
OP-1 implant (US), Osigraft (EU) (eptotermin alfa), rh BMP-7, produced in CHO cells. Olympus Biotech (Limerick, Ireland)
Stryker Biotech (Hopkinton, MA, USA)
Non-union of tibia 2001 (EU & US)
Withdrawn 2015 (EU)
Recombinant enzymes
Voraxaze (glucarpidase), Pseudomonas-derived exopeptidase enzyme capable of hydrolyzing the carboxy terminal glutamate residue from folic acid and its analogs, including methotrexate (MTX); produced recombinantly in E. coli. SERB SAS (Paris)
BTG International (West Conshohocken, PA, USA)
Reduce toxic plasma methotrexate concentrations 2022 (EU)
2012 (US)
Nexviazyme (avalglucosidase alfa-ngpt), rh α-glucosidase produced in a CHO cell line, conjugated with multiple synthetic bis-mannose-6-phosphate (bis-M6P)-tetra-mannose glycans. Genzyme (Cambridge, MA, USA) Late-onset Pompe disease 2021 (US)
Rylaze (asparaginase erwinia chrysanthemi (recombinant)-rywn), Erwinia chrystanthemi-derived asparaginase, produced recombinantly in P. fluorescens. Jazz Pharmaceuticals (Palo Alto, CA, USA) Acute lymphoblastic leukemia and lymphoblastic lymphoma 2021 (US)
Idefirix (imlifidase; r Streptococcus pyogenes–derived protease that degrades IgG in the lower hinge region, produced in E. coli. Hansa Biopharma (Lund, Sweden) Preventing kidney transplant rejection 2020 (EU)
Palynziq (pegvaliase (EU), pegvaliase-pqpz (US)), r phenylalanine ammonia lyase derived from the cyanobacterium Anabaena variabilis, produced in E. coli and PEGylated. BioMarin International (Cork, Ireland)
BioMarin (Novato, CA, USA)
Phenylketonuria 2019 (EU)
2018 (US)
Lamzede (velmanase alfa), rh α-mannosidase, expressed in precursor form in CHO cells. Chiesi Farmaceutici (Parma, Italy) α-mannosidosis 2018 (EU)
Mepsevii (vestronidase alfa-vjbk (US), vestronidase alfa (EU)), r human lysosomal β-glucuronidase, produced in CHO cells. Ultragenyx Germany (Berlin)
Ultragenyx Pharmaceutical (Novato, CA, USA)
Mucopolysaccharidosis VII 2018 (EU)
2017 (US)
Revcovi (elapegademase-lvlr), PEG-conjugated r bovine adenosine deaminase, produced in E. coli. Leadiant Biosciences (Gaithersburg, MD, USA) Adenosine deaminase severe combined immune deficiency (ADA-SCID) 2018 (US)
Brineura (cerliponase alfa), rh serine tripeptidyl peptidase-1, expressed in proenzyme form in CHO cells. BioMarin (Cork, Ireland)
BioMarin
CLN2 disease (tripeptidyl peptidase-1 deficiency) 2017 (EU & US)
Oncaspar (pegaspargase), r asparaginase, produced in E. coli and conjugated to monomethoxypropylene glycol. Les Laboratoires Servier (Suresnes, France) Lymphoblastic leukemia, lymphoma 2016 (EU)
Spectrila (asparaginase), r asparaginase, produced in E. coli. Medac Gesellschaft für klinische Spezialpräparate (Wedel, Germany) Lymphoblastic leukemia, lymphoma 2016 (EU)
Kanuma (sebelipase alfa), rh lysosomal acid lipase, produced in the eggs of transgenic chickens.Alexion Europe (Rueil-Malmaison, France), Alexion Pharmaceuticals (Cheshire, CT, USA) Enzyme replacement therapy in patients with lysosomal acid lipase deficiency 2015 (EU & US)
Strensiq (asfotase alfa), dimeric fusion protein containing a soluble catalytic domain of human tissue-nonspecific alkaline phosphatase linked to an IgG Fc domain and a deca-aspartate peptide domain, produced in CHO cells. Alexion Europe (Rueil-Malmaison, France)
Alexion (Cheshire, CT, USA)
Enzyme replacement therapy in patients with pediatric-onset hypophosphatasia 2015 (EU & US)
Vimizim (elosulfase alfa), rh N-acetlygalactosamine-6-sulfatase, produced in CHO cells. BioMarin (Cork, Ireland) Mucopolysaccharidosis IVA (Morquio A syndrome) 2014 (EU & US)
Krystexxa (pegloticase), r urate oxidase, produced in E. coli and PEGylated. Savient Pharma (Dublin)
Crealta Pharmaceuticals (Lake Forest, IL, USA)
Gout 2013 (EU)
2010 (US)
Withdrawn 2016 (EU)
Elelyso (taliglucerase alfa), rh glucocerebrosidase, produced in engineered carrot root cell culture. Pfizer (New York, NY, USA) Gaucher disease 2012 (US)
Lumizyme (alglucosidase alfa), rh acid-α-glucosidase, produced in CHO cells. Sanofi Genzyme Pompe disease (glycogen storage disease type II) 2010 (US)
VPRIV (velaglucerase alfa), rh glucocerebrosidase, produced in a human fibroblast cell line. Shire (Dublin)
Shire (Cambridge, MA USA)
Gaucher disease 2010 (EU & US)
Elaprase (idursulfase), rh iduronate-2-sulfatase, produced in a human cell line. Shire Mucopolysaccharidosis II (Hunter syndrome) 2007 (EU)
2006 (US
Naglazyme (galsulfase), rh N-acetylgalactosamine-4-sulfatase, produced in CHO cells. BioMarin (Cork, Ireland & Novato, CA, USA) Long-term enzyme replacement therapy in mucopolysaccharidosis VI 2006 (EU)
2005 (US)
Myozyme (algulcosidase alfa), rh acid glucosidase, produced in CHO cells. Genzyme (Amsterdam) Pompe disease 2006 (EU & US)
Discontinued 2014 (US)
Aldurazyme (laronidase), r α-l-iduronidase, produced in CHO cells. Genzyme (Amsterdam) Long-term replacement in mucopolysaccharidosis I 2003 (EU & US)
Hylenex (hyaluronidase), rh hyaluronidase, produced in CHO cells. Halozyme Therapeutics (San Diego) Adjuvant to increase absorption and dispersion of other drugs 2005 (US)
Fabrazyme (agalsidase beta), rh α-galactosidase, produced in CHO cells. Genzyme Fabry disease (α-galactosidase A deficiency) 2003 (US)
2001 (EU)
Replagal (agalsidase alfa), rh α-galactosidase, produced in a human cell line. Takeda (Dublin) Fabry disease (α-galactosidase A deficiency) 2001 (EU)
Fasturtec (EU), Elitek (US) (rasburicase), r urate oxidase, produced in S. cerevisiae. Sanofi (Paris) Hyperuricemia 2002 (US)
2001 (EU)
Cerezyme (imiglucerase), rh β-glucocerebrosidase, produced in CHO cells. Genzyme Gaucher disease 1997 (EU)
1994 (US)
Pulmozyme (dornase alpha), r DNase, produced in CHO cells. Roche/Genentech Cystic fibrosis 1993 (US)
Fusion proteins
Kimmtrak (tebentafusp-tebn (US), tebentafusp (EU)); bispecific T cell engager fusion protein, produced in E. coli. Immunocore (Dublin; EU)
Immunocore (Conshohocken, PA, USA; US)
Uveal melanoma (type of eye cancer) 2022 (EU & US)
Ngenla (somatrogon), r chimeric fusion protein of hGH with one copy of the C-terminal peptide (CTP) from the β-chain of human chorionic gonadotropin at the N-terminus and two copies of CTP at the C-terminus, produced in CHO cells. Pfizer Europe MA EEIG (Brussels) Growth disturbances due to growth hormone deficiency 2022 (EU)
Elzonris (tagraxofusp-erzs (US), tagraxofusp (EU)), rh IL-3–truncated diphtheria toxin fusion protein, produced in E. coli. Stemline Therapeutics (Amsterdam)
Stemline Therapeutics (New York)
Blastic plasmacytoid dendritic cell neoplasm 2021 (EU)
2018 (US)
Lumoxiti (moxetumomab pasudotox (EU), moxetumomab pasudotox-tdfk (US)), r-immunotoxin fusion protein consisting of an Ig light-chain variable domain (VL) and heavy-chain variable domain (VH) genetically fused to a truncated form of Pseudomonas exotoxin, targeting CD22 cell surface receptors, produced in E. coli. AstraZeneca (Sodertalje, Sweden)
AstraZeneca Pharmaceuticals (Wilmington, DE, USA)
Hairy cell leukemia 2021 (EU)
2018 (US)
Withdrawn 2021 (EU)
Nepexto (etanercept), r dimeric protein comprising 2 soluble p75 TNFR molecules fused to the human IgG1 Fc fragment, produced in a CHO cell line. Biosimilar to Enbrel. Mylan (Dublin) Various inflammatory conditions 2020 (EU)
Reblozyl (luspatercept (EU), luspatercept-aamt (US)), r-fusion protein consisting of two modified extracellular domains of human activin receptor type IIB (ActRIIB) linked to the human IgG1 Fc domain. Binds selectively to transforming growth factor-beta (TGF-β) superfamily ligands; produced in CHO cell line. Bristol Myers Squibb Pharma EEIG (Dublin)
Celgene (Summit, NJ, USA) & Acceleron Pharma, (Cambridge, MA, USA))
Certain (rare) forms of anemia 2020 (EU)
2019 (US)
Benepali (etanercept, EU), Eticovo (etanercept-ykro, US)), rh TNF receptor–IgG Fc fusion protein, produced in CHO cells. Biosimilar to Enbrel. Samsung Bioepis (Delft, the Netherlands)
Samsung Bioepis
Arthritis, psoriasis, axial spondyloarthritis 2019 (US)
2016 (EU)
Erelzi (etanercept (EU), etanercept-szzs (US)), r dimeric fusion protein consisting of TNF receptor extracellular domains linked to an IgG1 Fc region, produced in CHO cells. Biosimilar to Enbrel. Sandoz (Kundl, Austria, & Princeton, NJ, USA) Rheumatoid arthritis, selected other inflammatory diseases 2017 (EU)
2016 (US)
Lifmior (etanercept), r dimeric fusion protein consisting of TNF receptor extracellular domains linked to an IgG1 Fc region, produced in CHO cells. Same product as Enbrel (see below). Pfizer Europe MA EEIG (Brussels) Rheumatoid arthritis, selected other inflammatory diseases 2017 (EU)
Withdrawn 2020
Zaltrap (aflibercept), combination drug comprising binding domains of VEGF receptors 1 and 2 fused to an IgG Fc, produced in CHO cells. Same active substance as in Eylea (see below). Sanofi (Paris)
Sanofi-Aventis US (Bridgewater, NJ, USA)
Metastatic colorectal cancer 2013 (EU)
2012 (US)
Eylea (aflibercept), fusion protein comprising extracellular ligand-binding domains of VEGF receptor fused to IgG Fc, produced in CHO cells. Same active substance as in Zaltrap (see above). Regeneron Pharmaceuticals (Tarrytown, NY, USA)
Bayer (Berlin)
Neovascular (wet) age-related macular degeneration 2012 (EU)
2011 (US)
Nulojix (belatacept), fusion protein comprising extracellular domain of human CTLA4 fused to IgG Fc, which binds CD80 and CD86 on antigen-presenting cells, thereby inhibiting T cell activation; produced in CHO cells. Bristol-Myers Squibb (Dublin) Prophylaxis of organ rejection following kidney transplant 2011 (EU & US)
Arcalyst (US), Rilonacept Regeneron (EU) (rilonacept), dimeric fusion protein with each monomer consisting of the ligand-binding domains of the human IL-1 receptor and IL-1 receptor accessory protein along with the Fc region of human IgG-1, produced in CHO cells. Regeneron Pharmaceuticals Cryopyrin-associated periodic syndromes (CAPS) 2009 (EU)
2008 (US)
Withdrawn 2012 (EU)
Nplate (romiplostim), dimeric fusion protein with each monomer consisting of two thrombopoietin RBDs and the Fc region of human IgG-1, produced in E. coli. Amgen Europe Thrombocytopenia 2009 (EU)
2008 (US)
Orencia (abatacept), fusion protein that links the extracellular domain of human cytotoxic-T-lymphocyte-associated antigen-4 with modified Fc region of IgG1, produced in a mammalian cell line. Bristol-Myers Squibb Rheumatoid arthritis 2007 (EU)
2005 (US)
Amevive (alefacept), dimeric fusion protein comprising the extracellular CD2-binding portion of human LFA-3 linked to the Fc region of human IgG1, produced in CHO cells. Astellas Pharma (Deerfield, IL, USA) Moderate to severe chronic plaque psoriasis in adults 2003 (US)
Withdrawn 2011
Enbrel (etanercept), r TNF receptor–IgG fragment fusion protein, produced in CHO cells. Same product as Lifmior (see above). Amgen (Thousand Oaks, CA)
Pfizer (Brussels)
Rheumatoid arthritis 2000 (EU)
1998 (US)
Ontak (denileukin diftitox), r IL-2–diphtheria toxin fusion protein that targets cells displaying a surface IL-2 receptor, produced in E. coli. Eisai (Tokyo)
Ligand Pharmaceuticals (San Diego)
Cutaneous T cell lymphoma 1999 (US)
Discontinued 2014
Gene-therapy and nucleic acid-based products (nucleic acid-based vaccines are included in the ‘Vaccine’ section)
Amvuttra (vutrisiran), a transthyretin-directed siRNA. Alnylam (Cambridge, MA, USA) Polyneuropathy of hereditary transthyretin-mediated amyloidosis 2022 (US)
Amondys 45 (casimersen), chemically synthesized PMO antisense oligonucleotide. Sarepta Therapeutics (Cambridge, MA, USA) Duchenne muscular dystrophy 2021 (US)
Leqvio (inclisiran), chemically synthesized ds siRNA covalently linked to a triantennary GalNAc, facilitating hepatocyte update. Novartis (Dublin)
Novartis (East Hanover, NJ, USA)
Hypercholesterolemia, mixed dyslipidemia 2021 (US)
2020 (EU)
Givlaari (givosiran), chemically synthesized, chemically modified ds siRNA conjugated to a triantennary GalNAc ligand to facilitate hepatic delivery. Silences aminolevulinate hepatic synthase 1 (ALAS1) mRNA. Alnylam Netherlands (Amsterdam)
Alnylam (Cambridge, MA, USA)
Acute hepatic porphyria 2020 (EU)
2019 (US)
Oxlumo (Lumasiran), chemically synthesized ds siRNA covalently linked to a triantennary GalNAc, facilitating hepatocyte update. Alnylam (Amsterdam)
Alnylam (Cambridge, MA, USA)
Primary hyperoxaluria type 1 2020 (EU & US)
Viltepso (viltolarsen), chemically synthesized PMO antisense oligonucleotide. NS Pharma (Paramus, NJ, USA) Duchenne muscular dystrophy 2020 (US)
Zolgensma (onasemnogene abeparvovec), nonreplicating adeno-associated vector housing the human survival motor neuron gene (SMN1). Novartis Europharm (Dublin)
Novartis Gene Therapies (Bannockburn, IL, USA)
Spinal muscular atrophy 2020 (EU)
2019 (US)
Viondys 53 (golodirsen), chemically synthesized PMO antisense oligonucleotide. Sarepta Therapeutics (Cambridge, MA, USA) Duchenne muscular dystrophy 2019 (US)
Waylivra (volanesorsen), synthetic antisense PTO oligonucleotide. Akcea Therapeutics (Dublin) Familial chylomicronemia syndrome 2019 (EU)
Luxturna (voretigene neparvovec-rzyl (US), voretigene neparvovec (EU)), a live, nonreplicating adeno-associated virus genetically modified to express the human RPE65 gene. Novartis (Dublin)
Spark Therapeutics (Philadelphia)
Retinal dystrophy 2018 (EU)
2017 (US)
Onpattro (patisiran), chemically synthesized, 21-nucleotide ds siRNA oligonucleotide, formulated as lipid nanoparticles. Alnylam (Amsterdam)
Alnylam Pharmaceuticals (San Diego)
Hereditary transthyretin amyloidosis 2018 (EU & US)
Tegsedi (inotersen), a 20-nucleotide ss oligonucleotide manufactured by direct chemical synthesis. Akcea (Dublin)
Ionis Pharmaceuticals (Carlsbad, CA, USA)
Hereditary transthyretin amyloidosis 2018 (EU & US)
Spinraza (nusinersen sodium), an 18-nucleotide antisense oligonucleotide manufactured by direct chemical synthesis. Biogen (Badhoevedorp, the Netherlands)
Biogen (Cambridge, MA, USA)
Spinal muscular atrophy 2017 (EU)
2016 (US)
Exondys 51 (eteplirsen), a chemically synthesized antisense oligonucleotide. Sarepta Therapeutics (Cambridge, MA, USA) Duchenne muscular dystrophy 2016 (US)
Imlygic (talimogene laherparepvec), an engineered herpes simplex virus type 1 capable of producing GM-CSF. Amgen Melanoma 2015 (EU & US)
Kynamro (mipomersen sodium), a chemically synthesized antisense oligonucleotide. Kastle Therapeutics (Chicago) Familial hypercholesterolemia 2013 (US)
Discontinued 2022
Glybera (alipogene tiparvovec), a human LPL gene housed in an engineered adeno-associated virus 1 vector. uniQure (Amsterdam) Lipoprotein lipase deficiency 2012 (EU)
Withdrawn 2017
Macugen (pegaptanib sodium injection), a synthetic PEGylated oligonucleotide that specifically binds VEGF. Eyetech (Palm Beach Gardens, FL, USA)
PharmaSwiss (Prague)
Neovascular, age-related macular degeneration 2006 (EU)
2004 (US)
Withdrawn 2019
Vitravene (fomivirsen), an antisense oligonucleotide. Isis Pharmaceuticals (Carlsbad, CA, USA)
Novartis Ophthalmics Europe (Farnborough, UK)
Cytomegalovirus retinitis in AIDS patients 1999 (EU)
1998 (US)
Withdrawn 2002 (EU), 2005 (US)
Engineered cell-based
Breyanzi (lisocabtagene maraleucel), autologous, purified CD8+ and CD4+ T cells, both engineered to encode an anti-CD19 CAR. Bristol-Myers Squibb (Dublin)
Bristol-Myers Squibb (Bothell, WA, USA)
B cell lymphoma 2022 (EU)
2021 (US)
Carvykti (ciltacabtagene autoleucel), BCMA-directed genetically modified autologous T cell immunotherapy. Janssen Biotech (Raritan, NJ, USA) Multiple myeloma 2022 (US)
Abecma (idecabtagene vicleucel), genetically modified autologous T cells transduced with an anti-BCMA CAR lentiviral vector. Bristol-Myers Squibb (Dublin)
Celgene (Summit, NJ, USA)
Bluebird Bio (Cambridge, MA, USA)
Multiple myeloma 2021 (EU & US)
Skysona (elivaldogene autotemcel), autologous CD34+-cell-enriched population containing hematopoietic stem cells transduced with a lentiviral vector (LVV) encoding ABCD1 cDNA for human adrenoleukodystrophy protein (ALDP). Bluebird Bio (Utrecht, the Netherlands) Early cerebral adrenoleukodystrophy 2021 (EU)
Withdrawn 2021
Libmeldy (atidarsagene autotemcel), autologous CD34+ hematopoietic stem and progenitor cells (HSPCs), transduced with a lentiviral vector housing the arylsulfatase A gene. Orchard Therapeutic (Amsterdam) Metachromatic leukodystrophy 2020 (EU)
Tecartus (brexucabtagene autoleucel), autologous peripheral blood T cells, CD4 and CD8 selected and CD3 and CD28 activated and transduced with retroviral vector expressing anti-CD19 CD28/CD3ζ chimeric antigen receptor. Kite Pharma (Amsterdam)
Kite Pharma (Santa Monica, CA, USA)
Mantle cell lymphoma 2020 (EU & US)
Zynteglo (betibeglogene autotemcel), autologous CD34+-cell-enriched population containing hematopoietic stem cells transduced with a lentiglobin lentiviral vector encoding the β-A-T87Q-globin allele. Bluebird Bio (Utrecht, the Netherlands) β-thalassemia 2019 (EU)
Withdrawn 2022
Kymriah (tisagenlecleucel), autologous T cells genetically modified to encode an anti-CD19 CAR comprising a murine single-chain antibody fragment (scFv) specific for CD19, followed by a CD8 hinge and transmembrane region fused to the intracellular signaling domains for 4-1BB (CD137) and CD3ζ. Novartis (Dublin)
Novartis (East Hanover, NJ, USA)
Acute lymphoblastic leukemia, large B cell lymphoma 2018 (EU)
2017 (US)
Yescarta (axicabtagene ciloleucel), autologous T cells genetically modified to express a CAR comprising a murine anti-CD19 single-chain variable fragment (scFv) linked to CD28 and CD3ζ co-stimulatory domains. Kite Pharma (Amsterdam)
Kite Pharma (Santa Monica, CA, USA)
Large B cell lymphoma 2018 (EU)
2017 (US)
Strimvelis, autologous CD34+ cells transduced with an engineered retroviral vector encoding the human adenosine deaminase sequence. Orchard Therapeutics (Amsterdam) Severe combined immunodeficiency 2016 (EU)
Zalmoxis, allogeneic T cells genetically modified to express the herpes simplex thymidine kinase suicide gene and a truncated form of the human low-affinity nerve growth factor receptor gene. MolMed (Milan) Hematopoietic stem cell transplantation, graft-versus-host disease 2016 (EU)
Withdrawn 2019
Data were collected from several sources (http://www.fda.gov/, https://www.ema.europa.eu/en). Products are listed consecutively from most recent approval in each class, with registrations since 2018 in boldface and withdrawals and discontinuations in italics. r, recombinant; rh, recombinant human. ADC, antibody–drug conjugate; BHK, baby hamster kidney cell line; BMP, bone morphogenetic protein; CAR, chimeric antigen receptor; CGRP, calcitonin gene-related peptide; CHO, Chinese hamster ovary cell line; CLL, chronic lymphocytic leukemia; ds, double-stranded; EGF, epidermal growth factor; EPO, erythropoietin; FSH, follicle stimulating hormone; G-CSF, granulocyte colony-stimulating factor; GalNAc, N-acetylgalactosamine; GLP, glucagon-like peptide; GM-CSF, granulocyte-macrophage colony stimulating factor; HBsAg, hepatitis B surface antigen; HEK, human embryo kidney cell line; HER2, human epidermal growth factor receptor 2; hGH, human growth hormone; HPV, human papillomavirus; IFN, interferon; Ig, immunoglobulin; IGF, insulin-like growth factor; IL, interleukin; mAb, monoclonal antibody; PEG, polyethylene glycol; PTH, parathyroid hormone; RBD, receptor-binding domain; siRNA, small interfering RNA; ss, single-stranded; TNF, tumor necrosis factor; tPA, tissue plasminogen activator; VEGF, vascular endothelial growth factor.
Annual approval numbers over the current survey period ranged from a low of 19 in Europe in 2019 to a high of 42, also in Europe, in 2018 (Fig. 1a). Annual approval rates were sustained or exceeded in both regions in 2020 and 2021, reflecting strong regulatory response, despite the unexpected burden on the agencies caused by the pandemic. Products approved over the current period include 97 monoclonal antibodies, 19 hormones, 16 nucleic acid/gene-therapy-based products and 16 vaccines (the latter two categories overlap as five of the (COVID-19) vaccines are nucleic acid based). Additional notable approval categories include colony-stimulating factors (CSFs; 12 products, all biosimilars), cell-based products (9), enzymes (8), fusion products (7) and clotting factors (6).Fig. 1 Product approvals profile.
a, Annual product approval numbers (by product trade name) by individual region. b, Number of product approvals in one or both regions over the indicated periods.
Here we list all biopharmaceuticals approved from January 2018 to June 2022, examining what types of product reached the US and EU markets as well as the indication for which they were approved. As in previous articles1–4, we have not included tissue-engineering products, which the US Food and Drug Administration (FDA) classifies as medical devices.
In a snapshot
As in previous survey periods, new approvals followed predictable lines. Cancer was by far the most common indication (50 products). Other common indications included inflammation-related conditions (15 products), neutropenia (12 products), COVID-19 (11 products) and diabetes (10 products). Additional indications, less commonly targeted by biopharmaceuticals, included ebolavirus (the vaccines Mvabea, Zabdeno and Ervebo and the therapeutics Ebanga and Inmazeb), anthrax (the inhalation therapeutic Obiltoxaximab SFL), weight control and weight loss (Wegovy) and Alzheimer’s disease (Aduhelm).
Of the 197 biopharmaceutical products approved within the survey timeframe, 90 (46%) were genuinely new to the market, with the remainder representing biosimilars, me-too products and products previously approved elsewhere. Those 90 new products (by trade name) contained a total of 85 distinct active biopharmaceutical ingredients (Table 2). Looking at each region separately, 121 products were licensed in the United States, of which 70 (58%) were genuinely novel; 144 products gained marketing Authorization in the EU, of which 65 (45%) were genuinely novel.Table 2 Biopharmaceuticals approved in the United States and/or EU during the current survey period (January 2018–June 2022) by category
Category Products (by trade name)
Genuinely novel biopharmaceuticals (85 products) Amvuttra, Lunsumio, Ondexxya, Veyvondi, Voxzogo, PreHevbri/Prehevbrio, Nuvaxovid/Novavax COVID-19 Vaccine, Spikevax, Jcovden, Vaxzevria, Comirnaty, Mvabea, Vaxchora, Zabdeno, Dengvaxia, Ervebo, Bebtelovimab, Enjaym, Evusheld, Opdualag, Padcev, Saphnelo, Uplizna, Vabysmo, Vyepti, Adbry, Aduhelm, Bamlanivimab & eteseviman, Enspryng, Evkeeza, Minjuvi/Monjivi, Regkirona, Ronapreve/Regen-cov, Rybrevant, Tezspire, Tivdak, Trodelvy, Vyvgart, Xevudy/Sotrovimab, Zynlonta, Adakveo, Blenrep, Danyelza, Ebanga, Inmazeb, Obiltoxaximab SFL, Polivy, Tepezza, Ajovy, Cablivi, Evenity, Trogarzo, Ultomiris, Aimovig, Crysvita, Emgality, Gamifant, Poteligeo, Takhzyro, Idefirix, Palynziq, Lamzede, Revcovi, Kimmtrak, Ngenla, Elzonris, Lumoxitib, Reblozyl, Amondys 45, Leqvio, Givlaari, Oxlumo, Viltepso, Zolgensma, Viondys 53, Waylivra, Onpattro, Tegsedi, Breyanzi, Carvykti, Abecma, Skysonab, Libmeldy, Tecartus, Zynteglo
Biosimilars (58 products) Inpremzia, Truvelog Mix 30, Kirsty, Rezvoglar, Semglee, Insulin aspart Sanofi, Sondelbay, Livogiva, Qutavinab, Retacrita, Fylnetra, Releuko, Stimufend, Nyvepria, Cegfila, Grasustek, Ziextenzo, Fulphila, Nivestym/Nivestima, Pelgraz, Pelmeg, Udenycab, Alymsys, Abevmy, Byooviz, Hukyndra, Lextemyb, Libmyris, Onbevzi, Oyavas, Yuflyma, Yusimry, Amsparity, Aybintio, Equidacentb, Hulio, Riabni, Ruxience, Zercepac, Abrilada, Avsola, Hadlima, Idacio, Kanjinti, Kromeyab, Ontruzanta, Trazimera, Zirabev, Halimatozb, Hefiya, Herzuma, Hyrimoz, Mvasia, Ogivria, Truximaa, Zessly, Nepexto, Benepalia
‘Me-too’ or incremental improvement on existing API: for example, reformulation, PEGylation, use in combination, different indication & related (31 products) Esperoct, Adynovi, Jivi, Sevenfact, Lyumjev, Myxredlin, Lonapegsomatropin Ascendis Pharma, Skytrofa, Sogroya, Wegovy, Besremi, Heplisav B, Vaxelis, Vaxneuvance, Supemtek, Bimzelx, Enhertu, Jemperli, Kesimpta, Susvimo, Beovu, Margenza, Phesgo, Darzalex Faspro, Sarclisa, Herceptin Hylecta, Libtayo, Skyrizi, Ilumya/Ilumetri, Nexviazyme, Rylaze
Previously approved elsewhere1 (15 products) Rybelsus, Myalepta/Myalept, Ozempic, Oxervate, Shingrix, Fasenra, Hemlibra, Imfinzi, Mylotarg, Ocrevus, Voraxaze, Mepsevii, Luxturna, Kymriah, Yescarta
aBiosimilars approved in one region since 2018, but that were approved in the other region before 2018.
bProducts that were both approved and subsequently withdrawn from one or both regions within the survey timeframe.
In the same period, US regulators approved in total 244 non-biological pharmaceutical products containing novel molecular (chemical and biopharmaceutical) entities (NME); thus, 29% (70/244) of all genuinely novel drug approvals in the US were biopharmaceuticals. This compares to 40% for the previous survey period and 21–26% in survey periods before 2014. EU reporting formats for pharmaceuticals preclude calculation of an analogous figure for Europe.
Overall trends
Comparing approvals over the current survey period to those in earlier periods or to cumulative approvals confirms some interesting, if predictable, trends.
Since 2015, the rise in biopharmaceutical approval rates has been sustained. Between 2015 and 2019, 178 products gained approval, approximately three times the historical five-year approval average (Fig. 1b). Moreover, a further 117 products were approved in just the past year and a half, from January 2020 to June 2022. Contributing to this was a substantial increase in the numbers of both biosimilar and ‘me-too’-type products (Table 2) gaining approval in recent years. Although the absolute number of genuinely new biopharmaceutical entities also continued to increase (74 for the 2014–2018 survey, 85 for the current 2018–2022 period), as a proportion of total biopharmaceutical approvals the number of novel biopharmaceuticals has decreased over this period, to 45% (85/189) as compared to the previous period’s 56%.
Monoclonal antibodies stay strong
Monoclonal antibodies (mAbs) remain dominant in overall approvals, representing 53.5% of all approvals in the past four years (Fig. 2a) They also remain the most prominent category of genuinely new biopharmaceuticals coming on the market, constituting 51% of all genuinely new products approved in this survey period (Table 2) compared to 49% in the previous survey period (2014–2018).Fig. 2 Monoclonal antibody statistics.
a, mAbs approved for the first time within the indicated periods, expressed as a percentage of total biopharmaceuticals approved for the first time within the same time period. b, Global annual mAb sales value, expressed as a percentage of total protein-based biopharmaceutical global sales for the indicated years. Financial data from LaMerie Business Intelligence.
The importance of mAbs to biopharmaceutical sales remains evident (Fig. 2b); the percentage of the total market value contributed by mAbs grew steadily during this survey, although COVID-19 vaccine sales affected this trend. However, with these vaccine revenues excluded, mAbs still represented 80% of total protein-based global biopharmaceutical sales last year. Also notable is an increase in approval rates for biosimilars, as well as for nucleic acid-based products and gene-engineered cells (Table 1).
Mammalian cell systems continue to be the most often used expression system during this time period. Of the 159 approved products made by recombinant means in cell-based systems, most (107, or 67%) are produced in mammalian cells. Nonetheless, this reverses a trend seen over many decades, as it is lower than the percentage of mammalian-cell-produced biopharmaceuticals approved during the last survey period (84%; Fig. 3). The expression systems used are invariably dictated by the post-translational modification (PTM) requirements of the products. A large proportion of, in particular, biosimilar and ‘me-too’-type products approved over the current survey period (Table 2) do not require glycosylation or other mammalian PTMs, enabling their production in nonmammalian and less expensive systems, most commonly Escherichia coli. Interestingly, when focusing solely on the genuinely novel active biopharmaceutical ingredients approved in this current period, a different story emerges, with 85% of these products made in mammalian systems.Fig. 3 Expression systems.
Relative use of mammalian- versus non-mammalian-based production cell lines in the manufacture of biopharmaceuticals approved over the indicated periods. Each dataset is expressed as a percent of total biopharmaceutical product approvals for the period indicated.
As in previous surveys, the most often used mammalian cell culture system remains Chinese hamster ovary (CHO cells), which were used to produce 95 of those 107 individual products made in mammalian systems (89%). This reflects the well-known strengths of this production platform, including the ability to produce antibodies at titers of 3–8 g/liter at production scale5. Other mammalian systems used included NS0 mouse myeloma cells (7 products), as well as baby hamster kidney (BHK), human embryonic kidney (HEK), sp2/0 mouse myeloma cells and PER C6 immortalized primary human embryonic retinal cells (1 product each). Moreover, a single new product (Sevenfact) is produced via transgenic means, in the milk of transgenic rabbits—only the second recombinant protein produced in this transgenic system. (Two existing products are also made in transgenic systems: Atryn, approved in 2009, in transgenic goats' milk and Kanuma, approved in 2015, in transgenic chicken eggs.)
Of the nonmammalian production platforms, E. coli continues to dominate, used in the production of 36 products approved since 2018, with smaller numbers of products produced in Pichia pastoris (5) and Saccharomyces cerevisiae (4). Also notable is the bacterium Pseudomonas fluorescens, used to recombinantly produce the active ingredient (teriparatide) of the biosimilar Livogiva/Qutavina, as well as the active constituent of Rylaze (asparaginase) and one component of the multicomponent vaccine Vaxneuvance. Historically, P. fluorescens was used to produce a single biopharmaceutical, Bonsity, a recombinant parathyroid hormone (PTH) initially approved in 1987. The yeast Hansenula polymorpha is also used to produce one product approved in the current period (Heplisav B, a recombinant hepatitis B surface antigen). It was also used to produce the recombinant hepatitis B surface antigen active pharmaceutical ingredient (API) found in Hexacima/Hexyon, initially approved in 2013.
As with past surveys, most products approved during the current survey period are administered parenterally. A small number are administered directly to their intended site of action via nonparenteral means, such as the oral recombinant cholera vaccine Vaxchora (Table 1). Rybelsus (semaglutide), for type 2 diabetes, represents an interesting exception: this acylated, 39-amino-acid polypeptide is administered orally in tablet form, a first for the biopharma sector. The tablet also contains a novel excipient (salcaprozate sodium) as an absorption enhancer. This facilitates uptake of semaglutide across the epithelium of the gastrointestinal tract, and hence into the bloodstream. A bioavailability of 1% was recorded in humans during clinical studies.
Another interesting approval with challenging delivery is the Alzheimer’s product Aduhelm. This human IgG1, directed against aggregated soluble and insoluble forms of amyloid-β in the brain (a defining pathophysiological feature of Alzheimer’s), was approved in 2021 by the FDA under its accelerated approval process. Clinical studies confirmed that intravenous infusion of Aduhelm results in a reduction of amyloid-β plaques, although a clear and unambiguous link between this effect and appreciable clinical improvement remains to be established. This, along with some safety concerns, led the European Medicines Agency (EMA) to refuse to recommend approval in Europe. That an intravenous infusion of Aduhelm reduces amyloid-β plaques in the brain suggests that sufficient quantities of the antibody cross the blood–brain barrier to have a physiological effect. This finding may benefit other mAb-based therapies in development for diseases of the brain.
The impact of COVID-19
Clearly, COVID-19 represents the most significant and challenging new global threat to human health during the period of this survey. Since the first reported cases in November 2019, 636 million confirmed cases and 6.6 million deaths have been reported globally to the WHO (updated statistics available at https://COVID19.who.int).
Development and deployment of effective COVID-19 vaccines and therapeutics occurred with unprecedented speed, thanks to industry action and regulatory agility. Regulators shifted resources toward COVID-19-related activities and provided rapid scientific advice, compliance checks and accelerated assessment and evaluation procedures to product developers. Rolling reviews (regulatory assessment as data came in, rather than as part of a final marketing application) proved particularly effective. Such agility notwithstanding, FDA approvals of COVID-19 products were made through an existing framework for authorizing new drugs in emergency circumstances—the Emergency Use Authorization pathway (which is not strictly an approval)—whereas the EMA expedited approvals using their pre-existing Conditional Marketing Authorisation procedure. As a result, by September 2022, the FDA and EMA had, between them, approved or authorized 22 different COVID-19 medicines (6 vaccines and 16 therapeutics), of which 16 are biopharmaceuticals, mainly vaccines and mAbs. Updated product lists are available on the dedicated COVID-19 pages of both regulators’ websites.
Vaccination has had the greatest single impact on pandemic amelioration. As of November 2022, the World Health Organization estimates that a total of 13 billion vaccine doses have been administered globally. Data from the CDC show that, for those over 50 years of age, full vaccination decreases the risk of death by 12-fold). Approaches to vaccine API development and manufacture vary; approved vaccines include mRNA-based vaccines (Comirnaty and Spikevax), inactivated and adjuvanted SARS-CoV-2 virus (Valneva), engineered adenovirus encoding the SARS-CoV-2 spike protein (Vaxzevria and Jcovden) and recombinant spike protein (Nuvaxovid). From a technological perspective, mRNA-based vaccines have the greatest novelty and are likely to pave the way toward additional mRNA vaccines for COVID and non-COVID indications (Box 2).
Box 2 mRNA vaccines, COVID-19 and beyond The first two COVID-19 vaccines approved in the United States and EU were both mRNA-based, encoding the full-length SARS-CoV-2 spike protein. SARS-CoV-2 was identified as the causative agent of COVID-19 in December 2019. The first known cases of the disease in Europe and the United States were recorded on 12 and 16 January 2020, respectively. The full genome sequence of the original Wuhan strain (Wuhan-Hu-1) was published in GenBank on 13 January 2020, and the WHO declared COVID-19 to be a global pandemic on 11 March 2020. Pfizer-BioNTech’s mRNA COVID-19 Vaccine (Comirnaty) first gained Emergency Use Authorization in the United States on 11 December 2020 followed by conditional approval in the EU on 21 December 2020. Moderna’s mRNA COVID-19 Vaccine (Spikevax) gained Emergency Use Authorization status on 18 December 2020 in the United States and conditional approval in the EU on January 6th 2021.
The Authorization or approval of two vaccines within one year of pathogen identification is unparalleled. Historically, for example, it took almost 200 years from discovery of the infectious agent to develop a measles vaccine, and over 150 years in the case of polio. Luckily, several technical advancements were reported over the previous decade in the then nascent field of mRNA therapeutics, and several companies had already initiated vaccine developmental programs based on this technology, including BioNTech and Moderna.
Mimicking the native cellular transcription process, mRNA can be produced in vitro via incubation of (usually phage) RNA polymerase enzymes and ribonucleotide triphosphates (NTPs) with template DNA (usually linearized, plasmid DNA). Although protein synthesis following administration of in-vitro-transcribed mRNA to mice was reported in the 1990s, practical therapeutic application of the approach was beset by technical challenges, including mRNA instability, immunogenicity and inefficient in vivo delivery. More recently, many of these challenges have been largely overcome9. Optimization of mRNA sequences flanking the protein-coding region (the 5′ cap and 5′ untranslated region (UTR) at one end and the 3′ UTR and polyadenosine tail at the other) helps enhance both stability and the levels of expression. Incorporating chemically modified nucleosides (such as 1-methylpseudouridine) reduces the native immune response to naked mRNA, and the development of, in particular, lipid-based nanoparticles has substantially enhanced mRNA cellular delivery.
Usually administered intramuscularly, either the mRNA vaccines or some locally produced antigen are taken up by antigen-presenting cells, such as dendritic cells10,11. These cells then travel to lymph nodes, where they elicit adaptive immunity, incorporating both T cell and B cell immune responses.
Compared to conventional vaccines, mRNA-based vaccines have been considered to have several advantages, including a capacity for rapid development, relatively low cost, straightforward scale-up and manufacture, a potential for high level of efficacy and a strong safety profile (no risk of infection or insertional mutagenesis). The development, approval and deployment of Comirnaty and Spikevax validated such cited advantages and provides a sound platform for further mRNA-based approvals. The sequence-independent flexibility of the platform is further underscored by the recent introduction of bivalent versions of Spikevax and Comirnaty, each containing mRNA sequence combinations encoding the S proteins of both original and selected Omicron variants of SARS-CoV-2.
Several dozen such product, mainly targeting cancer and infectious disease, are at various stages of clinical development9–12. The ascendancy of mRNA-based vaccines is unlikely, however, to signal the demise of traditional vaccine modalities. Within a few months (and, in one case, within weeks) of the approval of Comirnaty and Spikevax, several additional SARS-CoV-19 vaccines based upon more traditional recombinant subunit and viral vector modalities gained approval. Moreover, mRNA vaccines still suffer from some drawbacks, including the requirement for cold chain storage and distribution (usually between –15 °C and –90 °C, depending on the product). mRNA-based platforms are thus likely to broaden as opposed to replace existing vaccine production modalities in the future.
Market value
In the current survey period, the market value of biopharmaceuticals has continued to rise. Consolidated data from various La Merie (http://www.lamerie.com) and Fierce Pharma (http://www.fiercepharma.com) financial reports indicate that total global sales for 2021 reached US $343 billion (Table 3). Indeed this figure is likely an under-representation, as revenues for biosimilars in some regions have not been publicly reported. Recombinant originator proteins, both mAb and non-mAb, collectively account for a lion’s share of this value ($271 billion), representing an increase of 44% over the $188 billion reported for this product category in our last survey, for 2017.Table 3 Total reported 2021 biopharmaceuticals global sales values
Biopharmaceutical category Reported sales value ($ billion)
Originatora recombinant proteins: mAbs 217.3
Originator recombinant proteins: non-mAbs 53.6
Covid vaccines (Comirnaty and Spikevax) 54.5
Biosimilars 11.1
Nucleic acid and engineered cell based 6.8
Total value 343.3
aOriginator’ signifies non-biosimilar.
COVID-19 vaccines had the largest impact upon the biopharmaceutical landscape in commercial as well as technological and medicinal terms, with Comirnaty and Spikevax cumulatively generating revenues of $54.5 billion in 2021 (Table 3). Comirnaty ($36.8 billion) has displaced the long-time best-selling biopharmaceutical Humira ($21.2 billion) as the top-selling biopharmaceutical product, with Spikevax ($17.7 billion) ranking third in 2021. Indeed, Humira’s pre-eminence in the global biopharmaceutical market is likely over. In addition to the advent of COVID-19 vaccines, its ‘patent wall’ has all but ended, and a number of biosimilar rivals are likely to stream onto the US market in particular in the next year or two. Whereas Comirnaty is poised to retain the top spot globally this year, it is difficult to forecast the market for COVID-19 vaccines in future years. Much will depend on factors such as the course of the pandemic, the future need for booster programs, the severity of evolving viral strains and future approvals of additional COVID-19 medicines, both prophylactic and therapeutic. The unpredictability of the COVID-19 therapeutics markets is illustrated by Regeneron’s anti-spike-protein mAb-based product Regen-Cov (Ronapreve). After initially gaining an Emergency Use Authorization in November 2020, Regen-Cov generated $7.6 billion in global sales in 2021, but its lack of effectiveness against newer viral variants caused the FDA to effectively pause its use in January 2022.
From a commercial perspective, revenues generated by biosimilar, nucleic acid (excluding COVID-19 mRNA vaccines) and engineered cell-based products remain relative modest. Collectively they generated an estimated $17.9 billion in 2021, representing some 5% of the total biopharmaceutical market, and less than sales of Humira alone. Of the 73 biopharmaceuticals recording blockbuster status (sales above $1 billion) last year, two were biosimilars (Erelzi and Mvasi, recording sales of $1.5 and $1.1 billion, respectively) and two were (non-COVID) nucleic acid/gene-therapy-based products (Spinraza and Zolgensma, with sales of $1.9 and $1.3 billion, respectively). mAb-based products (including Fc fusion products) continue to represent the most lucrative single product class. Their total sales reached $217 billion last year, and they represented 15 of the top 20 products by sales generated (Table 4). In terms of target indications, the vast majority of such antibody-based products target inflammatory and autoimmune conditions (cumulative 2021 sales of $99.3 billion) and cancer (2021 cumulative sales of $68.4 billion).Table 4 The 20-top selling biopharmaceutical products in 2021
Rank Product Sales, 2021 ($ billions)a Year first approved Company Patent expiryb Biosimilar version(s) approved
1 Comirnaty (COVID-19 Vaccine, mRNA) 36.8 2020c Pfizer & BioNTech N/A
2 Humira (adalimumab) 21.2 2002 AbbVie & Eisai 2016 (US)
2018 (EU)
Halimatoz/Hefiya/Hyrimoz, Amgevita/Amjevita/Solymbic, Cyltezo, Imraldi, Kromeya, Idacio, Hadlima, Abrilada, Hulio, Amsparity, Yusimry, Yuflyma, Libmyris, Hukyndra
3 Spikevax (COVID-19 Vaccine, mRNA) 17.7 2020c Moderna N/A
4 Keytruda (pembrolizumab) 17.2 2014 Merck 2036 (US)
2028 (EU)
5 Stelara (ustekinumab) 9.5 2009 Janssen (Johnson & Johnson) 2023 (US)
2024 (EU)
6 Eylea (aflibercept) 9.4 2011 Regeneron, Bayer 2027 (EU & US)
7 Opdivo (nivolumab) 8.5 2014 BMS, Ono 2027 (US)
2026 (EU)
8 Ronapreve/Regen-Cov (casirivimab & imdevimab) 7.6 2020 Roche, Regeneron N/A
9 Trulicity (dulaglutide) 6.7 2014 Eli Lilly 2026 (US)
2024 (EU)
10 Darzalex (daratumumab) 6.0 2015 Janssen 2027 (US)
2026 (EU)
11 Dupixent (dupilumab) 5.9 2017 Sanofi-Aventis, Regeneron N/A
12/13 Prolia/Xgeva (denosumab) 5.7 2010 Amgen 2025 (US)
2022 (EU)
12/13 Gardasil 9 (human papillomavirus 9-valent vaccine, recombinant) 5.7 2014 Merck 2028 (US & EU)
14 Enbrel (etanercept) 5.6 1998 Amgen, Pfizer, Takeda Pharmaceuticals 2015 (EU) 2028 (US) Erelzi, Benepali/Eticovo, Nepexto
15 Ocrevus (ocrelizumab) 5.5 2017 Roche/Genentech 2027 (EU)
2029 (US)
16 Cosentyx (secukinumab) 4.7 2015 Novartis 2026 (US)
N/A (EU)
17 Entyvio (vedolizumab) 4.4 2014 Takeda 2026 (US)
N/A (EU)
18 Perjeta (pertuzumab) 4.3 2012 Roche/Genentech 2024 (US)
2023 (EU)
19 Soliris (eculizumab) 4.2 2007 Alexion 2027 (US)
2020 (EU)
20 Lantus/Toujeo (insulin glargine) 3.9 2000 Sanofi 2014 (EU & US) Semglee, Lusduna, Abasaglar, Rezoglar
aFinancial data from LaMerie Business Intelligence and Fierce Pharma.
bPatent data from various sources, predominantly http://gabi-journal.net/. Note that patent landscape for biologics can be particularly complex: issues such as follow-on patents subsequent to the main patent and patent litigation can delay biosimilar development and approval. cInitial date of Emergency Use Authorization or Conditional Marketing Authorisation.
N/A, data not available.
Although most classes of originator biopharmaceuticals continue to show strong year-on-year growth, a notable exception is that of originator ‘established therapeutic proteins’ (erythropoietins, interferons, CSFs, human growth hormone (hGH) and follicle-stimulating hormone (FSH)). Data from La Merie publishing shows that this product class generated total global revenues of $11.7 billion in 2021, down 14% compared with 2020 ($13.6 billion). This mirrors a longer-term trend, in which the sales value of this class of product has more than halved in the past decade (down from $26.6 billion in 2012) The underlying reasons for this decline include competition from biosimilars and the approval of additional therapeutics targeting the same indications.
Biosimilars hit the big time
The survey period witnessed a continued surge in biosimilar approvals, as this class of product gains global acceptance. When considered by product trade name, 94 biosimilars have gained approval in the EU and/or the United States since 2006, although 10 have been subsequently withdrawn for commercial reasons and not all are actively marketed as yet.
By product category, the 94 biosimilar approvals thus far include 2 hGHs, 5 erythropoietins (EPOs), 20 granulocyte CSFs (G-CSFs; filgrastim and PEGylated filgrastim), 2 FSHs, 9 engineered insulins, 51 antibody- or antibody-fusion-based products and 5 PTHs. The 94 licensed products are based on 72 distinct active ingredients (Table 5).Table 5 Biosimilar products that had gained marketing Authorization within the EU and/or the US by June 2022
Product type Trade name(s) Year (and region) approved Reference product Manufacturer(s) of the biologically active substance
Somatropin-based
hGH-based Omnitrope 2006 (EU) Genotropin Sandoz (Kundl, Austria)
Valtropin 2006 (EU)
Withdrawn 2012
Humatrope LG Life Sciences (Jeonbuk-do, Republic of Korea)
Epoetin-based
EPO-based Retacrit 2018 (US)
2007 (EU)
Eprex/Erypo (EU)
Epogen/Procrit (US)
Norbitec (Uetersen, Germany; EU)
Binocrit 2007 (EU) Eprex/Erypo Rentschler (Laupheim, Germany) & Lek (Menges, Slovenia)
Epoetin alfa hexal 2007 (EU) Eprex/Erypo
Abseamed 2007 (EU) Eprex/Erypo
Silapo 2007 (EU) Eprex/Erypo Norbitec
Filgrastim-based
G-CSF-based Releuko 2022 (US) Neupogen Kashiv Biosciences (Chicago)
Nivestim (EU)/Nivestym (US) 2010 (EU)
2018 (US)
Neupogen Hospira (Zagreb, Croatia)
Ratiograstim 2008 (EU) Neupogen Sicor (Vilnius, Lithuania)
Filgrastim Ratiopharm 2008 (EU)
Withdrawn 2011
Neupogen
Biograstim 2008 (EU)
Withdrawn 2015
Neupogen
Tevagrastim 2008 (EU) Neupogen
Zarzio (EU)/Zarxio (US) 2009 (EU)
2015 (US)
Neupogen Sandoz (Kundl, Austria)
Filgrastim hexal 2009 (EU) Neupogen
Grastofil 2013 (EU) Neupogen Intas Biopharmaceuticals (Gujarat, India)
Accofil 2014 (EU) Neupogen
Pegfilgrastim Fylnetra 2022 (US) Neulasta Kashiv Biosciences (Chicago)
Stimufend 2022 (EU) Neulasta Fujifilm Diosynth Biotechnologies (Billingham, UK)
Nyvepria 2020 (EU & US) Neulasta Hospira
Cegfila (previously pegfilgrastim Mundipharma) 2019 (EU) Neulasta 3P Biopharmaceuticals, (Noain, Spain)
Pelmeg 2018 (EU) Neulasta
Grasustek 2019 (EU) Neulasta USV Private (Navi Mumbai, India)
Ziextenzo 2019 (US)
2018 (EU)
Neulasta Lek & Sandoz (Kundl, Austria)
Pelgraz 2018 (EU) Neulasta Intas Pharmaceuticals (Ahmedabad, India)
Udenyca 2018 (EU & US)
Withdrawn (EU)
Neulasta KBI Biopharma (Boulder, CO, USA)
Fulphila 2018 (US & EU) Neulasta Biocon Biologics (Bangalore, India)
FSH-based
FSH-based Ovaleap 2013 (EU) Gonal F Merckle Biotech (Ulm, Germany)
Bemfola 2014 (EU) Gonal F Polymun Scientific Immunbiologische Forschung (Klosterneuburg, Austria)
Insulin-based
Insulin-based Inpremzia 2022 (EU) Actrapid Biocon (Bangalore, India)
Insulin glargine-based Rezvoglar 2021 (US) Lantus Eli Lilly (Indianapolis, IN, USA), Lilly del Caribe (Carolina, Puerto Rico, USA) & Lilly France (Fegersheim, France)
Semglee 2021 (US)
2018 (EU)
Lantus Biocon (Johor, Malaysia)
Abasaglar 2014 (EU) Lantus Lilly del Caribe Eli Lilly
Lusduna 2017 (EU)
Withdrawn 2018
2017 (tentative, US)
Withdrawn 2018
Lantus Merck Sharp & Dohme (Elkton, VA, USA)
Insulin lispro-based Insulin lispro Sanofi 2017 (EU) Humalog Sanofi-Aventis (Frankfurt)
Insulin aspart-based Truvelog Mix 30 2022 (EU) NovoMix Sanofi-Aventis
Kirsty 2021 (EU) NovoRapid Biocon
Insulin aspart Sanofi 2020 (EU) NovoRapid Sanofi-Aventis
Mab-based and related
Infliximab-based Avsola 2019 (US) Remicade R*
Inflectra 2013 (EU)
2016 (US)
Remicade Celltrion (Incheon, Republic of Korea)
Remsima 2014 (EU) Remicade
Flixabi 2016 (EU) Remicade Biogen (Hillerod, Denmark) & Samsung Bioepis (Incheon, Republic of Korea)
Renflexis 2017 (US) Remicade
Ixifi 2017 (US) Remicade Pfizer
Zessly 2018 (EU) Remicade Boehringer Ingelheim (Biberach an der Riss, Germany)
Adalimumab-based Hukyndra 2021 (EU) Humira Alvotech (Reykjavik)
Libmyris 2021 (EU) Humira
Yuflyma 2021 (EU) Humira Celltrion
Yusimry 2021 (US) Humira R*
Amsparity 2020 (EU) Humira Wyeth BioPharma (Andover, MA, USA)
Hulio 2020 (US)
2018 (EU)
Humira Kyowa Kirin, Takasaki (Gunma, Japan)
Abrilada 2019 (US) Humira R*
Hadlima 2019 (US) Humira Samsung Bioepis
Imraldi 2017 (EU) Humira
Idacio 2019 (EU) Humira Merck Serono (Corsier-sur-Vevey, Switzerland)
Kromeya 2019 (EU)
Withdrawn 2019
Humira
Amgevita (EU)/Amjevita (US) 2016 (US)
2017 (EU)
Humira Amgen (Thousand Oaks, CA, USA)
Solymbic 2017 (EU) Humira
Cyltezo 2017 (EU & US) Humira Boehringer Ingelheim (Fremont, CA, USA)
Halimatoz 2018 (EU)
Withdrawn 2020
Humira Catalent Biologics (Bloomington, IN, USA) & Sandoz (Langkampfen, Austria)
Hefiya 2018 (EU) Humira
Hyrimoz 2018 (EU & US) Humira
Rituximab-based Riabni 2020 (US) Rituxan Immunex (West Greenwich, RI, USA)
Ruxience 2020 (EU)
2019 (US)
MabThera Boehringer Ingelheim (Biberach an der Riss, Germany)
Truxima 2018 (US)
2017 (EU)
MabThera Celltrion
Blitzima 2017 (EU) MabThera
Ritemvia 2017 (EU) MabThera
Rituzena 2017 (EU) MabThera
Rixathon 2017 (EU) MabThera Sandoz (Langkampfen, Austria)
Riximyo 2017 (EU) MabThera
Trastuzumab-based Zercepac 2020 (EU) Herceptin Shanghai Henlius Biopharmaceutical (Shanghai, China) & WuXi Biologics (WuXi, China)
Kanjinti 2019 (US)
2018 (EU)
Herceptin Patheon Biologics (Groningen, the Netherlands) & Immunex
Ontruzant 2019 (US)
2017 (EU)
Herceptin Fujifilm Diosynth (Hillerød, Denmark) & Samsung Biologics (Incheon, Republic of Korea)
Trazimera 2019 (US)
2018 (EU)
Herceptin Boehringer Ingelheim (Biberach an der Riss, Germany)
Herzuma 2018 (EU & US) Herceptin Celltrion
Ogivri 2018 (EU)
2017 (US)
Herceptin Biocon (Bangalore, India)
Bevacizumab-based Alymsys 2022 (US) Avastin GH GENHELIX (Armunia, Spain)
Oyavas 2021 (EU) Avastin
Abevmy 2021 (EU) Avastin Biocon Biologics (Bangalore, India)
Lextemy 2021 (EU)
Withdrawn 2021
Avastin
Onbevzi 2021 (EU) Avastin Biogen (Hillerød, Denmark)
Aybintio 2020 (EU) Avastin Fujifilm Diosynth Biotechnologies (Hillerød, Denmark)
Equidacent 2020 (EU)
Withdrawn 2020
Avastin Kyowa Kirin (Takasaki, Japan)
Zirabev 2019 (EU & US) Avastin Wyeth (Andover, MA, USA)
Mvasi 2018 (EU)
2017 (US)
Avastin Amgen
Ranibizumab-based Byooviz 2021 (EU & US) Lucentis Wacker Biotech (Jena, Germany)
Etanercept-based Nepexto 2020 (EU) Enbrel Lupin (Taluka Mulshi, India)
Benepali/Eticovo 2019 (US)
2016 (EU)
Enbrel Fujifilm Diosynth & Samsung (Incheon, Republic of Korea)
Erelzi 2016 (US)
2017 (EU)
Enbrel Sandoz (Langkampfen, Austria) & Novartis (Singapore)
Teriparatide
Teriparatide-based Sondelbay 2022 (EU) Forsteo Intas Pharmaceuticals (Ahmedabad, India)
Livogiva 2020 (EU) Forsteo Cytovance Biologics (Oklahoma City, OK, USA)
Qutavina 2020 (EU)
Withdrawn 2020
Forsteo Cytovance Biologics
Movymia 2017 (EU) Forsteo Richter-Helm BioLogics (Bovenau, Germany)
Terrosa 2017 (EU) Forsteo
R*, manufacturing site details of biological active substance redacted in FDA documentation.
By region, 83 biosimilar products have received marketing Authorization in the EU, with 44 of these (53%) having gained Authorization within the current survey period. In the United States, a total of 37 products have thus far been licensed, of which 27 (73%) were approved within this survey period. The acceleration in biosimilar approval rates seen in our last survey is thus maintained in this one. Notable approval trends since 2018 include the approval of a raft of polyethylene glycol (PEG)-filgrastims (biosimilars to Neulasta; 2021 global sales of $2 billion), a number of engineered insulins and mAbs with biosimilarity to adalimumab (Humira; 2021 sales of $21 billion), trastuzumab (Herceptin; 2021 sales of $2.9 billion and bevacizumab (Avastin; 2021 sales of $3.3 billion).
Despite the large number of recent biosimilar approvals, both the revenues generated and the overall savings accrued to patients and healthcare systems remain relatively modest in both the EU and United States. A recent report by IQVIA6 prepared for the European Commission, estimates the total European biosimilars market to have reached €8.8 billion in 2021, amounting to savings of €5.7 billion (savings calculated as actual spend versus the pre-biosimilar cost of the originator, reference product).
Moreover, the report finds that biosimilars recently launched in Europe achieved 50% penetration of the originator market in less than a year, whereas earlier biosimilars typically took over two years to reach an equivalent position. Biosimilars approved in the EU are considered automatically interchangeable from a medical viewpoint, although decisions regarding actual substitution (dispensing one medicine instead of another medicine without consulting the prescriber) are made at individual EU member state level.
According to FDA data, generic drugs account for 90% of all prescriptions in the United States and provided savings of more than $1 trillion to the US health care system over a decade. The statistics for biosimilars are, predictably, more modest. The Pharmaceutical Research and Manufacturers of America (PhRMA; www.phrma.org) reported that annualized savings from biosimilars reached $6.5 billion in 2020, with average biosimilar sales prices being as much as 45% less than the branded biologics price at the time of first biosimilar launch.
US biosimilar approval and market penetration is influenced by regulatory, legal and developmental cost considerations. For example, biosimilar status in the United States does not automatically equate to interchangeability (and hence substitution for the reference product without the involvement of the prescriber). Interchangeable biosimilar products must meet additional regulatory requirements, as outlined by the Biologics Price Competition and Innovation Act. The US patent litigation landscape in this space can also slow or stop putative biosimilar products reaching the market. Additionally, a recent study found that most comparative efficacy trials supporting FDA biosimilar approvals were larger (median 504 patients), longer (median of 52 weeks) and more costly (estimated median cost of $20.8 million) than pivotal trials for new molecular entities7. As witnessed in Europe, however, more recent US biosimilars are achieving faster market uptake, with bevacizumab, trastuzumab and rituximab biosimilars achieving 42%, 38% and 20% uptake within their first year on the market, trending toward 60% by the end of year two.
mAb approvals
Monoclonal antibodies continue to dominate both in approval numbers (in the case of both originator and biosimilar categories) and commercial value. All newly approved antibodies were engineered in some way: they are either humanized or fully human, and most were additionally engineered to enhance or stabilize specific functional and/or structural characteristics. Jemperli and Evkeeza, both IgG4 mAbs, reportedly tend to form half-antibodies. To prevent this, each heavy chain contains a serine-to-proline substitution in the hinge region of the Fc domain, which stabilizes disulfide bonds between the two heavy chains.
Skyrizi, a humanized IgG1, represents another example of engineering. Used to treat plaque psoriasis and psoriatic arthritis, it acts by selectively binding the p19 subunit of IL-23, thereby inhibiting the latter from binding to its receptor. The framework of the antibody was engineered with two mutations in the Fc region, Leu234Ala and Leu235Ala, to reduce its potential effector function, which does not contribute to the product’s mode of action. The C-terminal lysine of the heavy chain was also deleted to reduce potential charge heterogeneity.
The period also witnessed the approval of five glycoengineered (afucosylated or low-fucose) products: Uplizna, Rybrevant, Blenrep, Fasenra and Poteligeo. Removal of the fucose residue in the antibody’s Fc glycocomponent can increase antibody-dependent cellular cytotoxicity (ADCC), potentially boosting the potency of mAbs whose mode of action depends on this antibody effector function.
Additional engineered formats that came on stream include three bispecific full-size mAbs: Vabysmo, the above-mentioned Rybrevant and the bispecific T cell engager (BiTE) product Lunsumio. Cabilivi, a bivalent nanobody, also gained approval, the first approval of a domain fragment. Three antigen-binding fragments also entered the market: Byooviz, Susvimo and Beovu. All three target macular degeneration and are administered by intravitreal injection. The smaller size of antibody fragments enables delivery of a high molar dose to the limited volume of the eye’s vitreous body, which may enhance tissue penetration at the retina and prolong the therapeutic effect.
Six new antibody–drug conjugates (ADCs) were approved during the survey period (Padcef, Enhertu, Tivdak, Trodelvy, Zynlonta and Blenrep), joining five previously approved ADC products. ADCs consist of an antibody chemically conjugated to a cytotoxic payload. Antibody-mediated binding to the target cell is followed by internalization, with subsequent intracellular cytotoxin release and action. Advances in cytotoxin discovery and chemical linker design have fueled increasing numbers of ADCs coming on stream. Cumulatively, ADCs generated $5.4 billion in 2021, with two such products achieving blockbuster status (Kadcyla and Adcetris).
The migraine therapy Vyepti, a humanized anti-calcitonin-gene-related peptide (CGRP) IgG1 antibody, is the first antibody to be produced in P. pastoris. Following intravenous administration, it binds CGRP, preventing its binding to its receptors, which influence the initiation, frequency and severity of migraine attacks. The mAb’s heavy chain N-glycosylation site has been removed via protein engineering, which eliminates any potential immunogenicity issues in humans due to a yeast-derived glycocomponent. Although the lack of a glycocomponent prevents ADCC and complement-dependent cytotoxicity (CDC) effector functions, the product’s mode of action does not rely on such functionality.
The current period also witnessed the conditional approval and emergency Authorization of several mAb-based products to treat COVID-19. The efficacy of mAb-based preparations aimed at SARS-CoV-2 may be compromised by mutations affecting the viral spike protein, as illustrated by products such as bamlanivimab and eteseviman (which are administered together) and REGEN-COV. This year, the FDA restricted the use of both products due to the emergence of the Omicron variant.
Nucleic acid-based approvals
Two of the most technically innovative, medically impactful and commercially successful products coming on stream in this survey period fall into this category—the COVID-19 mRNA vaccines Spikevax and Comirnaty. An additional 12 nucleic acid-based products were approved, adding substantially to the seven such products previously approved (Table 1). The new approvals include five small interfering RNA (siRNA)-based products (Amvuttra, Leqvio, Givlaari, Oxlumo and Onpattro), five antisense-based products (Amondys 45, Viltepso, Viondys 53, Waylivra and Tegsedi) and two gene therapy products (Zolgensma and Luxturna), which deliver therapeutic genes in adeno-associated viral vectors. Although 12 approvals signal progress in this field, almost all are orphan products and undergoing additional monitoring.
siRNA, antisense RNA and gene therapies therefore have as yet to make a broad impact on the mainstream biopharma market, particularly in regard to sales value. These modalities may benefit from lessons learned during the development of COVID-19 mRNA vaccines, but they face steeper technical challenges. mRNA vaccines capitalize on the massive amplification provided by the immune system—small doses administered intramuscularly and taken up by local antigen-presenting cells lead to a system-wide adaptive immune response (Box 2). In contrast, most non-vaccine nucleic acid products require substantially higher dosages, systemic administration, delivery to a specific tissue, prolonged therapeutic action and, in many cases, a non-immunogenic profile that allows chronic administration. These additional technical hurdles remain largely unresolved.
Engineered cell-based approvals
New cell-based therapies flooded into the market during this survey period, with nine such products gaining approval in the EU and/or United States. Previously there were but two. The majority of the new approvals (six products) are based on CAR-T cells, indicated for the treatment of blood-borne malignancies (multiple myeloma, leukemia and, in particular, lymphoma).
Many tumors manage to evade immune surveillance by downregulating the expression of major histocompatibility antigen class I (MHC-I) molecules. This prevents MHC-I-mediated presentation of tumor-specific peptides on the cancer cell surface and recognition of the MHC-I–peptide complex by cytolytic T lymphocytes via their T cell receptors (TCRs), which triggers cancer cell destruction by activated T cells.
CAR-T cells harness cancer-killing T cells independent of the MHC–TCR pathway. The CAR-T cell approach is now arguably the leading technology in this regard, surpassing alternatives such as T-cell-directed bispecific antibodies. CAR-T cells are genetically engineered to express on their surface a chimeric antigen receptor (CAR) that fuses an extracellular antibody fragment (usually a single-chain variable fragment, or scFv) specific for the target tumor surface antigen to intracellular T-cell-activating domains. CAR-T cell therapies are autologous, requiring isolation of a patient’s T lymphocytes via leukapheresis and ex vivo engineering of the cells to express the CAR. The engineered T cells are expanded in cell culture and cryopreserved until infused back into the patient.
CAR-T cell therapies have proven most effective against B cell cancers, whereas their extension to solid tumors remains challenging. Initial efficacy can be followed by cancer recurrence arising from tumor evolution. The approach can also present safety concerns, particularly cytokine release syndrome. The autologous nature of CAR-T cell therapy is inherently costly, with treatment list prices typically in the region of $400,000–$500,000.
Genetically engineered cell-based products have also been developed for non-cancer indications. One example is Zynteglo, a hematopoietic-stem-cell-based gene therapy approved in the EU in 2019 as an orphan product for the treatment of transfusion-dependent β-thalassemia. Zynteglo consists of autologous hematopoietic stem cells transduced with a functional β-globin gene. After infusion, the engineered cells repopulate the hematopoietic compartment, with clinical studies reporting ongoing expression of the β-globin gene 36 months after treatment. However, for commercial reasons, the sponsor company, Bluebird Bio, informed the EMA earlier this year of its intention to withdraw the product from the market. The treatment cost was in the region of €1.5 million per patient. In a further twist, the FDA approved Zynteglo in August of this year, reportedly with an associated price tag of $2.8 million per patient.
Traditional biotech product approvals
The current survey period also witnessed the approval of 37 traditional biotech products classified as new by regulatory authorities in terms of active substance—nine fewer than in our previous survey. Traditional products refer to those produced naturally or via nonrecombinant means in or by a biological source. The profile of approvals (Supplementary Table 1) largely mirrors product types approved in previous surveys, and include a range of blood-derived products and natural extracts, as well as traditional (nonrecombinant) vaccines and un-engineered cells.
Future directions
Although estimates vary, data published by PhRMA indicate that there are more than 7,800 biopharmaceutical products in clinical development globally, of which over 1,000 have reached phase 3 trials. Cancer remains by far the single most common indication, with other common target indications including genetic disorders, cardiovascular disease, as well as neurological, eye and blood disorders—all leading causes of mortality or morbidity, particularly in the West. Almost a third of products in clinical development (2,533) are mAb based, maintaining these as the single largest experimental product class. Smaller but still notable numbers of gene-modified cell therapies (348) and nucleic acid- and gene-based therapies (546) are currently being assessed in the clinic. On the whole, therefore, the industry retains a strong experimental product pipeline. Data from Evaluate Pharma indicates that total global biotech products sales continue to steadily increase as a percentage of overall global pharmaceutical sales, growing from 18% in 2010 to over 30% currently.
There are more than 100 (non-COVID-19) mAb-based products currently in late-stage clinical development. Antibody approvals over the next several years will likely mirror the profile of this antibody cohort. Some 60 of these experimental mAbs target cancer. Although 18 target liquid malignancies, the majority target a range of solid tumor types including ovarian, prostate, melanoma, breast, small-cell lung cancer and renal cancer. Almost a third (18 products) are bispecific, and one-fifth (12 products) are antibody conjugates. The remaining 54 non-cancer mAbs target a wide range of conditions; almost all are human or humanized monospecific products. In addition to this cohort of experimental products, over a dozen anti-COVID-19 mAbs remain in clinical studies, although the impact of these products will ultimately depend upon their efficacy against current and future SARS-CoV-2 variants.
Earlier stages in the mAb developmental pipeline display a greater diversity of antibody formats (ADCs, bispecific and fragments) and a larger proportion of products targeting solid as opposed to hematological malignancies. For example, 80% of ADCs in oncology clinical trials target solid tumor types8. Solid tumors were the most common global causes of cancer death in 2020 according to the WHO, including lung (1.80 million deaths), colon and rectum (916,000 deaths), liver (830,000 deaths), stomach (769,000 deaths) and breast (685.000 deaths).
Nucleic acid and engineered cell-based therapies continue to represent a vibrant and growing sector of experimental as well as approved biopharmaceuticals. Recent validation by COVID-19 is providing particular impetus to the field of mRNA vaccines, and advances in CAR-T-cell-based therapeutic approaches will continue to drive the developmental pipeline in this field, particularly against solid tumors. Although only two gene therapy products based upon viral delivery were approved in the current survey period (Zolgensma and Luxturna), several such products are showing success in clinical trials. Indeed, one additional such product (BioMarin’s hemophilia A product Roctavian) has recently gained approval in Europe, and a biological license application (BLA) is currently being considered by the FDA. Roctavian’s active substance, valoctocogene roxaparvovec, comprises a nonreplicating recombinant adeno-associated viral vector housing a functional human factor VIII cDNA under the control of a liver-specific promoter. Clinical studies show that increased factor VIII expression was sustained for (so far) at least two years, with the need for additional factor VIII replacement treatment dropping by 97.5%. Reports from industry sources indicate that Biomarin anticipates Roctavian’s list price in Europe to be on the order of €1.5 million euros, net of all discounts.
Biosimilars will also continue to feature with increasing prominence on the biopharmaceutical landscape. Various US-facing reports indicate that almost 100 biosimilars targeting the American market are in clinical development and that cumulative sales of biosimilars over the next five years could total $80 billion. A recent report by Allied Market Research forecasts the global biosimilars market to reach as much as $143 billion by 2031, fuelled by sales of biosimilar mAbs, CSFs, EPO, insulins and hGH. Forecasts can vary, however. A report from Research & Markets predicts that global biosimilar sales will reach $88 billion by 2030, whereas Global Market Insights put the value at $100 billion.
COVID-19 is likely to feature on the biopharmaceutical landscape over the foreseeable future. mRNA and other vaccines are expected to require updating to match novel SARS-CoV-2 variants. Tracking data maintained by the WHO estimates there are currently 172 Covid vaccines in clinical development globally, of which 55 (32%) are protein subunit based, 40 (23%) are RNA based, and 23 (13%) are (nonreplicating) viral vector based.
The biopharmaceutical sector’s impressive response to the global COVID-19 pandemic is likely to inform and accelerate broader innovation in the sector, particularly within the vaccine space. Finally, regulatory experience accrued in the last survey period should accelerate the speed of the drug development and approval processes for future medicines.
Supplementary information
Supplementary Information Supplementary Table 1
Supplementary information
The online version contains supplementary material available at 10.1038/s41587-022-01582-x.
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| 36471135 | PMC9735008 | NO-CC CODE | 2022-12-15 23:15:17 | no | Nat Biotechnol. 2022 Dec 5; 40(12):1722-1760 | utf-8 | Nat Biotechnol | 2,022 | 10.1038/s41587-022-01582-x | oa_other |
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Im Fokus Onkologie
Im Fokus Onkologie
1435-7402
2192-5674
Springer Medizin Heidelberg
2979
10.1007/s15015-022-2979-z
Pneumoonkologie
NSCLC: Holpriger Weg zu neuer Checkpointblockade
Klein Friederike
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8 12 2022
2022
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© Springer Medizin Verlag GmbH, ein Teil von Springer Nature 2022
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==== Body
pmcAntikörper zur Blockade der hemmenden Checkpoints CTLA-4 und PD-1 haben die Therapie solider Tumoren verändert. Das Ansprechen der verschiedenen Tumore auf diese Immuntherapie ist aber unterschiedlich und es gibt primäre und sekundäre Resistenzen. Helfen sollen dagegen Antikörper gegen koinhibitorische Checkpoints wie TIGIT oder LAG-3.
Der Checkpoint TIGIT führt dazu, dass regulatorische T-Zellen (Treg) zum Tumor wandern und im Tumor zurückgehalten werden. Dort haben sie einen immunsupprimierenden Effekt, erläuterte Thorsten Füreder von der Medizinischen Universität Wien, Österreich [Füreder T et al. DGHO. 2022;Abstr V60].
Bei einer Anti-PD-1-Blockade werden die Treg noch stärker immunsuppressiv. Dem sollen Anti-TIGIT-Antikörper entgegenwirken. In der Phase-II-Studie CITYSCAPE wurde der gegen TIGIT-gerichtete Antikörper Tiragolumab mit dem Anti-PD-1-Antikörper Atezolizumab kombiniert, um Erkrankte mit einem nichtkleinzelligen Lungenkarzinom (NSCLC) im Stadium IV in der Erstlinie zu behandeln. Im Kontrollarm wurde Placebo plus Atezolizumab verabreicht. In der Subgruppe von Betroffenen mit einem Tumor, der stark PD-L1 exprimierte (TPS ≥ 50 %), zeigte sich ein signifikanter Effekt der Kombination, bei einer PD-L1-Expression von TPS 1-49 % allerdings nicht [Rodriguez-Abreu D. ASCO. 2020; Abstr 9503]. In der anschließenden Phase-III-Studie SKYSCRAPER-01 wurden daraufhin nur Personen mit metastasiertem NSCLC und hoher PD-L1-Expression eingeschlossen. Dennoch wurde kürzlich berichtet, dass die Studie den koprimären Endpunkt des progressionsfreien Überlebens nicht erreicht hat. Da noch viele weitere Studien mit Kombinationen bisheriger Immuncheckpointinhibitoren mit Anti-TIGIT-Antikörpern laufen, sei das letzte Wort hier noch nicht gesprochen, sagte Füreder.
Auch LAG-3 wird auf verschiedenen Immunzellen exprimiert, darunter aktivierte T-Zellen, dendritische Zellen, B-Zellen und natürliche Killer(NK)-Zellen. Die Funktionen von LAG-3 sind vielfältig und noch gar nicht umfassend verstanden. "Aber wir probieren das bereits aus", berichtete Füreder. In der Studie NEOpredict-Lung wurde der Anti-LAG-3-Antikörper Relatlimab bei Personen mit resektablem NSCLC neoadjuvant mit Nivolumab kombiniert und mit Nivolumab neoadjuvant alleine verglichen. In allen Fällen war die Resektion möglich und das Ansprechen war mit der Kombination etwas besser, aber krankheitsfreies und Gesamtüberleben zeigten letztlich keinen Unterschied [Schuler MHH et al. ESMO. 2022;Abstr S808]. "Es ist sicher zu früh, diesen Ansatz zu beerdigen", meinte Füreder. Zur Therapie des Melanoms ist die Kombination schließlich schon zugelassen. Das Nebenwirkungsprofil der Kombination mache zumindest wenig Kopfzerbrechen - es sei günstiger als mit Nivolumab alleine.
Eftilagimod alpha (Efti) ist ein lösliches LAG-3-Protein, das auf bestimmte MHC-II-Klasse-Moleküle zielt und so Antigenpräsentierende Zellen und CD8-T-Zellen aktivieren soll. In der Phase-II-Studie TACTI-002 führte die Therapie mit Efti zusätzlich zu Pembrolizumab bei Erkrankten mit NSCLC im Stadium IIIB/IV zu einem sehr gemischten Ansprechen, das unabhängig von der PD-L1-Expression war [Felip E et al. ASCO. 2022;Abstr 9003].
"Das lässt uns etwas ratlos zurück", meinte Füreder, der sich unsicher ist, ob da ein großer Zusatzeffekt über die Wirkung von Pembrolizumab hinaus zu erwarten ist. Auch in der Gruppe der LAG-3-gerichteten Therapien läuft eine Vielzahl von Studien mit verschiedenen Wirkstoffen.
Bericht von der Jahrestagung der DGHO vom 7. bis 10. Oktober 2022 in Wien, Österreich
DGHO-Jahrestagug 2022 Dem SARS-CoV2-Virus zum Trotz trafen sich in diesem Jahr deutsche, schweizerische und österreichische Kolleginnen und Kollegen aus Hämatologie und Onkologie in Wien, um in persona aktuelle Aspekte der Diagnostik und Therapie maligner Erkrankungen zu diskutieren.
| 0 | PMC9735010 | NO-CC CODE | 2022-12-14 23:28:32 | no | Im Fokus Onkologie. 2022 Dec 8; 25(6):50-51 | utf-8 | null | null | null | oa_other |
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Educ Inf Technol (Dordr)
Educ Inf Technol (Dordr)
Education and Information Technologies
1360-2357
1573-7608
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11495
10.1007/s10639-022-11495-6
Article
Promote collaborations in online problem-based learning in a user experience design course: Educational design research
http://orcid.org/0000-0002-5901-9924
Zhu Meina [email protected]
Zhang Ke
grid.254444.7 0000 0001 1456 7807 Learning Design and Technology, Wayne State University, Education Building, 5425 Gullen Mall, Detroit, MI 48202 USA
7 12 2022
119
20 8 2022
28 11 2022
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Since the Covid-19 pandemic, there has been an increasing growing need for learning experience or instructional designers. As a result, online courses on user experience (UX) design for learning are in demand to prepare those much-needed professionals. This paper reports the first circle of educational design research (EDR) on such a completely online problem-based course using group contracts and peer-evaluations to promote collaborations. Multiple datasets were collected from a range of data sources from a graduate-level course and were analyzed by two researchers. The study yielded several meaningful results: (1) group contracts helped students work smoothly and keep goals focused on collaborative learning in PBL; (2) the instructor could facilitate the group formation process; (3) peer evaluations helped group collaboration and monitoring; and (4) collaborative technologies are critical for collaboration. The findings also revealed important design principles for collaborative learning in PBL that can be used in similar courses. In addition, this study provides a successful example of how to teach UX design in an online PBL environment, and sheds light on how to further improve similar practices while contributing to the limited body of research on UX design for learning.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10639-022-11495-6.
Keywords
Problem-based learning
Collaborative learning
Online education
User experience design for learning
Human–computer interaction
User experience design
==== Body
pmcPurpose
Online learning as an instructional delivery format has been around for approximately three decades. However, due to the COVID-19 pandemic, the need for online learning strategies exploded when over 1.5 billion students and youth, 87% of all students worldwide, were suddenly faced with university and school closings as of March 2020 (UNESCO, 2022). As a result, the course modality switched to online education at many schools, colleges, and universities (Gardner, 2020). Many instructors suddenly realized that they needed to change their approach to engage students who were often physically separated from each other. One of the strategies to engage online learners and develop higher-order thinking skills (Delialioğlu, 2012) and learning achievement (Schmidt et al., 2011) is problem-based learning (PBL). PBL, in which learners collaborate in a group to solve problems, has great potential to develop learners’ critical thinking, creative thinking, and problem-solving skills, and to support knowledge acquisition (Hmelo-Silver, 2004; Lajoie et al., 2014). A typical PBL assignment involves identifying problems, collecting and analyzing data, negotiating with group members, reflection, and presentation of the results (Glazewski & Ertmer, 2020; Kim et al., 2016). Since learners take the primary responsibility for their learning in PBL, they need to be motivated and engaged, and effectively and collaboratively manage and monitor learning progress and seek information and support. However, research has shown that learners often do not have these skills (English & Kitsantas, 2013). Group members typically encounter challenges, such as social loafing (Lee & Lim, 2012), lack of motivation, negative attitudes, lack of responsibility for learning, and management, all of which hinder effective PBL (English & Kitsantas, 2013). Therefore, learners need instructors to facilitate and support group collaboration and problem-solving skills through scaffolding (Savery, 2006).
Moreover, PBL could be one of the great approaches for courses on learning experience (LX) design. LX is an interdisciplinary area that involves both user experience (UX) design and instructional design (ID) (Schmidt et al., 2020). As a new, emerging area, it is critical to prepare future LX designers with the necessary skills to develop courses, particularly online. However, very little research and few practical examples exist for online courses focusing on LX/ UX design. This educational design research (EDR) study aimed to fill this gap by addressing two essential aspects: (1) provide an authentic example of such a course, and (2) conduct the first circle of EDR and explore selected strategies in the course. This study also explores students’ perceptions of their collaborative PBL. The primary aspects of this research include: (1) designing and developing a course focusing on UX design for learning, (2) using various methods to evaluate the effectiveness of the instructional approaches, (3) grounding findings in theory, and (4) establishing general design principles.
Theoretical framework
User experience design for learning
LX design consists of two primary interactions: (1) with the learning environment and (2) with learning spaces (Tawfik et al., 2022). Interactions with learning environments include customization for learning, expectation of content placement, functionality of the components, interface terms aligned with learners’ existing mental models, and navigation. And the interaction with the learning space consists of engagement the content, dynamic interaction, perceived value of technology affordance for learning, and scaffolding (Tawfik et al., 2022). LX design typically leverages UX design approaches to improve learning. UX refers to “a person’s perceptions and responses that result from the use or anticipated use of a product, system, or service” (International Organization for Standardization [ISO], 2010, Terms and Definitions section, para 2.15). UX originated and has been used in multiple disciplines, including human–computer interaction (HCI), interaction design, and cognitive psychology (Gary, 2020). However, in education, UX design for learning has been relatively limited compared to the more common user-centered design (UCD) approaches for learning design (Baek et al., 2008; Ebner & Holzinger, 2007; Fernandez-Lopez et al., 2013).
UX and traditional ID have some similarities, including a focus on UCD, as well as differences such as the processes and concepts. Gary (2020) compared the terms and conceptual vocabulary used to describe design activities in ID and UX and emphasized that the two fields have used different terms to describe design processes. For example, ID has traditionally included analysis, design, development, implementation, and evaluation, and UX has included user research (personas, scenarios, contextual inquiry, ethnographic engagement, interviews), prototyping (sketches, wireframing), and user testing (Gary, 2020).
To create an effective learning experience, one of the approaches is to leverage UX processes and approaches for LX design. However, teaching strategies in UX courses vary. Consequently, it is important to create effective courses on UX design for learning. Given that both theory and practice are essential in the UX field (Churchill et al., 2013), UX courses typically include both lectures and laboratory sessions (Koppelman & Dijk, 2006; Moroz-Lapin, 2009) so students can apply the theories in practical projects. For practice, students typically work on practical projects in groups of 3–6 students (Culen et al., 2014; Urquiza-Fuentes & Paredes-Velasco, 2017). More specifically, some UX courses have leveraged PBL to help students solve authentic problems in education (Koutsabasis & Vosinakis, 2012; Nordahl & Serafin, 2008).
Problem-based learning
PBL, based on constructivism theory, is an instructional approach that emphasizes learners’ autonomy, integrates theory and practice, and implements knowledge and skills to solve ill-structured authentic problems (Barrows & Tamblyn, 1980; Savery, 2006). In PBL, students work in small groups to learn and solve problems, and instructors are facilitators (Hmelo-Silver, 2004). PBL has several unique characteristics: (1) students have ownership of their own learning, (2) the problems are ill-structured, (3) it involves multiple disciplines, (4) students collaborate in a group, (5) PBL enables students to apply individual knowledge to solve problems, (6) the learning process is monitored, (7) PBL involves self-and peer- assessment, (7) the problems are authentic, and (8) both the knowledge and process are important (Savery, 2006). In online learning, PBL has been used to enhance students' higher-order thinking, knowledge acquisition, and learning outcomes (Delialioğlu, 2012; Hmelo-Silver, 2004; Lajoie et al., 2014; Schmidt et al., 2011). In addition, group collaboration plays an important role in enabling students to take responsibility for their learning and collaborate successfully with peers in PBL (Sun et al., 2022).
Collaborative learning
Collaborative learning as an educational approach provides an opportunity for students to work in a group to solve problems or create a product (Johnson et al., 1998). It includes five essential components: (1) positive dependence with common goals; (2) individual accountability; (3) encouragement for interaction and enhanced group communication; (4) education on soft social skills; and (5) reflection on the group process and learning from group members (Johnson & Johnson, 1989). Self-regulated learning (SRL; Wong et al., 2021) and socially shared regulated learning (SSRL) are critical for successful collaborative PBL (Bannert et al., 2014; Hadwin & Oshige, 2011; Rogat & Linnenbrink-Garcia, 2011). SRL refers to learners adjusting their learning process to achieve individual learning goals (Zimmerman, 2000), while SSRL highlights the social perspectives, such as interactions among team members to realize shared learning goals (Hadwin & Oshige, 2011; Järvelä & Hadwin, 2013; Malmberg et al., 2017).
Challenges exist in collaborative learning. The challenges include: (1) teamwork, (2) communication, (3) personal priorities, and (4) external constraints (Järvenoja & Järvelä, 2009). Researchers indicated that collaborative learning does not naturally happens and needs well-designed instruction to facilitate it (Pang et al., 2018).
To support successful collaborative PBL and facilitate students' SRL and SSRL, a new framework, namely 4S PBL, has been proposed. The framework provides detailed strategies for facilitating learning in four domains (i.e., motivation, affect, cognition, and behavior) in the three primary stages of PBL (i.e., launching the project, creating solutions, and concluding the project). Two of the strategies that support collaborative PBL are a group contract and peer evaluations.
Group contract and peer evaluations
The approach to forming a group and maintaining active participation in the group is critical in online collaborative learning since the success of group learning depends on the quality of student interaction in a group (Scager et al., 2016). This process may require instructor facilitation (Kirschner, 2001). Another strategy is to use a contract to facilitate learners’ group learning behavior (Volet & Mansfield, 2006; Zhang & Ge, 2006). Knowles (1986) proposed a learning contract for learner-centered instruction to foster personalized learning. A learning contract outlines the actions that the student expects and promises to take to achieve learning goals and is signed by the individual student and the instructor. The advantages of the learning contract are that it provides structure and support, engages students in learning, regulates their behavior, and creates an open communication platform among students and the instructor on learning goals and the approaches to achieve them (Frank & Scharff, 2013). A group contract, as a learning contract, helps groups create a shared understanding of group work and collaboration behaviors. It can be created by the instructor or generated by group members or formulated cooperatively by the instructor and the students (Zhang & Ge, 2006).
Besides a group contract, requiring peer evaluations is another effective approach to help collaborative work by motivating students, reducing free-rider issues, and engaging group members (Lin et al., 2015). Anonymous peer evaluations and recognizing individual contributions could motivate learners to actively participate in group projects.
This study aims to (1) document and critically analyze the first circle of EDR, (2) examine the impact of a group contract and peer evaluations in supporting collaborative learning in online PBL, and (3) explore students’ perceptions of their learning experiences. The following research questions guided our inquiry:How did the group contract and peer evaluations support student online collaborative learning in PBL?
What challenges did students encounter in online collaborative learning in PBL?
Method
This study adopted the EDR approach using a qualitative approach to improve teaching practices through different iterations and to develop design principles and theories (McKenney & Reeves, 2018). EDR aims to make an impact on real education interventions and form or validate theoretical concepts. EDR typically has several basic characteristics indicating that the study findings are related to the design process in that it (1) refines theory and practice, (2) is conducted in authentic, real-world settings, (3) is iterative, and (4) is contextual (Wang & Hannafin, 2005).
We aimed to (1) investigate the effectiveness of the interventions, (2) track the process of iterative design, development, implementation, and evaluation, and (3) develop design principles and theories for UX design for learning technology courses in this project. EDR allowed us to continually design, evaluate, and re-design instructional interventions. This approach also provided an opportunity to conduct iterative revisions. Thus, EDR principles guided our efforts. The different data sources can increase the trustworthiness of the study through data triangulation.
McKenney and Reeves (2018) created a generic model for conducting design research in education. This model has three primary features: (1) the model has three core iterative phases: investigation/analysis, design/prototyping, evaluation/retrospection; (2) it has a dual focus on theory and practice (i.e., integrated research and design processes, theoretical and practical outcomes); and (3) it is planned for implementation and spread and is contextually responsive.
Guided by the model from McKenney and Reeves (2018), this project, designing, assessing, and revising the course, was conducted in two cycles over two years. Theoretical and pedagogical tasks and activities were used to improve students’ collaborative learning and satisfaction. This paper focuses on the first circle of EDR.
Context
The context of this study was an online graduate-level course at a public university located in the Midwest of the U.S. in winter semester, from January to May 2021. This course aimed to introduce UX design principles and processes for learning. The outcomes of this course were that upon successful completion, students would be able to apply current best practices in UX design and employ the fundamental principles of UX design to create an effective learning experience. Participants were graduate students recruited from the class who were majoring in learning design and technology (see Table 1). The nine participants had full- or part-time jobs while taking the course.Table 1 Participant information
Pseudo Name Gender Enrolled Program Professional background
Rebecca F Ph.D Health professional
Kate F Master Lecturer in higher education
Kacy F Master eLearning Specialist
Henry M Master School staff member (K-12)
Selina F Master Corporate instructional designer
Jane F Ph.D Program coordinator in higher education
Laura F Master Technology integration specialist in K-12
Amy F Master Graphic designer in higher education
Hellen F Master Medical educator in a hospital
The online PBL UX course environment
The design of this course was guided by constructivism (Vygotsky, 1978), which emphasized students’ active construction of knowledge by integrating new knowledge into existing knowledge in social interaction. Extending the PBL literature, the authors created a new framework, 4S PBL, to promote and facilitate self- and socially-regulated learning in online PBL, especially in technology-intense courses. This course was created based on general PBL principles and 4S PBL strategies. The course was a 15-week asynchronous course with several synchronous meetings with guest speakers and weekly synchronous office hours (see Table 2). The instructor recorded weekly 5–10 min instructional videos. The course was hosted in Canvas, a popular learning management system in higher education, and was organized in weekly modules. The typical module included weekly learning objectives and a to-do list, instructional videos, a reading list, online discussion, hallway conversations, and assignments. The weekly learning objectives and to-do list set overarching goals for the week and actions/tasks students should complete during the week. The instructional videos included lectures on the content knowledge of the week. Reading lists described all the readings that students needed to read. The online discussion forum provided a platform for students to discuss, reflect, and share their thoughts about the topic of the week. Hallway conversations were used as a channel for students to ask the instructor and teaching assistant questions.Table 2 Primary instructional design component in the UX course
Design component Detailed descriptions
Course participation Online engagement (self-introduction, discussion board responses, readings, peer evaluation & interactions)
Assignments Learning product analysis (I)
Learning design problem description (G)
Design project plan (G)
Sketches of design ideas (paper) (I)
Create your personas and scenarios (G)
Storyboard (G)
Mapping out inputs and outputs (G)
Wireframes of your design (digital) (G)
Interaction with the instructor Weekly online office hours
Hallway conversations in discussion forum
Emails
Scheduling individual meetings
Note: I: individual; G: group
The course focused on using the PBL approach for learning. Thus, the assignments of the course were based on PBL and a design thinking approach. Specifically, the assignment design was guided by the design thinking process (i.e., empathize, define, ideate, prototype, test), which is commonly practiced in the UX design field. The first stage was to obtain an empathic understanding of the real problems that students wanted to solve. The next stage was to define the core problems based on observations and synthesis. The third stage was ideation, when the designers were ready to start generating ideas and brainstorming solutions. Then, the design team started to create some inexpensive products using the ideas generated in the prior step for experimentation purposes. The fifth step was the user test, where the design team tested and evaluated the product with target users. However, the fifth step was not the end of the process. It was an iterative process in which the user test results could be used to refine and revise the product.
The first individual assignment, related to empathy, was learning product analysis, in which students critically analyzed the existing learning management system (LMS) and identified the pros and cons and areas that needed improvement. Then, students formed a team based on their background and expertise. As a group, they identified the design problems that they had identified for their project at the beginning of the class. As a team, they then developed a project plan that could guide their project throughout the semester. Once they had a plan, each person sketched possible solutions for the problems and brainstormed with other team members. To make the design ideas more concrete and easier to communicate, they created personas and scenarios, storyboards, mapped out inputs and outputs, and developed wireframes and prototypes as a group. Guided by the user-centered approach for the design, students conducted user tests to gather feedback from users and then finalized their design solution. In the end, students wrote a project report and presented their project in a synchronous online meeting. At the end of the course, individual students reflected on what they achieved and areas to improve in their project and collaborative process. Reflection is critical for designers so they can engage in constant improvement (Schön, 1983).
Group collaboration is critical for online PBL. To facilitate online collaboration, a group contract was adopted to support teamwork. Students formed three groups of three members based on their interests and background. Once they formed the group, students in one group met synchronously to develop their group contract, including the communication channels, frequency of meetings, and approaches to solving conflict. As a team, they were also encouraged to constantly reflect on their collaborative process and the project progress.
In addition, to better support group work, a peer evaluation was used to encourage students to actively contribute to the group project. The instructor graded the group project based on the quality of the group assignment (70%) and contributions to the group project (30%). The contribution to the group project was measured by peer evaluations. To do so, the instructor created a peer evaluation online survey via Qualtrics, an online survey tool. The peer evaluation questions included six 5-point Likert scale questions and three open-ended questions collecting data. For example, the Likert scale questions included attendance at group meetings, contributions to the group discussion, communication etiquette, and collaborative attitude. The open-ended questions related to specific comments about individual group members, and major issues. Once students submitted their group project, they submitted the peer evaluation through Qualtrics.
Last, the researcher-instructors consistently integrated various scaffolding strategies to foster collaborative PBL in a timely and dynamic manner. For example, the instructors held synchronous online office hours every week to address students’ questions and cleared up any confusion regarding the project and group collaboration. In addition, students were encouraged to schedule individual meetings with the instructor for help. Thus, the instructors played a key role in facilitating students’ PBL.
Data sources
The data sources of this study included: (1) students’ course evaluation, (2) students’ evaluations of peers’ participation and contributions throughout the semester, (3) students’ final reflection survey, (4) a group contract, and (5) the instructor’s reflection. The final course evaluation was conducted at the end of the semester and administrated by the university. The peer evaluations were conducted after each group project, where individuals evaluated their group members. The final reflection survey related to students’ achievement, challenges, experience with group collaboration, and suggestions for the course. Sample questions in the reflection survey included, “What went well in your group collaboration?” and “What needs to be improved in your group collaboration?” For the group contract, each team submitted their group contract at the beginning of the course. All the assignments throughout the semester were also used as data sources. Last, the two instructors wrote reflection notes regarding the challenges encountered and lessons learned.
Data analysis
For the qualitative data from the course evaluation, peer evaluations, group contracts, and reflection survey, the researchers conducted an inductive content analysis (Elo & Kyngäs, 2008). The researcher went through all the data to get a general sense of these components. For data from group contracts and reflection survey, the open coding, grouping, categorization, and abstraction were conducted. The data from the course evaluation and peer evaluations were analyzed using descriptive statistics. All data were then triangulated to ensure the trustworthiness of the study.
Findings
Overall, students were satisfied with using collaborative PBL in the online course. Students rated the course and the instructor, on average, 4.3 out of 5 in the final course evaluation. Although this course was an elective for all of the students, they rated whether they wanted to take this course 4.5 out of 5, on average. Students’ final artefacts also demonstrated a great success in the semester-long learning experience in this course. For examples, one group designed a learning management system integration feature to address the problem that Canvas does not integrate well with specific school district information systems, such as MISTAR (see Fig. 1).Fig. 1 Canvas MISTAR integration core step interfaces. Images were intentionally blurred to protect participant’s personal or identifiable information
Research question 1 (RQ#1): How did the group contract and peer evaluations support student online collaborative learning in PBL?
All three groups finished a group contract at the beginning of the semester. The group contract helped students discuss and consider diverse aspects in their group collaboration for SSRL, such as their communication approach and frequency of meetings, individual group members’ contributions and roles, time management, collaborative working space, and strategies to solve possible conflicts. For communication, the three groups identified diverse approaches for communication, including both synchronous and asynchronous meetings. Two groups adopted Microsoft Teams, while one group used Zoom for synchronous communication. These two tools were available to students and faculty for free. All of the groups met synchronously at least once each week. For asynchronous communication, emails, phone text, and Google Docs were used. For regular communication, they used emails or Microsoft Teams and indicated that they checked these tools daily. In addition, phone texts or Teams chat were used as time-sensitive communication tools.
For individual group members’ contributions, all three groups mentioned that they used the weekly meeting to specify tasks for each group member. For example, the contract in Group A stated, “Each task will be evaluated prior to the due date. We will meet to discuss each project and assign individual tasks and due dates.” Similarly, Group B stated in the contract, “As we get into our project, we'll use our weekly meeting to specify additional tasks.” Some groups defined the role of individual members based on the project and rotated roles. For example, Group C indicated that “The roles will shift based on project need. We plan to rotate the roles, so each person has an opportunity to perform each role.”
Regarding the timeline, all three groups stated in the group contracts that they would finish the group projects ahead of time. For example, Group A’s contract indicated, “All final draft communications for submission will be made one day prior to assignment due date.”
Regarding collaborative working spaces, all the three groups identified some digital tools for collaboration such as Teams, Google Docs, or OneDrive. For example, Group C stated in the contract, “Our group will use [Microsoft] Teams to share documents and communicate updates on tasks throughout the week.” The final reflection survey results discussed their group contract statements. For example, Kate expressed how Microsoft Teams helped her group collaborate in the reflection survey:Our group met every Sunday on MS Teams and made a plan for the week. We housed all documents on there and created a folder for each assignment. This system allowed all three of us to contribute. A few times, group members were unable to work on specific segments. However, since all content was housed on Teams, a different group member took on a more prominent role. The Teams’ technology allowed us to chat and communicate very quickly and keep each other updated.
When one member failed to deliver their part on time, the group contract stated that the other two members would try to step up and help out if the communication was made in advance. If one group member just did not work without any reason, they would notify the instructor. For example, Group B stated,First, we'll make several attempts to reach out via multiple channels (Teams, text, email). If we lose track of someone, the remaining two people will divide and conquer. The remaining two people will have transparent conversations with each other and the professor about the situation and notify the professor in a timely manner.
If they had disagreements or conflicts, three groups suggested open communication and democracy in the group contracts. For example, Group B’s contract indicated, “If we have a disagreement about how to approach part of the project, we could each show facts or reasons why we feel a certain way to help others understand. Additionally, in situations of disagreement, we can move forward by voting (best 2 out of 3).” In addition, some groups emphasized the importance of respect in group collaboration. For example, Group A’s contract stated, “We will address all conflicts and disagreements directly and respectfully.” These indicated that learners socially shared regulated their behavior, motivation, and cognitions using group contract.
The last stage of self-regulated learning is evaluation. Consequently, in the peer evaluations and final reflection survey, most students reported that their group worked very well throughout the semester, and students received high peer evaluation results. The average score of each student's peer evaluation ranged from 4.9–5 out of 5. For example, Ellen commented, “Our group worked well and collaborated effectively to execute the assignment.” Amy also expressed her satisfaction with group work, “Each week I am amazed at the team effort my peers put in.” Similarly, Henry said, “We worked well together on this assignment.” In the individual final reflection survey, Henry expressed the achievement that he was proud of: “Completing a project in a design team. Initially, I was hesitant about working in a group, but I was able to learn how to manage that. I felt as though I learned some of my strengths in a design team.”
Students reported that the group contract played an important role in group collaboration in PBL. Group contracts helped them with effective communication and created shared learning goals. Laura shared her thoughts on how the group contract helped their communication in the reflection survey:I think the best part of our group collaboration was the communication. This was the first group where we exchanged phone numbers at the beginning of the semester, and all agreed to communicate via text or email as necessary. Being able to text the group made a huge difference in communication and effectiveness, in my opinion. We all agreed to use those forms of communication in our team contract, so no one ever felt like boundaries were being crossed.
Jane also expressed that the group contract helped them communicate and helped them create shared goals in the reflection survey:There are a few things that I believe went well in my group’s collaboration: 1) we were effective communicators. At the beginning of our newly formed group, we amended our group contract to outline our expectations and set the intention for the group. We then followed through with the contract by establishing ways to communicate through a Teams channel... 2) we had a shared goal. Each member of our team wanted to be successful in this course. Since this was a desire of each person, it made for commonality and bond amongst the team. It also helped us to maintain focus on each task and how to work together to achieve the tasks.
It is worth noting that graduate students as those in this course are typically working professionals with full time jobs and family obligations. In addition, online students may be from different time zones, including those outside of the USA. Thus, personal cell phone is not necessarily the preferred way of communication.
RQ#2: What challenges did students encounter in online collaborative learning in PBL?
Students had several challenges in group collaboration. First, they struggled with group formation after some students withdrew from the course. The group was formed by the students, with three or four students in a group in Week 1. However, one student from a group of three members withdrew from the class in Week 3. By that time, the groups had already completed their group contract and started working on the design problem. As a result, three groups had an uneven number of students: two, three, and four students, respectively. Considering the group dynamics for PBL, the instructor suggested that one group member from a group with four members move to the group with two members. It was complicated to negotiate and coordinate adjusting the groups as students were afraid of changing to a new group, which brought uncertainty to the group morale and atmosphere. One student who had a change in group members shared the issues he encountered in the peer evaluation: “I just wish we could have started together rather than shuffling groups after the start.”
Another critical issue also related to group formation: a lack of information about other students’ skills and strengths before forming the groups. Henry suggested, “I think what would have been helpful is a list of skills and times available prior to even selecting team members. We all work and find a regular meeting schedule is difficult.” Kate suggested using the survey to gain knowledge about group members’ skills and backgrounds as “most of the class did not know each other and finding group members in the first few weeks was anxiety-inducing for most.”
Third, most students in the class had full-time jobs or families, so some life events may have influenced their group collaboration even though they had a group contract. For example, Hellen said, “This week we all struggled with other life events which led to some confusion in the meeting; however, we as a team were able to communicate and get things done by the due date.” Moreover, Laura said,I am most proud of how well our group worked together. Despite our full-time work schedules, multiple class course loads, childcare, surgeries, quarantines, and pregnancy, we were all able to commit to working together as a team. Both Amy and Hellen were fantastic communicators, and I found that collaborating on assignments with them was easy and beneficial. I'm proud of all of the work that we accomplished.
The course involved the use of Adobe XD and Figma software for the wireframe and prototype. Adobe XD is a design tool, developed and published by Adobe Inc. It can be used to create wireframe and click-through prototypes in both macOS and Windows system. Figma is a tool for interface design with both collaborative web application and desktop applications for macOS and Windows. Figma is used for vector graphics editing and prototyping. Although the students could access these tools for free, they said that they encountered challenges regarding collaborative use. It is critical to have software that enables students to collaborate together. For example, Kate said,One significant challenge was access to the software…The limited access meant the collaboration was very challenging since not everyone could work on it simultaneously or at the same level. If the course could provide access to software for all the students, that would be amazing.
Most students reported that they liked the peer evaluations. However, it was challenging to complete a peer evaluation for each group project, and students felt that it was difficult to keep track of the evaluations. For example, Kacy expressed her struggle with keeping track of the peer-evaluation surveys,I think the surveys were a bit challenging to keep track of. I wonder if a survey early in the semester, one mid-semester, and one at the end of the semester would suffice. I've never missed assignments like this before in my life, and I am excessively stressed out about the impact that had on my grade with how hard I worked this semester.
Laura suggested that the course should “make weekly peer-reviews optional and give students a choice to fill out one at the end of the semester instead.” For other students, completing a peer evaluation for each group project was also considered trivial when the group collaboration went well. Helen said,I did not care for the week-by-week peer evaluations, but that's probably because everything went smoothly with my group. I never had anything specific to report on, but I can see how it would help in groups where someone was missing meetings or not contributing fully. I wish the weekly peer evaluations were optional and could be exchanged for an end-of-the-semester review if there were no issues arising week by week.
Discussion
This paper reports the first circle of EDR and the use of two key strategies, a group contract and peer evaluations, to support collaborative learning in online PBL courses. The research explored students’ perceptions of the learning experience, particularly strategies they used for group collaboration, and the challenges they encountered. We found that group contracts helped students work smoothly and keep goals focused on collaborative learning in PBL. This finding supports the conclusions by Frank and Scharff (2013).
Another finding is that students’ life events may influence the group collaboration process, even though students in this study handled it well and demonstrated mutual respect. This success can be attributed to creating a group contract that helped them think through different situations in the group collaboration process. As Zhang & Ge (2006) found in earlier work, group contracts help students create a shared understanding of the group work. The group contract could be created by the instructor or student group members or generated cooperatively by both the instructor and group members (Zhang & Ge, 2006).
Regarding group formation, as suggested by our previous work, Zhang & Ge (2006), this study found that the instructor could facilitate the group formation process. One strategy is that the instructor could survey all of the students regarding their skills, strengths, education, and working background, and then assign students to different groups. Alternatively, the instructor could encourage students to share their information in the class discussion forum so they could get to know each other better in terms of skill sets and be able to form groups on their own. Occasionally, group members may need to change groups, so the instructor could facilitate changing the groups and help them adjust to different groups, and revisit the group contract. Regarding the size of the groups, this study found that a group of three works well, which aligns with prior studies that 3–6 students for group projects are appropriate (Culen et al., 2014; Leslie, 2020; Urquiza-Fuentes & Paredes-Velasco, 2017). It may be even more important in online courses to keep the group size relatively small, given that students need to navigate out-of-class tasks and time.
For peer evaluations, most students liked their group members and evaluated their peers highly, which supports Lin’s et al. (2015) statement that peer evaluations could reduce free-rider issues and keep learners engaged. In this study, given that group collaboration went well for the majority of the groups, some students stated that a peer evaluation for each assignment was tedious and preferred to have them be optional or only at the end of the semester. Thus, the instructor may constantly monitor the peer-evaluation results and consider adjusting the peer-evaluations and making them optional or less frequent. More detailed strategies on how to effectively leverage peer evaluations need to be explored, including the frequency and the timing.
Given that both theory and practice are essential in the UX field (Churchill et al., 2013), this UX design for learning course involved hands-on activities using digital technologies to create the final project. Moreover, based on activity theories, “instruments” is one of the important elements along with “object,” “subject,” “community,” “division of labor,” and “rules” (Engeström, 2001). Therefore, in group collaboration, selecting the appropriate tool or instrument is critical. This study found that students encountered challenges regarding working collaboratively on a project using UX technologies. The Figma tool used in this class does have a free group collaboration function. Adobe XD also provides group collaboration functions; however, we provided a virtual desktop for students to access, which does not support collaborative group work. Due to the high cost, we did not purchase collaborative accounts for the students. It is critical to think through the collaborative technology used and the cost-benefits in the course design.
The research findings of this study support a few imperative design principles for collaborative PBL in similar online courses, including (1) balancing students’ autonomy and instructors’ facilitation or interventions in group formation, (2) encouraging group goal setting and constant reflections, (3) providing opportunities for peer-feedback in collaborative PBL (Scager et al., 2016; Volet & Mansfield, 2006; Zhang & Ge, 2006), and (4) considering accessibility, affordability, and cost-benefits of technology use for group collaboration.
Limitations and future research
As a first cycle of EDR, this study is limited in its scope by nature. First, the context of this study was a small graduate class with. Thus, applications of the findings of this study in large classes should be approached with caution. Future research is recommended to verify similar strategies in large online classes and with different body of students. Second, most participants in this class were non-traditional adult learners with full-time jobs and family obligations. It should also be noted that this was not a required course, so the students who chose to attend were a self-selected group with likely a higher level of motivation. Thus, the findings of this study may not apply to other students with different backgrounds. Future research could experiment with the strategies at different educational levels and in different settings. Last, despite that this study does not include detailed description about the course design and development process, sufficient information is provided regarding the context of the study, which avoids distracting readers from the purpose of this research study. Future research could share a practical design case study focusing on the design and development process and final course design to help instructional designers or educators who are interested in designing similar courses in the future.
Implications for practice
This study provides practical implications for courses utilizing online PBL, collaborative learning, or UX design, respectively. First, using group contract to set expectations for group collaboration and communication is important. It avoids potential conflicts due to lack of mutual understanding about group collaboration (Zhang & Ge, 2006). Second, peer evaluations incentivize active participation and meaningful contributions while minimizing social loafing in group assignments and promoting collaborative learning. Last, for online courses, like user experience design, that involves using learning technologies or tools to work on hands-on activities, it is critical to consider whether the tools support smooth group collaboration or not.
Conclusion
Group collaboration plays a critical role in problem-based learning (PBL), but it also has challenges in user experience design for learning courses. This study indicated that (1) group contracts helped students work smoothly and keep goals focused on collaborative learning in PBL; (2) the instructor could facilitate the group formation process; (3) peer-evaluation helped group collaboration and monitoring; and (4) the instructor could streamline technology used for collaborative projects. The findings confirm that strategies like group contract and peer evaluations support online PBL, through self- and socially-shared regulated learning as in the 4S PBL framework. With the increasing demand for UX design professionals and the lack of online training opportunities to prepare qualified UX designers, this timely study provides a successful example of how to teach UX design in an online PBL environment. It also sheds light on how to further improve similar practices, while contributing to the limited body of research on UX design for learning. As a first-cycle of the EDR, this study also sets up a foundation for future studies to strengthen and extend the research on online PBL and collaborative learning in authentic contexts.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 24 KB)
Availability of data and materials
The datasets used and/or analyzed during the current study are not publicly available due to their personal and private nature but are available from the corresponding author on reasonable request.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Article
Colonial Biopolitics and the Great Bengal Famine of 1943
http://orcid.org/0000-0003-2721-9064
Mallik Senjuti [email protected]
grid.266515.3 0000 0001 2106 0692 Department of Geography and Atmospheric Science, University of Kansas, 1475 Jayhawk Blvd, Lawrence, KS 66045 USA
6 12 2022
117
23 11 2022
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An estimated 3 million people died due to the Bengal famine of 1943. The purpose of this article is to theorize the Bengal famine through the lens of colonial biopolitics. The colonial strategies and utilitarian principles by the British authorities exacerbated the Bengal famine. Utilizing Foucault’s concept of biopolitics, I point out how the British viewed Indian bodies discursively. To reaffirm their sense of superiority, they reduced their Indian subjects to animal-like beings’ incapable of controlling their own reproduction. In order to fulfil British goals, Indian people were forced to participate in the war effort. This paper situates the local and global politics of the famine as they were wrapped up in the geopolitics of World War II, during which the British colonial authorities were far more concerned about a Japanese invasion of South Asia than they were with the lives of people dying of hunger. The article highlights how the implementation of racist policies worsened the famine since it was a product of wartime priorities and calculations. I argue that the Bengal famine of 1943 is a historic tragedy of the colonial past, which was transformed into a socially constructed catastrophe by the British colonizers.Geographers have never studied the Bengal famine of 1943, and one of the principal purposes of this paper is to fill this void.
Keywords
Colonial biopolitics
Famine
Bengal famine of 1943
Governmentality
Colonial authorities
War
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pmcIntroduction
I hate Indians. They are a beastly people with a beastly religion. The famine was their own fault for breeding like rabbits.
–Winston Churchill (quoted in Choudhury,; 2021, p. 1; Portillo, 2007; Tharoor, 2010).
Churchill’s words seem shocking today, but they reflected orthodox British imperial attitudes toward Indians in the mid-twentieth century. Tragically, this dehumanization carried significant policy implications that affected the lives of millions, notably during the great Bengal famine of 1943. Several scholarly works have examined the Bengal famine in disciplines like economics (Goswami, 1990; Sen, 1977), history (Islam, 2007; Mukherjee, 2015; Tauger, 2003), and English literature (Bhattacharya, 2016), but geographers have never contributed to this body of work. This paper seeks to fill this void.
Geographical interpretations of hunger and famine have become more sophisticated over time. Scholars in famine studies who examined the complex phenomenon of famine gradually realized that famines can hardly be explained by any single, overarching theory (Devereux, 1993); rather, famines reflect complex constellations of social and environmental forces. A predominant line of thought was that of Malthus, who blamed the occurrence of food shortages on overpopulation and these Malthusian beliefs were common among British colonial administrators who interpreted famine as examples of Darwinian natural selection (Tauger, 2003). The idea of ‘complex emergencies’ introduced by Keen (2008) and later adopted by the UN is also worth mentioning in this respect, as colonial famines are manifestations of ‘conflict- generated emergencies.’ The United Nations Office for the Coordination of Humanitarian Affairs (OCHA) defined a complex emergency as a “humanitarian crisis in a country, region, or society where there is total or considerable breakdown of authority resulting from internal or external conflict [that] requires an international response that goes beyond the mandate or capacity of any single agency and /or the ongoing United Nations country program” (Keen, 2008, p. 2).
Famine studies have been transformed in recent times and the focus on the causes of famine has been relocated from crop failures to the consequences of economic relations, social structures, and political actions (Tauger, 2003). In essence, the understanding of famine shifted from Malthusian to a much more politically informed one. Concomitantly, as geographers’ understanding of power and politics evolved, they delved into biopolitics (Foucault et al., 2008) and subsequently colonial biopolitics (Nally, 2008). This line of thought emphasized the geopolitics of famine as well as the analysis of colonial bodies, which were subject to European panopticism, monitoring and regulation. Such a perspective is useful in unveiling the political dynamics of famines, how they are produced and reproduced over time and space, and how they were contested.
This paper explores the infamous Bengal famine of 1943 by visualizing it through the lens of colonial biopolitics. It seeks to expose the colonial strategies and utilitarian principles of the British government. It highlights the role of the British government during this crisis and how the British viewed Indian bodies. This essay seeks to comprehend the local and global politics of the famine as they were enveloped in the geopolitics of World War II, during which the British colonial authorities were far more concerned about a Japanese invasion of South Asia than they were with the lives of people dying of hunger. This paper lays out the argument of how the British prioritized their military needs during World War II and how colonial authorities utilized Bengal’s resources and labor power for a war effort even during a catastrophic famine. It also points out how the famine was exacerbated by the British authorities due to their incompetence and implementation of various erroneous governmental policies.
The principal aim of biopolitics is to turn individuals into governable objects, and colonial famines in India provide a perfect context to examine the role of biopolitics in consolidating and expanding bio-inequality in the Global South and how indifferences of those at the top of the power structures disregard the bodies of the poor people forcing them to die. Geographers have never used the concept of biopolitics in their attempts to comprehend the colonial famines that occurred in India. When seen through the perspective of biopolitics, I believe that researching colonial famines in India offers up new research avenues to interpret biopolitics empirically. Adopting a biopolitical approach helps us to critically analyze how the use of statistics and surveys categorized populations based on factors such as race, religion, class, caste, gender, and so on during a disaster. To the best of my knowledge, no geographer has studied the Bengal Famine of 1943 yet, and I believe that this vacuum could be filled profitably given geographers' interest in spaces of violence, development, colonialism and famines. I want to draw attention here to the geographical silences in studying colonial famines in India and how famines in Bengal inform biopolitics in critical geographical thought.
This paper begins with a discussion of the literature on famine, including the critical analyses of scholars in famine studies. The second section lays out a brief account of the historical context of famines in colonial India. The third part delves into the Great Bengal famine of 1943, foregrounding its context and background, debates concerning the famine’s origin, and the role and responsibilities of the colonial authorities featuring the various policies created by the British government during the holocaust. The final section underscores how colonial biopolitics intertwined with power relations and racism affected the most vulnerable members of the society. The conclusion summarizes the major themes and proposes future avenues of research.
Theoretical Perspectives on Famine
The definition of famine evolved from hunger, food shortages and mass starvation to include war, poverty, and market failure (for details see Devereux, 1993, pp. 10–18). Famine relief at the appropriate time was especially considered and researchers began focusing on the food distribution system rather than just on total crop production and food availability (Sen, 1981). The number of people affected, and the mortality rate became important parameters in separating famines from starvation as starvation distresses small groups of people compared to famines. In the event of a famine, people will starve to death unless external food supplies and intervention are provided. In addition to mortality, the concept of ‘excess mortality’ was incorporated (Alamgir, 1980), which consists of more deaths than normally demographically expected. Famines, according to de Waal (2017), are social, economic, and political phenomena; famines are related to production, market, and political or military shocks, even if these aspects are not present at the same time.
Famine theories also transformed through several bodies of research and debates. According to Devereux (1993), prosperous nations seldom face famines because markets are interconnected, and economies are open. As a result, the supply and demand dynamics of food play a significant role in the development of famines. Sen (1982) argued that a major cause of famine is not a sudden decline in food availability, but a sudden redistribution of whatever food is available, highlighting the deeply political nature of famines. Watts (1993) emphasized that while impoverished people are disproportionately affected by famine, hunger, and malnutrition, not all poor people are equally vulnerable to hunger. Vulnerability in this context is crucial here and it is defined by the mechanisms that explain why certain people are more prone than others to suffer from hunger or malnutrition.
Perspectives on famine changed from crude Malthusianism to ‘political events’ and eventually to biopolitics. One example is the paper by Nally (2008), who examined the Irish famine of the 1840s and dissected it from the perspective of colonial biopolitics. Famines were a way of controlling or terrorizing the population so that they would acquiesce to British rule. He highlighted how the Great Irish Famine (1845–1852) was shaped by a particular colonial regulatory order to exploit the catastrophe and maximize state power, thus driving Irish life by a logic both deeply colonial and biopolitical.
Sen (1982) developed the entitlements approach for interpreting famine. In this approach, in a market economy, a person can exchange what he or she owns for a different collection of commodities. He or she can do this exchange either through trading or production or a combination of both. These analyses define why some groups of people who belong to specific occupations such as landless laborers, informal sector workers, artisans, pastoralists, and service- people as vulnerable (Watts & Bohle, 1993). Michael Watts envisaged this exchange-entitlement model as a logical first step in building a historical account of famines in different social formations. Famine scholars such as Amrita Rangasami (1985) similarly reminded us that famine “cannot be defined with reference to the victims of starvation alone and the great hungers have always been re-distributive class struggles: ‘a process in which benefits accrue to one section of the community’ while losses flow to the other” (quoted in Davis, 2002, p. 22).
Colonial Biopolitics and Famine
Michel Foucault (1981) used the term biopolitics for investigating governing practices in modern times. The regulation of the population is referred to as ‘biopolitics’ and was initially accomplished by “diagnosing and dealing with a population that was conceived in the abstract, such as by birth rates, infant mortality, and longevity” (Legg, 2005, p. 139). Foucault (2007) introduced the notion of biopolitics (see Foucault, 2003, 2007), which is defined as “the state-led management of life, death, and biological being a form of politics that placed human life at the very center of its calculations” (quoted in Nally, 2008, p. 716). Food crises and disease were conceived by authorities to be “public health” issues requiring new regimes of calculation, intervention, and direction and these crises are not necessarily accompanied by the prevention of famines or other catastrophes, but rather “allowing them to happen and then being able to orientate them in a profitable direction” (Nally, 2008, p. 717).
Nally (2008), in describing the Irish famine, explored the British government’s famine relief policies and how different laws and disciplines permitted the colonial state to target subaltern bodies. Even though Ireland and Bengal were very different in culture and context, both were British colonies and both experienced famines. In this instance, I am not blindly exporting the model from Ireland to India; rather, I am applying Nally’s broad analytical approach but paying attention to the unique specificities of biopolitics in India. During the Great Exhibition of 1851 in London, held during the Irish famine, Britain's superiority in invention and technology was brazenly showcased to the whole world. Analogous to the 1943 Bengal famine, the British colonial authority blamed the Irish famine on natural causes, accusing nineteenth century Ireland of being overpopulated to avert such misery.
Biopower has long been associated with the management of famines and the implementation of controls, surveillance, and regulations to handle disease epidemics. The concept of biopower evolved from its original connotation of enslavement of bodies and control of the population (Legg, 2006). Among the numerous approaches used to achieve this control were demographic science, the census, statistical analyses, and the interrelationship between a territory’s resources and its occupants. Foucault (2003, p. 256) while describing biopower writes “in a normalizing society, you have a power which is…a biopower, and racism is the indispensable precondition that allows someone to be killed, that allows others to be killed”. He noted that by ‘killing’, he never meant direct killing or murder, but it is indirect murder in every other form i.e., “the fact of exposing someone to death, increasing the risk of death for some people, or, quite simply, political death, expulsion, rejection and so on” Biopolitics thus is the power to ‘make’ live and ‘let’ die.
The various ways by which a state manages its people and territories are referred to as its governmentality (Foucault, 1978). Governmentality, according to Foucault (1981, p. 139; 1979, p. 213) includes the “exercise of discipline over bodies and ‘police’ supervision of the inhabitants of the sovereign’s territory.” As Heath and Legg (2018, p. 1) write “Enacted through institutions (such as the family or school), discourses (such as medicine or criminal justice) and procedures and analyses (such as surveys and statistics), governmentality aims to maintain a healthy and productive population.” Sasson and Vernon (2015) claimed, in analyzing the actions of British authorities throughout past famines, that it was not until the Irish famine that they understood famines could be prevented, and the notions of launching relief began between 1846 and 1883, intending to civilize the colonial people. One notable trait shared by the colonial famines of Bengal and Ireland is that many lives may have been saved if effective policies had been adopted at the appropriate times (Nally, 2011a, 2011b). Several forms of colonial governmentality were called into question, including the organization of famine camps based on who could work 12 h a day and who would just get relief. Residency in the camps was made mandatory, and restrictions were imposed to purchase only specific amounts of grains. Duncan (2020) emphasized the British authorities' state-sanctioned atrocities, such as withholding food from prisoners, evicting people from their lands, and employing police constables, minor court officials, and prison guards while paying them a pittance and entrusting them with the job of enforcing the law.
Famines can also be visualized as another form of excessive geopolitics as Chaturvedi (2003) argued that the partition of India (a direct consequence of British imperial mapping) is a perfect example of excessive geopolitics, tearing apart the country of India into communities of Hindus and Muslims, resulting in never-ending conflicts and violence. He raises the issue of geopolitical imaginations and images of India, posing the question of whose land was partitioned, thereby claiming that excessive geopolitics transforms borders into rivalries such as 'our' land vs. 'their' land. Divisive categories such as religion, caste, tribe, and community were implanted at the core of the social structure of India by the British rulers. Legg (2006) argued that maps were used as a means of regulating space. These maps obscured the tales underlying local struggles and conflicts, and so served as a vehicle for fresh calculations of territorial conquest and forcible land acquisition.
A Brief Geo-history of Famines in South Asia
Famines were frequent phenomena throughout South Asian history, but it was not until the establishment of colonial censuses and vital registration after the 1860s that their demographic characteristics could be accurately analyzed. Famines were also widespread throughout the pre-colonial period, albeit they were far less severe and frequent than during the colonial period (for further information on the famines of the sixteenth and seventeenth centuries, see (Parwez & Khan, 2017, p. 35). It is also worth noting that historians lack extensive data on pre-colonial famines due to low literacy rates in medieval and ancient times, a lack of censuses, modern record-keeping systems, mass media, and other modern modes of communication such as telephones, telegrams, trains, and aircraft. Famines occurred mostly because of the aftereffects and damage of wars and rebellions throughout the Mughal dynasty. Khondker (1986) claimed that pre-British famines were caused by localized food shortages for a limited time, but colonial famines were caused by repeated economic crises when a significant number of people were unemployed with no income to buy food. The reasons for the periodic occurrence of famines in colonial India have been long debated. Although other reasons such as colonial exploitation, population expansion, and global geopolitics were blamed for these calamities, El Niño-induced droughts and the failure of monsoon rains over South Asia were widely viewed as the proximate cause in each of these 19th-century famines (Purkait et al., 2020). There were approximately 25 major famines during the British Raj (the period of rule by the British Crown over the Indian subcontinent from 1858 to 1947 following the dissolution of the British East India Company). Tharoor (2018, p. 235) points out that from 1770 to 1900, 25 million Indians are estimated to have died in famines, compared to only 5 million deaths throughout the entire world from wars from 1793 to 1900.
Among the countless famines that India suffered, Bengal was affected most severely. The first and worst of these was in 1770, which is estimated to have taken the lives of 10 million people The Great Bengal Famine of 1770 was the first of the horrendous famines and it opened the door to future famines in South Asia during colonial rule. The list of major famines during the British rule as pointed out by Tharoor (2016) are: The Great Bengal Famine (1770), Madras (1782–1783), Chalisa Famine (1783–1784) in Delhi and surrounding areas, Doji bara Famine (1791–1792) around Hyderabad, Agra Famine (1837–1838), Orissa Famine (1866), Bihar Famine (1873–1874), Southern India Famine (1876–1877), Bombay Famine (1905–1906) and the Bengal Famine (1943–1944). Purkait (2020) illustrated the 12 major famines during the British Rule (1765-1947), which were unevenly distributed throughout the colony (Fig. 1). The famine in 1876–1878 initiated the foundation of the first Indian Famine Commission of 1880 that consequently laid the commencement of India's subsequent relief system, namely the Famine Codes (Maharatna, 1992).Fig. 1 Major Famines India during British Rule.
Source: (Purkait et al., 2020)
The Great Bengal Famine of 1943
The Bengal famine of 1943 was one of the worst disasters in twentieth century South Asia. It was devastating in terms of its scale, causing three million deaths and occurred during the midst of World War II, when India was under the British Raj. This period during the Second World War, Asia faced several famines simultaneously. Other famines that occurred during the same time as Bengal included the Henan Famine in China (1942–1943), as well as the Vietnamese famine in 1944–1945. The estimates of the magnitude of mortality during the Great Bengal famine of 1943 have been questioned. The famine took the lives of 3 million people, which is the cited maximum (Dyson & Maharatna, 1991). Before the partition of the Indian colony in 1947, Bengal included the state of West Bengal in India and present-day Bangladesh. Its most important and populous city was Calcutta (now Kolkata). From 1772 to 1911, Calcutta was the capital of colonial India. From 1912 until today, Calcutta has been the capital of the state of West Bengal in India.
The main causes of the Bengal famine of 1943 accepted by many researchers after innumerable debates are: (a) an absolute shortage of rice, due to the loss of imports from Burma, and rice exports from Bengal to Sri Lanka (since it was one of the strategic bases against Japan; the British called it Ceylon) and to those regions of the British empire that could not get rice from Southeast Asia after the fall of Burma; (b) the 'material and psychological' consequences of World War II, creating a drastic increase in the price of rice; (c) the incompetence of the government of Bengal to control the supply and distribution of food grains in the market, thus generating large scale hoarding; (d) delayed response after the onset of famine; and (e) the government of India's procrastination in putting into operation a nation-wide system of moving supplies from food surplus to deficit areas (Law‐Smith, 2007; Mishra, 2000).
One important characteristic of the famine that Sen (1977) noted was it created an uneven expansion of incomes and purchasing power. People who were involved in military and civil defense works, in the army, or industries associated with war activities were covered by distribution arrangements and subsidized food prices. Ó Gráda (2015) pointed out that more than half of India’s war-related output was produced in Calcutta and the number of military workers in the city was one million. As a result, they could access abundant supplies of food while others faced the consequences of rising food prices. Impoverished families sold their lands in exchange for stacks of rice. Due to this gruesome situation, the city of Calcutta witnessed crimes such as selling girls and women and even consumption of meat from dead cows.
Calcutta witnessed the famine in the form of destitute masses from the rural areas who travelled there from the surrounding rural districts. People thought if they could move to Calcutta, they had a better chance of survival than anywhere else in Bengal because the city had so many people engaged in war-related activities (Mukherjee, 2015). Figure 2 depicts a picture of a family who moved to Kolkata to obtain food. Charitable organizations offered relief by providing meals in their kitchens. Meals were given at the same time of the day in more than one kitchen, which prevented poor people from getting more than one meal. The soup supplied in the kitchens was cooked with low-quality millet and vegetables. Collingham (2012) observed that poor food quality in the kitchen induced ‘famine diarrhea’, which resulted in more fatalities. In the same vein, Nally (2011a, 2011b, p. 221) argued that material space acted as a means of biopolitical regulation as during the Irish famine, several locations, like as "workhouses, food depots, soup kitchens, public work operations, outdoor relief schemes, allowed the state to target and manage Irish destitution.". The famine swept across at least 60% of Bengal's net cultivable area, affecting more than 58% of the rural households and reducing over 486,000 rural families to a state of beggary (Goswami, 1990). The harshest phase of the famine lasted for eight months (March to October 1943) but its impacts were felt for a much longer period, creating starvation and epidemics. Among the numerous devastating effects of the famine, the mass starvation phase culminated in epidemics caused by weak immune systems due to hunger. Throughout Bengal even during the end of January 1944, it is estimated that there was a total of 13,000 hospital beds available for famine victims considering an average of 2300 people dying each day out of starvation and diseases (Mukherjee, 2011). Cholera mortality (58,230 persons) reached its maximum in October and November together with a severe rate of smallpox following thereafter (March and April 1944). Concurrently, malaria peaked in December 1943 (168,592 persons) (Sen, 1982).Fig. 2 A family arrived in Kolkata in search of food in November 1943. Photograph: Keystone/Getty images.
Source: The Guardian, March 2019 (https://www.theguardian.com/world/2019/mar/29/winston-churchill-policies-contributed-to-1943-bengal-famine-study" https://www.theguardian.com/world/2019/mar/29/winston-churchill-policies-contributed-to-1943-bengal-famine-study)
Context and background of the famine
In March 1942, the Japanese Army completed the occupation of Burma (now Myanmar). During this time, there was a serious shortage in rice production as India used to have 15% of its rice imports from Burma. After the capture of Rangoon in 1942, the shipments of Burmese rice to Bengal were stopped by the Japanese army, contributing greatly to the food shortage there (Ó Gráda, 2008). The loss of Japanese imports resulted in the requisitioning of rice reserves in areas vulnerable to the Japanese invasion, as well as large-scale hoarding (Ó Gráda, 2015). Bengal was also lacking wheat, dried legumes, mustard, sugar, and salt. As a result, the wholesale price of rice rose from 14 Rupees (Rs) per maund on December 11, 1942, to 37 Rs per maund by August 20 (1 maund = 37.32 kg) (Sen, 1977).
Alarmed by Japan’s military successes, the British colonial authorities started preparing for a Japanese invasion of eastern and coastal Bengal. They initiated it by executing a scorched-earth policy, seizing and hoarding food supplies (Famine Commission, 1945). The denial policy, a Government of India plan, was implemented by L.G. Pinnell (Director of Civil Supplies until April 1943) in 1942 that played a consequential role before the famine. The policy included two important measures: the removal of rice in excess from coastal districts, and the removal of boats that could carry ten or more passengers to deny supplies and transport to the Japanese. Due to the ‘denial policy of rice’, the districts of Midnapore, Khulna and Bakarganj, which used to have a surplus of rice, were ordered by the colonial authorities to demolish their pre-existing stacks of rice. Moreover, due to the fear of the Japanese invasion, the government of Bengal impounded 66,653 boats, thereby halting all rice movement from surplus zones to the deficit districts of East Bengal (Goswami, 1990). In these districts of Khulna, Midnapore and Bakarganj, the economy of the fishing class was completely shattered. People who were engaged in pottery in different districts went out of trade and their families became homeless, as this industry required large inland shipments of clay.
Aggravating the agony of the people of Bengal, on October 16, 1942, a massive cyclone devastated the coastal areas of Midnapore and 24 Parganas, inundating over 3,200 square kilometers. Midnapore was the largest rice-growing and exporting district of the province. The standing winter rice crop as well as the reserve stocks were destroyed. Besides the deaths of 14,000 people, an estimated 12 million Rupees (Rs) worth of standing and stored rice was lost (Weigold, 1999).
Theories and debates on the causes of the 1943 famine
The reasons behind the causes of the Bengal famine have been widely scrutinized. The Family Inquiry Commission (FIC) was appointed by the Government of India in 1944 to investigate the causes of famine. According to the FIC, the famine was caused by two factors: First, during 1943 there was a serious shortage in the total supply of rice available for consumption in Bengal, as compared to the normal supply (Islam, 2007). Secondly, there was an exorbitant increase in the price of food beyond the purchasing power of people who were usually reliant on the supply of rice in the markets throughout the year.
The Famine Inquiry Commission (FIC) upheld a Malthusian view of food shortages by blaming the local population and explaining that food shortages and famine were routine phenomena of colonial India (Mukerjee, 2014). The Commission blamed natural calamities along with the tendency of Indians to breed excessively. It advocated the Food Availability Decline theory (FAD) by highlighting those shortages of rice were one of the basic causes of the famine (Famine Commission, 1945). The report was viewed as fallacious by different scholars after it was thoroughly investigated as there were discrepancies between the testimonies and the information published by the FIC. (see Mukerjee, 2014).
The degree of crop shortfall in late 1942 and its impact in 1943 have dominated the historiography of the famine. The issue reflects a larger debate between two perspectives: one emphasizes the importance of Food Availability Decline (FAD) as a cause of famine, and the other focuses on the Failure of Exchange Entitlements (FEE). The FAD explanation blames famine on crop failures brought on principally by crises such as drought, flood, or devastation from war. The FEE account agrees that such external factors are in some cases critical, but holds that famine is primarily the interaction between pre-existing "structural vulnerability" (such as poverty) and a shock event (such as war or political interference in markets) that disrupts the economic market for food. When these interact, some groups within society can become unable to purchase or acquire food even though sufficient supplies are available. Both the FAD and the FEE perspectives would agree that Bengal experienced at least some grain shortages in 1943 due to the loss of imports from Burma, damage from the cyclone, and crop disease due to pest attack (Padmanabhan, 1973). However, the FEE analyses do not consider food shortages as the predominant factor.
Academic consensus generally follows the FEE account, as formulated by Amartya Sen, in conceptualizing the Bengal famine of 1943 as an “entitlements famine”. In this view, the prelude to the famine was generalized war-time inflation. The problem was exacerbated by prioritized distribution and abortive attempts at price control. High inflation rates caused a fatal decline in the real wages of landless agricultural workers. Sen (1981) disagreed with the explanation put forward by the Famine Inquiry Commission and affirmed that the Bengal famine was not caused by a decline in food availability, but by a failure of entitlement to food. He termed the Bengal famine an “artificial famine” and emphasized class as one of the main determinants of famine vulnerability. He also pointed out that the supply of rice was just around 5% lower than the previous five-year average and was, in fact, 13% greater than in 1941, even though there was no famine in 1941 (Sen, 1982).
In Bengal during that time, the zamindars (local landlords) were at the top of the revenue-collecting ladder. The peasant or chasi (primarily lower caste Hindus or lower caste Muslims) cultivated the land and paid his rent to the landowner (Mukherjee, 2011). Food hoarding was a crucial factor in the case of this famine. The most noteworthy factor that Sen (1981) emphasized was that in the Bengal famine, it was the underprivileged occupations that were most affected—fishermen, agricultural laborers, and transporters – whereas the beneficiaries were big farmers, merchants, and rice mill owners (Sen, 1977). The inflation benefitted these latter groups, whose incomes soared, and whose food consumption also climbed up. Food was deliberately stockpiled in the village stores of wealthy landlords and tradesmen, who were impatiently awaiting the appropriate moment for inflation to cause price increases (Collingham, 2012). The years 1942 and 1943 experienced inflation across all sectors, predominantly because of high war expenditures due to the Japanese invasion of Burma in 1942. The colonial government financed its expenses by printing more money and the Reserve Bank of India was compelled to print notes about two and half times their total value (Gadgil & Sovani, 1944), creating an enormous increase in prices.
More recently, a groundbreaking work was done by Mishra et al. (2019) who used weather data to study soil moisture levels where they discovered that out of the six major famines between 1870 and 2016 in India, five were linked to soil moisture drought, but that the Bengal famine of 1943 was not caused by drought. Even the rainfall was also above average during that year. They concluded that the 1943 Bengal famine was not caused by drought but rather was a result of a policy failure during the British era. This cutting-edge approach to uncovering the causes of famine during 1943 attracted widespread media attention (Safi, 2019). One study (from a commentary) recently published even conceptualized the Bengal famine as a genocide (please see Mookerjee, 2022).
Responsibility of the colonial authorities
The role and responsibility of the British government during these crisis months were always highly questioned. The interventions by the government of Bengal in the province’s wholesale rice markets in 1942 and 1943 triggered the crisis. Greenough (1982) calculated that even after deducting the losses due to the halt of Burmese imports, the Midnapur cyclone, flood, and crop disease due to pest attack (see Padmanabhan, 1973), 90% of the usual supply of rice was available in 1943. There was also no deficiency of rice in Bihar, Orissa and Assam indicating that there should not have been any shortages in Bengal provided the surplus grain was accurately circulated, which the Indian Government failed to accomplish (Law‐Smith, 2007).
During the famine, the utilitarian principles and profit-seeking attitude of the British administrators dictated that for Britain to satisfy Indian demands, shipping and supplies had to be sourced for British soldiers fighting the Germans at that time. Also, supplying food to Indian civilians would have risked British civilian food supplies. The total amount of wheat harvested in the British Empire during the 1943–1944 year was 29 million tons, but the war cabinet strategically preserved it for the future. So, despite Bengal’s rice shortages, the British Empire had sufficient wheat to send to the famine victims (Mukerjee, 2014). Even in 1943, at the height of the famine, the UK imported 26 million tonnes of food and raw materials for its civilian population, creating a stockpile of 18.5 million tonnes at the end of the year. The Indian Central Food Department intended to set up a central purchasing organization, but the government mismanaged the situation and did not inform the surplus provinces about setting up procurement machinery until the end of January 1943. Bengal expected delivery of 350,000 tonnes of rice between April 1943 to March 1944 from neighboring states, but, unfortunately, received only 25,000 tonnes of rice supplied by Orissa (Law‐Smith, 2007). The total imports and exports during 1942–1943 are shown in Fig. 3.Fig. 3 Bengal’s rice trade, 1942–1943.
(Source: Ó Gráda, 2015, p. 59)
It is simplistic to ascribe all the failures by putting the entire blame only on the British government. As mentioned earlier, there were different other complex issues like market failures, policy failures, malfeasance by government agencies, as well as different unethical practices by private companies. A more nuanced view also acknowledges the role of Punjab, which had a surplus of food grains in 1943–1944. There was an ongoing politics between the Punjab peasants’ lobbies and the ruling party that utilized the wartime soaring prices of food grains to compensate for the losses the Punjab peasantry had suffered earlier during the economic depression of the 1930s. The government sought to safeguard its rural vote bank by publicly advocating for allowing the wartime grain markets to operate on a laissez-faire basis (Yong, 2005). Many peasant leaders in Punjab encouraged farmers to resist the procurement of food crops by government agencies at a fixed price. This wartime prosperity of Punjab specifically when Bengal suffered helped to reproduce uneven development within India.
Official declaration and news of this ‘British- induced famine’ were deliberately suppressed from the people of Bengal to serve British interests. In August 1942, Bengal’s chief finance minister, Fazlul Huq, warned colonial authorities of a potential famine because of these policies. He was ignored by the British Governor of Bengal, John Herbert. At the same time, press regulations were employed to interrupt the circulation of any information from Bengal. This was not the first time the government have concealed news of the famine. While researching British responses to famine throughout the last 200 years, Sasson and Vernon (2015) discovered that famine news was not extensively disseminated in the British press and that the key concern was the negative impacts on tax reduction, as noted during the 1770 Bengal famine as well.
Colonial Biopolitics and the Great Bengal Famine of 1943
Racism reduces human beings to the race (phenotype) to which an individual belongs (Sharp, 2008). Racist ideology involves an elaborate classification of mind and personality linked to physical features. In the European geopolitical imagination, any race other than whites was conceived to be more bodily driven in their instincts and even viewed as having animal instincts more tied to the body than their minds (Sharp, 2008). Duncan (2007) demonstrated how race was used as a significant criterion to intensify the internal differentiation within the native Ceylonese population and used as biopower by the British colonizers to fragment and govern the indigenous people in nineteenth-century Ceylon. Race here was analyzed not only as utilized as a useful tool for segregation but also in the context of 19th-century environmental determinism and theories of tropical degeneration. Europeans who were born in Ceylon were regarded inferior to other Europeans born in Europe and close to the indigenous population (Duncan, 2020). Brown bodies were portrayed as disease-prone due to body odor, and these smells were viewed as spreading illness by contaminating the air.
Environmental determinism was defined at the time as the belief that individuals from cooler regions would deteriorate physically, ethically, and psychologically if they spent too much time in the tropics. The heat of the tropics was assumed to change the blood of Europeans, creating tropical anemia. The connection of Indians to land, tradition, and climate was regarded and supposed to be the cause of India's collapse, and tropical climate was blamed by the British as the primary cause of draining away vitality for productive labor. The British feared that their talents would deteriorate because of their intimate interaction with both the natural and cultural environments of India (Duncan, 2007, 2020).
The British generally perceived their colonial subjects as childlike, needing guidance in their every step of how to behave properly. The Indian working classes were believed to lack intellect and were always driven by bodily passions. When the Delhi government sent a telegram to Churchill depicting the horrible devastation generated by the famine and briefed him about the total number of deaths, his response was “Then why hasn't Gandhi died yet?” (quoted in Choudhury, 2021, p. 4). Churchill even claimed that the Indian population were the beastliest in the world after the Germans, the famine was created by themselves caused by overpopulation, and that Indians should pay the price for their negligence (Collingham, 2012). These statements paint a coherent picture of how the British colonial authorities marginalized their colonial subjects and reified racial exclusion.
Power is inscribed as well as resisted on the surface of the skin. In October 1943, when Archibald Wavell arrived in India to assume the post of Viceroy, he faced enormous pressure from Indian politicians for an investigation into the famine in Bengal. Leopold Armery, the Secretary of State was opposed to this investigation and wanted to silence these voices: “My own view was and is that inquiry now would be disastrous and that inquiry at future is undesirable” (quoted in Mukerjee, 2014, p. 71). He wanted to shift the interpretation of famine towards Malthusianism and said, “In the past 12 years the population of India had increased by about 60 million, and it had been estimated that the annual production of rice per head in Bengal had fallen from 384 to 283 lb. in the last 30 years” (quoted in Tharoor, 2018, p. 248). He linked the famine to population growth to divert the attention away from inflationary factors and India’s war effort funds.
As food prices increased, and signs of famine became prominent, in August 1942 the Bengal government launched the Bengal Chamber of Commerce Foodstuffs Scheme, which provided food and distribution of goods and services mainly to workers in high-priority war industries, so that they were forced to stick to their existing positions. These soldiers were more valuable than Indian citizens since they were fighting a war for the British, which was most important to them at the time. To avoid offending the Indian upper classes, the government spared them from high taxes, price limitations, and consumption restrictions during 1942. The backing of India's corporate and industrial classes was critical for the rise of Indian industry, which contributed significantly to the war effort (Collingham, 2012). Surprisingly, Sasson and Vernon (2015) observed that these erroneous relief strategies were gendered as well as dependent on the class. Men were taught that because women and children were not permitted to work, it was the man's obligation to support them. Only in exchange for employment, the underprivileged were given food.
Longhurst (2001, p. 3) argued that bodies play a significant role in people’s experiences of place, and, drawing on work concerned with embodiment and spatiality, she proclaimed, “the body is the potential to prompt new understandings of power, knowledge and social relations between people and places.” Similar notions can be linked to the Bengal famine. For example, the British considered the Greeks to be sturdier than anyone else and prioritized them based on their skin color and body stature. Choudhury (2021, p. 7) highlighted these remarks when Leopold Armery, commented: “Winston may be right in saying that the starvation of anyhow under-fed Bengalis is less serious than sturdy Greeks, but he makes no sufficient allowance for the sense of Empire responsibility in this country.” An additional statement uttered by Lord Wavell was “Apparently it is more important to save the Greeks and liberated countries than the Indians and there is reluctance either to provide shipping or to reduce stalks in this country.”
It is worth emphasizing that while most biographies of Churchill mention the bombing of Germany, none of them includes the 1943 Bengal famine. The absence of this disaster in popular biographies of Churchill symbolizes it as a non-significant event. Hickman (2009, p. 242) analyzed popular Churchill biographies and the 1943 Bengal famine, where he documented one quote when Churchill responded to an American critic of the British Raj: “Before we proceed any further, let us get one thing clear. Are we talking about the Brown Indians, who have multiplied alarmingly under the benevolent British rule? or are we speaking of the red Indians who, I understand, are almost extinct?”.
Orientalism, according to Edward Said (1979), is a discursive and geopolitical assertion of difference between East and West that is written throughout the texts of Western culture, whether through travel diaries, news stories, paintings, or other representations. In the case of orientalism, power was exercised through institutions that described the Orient. The people within the spaces of the Orient were not allowed to speak for themselves but were described and characterized by others (Sharp, 2008). The Orient was always seen as being different and backward from Europe, which was considered developed. Both Heath and Legg (2018) and Duncan (2007) pointed out that in terms of science, Asian sciences were considered far inferior, and like ‘mere children’ in comparison to Europeans. The natives were visualized to be close to nature, but Europeans held that the native people are incapable of modifying nature and were unable to exploit natural resources. The Bengal famine exemplifies this notion, in which the Bengali people were dependent on the British for the allocation and distribution of their resources even in a crisis. Duncan (2007), while exploring the consequences faced by coffee plantation workers noted how industrialization, commercialization, and Western technologies were introduced to the colonial sites for future calculation and enforcing discipline to the plantation laborers. Every ounce of labor was sucked from their body to fulfil the demands of the planters to make more money. Kandyan highlands were deforested to produce coffee that was exported for financial benefits. Just like Ceylon, food grains even could not be imported to Bengal from other neighboring states within India but instead exported (Law-Smith, 2007).
Paralleling orientalism, a unique focus on the notion of subaltern geopolitics by Ashutosh (2019) gives a counter topography of South Asian territories that do not center around the state. He revisited the 1955 Asia-Africa Conference in Bandung, referring to it as the "threshold moment for postcolonial geography" (p. 7) since it depicted an alternate South Asia with the capability implanted in postcolonial nation-states where anticolonialism succumbed to postcolonial state formation. This event transcended national and state lines, serving as a model for overcoming marginalization and forging new kinds of belonging.
Foucault’s biopolitics placed human life as the center of calculations, and rather than preventing a catastrophe, the state-led management or government allowed these calamities to occur to acquire a profit (Foucault et al., 2008). In the Bengal famine, the government’s role in dealing with the famine, including famine relief, was arranged from the vantage point of prioritizing their interests. The primary focus was on winning the ongoing war, and all requirements related to the war were reinforced. Correspondingly, all actions undertaken by the colonial government during the Irish famine were delayed (Nally, 2011a, b). The government's measures and policies (closure of Irish food depots, delayed suspension of the Navigation Act, retraction of the Corn-laws, etc.) were not aimed at alleviating food scarcity or saving Irish lives; rather, they were all strategically implemented to achieve desirable outcomes for the British.
Foucault’s governmentalized state included the population as a field of intervention and political economy was one of the prime objectives of the state. This conception is explicitly portrayed in the Bengal famine. From compelled tax collection during a crisis to forced participation in the war, Bengal was the site of exploitation for the British and the subaltern body served as a platform to exercise their power. Legg (2006) noted that for analyzing the population expansion of Delhi (1911–1947), the released report on the Relief of Congestion in Delhi paid no attention to the working conditions of the workers or the issues of illness and their causes of transmissions. The measuring parameter was the minimal space required for a person, without delving into the underlying issues. Overcrowding and poor sanitation were blamed only for illness transmission, ignoring the socioeconomic consequences of poor living circumstances and poverty. Humans were not viewed as persons but as objects. People were regarded as items that may be discarded at any time in this "extended laboratory of urban modernity" (Legg, 2006, p. 724).
While analyzing Foucault’s discourses on governmentality and biopower, Duncan (2007) argues that while the government has the purpose of managing the welfare and improvement of its people's lifestyle (wealth, health, life span), the assumption surrounding it involves a modern and broadened view of managing and regulating the population. This 'modern' assumption was founded on such goals, which could only be fulfilled by replacing traditional practices and unscientific beliefs with “modern” rational ones. Through agricultural commercialization, colonial regimes in India devastated indigenous agrarian food systems. The physical landscape of India was transformed by the construction of dams, telegraph lines, roads, and railways. Wilson (2016) argued that this geological imperialism was motivated by a desire to enhance a civilization that was perceived to be backward. Often studies (Duncan, 2020; Scott, 1995) include modern governmentality highlighting the daily and moral lives of the colonized population. Scott (1995) asserted that modern power is not about capitalism, but the very point of its application, which is involving the conditions in which a body has to live and define its life and noted how South Asian governmentalities were inaugurated by the insertion of Europe into the lives of colonial subjects.
The government of India begged London for wheat imports, but the colonial authorities instructed the Bengal government to publicly claim sufficiency. Justice Henry Braund of Bengal’s Department of Civil Supplies said that he was told “This shortage is a thing entirely of your own imagination. We do not believe it and you have got to get it out of your head that Bengal is deficit” (quoted in Mukerjee, 2014, p. 72). Similar instances such as the export of food commodities including oats, wheat, and animals from Irish ports had been detected during 1841 during the Irish famine. At the height of the famine, the British colonial authorities did not restrict these exports. As Sen labelled the Bengal famine as ‘artificial’, Nally’s book (2011, p. 12) reiterated the colonial government's “atrificial scarcity of shipping”, which was caused by the compelled importation of food aboard British ships, resulting in exorbitant freight prices.
Geo-power is an amalgamation of technologies of power associated with the management of territorial space and was legitimized by the self-interest of the British government. Mukerjee's work illustrated geo-power where she documented that some of India's grain was also exported to Sri Lanka and Australian wheat sailed past Indian cities to various other destinations in the Mediterranean. Lord Linlithgow, the Viceroy to Leo Amery, stated on January 26, 1943: “Mindful of our difficulties about food I told [Fazlul Huq] that he simply must produce more rice out of Bengal for Ceylon even if Bengal itself went short!” (quoted in Mukherjee, 2015, p. 93). Sinha (2009) argued as far as international politics is concerned, the United States was also reluctant to provide food aid to the Indian victims. The US Congress and the Roosevelt administration did not want to provide favors that might embarrass the British government and arouse opposition. Sinha (2009) reported that in August 1943, Syed Badrudduja, the Mayor of Calcutta, cabled Roosevelt urging the shipment of food grains, but American officials chose to ignore the gruesome situation in Bengal in late 1943. A committee investigating the food supplies of India even declined Canada’s offer of 100,000 tons of wheat for India. Together with this the British government also prevented the Indian legislative assembly from applying to the United Nations Relief and Rehabilitation Administration for any food aid.
Social categorization was successfully illustrated in the Bengal famine, reflecting how an atrocity can induce strategic opportunity that was embraced by the British Government. Nally (2011a, b), invoking Foucault’s notion of biopower, illustrates how the government's principle and the exercise of sovereignty acquired a modern connotation by the end of the late eighteenth century using Foucault's idea of biopower and biopolitics. It further states that if foreign foes threaten the sovereign authority, he may continue the battle and order his citizens to participate in the war for the defense of the state. According to Nally's interpretation of Foucault's liberal biopolitical model, starvation is even permitted if it results in a desirable social and economic transformation. This perception can be illustrated by class segregation during the famine. The ‘privileged classes’ of Calcutta who were important to the war effort were supported by rations. Native people were forced to join in the war during the Bengal famine, and they were rewarded by providing meals during the calamity. This sovereign power, therefore, included the authority to make life and death decisions, as well as control and management of the people and land. During a cabinet war meeting, Churchill’s militant policy stated that only those Indians who have a direct contribution to the war effort needed to be fed (Mukerjee, 2014). Sarkar (2020) explored how indigenous factors of caste discrimination and religious communalism worsened famine conditions. With respect to the government free-kitchen, his article (p. 2069) stated that in Calcutta, special relief was added to the middle classes and higher caste people who enjoyed quick distribution of uncooked rice (so that they could take rice into their homes and cook in private), sparing them from the public eating with other lower castes at the relief kitchens.
As a ramification of the British rulers' vision of India, the local people and the land are prepared to accept orders set by the colonial authority. The various dividing divisions of caste, tribe, religion, and community established by colonial administrations can be attributed to excessive geopolitics. During the famine also, these communal conflicts arose throughout the rationing process. Among the 3 million people who died, it is estimated that none of them was from the bhadralok [usually means an educated Bengali man who belongs to a high caste or often what might be called as Hindu-middle class] (Sarkar, 2020). At the end of August, two private groups, the Hindu Satkar Samiti and the Anjuman Mofidul Islam, were selected to dispose of deceased remains associated with religious affiliation. Hindu remains were intended to be brought to the burning ghats, whereas Muslim bodies were supposed to be transferred to the burial sites. These distinctions were even considered in light of the deplorable state of the corpses after death (Mukherjee, 2015).
The 1943 famine is not the only example of ‘utilitarian principles’ implemented by colonial officials as a result of the ongoing World War II; similar incidents were also witnessed during the 1770 Great Bengal Famine, in which it was believed that nearly 10 million people died (Greenough, 1982). The East India Company, being a “profit-seeking entity” (Chaudhary et al., 2016, p. 101), continued collecting taxes ruthlessly even after the famine. It was not only in the 1943 famine that there were debates about the causes; different literature on the 1770 famine also argued that the severity of the 1770 famine was augmented due to the self-serving interests of the British officials who prioritized the profits that the Company could make by collecting revenues from Bengal as this forced tax collection increased the company’s revenue assessments by 10%. de Waal (2017) holds that the East Indian Company is a "villain" since it was directly responsible for the continual number of famines that have occurred since its inception.
Hegemony is always contested, and this is evidenced during several instances before the onset of the famine. There was massive resistance to governmental policies and schemes, several political movements, protests, and rebellions throughout India and Bengal from the beginning of the twentieth century. Some notable movements were the ‘first’ partition of Bengal in 1905, followed by the Swadeshi Movement (1905–1917; again from 1918 to 1947), the Khilafat Movement and Communal Violence (1919–1924), and Quit India Movement (August 1942) just before the Bengal famine (please see Bhowmik, 2021 for details of these movements and the role of Bengal to understand the political context). There was severe unrest in India during 1942 since Indians were reluctant to fight a war that never assured them that they would obtain their freedom. In August 1942, the Indian National Congress called for civil disobedience to oppose the colony’s compelled participation in World War II. The British authorities arrested more than 90,000, people and killed up to 10,000 political protesters (Mukerjee, 2011). Comparably, when the native Ceylonese people attempted to challenge hegemony, they suffered in the same way as colonial Indians did. Duncan (2007, p. 35) documented how everyday violence was exercised by the British colonizers on the Ceylonese people. Some examples are beating suspects for getting confessions to solve the cases and punishing prisoners whose families were unable to pay bribes. These incidents illustrate how “tropical colonies became laboratories of modern governmentality.”
Conclusion
The colonial landscape was not only a place to exert unequal power relations but also a surface to extract resources, creating various conflicts where both the colonizer and the colonized groups were involved and bound together. The British discriminated against Indians predicated on location and class (rural vs. urban, rich vs. poor) and implemented several policies that amplified the famine. The Indian landscape, the people, and their resources were all taken for granted, rendered invisible, and deprived of a voice in managing their own food shortage.
This paper illustrates that social relations are inevitably embodied, and power relations do not operate only from above (i.e., between colonizers and the colonial subjects), but as Amartya Sen demonstrated, can emanate from below and within the same community or family. In this famine, the privileged classes did not face the same consequences as the poor and the landlords (who belonged to the same community) took advantage of the inflated prices of food. This process accentuated income inequality.
This study not only focuses on food shortages in the twentieth century in Bengal, but it also argues for the need for further research today in this region about sustainability and adaptive measures to climate change in vulnerable communities. I want to give the example of Sundarbans here in this context, which is a climate change vulnerability hotspot. Sundarbans (a mangrove area in both West Bengal and Bangladesh's delta region) is susceptible to tropical cyclones and has been ravaged by numerous cyclones in the recent past, including Fani (May 2019), Bulbul (November 2019), Amphan (May 2020), and Yaas (May 2021). Due to these storms, farmlands and the houses of farmers were inundated with saline water. Several natural disasters in the recent past together with strict lockdown restrictions during the COVID-19 pandemic have repeatedly devastated people’s source of income and livelihood, resulting in food insecurity in this region. I would want to propose that research integrating biopolitics and food scarcity is necessary and required to address and combat any food crises in Bengal, both now and in the future.
The Bengal famine depicts how colonial biopolitics unfolds, where the laws, and policies were implemented only to serve the British government’s priorities. It reflected how the colonial landscapes were molded and how strategies of power were incorporated to categorize, control, and reform the citizens of Bengal. People were used as laborers to fulfil British goals and were forced to participate in the war. This appropriation perpetuated the interests of the British colonizers and I argue for a deeper understanding of how this subjugation of power was internalized by the Indian people.
Geographers have not studied the Bengal famine of 1943, and one of the principal purposes of this paper is to fill this void. This paper can serve as a stepping-stone to studying famines by geographers that occurred under colonial rule in India and elsewhere. Work on colonial biopolitics offers a multi-scalar perspective in which the world system and the bodies of the victims of the famine are intimately tied together. The argument that I want to highlight in this article is that biopolitics not only informs famine, but famine also informs biopolitics, thereby contributing to theory and reinforcing the empirical value of biopolitics. While few Indian researchers have deployed biopolitics in animal geographies, the notion is yet to be applied in the context of Indian famines.
Geographers have overlooked the event of the Bengal famine and I suggest the discipline has much to offer considering its nuanced understanding of space and place. This paper focuses on how politics and place are intertwined with one another and how British colonial politics remade the place of Bengal. It reveals how colonial biopolitics became part of the place-based strategy, which is so similar to the Irish famine. The famine was used by the British to reaffirm their sense of superiority in that they reduced their Indian subjects to animal-like beings incapable of controlling their reproduction. The British colonial authorities used landscapes as a tool to naturalize British superiority. This paper seeks to bring the literature of biopolitics and famine into a dialogue with one another. The reverse relationship of famine also informing biopolitics has never been acknowledged before in the context of Indian famines during the colonial period. The Bengal famine of 1943 will always remain a historic tragedy and a symbolically significant event in the light of the colonial past, which was transformed into a socially constructed catastrophe by the British colonizers.
Acknowledgements
I am very much grateful to the anonymous reviewers for their constructive and insightful comments and suggestions. I would also like to thank the Editor for his helpful comments and his support during the review process. All remaining mistakes are my own.
Declarations
Conflict of interest
No potential conflict of interest was reported by the author.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9735018 | NO-CC CODE | 2022-12-14 23:28:32 | no | GeoJournal. 2022 Dec 6;:1-17 | utf-8 | GeoJournal | 2,022 | 10.1007/s10708-022-10803-4 | oa_other |
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Behav Anal Pract
Behav Anal Pract
Behavior Analysis in Practice
1998-1929
2196-8934
Springer International Publishing Cham
763
10.1007/s40617-022-00763-z
Research Article
Examination of a Telehealth-Based Parent Training Program in Rural or Underserved Areas for Families Impacted by Autism
http://orcid.org/0000-0002-0967-0612
Boydston Paige [email protected]
1
Redner Ryan 2
Wold Kari 3
1 grid.261915.8 0000 0001 0700 4555 Pittsburg State University, Pittsburg, KS USA
2 grid.263856.c 0000 0001 0806 3768 Southern Illinois University, Carbondale, Carbondale, IL USA
3 grid.454433.1 Integrated Behavioral Technologies, Inc., Basehor, KS USA
6 12 2022
117
15 11 2022
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This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Families of children with disabilities in rural areas face challenges accessing services due to location and lack of health-care providers. Telehealth-based intervention can mitigate challenges in accessing services. The present study sought to replicate and extend the telehealth-based, behavioral parent-training program, the Online and Applied System for Intervention Skills (OASIS), utilizing a multiple-baseline approach. Four parent–child dyads participated, with all children diagnosed with autism spectrum disorder. All dyads resided in rural/underserved areas. All dyads demonstrated an improvement on skill and knowledge assessments. The mean gain from baseline-to-treatment completion on skills assessments was 80.9% (range: 67.6%–95.5% points). The mean gain on knowledge assessments was 35.3% (range: 19.0%–49.0% points). It should be noted that parent skill gains were maintained over time. The present results provided additional empirical evidence demonstrating the effectiveness of OASIS, a telehealth-based parent-training model.
Keywords
Telehealth
Parent training
Autism
OASIS
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pmcRoughly 97% of the landmass in the United States is designated as rural, yet only 19% of the population (approximately 60 million people, or 1 in 5 Americans) live in rural areas (U.S. Census Bureau, 2010). When compared to those living in urban areas, individuals living in rural areas tend to suffer more adverse health outcomes and engage in more unhealthy behaviors (Befort et al., 2012; Boring et al., 2017; Cossman et al., 2017). Disparities in care exist for children with autism spectrum disorder (ASD) in rural locations beginning with diagnosis (Antezana et al., 2017), with some states reporting both child location in the state and availability of services in their location as crucial challenges in service delivery (Mauch et al., 2011). In addition, Mello et al., (2016) found that only 44.2% of surveyed rural families had any applied behavior analytic (ABA) services for their child with ASD, compared to 51.4% of nonrural families. Furthermore, only 59.6% of rural children had home-based behavior support when compared to 82.2% of urban children. In order to ameliorate disparities in treatment and outcomes, telehealth services have begun bridging the gaps by bringing professionals to rural areas through technological means.
Telehealth services (for the purposes of this article) are synchronous services delivered to individuals separated from providers by physical distance via an internet connection that allows for video and audio communication. A variety of telehealth-based studies specifically related to ASD have been conducted. Telehealth use has increased for varied professions, including ABA services, with the onset of the COVID-19 pandemic (Koonin et al., 2020). The increase in use of telehealth-delivered ABA services also prompted the Council of Autism Service Providers (2021) to delineate guidelines to assist practitioners in practicing in an effective and ethical manner following the expansion of telehealth coverage.
Ferguson et al., (2019) conducted a systematic review of literature pertaining to telehealth and ABA, finding that 100% of reviewed studies (n = 28) indicated positive outcomes in relation to identified participants. The authors further stated that research related to comprehensive treatment packages delivered via telehealth is an underdeveloped area. Within a randomized controlled trial design, Lindgren et al., (2020) utilized a telehealth-delivery model for teaching parents to use functional communication training to reduce problem behavior displayed by their children. Results indicated increases in functional communication, decreases in moderate to severe child problem behavior, and high treatment acceptability only following implementation of functional communication training. Changes in important behavioral outcomes (e.g., increased child skill, increased parent skill) following both in-person parent training and online parent training are apparent (e.g., Crone & Mehta, 2016; Fisher et al., 2020; Jang et al., 2012; Koegel et al., 2002). Telehealth training, similar to in-person parent training, has also focused on training specific programs or models (as seen in Solomon et al., 2008), as well as training general components of early intervention procedures (e.g., Crone & Mehta, 2016). A recent study by Fisher et al., (2020) assessed the utility of a virtual parent-training program in a randomized clinical trial. Authors utilized online modules in addition to scripted role play situations to teach and evaluate implementation of skills displayed by parents. Authors found high parent satisfaction as well as statistically significant improvements in parents in the intervention group (compared to the waitlist control group). Overall, research on telehealth practices, increased internet access, and increased availability of electronic tools (e.g., computer-based cameras, video capabilities, and even cellular phones) have made dissemination of evidence-based practice to rural areas much more reasonable. Given the essential nature of effective parent training in ABA services (Jang et al., 2012), research on virtually delivered, comprehensive training has become crucial.
One parent-training model that was developed for delivery via telehealth is the Online and Applied System for Intervention Skills parent training program (OASIS; Heitzman-Powell et al., 2014). The OASIS program is a holistic approach to parent training that teaches parents both basic skills (e.g., reinforcement, prompting) and behavioral concepts/principles (e.g., functions of behavior, extinction) to utilize and understand when working with their child (see Heitzman-Powell et al., 2014, Table 1, for a breakdown of module goals and content). In addition, the OASIS training program addresses currently identified gaps in the telehealth literature, such as teaching discrete trial instruction (Ferguson et al., 2019) as a component of intervention. OASIS was designed for telehealth delivery to reach a wider range of parents who might otherwise not contact evidence-based treatment services for their children due to their location.Table 1 Overall skills and number of corresponding micro skills on the comprehensive skills assessment (i.e., the dependent measure)
# Skill Number of Micro Skills
1 Preference assessment 11
2 Teaching a new skill 9
3 Reinforcement 3
4 Prompt fading 5
5 Prompting 7
6 Structuring the environment 7
7 Attending 2
8 Role play 7
9 Generalization 2
10 Massed trial 6
11 Interspersed trial 6
12 Extinction 1
13 Overcorrection 1
Heitzman-Powell et al. (2014) provided the OASIS training to a total of seven parents across four families. The parents’ education levels ranged from a high school diploma to graduate degree. All parents were required to complete online training modules and online coaching sessions. Parents were taught specific behavioral techniques and were required to correctly utilize those skills prior to progressing through training. Parents completed the online activities before scheduled telehealth-delivered coaching sessions. Children were present for all telehealth-delivered coaching sessions. Gains across all skills averaged 41.2% (range: 28.0%–59.0%) for all participants. Knowledge gains on a 48-item assessment averaged 39.1% (range: 12.5%–90.0%) for all participants. Parents also reported their satisfaction with the training program, indicating overall that each major component of training (i.e., online modules and telehealth coaching sessions) was both important and satisfactory. Moreover, the researchers calculated that the use of telehealth procedures saved the participants from driving a total of 9,052 miles total across all live coaching sessions. Implications of the study are clear: parents can be effectively and efficiently trained to conduct basic procedures of ABA with their child with autism via a structured telehealth training program. In addition, allowing parents to access the full training remotely saves time and resources. Despite the promising outcomes from the original study, limitations were apparent. In particular, parents were required to drive from their home to a telehealth site instead of having access directly from home, and parent outcomes were reported as overall changes in parent behavior (pre/post-assessment) rather than as gradual changes over time (repeated measures of parent behavior throughout the course of participation).
The purpose of the present study was to replicate and extend the findings of Heitzman-Powell et al., (2014) that demonstrated increases in parent knowledge and skills following completion of the OASIS parent-training program. In particular, the present study replicated and extended methodology of the seminal OASIS study (Heitzman-Powell et al., 2014) with parents who resided in rural or service-impoverished geographic locations by (1) delivering the program to parents in their own homes via telehealth (rather than at a remote site) and (2) measuring parent behavior change (i.e., comprehensive skill assessment) throughout training within a repeated measures design (rather than solely pre-/post-data).
Methods
Participants
Parent–child dyads were considered eligible for participation if the following criteria were met: (1) the child in the dyad was diagnosed with an ASD; (2) the primary parent had not previously received structured parent training (e.g., any training with a behavior analyst or autism specialist, coursework or online work specifically reviewing ABA concepts, individualized instruction with their child); (3) the parent(s) and child were available for a 1.5-hr meeting per week for 16–21 weeks; (4) the parent had access to the internet and a device (e.g., tablet, laptop) capable of running a video chat application; (5) the child was between the ages of 2–13 years; and (6) the child was not currently receiving home or clinic based ABA therapy (to ensure additional learning did not occur outside of OASIS sessions). Although the requirement for the child to not be engaged in home or clinic-based services was limiting for the family, none of the participants who were recruited had access to ABA services for their child during the timeframe in which they completed the study. Parents were asked to not speak to other research participants about the training program or their progress.
Participants (a parent and child dyad) were recruited from rural areas (as indicated by the U.S. Census Bureau, 2010), or areas that had decreased access to services due to their geographic location (locations with one or less service provider and no access to immediate services). Recruitment was conducted in a variety of ways. First, an agency that provided ABA services and diagnostic assessments in rural and underserved areas of Kansas contacted families that were on their waitlist (agreeing or declining to participate did not affect their position on the waitlist for comprehensive services, except for the family being informed that they were not permitted to have comprehensive home-based services during the study). Parents whose children were evaluated in the agency’s diagnostic clinic were also given information for participation at the same time they were given a referral packet. Second, flyers were distributed via social media and in Kansas and Southern Illinois based groups (e.g., parent support groups, autism networks). Potential participants contacted the researcher via email and were then screened for eligibility via a Zoom meeting and/or email. During the screening, families were required to provide documentation of their child’s autism diagnosis and confirm they had never received parent training in the past (see inclusion criteria below). Each family’s physical location was also reviewed to ensure they met the rural and/or underserved area qualification. After determining eligibility, informed consent included a meeting via telehealth with the parent and the researcher to review all components of the study, including assessments, time commitments, training requirements, and meeting times.
Dyad 1 consisted of a 5-year-old boy (Kal) and his mother (Lyanne; 30 years old). They lived in a rural area, with Lyanne reporting that she did not know where to access services. They heard about the study via a local parent support group. Lyanne was white, had an associate’s degree, was married, and both spouses earned an income totaling $66,000–$75,000 per year. Kal attended a local preschool program where he received special education services. He was a nonvocal communicator (he only clearly vocalized and repeated a limited number of words) and utilized an iPad with a communication application to communicate with others. Per parent report, Kal engaged in very limited problem behaviors (e.g., get upset, cry); however, over the course of training it was observed that Kal frequently screamed, cried, and protested when demands (including low response effort demands) were placed on him. His problem behavior occurred at an intensity and frequency that was problematic (per parent report) in the household and consistently interfered with his participation in a variety of daily tasks.
Dyad 2 consisted of a 2-year-old boy (Benjy) and his mother (Shay; 29 years old). They lived in an area with only one service provider and limited access to resources, with Shay reporting that they were on a waitlist for in-home services with an agency that was approximately 45 min away (one way). The family heard about the study via a diagnostic clinic (the same agency where they were on a waitlist). Shay was white, had a master’s degree, was married, and both spouses earned an income totaling $96,000–$105,000 per year. Benjy attended an in-home daycare but had previously been dismissed from other center-based daycare settings due to problem behavior, specifically biting his peers. He communicated vocally but had a very limited repertoire for spoken language and other modes of communication (i.e., gestures, simple signs). Most of his language was limited to simple one-word requests with full words or approximations. Benjy was reported to engage in a variety of problem behaviors, including aggression (e.g., hitting, biting), property destruction (e.g., throwing toys), tantrum behaviors (e.g., screaming, crying, flopping on the floor), and other general task refusals (e.g., saying “no,” leaving the teaching area, laying on the floor instead of working).
Dyad 3 consisted of a 4-year-old boy (Jorah) and his mother (Rose; 43 years old). They lived in a rural area, with Rose reporting that they were on a waitlist for in-home services with an agency approximately 2 hr away (one way). They heard about the study via a local parent support group. Rose was white, had a high school diploma, was married, and both spouses earned an income totaling $56,000–$65,000 per year. Jorah attended a local preschool program where he received special education services. He was a vocal communicator with some language delays and articulation errors; however, his language repertoire was similar to same-aged peers and familiar adults and family members were able to understand what he said. Rose reported that Jorah escalated if he was unable to make his meaning clear when attempting to communicate. Jorah engaged in a variety of varying intensity problem behaviors, including tantrums (e.g., screaming, yelling, crying, dropping to the floor, physical resistance to prompting, elopement) and general noncompliant behavior throughout his day (e.g., arguing with parents and caregivers, verbal refusal to follow instructions), with some instances of problem behavior lasting 20 or more min.
Dyad 4 consisted of a 3-year-old girl (Kalee) and her mother (Sasha; 39 years old). They lived in a rural area, with Sasha reporting that she did not know where to access services. They heard about the study via Lyanne from Dyad 1. Sasha was Asian, had some college, was single, and had a single income household of less than $10,000 per year. Kalee attended a local preschool program where she received special education services. She was a nonvocal communicator and was waiting for an iPad with a communication application (LAMP Words for Life) at the onset of the study. Sasha reported that she knew what Kalee wanted based on gestures and some very simple sign language (e.g., milk, eat). Kalee was reported and observed to engage in a variety of problem behaviors, including skin scratching/picking, nail biting, crying, and task refusal (e.g., wafting hand at materials or tasks, crying and nonresponding).
Setting
Participants were encouraged to use the same room of their home and the same devices for all coaching sessions. Dyad 1 completed sessions in their dining room or in the child’s bedroom, Dyad 2 completed sessions in the child’s bedroom, Dyad 3 completed sessions in a small room dedicated to instruction, and Dyad 4 completed sessions in the child’s bedroom. Family participants were encouraged to have a quiet and dedicated environment to minimize distractions and potential interruptions, but interruptions from other family members (e.g., siblings, spouses) or for child needs (e.g., toileting, snacks) occurred frequently throughout live coaching sessions.
OASIS Materials
Parent Materials
Parent materials included online tutorials, printed data sheets for incidental teaching and problem behavior information, and a parent binder that contained information related to each coaching session (e.g., materials needed, content covered). Online materials were available through a variety of platforms (e.g., phone, tablet), locations, and times allowing for easy access for the parents. The online materials were broken into eight modules. All coaching sessions between the researcher and parent–child dyads were conducted via a Zoom account that met Health Insurance Portability and Accountability Act (HIPAA) compliance standards. In total, training required a minimum of 15 Zoom-based coaching sessions, with one coaching session for all of Module 1, and two coaching sessions for the remainder of the modules (e.g., Module 2’s Zoom-based coaching sessions were broken into “Module 2.1” and “Module 2.2”).
Child Materials
Materials for child participants included various toys, preferred items, and materials related to tasks (e.g., cause and effect, blocks). Materials for each child varied based on their preferences, skill level, and available resources of the family.
OASIS Coach and Coach Materials
The first author worked with each parent–child dyad for all baseline, training, and follow-up sessions. Sessions were conducted from the same computer each time. The researcher had both the OASIS Coach Protocol (a booklet that contained scripts and prompts) and the family’s assessment protocol (a booklet that contained data collection sheets for parent behaviors and general training requirements). The researcher also had access to the OASIS online platform in which parents took quizzes and submitted problem behavior recording forms (PBR) and incidental teaching checklists (ITC).
Dependent Variable
Comprehensive Skill Assessment
A comprehensive skill assessment, that measured 13 overall parent target skills taught throughout training, functioned as the primary dependent measure (see Table 1 for specific target skills and the number of included micro skills) and provided a granular analysis of parent behavior. Target skills were operationally defined in individual micro skills for scoring purposes. The number of micro skills varied on each skill. The comprehensive skill assessment included a total of 67 individual micro skills across 13 target skills. The setup of the comprehensive skill assessment allowed for repeated measures on parent target skills as training progressed and provided a method of reviewing not only performance on overall hands-on target skills but also performance on the individual micro skills required for overall target skills (e.g., if a parent scored less than 100% on target skills, such as a preference assessment, the first author reviewed which individual micro skills of the target skill were being missed). Comprehensive skill assessments were conducted less frequently during baseline (i.e., probes) to reduce response effort and frustration for parents. During intervention, comprehensive skill assessments occurred on a biweekly basis after every other intervention session (i.e., following the meetings for Modules 2.1, 3.1, 4.1, 5.1, 6.1, 7.1, and 8.1), for a total of seven measurements of the primary dependent variable during intervention.
Lay terms were used when prompting the parents to engage in each activity during the skills assessment to reduce confusion related to the technical language the parent learned during training. For example, instead of saying “show me a preference assessment,” the researcher said, “show me how you would find something that your child would work for or earn.” Parents were observed after each prompt and if they engaged in any micro skill of the target skill being assessed a “+” was recorded on the data sheet. After the parent indicated they were finished or stopped responding for approximately 10 s, the researcher scored any micro skills that were not exhibited or exhibited incorrectly as a “-” and moved on to the next target skill. Scores were calculated by taking the total number of correctly completed micro skills across all 13 target skills divided by total possible micro skills (67) across all 13 target skills and multiplied by 100%.
Knowledge Assessment
A knowledge assessment was also provided to parents during each skills assessment and functioned as a secondary dependent variable. Knowledge assessments were an online test administered through an online survey platform (Qualtrics) that randomly pulled 60 questions from an overall pool of 159. The question pool contained all possible questions that had been developed for the existing OASIS online module quizzes (i.e., the quizzes the parents were required to take in the online modules/system). Questions from the OASIS modules were based off the information presented in each module. In addition, the pool of questions was the same pool of questions utilized in the OASIS pre- and posttest embedded in the training. Knowledge assessments were conducted less frequently during baseline (i.e., probes) to reduce response effort for parents. During intervention, knowledge assessments occurred on a biweekly basis after every other intervention session (i.e., following the meetings for Modules 2.1, 3.1, 4.1, 5.1, 6.1, 7.1, and 8.1), for a total of seven measurements of the secondary dependent variable during intervention. Scores were calculated automatically by Qualtrics by taking the total number of correctly answered questions divided by the total number of questions presented (60) and multiplied by 100%.
Interobserver Agreement
Interobserver agreement (IOA) was collected via video review for 43.0% of all opportunities in baseline, intervention, and follow-up for the comprehensive skills assessment across all four dyads. IOA was calculated on the comprehensive skill assessment by totaling the number of items to be scored in which two raters had an agreement, divided by the total number of items to be scored, and multiplied by 100%. The average IOA for the comprehensive skills assessments were as follows: Dyad 1 at 92.0% (range: 82%–100.0%), Dyad 2 at 93.0% (range: 81.0%–97.0%), Dyad 3 at 85.0% (range: 81.0%–88.0%), and Dyad 4 at 88.0% (range: 82%–100%).
For the knowledge assessments, IOA was calculated for 43.0% of all opportunities in baseline, intervention, and follow-up across all four dyads. IOA was calculated on the knowledge assessment by two raters checking both the accuracy of the calculated score from the Qualtrics report and the accuracy of the score being transferred onto the graphs. The average IOA for the knowledge assessment was 100% across all reviews and all dyads.
Experimental Design
A concurrent multiple baseline across parent–child dyads was used in the present study. A multiple baseline design across participants has been used frequently in other parent-training studies (e.g., Vismara et al., 2012; Vismara et al., 2013; Wainer & Ingersoll, 2013, 2015) though single subject data were not published on the seminal OASIS study. Weeks on the x-axis represent concurrent weeks from September 2019 (start of baseline for Dyad 1) until June 2020 (final follow-up for Dyad 4). Parent training sessions occurred once per week and typically occurred on the same day of the week and at the same time unless a parent requested to reschedule. Dyad 4 was recruited later than other dyads; therefore, Dyad 4’s baseline sessions do not overlap with Dyad 3’s baseline sessions.
OASIS Procedures
OASIS Coach Information
OASIS is a highly structured, manualized training program conducted by trained coaches. Coaches were trained to criterion utilizing a behavioral skills training model delivered at the University of Kansas Medical Center, where the OASIS parent training was developed. Coach training consisted of 40 hr of instruction and hands-on skill practice with feedback. Coaching sessions were scripted and manualized to ensure necessary content was reviewed with parents and to ensure consistent delivery across participants. Live coaching session information was contained in a booklet (OASIS “Coach Protocol”), with all scripts and information for each module and coaching session. A copy of a secondary booklet (“Assessment Protocol”) was provided to the coach for each family that participated in training. The Assessment Protocol served as the data sheet for each live coaching session and the booklet contained spaces for the coach to check off when specific activities were completed (e.g., check in, review of the online materials). Data collection on target skills being reviewed in each module were also located in the Assessment Protocol booklet. The coach was trained to use both booklets during the 40-hr training with 90% fidelity of implementation for all procedures (e.g., following the scripts, scoring parents accurately).
Parent Training Sequence
Parents were required to complete online modules that provided detailed information on techniques and strategies to be reviewed during live coaching sessions. Parents then attended scheduled live coaching sessions via Zoom. Due to the scripted nature of the training, parents followed the same sequence for live coaching sessions (see Table 2 for the general sequence of each live training session). For example, the beginning of Module 1 (Introduction to Autism and Behavioral Treatment) included a script of the goals for the session, a script to welcome the family to the session, a script to provide a brief overview of the session, prompts for the coach to review online materials, and prompts to engage in any hands-on activities. Although the scripted nature of the program attempted to limit variations in delivery of the training, the script cannot account for every aspect of a session, such as answering parent questions. Individualized content varied from participant to participant based on requests for additional information or questions.Table 2 Live coaching session sequence of events
Step Activity
0 Pre-live training: Parent completed the online module
1 Review session goals (<5 min)
2 Discuss online materials (5 min)
3 Module overview with questions (10–15 min)
4 Skills assessment (5–10 min per skill)
5 Coaching session on skills if below criterion (10–15 min per skill)
6 Unstructured activity (5 min)
7 Question and answer (5 min)
8 Discuss next appointment (2 min)
9 Confirm next appointment (2 min)
• Comprehensive skills assessment (if scheduled)
• Prompt to complete the knowledge assessment (if scheduled)
Intake
Similar to Heitzman-Powell et al., (2014), varied intake measures were collected to determine if scores on each measure differed during intake and follow-up assessments based solely on the use of the OASIS program. Child intake measures included: The Childhood Autism Rating Scale-2 (CARS-2; Schopler et al., 1980), Vineland Adaptive Behavior Scales, Third Edition (Vineland-3; Sparrow et al., 2016), behavioral observations (parent checklist; child-parent interaction), Autism Treatment Evaluation Checklist (ATEC; Rimland & Edelson, 1999), and the Family Quality of Life (FQoL; Hu et al., 2011). Unlike Heitzman-Powell et al., (2014), the Child Behavior Checklist (CBCL; Achenbach, 1994) was added to the intake and follow-up measures. Basic demographic data were also collected.
Baseline
Parent dependent measures (comprehensive skill assessments and knowledge assessments) were collected during a small number of sessions (i.e., probes). Each baseline session lasted between 1.0 and 2.0 hr for the comprehensive skill assessment, dependent upon both parent preparedness and the child’s displays of problematic behavior. During the sessions, parents were presented with the prompts from the comprehensive skill assessment and asked to engage in each of the 13 target skills. For example, parents were told, “show me how you would find something that your child would work for or earn,” and then permitted time to respond as they felt appropriate. If they completed any of the micro skills under the “Preference Assessment” target skill, the micro skill was scored as a “+” on the data sheet by the first author. If they did not engage in steps or performed steps in error, the step was scored as a “-” on the data sheet by the first author. Parents were not provided with any feedback, prompts, or the results/scores of the assessments. The parent was permitted to request to end their time with each target skill. For example, one target skill prompt was for the parent to show the OASIS coach how to overteach something to their child. If the parent did not know what “overteach” meant, they were instructed to say “I don’t know” to move on to the next target skill prompt. Some encouragement was given to the parents by the OASIS coach saying something such as “try your best.” Following the end of the live baseline session, the parent was prompted to complete the knowledge assessment at their convenience and then emailed a direct link as an additional prompt.
Intervention
Intervention sessions for each parent–child dyad were scheduled once per week for 16–21 weeks for 1.5–2.0 hr per week and were conducted via Zoom (i.e., live coaching sessions). Each intervention session followed the same general pattern as outlined in the OASIS training materials (see above; e.g., OASIS Coach Protocol). There were two main components to each intervention session, including the parent preparation and the live coaching session.
For parent preparation, parents were required to complete one of the online modules (an interactive PowerPoint) and reach the mastery criterion (80%) on the online module’s knowledge assessment prior to each live coaching session. Online modules and content were completed at a time most convenient for the parent, with the only requirement being that they complete it prior to the scheduled coaching session (e.g., if the coaching session was Sunday at 5:00 pm, the parent was permitted to complete the online content by 4:59 pm). There were eight online modules in total, with two intervention sessions occurring for Modules 2–8. Therefore, parents completed Module 1 content and knowledge assessment prior to meeting for the Module 1.0 live coaching session and for subsequent modules, parents completed the online module content and knowledge assessment but attended two live coaching sessions (e.g., parents completed Module 2, but then attended Module 2.1 and Module 2.2 coaching sessions prior to completing Module 3 online, and so on). All preparation activities (e.g., the modules, problem behavior forms) typically take approximately 1 hr, depending on the parent’s speed and if they chose to review content more than once.
During live coaching sessions, the OASIS coach progressed through the scripted information (see Table 2, starting at Step 1). Each session began by greeting the parent and child, reviewing the overall session goals and general sequence (e.g., “We’ll start today by reviewing the online materials and talking through some concepts with just you, and then later we’ll get to activities and interactions with [child’s name]”). Next, the online materials (e.g., quiz, problem behavior forms) were reviewed, followed by a scripted review of the module content and information. Following the review of content, the live coaching session then moved on to hands-on skills training with the parent and child (see Table 3 for a list of hands-on skill activities scripted into each OASIS module) with three attempts or opportunities to practice the target skill. Hands-on skills training was individualized to each module, with one to three target skills being taught directly with behavioral skills training. Major target skills from the OASIS modules also comprised the comprehensive skills assessment (i.e., the dependent measure). Additional coaching for hands-on skills was conducted if the parent was not at a score of 80% following the initial training component. Parents progressed through training based on their progress and scores in training, rather than progressing based on their scores on the comprehensive skills assessment (i.e., dependent measure). The live coaching session then included a 5-min unstructured activity with the parent and child (e.g., rapport building and child-led playtime). The live coaching session closed with probing for parent questions, discussing the next module content, and confirming the next appointment time.Table 3 Scripted parent target skills taught and tested in each module of the OASIS training program during live coaching sessions
Module Session Skill
1.0 1 Discussing skills across varied domains (e.g., preparation for skills to work on during training)
2.1 2 Defining and observing behavior (e.g., operational definitions)
2.2^ 3 Collecting and graphing data (e.g., dimensions of behavior, measuring dimensions)
3.1^ 4 Preference assessments and reinforcer delivery (e.g., forced choice preference assessment, principles of reinforcement); three term contingency
3.2 5 Short instructions, differential/immediate reinforcement (e.g., concise SD, reinforcing appropriate behaviors only, token delivery, shaping)
4.1^ 6 Prompt and prompt fading (e.g., types of prompts, using prompts, removing prompts)
4.2^ 7 Errorless learning (e.g., including prompts, reinforcement)
5.1 8 Teaching environment, breaks, attending (e.g., how to structure the environment to reduce problem behavior, providing breaks, reinforcing attending)
5.2^ 9 General teaching strategies and teaching a new skill (e.g., thinning reinforcement, choosing prompts, delivering SDs, pace of instruction) and role play (e.g., practicing specific behaviors in a pretend-play scenario)
6.1 10 Antecedent control (e.g., behavioral momentum, pre-corrects, generalization)
6.2 11 Antecedent control (e.g., mass versus interspersed trials)
7.1^ 12 Consequential control (e.g., escape extinction, access extinction)
7.2 13 Consequential control (e.g., overcorrection)
8.1 14 Discussion of child specific skills to be addressed and development of instructional programs with the parent
8.2 15 Parent practice of implementation of programs written by parents (across 8 domains); feedback and adjustments offered
A ^ indicates that at least one of the micro skills included in the module also then occurred in subsequent skills and modules. Micro skills are only marked the first time they occur if they occur across modules. Also, note that some target skills from Modules 4.1-7.2 were used in the comprehensive skill assessment (i.e., dependent measure)
Data collection occurred in the “Assessment Protocol” booklet for each dyad across all activities included in the live coaching session (e.g., a spot to record an X to indicate that each step of training occurred as outlined was provided in the Assessment Protocol booklet). In addition, data were collected in the Assessment Protocol booklet for the hands-on skills training in each module, including data on the individual micro skills of each target skill being taught. A “+” was recorded for accurate responding and a “–“ was recorded for incorrect responding or failing to engage in the micro skill. The parent handbook contained suggested activities based on beginner, intermediate, and advanced child skills for parents to select or modify based on the child’s skill level. For example, a beginner skill was one-step gross motor imitation and an advanced skill was drawing specific shapes. Parents were permitted to choose an activity they felt appropriate or worked with the OASIS coach to choose a skill they felt valuable for their child. Hands-on practice of target skills required the parent to obtain 80% mastery across all opportunities and to engage in accurate responding at least once across every micro skill (e.g., scoring a “–“ on the same micro skill all three times prevented parents from moving on with training). If the parent failed to score an 80%, additional training was provided for the target skill. If parents were still unable to appropriately complete the materials for a module, a second intervention session for the same material was scheduled within the same week to provide another opportunity to reach criterion. Parents were allowed to request a second session for any of the modules. None of the four dyads required or requested a second session for any of the modules.
In between live coaching sessions, parents were also required to fill out information related to their child’s problem behavior during naturalistic times throughout their week (i.e., Problem Behavior [PBR] Recording forms) and information related to teaching opportunities they engaged in outside of the live coaching sessions (i.e., Incidental Teaching Checklists [ITC]). The PBR forms were utilized as additional training for the parents by reviewing problematic behaviors displayed by the child that occurred in between live coaching sessions. Reviewing the display of problematic behavior and parent responses allowed time to discuss potential strategies as well as how to incorporate information from the modules into their day-to-day activities to help prevent the occurrence of problem behavior. The ITC forms were also utilized as additional teaching on the use of target skills outside of live coaching sessions. The ITC forms also served the purpose of checking in on parent’s generalization of training materials to naturalistic situations.
Follow-up
Follow-up sessions occurred at 1-, 3-, and 5 weeks after training and were identical to baseline sessions for dependent measures, with one exception. Standardized assessment measures presented initially during the intake process (e.g., the Vineland-3, CARS-2, and CBCL) were administered at the end of first follow-up session.
Treatment Fidelity
An independent observer watched videos of the live coaching sessions and recorded whether the OASIS coach (i.e., the first author) completed each section of information in the training as designed to ensure fidelity of implementation of the intervention. The independent observer scored each element of the training session as a + for occurring and – for not occurring. The total number of items delivered during training was divided by the total number of items outlined in the training protocol and then multiplied by 100%. All four dyads had 33.0% of their live coaching sessions reviewed for treatment fidelity, with 100% treatment fidelity reported across all four dyads.
Social Validity
All parents were also asked to complete a brief social validity survey following completion of intervention. Social validity was collected by presenting 24 questions (e.g., “I would be willing to use this outside of the training sessions”; “This was an acceptable training program for my child’s problem behavior”) and asking the parent to rate how much they agreed with each statement on a Likert scale of 1–5 (1 = strongly disagree, 5 = strongly agree).
Time and Cost Savings
Time and cost savings were calculated in the same manner as Heitzman-Powell et al., (2014). The OASIS parent-training program is relatively new, with few practitioners trained and approved to deliver services. Time was calculated by taking the drive time from each dyad’s city of residence to the main office of the agency that provides OASIS parent training. Cost savings were calculated for the total cost of travel from each dyad’s city of residence to the main office of the agency that provides OASIS parent training by taking the total number of miles and multiplying by the 2019 Internal Revenue Service (IRS) rates of $.575/mile (IRS, 2019). Cost and time savings were calculated for each dyad’s round trip to the office location for every session they attended during the intervention portion of training.
Results
Comprehensive Skill Assessment
Scores for comprehensive skills checks for each dyad are displayed in Fig. 1. Overall, all four dyads demonstrated a gradual improvement in their use of target skills following the introduction of training. All four dyads had a sharp increase in scores from their final baseline to their first two data points in intervention, with three of the four dyads (Dyads 1, 3, and 4) accuracy decreasing slightly during the third (Dyad 3) or fourth (Dyads 1 and 4) intervention probes prior to continuing an upward trend for the remainder of intervention. Dyad 2 (e.g., Shay) was the only dyad to make continuous progress on an upward trend without evidence of skill regression. All four dyads’ accuracy peaked during the sixth intervention probe. During follow-up, three of the four dyads (Dyads 1, 2, and 3) showed stable and/or increasing maintenance. The fourth dyad (Dyad 4) showed stable maintenance during the first two probes before decreasing slightly during the third probe. All four dyads made gains in their applied skills over the course of training. The mean gain from the first baseline session to the first follow-up session was 80.9% (range: 67.6%–95.5%) Scores for pre- and post-comprehensive skill assessments are displayed in Table 4.Fig. 1 Percentage of comprehensive skills steps completed correctly across dyads
Table 4 Comprehensive skill assessment scores (Top Panel) and knowledge assessment scores (Bottom Panel) for the first baseline probe, first intervention probe, first follow-up probe, and final follow-up probe
Comprehensive Skills Assessment
Baseline (pretest) Intervention Follow Up #1 (posttest) Follow Up #3 Mean Gains
Lyanne 4.4% 94.1% 94.1% 98.5% 80.9% (range: 67.6%–95.5%)
Shay 1.5% 97.0% 97.0% 98.5%
Rose 13.0% 80.6% 80.6% 83.5%
Sasha 11.8% 82.4% 79.4% 77.9%
Knowledge Assessment
Baseline (pretest) Intervention Follow Up #1 (posttest) Follow Up #3 Mean Gains
Lyanne 35% 75% 75% 77% 35% (range: 19%–49%)
Shay 39% 87% 87% 95%
Rose 40% 73% 73% 73%
Sasha 43% 62% 70% 58%
A secondary analysis of parent skill data was conducted by evaluating the scores on each target skill over time, as they occurred in the context of training. Although the primary dependent variable was the overall target skill score, an additional analysis of data is warranted given the present study sought to provide a preliminary but comprehensive analysis of the OASIS training program. As an example, Fig. 2 displays the data on each individual target skill for the parent in Dyad 2 (Shay) in the order in which the target skills were presented during live coaching sessions. Some target skills, such as reinforcement and structuring the environment, increased prior to the introduction of specific teaching; however, as previously noted, some micro skills in many target skills were likely prompted in a general manner during initial training sessions, leading to increases in scores prior to structured teaching on some of the target skills. For example, gaining attention may have been prompted during initial live coaching sessions to ensure the parent practiced a target skill, despite gaining attention not occurring as a micro skill until Module 3.2. The results displayed in Fig. 2 demonstrate skill acquisition and maintenance for targets that had not yet been introduced. In particular, during baseline Shay increased her scores on reinforcement and prompting (second panel) following stable low to moderate levels across four probes prior to the introduction of these target skills during live coaching sessions. Likewise, structuring the environment and attending (third panel) were variable or low during baseline initially, but then increased to 80%–100% accuracy prior to the introduction of these target skills during live coaching sessions. Skill acquisition was also observed for mass and interspersed trials (sixth panel) and overcorrection (eighth panel) following 0% accuracy across seven and eight probes, respectively, during baseline.Fig. 2 Percentage of comprehensive skill steps completed correctly (on the dependent measure) across training modules for dyad 2 (shay). Note. Data are located under “baseline” until they were formally introduced during a module, at which point they are moved to “intervention”
Similar results were observed for other participants during secondary analysis. Lyanne (Dyad 1) consistently displayed accuracy in reinforcement and attending behavior during baseline (the only two skills she displayed with 100% accuracy), which maintained at 100% accuracy in all dependent measure probes apart from one session for each target skill. In addition, Lyanne demonstrated an increase in accuracy with mass trial instruction, prompting, and structuring the environment prior to the introduction of structured teaching procedures. Roslin (Dyad 3) engaged in inconsistent accurate responding on target skills in baseline, except for teaching a new skill, which varied from 33% to 44%. During parent training, her accuracy across several target skills increased prior to the introduction of structured teaching procedures, including reinforcement, structuring the environment, generalization, mass trial instruction, interspersed trial instruction, and extinction. Sansa (Dyad 4) inconsistently displayed accuracy responding for all target skills throughout baseline. Similar to the other dyads, she demonstrated an increase in accuracy across a variety of target skills prior to their introduction in structured teaching procedures, including reinforcement, structuring the environment, attending, mass trial instruction, and extinction.
Knowledge Assessments
Scores for knowledge assessments (initial baseline data point, final data point in intervention, first data point in follow-up, and final data point in follow-up) are displayed in Table 4. All four parents displayed an increase in their knowledge from baseline and intervention, with sustained increases of at least 15% (range: 15%–56%) from the pretest to the final follow-up probe. The mean gain from pretest to the initial posttest was 35.3% (range: 19.0%–49.0%). Dyad 3 missed one knowledge assessment during intervention and Dyad 4 had multiple delays in completing knowledge assessments, leading to fewer assessments overall.
Pre- and Postintervention Standardized Assessments of Behavior Change
Data from pre- and postintervention standardized assessments of behavior change (e.g., CBCL, CARS-2) did not demonstrate any reliable changes in scores across all four child participants except for the ATEC, which can be used to monitor treatment efficacy and child progress over time. Scores on the ATEC changed in the expected direction for three of four child participants (Dyads 1–3, Kal, Benjy, Jorah), with a decrease in scores from pre- to postintervention for both the overall score and the four individual subscales of the ATEC. The fourth participant (Dyad 4, Kalee) was the only participant to have reported increases in the overall ATEC score, with stable data on two scores, an increase in scores on one subscale, and a decrease in scores on one subscale. Preintervention scores on the ATEC averaged 76.8 (range: 63.0–96.0), with scores of 63, 69, 79, and 96 for Dyads 1-4, respectively. Post-intervention scores averaged 62.3 (range, 39.0-106.0), with scores of 25, 49, 55, and 106 for Dyads 1–4, respectively. Decreasing scores on the ATEC for Dyads 1–3 suggested improvement in the parent-perceived level of concern on assessed behaviors, with the increasing score for Dyad 4 suggesting a worsening in the parent-perceived level of concern on assessed behaviors.
Social Validity
All four parents rated the OASIS program socially valid overall, with a total average score of 4.85/5.00. Dyad 1 (Lyanne) rated social validity at 4.83/5.00, Dyad 2 (Shay) rated social validity at 4.74/5.00, Dyad 3 (Rose) rated social validity at 4.83/5.00, and Dyad 4 (Sasha) rated social validity at 5.00/5.00. Parents rated all items at a 4 or 5 on the Likert scale, except for one item. “The training program is consistent with those I have used in the home setting” was scored a 3 by Dyad 1 and was marked “N/A” by Dyad 2. Dyad 1 had previously had birth-to-three services that did not incorporate a full parent training component.
Time and Cost Savings
Results for time and cost savings are displayed in Table 5. Intake, baseline, and follow-up were excluded in time and cost calculations for all four dyads because they do not occur during a parent-training only model. Three of the participants lived in the same town (Dyads 1, 3, and 4). The total round-trip mileage for Dyads 1, 3, and 4 was 242 miles. Dyads 1, 3, and 4 had 15 total sessions during intervention, requiring 3,630 miles total at a cost of $2,087.25, and 67.50 total hr of travel time (per dyad) if they had traveled to a treatment site. Dyad 2, the closest participant to the office location, had 16 total sessions during intervention. Travel costs required 1,504 miles total at a cost of $864.80, and 24 total hr of travel time if they had traveled to a treatment site.Table 5 Participant mileage and cost breakdown
Number of Sessions Round Trip Miles Total Miles Required Total Cost ($.575/mile*) Number of Calendar Weeks (Baseline-Follow-Up)
Dyad 1: Kal & Lyanne 15 242 3,630 $2,087.25 29
Dyad 2: Benjy & Shay 16 94 1,504 $864.80 32
Dyad 3: Jorah & Rose 15 242 3,630 $2,087.25 31
Dyad 4: Kalee & Sasha 15 242 3,630 $2,087.25 26
Total time commitment from start to finish for participation in the study is important to note and is therefore included in Table 5 because cancellations for illness or holidays may affect how quickly parents progress through the entire training program. The OASIS program is designed to be completed in as little as 15 weeks. For the present study, the minimum number of weeks required for live coaching sessions was 15, with an additional 1 to 3 weeks of baseline, and 5 weeks of follow-up. In total, all parents should have completed the entire study in 21–23 weeks. Including baseline and follow-up measures, Dyad 1 required 29 calendar weeks to complete participation, Dyad 2 required 32 calendar weeks to complete participation, Dyad 3 required 31 calendar weeks to complete participation, and Dyad 4 required 26 calendar weeks to complete participation. Based on the number of baseline and follow-up sessions for each dyad, participation in the study took 8, 9, 8, and 3 additional weeks beyond the minimum number required for participation for Dyads 1–4, respectively. The additional weeks to complete the study resulted in increased total time commitments of 13%–39%.
Discussion
The present study replicated the primary outcomes of seminal research on OASIS. Most notable is that parent target skills increased to 80%–100% on comprehensive skills checks and were maintained at high levels for all four participants following treatment (see Fig. 1). Target skill gains in the present study (80.9%) were higher than the 2014 evaluation of OASIS (41.2%). Overall, parents were consistently able to implement necessary skills when working one-on-one with their child. This led to more productive teaching sessions and more potential for parent skill gains despite instruction and feedback being given via Zoom rather than in-person. Skill gains maintained following treatment for all four dyads, despite inconsistencies they may have displayed during treatment. The maintenance of these skills also ensured parents were able to continue effective treatment procedures in the absence of the OASIS coach, an important finding as many parents can be the main and most natural treatment provider for their child.
As dyads progressed through OASIS training modules their skill gains were demonstrated on comprehensive skills assessments. By the first comprehensive skill assessment in training, parents had completed the first module (Module 1: Introduction to Autism and Behavioral Treatment) and the first half of the second module (Module 2.1: Defining and Observing Behavior); however, neither module contained a target skill from the comprehensive skill assessment. The first target skill probed on the comprehensive skill assessment (preference assessment) was not introduced until Module 3.1: Principles of Behavior. At first, increases in comprehensive skill check scores did not come from the first few target skills taught during training (see Fig. 3 for data related to the first two skills). Parents were required to engage in structured activities with their child prior to Module 3.1, with micro skill gains likely occurring, which account for the increase in overall scores during the first comprehensive skills assessment conducted during intervention. Micro skills were the individual steps within each of the 13 target skills. For example, the target skill of “Teaching a New Skill” contained nine individual steps including gaining the child’s attention, giving the instruction in statement format once, and pairing praise with reinforcement. Although a parent was not taught how to teach a new skill in initial sessions, prompts to gain attention or deliver praise and reinforcers occurred as they began working with their child in the first few training sessions. Feedback received in those first few training sessions likely led to parent gains on micro skills, accounting for increases in their total comprehensive skill scores. Gains on micro skills occurred in several instances prior to the introduction of specific teaching to any target skill, such as “Teaching a New Skill.”Fig. 3 Percentage of comprehensive skill steps completed correctly (on the dependent measure) across the first two skills taught during training (preference assessment and teaching a new skill) for each dyad
Results from the parent knowledge assessments replicated the gains observed in the 2014 evaluation of OASIS with a mean gain of 37.3 points in the present study and a mean gain of 39.1 points in the seminal publication (Heitzman-Powell et al., 2014). The online delivery of instructional modules was an effective method of increasing parent knowledge. Basic knowledge of procedures can facilitate hands on learning experiences, which appears to have occurred during training sessions. It should be noted that parents in all four dyads referenced specific information from the modules or by asking clarifying questions when attempting to implement skills directly with their child (e.g., stating what they had read and then asking how it applied to the task they were performing). Knowledge changes may also increase parental acceptance of behavioral procedures because they have been provided background information that explains why or how a particular skill or procedure is effective or important. Knowledge checks potentially served as a form of written instructions that may typically be seen in a behavior skills training model (e.g., Sarokoff & Sturmey, 2008), which may have facilitated skill gains on comprehensive skill assessments. Parent knowledge final scores were not as high as the final scores on skills, nor did knowledge scores maintain as well as the skills scores. Lower scores on the knowledge assessment may have been due to a variety of factors, including inattention during the online test, lack of generalization of the questions from the format of the modules to the format of the online test, testing environment, or the parents general test taking skills and behaviors. The highest knowledge assessment scores were seen with Dyad 2 (Shay), who also had the highest education level (graduate degree). Despite the lower knowledge scores, parents all increased their fluency in applying skills and maintained their ability to implement behavior-analytic strategies at follow-up measures. Low knowledge scores are likely to not have as great an impact because low skill scores because the parents are far more likely to engage in activities related to their hands on skills on a consistent basis then to apply general knowledge and background information.
The present study had two important differences compared to Heitzman-Powell et al., (2014). First, the present study was conducted with parents located in their homes and using personal electronic devices, rather than the parents being required to drive to a telehealth-capable site. Remaining in their homes for training was of particular importance given that they lived in rural or underserved areas and treatment locations were up to 2 hr, 10 min away (one way). The parents all had access to Zoom on their personal devices and were able to connect with the OASIS coach consistently. Parents were able to successfully access online training, resulting in significant behavior change, by use of iPads or desktop computers (live coaching sessions occurred via tablet or cell phone). This increased accessibility of OASIS training is important for individuals living in rural and remote areas because travel may be a barrier to treatment access. Second, rather than an analysis of pre/post skill data, the present study utilized a granular measure of behavior change within a single-subject design (i.e., multiple baseline) by collecting data throughout the 16 weeks of parent training sessions. A granular measure of behavior change allowed for a more precise analysis of how parents developed and maintained their skills over time. In particular, although some variability occurred in skill acquisition, parent skills on all tasks consistently increased and maintained by the end of training and into the maintenance condition. The repeated measures analysis of the intervention allowed for more confidence that the intervention was effective because: (1) immediate increases in skills were observed when the intervention was introduced for each participant; (2) continued increases occurred throughout training; and (3) skill gains were maintained after treatment was terminated.
Implications for Clinicians
In a changing treatment landscape, telehealth has gained momentum as an alternative to face-to-face treatment and has continued to expand with the development of technology that increases accessibility, reaching larger pools of people in more underserved areas (e.g., Baggett et al., 2010). Given current global health concerns, telehealth has become an increasingly relevant issue for a variety of health professionals, with the CDC urging use of telework to mitigate community spread of illness (e.g., COVID-19; National Center for Immunization and Respiratory Diseases, 2020). Telehealth as a treatment delivery mechanism may also increase the reach and scope of behavior analytic services. Unfortunately, the use of telehealth in behavior analytic services lagged behind its use in other helping professions (Tomlinson et al., 2018), despite the benefits of increased access to treatment services, such as the use of telehealth to support and train parents. However, with the onset of the COVID-19 pandemic in 2020, the research related to telehealth feasibility and the available information regarding implementation of ABA services via telehealth has been on an increasing trend (Ellison et al., 2021).
Parents are a critical and integral part of their child’s treatment services (e.g., Jang et al., 2012) and research related to increasing their participation in their child’s treatment is critical, though some limitations have existed in reviews of parent training literature. In particular, Schultz et al., (2011) noted that only 3 of 30 reviewed studies mentioned teaching behavior analysis in particular. Furthermore, Ferguson et al., (2019) found that despite articles being related to behavior analysis and telehealth, only 7% indicated providing comprehensive knowledge and skills. The OASIS program offers the structure and support needed to teach parents how to provide behavior-analytic services effectively and efficiently to their child in the absence of other intervention options. The OASIS program also provides a more comprehensive approach to parent training, teaching skills across both behavior acquisition and behavior reduction, further filling a gap in the current literature.
Telehealth-based parent training has additional benefits for families. Travel time and cost savings from remaining at home for training can help offset the health-care costs of having a child with autism (estimated at $22,772 in Medicaid costs; Wang & Leslie, 2010). The families in the present experiment had cost savings of $864.80-$2,087.25 in travel costs alone for approximately 6 months of participation. Two parents had other children in the home during training times. Although at times they had to step away from training to engage the additional children in tasks or activities, there was minimal interference. Both parents were able to engage in training without requiring childcare for other children in their care, leading to not only more cost savings but also more flexibility in meeting with the researcher. Furthermore, the training is also provided in the child’s natural environment with their toys and items (not requiring generalization training in the home). In addition, parents accessed services while on a waitlist for additional services. Agencies that are unable to provide comprehensive services (e.g., lack of direct service providers, consultants with short-term availability) may turn to parent training as a means of providing services to wait listed families until other treatment options or slots open. Parent training via telehealth is particularly important in rural areas where there may be no in-person service options or long drive times to the nearest treatment location.
Limitations
Several limitations occurred throughout the study. First, multiple technical issues occurred throughout the course of the study. Zoom closed unexpectedly and a baseline video for Dyad 2 was lost; however, this issue only occurred once across all sessions. Related to this, background noise in the room with participants at times made it difficult to hear what was being said. During some of Dyad 3’s sessions, other people in the household were heard, making training more difficult. In addition, the audio was sometimes delayed due to background noise reduction features built into Zoom, resulting in the coach and parent occasionally talking at the same time. Technical issues may be fixed by providing families with materials they need to have stable audio and visual connections in place of using a cell phone or tablet that must connect wirelessly. Second, getting required paperwork to/from families was difficult. Some dyads printed and scanned information that was sent via email whereas other dyads required mailed paperwork to send back. Regardless of the method for paperwork transmission, some paperwork was lost. Families were also required to complete the majority of received paperwork on their own, rather than face-to-face with a clinician or the researcher.
Future Directions
Continued research on the generality of OASIS is necessary for reaching more families affected by autism in resource-low areas, but also in areas where resources may be available but subject to wait lists, age limits, and a myriad of other factors. Future research should include variations of replications such as outcomes across different clinicians, outcomes across different client ages, outcomes based on time spent in each training module, and outcomes across different delivery modalities. Furthermore, extensions of the current and existing research should include better monitoring of child-specific outcomes related to both skills and problem behaviors. In the end, child behavior change is the goal of parent training programs like OASIS, and child outcomes should be both included in studies and verified experimentally. With a limited amount of time to provide training (e.g., the 16–21 weeks of OASIS), immediate child changes may not be evident. Individual skill acquisition targets may lend themselves better to consistent data collection during sessions as opposed to problem behavior and pre-/postmeasures may be more reflective of actual behavior change if included during a long-term follow-up. For example, in the present study child problem behavior was displayed intermittently during baseline/training sessions and no clear pattern or trend was evident in any of the dyads. However, Dyad 1 (Lyanne) and Dyad 2 (Shay) reported that their child was easier to work with as the training progressed and they felt they were better able to get their child to attend to and complete tasks during training sessions as time progressed. The amount of time parents spent outside of sessions working with their child is also worth investigation, as Dyad 1 and Dyad 2 may have had more exposure to training activities if items were completed more regularly in between meetings with the OASIS coach. Furthermore, pre-/postmeasures of training (e.g., the Vineland-3 and ATEC) may not indicate meaningful changes in the typical timeframe in which OASIS is delivered, and more directly observable measures that can be both reliable and readily implemented via telehealth may be a necessary component of parent training.
Additional research should also focus on data collection and analyses focused on more granular measures of treatment effects, similar to the secondary analysis presented in the present study. Parent training is a comprehensive service with numerous variables that may contribute to behavior change. Furthermore, skill gains (such as those taught in the current study) are not independent of one another. Gains in some areas can increase skills in other areas. For example, increasing reinforcement by the parent may also increase their scores on presenting mass or interspersed trials when reinforcement is included as a step in the overall skill. A granular analysis will assist in parsing apart the effects from specific components of training and will allow researchers to gain a better understanding of how behavior changes within complex teaching technologies. Furthermore, skill deficits that are identified in the granular analysis can be remedied through changes in the OASIS curriculum.
Parents increased hands-on skills and knowledge after completing OASIS training. Parents and families in rural and remote areas also accessed critical services and gained a better understanding of evidence-based practices. The present results provided additional empirical evidence demonstrating the effectiveness of OASIS, a telehealth-based parent-training model. Amid growing health crises, increasing prevalence rates of autism, and a lack of qualified providers, telehealth and parent training are poised to create large-scale changes in how services are accessed and provided.
Data Availability
Data is available upon request. Specific materials for the OASIS training are proprietary and must be obtained by the original authors.
Declarations
This project was considered exempt by the Southern Illinois University (Carbondale) Human Subject Committee (HSC: Protocol #19145), with the HSC reporting to researchers that the methods of parent training were considered part of typical clinical care and not subject to standard review.
Informed Consent
Informed consent was obtained for all participants per the guidelines of the SIU-C HSC.
• Telehealth-based parent training is an effective tool in integrating parents into treatment services
• Manualized parent training can increase parent skills and knowledge
• Skill gains may occur quickly under the OASIS model, with skills maintaining over time
• Use of parent training can inform or strengthen delivery of more comprehensive treatment models
• The use of structured parent training may assist in treatment planning and authorization of services
This research was completed in partial fulfillment for the first author’s doctoral degree as a portion of dissertation requirements at Southern Illinois University.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9735022 | NO-CC CODE | 2022-12-14 23:28:32 | no | Behav Anal Pract. 2022 Dec 6;:1-17 | utf-8 | Behav Anal Pract | 2,022 | 10.1007/s40617-022-00763-z | oa_other |
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AAPS J
The AAPS Journal
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Springer International Publishing Cham
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Research Article
Overcoming Biopharmaceutical Interferents for Quantitation of Host Cell DNA Using an Automated, High-Throughput Methodology
Lauro Mackenzie L. [email protected]
Bowman Amy M.
Smith Joseph P.
Gaye Susannah N.
Acevedo-Skrip Jillian
DePhillips Pete A.
Loughney John W.
grid.417993.1 0000 0001 2260 0793 Analytical Research & Development, MRL, Merck & Co., Inc., West Point, Pennsylvania 19486 USA
8 12 2022
2 2023
25 1 1027 6 2022
21 10 2022
© The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The rapid development of biologics and vaccines in response to the current pandemic has highlighted the need for robust platform assays to characterize diverse biopharmaceuticals. A critical aspect of biopharmaceutical development is achieving a highly pure product, especially with respect to residual host cell material. Specifically, two important host cell impurities of focus within biopharmaceuticals are residual DNA and protein. In this work, a novel high-throughput host cell DNA quantitation assay was developed for rapid screening of complex vaccine drug substance samples. The developed assay utilizes the commercially available, fluorescent-sensitive Picogreen dye within a 96-well plate configuration to allow for a cost effective and rapid analysis. The assay was applied to in-process biopharmaceutical samples with known interferences to the dye, including RNA and protein. An enzymatic digestion pre-treatment was found to overcome these interferences and thus allow this method to be applied to wide-ranging, diverse analyses. In addition, the use of deoxycholate in the digestion treatment allowed for disruption of interactions in a given sample matrix in order to more accurately and selectively quantitate DNA. Critical analytical figures of merit for assay performance, such as precision and spike recovery, were evaluated and successfully demonstrated. This new analytical method can thus be successfully applied to both upstream and downstream process analysis for biologics and vaccines using an innovative and automated high-throughput approach.
Graphical Abstract
Keywords
High-throughput experimentation
Fluorescence
Vaccine development
Biological development
Process research and development
Automated assay development
DNA quantification
Protein interference
RNA interference
Enzymatic digestion
issue-copyright-statement© The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists 2023
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pmcIntroduction
Recent world crises, including the Ebola outbreak and COVID-19 pandemic, have brought to light the demand for accelerated timelines for the development of biologics and vaccines (1–4). In turn, analytical methodologies need to increase their throughput to meet these rapid timelines without compromising data integrity. To accomplish this feat, the development of platform assays that can be applied in a modality agnostic manner is highly beneficial for the robust assessment of both biologics and vaccines.
The manufacture of biopharmaceuticals, including both biologics and vaccines, often requires the use of a cell substrate to efficiently produce the desired drug substance (5–7). The resulting drug substance must in turn be carefully scrutinized for the presence of process related impurities such as residual host cell protein and deoxyribonucleic acid (DNA) (8–10) to maintain the quality, safety, and efficacy of the product. In particular, residual host cell DNA is defined as the sum of DNA and fragments present in biological samples derived from recombinant host cells during expression (11). The World Health Organization and U.S. Food and Drug Administration have strict guidelines as to the accepy limits of both the concentration of host cell DNA (10 ng/dose) and the size of the residual DNA (200 base pairs) in the final drug product (12, 13).
A variety of methodologies exist that can be applied for precise host cell DNA quantification. The most widely used technology is quantitative polymerase chain reaction (qPCR) (14–16). This approach uses highly specific DNA primers to detect the host cell DNA (17). For this reason, a number of qPCR assays have been commercialized for popular cell substrates, such as Escherichia coli, Pichia pastoris, Vero, and Chinese Hamster Ovary cells. Highly specific primers allow for minimal interference; however, depending on the commercial assay being utilized, varying coverages may exist. Additionally, DNA extraction may be needed in complex matrices, adding to the time and complexity of the assay. While qPCR allows for a highly specific method, the early development of biopharmaceuticals would benefit from a platform method to be universal to all cell substrates, measure smaller DNA fragments, and rapidly assess samples.
In addition to qPCR, fluorescence-based probe methods are frequently used to quantify host cell DNA. These methods rely on a fluorogenic dye, like SYBR Green (18) or Picogreen (19), that has specific interactions with the DNA. Fluorescence-based methods are highly advantageous, as their application can be generally applied across all biopharmaceuticals, have lower associated costs than qPCR, and are easily transferrable (20). However, a variety of common pharmaceutically relevant process impurities and formulation components, such as protein, RNA, and detergents (21, 22), can interfere with DNA quantitation using these fluorescent dyes. Therefore, to enable a robust fluorescence-based method, a thorough evaluation of the potential interference effects and their subsequent removal needs to be performed.
In this work, the commercially available, fluorescent sensitive Picogreen dye was selected as the basis for a quantitative, high-throughput host cell DNA assay. Picogreen is able to bind to double-stranded DNA through specific charge interactions (19). Picogreen has been applied in several formats to successfully quantify host cell DNA (21, 23, 24). However, these studies fail to overcome the common, pharmaceutically relevant interferences associated with non-specific binding to the reagent, including protein, RNA, and detergents (21, 22). This renders the current methodologies incompatible with many prominent vaccines such as mRNA vaccines and others utilizing RNA-based viruses as they contain high levels of RNA (2, 3, 25). Here, we assess the application of our proposed fluorescence-based assay to measure residual DNA in complex live-virus vaccine (LVV) drug substance. This enveloped RNA virus contained significant concentrations of RNA encapsulated in a protein and lipid shell as well as process related impurities including extracellular vesicles and large aggregates of host cell DNA and protein. Systems of a similar nature have been utilized in the development of vaccines targeting HIV, Chikungunya, West Nile Virus, and many other prominent pathogens (26–28). Interactions of the process related impurities in the drug substance were shown to have shielding effects, preventing access to the nucleotides within the drug substance. We herein demonstrate that these shielding-based interference effects can be overcome via addition of the detergent deoxycholate (DOC). Additionally, DOC has a known virucidal effect on various viruses such as influenza, HIV-1 viruses, and Rauscher leukemia by causing partial or complete disruption of the virion lipid membrane (29–31). This is a critical function of DOC to disrupt the viral components as well. DOC addition was further optimized to overcome this interference most effectively. Next, we demonstrate successful removal of RNA and protein interferences by enzymatic digestion with RNase A followed by Proteinase K addition. Finally, detailed evaluation and subsequent optimization of interferences of our proposed assay, resulting from addition of these reagents, was accomplished. To the best of our knowledge, this is the first report of a high-throughput, fluorescence-based analytical method utilizing the commercial Picogreen dye to quantitate host cell DNA in the presence of significant interferents commonly encountered within biopharmaceuticals, including RNA, protein, and detergents. Our proposed analytical method can thus be broadly applied to complex biopharmaceuticals with high specificity, precision, and accuracy for host cell DNA quantitation.
Materials and Methods
Reagents and Materials
Components of the Quant-iT™ Picogreen™ dsDNA Assay Kit, including the Picogreen reagent and 100 µg/mL λDNA standard stock (Thermo Fisher Scientific), were utilized. A calf thymus DNA (Sigma-Aldrich) standard and ribosomal RNA standard — 16S and 23S rRNA from E. coli (Thermo Fisher Scientific) — were diluted in phosphate-buffered saline (PBS) (Cytiva). Buffering components such as PS-80 (Thermo Fisher Scientific), Proteinase K (Thermo Fisher Scientific), Tris–EDTA 100 × buffer (Sigma-Aldrich), and 5 M sodium chloride solution (Invitrogen) were also utilized. The process-related samples of a live-virus vaccine drug substance were obtained from our Vaccine Process Development colleagues.
Consumable materials equipped on the Freedom EVO 200 Liquid Handling system (Tecan) include the following: 180 µL MCA 96 filtered, sterile tips (Corning-Axygen), 300 mL Nalgene Flat Bottom Reservoir (Thermo Fisher Scientific), Costar 96-well 2 mL polypropylene assay block (Thermo Fisher Scientific), 2 mL cryogenic vials (Nalgene), and Costar opaque 96-well microplates (Thermo Fisher Scientific). Additionally, a reusable 1000 mL Reagent Trough (Tecan) was equipped on the deck.
DNA Quantitation Assay on an Automated Liquid Handler
Our proposed analytical method is based on the commercially available Picogreen Assay. In short, this is a fluorogenic technique that results in increased fluorescence of the Picogreen dye upon binding to DNA. A Freedom EVO 200 Liquid Handling system (Tecan) was utilized to automate our proposed analytical method and applied throughout all experiments described in this work. The liquid handling system is equipped with an 8-channel pipetting arm, a multichannel arm (96 channels), and a microtiter-plate gripping arm. The system also has an integrated Infinite F500 microplate reader (Tecan). Microcide SQ (Hamilton) (3.05%) and 1 N NaOH (Fisher) were used as solvents to clean the fixed tips on the 8-channel arm in between sample handling steps. Samples are prepared in a Costar 96-well 2-mL deep well polypropylene plate (Fisher Scientific). The following steps were performed by the Tecan workstation. First, a standard curve was prepared in duplicate from a 100-µg/mL λDNA standard stock (Thermo Fisher Scientific) by dilution with a diluent consisting of 10 mM Tris, 1 mM EDTA, 100 mM NaCl, 200 µg/mL Proteinase K, and 0.01% Polysorbate-80, pH 8.0. Concentrations of 1, 2.5, 5, 10, 25, 50, 100, 150, 250, 400, and 500 ng/mL λDNA were prepared. Drug substance samples were diluted in 10 mM Tris, 1 mM EDTA, 100 mM NaCl, 200 µg/mL Proteinase K, and 0.01% Polysorbate-80, pH 8.0. Multiple sample dilutions were prepared to target the quantitative range of the assay, and drug substance samples were analyzed in triplicate. Standards and samples were both incubated for 10 min. A minimum dilution of 1:1 with 10 mM Tris, 1 mM EDTA, 100 mM NaCl, 200 µg/mL Proteinase K, and 0.01% Polysorbate-80, pH 8.0, was necessary to ensure proper digestion of residual protein within the samples via Proteinase K. Next, 100 µL of each prepared standard and sample was transferred to a Costar opaque 96-well plate (Fisher Scientific). An SBS reservoir containing Picogreen reagent (Thermo Fisher Scientific) diluted 1:200 in 10 mM Tris and 1 mM EDTA was placed on the automated liquid sample handler. To each standard and sample, 100 µL of the pre-diluted Picogreen reagent was added using the multichannel arm. The plate is then transferred using the robotic gripper arm to the Infinite F500 plate reader (Tecan), and the fluorescence of each well is measured at an excitation of 485 nm and emission of 535 nm. Ten exposures were performed per well and the gain is optimized based on the well with the highest intensity. The standard curve was generated by log–log linear regression of the mean of the given replicates. The DNA concentration of each sample was then interpolated from this standard curve.
Method to Overcome Interference Effects via Enzymatic Pretreatment of Drug Substance
Pre-treatment buffers were prepared containing 25 U of Benzonase (Millipore Sigma) and/or 0.4% DOC (Sigma-Aldrich) in PBS (Cytiva). Benzonase was prepared in a solution of PBS containing 100 mM MgCl2 (Sigma-Aldrich), as Mg2+ is a necessary co-factor for Benzonase activity (32). The pretreatment of the drug substance was performed using the automated Freedom EVO 200 Liquid Handling system (Tecan). The drug substance was then diluted 1:1 into the pre-treatment buffer within a 96-well 2 mL deep well plate. For untreated samples, the drug substance was diluted 1:1 in PBS within the 96-well 2 mL deep well plate. The samples were incubated at room temperature for 2 h. Samples were subsequently diluted 1:1 with 10 mM Tris, 1 mM EDTA, 100 mM NaCl, 200 µg/mL Proteinase K, and 0.01% Polysorbate-80, pH 8.0. The 96-well plate containing both Benzonase-treated and untreated samples was then transferred to the Liquid Handler (Tecan) and the automated, high-throughput Picogreen Assay proceeded as described above. As needed, further dilution of the samples into the linear range of the assay was performed. Measurements of each sample were taken in triplicate, with the mean result reported.
Pre-treatment buffers were prepared containing 5 µg/mL RNase A (Invitrogen) and/or DOC (Sigma-Aldrich) at varied concentrations (0.0125 to 0.4%) in PBS (Cytiva). The drug substance was then diluted 1:1 into the pre-treatment buffer or diluted 1:1 in PBS for untreated samples in a 96-well 2-mL deep well plate. The samples were incubated at room temperature for 2 h before being diluted 1:1 with 10 mM Tris, 1 mM EDTA, 100 mM NaCl, 200 µg/mL Proteinase K, and 0.01% Polysorbate-80, pH 8.0. The 96-well plate was then transferred to the Liquid Handler (Tecan), and the automated, high-throughout Picogreen Assay proceeded as described above.
Results and Discussions
Fully Automated, High-Throughput Picogreen DNA Quantitation Assay
A fully automated Picogreen-based assay has been developed using the Tecan Evo Liquid Handling system to allow for high throughput preparation and analysis of samples. In brief, an 11-point standard curve is generated in duplicate through serial dilution of a controlled DNA reference material from 1 to 500 ng/mL. Unknown samples are diluted into this linear range, in which multiple dilutions can be prepared of the same sample to ensure accuracy and precision of the resulting host cell DNA quantitation. After the designated dilution, the samples and standards are incubated with the assay diluent for 10 min to allow the Proteinase K, which is present in the diluent, to digest residual protein and remove this interferent (21). The samples and standards are transferred to an opaque, black 96-well plate suitable for fluorescence measurements. The Quant-iT™ Picogreen® double stranded DNA reagent is added and mixed with both the samples and references through a controlled aspiration and dispense process. The plate is transferred to a plate reader directly connected to the liquid handler. For analysis, the plate is exposed to 485 nm excitation, and the fluorescence emission is measured at 535 nm.
A standard curve is generated for each independent analysis of our proposed platform Picogreen-based assay (Fig. 1). Specifically, duplicate measurements of the given standards are averaged, and the log of the mean result is reported as the y-axis of the calibration curve. The x-axis is the log of the prepared DNA concentration of the standards, ranging from 1 to 500 ng/mL DNA. The lower limit of the reference curve is set by the limit of quantification. The acceptance criteria set by the FDA and WHO guidance is to have less than 10 ng/dose, making the 1 ng/mL detection limit reasonable. The upper limit of the reference curve was determined based upon the expected range of hcDNA concentrations observed through process development. Concentrations of hcDNA are not expected to exceed 5000 ng/mL, and with the ability of the automated system to dilute samples in the linear range, the upper limit of 500 ng/mL lends itself to realistic dilutions. The resulting calibration curve (Fig. 1) demonstrates extremely high linearity, in which an R2 value of 0.99 is observed. Furthermore, the dynamic range of this method is observed to be high, in which the 11 total standards analyzed across 2.5 orders of magnitude of DNA concentration all shows high linearity. Given this method is able to assess both low and high concentrations of DNA (i.e., 1 to 500 ng/mL DNA), the analysis of diverse biopharmaceuticals with wide-spanning DNA concentrations can be accomplished in a broad, straightforward manner. In order to be applicable as a platform methodology, the large range in the calibration curve and ability to prepare multiple dilutions through an automated approach is critical to the feasibility to implement appropriately.Fig. 1 Results from analysis of DNA reference material using the fluorescence-based analytical method. DNA standards were analyzed at concentrations of 1, 2.5, 5, 10, 25, 50, 100, 150, 250, 400, and 500 ng/mL in duplicate. The resulting standard curve displays the log of the average fluorescence signal of duplicate measurements of all prepared DNA reference materials
Additional analytical figures of merit for analysis of DNA reference materials were elucidated (Table I). In brief, the percent relative standard deviation (%RSD) confirms the high immediate precision of the automated assay, in which values range from 0.6 to 6.3%. The average %RSD across all concentration ranges analyzed is 2.6%, further highlighting the precision of the method. In addition, the percent error observed when correlating the expected DNA concentration of a given standard to that of the measured DNA concentration was also very low, with values ranging from 0.2 to 7%. Moreover, the average error across all concentration ranges analyzed is 3.9%, highlighting the low error observed for this method.Table I Results of Quantitation of DNA Reference Standards for Evaluation of Analytical Method. Expected DNA Concentration (ng/mL) Determined by Preparation of Reference Standard at Varying Concentrations. Measured DNA Concentration (mg/mL) Is the Mean Value of Duplicate Measurements. Statistical Analysis of Measured vs. Expected DNA Concentrations Are Provided as Relative Standard Deviation (RSD, %) and Error (%)
Expected DNA concentration (ng/mL) Measured DNA concentration (ng/mL) RSD (%) Error (%)
1.0 × 100 1.0 × 100 1.4 0.2
2.5 × 100 2.4 × 100 1.2 3.2
5.0 × 100 5.2 × 100 6.3 4.8
1.0 × 101 9.6 × 100 0.6 4.3
2.5 × 101 2.3 × 101 4.0 4.8
5.0 × 101 5.2 × 101 2.6 4.3
1.0 × 102 1.1 × 102 2.4 7.3
1.5 × 102 1.6 × 102 5.4 4.2
2.5 × 102 2.5 × 102 0.9 0.9
4.0 × 102 3.9 × 102 2.3 2.1
5.0 × 102 4.7 × 102 1.0 6.3
Using this automated, high-throughput platform assay, drug substance samples can undergo multiple dilutions along the given linear range, a key aspect for reliable quantitation. Moreover, using this fully automated platform, it is possible to quantify DNA in 384 samples in less than 4 h. With the basic analytical figures of merit now established for our proposed method, a detailed evaluation can now be performed to determine how process-related impurities in biopharmaceuticals may interfere with the assay and subsequent strategies to overcome these interferences.
Matrix Interactions Shield Host Cell DNA and RNA from Digestion
Several common, pharmaceutically relevant species are known to interfere with Picogreen-based DNA quantitation, including protein, RNA, and detergents (21, 22). In order to have a platform technology applicable to a wide range of biopharmaceuticals, a robust method for mitigating these interferences needed to be developed. As described here, Proteinase K is incorporated for digestion of protein, and thus, protein interference effects are overcome and accounted for. This work now focuses on understanding RNA and detergent interferences.
A complex LVV drug substance containing an enveloped RNA genome was selected for evaluation using the Picogreen DNA quantitation assay to assess methods for overcoming interferences. The sample had known complexities, such as high residual protein and genomic RNA. Due to the intricacies of the LVV drug substance, there was a high probability of interactions between components of the sample (i.e., host cell proteins, vesicles, process impurities) with the host cell DNA and genomic RNA. Such interactions with DNA could lead to a shielding effect — a prevention of the dye reaching the DNA (33) — that would result in inaccurate quantitation, as the Picogreen dye would be unable to interact appropriately with the host cell DNA (19). Additionally, sample matrix interactions with RNA may make it more difficult to remove this interference (34).
To investigate the potential shielding effects of the sample matrix, an evaluation was first done to determine the accessibility of the host cell DNA and genomic RNA by digestion via Benzonase (35, 36). Benzonase is an endonuclease that is commonly used in purification processes to remove residual DNA and RNA by digestion into small nucleotides (37–39). As the Picogreen Assay signal is a result of the presence of DNA and RNA interference, the addition of Benzonase should result in a very large decrease in the observed DNA concentration. If a large decrease in signal is not observed, this would be indicative that Benzonase activity is being decreased. Our hypothesis is that if signal does not largely decrease, it is because Benzonase is unable to access the DNA and RNA. Interactions the nucleic acids have with matrix interferants could be inadvertently blocking it from interacting with Benzonase. Benzonase has very robust activity and is widely used in the pharmaceutical industry; activity would not be compromised by the pH, ionic strength, or temperature of this system (32).
Analysis of the drug substance was performed in triplicate using this Picogreen-based assay. The resulting DNA concentration was 2720 ± 82 ng/mL (Fig. 2). A pre-treatment with 25 U of Benzonase was applied to the same sample, and the resulting concentration was 1460 ± 97 ng/mL, a decrease of only 48%. The decrease in concentration was substantially less than expected, indicating that the DNA and RNA in the system were shielded from digestion by Benzonase. To disrupt potential interactions, overcome shielding, and allow the enveloped nucleic acids to be more susceptible to digestion, DOC was selected as a pre-treatment for the drug substance because of its ability to break up interactions and viral envelopes (31). DOC has demonstrated success in disrupting lipids, improving the accessibility of hydrophobic proteins to digestion, as well as increasing the activity of the protease trypsin (40, 41). Applying a pre-treatment buffer containing DOC therefore could disrupt shielding interactions and increase the activity of Benzonase and Proteinase K in the diluent as well.Fig. 2 Benzonase treatments reveal inaccessibility of DNA/RNA in matrix. The LVV drug substance was treated with 25U of Benzonase which resulted in only a 48% decrease in apparent DNA concentration. In order to disrupt the sample matrix interactions and viral components, a pre-treatment with 0.4% deoxycholate (DOC) was applied. In pre-treatments containing 0.4% DOC, Benzonase digestion now led to a 90% decrease in DNA and RNA content. Reported values are the mean of triplicate measures and the standard deviation is represented by error bars
The addition of 0.4% DOC to the drug substance was evaluated in the Picogreen-based method. The resulting apparent DNA concentration was 3460 ± 185 ng/mL (Fig. 2). An increase of the apparent DNA concentration was observed, indicating that a portion of the nucleotides was previously being shielded from interacting with the Picogreen reagent. The drug substance was then pre-treated with a solution containing 25 U of Benzonase and 0.4% DOC, and the resulting apparent DNA concentration was 323 ± 9 ng/mL. This 90% decrease indicates that DOC was largely successful in breaking up matrix interactions and viral components to make the DNA and RNA more accessible and increasing the Benzonase activity. The positive shift of the DOC is also reflected in this measurement, as the resulting measurement is non-zero, and as such, a matrix matching of all reagents can further assist in platform, robust analysis. These results confirm that the biopharmaceutical drug substance benefits from the presence of a surfactant, such as DOC, to break up matrix interactions and fully expose DNA and process impurities.
RNase A Selectively Removes RNA Interferences
The addition of deoxycholate to the LVV drug substance allowed for full accessibility of the host cell DNA and genomic RNA in the sample matrix for subsequent Benzonase digestion. To quantify solely the host cell DNA, next RNA needed to be selectively removed (21, 22), and given the success of the Benzonase treatments, an enzymatic digestion was performed. Enzymatic pre-treatments have the benefit of high specificity to their substrate as well as low costs (42). Additionally, all enzymes added as a pre-treatment will eventually themselves be digested by Proteinase K in the designed platform assay, removing any potential interference they may cause. RNase A was selected as the most specific means to digest RNA in the sample (43).
Several controls were evaluated to ensure RNA could be removed as an interferant and allow for selective quantitation of DNA in the Picogreen-based assay (Table II). A control of calf thymus DNA was quantified using the Picogreen-based assay, and the resulting mean DNA concentration of triplicate measurements was 89 ± 4 ng/mL. A control of 500 ng of RNA resulted in a measurement of 459 ± 26 ng/mL, and the large positive shift was noted, confirming RNA is a strong interferant. The linearity of the RNA response was not explored, as the intention was to only determine the signal interference and not quantify RNA in this assay. The DNA control was then treated with 5 µg/mL of RNase A. The resulting DNA quantification was 88 ± 3 ng/mL, a recovery of 99% of the control DNA. As we observed full recovery of the control DNA, this serves as confirmation that RNase A at this concentration will not non-specifically digest DNA, a challenge that has been noted in the literature at high concentrations of RNase A (44). In addition, the negligible differences between the DNA control with and without the presence of RNase A further confirm RNase A is not itself causing any interference, as the Proteinase K in the assay diluent is able to eliminate all potential protein interference. When evaluating 500 ng of RNA in the presence of RNase A, robust digestion of the RNA is noted, with signals nearing the limit of quantitation. A baseline of the total interferences proposed to arise in the system was evaluated by measuring the DNA concentration of the control DNA, 500 ng RNA, and 0.4% DOC. The resulting DNA quantification was determined to be 516 ± 16 ng/mL. The percent recovery of the control DNA was 580%, indicating the severity of the interferences from RNA and DOC. Next, a control containing DNA and RNA with an RNase A pre-treatment was evaluated. The resulting DNA concentration was determined to be 97 ± 6 ng/mL, a percent recover of 109%, suggesting that the RNA interference was greatly diminished, but the RNA was not fully digested. Lastly, the ability for RNase A to function in the presence of DOC was evaluated, as DOC is a critical component of our proposed method’s pre-treatment process for complex biological samples. The control confirms that RNase A is still active in the presence of DOC as the resulting DNA concentration was determined to be 101 ± 4 ng/mL DNA, a recovery of 113% of the control DNA.Table II RNase A Selectively Degrades RNA and Is Unaffected by DOC. A Control Study Was Evaluated to Determine the Specificity of the Picogreen-Based DNA Quantitation Assay After Pre-treatment with RNase A. A Control of DNA Was Evaluated with and without the Presence of RNA. RNA Led to a Large Interference That Was Removed in Conditions with RNase A. RNase A Remained Effective in the Presence of DOC. Reported Values Are the Mean of Triplicate Values Unless Otherwise Indicated
Sample description Mean DNA concentration (ng/ml) Standard deviation (ng/mL) Recovery of DNA (%)
DNA control 89 4 100
500 ng RNA 459 26 -
0.4% DOC 23 N/A* -
DNA; 5 µg/mL RNase A 88 3 99
500 ng RNA; 5 µg/mL RNase A 3.8 N/A* -
DNA; 500 ng RNA; 5 µg/mL RNase A 97 6 109
DNA; 500 ng RNA; 0.4% DOC 516 16 580
DNA; 500 ng RNA; 5 µg/mL RNase A; 0.4% DOC 101 4 113
*Further dilutions resulted in quantitation below LOD; one replicate performed
With established controls in place, a sample of the same LVV drug substance used in the previous studies described herein (Fig. 2) was applied again to the Picogreen-based platform assay. The resulting DNA concentration, reported as the mean of three replicates, was 2650 ± 56 ng/mL (Table III). The resulting DNA quantification confirms the high precision of the assay with a %RSD of 2% across the two replicate runs. The sample was again subjected to pre-treatment with 0.4% DOC, resulting in a DNA concentration of 3130 ± 185 ng/mL. The increase of 18% in DNA concentration again suggesting that the host cell DNA is now fully exposed. An increase of this magnitude is well above the observed variability of the assay and is thus considered significant. A concentration of 5 µg/mL of RNase A was incorporated into a pre-treatment with the drug substance, and a significant decrease in DNA concentration was noted to a value of 848 ± 49 ng/mL. This finding suggests that RNA was indeed causing interference and RNase A is successfully able to overcome this interference. Finally, the sample was pre-treated with a mixture of 0.4% DOC and 5 µg/mL RNase A. The pre-treatment was successful in digesting a larger portion of RNA, thus indicating that a portion of RNA was inaccessible to RNase A. This also suggests that the concentration of DOC selected was sufficient for disrupting the viral components as previous precent indicating that only 500 µg/mL was necessary to disrupt influenza-A virus (31). The final DNA concentration was reported as 535 ± 20 ng/mL, a decrease of 80% of the initial untreated condition. In order to fully elaborate on the criticality of DOC in providing the most accurate result, a t-test was performed comparing the resulting DNA concentration for “drug substance; 5 µg/mL RNase A” and “drug substance; 0.4% deoxycholate; 5 µg/mL RNase A.” The resulting p value was 0.001, well below 0.05, indicating the statistical significance of DOC in increasing the efficiency of RNase A in our treatments. Through a combination of disrupting matrix interactions and digesting RNA interferences, the Picogreen-based platform method is now applicable to complex biological samples. The studies presented in this work demonstrate that RNase A selectively removes RNA as an interferant in complex biological samples and that DOC continues to provide a means of disrupting matrix interactions.Table III RNase A Treatment Removes RNA Interference. The Function of RNase A in the Complex LVV Drug Substance Sample Matrix Was Evaluated. RNase A Digestion Led to a Decrease in the Interference of RNA and the Addition of Deoxycholate Enhanced the RNA Digestion. The Reported Mean DNA Concentration Is the Result of Triplicate Measurements
Sample description Mean DNA concentration (ng/mL) Standard deviation (ng/mL) Comparison to untreated (%)
Untreated drug substance 2650 56 100
Drug substance; 0.4% deoxycholate 3130 185 118
Drug substance; 5 µg/mL RNase A 848 49 31
Drug substance; 0.4% deoxycholate; 5 µg/mL RNase A 554 20 20
Deoxycholate Optimization Achieves Disruption of Interactions in the Matrix and Viral Components While Maintaining the Lowest Possible Concentration to be Amenable to Liquid Handling
DOC was found to be a critical reagent in disrupting interactions within a complex biopharmaceutical sample. However, DOC was also found to produce a small positive shift in the assay (Table II). An evaluation of potential DOC concentrations was conducted to identify the lowest DOC concentration that still provides matrix disruptions, to decrease any potential effects of the observed DOC-based positive shift. The host cell DNA was quantified in the LVV drug substance against concentrations of DOC ranging from 0.4 to 0.0125% with 5 µg/mL of RNase A also present (Fig. 3). The critical micelle concentration (CMC) of DOC varies from 2 to 6 mM (0.08 to 0.25% w/v) depending on the ionic strength of the solution; therefore, the full range of the CMC was evaluated as well as points above and below the range.Fig. 3 Optimization of deoxycholate (DOC) concentrations in pre-treatment conditions. Varied concentrations of DOC were evaluated for their ability to disrupt interactions within the LVV drug substance matrix and allow for interferences, such as RNA, to be fully exposed to digestion via RNase A. The selected concentrations range from 0.0125 to 0.4%. The lowest apparent DNA concentration was noted at 0.2% DOC. Reported values are the mean of triplicate measures and the standard deviation is represented by error bars
At lower concentrations of DOC, a positive shift in the apparent DNA concentration was noted. Our findings suggest that at low concentrations of DOC, full disruption of the matrix interactions does not occur. The genomic RNA is not fully exposed to digestion and is likely leading to the increased apparent DNA concentration. As the concentration of DOC increases, the apparent DNA quantification decreases again indicating that a minimal level of DOC is required to fully expose interferent RNA. A plateau of the DNA concentration readout begins occurring from 0.1 to 0.4% DOC, until there is an observed percent difference of 1.2% between DOC concentrations of 0.2 and 0.4%. As the expected CMC concentration has a maximum value of 0.25%, the combination of the small percent difference and this known value drew the conclusion that we had accomplished reaching the CMC. As such, further increases to the DOC concentration would provide no benefit or further disruption to the matrix and virus components.
Selecting the lowest DOC concentration is advantageous to minimize interference and be more amenable to the automated instrumentation, so 0.2% DOC was determined to be the optimal concentration. The final selected concentration of DOC was also at the high end of the proposed concentration to achieve CMC. This allows the flexibility in this platform method to assess a range of ionic strengths in the sample buffers. For samples with extraordinarily high ionic strengths like the elution from ion exchange chromatography, the samples can be greatly diluted and still fall within the linear range of the technique to ensure varying ionic strengths do not interfere with the function of DOC.
The final optimal conditions for pre-treatment of the drug substance were selected as 0.2% DOC and 5 µg/L RNase A. In order to fully account for all matrix interferences of the pre-treatment buffer, equal proportions of DOC and RNase A were added to the DNA standard and assay diluent in the Picogreen-based platform method. A summary of the entirety of the proposed analytical method, including pre-treatment, dilution, and analysis, is displayed (Fig. 4).Fig. 4 Summary of the proposed analytical method, including pre-treatment, dilution, and Picogreen-based analysis, in which elimination of common biopharmaceutical interferences was accomplished. During the first phase of the method, the samples are pre-treated with RNase A and deoxycholate (DOC). This eliminates RNA contaminants and minimizes interactions within the sample. In the second phase, the samples are diluted into the linear range of the assay. The dilution buffer contains Proteinase K to eliminate the RNase A and any residual host cell proteins. Finally, in the last phase, DNA is the only species left to interact with the Picogreen dye. Background fluorescence of DOC is eliminated by keeping its concentration constant in all buffers, reagents, and reference material
The final optimized method, including pre-treatments and matrix-matched reagents, was applied to an upstream, complex sample of the biopharmaceutical drug substance for a final evaluation with a spiking recovery study (Table IV). The sample was specifically chosen as a rigorous test for the proposed method, in which the upstream, complex biopharmaceutical sample represents a historically difficult-to-analyze scenario. A successful recovery was noted ranging from 78 to 83% in various spiking amounts. These values align well with reported spike recoveries for host cell DNA in live-attenuated vaccines drug substance, which are far less complex matrices. Reported values for rabies, dengue, and inactivated poliovirus vaccine have spike recoveries that range from 77 to 128% using a highly specific qPCR methodology (9). This demonstrates both the precision and the robustness of this assay to be applied to not only purified drug substance, but also in-process, unpurified, or upstream samples — enabling rapid process and formulation development efforts across biologic and vaccine production. Furthermore, all samples, from early-stage purification through to the final drug substance, demonstrated improved accuracy, specificity, and precision of the reported DNA concentration after the applied pre-treatment method outlined herein was adopted. This method thus provides a direct means of quantifying host cell DNA in complex biopharmaceutical in a straightforward, high-throughput manner.Table IV Results of Spike Recovery Studies Using Upstream LVV Sample. The DNA Spike Solution Had a Concentration of 30 ng/mL and the Drug Substance Sample Used Had an Initial Concentration of 58 ng/mL. Measured DNA Concentration (mg/mL) Is the Mean Value of Triplicate Measurements, and the Expected DNA Concentration Is Based Upon the Concentration of the Amount of Spiking Solution Used
Sample description Expected DNA concentration (ng/mL) Measured DNA concentration (ng/mL) Spike recovery (%)
Low DNA spike in sample 87 69 80
Medium DNA spike in sample 132 103 78
High DNA spike in sample 207 173 83
Conclusions
A novel method was developed to provide an efficient, high-throughput assay for host cell DNA quantitation in complex biopharmaceuticals. This work was able to overcome common, pharmaceutically relevant interferences, such as protein, RNA, and detergent, with a Picogreen fluorescence-based approach. RNA was determined to be an interferent that produced a large positive increase in the apparent DNA concentration. Through a strategically designed method, RNase A was able to digest the RNA and then itself be digested by Proteinase K to remove residual protein interferences. Additionally, deoxycholate (DOC) was shown to have a profound effect on disrupting matrix interactions and allowing for full removal of the RNA interference through disruption of the viral components. Matrix-matching efforts in the reference material and assay diluent allow for the interference of this detergent to be easily overcome, as well. This robust design allows for rapid analysis of diverse, complex samples to accelerate process development of biopharmaceuticals. This methodology is the first, fluorescence-based host cell DNA quantification that is appliable to vaccines with high concentrations of RNA like the mRNA vaccines as well as biologics and vaccines from all cell substrates. In a time of accelerated needs for the development of biologics and vaccines, the method outlined herein is readily automated and can help accelerate research and development efforts with low costs and high output.
Acknowledgements
The authors would like to thank Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA, for providing funding for this work. The authors would like to thank Brittany Paporello, Daisy Richardson, and Caroline McGregor for helpful discussion. The authors would also like to thank Andrew Swartz, Emily Berckman, Justin Ma, and Adam Kristopeit for providing sample retains of the live virus vaccine drug substance.
Author Contribution
Mackenzie L. Lauro: conceptualization, investigation, methodology, formal analysis, data curation, visualization, writing, supervision. Amy M. Bowman: methodology, investigation, data curation, writing. Joseph P. Smith: methodology, investigation, writing, visualization. Susannah N. Gaye: investigation, data curation, writing. Jillian Acevedo-Skrip: investigation, data curation, writing. Pete A. Phillips: methodology, supervision. John W. Loughney: methodology, supervision.
Declarations
Conflict of Interest
The authors declare no competing interests.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36482268 | PMC9735023 | NO-CC CODE | 2022-12-14 23:28:32 | no | AAPS J. 2022 Dec 8; 25(1):10 | utf-8 | AAPS J | 2,022 | 10.1208/s12248-022-00764-4 | oa_other |
==== Front
J Thromb Thrombolysis
J Thromb Thrombolysis
Journal of Thrombosis and Thrombolysis
0929-5305
1573-742X
Springer US New York
36480147
2737
10.1007/s11239-022-02737-y
Article
Effects of intravenous lysine acetylsalicylate versus oral aspirin on platelet responsiveness in patients with ST-segment elevation myocardial infarction: the ECCLIPSE-STEMI trial
Vivas David [email protected]
1
Jiménez José Julio 2
Martín-Asenjo Roberto 3
Bernardo Esther 1
Ortega-Pozzi María Aranzazu 1
Gómez-Polo Juan Carlos 1
Moreno Guillermo 3
Vilacosta Isidre 1
Pérez-Villacastín Julián 1
Fernández-Ortiz Antonio 1
1 grid.411068.a 0000 0001 0671 5785 Cardiovascular Institute, San Carlos University Hospital, Profesor Martin Lagos S/N. 28040, Madrid, Spain
2 SUMMA 112 Emergency Medical Service, Madrid, Spain
3 grid.144756.5 0000 0001 1945 5329 Cardiology Unit, 12 Octubre University Hospital, Madrid, Spain
8 12 2022
18
20 11 2022
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This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Prasugrel and ticagrelor, new P2Y12-ADP receptor antagonists, are associated with greater pharmacodynamic inhibition and reduction of cardiovascular events in patients with an acute coronary syndrome. However, evidence is lacked about the effects of achieving faster and stronger cyclooxygenase inhibition with intravenous lysine acetylsalicylate (LA) compared to oral aspirin. Recently, we demonstrated in healthy volunteers that the administration of intravenous LA resulted in a significantly reduction of platelet reactivity compared to oral aspirin. Loading dose of LA achieves platelet inhibition faster, and with less variability than aspirin. However, there are no data of this issue in patients with an ST-segment elevation myocardial infarction (STEMI). This is a prospective, randomized, multicenter, open platelet function study conducted in STEMI patients. Subjects were randomly assigned to receive a loading dose (LD) of intravenous LA 450 mg plus oral ticagrelor 180 mg, or LD of aspirin 300 mg plus ticagrelor 180 mg orally. Platelet function was evaluated at baseline, 30 min, 1 h, 4 h and 24 h using multiple electrode aggregometry and vasodilator-stimulated phosphoprotein phosphorylation (VASP). The primary endpoint of the study is the inhibition of platelet aggregation (IPA) after arachidonic acid (AA) 0.5 mM at 30 min. Secondary endpoints were the IPA at 1, 4, and 24 h after AA, and non-AA pathways through the sequence (ADP and TRAP). A total of 32 STEMI patients were randomized (16 LA, 16 aspirin). The inhibition of platelet aggregation after AA 0.5 mM at 30 min was greater in subjects treated with LA compared with aspirin: 166 vs. 412 respectively (p = 0.001). This differential effect was observed at 1 h (p = 0.01), but not at 4 and 24 h. Subjects treated with LA presented less variability and faster inhibition of platelet aggregation wit AA compared with aspirin. The administration of intravenous LA resulted in a significantly reduction of platelet reactivity compared to oral aspirin on ticagrelor inhibited platelets in patients with STEMI. Loading dose of LA achieves an earlier platelet inhibition, and with less variability than aspirin.
Trial Registration: Unique identifier: NCT02929888; URL: http://www.clinicaltrials.gov
Keywords
Platelets
Lysine acetylsalicylate
Aspirin
Acute coronary syndrome
http://dx.doi.org/10.13039/501100004587 Instituto de Salud Carlos III PI16/00191 Vivas David
==== Body
pmcHighlights
Antiplatelet therapy plays a key role in patients with ST-segment elevation myocardial infarction (STEMI)
Although potent P2Y12-ADP receptor inhibitor-drugs have shown a reduction in cardiovascular outcomes in this scenario, evidence is lacked about achieving faster cyclooxygenase inhibition
The results of our study suggest that, compared with oral aspirin, intravenous lysine acetylsalycilate significantly achieved an earlier platelet inhibition in STEMI patients, with less variability
Larger studies are warranted to assess whether this strategy could decrease cardiovascular ischemic events in this scenario
Introduction
In patients with an acute coronary syndrome (ACS), platelets play a key role, particularly in the early phases of the disease [1, 2]. Activated platelets release thromboxane A2 (TXA2), adenosine diphosphate (ADP) and adenosine triphosphate (ATP), stimulating platelet activation and aggregation processes [3]. Thus, antiplatelet therapy is the cornerstone of treatment for patients with coronary artery disease [4]. Currently, the combination of aspirin, an irreversible inhibitor of cyclooxygenase (COX) and a P2Y12-ADP receptor inhibitor, is the antiplatelet treatment of choice in patients with ACS, where a fast and strong platelet inhibition is needed [5, 6]. Although prasugrel and ticagrelor have shown a better profile than clopidogrel by reducing cardiovascular outcomes in patients with ACS [7–11], evidence is lacked about achieving faster and stronger COX inhibition. In fact, current guidelines of management of ACS only recommend loading dose of oral non-enteric-coated aspirin (162–325 mg), and intravenous use only when oral ingestion is not possible [5, 6].
Lysine acetylsalicylate (LA) is a soluble salt that, shortly after being administered, is converted into acetylsalicylic acid, which is metabolized in the liver to salicylic acid (active form) [12, 13]. LA presents potent antiplatelet compound with fewer gastrointestinal adverse effects than aspirin and has the unique property of being able to be administered both orally and intravenous [14]. Some studies have compared aspirin with LA in both, healthy volunteers and patients with stable coronary artery disease, and showed similar or higher effectiveness on platelet inhibition with LA [15, 16]. Recently, it has demonstrated that the administration of intravenous LA resulted in a significantly reduction of platelet reactivity compared with aspirin orally in healthy volunteers; moreover, LA achieves faster platelet inhibition, and with less intra- and interindividual variability than aspirin [17]. However, there is no data about this finding in the setting of ST-segment elevation acute myocardial infarction (STEMI) patients, where early platelet inhibition could be associated with a reduction in cardiovascular events [18–20].
Therefore, the present study aims to analyze the effects of combined administration of intravenous LA versus aspirin orally on platelet aggregation, and to assess whether the administration of these different drug regimens affect the time to onset of platelet inhibition.
Methods
Patient population
The ECCLIPSE-STEMI (“Impact of intravenous Lysine Acetylsalicylate versus oral Aspirin on in Patients with ST-segment Elevation Myocardial Infarction”, www.controlled-trials.com number NCT02929888) trial was a prospective, randomized, multicenter, open, pharmacodynamic platelet function study in patients with an acute myocardial infarction. Patients were enrolled if they were ≥ 18 years-old and were admitted with a diagnosis of STEMI by the emergency units, defined by an episode of chest pain or equivalent symptoms, associated to ECG typical disorder (persistent elevation of ST-segment ≥ 1 mm in frontal leads, or ≥ 2 mm in precordial leads in at least 2 adjoining leads; or new onset left bundle branch block). Exclusion criteria included: known allergies to aspirin, clopidogrel, prasugrel or ticagrelor, cardiogenic shock or hemodynamic instability, recent antiplatelet therapy (< 14 days), including nonsteroidal anti-inflammatory drugs (NSAIDs.), oral anticoagulation, any active bleeding or blood dyscrasia, recent gastrointestinal bleeding (< 6 months prior to inclusion), recent history of stroke or intracranial bleeding (< 6 months prior to inclusion), known anemia, thrombopenia or severe chronic kidney/liver disease, any known active neoplasm, or pregnant females. The study complied with the Declaration of Helsinki and it was approved by the Ethical Committee of the San Carlos University Hospital [21]. All patients gave their written informed consent to participate in the study. A clinical research organization (CRO) was contracted to hold the data and perform the data analysis after data lock. An independent data safety monitoring committee was instituted for adjudication of adverse clinical events.
Study design and randomization
Patients were randomly allocated in a 1:1 fashion to receive 450 mg intravenous LA or 300 mg of oral aspirin (non-enteric coated formulation). Both groups will receive routine care in the setting of the STEMI clinical practice guidelines, including concomitant administration of a potent P2Y12 ADP-receptor inhibitor: ticagrelor (this drug was selected because it is the P2Y12 ADP-receptor inhibitor available in our emergency care setting). Blood samples will be extracted at baseline (before the administration of antithrombotic drugs), at 30 min, 1, 4, and at 24 h so as to measure platelet function. All subjects underwent standard cardiology care including, unless contraindicated, primary percutaneous coronary intervention (PCI). Use of glycoprotein (GP) IIb/IIIa inhibitors and choice of anticoagulant were left to the criteria of the treating physician. Concomitant treatments, such as beta-blockers, angiotensin-converting enzyme -inhibitors and statins were used according to current clinical guidelines [5, 6]. The ECCLIPSE-STEMI trial started including patients in June 2017, and recruitment were extended until December 2020 due to COVID-19 pandemic situation.
Platelet function testing
Blood samples were collected from an antecubital vein using a 21-gauge needle into 5 ml plastic tubes containing hirudin (25μg/mL) after randomization and each of the previously specified set time points. First 3 ml of blood were discharged to avoid spontaneous platelet activation. All samples were processed within 1 h by researchers that were blinded to the treatment assigned.
Platelet aggregation
Platelet aggregation were assessed using multiple electrode aggregometry (MEA), in whole blood with the Multiplate™ analyzer (Roche Diagnostics, Basel, Switzerland) as previously described [22]. This instrument assesses the change in impedance caused by the adhesion of platelets onto sensor units formed by silver-covered electrodes. Curves were recorded for 6 min, and platelet aggregation was determined as area under the curve of arbitrary aggregation units (AU*min). In the present investigation, 0.5 mM arachidonic acid (AA) were used to evaluate COX inhibition, 6.4 μM ADP was used as agonist to evaluate P2Y12 inhibitors responsiveness, and thrombin receptor-activated peptide (TRAP) 32 μM were used to stimulate thrombin-dependent platelet aggregation. Inhibition of platelet aggregation (IPA) was defined as the relative percent decrease in maximal aggregation and was calculated as [(baseline aggregation response—aggregation at the different timepoints of the study)/baseline aggregation response] × 100.
Platelet P2Y12 reactivity index (PRI)
The PRI was determined through assessment of vasodilator stimulated phosphoprotein (VASP) phosphorylation according to standard protocols [23]. In brief, VASP phosphorylation was measured by quantitative flow cytometry (Gallios cytometer Beckman Coulter, Miami, Florida) using commercially available labeled monoclonal antibodies (Biocytex Inc., Marseille, France). The PRI was calculated after measuring the mean fluorescence intensity (MFI) of VASP phosphorylation levels following challenge with prostaglandin E1 (PGE1) and prostaglandin E1 plus ADP. PGE1 increases VASP phosphorylation levels through stimulation of adenylate cyclase, while ADP binding to purinergic receptors leads to the inhibition of adenylate cyclase. Therefore, the addition of ADP to prostaglandin E1-stimulated platelets reduces levels of prostaglandin E1-induced VASP phosphorylation. PRI = [(MFI PGE1) − (MFI PGE1 + ADP)/(MFI PGE1)] × 100. Elevated PRI values are indicative of upregulation of the P2Y12 signaling pathway.
Endpoints and sample size
The primary endpoint of the study was the inhibition platelet aggregation (IPA) responses to AA stimuli 30 min after administration of study drugs. Secondary endpoints were the IPA at 1, 4 and 24 h after AA, and non-AA pathways through the sequence. Another secondary endpoints were the cardiovascular outcomes (death, reinfarction, stroke) and bleeding events during admission. To estimate the sample size, and according to previous pharmacodynamics studies, we hypothesized a 27% mean reduction in the primary endpoint following treatment with intravenous LA compared with oral aspirin [15–17]. Therefore, at least 60 subjects would be required to provide a 80% power to detect statistical differences between groups with a two-sided ∝ level of 0.05. Given that the effect size found was larger than initially considered for the primary objective, the contrast finally had sufficient power (more than 85%) to detect differences with an n = 16 size in each group.
Statistical analysis
Endpoints were analyzed for all recruited patients in an intention to treat analysis. Statistical analysis will be performed by an independent investigator, blinded to the study group assignment. Variables were analyzed for a normal distribution with the Kolmogorov–Smirnov test. Normally distributed variables are presented as mean ± standard deviation and were compared using the Student t test. Variables that did not follow a normal distribution are presented as median and interquartile range and were compared with the Mann–Whitney U test. Categorical variables are expressed as frequencies and percentages and were compared with the χ2 test or the Fisher exact test when at least 25% of values showed an expected cell frequency below 5. Confidence intervals (CI) and all test of statistical significance for treatment comparisons were evaluated at a two-tailed significance level of 0.05. All analyses of platelet function were conducted in all randomized subjects who received at least one dose of study drug. Statistical analysis was performed using SPSS/PC 17 (SPSS Inc. Chicago, Illinois).
Results
Patient population
A total of 32 patients with STEMI were randomized (16 in intravenous LA group and 16 in oral aspirin group). Baseline demographics, clinical characteristics, laboratory data and angiographic findings of both groups are shown in Table 1. There were no significant differences between groups. Table 2 shows in-hospital management and cardiovascular outcomes, and no differences were found between LA and aspirin group.Table 1 Baseline characteristics according to treatment group
Lysine acetylsalicylate Aspirin p-value
(n = 16) (n = 16)
Age (yrs), mean ± SD 64.2 ± 9.8 64.3 ± 8.9 NS
Male, n (%) 9 (56.3) 8 (50.0) NS
Risk factors, n (%)
Current smoking 7 (43.8) 6 (37.5) NS
Hypertension 6 (37.5) 6 (37.5) NS
Dyslipidemia 7 (43.8) 8 (50.0) NS
Known DM 2 (12.5) 3 (18.8) NS
Obesity (BMI > 30 kg/m2) 2 (12.5) 4 (25.0) NS
Medical history, n (%)
Previous stroke 1 (6.3) 0 (0.0) NS
Previous COPD 2 (12.5) 1 (6.3) NS
Chronic kidney disease 1 (6.3) 1 (6.3) NS
Clinical and angiographic characteristics, n (%)
Anterior STEMI 9 (56.3) 8 (50.0) NS
Killip class ≥ 2 2 (12.5) 1 (6.3) NS
Left ventricular ejection fraction (%), mean ± SD 53.7 ± 12.4 54.7 ± 12.9 NS
FMC to balloon (min), median (IQR) 91.5 (69.8–106.0) 86.0 (70.3–111.0) NS
Multivessel disease 6 (37.5) 7 (43.8) NS
Laboratory data
Hematocrit (%) 42.9 ± 3.1 42.5 ± 5.3 NS
Platelet count (1000/mm3) 257.4 ± 82.4 256.6 ± 63.78 NS
Creatinine clearance (mL/min)* 85.4 ± 14.2 84.5 ± 16.8 NS
HbA1c (%), median (SD) 5.5 (0.8) 5.6 (0.6) NS
LDL-c (mg/dL), median (SD) 118.0 ± 33.1 123.9 ± 25.5 NS
Peak troponin I (ng/mL), median(IQR) 74.9 (22.9–126.5) 77.9 (33.2–163.8) NS
BMI body mass index, COPD chronic obstructive pulmonary disease, DM diabetes mellitus, FMC first medical contact. HbA1c glycated haemoglobin. IQR interquartile range, LDL-c low density lipoprotein-cholesterol. SD standard deviation. STEMI ST elevation myocardial infarction. * assessed by de Crockcroft & Gault formula
Table 2 In-hospital management and adverse outcomes according to treatment group
Lysine acetylsalicylate Aspirin p-value
(n = 16) (n = 16)
Coronary revascularization procedures, n (%)
Primary PCI 15 (93.8) 14 (87.5) NS
CABG 0 (0.0) 1 (6.3) NS
No revascularization 1 (6.3) 1 (6.3) NS
Drug therapy during hospitalization, n (%)
GP IIb/IIIa inhibitors 2 (12.5) 3 (18.8) NS
Unfractioned heparin 14 (87.5) 13 (81.3) NS
Enoxaparin 2 (12.5) 3 (18.8) NS
Beta-blockers 16 (100.0) 15 (93.8) NS
ACE inhibitors/ARB 12 (75.0) 11 (68.8) NS
Statins 16 (100.0) 16 (100.0) NS
Adverse in-hospital outcomes, n (%)
Death 0 (0.0) 0 (0.0) N/A
Stent thrombosis 0 (0.0) 1 (6.3) NS
Ventricular arrhythmias 1 (6.3) 0 (0.0) NS
Cardiogenic shock 1 (6.3) 2 (12.5) NS
Complete AV block 1 (6.3) 1 (6.3) NS
Major bleeding 1 (6.3) 1 (6.3) NS
ACE angiotensin-converting enzyme, ARB angiotensin receptor blocker, AV auriculo-ventricular; CABG coronary artery bypass graft, GP glycoprotein, IQR interquartile range, NS non-significant, PCI percutaneous coronary intervention
Platelet function profiles
There were no differences in platelet function at baseline between intravenous LA plus ticagrelor and oral aspirin plus ticagrelor groups with all platelet function test assessed (Table 3). Platelet reactivity at 30 min after AA 0.5 mM was significantly lower in patients treated with intravenous LA compared with oral aspirin: 166.0 (64.5–247.0) vs. 412.0 (241.0–589.0), p = 0.001. These results were observed at 1 h [148.0 (86.0–188.5) vs. 221.0 (170.0–311.0), p = 0.013], but not at 4 h and 24 h. Figure 1 shows IPA with AA 0.5 mM at any time points.Table 3 Platelet function profiles according to treatment assigned
Lysine acetylsalicylate Aspirin p-value
(n = 16) (n = 16)
AA 0.5 mM (%)
Baseline PR 635.0 (334.0–10.009.0) 574.0 (390.0–805.0) 0.802
30 min PR 166.0 (64.5–247.0) 412.0 (241.0–589.0) 0.001
1 h PR 148.0 (86.0–188.5) 221.0 (170.0–311.0) 0.013
4 h PR 124.0 (23.0–129.0) 81.5 (60.0–93.0) 0.774
24 h PR 107.0 (46.0–180.0) 147.5 (92.0–211.0) 0.228
ADP 6.4 μM (%)
Baseline PR 351.5 (221.5–683.0) 507.0 (313.0–700.0) 0.464
30 min PR 313.0 (214.0–499.0) 419.0 (290.5–598.0) 0.609
1 h PR 232.5 (166.5–452.5) 351 (188.0–478.0) 0.407
4 h PR 154.0 (122.3–255.0) 127.5 (114.0–204.0) 0.391
24 h PR 152.0 (93.0–213.0) 137.5 (89.0–191.0) 0.827
TRAP 32 μM (%)
Baseline PR 678.0 (387.5–904.0) 805.0 (651.0–947.0) 0.272
30 min PR 617.0 (481.0–758.0) 874 (819.0–1023.0) 0.057
1 h PR 826.0 (598.0–964.5) 729.0 (568.0–961.0) 0.733
4 h PR 462.0 (266.0–731.0) 630.5 (435.0–727.0) 0.568
24 h PR 520.0 (320.5–797.0) 561.5 (303.0–710.0) 0.820
PRI (%)
Baseline 71.8 (48.8–76.8) 71.9 (56.1–80.7) 0.864
30 min 55.8 (46.8–80.9) 67.8 (55.1–82.4) 0.492
1 h 23.0 (14.6–82.1) 39.4 (6.4–88.2) 0.868
4 h 22.4 (10.6–29.8) 17.3 (6.5–30.5) 0.423
24 h 14.4 (1.36–34.8) 13.8 (4.1–25.4) 0.843
Values are median (interquartile range). AA arachidonic acid. ADP adenosin diphosphate. IPA inhibition of platelet aggregation. TRAP thrombin receptor-activated peptide. PR platelet reactivity. PRI platelet P2Y12 reactivity index
Fig. 1 Mean inhibition of platelet aggregation (IPA) responses to Arachidonic Acid (AA) 0.5 mM at timeline 0 (baseline), 30 min, 1 h, 4 h, and 24 h after Lysine Acetylsalicylate 450 mg iv (n = 16), or Aspirin 300 mg orally (n = 16)
Platelet function profiles according to P2Y12-dependent pathway and thrombin-dependent platelet aggregation were tested with ADP 6.4 μM and TRAP 32 μM respectively. There were no differences between intravenous LA and oral aspirin groups at any time points (p = NS). These results were similar when exploring platelet activation with PRI.
Figure 2 shows individual subject antiplatelet response after AA 0.5 mM at baseline, 30 min, 1, 4 and 24 h. Subjects treated with LA presented less variability and faster decrease in platelet inhibition compared with aspirin group.Fig. 2 Individual subject inhibition of platelet aggregation (IPA) responses to Arachidonic Acid (AA) 0.5 mM stimuli at baseline, 30 min, 1 h, 4 h and 24 h after Lysine Acetylsalicylate 450 mg iv (upper panel), or Aspirin 300 mg orally (lower panel)
Discussion
Antiplatelet therapy plays a pivotal role in the management of STEMI patients. Current practical guidelines recommend in these patients the combination of aspirin and a P2Y12 inhibitor (preferably prasugrel/ticagrelor than clopidogrel, if no contraindicated) [6]. Specifically, and according to these recommendations, aspirin should be given orally including chewing, or intravenous (if oral ingestion is not possible) to ensure complete inhibition of thromboxane A2-dependent platelet aggregation. However, it is unclear whether the administration of intravenous antiplatelet in this scenario leads to a better prognosis [24]. This is the first randomized trial to analyze the pharmacodynamic effects of intravenous LA compared to aspirin orally in patients with STEMI. In particular, the results of the study show that intravenous LA was associated with higher platelet inhibition than oral aspirin group. Further, the administration of intravenous LA resulted in a rapid and marked reduction on platelet reactivity by 30 min compared to oral aspirin. Finally, LA achieved a more consistent platelet inhibition and less inter- and intraindividual variability.
Interestingly, the results of our study were consistent with previous report in healthy volunteers [17]. Thus, the STEMI scenario is associated with a prothrombotic and inflammation state, and an early platelet inhibition reveals as a key role in the treatment of acute coronary disease. Despite of this unfavorable situation, patients treated with intravenous LA showed faster platelet inhibition. Due to a lower sample size, the study was not designed to detect differences in cardiovascular outcomes, and more studies are needed to know whether a faster platelet inhibition in STEMI patients could be associated with a reduction in cardiovascular events [18–20].
It has been hypothesized that LA not only reduces platelet reactivity when COX pathway was assessed, but also showed and early and faster reduction with other platelet inhibition receptors [17]. Although in healthy volunteers intravenous LA compared with oral aspirin showed a significant reduction in thrombin-dependent platelet pathway aggregation, the ECCLIPSE-STEMI trial did not find significant differences in any stage of the analysis.
Current investigation concentrates on the field of P2Y12-ADP platelet receptor inhibition. Prasugrel and ticagrelor are characterized by more prompt, potent and predictable antiplatelet effects and greater clinical efficacy than clopidogrel [10, 11]. However, these drugs also present limitations, including a delayed antiplatelet effect, particularly in the setting of STEMI. In the ECCLIPSE-STEMI trial, all patients were treated with loading dose of ticagrelor 180 mg, and differences in platelet reactivity were shown despite a faster ADP-P2Y12 inhibition. Therefore, these findings show that, despite of a high ticagrelor platelet inhibition, intravenous LA could reduce platelet reactivity faster than aspirin, which could have clinical implications.
Other intravenous antiplatelet agents have been assessed in the setting of the ACS, such as Glycoprotein IIb/IIIa inhibitors or cangrelor [25–27]. However, current STEMI clinical guidelines did not recommend the routine use of these drugs, and only cangrelor could be considered in patients not pre-treated with oral P2Y12 inhibitors at the time of primary percutaneous coronary intervention [6]. In the ECCLIPSE-STEMI trial, only 5 patients (2 in LA and 3 in aspirin group) received downstream intravenous abciximab, none of them in the first 60 min after study drug administration. The effect of Glycoprotein IIb/IIIa inhibitor in these patients did not affect platelet function test at 30 and 60 min, although we could not dismiss some biases in the rest of study timepoints.
This study has some limitations. First, the trial enrolled patients with STEMI, and this fact may limit the generalization to clinical patient population with another cardiovascular disease. Second, the relation between clinical outcomes and the speed of onset and magnitude of platelet inhibition with LA is unknown. Moreover, this study has a small sample size (eventually less patients than those initially planned) and the final results should be considered carefully. Finally, the present study was not designed to evaluate maintenance doses. However, protocol design and statistical analyses reinforced the value of the results obtained, which suggested a pharmacodynamic benefit of intravenous LA compared with oral aspirin.
Conclusions
The administration of intravenous LA resulted in a significantly reduction of platelet reactivity compared to oral aspirin on ticagrelor inhibited platelets in patients with STEMI. Loading dose of LA achieves an earlier platelet inhibition, and with less variability than aspirin.
Funding
This study was supported by the CTU-SCReN (Clinical Trial Unit—Spanish Clinical Research Network) from San Carlos University Hospital (Madrid, Spain), financed by the ISCII (Project PI16/00191). Principal Investigator: David Vivas, MD, PhD.
Data Availability
The data that support the findings of this study are available on request from the corresponding author, on reasonable request.
Declarations
Conflict of interest
The authors declare that there is no conflict of interest in this manuscript.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36480147 | PMC9735024 | NO-CC CODE | 2022-12-14 23:28:32 | no | J Thromb Thrombolysis. 2022 Dec 8;:1-8 | utf-8 | J Thromb Thrombolysis | 2,022 | 10.1007/s11239-022-02737-y | oa_other |
==== Front
Nat Rev Gastroenterol Hepatol
Nat Rev Gastroenterol Hepatol
Nature Reviews. Gastroenterology & Hepatology
1759-5045
1759-5053
Nature Publishing Group UK London
36481812
716
10.1038/s41575-022-00716-5
Perspective
Environmental effects of surgical procedures and strategies for sustainable surgery
http://orcid.org/0000-0002-7353-2425
Cunha Miguel F. [email protected]
12
http://orcid.org/0000-0002-8322-6421
Pellino Gianluca [email protected]
34
1 grid.7157.4 0000 0000 9693 350X Colorectal Surgery group - General Surgery Department, Algarve University Centre, Portimão, Portugal
2 Algarve Biomedical Centre, Portimão, Portugal
3 grid.9841.4 0000 0001 2200 8888 Department of Advanced Medical and Surgical Sciences, Universitá degli Studi della Campania ‘Luigi Vanvitelli’, Naples, Italy
4 grid.411083.f 0000 0001 0675 8654 Colorectal Surgery, Vall d’Hebron University Hospital, Barcelona, Spain
8 12 2022
112
17 11 2022
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This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
There is a bidirectional relationship between climate change and health care. Climate change threatens public health, and health care contributes to climate change. For example, surgery is the most energy-intensive practice in the health-care sector, and gastrointestinal conditions are responsible for a substantial environmental burden. However, environmental costs associated with health care are often overlooked. This issue has been examined more closely in current times. Emerging data are mainly focused on surgery, as the most resource-intensive practice. However, there is still a lack of global awareness and guidance on sustainable surgical practices. This Perspective aims to reassess the evidence on health care and surgery carbon footprints, focusing on gastrointestinal conditions, identify issues that need to be addressed to achieve a more sustainable practice and develop perspectives for future surgical procedures. The proposed framework to mitigate the environmental effects of surgery could be translated to other health-care sectors.
Health care contributes to the climate change burden, and measures should be taken to mitigate these effects. This Perspective discusses the carbon footprint of surgery in gastroenterology and hepatology and offers an overview of sustainable strategies.
Subject terms
Surgery
Gastroenterology
==== Body
pmcIntroduction
Climate change is one of the greatest threats to public health worldwide. The association of air pollution, rising temperatures, flooding and drought with changes in the spread of vector diseases presents a risk to humanity1. Also, the health-care sector is one of the largest waste-generating entities contributing to climate change. For example, in the USA, health care produces 655 million tons of carbon dioxide equivalent (CO2e) per year, representing 8–10% of all national greenhouse gas emissions1.
Among health-care sectors, operating theatres are the most energy-intensive sites, three to six times more energy intensive than the rest of the hospital, greatly contributing to this environmental burden1,2. Thus, achieving sustainability in surgery is emerging as a strategy to reduce environmental effects3. Data on the surgical carbon footprint are emerging1,4. However, there have been insufficient efforts to address this problem5. Finally, gastrointestinal diseases are one of the world’s largest therapeutic areas and represents a heavy global burden. Peery et al.6 showed that, annually, in the USA, there are more than 43.4 million ambulatory visits and 3.8 million hospitalizations due to a primary gastrointestinal diagnosis. Moreover, 284,844 new gastrointestinal cancers were diagnosed in 2019. The diagnosis of gastrointestinal diseases and their advanced management substantially affect the generation of health-associated waste and the consumption of environmental resources7–9.
This Perspective aims to reassess the evidence on health care, the carbon footprint of surgery and gastrointestinal diseases, identify issues that need to be addressed to achieve more sustainable practice and develop strategies for more environmentally friendly surgery and gastrointestinal practice.
Climate change effects on health
Health promotion remains a development goal defined by the WHO10. Health professionals are crucial to this health promotion path, working directly with patients, from health centres to university hospitals. However, health facilities are greatly responsible for greenhouse gas emissions and global warming, directly related to health-promoting strategies and diseases10. Climate change affects public health, and the environmental footprint deserves all our attention with regard to health promotion development.
Global warming affects health in several ways. For example, over the past 20 years, high temperatures and heat waves have been responsible for a global 53.7% increase in heat-related mortality in people older than 65 years, owing to the exacerbation of cardiovascular and respiratory diseases10,11. In addition, climate change represents the ideal setting for spreading viral, bacterial and vector-borne infections12–14. Since the 1950s, there has been a higher incidence and broader distribution of dengue, malaria and Vibrio bacterial infections12,13 As an example, the worldwide incidence of dengue has increased 30-fold over the past 50 years14, and the daily mean temperature, temperature variation and precipitation extremes are considered the most important drivers14.
However, the effect of climate change on gastrointestinal diseases seems to go beyond the global warming and infectious diseases tie-up. Seo et al.15 developed a mathematical model using meteorological factors and air pollutants obtained from eight metropolitan areas and showed a significant correlation between air pollutants such as carbon monoxide and gastro-oesophageal reflux disease (GERD), according to data from the GERD-related medical care utilization of the Korean National Health Insurance Service between 2002 and 2007 (r2 = 0.22; P < 0.001).
Undernutrition due to challenges with food production and the mental health effects of floods and droughts are also outcomes of the emerging global warming crisis in China, Bangladesh, Ethiopia and South Africa16,17.
Regarding pregnancy and obstetric outcomes, a 2020 systematic review, with 68 studies from the USA that analysed 32,798,152 births, concluded that air pollution and high-temperature exposure increased the risk of low birth weight and preterm labour18. These factors can exacerbate asthma in children, as confirmed in two studies with 990 and 315 children19–21. In addition, Fecht et al.22 observed higher rates of cardiac arrest and emergency admissions for stroke and asthma on days of high air pollution in England. Research in this field is emerging, and it is anticipated that more health outcomes due to climate change will be observed soon10. Consequently, WHO predicts that by 2030, there might be 250,000 additional deaths globally per year due to climate change23,24.
Carbon footprint definitions
Harmonization of the definitions and technical aspects of climate change and carbon footprint is crucial because it enables researchers to share the same language across different sectors. For example, if one aims to analyse the overall carbon footprint of rectal cancer diagnostic work-up, it is necessary to account for endoscopies, CT and magnetic resonance scans. However, it will not be easy to reach this understanding if the effect of these diagnostic procedures is measured in different units. On the other hand, if their functional units were converted into the CO2e (ref.25) standard metric, adequate comparisons and summing could be performed. Most typically, CO2e emission is obtained by multiplying the emission of a greenhouse gas by its global warming potential for a 100-year time horizon. However, there are several ways to compute such equivalent emissions and choose appropriate time horizons25. Thus, different entities have defined carbon footprint methods of estimation. Wiedmann and Minx26 elaborated on these different methods and the associated methodological issues. For example, one can use a process analysis developed to understand the environmental impact of a product’s life cycle, an environmental input–output analysis that combines environmental data and economic data or a hybrid approach, integrating the two methods. The method of choice will depend on the investigator’s aim and data availability26.
The Intergovernmental Panel on Climate Change guidelines define greenhouse gases as “gaseous atmosphere constituents that absorb and emit radiant energy within the thermal infrared range”, responsible for the greenhouse gas effect27. The term ‘carbon footprint’ was also defined as “the greenhouse gas produced by activities of an organisation measured in units of CO2e”10,25. Thus, the carbon footprint is an objective measure of the greenhouse gas emissions “emitted into the atmosphere by an individual, organisation, process, product, or event” measured in CO2e (refs.25,28). However, the carbon footprint measurement is not limited to quantification of greenhouse gases. Life-cycle assessments are part of this complex process because both the product and its production and disposal have an environmental effect19. Life-cycle assessments integrate a ‘cradle to grave’ analysis, including material manufacturing, transport, decontamination (for reusable products) and disposal3. Familiarity with these definitions is crucial for understanding the effect of various sectors on the environment and identifying measures that can mitigate this impact (Box 1).
Box 1 Definitions and nomenclature commonly used to characterize climate change and measure its impact Greenhouse gas: gaseous constituents in the atmosphere that absorb and emit radiant energy within the thermal infrared range
Carbon dioxide equivalent (CO2e): a standard metric used to compare the emissions from various greenhouse gases based on their global warming potential over a specified timescale to express a carbon footprint
Carbon footprint: an objective measure of the quantity of greenhouse gas emissions emitted into the atmosphere by an individual, organization, process, product or event measured in CO2e
Life-cycle assessments: methodological and detailed ways to assess the financial cost and environmental impact of a product from its production until its disposal
Health-care carbon footprint
Impact of the health-care sector on global carbon footprint
Climate change substantially affects public health and constitutes a barrier to health promotion. However, in the past few years, attention has been drawn to the effect of the health-care sector on climate change. Globally, the health-care sector was responsible for 4.6% of global greenhouse gas emissions in 2017 (ref.10). However, the figures might be higher per territory. For example, the health-care sector in the UK accounts for approximately 6% of the country’s total CO2e emissions29; Australia’s health-care contribution is 7%; the health-care sector of the USA represents nearly 10% of the country’s total CO2e emissions29,30. Importantly, these estimates are not yet available for many territories, and the figures are getting higher. In the USA, for example, greenhouse gas emissions have increased by more than 30% over the past decade compared with the the country’s previous emissions31.
The sources of these emissions can be directly related to health-care activities, representing 17% of the sector’s worldwide carbon footprint; to indirect emissions related to energy consumption (electricity, temperature conditioning and power), representing approximately 12% of the health-care sector’s footprint; and to the health-care chain supply (energy, transport, use and disposal of materials), representing approximately 71% of the total emissions worldwide30,32,33. Finally, the use of goods and services, such as pharmaceuticals and medical devices, cannot be ignored because manufacturing is also energy demanding30 (Fig. 1).Fig. 1 Health-care impact on the environment.
Health-care directly contributes to climate change. This contribution comes from various vectors. Anaesthetic gases, waste generation and disposable devices are considered direct vectors. Energy use, such as electricity and temperature conditioning, also contributes to the carbon footprint of health care. Indirect vectors, such as fossil fuel used for transport of patients and health-care providers and the life-cycle assessment of the health supply manufacture (such as its production, including transportation and water use), are all contributors to this environmental effect. CO2, carbon dioxide.
Surgical carbon footprint
Hospitals are considered the second most energy-intensive buildings in the USA30,34. Unsurprisingly, although operating theatres represent a small area in the hospital, they are more energy intensive than clinical wards and generate 50–70% of total hospital clinical waste2. Indeed, in the USA, operating theatres are the most resource-intensive practice in the health-care sector35. For example, one surgical procedure generates the same amount of waste as a family of four weekly in the USA36. In addition, most operating theatres are ready to serve 24 h a day, 7 days per week. Maintaining this activity level requires lighting, heating, ventilation and strict air conditioning settings1. These requirements account for up to 40% of global health-care emissions19,37.
The surgical pathway can be further divided into pre-procedure and intraprocedural timetables to determine the surgical carbon footprint and identify potentially approachable issues to address its environmental burden (Fig. 2).Fig. 2 Surgical carbon footprint.
Surgical environmental impact can be evaluated before, during and after surgery. Patient and staff transport is responsible for 18% of all health-care emissions. The diagnostic work-up before surgery accounts for a significant impact driven by CT scans, MRI and endoscopy. During surgery, there are multiple vectors to consider: water waste due to hand disinfection; anaesthetic gases are responsible for 40% of ‘surgical emissions’; operating theatre energy and temperature conditioning; disposable surgical linens; and single-use devices. Moreover, different surgical approaches have different carbon footprints. Data on hysterectomy show that laparotomy has a lesser carbon footprint, followed by laparoscopy and robotics. CO2e, carbon dioxide equivalent.
Before the surgical procedure
The first step in this pathway is transfer of the patient and staff to the hospital. In England, this journey occurs by public transport in only a minority of cases and accounts for up to 18% of the CO2e health-care emissions38.
Before surgery, the patient usually needs to undergo a diagnostic work-up for which the carbon footprint is often substantial. For example, if a patient needs CT, the environmental footprint will be 10.2–15.8 kg CO2e per patient39. By contrast, the carbon footprint for MRI is 22.4 kg CO2e per patient40. Finally, endoscopies are procedures with considerable environmental effects owing to waste generation, accounting for approximately 3.09 kg of waste per bed per day, which is equivalent to 3 kg CO2e (ref.41). In addition, the use of disposable equipment, the decontamination process of reusable scopes and patient travel should be added to the endoscopic environmental burden42 (Fig. 2).
During the surgical procedure
After the diagnostic work-up, the patient arrives at the operating theatre, and anaesthesia is the first vector for analysis. The current data show that an anaesthetic plan can considerably affect the environment. Inhaled anaesthetic agents are mainly expired and are released directly into the atmosphere. These gases (sevoflurane, isoflurane and desflurane) are potent greenhouse gases19,43,44. A study that compared the carbon footprint of inhaled agents and propofol concluded that desflurane had the highest footprint, 15 times greater than isoflurane and 20 times greater than sevoflurane. Furthermore, 80% of all volatile anaesthetic pollution results from desflurane29,45. Importantly, propofol had the lowest carbon footprint. Regarding global warming potential, desflurane has a global warming potential of 2,540 (that is, 1 g of desflurane has the same global warming potential as 2,540 g of CO2), sevoflurane 130 and isoflurane 510 (ref.29).
Surgical hand disinfection traditionally requires 18.5 l of water46. Current guidelines recommend using water with antiseptic in the first operating theatre procedure and alcohol gel in subsequent procedures47. Adopting these recommendations could save water and reduce costs48. After hand disinfection, one must consider surgical linens such as gowns, drapes and table covers. Despite the availability of reusable ones, disposables (single-use) are more commonly used worldwide49.
Finally, for the surgery itself, surgical packs of sterile instruments are frequently opened before surgery begins50. Eighty per cent of surgical solid waste is generated before the patient enters the operating theatre, and most of this waste is associated with packaging51,52. There is a lack of robust evidence on how much waste could be avoided if sterile pack openings were delayed until the start of surgery. The introduction of minimally invasive surgery over the past 20 years has brought undeniable benefits to patients53. However, this type of surgery involves more single-use instruments (disposables)54, mistakenly viewed as a more economical choice, and all hidden costs (for example, disposal, loss of resources when a not-needed device is opened, maintaining a high-volume inventory) are often skipped54. Infection control is one of the premises used to justify use of single-use instruments. However, the data show that the infection rates are comparable to those with reusable instruments5,55. In a study with 100 patients submitted to appendectomy using reusable or single-use instruments, the infection rates were similar (2% in each group; P = 0.536)56. In addition, when the environmental effects and costs are accounted for, the negative effect of single-use instruments on the environment is evident5,57. Notably, a multicentre audit in the UK concluded that 40% of the waste generated in operating theatres was potentially recyclable58. However, operating theatre recycling is not largely applied59.
Studies have broadly examined minimally invasive surgery. Laparoscopic and robotic approaches are associated with higher carbon footprints than the open approach. Woods et al.60 concluded that an abdominal hysterectomy performed using an open approach (laparotomy) accounted for 22.7 kg CO2e. In comparison, the laparoscopic and robotic procedures were responsible for 29.2 kg CO2e and 40.3 kg CO2e, respectively (Table 1). Notably, data on the effect of different surgical approaches are scarce and limited by not considering all surgical pathways60–62. Evaluating surgical procedures without assessing inpatient days and patient outcomes is reductive from the clinical and environmental perspectives.Table 1 Environmental burden of the various processes during the surgical pathway
Study Method Aim Speciality Environmental effect measure Outcome
Esmaeili et al. (2015)39 Multicentre, retrospective cohort study “Provide quantitative information to radiologists so that they can be involved in making energy improvements while maintaining quality patient care.” Radiology — CT Life-cycle assessment (energy and consumables), kg CO2e CT 5.1–7.3 kg CO2e
Esmaeili et al. (2018)40 Multicentre, retrospective cohort study “Provide a detailed accounting of energy and materials consumed during magnetic resonance imaging (MRI).” Radiology — MRI Life-cycle assessment (energy and consumables), kg CO2e MRI 22.54 kg CO2e
Woods et al. (2015)60 Single-centre, retrospective cohort study “Our research intends to quantify the carbon footprint of the procedures based on their energy consumed and waste produced.” Gynaecology — hysterectomy (robotic; laparoscopic; open approach) Waste and energy, kg CO2e Robotics 40.3 kg CO2e
Laparoscopic 29.2 kg CO2e
Open 22.7 kg CO2e
Thiel et al. (2018)127 Single-centre, prospective cohort study “To determine the carbon footprint of various sustainability interventions used for laparoscopic hysterectomy.” Gynaecology — hysterectomy (laparoscopic approach) Hybrid environmental life-cycle assessment, kg CO2e Laparoscopic hysterectomy 562 kg CO2e
Rizan and Bhutta (2022)61 Single centre “Compare the environmental and financial life cycle cost of currently available hybrid instruments for laparoscopic cholecystectomy and compare these to single-use equivalents.” General surgery; cholecystectomy Life-cycle assessment of the single-use and non-single-use (hybrid), kg CO2e Hybrid: 1,756 kg CO2e
Single-use: 7,194 kg CO2e
Vaccari et al. (2018)41 Single-centre, prospective, cohort study “Understand the nature of the relationship between generation patterns hazardous health-care waste and the associated costs.” All specialities (anaesthetics, paediatric; ICU; digestive endoscopy) Amount of hazardous waste, kg Anaesthetics 5.96 kg per day per bed
ICU 3.37 kg per day per bed
Digestive endoscopy 3.09 kg per day per bed
A summary of articles that measured the environmental effect of diagnostic modalities (CT, MRI and digestive endoscopy), surgical procedures (hysterectomy and cholecystectomy) and surgical approaches (open, laparoscopic and robotic). CO2e, carbon dioxide equivalent; ICU, intensive care unit.
Sustainable surgery
Sustainability applied to health systems is defined by the WHO as a process to “improve, maintain, or restore health while minimizing negative effects on the environment”63–65. As health professionals working in a high-impact field, surgeons should be proactive and openly promote sustainable surgery. Guidance on this pathway was disclosed in 2012 by Kagoma et al.5, focusing on the 5R principles of waste management (reduce, reuse, recycle, rethink and research) to outline solutions to decrease the waste generated in operating theatres5. However, in addition to solutions to decrease waste generation, these principles can be broadly applied as future strategies for more sustainable surgical practice (Fig. 3). The authors of this Perspective believe that the proposed framework to mitigate the environmental effects of surgery could be translated to other fields.Fig. 3 Areas for action to make the surgical pathway more sustainable.
Before patient admission, health promotion measures and the use of sustainable means of transport by patients, health-care professionals and products are important interventions. At the hospital, using renewable energy sources and optimizing electricity and cooling systems should be considered. During surgery, avoiding anaesthetic gases and promoting intravenous and local anaesthesia can have a remarkable effect. Additionally, reducing disposables and implementing recycling would reduce waste production. Telemedicine represents a good example of how technology can facilitate sustainability. Research and education are important to evaluate the impact of sustainable actions and can help to continue this process across generations. CO2e, carbon dioxide equivalent.
Reduce
The reduction principle can be applied before and beyond surgery. For example, data published in 2015 showed that 143 million additional surgical procedures were required annually to prevent disability66. The calculation was made using “the frequency of operation per WHO Global Health Estimate disease subcategory” and then “the estimated surgical frequency for each disease subcategory to condition prevalence data for each global region” was applied66. Thus, health promotion to reverse these statistics should be the first priority66. Health promotion is a global responsibility that involves patients, caregivers, health professionals and governments. Reducing the disease burden through healthy behaviour could reduce disease-related health-care requirements and surgical demand.
Addressing waste generation in operating theatres could further reduce the surgical carbon footprint. Correct segregation process, recycling59 and reformulating prepackaged surgical kits and instrument boxes (by removing inessential items and plastic components)67 could serve this purpose. A study in the USA on hand surgery showed that these measures alone reduced 2.3 kg of waste and saved US$10.64 per case68. These principles could be further applied to endoscopy units.
Water waste from hand disinfection has already been addressed. According to current international guidelines, water consumption and its direct environmental effect can be easily reduced47,48. Accordingly, after an adequate first hand wash with water, choosing alcohol gel for the second hand wash might reduce water consumption by 2.7 million litres over 1 year67 and reduce costs by 67%69.
Finally, energy consumption should also be addressed. As previously mentioned, operating theatres are the most energy-intensive sector in hospitals. However, operating theatres in northern America are unoccupied up to 40% of the time over a 24 h period5. For example, in Washington State, USA, a hospital reduced energy consumption by 60% by decreasing ventilation output during inactive periods63,70.
Reuse
Reusable surgical linens and instruments are considered to be environmentally friendly. Preferring reusables will lead to less waste generation and reduce landfill and incineration costs. In addition, when all processes are accounted for, from production to sterilization, the reusable carbon footprint remains favourable compared with disposable products57. For example, using reusable surgical devices (port trocars and clip appliers) in laparoscopic cholecystectomy surgery can save approximately 122 kg of waste per case71. Moreover, reusable gowns could lead to a 70% final waste reduction. Currently, reusable gowns are preferred by surgeons and operating theatre technicians, but disposable ones are still broadly used72.
The reprocessing of single-use devices is controversial. Health-care personnel might think reprocessing single-use devices can be associated with an increased infection rate, but this might not be correct36,73. For example, a study of 590 patients that compared reprocessed versus original single-use endolaser probes in ophthalmological surgery (215 versus 375 patients) showed no infections in either group74. In a similar study involving 733 patients submitted to gastrointestinal surgery with original and reprocessed advanced energy devices and gastrointestinal staplers, there was no difference between the infection rates in the two groups (12.9% original and 13.4% reprocessed; P = 0.664)75. However, devices initially labelled as single-use can often be repaired and sterilized, making their reuse safe76. Although reprocessing is not a standard procedure and protocols might differ according to territory36, in 2019, the FDA and the European Commission developed regulations to control in-hospital reprocessing77. Moreover, outsourcing of commercial reprocessing that complies with these regulations is emerging. According to the Association of Medical Device Reprocessors, 5,438,254 kg of medical waste was diverted from incinerators worldwide through remanufactured single-use devices in 2020 (ref.78). Reuse through reprocessing and remanufacturing is expanding and offers environmental and financial benefits. For example, the authorities in the USA support reprocessing under approved conditions. However, reprocessing is not a standard procedure, and protocols differ according to country36,55,79. Thus, awareness and support from the medical device industry are crucial for the broader implementation of this practice36,57.
Recycle
In England, 80% of operating theatre waste is generated preoperatively, 90% is misallocated and 40% is potentially recyclable. Thus, implementing and disseminating the recycling process in the operating theatre and beyond is crucial52,63,80.
However, recycling in the health-care setting presents several challenges. Educating operating theatre staff on waste handling and strict infection control rules will help to overcome the fear of contamination63,81. A cohort study that evaluated the waste generated by 237 operations concluded that recycling is not associated with additional costs and has several advantages if the practice is globally expanded82.
Rethink
Sustainability should be a part of health-care professionals’ practice. Patient health and outcomes will always be the main focus. However, the consequences of climate change on current and future generations must not be ignored, and strategies to address this issue should not be delayed. Rethinking entails selecting the most sustainable choice to treat patients without causing any harm. For example, the American Society of Anaesthesiologists Task Force on the Environment recommended using regional and total intravenous anaesthesia as the most sustainable option (instead of high-impact inhaled anaesthetics such as desflurane and sevoflurane) when clinically appropriate2,59.
The severe acute respiratory syndrome coronavirus 2 pandemic forced us to rethink how we practise medicine. Telemedicine has emerged as an adequate solution that is appropriate for professionals and patients for the follow-up of chronic conditions83–85. This emergency and contingency solution can be maintained in the future when appropriate, as telemedicine reduces patient travel and vehicle emissions. Also, some applications could work with telemedicine, allowing patients to remotely monitor their health status, reducing pressure on oversaturated health systems85,86. Furthermore, technology might be applied to training and education as a distance-learning tool, allowing telementoring in surgery and beyond. For example, this modality is gaining popularity at virtual conferences87. Telementoring enables international networking and avoids unnecessary travel.
In addition, the medical device industry should be part of this rethinking process. Single-use devices are more profitable for medical companies than reusable ones78. For example, in a laparoscopic cholecystectomy study of 1,803 surgeries, the costs of disposables (including trocars, ports and clip applicators) were found to be 6.4 times higher than reusables71. Therefore, the creation and promotion of reusable medical devices are of utmost importance, and this reflection should begin within the industry, presenting sustainable devices to medical professionals.
The carbon cost of various treatment options for the same disease will also probably need to be equated in the future. Two multicentre studies88,89 on GERD surgery (288 patients) compared with medical therapy (266 patients) were carried out. The first multicentre study focused on clinical outcomes: for up to 3 years, 90% of the patients in the surgical arm remained in remission compared with 93% in the medical arm (P = 0.25)88. In the second study, Gatenby90 studied the carbon footprint of the two approaches. The surgical arm was more sustainable than the medical arm (30 kg CO2 versus 100 kg CO2 per year, respectively). Although these estimates pointed out methodological flaws, because the data used were collected from a large multicentre cohort created for another purpose and the model did not take into account different manufacturing origins, which can have different carbon footprints90, this study raised questions regarding the need to equate carbon cost with different treatment options.
Finally, systematic measurement is necessary to reduce the surgical carbon footprint adequately. Scales to standardize carbon footprint measurement have been developed, such as the Spark2 (ref.91) for the broad surgical process or those described by Misrai et al.52 for the evaluation of disposable minimally invasive surgical devices52,91. Technology that will allow for global implementation of these scales is under development, and this will warrant a systematic measurement and identify health-care sectors in which sustainable intervention is necessary (Open Medical). In addition to the remote monitoring of patients, technology could be applied to monitor hospital material, track maintenance and replacement timings, and boost the efficiency of hospital supplies (Loopcycle).
Research
Climate change and health have attracted the attention of scientists in the past few years, and novel data on the environment and health are being issued daily. However, only 9.2% of the available literature focuses on the environmental effects of the health-care sector on health57, and this topic has not received the attention it deserves from researchers92. For example, endoscopy is an important diagnostic procedure for many surgical patients. Although there has been an increased focus on sustainable surgery, research on more sustainable endoscopy practices is still in the early stages of development.
Gastroenterologists and surgeons are leaders in wards, endoscopy units, operating theatres and scientific research. There have been excellent examples of surgical leadership in developing and delivering global quality research that affects patients’ lives and medical practices93,94. It is time to gather the same energy and effort for sustainability in surgery and beyond. Sustainable surgery must be evidence based, and there must be a real investment in quality research to achieve this. Although the motivation of practitioners and researchers is crucial, the support of national and international entities is needed to address this issue adequately. Environmental choices are typically economical, and promoting more sustainable surgical practice would advocate environmental protection and financial savings. This financial benefit is a strong argument, and further high-quality research to demonstrate this premise is required.
Re-educate
The authors of this Perspective consider the lack of awareness and education on sustainability in surgery as a reality. The surgical carbon footprint has been demonstrated2, and guidance on possible solutions to address some of the carbon footprint drivers has been available since 2012 (refs.5,90,95–97). However, sufficient real-world effort has not been made.
A survey published in 2020 showed that 19% of ophthalmology surgeons in New Zealand believe that climate change is not due to human activity and does not require any human action98. Moreover, 61% affirmed that they were not concerned about sustainability in their current practice98. In addition, fewer than 20% had received education or guidance regarding this subject. These data conclusively show that education regarding surgery sustainability is urgently needed.
The UK is at the forefront of sustainability education in health care. For example, the General Medical Council and Nursing Midwifery Council require education and the clinical application of sustainable methods99,100. In addition, in the UK, guidance starts in universities with lectures on sustainable health care for prospective doctors and nurses101.
The ‘re-education process’ has already begun. Sustainability in surgery is being promoted by multiple organizations worldwide created to address this issue. Also, European surgical societies such as the European Society of Coloproctology102 and the European Society of Gastrointestinal Endoscopy103 are developing campaigns to address sustainability102. However, more focus should be placed on sustainability during surgical conferences, social media channels and medical and surgical training to better educate current and future generations of surgeons.
Notably, accounting for clinical best practices and patient safety is mandatory in a sustainable surgical model. The ultimate goal of surgery is to cure and offer a good health-related quality of life. Clinical best practices are starting to recognize sustainability as an aim, and ‘doing no harm’ is starting to concern both patients and the environment59,104. In the available studies on this topic, implementing sustainable policies in surgery did not increase the risk of adverse events nor result in suboptimal treatment outcomes54,105,106. Patients must also be integrated into this novel approach to surgery1,19. Future studies on sustainability in surgery should confirm the acceptability and safety of a ‘greener’ surgical path by evaluating patient-reported and surgical outcomes1,19.
Gastroenterology and hepatology
Gastrointestinal conditions
In the USA, gastrointestinal diseases are a source of substantial burden and costs, and this burden is likely to continue increasing6,8. Several considerations explain why this field should be considered central to — and should likely lead to — a change in practice towards a sustainable approach (Box 2). The prevalence of these conditions is one of the most important aspects, and the associated need for invasive treatment, such as appendectomy, which is among the most common procedures performed globally, with increasing figures over the past few years107. Screening and treatment for cancers of the digestive system represent another major determinant. According to the International Agency for Research on Cancer of WHO, in 2020, approximately 31,179 million people had had cancer of the stomach, colon and rectum, or liver and intrahepatic bile ducts. Figures on these specific cancers are expected to increase to 36,795 million by 2040 (+59.7%)108. Notably, although the rates and cumulative risk of prostate (age-specific rate (ASR) 65.5) and lung (ASR 41.7) cancers were the highest globally in men in 2010, gastrointestinal tract cancers (oesophagus, stomach, colon, rectum and anus, liver, gallbladder and pancreas) were by far the first if taken all together (ASR 6.6, 15.9, 22.7, 16.3, 9.1, 2.3, 8.1, respectively)109. The prevalence of obesity and overweight should also be considered because this affects the number of patients requiring surgical or endoscopic interventions for such conditions, often involving minimally invasive approaches and single-use consumables. Unprecedented adoption of minimally invasive surgery has been recorded during the past decade for treating gastrointestinal diseases110, which seems to have surpassed the rates of open surgery between 2012 and 2018 in the USA, and the associated implications for the environment can easily be inferred. Thus, it becomes apparent that treatment of gastrointestinal diseases is a major player in determining the sustainability of health care — and at the same time, this sector represents an opportunity to drive the development and implementation of novel strategies to protect the environment (Box 2).
Box 2 Relevance of gastroenterology and hepatology to sustainable health-care practices Priority Epidemiological relevance (gastro-oesophageal reflux disease; functional disorders; gastrointestinal infections; chronic liver disease; inflammatory bowel disease; gastrointestinal cancer)
One of the world’s largest therapeutic areas representing a heavy global burden
Advanced management demand (endoscopy, surgery)
Endoscopy is a burdensome practice owing to waste generation, disposable equipment, and energy and water consumption
Sustainable applications Disease prevention (vaccination, policies to counteract alcohol abuse and healthy lifestyle advocation)
Use of lower effect and more widely accessible medications that are safe and effective (for example, biosimilars)
Reduce unnecessary patient travelling (subcutaneous alternatives to intravenous medication; teleconsultation)
‘5Rs plus one’ interventions in endoscopy units and gastroenterology departments
Ethics Reuse through reprocessing and remanufacturing (regulation development and advice from the medical device industry)
Ensure acceptability and safety of sustainable choices through outcome measures (patient-reported; productivity estimates)
Digestive endoscopy principles
It has been estimated that between 11 and 15 million colonoscopies and 6 and 7 million upper gastrointestinal endoscopies are performed in 1 year in the USA alone6. This Perspective deconstructs the carbon footprint of the surgical pathway, as discussed earlier, and, indeed, endoscopy is part of this pathway, and its carbon footprint is substantial41,42,111. However, most endoscopy environmental effect drivers overlap the surgical ones, and these areas share solutions and barriers to mitigate climate change effects. Haddock et al.112 emphasized the importance of energy and water use, waste generation and handling, minimization of packaging and education of the staff on sustainable activities such as recycling and reducing unnecessary resource use. This Perspective promotes application of the ‘reduce, reuse and recycle’ principles but acknowledges that funding benchmarking research and education are important efforts towards sustainability112. Thus, the previously presented solutions (5Rs plus 1) apply to the daily practice of endoscopy (Box 2).
Moreover, Siddhi et al.113 highlighted that the challenges to achieving environmentally sustainable endoscopic practice range from standardized and reproducible carbon footprint measurement to transforming industrial, governmental and public health policies. The same multidisciplinary approach needs to be implemented in surgery and other health-care sectors to mitigate the climate change burden. Lastly, some endoscopy-specific factors should be considered — the first concerns endoscope reuse, which is currently a source of major debate114. Reprocessing entails costs, but manufacturing, assembly and transportation might result in a higher environmental burden. Secondly, faecal immunohistochemical testing could be a sustainable strategy to triage patients for the risk of harbouring colorectal cancer and potentially be used to prioritize endoscopic procedures115. However, further research and cut-off level adjustment might be needed115.
Sustainability of invasive procedures
Disease prevention and prompt treatment are of utmost importance in addressing the indirect environmental burden of diseases. Furthermore, climate change can negatively affect the gastrointestinal tract and its function. The incidence of gastrointestinal infectious disease parallels global warming116, and GERD-related medical care utilization increases in air-polluted environments (defined according to carbon monoxide and particulate matter with a diameter of ≤2.5 µm)15. However, if these are relatable associations, other correlations might not be straightforward, such as those linking functional gastrointestinal diseases to climate change17,117 and inflammatory bowel disease (IBD) to aeroallergens and air pollution118. It is very difficult to tackle environmental challenges beyond clinicians’ practice. Clean energy promotion towards a fossil-free recovery and recognizing the importance of biodiversity preservation are some of the measures in the COP 26 special report by WHO, focusing on “the health argument for climate action”119. However, there are potential paths for health professionals and health-care administrations regarding diseases such as IBD that might result in more sustainable practices compared with current practices.
For example, biosimilars are bending the cost curve120 and might represent wider global access to therapy for IBD and patients with cancer than currently. The wider availability of these therapies might allow reduction in the disease burden, which is a sustainable measure as it promotes health. Also, the emergence of subcutaneous alternatives to the conventional formulations of biologic agents for IBD reduces unnecessary patient travelling and hospital burden because patients can administer these therapies at home121. IBD and other chronic gastrointestinal disorders might lead to iron deficiency anaemia. Comorbid anaemia is an important predictor of increased risk of hospitalization and patient mortality. There is evidence regarding the use of ferric carboxymaltose as the most sustainable intravenous iron preparation owing to the lower number of infusions needed, this reducing hospital burden and costs related to individual patient management122.
Another example is patients with chronic liver diseases, who are high need and high cost. Governmental health agencies should implement policies to prevent hepatitis transmission, counteract alcohol abuse and encourage lifestyles that prevent obesity and metabolic syndrome123. As stated, these interventions advocating a healthier lifestyle could further reduce the need for obesity surgery and bariatric endoscopy. Hepatitis B vaccine equity, recommended for all newborns and individuals in high-risk groups, could profoundly affect not only reduction of the hepatocellular carcinoma burden worldwide but also reduction of disease vulnerability in low and lower-middle-income countries. As stated by WHO, “until everyone is safe, no one is safe”119.
Barriers to sustainable health care
Various barriers (‘roadblocks’ that prevent the adoption of strategies to reduce climate change) have been reported and categorized throughout the past few years124. However, these barriers are not hurdles specific to health systems. Various contexts, such as health care, households, cities and agriculture, will share barriers that hold back climate change mitigation; these are all relevant when developing sustainable medical and surgical practice. For example, barriers faced by cities that aim to reduce greenhouse gas emissions and become more resilient to face the effects of climate change (for example, “access to funding is the single biggest obstacle to cities delivering greater climate action”) are similar to the barriers faced by health systems (for example, “the financial environment of health-care conflicts with climate change mitigation”)125 (Box 3).
Health systems operate in a constrained context that aims for optimal clinical care delivery, and sustainability considerations are seldom made117. Nevertheless, there is evidence that initiatives to promote sustainable development are being made. However, health-care system transformations to address climate deterioration will require paradigm shifts in health-care aims and practices126, and changing behaviours is challenging. This necessity suggests the importance of an additional principle to the 5Rs rule because re-education can be a pillar in facilitating cultural change that should not be neglected.
Box 3 Common barriers to adopting a sustainable approach that apply to health care Economic and financial — access to funding to implement greater climate action
Policy and leadership — difficulties in implementing long-term measures when governments usually change on shorter-term cycles
Institution, regulatory and legislative — conflicting interests
Information and knowledge — lack of global awareness and advice
Social and cultural — influence, adaptation, change and decision-making
Technology and infrastructure
Physical and human context — adaptive capacity limited by human resources
Conclusion
Surgery is the most energy-intensive sector, and achieving sustainability in surgery is an emerging strategy for decreasing the carbon footprint of the health-care system (see Box 4). However, environmental costs associated with surgical care are often overlooked, and this issue has been largely ignored in the past but is gaining increased recognition. Therefore, it is vital to undertake high-quality research to demonstrate that promoting more sustainable surgical practice protects the environment and results in financial savings that would serve political interests. Specific areas for further investigation include the environmental burden of various surgical approaches, the implementation of operating theatre recycling, the promotion of reusables, advocacy for sustainable anaesthetic options, the environmental gains associated with telemedicine, telementoring and technological developments, and looking beyond specific surgical procedures to the overall surgical pathway.
In conclusion, climate change and environmental burdens are global problems. However, the environmental effect of health systems goes beyond surgical practice. Indeed, endoscopy, gastroenterology and hepatology are versatile areas in which sustainability interventions are also pertinent. The framework presented here to mitigate the effects of surgery can be easily transferred to other departments and health services. The insights provided in a stepwise manner can be applied to surgical departments and beyond (hospitals and health services) within a multidisciplinary perspective, leading to the implementation of climate change mitigation efforts.
Box 4 Key points on environmental effects of surgical procedures and strategies for sustainable surgery Climate change dramatically threatens public health and the health-care sector.
Surgery is the most energy-intensive practice, directly contributing to climate change.
Gastrointestinal diseases are among the most common conditions requiring invasive diagnostic and therapeutic procedures globally.
Sustainable gastroenterology and endoscopy practices are still in the early stages of development.
The ‘5Rs plus 1’ principle (reduce, reuse, recycle, rethink, research and re-educate) can be used as a template for more sustainable surgical practice. It can be easily applied to other health-care fields.
Sustainability in surgery encompasses a surgical pathway that aims to achieve the best outcomes for patients in an environmentally friendly way.
The impact of the health-care sector should be addressed from a multidisciplinary perspective, including health professionals, patients, companies, health-care managers and governments.
Acknowledgements
The authors thank P. Castelo Branco for his insights during manuscript revision and J. Roseira for her support with this article.
Author contributions
The authors contributed equally to all aspects of the article.
Peer review
Peer review information
Nature Reviews Gastroenterology & Hepatology thanks Craig McClain, Nitin Ahuja and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Competing interests
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Related links
Loopcycle: https://loopcycle.io/
Open Medical: https://www.openmedical.co.uk/
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| 36481812 | PMC9735025 | NO-CC CODE | 2022-12-14 23:28:32 | no | Nat Rev Gastroenterol Hepatol. 2022 Dec 8;:1-12 | utf-8 | Nat Rev Gastroenterol Hepatol | 2,022 | 10.1038/s41575-022-00716-5 | oa_other |
==== Front
Virtual Real
Virtual Real
Virtual Reality
1359-4338
1434-9957
Springer London London
733
10.1007/s10055-022-00733-4
S.i. : New Trends on Immersive Healthcare
Dropout rate in randomised controlled trials of balance and gait rehabilitation in multiple sclerosis: is it expected to be different for virtual reality-based interventions? A systematic review with meta-analysis and meta-regression
http://orcid.org/0000-0002-4217-6827
Casuso-Holgado María Jesús 15
http://orcid.org/0000-0003-2621-2098
García-Muñoz Cristina [email protected]
25
http://orcid.org/0000-0002-1664-3647
Martín-Valero Rocío 3
http://orcid.org/0000-0003-2441-5342
Lucena-Anton David 2
http://orcid.org/0000-0002-6465-982X
Moral-Munoz Jose A. 24
http://orcid.org/0000-0002-9514-8811
Cortés-Vega María-Dolores 1
1 grid.9224.d 0000 0001 2168 1229 Department of Physiotherapy, University of Seville, Seville, Spain
2 grid.7759.c 0000000103580096 Department of Nursing and Physiotherapy, University of Cadiz, Cadiz, Spain
3 grid.10215.37 0000 0001 2298 7828 Department of Physiotherapy, University of Malaga, Malaga, Spain
4 grid.7759.c 0000000103580096 Institute of Research and Innovation in Biomedical Sciences of the Province of Cadiz (INiBICA), University of Cadiz, Cadiz, Spain
5 grid.9224.d 0000 0001 2168 1229 UMSS Research Group, Universidad of Seville, Seville, Spain
7 12 2022
117
22 3 2022
29 11 2022
© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
To assess and meta-analyse the pooled dropout rate from the randomised control trilas that use virtual reality for balance or gait rehabilitation in people with multiple sclerosis. A systematic review of randomised control trials with meta-analysis and meta-regressions was performed. A search was conducted in PubMed, Scopus, Web of Science, the Physiotherapy Evidence Database, the Cochrane Database, CINHAL, LILACS, ScienceDirect, and ProQuest. It was last updated in July 2022. After the selection of studies, a quality appraisal was carried out using the PEDro Scale and the Revised Cochrane risk-of-bias tool for randomised trials. A descriptive analysis of main characteristics and dropout information was performed. An overall proportion meta-analysis calculated the pooled dropout rate. Odds ratio meta-analysis compared the dropout likelihood between interventions. The meta-regression evaluated the influence of moderators related to dropout. Sixteen studies with 656 participants were included. The overall pooled dropout rate was 6.6% and 5.7% for virtual reality and 9.7% in control groups. The odds ratio (0.89, p = 0.46) indicated no differences in the probability of dropouts between the interventions. The number, duration, frequency, and weeks of sessions, intervention, sex, multiple sclerosis phenotype, Expanded Disability Status Scale score, and PEDro score were not moderators (p > 0.05). Adverse events were not reported and could not be analysed as moderators. Dropouts across the virtual reality and control comparators were similar without significant differences. Nonetheless, there is a slight trend that could favour virtual reality. Standardisation in reporting dropouts and adverse events is recommended for future trials.
PROSPERO database, registration number ID
CRD42021284989.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10055-022-00733-4.
Keywords
Dropout rate
Multiple sclerosis
Adherence
Virtual reality
Attrition
==== Body
pmcIntroduction
Different types of virtual reality technology (e.g. non-immersive, semi-immersive, or fully immersive) have emerged as an useful tool in neurorehabilitation with promising results for physical and cognitive rehabilitation (Voinescu et al. 2021). In this way, virtual reality-based interventions have been enhanced as a technological solution for telerehabilitation at the time of the COVID-19 pandemic (Matamala-Gomez et al. 2021). Furthermore, the previous literature has proposed that virtual reality strategies present higher adherence in patients with neurological disorders (Asadzadeh et al. 2021; Dalmazane et al. 2021). Multitask training, patient motivation, safety, and the low cost of commercial devices are some of the benefits of using virtual reality for neurological rehabilitation (Forsberg et al. 2015; Gustavsson et al. 2021; Moan et al. 2021). Nonetheless, some undesired effects (e.g. headache, sickness, or nausea) (Massetti et al. 2018), as well as the difficulty of transferring the complex skills trained in virtual environments to the real world and the lack of ecological validity in a neurologically impaired population (Levac et al. 2019), were reported. Specifically, for balance training, the time of latency, the underestimation of perceived distances, and the dependence on specific systems (e.g. balance board) and virtual contexts were proposed as potential weaknesses of virtual reality environments (Morel et al. 2015).
Multiple sclerosis is a global neurodegenerative disease affecting approximately three million people in the world (Tafti et al. 2022). Balance disorders, gait impairments, and fatigue are the main symptoms in patients with multiple sclerosis that obtain positive effects with physical therapy intervention (Amedoro et al. 2020; Abou et al. 2022). Particularly, virtual reality-based physical rehabilitation showed benefits for balance and gait training (Casuso-Holgado et al. 2018; Nascimento et al. 2021); however, fatigue is a significant barrier to participation in physical activity, which influences the participants’ adherence (Moore et al. 2022). A recent systematic review has summarised dropout data from randomised control clinical trials about exercise interventions in people with multiple sclerosis, concluding that mean age, the proportion of females, and intervention duration were moderators inversely associated with adherence (Dennett et al. 2020). Therefore, these findings could impact the sample size calculation, promoting an under- or overestimation. Furthermore, this could influence the differential dropout rate, which is how the degree of dropout differs between the intervention and comparator conditions after randomisation (Crutzen et al. 2015). It might affect the power of research and could present a risk of bias for randomised control clinical trials (Cooper et al. 2018). In view of this background, setting accurate expected dropout rates in virtual reality studies for rehabilitation in multiple sclerosis could help future trials to avoid problems in their internal or external validity. In addition, the identification of factors specifically associated with dropout in virtual reality trials could help clinicians when translating research into practice.
As far as we are concerned, no previous systematic reviews were found reporting dropout in virtual reality interventions for balance and gait rehabilitation in this population. Thus, the present systematic review and meta-analysis aimed to: (1) systematically assess and meta-analyse the overall pooled dropout rate of randomised controlled trials using virtual reality as an intervention for balance or gait training in people with multiple sclerosis in both absolute and comparative terms; (2) analyse whether any participant or intervention factors are related to dropout; and (3) identify adverse events that could be the reason for dropouts.
Methods
Data sources and search strategy
This systematic review was carried out following the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al. 2009). The review protocol was registered in the PROSPERO database (Registration number: CRD42021284989).
Two independent reviewers (M.J.C.-H., C.G.-M.) conducted an electronic search in MEDLINE (PubMed), Scopus, Web of Science (WOS), the Physiotherapy Evidence Database (PEDro), the Cochrane Database of Systematic Reviews (CDSR), CINHAL, LILACS, ScienceDirect, and ProQuest. The search was performed between July and November 2021. Neither language nor date filters were applied in the different databases. Key terms concerning intervention (‘virtual reality’, ‘game’, ‘gaming’, ‘exergaming’, and ‘interactive’), balance (‘balance’ or ‘postural control’), gait (‘gait’, ‘walking’, and ‘ambulation’), and ‘multiple sclerosis’ were combined as search terms in the strategies. The search strategy is shown in detail in Supplemental Material 1.
Research question and study selection
The participants, interventions, comparisons, outcomes, and study design (PICOS) model was considered to set the following research questions: what dropout data are reported during the intervention and follow-up period by randomised control clinical trials conducting virtual reality intervention to improve balance or gait in multiple sclerosis and what are the possible moderators affecting dropout in these studies?
Participants included in the review were female or male, aged between 18 and 65 years old, with any diagnosis of multiple sclerosis phenotype meeting the revised McDonald criteria (Thompson et al. 2018). Walking ability was preserved according to the Expanded Disability Status Scale (EDSS) score (EDSS ≤ 6). Included interventions involved any type of virtual reality systems aimed at improving balance or gait compared to other interventions based on physical activity with or without external aid use. Furthermore, studies that reported dropout event information were included.
Data extraction and quality assessment
First, two independent reviewers (C.G.-M. and M.J.C.-H.) identified potential articles in databases to be included in the systematic review through the title and abstract information. Next, duplicates were removed, and an exhaustive analysis of articles was carried out based on their full-text reading. This step was particularly focussed on the selection criteria assessment, ensuring that the inclusion criteria were met before selecting suitable studies. In the case of disagreement, a third reviewer (M.-D.C.-V.) was consulted to decide on the inclusion of the documents.
Once articles were selected, the quality assessment was conducted using the PEDro scale (Maher et al. 2003) and the Revised Cochrane risk-of-bias tool for randomised trials (RoB-2) (Higgins et al. 2019). PEDro is a reliable tool of 11 items that evaluates the inner validity of a clinical trial. If studies score above 6 points, they are classified as level I evidence (6–8: good; 8–10: excellent). If the score is below 5, they are classified as level II (4–5: deficient; < 4: poor). ROB-2 allows the evaluation of bias in randomised control trials, comprising five domains (bias arising from the randomisation process, due to deviations from the intended interventions, to missing outcome data, in the measurement of the outcome, and in the selection of the reported result) that are qualified as a low or high risk of bias with some concerns (Sterne et al. 2019).
Next, reviewers recorded the data for qualitative and quantitative synthesis. The extracted data were country, multiple sclerosis phenotype and disability status, female and male percentages, age, experimental and comparator group intervention characteristics, number of participants recruited and analysed, retention rate, dropout rates (for the experimental and control groups), reasons for dropout (in each group), and adverse events. Disagreements in data were solved by consensus with a third reviewer. Information provided by the included studies allowed us to calculate dropout rates in all cases, so no corresponding authors were contacted.
Data analysis
Dropout rate was calculated as the number of participants who did not complete the intervention and follow-up period divided by the total number of participants that underwent the randomisation process. Moreover, retention rate was the total number of participants that concluded the intervention, showing the adherence rate to treatment. For those studies that included more than two groups of intervention, comparison between groups was analysed separately two by two.
To conduct the meta-analysis, the R Studio software (version 4.0.0) and its packages meta, metafor, and dmetar were used (Viechtbauer 2010; Balduzzi et al. 2019; Harrer et al. 2021). The proportion meta-analysis was performed through the metaprop function to determine the estimated dropout rate in virtual reality intervention, the control comparator, and all arms. Proportions were transformed using the logit transformation (Schwarzer et al. 2019).
A binary meta-analysis based on odds ratios (ORs) was conducted to examine whether the probability of dropouts is higher in the virtual reality or in the comparator interventions. To assess the effect measure in binary outcomes, the OR with a 95% confidence interval (95%CI) was calculated, and the inverse variance method was used to adjust pooling estimations to sparse data (considering that dropouts are a rare event). Likewise, the Hartung–Knapp adjustment for a random effects model was implemented. Focussing on ORs, if the value is 1, there are no differences in dropouts between the experimental and comparator groups. In contrast, if the OR is greater than 1, a higher dropout rate was registered for the experimental group. The restricted maximum-likelihood estimator for tau2 was selected to estimate the between-study variance (Viechtbauer 2005). As some studies could present zero events in the experimental and/or comparator arm, a 0.5 continuity correction was added to all meta-analyses, as suggested by Gart and Zweifel (1967).
Heterogeneity between studies was assessed through I2, tau2, and Cochrane’s Q (p < 0.05 indicates heterogeneity). When I2 presents a value above 50%, it means that large heterogeneity is found across studies (Higgins et al. 2021). A random effects model was employed considering the possible degree of heterogeneity between the included studies.
Forest plots were used to show the outcomes of proportions and binary meta-analyses. The prediction interval was added as a red line to the forest plot to provide a measure of reliability of future treatment effects in new studies (Nagashima et al. 2019). Depending on the level of immersion of the subject within the virtual environment, virtual reality was classified as non-immersive, semi-immersive, and fully immersive for subgroup analysis.
A sensitivity analysis was carried out to assess the influence of studies on the overall binary meta-analysis results. The influence was explored to detect the presence of outlier data and whether there were studies that contributed to heterogeneity or bias pooled results. A Baujat plot, a L’Abbé plot, and influence graphs were created to represent influential cases in meta-analysis. The influence graphs showed the studies that significantly influenced the pooled effect size in red. In addition, an exploratory graphical analysis of data was performed to examine whether there is a clear trend of effect size related to independent variables.
Meta-regression was conducted to evaluate possible associations between participants or study characteristics which could vary in the presence of dropout events. Studies with no available data were excluded from the meta-regression analysis. Moreover, to run the meta-regression, at least three studies with the predictor were needed. The analysed moderators were interventions, number, duration, frequency and weeks of sessions, EDSS score, multiple sclerosis phenotype, and sex.
Publication bias and small study effects were evaluated through a contour-enhanced funnel plot adjusted by the Duval and Tweedie trim and fill method (Shi and Lin 2020). Asymmetry in the funnel plot indicated the effect of small studies in the pooled results. To confirm the absence of asymmetry, a p value greater than 0.05 must be reached in the Harbord’s test (Harbord et al. 2006) and the Egger bias test (Egger et al. 1997).
Results
Study selection and methodological quality assessment
In total, 7024 articles were identified through the initial database search based on titles and abstracts. After that, duplicates were removed, obtaining 5995 articles. Once the studies underwent the screening and eligibility steps, 16 randomised control trials were included for the qualitative synthesis and quantitative analysis. There was no disagreement between reviewers in the study selection process. Figure 1 showed the PRISMA flowchart detailing the selection procedure. Excluded studies and their reasons are detailed in Supplemental Material 2.Fig. 1 Flow diagram of trials selection based on PRISMA 2020 guidelines. *Consider, if feasible to do so, reporting the number of records identified from each database or register searched (rather than the total number across all databases/registers). **If automation tools were used, indicate how many records were excluded by a human and how many were excluded by automation tools. From: Page et al. (2021). For more information, visit: http://www.prisma-statement.org/
Regarding the quality assessments, the PEDro scale results are shown in Supplemental Material 3. PEDro scores were reported from the included studies: thirteen with level I evidence (Lozano-Quilis et al. 2014; Hoang et al. 2016; Kalron et al. 2016; Calabrò et al. 2017; Peruzzi et al. 2017; Russo et al. 2018; Khalil et al. 2019; Munari et al. 2020; Ozkul et al. 2020; Tollar et al. 2020; Molhemi et al. 2021, 2022; Pagliari et al. 2021) and three with level II (Brichetto et al. 2015; Robinson et al. 2015; Yazgan et al. 2020). Most studies were single blinded, with the assessor being blinded to participant allocation. In addition, the ROB-2 overall score reported that most studies presented some concerns, but only three studies (Robinson et al. 2015; Ozkul et al. 2020; Yazgan et al. 2020) had a ‘high risk’ of bias (Fig. 2). Disagreements between reviewers occasionally occurred for domain 2, but consensus was always reached without the participation of the third reviewer.Fig. 2 Cochrane risk of bias tool-2 summary
Study design and population characteristics
The main characteristics of the participants and the interventions are shown in Table 1. The randomised pooled population obtained from the reviewed studies reached a total of 656 participants with a mean EDSS score of 4.22 (95%CI 4.15–4.30). The mean age was 45.12 (95%CI 44.66–45.59), and 65.57% of the population were female. All studies involved patients with relapsing–remitting type, except for three studies which did not specify the phenotype of multiple sclerosis (Robinson et al. 2015; Kalron et al. 2016; Pagliari et al. 2021). Furthermore, eight studies (Lozano-Quilis et al. 2014; Brichetto et al. 2015; Hoang et al. 2016; Munari et al. 2020; Tollar et al. 2020; Yazgan et al. 2020; Molhemi et al. 2021, 2022) involved participants with any type of multiple sclerosis (relapsing–remitting, secondary progressive, and primary progressive) without subgroup analysis.Table 1 Characteristic of studies included in the systematic review
Study/country MS phenotype/EDSS (mean; SD) Recruited/analysed (n) % Sex/age (mean ± SD) Experimental intervention Control group intervention Retention rate (%) Dropout rate (%) Reason for dropouts (EG/CG) Adverse events
Brichetto et al. (2015)
Italy
19 RRMS
9 SPMS
4 PPMS
EDSS = 3.7 ± 1.2
EG: 16/16
CG: 16/16
F: 28.13%
M: 71.88%
50.5 ± 11.6
12 sessions (60 min and 3 s/w, 4 weeks)
Exergaming through Nintendo Wii Fit Balance Board, plus balance exercises in Balance Master Neurocom
12 sessions (60 min and 3 s/w, 4 weeks)
Conventional balance training
100% (32/32) DOEG: 0% (0/16)
DOCG: 0% (0/16)
–- NR
Calabrò et al. (2017)
Italy
RRMS
EDSS = 4.56
EG: 20/20
CG: 20/20
F: 62.5%
M: 37.5%
42.5
40 sessions (5 s/w, 8 weeks)
Standard physical treatment (5 min of warning up, 5 min of strengthening, 20 min of postural control exercises) + 40 min of Lokomat + VR (avoid obstacles or catch objects on the trail)
40 sessions (5 s/w, 8 weeks)
Standard physical treatment (5 min of warning up, 5 min of strengthening, 20 min of postural control exercises) + 40 min of Lokomat
100% (40/40) DOEG: 0% (0/20)
DOCG: 0% (0/20)
–– No adverse or harmful events during the intervention
Hoang et al. (2016)
Australia
RRMS: 26
SPMS: 12
PPMS: 10
Unknown: 2
EDSS = 4.15 ± 1.3
EG: 28/23
CG: 22/21
F: 76%
M: 24%
52.4 ± 11.75
24 sessions (30 min; 2 s/w, 12 weeks)
Exergames (Stepmania and Choice stepping reaction time; Home step training system.)
24 sessions (30 min; 2 s/w, 12 weeks) Conventional balance training + stretching + strength exercises 88% (44/50) DOEG: 17.9% (5/28)
DOCG: 4.5% (1/22)
Discontinued intervention due to personal circumstances (EG), relapse (EG), health problems during reassessment not related to MS (CG) No adverse or harmful events during the intervention
Kalron et al. (2016)
Israel
EDSS = 4.1 ± 1.3 EG: 16/15
CG: 16/15
F: 63.33%
M: 36.67%
45.2 ± 11.6
12 sessions (30 min; 2 s/w, 6 weeks)
Immersive virtual reality system CAREN
12 sessions (30 min; 2 s/w, 6 weeks)
Conventional balance training 10 min of stretching + 20 min of training (static postural control, weight shifting and perturbation exercises)
93.75%
(30/32)
DOEG: 6.3% (1/16)
DOCG: 6.3% (1/16)
EG/CG: Difficulties in arrival to the MS centre No adverse or harmful events during the intervention
Khalil et al. (2019)
Jordan
RRMS: 40
EDSS = 3 ± 1.25
EG: 20/16
CG: 20/16
F: 68.75%
M: 31.25%
37.38 ± 10.87
18 sessions (3 s/w, 6 weeks)
Exergame through Wii Fit and Microsoft Kinect sensor allows to interact with six VR scenarios
18 sessions (3 s/w, 6 weeks)
Home-based conventional balance training
80% (32/40) DOEG: 20% (4/20)
DOCG: 20% (4/20)
EG: Lack of family support, lack of outcome expectation, need to travel long distance,
CG: not provided reason, lack of time and motivation
No adverse or harmful events during the intervention
Lozano-Quilis et al. (2014)
Spain
RRMS
SPMS
EDSS = NR
EG: 6/6
CG: 6/5
F: 58.33%
M: 41.67%
44.82 ± 10
10 sessions (45 standard rehabilitation + 15 min of virtual reality training; 1 s/w, 10 weeks)
RemoviEMVR system
10 sessions (60 min; 1 s/w, 10 weeks)
Conventional balance and gait training
91.67% (11/12) DOEG: 0% (0/6)
DOCG: 16.7% (1/6)
NR No adverse or harmful events during the intervention
Molhemi et al. (2021)
Iran
RRMS: 30
SPMS: 9
EDSS: 4.8
EG: 19/19
CG: 20/20
F: 61.54%
M: 38.46%
39.2 ± 8.4
18 sessions (35 min; 3 s/w for 6 weeks)
Exergame with Microsoft Kinect
18 sessions (35 min; 3 s/w for 6 weeks)
Conventional balance training
82.05% (32/39) DOEG: 15.8% (3/19)
DOCG: 20% (4/20)
EG/CG (During intervention): Difficulties in arrival to the research centre, work schedules problems and transport problems, fall data
EG: illness and exacerbation of symptoms
CG: interference of treatment time with patient’s work hours and moving to another city
No adverse event during intervention
Molhemi et al. (2022)
Iran
RRMS: 27
SPMS: 9
EDSS: 4.8
EG:18/18
CG: 18/18
F: 58.33%
M: 41.67%
39.2
18 sessions (35 min; 3 s/w for 6 weeks)
Exergames with Microsoft Kinect
18 sessions (35 min; 3 s/w for 6 weeks)
Conventional balance training
86.11% (31/36) DOEG: % (2/18)
DOCG: 22.2% (3/18)
EG: Transport problems and exacerbation symptoms
CG: Lack of interest, work schedule and personal issue
NR
Munari et al. (2020)
Italy
RRMS: 3
SPMS: 14
EDSS: 5.2
EG: 8/8
CG: 9/7
F: 58.82%
M: 41.17%
57 ± 8.04
12 sessions (40 min; 2 s/w for 6 weeks):
Robot-assisted gait training GE–O system + VR environment
12 sessions (40 min; 2 s/w for 6 weeks):
Robot-assisted gait training GE–O system
88.23% (15/17) DOEG: 0% (0/8)
DOCG: 22.2% (2/15)
CG: Difficulties in arrival to the study place No adverse or harmful events during the intervention
Ozkul et al. (2020)
Turkey
RRMS
EDSS = 1.5
EG: 17/13
G1: 17/13
G2: 17/13
F: 58.33%
M: 41.67%
32.3
16 sessions (60 min; 2 s/w, 8 weeks)
30 min of Pilates + 10 min of rest + 20 min of immersive virtual reality (HMD). Two supervised exergames in standing position wearing a harness (Football game and Guillotine game)
G1: 16 sessions (60 min; 2 s/w, 8 weeks)
30 min of Pilates + 10 min of rest + 20 min of conventional balance training
G2: 16 sessions (15–20 min; 2 s/w, 8 weeks) Jacobson's progressive relaxation exercise
76.4% (26/34) DOEG: 23.5% (4/17)
DOCG: 23.7% (4/17)
EG/CG: Work intensity No adverse or harmful events during the intervention
Peruzzi et al. (2016)
Italy
RRMS
EDSS = 3.8 ± 0.9
EG: 16/14
CG:15/11
F: 60%
M: 40%
42.8 ± 11.1
18 sessions (45 min; 3 s/w, 6 weeks): supervised treadmill walking 80% of the subject’s overground walking
speed. Each week speed increased a 10%. Last week the subject removed one or both hands from the handrails + Virtual tree-lined trail in which obstacles have to be passed (also train memory, attention and planning)
18 sessions (45 min; 3 s/w, 6 weeks): supervised treadmill walking 80% of the subject’s overground walking
speed. Each week speed increased a 10%. Last week the subject removed one or both hands from the handrails
77.41% (24/31) DOEG: 26.7% (4/15)
DOCG: 18.8% (3/16)
EG/CG: Personal issues No adverse or harmful events during the intervention
Pagliari et al. (2021)
Italy
EDSS = 4.7 EG: 30/35
CG: 30/35
F: 60%
M: 40%
50.28
30 sessions (45 min; 5 s/w, 6 weeks)
VRRS Khymeia telerehabilitation home-based kit + cognitive training
30 sessions (45 min; 5 s/w, 6 weeks)
Conventional balance training + cognitive training
85.71% (60/70) DOEG: 14.28% (5/35)
DOCG: 14.28% (5/35)
EG/CG: No compliance to intervention
EG: problem with internet connection and unrelated comorbidities
CG: personal difficulties, moving to new home and unable to come in for follow-up
NR
Robinson et al. (2015)
United Kingdom
Phenotypes NR
EDSS = 3.5
EG: 20/20
G1: 18/16
G2: 18/15
F: 67.86%
M: 32.14%
52 ± 5.8
8 sessions (40 min; 2 s/w, 4 weeks)
Exergames with Wii Fit
G1: 8 sessions (40 min; 2 s/w, 4 weeks)
Conventional balance training
G2: no intervention
89.3% (50/56) DOEG: 0% (0/20)
DOG1: 11.1% (2/18)
DOG2: 22.2% (4/18)
G2: Suspected MS remission, hospitalisation (not related to the study)
CG: family-matters
NR
Russo et al. (2018)
Italy
RRMS EDSS = 5 EG: 30/30
CG: 15/15
F: 57.78%
M: 42.22%
42 ± 7
54 sessions (60 min; 3 s/w, 18 weeks)
6 weeks of Lokomat-PRO sum to VR (2D) + 12 weeks of conventional balance training
54 sessions (60 min; 3 s/w, 18 weeks)
Conventional balance training
100% (45/45) DOEG: 0% (0/30)
DOCG: 0% (0/15)
– No adverse or harmful events during the intervention
Tollar et al. (2020)
Hungary
RRMS:42
PPMS: 26
EDSS = 5
EG: 14/14
G1: 14/14
G2: 14/14
G3: 14/14
G4: 12/12
F: 90%
M: 10%
47
25 sessions (60 min; 1–2 s/w, 5 weeks)
High- intensity exergaming training
25 sessions (60 min; 1–2 s/w, 5 weeks)
G1: high-intensity balance training
G2: Cycling
G3: Active proprioceptive neuromuscular facilitation (PNF)
G4: Standard care wait-listed control group
97.14% (68/70) DOEG: 0% (0/14)
DOG1: 0% (0/14)
DOG2:0% (0/14)
DOG3: 0% (0/14)
DOG4: 16.7% (2/12)
CG: Disease exacerbation and illness No adverse or harmful events during the intervention
Yazgan et al. (2020)
Turkey
RRMS: 33
SPMS: 2
PPMS: 1
Progressive relapsing: 6
EDSS = 4.02 ± 1.37
EG: 16/15
G1: 16/12
G2: 15/15
F: 82.61%
M: 17.39%
43.73 ± 9.36
16 sessions (60 min; 2 s/w, 8 weeks)
supervised Nintendo Wii Fit exergames in standing position
G1: 16 sessions (60 min; 2 s/w, 8 weeks) Collect
Apples, Outline, Paddle War, and Evaluation of Movement games
G2: waiting list group
89.4% (42/47) DOEG: 6.3% (1/16)
DOG1: 25% (4/16)
DOG2: 0% (0/15)
EG/CG: Personal problems
CG: transportation problems
No adverse or harmful events during the intervention
CG control group, DO dropout, DOCG dropouts in control group, DOEG dropouts in experimental group, DOG2 dropouts in the second comparator group, EDSS Expanded Disability Status Scale, EG experimental group, F female, G1 first control intervention, G2 second control intervention, G3 third control intervention, M male, min minutes, MS multiple sclerosis, n number of participants, NR no reported, PPMS primary-progressive multiple sclerosis, RRMS relapsing–remitting multiple sclerosis, SD standard deviation, SPMS secondary-progressive multiple sclerosis, s/w sessions per week
Concerning the immersion of the virtual reality systems, 14 studies employed non-immersive virtual reality as the main experimental intervention and four of them used the Wii Fit system (Brichetto et al. 2015; Robinson et al. 2015; Khalil et al. 2019; Yazgan et al. 2020). Only two trials used fully immersive virtual reality (Kalron et al. 2016; Ozkul et al. 2020).
Most studies compared the virtual reality intervention to improve balance or gait to conventional balance training (n = 13, 81.25%) (Lozano-Quilis et al. 2014; Brichetto et al. 2015; Robinson et al. 2015; Hoang et al. 2016; Kalron et al. 2016; Peruzzi et al. 2016; Calabrò et al. 2017; Russo et al. 2018; Khalil et al. 2019; Ozkul et al. 2020; Molhemi et al. 2021, 2022; Pagliari et al. 2021), followed by robotic-assisted gait training (n = 3, 18.75%) (Calabrò et al. 2017; Peruzzi et al. 2017; Munari et al. 2020). The lowest number of sessions performed was 8 (Robinson et al. 2015), while the highest was 54 (Russo et al. 2018). Most authors proposed a frequency of intervention of 2 times per week with a minimum time per session of 30 min (Hoang et al. 2016; Kalron et al. 2016) and a maximum of 85 min (Calabrò et al. 2017).
The mean number of dropout events for the experimental group was 1.61 cases and 1.88 for the comparator group. The highest number of dropouts in the virtual reality groups was registered by Hoang et al. (2016) and Pagliari et al. (2021). The reasons reported by the authors for dropout in both groups were: difficulties reaching the research centre, transportation problems, scheduling problems, moving to another city, refusal to participate, personal or familial issues, lack of motivation or time, loss of data due to administrative problems, exacerbation of symptoms, disease relapse, work intensity, and illness/medical reasons/hospitalisation not related to multiple sclerosis. Three studies did not report any dropout events during the intervention or follow-up period (Brichetto et al. 2015; Calabrò et al. 2017; Russo et al. 2018).
Meta-analysis of proportions
A total of 18 arms (k) from 16 studies were included in the proportion and binary meta-analysis, since one of the randomised control trials presented three study groups (Tollar et al. 2020). From a total of 638 participants, 63 cases of dropouts were reported. The forest plot showed an overall pooled dropout rate of 6.6% (95%CI 3.2–12.9%) without heterogeneity between studies (tau2 = 1.18, Q = 10.07, df = 17, I2 = 0%, 95%CI 0–50%, p = 0.90) (Fig. 3). The dropout rate for the virtual reality-based interventions was 5.7% (95%CI 2.3–13.6%) against the 9.7% (95%CI 5.7–16.02%) in the comparator groups (Supplemental Material 4). Conversely, the retention rate for the virtual reality and comparator groups was 94.3% and 90.3%, respectively. None of the prediction intervals calculated across the meta-analysis suggested that the intervention would achieve the same effects in the future.Fig. 3 Forest plot of dropout rate for all groups of studies
Binary meta-analysis (OR)
The main results showed a slightly lower probability that dropouts occurred in the virtual reality-based interventions than in the comparator groups, but a significant difference was not obtained (OR = 0.89, 95%CI 0.64–1.24, p = 0.46). No significant heterogeneity between studies was found (tau2 = 0, Q = 5.6, df = 17, I2 = 0%, 95%CI 0–50%, p = 0.99) (Fig. 4). The prediction interval confirmed that the same effects would not happen in the future studies. A subgroup meta-analysis according to the immersion level of the virtual reality was not carried out because the number of studies using immersive systems did not reach the minimum required (3 studies).Fig. 4 Forest plot of odds ratio comparing attrition from virtual reality intervention and other comparator interventions in people with multiple sclerosis to improve balance or gait
A post hoc sensitive analysis using the L’Abbé and Baujat plots and influence graphs (Supplemental Material 5) showed that none of the included studies influenced heterogeneity or bias for the pooled effect size, and no outliers were found. Additionally, no small study effects or publication bias was shown in the contour-enhanced funnel plot (Fig. 5), the Harbord test (p = 0.37), or the Egger bias test (p = 0.34).Fig. 5 Contour-enhanced funnel plot
Meta-regression
The meta-regression revealed that the type of intervention, number, frequency, and duration of session, weeks of intervention, EDSS score, multiple sclerosis phenotype, sex, and methodological quality could not be related to the dropout events. A detailed description of the analysis is shown in Table 2.Table 2 Meta-regression analysis
Predictors SE t value 95%CI p value
Type of intervention 0.45 − 0.30 − 1.09, 0.82 0.76
Number of sessions 0.02 1.01 − 0.02, 0.06 0.33
Duration of sessions 0.15 − 1.24 − 0.05, 0.013 0.23
Frequency of sessions 0.15 0.54 − 0.23, 0.39 0.59
Weeks of intervention 0.07 0.89 − 0.08, 0.21 0.38
EDSS score 0.15 − 0.42 − 0.39, 0.26 0.68
RRMS 0.38 0.28 − 0.70, 0.92 0.78
PPMS 0.52 0.40 − 0.91, 1.32 0.69
SPMS 0.43 − 0.20 − 1.01, 0.84 0.84
Female gender 0.16 0.02 − 0.37, 0.03 0.86
Male gender 0.16 0.16 − 0.03, 0.04 0.87
Age 0.03 0.27 − 0.046, 0.06 0.79
PEDro score 0.14 1.97 − 0.02, 0.57 0.07
95%CI 95% confidence interval, PPMS primary progressive multiple sclerosis, RRMS remittent–recurrent multiple sclerosis, SPMS secondary progressive multiple sclerosis
Discussion
A total of 16 randomised control trials reporting dropouts were meta-analysed to calculate the overall pooled dropout rate of virtual reality-based interventions for the improvement of balance and gait in patients with multiple sclerosis. The main clinical implication of the results of our study was that the virtual reality-based training for balance and gait in people with multiple sclerosis was highly accepted with a low dropout rate and high adherence during the study period. Torous et al. (2020) suggested that the retention in research contexts could change when experimental approaches are translated into a clinical setting. This could be especially important for long rehabilitation programmes in chronic conditions. A recent study (Hortobágyi et al. 2022) reported a high adherence rate to a two-year maintenance programme including exergaming in people with multiple sclerosis; however, the sample size was very small, and more research about long-term adherence to virtual reality rehabilitation in this population is needed.
Adherence is one of the main conflicts faced in rehabilitation; the therapeutic approach of multiple sclerosis is not an exception. As a result, looking for rehabilitation therapies that achieve higher participant compliance to treatment is vital (Arafah et al. 2017). If correct adherence is not achieved, the effectiveness of the rehabilitation might be limited and incur additional healthcare costs (Jack et al. 2010; Room et al. 2021). Accordingly, the previous literature has proposed that virtual reality strategies presented higher adherence in patients with neurological disorders (Asadzadeh et al. 2021; Dalmazane et al. 2021). Nonetheless, our results suggested lower dropout rates in virtual reality-based interventions, which may be confirmed with larger sample sizes. This idea is supported by the prediction intervals, which stated that our findings could change with future trials. The recent systematic review of Bevens et al. (2021) analysed the dropout rate in people with multiple sclerosis who received digital health interventions, showing no significant differences between experimental and control comparators. Therefore, we can consider that the adherence to virtual reality or other technological approaches were at least similar to other interventions.
During the screening process, several studies were discarded because dropouts were not mentioned. Despite CONSORT guidelines stating the need to report complete data, many authors do not know how to handle dropouts (Bell et al. 2013). To address this issue, it is necessary to standardise the way in which the reason and number of dropouts are described, for example, using the CONSORT flowchart of the study period. Also, further details of dropouts could help to make decisions regarding which interventions to offer to whom (Wright et al. 2021).
Our meta-regression data showed that the type of intervention, number, duration, and frequency of sessions, weeks of intervention, disability score, phenotype, sex, and methodological quality were not predictors of dropouts. Although it seems that a higher frequency of sessions could favour participant dropouts, no significant results were found. Similar results were obtained by Dennett et al. (2020), who stated that there was no relationship between the frequency of exercise-based sessions and dropouts, but duration modified the likelihood of dropouts. Although our protocol included the analysis according to the level of immersion, fully immersive and semi-immersive virtual reality was excluded from the moderator analysis because of the limited number of studies included. Therefore, we suggest to provide a specific dropout rate analysis when the proportion of studies using immersive virtual reality rises, since higher immersion and presence levels are expected to achieve a higher treatment adherence (Rose et al. 2018; Dębska et al. 2019). Additionally, future studies should evaluate enjoyment and motivation with specific measurement scales, allowing researchers to understand whether motivation or enjoyment during the intervention is predictors of dropout or adherence to treatment in the targeted population.
According to the literature (Grover et al. 2021), adverse events due to treatment are considered one of the main causes of dropouts. Nonetheless, we were unable to analyse them as a moderator of dropout rate, since none of the studies included reported the undesired effects of the virtual reality intervention. Two possible explanations behind the low number of studies describing adverse events or side effects because of the intervention were considered: the first is that participants did not actually have adverse effects due to the virtual reality-based intervention, and the second is that the authors decided not to report them. The latter idea is supported by Phillips et al. (2019) and Pitrou et al. (2009), who addressed methodological weaknesses in reporting adverse events in randomised control trials, leading to a misinterpretation of intervention safety.
Strength and limitations
This is the first meta-analysis to calculate the overall pooled dropout rate for innovative virtual reality-based interventions in patients with multiple sclerosis. The findings of this review could help future randomised control trials to calculate their sample size to avoid dropout bias. Furthermore, no heterogeneity between the included studies was found in the analysis. The sensitivity analysis did not report any randomised control trial as an outlier that could strongly influence the overall size effect. Moreover, the funnel plot did not show any publication bias.
The main limitation of this review was the small sample size that the randomised control trials included, so a larger overall sample size would make our results more reliable. Another issue was that many studies did not report detailed reasons for dropouts. Furthermore, adverse events were not reported, so it was not possible to determine whether they could be moderators for dropout rate.
Conclusion
The overall pooled dropout rate of randomised control trials on virtual reality for balance or gait training in people with multiple sclerosis was 6.6%. Our analysis reported no differences in dropout rate for participants who received virtual reality-based interventions versus other comparators; however, the lower dropout rate in the virtual reality group could indicate that the inclusion of larger sample sizes would show a significant difference in favour of the virtual reality group. The number, duration, frequency, and weeks of sessions, sex, age, phenotype, disability, and methodological quality were not determined to be moderators of dropouts. Adverse events were not reported by the studies included, making it impossible to analyse their influence as moderators.
Future randomised control trials should standardise the description of dropout causes and adverse effects of the rehabilitation treatments. Furthermore, the advantages of virtual reality, such as motivation and enjoyment, should be systematically assessed in clinical trials to determine whether these outcomes are indeed moderators of dropout and adherence.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (PDF 846 kb)
Supplementary file2 (DOCX 37 kb)
Authors contribution
MJC-H and CG-M were involved in conceptualisation and writing, review and editing; CG-M, MJC-H contributed to methodology; CG-M were involved in software and formal analysis; MJC-H, CG-M, MDC-V, RM-V, JAM-M and DL-A contributed to writing—original draft preparation; MDC-V and R-MV were involved in visualisation; MDC-V, JAM-M and DL-A contributed to supervision; MJC-H and CG-M contributed equally to this work. All authors have read and agreed to the published version of the manuscript.
Data availability
Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
Declarations
Conflict of interest
The authors declare no conflicts of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9735030 | NO-CC CODE | 2022-12-14 23:28:32 | no | Virtual Real. 2022 Dec 7;:1-17 | utf-8 | Virtual Real | 2,022 | 10.1007/s10055-022-00733-4 | oa_other |
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S.i. : New Trends on Immersive Healthcare
Dropout rate in randomised controlled trials of balance and gait rehabilitation in multiple sclerosis: is it expected to be different for virtual reality-based interventions? A systematic review with meta-analysis and meta-regression
http://orcid.org/0000-0002-4217-6827
Casuso-Holgado María Jesús 15
http://orcid.org/0000-0003-2621-2098
García-Muñoz Cristina [email protected]
25
http://orcid.org/0000-0002-1664-3647
Martín-Valero Rocío 3
http://orcid.org/0000-0003-2441-5342
Lucena-Anton David 2
http://orcid.org/0000-0002-6465-982X
Moral-Munoz Jose A. 24
http://orcid.org/0000-0002-9514-8811
Cortés-Vega María-Dolores 1
1 grid.9224.d 0000 0001 2168 1229 Department of Physiotherapy, University of Seville, Seville, Spain
2 grid.7759.c 0000000103580096 Department of Nursing and Physiotherapy, University of Cadiz, Cadiz, Spain
3 grid.10215.37 0000 0001 2298 7828 Department of Physiotherapy, University of Malaga, Malaga, Spain
4 grid.7759.c 0000000103580096 Institute of Research and Innovation in Biomedical Sciences of the Province of Cadiz (INiBICA), University of Cadiz, Cadiz, Spain
5 grid.9224.d 0000 0001 2168 1229 UMSS Research Group, Universidad of Seville, Seville, Spain
7 12 2022
117
22 3 2022
29 11 2022
© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
To assess and meta-analyse the pooled dropout rate from the randomised control trilas that use virtual reality for balance or gait rehabilitation in people with multiple sclerosis. A systematic review of randomised control trials with meta-analysis and meta-regressions was performed. A search was conducted in PubMed, Scopus, Web of Science, the Physiotherapy Evidence Database, the Cochrane Database, CINHAL, LILACS, ScienceDirect, and ProQuest. It was last updated in July 2022. After the selection of studies, a quality appraisal was carried out using the PEDro Scale and the Revised Cochrane risk-of-bias tool for randomised trials. A descriptive analysis of main characteristics and dropout information was performed. An overall proportion meta-analysis calculated the pooled dropout rate. Odds ratio meta-analysis compared the dropout likelihood between interventions. The meta-regression evaluated the influence of moderators related to dropout. Sixteen studies with 656 participants were included. The overall pooled dropout rate was 6.6% and 5.7% for virtual reality and 9.7% in control groups. The odds ratio (0.89, p = 0.46) indicated no differences in the probability of dropouts between the interventions. The number, duration, frequency, and weeks of sessions, intervention, sex, multiple sclerosis phenotype, Expanded Disability Status Scale score, and PEDro score were not moderators (p > 0.05). Adverse events were not reported and could not be analysed as moderators. Dropouts across the virtual reality and control comparators were similar without significant differences. Nonetheless, there is a slight trend that could favour virtual reality. Standardisation in reporting dropouts and adverse events is recommended for future trials.
PROSPERO database, registration number ID
CRD42021284989.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10055-022-00733-4.
Keywords
Dropout rate
Multiple sclerosis
Adherence
Virtual reality
Attrition
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pmcIntroduction
Different types of virtual reality technology (e.g. non-immersive, semi-immersive, or fully immersive) have emerged as an useful tool in neurorehabilitation with promising results for physical and cognitive rehabilitation (Voinescu et al. 2021). In this way, virtual reality-based interventions have been enhanced as a technological solution for telerehabilitation at the time of the COVID-19 pandemic (Matamala-Gomez et al. 2021). Furthermore, the previous literature has proposed that virtual reality strategies present higher adherence in patients with neurological disorders (Asadzadeh et al. 2021; Dalmazane et al. 2021). Multitask training, patient motivation, safety, and the low cost of commercial devices are some of the benefits of using virtual reality for neurological rehabilitation (Forsberg et al. 2015; Gustavsson et al. 2021; Moan et al. 2021). Nonetheless, some undesired effects (e.g. headache, sickness, or nausea) (Massetti et al. 2018), as well as the difficulty of transferring the complex skills trained in virtual environments to the real world and the lack of ecological validity in a neurologically impaired population (Levac et al. 2019), were reported. Specifically, for balance training, the time of latency, the underestimation of perceived distances, and the dependence on specific systems (e.g. balance board) and virtual contexts were proposed as potential weaknesses of virtual reality environments (Morel et al. 2015).
Multiple sclerosis is a global neurodegenerative disease affecting approximately three million people in the world (Tafti et al. 2022). Balance disorders, gait impairments, and fatigue are the main symptoms in patients with multiple sclerosis that obtain positive effects with physical therapy intervention (Amedoro et al. 2020; Abou et al. 2022). Particularly, virtual reality-based physical rehabilitation showed benefits for balance and gait training (Casuso-Holgado et al. 2018; Nascimento et al. 2021); however, fatigue is a significant barrier to participation in physical activity, which influences the participants’ adherence (Moore et al. 2022). A recent systematic review has summarised dropout data from randomised control clinical trials about exercise interventions in people with multiple sclerosis, concluding that mean age, the proportion of females, and intervention duration were moderators inversely associated with adherence (Dennett et al. 2020). Therefore, these findings could impact the sample size calculation, promoting an under- or overestimation. Furthermore, this could influence the differential dropout rate, which is how the degree of dropout differs between the intervention and comparator conditions after randomisation (Crutzen et al. 2015). It might affect the power of research and could present a risk of bias for randomised control clinical trials (Cooper et al. 2018). In view of this background, setting accurate expected dropout rates in virtual reality studies for rehabilitation in multiple sclerosis could help future trials to avoid problems in their internal or external validity. In addition, the identification of factors specifically associated with dropout in virtual reality trials could help clinicians when translating research into practice.
As far as we are concerned, no previous systematic reviews were found reporting dropout in virtual reality interventions for balance and gait rehabilitation in this population. Thus, the present systematic review and meta-analysis aimed to: (1) systematically assess and meta-analyse the overall pooled dropout rate of randomised controlled trials using virtual reality as an intervention for balance or gait training in people with multiple sclerosis in both absolute and comparative terms; (2) analyse whether any participant or intervention factors are related to dropout; and (3) identify adverse events that could be the reason for dropouts.
Methods
Data sources and search strategy
This systematic review was carried out following the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al. 2009). The review protocol was registered in the PROSPERO database (Registration number: CRD42021284989).
Two independent reviewers (M.J.C.-H., C.G.-M.) conducted an electronic search in MEDLINE (PubMed), Scopus, Web of Science (WOS), the Physiotherapy Evidence Database (PEDro), the Cochrane Database of Systematic Reviews (CDSR), CINHAL, LILACS, ScienceDirect, and ProQuest. The search was performed between July and November 2021. Neither language nor date filters were applied in the different databases. Key terms concerning intervention (‘virtual reality’, ‘game’, ‘gaming’, ‘exergaming’, and ‘interactive’), balance (‘balance’ or ‘postural control’), gait (‘gait’, ‘walking’, and ‘ambulation’), and ‘multiple sclerosis’ were combined as search terms in the strategies. The search strategy is shown in detail in Supplemental Material 1.
Research question and study selection
The participants, interventions, comparisons, outcomes, and study design (PICOS) model was considered to set the following research questions: what dropout data are reported during the intervention and follow-up period by randomised control clinical trials conducting virtual reality intervention to improve balance or gait in multiple sclerosis and what are the possible moderators affecting dropout in these studies?
Participants included in the review were female or male, aged between 18 and 65 years old, with any diagnosis of multiple sclerosis phenotype meeting the revised McDonald criteria (Thompson et al. 2018). Walking ability was preserved according to the Expanded Disability Status Scale (EDSS) score (EDSS ≤ 6). Included interventions involved any type of virtual reality systems aimed at improving balance or gait compared to other interventions based on physical activity with or without external aid use. Furthermore, studies that reported dropout event information were included.
Data extraction and quality assessment
First, two independent reviewers (C.G.-M. and M.J.C.-H.) identified potential articles in databases to be included in the systematic review through the title and abstract information. Next, duplicates were removed, and an exhaustive analysis of articles was carried out based on their full-text reading. This step was particularly focussed on the selection criteria assessment, ensuring that the inclusion criteria were met before selecting suitable studies. In the case of disagreement, a third reviewer (M.-D.C.-V.) was consulted to decide on the inclusion of the documents.
Once articles were selected, the quality assessment was conducted using the PEDro scale (Maher et al. 2003) and the Revised Cochrane risk-of-bias tool for randomised trials (RoB-2) (Higgins et al. 2019). PEDro is a reliable tool of 11 items that evaluates the inner validity of a clinical trial. If studies score above 6 points, they are classified as level I evidence (6–8: good; 8–10: excellent). If the score is below 5, they are classified as level II (4–5: deficient; < 4: poor). ROB-2 allows the evaluation of bias in randomised control trials, comprising five domains (bias arising from the randomisation process, due to deviations from the intended interventions, to missing outcome data, in the measurement of the outcome, and in the selection of the reported result) that are qualified as a low or high risk of bias with some concerns (Sterne et al. 2019).
Next, reviewers recorded the data for qualitative and quantitative synthesis. The extracted data were country, multiple sclerosis phenotype and disability status, female and male percentages, age, experimental and comparator group intervention characteristics, number of participants recruited and analysed, retention rate, dropout rates (for the experimental and control groups), reasons for dropout (in each group), and adverse events. Disagreements in data were solved by consensus with a third reviewer. Information provided by the included studies allowed us to calculate dropout rates in all cases, so no corresponding authors were contacted.
Data analysis
Dropout rate was calculated as the number of participants who did not complete the intervention and follow-up period divided by the total number of participants that underwent the randomisation process. Moreover, retention rate was the total number of participants that concluded the intervention, showing the adherence rate to treatment. For those studies that included more than two groups of intervention, comparison between groups was analysed separately two by two.
To conduct the meta-analysis, the R Studio software (version 4.0.0) and its packages meta, metafor, and dmetar were used (Viechtbauer 2010; Balduzzi et al. 2019; Harrer et al. 2021). The proportion meta-analysis was performed through the metaprop function to determine the estimated dropout rate in virtual reality intervention, the control comparator, and all arms. Proportions were transformed using the logit transformation (Schwarzer et al. 2019).
A binary meta-analysis based on odds ratios (ORs) was conducted to examine whether the probability of dropouts is higher in the virtual reality or in the comparator interventions. To assess the effect measure in binary outcomes, the OR with a 95% confidence interval (95%CI) was calculated, and the inverse variance method was used to adjust pooling estimations to sparse data (considering that dropouts are a rare event). Likewise, the Hartung–Knapp adjustment for a random effects model was implemented. Focussing on ORs, if the value is 1, there are no differences in dropouts between the experimental and comparator groups. In contrast, if the OR is greater than 1, a higher dropout rate was registered for the experimental group. The restricted maximum-likelihood estimator for tau2 was selected to estimate the between-study variance (Viechtbauer 2005). As some studies could present zero events in the experimental and/or comparator arm, a 0.5 continuity correction was added to all meta-analyses, as suggested by Gart and Zweifel (1967).
Heterogeneity between studies was assessed through I2, tau2, and Cochrane’s Q (p < 0.05 indicates heterogeneity). When I2 presents a value above 50%, it means that large heterogeneity is found across studies (Higgins et al. 2021). A random effects model was employed considering the possible degree of heterogeneity between the included studies.
Forest plots were used to show the outcomes of proportions and binary meta-analyses. The prediction interval was added as a red line to the forest plot to provide a measure of reliability of future treatment effects in new studies (Nagashima et al. 2019). Depending on the level of immersion of the subject within the virtual environment, virtual reality was classified as non-immersive, semi-immersive, and fully immersive for subgroup analysis.
A sensitivity analysis was carried out to assess the influence of studies on the overall binary meta-analysis results. The influence was explored to detect the presence of outlier data and whether there were studies that contributed to heterogeneity or bias pooled results. A Baujat plot, a L’Abbé plot, and influence graphs were created to represent influential cases in meta-analysis. The influence graphs showed the studies that significantly influenced the pooled effect size in red. In addition, an exploratory graphical analysis of data was performed to examine whether there is a clear trend of effect size related to independent variables.
Meta-regression was conducted to evaluate possible associations between participants or study characteristics which could vary in the presence of dropout events. Studies with no available data were excluded from the meta-regression analysis. Moreover, to run the meta-regression, at least three studies with the predictor were needed. The analysed moderators were interventions, number, duration, frequency and weeks of sessions, EDSS score, multiple sclerosis phenotype, and sex.
Publication bias and small study effects were evaluated through a contour-enhanced funnel plot adjusted by the Duval and Tweedie trim and fill method (Shi and Lin 2020). Asymmetry in the funnel plot indicated the effect of small studies in the pooled results. To confirm the absence of asymmetry, a p value greater than 0.05 must be reached in the Harbord’s test (Harbord et al. 2006) and the Egger bias test (Egger et al. 1997).
Results
Study selection and methodological quality assessment
In total, 7024 articles were identified through the initial database search based on titles and abstracts. After that, duplicates were removed, obtaining 5995 articles. Once the studies underwent the screening and eligibility steps, 16 randomised control trials were included for the qualitative synthesis and quantitative analysis. There was no disagreement between reviewers in the study selection process. Figure 1 showed the PRISMA flowchart detailing the selection procedure. Excluded studies and their reasons are detailed in Supplemental Material 2.Fig. 1 Flow diagram of trials selection based on PRISMA 2020 guidelines. *Consider, if feasible to do so, reporting the number of records identified from each database or register searched (rather than the total number across all databases/registers). **If automation tools were used, indicate how many records were excluded by a human and how many were excluded by automation tools. From: Page et al. (2021). For more information, visit: http://www.prisma-statement.org/
Regarding the quality assessments, the PEDro scale results are shown in Supplemental Material 3. PEDro scores were reported from the included studies: thirteen with level I evidence (Lozano-Quilis et al. 2014; Hoang et al. 2016; Kalron et al. 2016; Calabrò et al. 2017; Peruzzi et al. 2017; Russo et al. 2018; Khalil et al. 2019; Munari et al. 2020; Ozkul et al. 2020; Tollar et al. 2020; Molhemi et al. 2021, 2022; Pagliari et al. 2021) and three with level II (Brichetto et al. 2015; Robinson et al. 2015; Yazgan et al. 2020). Most studies were single blinded, with the assessor being blinded to participant allocation. In addition, the ROB-2 overall score reported that most studies presented some concerns, but only three studies (Robinson et al. 2015; Ozkul et al. 2020; Yazgan et al. 2020) had a ‘high risk’ of bias (Fig. 2). Disagreements between reviewers occasionally occurred for domain 2, but consensus was always reached without the participation of the third reviewer.Fig. 2 Cochrane risk of bias tool-2 summary
Study design and population characteristics
The main characteristics of the participants and the interventions are shown in Table 1. The randomised pooled population obtained from the reviewed studies reached a total of 656 participants with a mean EDSS score of 4.22 (95%CI 4.15–4.30). The mean age was 45.12 (95%CI 44.66–45.59), and 65.57% of the population were female. All studies involved patients with relapsing–remitting type, except for three studies which did not specify the phenotype of multiple sclerosis (Robinson et al. 2015; Kalron et al. 2016; Pagliari et al. 2021). Furthermore, eight studies (Lozano-Quilis et al. 2014; Brichetto et al. 2015; Hoang et al. 2016; Munari et al. 2020; Tollar et al. 2020; Yazgan et al. 2020; Molhemi et al. 2021, 2022) involved participants with any type of multiple sclerosis (relapsing–remitting, secondary progressive, and primary progressive) without subgroup analysis.Table 1 Characteristic of studies included in the systematic review
Study/country MS phenotype/EDSS (mean; SD) Recruited/analysed (n) % Sex/age (mean ± SD) Experimental intervention Control group intervention Retention rate (%) Dropout rate (%) Reason for dropouts (EG/CG) Adverse events
Brichetto et al. (2015)
Italy
19 RRMS
9 SPMS
4 PPMS
EDSS = 3.7 ± 1.2
EG: 16/16
CG: 16/16
F: 28.13%
M: 71.88%
50.5 ± 11.6
12 sessions (60 min and 3 s/w, 4 weeks)
Exergaming through Nintendo Wii Fit Balance Board, plus balance exercises in Balance Master Neurocom
12 sessions (60 min and 3 s/w, 4 weeks)
Conventional balance training
100% (32/32) DOEG: 0% (0/16)
DOCG: 0% (0/16)
–- NR
Calabrò et al. (2017)
Italy
RRMS
EDSS = 4.56
EG: 20/20
CG: 20/20
F: 62.5%
M: 37.5%
42.5
40 sessions (5 s/w, 8 weeks)
Standard physical treatment (5 min of warning up, 5 min of strengthening, 20 min of postural control exercises) + 40 min of Lokomat + VR (avoid obstacles or catch objects on the trail)
40 sessions (5 s/w, 8 weeks)
Standard physical treatment (5 min of warning up, 5 min of strengthening, 20 min of postural control exercises) + 40 min of Lokomat
100% (40/40) DOEG: 0% (0/20)
DOCG: 0% (0/20)
–– No adverse or harmful events during the intervention
Hoang et al. (2016)
Australia
RRMS: 26
SPMS: 12
PPMS: 10
Unknown: 2
EDSS = 4.15 ± 1.3
EG: 28/23
CG: 22/21
F: 76%
M: 24%
52.4 ± 11.75
24 sessions (30 min; 2 s/w, 12 weeks)
Exergames (Stepmania and Choice stepping reaction time; Home step training system.)
24 sessions (30 min; 2 s/w, 12 weeks) Conventional balance training + stretching + strength exercises 88% (44/50) DOEG: 17.9% (5/28)
DOCG: 4.5% (1/22)
Discontinued intervention due to personal circumstances (EG), relapse (EG), health problems during reassessment not related to MS (CG) No adverse or harmful events during the intervention
Kalron et al. (2016)
Israel
EDSS = 4.1 ± 1.3 EG: 16/15
CG: 16/15
F: 63.33%
M: 36.67%
45.2 ± 11.6
12 sessions (30 min; 2 s/w, 6 weeks)
Immersive virtual reality system CAREN
12 sessions (30 min; 2 s/w, 6 weeks)
Conventional balance training 10 min of stretching + 20 min of training (static postural control, weight shifting and perturbation exercises)
93.75%
(30/32)
DOEG: 6.3% (1/16)
DOCG: 6.3% (1/16)
EG/CG: Difficulties in arrival to the MS centre No adverse or harmful events during the intervention
Khalil et al. (2019)
Jordan
RRMS: 40
EDSS = 3 ± 1.25
EG: 20/16
CG: 20/16
F: 68.75%
M: 31.25%
37.38 ± 10.87
18 sessions (3 s/w, 6 weeks)
Exergame through Wii Fit and Microsoft Kinect sensor allows to interact with six VR scenarios
18 sessions (3 s/w, 6 weeks)
Home-based conventional balance training
80% (32/40) DOEG: 20% (4/20)
DOCG: 20% (4/20)
EG: Lack of family support, lack of outcome expectation, need to travel long distance,
CG: not provided reason, lack of time and motivation
No adverse or harmful events during the intervention
Lozano-Quilis et al. (2014)
Spain
RRMS
SPMS
EDSS = NR
EG: 6/6
CG: 6/5
F: 58.33%
M: 41.67%
44.82 ± 10
10 sessions (45 standard rehabilitation + 15 min of virtual reality training; 1 s/w, 10 weeks)
RemoviEMVR system
10 sessions (60 min; 1 s/w, 10 weeks)
Conventional balance and gait training
91.67% (11/12) DOEG: 0% (0/6)
DOCG: 16.7% (1/6)
NR No adverse or harmful events during the intervention
Molhemi et al. (2021)
Iran
RRMS: 30
SPMS: 9
EDSS: 4.8
EG: 19/19
CG: 20/20
F: 61.54%
M: 38.46%
39.2 ± 8.4
18 sessions (35 min; 3 s/w for 6 weeks)
Exergame with Microsoft Kinect
18 sessions (35 min; 3 s/w for 6 weeks)
Conventional balance training
82.05% (32/39) DOEG: 15.8% (3/19)
DOCG: 20% (4/20)
EG/CG (During intervention): Difficulties in arrival to the research centre, work schedules problems and transport problems, fall data
EG: illness and exacerbation of symptoms
CG: interference of treatment time with patient’s work hours and moving to another city
No adverse event during intervention
Molhemi et al. (2022)
Iran
RRMS: 27
SPMS: 9
EDSS: 4.8
EG:18/18
CG: 18/18
F: 58.33%
M: 41.67%
39.2
18 sessions (35 min; 3 s/w for 6 weeks)
Exergames with Microsoft Kinect
18 sessions (35 min; 3 s/w for 6 weeks)
Conventional balance training
86.11% (31/36) DOEG: % (2/18)
DOCG: 22.2% (3/18)
EG: Transport problems and exacerbation symptoms
CG: Lack of interest, work schedule and personal issue
NR
Munari et al. (2020)
Italy
RRMS: 3
SPMS: 14
EDSS: 5.2
EG: 8/8
CG: 9/7
F: 58.82%
M: 41.17%
57 ± 8.04
12 sessions (40 min; 2 s/w for 6 weeks):
Robot-assisted gait training GE–O system + VR environment
12 sessions (40 min; 2 s/w for 6 weeks):
Robot-assisted gait training GE–O system
88.23% (15/17) DOEG: 0% (0/8)
DOCG: 22.2% (2/15)
CG: Difficulties in arrival to the study place No adverse or harmful events during the intervention
Ozkul et al. (2020)
Turkey
RRMS
EDSS = 1.5
EG: 17/13
G1: 17/13
G2: 17/13
F: 58.33%
M: 41.67%
32.3
16 sessions (60 min; 2 s/w, 8 weeks)
30 min of Pilates + 10 min of rest + 20 min of immersive virtual reality (HMD). Two supervised exergames in standing position wearing a harness (Football game and Guillotine game)
G1: 16 sessions (60 min; 2 s/w, 8 weeks)
30 min of Pilates + 10 min of rest + 20 min of conventional balance training
G2: 16 sessions (15–20 min; 2 s/w, 8 weeks) Jacobson's progressive relaxation exercise
76.4% (26/34) DOEG: 23.5% (4/17)
DOCG: 23.7% (4/17)
EG/CG: Work intensity No adverse or harmful events during the intervention
Peruzzi et al. (2016)
Italy
RRMS
EDSS = 3.8 ± 0.9
EG: 16/14
CG:15/11
F: 60%
M: 40%
42.8 ± 11.1
18 sessions (45 min; 3 s/w, 6 weeks): supervised treadmill walking 80% of the subject’s overground walking
speed. Each week speed increased a 10%. Last week the subject removed one or both hands from the handrails + Virtual tree-lined trail in which obstacles have to be passed (also train memory, attention and planning)
18 sessions (45 min; 3 s/w, 6 weeks): supervised treadmill walking 80% of the subject’s overground walking
speed. Each week speed increased a 10%. Last week the subject removed one or both hands from the handrails
77.41% (24/31) DOEG: 26.7% (4/15)
DOCG: 18.8% (3/16)
EG/CG: Personal issues No adverse or harmful events during the intervention
Pagliari et al. (2021)
Italy
EDSS = 4.7 EG: 30/35
CG: 30/35
F: 60%
M: 40%
50.28
30 sessions (45 min; 5 s/w, 6 weeks)
VRRS Khymeia telerehabilitation home-based kit + cognitive training
30 sessions (45 min; 5 s/w, 6 weeks)
Conventional balance training + cognitive training
85.71% (60/70) DOEG: 14.28% (5/35)
DOCG: 14.28% (5/35)
EG/CG: No compliance to intervention
EG: problem with internet connection and unrelated comorbidities
CG: personal difficulties, moving to new home and unable to come in for follow-up
NR
Robinson et al. (2015)
United Kingdom
Phenotypes NR
EDSS = 3.5
EG: 20/20
G1: 18/16
G2: 18/15
F: 67.86%
M: 32.14%
52 ± 5.8
8 sessions (40 min; 2 s/w, 4 weeks)
Exergames with Wii Fit
G1: 8 sessions (40 min; 2 s/w, 4 weeks)
Conventional balance training
G2: no intervention
89.3% (50/56) DOEG: 0% (0/20)
DOG1: 11.1% (2/18)
DOG2: 22.2% (4/18)
G2: Suspected MS remission, hospitalisation (not related to the study)
CG: family-matters
NR
Russo et al. (2018)
Italy
RRMS EDSS = 5 EG: 30/30
CG: 15/15
F: 57.78%
M: 42.22%
42 ± 7
54 sessions (60 min; 3 s/w, 18 weeks)
6 weeks of Lokomat-PRO sum to VR (2D) + 12 weeks of conventional balance training
54 sessions (60 min; 3 s/w, 18 weeks)
Conventional balance training
100% (45/45) DOEG: 0% (0/30)
DOCG: 0% (0/15)
– No adverse or harmful events during the intervention
Tollar et al. (2020)
Hungary
RRMS:42
PPMS: 26
EDSS = 5
EG: 14/14
G1: 14/14
G2: 14/14
G3: 14/14
G4: 12/12
F: 90%
M: 10%
47
25 sessions (60 min; 1–2 s/w, 5 weeks)
High- intensity exergaming training
25 sessions (60 min; 1–2 s/w, 5 weeks)
G1: high-intensity balance training
G2: Cycling
G3: Active proprioceptive neuromuscular facilitation (PNF)
G4: Standard care wait-listed control group
97.14% (68/70) DOEG: 0% (0/14)
DOG1: 0% (0/14)
DOG2:0% (0/14)
DOG3: 0% (0/14)
DOG4: 16.7% (2/12)
CG: Disease exacerbation and illness No adverse or harmful events during the intervention
Yazgan et al. (2020)
Turkey
RRMS: 33
SPMS: 2
PPMS: 1
Progressive relapsing: 6
EDSS = 4.02 ± 1.37
EG: 16/15
G1: 16/12
G2: 15/15
F: 82.61%
M: 17.39%
43.73 ± 9.36
16 sessions (60 min; 2 s/w, 8 weeks)
supervised Nintendo Wii Fit exergames in standing position
G1: 16 sessions (60 min; 2 s/w, 8 weeks) Collect
Apples, Outline, Paddle War, and Evaluation of Movement games
G2: waiting list group
89.4% (42/47) DOEG: 6.3% (1/16)
DOG1: 25% (4/16)
DOG2: 0% (0/15)
EG/CG: Personal problems
CG: transportation problems
No adverse or harmful events during the intervention
CG control group, DO dropout, DOCG dropouts in control group, DOEG dropouts in experimental group, DOG2 dropouts in the second comparator group, EDSS Expanded Disability Status Scale, EG experimental group, F female, G1 first control intervention, G2 second control intervention, G3 third control intervention, M male, min minutes, MS multiple sclerosis, n number of participants, NR no reported, PPMS primary-progressive multiple sclerosis, RRMS relapsing–remitting multiple sclerosis, SD standard deviation, SPMS secondary-progressive multiple sclerosis, s/w sessions per week
Concerning the immersion of the virtual reality systems, 14 studies employed non-immersive virtual reality as the main experimental intervention and four of them used the Wii Fit system (Brichetto et al. 2015; Robinson et al. 2015; Khalil et al. 2019; Yazgan et al. 2020). Only two trials used fully immersive virtual reality (Kalron et al. 2016; Ozkul et al. 2020).
Most studies compared the virtual reality intervention to improve balance or gait to conventional balance training (n = 13, 81.25%) (Lozano-Quilis et al. 2014; Brichetto et al. 2015; Robinson et al. 2015; Hoang et al. 2016; Kalron et al. 2016; Peruzzi et al. 2016; Calabrò et al. 2017; Russo et al. 2018; Khalil et al. 2019; Ozkul et al. 2020; Molhemi et al. 2021, 2022; Pagliari et al. 2021), followed by robotic-assisted gait training (n = 3, 18.75%) (Calabrò et al. 2017; Peruzzi et al. 2017; Munari et al. 2020). The lowest number of sessions performed was 8 (Robinson et al. 2015), while the highest was 54 (Russo et al. 2018). Most authors proposed a frequency of intervention of 2 times per week with a minimum time per session of 30 min (Hoang et al. 2016; Kalron et al. 2016) and a maximum of 85 min (Calabrò et al. 2017).
The mean number of dropout events for the experimental group was 1.61 cases and 1.88 for the comparator group. The highest number of dropouts in the virtual reality groups was registered by Hoang et al. (2016) and Pagliari et al. (2021). The reasons reported by the authors for dropout in both groups were: difficulties reaching the research centre, transportation problems, scheduling problems, moving to another city, refusal to participate, personal or familial issues, lack of motivation or time, loss of data due to administrative problems, exacerbation of symptoms, disease relapse, work intensity, and illness/medical reasons/hospitalisation not related to multiple sclerosis. Three studies did not report any dropout events during the intervention or follow-up period (Brichetto et al. 2015; Calabrò et al. 2017; Russo et al. 2018).
Meta-analysis of proportions
A total of 18 arms (k) from 16 studies were included in the proportion and binary meta-analysis, since one of the randomised control trials presented three study groups (Tollar et al. 2020). From a total of 638 participants, 63 cases of dropouts were reported. The forest plot showed an overall pooled dropout rate of 6.6% (95%CI 3.2–12.9%) without heterogeneity between studies (tau2 = 1.18, Q = 10.07, df = 17, I2 = 0%, 95%CI 0–50%, p = 0.90) (Fig. 3). The dropout rate for the virtual reality-based interventions was 5.7% (95%CI 2.3–13.6%) against the 9.7% (95%CI 5.7–16.02%) in the comparator groups (Supplemental Material 4). Conversely, the retention rate for the virtual reality and comparator groups was 94.3% and 90.3%, respectively. None of the prediction intervals calculated across the meta-analysis suggested that the intervention would achieve the same effects in the future.Fig. 3 Forest plot of dropout rate for all groups of studies
Binary meta-analysis (OR)
The main results showed a slightly lower probability that dropouts occurred in the virtual reality-based interventions than in the comparator groups, but a significant difference was not obtained (OR = 0.89, 95%CI 0.64–1.24, p = 0.46). No significant heterogeneity between studies was found (tau2 = 0, Q = 5.6, df = 17, I2 = 0%, 95%CI 0–50%, p = 0.99) (Fig. 4). The prediction interval confirmed that the same effects would not happen in the future studies. A subgroup meta-analysis according to the immersion level of the virtual reality was not carried out because the number of studies using immersive systems did not reach the minimum required (3 studies).Fig. 4 Forest plot of odds ratio comparing attrition from virtual reality intervention and other comparator interventions in people with multiple sclerosis to improve balance or gait
A post hoc sensitive analysis using the L’Abbé and Baujat plots and influence graphs (Supplemental Material 5) showed that none of the included studies influenced heterogeneity or bias for the pooled effect size, and no outliers were found. Additionally, no small study effects or publication bias was shown in the contour-enhanced funnel plot (Fig. 5), the Harbord test (p = 0.37), or the Egger bias test (p = 0.34).Fig. 5 Contour-enhanced funnel plot
Meta-regression
The meta-regression revealed that the type of intervention, number, frequency, and duration of session, weeks of intervention, EDSS score, multiple sclerosis phenotype, sex, and methodological quality could not be related to the dropout events. A detailed description of the analysis is shown in Table 2.Table 2 Meta-regression analysis
Predictors SE t value 95%CI p value
Type of intervention 0.45 − 0.30 − 1.09, 0.82 0.76
Number of sessions 0.02 1.01 − 0.02, 0.06 0.33
Duration of sessions 0.15 − 1.24 − 0.05, 0.013 0.23
Frequency of sessions 0.15 0.54 − 0.23, 0.39 0.59
Weeks of intervention 0.07 0.89 − 0.08, 0.21 0.38
EDSS score 0.15 − 0.42 − 0.39, 0.26 0.68
RRMS 0.38 0.28 − 0.70, 0.92 0.78
PPMS 0.52 0.40 − 0.91, 1.32 0.69
SPMS 0.43 − 0.20 − 1.01, 0.84 0.84
Female gender 0.16 0.02 − 0.37, 0.03 0.86
Male gender 0.16 0.16 − 0.03, 0.04 0.87
Age 0.03 0.27 − 0.046, 0.06 0.79
PEDro score 0.14 1.97 − 0.02, 0.57 0.07
95%CI 95% confidence interval, PPMS primary progressive multiple sclerosis, RRMS remittent–recurrent multiple sclerosis, SPMS secondary progressive multiple sclerosis
Discussion
A total of 16 randomised control trials reporting dropouts were meta-analysed to calculate the overall pooled dropout rate of virtual reality-based interventions for the improvement of balance and gait in patients with multiple sclerosis. The main clinical implication of the results of our study was that the virtual reality-based training for balance and gait in people with multiple sclerosis was highly accepted with a low dropout rate and high adherence during the study period. Torous et al. (2020) suggested that the retention in research contexts could change when experimental approaches are translated into a clinical setting. This could be especially important for long rehabilitation programmes in chronic conditions. A recent study (Hortobágyi et al. 2022) reported a high adherence rate to a two-year maintenance programme including exergaming in people with multiple sclerosis; however, the sample size was very small, and more research about long-term adherence to virtual reality rehabilitation in this population is needed.
Adherence is one of the main conflicts faced in rehabilitation; the therapeutic approach of multiple sclerosis is not an exception. As a result, looking for rehabilitation therapies that achieve higher participant compliance to treatment is vital (Arafah et al. 2017). If correct adherence is not achieved, the effectiveness of the rehabilitation might be limited and incur additional healthcare costs (Jack et al. 2010; Room et al. 2021). Accordingly, the previous literature has proposed that virtual reality strategies presented higher adherence in patients with neurological disorders (Asadzadeh et al. 2021; Dalmazane et al. 2021). Nonetheless, our results suggested lower dropout rates in virtual reality-based interventions, which may be confirmed with larger sample sizes. This idea is supported by the prediction intervals, which stated that our findings could change with future trials. The recent systematic review of Bevens et al. (2021) analysed the dropout rate in people with multiple sclerosis who received digital health interventions, showing no significant differences between experimental and control comparators. Therefore, we can consider that the adherence to virtual reality or other technological approaches were at least similar to other interventions.
During the screening process, several studies were discarded because dropouts were not mentioned. Despite CONSORT guidelines stating the need to report complete data, many authors do not know how to handle dropouts (Bell et al. 2013). To address this issue, it is necessary to standardise the way in which the reason and number of dropouts are described, for example, using the CONSORT flowchart of the study period. Also, further details of dropouts could help to make decisions regarding which interventions to offer to whom (Wright et al. 2021).
Our meta-regression data showed that the type of intervention, number, duration, and frequency of sessions, weeks of intervention, disability score, phenotype, sex, and methodological quality were not predictors of dropouts. Although it seems that a higher frequency of sessions could favour participant dropouts, no significant results were found. Similar results were obtained by Dennett et al. (2020), who stated that there was no relationship between the frequency of exercise-based sessions and dropouts, but duration modified the likelihood of dropouts. Although our protocol included the analysis according to the level of immersion, fully immersive and semi-immersive virtual reality was excluded from the moderator analysis because of the limited number of studies included. Therefore, we suggest to provide a specific dropout rate analysis when the proportion of studies using immersive virtual reality rises, since higher immersion and presence levels are expected to achieve a higher treatment adherence (Rose et al. 2018; Dębska et al. 2019). Additionally, future studies should evaluate enjoyment and motivation with specific measurement scales, allowing researchers to understand whether motivation or enjoyment during the intervention is predictors of dropout or adherence to treatment in the targeted population.
According to the literature (Grover et al. 2021), adverse events due to treatment are considered one of the main causes of dropouts. Nonetheless, we were unable to analyse them as a moderator of dropout rate, since none of the studies included reported the undesired effects of the virtual reality intervention. Two possible explanations behind the low number of studies describing adverse events or side effects because of the intervention were considered: the first is that participants did not actually have adverse effects due to the virtual reality-based intervention, and the second is that the authors decided not to report them. The latter idea is supported by Phillips et al. (2019) and Pitrou et al. (2009), who addressed methodological weaknesses in reporting adverse events in randomised control trials, leading to a misinterpretation of intervention safety.
Strength and limitations
This is the first meta-analysis to calculate the overall pooled dropout rate for innovative virtual reality-based interventions in patients with multiple sclerosis. The findings of this review could help future randomised control trials to calculate their sample size to avoid dropout bias. Furthermore, no heterogeneity between the included studies was found in the analysis. The sensitivity analysis did not report any randomised control trial as an outlier that could strongly influence the overall size effect. Moreover, the funnel plot did not show any publication bias.
The main limitation of this review was the small sample size that the randomised control trials included, so a larger overall sample size would make our results more reliable. Another issue was that many studies did not report detailed reasons for dropouts. Furthermore, adverse events were not reported, so it was not possible to determine whether they could be moderators for dropout rate.
Conclusion
The overall pooled dropout rate of randomised control trials on virtual reality for balance or gait training in people with multiple sclerosis was 6.6%. Our analysis reported no differences in dropout rate for participants who received virtual reality-based interventions versus other comparators; however, the lower dropout rate in the virtual reality group could indicate that the inclusion of larger sample sizes would show a significant difference in favour of the virtual reality group. The number, duration, frequency, and weeks of sessions, sex, age, phenotype, disability, and methodological quality were not determined to be moderators of dropouts. Adverse events were not reported by the studies included, making it impossible to analyse their influence as moderators.
Future randomised control trials should standardise the description of dropout causes and adverse effects of the rehabilitation treatments. Furthermore, the advantages of virtual reality, such as motivation and enjoyment, should be systematically assessed in clinical trials to determine whether these outcomes are indeed moderators of dropout and adherence.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (PDF 846 kb)
Supplementary file2 (DOCX 37 kb)
Authors contribution
MJC-H and CG-M were involved in conceptualisation and writing, review and editing; CG-M, MJC-H contributed to methodology; CG-M were involved in software and formal analysis; MJC-H, CG-M, MDC-V, RM-V, JAM-M and DL-A contributed to writing—original draft preparation; MDC-V and R-MV were involved in visualisation; MDC-V, JAM-M and DL-A contributed to supervision; MJC-H and CG-M contributed equally to this work. All authors have read and agreed to the published version of the manuscript.
Data availability
Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
Declarations
Conflict of interest
The authors declare no conflicts of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Lozano-Quilis J-A Gil-Gómez H Gil-Gómez J-A Albiol-Pérez S Palacios-Navarro G Fardoun HM Mashat AS Virtual rehabilitation for multiple sclerosis using a kinect-based system: randomized controlled trial JMIR Serious Games 2014 2 e12 10.2196/games.2933 25654242
Maher CG Sherrington C Herbert RD Reliability of the PEDro scale for rating quality of randomized controlled trials Phys Ther 2003 83 713 721 10.1093/ptj/83.8.713 12882612
Massetti T Dias T Crocetta TB Guarnieri R de Freitas BL Bianchi Lopes P Watson S Tonks J de Mello Monteiro CB The clinical utility of virtual reality in neurorehabilitation: a systematic review J Cent Nerv Syst Dis 2018 10.1177/1179573518813541
Matamala-Gomez M Bottiroli S Realdon O Riva G Galvagni L Platz T Sandrini G De Icco R Tassorelli C Telemedicine and virtual reality at time of COVID-19 pandemic: an overview for future perspectives in neurorehabilitation Front Neurol 2021 12 1 9 10.3389/fneur.2021.646902
Moan ME Vonstad EK Su X Vereijken B Solbjør M Skjæret-Maroni N Experiences of stroke survivors and clinicians with a fully immersive virtual reality treadmill exergame for stroke rehabilitation: a qualitative pilot study Front Aging Neurosci 2021 13 1 12 10.3389/fnagi.2021.735251
Moher D Liberatu A Tetzlaff j, Altman D, Preferred reporting items for systematic reviews and meta-analyses: the prisma statement Ann Intern Med 2009 151 264 10.7326/0003-4819-151-4-200908180-00135 19622511
Molhemi F Monjezi S Mehravar M Shaterzadeh-Yazdi MJ Salehi R Hesam S Mohammadianinejad E Effects of virtual reality vs conventional balance training on balance and falls in people with multiple sclerosis: a randomized controlled trial Arch Phys Med Rehabil 2021 102 290 299 10.1016/j.apmr.2020.09.395 33161005
Molhemi F Mehravar M Monjezi S Monjezi S Salehi R Negahban H Shaterzadeh-Yazdi MJ Majdinasab N Effects of exergaming on cognition, lower limb functional coordination, and stepping time in people with multiple sclerosis: a randomized controlled trial Disabil Rehabil 2022 10.1080/09638288.2022.2060332
Moore H Nair KPS Baster K Middleton R Paling D Sharrack B Fatigue in multiple sclerosis: a UK MS-register based study Mult Scler Relat Disord 2022 64 103954 10.1016/j.msard.2022.103954 35716477
Morel M Bideau B Lardy J Kulpa R Advantages and limitations of virtual reality for balance assessment and rehabilitation Neurophysiol Clin 2015 45 315 326 10.1016/j.neucli.2015.09.007 26527045
Munari D Fonte C Varalta V Battistuzzi E Cassini S Montagnoli AP Gandolfi M Modenese A Filippetti M Smania N Picelli A Effects of robot-assisted gait training combined with virtual reality on motor and cognitive functions in patients with multiple sclerosis: a pilot, single-blind, randomized controlled trial Restor Neurol Neurosci 2020 38 151 164 10.3233/RNN-190974 32333564
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| 0 | PMC9735032 | NO-CC CODE | 2022-12-14 23:28:32 | no | Uro-News. 2022 Dec 6; 26(12):38-39 | latin-1 | null | null | null | oa_other |
==== Front
Ann Surg Oncol
Ann Surg Oncol
Annals of Surgical Oncology
1068-9265
1534-4681
Springer International Publishing Cham
36474094
12896
10.1245/s10434-022-12896-0
Reconstructive Oncology
Complications, Costs, and Healthcare Resource Utilization After Staged, Delayed, and Immediate Free-Flap Breast Reconstruction: A Longitudinal, Claims-Based Analysis
http://orcid.org/0000-0001-5468-8646
Shammas Ronnie L. MD 1
Gordee Alexander MA 2
Lee Hui-Jie PhD 2
Sergesketter Amanda R. MD 1
Scales Charles D. MD 3
Hollenbeck Scott T. MD 1
Phillips Brett T. MBA, MD [email protected]
1
1 grid.189509.c 0000000100241216 Division of Plastic and Reconstructive Surgery, Duke University Medical Center, Durham, NC USA
2 grid.26009.3d 0000 0004 1936 7961 Department of Biostatistics and Bioinformatics, Duke University, Durham, NC USA
3 grid.189509.c 0000000100241216 Division of Urologic Surgery, Duke University Medical Center, Durham, NC USA
6 12 2022
116
16 8 2022
15 11 2022
© Society of Surgical Oncology 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Background
There is a lack of consensus detailing the optimal approach to free-flap breast reconstruction when considering immediate, delayed, or staged techniques. This study compared costs, complications, and healthcare resource utilization (HCRU) across staged, delayed, and immediate free-flap breast reconstruction.
Patients and Methods
Retrospective study using MarketScan databases to identify women who underwent mastectomies and free-flap reconstructions between 2014 and 2018. Complications, costs, and HCRU [readmission, reoperation, emergency department (ED) visits] occurring 90 days after mastectomy and 90 days after free flap were compared across immediate, delayed, and staged reconstruction.
Results
Of 3310 women identified, 69.8% underwent immediate, 11.7% underwent delayed, and 18.5% underwent staged free-flap reconstruction. Staged reconstruction was associated with the highest rate (57.8% staged, 42.3% delayed, 32.0% immediate; p < 0.001) and adjusted relative risk [67% higher than immediate (95% CI: 49–87%; p < 0.001)] of surgical complications. Staged displayed the highest HCRU (staged 47.9%, delayed, 38.4%, immediate 25.2%; p < 0.001), with 16.5%, 30.7%, and 26.5% of staged patients experiencing readmission, reoperation, or ED visit, respectively. The adjusted probability of HCRU was 206% higher (95% CI: 156–266%; p < 0.001) for staged compared with immediate. Staged had the highest mean total cost (staged $106,443, delayed $80,667, immediate $76,756; p < 0.001) with regression demonstrating the adjusted mean cost for staged is 31% higher (95% CI: 23–39%; p < 0.001) when compared with immediate.
Conclusions
Staged free-flap reconstruction is associated with increased complications, costs, and HCRU, while immediate demonstrated the lowest. The potential esthetic benefits of a staged approach should be balanced with the increased risk for adverse events after surgery.
Supplementary Information
The online version contains supplementary material available at 10.1245/s10434-022-12896-0.
http://dx.doi.org/10.13039/100006108 National Center for Advancing Translational Sciences CTSA Grant (UL1TR002553)
==== Body
pmcApproximately 250,000 new cases of invasive breast cancer are diagnosed each year, with 50–60% of mastectomy patients electing to undergo reconstructive surgery.1 When considering reconstructive options, there has been a gradual rise in the rates of free-flap breast reconstruction with an increasing amount of evidence supporting superior long-term satisfaction and improved quality of life compared with implant-based techniques.2 However, there remains a lack of consensus regarding the optimal timing and approach to free-flap reconstruction, with improved patient well-being and superior esthetic outcomes being associated with immediate (performed at the time of mastectomy) as opposed to delayed (performed after mastectomy) reconstructive techniques.3,4
In 2002, Kronowitz et al. introduced the concept of a staged (i.e., delayed–immediate) approach to free-flap breast reconstruction.5 With this technique, a tissue expander is placed at the time of mastectomy to preserve the native breast skin envelope, allowing for decreased skin requirements during free-flap reconstruction and improved esthetic outcomes.6 While the indications for a staged approach were initially described for patients with an uncertain need for radiation therapy, these indications have expanded to include patients with significant medical comorbidities, tenuous mastectomy skin flaps, and those who have not yet made a final decision regarding their preferred type of breast reconstruction. Furthermore, with evidence suggesting that an immediate form of reconstruction to preserve the breast mound may confer improved psychosocial well-being, a two-stage approach has been increasingly utilized when immediate reconstruction is unable to be performed.7–9
Complications following staged reconstruction are reported to approach 30–40%, especially in the setting of radiation therapy.10–13 However, there remains a lack of consensus detailing the optimal timing of free-flap breast reconstruction when considering an immediate, delayed, or staged approach. Thus, to inform high-quality treatment decisions, this study aimed to compare costs, complications, and healthcare utilization across patients undergoing immediate, delayed, or staged free-flap breast reconstruction.
Patients and Methods
Data Source and Study Cohort
This study utilized the IBM MarketScan commercial claims and encounters and medicare supplemental databases to identify women ≥ 18 years old who were diagnosed with breast cancer and underwent a mastectomy with eventual free-flap breast reconstruction. The MarketScan research databases capture receipt of care in inpatient and outpatient settings and patient-level utilization of healthcare services in a longitudinal manner, making it uniquely suited to capture episodes of care related to breast reconstruction. Women who were diagnosed with breast cancer and underwent a mastectomy between 1 January 2014 and 31 December 2018, were identified and included, utilizing International Classification of Diseases, Ninth Revision (ICD-9) procedure codes, ICD-10 procedure codes, and/or Current Procedural Terminology (CPT) codes. The algorithm proposed by Nattinger et al. was used to identify whether patients with a mastectomy were incident and prevalent cases of breast cancer.14 Only patients who underwent a form of free-flap breast reconstruction after mastectomy were included. Relevant ICD and CPT codes used for identification of the cohort are included in Supplementary Digital Content (SDC) Tables 1 and 2.Table 1 Demographics and clinical characteristics by reconstruction method
Immediate (N = 2310) Delayed (N = 388) Staged (N = 612) Total (N = 3310)
Age at mastectomy (years)
Mean (SD) 51.3 (8.3) 49.6 (8.8) 49.4 (8.1) 50.7 (8.4)
Median 52.0 50.0 49.0 51.0
Q1, Q3 45.0, 58.0 43.0, 57.0 44.0, 56.0 45.0, 57.0
Range (21.0–75.0) (19.0–68.0) (22.0–68.0) (19.0–75.0)
Urban MSA
No 139 (6.0%) 56 (14.4%) 35 (5.7%) 230 (6.9%)
Yes 2171 (94.0%) 332 (85.6%) 577 (94.3%) 3080 (93.1%)
Geographic region
Northeast 636 (27.5%) 34 (8.8%) 103 (16.8%) 773 (23.4%)
North Central 280 (12.1%) 54 (13.9%) 89 (14.5%) 423 (12.8%)
South 1137 (49.2%) 229 (59.0%) 347 (56.7%) 1713 (51.8%)
West 243 (10.5%) 69 (17.8%) 69 (11.3%) 381 (11.5%)
Unknown 14 (0.6%) 2 (0.5%) 4 (0.7%) 20 (0.6%)
Insurance plan type
Missing 45 8 15 68
Comprehensive 52 (2.3%) 7 (1.8%) 24 (4.0%) 83 (2.6%)
EPO or HMO 322 (14.2%) 51 (13.4%) 66 (11.1%) 439 (13.5%)
POS or PPO 1495 (66.0%) 255 (67.1%) 364 (61.0%) 2114 (65.2%)
Basic/major medical, CDHP, HDHP 396 (17.5%) 67 (17.6%) 143 (24.0%) 606 (18.7%)
Employment status
Active full or part time 1522 (65.9%) 270 (69.6%) 459 (75.0%) 2251 (68.0%)
Retiree 186 (8.1%) 25 (6.4%) 28 (4.6%) 239 (7.2%)
Other/unknown 595 (25.8%) 91 (23.5%) 119 (19.4%) 805 (24.3%)
Long term disability 7 (0.3%) 2 (0.5%) 6 (1.0%) 15 (0.5%)
Bilateral mastectomy
No 1455 (63.0%) 312 (80.4%) 435 (71.1%) 2202 (66.5%)
Yes 855 (37.0%) 76 (19.6%) 177 (28.9%) 1108 (33.5%)
Lymph node surgery at time of mastectomy
No 901 (39.0%) 187 (48.2%) 182 (29.7%) 1270 (38.4%)
Yes 1409 (61.0%) 201 (51.8%) 430 (70.3%) 2040 (61.6%)
Chemotherapy
None 1543 (66.8%) 129 (33.2%) 261 (42.6%) 1933 (58.4%)
Before mastectomy 184 (8.0%) 58 (14.9%) 84 (13.7%) 326 (9.8%)
After mastectomy 421 (18.2%) 110 (28.4%) 167 (27.3%) 698 (21.1%)
Before and after mastectomy 162 (7.0%) 91 (23.5%) 100 (16.3%) 353 (10.7%)
Radiation
None 2178 (94.3%) 198 (51.0%) 367 (60.0%) 2743 (82.9%)
Before mastectomy 37 (1.6%) 2 (0.5%) 2 (0.3%) 41 (1.2%)
After mastectomy 95 (4.1%) 188 (48.5%) 242 (39.5%) 525 (15.9%)
Before and after mastectomy 0 (0.0%) 0 (0.0%) 1 (0.2%) 1 (0.0%)
Other cancer diagnosis in year prior to or within 90 days of mastectomy
No 2048 (88.7%) 351 (90.5%) 536 (87.6%) 2935 (88.7%)
Yes 262 (11.3%) 37 (9.5%) 76 (12.4%) 375 (11.3%)
Dermal matrix placed at index mastectomy or reconstruction
No 2113 (91.5%) 351 (90.5%) 162 (26.5%) 2626 (79.3%)
Yes 197 (8.5%) 37 (9.5%) 450 (73.5%) 684 (20.7%)
NCI comorbidity index
Missing 0 0 0 0
Mean (SD) 0.2 (0.3) 0.2 (0.3) 0.2 (0.3) 0.2 (0.3)
Median 0.0 0.0 0.0 0.0
Q1, Q3 0.0, 0.3 0.0, 0.5 0.0, 0.3 0.0, 0.3
Range (0.0–2.2) (0.0–1.9) (0.0–1.6) (0.0–2.2)
Table 2 Complications within 90 days after mastectomy or free flap
Immediate (N = 2310) Delayed (N = 388) Staged (N = 612) Total (N = 3310) p-Value
Individual systemic complications
Stroke
Mastectomy – 0 (0.0%) 0 (0.0%) 0 (0.0%)
Free flap – 0 (0.0%) 0 (0.0%) 0 (0.0%)
Mastectomy or free flap 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) –
Urinary
Mastectomy – 0 (0.0%) 1 (0.2%) 1 (0.1%)
Free flap – 0 (0.0%) 0 (0.0%) 0 (0.0%)
Mastectomy or free flap 4 (0.2%) 0 (0.0%) 1 (0.2%) 5 (0.2%) 0.71611
DVT/PE
Mastectomy – 1 (0.3%) 6 (1.0%) 7 (0.7%)
Free flap – 13 (3.4%) 18 (2.9%) 31 (3.1%)
Mastectomy or free flap 73 (3.2%) 14 (3.6%) 21 (3.4%) 108 (3.3%) 0.86981
Digestive
Mastectomy – 4 (1.0%) 3 (0.5%) 7 (0.7%)
Free flap – 2 (0.5%) 9 (1.5%) 11 (1.1%)
Mastectomy or free flap 33 (1.4%) 6 (1.5%) 12 (2.0%) 51 (1.5%) 0.63651
Cardiovascular
Mastectomy – 9 (2.3%) 26 (4.2%) 35 (3.5%)
Free flap – 10 (2.6%) 38 (6.2%) 48 (4.8%)
Mastectomy or free flap 94 (4.1%) 18 (4.6%) 60 (9.8%) 172 (5.2%) < 0.00011
Respiratory
Mastectomy – 3 (0.8%) 5 (0.8%) 8 (0.8%)
Free flap – 11 (2.8%) 18 (2.9%) 29 (2.9%)
Mastectomy or free flap 65 (2.8%) 14 (3.6%) 22 (3.6%) 101 (3.1%) 0.48241
Individual surgical complications
Wound dehiscence
Mastectomy – 9 (2.3%) 47 (7.7%) 56 (5.6%)
Free flap – 48 (12.4%) 75 (12.3%) 123 (12.3%)
Mastectomy or free flap 266 (11.5%) 52 (13.4%) 113 (18.5%) 431 (13.0%) < 0.00011
Wound infection
Mastectomy – 18 (4.6%) 66 (10.8%) 84 (8.4%)
Free flap – 20 (5.2%) 46 (7.5%) 66 (6.6%)
Mastectomy or free flap 93 (4.0%) 13 (3.4%) 64 (10.5%) 170 (5.1%) < 0.00011
Flap revision
Mastectomy – 0 (0.0%) 2 (0.3%) 2 (0.2%)
Free flap – 9 (2.3%) 13 (2.1%) 22 (2.2%)
Mastectomy or free flap 51 (2.2%) 9 (2.3%) 15 (2.5%) 75 (2.3%) 0.93481
Hematoma
Mastectomy – 17 (4.4%) 10 (1.6%) 27 (2.7%)
Free flap – 19 (4.9%) 23 (3.8%) 42 (4.2%)
Mastectomy or free flap 132 (5.7%) 36 (9.3%) 33 (5.4%) 201 (6.1%) 0.01821
Microvascular
Mastectomy – 0 (0.0%) 1 (0.2%) 1 (0.1%)
Free flap – 27 (7.0%) 95 (15.5%) 122 (12.2%)
Mastectomy or free flap 138 (6.0%) 27 (7.0%) 96 (15.7%) 261 (7.9%) < 0.00011
Transfusion
Mastectomy – 3 (0.8%) 0 (0.0%) 3 (0.3%)
Free flap – 1 (0.3%) 5 (0.8%) 6 (0.6%)
Mastectomy or free flap 9 (0.4%) 4 (1.0%) 5 (0.8%) 18 (0.5%) 0.16841
Seroma
Mastectomy – 18 (4.6%) 33 (5.4%) 51 (5.1%)
Free flap – 15 (3.9%) 21 (3.4%) 36 (3.6%)
Mastectomy or free flap 80 (3.5%) 31 (8.0%) 53 (8.7%) 164 (5.0%) < 0.00011
Fat necrosis
Mastectomy – 12 (3.1%) 34 (5.6%) 46 (4.6%)
Free flap – 20 (5.2%) 21 (3.4%) 41 (4.1%)
Mastectomy or free flap 126 (5.5%) 31 (8.0%) 53 (8.7%) 210 (6.3%) 0.00561
Mechanical complications
Mastectomy – 0 (0.0%) 35 (5.7%) 35 (3.5%)
Free flap – 11 (2.8%) 29 (4.7%) 40 (4.0%)
Mastectomy or free flap 62 (2.7%) 11 (2.8%) 60 (9.8%) 133 (4.0%) < 0.00011
Individual surgical complications requiring a return to OR
Hematoma requiring reoperation
Mastectomy – 25 (6.4%) 19 (3.1%) 44 (4.4%)
Free flap – 18 (4.6%) 28 (4.6%) 46 (4.6%)
Mastectomy or free flap 128 (5.5%) 41 (10.6%) 45 (7.4%) 214 (6.5%) 0.00061
Wound infection requiring reoperation
Mastectomy – 9 (2.3%) 32 (5.2%) 41 (4.1%)
Free flap – 15 (3.9%) 30 (4.9%) 45 (4.5%)
Mastectomy or free flap 148 (6.4%) 24 (6.2%) 57 (9.3%) 229 (6.9%) 0.03481
Tissue expander requiring reoperation
Mastectomy – 2 (0.5%) 68 (11.1%) 70 (7.0%)
Free flap – 2 (0.5%) 52 (8.5%) 54 (5.4%)
Mastectomy or free flap 5 (0.2%) 4 (1.0%) 114 (18.6%) 123 (3.7%) < 0.00011
Wound complication requiring reoperation
Mastectomy – 0 (0.0%) 16 (2.6%) 16 (1.6%)
Free flap – 10 (2.6%) 17 (2.8%) 27 (2.7%)
Mastectomy or free flap 46 (2.0%) 10 (2.6%) 32 (5.2%) 88 (2.7%) 0.00011
Flap compromise requiring reoperation
Mastectomy – 0 (0.0%) 2 (0.3%) 2 (0.2%)
Free flap – 7 (1.8%) 17 (2.8%) 24 (2.4%)
Mastectomy or free flap 39 (1.7%) 7 (1.8%) 19 (3.1%) 65 (2.0%) 0.07811
Microvascular requiring reoperation
Mastectomy – 0 (0.0%) 1 (0.2%) 1 (0.1%)
Free flap – 27 (7.0%) 95 (15.5%) 122 (12.2%)
Mastectomy or free flap 138 (6.0%) 27 (7.0%) 96 (15.7%) 261 (7.9%) <0.00011
Reconstruction failure
Additional flap
Mastectomy – 0 (0.0%) 0 (0.0%) 0 (0.0%)
Free flap – 16 (4.1%) 17 (2.8%) 33 (3.3%)
Mastectomy or free flap 68 (2.9%) 16 (4.1%) 17 (2.8%) 101 (3.1%) 0.41611
Tissue expander replacement or extrusion
Mastectomy – 0 (0.0%) 68 (11.1%) 68 (6.8%)
Free flap – 0 (0.0%) 0 (0.0%) 0 (0.0%)
Mastectomy or free flap 0 (0.0%) 0 (0.0%) 68 (11.1%) 68 (2.1%)
Grouped complication
Systemic complication
Mastectomy – 15 (3.9%) 38 (6.2%) 53 (5.3%)
Free flap – 32 (8.2%) 79 (12.9%) 111 (11.1%)
Mastectomy or free flap 241 (10.4%) 46 (11.9%) 107 (17.5%) 394 (11.9%) < 0.00011
Surgical complication
Mastectomy – 69 (17.8%) 167 (27.3%) 236 (23.6%)
Free flap – 124 (32.0%) 273 (44.6%) 397 (39.7%)
Mastectomy or free flap 739 (32.0%) 164 (42.3%) 354 (57.8%) 1257 (38.0%) < 0.00011
Complication requiring return to OR
Mastectomy – 32 (8.2%) 100 (16.3%) 132 (13.2%)
Free flap – 67 (17.3%) 188 (30.7%) 255 (25.5%)
Mastectomy or free flap 402 (17.4%) 93 (24.0%) 252 (41.2%) 747 (22.6%) < 0.00011
Reconstruction failure
Mastectomy – 0 (0.0%) 82 (13.4%) 82 (8.2%)
Free flap – 26 (6.7%) 44 (7.2%) 70 (7.0%)
Mastectomy or free flap 120 (5.2%) 26 (6.7%) 116 (19.0%) 262 (7.9%) < 0.00011
Primary outcome
Any complication
Mastectomy – 78 (20.1%) 187 (30.6%) 265 (26.5%)
Free flap – 145 (37.4%) 314 (51.3%) 459 (45.9%)
Mastectomy or free flap 887 (38.4%) 182 (46.9%) 393 (64.2%) 1462 (44.2%) < 0.00011
1Chi-square
To be eligible for inclusion in the final study cohort, a patient had to demonstrate continuous enrollment 12 months pre-mastectomy to 90 days post free-flap breast reconstruction. Patients were excluded from analysis if they: (1) displayed codes for a free-flap prior to their mastectomy, (2) did not have a breast cancer diagnosis on the date of or in the year prior to mastectomy, (3) had distant metastasis, (4) had a breast implant procedure within 1 year of mastectomy to 90 days after the free-flap was performed, (5) had a tissue expander placed prior to their mastectomy and not on the index surgery, (6) had a free-flap performed within 2 weeks of the index mastectomy but not within the index admission, (7) had a tissue expander placed after the index admission but before free-flap reconstruction, and (8) had a pedicled flap performed prior to their free-flap procedure. For the cost analysis, patients with capitated service claims and patients with outlying values below the 1st percentile or above the 99th percentile were excluded. The ICD-9, ICD-10, and CPT codes used to identify patients fitting the exclusion criteria are included in SDC Table 3.Table 3 Modified Poisson regression of at least one complication
Variable Relative risk (95% confidence interval) p-Value
Reconstruction method
Immediate Reference –
Delayed 1.28 (1.13, 1.46) < 0.001
Staged 1.67 (1.49, 1.87) < 0.001
Staged versus delayed 1.30 (1.13, 1.50) < 0.001
Age (years) 1.01 (1.00, 1.01) 0.014
NCI comorbidity index 1.18 (1.06, 1.31) 0.002
Rural versus urban 0.92 (0.79, 1.08) 0.303
Region
South Reference –
North Central 1.06 (0.95, 1.19) 0.324
Northeast 0.98 (0.89, 1.08) 0.667
West 0.99 (0.87, 1.11) 0.834
Employment status
Employed full or part-time Reference –
Disability 0.80 (0.44, 1.46) 0.473
Other/unknown 1.05 (0.96, 1.15) 0.302
Retiree 0.98 (0.83, 1.15) 0.778
Bilateral mastectomy 1.08 (0.99, 1.17) 0.071
Lymph node surgery at time of mastectomy 0.90 (0.84, 0.98) 0.012
Chemotherapy before or after mastectomy 1.01 (0.93, 1.10) 0.756
Radiation before or after mastectomy 0.91 (0.82, 1.02) 0.095
Other cancer diagnosis 1.07 (0.95, 1.19) 0.266
Dermal matrix 1.10 (0.99, 1.22) 0.083
Episodes of Care Duration and Categorization of Study Groups
The episodes of care durations were designed to capture complications, costs, and healthcare utilization related to the mastectomy, tissue expander, or free-flap procedure for patients undergoing reconstruction in either an immediate, delayed, or staged setting. Thus, complications, costs, and healthcare utilization were assessed in periods of 90 days after the index mastectomy and 90 days after the free-flap procedure. Immediate reconstruction was classified as patients who underwent a free flap for breast reconstruction on the date of mastectomy or within the index admission. Staged reconstruction was classified as patients who had a tissue expander placed on the date of mastectomy or within the index admission and who underwent a free flap for breast reconstruction after tissue expander placement. Delayed reconstruction was classified as patients who had a mastectomy without tissue-expander or free-flap reconstruction on the date of mastectomy or within the index admission and who later underwent a free flap for breast reconstruction. A flow diagram detailing selection of the patient cohort is shown in SDC Fig. 1.Fig. 1 Flow diagram of patient selection criteria
Study Variables
Clinical and socioeconomic variables were identified using 1-year pre-mastectomy claims to characterize the study population and to be utilized as covariates in the univariable and multivariable analyses. The National Cancer Institute (NCI) comorbidity index was used to estimate the comorbidity burden across the study population.15,16 The primary outcomes of interest were complications, costs, and healthcare resource utilization (HCRU), which occurred within 90 days after the index mastectomy and 90 days after the free-flap procedure. Complications were categorized as systemic or surgical complications. Individual systemic complications were identified in addition to individual surgical complications, which were further subcategorized as those requiring a return to the operating room and those denoting reconstructive failure.13,17–19 Reconstructive failure was defined as having the following events: (1) Tissue expander removal without replacement prior to the free-flap being performed, (2) a second flap procedure being performed after the index free-flap, and/or (3) tissue expander extrusion. The claims codes used to define the outcomes of interests are shown in SDC Table 4.Table 4 Healthcare resource utilization
Immediate (N = 2310) Delayed (N = 388) Staged (N = 612) Total (N = 3310) p-Value
Any readmissions within 90 days
Mastectomy – 21 (5.4%) 64 (10.5%) 85 (8.5%)
Free flap – 30 (7.7%) 49 (8.0%) 79 (7.9%)
Mastectomy or free flap 189 (8.2%) 49 (12.6%) 101 (16.5%) 339 (10.2%) < 0.00011
Any reoperations within 90 days
Mastectomy – 28 (7.2%) 97 (15.8%) 125 (12.5%)
Free flap – 42 (10.8%) 113 (18.5%) 155 (15.5%)
Mastectomy or free flap 276 (11.9%) 67 (17.3%) 188 (30.7%) 531 (16.0%) < 0.00011
Any ED visits within 90 days
Mastectomy – 46 (11.9%) 104 (17.0%) 150 (15.0%)
Free flap – 57 (14.7%) 80 (13.1%) 137 (13.7%)
Mastectomy or free flap 325 (14.1%) 95 (24.5%) 162 (26.5%) 582 (17.6%) < 0.00011
Any readmission, reoperation, or ED visit within 90 days
Mastectomy – 77 (19.8%) 182 (29.7%) 259 (25.9%)
Free flap – 94 (24.2%) 177 (28.9%) 271 (27.1%)
Mastectomy or free flap 582 (25.2%) 149 (38.4%) 293 (47.9%) 1024 (30.9%) < 0.00011
1Chi-square
Costs and Healthcare Resource Utilization
Costs incurred within 90 days of the index mastectomy and free-flap reconstruction were calculated and compared. For patients undergoing delayed and staged reconstruction, costs within 90 days of both the mastectomy and the free flap were calculated. The following components of cost were considered: (1) index reconstruction (initial free-flap procedure or tissue expander placement) and index mastectomy, (2) complications, (3) complications requiring reoperation, (4) inpatient readmission, and (5) emergency department (ED) visits. Unplanned costs were defined as those incurred due to complications, ED visits, readmission, and reoperation. Rates of HCRU were also defined across the cohort as readmission, reoperation, and ED visits.
Statistical Analysis
Demographic characteristics, clinical characteristics, and payments to healthcare providers were summarized using means with standard deviation, medians with interquartile range, or frequencies with percentage as appropriate, and presented by reconstruction approaches. The proportions of individuals experiencing various complications and different types of all-cause HCRU were summarized using frequencies with percentages and compared between approaches using chi-square tests. The relative risks of any complication and HCRU were compared between approaches using modified Poisson regression, adjusting for age, NCI comorbidity index, urban/rural ZIP code, geographic region, employment status, laterality of mastectomy, lymph node surgery at the time of mastectomy, chemotherapy before or after mastectomy, radiation before or after mastectomy, and presence of other cancer diagnoses. The analysis of complications also adjusted for the use of dermal matrix. Payments to healthcare providers were compared between approaches using Kruskal–Wallis tests. Adjusted mean payments were compared using Gamma regression, adjusting for the same variables. Marginal mean costs for each reconstruction approach were calculated using separate Gamma regression models to assess the incremental costs associated with each type of adverse event for each type of reconstruction. Models adjusted for all covariates considered in the analysis of cost and included the interaction between adverse events and the reconstruction approach. All analyses were performed using SAS software version 9.4 (SAS Institute, Cary, NC). Statistical significance was defined as p < 0.05, without accounting for multiple testing due to the exploratory nature of the analysis. Any positive results should be confirmed in further studies.
Results
Participant Characteristics
Overall, 3310 women were included with 2310 (69.8%) undergoing immediate reconstruction, 388 (11.7%) undergoing delayed reconstruction, and 612 (18.5%) undergoing staged free-flap breast reconstruction. The average age of the patient cohort was 50.7 (SD 8.4) years. Most patients were in the South (51.8%), had full or part-time employment (68.0%), underwent a unilateral mastectomy (66.5%) with a sentinel or axillary lymph node dissection (61.6%), did not receive chemotherapy (58.4%) or radiation therapy (82.9%), and had minimal comorbidities with an average NCI comorbidity index of 0.2 (SD 0.3). Patient demographics and clinical characteristics are presented in Table 1.
Complications
When analyzing complications within 90 days after the mastectomy and/or free-flap procedure, patients undergoing staged reconstruction were found to have the highest overall rate of any complication that occurred (64.2% staged, 46.9% delayed, 38.4% immediate; p < 0.001). Staged reconstruction was associated with higher rates of systemic (17.5% staged, 11.9% delayed, 10.4% immediate; p < 0.001) and surgical complications (57.8% staged, 42.3% delayed, 32.0% immediate; p < 0.001), in addition to higher rates of complications that required a return to the operating room (OR) (41.2% staged, 24.0% delayed, and 17.4% immediate; p < 0.001) or resulted in reconstruction failure (19.0% staged, 6.7% delayed, 5.2% immediate; p < 0.001). Specifically, patients undergoing staged reconstruction displayed significantly higher rates of wound dehiscence, seroma, and mechanical complications (p < 0.001), with 15.7% of staged patients experiencing microvascular complications compared with 7.0% delayed and 6.0% immediate, and 11.1% of staged patients requiring tissue expander replacement or explant (Table 2).
A modified Poisson regression assessed the independent association of the modality of free-flap breast reconstruction with complications in the 90 days following mastectomy and/or the free-flap procedure. After adjusting for covariates, the estimated probability of experiencing a complication was 67% higher (95% CI: 49–87%; p < 0.001) for those undergoing staged when compared with immediate, 30% higher (95% CI: 13–50%; p < 0.001) for those undergoing staged when compared with delayed, and 28% higher (95% CI: 13–46%; p < 0.001) for those undergoing delayed when compared with immediate (Table 3). Overall, immediate reconstruction demonstrated the lowest rate of overall complications.
Healthcare Resource Utilization
HCRU in the 90-day period following mastectomy, reconstruction, and the combined periods following either was assessed by examining the occurrence of reoperations, all-cause readmission, and all-cause ED visits. Immediate reconstruction was found to have the lowest rate of all types of HCRU, with staged reconstruction displaying the highest (staged 47.9%, delayed 38.4%, immediate 25.2%; p < 0.001). More specifically, 16.5%, 30.7%, and 26.5% of patients undergoing staged reconstruction experienced readmission, reoperation, or an ED visit respectively within 90 days of their mastectomy and/or free-flap (Table 4).
A modified Poisson regression assessed the association of the type of reconstruction with any HCRU, finding that the adjusted probability of experiencing any post-operative HCRU was 206% higher (95% CI: 156–266%; p < 0.001) for those undergoing staged when compared with immediate, 63% higher (95% CI: 28–106%; p < 0.001) for those undergoing staged when compared with delayed, and 88% higher (95% CI: 50–137%; p < 0.001) for those undergoing delayed when compared with immediate (Table 5).Table 5 Modified Poisson regression of healthcare resource utilization
Variable Relative risk (95% confidence interval) p-Value
Reconstruction method
Immediate Reference –
Delayed 1.88 (1.50, 2.37) < 0.001
Staged 3.06 (2.56, 3.66) < 0.001
Staged versus delayed 1.63 (1.28, 2.06) < 0.001
Age (years) 1.00 (0.99, 1.01) 0.836
NCI comorbidity index 1.27 (1.04, 1.55) 0.017
Rural versus urban 1.06 (0.81, 1.39) 0.681
Region
South Reference –
North Central 1.08 (0.86, 1.35) 0.514
Northeast 1.08 (0.89, 1.32) 0.422
West 0.80 (0.62, 1.03) 0.078
Employment status
Employed full or part-time Reference –
Disability 0.60 (0.22, 1.61) 0.306
Other/unknown 1.16 (0.97, 1.38) 0.101
Retiree 0.87 (0.64, 1.17) 0.344
Bilateral mastectomy 1.28 (1.09, 1.51) 0.003
Lymph node surgery at time of mastectomy 0.96 (0.82, 1.11) 0.558
Chemotherapy before or after mastectomy 1.10 (0.94, 1.30) 0.233
Radiation before or after mastectomy 0.83 (0.66, 1.04) 0.104
Other cancer diagnosis 1.21 (0.98, 1.50) 0.076
Costs of Care
Total costs were calculated and analyzed for each reconstruction type. The costs of the index procedures, that is the costs associated with the mastectomy (and placement of tissue expanders, dermal matrix, etc.) and the initial free-flap reconstruction, were significantly higher for the staged cohort as compared with immediate or delayed (mean costs: staged $106,443, delayed $80,667, immediate $76,756; p < 0.001). Among those who experienced a complication, staged patients displayed significantly higher costs associated with each complication than delayed or immediate reconstruction (mean costs: staged $44,479, delayed $37,148, immediate $40,975; p = 0.03), with similar trends seen among patients who required reoperation (staged $13,861, delayed $7601, immediate $9925; p = 0.004). However, no significant differences in cost were seen according to the method of reconstruction when evaluating readmission (p = 0.31) or ED visits (p = 0.12) (Table 6). In addition, out-of-pocket expenses did not differ across the study cohorts (data not shown).Table 6 Payments to healthcare providers
Immediate (N = 2081) Delayed (N = 353) Staged (N = 560) Total (N = 2994) p-Value
Index procedures
Mastectomy and free flap < 0.0011
N 2039 350 539 2928
Mean (SD) 76,756.8 (50,231.3) 80,667.7 (44,433.0) 106,443.2 (53,781.9) 82,689.1 (51,505.4)
Median 61,969.5 68,950.1 92,873.3 68,634.0
Q1, Q3 41,729.7, 98,102.2 51,473.8, 100,628.8 68314.8, 130,166.4 45,836.2, 104,966.6
Range (14,197.8–329,564.5) (15,309.1–265,721.8) (19,710.4–337,884.4) (14,197.8–337,884.4)
Complications
Mastectomy
N 71 168 239
Mean (SD) 11,610.8 (17,144.4) 18,937.1 (20,318.3) 16,760.7 (19,682.1)
Median 5343.4 11,578.1 9508.0
Q1, Q3 548.1, 16,161.6 3935.5, 25,188.9 1977.5, 23,533.6
Range (16.3–87,845.8) (15.7–96245.4) (15.7–96,245.4)
Free flap
N 129 289 418
Mean (SD) 39,188.9 (47049.5) 46,379.8 (50,707.6) 44,160.6 (49,662.7)
Median 28,848.0 36,274.0 33,327.7
Q1, Q3 2475.0, 57,539.3 4426.8, 73,202.8 3212.9, 68,307.9
Range (0.0–242,821.8) (0.0–285,981.0) (0.0–285,981.0)
Mastectomy or free flap 0.03261
N 792 161 354 1307
Mean (SD) 40,975.1 (49,444.3) 37,147.7 (45,234.4) 44,578.6 (45,773.3) 41,479.7 (47,987.0)
Median 19294.6 21323.4 33458.7 23,133.7
Q1, Q3 3920.9, 62,285.0 2773.0, 54,734.9 6446.0, 68,376.3 4594.4, 64,291.2
Range (48.5–261,618.9) (30.9–242,821.8) (17.4–276,921.9) (17.4–276,921.9)
Reoperations
Mastectomy
N 26 89 115
Mean (SD) 6358.1 (7168.7) 13,992.8 (12,734.6) 12,266.7 (12,113.7)
Median 4902.9 10,239.2 8584.5
Q1, Q3 986.8, 8336.1 4226.1, 19,209.0 3648.4, 18,099.5
Range (84.2–29,952.0) (173.7–68,335.2) (84.2–68,335.2)
Free flap
N 38 105 143
Mean (SD) 8250.0 (11,524.6) 10,278.5 (14,954.8) 9739.4 (14,114.3)
Median 3238.0 5380.6 4153.5
Q1, Q3 1376.8, 12,699.6 633.1, 14,017.9 764.2, 13,398.1
Range (82.6–54,729.5) (0.0–82,257.8) (0.0–82,257.8)
Mastectomy or free flap 0.0041
N 249 63 173 485
Mean (SD) 9925.0 (12,247.9) 7600.9 (10,208.8) 13,861.0 (16,134.0) 11,027.1 (13,702.0)
Median 6071.0 3826.7 9572.5 6385.6
Q1, Q3 2020.1, 11,896.5 1084.4, 10,589.0 2195.5, 18,433.2 1877.4, 14,557.4
Range (0.0–69,158.8) (0.0–54,729.5) (0.0–82,257.8) (0.0–82,257.8)
Readmissions
Mastectomy
N 19 56 75
Mean (SD) 21,439.4 (20,479.7) 30,296.4 (28,444.1) 28,052.6 (26,802.9)
Median 17,348.7 22,103.6 19,715.1
Q1, Q3 11,093.1, 22,940.0 12,771.8, 37,517.0 12,320.1, 31,545.7
Range (6307.1–101,254.2) (5031.4–138,444.3) (5031.4–138444.3)
Free flap
N 25 43 68
Mean (SD) 43,642.8 (42,655.2) 30,174.1 (24,088.4) 35,125.8 (32,531.4)
Median 31,865.9 23,506.3 24,291.9
Q1, Q3 13,564.4, 58,085.3 12,492.0, 44,017.4 13,028.2, 44,769.3
Range (5782.1–153,354.2) (4983.2–98,500.3) (4983.2–153,354.2)
Mastectomy or free flap 0.311
N 169 41 91 301
Mean (SD) 28,160.5 (25,259.7) 32,806.4 (33,233.7) 32,695.3 (29,472.3) 30,164.3 (27,754.6)
Median 18,814.1 18,445.9 23,506.3 19,863.3
Q1, Q3 11,696.0, 36,407.0 11,892.5, 36,741.4 13,680.3, 39,417.0 12,241.0, 37,406.1
Range (2073.2–128283.3) (5782.1–13,6854.7) (4983.2–138,444.3) (2073.2–138,444.3)
ED visits
Mastectomy
N 41 85 126
Mean (SD) 2495.4 (2159.8) 3288.3 (3972.9) 3030.3 (3498.4)
Median 2635.1 1788.4 1883.1
Q1, Q3 801.6, 3150.4 836.9, 3381.1 801.6, 3265.5
Range (63.3–9585.8) (11.8–19242.3) (11.8–19242.3)
Free flap
N 50 69 119
Mean (SD) 3128.2 (3253.0) 2877.1 (3589.9) 2982.6 (3440.4)
Median 2239.2 1783.0 1791.2
Q1, Q3 1184.3, 4402.2 826.2, 3107.7 983.7, 3348.6
Range (45.0–15,941.7) (10.1–19,117.4) (10.1–19,117.4)
Mastectomy or free flap 0.121
N 286 118 195 599
Mean (SD) 2892.7 (3097.5) 3712.5 (5121.6) 3794.3 (4439.1) 3347.7 (4035.8)
Median 1936.8 2650.9 2235.9 2099.5
Q1, Q3 1005.8, 3441.7 1083.8, 4274.9 1031.1, 4497.8 1007.1, 3883.8
Range (0.0–18,724.3) (7.5–45,423.3) (0.0–26,201.2) (0.0–45,423.3)
Total pay within 90 days of procedure(s)
Mastectomy
N 343 550 893
Mean (SD) 52,936.7 (34,178.7) 69,433.3 (36,910.5) 63,097.0 (36,753.9)
Median 44,665.9 62,074.9 55,081.4
Q1, Q3 27,761.0, 68,257.7 41,118.5, 91,734.6 35,748.5, 83,215.1
Range (8916.9–183,553.1) (9474.2–210,533.6) (8916.9–210,533.6)
Free flap
N 346 545 891
Mean (SD) 73,354.3 (47,529.5) 82,752.9 (54,895.8) 79,103.2 (52,332.5)
Median 59,924.2 68,612.9 65,131.6
Q1, Q3 40,218.4, 93,538.2 45,734.8, 98,376.4 43,847.1, 96,863.8
Range (10,884.9–309,972.9) (11,116.6–341,769.2) (10,884.9–341,769.2)
Mastectomy or free flap < 0.0011
N 2041 350 538 2929
Mean (SD) 97,687.5 (59,546.4) 124,405.4 (63,682.3) 147,476.6 (65,949.9) 110,025.5 (64,343.1)
Median 81,612.4 110,467.7 136,033.3 95,483.4
Q1, Q3 54,697.8, 124,833.8 78,158.2, 152,687.0 99,133.1, 179,311.1 62,751.9, 141,316.2
Range (20,025.2–407,256.9) (20,117.3–354,747.4) (20,957.7–395,388.8) (20,025.2–407,256.9)
1Kruskal–Wallis
This table only includes patients who did not have a capitated service plan. Costs greater than 99th percentile or below 1st percentile were excluded.
A gamma regression assessed the association of the type of reconstruction with total cost, demonstrating that after adjusting for covariates, the mean cost was 31% higher (95% CI: 23–39%; p < 0.001) for those undergoing staged when compared with immediate, 11% higher (95% CI: 3–20%; p = 0.008) for staged when compared with delayed, and 18% higher (95% CI: 10–25%; p < 0.001) for delayed when compared with immediate (Table 7).Table 7 Gamma regression of cost
Variable Cost ratio (95% confidence interval) p-value
Reconstruction method
Immediate Reference –
Delayed 1.18 (1.10, 1.25) <0 .001
Staged 1.31 (1.23, 1.39) < 0.001
Staged versus delayed 1.11 (1.03, 1.20) 0.008
Age (years) 1.00 (1.00, 1.00) 0.148
NCI comorbidity index 1.02 (0.97, 1.08) 0.401
Rural versus urban 0.96 (0.89, 1.03) 0.267
Region
South Reference –
North Central 1.05 (0.99, 1.11) 0.104
Northeast 1.19 (1.14, 1.25) < 0.001
West 1.03 (0.97, 1.09) 0.362
Employment status
Employed full or part-time Reference –
Disability 0.93 (0.72, 1.21) 0.602
Other/unknown 0.82 (0.78, 0.86) < 0.001
Retiree 1.12 (1.04, 1.21) 0.003
Bilateral mastectomy 1.04 (1.00, 1.09) 0.034
Lymph node surgery at time of mastectomy 1.07 (1.03, 1.12) < 0.001
Chemotherapy before or after mastectomy 1.26 (1.21, 1.31) < 0.001
Radiation before or after mastectomy 1.12 (1.05, 1.18) < 0.001
Other cancer diagnosis 1.07 (1.01, 1.13) 0.022
Dermal matrix 1.11 (1.05, 1.18) < 0.001
Sensitivity Analysis
Due to the significant impact of radiation therapy on surgical outcomes,20 a sensitivity analysis was conducted with patients who did not undergo radiation. Increased costs and risk of complications and HCRU continued to be observed with staged reconstruction irrespective of the status of radiation therapy. The demographics and results of the sensitivity analysis are presented in SDC Tables 5 and 6, respectively.
Discussion
In this study, we conducted a longitudinal assessment of complications, costs, and HCRU across patients who underwent a mastectomy and free-flap breast reconstruction. Specifically, we focused on comparing outcomes between the staged technique with immediate and delayed techniques for free-flap breast reconstruction. We observed that when compared with immediate or delayed techniques, patients who undergo staged reconstruction experience a significantly increased risk of developing complications, both after the mastectomy and after the free flap is performed. Furthermore, we observed that this increased risk of complications translates into significantly increased costs and HCRU, including ED visits, reoperation, and readmission. Overall, staged free-flap breast reconstruction is associated with a higher rate of complications and significant consumption of healthcare resources in the 90 days following both the mastectomy and the free-flap procedure.
Overall complication rates after free-flap breast reconstruction are reported to approach 20–50%.13,18,21–25 Most studies, however, have excluded patients undergoing staged free-flap breast reconstruction. Olsen et al. reported in a claims-based analysis that rates of infection and wound healing complications were not influenced by the timing of immediate, delayed, or staged autologous reconstruction. However, their study captured all forms of autologous reconstruction including pedicled flap procedures, and reported a relatively small cohort size of 95 patients who underwent two-stage autologous reconstruction.24 Phillips et al. reported in an institutional review that patients undergoing staged free-flap breast reconstruction display a three-times higher rate of skin complications following radiation therapy and a 7.5-times higher rate of microvascular-related complications (flap loss and vessel thrombosis) when compared with standard delayed patients.10 This increased complication rate was supported in a separate institutional review that described significantly increased rates of surgical complications that predominately occurred after mastectomy in the first reconstructive stage with tissue expander placement.11
The results of this study provide a granular evaluation of complications that occur after each reconstructive stage and echo previous institutional reports demonstrating a significantly increased risk of all-cause complications among patients undergoing staged free-flap breast reconstruction. This includes over a tenth of patients experiencing tissue expander infection, extrusion, and/or microvascular-related complications after the free-flap procedure. High rates of tissue expander-related complications may be attributed to the placement of the tissue expander in a hypovascular field with a large amount of dead space following mastectomy, leading to complication rates that parallel those seen with direct implant reconstruction.13,24 In addition, as previously proposed, we believe that an increased rate of microvascular-related complications may be attributed to increased compression and scarring of the chest wall secondary to tissue expander placement, ultimately leading to increased fibrosis and friability of the internal mammary vessels.
Prior studies have focused on comparing healthcare expenditures between implant and autologous techniques, with all studies concluding that early postoperative complications and risk profiles favor implant-based reconstruction; however, long-term resource utilization favors autologous and free-flap procedures.18,21 To date, no studies have provided an in-depth examination of the effect of the timing of free-flap breast reconstruction on costs and HCRU to better inform clinical decision-making. The results of this study suggest that immediate free-flap breast reconstruction is associated with the lowest rate of readmission, reoperation, and ED visits. However, patients who undergo a staged procedure demonstrate a significantly increased risk of experiencing HCRU, with nearly 50% of staged patients experiencing a component of HCRU within 90 days of their mastectomy and/or free-flap. These significantly increased rates of utilization may be attributed to more than 60% of staged patients experiencing a systemic or surgical complication after their mastectomy and/or free-flap procedure.
Reconstructive pathways, comorbidities, and adjuvant therapies distinctly contribute to the total costs of reconstructive care. As the costs accrued following free-flap reconstruction are most pronounced within the first year, it is important to understand how different timings and modalities of free-flap reconstruction may influence total costs. Additionally, as operating room efficiency continues to be prioritized in the COVID-19 era and staffing shortages lead to decreased operating room availability, renewed emphasis has been placed on staged reconstruction to offer an efficient treatment to breast cancer patients.26,27 Fischer et al. conducted a longitudinal assessment of costs accrued following immediate tissue expander, implant, or autologous breast reconstruction, demonstrating that tissue expander reconstruction was associated with the lowest charges ($39,470) within 90 days and autologous reconstruction was associated with the highest ($54,309).18 Expanding on these results, Berlin et al. demonstrated how costs accrued secondary to complications, comorbidities, or adjuvant therapies differ significantly based on the reconstructive modality.28 Our results uniquely contribute to these findings by expounding on the influence of the timing of free-flap reconstruction on costs accrued within 90 days following the mastectomy and free-flap procedure. More specifically, our results demonstrate that combining tissue expander and free-flap reconstruction for a staged procedure is associated with significantly higher costs throughout both 90-day episodes of reconstructive care. Notably, among patients experiencing an adverse event, those who undergo staged reconstruction had significantly higher costs associated with complications and reoperations as compared with patients undergoing immediate or delayed reconstruction. As physician reimbursement for breast reconstruction continues to change with mean payments for tissue expanders shown to increase over time (estimated 6.5% growth of a 4-year period) future research should assess how changes in reimbursement patterns may ultimately influence surgeon decision-making for a staged approach to free-flap breast reconstruction.29,30
Berlin et al. suggest that adjuvant chemotherapy and/or post-mastectomy radiation therapy (PMRT) independently contribute significant amounts to the total cost of reconstructive care; thus, a higher total cost among the staged cohort may partially be attributed to a higher proportion of staged patients receiving chemotherapy and/or PMRT.28 This finding may also be attributed to attempts to salvage the tissue expander, including intravenous antibiotics, tissue expander replacement, and/or prolonged readmissions. Interestingly, in our study, out-of-pocket costs did not demonstrate a clinically significant difference when comparing the patient cohorts. These results echo findings by Bailey et al. that demonstrated no differences in out-of-pocket costs according to breast reconstruction subtype, possibly due to most financial exposure being accepted by the insurer regardless of the reconstructive modality; however, future studies are needed to further examine the potential financial toxicity attributed to staged free-flap procedures.31
A primary goal of staged free-flap reconstruction is to preserve the direct psychosocial and esthetic benefits that are seen with an immediate procedure. Albino et al. previously reported that staged reconstruction was associated with improved esthetic outcomes compared with delayed reconstruction.6 This finding was attributed to a staged approach allowing for more native mastectomy skin to be available at the time of reconstruction, resulting in improved scar placement and shaping of the breast mound. However, previous studies have suggested that long-term satisfaction is not influenced by the timing of breast reconstruction, with staged, immediate, and delayed techniques reporting similar degrees of long-term satisfaction after surgery.12,32,33 The findings of our study suggest that staged free-flap reconstruction is associated with significantly increased rates of complications, costs, and HCRU as compared with immediate and delayed techniques. When counseling a patient who has decided to pursue free-flap reconstruction, the potential esthetic benefits of a staged approach should be balanced with an increased risk of complications, costs, and HCRU.
Study Limitations
Clinical data were derived from claims, which were dependent on accurate medical coding. Additionally, women who undergo a bilateral mastectomy may have mixed timing of their reconstruction. We were unable to reliably identify these cases of mixed-reconstruction timing because the contralateral reconstruction may be mistakenly identified as a reconstruction failure. However, we anticipate that mixed-reconstruction timing is rare and should not impact the analysis. In addition, due to the immediate cohort requiring less time for continuous enrollment, this patient population is likely over-represented in our study sample as compared with patients who underwent staged and delayed free-flap reconstruction.
Conclusions
Staged free-flap breast reconstruction is associated with significantly increased complications, costs, and HCRU, while immediate reconstruction is associated with the lowest. These results emphasize the need for health systems to support coordinated, multidisciplinary care to facilitate immediate reconstruction when possible. Patients considering a staged approach should be counseled about the potential esthetic benefit of this procedure in the context of an increased risk for experiencing adverse outcomes, increased costs, and increased HCRU.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 37 KB)
Acknowledgment
The Duke Biostatistics, Epidemiology, and Research Design Core’s support was made possible by the CTSA grant (UL1TR002553) from the National Center for Advancing Translational Sciences (NCATS) of the NIH and the NIH Roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not represent the official views of NCATS or NIH.
Funding
CTSA Grant (UL1TR002553) from the National Center for Advancing Translational Sciences (NCATS) of the NIH and the NIH Roadmap for Medical Research.
Disclosure
No conflicts of interest pertaining to this manuscript are present or need to be disclosed
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36474094 | PMC9735033 | NO-CC CODE | 2022-12-14 23:28:32 | no | Ann Surg Oncol. 2022 Dec 6;:1-16 | utf-8 | Ann Surg Oncol | 2,022 | 10.1245/s10434-022-12896-0 | oa_other |
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Naunyn Schmiedebergs Arch Pharmacol
Naunyn Schmiedebergs Arch Pharmacol
Naunyn-Schmiedeberg's Archives of Pharmacology
0028-1298
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10.1007/s00210-022-02346-9
Review
Cholinergic dysfunction in COVID-19: frantic search and hoping for the best
Nadwa Eman Hassan [email protected]
12
Al-Kuraishy Hayder M. [email protected]
3
Al-Gareeb Ali I. [email protected]
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Elekhnawy Engy [email protected]
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Alorabi Mohammed [email protected]
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Batiha Gaber El-Saber [email protected]
6
De Waard Michel [email protected]
789
1 grid.440748.b 0000 0004 1756 6705 Department of Pharmacology and Therapeutics, College of Medicine, Jouf University, Sakakah, 72345 Saudi Arabia
2 grid.7776.1 0000 0004 0639 9286 Department of Medical Pharmacology, Faculty of Medicine, Cairo University, Giza, 12613 Egypt
3 grid.411309.e 0000 0004 1765 131X Department of Pharmacology, Toxicology and Medicine, College of Medicine, Al-Mustansiriyah University, Baghdad, 14132 Iraq
4 grid.412258.8 0000 0000 9477 7793 Microbiology and Immunology Department, Faculty of Pharmacy, Tanta University, Tanta, 31527 Egypt
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6 grid.449014.c 0000 0004 0583 5330 Department of Pharmacology and Therapeutics, Faculty of Veterinary Medicine, Damanhour University, Damanhour, 22511 Al Beheira Egypt
7 Smartox Biotechnology, 6 Rue Des Platanes, 38120 Saint-Egrève, France
8 grid.4817.a 0000 0001 2189 0784 L’Institut du Thorax, INSERM, CNRS, UNIV NANTES, 44007 Nantes, France
9 grid.460782.f 0000 0004 4910 6551 LabEx “Ion Channels, Science & Therapeutics”, Université de Nice Sophia-Antipolis, 06560 Valbonne, France
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A novel coronavirus known as severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is a potential cause of acute respiratory infection called coronavirus disease 2019 (COVID-19). The binding of SARS-CoV-2 with angiotensin-converting enzyme 2 (ACE2) induces a series of inflammatory cellular events with cytopathic effects leading to cell injury and hyperinflammation. Severe SARS-CoV-2 infection may lead to dysautonomia and sympathetic storm due to dysfunction of the autonomic nervous system (ANS). Therefore, this review aimed to elucidate the critical role of the cholinergic system (CS) in SARS-CoV-2 infection. The CS forms a multi-faceted network performing diverse functions in the body due to its distribution in the neuronal and non-neuronal cells. Acetylcholine (ACh) acts on two main types of receptors which are nicotinic receptors (NRs) and muscarinic receptors (MRs). NRs induce T cell anergy with impairment of antigen-mediated signal transduction. Nicotine through activation of T cell NRs inhibits the expression and release of the pro-inflammatory cytokines. NRs play important anti-inflammatory effects while MRs promote inflammation by inducing the release of pro-inflammatory cytokines. SARS-CoV-2 infection can affect the morphological and functional stability of CS through the disruption of cholinergic receptors. SARS-CoV-2 spike protein is similar to neurotoxins, which can bind to nicotinic acetylcholine receptors (nAChR) in the ANS and brain. Therefore, cholinergic receptors mainly nAChR and related cholinergic agonists may affect the pathogenesis of SARS-CoV-2 infection. Cholinergic dysfunction in COVID-19 is due to dysregulation of nAChR by SARS-CoV-2 promoting the central sympathetic drive with the development of the sympathetic storm. As well, nAChR activators through interaction with diverse signaling pathways can reduce the risk of inflammatory disorders in COVID-19. In addition, nAChR activators may mitigate endothelial dysfunction (ED), oxidative stress (OS), and associated coagulopathy in COVID-19. Similarly, nAChR activators may improve OS, inflammatory changes, and cytokine storm in COVID-19. Therefore, nAChR activators like varenicline in virtue of its anti-inflammatory and anti-oxidant effects with direct anti-SARS-CoV-2 effect could be effective in the management of COVID-19.
Keywords
ACE2
COVID-19
Cholinergic dysfunction
Vagus nerve stimulation
SARS-CoV-2
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pmcIntroduction
A novel coronavirus known as severe acute respiratory syndrome CoV type 2 (SARS-CoV-2) is the potential cause of acute respiratory infection called coronavirus disease 2019 (COVID-19). SARS-CoV-2 uses specific receptors for entry to human cells; one of the most predominant receptors is an angiotensin-converting enzyme type 2 (ACE2) (Al-Kuraishy et al. 2021b) as shown in Fig. 1. The binding of SARS-CoV-2 with ACE2 leads to a series of inflammatory cellular events with cytopathic effects causing cell injury and hyperinflammation. ACE2 is largely distributed and expressed in diverse cellular systems, including enterocytes, cardiomyocytes, pulmonary alveolar cells, neurons, and testes (Moubarak et al. 2021).Fig. 1 Binding of SARS-CoV-2 to ACE2 receptors
The clinical presentation of COVID-19 is mainly asymptomatic or presented with mild symptoms in 85% of cases. However, 15% of COVID-19 patients presented with moderate to severe form due to the progress of acute lung injury (ALI). As well, 5% of COVID-19 patients may be critical and require supported ventilation due to the development of acute respiratory distress syndrome (ARDS) (Al-Kuraishy et al. 2021a). The clinical presentation of COVID-19 has been reported to be considerably different among types and subtypes of SARS-CoV-2 infection. The relationship between SARS-CoV-2 genetic specificities among variants and clinical presentation is scarce (Al-kuraishy et al. 2022c). One variant with a deletion (∆382) in the open reading frame 8 has been associated with milder infections in Singapore and may have played a role in the very low case fatality rate in this country. Spike mutation D614G which probably occurs in China before its diffusion in Europe is associated with a decreased age of COVID-19 patients possibly due to an increased viral load in younger patients. The N501Y mutation is associated with adaptation to rodents, for instance, mice, and may increase SARS-CoV-2 spike protein binding to ACE2 because of conformational changes, thus increasing its transmissibility. The role of ∆69/∆70 on the spike protein is also potentially involved in the increased transmissibility (Al-Thomali et al. 2022). As well, the Gamma variant of SARS-CoV-2 infection was coincident with an increased COVID-19 incidence in younger patients (Luna-Muschi et al. 2022). The increase in the proportion of COVID-19 cases caused by the Gamma variant in early 2021 was temporally associated with the beginning of the vaccination campaign in Brazil. This context raised the concern that the Gamma variant could evade previous SARS-CoV-2 immune response (Goller et al. 2022). A retrospective study and comparative analyses revealed significant differences between recorded symptoms of BA.2 and BA.5 SARS-CoV-2 variants in infected individuals and found strong correlations of associations between symptoms. In particular, the symptoms chills or sweating, freezing, and runny nose were more frequently reported in BA.2 infections. In contrast, other clinical symptoms appeared more frequently in Omicron infections with BA.5. However, there was no evidence that BA.5 has higher pathogenicity or causes a more severe course of infection than BA.2. (Kopańska et al. 2022). These findings highlighted the difference in the clinical presentation of SARS-CoV-2 and its variants.
SARS-CoV-2 is highly identical to other CoVs like SARS and the Middle East Respiratory Syndrome CoV (MERS-CoV) and shares 80% and 60% genomic similarity correspondingly. In addition, SARS-CoV-2 is highly similar at the genomic level to bat CoV (96% similarity percentage) (Babalghith et al. 2022). Nevertheless, SARS-CoV-2 has 20 times higher binding affinity to ACE2 than other CoVs. ACE2 is a peptidase that metabolizes vasoconstrictor angiotensin II (Ang II) to the vasodilators Ang1-7 and Ang1-9 (Halder and Lal 2021). Consequently, downregulation of ACE2 during SARS-CoV-2 infection induces vasoconstriction and development of endothelial dysfunction (ED), oxidative stress (OS), and inflammatory disorder SARS-CoV-2-induced OS triggers activation of different signaling pathways which counterbalances this type of complication (Moran et al. 2019). It has been shown that severe SARS-CoV-2 infection may lead to dysautonomia and sympathetic storm due to dysfunction of the autonomic nervous system (ANS). In this context, Tizabi et al. (2020) hypothesized that nicotinic CS including nicotinic receptor agonists and partial agonists could be beneficial in COVID-19 management. Thus, nicotine, nicotinic receptor agonists, or positive modulators of these receptors may be of therapeutic potential in a variety of diseases including countering at least some of the harms of COVID-19. A review of the latest research recently conducted by Kopańska et al. (2022) regarding disorders of CS in COVID-19 showed that the presence of the SARS-CoV-2 virus disrupts the activity of the CS, for example, causing the development of myasthenia gravis or a change in acetylcholine (ACh) activity (Kopańska et al. 2022). The SARS-CoV-2 spike protein has a sequence similar to neurotoxins, capable of binding nicotinic acetylcholine receptors (nAChR). Nicotine and caffeine have similar structures to anti-viral drugs, capable of binding ACE 2 epitopes that are recognized by SARS-CoV-2, with the potential to inhibit the formation of the ACE 2/SARS-CoV-2 complex. The blocking is enhanced when nicotine and caffeine are used together with anti-viral drugs (Tizabi et al. 2020). These recent studies confirmed that SARS-CoV-2 infection adversely affects CS. However, the mechanistic role of CS against inflammatory signaling pathways in COVID-19 and how nAChR modulators affect the pathogenic role of SARS-CoV-2 infection need to be elucidated. Therefore, this review aimed to clarify the critical role of CS and its modulators in SARS-CoV-2 infection.
Cholinergic system
CS is one of the main parts of ANS that regulate different body functions including memory, cognitive function, sensation, digestive, cardiovascular, and sexual performance (Moran et al. 2019). ACh is the main neurotransmitter of CS that is synthesized from choline by the action of ACh acyltransferase (ChAT) which is mainly found in the cholinergic neurons. ChAT is also expressed in non-neuronal cells including immune cells and splenic cells serving as a major source of extra-neuronal ACh (Jackisch et al. 2009). ACh is metabolized by ACh esterase (AChE) which is found in two forms; true AChE is found in the neurons and neuromuscular junction (NMJ) while pseudo AChE is present mainly in plasma, and can metabolize other agents like procaine (Moran et al. 2019). AChE inhibitors like neostigmine and physostigmine improve cholinergic neurotransmission in the brain and NMJ (Jackisch et al. 2009).
Certainly, ACh acts on two main types of receptors which are either nicotinic or muscarinic. NRs are ion channels consisting of 4 subunits (α, β, γ, and δ) which are bound in different ratios around the channel central pore (Jackisch et al. 2009). NRs are present either as homomers or heteromers. Human NR α3β4 type which is present in the brain and autonomic ganglions is known as neuronal NR (nNR). However, NRs present in the NMJ are known as muscular NRs (mNRs) (Bekdash 2021).
The MRs are metabotropic receptors, which have seven trans-membrane subunit G-protein-coupled receptors, and respond to both muscarine and ACh. There are five types of MRs. The M1, M3, and M5 receptors mediate activation of phospholipase C, while M2 and M4 act via inhibition of adenylate cyclase with reduction of cAMP (Bekdash 2021). Depending on the physiological distributions of MRs, these receptors provoke many signal transductions in a tissue-specific manner. M1 is present mainly in the brain, M2 in the heart, and M3 in the exocrine glands and intestines. The M3 muscarinic receptor is clinically significant in the bladder, airway, eye, and blood vessels in addition to exocrine glands and intestines. M4 and M5 are distributed non-specifically but mainly in the brain (Jackisch et al. 2009).
Cholinergic system and inflammation
The CS forms a complex network that performs different functions in the body due to its distribution in the neuronal and non-neuronal cells (Yuan et al. 2019). Immune cells have a full machinery system for the synthesis and release of ACh. It has been reported that ACh affects the immune cells in paracrine and autocrine manners (Cox et al. 2020). Different studies revealed that ACh level is elevated in various diseases including periodontal diseases, chronic obstructive airway diseases, ischemic stroke, and atopic dermatitis (Yuan et al. 2019). However, the ACh level is reduced in neurodegenerative-associated inflammatory reactions like multiple sclerosis and vascular dementia. Moreover, ChAT is expressed constitutively in B and T cells, macrophages, and mononuclear lymphocytes. Notably, immunological activation induces transcription of ChAT in the immune cells. ChAT is also expressed in the lung alveolar epithelial cells and lung macrophages. Therefore, ChAT agonists and antagonists used in various neurological disorders may affect the immune cells (Nizri et al. 2006).
Furthermore, ACh is highly expressed in lymphocytes, macrophages, and dendritic cells. It has been shown that the AChE serum level was increased in irritable bowel syndrome, liver cirrhosis, multiple sclerosis, and Alzheimer’s disease (Snider et al. 2018). AChE inhibitors like rivastigmine, galantamine, and donepezil may affect autoimmunity and inflammation. Nizri et al. (2006) found that rivastigmine can reduce neuroinflammation and immune reactions.
Indeed, choline transporters (ChTs), which are expressed in the macrophages, microvascular cells, and immune cells, have a significant immunomodulatory effect (Leite et al. 2016). Of note, vesicular ACh transporters (VAChTs) are involved in the storage of ACh. Alterations of VAChTs are linked with the release of pro-inflammatory cytokines including tumor necrosis factor-alpha (TNF-α), interleukin 1-beta (IL-1β), and interleukin 6 (IL-6) (Leake 2019). The exact functions of VAChTs in the immune cells were not elucidated. The experimental study demonstrated that choline uptake is necessary for macrophage activation and IL-1β-mediated inflammation (Leake 2019; Hernandez et al. 2013).
ACh released from the vagus nerve and via its action on the NRs attenuates the release of the pro-inflammatory cytokine from activated macrophages but does not affect the release of the anti-inflammatory interleukin, IL-10. In endotoxemia, stimulation of the vagus nerve prevents the development of homeostatic disturbance (Hong et al. 2019). However, vagus nerve stimulation fails to attenuate inflammatory reactions in NR knockout mice which develop exaggerated immune response and release of pro-inflammatory cytokine (Hampel et al. 2018). In addition, vagus nerve stimulation inhibits the release of TNF-α which is mediated by endotoxemia. Atropine administration does not reduce the anti-inflammatory effect of vagus nerve stimulation as it is mainly mediated by NRs. Despite these findings, central MRs have anti-inflammatory effects through the vagus nerve (Kabata and Artis 2019). Thus, the spleen represents the connecting point between the CNS and the peripheral immune system. Experimental stimulation of the hypothalamus triggers anti-inflammatory effects in the spleen (Huston et al. 2006).
Cholinergic receptors and immune cells
NRs are involved in the regulation of immune cells; ACh generated at the microenvironment stimulates these receptors with subsequent regulation of the proliferation and activation of T cells. In vitro studies demonstrated that the administration of nicotine blocks the activation of T cells through the inhibition of cytotoxic T lymphocyte-associated protein 4 (CTLAP4) (De Rosa et al. 2009). As well, NRs induce T cell anergy with impairment of antigen-mediated signal transduction. Nicotine through activation of T cell NRs inhibits the expression and release of pro-inflammatory cytokines. Thus, α7nAChR antagonists like methyllycaconitine and bungarotoxin accelerate T cells’ proliferative response. A previous study revealed that nicotine attenuates the experimental autoimmune encephalomyelitis in mice through the polarization of T cells toward anti-inflammatory IL-4-producing T cells. Nicotine-induced activation of α7nAChR on the T cells promotes the proliferation of anti-inflammatory regulatory T cells (Pan et al. 2021).
Notoriously, NRs are essential for the maturation and proliferation of B lymphocytes within the spleen and other lymphoid organs. An experimental study revealed that NR knockout mice experienced noteworthy depletion of circulating B lymphocytes with a reduction of IgG-producing cells (Koval et al. 2018). NRs promote the proliferation and activation of B lymphocytes as well as immune-mediated interaction. Further, NRs inhibit the activation of dendritic cells (DC); thus, nicotine-treated DCs cannot activate T cells and produce pro-inflammatory cytokines. As well, NR agonist induces a robust anti-inflammatory effect in mice with collagen-induced arthritis by inhibiting the expression of CD80 on the DC surface (Kanauchi et al. 2022). However, ACh-treated DCs trigger the release of chemokines which promote the recruitment of Th2 cells at the site of inflammation (Gori et al. 2019). ACh-treated murine DCs increased the lung inflammation through the MR-dependent pathway in mice (Gori et al. 2019). In addition, ACh-treated DCs trigger the expression of anti-inflammatory peroxisome proliferator-activated receptor gamma (PPRA-γ) which favors the Th2 lineage through modulation of the balance of Th1/Th2 (Nouri-Shirazi et al. 2015). Notably, activation of NRs on the immature DCs enhances the expression of costimulatory CD80 and CD86 which accelerate the proliferation of T cells (Nouri-Shirazi et al. 2015).
Moreover, activation of NRs on the macrophages attenuates the release of the pro-inflammatory cytokines. NR knockout mice experience high levels of pro-inflammatory cytokines compared to wild-type mice (Fujii et al. 2007). A previous study conducted by Borovikova et al. (2000) found that ACh attenuates LPS-induced activation of human macrophages, preventing the release of pro-inflammatory cytokines. In addition, NR activation by vagus nerve stimulation hampers systemic inflammation. It was illustrated that nicotine through activation of NRs promotes the expression of IL-1 receptor-associated kinase M (IRAK-M) a negative regulator of TLR4, leading to potent anti-inflammatory effects (Youssef et al. 2021).
On the neutrophils, NRs negatively regulate recruitments and maturations of neutrophils at the site of inflammation. It has been reported that the administration of nicotine inhibits the expression of CD11b molecules on the surface of neutrophils through suppression of actin polymerization with subsequent inhibition of neutrophil recruitments. NR agonists block the interaction between monocytes and endothelial cells through suppression of the expression of adhesion molecules (Wu et al. 2022). Moreover, NR agonists attenuate mast cell activation with the inhibition of the release of pro-inflammatory cytokines and leukotrienes. In addition, NR agonists reduce the interaction and affinity of IgG on the surface of mast cells (Kutukova and Nazarov 2020).
Regarding the effects of MRs, it has been shown that neutrophil chemotactic is mediated by MR activation; thus, tiotropium, a selective M3R antagonist, blocks this interaction. As well, M3R participates in the induction of immunothrombosis due to the generation of NET formation. Blocking of M3R prevents release of pro-inflammatory cytokines (Lo et al. 2018). Profita et al. (2012) observed that sputum from smoker patients with chronic obstructive airway disease had a higher concentration of ACh and TGF-β1, and depletion of TGF-β1 reduces the expression of MRs on the lung epithelial cells. In addition, vagal-induced bronchoconstriction is mediated MR3 activation and expression of TNF-α (Profita et al. 2012). It has been demonstrated that MR agonist carbachol augments the phagocytosis in the peritoneal macrophages. However, activation of M1–M3 induces proliferation of macrophages while activation of M1–M2 induces activation of prostaglandin E2 through stimulation expression of protein kinase C (Profita et al. 2012).
These findings suggest that NRs play important anti-inflammatory effects while MRs promote inflammation by inducing the release of pro-inflammatory cytokines.
Clinical significance
The vagus nerve plays a critical role in the modulation of innate immune response and blood pressure control (Tracey 2009). Vagus nerve activity is reduced in response to hyperinflammation and cytokine storm as in sepsis, systemic lupus erythematosus, and rheumatoid arthritis. Vagus nerve stimulation inhibits the release of pro-inflammatory cytokines in various inflammatory disorders (Yang et al. 2022). Notably, H2-blocker famotidine, through vagus nerve stimulation, inhibits the development of pro-inflammatory cytokines. Because evidence is lacking for a direct anti-viral activity of famotidine, a proposed mechanism of action is blocking the effects of histamine released by mast cells (Mendez-Enriquez et al. 2021). As well, famotidine activates the inflammatory reflex via the brain-integrated vagus nerve mechanism which inhibits inflammation through α7nAChR signal transduction, to prevent cytokine storm. Intracerebroventricular administration of famotidine inhibits the release of pro-inflammatory cytokines independent of mast cell inhibition which could be through vagus nerve stimulation (Mendez-Enriquez et al. 2021). This observation confirmed the vagus nerve-dependent anti-inflammatory effect of famotidine in the setting of cytokine storm which is not replicated by high dosages of other H2R antagonists in clinical use (Seyedabadi et al. 2018).
Additionally, MR agonists like methacholine trigger the activation of inflammation and bronchial hyperresponsiveness through the expression of costimulatory molecules. Of interest, M3R activation is associated with immunopathogenesis of B cell lymphoma and Sjogren syndrome which is mainly mediated due formation of excitatory autoantibodies against the parotid gland (Cox et al. 2019). An elegant study illustrated that use of non-selective MR agonist arecoline in the management of cognitive dysfunction led to a reduction in the size of lymphoid organs and spleen. In contrast, the administration of non-selective MR agonist oxotremorine activates heat shock protein factor in rat hippocampus rats leading to anti-inflammatory and anti-oxidant effects in mice (Cox et al. 2019).
Taken together, ACh, NRs, and MRs have important immunoregulatory effects in the mitigation of different inflammatory disorders.
Cholinergic system and viral infections
ACh in virtue of its anti-inflammatory effects is known to cause vasodilatation a marker of acute inflammation thereby facilitating the recruitment and migration of immune cells to the site of inflammation. MRs expressed by the endothelial cells provoke the generation of nitric oxide (NO) which induces vasodilatation. This effect is abolished by MR antagonists, atropine, or NO inhibitors. Of note, deficiency of T cell CAChT in mice promotes T cell exhaustion during viral infections. Therefore, the expression of CAChT and ACh in the immune cells is necessary to combat viral infections (Sajjanar et al. 2016).
Remarkably, the entry of rabies virus into the host cells is through NRs, and this may induce autoimmune disorders and myasthenia gravis. An experimental study confirmed that rabies virus infection is associated with specific alterations in MRs in the brain stem and hippocampus independent of the viral load. Of interest, a specific peptide that binds NRs can abrogate the binding of the rabies virus to the host cells (Sajjanar et al. 2016). Up to date, rabies virus induces substantial downregulation of nAChR with subsequent release of pro-inflammatory cytokines (Lian et al. 2022). In addition, the persistent infection of neuroblastoma cells by the lymphocytic choriomeningitis virus inhibits the expressions of AChE and AChT with subsequent abnormal anti-viral immune response. Furthermore, M2R, which is an autoreceptor inhibiting the release of ACh in the lung, is highly reduced in viral infection, and associated INF release causing an increased release of ACh. However, dexamethasone augments the expression of M2R with subsequent inhibition release of ACh. Different human and animal model studies observed that M3R on bronchial smooth muscles are downregulated by viral infections due to phosphorylation of these receptors by viral neuraminidases with subsequent reduction in affinity to the ACh (Laguna Merced 2021). An experimental study illustrated that infections by influenza and parainfluenza viruses induce bronchial hyperreactivity by encouraging the release of ACh mainly at day 3, reaches the peak at 2 weeks, and then returns to normal level in dogs through the destruction of M2R (Pawełczyk and Kowalski 2017).
Notably, herpes virus infection can induce reactive immunoreactive antibodies which block NRs at NMJ leading to the development of myasthenia gravis. Capo-Velez et al. (2018) disclosed that the expression of α7nAChR in the immune cells and neurons could be a possible link between the pathogenesis of HIV-1 infection and associated cognitive dysfunction in AIDS patients (Pawełczyk and Kowalski 2017). It has been shown that molecular mimicry between gp120 and viral coat protein with α7nAChR may trigger the generation of neurotoxin-affecting NRs in the NMJ with the development of myasthenia. A clinical study involved an AIDS patient treated with pyridostigmine which is an effective agent in the management of under-reactive bladder and myasthenia gravis illustrated that this drug inhibits T cell over-activity with induction of the release of pro-inflammatory IL-10 and increases circulating CD4 level (Valdés-Ferrer et al. 2017). Furthermore, HIV-induced neuroinflammation can affect the expression of anti-inflammatory α7nAChR on the microglia cells. Besides, anti-retroviral drugs like indinavir act as positive allosteric modular of this receptor but it acts as an inhibitor for them at higher concentrations (Ekins et al. 2017). These observations suggest that α7nAChR is highly disturbed in HIV infection and associated with the development of neuroinflammation in AIDS patients.
These observations suggest that CS is highly distorted during various viral infections with subsequent propagation of pro-inflammatory response. Taken together, downregulation of NRs and over-expression of MRs together with dysregulation of M2R in various viral infections lead to hyperinflammation and associated tissue injury.
Cholinergic dysfunction in COVID-19
SARS-CoV-2 infection can affect the morphological and functional stability of the cholinergic system through the disruption of cholinergic receptors. SARS-CoV-2 spike protein is similar to the neurotoxins that can bind nAChR in the ANS, NMJ, and brain (Kopańska et al. 2022). Interestingly, SARS-CoV-2 spike protein epitopes have higher similarity with neurotoxins affecting nAChR (Lagoumintzis et al. 2021). Different in silico studies demonstrated that SARS-CoV-2 spike protein interacts with nAChR through cryptic epitopes similar to that of snake toxins (Batiha et al. 2021).
Of interest, nicotine can bind to ACE2, thus preventing the interaction between SARS-CoV-2 and ACE2 (Al-Kuraishy et al. 2022b). Therefore, cholinergic receptors mainly nAChR and related cholinergic agonists may affect the pathogenesis of SARS-CoV-2 infection (Al-Kuraishy et al. 2021c). It has been observed that the SARS-CoV-2 spike protein has a higher affinity to bind nAChR and produce an antagonist effect. Notably, SARS-CoV-2 spike protein and other proteins have an identical sequence to the nicotinic receptor antagonists indicating that SARS-CoV-2 blocks the functional activity and stability of nAChR (Kloc et al. 2020). Tizabi et al (2020) proposed that downregulation of nAChR during SARS-CoV-2 infection promotes the release of pro-inflammatory cytokines. This effect is due to the suppression of anti-inflammatory nAChR on the immune cells. In turn, the pro-inflammatory cytokines inhibit the expression and functional capacity of nAChR (Tizabi et al. 2020). This finding suggests that nAChR are inhibited either directly by SARS-CoV-2 or indirectly by exaggerated immune response and high level of pro-inflammatory cytokines.
Therefore, the interaction between SARS-CoV-2 spike protein and nAChR triggers hyperinflammation and the development of cytokine storm in COVID-19. In addition, dysregulation of brain nAChR in SARS-CoV-2 infection exaggerates neuroinflammation in COVID-19 (Farsalinos et al. 2020). Remarkably, a positive allosteric modulator of nAChR ivermectin can modulate SARS-CoV-2 infection-induced dysautonomia and neuroinflammation (Pąchalska et al. 2021).
Moreover, inhibition of platelet nAChR by SARS-CoV-2 promotes platelet hyperreactivity and thrombosis a hallmark of COVID-19. Of note, ACh acts as an endogenous inhibitor of platelet aggregation; thus, augmentation of ACh and activation of platelet nAChR could be a promising option in the mitigation of SARS-CoV-2-induced thrombosis (Farsalinos et al. 2020).
Cholinergic dysfunction in COVID-19 is due to dysregulation of nAChR by SARS-CoV-2 which promotes the central sympathetic drive with the development of sympathetic storm (Alexandris et al. 2021). In turn, sympathetic storm triggers oxidative stress and hyperinflammation by increasing the generation of ROS and release of pro-inflammatory cytokines (Al-Kuraishy et al. 2021c). Therefore, the use of cholinergic agonists or β-adrenoceptor antagonists might be beneficial in severely affected COVID-19 patients. Of note, β-blockers are effective in the mitigation of sympathetic and cytokine storms. Uncontrolled sympathetic activation in COVID-19 is due to the inhibition of counterbalance CS. Therefore, activation of CS and inhibition of the sympathetic nervous system (SNS) could be an effective therapeutic strategy in the mitigation of COVID-19 complications (Al-Kuraishy et al. 2021d).
Furthermore, a prospective study involving 37 COVID-19 patients compared to 14 healthy controls revealed that the expression of the nAChR gene was reduced in COVID-19 due to exaggerated pro-inflammatory cytokines (Courties et al. 2021). Of note, IL-6 and TNF-α, which are the major pro-inflammatory cytokines, inhibit the expression of anti-inflammatory effect of nAChR (Courties et al. 2021). Consequently, reduction of nAChR promotes the release of pro-inflammatory cytokines with increasing risk for development of cytokine storm (Mehranfard and Speth 2022).
Higher expression of pro-inflammatory cytokines inhibits expression of the nAChR gene (Courties et al. 2021). As well, AChE activity was dysregulated in severely affected COVID-19 patients causing an additional impact on the cholinergic activity. Bahloul et al. (2022) observed that low level of AChE activity was associated with high mortality so it can be used as a prognostic biomarker of COVID-19 patient severity. A retrospective study, which involved 137 COVID-19 patients, illustrated that AChE activity was reduced in critically affected COVID-19 patients compared to the mild one (Bahloul et al. 2022). AChE is reduced in sepsis due to the inflammatory process and acute phase reaction. AChE level at the time of admission is regarded as an independent predictor for mortality in COVID-19 patients (Nakajima et al. 2021).
Taken together, as the virus replicates, the virions may interact with the nAChRs blocking the action of the cholinergic anti-inflammatory pathway. If the initial immune response is not enough to combat the viral invasion at an early stage, the extensive and prolonged replication of the virus will ultimately disturb the cholinergic anti-inflammatory pathway seriously compromising its ability to control and regulate the immune response (Farsalinos et al. 2020). The uncontrolled action of pro-inflammatory cytokines will result in the development of cytokine storm, with ALI leading to ARDS, coagulation disturbances, and multi-organ failure. Based on this hypothesis, COVID-19 appears to eventually become a disease of the nicotinic CS. Nicotine could maintain or restore the function of the cholinergic anti-inflammatory system and thus control the release and activity of pro-inflammatory cytokines. This could prevent or suppress the cytokine storm (Mazloom 2020).
Overall, the changes in the CS in viral infection are not consistent with those in COVID-19 which might due to distinct binding activity of SARS-CoV-2 to nAChR. These verdicts proposed that deregulation of nAChR expression and AChE activity in severe SARS-CoV-2 lead to propagation of immunoinflammatory disorders associated with COVID-19 severity.
nAChR and inflammatory signaling pathways in COVID-19
SARS-CoV-2 infection and irregular immune response are linked with the commencement of various types of inflammatory signaling pathways leading to hyperinflammation. NLRP3 inflammasome is extremely activated during exaggerated immune response leading to multiple complications in COVID-19 (Mostafa-Hedeab et al. 2022). Targeting of NLRP3 inflammasome pathway by selective inhibitors may reduce COVID-19-induced complications (Al-Kuraishy et al. 2022e). Activation of anti-inflammatory nAChR inhibits various inflammatory signaling pathways like NLRP3 inflammasome via inhibition of β-arrestin 1in mice. Deng and coworkers observed that activation of nAChR reduces the development of pulmonary hypertension induced by monocrotaline in rats (Deng et al. 2019). Consequently, nAChR activators could play important role in the reduction of SARS-CoV-2 infection-induced inflammation through suppression of NLRP3 inflammasome in COVID-19 (Ke et al. 2017).
As well, activation of NLRP3 inflammasome is associated with more expression of NF-κB which increases inflammatory disorders via the release of pro-inflammatory cytokines in COVID-19 (Al-Kuraishy et al. 2022g). Worth mentioning, nAChR activators attenuate the expression of NF-κB leading to potent anti-inflammatory effects. nAChR activators prevent the development of ALI in mice by suppressing the NF-κB pathway (Patel et al. 2017).
Notably, immune response during acute cell injury persuades expression of toll-like receptor 4 (TLR4) and high-mobility box protein 1 (HMBP1). As well, nAChR activators reduce the expression of pro-inflammatory cytokines including MCP-1, TNF-α, IL-6, and IL-1β by inhibiting the recruitment of RNA polymerase II and macrophage activation. Thus, nAChR activators attenuate the development of inflammatory changes through modulation of the expression of the pro-inflammatory cytokines (Mizrachi et al. 2021).
In COVID-19, the expressions of TLR4 and HMBP1 are exaggerated leading to induction of the release of pro-inflammatory cytokine and immunothrombosis, respectively. HMBP1 induction in COVID-19 provokes the recruitment of neutrophils with the formation of neutrophil extracellular traps (NETs) which cause more inflammation and thrombosis termed immunothrombosis. Interestingly, nAChR activators suppress inflammatory reactions and inhibit the expression of MCP-1, TNF-α, IL-6, and IL-1β as well as the expression of adhesion molecules (Abdallah et al. 2007).
In addition, the mechanistic target of the rapamycin (mTOR) pathway promotes viral replication and growth in COVID-19. Notably, mTOR is a serine/threonine kinase that controls cell growth by enhancing mTOR1 and mTOR2. Previous research identified that metformin which is an agent widely used to treat type 2 diabetes due to AMPK activation was effective in treating influenza virus infection through inhibition of the mTOR inhibitor pathway (Karam et al. 2021). It has been suggested that the mTOR pathway is essential for the replication of SARS-CoV-2, and the use of mTOR inhibitors and modulators like sapanisertib and metformin, respectively, may reduce COVID-19 severity. Witayateeraporn et al. (2020) showed that nAChR blocks migration and proliferation of non-small-cell lung cancer via inhibition of the mTOR pathway. Besides, nAChR activators and allosteric modulators mitigate inflammatory changes in inflammatory bowel disease by inhibiting autophagy and expression of mTOR (Witayateeraporn et al. 2020).
In this state, nAChR activators may decrease the severity of SARS-CoV-2 infection and associated complications via modulation of the mTOR pathway. Noticeably, advanced glycation end products (AGEs) encourage the release of pro-inflammatory cytokines and induce the propagation of OS and inflammatory disorders. Receptors for AGEs (RAGE) expressed in pulmonary epithelial alveolar cells are intricate in the pathogenesis of SARS-CoV-2 infection and associated lung inflammation, ALI, and ARDS (Perrone et al. 2020). Both diabetes and the aging process accelerate the production of AGEs, which via interaction with RAGE on the macrophages, triggers lung inflammation in COVID-19. It has been shown that nAChR activators decrease AGE-induced inflammatory changes in myasthenia gravis. Preclinical evidence showed that RAGE and its legends are exaggerated in experimental autoimmune myasthenia gravis which is associated with nAChR dysfunction in the NMJ (Lim et al. 2021). AGEs are produced due to the glycation of DNA, proteins, and lipids that participates a critical role in the pathogenesis of metabolic and inflammatory disorders. Besides, nAChR is reduced in different metabolic disorders including diabetes mellitus. This may explain the susceptibility of patients with metabolic disorders to the risk of SARS-CoV-2 infection and COVID-19 severity. Therefore, activation of nAChR may attenuate AGE-mediated hyperinflammation in COVID-19 patients (Xie et al. 2020).
Similarly, soluble RAGE (sRAGE) plasma level is correlated with COVID-19 severity. A prospective cohort study included 164 COVID-19 patients compared to 23 non-COVID-19 pneumonia illustrating that high sRAGE plasma level was linked with the need for oxygen therapy and 30-day mortality (Lim et al. 2021). Hence, sRAGE is regarded as a potential biomarker that predicts COVID-19 severity and mortality. Furthermore, signal transducer and activator of transcription 3 (STAT3) are exaggerated in SARS-CoV-2 infection leading to hyperinflammation, thrombosis, and lung fibrosis (Al-Kuraishy et al. 2022f). In addition, STAT3 impairs the anti-viral immune response and the development of lymphopenia. In this, targeting STAT3 in COVID-19 may mitigate hyperinflammation and related fatal complications. Likewise, ADAM-metalloproteinase domain 17 (ADAM17) activates TNF-α and shedding of ACE2, with the facilitation of SARS-CoV-2 entry (Palau et al. 2020). It has been recognized that nAChR activators reduce COVID-19 severity through inhibition of the ADAM17 pathway. Thus, nAChR activators play a crucial role in the attenuation of inflammatory disorders in COVID-19 through the inhibition of STAT3 and ADAM17 pathways (Palau et al. 2020).
This greater activation is accompanied by greater activity in the vagus efferent nerve that can increase the release of acetylcholine through direct or indirect pathways and mediated by T lymphocytes (Al-kuraishy et al. 2022d). Thus, the components of this pathway act in a way to reduce the production and release of pro-inflammatory cytokines, such as TNF-α and IL-6, of the immune system. In this perspective, when the severity of the cytokine storm in the pathological scenario of COVID-19 and its involvement with MS is understood, the activation of the anti-inflammatory reflex mechanism can modulate the exaggeration of the effects of pro-inflammatory cytokines and reduce the symptom level (Al-Kuraishy et al. 2022a).
These verdicts pointed out that nAChR activators are intricate with diverse signaling pathways to reduce the risk of inflammatory disorders in COVID-19.
nAChR and endothelial dysfunction in COVID-19
SARS-CoV-2 infection primarily affects the vascular endothelium leading to ED and the development of coagulopathy. SARS-CoV-2 infects the endothelial cells directly due to abundant expression of ACE2 causing cellular injury and apoptosis with subsequent reduction of endothelial cells’ capacity to release anti-thrombotic factors (Gavriilaki et al. 2020). In addition, injury of pulmonary vascular endothelial cells, by direct cytopathic effects of SARS-CoV-2 or due to OS and hyperinflammation, leads to pulmonary microthrombosis, a marked feature of COVID-19 (Bonaventura et al. 2021). Notably, circulating endothelial cells and soluble intercellular adhesion molecule 1 levels are augmented in severely affected COVID-19 patients. ED is regarded as a risk factor for the development of microvascular dysfunction and immunothrombosis due to NET formation and platelet activation. It has been reported that nicotine improves endothelial function via the enhancement of the nAChR on the endothelial progenitor cells. As well, nAChR plays an essential role in the prevention of endothelial injury and rupture of atherosclerotic plaque. Besides, activation of non-neuronal endothelial nAChR improves inflammatory changes, OS, migration, and survival of endothelial cells (Vieira-Alves et al. 2020).
Moreover, the vascular endothelium is an active paracrine, endocrine, and autocrine organ that is indispensable for the regulation of vascular tone and the maintenance of vascular homeostasis. ED is a principal determinant of microvascular dysfunction by shifting the vascular equilibrium towards more vasoconstriction with subsequent organ ischemia, inflammation with associated tissue edema, and a pro-coagulant state (Varga et al. 2020). SARS-CoV-2 infection facilitates the induction of endothelins in several organs as a direct consequence of viral involvement and of the host inflammatory response. In addition, induction of apoptosis and pyroptosis might have an important role in endothelial cell injury in patients with COVID-19. COVID-19-endotheliitis might explain the systemic impaired microcirculatory function in different vascular beds and their clinical squeal in patients with COVID-19 (Simões et al. 2021; Elekhnawy et al. 2022). Vascular endothelins and consequent ED can be a principal determinant of microvascular failure, which would favor impaired perfusion, tissue hypoxia, and subsequent organ failure. In severe COVID-19, emerging data indicate a crucial role of widespread endothelins as a key player in provoking scattered microvascular disruption and eventually dysfunction of different organ systems (Hattori et al. 2022; Attallah et al. 2021). Calabretta et al. (2021) suggest that SARS-CoV-2 directly targets endothelial cells, promoting the release of pro-inflammatory and pro-thrombotic molecules. ED appears to be a crucial initiating step in the pathogenesis of the disease and its ensuing morbidity and mortality. Endothelins with the hyperproduction of cytokines lead to cytokine-releasing syndrome, hypercoagulability, and thrombotic microangiopathy which are hallmarks shared by COVID-19 and endothelial injury syndromes (Calabretta et al. 2021). Most importantly, endothelial-protective agents represent a promising and rational therapeutic strategy for COVID-19. As a unifying concept, heparanase inhibition, with the modulation of related pathways and other effects on endothelial stress responses, may thus be crucial in mediating anti-viral and anti-inflammatory activity (Calabretta et al. 2021; Elekhnawy and Negm 2022).
Furthermore, nAChR activators attenuate the development of immunothrombosis and coagulopathy through mitigation of hyperinflammation and OS which is involved in the propagation of ED and associated coagulopathy (Yilmaz et al. 2010; Al-kuraishy et al. 2022c). These verdicts suggested that nAChR activators may mitigate ED, OS, and associated coagulopathy in COVID-19.
nAChR and renin angiotensin system in COVID-19
SARS-CoV-2 infection provokes the downregulation of ACE2 which is involved in the metabolism of angiotensin II (AngII) to angiotensin 1–7 (Ang1–7). This interaction leads to the over-expression of pro-inflammatory AngII and reduction of anti-inflammatory Ang1-7 with subsequent development of ALI/ARDS. Dysregulation of the renin-angiotensin system (RAS) is connected with the development of OS and inflammation by increasing the expression of NADPH and pro-inflammatory cytokines, respectively (Alomair et al. 2022). Advanced circulating AngII level inhibits endogenous anti-oxidant capacity and may inhibit the expression of nAChR. It has been shown that nicotine affects RAS homeostasis through upregulation of the expression of ACE, AngII, and AT2R with downregulation of the expression of ACE2 and Ang1-7 (Batiha et al. 2022). However, an experimental study showed that activation of nAChR reduced AngII-induced vascular smooth cell senescence by promoting the expression of nicotinamide adenine dinucleotide (NAD) (Li et al. 2016). Therefore, dysregulation of RAS in COVID-19 could be a possible reason behind the reduction of nAChR activity. Thus, angiotensin receptor blockers (AT1R) may be beneficial in preventing OS and inflammatory reactions via upregulation of the anAChR pathway (Mogi et al. 2012).
nAChR and cytokine storm in COVID-19
Cytokine storm is developed in severe cases of COVID-19 due to exaggerated immune response and release of a huge amount of pro-inflammatory cytokines in parallel with the reduction of anti-inflammatory cytokine (Zanza et al. 2022). Cytokine storm is also developed due to cholinergic dysfunction and sympathetic over-activity in severe COVID-19. Direct inhibition of nAChR by SARS-CoV-2 induces hyperinflammation and immunopathogenesis (Tillman et al. 2022). In addition, pro-inflammatory cytokines which cross the blood–brain barrier (BBB) can inhibit the autonomic center and central anti-inflammatory nAChR with the development of neuroinflammation (Jiang et al. 2021). In turn, neuroinflammation and dysregulated central nAChR trigger sympathetic discharge with the development of a sympathetic storm (Yue et al. 2015). Notably, dysregulated nAChR on the immune cells by SARS-CoV-2 provokes the release of pro-inflammatory cytokines with the development of cytokine storm. These observations proposed that dysregulation of central and peripheral nAChR during SARS-CoV-2 infection could be the potential mechanism for the development of cytokine storm in COVID-19 (Yue et al. 2015; Khudhair et al. 2022).
On the other hand, nAChR activators can inhibit the expression of pro-inflammatory cytokines and the development of cytokine storm in COVID-19. Above all, nAChR has an important role in the regulation of immune response and the promulgation of inflammation. It decreases the expression of pro-inflammatory cytokines including MCP-1, TNF-α, IL-6, and IL-1β by inhibiting the recruitment of RNA polymerase II and macrophage activation. Diverse experimental studies confirmed that nAChR activators inhibit the expression and release of pro-inflammatory cytokines (Jiang et al. 2021). Likewise, nAChR activators attenuate the development of airway inflammatory disorders, ED, and lung inflammation. The nAChR activators inhibit the activation of different inflammatory signaling pathways including NLRP3 inflammasome, TLR4, HMBP1, NF-κB, and STAT3 that are involved in the development of cytokine storm. Amazingly, nAChR activators block the OS pathway which activates inflammatory signaling pathways like NF-κB and NLRP3 inflammasome (Liu et al. 2015). Similarly, nAChR activators inhibit abnormal and exaggerated immune through the inhibition of INF activation, thereby preventing the excessive release of pro-inflammatory cytokines. Thus, nAChR activators could be effective in the attenuation of SARS-CoV-2 infection-induced cytokine storm (Ren et al. 2018). Therefore, nAChR activators may alleviate oxidative stress and inflammatory changes as well as prevent the development of cytokine storm in COVID-19.
Role of nAChR agonists/antagonists in COVID-19
Varenicline
Different nAChR agonists had been repurposed in treating SARS-CoV-2 infection. Varenicline is a selective nAChR agonist; it affords a full agonist effect on the α7 subunit and a partial agonist effect on the other subunit of nAChR. Varenicline is an FDA drug for the treatment of smoking cessation and was recently hypothesized as a potential drug for the treatment of SARS-CoV-2 infection by inhibiting binding and proliferation processes (Nau et al. 2021). In silico study demonstrated that varenicline binds SARS-CoV-2 spike protein with higher affinity (Ramírez-Salinas et al. 2020). Topical administration of varenicline via the trans-nasal route may attenuate the transmission of SARS-CoV-2 at the site of infection through modulation of nAChR on the olfactory bulb. In vitro study confirmed that varenicline had an anti-SARS-CoV-2 effect without a negative effect on cell viability (Nau et al. 2021). Therefore, varenicline can inhibit transmission and pathogenesis of SARS-CoV-2 infection via inhibition of the interaction between SARS-CoV-2 and ACE2. Notoriously, varenicline can inhibit the proliferation of different variants of SARS-CoV-2 infection (Ramírez-Salinas et al. 2020). It has been revealed that varenicline attenuates inflammatory changes in mice with an experimental stroke model. Ho et al. demonstrated that varenicline could attenuate ischemic-reperfusion injury and associated inflammation in mice following testicular torsion via inhibition of the release of pro-inflammatory cytokines. In addition, varenicline reduces LPS-induced hyperinflammation by inhibiting macrophage activity. A prospective study that involved 100 smokers randomized into varenicline and nicotine replacement therapy for 3 months showed that varenicline replacement therapy was more effective in reduction of OS and ED (Ikonomidis et al. 2017). The activation of nAChRs by either endogenous or exogenous agonists is induced by opening the ion channel in the receptor, allowing the flow of cations, and results in a variety of biological responses. nAChR antagonists, such as α-neurotoxins, compete with typical agonists for binding, and their binding is restricted to nAChR α-subunits. Nicotine and other nicotinic cholinergic agonists are FDA-approved drugs for several pathologies including for smoking cessation and may reverse this binding, by competing for binding with the SARS-CoV-2 spike glycoprotein and promoting the activity of the cholinergic anti-inflammatory pathway (Seyedaghamiri et al. 2022). These verdicts suggest that varenicline in virtue of its anti-inflammatory and anti-oxidant effects with direct anti-SARS-CoV-2 effect could be effective in the management of COVID-19.
Memantine
Memantine is an FDA-proofed drug for the treatment of Alzheimer’s disease acts by blocking N-methyl-D-aspartate (NMDA) receptors (Zhu et al. 2020). It acts by different mechanisms; it blocks α7nAChR which may explain the worsening of cognitive function of patients with Alzheimer’s disease during the early phase of treatment. Later on, the α7nAChRs are rapidly upregulated, and this may explain the positive effect in the enhancement of the cognitive function of patients with Alzheimer’s disease. In vitro experiments illustrated that memantine inhibits the SARS-CoV-2 E protein which is necessary for pathogenesis and viral proliferation (Matsunaga et al. 2018). As well, NMDA antagonists like memantine and amantadine could be used as prophylactic agents and reduce neuropsychiatric complications in COVID-19 patients (Marinescu et al. 2020). Memantine also reduced HCoV‐OC43 replication in the CNS, indicating that it could be utilized as an anti-viral agent and improve neurological diseases. Besides coronavirus OC43, memantine has also been investigated regarding other neurotrophic viruses such as rabies and Japanese encephalitis virus (JEV), and while of limited effectiveness in a rabies challenge experiment, mildly extending survival time in mice, in JEV, survival time was significantly increased, inflammatory cell infiltrates, and intravascular cuffing were significantly reduced and mouse brain JEV content was less (Sun et al. 2019). There were several patients with multiple sclerosis (n = 10), Parkinson’s disease (n = 5), and cognitive impairment (n = 7), who were treated with adamantanes, 15 with amantadine, and seven with memantine; all the patients had SARS‐CoV‐2 documented by real‐time polymerase chain reaction nasopharyngeal swabs, undergoing 2-week quarantine since documented exposure, and none developed clinical disease (Rejdak and Grieb 2020). Hasanaic and Serdarevic (2020) illustrated that memantine could be effective against SARS-CoV-2 infection through the downregulation of ACE2 and reduction of glutamate excitotoxicity. ACE2 is protective rather than harmful as expected earlier in the COVID-19 pandemic. Recombinant ACE2 has protective effects against ALI/ARDS in COVID-19 through its anti-inflammatory effects (Wang et al. 2022). Children and female sex are less susceptible to SARS-CoV-2 infection due to higher expression of ACE2. As well, low expression of ACE2 in the old age group makes them more vulnerable to SARS-CoV-2 infection. Particularly, drugs that increase the expression of ACE2 were more effective in the management of COVID-19. Thus, the protective effect of memantine against SARS-CoV-2 infection could be independent of nAChR/ACE2 axis (Wang et al. 2022).
Further, memantine has a potent anti-inflammatory effect through the inhibition of the release of the pro-inflammatory cytokine and the development of cytokine storm. Likewise, memantine reduces the expression of NF-κB which can prevent microglial activation and associated neuroinflammation in COVID-19 (Jiménez-Jiménez et al. 2020). Despite these findings, clinical evidence for use of memantine in COVID-19 patients is limited. A questionnaire-based study that involved 10 patients with multiple sclerosis and 5 patients with Parkinson’s disease showed that those patients remain asymptomatic despite a positive PCR test for SARS-CoV-2 (Rejdak and Grieb 2020). So, memantine could be effective against the development of symptomatic COVID-19. As well, memantine can provide protection for olfactory neurocircuits, decrease the aggressiveness of NMDA receptor hyperactivity, alveolar protection, and regulate cytokine mechanisms (Marinescu et al. 2020).
Therefore, memantine can decrease COVID-19 severity through its anti-inflammatory effect and modulation of NMDA activity independent of nAChR blocking effect and ACE2 expression as shown in Fig. 2.Fig. 2 Effect of nicotine agonist on the pathogenesis of SARS-CoV-2 infection
Taken together, both memantine and varenicline seem to be effective in the prevention and treatment of SARS-CoV-2 infection through modulation of the anti-inflammatory CS. In this state, clinical trials for use of memantine and varenicline in COVID-19 patients are recommended.
Vagus nerve stimulation in COVID-19
It has been reported that non-invasive vagus nerve stimulation was approved by FDA for the treatment of cluster headache and migraine. Vagus nerve stimulation is effective in SARS-CoV-2 infection via suppression of the release of the pro-inflammatory cytokines. Remarkably, vagus nerve stimulation attenuates the development of cytokine storm and the need for invasive oxygen therapy and mechanical ventilation in severely affected COVID-19 patients (Mwamburi et al. 2017). Stimulation of the vagus nerve triggers bronchial parasympathetic reflex with induction of the anti-inflammatory cholinergic pathway in a nAChR-dependent manner (Mwamburi et al. 2017). Of interest, vagus nerve stimulation inhibits the expression and the release of IL-6, a pro-inflammatory cytokine involved in tissue injury and the development of cytokine storm (Koopman et al. 2016). Indeed, vagus nerve stimulation provokes the release of ACh which through activation of nAChR inhibits the expression of NF-κB with subsequent release of pro-inflammatory cytokines and propagation of cytokine storm (Mehta et al. 2020). It was observed that vagus nerve stimulation blocks fibrinolysis and coagulation activation in rats with endotoxemia. Thrombotic events are hallmarks associated with COVID-19 severity (Levy et al. 2021).
Moreover, famotidine activates the vagus nerve leading to a significant anti-inflammatory effect in COVID-19. Yang et al. (2022) illustrated that famotidine prevents the development of cytokine storm in COVID-19 via activation of the vagus nerve. Taken together, vagus nerve stimulation plays a critical role in preventing cytokine storm and coagulation disorders in COVID-19 (Yang et al. 2022).
Conclusions
The binding of SARS-CoV-2 with ACE2 leads to a series of inflammatory cellular events with cytopathic effects causing cell injury and hyperinflammation. Severe SARS-CoV-2 infection may lead to dysautonomia and sympathetic storm due to dysfunction of ANS. The CS forms a complex network doing different functions in the body due to its distribution in the neuronal and non-neuronal cells. ACh acts on two main types of receptors which are NRs and MRs. NRs induce T cell anergy with impairment of antigen-mediated signal transduction. Nicotine through activation of T cell NRs inhibits the expression and the release of pro-inflammatory cytokines. NRs play important anti-inflammatory effects while MRs promote inflammation by inducing the release of pro-inflammatory cytokines. SARS-CoV-2 infection can affect the morphological and functional stability of the cholinergic system through the disruption of cholinergic receptors. SARS-CoV-2 spike protein is similar to the neurotoxins that can bind nAChR in the ANS, NMJ, and brain. Interestingly, SARS-CoV-2 spike protein epitopes have higher similarity with neurotoxins affecting nAChR. Therefore, cholinergic receptors mainly nAChR and related cholinergic agonists may affect the pathogenesis of SARS-CoV-2 infection. Cholinergic dysfunction in COVID-19 due to dysregulation of nAChR by SARS-CoV-2 promotes central sympathetic drive with the development of the sympathetic storm. In turn, sympathetic storm triggers oxidative stress and hyperinflammation by increasing the generation of ROS and release of pro-inflammatory cytokines. As well, nAChR activators are intricate with diverse signaling pathways to reduce the risk of inflammatory disorders in COVID-19. In addition, nAChR activators may mitigate ED, OS, and associated coagulopathy in COVID-19. Similarly, nAChR activators may alleviate OS and inflammatory changes as well as prevent the development of cytokine storm in COVID-19. Thus, nAChR activator varenicline in virtue of its anti-inflammatory and anti-oxidant effects with direct anti-SARS-CoV-2 effect could be effective in the management of COVID-19. Remarkably, vagus nerve stimulation attenuates the development of cytokine storm and the need for invasive oxygen therapy and mechanical ventilation in severely affected COVID-19 patients. Indeed, vagus nerve stimulation blocks fibrinolysis and coagulation activation which are hallmarks associated with COVID-19 severity. Taken together, the nAChR activator and vagus nerve stimulation could be a possible therapeutic strategy for COVID-19.
Author contribution
H. M. A., A. I. A., E. E., and G. E. B. contributed to the study conception and design. Material preparation, data collection and analysis, and writing the first draft were performed by H. M. A., A. I. A., E. E., and G. E. B. E. H. N., S. M. A., M. A., and M. D. W. revised the manuscript. E. H. N., H. M. A., A. I. A., E. E., S. M. A., M. A., G. B. E., and M. D. W. read and approved the final manuscript. The authors declare that all data were generated in-house and that no paper mill was used.
Funding
French Agence Nationale de la Recherche and the Région Pays de la Loire provided financial support on COVID-19 research (ANR Flash COVID-19 call — name: CoV2-E-TARGET — grant number: 2020 07132).
Data availability
All data are available in the manuscript.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36460816 | PMC9735034 | NO-CC CODE | 2022-12-14 23:28:32 | no | Naunyn Schmiedebergs Arch Pharmacol. 2022 Dec 3;:1-16 | utf-8 | Naunyn Schmiedebergs Arch Pharmacol | 2,022 | 10.1007/s00210-022-02346-9 | oa_other |
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Eur Geriatr Med
Eur Geriatr Med
European Geriatric Medicine
1878-7649
1878-7657
Springer International Publishing Cham
36477605
721
10.1007/s41999-022-00721-6
Research Paper
Scope of treatment and clinical-decision making in the older patient with COVID-19 infection, a European perspective
http://orcid.org/0000-0002-6833-7641
van Bruchem-Visser Rozemarijn Lidewij [email protected]
1
Vankova Hana 2
http://orcid.org/0000-0002-5479-6038
Rexach Lourdes 3
Ahmed Marc Vali 4
Burns Eileen 5
http://orcid.org/0000-0001-7248-3513
Pautex Sophie 6
http://orcid.org/0000-0001-5261-220X
Piers Ruth 7
1 grid.5645.2 000000040459992X Division of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
2 grid.4491.8 0000 0004 1937 116X Cooperation 34, Internal Disciplines, Third Faculty of Medicine, Charles University, Prague, Czech Republic
3 grid.411347.4 0000 0000 9248 5770 Unidad de Cuidados Paliativos, Hospital Universitario Ramón y Cajal, Madrid, Spain
4 grid.55325.34 0000 0004 0389 8485 Department of Geriatrics, Division of Internal Medicine, Oslo University Hospital (Ullevaal), Oslo, Norway
5 grid.415967.8 0000 0000 9965 1030 Leeds Teaching Hospitals NHS Trust, Leeds, UK
6 grid.150338.c 0000 0001 0721 9812 Palliative Medicine Division and Primary Care Division, University Hospital Geneva, Geneva, Switzerland
7 grid.410566.0 0000 0004 0626 3303 Department of Geriatrics, Ghent University Hospital, Ghent, Belgium
8 12 2022
18
12 7 2022
15 11 2022
© The Author(s), under exclusive licence to European Geriatric Medicine Society 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Key summary points
Aim
To better characterize the management of older people presenting with COVID-19 in European hospitals during the first two waves.
Findings
The majority of older patients admitted to the hospital were transferred to a specific geriatric COVID-19 unit. Respondents found it important to consult a palliative care specialist and spiritual counsellor. In some national guidelines in Europe, the clinical frailty scale was used in combination with other variables for decisions on treatment.
Message
This pandemic has illustrated collaboration between geriatricians and palliative care specialists to improve the care for older patients with severe disease and an uncertain prognosis. Screening for frailty can prove to be useful in decision-making in this scenario.
Supplementary Information
The online version contains supplementary material available at 10.1007/s41999-022-00721-6.
Purpose
Older patients were particularly vulnerable to severe COVID-19 disease resulting in high in-hospital mortality rates during the two first waves. The aims of this study were to better characterize the management of older people presenting with COVID-19 in European hospitals and to identify national guidelines on hospital admission and ICU admission for this population.
Methods
Online survey based on a vignette of a frail older patient with Covid-19 distributed by e-mail to all members of the European Geriatric Medicine Society. The survey contained questions regarding the treatment of the vignette patient as well as general questions regarding available services. Additionally, questions on national policies and differences between the first and second wave of the pandemic were asked.
Results
Survey of 282 respondents from 28 different countries was analyzed. Responses on treatment of the patient in the vignette were similar from respondents across the 28 countries. 247 respondents (87%) would admit the patient to the hospital, in most cases to a geriatric COVID-19 ward (78%). Cardiopulmonary resuscitation was found medically inappropriate by 85% of respondents, intubation and mechanical ventilation by 91% of respondents, admission to the ICU by 82%, and ExtraCorpular Membrane Oxygenation (ECMO) by 93%. Sixty percent of respondents indicated they would consult with a palliative care specialist, 56% would seek the help of a spiritual counsellor. National guidelines on admission criteria of geriatric patients to the hospital existed in 22 different European countries.
Conclusion
This pandemic has fostered the collaboration between geriatricians and palliative care specialists to improve the care for older patients with a severe disease and often an uncertain prognosis.
Supplementary Information
The online version contains supplementary material available at 10.1007/s41999-022-00721-6.
Keywords
Covid-19
Older patients
Collaboration
Palliative care
Advance care planning
Resuscitation order
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pmcIntroduction
Older patients were particularly vulnerable to develop a severe COVID-19 disease resulting in an estimated 30% intra-hospital mortality [1, 2]. Due to extreme strain on the healthcare system, the question of how to provide the most optimal care with limited resources has been an issue in all European countries, in particular for these older frail patients. Decisions whether or not to admit them to intensive care units (ICU) have been discussed extensively, arguing that older frail patients have worse overall outcomes and high mortality rates [3, 4]. Therefore, a less interventionist approach led to an increasing demand for palliative care for a large group of frail old patients with respiratory failure [5]. New challenges were raised, for example, related to visiting policies for the relatives of these sick or dying patients. Even with a large part of this vulnerable older group of patients now vaccinated, the Special Interest Group on Palliative Care (SIG-PC) of the European Geriatric Medicine Society (EuGMS) decided to work on the lessons learned with this pandemic and on the next steps to improve the management of old frail patients with severe diseases. The aims of this online survey were to better characterize: Management of older people presenting with COVID-19 in European hospitals (admission policy, visitation policy, resuscitation policy, advance care planning, use of services) and
National guidelines in European countries on hospital admission and ICU admission in older people with COVID-19.
Methods
Three members (RP; RvB; SP) of the SIG-PC wrote a vignette of a geriatric patient with a Clinical Frailty Score of 6, presenting with COVID-19. Questions regarding the treatment of the vignette patient as well as general questions regarding available services and national policies were drafted.
Three demographic questions were also added for the participants: country, age, number of years of working experience and the clinical setting (acute or long-term care).
Several other members of the SIG-PC commented on the text, until a consensus was formed.
The questionnaire was uploaded to Surveymonkey®, an online survey tool. The online link to the questionnaire was distributed by e-mail to all members of the EuGMS by the secretariat with a short accompanying note explaining the goal of the questionnaire and the request to answer the questions on February 15th 2021. The questionnaire was closed on March 30th 2021, placing it at the end of the second wave of COVID-19 in Europe, according to Eurostat. Answers were stored in a safe environment and analyzed using Microsoft Excel®. The study was approved by the scientific research committee SARS-CoV-2 and COVID19 of the Erasmus Medical Center as well as the medical ethics research committee of the Erasmus Medical Center, registration number MEC-2021-0085.
Results
Respondents
Six thousand six hundred and twenty members of the EuGMS received an email with a link to the questionnaire. The link was also posted on the social media accounts and website of the EuGMS. In total 296 answers from 38 different countries (10 non-European). With the exclusion of non-European respondents, 282 respondents from 28 different countries remained. The number of respondents differed between the countries, 1 to 35 answered questionnaires per country were received (see Fig. 1).Fig. 1 Country of origin of respondents
218 respondents provided information on their age. Mean age was 45.3 years, ranging from 23 to 69. The majority of respondents were female (n = 147, 68%) and worked as geriatricians (n = 173, 80%). 55% of respondents had over 10 years of working experience and 92% of respondents worked in a hospital (see Table 1).Table 1 Demographics of the respondents
No. (%)
Age (n = 218)
23–30 18 (8)
31–40 66 (30)
41–50 61 (28)
51–60 47 (22)
61–70 26 (12)
Gender (n = 218)
Female 147 (68)
Male 70 (32)
Other 1 (0)
Profession (n = 216)
Geriatrician 173 (80)
Internal medicine 16 (7)
Internist-geriatrician 5 (2)
General practitioner 5 (2)
Palliative care specialist 3 (1)
Other 14 (6)
Years of working experience (n = 219)
0–5 years 56 (26)
5–10 years 43 (20)
10–15 years 32 (15)
> 15 years 88 (40)
Location of work (n = 211)
Hospital 193 (92)
Nursing home 9 (4)
Other 9 (4)
Treatment of COVID-19
The main results on management of the vignette patient (a COVID-19 positive geriatric patient with a Clinical Frailty Scale score of 6) are shown in Table 2. Responses regarding the treatment of the patient were fairly consistent. 97% of respondents would start one or more forms of treatment, with the majority starting oxygen (82%), corticosteroids (71%) and/or low molecular weight heparin (85%). A smaller portion of respondents would start antibiotics (39%) and/or antiviral drugs (20%). 247 respondents (87%) would admit the patient to the hospital, in most cases to a geriatric COVID-19 ward (78%). 18% would admit the patient to a regular COVID-19 ward or a high oxygen ward (4%). One respondent answered they would admit the patient to the intensive care unit (ICU).Table 2 Management of a COVID-19 positive geriatric patient with a CFS-score of 6
Questions (total of surveys = 282) Yes (%) No (%)
Start treatment 273 (96.8) 9 (3.2)
Start oxygen 232 (82.3) 50 (17.7)
Start antibiotics 113 (40.1) 169 (59.9)
Antiviral drug 55 (19.5) 227 (80.5)
Corticosteroid 200 (70.9) 82 (29.1)
Low molecular weight heparin 240 (85.1) 42 (14.9)
Admit patient to the hospital? 247 (87.6) 35 (12.4)
On geriatric covid ward 192 (68.1)
On regular covid ward 44 (15.6)
On ward for Optiflow or NIV 10 (3.6)
On ICU 1 (0.4)
Resuscitation policy added to medical file on ED? 201 (71.3) 81 (28.7)
No, this will be done on the ward 17 (6.0%)
No, not until the patient is able to speak on the matter 3 (1.0%)
No, not until the opinion of his children is known 12 (4.3%)
No, not until it is clear whether or not previous advance care planning was recorded 24 (8.5%)
Combination of 2 or more of the “no” answers 25 (8.9%)
Medically appropriate?
Cardiopulmonary resuscitation 42 (14.9) 240 (85.1)
Intubation and mechanical ventilation 25 (8.9) 257 (91.1)
Admission to ICU 52 (18.4) 230 (81.6)
High flow oxygen 208 (73.8) 74 (26.2)
ECMO 19 (6.7) 263 (93.3)
Visitors allowed during non-palliative stage* 145 (51.6) 136 (48.4)
Visitors allowed during palliative stage 262 (92.9) 20 (7.1)
Additional services 232 (82.3) 50 (17.7)
Palliative care specialist 172 (60.9)
Spiritual counseling 157 (55.7)
NIV non-invasive ventilation, ICU intensive care unit, ECMO extracorpular membrane oxygenation
*This question was answered by 281 respondents
Advance care planning
71% of respondents would add a resuscitation policy to the patient file. The remaining 29% (n = 81) would not add a resuscitation policy while the patient was still at the ER. 24 respondents (30%) would wait until it was clear whether or not previous advance care planning (ACP) was registered, 17 (21%) would leave the decision to the physicians on the COVID-19 ward, 12 (15%) would first want to know what the opinion of the patient’s children was on this matter, 3 (4%) would wait until the patient was able to speak on the matter and 25 respondents (31%) combined two or more of the before mentioned arguments.
Cardiopulmonary resuscitation was felt to be medically inappropriate by 85% of respondents, intubation and mechanical ventilation by 91% of respondents, admission to the ICU by 82%, and ExtraCorpular Membrane Oxygenation (ECMO) by 93%.
Visiting policy and additional services
51% of the respondents said that visitors would be allowed during the non-palliative stage of the vignette patient, most respondents stating one or two visitors per day with duration of visiting hours in general maximized to one hour. During the palliative stage, visitors were allowed more often (93%), more visitors were allowed and duration of visit was generally more than one hour per day, often unlimited hours.
82% of respondents (n = 232) would call additional services: 172 respondents indicated they would consult with a palliative care specialist, 157 respondents would seek the help of a spiritual counsellor.
National guidelines
Table 3 illustrates that a combination of multiple criteria were used to decide on the ceiling of treatment in older COVID-19 patients.Table 3 Criteria mentioned in national guidelines
Country No* Criteria in national guidelines regarding hospital admission Criteria in national guidelines regarding ICU admission
AG LE FU CO PO CF CFS AG LE FU CO PO CF CFS
Austria 2 X X X X X X X X X
Belgium 7 X X X X X X X X X X X X X
Czech Republic 1 X X
Denmark 1 X X X X X X X X X X X X
Finland 2 X X X X X X X X X X X X
France 5 X X X X X X X X X X X X
Germany 3 X X X X X X X X X X X X X X
Greece 2 X X X X X X X X X X X X X X
Iceland 2 X X X X X X X X X X
Ireland 1 X X X X X X X X X X
Italy 2 X X X X X X X X X X X X
Malta 2 X X X X X X X X X X
Netherlands 6 X X X X X X X X X X X X
North Macedonia 1 X X X X X X X X X X X X X X
Norway 3 X X X X X X X X X X X X
Portugal 3 X X X X X X X X X X X X
Romania 1 X X X X X X X X X X
Slovenia 1 X X X X X X
Spain 15 X X X X X X X X X X X X X X
Sweden 1 X X X X X X X X
Switzerland 1 X X X X X X X X X X
Turkey 4 X X X X X X
United Kingdom 10 X X X X X X X X X X X X X X
Total 17/22 19/22 21/22 21/22 10/22 18/22 19/22 17/23 20/23 21/23 21/23 9/23 16/23 19/23
AG age, LE life expectancy, FU functionality, CO comorbidity, PO polypharmacy, CF cognitive function, CFS clinical frailty scale, X criterium present in guideline
*No refers to numbers of respondents from that country
National guidelines on admission criteria of geriatric patients to the hospital existed in 22 different European countries (see Table 3). Criteria that were most often present in the guidelines regarding admission to the hospital were functionality and comorbidity (19/22 guidelines), life expectancy and clinical frailty scale (19/22), cognitive function (18/22) and age (17/22). Polypharmacy was mentioned in 10 out of 22 national guidelines.
23 different European countries were reported to have national guidelines for admission of geriatric patients to the ICU (see Table 3). Criteria that were most often present in the guidelines were functionality and comorbidity (21/23 guidelines), life expectancy (20/23), clinical frailty scale (19/23), age (17/23) and cognitive function (16/23). Polypharmacy was mentioned in 9 out of 23 national guidelines.
Differences between first and second COVID-19 wave
Differences in management of older people with COVID-19 in European hospitals were reported between the first and second wave (see Fig. 2). Data were not collected per wave, separate questions were included regarding the first and second waves. It was left up to the discretion of the respondents to identify the first and second wave as this could vary between different countries. COVID-19 was more often present in the general geriatric population during the second wave, but less frequent in nursing homes. Older persons were more often admitted to the hospital in the second wave and there was a greater drop-out of personnel.Fig. 2 Developments in care during the COVID-19 pandemic
All proposed treatments (high flow oxygen, mechanical ventilation, corticosteroids and antiviral drugs) were reported to be used more often in the second wave. However, there was less difference in decision-making regarding palliative care, with almost half of the respondents reporting no difference between first and second wave.
Discussion
The majority of older patients admitted to the hospital were transferred to a specific geriatric COVID-19 unit. This reflects the important role geriatricians play in in-hospital care of older frail people with COVID-19 throughout Europe. With the use of the comprehensive geriatric assessment, geriatricians can provide a broad range of care to older people, from full therapy to comfort care [5]. As the majority of patients suffering from a severe form of COVID-19 were of older age [6], it was especially important for geriatricians to take a leading role.
Assessment of frailty
In many hospitals, the clinical frailty scale (CFS) was used to assess the level of frailty in older persons. The CFS proved to be an important predictor of worse outcome in COVID-19 [5–8]. Importantly, CFS was always used in combination with other variables for decisions on ceiling of treatment. Many European guidelines included comorbidities, life expectancy and cognitive function. Age is not suitable to be used as a rigid criteria but could be used as a predictor for worse outcomes.
Treatment options and limitations
Treatment options for our vignette patient were in almost all cases limited to therapy that could be provided on the clinical ward, such as administration of oxygen, corticosteroids and low molecular weight heparin. Antiviral drugs and/or antibiotics were started by a minority of respondents. This course of treatments is in line with scientific research and protocols available at the time the questionnaire [9]. Respondents indicated that more treatment options were available during the second wave, as was to be expected.
The vast majority of respondents deemed more invasive treatment options such as transfer to the ICU and mechanical ventilation to be medically inappropriate. 74% of respondents found high-flow nasal canula (HFNC) oxygen treatment medically appropriate. It is unknown whether the respondents found this option medically appropriate because they felt HFNC would be a less invasive alternative for mechanical ventilation or because they believed HFNC would be a way to keep the patient as comfortable as possible. Research showed that HFNC does reduce numbers of intubation and ventilation, but does not affect case fatality [10]. Effects on comfort for the patients are not clear. A Cochrane review stated it was uncertain whether HFNC made any difference on both short-term as well as long-term comfort [11]. It could be argued that HFNC can be of value for both patients, family and physicians in the sense that all options were explored to give the patient the best chance of survival. On the other hand, not all patients are comfortable undergoing HFNC treatment. Thus, more research is needed to understand what HFNC means to all parties involved and if and when it should be started or discontinued.
Patients with a CFS of 5 or more have been reported to have a higher mortality rate both during an ICU admission as well as within 30 days (OR 1.22 and 1.50, respectively) in one study [12]. Consequently, some countries used a CFS score of 6 or higher as a contra-indication for ICU referral during the COVID-19 pandemic, as this was considered disproportional care, especially in the context of an (impending) shortness on ICU beds [13]. This is reflected in the answers from our respondents. Frailty is considered an important predictor on mortality. On the other hand, frailty is a syndrome, which is potentially reversible; in an individual patient all frailty components may be reversible after intervention [14]. Furthermore, the CFS scale is a screening tool, not appropriate to be used in isolation for clinical decision-making. According to the published National Institute for Health and Care Excellence COVID-19 rapid guideline critical care in adults, higher CFS score should be a trigger of individualized evaluation of appropriateness of therapeutic modalities/critical care for the patient [15]. Individual evaluation is expected to be based on premorbid functional status, life-expectancy and the shared decision-making principle, including comprehensive geriatric assessment in geriatric patients. It has been stated that the CFS scale should not be used in isolation to dictate access to healthcare resources, but should be used as one part of an assessment process to help ensure that decisions about healthcare interventions are appropriate in the context of an individual’s healthcare needs [16]. It has been suggested that geriatric input early in the hospital admission of older people with COVID-19 could ensure better holistic assessments [16].
71% of respondents would add a resuscitation policy to the file, indicating that they found the described interventions (such as resuscitation, transfer to the ICU) medically inappropriate. This is in line with previously found results [5].
Visitation policy
Relatives were not always allowed during a COVID-related admission while the patient was in a non-life-threatening situation. However, from the moment the situation became critical, relatives were allowed to stay with the patient in most cases. Even with the ethical questions surrounding visiting policies in times of a pandemic, it was often felt that the presence of family members in the last hours of life outweighed the risks of being exposed to the virus [17].
Collaboration with palliative care specialists
Respondents found it important to provide the patient with a good death and consulted a palliative care specialist in 61% and spiritual counseling in 56%. This is in line with guidelines and we were glad to see that even amidst the chaos of the pandemic, geriatricians strived to alleviate the dying process as much as possible.
Strengths and limitations
A major strength of the study is that physicians from 28 different countries responded to this online survey, giving insight into many different national policies and standards. A main limitation to this study is the low response rate, this is most likely due to the usage of an online survey, combined with the workload of the respondents.
Conclusion
The majority of older patients admitted to the hospital were transferred to a specific geriatric COVID-19 unit. Respondents found it important to consult a palliative care specialist and spiritual counseling. In national guidelines in Europe, the clinical frailty scale was used in combination with other variables for decisions on treatment. This pandemic has also illustrated collaboration between geriatricians and palliative care specialists to improve care for older patients with severe disease and often an uncertain prognosis. The experiences of the pandemic provide strong arguments for geriatric and palliative care specialists working together on guidelines and establishing multidisciplinary teams to provide optimal and holistic care for severely ill patients [18, 19].
This pandemic has illustrated the importance of collaboration between geriatricians and palliative care specialists to improve the care for older patients with severe disease and often an uncertain prognosis. Working together on guidelines development and in multidisciplinary teams may provide the optimal care for severely ill patients [18, 19].
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (PDF 440 KB)
Author contributions
All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by RLvB-V, RP and SP. The first draft of the manuscript was written by RLvB-V and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
No funds, grants, or other support was received.
Data availability
Data are available.
Declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
Ethical approval
Ethical approval was granted by the ethical committee of the Erasmus MC (MEC-2021-0085).
Informed consent
There was no research involving human participants and/or animals.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36477605 | PMC9735039 | NO-CC CODE | 2022-12-14 23:28:32 | no | Eur Geriatr Med. 2022 Dec 8;:1-8 | utf-8 | Eur Geriatr Med | 2,022 | 10.1007/s41999-022-00721-6 | oa_other |
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Research Article
Climate change and the Western Himalayan community: Exploring the local perspective through food choices
http://orcid.org/0000-0002-5644-0123
Das Suraj [email protected]
Suraj Das
is a Senior Research Fellow at the Indian Institute of Technology (IIT) Roorkee, India. Currently, he is pursuing his Ph.D. degree in Sociology and is working in the Western Himalayan Region. He is explicitly exploring and analyzing the dynamic of traditional dietary practices in times of climate change for sustainable food security and adaptation policies.
Mishra Anindya Jayanta [email protected]
Anindya Jayanta Mishra
is a Professor of Sociology at the Indian Institute of Technology (IIT) Roorkee, India. He has been teaching for more than two decades. He is a renowned gerontologist in India and has supervised many doctoral fellows.
grid.19003.3b 0000 0000 9429 752X Indian Institute of Technology (IIT) Roorkee, Roorkee, Uttarakhand 247667 India
8 12 2022
112
18 12 2021
21 4 2022
7 11 2022
© The Author(s) under exclusive licence to Royal Swedish Academy of Sciences 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The local belief systems are crucial for climate change adaptation. Even climate experts are unanimous about the fundamental association between local beliefs and climate change adaptation strategies. However, the local perspective is missing from the significant policy dialog platforms. The local beliefs can potentially serve as both objective and psychological refuge for local societies during climate-related emergencies. Similarly, only limited studies have acknowledged the significance of local food choices, providing a model for global responses to climate change. The objective of the study is (i) to explore the local community’s insights and awareness of climate change and (ii) to assess the impact on local food choices affecting their food security in the face of climate change in the Western Himalayan Region, India. The study is based on 210 in-depth household interviews and surveys in 10 villages of Uttarakhand, India. The exploratory factor and thematic analysis results highlight the significance of local perception of climatic variabilities, food choices, and beliefs in climate change adaptation policies. Hence, the current study’s outcomes emphasize on the integration and promotion of both scientific methods and local knowledge for inclusive climate change adaptation and food security policies in the Himalayan Region.
Keywords
Factor analysis
Local food choices
Qualitative approach
Socio-climatological perspective
The Western Himalayan Region
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pmcIntroduction
Climate change is one of the significant challenges the world is facing in the twenty-first century, and the local community of the Himalayan region is among the most vulnerable communities due to their closer proximity to the natural environment (IPCC 2014, 2018, 2021). Further, the local belief systems are crucial for climate change adaptation. Even climate experts are unanimous about the fundamental association between local beliefs and climate change adaptation strategies. Nevertheless, the local perspective is missing from most of the policy platforms. Therefore, it is crucial to acknowledge the significance of local food choices, providing a model for global responses to climate change (UNDP 2007; FAO 2010; UNEP 2021; UNESCO 2021).
Thus, this study was conducted, and the findings indicate that incorporating local beliefs about climate change can significantly aid in the success of climate change adaptation policy. Therefore, understanding the local perception can assist climate experts in better communication about climate action and alternative adaptation policies.
Theoretical framework
The Himalayan region assumes great importance to India’s communities socially, culturally, and economically. Approximately, 51 million of the population in the mountain region practices sustainable agriculture, which is primarily dependent on favorable natural climatic conditions. Therefore, the rapid pace of climate change has affected their food security. Here, food security is defined as healthy people with access to adequate, affordable, good quality, and nutritious food (Wester et al. 2019). For decades, the Himalayan region has remained carefully balanced, resulting in the region’s remarkable biodiversity. Nevertheless, in the recent two decades, the rapid pace of climate change has increased vulnerability (NAPCC 2010). The decrease in rainfall and extreme precipitation during monsoons have led to an increased incidence of floods and drought. Also, the increased incidence of heat stress affects crop yield in the region (IPCC 2018).
Further, the mountain region exemplifies a unique approach to climate change research. At higher elevations, climate change is occurring rapidly, which results in changes in vegetation and ecological and geographical conditions. Also, due to climate change, the cultural value of local communities is changing, hence, acknowledging the intricacies of environment–society interaction (IPCC 2022). Moreover, the Himalayan region is vulnerable to natural interferences such as landslides and erosion. The outcomes of the interaction of these multifaceted elements of change are difficult to forecast but will have significant consequences not in the mountain region but globally. Thus, exploring and assessing possible dimensions of climate change in the Himalayan region is imperative. Therefore, the urgency of a holistic approach arises to bring all the stakeholders, viz., local community, climate experts, and policymakers, together for the ideal solution for sustainable climate change action (Wester et al. 2019).
Therefore, in 2008, the Department of Science and Technology (DST), India, launched the National Action Plan on Climate Change (NAPCC), which draws a framework of how national agencies can support all stakeholders through local and regional policymakers to aid in climate adaptation. Therefore, National Mission for Sustaining Himalayan Ecosystem (NMSHE) and National Mission on Strategic Knowledge for Climate Change (NMSKCC) are among the eight missions for integrating the geographical and social context (DST 2010). Subsequently, DST recommended certain location-specific adaptation measures to the Government of India measures with various organizational supports.
Thus, integrating local communities’ perspectives is crucial for sustainable climate change policy due to their inherited local knowledge about nature from generation to generation (UNFCCC 2020). According to some estimates, local communities take care of approximately 80% of the world’s biodiversity; community forests store at least 24% of the above-ground carbon emissions through their local beliefs and practices (IUCN 2020). Hence, recognizing local understanding, traditions, belief systems, and their involvement in environmental governance can significantly improve the sustainable efforts to conserve and mitigate the challenge of climate change (IPBES 2019).
In the recent two decades, climatic variabilities like forest fires, cloud bursts, floods, and landslides have exponentially increased in Uttarakhand, a part of the Western Himalayan Region, India. Moreover, the production and harvesting of locally significant food crops and fruits are declining and have also affected food choices due to dietary shifts (Bagchi et al. 2004; Wang et al. 2013). Since food choice is associated with local beliefs, changing food choices also affects the food security of the local community (Saxena et al. 2005; Negi et al. 2017); therefore, the local perspective is crucial for inclusive climate policy. Nevertheless, most of the research has been done on agrobiodiversity (Pandey et al. 2017; Ravera et al. 2019), ethnobiology (Ramakrishnan 2001; Chaudhary and Bawa 2011; Junqueira et al. 2021), and socio-economic perspective (Arnell 2004; Senapati and Gupta 2017), which involves considering the specific target groups such as farmers (Shukla et al. 2019; Baig et al. 2020; Cuaton and Su 2020), and climate experts (Rosenberg et al. 2010; Stoutenborough et al. 2014). Due to this, the local perspective, especially the local communities’ perspective, gets little attention. Thus, the present study will fill the research gaps for evidence-based policy formation linked to sustainable consumption patterns and practical future adaptive measures for the mountain community.
Hence, the current study assesses the climate change impacts and local communities’ approaches toward climate change. We hypothesize that the apprehension of climate change will aid in climate action. The study aims for a comprehensive understanding of local perspectives in the face of mixed outcomes from existing literature. This study employs exploratory factors and thematic analysis to explore the localized meaning of climate change and propose an evidence-based food security policy. The objective of the study is (i) to explore the local community’s insights and awareness of climate change and (ii) to assess the impact on local food choices affecting their food security in the face of climate change in the Western Himalayan Region of India.
Materials and methods
Research setting
Uttarakhand has a ‘Pahari’ culture, i.e., the culture is mainly followed in India’s mountain region. The state is located in the Western Himalayan Region of India, with a total population of 10,086,292, where 49.03% are women and 50.93 men, with 69.77% rural population and 30.23% urban population. About 75% of the population practice local subsistence farming through local methods and depend on natural rainfall, ensuring resilience against climatic change (Bisht et al. 2018). Most of the local community follows the norms and values set by social institutions.
Sampling technique and participants
A cross-sectional household study was conducted in five select districts: Haridwar, Dehradun, Tehri Garhwal, Nainital, and Almora of Uttarakhand, India (Fig. 1), from March to August 2021. The very reason for selecting the mentioned district is because these districts are on a higher rank on the high vulnerability index due to climate-induced disasters (NIDM 2012; World Bank 2019; GoI 2021). Similarly, in the recent two-decade, the climate has been changing at a rapid pace. Therefore, only those respondents were interviewed and surveyed who were above 18 years old expressed interest and readiness to participate in the interviews and surveys. A total of 210 households aged between 18 and 75 years old were selected (58.1% of men and 41.9% of women). Since mixed-gender participation brings the element of inclusivity, thus, the perception of both males and females was incorporated. The highest number of participants was between 20 and 49 years old, i.e., 59.5% of the total participants (Table 1). Most importantly, the participants’ informed consent was obtained before the interview.Fig. 1 Map of the surveyed region, Uttarakhand, India
Table 1 Demographic and lifestyle profile of the participants
Attributes Categories % total respondents
Family type Nuclear family 49.5
Joint family 50.5
Gender Male 58.1
Female 41.9
Age 20–29 8.60
30–39 19.0
40–49 31.9
50–59 18.1
Above 60 years 22.4
Social category General 54.8
Other Backward Classes 33.3
Schedule caste 11.0
Schedule tribe 1.0
Marital status Unmarried 10.5
Married 89.5
Education Illiterate 8.6
Primary 11.9
Middle 13.8
High 21.9
Senior Secondary 20.5
Graduation 18.6
Post-graduation and above 4.8
Profession Service 24.8
Agriculture 42.9
Business 19.0
Others 13.3
Data collection
The mixed-method technique is used for data collection, ****which includes both structured surveys, i.e., a 5-point Likert scale, and semi-structured interviews in Hindi and English in natural surroundings allowing the respondents a comfortable space for meaningful responses. The reason for using the mixed-method techniques is that it allows the researchers to develop in-depth insights on the topic (Creswell and Clark 2017). Structured surveys were taken because quantitative surveys assist in determining the degree of conformity and differences among participants owing to specific rationale (Newig and Fritsch 2009). The statements were designed to capture the degree of variabilities toward the specific statement. For example, “Do you think rainfall patterns have changed in recent two decades?” Accordingly, five options were given, i.e., from strongly disagree, disagree, neutral, agree, to strongly agree. Also, the value was assigned to each option from 1 to 5, respectively. The semi-structured interviews were based on the fundamental themes, namely, local awareness and perception of climate change, the impact of infrequent rainfall, unstable temperature, unpredictable seasonal variations, and forest fires on local food.
Further, reliable research principles are followed to establish the study’s research quality (Athens 2010). Primarily, the triangulation approach was incorporated for interviews, response forms, diary notes, and some audiotapes of the conversations during the field study. Further, participants were allowed to cross-check their respective responses, contributing to the research work’s credibility and accuracy of the collected data. Moreover, the descriptive records of the 210 responses were explored and analyzed to ensure the transferability of the field research’s outcome.
Analytical tools and techniques
Factor analysis
The Principal Components Analysis (PCA) is used to explore the interrelationships between the items on Statistical Package for the Social Sciences (SPSS 23). Since the acceptable value of Cronbach’s Alpha is greater than the .7 value. Thus, the reliability of each factor has been checked through Cronbach’s Alpha values, which are .864, .808, and .743, respectively, for F1, F2, and F3. Additionally, Cronbach’s Alpha (0.846) test was run to verify the reliability of the questionnaires used for response collections. Also, only those statements with loading factors of at least 0.35 were kept; accordingly, 12 items were analyzed, which explained 72.54%. Moreover, the suggested minimum sample size for exploratory factor analysis is 3 to 20 times the number of variables. Thus, the sample size was 210 households (Mundfrom et al. 2005). Further KMO value is .73, which shows the sample size adequacy, and Bartlett’s text value is .000, which shows a substantial degree of correlation in the data (Table 2).
Climate change means the change of climate, which is directly or indirectly influenced by human actions besides the natural activities that change the atmosphere’s composition. Further, the impact of climate change has been observed over a while (UNFCCC 2020). Local food is defined as food that belongs to a specific region, has region-specific unique ingredients passed from generation to generation, and is commercially available for at least 50 years (Ostrom 2006). Therefore, fourteen variables were initially used, which could explain climate change’s meaning and impact on local food and associated local belief. Hence, after PCA, only twelve variables were incorporated based on the acceptable loading factors criteria for the study. Additionally, analysis of the scree plot depicted the inflexion point, which is the further justification for retaining three factors (Field 2009).
Finally, three broad factors evolved. The first factor (food choices and local beliefs) used the six variables, which explored the impact on local food choice, overall food choice, community’s food choices, the impact of deforestation in the region, the importance of local knowledge, and harm to nature. Thus, these variables assisted in defining the significance of local knowledge and food choices, which can form the basis for developing the natural ecosystem and resources management strategies for climate change (IPCC 2007). The second factor (the local context of climate change) employed the four variables (i.e., change in rainfall pattern, temperature pattern, seasonal variation, and impact of snowfall (on the harvesting of locally grown crops) to describe the localized meaning of climate change. In the third factor (importance of customary beliefs), two variables (importance of customary norms beliefs and religious beliefs) were used to explain the importance of local beliefs and practices of local societies. Since the twelve variables were able to explore and assess the association between climate change and local knowledge through local food choices, the same were incorporated for the current study (Table 2).Table 2 PCA and descriptive statistics
Items F1 F2 F3 Mean Std. D
Food choice and local beliefs
Local food practices .418 4.18 .702
Overall food choices .848 4.23 .704
Community’s food choices .867 3.92 .963
Deforestation .927 4.30 .706
Local knowledge .928 4.29 .703
Harmony with nature .928 4.29 .703
The local context of climate change
Rainfall pattern .890 4.05 .826
Temperature pattern .827 4.10 .858
Seasonal changes .848 4.17 .818
Snowfall .506 4.29 .659
Importance of local beliefs
Customary norms .894 3.82 .981
Religious beliefs .870 3.81 .922
% Variance explained (72.54) 36.68 22.07 13.79
Cronbach's alpha (.846) 0.864 0.808 0.743
Bartlett test of sphericity (p-value) .000
Kaiser–Meyer–Olkin 0.73
Thematic analysis
Thematic analysis is a qualitative approach used to discover new themes, ‘some level of patterned response or meaning’ (Braun and Clarke 2006). Thus, qualitative research often involves exploring an in-depth understanding of specific phenomena. Thus, the sample size is usually smaller. The existing literature suggests that a sample size of around 5 to 50 respondents is enough (Dworkin 2012; Fugard and Potts 2015; Malterud et al. 2016). Hence, 42 household surveys from every five districts were selected for this research. Therefore, in total, 210 household surveys were conducted. Hence, the deductive approach is used to analyze the qualitative data to substantiate the factors further.
Qualitative data analysis software (NVivo 12) was also used to conduct thematic analysis interviews based on the factors generated through PCA to describe the results further. NVivo 12 permits the creation of files called ‘nodes’ and aids in categorizing and conceptualizing the qualitative responses (Elo et al. 2014). Therefore, the descriptive qualitative data were extracted using the codes to substantiate further the three factors that evolved through PCA. The codes were assigned manually to the relevant statements, potentially explaining broader perspectives in sync with the defined themes (Table 3).Table 3 Coding and major themes
Codes Perspectives Themes
Climatic factors, unpredictable rainfall,
Extreme temperature
Suitable climatic conditions are missing to grow local food crops; heavy rainfall damages the local crops; extreme temperature causes loss of productivity; Landslide and cloud burst is very common Phenomena of climate change
Local food,
Conventional farming,
Local communities,
Lifestyle change,
Migration
Local foods are less grown; Local food is ignored; Local ways of cooking and food choices are forgotten; Unfavorable environmental change has created havoc among the local communities; People like the sedentary lifestyle; Emotions and feelings have severely been affected due to delayed seasonal change Food choices and local lifestyle
Further, comprehensive knowledge of the local meaning of climate change can be valuable for successful strategies during climatic variabilities. Inclusion and recognition of local approaches during climate action at the local community’s level aid in greater adaptation and resilience to the disastrous impact of climate change. Moreover, for inclusive food security, the policies must be in sync with the local beliefs of the communities. For example, locally produced food has the potential to lower the cost of transportation, reduce wastage, and help in the revival of local economies (Terry 2009; IPCC 2014; UNFCCC 2020). Therefore, the second factor (F2) has been used to explore the theme associated with the localized meaning of climate change. The PCA’s first (F1) and third factors (F3) were clubbed to explore the food security and climate change adaptation dynamics.
Results
The localized meaning of climate change
The degree of awareness for climatic variabilities is time and space context-specific, which varies according to local communities’ own experiences with their ecosystem. The preliminary knowledge of climate change comes from the direct observation of the environment and its physical consequences. A comprehensive understanding of change is a significant factor in the local knowledge base of the communities.
The evidence suggests that communities’ opinion about changing climate is significantly affected by the region’s fluctuating temperature, i.e., cool and warm years of the region (Donner and McDaniels 2013; Bauerfeind and Fischer 2014). For example, the precipitation in the lowland district has decreased; the respondents in the Haridwar district defined climate change in terms of temperature and rainfall patterns in recent decades.The rainfall pattern is no more the same as it used to be in the early 2000s. In the early decades in the plane region, it used to rain heavily, but now a decline in rainfall has been observed. It is erratic and scanty nowadays. Similarly, now it is too hot to go outside during summer. Summer is not suitable for health due to harmful rays. (a 46-years old female)
Similarly, the snowfall pattern’s spatial dependence structure significantly influences the perception of climate change (Nicolet et al. 2016). The variability in snowfall and rainfall has increased with time and is not constant now. Similarly, the villagers in Tehri Garhwal districts associated the concept of climate change with decreased snowfall, increased rainfall, and loss of local plant varieties.Earlier, there used to be heavy snowfall in my region, but the incidence of snowfall has decreased with the passage of time. Besides, sometimes the rainfall is heavy, and sometimes it is low. For me, this is the definition of climate change. (a 49-year old male)
The degree of unstable change in rainfall patterns both within and between seasons (Mondal et al. 2016) affects the regional vegetation. Hence, the notion of climate change is being shaped by the availability of region-specific plant species. For example, the villagers in the Dehradun district explained climatic variabilities in terms of loss of vegetation besides other factors like high temperature and lesser rainfall. The region used to be heavily covered with green vegetation and trees. Similarly, the respondents of the Almora district defined climate change with the notion of dietary shifts.We used to have Jhangora (Indian barnyard millet), Koda (finger millet), and Koni (foxtail millet), which are no longer found or grown in the mountains due to unfavorable climatic conditions. Similarly, this time it rained heavily and affected the pollination of Kafal (a fruit), mainly found in the mountainous regions. (a 57-years old female)
The concept of climate change has now been associated with risk caused by natural disasters and has become part of the general awareness among the local communities (Andersson-Sköld et al. 2013). When asked the same question from the villagers about climate change, they correlated the change in climate with natural disasters like frequent cloudbursts, landslides, and forest fires.We used to consume the juice of the local flower for our daily needs. But, the increased incidence of forest fires has drastically affected production. (61-year old female)
The changing patterns of rainfall, snowfall, and irregular precipitation patterns, i.e., fluctuating temperature, are the modes of direct observations in the climate and have been incorporated into the standard definition of climate change. Nevertheless, there is a contextual meaning of climate change as acknowledged by local respondents, which acts as proof of climate change, for example, atmospheric, ecological, and biological indicators (Table 4). The atmospheric indicators can be observed in the change in the sky and clouds’ colors, which also helps predict wind direction; ultimately, the fluctuation is observed as a long-term trend. Similarly, the ecological indicators can be the direction of river streams, landslides, and forest fires, which affects the local ecosystem and eventually results in the retreat of glaciers’ rise in sea level as an indication of climate change.Table 4 Local concept of climate change
Categories Local understanding of
Climatic events Seasonal projections Long-term trends
Atmospheric indicators Changing colors of clouds and incidents of cloudburst The direction of the wind can be predicted Fluctuations in temperature, rainfall, snowfall pattern
Ecological indicators Change in the direction of waves in the river streams
Incidents of landslides
Drying of rivers
Declining water level
Forest fires
Shifting in the water level of a local source affects the farming and household consumption pattern The rise in sea level
Retreat of glaciers
Land-use change
Shifts in ecology
Biological indicators Change in flowing times of fruits and local plants
Shifts and extinction of local plant varieties
Early budding of the flowers negatively affects the level of productivity Decrease in Madua and Kala Bhat production
The observed change in the timing of local crops harvesting
Moreover, the changing dynamics of natural resources and local vegetation varieties act as biological indicators, influencing the productivity level and change in the harvesting time of local crops. Thus, the knowledge of climate change warns of forthcoming extreme weather conditions and aids in identifying inconsistent climate-related trends in the region. Thus, the inclusive insight of weather forecasting is imperative, especially in the regions such as the Western Himalayan Region, which is among the most vulnerable and has limited resources to tackle the natural disasters induced due to climate change.
Moreover, 89.5% of respondents agreed on climate change, and 7.6% disagreed that climate change is the reality of modern times. Additionally, when the questions related to indicators of climate change were asked, 85.2% agreed, 6.2% disagreed with unpredictable rainfall patterns, 80.0% agreed, 3.8% disagreed with unstable temperature change, 90.5 agreed, and 6.2 disagreed with delayed seasonal change. Further, regarding the impact of climatic variabilities, namely, change in land-use pattern, 93.4% agreed, and 2.4% agreed; shifting cropping pattern, 59.5% agreed, and 13.3% disagreed. Similarly, on the negative impact on biodiversity, 75.7% agreed, 7.1% disagreed, impact on local food choices, 73.4% agreed, and 11.9 disagreed.
Food security and adaptation
The local subsistence method of farming and local food choices have been a significant part of the mountain regions of Uttarakhand, which further ensure the diversity of food choices, hence increasing the chance of more remarkable adaptation against climate change (Bisht et al. 2018). The local communities of the Western Himalayan mountains are well known for their distinctive ethnic food culture and local knowledge. The plant species are significant in their local food practice (Abdullah et al. 2021). Nonetheless, the local food system has experienced a significant transition in recent decades due to seasonal shortfalls (Dame and Nüsser 2011; Hussain and Qamar 2020).
The food consumption pattern and the local agricultural techniques in the Western Himalayan Region have shifted in recent decades (Shukla et al. 2018). The food choices of local communities are characterized by a substantial portion of culturally significant local foods. Consumption of local produce is essential for nutritional needs and other necessary elements essential for local people in critical climatic conditions. Nevertheless, due to climatic instabilities, local food consumption has been disrupted (Andronov et al. 2020).We used to consume Bajra (maize), Makki ki roti (maize flour), and Jhangora ki kheer (barnyard millet), but it is no more found here. Also, Loki (bottle gourd) and Tori (ridged gourd) used to be the staple food, but now, the production has been affected due to climate change. (57-year old female)
The experience of susceptibility to local food practices to natural hazards frequently results in food insecurity. Hence, understanding the multifaceted dimensions of local food is imperative in the face of the ever-increasing risk of climate disasters. Moreover, the local values and beliefs associated with the communities’ food are not accounted for during disaster preparedness (Wentworth 2020). Sometimes due to landslides, the mode of transportation gets badly affected, which results in various issues ranging from scarcity of water and food to vegetables for human consumption. So, at that time, they have to manage with available options for months.Climate change has undoubtedly affected the local food crops in the mountain regions such as Bajra, Kodu, etc.; the production has severely been affected. We have to be reliable on local food like Pahari Aloo (potatoes grown in the mountainous regions) (a 52-year old male)
Drastically climatic variations at higher latitudes and altitudes have a significant impact on the biodiversity of the region affecting the growth pattern and nutrient quality of the native species. Hence compels the community to shift their food choices to get the required nutrition for their daily needs (Srivastava and Kumar 2021). The local communities of the Himalayan region practice local agriculture strategies to produce culturally accepted food crops. Still, due to climatic vagaries, the communities have shifted to new cash crop-based farming (for example, a shift from wheat to sunflower oil) and local hunting choices.
The local food choices were organic. A few decades back, the climatic conditions were stable and favorable for local food varieties, and people were also hard working. However, global environmental change has completely changed the scenario. Besides that, the high nutrition profile of local food choices. The local eating practice has changed; for example, people used to sow rice and Madua on a larger scale for personal consumption at the local level. Also, sunflower seeds were used for oil, but now these things have changed. Now people are more focused on cash crops like beans because of the change in the tradition of consuming home-grown or customary foods, as told by a 46-year-old female.Now, I have observed the drastic shift in the food choices of my community. They are neither practicing the local ways and means of cooking nor eating locally grown food.
Furthermore, the inclusion of the socio-ecological dimension is a fundamental adaptation strategy at the policy formation stage. Thus, the long-term sustainable solution to climatic variabilities, the role of local biodiversity conservation, and the local lifestyle become vital. Local food crops should be promoted due to their availability, accessibility, and greater acceptance among local communities. Hence, explicit modeling of local biodiversity in response to environmental change is significant (Kumar 2012). When the question of adaptation strategies was asked, respondents agreed on the significance of the local food practice, which helps to adapt better during natural calamities. For example, the phenomenon of ‘Kitchen Gardening’ was prevalent that used to help the local communities to adapt during unstable climatic conditions. But now, due to a lesser focus on local adaptation strategies, the pattern has also changed.To adapt to the climatic conditions, we prepare ourselves and stock food and other essential items in advance. In the earlier days, we used to grow food in our backyard for personal consumption. For example, Kala Bhat (black soybean, vegetables like Kandali (nettle plant) and Linguda (fiddleheads greens) are used to grow in mountainous regions, which are no more or rarely found in my district (a 62-year old female)
In addition, on the questions related to the impact of climate-induced changes on the native community’s cultural norms associated with food choices, viz., food choices are based on cultural beliefs, 63.3% agreed, and 22.9% disagreed, community’s beliefs are significant 75.2 agreed, and 22.4% disagreed, with religious beliefs are essential 69.0% agreed and 14.8 disagreed, impact on local food practices 76.7% agreed, and 9.0 disagreed.
Discussion
The thematic analysis of the local community’s perception is consistent with the Indian Meteorological Department’s (IMD) observation, which observed the fluctuation in the mean annual rainfall pattern. The recent forecast of 868.6 mm based on 1971–2020 data is less than the 1961–2010 data, which forecasted 880.6 mm of rainfall (IMD 2020). India falls under the tropical zone; thus, annual rainfall depends heavily on the monsoon. Nevertheless, the analysis of 30 years of data (1989–2018) uncovers the region’s high spatial and temporal variability of rainfall. Climate change has adversely affected the frequency and intensity of rainfall patterns in the region. For example, the Garhwal region has received lesser annual rainfall. In contrast, the Kumaon region (mountainous areas) has shown increased annual rainfall if the comparison is made to the mean annual rainfall pattern of the Garhwal region (Guhathkurta 2021). But, in the overall region, the rainfall has decreased.
Further, the local understanding of temperature is consistent with various scientific reports, showing a significant temperature rise in the Western Himalayan Region (Friedlingstein et al. 2021; IPCC 2022). India’s average temperature has risen by around 0.7 °C from 1901 to 2018 (Krishnan et al. 2020). The difference in the perception attached to temperature among the plane and mountainous regions is due to latitude variations. Also, at higher altitudes, the rise in temperature is significant compared to low altitudes affecting the local food choices due to uncertainty in productivity (Das 2021). Likewise, multiple studies have found that due to climate change, the phenomena of early flowering frequently affect the crop productivity of local communities. The current study’s finding is in synch with the earlier research and reports. The anticipated effect will also be disastrous for agriculture and food security (Gupta and Pathak 2016; Vernooy et al. 2017; Pandey et al. 2018).
The majority of Uttarakhand’s population is dependent on subsistence farming; therefore, a large section of local people subsist on local agriculture and allied activities for their socio-economic and nutritional requirements. Moreover, local diversified crops in the Western Himalayan Region are vital for a sustainable ecosystem and for conserving local knowledge of ethnic food. Locally grown food has evolved, acting as a nutritional need and food security source. But, due to seasonal instabilities, biodiversity is also shifting and changing; hence, the conservation of local food choices and crop systems requires policymakers’ urgent attention (Negi et al. 2009). Thus, the in-depth analysis of local community attitudes about climate change and its impact on food choices can significantly aid in climate change adaptation strategies in the mountain region, which also have global significance (Chaudhary and Bawa 2011).
The natural ecosystem is the primary source of ecosystem services, including provisioning, cultural, and other supportive services (UNESCO 2021). Hence, the facilities delivered by the mountain ecosystem aid in the sustenance of more than half of the global population and are critical in the maintenance of the integrity of the Earth system through various ecological functions (IPCC 2021). For example, conventionally, two crop cycles are followed in the Western Himalayan Region, i.e., Ravi and Kharif, but delayed seasonal rainfall has affected the productivity of locally grown crops and hence, affected the food choices.
Furthermore, food choices are not only the source of satisfying human’s nutritional needs; it also illustrates the social and cultural identity of the local community (Clark et al. 2020; Adaawen 2021). It is imperative to document and analyze the local food choices, which will assist in a comprehensive understanding of the ecologically and culturally significant local foods for the inclusive approach to tackling the issue of food security in times of climate change (NAPsC 2010).
There are certain limitations associated with both local knowledge and scientific knowledge. For example, knowledge about the future climate is uncertain, location-specific understanding is inadequate to tackle the high-intensity climatic variabilities, and local knowledge is suitable at the local level. While scientific studies on climate change are essential for suitable resilience-building solutions, local knowledge helps reinforce adaptive capacity as a strategy for building resilience (IPCC 2007; Karki et al. 2017). Therefore, Knowledge integration is crucial for climate action because much of the scientific research on the impact of climatic variabilities offers a generalized view. At the same time, engagement with the local community requires a comprehensive understanding of their social, ecological, and lifestyle attributes. Local knowledge comprises various elements of understanding and practices, and hence, policy approaches should be tailored and developed to the local context (Wheeler and Root-Bernstein 2020).
Thus, insights on local issues and resources are sufficiently specialized, which requires the adequate participation of all stakeholders, i.e., community members, and the support of policymakers (Grêt-Regamey et al. 2013). Efforts to integrate local and scientific knowledge, such as “bottom-up/top-down” approaches, are increasingly recognized as valuable in risk assessment and climate change adaptation policy. Also, the integration of local knowledge provides prospects to generate inclusive understanding for both scientists and policymakers in decision-making and faster implementation since it aids in connecting climate change and to impact and consequences on their community (Failing et al. 2007; Kettle et al. 2014).
The current study’s findings emphasize and suggest a way forwards with a series of steps that can help in socio-economic and socio-cultural policy measures from local communities’ perspective to minimize the effect of climatic change and safeguard the local community’s food security in the Western Himalayan Region of India.
Socio-economic policy: the local communities with low and medium Human Development Index (HDI) are severely affected by climate change. For example, in 2020, due to extreme temperature, approximately half of 295 billion potential work hours were lost because of extreme heat (Romanello et al. 2021). Climate change has generated various opportunities and challenges for the local societies of the Himalayan region. Therefore, policy planners should also integrate the regional concerns of vulnerable communities, and accordingly, schemes and policies should be formulated. For example, Kafal and Buransh could be integrated into the national livelihood mission. Accordingly, the provision of insurance could promote local foods.
Socio-cultural policy: the local edible plants are socially and culturally acceptable to the local people. Thus, stress should be given to the inclusion of local species (e.g., Madua and Kala Bhat) in the national food security mission to improve the nutritional status and conservation of local foods of the vulnerable mountainous communities.
The native communities of the Himalayan region use locally grown food crops and various plant species for food, medicinal, and socio-cultural purposes. But, due to climate change, the importance of local knowledge of collecting and consuming locally grown foods is eroding. Therefore, assimilating socially and culturally synchronized foods is inevitable for ensuring food security and enhanced climate change adaptation strategies (Clark et al. 2020).
Conclusion
This study was conducted to explore the local community’s understanding of climate change for an integrated response of the communities against climatic instabilities. The local context significantly influences the action and attitudes associated with risks because they are inherited through everyday experience. Further, the socio-ecological beliefs of the local communities act as both objective and psychological refuge for climate-related emergencies (IPCC 2021, 2022; UNESCO 2021). Moreover, it is the perception of danger that dominate people’s action. Hence, perceptual knowledge of the local communities is imperative for effective communication and adaptation strategies (Becken et al. 2013; Schowalter et al. 2018; Wahab and Popoola 2019). Therefore, this study emphasizes integrating and promoting scientific methods and local knowledge for a holistic approach to climate change adaptation in the Western Himalayan Region of India.
Data collected for the current research may not be a true representative of the plain region due to socio-climatic and geographical variation. Further, the district was purposively selected based on the IMD’s high vulnerability index. Also, the small sample size would not have captured the perception of the whole population. In addition, the economic and wealth profile was not incorporated in this study. However, the in-depth interviews unfolded the local meaning of climate change, which corresponded with the finding of scientific reports. Thus, the present study may be a starting point for future studies. Since climate change is a worldwide phenomenon, a parallel and comparative study might be conducted to confront the present study’s findings with a larger population size. Likewise, the longitudinal study is desirable to assess if the climatic conditions remain constant after a few years to integrate other significant elements, such as the wealth component and socio-economic factors that the current study has not investigated. Also, the dynamics of COVID-19 and climate change might be corroborated in future research.
Acknowledgements
The authors would like to thank the Department of Humanities and Social Sciences, Indian Institute of Technology (IIT) Roorkee community, for providing access to all necessary resources and Ms. Priya (Senior Research Fellow at IIT Roorkee) for her valuable feedback. We would also like to thank the respected editor and anonymous reviewers for their valuable suggestions in further improving the quality of the manuscript.
Author contributions
Mr. SD developed the idea for the current research paper, reviewed the relevant literature, analyzed and wrote the manuscript. Dr. AJM helped in every step from the formatting, proofreading to the finalization of the draft.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Declarations
Conflict of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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1501684039002
Münchau Alexander [email protected]
1501684039003
1501684039001 grid.4562.5 0000 0001 0057 2672 Universität zu Lübeck, Institut für Systemische MotorikforschungCenter of Brain, Behavior and Metabolism (CBBM), Lübeck, Germany
1501684039002 grid.4562.5 0000 0001 0057 2672 Universität zu Lübeck, Institut für Systemische Motorikforschung, CBBM, Lübeck, Germany
1501684039003 grid.4562.5 0000 0001 0057 2672 Universität zu Lübeck und UKSH, Arbeitsgruppe Bewegungsstörungen & Neuropsychiatrie, Marie-Curie-Straße, 23562 Lübeck, Germany
9 12 2022
2022
33 12 3845
© Berufsverband Deutscher Nervenärzte e.V. (BVDN) 2022
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
issue-copyright-statement© Berufsverband Deutscher Nervenärzte e.V. (BVDN) 2022
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pmcTics können im Kindesalter häufig beobachtet werden und sind für Betroffene meist keine große Belastung, vorausgesetzt, sie selbst sowie das Umfeld sind über die neurobiologischen Grundlagen von Tics und den zu erwartenden, meist günstigen Verlauf, aufgeklärt und verständnisvoll. Eine gezielte medizinische Behandlung ist bei Kindern in der Regel nicht erforderlich. Sollten Tics jedoch über Jahre oder sogar bis ins Erwachsenenalter fortbestehen und Betroffene belasten oder einschränken, ist klinisch eine Abwägung unterschiedlicher Behandlungsmöglichkeiten geboten. Die diagnostische Zuordnung von Tics und Abgrenzung von anderen Störungsbildern ist meist unproblematisch, die Behandlung von Tics mit medikamentösen oder verhaltenstherapeutischen Methoden ist mittlerweile gut etabliert.
Tics sind kurze, plötzlich und repetitiv auftretende Bewegungen oder Laute, die nicht zum Kontext passen und keinen ersichtlichen Zweck haben [1]. Sie werden in motorische und vokale Tics unterteilt [2]. Bei einem Erkrankten sind sehr unterschiedliche Tics möglich. Meist treten zunächst einfache motorische Tics, vorrangig im Gesicht, an Nacken und an der Schulter auf, Tics an den Extremitäten sind seltener [3]. Es werden einfache und komplexe motorische Tics unterschieden [4], wobei einfache Tics einen oder wenige Muskeln (z. B. Blinzeln, Zwinkern, Naserümpfen) betreffen, komplexe Tics dagegen mehrere Muskelgruppen (z. B. konzertierte Kopf- und Schulterbewegungen). Vokale Tics sind beispielsweise Tiergeräusche, Husten, Fiepen oder Piepsen.
Viele Patientinnen und Patienten berichten, in der Lage zu sein, Tics zumindest zeitweise zu unterdrücken, was jedoch meist als anstrengend empfunden wird. Anschließend an eine Phase der Unterdrückung werden die Tics manchmal als verstärkt wahrgenommen, wobei das empirisch bislang nicht gezeigt werden konnte [5].
Zusätzlich zu Tics berichten Betroffene häufig ein Tic-assoziiertes Vorgefühl, das sehr unterschiedlich beschrieben wird, etwa als Hitzegefühl, Kribbeln oder Druck [6]. Das Vorgefühl kann im ganzen Körper vorkommen, tritt aber gehäuft in der Körperregion auf, in der der Tic folgt [7]. Es gibt Studien, die belegen, dass die Intensität des Vorgefühls im Zusammenhang mit der Tic-Schwere steht [8]. Ein Vorgefühl ist bei Jugendlichen und Erwachsenen weiter verbreitet als bei Kindern [6]. Häufig nimmt das Vorgefühl durch die Ausführung der Tics ab, während es beim Unterdrücken der Tics zunimmt [9]. Tics und Vorgefühl stehen also in Verbindung. Was einen kausalen Zusammenhang angeht, ist die Studienlage aber uneinheitlich [8, 9].
Bei einigen Betroffenen kann es zu Echophänomenen (Echopraxie und Echolalie) kommen, das heißt Nachahmung beobachteter beziehungsweise gehörter Bewegungen oder Geräusche/Äußerungen [10]. Auch gibt es Paliphänomene, bei denen eigene Bewegungen oder Äußerungen wiederholt werden. Bei etwa 20 % treten Koprophänomene auf, das heißt Koprolalie (Aussprechen von Schimpfwörtern) oder Kopropraxie (Zeigen von obszönen Gesten) [11]. Diese Phänomene sind in der öffentlichen Darstellung, da aufmerksamkeitswirksam, oft überbetont oder überrepräsentiert. Klassische Koprophänomene bestehen bei Menschen mit Tics selten aus ganzen Sätzen, vielmehr aus einzelnen Wörtern oder auch nur Anteilen von Schimpfwörtern.
Klassifikation von Tics
Tics und Ticstörungen lassen sich nach Komplexität und der Zeitspanne seit Beginn der Beschwerden unterscheiden. Halten die Tics für weniger als ein Jahr an, ist nach ICD-10 und DSM-5 von einer vorübergehenden Ticstörung auszugehen [12]. Bestehen ausschließlich motorische oder vokale Tics, die jedoch länger als ein Jahr anhalten, wird von einer chronischen motorischen (wenn vokale Tics fehlen) oder vokalen (in Abwesenheit motorischer Tics) Ticstörung gesprochen. Beim gleichzeitigen Vorhandensein von sowohl motorischen als auch mindestens eines vokalen Tics, die über mindestens ein Jahr bestehen und vor dem 18. Lebensjahr erstmalig aufgetreten sind, kann die Diagnose eines Tourette-Syndroms gestellt werden [13]. Das Tourette-Syndrom ist tendenziell mit einem höheren Schweregrad der Tics sowie mit häufigeren komorbiden psychiatrischen Erkrankungen assoziiert [14]. Allerdings weisen jüngere Arbeiten darauf hin, dass das Tourette-Syndrom keine eigenständige Entität ist, sondern dass es vielmehr fließende Übergänge zwischen chronisch motorischen Ticstörungen und dem Tourette-Syndrom gibt [15].
Epidemiologie und Verlauf
Für das Tourette-Syndrom wird eine Prävalenz von zirka 1 % in der Gesamtbevölkerung berichtet, die Prävalenz für Ticstörungen ist insgesamt deutlich höher, wobei die Angaben hier mit 1-25 % je nach Studie sehr unterschiedlich sind [14].
Häufig können bei Kindern vor allem einfache motorische Tics beobachtet werden, die meist im Alter von sechs bis acht Jahren beginnen und dabei oft vorübergehend und nicht behandlungsbedürftig sind. Vokale Tics treten in der Regel etwa zwei Jahre nach Einsetzen der motorischen Tics auf. Jungen haben ungefähr drei- bis viermal häufiger Tics als Mädchen. Typisch ist ein schwankender Verlauf mit Phasen verminderter und deutlich verstärkter Tics [2]. Obwohl es im Verlauf der Jugend und des jungen Erwachsenenalters meist zu einer Voll- oder Teilremission kommt, persistiert die Symptomatik in einer klinisch bedeutsamen Weise bei zirka 20 % der Betroffenen bis ins Erwachsenenalter [2].
Differenzialdiagnosen
Tics werden nach Anamnese und Befund klinisch diagnostiziert. Die derzeit wichtigste und häufigste Differenzialdiagnose sind funktionelle Tic-ähnliche Bewegungsstörungen (FTB). Sie bilden sich typischerweise bei Jugendlichen oder jungen Erwachsenen aus, aber nicht, oder nur sehr selten bei Kindern unter zehn Jahren. Meist kommt es zu einem plötzlichen Symptombeginn innerhalb von Stunden oder Tagen, mit multiplen und teils hochkomplexen Bewegungen, die oft einen kommunikativen Charakter haben und personenbezogen sein können. So kann es etwa zu kommentierenden Ausrufen oder Anfassen anderer kommen. Symptome bei FTB verstärken sich meist, wenn Betroffene anderen Menschen begegnen und flauen ab, wenn sie alleine sind. Bei dem Tourette-Syndrom ist das genau umgekehrt. Bei FTB sind Kopropraxie und Koprolalie häufiger als beim Tourette-Syndrom und stehen stärker im Vordergrund [16]. Während Tourette-Syndrom-Tics gehäuft im Gesicht, an Hals und Kopf auftreten, sind bei Patientinnen und Patienten mit FTB öfter die Extremitäten und der Rumpf betroffen. Ein Unterdrücken der Bewegungen bei FTB ist oft nicht möglich. Auch sind bei FTB Komorbiditäten wie generalisierte Angststörung, Panikstörung oder Depression häufiger als beim Tourette-Syndrom [17]. Bei manchen Patientinnen und Patienten treten sowohl klassische Tics (mit Beginn meist in der Grundschulzeit) als auch FTB auf (später im Verlauf).
Wie auch bei anderen funktionellen Bewegungsstörungen ist die präzise frühzeitige Diagnose sehr wichtig, um rasch eine adäquate Therapie einzuleiten. Neben umfassender Aufklärung bieten sich verhaltenstherapeutischen Behandlungen an.
Während der ersten beiden Jahre der COVID-19-Pandemie war eine Zunahme von FTB zu beobachten. Parallel, jedoch auch schon in den Jahren davor, traten FTB gelegentlich infolge des Konsums von Social-Media-Beiträgen (z. B. bei YouTube) auf, in denen unter dem Label "Tourette-Syndrom" nicht Tourette-typisches bizarres, obszönes, grenzüberschreitendes Fehlverhalten gezeigt wurde [18, 19]. Teilweise hatten diese Patientinnen und Patienten sogar die gleichen Verhaltensweisen, die auf den Videos zu sehen waren [20].
Eine weitere Differenzialdiagnose von Tics sind Stereotypien. Sie treten hauptsächlich bei jüngeren Kindern auf, sind ebenfalls repetitiv, jedoch komplexer und ähneln Handlungsroutinen, zum Beispiel wiederholt ablaufende dirigentenartige, wedelnde Armbewegungen. Üblicherweise treten sie in Phasen der Versunkenheit in bestimmte Aktivitäten auf, zum Beispiel beim Spielen. Häufig sind die motorischen Abläufe gleich. Wird das betroffene Kind währenddessen angesprochen, sistiert die Bewegung meist prompt. Ein Vorgefühl ist bei Stereotypien untypisch. Meist fühlen sich Kinder durch Stereotypien nicht belastet, sie können aber anderen auffallen, werden dann nicht selten fragend oder abwertend kommentiert und können den Tagesablauf beeinträchtigen.
Tics lassen sich meist problemlos von Chorea abgrenzen, charakterisiert durch rasche, fließende, unvorhersagbare regellose Extrabewegungen und Myoklonus, blitzartige Bewegungen, die meist wenige Muskelgruppen betreffen. Chorea und Myoklonus lassen sich üblicherweise nicht unterdrücken und sind auch nicht mit einem Vorgefühl assoziiert. Im Zweifel kann ein EMG bei der Unterscheidung helfen: Myoklonien sind meist durch kurze Bursts (50-150 ms) gekennzeichnet, während Tics länger anhalten (> 150 ms) [21]. Länger anhaltende dystone Tics können einer Dystonie ähneln.
Weiterhin sind Tics von Zwängen oder zwanghaftem Verhalten zu differenzieren, besonders, wenn dieses Verhalten kurze oder repetitive Bewegungen beinhaltet. Im Gegensatz zu Tics sind für Zwänge Befürchtungen oder Ängste normal, die mit dem Nichtausführen von Zwangshandlungen verbunden sind. Teilweise sind zwanghafte Bewegungen jedoch nicht oder nur schwer von Tics zu trennen, vor allem da Empfindungen im Zusammenhang mit Zwängen den mit Tics assoziierten Vorgefühlen ähneln können.
Eine seltene Differenzialdiagnose stellen außerdem fokale motorische epileptische Anfälle dar. Sie können mittels simultaner EEG-Aufzeichnungen bestätigt werden.
Differenzialdiagnosen von Tics zeigt Tab. 1.— funktionelle Tic-ähnliche Bewegungsstörung (FTB)
— Stereotypien
— Chorea
— Zwänge/zwanghaftes Verhalten
— fokale motorische epileptische Anfälle
Tourette-Syndrom: Komorbiditäten
Die meisten Patientinnen und Patienten mit Tourette-Syndrom haben eine oder mehrere Komorbiditäten. Eine häufige Komorbidität ist die Aufmerksamkeits-Defizit-Hyperaktivitätsstörung (ADHS), die 50-60 % der Kinder mit Gilles-de-la-Tourette-Syndrom aufweisen [2]. Zum Teil besteht die ADHS-Symptomatik auch im Erwachsenenalter fort und verursacht in einigen Fällen einen nennenswerten Leidensdruck, insbesondere in verschiedenen Bereichen des Alltags und des psychosozialen Funktionierens. Weiterhin gehen Ticstörungen in zirka 50 % der Fälle mit komorbiden Zwangsstörungen einher [22], wobei diese im Gegensatz zu einer ADHS, die der Ticstörung für gewöhnlich vorausgeht, sich meist erst einige Jahre nach Beginn der Ticstörung entwickeln. Darüber hinaus sind auch Angststörungen und Depressionen häufig mit Ticstörungen vergesellschaftet [2].
Anamnese und Untersuchung
Die Diagnose der Ticstörung kann in der Sprechstunde gestellt werden. Eine ausführliche Anamnese und Untersuchung sind Grundlage der Diagnose.
Wichtige Aspekte sind hier vor allem der klinische Verlauf, der meist bereits in der Kindheit der Betroffenen begonnen hat. Zusätzlich sind die unterschiedlichen Charakteristika der Tics sowie die verstärkenden und erleichternden Faktoren wichtig. Außerdem sollte gezielt nach einem Vorgefühl gefragt werden.
Ein besonderer Fokus sollte auch auf der Sozial- und Familienanamnese liegen. Hierbei sind vor allem Bildungsstand, Berufstätigkeit, soziales Netzwerk und Ressourcen zu beachten. Weiterhin sind Symptome von möglichen Komorbiditäten, insbesondere Zwängen und ADHS zu erfragen. Ebenso sollte die Einnahme von Medikamenten und alternativmedizinischen Präparaten erfragt werden.
Die neurologische Untersuchung zeigt in der Regel bis auf Tics keine weiteren Auffälligkeiten. Eine Zusatzdiagnostik, insbesondere eine MRT, ist bei typischer Klinik, nicht erforderlich.
Behandlung von Tics
Ob eine spezifische Behandlung der Tics notwendig ist, richtet sich danach, wie schwer diese, aber auch komorbide Störungen ausgeprägt sind und wie hoch der Leidensdruck der Betroffenen in Bezug auf die Symptomatik ist. Häufig tragen bereits psychoedukative Maßnahmen in Bezug auf Tics und Hinweise zum Umgang mit diesen im Alltag zu einer deutlichen Entlastung von Patientinnen und Patienten sowie deren Angehörigen bei und können in vielen Fällen schon ausreichend sein [23].
Viele der Erwachsenen mit Ticstörungen leben bereits seit Jahren damit. Während einige einen zufriedenstellenden Umgang in dieser Situation entwickeln konnten, erleben andere die Tics als sehr belastend und einschränkend. Obwohl es bislang keine ursachenorientierte Behandlung gibt, stehen unterschiedliche symptomatische Therapien zur Verfügung. Dabei sollte in jedem Fall die Ausprägung eventueller Komorbiditäten geprüft werden und im Behandlungsplan Berücksichtigung finden. Gegebenenfalls sollte die Behandlung der komorbiden Störung priorisiert werden, sollte diese deutlich im Vordergrund stehen. Im Falle einer Besserung der komorbiden Störung ist häufig auch eine Linderung der Tics zu beobachten [23].
Verhaltenstherapie
Die im Jahr 2021 erschienenen "Europäischen klinischen Leitlinien für das Tourette-Syndrom und andere Ticstörungen" betonen die Rolle verhaltenstherapeutischer Ansätze bei der Behandlung von Ticstörungen [24]. Als Methoden der ersten Wahl gelten insbesondere Habit Reversal Training (HRT)/ Comprehensive Behavioral Intervention for Tics (CBIT) und Exposition mit Reaktionsverhinderung (Exposure and Response Prevention - ERP). In den vergangenen Jahren konnte durch randomisiert kontrollierte Studien, bei denen insbesondere das HRT im Fokus stand, die Wirksamkeit sowohl von HRT als auch ERP aufgezeigt werden [25, 26, 27]. Beide Methoden sind sowohl für die Anwendung bei Kindern und Jugendlichen als auch Erwachsenen geeignet, wobei bei ersteren der aktiven Einbindung der Eltern in den Therapieprozess eine große Bedeutung zukommt [28].
Gleichzeitig besteht in Deutschland jedoch ein großer Mangel an derartigen Therapieangeboten, insbesondere im Erwachsenenbereich. Diese Therapien werden bei Erwachsenen aktuell vorwiegend im Rahmen von Studien angeboten. Aufgrund dessen kommt der Entwicklung und Erprobung neuer Behandlungsformate, beispielsweise der ortsunabhängigen Behandlung mittels Videotherapie oder internetbasierten Therapieangeboten, eine große Bedeutung zu.
Habit Reversal Training/Comprehensive Behavioral Intervention for Tics
Die größte Evidenz für die Wirksamkeit verhaltenstherapeutischer Interventionen in der Behandlung von Ticstörungen gibt es für das HRT [24]. CBIT stellt dabei im Wesentlichen eine Erweiterung des HRT um einige Behandlungsbausteine dar. Insgesamt besteht CBIT aus zwei grundlegenden Komponenten, dem HRT einerseits und einer Funktionsanalyse zur Identifikation verstärkender (innerer oder äußerer) Faktoren mit anschließender Erarbeitung darauf bezogener Interventionen andererseits. Weitere Elemente bilden Psychoedukation und das Einüben von Entspannungstechniken. Dabei wird jeder als störend empfundene Tic einzeln und in separaten Sitzungen adressiert. Das HRT (Gewohnheitsumkehrtraining) beruht auf der bewussten Wahrnehmung des einem Tic vorangehenden Vorgefühls. Das wird im Rahmen des Wahrnehmungstrainings zunächst in mehreren Schritten ausführlich trainiert. Anschließend wird für den jeweiligen Tic nach bestimmten Kriterien eine Gegenbewegung ausgewählt und eingeübt, die idealerweise mit der gleichzeitigen Ausführung des eigentlichen Tics nicht zu vereinbaren ist. Das wird schließlich im Alltag ausführlich erprobt und trainiert. Dadurch soll es den Betroffenen ermöglicht werden, anstelle der Tics als gewohnte Reaktion, mit einer alternativen (weniger auffälligen und weniger störenden) Verhaltensantwort auf das Vorgefühl zu reagieren und demnach ein neues Verhalten zu erlernen [14].
Exposition mit Reaktionsverhinderung
Ebenso wie beim HRT kommt auch bei der ERP der bewussten Wahrnehmung des dem Tic vorangehenden Vorgefühls eine große Bedeutung zu. Diese verhaltenstherapeutische Methode wird bereits seit Jahren in der psychotherapeutischen Behandlung, beispielsweise von Zwangserkrankungen, eingesetzt und fand schließlich auch in der Therapie von Tics ihren Platz. Im Gegensatz zum HRT wird hierbei aber nicht jeder Tic im Einzelnen behandelt, stattdessen sollen alle Tics auf einmal unterbleiben. Zunächst wird trainiert, der Ausführung der Tics für eine immer längere Zeitspanne zu widerstehen (Reaktionsverhinderung). Im Anschluss wird der Fokus nach und nach auf die Wahrnehmung der Vorgefühle gelenkt, wobei der Schwierigkeitsgrad zunehmend gesteigert wird, etwa durch Provokationsversuche in Bezug auf das Vorgefühl durch individuelle Triggerfaktoren. Ziel ist es hierbei, die automatisierte Ausführung von Tics aufgrund des Vorgefühls zu unterbinden [14, 24].
Dritte-Welle-Verfahren
Derzeit liegen erste Hinweise dafür vor, dass sich auch neuere verhaltenstherapeutische Methoden, wie beispielsweise metakognitive Therapie, Akzeptanz- und Commitment-Therapie oder achtsamkeitsbasierte Stressreduktion in der Behandlung von Ticstörungen als wirksam erweisen könnten [29, 30, 31]. Diese werden wegen fehlender wissenschaftlicher Evidenz beziehungsweise einem Mangel an randomisiert-kontrollierten Studien aktuell allerdings nicht als alleinige therapeutische Maßnahme zur Behandlung von Ticstörungen empfohlen [24].
Medikamentöse Therapie
Über die psychotherapeutischen und psychoedukativen Verfahren hinaus ist auch die medikamentöse Therapie der Ticstörungen gut etabliert.
Zu den medikamentösen Therapiemöglichkeiten gehören in erster Linie Dopaminrezeptor-Antagonisten (Antipsychotika) Grundsätzlich sollte eine Behandlung mit einer niedrigen Anfangsdosis begonnen werden und diese im Verlauf gegebenenfalls allmählich gesteigert werden. An Präparaten steht bei Erwachsenen insbesondere Aripiprazol (Off-Label) im Vordergrund, das mit 1 × 2,5 mg/Tag morgens eindosiert und im Verlauf alle sieben Tage um 2,5 mg gesteigert werden kann, bis eine wirksame Dosis gefunden wurde [32]. Die Maximaldosis beträgt 20-30 mg/Tag. Häufige Nebenwirkungen sind Gewichtszunahme, Müdigkeit und Konzentrationsprobleme. Alternativ kommt insbesondere Risperidon (Off-Label) für die Behandlung infrage [32]. Hierbei wird anfangs eine Dosis von 1 × 0,5 mg/Tag am Abend empfohlen sowie eine wöchentliche Steigerung um 0,25 mg. Die übliche Höchstdosis beträgt 4 mg pro Tag. Risperidon hat typischerweise mehr Nebenwirkungen als Aripiprazol und wird deshalb seltener eingesetzt. Alternative Antipsychotika zur Behandlung von Tics bei Erwachsenen sind Pimozid und Sulpirid, letzteres vor allem bei komorbiden Zwängen. Bei Kindern sind neben dem Dopaminantagonisten Tiaprid auch Guanfacin und Clonidin, zentrale Alpha-2-Agonisten, als Medikamente möglich [2]. Diese Medikamente sind jedoch bei Erwachsenen nicht oder nur sehr gering wirksam.
Des Weiteren profitieren manche Patientinnen und Patienten von Cannabinoiden [33]. Die Kostenübernahme der Medikamente durch die Krankenkasse muss gesondert beantragt werden und erfolgt erst nach Therapieversuchen mit First-Line-Medikamenten. Cannabinoide, die auch gegen Zwänge wirksam sein können, sollten ebenfalls vorsichtig eindosiert werden. Typische Nebenwirkungen sind Schwindel und Übelkeit [34]. Wenn sich Tics auf bestimmte Muskelgruppen beschränken, kann eine Behandlung mit Botulinumtoxin zu einer Symptomerleichterung führen [35].
Tiefe Hirnstimulation
Eine weitere, bisher experimentelle, Methode bei Patientinnen und Patienten mit Tourette-Syndrom oder chronischer Ticstörung ist die tiefe Hirnstimulation. Bisher wurden der Globus pallidus internus und centro-mediane Thalamuskerne am erfolgreichsten stimuliert [36]. Der Einsatz erfolgt vorwiegend im Rahmen klinischer Studien.
Behandlungsoptionen von Tics sind in Tab. 2 zusammengefasst.— Verhaltenstherapie
— Habit Reversal Training (HRT)
— Comprehensive Behavioral Intervention for Tics (CBIT)
— Exposition mit Reaktionsverhinderung (Exposure and Response Prevention, ERP)
— Dritte-Welle-Verfahren
— Medikamentöse Therapie
— Dopaminrezeptorantagonisten (Antipsychotika)
— Aripiprazol (Off-Label)
— Risperidon (Off-Label)
— Pimozid (Off-Label)
— Sulpirid (Off-Label)
— Tiaprid (Kinder)
— zentrale Alpha-2-Agonisten (Kinder)
— Guanfacin (Off-Label)
— Clonidin (Off-Label)
— Cannabinoide (Off-Label)
— Botulinumtoxin (Off-Label)
— tiefe Hirnstimulation (im Rahmen von Studien)
Fazit für die Praxis
Obwohl Tics vor allem im Kindesalter auftreten und häufig ohne die Notwendigkeit des Einsatzes therapeutischer Maßnahmen wieder abklingen, bestehen sie bei zirka 20 % der Betroffenen auch im Erwachsenenalter fort und verursachen in einigen Fällen einen relevanten Leidensdruck. Tics sind von nicht seltenen funktionellen Tic-ähnlichen Extrabewegungen abzugrenzen. Bislang gibt es keine ursachenorientierten Therapien, allerdings stehen eine Reihe etablierter und gut wirksamer Behandlungen zur Linderung von Tics zur Verfügung. Neben medikamentösen Ansätzen hat insbesondere die Bedeutung verhaltenstherapeutischer Methoden in den vergangenen Jahren zugenommen, die mittlerweile als erste Wahl in der Behandlung von Ticstörungen empfohlen werden. Die Versorgungslage ist jedoch im Hinblick auf Therapeutinnen und Therapeuten, die mit der Behandlung von Ticstörungen anhand der genannten Methoden vertraut sind, insbesondere im Erwachsenenbereich in Deutschland aktuell noch unzureichend.
Online-Links zu Tic-Störungen Tourette-Gesellschaft Deutschland e. V. (TGD): www.tourette-gesellschaft.de
Tourette-Syndrom Homepage: www.tourette.de
InteressenVerband Tic & Tourette Syndrom e. V.: IV-TS.de
CME-Fragebogen Tics bei Erwachsenen
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Welche Aussage in Bezug auf Tics trifft am ehesten zu?
Tics treten im Kindesalter selten auf, aber bedürfen dann oft einer Behandlung.
Ein häufiges Symptom des Tourette-Syndroms stellen Koprophänomene dar.
Häufig treten am Anfang zunächst komplexe Tics auf.
Das Tourette-Syndrom unterscheidet sich von einer chronischen Ticstörung im Wesentlichen durch das gleichzeitige Vorliegen motorischer und vokaler Tics.
Per Definition gibt es bei einem Patienten nur einen spezifischen Tic.
Welche Aussage in Bezug auf differenzialdiagnostische Überlegungen trifft am ehesten zu?
Tics gehen so gut wie nie mit Zwängen einher.
Eine Komorbidität mit ADHS stellt eine Ausnahme dar.
Die Begriffe Tic und Stereotypie können synonym verwendet werden.
Seit Beginn der COVID-19-Pandemie konnte eine Zunahme der ärztlichen Konsultationen aufgrund von funktionellen Tic-ähnlichen Bewegungen beobachtet werden.
Funktionelle Tic-ähnliche Bewegungsstörungen (FTB) kommen gleichermaßen wie Tics vor allem am Kopf und im Gesicht vor.
Welche Aussage trifft in Bezug auf die Behandlung von Tics zu?
Eine medikamentöse Behandlung stellt immer die erste Wahl bei der Behandlung von Tic-Störungen dar.
Psychoedukative Maßnahmen sind keinesfalls ausreichend in der Behandlung von Tics und sollten stets mit medikamentösen und/oder verhaltenstherapeutischen Behandlungsversuchen kombiniert werden.
Als wirkungsvoll in der Behandlung von Tic-Störungen haben sich nach aktuellem Forschungsstand insbesondere Comprehensive Behavioral Intervention for Tics (CBIT), Habit Reversal Training (HRT) und Exposition mit Reaktionsverhinderung (ERP) erwiesen.
Der Vorteil von Risperidon in der Behandlung von Tics gegenüber einer Behandlung mit Aripiprazol besteht insbesondere in einem geringeren Nebenwirkungsprofil.
Die tiefe Hirnstimulation ist heutzutage Mittel der ersten Wahl.
Welche Aussage trifft in Bezug auf den Tics vorausgehende Vorgefühle zu?
Kinder berichten im Gegensatz zu Erwachsenen häufig Vorgefühle, die den Tics vorausgehen.
Vorgefühle sind meist unspezifisch, das heißt nicht lokal begrenzt, sondern lassen sich eher als diffuses Unwohlsein bezeichnen.
Nach Ausführung eines Tics, tritt das Vorgefühl an der entsprechenden Stelle häufig über Stunden oder gelegentlich auch über Tage nicht mehr auf.
Studien konnten zeigen, dass die Intensität des Vorgefühls mit der Schwere der Tics korreliert.
Vorgefühle entsprechen der epileptischen Aura und sollten entsprechend behandelt werden.
Welche Aussage bezüglich verhaltenstherapeutischer Ansätze bei Tics trifft am ehesten zu?
Das Habit Reversal Training (HRT), ebenso wie Exposition mit Reaktionsverhinderung (ERP) basieren auf der unbewussten Analyse der dem Tic vorausgehenden Ich-Störungen.
Comprehensive Behavioral Intervention for Tics (CBIT) enthält das Habit Reversal Training (HRT) als eine grundlegende Behandlungskomponente.
Bislang liegt eine gute Evidenz für die Wirksamkeit von Dritte-Welle-Methoden bei Tics vor, sodass diese als Standardinterventionen bei Tic-Störungen empfohlen werden.
Beim Habit Reversal Training (HRT) werden alle Tics zeitgleich behandelt.
Nur die systemische Familienverhaltenstherapie hat bislang Erfolge gezeigt.
Funktionelle Tic-ähnliche Bewegungen (FTB) sind eine wichtige Differenzialdiagnose zum Tourette-Syndrom. Welche Aussagen zu FTBs trifft am ehesten zu?
FTBs treten besonders bei Menschen ab dem 40. Lebensjahr auf.
FTBs zeigen oft multiple und hochkomplexe Tics sowie vermehrt Koprophänomene.
FTBs treten häufig nach Drogenkonsum auf.
FTBs lassen sich am besten mit Antipsychotika behandeln.
Eine typische Begleiterscheinung bei Morbus Huntington sind einfache FTBs.
Ein 25-jähriger Patient stellt sich mit dem Verdacht auf eine Ticstörung vor. Er selbst befürchtet, unter einem Tourette-Syndrom zu leiden. Welche Aussage zur Diagnostik ist am ehesten korrekt?
Ein MRT ist eine Standarduntersuchung.
Eine ausführliche Anamnese vor allem in Bezug auf Krankheitsverlauf, Vorgefühl, Komorbiditäten sowie Sozial- und Familienanamnese stellt die Grundlage dar.
Die neurologische Untersuchung ist nicht erforderlich.
Eine apparative Diagnostik wie EEG zum Ausschluss fokaler epileptischer Anfälle ist nicht sinnvoll.
Durch das EMG kann eine Myoklonusepilepsie einfach abgegrenzt werden.
Welche Aussage zur Phänomenologie von Tics ist richtig?
Tics treten am häufigsten an den unteren Extremitäten auf.
Typischerweise beginnt die Erkrankung bei den meisten Kindern mit einfachen motorischen Tics.
Zu den einfachen vokalen Tics gehören unter anderem Mehrwortsätze.
Tics treten klassischerweise im Kontext der Situation auf, beispielsweise kommentieren vokale Tics oft die umgebende Situation.
Ein Vorgefühl kommt bei Tics im Gegensatz zur Epilepsie nicht vor.
Eine 47-jährige Patientin mit einer Ticstörung stellt sich vor und fragt nach der Behandlungsoption einer tiefen Hirnstimulation (THS). Welche Antwort ist am ehesten richtig?
Die THS ist ein Standardverfahren in der Therapie des Tourette-Syndroms.
Alle Patienten profitieren gleich von einer THS-Behandlung.
Die Stimulation bei der THS erfolgt hauptsächlich über den Globus pallidus oder centro-mediane Thalamuskerne.
Es ist nicht notwendig, dass die Patienten vorher bereits andere Behandlungsmethoden probiert haben.
Klinische Studien sind hier nicht möglich, da es ein invasives Verfahren ist.
Die medikamentöse Therapie bei der Behandlung des Tourette-Syndroms oder einer chronischen Ticstörung stellt eine wichtige Behandlungssäule dar. Welche Aussage trifft am ehesten zu?
Die medikamentöse Behandlung sollte in absteigenden Dosierungen erfolgen, bis eine Stabilisierung eintritt.
Aripiprazol hat sowohl bei Kindern als auch Erwachsenen keinen Effekt gezeigt.
Tiaprid hat sich zur Behandlung von Tics bei Kindern bewährt.
Cannabiniode sind bei Patienten mit Tourette-Syndrom zugelassen.
Medikamente der ersten Wahl sind Lithiumsalze.
Interessenkonflikt
Die Autorinnen und der Autor erklären, dass sie sich bei der Erstellung des Beitrages von keinen wirtschaftlichen Interessen leiten ließen. Sie legen folgende potenzielle Interessenkonflikte offen: keine.
Der Verlag erklärt, dass die inhaltliche Qualität des Beitrags durch zwei unabhängige Gutachten geprüft wurde. Werbung in dieser Zeitschriftenausgabe hat keinen Bezug zur CME-Fortbildung. Der Verlag garantiert, dass die CME-Fortbildung sowie die CME-Fragen frei sind von werblichen Aussagen und keinerlei Produktempfehlungen enthalten. Dies gilt insbesondere für Präparate, die zur Therapie des dargestellten Krankheitsbildes geeignet sind.
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Live from London and Online, 28–30 September 2022
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Article
Bovine lactoferrin for the prevention of COVID-19 infection in health care personnel: a double-blinded randomized clinical trial (LF-COVID)
http://orcid.org/0000-0001-6099-7509
Navarro Rafaella 12
Paredes Jose Luis 12
Tucto Lourdes 1
Medina Carlos 23
Angles-Yanqui Eddie 24
Nario Juan Carlos 12
Ruiz-Cabrejos Jorge 5
Quintana Juan Luis 12
Turpo-Espinoza Kevin 12
Mejia-Cordero Fernando 23
Aphang-Lam Meylin 24
Florez Jorge 24
Carrasco-Escobar Gabriel 5
Ochoa Theresa Jean [email protected]
126
1 grid.11100.31 0000 0001 0673 9488 Laboratorio de Infectologia Pediátrica, Instituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
2 grid.11100.31 0000 0001 0673 9488 Facultad de Medicina Alberto Hurtado, Universidad Peruana Cayetano Heredia, Lima, Peru
3 Hospital Cayetano Heredia, Lima, Peru
4 Hospital Nacional Arzobispo Loayza, Lima, Peru
5 grid.11100.31 0000 0001 0673 9488 Laboratorio de Innovación en Salud, Instituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
6 grid.267308.8 0000 0000 9206 2401 School of Public Health, University of Texas Health Science Center at Houston, Houston, TX USA
7 12 2022
110
30 3 2022
24 11 2022
© The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Lactoferrin (LF) has in vitro antiviral activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aimed to determine the effect of bovine lactoferrin (bLF) in the prevention of SARS-CoV-2 infection in health care personnel. A randomized, double-blinded, placebo-controlled clinical trial was conducted in two tertiary hospitals that provide care to patients with SARS-CoV-2 infection in Lima, Peru. Daily supplementation with 600 mg of enteral bLF versus placebo for 90 days was compared. Participants were weekly screened for symptoms suggestive of SARS-CoV-2 infection and molecular testing was performed on suspected episodes. A serological test was obtained from all participants at the end of the intervention. The main outcome included symptomatic and asymptomatic cases. A sub-analysis explored the time to symptomatic infection. Secondary outcomes were the severity, frequency, and duration of symptomatic infection. The study was prematurely cancelled due to the availability of vaccines against SARS-CoV-2 in Peru. 209 participants were enrolled and randomized, 104 received bLF and 105 placebo. SARS-CoV-2 infection occurred in 11 (10.6%) participants assigned to bLF and in 9 (8.6%) participants assigned to placebo without significant differences (Incidence Rate Ratio = 1.23, 95%CI 0.51–3.06, p-value = 0.64). There was no significant effect of bLF on time to symptomatic infection (Hazard Ratio = 1.61, 95%CI 0.62–4.19, p-value = 0.3). There were no significant differences in secondary outcomes. A significant effect of bLF in preventing SARS-CoV-2 infection was not proven. Further studies are needed to assess the effect of bLF supplementation on SARS-CoV-2 infection.
Clinical trial registration ClinicalTrials.gov Identifier: NCT04526821, https://clinicaltrials.gov/ct2/show/NCT04526821?term=LACTOFERRIN&cond=COVID-19&cntry=PE&city=Lima&draw=2&rank=1.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10534-022-00477-3.
Keywords
Lactoferrin
SARS-CoV-2
Health care personnel
Prevention
Clinical trial
http://dx.doi.org/10.13039/501100009583 Morinaga Foundation For Health and Nutrition
==== Body
pmcIntroduction
The current pandemic by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to more than 200 million COVID-19 cases and around 4.3 million deaths worldwide until August 14th, 2021 (COVID-19 Map—Johns Hopkins Coronavirus Resource Center 2021). Despite the current availability of some vaccines, access to vaccines is limited, especially in low and middle-income countries and the long-term immunity is not completely understood (Figueroa et al. 2021); therefore, interventions are needed to prevent COVID-19. Health care workers are at higher risk of developing COVID-19 and transmitting it to their households (Shah et al. 2020). Therefore, it is fundamental to develop interventions to prevent COVID-19 in this key population.
Lactoferrin (LF) is an iron-binding protein found in most mammal’s exocrine secretions. LF has several mechanisms to protect against viral infections; it improves the immune system by activating Natural Killer cells and promotes Interferon production (Legrand 2016). LF has demonstrated in vitro activity against enveloped and non-enveloped viruses preventing their entry to target human cells by binding to heparan sulfate receptors or by interacting with other viral particles during the early stages of infection (Berlutti et al. 2006; Beljaars et al. 2004; Drobni et al. 2004; Marchetti et al. 2004; Superti et al. 2001; Ishikawa et al. 2013; Di Biase et al. 2003). Some clinical studies have described positive effects of LF against upper respiratory tract infections such as a decrease in the incidence of upper respiratory tract infections and a decrease in the incidence and the duration of symptoms of common colds (Chen et al. 2016; Oda et al. 2020; Vitetta et al.2013).
Regarding SARS-CoV-2 infection, in vitro studies suggest that LF can be beneficial by inhibiting the fusion of spike proteins with the angiotensin-converting enzyme 2 (Lang et al. 2011). Furthermore, the uncontrolled inflammatory response of some COVID-19 patients alters iron homeostasis and leads to poor prognosis, which could be improved by the iron-binding properties of LF. Preliminary studies in humans describe a 150-fold increase in LF production among COVID-19 patients compared to non-infected controls, which suggests that LF might play an important role in the immune response against SARS-CoV-2 (Reghunathan et al. 2005). A prospective observational study in Spain reported a decrease in COVID-19 symptoms after supplementation with liposomal LF; however, there was no control group in this study (Serrano et al. 2020).
The evidence of in vitro and observational studies is encouraging; however, no results from randomized, placebo-controlled clinical trials have been reported (Chang et al. 2020). The present trial (LF-COVID) aims to determine the effect of bovine LF (bLF) in the prevention of symptomatic or asymptomatic SARS-CoV-2 infection in hospital workers from two tertiary health care centers providing care to SARS-CoV-2 infected patients in Lima, Peru.
Methods
Study design and ethical approval
This study was a randomized, double-blind, placebo-controlled trial in two general/tertiary hospitals [Hospital Nacional Cayetano Heredia (HCH) and Hospital Nacional Arzobispo Loayza (HNAL)] that provide care to COVID-19 patients in Lima Peru. The study was approved by the ethics committee of Universidad Peruana Cayetano Heredia, by each hospital, and by the Peruvian regulatory institutions. Written informed consent was obtained from all patients. The protocol is available online (ClinicalTrials.gov: NCT04526821).
Participants
Eligible participants were hospital workers > 18 years old without self-reported symptoms suggestive of SARS-CoV-2 infection (cough, fever, dyspnea, rhinorrhea) at enrollment. Exclusion criteria were a self-reported previous diagnosis of SARS-CoV-2 infection (defined as a positive RT-PCR alone or a positive antibody test with presence of suggestive symptoms of SARS-CoV-2 infection), untreated arterial hypertension or type 2 diabetes mellitus, BMI > 35, corticosteroids or immunosuppressors chronic treatment, participating in another clinical trial, a personal history of allergy to cow’s milk protein and a positive IgM, IgG, or RT-PCR for SARS-CoV2 at enrolment. The use of any other supplement to prevent SARS-CoV-2 infection, including ivermectin or chlorine dioxide, was not permitted. Study recruitment was conducted from October 2020 to February 2021. At the beginning of the study, there were no vaccines for SARS-CoV-2 available in Peru.
Randomization and masking
Participants were randomly assigned to bLF or placebo (1:1) after serological and molecular screening tests (both tests had to be negative). The randomization list was performed in random blocks of 4 by an independent statistician (not the researchers). There were 6 randomization groups stratified by the 2 participating hospitals and 3 professions groups (doctors, nursing staff, and technical nursing staff). Obstetricians were included in the pool of nursing staff and biologists, medical technologists, and cleaning and security staff were included in the technical nursing staff group due to similar exposure to SARS-CoV-2.
Bovine lactoferrin or placebo chewable tablets had the same color, size, and taste and were delivered to the participants in identical pouches for masking, according to the sequential order of the randomization list. An independent pharmacist did the treatment assignment; clinical, research, statistician staff, and participants were blinded until the end of the study analysis.
Procedures and interventions
We compared twice-daily supplementation with bLF versus placebo (maltodextrin), both were provided by Morinaga Milk Industry Co from Japan. For 90 days enteral bLF or placebo 600 mg/day was self-administered, participants chewed three 100 mg chewable tablets before breakfast and 3 after dinner and the residues were swallowed with water. The dose of 600 mg/day of lactoferrin was chosen based on previous studies that used between 400 and 600 mg/day of bLF for prevention of respiratory infections (Oda et al. 2020; Vitetta et al. 2013). Doses of bLF between 200 mg/day to 1.5 g/day have been previously used without describing any severe side-effect (Berthon et al. 2022). The LF chewable tablets were of 250 mg and composed of 100 mg of bLF and other ingredients (reduced maltose, dietary fiber—indigestible dextrin, maltodextrin and rapeseed hydrogenated oil) (Online Appendix 1). Pouches of 90 chewable tablets were delivered every 15 days in the follow-up visits. During these visits, evaluation of SARS-CoV-2 suggestive symptoms (fever, fatigue, nonproductive cough, anorexia, myalgia, dyspnea, productive cough, taste and smell disorders, headache, rhinorrhea, nausea, diarrhea, and abdominal pain), data about exposure to SARS-CoV-2, and compliance data were collected. The symptomatic SARS-CoV-2 infection surveillance was also assessed by weekly evaluation of SARS-CoV-2 suggestive symptoms through phone calls. When participants reported symptoms, they were evaluated by two medical doctors simultaneously. They classified the symptomatic episode as suggestive of SARS-CoV-2 infection or not (defined by the Infectious Diseases Society of America Guidelines on the Diagnosis of COVID-19) (Hanson et al. 2020) and decided whether the episode required a RT-PCR for confirmation. Participants with any symptom suggestive of SARS-CoV-2 infection considered as a close contact of a COVID-19 positive patient in the previous 2 weeks also underwent RT-PCR. We followed up the participants with positive RT-PCR every 3 days until all the symptoms have completely disappeared for 3 consecutive days. During this follow-up, the start and end date of the symptoms was recorded by the clinical staff. Asymptomatic SARS-CoV-2 infection was assessed by an antibody test performed at the end of the intervention (day 90) in patients who did not have a positive RT-PCR during follow-up.
Study data were collected and managed using Research Electronic Data Capture (REDCap) electronic data capture tools hosted at Cayetano Heredia University (Harris et al. 2009; 2019). Virological and serological testing was done at the Instituto de Medicina Tropical “Alexander Von Humboldt” using quantitative real-time RT-PCR and chemiluminescence IgM/IgG antibodies test (BioMérieux, Marcy-l’Etoile, France).
Outcomes
SARS-CoV-2 infection was the primary composite outcome, which consisted of either (1) symptomatic SARS-CoV-2 infection confirmed by RT-PCR at the time of symptoms or (2) asymptomatic SARS-CoV-2 infection, defined as having a positive antibody (IgM and/or IgG) test at the end of the study without having symptoms during the follow-up period. A sub-analysis was conducted to analyze the time to symptomatic SARS-CoV-2 infection. The secondary outcomes were (1) severity of SARS-CoV-2 infection defined as asymptomatic, mild, moderate, or severe as categorized by the WHO (2021); (2) presence of symptoms of SARS-CoV-2 infection; and (3) duration of the symptoms in confirmed SARS-CoV-2 infections. All secondary outcomes were collected by participants’ follow-up every 3 days until symptoms resolved for 3 consecutive days.
Sample size and statistical methods
Assuming 20% confirmed SARS-CoV-2 infections in the placebo groups, based on international reports, and a 5% attrition rate, 168 participants were needed in each group to detect a 55% decrease in the COVID-19 cases (alpha = 0.05; power = 0.80). The study was interrupted on February 10th 2021 due to the arrival and distribution of the COVID-19 vaccine to hospital workers in Peru when we had 209 patients enrolled.
Treatment groups were compared concerning the baseline demographic information of the participants using Fisher’s exact with a significance level of 0.05. We did all analyses on an intention-to-treat (ITT) basis with no correction for multiplicity for prespecified secondary outcomes. Thus, caution is recommended with secondary outcomes that were reported as point estimates and 95% Confidence Interval (95%CI). To assure randomization balance to obtain an unbiased estimate of the causal effect of the treatment, double-robust (DR) estimation was performed by using Inverse Probability of Treatment Weighting (IPTW). IPTW generates a single pseudo-population in which the balance of pre-treatment covariates is similarly based on the construction of Propensity Scores (PS).
PS were generated using logistic regression modelling based on age, sex, comorbidity, BMI, smoker, hospital, profession, working in another place, principal work area, hours working, hours working in COVID-19 areas, and transportation covariates. IPTW was calculated by the inverse of the PS of receiving the treatment that a patient indeed received.
DR-Poisson regression with robust standard errors was used to calculate Incidence Rate Ratios (IRR) of SARS-CoV-2 infection at the end of the study. In addition, a Kaplan–Meier cumulative incidence curve was used to describe the incidence of symptomatic SARS-CoV-2 infection over time (90-day period) and compared between the two treatment groups with the stratified log-rank test. A DR-Cox proportional-hazards model was used to estimate the hazard ratio (HR) (for bLF versus placebo) and 95% CI. In this analysis, data on patients who survived (no SARS-CoV-2 infection) the entire follow-up period were censored at the last follow-up date or day 100, whichever occurred first. For secondary endpoints, we use the Fisher exact test for categorical variables (severity of episode and frequency of symptoms) and the Wilcoxon test for continuous (skewed) variables (duration of episode and symptoms). All analyses were performed with the use of R v.4.0.1 [R: A language and environment for statistical computing, R Core Team, R Foundation for Statistical Computing, Vienna, Austria (2021) http://www.R-project.org/].
Results
Participants
Of 764 hospital workers invited to participate, 209 (27%) were enrolled and randomized, 104 allocated to receive bLF, and 105 allocated to receive placebo (Fig. 1). The median age was 37 (IQR 31–50); 158 (75.6%) were females. Sixty-four (31%) were doctors, 75 (36%) nurses or obstetricians, and 70 (33%) other professions. There were 111 hospital workers (53%) from HCH and 98 (47%) HNAL. Most baseline characteristics were comparable between the groups (Table 1), but there was a significant difference between both groups in the distribution of sex and hospital work area. The median of total days in observation was 63 days (IQR 31–86). Treatment compliance median was the same in both groups (93%) (Table 2).Fig. 1 Consort diagram: lactoferrin vs placebo. aHospital workers that had a positive PCR (n = 3) positive antibodies (n = 16), or reported being diagnosed with SARS-CoV-2 infection in the past (n = 109)
Table 1 Baseline characteristics of the participants enrolled in the LF-COVID study
bLf group
(n = 104) Placebo group
(n = 105) p value*
Sex, women 86 (83%) 72 (69%) 0.024
Age years 38 (30–50) 35 (31–50) 0.9
Any comorbidities 12 (12%) 20 (19%) 0.2
Comorbidities 0.2
Hypertension 3 (2.9%) 4 (3.8%)
Glucose disorders 0 (0%) 3 (2.9%)
Thyroid disease 3 (2.9%) 5 (4.8%)
Asthma 4 (3.8%) 7 (6.7%)
Others 3 (2.9%) 0 (0%)
BMI, kg/m2 26 (24–29) 27 (25–29) 0.3
BMI 0.2
< 25 kg/m2 37 (36%) 27 (26%)
25–30 kg/m2 47 (45%) 61 (58%)
≥ 30 kg/m2 20 (19%) 17 (16%)
Current smoker 6 (5.8%) 11 (10%) 0.3
Hospital 0.9
Cayetano Hospital 55 (53%) 56 (53%)
Arzobispo Loayza Hospital 49 (47%) 49 (47%)
Healthcare occupations 0.9
Physician 31 (30%) 33 (31%)
Nurse/Obstetrician 38 (37%) 37 (35%)
Nurse assistance/medical technologist/biologist/cleaning staff/security staff 35 (34%) 35 (33%)
Hospital work area 0.05
Hospitalization 59 (57%) 49 (47%)
Emergency 16 (15%) 9 (8.6%)
Clinic 13 (12%) 18 (17%)
ICU 9 (8.7%) 11 (10%)
Others 7 (6.7%) 12 (11%)
Working at more than one health care center 17 (16%) 22 (21%) 0.4
Monthly working hours 150 (150–192) 150 (150–200) 0.6
Working in COVID-19 areas 55 (53%) 50 (48%) 0.5
Monthly working hours in areas designated to SARS-CoV-2 patients 75 (24–120) 75 (36–100) 0.5
Transportation used 0.13
Public bus 51 (49%) 36 (34%)
Taxi 22 (21%) 23 (22%)
Own car 13 (12%) 24 (23%)
Walking/Bicycle 10 (9.6%) 9 (8.6%)
More than 2 ways 8 (7.7%) 13 (12%)
Data are median (IQR) or n (%)
*Wilcoxon test for quantitative variables and Fisher for qualitative variables
Table 2 Follow-up of participants: study compliance and evaluations
bLF Placebo p value*
Total days of observation 65 (33–84) 61 (31–89) 0.9
Compliance (doses received/planned) 0.93 (0.85–1.00) 0.93 (0.85–1.00) 0.8
Compliance > 80% 90 (87%) 85 (81%) 0.3
Number of symptomatic events that required clinical evaluationa 62 (56.9%) 47 (43.1%)
Number of clinical committee evaluations where COVID-19 disease was suspectedb 26 (57.7%) 19 (42.2%)
Data are median (IQR) or n (%)
*Wilcoxon test for quantitative variables and Fisher’s exact test for qualitative variables
aThe participants could have more than one clinical committee evaluation, solicited at each follow-up call or clinical staff visit. There were a total of 109 evaluations in 82 participants
bThere were 45 clinical committee evaluations where SARS-CoV-2 infection was suspected in 40 participants
Primary outcome
During the 90 days of intervention, 109 patients reported symptoms (62 in the bLF group vs 47 in the placebo group). In 45 of them, COVID-19 was suspected (26 in the bLF group vs 19 in the placebo group). Among the 45 COVID-19 suspected cases, 18 had a positive RT-PCR test for COVID-19 (11 in the bLF group vs 7 in the placebo group) and symptomatic SARS-CoV-2 infection was confirmed. Follow-up characteristics were comparable between the groups (Table 2).
Overall, there were 20 SARS-CoV-2 infections confirmed (18 were symptomatic infections and 2 asymptomatic). The primary composite outcome occurred in 11 (10.6%) participants in the bLF group and 9 (8.6%) participants in the placebo group. There was no significant effect of bLF on the primary composite outcome, Incidence Rate Ratio (IRR) 1.23 (95%CI 0.51–3.06, p-value = 0.64). A Kaplan–Meier cumulative incidence curve for symptomatic SARS-CoV-2 infection comparing bLF and placebo is shown in Fig. 2. There was no significant effect of bLF on time to symptomatic SARS-CoV-2 infections, Hazard Ratio (HR) 1.61 (95%CI 0.62–4.19, p-value = 0.3).Fig. 2 Time to event of symptomatic SARS-CoV-2 infection by treatment group. Red line: lactoferrin; grey line: placebo; red shadow: lactoferrin 95% confidence interval; grey shadow: placebo 95% confidence intervals. *Symptomatic SARS-CoV-2 infection were those that tested positive on reverse-transcriptase–polymerase-chain-reaction (RT-PCR)
Secondary outcomes
There were no significant differences in secondary outcomes (severity of SARS-CoV-2 infection, presence, and duration of symptoms). Regarding the severity of SARS-CoV-2 infection, in the placebo group, 2 (22.2%) participants had an asymptomatic SARS-CoV-2 infection and in 7 (77.8%) the symptomatic episode was categorized as mild. In the bLF group, all 11 confirmed SARS-CoV-2 infections were symptomatic and categorized as mild. There were no moderate or severe SARS-CoV-2 infections. There was no difference between the severity of SARS-CoV-2 infection between groups (p-value = 0.369).
Duration and prevalence of secondary outcomes are shown in Table 3. The most common symptoms among the 18 symptomatic SARS-CoV-2 infections were: cough in 11 participants (61%), nasal secretion in 10 (56%), headache in 8 (44%), and sore throat in 8 (44%). The proportion of patients who developed fever during the study period and the duration of fever were slightly lower t in bLF than in the placebo group, but not significant different (Table 3).Table 3 Secondary outcomes: prevalence and duration of symptoms of SARS-CoV-2 infection
bLF group
(n = 11) Placebo group
(n = 7) p value*
Cough
Prevalence 6 (54.5%) 5 (71.4%) 0.637
Duration, days 12 (9.5–17.5) 10 (6.0–13.0) 0.461
Nasal secretion
Prevalence 6 (54.5%) 4 (57.1%) 1.000
Duration, days 7 (6.0–10.3) 5 (0.8–10.0) 0.7476
Headache
Prevalence 6 (54.5%) 2 (28.6%) 0.367
Duration, days 8.5 (3.3–10.8) 4.5 (4.3–4.8) 0.505
Fever
Prevalence 6 (54.5%) 1 (14.3%) 0.151
Duration, days 1.5 (1.0–2.8) 6 (6.0–6.0) 0.116
Sore throat
Prevalence 4 (36.4%) 4 (57.1%) 0.630
Duration, days 8 (3.3–13.8) 8.5 (5.3–11.0) 0.773
Myalgia
Prevalence 3 (27.3%) 3 (42.9%) 0.627
Duration, days 6 (5.0–14.0) 4 (3.5–7.0) 0.376
Taste disturbance
Prevalence 3 (27.3%) 2 (28.6%) 1.000
Duration, days 5 (4.5–10.0) 4.5 (3.8–5.3) 0.564
Smell disturbance
Prevalence 3 (27.3%) 2 (28.6%) 1.000
Duration, days 15 (9.5–15.5) 6 (6.0–6.0) 0.554
Fatigue
Prevalence 2 (18.2%) 2 (28.6%) 1.000
Duration, days 15.5 (13.8–17.3) 6 (4.5.7.5) 0.121
Diarrhea
Prevalence 2 (18.2%) 2 (28.6%) 1.000
Duration, days 2 (1.5–2.5) 1 (0.5–1.5) 0.439
Rash
Prevalence 0 (0%) 0 (0%) –
Duration, days – – –
Loss of appetite
Prevalence 0 (0%) 0 (0%) –
Duration, days – – –
Shortness of breath
Prevalence 0 (0%) 0 (0%) –
Duration, days – – –
Data are median (IQR) or n (%)
*Wilcoxon test for quantitative variables and Fisher’s exact test for qualitative variables
Regarding the duration of the SARS-CoV-2 symptomatic infections, there was no evidence of a difference between the bLF group (median days = 13, IQR 9.5–18.5) and the placebo group (median days = 10, IQR 6.5–13; p-value = 0.146).
We have followed closely all symptoms developed during the intervention. The numbers of subjects with adverse events were 49 in the bLF group and 32 in the placebo group. We found no differences among treatment groups (Table 4). None had a causal relationship with the intervention.Table 4 Diagnosis of participants evaluated because of symptoms suggestive of SARS-CoV-2 infection
Diagnosis bLF group
N = 104 Placebo group
N = 105 p value*
COVID-19 suspected 24 (23%) 16 (15%) 0.2
Gastrointestinal symptoms 5 (4.8%) 7 (6.7%) 0.8
Odynophagia 4 (3.8%) 1 (1.0%) 0.2
Allergic rhinitis 3 (2.9%) 2 (1.9%) 0.7
Primary headache 3 (2.9%) 1 (1.0%) 0.4
Headache 0 (0%) 3 (2.9%) 0.2
Common cold 2 (1.9%) 1 (1.0%) 0.6
Muscle contracture 2 (1.9%) 0 (0%) 0.2
Food poisoning 2 (1.9%) 0 (0%) 0.2
Others 4 (4.0%) 1 (1.0%)
Data are n (%)
*Fisher’s exact test
Discussion
This clinical trial was not able to demonstrate a protective effect of bLF supplementation against SARS-CoV-2 infection. Despite the small sample size, bLF was noticed as safe and well-tolerated.
In this study, bLF did not have an effect on COVID-19 incidence. Some previous studies have described the protective effects of LF against other viral infections. Among 260 infants aged 4–6 months LF decreased the incidence of upper respiratory (Chen et al. 2016) infections and in one study the combination of LF and milk serum protein with immunoglobulins decreased the incidence of common colds (Vitetta et al. 2013). Despite the evidence of a protective effect of bLF on other viral respiratory tract infections and the in vitro evidence of the inhibitory effect of LF on SARS-CoV-2 entry to target cells, this study failed to demonstrate a protective effect of LF against SARS-CoV-2 infection. This may be due to differences in the mechanism of action of bLF from the in vitro studies to the in vivo settings, however, the small sample size of this study limits the conclusions of the effect of bLF on SARS-CoV-2 infection.
Regarding the severity of SARS-CoV-2 infection, there were no severe infections and bLF did not have an effect on the severity of SARS-CoV-2 infections. At the study start, only people aged < 60 years, with a BMI < 30 and who did not have any uncompensated medical conditions (such as coronary heart disease, high blood tension and diabetes) were allowed to work at the hospital, thus were the only included in this study. This could limit the generalizability of our findings to the general population, since considering that these populations are less likely to develop severe COVID-19 disease, further studies should aim to include participants at higher risk of worse outcomes.
Furthermore, regarding the presence and duration of symptoms, LF decreased the duration of symptoms of cold in a clinical trial of 310 healthy adults in Japan at a dose of 600 mg/day LF (Oda et al. 2020). This study failed to demonstrate an effect of bLF supplementation on the presence and duration of symptoms. However, the sample size was not calculated for these secondary outcomes and further studies should aim to understand the effect of LF on the actual infection rather than as a preventive measure.
This study should be interpreted in light of its limitations. First, the early stop of the trial decreased the study sample size limiting its power; therefore, this study cannot provide definite evidence. Second, one in-vitro study reported that some bacteria present in the upper gastrointestinal tract have proteases that can degrade LF (Alugupalli and Kalfas 1996). This can limit the assumption of a systemic effect of bLF supplementation on COVID-19 prevention, which was the research question for this study. However, even when degradated, the active metabolits of bLF have antimicrobial properties which can be part of the mechanism of action against SARS-CoV-2 infection (Lizzi et al. 2016). It is essential that further studies, exploring the effect of bLF on SARS-CoV-2 infection assess the pharmacodynamics and pharmacokinetics of chewable tablets bLF supplementation and its metabolites to understand the possible action that this supplement may have on SARS-CoV-2 infection. Third, misclassification bias is possible because of the definition of suspected COVID-19 symptomatic cases and the criteria used for RT-PCR testing. However, since the physicians were blinded to the intervention arm and used a standardized criteria for diganosis, this could have possibly led to non-differential misclassification. Also, the fact that the same two physicians evaluated all participants simultaneously can reduce misclassification bias in this study.Fourth, compliance to treatment was self-reported, which could lead to measurement bias and could be a major unmeasured confounder since this could be affected by recall and acceptability bias (since participants may overestimate their compliance to the intervention). However, it improves the pragmaticism of the treatment effect. Fuerthermore, there were some differences in the baseline characteristics (sex and hospital working area), which could have arisen given the small sample size, but these differences could have also influenced the results. Finally, this study did not explore the effect of bLF supplementation in the inflammatory and immune response to SARS-CoV-2 infection, but only focused on its main outcomes (incidence of SARS-CoV-2 infection, presence and duration of symptoms). Future studies should aim to understand if the supplementation of bLF could have regulatory properties in the immune response against SARS-CoV-2 infection.
To our knowledge, this is the first clinical trial that explored the effects of bLF on SARS-CoV-2 infection. This trial was not able to show significant effects of bLF on SARS-CoV-2 infection incidence, severity and symptoms. Further studies with a larger sample size should be conducted to reach valid conclusions.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (DOCX 27 KB)
Funding
This work was supported by Morinaga Milk Company, Japan; Morinaga Foundation For Health and Nutrition. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Declarations
Conflict of interest
All authors have no conflict of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Navarro Rafaella and Paredes Jose Luis have contributed equally to this work and share first authorship.
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| 36474100 | PMC9735051 | NO-CC CODE | 2022-12-14 23:28:32 | no | Biometals. 2022 Dec 7;:1-10 | utf-8 | Biometals | 2,022 | 10.1007/s10534-022-00477-3 | oa_other |
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J Ambient Intell Humaniz Comput
J Ambient Intell Humaniz Comput
Journal of Ambient Intelligence and Humanized Computing
1868-5137
1868-5145
Springer Berlin Heidelberg Berlin/Heidelberg
4489
10.1007/s12652-022-04489-2
Original Research
Ubiquitous computing in light of human phenotypes: foundations, challenges, and opportunities
http://orcid.org/0000-0003-4188-735X
Bavaresco Rodrigo Simon [email protected]
Barbosa Jorge Luis Victória [email protected]
Applied Computing Graduate Program - PPGCA, University of Vale do Rio dos Sinos - UNISINOS, Av. Unisinos, São Leopoldo, Rio Grande do Sul, 93.022-000 Brazil
7 12 2022
19
26 10 2021
28 11 2022
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The interest in human phenotypes has leveraged interdisciplinary efforts encouraging a better understanding of the broad spectrum of psychological and behavioral disorders. Moreover, the usage of mobile and wearable devices along with unobtrusive computational capabilities provides an extensive amount of information that allows the characterization of phenotypes. This article describes the human phenotype through the lens of computational range and reviews state-of-the-art computational phenotyping. Furthermore, the article discusses computational phenotyping’s extension concerning the combination of intelligent environments and personal mobile devices, addressing technical, managerial, and ethical challenges. This combination reinforces ubiquitous computational capabilities for phenotyping as a facilitator of interdisciplinary information convergence in favor of clinical and biomedical research.
Keywords
Ambient intelligence
Smartphone
Wearable electronic devices
Phenotype
Psychiatry and psychology
http://dx.doi.org/10.13039/501100002322 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Financing Code 001 Bavaresco Rodrigo Simon
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pmcIntroduction
The indicators concerning substance use and mental health in the United States account for an unseen number of cases since 2017 on psychological and behavioral disorders. An estimated 47.6 million adults aged 18 or older had any mental illness, in which 11.4 million adults presented episodes that substantially interfered with one or more daily activities (SAMHSA 2019). Not enough, the world has faced the pandemic of Covid-19, which induces the alertness of possibilities to aggravate these episodes (Huang and Zhao 2020). Nevertheless, this situation also encourages a better understanding of the broad spectrum of disorders, searching for particular prevention, early diagnosis, treatments, and prognosis.
Interdisciplinary efforts concerning human phenotypes have contributed to this understanding. Human phenotype regards individuals’ intrinsic and observable characteristics, and phenotyping fosters these characteristics’ employment toward valuable information to clinical and biomedical research. In turn, deep phenotyping focuses on individuals’ biological specificity derived from novel types of data through algorithms to identify potential connections between phenotypes, genetic variations and biological data, and disease subtypes (Delude 2015). In this sense, opportunities due to the extensive amount of information source provided by the usage of mobile and wearable devices (Editorial 2015), and the continuous spread of unobtrusive sensors, actuators, computing, and interactive interfaces (Amft et al. 2020), also account for improvements in the precision medicine (Torous et al. 2016).
In this context, related studies have been conducted to elucidate literature’s advancements, mainly regarding mobile and wearable devices. Benoit et al. (2020) focused on machine-learning techniques applied to smartphone data to assess symptoms of psychosis spectrum illnesses. Montag et al. (2021) reviewed mobile sensing to neuroscientific phenotyping research to outline the potential of this combination. Saccaro et al. (2021) provided the application of portable or wearable digital tools for bipolar diagnosis, describing population, technologies, and computational approaches. Mendes et al. (2022) systematically identified sensing applications and data sets for digital phenotyping of mental health. Finally, Tomicic et al. (2022) explored ethical, legal, and social challenges relevant to the implementation of digital phenotyping technologies in healthcare.
Contributing to these researched areas and aligned with big data magnitude, Ubiquitous Computing (UbiComp) encourages phenotyping research given its inherent features, such as computational artifacts physically embedded into the natural environment, both indoor and outdoor (Bardram and Matic 2020). This provides a relevant aspect regarding additional information from individuals’ ecological experience about biological, psychological, and social phenomena (Borsboom 2017; Pierleoni et al. 2021). These phenomena comprise the multitude of psychopathology symptoms and provide daily analytical measurements to complement medical information recorded in clinics. Different from related literature, this study discusses the extension and complement of phenotyping concerning the combination of intelligent environments and personal mobile devices.
Therefore, this article first describes human phenotype through the lens of computational range, presenting an approach that considers environmental, social, and psychophysiological dimensions capable of being reached by UbiComp. Furthermore, the article reviews the state-of-the-art of computational phenotyping, revealing the course in which computing has approached the characterization of phenotype. Besides, this study emphasizes the role of UbiComp in light of clinical and biomedical research. Afterward, the study addresses research opportunities that originated from technical, managerial, and ethical challenges.
The remainder of this article is organized as follows. Section 2 details dimensions around human phenotype and how they are related to ubiquitous technology. Section 3 reviews computational phenotyping, and Sect. 4 discusses the relevance of ubiquitous computing for phenotyping. Section 5 presents challenges and opportunities regarding the combination of these research fields. Finally, Sect. 6 approaches the final remarks of this work.
Human phenotype
Encyclopedia of Biodiversity presents a historical perspective of phenotype, where the author refers to the term as observable characteristics being a product of the interaction between the inherited material, that is, genetics, and the environment (Berry 2001). These characteristics denominate phenotypic traits, and they encompass an organism’s physical appearance, function, or behavior, including descriptions of non-visual properties such as physiology. The usage of human phenotype in clinical and biomedical research contributes to the understanding of phenotypic abnormalities associated with diseases with a focus on prevention, treatment, and prognosis (Robinson 2012).
In light of clinical psychology and psychiatry literature, studies indicated that biological, psychological, and social factors affect the development of psychological and behavioral disorders (Borsboom 2017). Figure 1 depicts a reinterpretation of the complex interaction between these factors encompassing physical and virtual experiences. This reinterpretation employs a bidirectional interrelationship of social, environmental, and psychophysiological dimensions in respect to the biological. The interrelationship introduces the environmental factor and proposes a synergy among biological and psychological dimensions through the inclusion of psychophysiology. The biological dimension (A) concerns individuals expressing their intrinsic characteristics guided by genetics, that is, their genotypes. These characteristics are observed from situations in light of the environmental (B) and social factors (C), which may stimulate psychophysiological responses.Fig. 1 Interrelationship of biological (A), environmental (B), social (C), and psychophysiological (D) dimensions. Biological concerns individuals with their genotypes and developmental form. Environmental and Social consider virtual and physical experience where biological reveals itself. Psychophysiological features the reflexes on mind and body unleashed by the three first, but also characterizes the way individuals affect those factors. In combination, these factors reveal the portrayal of possible phenotypic traits relevant to characterize ecological phenotypes
The physical environment surrounds the most diverse indoor and outdoor circumstances, encompassing frequented places and movements from one to the other. The virtual environment represents interactions with mobile applications due to the widespread adoption of digital devices, particularly smartphones and smartwatches.
The social factor related to the physical environment regards personal relationships and how individuals behave in front of people in everyday environments. The virtual social factor comprises relationships on social media and virtual communities, and the respective social behavior considering the digital immersion, hence, adherent to a virtual environment.
Psychophysiological dimension (D) depicts the individuals’ psychological interpretation of life situations according to genotype and developmental information, their emotions and cognition, and the respective reflexes on the human body. Hence, this dimension leverages the usage of psychological (E) and physiological (F) responses, which are the underlying phenomena of psychophysiology.
Psychophysiology is a discipline concerned with the scientific pursuit of understanding human processes derived from the study of social, psychological, and behavioral phenomena related to and revealed through physiological principles (Cacioppo et al. 2001). In this sense, psychophysiology intersects smoothly with the human phenotype research since they meet in the biological and behavioral systematic observations concerning advances in the understanding of diseases. Besides, this discipline brings to light cognitive processes relevant to psychological and behavioral research. Hence, this intersection may provide directions into the study of the course of the genotype-phenotype correlation and how this course bidirectionally affects the environment. These directions emphasize recent literature gaps regarding physiology when mentioned the need to incorporate novel knowledge into the phenotyping (Weng et al. 2020).
In turn, phenotyping organizes phenotypes’ characterization, where interrelationship of social, environmental, and psychophysiological constitutes a holistic perspective of daily phenotypic traits. In this respect, the interrelationship approaches the phenotype in the reach of being gathered by computational methods, and capable of contributing to psychological and behavioral research. For example, researches have investigated physiological measurements as markers of psychological stress using smartphones and wearables (Smets et al. 2019). This investigation emphasizes the relevance of conducting studies in front of ecological situations, which indirectly approach a multitude of environmental and social involvement. Hence, this kind of study meets the inherent characteristics of phenotypes gathered by computational methods.
Computational phenotyping
Deep Phenotyping constitutes a broad research area regarding characterization and interpretation of phenotypes’ components, focusing on genotype and phenotype correlations according to individual characteristics (Robinson 2012; Delude 2015). Computational Phenotyping, in turn, provides algorithmic capabilities to deal with semantic representation, integration, and processing of phenotype information, which assists in the deep phenotyping research. In this context, two special issues have reviewed computational capabilities toward the advances in precision medicine concerning phenotyping. The first highlights the privacy preservation of personal genotype and phenotype, in addition to algorithms development for phenotyping, disease recognition and classification, and drug repositioning (Shen et al. 2019). The second features natural language processing for richer phenotypes, standardization beyond terminologies, the temporal trajectory of a phenotypes and sub-typing, besides identifying connections between diseases and the common phenotypic traits, and novel data for phenotyping (Weng et al. 2020). Regarding this latter, the reviewed studies originated from a diverse available information source, such as electronic health records, clinical and medical data, pathology reports, questionnaires, cardiovascular, and voice measurements.
Additionally, deep phenotyping has received two similar research disciplines derived from personal mobile devices and the respective information source, namely mobile sensors and smartphone usage patterns. The first discipline is named Digital Phenotyping, referring to the moment-by-moment quantification of the individual-level human phenotype in everyday life, using data from personal mobile devices (Torous et al. 2016). Similarly, Digital Phenotype refers to the redefinition of disease expression regarding individuals’ lived experience regarding wearable and mobile devices. This latter proposes that health-related data from digital devices and social media can shape human illness assessment. It can also expand the ability to understand diseases, using phenotypes as an underlying aspect (Jain et al. 2015).
Regardless of disciplines’ nomenclature, aforementioned works (Torous et al. 2016; Jain et al. 2015) leverage personal mobile devices as an information source for phenotyping since these devices present a high potential of providing longitudinal reflexes of ecological traits. Furthermore, mobile devices provide objective and subjective measurements of the experienced situation (Torous et al. 2016). The objective regards direct measures from the device’s sensors and occurs passively, characterizing unobtrusive gatherings concerning individuals. The subjective considers an active way to retrieve personal perspectives on ecological situations, typically through questionnaires. These measurements benefit information gathering since they are employed as close as possible to real-life contexts.
During the last decade, studies have employed these objective and subjective methods contributing to psychological and behavioral research (Bardram and Matic 2020). These researches reiterate where benefits from psychophysiology may be employed. This adoption considers the usage of wearable devices for physiological measurements primarily, hence, promoting opportunities to describe phenotypic traits regarding the psychophysiological dimension. For example, correlations between psychological states and physiological arousal have been employed supporting psychological and behavioral research (Bavaresco et al. 2020; Aranda et al. 2021).
More specifically, a review with a focus on sensing and computing techniques for digital phenotyping has approached challenges and opportunities in the concern of mental health (Liang et al. 2019). Throughout the review, the authors discuss large-scale data sensing, cognitive, emotional, and sentiment analysis, behavioral anomaly detection, social interaction, and biomarker analysis. The study also provides opportunities for knowledge representation, feature engineering, usage of advanced computational learning, non-intrusive human-computer interfaces, besides the accounting of missing applications for clinical diagnosis and treatment. In addition to these concerns, a recent viewpoint characterizes the combination of deep phenotyping and digital phenotyping as a promising proposal to understand diseases. This is because it benefits large clinical applications through advanced algorithms and data integration about behavioral and human-computer interactions (Fagherazzi 2020). Contributing to this integration, UbiComp has a prominent role in retrieving and gathering phenotypic traits due to computational capabilities concerning ecological observations. This role leverages ubiquitous computing resources to understand psychological and behavioral aspects that influence the course of health and disease.
Ubiquitous phenotyping
Individuals’ phenotypic traits are observed ubiquitously by nature, where virtual and physical environments encompass the experience of situations. Likewise, psychological and behavioral disorders manifest in most diverse forms according to social and environmental factors besides the individuals’ ability to cope with situations. For example, chronic stress or uncontrolled anxiety associated with social relationships do not rely only on physical experiences, such as conflicts at the workplace or home. These situations unleash from a combination of experiences and even manifest themselves in virtual communities.
This reveals the relevance of using ubiquitous technologies to describe phenotypic traits extending information gathering close to the natural experience. Therefore, ubiquitous phenotyping provides a view boosting phenotyping through opportunities from emerging fields. This harnesses the fact that UbiComp features invisible computing as an inherent step of artifacts physically embedded into the natural environment. Although invisible from a human perspective, these artifacts accompany individuals during real-life where the retrieval of phenotypic traits may be seamlessly employed to contribute to a series of biological and medical research.
In this sense, Fig. 2 depicts ubiquitous technologies characterized by outdoor and indoor observations that, in combination, provide opportunities to retrieve daily situations. More importantly, these technologies allow that systems become aware of physiological and psychological responses. Thus, the figure emphasizes personal mobile devices and intelligent environments as two research areas capable of providing information on social, environmental, and psychophysiological dimensions. In this figure, the biological dimension depicted in Fig. 1 is analogously reiterated through the individuals’ image into the circles.Fig. 2 The combination of personal mobile devices and intelligent environments in the complement of high-dimensional and heterogeneous ecological observations. Personal mobile devices are ubiquitously employed during outdoor activities, whereas intelligent environments provide indoor measurement capability, harnessing smart home, smart hospital, and smart factory research. This encourages the ubiquitous application of phenotyping research
According to the field of digital phenotyping (Torous et al. 2016), personal mobile devices represent a significant amount of computational devices employed outdoors that may accompany individuals wherever they are. This is because mobile devices are suitable to be always along with the person. For example, smartphones, tablets, smartwatches, or smart bands, usually are non-transferable from one person to another, and they rely on multimodal capabilities as an information source. In particular, sounds and voices, images, texts, locations, activities, screen gestures, scrolling, and applications’ usage patterns. Moreover, smartphones, tablets, and smart wrist devices are commercially available, whether compared to other specific wearables or physiological devices. In other words, smart glasses, smart t-shirts, and other smaller usable devices, for example, speakers or smart earplugs, currently foster research and market competitiveness (Brush et al. 2020).
In this respect, wearable devices leverage psychophysiological research due to the possibility to incorporate physiological measurements as an information source, such as the electrocardiogram (ECG), electrodermal activity (EDA), electromyogram (EMG), and electroencephalogram (EEG). Although most wrist devices have already incorporated heart-rate sensors, the remainder of physiological possibilities is upon research for large-scale natural usage. In other words, laboratory studies have advanced in the employment of, for instance, electrodermal activity and electromyogram (Smets et al. 2019), and according to the miniaturization and unobtrusiveness of them, researches will benefit from their daily usage (Pierleoni et al. 2021).
In addition to outdoor technologies, ubiquitous phenotyping looks to the advances in the field of intelligent environments. This field features ubiquitous sensors, actuators, and wireless communication networks to provide smart capabilities and amenities around individuals (Acampora et al. 2013; Röcker et al. 2014). For these reasons, UbiComp is a representative part of this field alongside artificial intelligence, and three examples of application are capabilities employed in smart homes, smart hospitals, and smart factories. Consequently, these capabilities meet personal mobile devices in the benefit of phenotyping regarding the limitations that mobile devices present in front of indoor situations’ characteristics. For instance, when situations hamper mobile devices’ use due to working tasks or by the use of another kind of device. Besides, activities that require putting mobile devices standing near, and problems in tracking activities using these devices due to high-intensity movements or missing connection characterize limitations. Moreover, indoor technology also allows this analysis of movements through body gestures, audio, and current location, providing patterns and traits of daily actions such as sociability, engagement, loneliness, aggressiveness, stressful or pleasant (Acampora et al. 2013). As more devices and machines become digitally involved and more innovative, the operational activities, gestures, movements, and usage patterns of these devices also may foster a similar analysis employed with smartphone applications (Altilio et al. 2021).
Additionally, Fig. 2 outlines the capabilities of intelligent environments regarding the unobtrusiveness that these technologies present. In particular, the figure highlights passive measurements from environmental sensors, cameras and microphones, and devices for wireless monitoring. Besides, active measurements are represented by human–machine interfaces, such as the usage of smart devices and smart machinery. These capabilities produce opportunities considering novel dimensions of information retrieval to complement digital phenotyping and clinical data.
The adoption of these different but complementary fields enhances deep phenotyping with a holistic perspective of ecological phenotypes. This is relevant in the study of diseases since normal and abnormal behavioral, psychological, and physiological responses propagate themselves naturally in the most diverse environments (Ebner-Priemer and Santangelo 2020). For example, ubiquitous phenotyping may investigate different environments during adolescents’ development prone to anxiety or major depression. More specifically, this investigation may indicate where symptomatology interferes with daily activities, characterizing a possible distinct type of disorder. In this respect, accompanying individuals during work environments may help discover traits associated with occupational diseases and work-related health problems.
In summary, Fig. 3 depicts an overview of topics discussed in the reviewed literature in light of three main aspects that characterized this study. These aspects are Ubiquitous Phenotyping (A), Computational Phenotyping (B), and Phenotyping and Deep Phenotyping (C). The figure details each aspect according to diverse topics that they comprise through a taxonomic organization. The first (A) and the second (B) intersect smoothly since both derive from computer science and engineering. The third (C) encompasses psychological and behavioral besides biomedical research, which originate subjective, objective, and biological knowledge to characterize phenotypes. Together, these aspects constitute an interdisciplinary research pathway derived from ubiquitous phenotyping.Fig. 3 Taxonomic organization of the interdisciplinary research pathway of ubiquitous phenotyping. The Ubiquitous Phenotyping (A) comprises technological and clinical approaches for gathering information. Computational Phenotyping (B) presents research trends derived from the literature in computational capabilities using data from (A) in support of Phenotyping and Deep Phenotyping (C). In turn, this latter encompasses high-level information focusing on psychological and behavioral research and low-level information regarding biomedical research
Challenges and opportunities
Efforts in the employment of UbiComp in social, environmental, and psychophysiological dimensions to characterize phenotypes, although promising, present technical, managerial, and ethical challenges. These efforts naturally involve interdisciplinary research, emphasizing the need to interchange knowledge between researchers from the biomedical area, engineering, and computer scientists (Fig. 3). This is because biological and medical are prevalent in the underlying aspects that will shape computational investigation to employ ecological phenotypes in prevention, diagnosis, and prognosis (Ebner-Priemer and Santangelo 2020).
In respect of this investigation, a technical challenge involves defining and representing the discovered information of phenotypic traits computationally and link this information with knowledge already existent in biomedical science. More specifically, this regards meaningfully understanding a person’s traits and their particularities in the most diverse physical and virtual environments and the correlations with possible diseases. Also, the extensions of these correlations may help discover cause and effect derived from phenotypic traits to disease. This is also a challenge because individuals differ in interpreting situations, physiological responses, and associated behavior. For example, the cause and effect of behavioral and physiological phenomena concentrate on understanding how and why specific environmental conditions unleash a particular psychological response. On the other hand, this also leads to an opportunity because although individuals are different in their traits but considering they inherit genetic material, a potential future scope may regard whether behavioral and physiological traits collected by ubiquitous resources are hierarchically and genetically propagated. Thus, this may produce potential insights regarding progeny diseases’ predisposition, facilitating possible inferences using computing for diagnoses and prognosis.
Another technical challenge comprises the intersection of information between personal mobile devices and intelligent environments. The intersection regards indoor and outdoor patterns that, in combination, assist in the holistic perception of situations and understanding of diseases. This combination encounters similar challenges of the high-dimensional and heterogeneous information source concerning the employment of digital phenotyping (Liang et al. 2019). For instance, the correlation of smartphone usage patterns or physiological measurements in respect of images captured from indoor cameras presents the need for timing and synchronization. Besides, ecological observations are noisy and may present missing information due to the sensors’ inaccuracy (Bardram and Matic 2020). Nevertheless, technical opportunities arise from these sources of information considering artificial intelligence methods and techniques. In particular, computational learning and reasoning, pattern analysis, and predictions may be employed for personalized behavior understanding, psychological and physiological correlations, and to identify environmental and social conditions.
Managerial challenges refer to technology’s employment in the everyday workplace environment, such as hospitals, factories, or even homes. Particularly in industries, despite adopting the industrial internet of things, there is a gap in considering sensing technologies to benefit workers’ health. Managers should be aware that observations during work activities, such as physiology and behavior, may help understand occupational and work-related diseases. This potentially presents opportunities for short- and long-term improvements regarding individuals’ health and productivity. Therefore, investments in this kind of observation are valuable both for individuals and companies. Furthermore, in the context of indoor monitoring, even with the widespread adoption of intelligent devices, this segment also accounts for research challenges, according to discussions about the usage of physiological devices, comfort, and privacy in monitoring (Brush et al. 2020).
In light of medical sciences, the research about ubiquitous phenotyping faces ethical challenges (Muller et al. 2021). This is because individuals’ ecological observations enter on particular aspects of privacy and confidentiality. The first regards authorization of personal information collection and usage, both indoors and outdoors. The second refers to having access to these data, which considers any individual or system. Moreover, if on the one hand, novel mobile and wearable technologies have been created to decrease device obtrusiveness and produce user acceptance regarding data sources, on the other, systems and applications may become invasive as long as computing artifacts begin to understand individual traits. This understanding, primarily leveraged by large-scale adoption of artificial intelligence on ubiquitous devices, also accounts for potential novel and unforeseen threats. This is why the interdisciplinary research community and practitioners must ensure some requirements in front of information collection and usage, for instance, safety, traceability, transparency, and validity (Holzinger et al. 2021).
In this sense, different data sources produce various degrees of obtrusiveness that instigates discussions. Retrieving objective and straightforward measurements such as physiological activation or intensity of movements seems less obtrusive than understanding behavioral habits as frequented places and daily routine. Because the first is less expressive and semantic than the second, and this second is also human-readable information. Therefore, beginning researches by those with less intrusiveness may become individuals adherent to the research, providing confidence to them as long as research advances. Besides, measurements collected for the specific purpose of an individual’s well-being may potentially be uncomplicated for users to consent whether compared to more general proposals.
Regardless of the obtrusive degree or purpose, any data collection and processing must have consent. The request for consent preceded by a didactic explanation may favor individuals to accept the collection of information. Explanations about the research’s final objective and the pathways to this become the process transparent, favoring awareness and acceptance by the individual. Further, it may be interesting for the individual to control when to enable and disable data collection at a system level. However, this generates a computational problem of frequent missing data, which also leads to technical challenges.
Finally, the storage of daily observation is also a challenge. Both individuals or research practitioners may own this information. The first provides a natural pathway, and it is positive since the information originated from individuals themselves, whereas the second requires additional consent due to confidentiality. Also, in the scenario of a workplace environment, companies may desire to have ownership of this knowledge, which may be explicit between the involved. These possibilities should consider storage strategies since they impact information retrieval and processing for indoor and outdoor data sources.
Conclusion
In view of the interdisciplinary clinical and biomedical research, computing allows sensing from a holistic perspective regarding indoors and outdoors, which present a relevant role to characterize phenotypes. With adequate conception and interpretation of phenotypic traits, this perspective will promote the consequent understanding of diseases. In addition to individuals’ historical information leveraged by computational analysis, this understanding advances toward possible correlations of phenotypes and the genetic predisposition related to health or disease.
According to phenotype characterization and interpretation advancements, computational alongside biological research potentially leverage the focus on genetics approaches concerning the understanding of genotype-phenotype linkage. This reflects an interest in genes’ roles on individual differences and similarities underlying health or disease, in light of the holistic perspective of social, environmental, and psychophysiological dimensions. Hence, the branch of psychology and psychiatry particularly will receive benefits from ubiquitous computing.
Acknowledgements
This work was financed by Fapergs (Foundation for the Supporting of Research in the State of Rio Grande do Sul), CNPq (National Council for Scientific and Technological Development), and Capes (Coordination for the Improvement of Higher Education Personnel - Financing Code 001). The authors would also like to thank the University of Vale do Rio dos Sinos (Unisinos) for embracing this research.
Declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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J Clin Psychol Med Settings
J Clin Psychol Med Settings
Journal of Clinical Psychology in Medical Settings
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Article
A Path Toward Equity and Inclusion: Establishing a DEI Committee in a Department of Pediatrics
http://orcid.org/0000-0002-4684-4343
Bersted Kyle A. [email protected]
Lockhart Kerri M.
Yarboi Janet
Wilkerson Marylouise K.
Voigt Bridget L.
Leonard Sherald R.
Silvestri Jean M.
grid.240684.c 0000 0001 0705 3621 Department of Pediatrics, Rush University Medical Center, 1620 W. Harrison Street, Chicago, IL 60612 USA
3 12 2022
114
9 11 2022
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
The Diversity, Equity, and Inclusion (DEI) committee was established in 2017 within the Department of Pediatrics at Rush University Medical Center (RUMC), an academic medical health center located on the near west side of Chicago, IL. Results from climate surveys highlighted the need for increased DEI initiatives within the department, and a renewed national reckoning on racial tensions sparked an additional sense of urgency for system-level change. This paper outlines the initial creation and ongoing efforts of the DEI committee. Information related to the structure of our committee, aims of our work, progress toward identified goals, as well as ongoing barriers is provided. Academic medical health centers are tasked not only with working and training together, but also to care for a diverse group of patients within a larger community. As such, academic medical health centers represent a unique backdrop and opportunity for individual and system-level change.
Keywords
Diversity
Equity
Inclusion
Academic health center
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pmcThose who identify as African American/Black, Hispanic/Latino, American Indian/Alaska Native or Native Hawaiian/Pacific Islander have been considered underrepresented in medicine (URiM) by the Association of American Medical Colleges (AAMC) since 2004. Seventeen years later, it is estimated that only 11.3% of Pediatric faculty at academic health centers (AHCs) are considered URiM (Yoo et al., 2021), and among trainees, only 16.5% of residents and 13.5% of fellows are in this category (Montez et al., 2021). Regarding other professionals employed by AHCs, recent data indicates that most medical assistants (48.9%; “Medical assistants,” 2020) and registered nurses (68.4%; “Registered nurses,” 2020) in the United States are White. Importantly, these percentages do not reflect the increasingly diverse patient populations that AHCs typically serve. In Chicago for example, recent census data shows that nearly 81% of its youth are children of color (Loury & Runes, 2021).
Physicians (Shanafelt et al., 2015) and other medical staff (Grace & VanHeuvelen, 2019) working in AHCs are at high-risk for burnout, a risk that has been exacerbated by a global pandemic (Morgantini et al., 2020). Employees who hold marginalized identities are at even higher risk, as they face microaggressions (Nfonoyim et al., 2021) and other forms of discrimination (Snyder & Schwartz, 2019) that contribute to hostile work environments. Thus, systemic discrimination permeates through academic medicine in several ways. In addition to its impact on the lack of diversity in medicine, systemic discrimination sustains environments that are not inclusive or equitable for those from marginalized backgrounds who work in AHCs. This contributes to troubling trends in attrition and lack of retention for URiM faculty (Lett et al., 2018), which has been evidenced by the recent exit of several Black physicians from AHCs (Miller, 2021; Blackstock, 2020). Failing to address issues of belonging and equity creates a revolving door of diversity: marginalized and minoritized individuals enter the healthcare organization but soon exit due, in part, to unsupportive environments characterized by an absence of mentorship and sponsors (Beech et al., 2013), barriers to career advancement (Kaplan et al., 2018), as well as the more overt forms of discrimination aforementioned. Thus, many AHCs have failed to understand the implications of bringing healthcare professionals from diverse backgrounds into non-equitable and non-inclusive environments.
The jarring collision of an unprecedented global pandemic with a renewed reckoning on racial tensions last summer (Krieger, 2020) led many organizations such as the AAP (American Academy of Pediatrics), AMA (American Medical Association), ACOG (American College of Obstetricians and Gynecologists) and more recently APA (American Psychology Association) to make statements of apology for or acknowledgement of health inequities and medical racism. Simultaneously, many healthcare institutions expanded their current diversity, equity, and inclusion (DEI) initiatives, or developed them, primarily focused on increasing the number of traditionally underrepresented minorities in the organization. While the importance of DEI work cannot be underscored enough, a significant challenge in this work has been that AHCs often primarily direct initiatives at increasing diversity, little on equity, and even less on inclusion (e.g., Rajaguru et al., 2021). According to APA’s Equity, Diversity, and Inclusion framework (“Equity, Diversity, and Inclusion Framework,” 2021), equity is a “an ongoing process of assessing needs, correcting historical inequities, and creating conditions for optimal outcomes by members of all social identity groups” and inclusion is “an environment that offers affirmation, celebration, and appreciation of different approaches, styles, perspectives, and experiences, thus allowing individuals to bring in their whole selves and to demonstrate their strengths and capacity” (p. 12).
Across the country, there has been a mounting pressure and exposed need among healthcare institutions to build effective infrastructures for moving DEI initiatives from idea to action to sustained change. Indeed, there is a rapidly growing body of work aimed at identifying and describing the apparent problems (e.g., Rosenkranz et al., 2021); providing suggested frameworks for potential solutions (e.g., Kang & Kaplan, 2019); and demonstrating favorable trends towards improvement (e.g., Nehemiah et al., 2021), particularly as it relates to increasing diversity in the recruitment and retention of students and trainees. In comparison, there has been notably less reporting on specific approaches for building or expanding institutional DEI work in academic healthcare settings despite its perceived value (e.g., Nora, 2021).
While comparatively limited, a review of this work reveals several recurring themes, including the importance of assessing the current DEI culture in a given space, developing a stepwise, strategic plan with specific interventions for addressing issues, and identifying specific outcomes to better track progress towards goals. In one example, Pino-Jones et al. (2021) outline a framework for advancing DEI in a new hospital medicine division that focuses on institutional structures (e.g., compensation, recruitment), people, environments, and core mission areas. Similarly, Lingras et al. (2021) describe their step-by-step approach for developing a DEI committee in a single department within a larger AHC. The authors highlight the importance of engagement, collaboration, and shared decision-making among all stakeholders, including from department membership at the grassroots level to promote local change (bottom up) and from leadership to support larger efforts at the systems level (top down).
Although these important contributions to the literature have demonstrated growth of the DEI space in academic medicine, we have found that the specific context in which an AHC functions (e.g., geographical location, size, characteristics of the patient population and neighboring communities) paints a unique picture. This picture captures the attributes that contribute to progress and, importantly, the unmet needs that contribute to inertia in advancing diversity, equity, and inclusion. Thus, an effective approach uses thoughtful assessment and careful tailoring of these broad frameworks to deliver on the needs of the communities within, around, and affected by a system holding as much institutional power as an AHC.
Overview
In this paper, we describe the formation and continued evolution of a DEI committee within the Department of Pediatrics at Rush University Medical Center (RUMC), a large AHC in Chicago, Illinois. Our DEI committee includes an executive board and five subcommittees. We will discuss the unique social and geographic context that motivates this work and the formation of our committee. We will also overview several DEI-related initiatives, including department climate surveys, changes in faculty and residency recruitment, community-building efforts, didactic and training opportunities, as well as changes in policy and procedures aimed at increasing diversity, promoting equity, and building a culture of inclusion in our department. Successful outcomes will be discussed within the context of barriers faced and areas in which continued work is needed. In this way, we hope that our paper can provide a practical guide for others who may be considering how to establish DEI initiatives in their departments.
RUMC: Socio-Geographic Context
RUMC is a large academic health center located just two miles outside of downtown Chicago in the Near West Side neighborhood, a notable location in a city as diverse yet historically segregated as Chicago (Sandoval, 2011). Directly to the east of RUMC is the affluent central business district commonly known as the Loop. At the same distance directly west of RUMC are the Garfield Park and North Lawndale neighborhoods, both predominantly Black communities affected by poverty and decades of disinvestment (Mumm & Sternberg, 2022). For additional context, consider that recent community data reveals a 14-year life expectancy gap between residents of the Loop and residents of East Garfield Park (82 years and 68 years, respectively), a gap that has been attributed to structural racism and socioeconomic deprivation (Ansell et al., 2021). Also within distance of RUMC are the majority Hispanic/Latino Lower West Side and Humboldt Park neighborhoods, both home to large foreign-born populations. This is the rich racial/ethnic and socioeconomic tapestry of the patient population served at RUMC.
Indeed, according to a recent Health Equity Report (2019), 72% of patients presenting to the RUMC emergency department, 49% of inpatient admissions, 56% of patients receiving primary care, and 40% of patients receiving specialty care identified as Black or Hispanic (Ansell et al., 2018). Given its size and location in a major city in the Midwest, RUMC also draws patients from the greater Chicagoland area, neighboring states, as well as international visitors, further diversifying the RUMC patient population not only with regard to race, ethnicity, and socioeconomic status, but also age, language, gender identity, sexual orientation, and religion/spirituality.
Trends in demographic data for the RUMC community of students, trainees, faculty and other staff are not as well reported. During the Fall 2021 term, 13% of the enrolled student body at Rush University identified as Hispanic, 12% Asian, and 8% Black/African American. In the same year, only 10% of faculty at the institution identified as Hispanic or Black/African American (“Rush University Report 2019 to 2021,” 2021). RUMC also reports that 46% of residents and fellows and 50% of all employees are from minoritized groups (“Diversity,” 2022). Taken together, these numbers help contextualize the state of DEI-related issues in the RUMC community. RUMC has been active in addressing such concerns (Ansell et al., 2021) from a top-down approach. Importantly, RUMC also recognizes that in order to fully meet the need of our patients and exist in accordance with our hospital’s values, we must encourage and support departments within the larger organization to also power the movement from the bottom up.
RUMC Department of Pediatrics: DEI Efforts
A diversity and inclusion (D&I) task force was first created by a prior department chair in 2017 (Fig. 1). At that time, two D&I co-chairs were appointed to organize the inaugural department-wide DEI retreat and develop a climate survey. In late 2019/early 2020, following the retirement of one co-chair and the transition of the second co-chair to other academic domains, a new DEI chair was appointed, and an executive board was established. The board was composed of three Black female pediatricians and two White female pediatricians, including the new DEI chair, the outgoing DEI chair (who has remained involved as an advisor in retirement), as well as three department members in leadership roles (department chair, residency program directors). Decisions about various initiatives and goals are discussed and agreed upon by a majority of executive board members.
Fig. 1 Timeline of major events and initiatives
Like many institutions, for better or worse, our DEI-related efforts received a newfound sense of attention and urgency in response to the murders of George Floyd, Breonna Taylor, and countless other people of color in 2020. In order to increase communication between the DEI committee and the department, encouraging visibility and accountability, a secretary position was also added to the executive board in 2020. This position also ensured that executive board meetings were scheduled and attended by all members on a biweekly to monthly basis, with agendas and minutes documented and distributed before and after each meeting.
The secretary position was advertised to the department and filled by a White male pediatric psychologist. The significance of a faculty member with several layers of societal privilege engaging with this work is worth mention. Because DEI work is often led by Black women and other women of color (Rogers & Jayasinghe, 2021), many are leading these efforts while simultaneously navigating issues of being marginalized in their daily lives, experiencing harm due to an incongruence of organizational DEI values and its actions or policies, being asked to facilitate trainings to educate others around painful lived experiences, or mitigating the potential consequences of calling out mistreatment. As such, it is crucial that those in power within organizations use their privilege to promote these efforts and then “step out of the way” for motivated and passionate colleagues from marginalized groups to use their voices, energy, and ideas toward building a more inclusive culture in the workplace (Tulshyan, 2022).
Climate Surveys
Perceived work climate has been studied extensively across disciplines and has been linked to a myriad of positive outcomes, including job satisfaction, productivity, and retention (Harter et al., 2003). Moreover, recent studies have suggested that for younger generations, workplace culture may be even more important to workplace satisfaction than pay or other benefits (Tulshyan, 2022). For our purposes, a climate survey was essential because employees draw conclusions about their employer’s priorities through their perceptions of work climate (Schneider et al., 1994), and we wanted to better understand the extent to which department members felt diversity, equity, and inclusion were prioritized in Pediatrics. In addition to assessing our culture, these surveys were also meant to identify targets for DEI-related initiatives and change.
Upon creation of the executive board, our first identified task was to review prior climate survey data and distribute a revised version later in 2020. The initial climate survey was adapted from the climate survey used at Rush University’s medical school. It was distributed within our department on two occasions in 2017 (n = 101) and in 2019 (n = 99). In addition to demographic information, the climate survey contained a combination of quantitative and qualitative questions and took approximately 15 minutes to complete. Three primary items relevant to the current paper were as follows: (1) I am satisfied with the climate regarding diversity in the department, (2) members of the department create an environment that is conducive to free and open expression of opinions and beliefs, and (3) I feel a sense of belonging as a member of the department. Respondents who selected agree or strongly agree were aggregated and considered to have a generally positive perception. Across both 2017 and 2019 surveys, responses to all three items remained relatively positive and stable, ranging from 75 to 82% of respondents who provided positive opinions. However, an important comparison between the opinions of faculty and staff was not possible due to the manner in which survey demographics were constructed. Additionally, although initial responses were generally positive, it cannot be overlooked that approximately one quarter of respondents reported a neutral to negative opinion of diversity and inclusion.
In 2020, several changes were made to our climate survey to support our continued evaluation of department culture. This updated survey was sent to and completed by a larger group of department members (n = 147), including faculty, residents, fellows, nurses, medical assistants, research teams, clinic coordinators, and other administrative staff. Notably, reaching a larger and more diverse group of department members proved crucial in more accurately assessing our climate. While faculty and trainees continued to provide positive responses regarding free and open expression (87%) and a sense of belonging (88%), staff members had less favorable opinions, with only 72% feeling as though the environment was conducive to free and open expression and 71% feeling a sense of belonging in the department. Moreover, while 80% of faculty and trainees reported feeling as though faculty members in the department are sensitive to issues regarding diversity, this was contrasted with only 68% of staff feeling the same.
Questions unique to our 2020 survey also revealed that 34% of respondents (n = 50) described experiencing microaggressions, 8% described experiencing discrimination, 7% encountered racism, and 15% described being mistreated more generally in the workplace. When asked if respondents knew someone who experienced any of these forms of harassment at work, reports across categories increased to 49%, 25%, 19%, and 22%, respectively. Despite these alarmingly high numbers, very few respondents described making a report about harassment experienced by themselves or others. When asked to elaborate, several important themes emerged from the qualitative data. These ranged from people feeling unsure how to make a report, doubting that any change would occur, and feeling fearful of being identified or potential retribution. A few employees also reflected that their experiences have been so commonly occurring that it was not until reflecting on them that they realized they were being mistreated.
Strategic Plan and Goals
In mid-2020, the DEI executive board reviewed data from all three climate surveys as well as department demographic data and came to the following two conclusions. First, it was clear that there were not enough URiM employees in our department. Of our 103 faculty (i.e., MD, DO, PhD, APP) at the time, only 17% were considered URiM and only 7% identified as Black. The percentage of non-faculty department members (e.g., clinic coordinators, medical assistants, nurses, administrative and research staff) considered URiM was higher; however, this group was still minoritized (46%). Overall, only 35% of our 276 department members were considered URiM, a trend consistently observed within other AHCs in the United States (Ajayi et al., 2021). Second, it was clear that we had work to do regarding our departmental climate. In addition to troubling data on microaggressions, a significant proportion of employees, most notably staff, were not feeling heard or included, and denied that the department was a space that was sensitive to diversity issues.
Therefore, in 2020 the executive board established the following strategic plan that could both address identified departmental challenges as well as create meaningful programming and policy change to facilitate progression toward the following aims. Related to diversity, the DEI committee pledged to work toward achieving a workforce, faculty, and student body that are reflective of the unique communities, patients, and region we serve. Related to equity, the DEI committee set forth to increase employee’s knowledge of the historical impact of systemic discrimination on people from marginalized backgrounds through various trainings and initiatives so that all department members gain an increased understanding of the importance of treating others equitably, rather than equally. Related to inclusion, the DEI committee aimed to build a culture of excellence that fosters an environment of cultural humility and mutual respect for those who work at RUMC, those whom we care for, those whom we educate, those who benefit from the scientific advances we achieve, and those with whom we interact in our surrounding communities.
Subcommittees and Related Initiatives
To begin working toward these goals, five subcommittees were formed in 2020 (Fig. 2): (1) the grand rounds/book club subcommittee was tasked with identifying speakers to present DEI-related topics to our department as well as suggesting book ideas for our book club; (2) the faculty recruitment subcommittee’s primary goal was to identify and implement initiatives meant to bring more URiM candidates and employees into the department; and (3) similarly, the residency recruitment subcommittee aimed to increase URiM representation in the pediatric residency program. Of note, our committee has chosen to change our use of the commonly used term ‘URiM’ to ‘URiM/historically excluded (URiM/HE),’ given the latter’s clearer implication that the underrepresentation of certain minoritized groups in medicine has been a direct result of systemic racism and other forms of oppression. Our final two subcommittees included (4) the retreat subcommittee to coordinate logistics related to our annual retreat; and (5) the operationalization subcommittee, who was tasked with spearheading meaningful “next steps” for transformative action and change in our department, such as identifying and addressing inequities in policies and procedures, establishing a reporting system, or improving inclusion through community-building initiatives.
Fig. 2 Structure and goals of the DEI Committee
Grand Rounds, Book Club, and Communication
Since 2017, the DEI committee has hosted five grand rounds per academic year. Previous speakers, historically identified by the department chair or prior D&I chair, have presented on a wide variety of topics, including social determinants of health, implicit and systemic bias in healthcare, sexual harassment in medicine, racial trauma, and caring for transgender patients. Following the creation of subcommittees in 2020, one member of the department volunteered to lead the grand rounds subcommittee by identifying speakers, soliciting ideas from other department members, and coordinating logistics for each presentation.
The DEI committee also established a monthly book club in 2019, led by one of our executive board members, that has collectively read over thirty books since its inception. Books range from fiction to nonfiction, often are written by women or people of color, and typically focus on issues related to discrimination. Although small group discussions have been well-received by those who regularly attended, book clubs have historically been less attended than the committee would have hoped (i.e., 5–7 people). To increase attendance, in 2020 we began including podcasts, videos, and other forms of media as well as changed the meeting time to fall during the lunch hour instead of after work. These changes have broadened the scope and impact of this initiative through increased participation, with more than twenty department members attending our most recent Book Club meeting. Grand rounds and book clubs have been occurring virtually since the onset of the COVID-19 pandemic, with minimal impact on attendance or participation for department members and generally greater ease and access for invited speakers.
Lastly, to improve communication with the department, the executive board debuted our “DEI Corner” in 2020, a monthly departmental newsletter that summarizes DEI-related events and trainings, provides updates on ongoing initiatives (including Grand Rounds and Book Clubs), offers information on community engagement opportunities, and highlights minority-owned businesses to support in Chicago. The information included each month is reviewed amongst members of the executive board and the residency program manager before being finalized and distributed via e-mail by a resident who volunteered to take this role.
Faculty Recruitment
To begin addressing our diversity issue at its core, the executive board examined our recruitment process. Regarding faculty positions specifically, since 2019 only 8% of our candidate pool has identified as URiM/HE. Although this number is likely an underestimate given that 56% of candidates did not report race or ethnicity, greatly increasing the number of URiM/HE candidates was identified as a top priority by our department in collaboration with Faculty Recruitment at the hospital level. Given that a more purposeful and targeted search for URiM/HE candidates from the start of the hiring process has been shown to increase diversity in new hires (Bhalla, 2019), open positions are now posted to over 50 different organizations and associations, many of which specifically focus on diversity in medicine (e.g., Minority Nurses Association, Professional Women of Color Network). Open positions are also advertised at conferences and career fairs that center UriM and other historically excluded minorities, including the National Medical Association (NMA), Student National Medical Association (SNMA), Health Professionals Advancing LGBTQ Equality (GLMA), and National Hispanic Medical Association (NHMA) conferences.
Collaboration with Faculty Recruitment has aimed to better integrate DEI into our interview process as well. Specifically, it was established that one ‘DEI liaison’ (either an executive board member or faculty recruitment subcommittee member) now participates in every faculty interview. Specific interview questions created by the executive board relate to topics such as how a candidate approaches their work with diverse patients, past experiences in which a project or decision was enhanced by including diverse perspectives, or ways in which the candidate has promoted or added to diversity, equity, or inclusion in previous positions. Candidates may also be asked questions related to their specialty; for example, a neonatologist might be asked to speak to racial disparities in low birth weight and infant mortality.
Notably, through collaboration with Faculty Recruitment on this initiative, a DEI liaison position has been formally created as a role to fill in every department at RUMC. By more purposefully centering DEI during the interview process, we can both illustrate our commitment to this work to prospective candidates (Bhalla, 2019) as well as identify and mitigate biases that may have impacted URiM/HE hires in the past (Tulshyan, 2022). Although we are currently focused on faculty interviews, we plan to eventually expand these efforts into interviews for all employee types.
Although we can only speak to correlation with recent efforts, we have seen an increase in URiM/HE hires in Pediatrics from 17% in 2019 to 43% of all new faculty hires in 2021. Moreover, from 2020 to 2021, the percentage of Black new staff hires increased from 19 to 25% and the percentage of Hispanic/Latino new hires increased from 26 to 37%. Despite these promising increases, continuing to improve in this area remains a priority of our committee. For example, we realized through collaboration with Faculty Recruitment that we were failing to assess the full impact of our initiatives by not asking candidates for feedback, especially URiM/HE candidates who were not employed by RUMC after being interviewed. To better assess the interview experience and candidates’ perception of Pediatrics and RUMC, Faculty Recruitment is creating a survey to be distributed to all candidates following interviews. Moreover, analysis of attrition data revealed that although our diversity trends are encouraging, the importance of equity and inclusion efforts are crucial to ensure that increased diversity in our department is not only temporarily observed. In 2020, 65% of voluntary and involuntary departures in the department were by URiM/HE employees, and in 2021 this percentage increased to 72%.
Residency Recruitment
Importantly, we recognize that an interest in pursuing a medical career develops earlier than residency, and unfortunately, minoritized groups are often excluded in efforts aimed at bringing undergraduates to medical school (Freeman et al., 2016). From 2018 to 2021, URiM/HE applicants have ranged from only 13% to 15% of our pediatric resident candidate pool. In response, we created the Building Blocks: Rush Scholars Program, modeled from a similar program that one of our directors participated in as a URiM/HE high school student. This mentorship program focuses on underrepresented minority junior and senior students attending high schools on the neighboring West Side of Chicago who are interested in medicine. The mission of this program is to provide an integrative curriculum of clinical immersion, personalized mentorship, and community service to prepare underrepresented minorities for matriculation into college, graduate education, and medicine. Students engage in monthly hands-on classroom activities taught by medical students and pediatric residents centered on professionalism, resume building, interviewing skills, life as a medical student, and clinical experiences. Students partner with a medical student and physician mentor to aid in the preparation of their college applications. Students also shadow their medical student mentor in the pre-clinical setting as well as their physician mentor in the clinic/hospital. By participating in this cross-generational community service experience, pediatric residents learn through advocacy, and we hope that student participants will eventually matriculate at Rush University.
In 2017, we began tracking the number of URiM/HE applicants that we invite, interview, rank, and match for our residency program. This data are used as a surrogate measure of department initiatives to increase diversity. Our curriculum for faculty has evolved over the years and currently, in accordance with the Accreditation Council for Graduate Medical Education (ACGME) guidelines for creating a diverse and inclusive workforce, includes implicit bias and bystander training, formal education regarding holistic applicant review, and guidance for expressing a genuine and authentic commitment to the success of each resident during recruitment (Gonzaga et al., 2020). Since 2020, we have adhered to the ACGME guidelines in addition to blinding interviewers to applicants’ academic metrics so they may focus on the other aspects of the holistic review. We also began sending representatives from our program to annual national recruitment and networking events, including SNMA, the Latino Medical Student Association (LMSA), and the Howard University Residency Fair.
In 2019, a panel of URiM/HE graduates from our program traveled back to RUMC to share their experiences during a grand rounds panel titled “Personal Reflections on Navigating Bias and Microaggressions.” The panel was moderated by a skilled facilitator from outside of our department who stimulated reflection and discussion. That year, we also collaborated with program leadership from an East coast psychiatry program who had seen significant success in their match after several years of efforts to increase diversity. Using feedback discussed in our meeting, program leadership developed a plan that included creating additional opportunities for applicants to meet URiM/HE faculty and residents at the end of their interview day as well as during monthly meetups. During these “hang-back sessions,” URiM/HE faculty and residents share their experiences with the applicants about the climate at RUMC, mentorship experiences, and career development. We have continued to hold these sessions virtually during the pandemic, receiving excellent feedback from participants.
In 2020, our residents stepped up with the seven other pediatric residency programs in the Chicagoland area, creating a pledge of solidarity with the Black Lives Matter movement. The statement is front and center on our pediatric residency website. Our residents also outlined their DEI goals for the year: to participate in departmental, institutional, and regional DEI committees; to improve the content of DEI curriculum, including creating programming to address bias, microaggressions and mistreatment; and to advocate for equitable policies affecting child health at RUMC while supporting scholarly work and community engagement activities to address health equity. Residents currently sit on our department’s DEI subcommittees as well as the RUMC-wide Housestaff DEI committee. We also created a formal Advocacy Track for residents specifically interested in community involvement and career development.
In 2021, additional programming to support all residents was added including a board preparation program, programs to support finding mentors of similar backgrounds, early research mentor pairing, career development counseling, and guidance in professional identity formation (Gonzaga et al., 2020). The residency program also funded networking and mentoring events for URiM/HE faculty and residents, including those who identify as LGBTQ+, to foster inclusion, support, and mentorship. Working closely with the residency program directors, we also added DEI-specific goals to resident rotations focusing on equity, disparities, and how to discuss race and ethnicity as it relates to health outcomes (Blanchard et al., 2022).
Although again we can speak only to its correlation with our efforts, URiM/HE applicants invited to interview for our program increased from 20 to 30% from 2019 to 2020. Although this number fell slightly to 27% of invited applicants in 2021, the percentage of URiM/HE applicants who matched with us increased significantly. After only one URiM/HE candidate matched with our program across our 2019 and 2020 classes, 36% (4/11) of residents in our 2021 class are considered URiM/HE. Although we are encouraged by this trend, we remain committed to continuing to increase the number of URiM/HE applicants who are interviewed and ultimately match at RUMC.
DEI Retreat
Our inaugural half-day DEI retreat took place in 2017 and has been held annually ever since. To maximize participation at our retreats, all outpatient clinic schedules are blocked months in advance and inpatient responsibilities are minimized as much as possible. In October 2020, our retreat took place virtually with approximately 240 participants in attendance, including faculty, trainees, nurses, research assistants, medical assistants, clinic coordinators, and other staff. Compared to prior retreats, overall attendance increased in 2020 due to the flexibility afforded by virtual attendance, a benefit of the change from an in-person format due to the COVID-19 pandemic. However, the effectiveness of aspects of the retreat meant to be more interactive (i.e., breakout rooms) was variable over the virtual platform, especially given that many rooms included participants who had never met previously.
Our 2020 retreat included a powerful keynote address by an invited speaker: a Black pediatrician, public health advocate, and scholar who is renowned for her work on the relationship between structural racism, inequity, and health. The retreat also included a facilitated discussion among a panel of invited RUMC leaders involved in DEI work across the system, a dedicated wellness break, as well as small group breakout discussions among participants. The keynote speaker provided thoughtful suggestions in response to some of our department’s most pressing questions, including how organizations can “move past symbolism and make actual change,” and how we as providers and staff can approach discussions of racism and other forms of oppression with our patients. Compared to previous years, the 2020 retreat included an even more purposeful and pointed emphasis on uncomfortable truths and dialogues about systemic racism in medicine.
The impact of the 2020 retreat was immediate; in addition to positive qualitative feedback from department members, participation in DEI subcommittees increased from nine to twenty-nine people and included a more diverse group of faculty, trainees, and staff. Thus, the retreat achieved its goal of challenging department members to engage in self-reflection and community building, and for some, to fuel motivation toward action and change.
Our 2021 retreat also was conducted virtually and was attended by approximately 200 people. It too included a keynote address, this time by speakers from a regional organization aimed at dismantling systemic racism in large institutions. The retreat also included several breakout groups and dedicated wellness breaks.
Operationalization
The fifth and final subcommittee, which focused on operationalizing ideas generated within the department into concrete initiatives, experienced significant growth following our 2020 retreat. In response to the results of our 2020 climate survey, one of their first goals was examining the system for reporting microaggressions and other forms of harassment occurring in the work environment. Unlike residents, who have access to a standardized and formalized process for reporting through graduate medical education, no formalized system exists at the department level for faculty or staff. Although a reporting system exists through the Human Resources (HR) department at the hospital level, their approach and system are not well understood by our department members. As such, the operationalization subcommittee formed three subgroups that included education (e.g., how do we ensure that everyone receives appropriate education and knows what to do when a harm has occurred), logistics (e.g., what does our current system look like and how can it be improved?), and consequences (e.g., what happens when harm has occurred?).
Conversations with HR are ongoing; however, some progress has been made through efforts to integrate aspects of restorative justice (RJ) into our department. RJ is a community-centered and relational approach that brings together those who have harmed and been harmed that brings accountability and healing to all involved in a meaningful way (DeWolf & Geddes, 2019). At this time, an informal system has been established by the executive board in which, following a report of mistreatment, all involved parties are invited to take part in a RJ-based conversation facilitated by one of our identified RJ facilitators. Although this system is not adequate for all types of reports, we intend to continue utilizing it when appropriate (e.g., microaggression, perceived unfair treatment) and when both parties are open to this type of healing.
Although examining RJ as a philosophical framework is outside the scope of this paper, one primary component that we are also beginning to implement is the community-building circle. These circles are designed to build connection and address conflicts that disrupt a group’s ability to function as a community; through facilitation by a trained circle-keeper, RJ circles allow for safe, inclusive spaces that foster personal connections and center on humanistic values (Behel, 2019). Although most often utilized in criminal justice settings, RJ practices are more recently being implemented in healthcare settings (Long et al., 2022).
Thus far, our residents have taken part in RJ circles, both during their orientation as well as intermittently throughout their training, and this year we had opportunities for division chiefs to participate as well. To further integrate this approach into our department, our next DEI retreat in 2022 will purposefully broaden the scope of the RJ framework by inviting all department members to participate in RJ circles. Specifically, we plan to create 14 circles based on job description and clinic location that will each meet with a RJ facilitator during our retreat as well as periodically throughout the year. Initially, circle prompts will focus solely on strengthening interpersonal connections; however, we hope that future circles can also address harms when they have occurred and promote healing among colleagues, therefore improving retention as well.
Changes in hospital policy have also been achieved through the operationalization subcommittee. In response to an incident in which a patient’s parent used racist language toward a Black pediatrician, we initiated dialogues with clinical and HR leaders, Patient Relations, and RUMC’s legal team to enact policy change. As a result of these conversations and ongoing advocacy, RUMC’s patient rights and responsibilities policy was updated to better protect and advocate for all RUMC employees who are victims of racist language and actions in the workplace. Knowing how important visibility is to DEI-related issues (Bourke & Titus, 2019), our policy now more explicitly refers to discrimination based on age, race, ethnicity, ancestry, marital or parental status, veteran’s status, religion, culture, language, disability, sex, sexual orientation, gender, gender identity/expression, socioeconomic status or any other category protected by federal/state law or country/city ordinance as behavior that is not tolerated.
Another initiative identified by the operationalization committee and executive board was improving the availability of resources (e.g., compensation, protected time) for DEI-related efforts, as these speak volumes about an organization’s commitment to DEI. As Singleton et al. (2021) recently noted, “by providing these resources in a top-down manner, it signifies that the voices of historically excluded scholars are not just heard but valued and essential to creating a productive and collaborative community” (p. 3366). Our department chair has successfully advocated for access to funds that allow our department to host nationally renowned speakers and provide relevant training during our DEI retreats. In terms of retention, our department recently participated in an analysis and adjustment of faculty compensation to better reflect national benchmarks as well as to eliminate any identified pay disparities among faculty. Medical assistants across RUMC were also offered a retention bonus.
Our efforts also focused on securing protected time given the myriad costs of DEI work on those who are asked to carry it out, especially employees of color. This is not only true at RUMC; research shows that UriM/HE faculty generally have greater clinical responsibilities and are more active in diversity efforts than non-UriM/HE faculty (Campbell, 2013; Palepu et al., 2000). This is one of several factors contributing to the ‘minority tax’ in academic medicine, defined as “the tax of extra responsibilities placed on minority faculty in the name of efforts to achieve diversity,” which “impact their recruitment, advancement, and retention” (Campbell, 2021; Rodríguez et al., 2015, Campbell & Pololi, 2015).
After dedicating 0.1 FTE (full-time equivalent) to the chair of our DEI committee in 2020, Pediatrics was the first department at RUMC to offer dedicated effort to support a department DEI chairperson through the chair’s endowment fund, followed more recently by the Department of Obstetrics and Gynecology (OB-GYN). In collaboration with other departments, our committee has asked hospital leadership for a dedicated DEI chairperson for every department at RUMC, and the interim dean is advocating for this to be departmentally funded in the future. In this way, DEI work can be created and salaried as a priority that is recognized as a contribution towards advancement, rather than as a supplemental experience that employees put uncompensated time and effort toward, often at the expense of their primary academic and clinical roles or personal lives.
Establishing department DEI chairpersons across RUMC also encourages collaborations among departments and promotes ongoing learning and improvement, another important aspect of DEI work in AHCs. Partnerships across sections, divisions, and teams represent a meaningful way to make connections, share ideas, and improve the culture of the AHC system at large. Our DEI committee has made efforts to not only connect with others outside our department about DEI-related initiatives, but to lead by example with our own efforts for others to follow. We have presented our efforts to other departments as well as to RUMC’s Racial Justice Action Committee (RJAC), a hospital-level group whose mission is to advance social and racial justice along with health equity at RUMC. We also have partnered with The Rush Center for Gender, Sexuality and Reproductive Health (AFFIRM), an organization that works to provide safe, comprehensive, and affirming care to LGBTQ+ patients and employees at Rush. More recently, our committee connected with physicians in Surgery and Psychiatry to better coordinate similar efforts around creating a faculty reporting system at the hospital level. We remain committed to meaningful partnerships across RUMC that promote equity and inclusion for all employees, as well as the patients that we serve.
2021 Check-in Survey
In response to departmental feedback following our 2020 retreat (i.e., comments made during the retreat to the secretary; comments made in the climate survey), the executive board implemented a new biennial climate check-in survey to more efficiently “check the pulse” of the department. Compared to the climate survey, the check-in survey was shorter (5–10 min to complete), easier to analyze (related questions eliminated or combined), and more specific and purposeful in its approach. Additionally, this survey was intended to better capture participation in DEI events, as well as provide an opportunity for department members to anonymously voice their opinions of the various initiatives put forth by the executive board and subcommittees since the 2020 retreat.
A few positive findings from the inaugural check-in survey included that 76% of respondents agreed that diversity, equity, and inclusion is moving in the right direction in the department and 81% of respondents agreed that the department is a safe and welcoming space for employees and families. A smaller majority, 62% of respondents, described feeling listened to by department/DEI leadership, and 43% of respondents indicated that they had been more engaged with DEI initiatives compared to the past. Qualitatively, some respondents reported that increased efforts by the DEI committee have made it easier to bring up related concerns and have more open dialogues in the department. Many respondents commented feeling grateful that DEI efforts became “more visible” in response to the events of 2020. Others described feeling inspired by grand rounds speakers and having learned a great deal through participation in book clubs and our retreat.
However, several concerning findings emerged from the data as well. First, although the number of respondents (n = 100) was commensurate with participation in the 2017 and 2019 surveys, it was a notable decrease from 2020 and represented a response rate of only 33%. For those who did complete this survey, the majority (62%) were faculty or trainees, meaning that the group who was most critical of the department climate in 2020 (i.e., staff) was largely missed. Although 25% of respondents reported having taken an active role in DEI efforts by volunteering as a subcommittee member, regular participation in DEI-related grand rounds (35%) and book club (11%) was extremely low. When asked to indicate their attendance more specifically for 14 DEI-related events over the past academic year, book club attendance (seven total meetings) ranged from 2 to 20% of respondents and grand rounds attendance (five presentations) ranged from 24 to 35%. Most notably, nearly half (48%) of respondents reported that they regularly have “no DEI involvement.”
When asked to elaborate on what barriers prevented more frequent involvement, several administrative and logistical challenges were identified, including lack of time, scheduling conflicts, and feeling overburdened by their primary work responsibilities (e.g., clinical time, documentation, staffing issues, other meetings). However, beyond these types of challenges, some respondents also described negative feelings (e.g., feeling alienated by the department) or philosophical differences (e.g., describing DEI initiatives as hostile) that led to a more intentional disengagement with the DEI curriculum. This begs these questions for leadership: which types of barriers are most easily changed in the short-term via allocation of additional resources, and how do we overcome barriers related to the attitudes and beliefs of those who do not buy-in to the benefits of this work in the long-term?
Concerning trends also emerge when looking closer at the department culture data. In response to the question regarding DEI moving in the right direction in the department, 8% disagreed and 16% described feeling neutral. In addition to addressing those who disagreed, more critically analyzing the ambivalence of the 16% is crucial. Do these respondents feel indifferent because they lack awareness of the prevalence and impact of institutional oppression in the department and in medicine more generally? Or are they aware yet burnt out, feeling helpless or lacking faith in leadership’s ability to enact real change? A comment from a subcommittee member raises this exact issue, as they noted that putting in hours of work related to identifying an adequate reporting system without seeing tangible change “takes the wind out of our sails.”
Similar questions arise during analysis of the remaining questions. Twelve percent of respondents disagreed when asked if they feel listened to by department leadership, and another 26% of respondents described feeling neutral about this. Also requiring attention are the additional 14% of those who replied neutrally when asked if the department is a safe and welcoming space. Of course, burnout, fatigue, or perceptions that there has been a lack of meaningful change in the past may be to blame. However, it is also possible that these department members are afforded the privilege of not needing to speak with leadership about DEI-related matters or needing to consider whether they feel safe or welcomed at work. Regardless of their cause, these findings represent a direct challenge to leadership to continue to work toward meaningful change through initiatives focused on equity and inclusion.
Conclusion and Future Directions
Our DEI committee was established with the aim of improving diversity in the Department of Pediatrics while simultaneously improving our culture to become more equitable and inclusive. We have made progress over the past several years but recognize that the work must continue. Although we have observed significant increases in URiM/HE new hires, faculty and staff members who identify as URiM/HE remain minoritized in our department and comprise a disproportionate majority of our attrition. Our residency recruitment subcommittee has successfully integrated several DEI initiatives into our program; however, our metrics remain lower than our targets. Although we are proud of the range and depth of educational opportunities we provide through grand rounds, book clubs, and retreats, barriers to greater departmental participation remain. While our operationalization subcommittee has been successful in changing some policies and fostering collaboration, our reporting system is a work in progress and our RJ work is in its infancy. Our climate surveys have shed light on several positive aspects of our department yet has also highlighted several ongoing barriers to DEI work, harassment and discrimination experienced by URiM/HE department members, as well as a difference in opinion across department members related to DEI efforts and their perceived importance.
Although difficult work remains, we believe it is important to highlight that engaged leadership has been a primary reason for the successes we have experienced. As outlined, the chair of Pediatrics sits on our DEI executive board and has made clear that DEI initiatives are a priority through (1) creative, economical, and flexible use of funds and (2) positive relationships with hospital finance and leadership. Through actions such as using the chair’s endowment money to fund speakers and trainings, planning months in advance to block schedules for the retreat, meeting with various administrators and leaders throughout the AHC to build the case for DEI-related resources, and advocating for protected FTE time, hospital leadership has received the message that this work is important to our department. Importantly, RUMC as a system embraces DEI efforts, which we know may not be the case at all institutions. In addition to frequently corresponding with employees about DEI-related current events and opportunities to celebrate diversity (i.e., Pride, Black History month), RUMC recently established the RUSH BMO Institute for Health Equity, an institution focused on funding education and training programs, school-based health centers, and community outreach and research initiatives meant to address health inequities.
Unfortunately, the systemic issues reviewed here do not only negatively impact our departmental climate; they also negatively impact the patients and communities that AHCs serve. A stark example of this was discussed in a recent study which found that racial concordance between Black infants and their physicians cuts infant mortality in half, especially in complicated cases as well as in hospitals that treat more Black infants (Greenwood et al., 2020). This is especially relevant for RUMC, given that its primary service area includes several predominantly Black neighborhoods and that our state-of-the art neonatal intensive care unit treats many medically complex children. Despite these realities, as previously mentioned, less than 10% of our Pediatric faculty members currently identify as Black. Although only one example of many, this disparity highlights the urgent need for a continued emphasis on DEI initiatives in AHCs. We have an obligation to ensure equitable healthcare is available for all who seek out our institutions.
Our findings demonstrate how vitally important it is for DEI initiatives to extend beyond recruiting people with diverse identities into our institutions to place equal, if not greater, emphasis on creating an inclusive culture that will cultivate success and a desire to stay in the RUMC community for those who work here. AHCs with successful DEI initiatives develop comprehensive strategies that are driven by institutional leadership; they are inclusive and centering of the most marginalized voices and, most importantly, they are transformative. As an anchor, commitment to these initiatives should include cluster hires (Valantine, 2020), dedicated budgets, autonomy, consideration for leadership roles, pathways for advancement for URiM/HE employees, and sufficient compensated FTE for DEI-related roles. However, initiatives providing only these basic supports are unlikely to produce meaningful and sustained changes to institutional culture. A commitment to doing this work is, categorically, a commitment to changing the institutional structures from the inside out, as this work cannot effectively occur in the absence of substantive change.
Several AHCs, including RUMC, were recently featured in a piece highlighting successful strategies to confront racism in healthcare by centering equity as a foundation (Hostetter & Klein, 2021). These strategies included the invaluable role of metrics as a tool in this work, engaged leadership, the need for safety and anonymity in reporting systems, and accountability for those engaging in harmful behaviors or failing to participate in DEI initiatives. For example, at Penn State, a digital platform is being piloted that allows employees to report racism anonymously and in real time. In its first two weeks of use, nine reports were generated using the program with 15 people reporting from a single department. At UCLA, an equity dashboard monitors a variety of metrics, including racial and other differences across hiring, promotion, training, contracting, patient and employee grievances, and vendors providing goods and services, and is reviewed by an equity council monthly.
This work requires tremendous courage. It requires pulling back the veneer and examining the source of deeply entrenched structural oppression and inequity. This is necessary work for healthcare institutions that endeavor to be equitable in their care delivery because it starts with equity inside the institution. It is not enough to declare our DEI values in mission statements. We must also demonstrate our commitment with actions that reflect these values. This means actively dismantling current harmful structures, and reimagining and rebuilding a health system that values those marginalized based on race or gender, those with disabilities, those who prefer care in a language other than English, and all other variations of marginalization that occur in our health system. This can be accomplished, but it will certainly mean making uncomfortable choices: choices about redistribution of resources, money, and power to be more just and equitable. It will require rebuilding our healthcare system to decentralize experiences and ideas that advance dominant culture so that marginalized groups are appropriately represented, evaluated, and cared for in our hands.
Funding
Not applicable.
Data Availability
Not applicable.
Code Availability
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Declarations
Conflict of interest
Kyle A. Bersted, Kerri M. Lockhart, Janet Yarboi, Marylouise K. Wilkerson, Bridget L. Voigt, Sherald R. Leonard and Jean M. Silvestri declare that they have no conflict of interest.
Ethical Approval
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Consent to Participate
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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36462109 | PMC9735055 | NO-CC CODE | 2022-12-14 23:28:32 | no | J Clin Psychol Med Settings. 2022 Dec 3;:1-14 | utf-8 | J Clin Psychol Med Settings | 2,022 | 10.1007/s10880-022-09929-x | oa_other |
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J Biol Inorg Chem
J Biol Inorg Chem
Journal of Biological Inorganic Chemistry
0949-8257
1432-1327
Springer International Publishing Cham
36484824
1974
10.1007/s00775-022-01974-z
Original Paper
Insights into the role of the cobalt(III)-thiosemicarbazone complex as a potential inhibitor of the Chikungunya virus nsP4
Martins Daniel Oliveira Silva 12
Souza Rafael Aparecido Carvalho 3
Freire Marjorie Caroline Liberato Cavalcanti 4
de Moraes Roso Mesquita Nathalya Cristina 4
Santos Igor Andrade 1
de Oliveira Débora Moraes 1
Junior Nilson Nicolau 5
de Paiva Raphael Enoque Ferraz 6
Harris Mark 7
Oliveira Carolina Gonçalves [email protected]
3
Oliva Glaucius 4
Jardim Ana Carolina Gomes [email protected]
12
1 grid.411284.a 0000 0004 4647 6936 Institute of Biomedical Sciences, Federal University of Uberlândia, Avenida Amazonas, 4C- Room 216, Umuarama, Uberlândia, MG 38405-302 Brazil
2 grid.410543.7 0000 0001 2188 478X São Paulo State University, IBILCE, São José do Rio Preto, SP Brazil
3 grid.411284.a 0000 0004 4647 6936 Bioinorganic Chemistry Group, Institute of Chemistry, Federal University of Uberlândia, Uberlândia, MG 38408-100 Brazil
4 grid.11899.38 0000 0004 1937 0722 Physics Institute of São Carlos, University of São Paulo, São Carlos, SP Brazil
5 grid.411284.a 0000 0004 4647 6936 Molecular Modeling Laboratory, Institute of Biotechnology, Federal University of Uberlândia, Uberlândia, Brazil
6 grid.11899.38 0000 0004 1937 0722 Department of Fundamental Chemistry, Institute of Chemistry, University of São Paulo, São Paulo, SP Brazil
7 grid.9909.9 0000 0004 1936 8403 Faculty of Biological Sciences and Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, UK
9 12 2022
115
26 5 2022
19 10 2022
© The Author(s), under exclusive licence to Society for Biological Inorganic Chemistry (SBIC) 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Chikungunya virus (CHIKV) is the causative agent of chikungunya fever, a disease that can result in disability. Until now, there is no antiviral treatment against CHIKV, demonstrating that there is a need for development of new drugs. Studies have shown that thiosemicarbazones and their metal complexes possess biological activities, and their synthesis is simple, clean, versatile, and results in high yields. Here, we evaluated the mechanism of action (MOA) of a cobalt(III) thiosemicarbazone complex named [CoIII(L1)2]Cl based on its in vitro potent antiviral activity against CHIKV previously evaluated (80% of inhibition on replication). Furthermore, the complex has no toxicity in healthy cells, as confirmed by infecting BHK-21 cells with CHIKV-nanoluciferase in the presence of the compound, showing that [CoIII(L1)2]Cl inhibited CHIKV infection with the selective index of 3.26. [CoIII(L1)2]Cl presented a post-entry effect on viral replication, emphasized by the strong interaction of [CoIII(L1)2]Cl with CHIKV non-structural protein 4 (nsP4) in the microscale thermophoresis assay, suggesting a potential mode of action of this compound against CHIKV. Moreover, in silico analyses by molecular docking demonstrated potential interaction of [CoIII(L1)2]Cl with nsP4 through hydrogen bonds, hydrophobic and electrostatic interactions. The evaluation of ADME-Tox properties showed that [CoIII(L1)2]Cl presents appropriate lipophilicity, good human intestinal absorption, and has no toxicological effect as irritant, mutagenic, reproductive, and tumorigenic side effects.
Graphical abstract
Supplementary Information
The online version contains supplementary material available at 10.1007/s00775-022-01974-z.
Keywords
Metal ion
Antiviral activity
Chikungunya virus
Mechanism of action
Molecular docking
ADME-Tox
Wellcome Trust096670 http://dx.doi.org/10.13039/501100001807 Fundação de Amparo à Pesquisa do Estado de São Paulo #2018/21537-6 http://dx.doi.org/10.13039/501100002322 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 001 #88881.506794/2020-01 Royal Society – Newton Advanced Fellowshiphttp://dx.doi.org/10.13039/501100003593 Conselho Nacional de Desenvolvimento Científico e Tecnológico #142495/2020-4 FAPEMIG (Minas Gerais Research FoundationAPQ-01487-22 APQ-02872-16
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pmcIntroduction
The chikungunya virus (CHIKV) is the etiological agent of chikungunya fever, a tropical disease characterized by high fever, rash, joint pain, and arthralgia [1]. The virus is transmitted through the bite of Aedes mosquitoes and the infection caused by CHIKV can progress to a disabling chronic disease or may cause neurological complications such as Guillain–Barre syndrome [2, 3].
CHIKV is an alphavirus that belongs to the family Togaviridae (ICTV, 2019). It is an enveloped virus of icosahedral capsid and a positive-sense single-strand RNA of approximately 12 kb [4]. CHIKV genome contains two open reading frames (ORFs) [4]. The 5’ ORF encodes four non-structural proteins (nsP1–nsP4) and the 3’ ORF is transcribed into a subgenomic RNA which is translated into five structural proteins (C, E1, E2, E3, and 6 K) [5, 6]. The non-structural proteins play substantial roles in the virus replication forming a replicase complex [7], nsP4 being defined as the CHIKV RNA-dependent RNA polymerase (RdRp). In this way, CHIKV replication is directly dependent on nsP4 activity that represents a promising target for antiviral therapeutic [8]. Therefore, disruption or inactivity of the nsP4 activity can result in the impairment of the CHIKV replicative cycle, decreasing virus replication and also impacting in the clinical progress of Chikungunya fever.
CHIKV was first isolated in Tanzania in 1952 and, for a while, cases related to CHIKV occurred in the Southeast Asian regions, Africa, and Oceania [9]. In 2006, an outbreak was documented in some Indian Ocean islands [10] and, a year later, France and Italy reported cases of this infection [11, 12]. In 2013, an outbreak occurred in Central America, in the Caribbean Islands [13, 14]. Then, the virus spread through North and South America [15]. In Brazil, according to the Urban Arboviruses Monitoring Report, 132,205 cases of chikungunya fever were registered in 2019, with an incidence rate of 62.9 cases/per 100,000 inhabitants in 2019. Northeast and Southeast were the regions with the highest incidence rates in the Country, with 104.6 and 59.4 cases/100,000 inhabitants, respectively. In the same year, 92 deaths were confirmed by CHIKV infection, and a higher lethality rate was observed in elderly people over 60 [16]. In 2020, during the outbreak of COVID-19, the Brazilian states of Bahia, Mato Grosso, Espirito Santo, and Rio de Janeiro showed an increase in likely cases of chikungunya, according to the bulletin released by the surveillance secretary [17]. Furthermore, according to CDC (Centers for Disease Control), over 110 countries reported CHIKV infection cases until October 2020 [18].
Currently, there is no licensed treatment against CHIKV showing the need for new molecules that possess antiviral activity [19]. The treatment of infected patients is palliative and aims to relieve the symptoms caused by the infection. According to the World Health Organization (WHO), the most appropriate drug is acetaminophen 1 g 3–4 times per day for adults, and 50–60 mg per kg per day for children [20]. Other non-steroidal analgesics are also recommended, except aspirin which can cause platelet dysfunction [21].
Thiosemicarbazones (TSCs) are a class of synthetic compounds known to have versatile chemistry, low costs of production, and few atoms waste (only molecules of water are usually released during synthesis reactions) [22]. Teitz and coworkers (1994) described the antiviral activity of N-methylisatin-β4′:4′-diethylthiosemicarbazone, a compound that demonstrated to disrupt the synthesis of Human Immunodeficiency Virus (HIV) structural proteins. TSCs derivatives have also demonstrated antiviral activity described against herpes simplex virus (HSV), affecting the expression of structural proteins of HSV, suppressing capsid assembly, and inhibiting cell-to-cell spread [23].
Besides that, TSCs are also recognized as excellent metal binders, therefore, being widely explored as ligands in coordination chemistry. It also provides very stable and high-quality chelating organometallics [24–26]. Interestingly, TSCs metal complexes have demonstrated antimicrobial [27], antiprotozoal [28], and anticancer [29], and antiviral activities [30]. Usually, thiosemicarbazones are coordinated with metals such as Copper(II) and cobalt(III). These metals are present in the human organism, therefore, representing pre-existing biological pathways that will regulate their therapeutic levels. For example, cobalt(III) is an essential trace element in the human body and also is a necessary component of vitamin B12 [31]. Physiological speciation involving these endogenous metal ions can increase the bioavailability of these compounds, decrease the cytotoxicity and even improve their biological activity [32].
Considering our previous findings on the antibacterial action and preliminary anti-CHIKV activities of the complexes of the type [CoIII(atc–R)2]Cl (R = methyl, Me or phenyl, Ph), as well as the free ligands [33], here we further characterized the anti-CHIKV activity of the cobalt(III) coordination compound with the thiosemicarbazone ligand [CoIII(L1)2]Cl (Fig. 1) and exploited its potential mode of action. Our data show that cobalt(III)-conjugated thiosemicarbazones may provide an interesting source of compounds for the development of future antivirals to treat chikungunya fever.Fig. 1 Chemical structure of the TSC free ligand L1 and its cobalt(III) complex [CoIII(L1)2]Cl
Materials and methods
Preparation of the compounds
The compounds studied here were previously synthesized and characterized as described by Fernandes and coworkers [34]. L1 was prepared by refluxing 4-phenyl-3-thiosemicarbazide and 2-acetylpyridine (1:1) in ethanolic solutions [35]. Briefly, the reaction of CoCl2∙6H2O and L1 (1:2) in ethanol (15 mL) provided [CoIII(L1)2]Cl (Fig. 1). The products were characterized and purities evaluated [33, 34]. The characterization of the compounds was previously certified by techniques such as 1H and 13C NMR, high-resolution mass spectrometry, LC–MS/MS and fragmentation study, and previously reported [34]. The compounds were dissolved in dimethyl sulfoxide (DMSO) and stored at − 20 °C for the biological assays. Dilutions of the compounds in a complete medium were made immediately prior to the experiments to reach a maximum final concentration of 0.1% DMSO. For all the assays performed, cells were treated with DMSO 0.1% as untreated control.
Cell culture
BHK-21 cells (fibroblasts derived from Syrian golden hamster kidney; ATCC® CCL-10™), which are susceptible to CHIKV infection [36], were maintained in Dulbecco’s modified Eagle’s medium (DMEM; Sigma-Aldrich) supplemented with 100U/mL of penicillin (Hyclone Laboratories, USA), 100 mg/mL of streptomycin (Hyclone Laboratories, USA), 1% of non-essential amino acids (Hyclone Laboratories, USA) and 1% of fetal bovine serum (FBS, Hyclone Laboratoires, USA) in a humidified 5% CO2 incubator at 37 °C.
Rescue of CHIKV-nanoluc reporter virus
The CHIKV expressing nanoluciferase reporter (CHIKV-nanoluc) used for the antiviral assays were designed from a CHIKV sequence based on CHIKV isolate LR2006OPY1 (East/Central/South African genotype). The cDNA plasmid of CMV-CHIKV-nanoluc contains a CMV promoter, SV40 terminator, and a sequence encoding nanoluciferase protein inserted into the region encoding the C-terminal domain of viral nsP3 protein [37, 38]. The production of CHIKV-nanoluc virions was carried out as previously described [39–41]. Briefly, 2.3 × 107 BHK-21 cells seeded in a cell culture flask were transfected with 1.5 µg of CMV-CHIKV-nanoluc plasmid, using lipofectamine 3000® and Opti-Mem medium to rescue CHIKV nanoluc reporter virus. Forty-eight hours post-transfection, the supernatant was collected and stored at − 80 °C.
To determine the viral titer, 5 × 105 BHK-21 cells were seeded in each of 6 wells plate 24 h prior to the infection. Then, the cells were infected with tenfold serially diluted supernatant of CHIKV nanoluc for 1 h at 37 °C. The inoculum was removed, and the cells were washed with phosphate-buffered saline (PBS) to remove the unbound virus and added of cell culture media supplemented with 1% penicillin, 1% streptomycin, 2% FBS and 1% carboxymethyl cellulose (CMC). Infected cells were incubated for 2 days in a humidified 5% CO2 incubator at 37 °C, followed by fixation with 3% formaldehyde and stained with 0.5% violet crystal and the viral foci were counted to determine CHIKV-nanoluc titers [42].
Cell viability through MTT assay
Cell viability was measured by MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide] (Sigma–Aldrich) assay. BHK-21 cells were cultured in 96 well plate and treated with concentrations of each compound for 16 h at 37 °C with 5% of CO2. Twenty-four hours post-treatment, compound-containing media was removed and MTT solution at 1 mg/mL was added to each well, incubated for 1 h, and replaced with 100 μL of DMSO to solubilize the formazan crystals. The absorbance was measured at 560 nm on Glomax microplate reader (Promega, USA). Cell viability was calculated according to the equation (T/C) × 100%, in which T and C represented the optical density of the treated well and control groups, respectively. DMSO was used as untreated control. The cytotoxic concentration of 50% (CC50) was calculated using GraphPad Prism 8 (Graph Pad Software).
Antiviral activity assays
BHK-21 cells were seeded at a density of 5 × 104 cells per well into 48-well plates 24 h prior to the infection. CHIKV-nanoluc [38, 41] at a multiplicity of infection (M.O.I) of 0.01 and compounds at the non-cytotoxicity concentration were simultaneously added to cells. Samples were harvested in Renilla luciferase lysis buffer (Promega, USA) at 16 h post-infection (h.p.i.) and virus replication levels were quantified by measuring nanoluciferase activity using the Renilla luciferase Assay System (Promega, USA). The effective concentration of 50% inhibition (EC50) was calculated using GraphPad Prism 8. The values of CC50 and EC50 were used to calculate the selectivity index (SI = CC50/EC50).
To evaluate the protective activity of the compound, cells were pre-treated for 1 h with 50 µM of [CoIII(L1)2]Cl, extensively washed with PBS to remove the compound, and infected with CHIKV-nanoluc (M.O.I. of 0.01). The effect of [CoIII(L1)2]Cl on early stages of infection was analyzed by incubating the virus and compound simultaneously with BHK-21 cells for 1 h. Then, the compound was removed, and cells were added of fresh medium. Additionally, to investigate the activity of the compound in the post-entry stages of the viral replicative cycle, cells were infected with CHIKV for 1 h, washed extensively with PBS to remove the unabsorbed virus, and added of compound-containing media. Luminescence levels were measured 16 h.p.i. to analyze the virus replication rates.
Intercalation assay
To investigate whether the compound interacts with the double-stranded RNA (dsRNA), an experiment using the previously described protocol [43, 44] was performed. Briefly, fifteen nanograms of the dsRNA were incubated with 50 µM of [CoIII(L1)2]Cl at room temperature for 45 min and electrophoresed on a 1% agarose gel prior to analysis by densitometry. DMSO and Doxorubicin (DOX) at 100 µM were used as the untreated and positive control, respectively.
CHIKV nsP4 cloning, overexpression, and purification
The coding region of chikungunya non-structural protein 4 (nsP4) (GenBank KP164572.1; PROT-ID AJY53709.1) was cloned into pET-SUMO expression vector, generating the nsP4_pET-SUMO/LIC expression vector. Rosetta (DE3) E. coli (Novagen) cells were transformed with nsP4_pET-M11/LIC and grown in TB (Terrific Broth) medium, supplemented with 50 μg ml−1 kanamycin and 34 μg ml−1 chloramphenicol at 37 °C. The cell growth was monitored until reaching the optical density (OD600nm) of 1.0. The protein expression was induced by adding 1 mM of Isopropyl β-d-1-thiogalactopyranoside (IPTG), at 18 °C and maintained for 16 h. Cells were harvested by centrifugation and cell pellets were resuspended in lysis buffer (50 mM Tris pH 8.0, 500 mM NaCl, and 10% glycerol). Cells were lysed by sonication and cell debris was separated by centrifugation.
The nsP4 was purified using an AKTA Purifier System (GE Healthcare). The first purification step was affinity chromatography using a HisTrap HP 5.0 ml column (GE Healthcare) and the elution was performed using 250 mM imidazole. Concomitantly, the buffer was exchanged through dialysis and the His-tag-SUMO was cleavaged by TEV protease overnight at 4 °C. Another affinity chromatography step was performed using the same system to collect the protein after cleavage. The protein was concentrated, and a final purification step was done through size-exclusion chromatography on an XK 26/1000 Superdex 75 column (GE Healthcare) pre-equilibrated in buffer 50 mM Tris pH 8.0, 200 mM NaCl and 5% glycerol. The final protein sample was analyzed by SDS-PAGE electrophoresis to confirm its purity. The concentration was determined spectrophotometrically in a Nanodrop 1000 spectrophotometer.
MicroScale thermophoresis (MST)
Experiments were performed on a Monolith® NT.115 instrument (Nanotemper technologies). The nsP4 was labeled on cysteine residues with NT-647-Maleimide dye (Nanotemper Technologies) using the Monolith NTTM Protein Labeling Kit RED-MALEIMIDE as per the manufacturer’s instructions. The cys-labeled nsP4 was used to perform MicroScale Thermophoresis experiments, at the final concentration of 25 nM. An initial binding test was carried out with compound [CoIII(L1)2]Cl at the concentration of 500 µM, to check the interaction between the protein and the compound. The assay control was performed using cys-labeled nsP4 with 5% DMSO. Then, a serial dilution of the [CoIII(L1)2]Cl from 500 to 0.015 µM (15 nM) was performed to obtain the binding curve. The dissociation constant (Kd) was obtained by fitting the binding curve with the Hill function, using GraphPad Prism 8 (Graph Pad Software).
Molecular docking analysis
The 3D structure of [CoIII(L1)2]Cl was obtained by DFT at the pbe0/def2-tzvp [45] level of theory using ORCA 4.2.0 [46, 47]. Auxiliary basis sets AuxJ (def2/J) [48] and AuxC (def2-svp/C) [49] were also used. Optimized structures were rendered using Chemcraft (graphical software for visualization of quantum chemistry computations, https://www.chemcraftprog.com). A representative sequence of nsP4 extracted from the viral polyprotein (UniProt id: Q8JUX6) was modeled using the RoseTTAFold [50] on the Rosetta online server (https://robetta.bakerlab.org/). The nsP4 tridimensional model was assessed using ERRAT [51], Ramachandran Plot [52], and Verify 3D [53] tools in the SAVES v6.0 server (https://saves.mbi.ucla.edu/). The nsP4 binding site was predicted using COACH [54] based on the RoseTTAFold-predicted structure. COACH is a meta-server approach that combines multiple function annotation results to generate ligand binding site predictions. COACH results indicate a binding site similar to the site where the Uridine 5′-Triphosphate (UTP) interacts with the crystal structure of HCV ns5B polymerase (PDBid: 4RY5). Thus, [CoIII(L1)2]Cl was docked with the modeled protein using GOLD [55]. GOLD performs a search for the best interacting pose of the chosen molecule in the receptor binding site using a genetic algorithm (GA) and the scoring function ChemPL. The binding site was defined by the UTP position based on the 4RY5 structure and extrapolated to the modeled nsP4. The GA parameters were set to the default values for the run, with M-L bonds treated as zero-order bonds. The poses generated are then ranked and the solution with the best score was chosen. The intramolecular interactions in the best-ranked pose were analyzed using DS Visualizer (BIOVIA, Dassault Systèmes, Discovery Studio Visualizer, v 20.1, San Diego: Dassault Systèmes, 2020).
ADME-Tox predictions
The free online platforms SwissADME (www.swissadme.ch) and OSIRIS Property Explorer® (http://www.cheminfo.org/Chemistry/Cheminformatics/Property_explorer/index.html) were used to evaluate the parameters of absorption, distribution, metabolism, excretion, and toxicity (ADME-Tox).
Statistical analysis
Individual experiments were performed in triplicate and in a minimum of three times to confirm the reproducibility of the results. Differences between means of readings were compared using analysis of variance (one-way or two-way ANOVA) or Student’s t-test using GraphPad Prism 8 (Graph Pad Software). P values ≤ 0.05 were considered to be statistically significant.
Results and discussion
CHIKV is an emerging arbovirus with a high impact on public health in tropical and non-tropical areas. In recent years, outbreaks have occurred around the world affecting many patients with chikungunya fever, the disease caused by CHIKV [2, 56, 57]. Currently, there is no antiviral therapy against CHIKV, demonstrating the need to identify new anti-CHIKV compounds [19].
In this context, thiosemicarbazones (TSCs) have previously been demonstrated to possess antiviral activity against HIV and HSV by disrupting the synthesis of structural proteins and also capsid assembly [23, 25]. Additionally, TSCs are described as possessing interesting motifs for metal binders and thus being coordinated with metals such as copper(II) and cobalt(III) [58, 59]. Cobalt(III) is an endogenous metal, and therefore, the bioavailability of cobalt(III)-like compounds can be increased, as well as their biological properties, in therapeutic protocols for human diseases [31, 60]. Considering the chemical versatility of the synthesis of TSC and the biological properties of cobalt(III)-like compounds, we previously analyzed complexes of the type [CoIII(atc–R)2]Cl which demonstrated interesting antibacterial and antiviral activities [33]. Here, we characterized the anti-CHIKV activity of the [CoIII(L1)2]Cl, a Cobalt(III) coordination compound with the thiosemicarbazone ligand with promising antiviral proprieties.
[CoIII(L1)2]Cl inhibits CHIKV infection in vitro
We previously demonstrated that the treatment of CHIKV-infected cells with the cobalt(III)-conjugated thiosemicarbazone [CoIII(L1)2]Cl (Fig. 1) reduced CHIKV infection, and cell viability was not affected compared to the treatment with its organic ligand [33]. In this work, [CoIII(L1)2]Cl had its antiviral activity characterized using a recombinant CHIKV engineered to express the nanoluciferase reporter (CHIKV-nanoluc) (Fig. 2A). To assess the effect of [CoIII(L1)2]Cl on cell viability and virus infection, we performed a dose–response assay to determine the effective concentration of 50% (EC50) and the cytotoxicity concentration of 50% (CC50) values for this complex. BHK-21 cells were infected with CHIKV-nanoluc and treated with [CoIII(L1)2]Cl at concentrations ranging from 0.14 to 300 µM, and viral replication levels were evaluated by measuring the nanoluciferase reporter activity at 16 h.p.i. (Fig. 2B). Employing this range of concentrations, it was determined that the [CoIII(L1)2]Cl has an EC50 of 19 µM, CC50 of 62 µM, and SI of 3.26 (Fig. 2B). For further analysis, cells were treated with [CoIII(L1)2]Cl at 50 µM, which significantly inhibited 94% of the CHIKV infection (cell viability > 80%) (Fig. 2C).Fig. 2 A Schematic representation of the engineered Chikungunya virus nanoluciferase genome (CHIKV-nanoluc). B The effective concentration (EC50) and cytotoxic concentration (CC50) of [CoIII(L1)2]Cl. BHK-21 cells were treated with increasing concentrations of [CoIII(L1)2]Cl ranging from 0.14 to 300 µM. CHIKV replication was measured by nanoluciferase activity (indicated by ■) and cellular viability was measured using an MTT assay (indicated by •). Mean values of three independent experiments each measured in quadruple including the standard deviation are shown. C BHK-21 cells were infected with CHIKV-nanoluc and simultaneously treated with [CoIII(L1)2]Cl at 50 µM for 16 h. After treatment, cells were lysed and nanoluciferase levels were measured to assess the CHIKV replication rate. An MTT assay was carried out in parallel. Mean values of a minimum of three independent experiments each measured in triplicate are represented
Our results showed that [CoIII(L1)2]Cl significantly reduced virus post-entry to host cells at non-toxic concentrations, and therefore, the effect of this complex was further evaluated. As shown by other authors, and in agreement with our results, TSCs had their antiviral activity previously described against HIV and HSV, in a post-entry manner. The authors suggested that the mechanism of action for these compounds was related to the disruption of the synthesis of the structural protein and also capsid assembly [23, 25]. Additionally, Langsjoen et al. showed that the gold salt auranofin displayed antiviral activity against CHIKV with a Therapeutic Index (TI) of 104.5 12 h.p.i, aiming to target oxidative folding pathways [61].
[CoIII(L1)2]Cl is a post-entry inhibitor of the CHIKV replicative cycle
To analyze the effects of [CoIII(L1)2]Cl on different stages of the CHIKV replicative cycle, viruses and compounds were added to BHK-21 cells at different times. First, cells were pre-treated with [CoIII(L1)2]Cl for 1 h, washed to remove the compound, and were infected with CHIKV-nanoluc (Fig. 3A). To assess the effect on the early stages of infection, CHIKV-nanoluc and [CoIII(L1)2]Cl were simultaneously added to the BHK-21 cells for 1 h, followed by repeated cell washes to remove the inoculum and addition of fresh media (Fig. 3B). To investigate the interference with post-entry steps of infection, cells were first infected with CHIKV-nanoluc, washed to remove the unbounded virus, and then a media-containing compound was added (Fig. 3C). The results obtained from all these experimental conditions demonstrated that [CoIII(L1)2]Cl at 50 µM inhibited up to 94% of the CHIKV post-entry replication step (Fig. 3C) but had no effect on the early stages of the replicative cycle (Fig. 3B) or in protecting cells from infection (Fig. 3A).Fig. 3 [CoIII(L1)2]Cl impairs post-entry stages of the CHIKV replicative cycle. A BHK-21 cells were pre-treated with [CoIII(L1)2]Cl for 1 h, washed to completely remove the compounds, and were infected with CHIKV-nanoluc. B BHK-21 cells were infected with CHIKV-nanoluc and simultaneously treated with [CoIII(L1)2]Cl 50 µM for 1 h. Then, cells were washed to remove the virus and compound and were replaced with fresh media. C BHK-21 cells were infected with CHIKV- nanoluc for 1 h, washed to remove unbound virus and added fresh media-containing compound. For all protocols, nanoluciferase activity levels were measured 16 h.p.i. Mean values of a minimum of three independent experiments each measured in triplicate are represented. ***P < 0.01 were considered significant
Despite being widely studied as antifungal [62], antibacterial [63], and largely exploited in cancer therapy [64], metal complexes are not studied nearly as much as antiviral agents in comparison to other applications such as anticancer [65], and only a few studies have reported the antiviral activity of cobalt(III) complexes [66]. In the latest 1990, a cobalt chelate series (CTC) (General formula [Co(acacen)(L)2]+) of cobalt(III) complexes were studied as antiviral molecules against Herpes Simplex I virus (HSV-I) in vitro. The drug Doxovir™ (also named Co-1 or CTC-96 in the literature) significantly inhibited HSV-I infectivity in Vero cells at 5 µg mL−1 [67]. In the earlies 2000, Schwartz and coworkers reported that Co-1 at 50 µg mL−1 inhibited the early stages of HSV-1 infection in Vero cells, impairing virus penetration in the initial fusion stage between cell and virus. They have also found that this compound inhibited Varicella-zoster virus (VZV) plaque formation [68]. The antiviral activity of Co-1 was also described against Human Adenovirus type 5 (Ad5) in cell culture, acting as a virucidal compound, and also in rabbit model [69].
Another cobalt complex, the CTC compound Co-sb, showed to inhibit HIV-1 in vitro by Louie and Meade, by disrupting zinc finger structures, inhibiting transcription factors, and also interactions of some viral proteins with zinc fingers domains [70]. Moreover, the cobalt(III) complex sodium hydrogen butylimino bis-8,8-[5-(3-oxa-pentoxy)-3-cobalt bis(1,2-dicarbollide)]di-ate([Co(NH2C(NH)-NHC(NH)NHsBu)3]3 +) showed antiviral activity against HIV-I, inhibiting HIV-I protease interactions in the hydrophobic sites of the protein, with EC50 0.25 µM in PM-1 cells [71, 72]. This compounds also showed antiviral activity against H1N1 virus, reducing H1N1 cytopathic effect in MDCK cells, with EC50 of 125 µg/mL and SI of 8 [73].
What is more, there are only two research articles reporting cobalt(III) complexes as antiviral agents against arboviruses: Miranda and coworkers described the activity of this class of metal complexes against Dengue virus (DENV) and Yellow fever virus (YFV) [73]; and our previous data published on CHIKV [33]. The compounds investigated by Miranda and coworkers were the cobalt(III) complex of protoporphyrin IX (CoPPIX) and tinprotoporphyrinIX (SnPPIX) [74]. For DENV-2, DENV-3 and YFV CoPPIX presented EC50 of 3.91, 0.77 and 3.74 µmol l−1 in HepG2 cells, while SnPPIX presented 3.26, 0.85 and 0.37 µmol l−1. For DENV, the compounds seem to disrupt or impair protein synthesis, and block virus adsorption and penetration in BHK 21 cells, with the same MOA that inhibited YFV.
Further compounds (non-metals) were reported with antiviral activity against post-entry stages of CHIKV replicative cycle. For example, the guanosine analog Ribavirin, described as a substrate of RdRp of HCV [75, 76], disrupted CHIKV replication with EC50 of 3.41 µM in Vero cells, 2 days post-infection [77]. Additionally, the 6-azauridine, an uridine analog used to treat psoriasis, also impaired CHIKV replication by disrupting CHIKV RNA replication. Briolant and coworkers showed that this compound possesses SI of 204 in Vero cells, 8.5 times higher than ribavirin used in the same study as a positive control [78].
Insights on mechanisms of action of [CoIII(L1)2]Cl
Based on the activity of the complex on CHIKV post-entry stages, we investigated whether this compound could interact with the viral dsRNA. During the chikungunya replicative cycle, a double-strand RNA (dsRNA) is formed as replicative intermediate molecules. Considering that some compounds possess antiviral activity by intercalating into this dsRNA [43] and that many metal complexes are DNA intercalators [79, 80] or DNA binders [81], we assessed the dsRNA interaction capabilities of [CoIII(L1)2]Cl by agarose gel electrophoresis. [CoIII(L1)2]Cl was incubated with 15 nM of dsRNA and analyzed in an agarose gel. Doxorubicin (DOX) at 100 µM and DMSO 0.1% were used as positive and untreated controls, respectively. Since [CoIII(L1)2]Cl had no intercalation activity, ethidium bromide was able to intercalate to the dsRNA and the band was visualized as observed in the untreated control (Fig. 4). Densitometry analysis confirmed that the cobalt(III) conjugated compound did not intercalate with dsRNA (Fig. 4).Fig. 4 [CoIII(L1)2]Cl does not intercalate intro dsRNA. [CoIII(L1)2]Cl was incubated with 15 nM of dsRNA for 45 min and submitted to electrophoresis using a 1% agarose gel (run in 1 × TAE buffer) stained with ethidium bromide, followed by densitometry analysis. DMSO 0.1% and Doxorubicin (DOX) at 100 µM were used as untreated and positive controls, respectively
Aiming to access initial information about a possible target for [CoIII(L1)2]Cl action, the CHIKV nsP4 was synthesized and purified in vitro (Fig. 5A). Thereby, the interaction between nsP4 and [CoIII(L1)2]Cl was evaluated by Microscale Thermophoresis (MST). The binding affinity curve was obtained using a serial dilution of the compound to obtain information on the dissociation constant (kd). The results demonstrated that the binding affinity curve presented well-defined bound and unbound states, suggesting the occurrence of interaction between the CHIKV nsP4 and the [CoIII(L1)2]Cl (Fig. 5B). Through the obtained curve, the estimated kd ± ∆kd for this interaction was 8.35 ± 0.681 µM.Fig. 5 [CoIII(L1)2]Cl interacts with CHIKV nsP4. A SDS-PAGE Electrophoresis gel of nsP4 purification. M: Molecular weight marker; Elu1: Elution of His-tag-SUMO-nsP4 (approximately 70 kDa) by affinity chromatography step; Ptev: sample after incubation with TEV protease, indicating the cleavage of His-tag-SUMO; Elu2: Elution of nsP4 (54.54 kDa) after TEV protease cleavage; The P1 and P2 refer to the two peaks in the chromatogram (right) of the gel filtration step, corresponding to the eluted fractions. The purified nsP4 was eluted in P2 (54.54 kDa). B Binding affinity curve of nsP4 and [CoIII(L1)2]Cl, obtained by Microscale Thermophoresis experiments. Estimated kd ± ∆kd = 8.35 ± 0.681 µM
To achieve evidence on the mechanism of action of this compound, we performed a dsRNA interaction assay. During the CHIKV replication cycle, a dsRNA is formed as a replicative intermediate molecule during the synthesis of a negative sense sRNA which is a template for the next viral replication stages. Considering that some compounds that acted on post-entry stages of virus replicative cycle demonstrated antiviral activity intercalating in dsRNA species [43], we investigated the interference of [CoIII(L1)2]Cl with a dsRNA, however, [CoIII(L1)2]Cl seems to not act by this mechanism.
Knowing that replication is a very important process in the virus replication cycle, we investigated the interaction of [CoIII(L1)2]Cl with the non-structural protein 4 (nsP4), a nsP which plays an essential role in the replicative complex activity. The nsP4 is an RNA-dependent RNA polymerase (RdRp) responsible for the synthesis of new RNA strands that will be incorporated into the viral progeny resulting from the replicative cycle. As it is crucial for viral replication, the RdRp has been an important target for antiviral therapies. Studies have shown compounds with antiviral activity against CHIKV replication, but only a few were documented suggesting nsP4 as a target. Some examples include benzimidazole [82], hesperetin-A derivates [83], and favipiravir [84]. The availability of only a few studies for nsP4 can be explained due to the lack of structural information about this protein, such as the absence of an experimentally solved three-dimensional structure of CHIKV nsP4, which limits studies on the search for specific inhibitors based on this target.
Thus, to investigate whether this protein could be a possible target for [CoIII(L1)2]Cl, we cloned, overexpressed, and purified CHIKV nsP4, and interaction studies were carried out by MicroScale Thermophoresis with different concentrations of the compound. Our data show that [CoIII(L1)2]Cl interacted with CHIKV nsP4, suggesting that it might be a potential mechanism of antiviral action of this complex. Furthermore, molecular docking analysis suggested that the compound potentially interacts with CHIKV nsP4 through hydrogen bonding and electrostatic interactions in the Uridine 5'-Triphosphate (UTP) binding site, and probably impairing the initiation and elongation of new viral RNA, corroborating with the in vitro results.
Molecular docking analysis
In view of CHIKV nsP4 as a possible target for [CoIII(L1)2]Cl complex, molecular docking was performed for a better understanding of the nature of the interactions between this protein and the compound. To this end, a prediction of the nsP4 protein structure was performed using the RoseTTAFold method and the structure was validated using Verify 3D, ERRAT, and Ramachandran Plot formalism (Supplementary Figs. 1–3). The 3D structure of [CoIII(L1)2]Cl was obtained by DFT (Fig. 6A). The compound [CoIII(L1)2]Cl was then submitted as a ligand for molecular docking analysis using the nsP4 protein model as a receptor. The COACH software suggested the Uridine 5'-Triphosphate (UTP) binding site as the probable spot for the [CoIII(L1)2]Cl interaction. The best scored pose (ChemPL = 66.92) was selected (Fig. 6B). Analyzing the intramolecular interactions, it can be observed a hydrogen bond involving the N–H group of Arg205 amino acid (2.95 Å). Furthermore, hydrophobic interactions with Pro298 and Lys295 amino acids (4.95 Å and 4.11 Å, respectively) were predicted, along with aromatic-sulfur interaction with Cys506 amino acid (5.30 Å). Finally, van der Waals interactions were observed with Pro307, Gln310, Glu304, Lys308, Val296, Thr297, Asp467, Ile464, Phe375, Ile372, Ser374, Asp376, and Asp466 (Fig. 7A and B).Fig. 6 Prediction of [CoIII(L1)2]Cl and CHIKV NSP4 structures. A DFT-optimized structure of compound [CoIII(L1)2]Cl at the pbe0/def2-tvp level of theory as implemented in ORCA 4.2.0. Color code: white—hydrogen; gray—carbon; blue—nitrogen; yellow—sulfur; light pink—cobalt. B The predicted nsP4 structure interacting with [CoIII(L1)2]Cl
Fig. 7 In silico analysis of potential interactions between [CoIII(L1)2]Cl and CHIKV NSP4. A Best ranked pose obtained by the molecular docking of [CoIII(L1)2]Cl (represented in red) into the CHIKV nsP4 model. B CHIKV NSP4 and [CoIII(L1)2]Cl atomic interactions. Green dashed line indicates hydrogen bond, magenta, and light magenta dashed lines indicate hydrophobic interactions, yellow dashed lines indicate electrostatic interactions, orange dashed lines indicate pi-sulfur interactions, and numbers in black indicate the interaction distances in angstroms (Å)
ADME-Tox predictions
The evaluation of ADME-Tox properties of L1 and [CoIII(L1)2]Cl complex was carried out to verify the physicochemical properties as lipophilicity, water-solubility, human intestinal absorption (HIA), blood–brain barrier penetration (BBB), inhibition of isoenzymes belonging to the CYP450 system and toxicological effect (irritant, mutagenic, reproductive and tumorigenic). The results are shown in Tables 1 and 2.Table 1 In silico evaluation of Lipinski parameters of L1 and [CoIII(L1)2]Cl complex
Parameters L1 [CoIII(L1)2]Cl
Physicochemical properties
Formula C14H14N4S C30H30N8S2ClCo
MWa 270.35 g/mol 661.13 g/mol
Num. rotatable bonds 5 6
Num. H–bonds acceptors 2 2
Num. H–bonds donors 2 2
MRb 81.92 191.87
TPSAc 81.40 Å2 133.96 Å2
Lipophilicity
log Po/wd,e 2.49 2.16
Water solubility
log S –3.44 –9.07
Classf Soluble Poorly soluble
Druglikeness
Lipinskig Yes No: MW > 500
Bioavailability score 0.55 0.55
aMW: Molecular Weight
bMR: Molar Refractivity
cTPSA: Topological Polar Surface Area
dConsensus log Po/w = Average of all five predictions
elog Po/w = partition coefficient between n-octanol/water
fClass = Ali classes: insoluble < –10 < poor < –6 < moderately soluble < –4 < soluble < –2 < very soluble < 0 < highly
gLipinski = MW ≤ 500; log Po/w ≤ 5; H–bond donors ≤ 5; H–bond acceptors ≤ 10
Table 2 Data on the main pharmacokinetic and toxicology properties of L1 and [CoIII(L1)2]Cl complex
Compound HIA BBB penetration CYP3A4 inhibitor CYP2D6 inhibitor Reproductive Mutagenic Tumorigenic Irritant
L1 High No No No High High Low Low
[CoIII(L1)2]Cl High No No No Low Median Low Low
According to the results listed in Table 1, the L1 is in according to Lipinski’s rules while [CoIII(L1)2]Cl complex breaks one of Lipinski’s rules because of its higher molecular weight (MW > 500). Other important parameters are Log S, MR, and TPSA concerning to hydrophobicity of a given compound, and, consequently, the ability to cross plasmatic membranes and permeate cells. Those parameters provide information about the absorption and distribution of a drug in the organism [85]. According to the results shown in Table 1, the L1 and [CoIII(L1)2]Cl complex could show good lipophilicity and the ability to cross plasmatic membranes. Although this is an initial study, these results reveal that [CoIII(L1)2]Cl has the potential to be used as a metal drug. Furthermore, these data may be useful for future studies in the case of evaluating the absorption and biodistribution of this complex and its analogs in vivo.
The L1 and [CoIII(L1)2]Cl complex were also evaluated for human intestinal absorption (HIA), blood–brain barrier penetration (BBB), and inhibition of isoenzymes belonging to the CYP450 system as a preliminary theoretical study (Table 2). The results showed that both candidates had high absorption in the intestine, none of the compounds were able to cross the blood–brain barrier as well as none inhibited the CYP2D6 and CYP3A4 isoenzymes belonging to the CYP450 system. Furthermore, the toxicological effects (irritant, mutagenic, carcinogenic, and tumorigenic) were also evaluated. In general, the L1 has higher toxic effects than the [CoIII(L1)2]Cl complex, which demonstrates the importance of complexation with a trace metal and shows that the introduction of the metal cobalt ion reduces the toxic effects of the free ligand [86].
Although the complex presents some unsatisfactory results as a potential to be carcinogenic and does not follow all the rules of Lipinsk, it still represents a candidate to the development of antiviral drugs. Some drugs used to treat diseases also violate specific rules and continue to be used as medications, such as ivermectin, tenofovir dis-oproxil fumarate (TDF), ceftadizime, and isoniazid. Acarbose, Chloroquine, Lopinavir, Amodiaquine are predicted by the web server Admetsar 2.0 as hepatotoxic and mutagenic [87].
Conclusion
In summary, we have shown that the [CoIII(L1)2]Cl inhibits the post-entry stage of CHIKV infection, potentially by interacting and interfering with the nsP4 activity. Due to the lack of studies with CHIKV nsP4, there is no positive control for in vitro assays, and also, there is no well-established structure yet. Therefore, we suggest that [CoIII(L1)2]Cl might interact with nsP4 and interferes with its activity, however, we acknowledge that interpretation of these experiments is challenging and further studies are necessary.
It is also important to emphasize the broad antimicrobial activities of this compound since it has already shown activity against Mycobacterium tuberculosis [34], E. faecalis, S. salivarius, S. sanguinis, S. mitis, S. mutans, and L. paracasei [33]. In this way, this compound could be applied for the treatment of multiple diseases caused by such bacteria and the chikungunya virus, which can be interesting for the pharmaceutical industry and generate great social impact. Although metallodrugs are widely exploited in cancer treatment, some antimicrobials and skin diseases, there is no metallodrug licensed to treat any virus infection. Herein we presented data about the antiviral activity and suggest potential MOA of [CoIII(L1)2]Cl against chikungunya, thus reinforcing the relevance of these results to the current state of antiviral research and the potential of this class of metal complexes as a proposed therapeutic molecule candidate to be further explored.
It is worth to mention that there are only a few published works using Cobalt(III) coordinated compounds as therapeutic molecules, highlighting the relevance to the published data exploring such combination. From a vast bibliography, with several papers exploring this coordination, we can then make a better scientific judgment whether the application of these complexes is worthwhile or not for in vivo and clinical trials, reinforcing the application of these data for the research landscape of therapeutic targets against chikungunya fever.
The conclusions obtained from molecular docking studies demonstrated a significant binding of the complex with CHIKV NSP4 structures which is consistent with the in vitro antiviral activity. Furthermore, the antiviral activity of [CoIII(L1)2]Cl against other viruses which impact human health may be the target of future investigation. Considering the pivotal role of RdRp in Alphavirus replication, our results may contribute to future studies on inhibitors of nsP4, representing a relevant contribution to the field of antiviral research against CHIKV. The significant antiviral profile together with ADME-Tox results provides an interesting approach for future in vivo studies.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (PDF 574 KB)
Acknowledgements
We thank Andres Merits (Institute of Technology, University of Tartu, Tartu, Estonia) for the provision of the CHIKV expressing-nanoluciferase reporter. The authors received financial support from the Royal Society—Newton Advanced Fellowship (grant reference NA 150195 to ACGJ and MH), FAPEMIG (Minas Gerais Research Foundation APQ-02872-16, APQ-01164-22 and APQ-01487-22), from the Wellcome Trust (Investigator Award—grant reference 096670 to MH), and CAPES—Finance Code 001. ACGJ is grateful to Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)—Brasil—Prevention and Combat of Outbreaks, Endemics, Epidemics and Pandemics—Finance Code #88881.506794/2020-01. REFP thanks the Sao Paulo Research Foundation (FAPESP), grant #2018/21537-6. IAS received a PhD scholarship (# 142495/2020-4) from the CNPq (National Councel of Technological and Scientific Development).
Data availability
All data generated or analyzed during this study are included in this published article and, its supplementary information files.
Declarations
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36484824 | PMC9735056 | NO-CC CODE | 2022-12-14 23:28:32 | no | J Biol Inorg Chem. 2022 Dec 9;:1-15 | utf-8 | J Biol Inorg Chem | 2,022 | 10.1007/s00775-022-01974-z | oa_other |
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Eur J Philos Sci
Eur J Philos Sci
European Journal for Philosophy of Science
1879-4912
1879-4920
Springer Netherlands Dordrecht
500
10.1007/s13194-022-00500-x
Paper in the Philosophy of the Biomedical Sciences
Reactive natural kinds and varieties of dependence
http://orcid.org/0000-0003-3612-776X
Fagerberg Harriet [email protected]
grid.212340.6 0000000122985718 Hunter College and The Graduate Center, City University of New York, New York, NY USA
7 12 2022
2022
12 4 7218 11 2021
7 11 2022
© Springer Nature B.V. 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
This paper asks when a natural disease kind is truly ‘reactive’ and when it is merely associated with a corresponding social kind. I begin with a permissive account of real kinds and their structure, distinguishing natural kinds, indifferent kinds and reactive kinds as varieties of real kind characterised by super-explanatory properties. I then situate disease kinds within this framework, arguing that many disease kinds prima facie are both natural and reactive. I proceed to distinguish ‘simple dependence’, ‘secondary dependence’ and ‘essential dependence’ between a natural kind and its classification, and argue that a natural kind is only really reactive, in an important sense, under conditions of essential dependence. On this basis, I offer a principled hypothesis for why psychiatric kinds may be more metaphysically unstable than paradigm somatic disease kinds.
Keywords
Medicine
Psychiatry
Neuroscience
Natural Kind
Interactive Kind
Biology
http://dx.doi.org/10.13039/501100000267 Arts and Humanities Research Council issue-copyright-statement© Springer Nature B.V. 2022
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pmcIntroduction
This paper is about disease kinds – the classes of illness, disorder and infirmity which feature in medical science and nosology. I argue that the property clusters featuring in medicine often have an interesting structure: they constitute natural kinds, but are in part explained or impacted upon by our practices of classification. For example, people with breast cancer share properties across instances both due to uncontrolled cell-division in their breast tissues and due to being classified as ‘people with breast cancer’ in a particular social context. This peculiar structure of disease kinds prompts the question: when is a natural disease kind truly reactive in response to our social classifications, and when is it merely correlating with a reactive social kind?
In this paper, I propose an answer to this question. I begin with a permissive account of real kinds and their metaphysical structure – following Millikan (2000, 2017) and Godman et al. (2020) – distinguishing natural kinds, indifferent kinds and reactive kinds. I proceed to situate disease kinds within this structure by arguing, via a number of cases studies, that many disease kinds prima facie satisfy the conditions for being natural as well as reactive. On this basis, I raise the question: when is a disease kind really reactive, and when is it just accompanied by or intersecting with a distinct social kind of the same name? I distinguish ‘simple dependence’, ‘secondary dependence’ and ‘essential dependence’, and argue that a disease kind is only truly reactive under conditions of essential dependence. I close by offering a principled neuroscientific hypothesis for why psychiatric kinds really may be more metaphysically unstable than other kinds in biomedicine – (some) psychiatric kinds are essentially dependent.
Kinds of kinds
In what follows, I provide an approach to real kinds in general, following Millikan (2000, 2017) and Godman et al. (2020), and to natural kinds in particular. On this view, natural kinds are property clusters which are explained by the presence of a super-explanatory property of the sort that feature within the natural sciences. Building on this framework, I distinguish reactive kinds and indifferent kinds. Reactive kinds are property clusters which are in part explained or impacted upon by our practices of classification, whereas indifferent kinds are those where this does not obtain.
Real kinds
A real kind is a category whose instances share a great many properties in common for some good, non-accidental reason (Millikan, 2000, 2017). Real kinds are sometimes called ‘property clusters’ for precisely this reason – they are characterised by many properties being co-instantiated across individual instances, such that the presence of some characteristic properties of the cluster in question increases the probability that the other properties will also be instantiated in a particular instance (see also Boyd, 1999). Knowledge of which sets of properties cluster in the case of a particular real kind allows us to make inferences, or at least educated guesses, about particular members of the kind. For example, as a matter of empirical generalisation, all instances of the kind Equus caballus share many properties in common; they have manes, they trot and gallop, they neigh, they have well-developed flight instincts and so on. Accordingly, if you observe that some particular organism trots and gallops and neighs, you may infer (not infallibly, but with reasonable reliability) that it is a member of the kind ‘horse’ and, in virtue of this, probably also has a mane and a well-developed flight instinct. One can easily see how inferences of this kind would be useful to us humans. As Millikan puts it, we live in a ‘clumpy world’ and our brains have evolved to exploit this fact:The world of physical objects is to a large extent filled with clusters each having densely interlocked properties, clusters that are for the most part distinctly though not always perfectly separated from one another. This kind of structure is what underlies the success of ordinary everyday induction, knowing what to expect of yet another member of what one takes to be the same cluster. It allows one to know what might be expected from a cat or a truck or a piano or a cathedral.
(Millikan p. 12 – 13, 2017)
Real kinds can be contrasted with ‘nominal categories’. Nominal categories are categories whose instances are grouped together for conventional, arbitrary or anthropocentric reasons, and which fail to pick out real property clusters. Because instances of nominal categories fail to share a plurality of properties in common, they lack the potential for induction and generalisation which characterises real property clusters.1
It is no accident or coincidence that instances of the kind Equus caballus have many properties in common. Instances of the kind ‘horse’ share properties in common because they share a common origin (Godman et al., 2020; see also Khalidi, 2013).2 Belonging to the same evolutionary lineage explains the fact that these properties tend to correlate. Godman et al. call these properties – that is, the non-accidental reasons which cause all the other properties to correlate – ‘super-explanatory properties’:When we have a Kind K whose instances share many different properties G, there will typically be some single property E of their instances that causally explains this multiple commonality. … For example, the atomic constitution of gold explains why all samples of solid gold have the same density, electrical and thermal conductivity, melting and boiling point, and so on. More generally, the molecular constitution of any given chemical substance will explain why its instances share many corresponding properties.
(p. 319, Godman et al., 2020)
Where Millikan requires simply that the correlating properties of a real kind cluster for some non-accidental reason, Godman et al. narrow down and draw our attention to the peculiar position of super-explanatory properties in the metaphysical structure of real kinds. Many real kinds share properties in common because of a shared super-explanatory property which occupies a privileged causal-explanatory position relative to the other properties which are typical of the kind.
On the account offered by Godman et al., super-explanatory properties need not be intrinsic, basic or microstructural. Indeed, the property which explains the cluster Equus Caballus – common origin – is relational and historical (Godman et al., 2020; see also Okasha, 2002). In this regard, super-explanatory properties are less philosophically demanding than traditional metaphysical essences (Khalidi, 2013).3 For present purposes, we shall call the other properties associated with a given real kind – those which are caused by the super-explanatory property but are not themselves super-explanatory properties – ‘secondary properties’ of the kind in question. For example, if ‘having atomic number 79’ is the super-explanatory property of the chemical kind gold, then ‘being malleable’ and ‘being highly heat conductive’ are among its secondary properties.
Is every real kind characterised by the presence of a super-explanatory underlying property (even providing that they may be higher level or extrinsic)? Godman et al. suggest that we view super-explanatory properties as an illustration of the principle of common cause: if A and B correlate, then either A causes B, B causes A, or A and B have common cause C.In general, when we find that some A and B are correlated (in the sense that they are co-instantiated more often than we would expect given their separate probabilities of occurrence), then it will be the case that either A causes B, or B causes A, or both A and B are joint results of some common cause.
(318 – 319, Godman et al., 2020)
Godman et al. entertain the possibility that some kinds will be characterised, not by a single super-explanatory property, but by a homeostatic feedback loop between the correlating properties of the kind – where A causes B, which causes C, which causes A. Perhaps, they hypothesise, some weather systems and psychiatric disorders fit this bill (Godman et al., 2020; Borsboom et al., 2019; Boyd, 1999). If so, the authors contend, these kinds do not count as being characterised by a super-explanatory property.
I shall take a slightly more permissive view on this point. Rather than rule out super-explanatory properties in such cases, I hold instead that where a kind K is maintained by some characteristic pattern of some mutually reinforcing properties A, B, and C, the interaction between A, B and C is the super-explanatory property of kind K. Indeed, the pattern of mutually reinforcing properties which characterises the kind may in turn be the cause of other correlating properties of K (such as properties D, E and F) which correlate with each other (and with A, B and C) precisely because of the interaction between A, B and C. In these cases, at least, the interaction itself should count as super-explanatory.4
Consider, as an example of this effect, drug abuse or, as it is termed within the DSM-5, Substance Use Disorder (SUD). It is sometimes hypothesised that SUD is caused by a maladaptive conditioned feedback loop between the reward system, the anti-reward/stress system and the executive system in the brain (see Koob & Simon, 2009; Koob & Volkow, 2016). To which of these neural systems and sub-systems can we attribute the complex behavioural symptoms associated with Substance Use Disorder, such as an inability to attend to important life commitments or to stop using drugs in spite of serious adverse consequences?5 It seems natural to say that these secondary behavioural properties of substance misuse are attributable precisely to the characteristic interaction between these altered systems in the brain, rather than to any one property in isolation. This interaction is, on my view, super-explanatory. One way to think of the metaphysics here is that there are four properties present when the interaction between A, B and C sustains a kind – (1) A, (2) B, (3) C and (4) their pattern of interaction.6
What motivates including feedback loops, or characteristic interactions, among the class of super-explanatory properties? As will become clear, I intend for this framework to apply to psychiatric kinds as well as somatic disease kinds, and many psychiatric kinds are hypothesised as being constituted by characteristic interactions or feedback loops, as Godman et al. (2020) themselves note. Accordingly, it is necessary to widen our notion of what sorts of processes can count as super-explanatory. Moreover, feedback loops may not be unique to psychiatry. For example, they have been implicated in systemic lupus and Alzheimer’s disease (see Shlomchik et al., 2001; Doig, 2018). As such, this view of super-explanatory properties is more friendly to thinking about disease kinds in general.
Because super-explanatory properties occupy a special causal-explanatory position in the metaphysical structure of real kinds, they also play special roles in our definitions and classifications thereof. Chemical elements, for example, are classified according to their particular atomic constitution (such as an atomic number of 79), and not by their secondary properties like hardness, colour or melting point. Likewise, species and higher taxa in biology are defined by their evolutionary lineage. As we shall see, a similar principle also underlies medical theorising and classification.
The view of kinds I outline here differs more in emphasis than in substance from the ‘simple causal view’ advanced by Khalidi (2013) and Craver (2009). However, I agree with Godman et al. that “an undifferentiated appeal to causal structure misses the widespread significance of super-explanatory properties” (p. 321, 2020). Moreover, for reasons that will become clear, explicitly postulating properties which occupy a special causal explanatory position within the kind – rather than vague “causal relations” (Khalidi, p 81, 2013) – will be useful in the present context to enable certain distinctions I wish to make. Provided we are not too demanding about what sorts of properties may occupy this special position (if we permit that they may be interactions, and need not be basic or microstructural), this model can provide a useful template for thinking about real kinds in general and disease kinds in particular.
The picture of real kinds which emerges looks something like this. In Fig. 1, SP represents a super-explanatory property, while each S represents a secondary property, and each arrow represents a causal explanatory relation.Fig. 1 A real kind
Natural kinds
Having defined real kinds as property clusters characterised by super-explanatory properties, we now turn to natural kinds. As I use the term here, natural kinds are a sub-set of real kinds defined by super-explanatory properties of the sort which feature within the natural sciences (broadly construed), for example common evolutionary lineage, shared atomic structure or a peculiar strain of fungal infection. Many contemporary philosophers, contrary to my usage in this papeer, use natural kind to mean real kind or property cluster. If so, copies of Alice in Wonderland – in that they form a real property cluster – would qualify as a natural kind.7 This is in the end a terminological issue, and I have no substantive quarrel with this alternative usage of the term ‘natural kind’.8 The definition of a natural kind which I shall employ here is, in this sense, mostly operational.
Within the broad category of natural kinds, we can draw more fine-grained distinctions according to the nature of the super-explanatory property characterising the kind in question, and the domain within which that property features as an object of study.9 So, for example, gold is a chemical kind – not because the kind gold features as an object of study only in chemistry (clearly it features as an object of study in other domains as well – e.g., goldsmithing, dentistry and economics) – but because the super-explanatory property of gold (atomic number 79) is the sort of property which features in chemistry. Similarly, the kind Equus caballus constitutes a biological kind because (as hypothesised) the property which explains the presence of all the other properties associated with Equus caballus is a common evolutionary origin (which is the sort of extrinsic property which features as an object of study in biology). As we shall see, many disease kinds – the sorts of kinds that feature in medical nosology – will qualify as natural kinds qua biological kinds on this view.10
The picture of a natural kind which emerges looks something like Fig. 2 below, where N is a natural property, each S is a secondary property of N and each arrow (as before) represents a causal explanatory relation:Fig. 2 A natural kind
Indifferent kinds and reactive kinds
Having defined real kinds (contra nominal categories) and natural kinds (contra real kinds that do not count as natural, such as copies of Alice in Wonderland), we shall now make one further distinction. Sometimes, the nature of our theories, concepts and classifications impact upon the objective properties of members of the category under description, such that the nature of the properties associated with the kind change. In turn, these changes may feed back into our theories, concepts and classifications thereof. In these cases, our category is ‘reactive’. Where there is no such relationship between the kind (or category) and its classification, our kind (or category) is ‘indifferent’.
Hacking sometimes implies that awareness, or the possession of a self-concept, is necessary for a reactive effect between members of a kind and its classification to count as reactive (Hacking, 1999; see also Tekin, 2014). I take a much broader view of this. There seems no principled reason to deny that interactive effects which bypass members’ conscious awareness of the classifications themselves, but act on them via other routes – such as through education, policy or the behaviours of other organisms – should not count as interactive (for a supporting argument, see Cooper, 2004; Khalidi, 2010 and Khalidi, 2013). Relatedly, I shall use ‘classification’ to mean the full social apparatus associated with a particular category, including official classification systems (such as the DSM-5 and the Periodic Table) but also legal constructions (refugee status), as well as more implicit social factors such as common biases, conceptions and socially accepted ways of thinking about the world.
Nominal categories like ‘round things’ and ‘gemstones’ are what we might call ‘indifferent nominal categories’. Indifferent nominal categories are categories which do not pick out real kinds upon first being classified, and which are not subject to reactive effects in response to being classified. For example, the act of categorising aesthetically pleasing samples of minerals, rocks and organic matter together does not yield a feedback loop between the category ‘gemstone’ and the samples under description such that where before there was no real property-cluster, one eventually emerges. In this sense, the category of ‘gemstone’ is indifferent to our classification practices. Natural kinds too can be indifferent. Indeed, Hacking hypothesises this to be a distinguishing feature of genuinely natural kinds (Hacking, 1999; cf. Cooper, 2004). Consider again the natural kind ‘gold’. Whether we classify, conceptualise and understand gold as ‘a chemical element with atomic number 79’ or a divine ‘king of metals’ with special celestial connections and healing powers is of no relevance to the objective properties (density, melting point) caused by gold’s atomic structure.11
Not all nominal categories persist in being nominal, however. Consider Hacking’s famous case of Multiple Personality Disorder (MPD). If Hacking’s story is to be believed, MPD started out as a nominal category, just like ‘round things’.12 There was no pre-existing real property cluster which MPD picked out upon first being coined. Instead, there were individual disparate instances of unhappiness and, perhaps, other types of mental ill-health, primarily among young females, upon which a name, a conception and a set of expectations were imposed. So far, MPD is like ‘gemstone’ and ‘farm animal’ – an ‘arbitrary’ grouping of individuals that reflects our interests, rather than a plurality of objective similarities across these instances in the world. However, those diagnosed with MPD did not react to the imposition of this arbitrary label in the same way as would a gemstone or a farm animal.Around 1970 there arose a few sensational paradigm cases of strange behaviour similar to phenomena discussed a century earlier and largely forgotten. A few psychiatrists began to diagnose multiple personality. It was rather sensational. More and more unhappy people started manifesting these symptoms. At first they had the symptoms they were expected to have. But then they became more and more bizarre. First a person had two or three personalities. Within a decade the mean number was seventeen. This fed back into the diagnoses, and entered the standard set of symptoms. It became part of the therapy to elicit more and more alters. The psychiatrists cast around for causes, and created a primitive, easily understood pseudo-Freudian aetiology of early sexual abuse, coupled with repressed memories. Knowing this was the cause, the patients obligingly retrieved the memories. … In 1983 I confidently said that there could never be split bars, analogous to gay bars. In 1991 I went to my first split bar.
(Hacking, p. 296, 2007; see also Hacking, 1998)
A label is allocated to a set of individuals. A standard of behaviours, feelings, expectations, self-perceptions and narratives is imposed on those labelled, and put to work in our institutions, our media and culture, our social and economic systems, and our systems for knowledge production. Those classified then adjust accordingly.
Note that Hacking’s suggestion is not (or not primarily) that those classified adjust to labels imposed upon them by pretending to display the objective properties associated with the label – in this case, MPD. The suggestion, rather, is that the individuals thus classified come to actually possess some properties, such as behaviours, feelings, dispositions etc., in virtue of, or in response to, the imposition of a classification. Changes to the properties of the subjects being classified then feed back into classification systems, which in turn re-inform the experience of the individuals being classified. This is Hacking’s famous looping effect: "[O]ur investigations interact with the targets themselves, and change them. And since they are changed, they are not quite the same kind of people as before” (Hacking, p. 293, 2007). One might worry, therefore, that a kind which is subject to these sorts of effects is an unstable object of scientific knowledge, changing under our feet, or, as Hacking suggests, a ‘moving target’ (2007). As we shall see, not all types of reactivity are equal threats in this regard.
As a consequence of this sort of reactive process, an originally nominal category can cease to be nominal and become real – what I shall term a ‘nominal reactive kind’. Even though these classifications did not track a real property cluster upon first being coined, through reactivity, individuals classified in this way may come to actually share properties in common, and thus the category may come to support the sorts of inductions and generalisations associated with real kinds. Where before there was nothing real to track, there is now a group of people who genuinely share characteristics – feelings, behaviours, dispositions, experiences and, indeed, memories. In other words, members of a nominal reactive kind do share a plurality of properties, and they share a plurality of properties because they share a super-explanatory property – they share the relational, extrinsic property of being classified in a particular way by their social and cultural collective. In other words, a classification (C) can, in the right circumstances, qualify as a super-explanatory property.
In Fig. 3 below, C represents a super-explanatory classificatory property and, as before, each S a secondary property, and each arrow a casual-explanatory relation:Fig. 3 A reactive, classificatory kind
Do nominal reactive kinds – i.e. real kinds that are real only in virtue of our classifications – count as natural kinds? This matter has been disputed in the literature. If you take constituting a natural kind to be nothing over and above constituting a real kind, and you take nominal reactive kinds to (sometimes at least) constitute real kinds, then nominal reactive kinds can count as natural kinds (see Cooper, 2004). According to the framework I have outlined here, however, they do not. What qualifies a real kind as a natural kind is the nature of its super-explanatory property, not its secondary properties. As such, even if different instances of a nominal reactive kind share objective (even biological) properties in common, they do not qualify as natural kinds, because the super-explanatory property they share – being classified in a particular way by the social collective – is not the sort of property which features in the natural sciences. They may, however, qualify as a real social and classificatory kind – that is, a real kind which is explained by the presence of a super-explanatory social classification.
Disease kinds
Having distinguished real kinds from nominal kinds, natural kinds from real kinds, reactive kinds from indifferent kinds, we now turn to disease kinds. What are disease kinds like? Disease kinds are not generally mere nominal categories (non-kinds) or nominal reactive kinds (real kinds, but mere products of our classification systems). Nor are disease kinds, generally speaking, indifferent natural kinds. Disease kinds, as I shall argue, seem prima facie to have both natural and reactive features. In Sect. 3.1., I argue that medical nosology, often enough, picks out real kinds, and that many of these will satisfy the conditions for being natural kinds. In Sect. 3.2. I shall argue that, in addition to satisfying the conditions for being natural kinds, many disease kinds also have a reactive element in that their properties are in part explained, or impacted upon, by our systems of classification.
Disease kinds as natural kinds
According to the framework outlined in earlier sections, natural kinds are real property clusters characterised by super-explanatory properties of the sort which feature within the natural sciences. Biological kinds, I suggested, constitute a subcategory within the broader category of natural kinds, characterised by super-explanatory biological properties. I also outlined a permissive notion of super-explanatory properties, according to which characteristic interactions between properties can count as super-explanatory. Do disease kinds fit this picture? We can split this question into three: (1) do medical kinds pick out real property clusters, (2) are these real property clusters characterised by super-explanatory properties, and (3) are the super-explanatory properties ‘natural’?
Real kinds, as we have defined them, following Godman et al., Millikan, Boyd and others in this area, are categories the instances of which share a great many properties in common – in other words, real kinds are property clusters. Assuming medical science and nosology are not severely off track, instances which are classed together in medicine do often share objective, real, projectible similarities in common.13 These similarities between instances, in turn, inform useful scientific generalisations and inductive inferences between cases. Real similarities between specific cases of disease allow us to infer (not infallibly, but reasonably reliably) from fatigue, hyperglycaemia and unexplained weight loss that the patient probably has diabetes and would respond to insulin. To put this differently, the success of medicine as a scientific endeavour is built upon the assumption of projectible similarities between instances of disease kinds. If we did not expect there to be real similarities between one person with testicular cancer and another, what would motivate giving a sample of them an experimental drug in a clinical trial (and generalising from here to the wider treatment population)? The existence of real property clusters in medicine is what underlies medical knowledge.14
Many medical kinds, then, are real property clusters. But are they characterised by super-explanatory properties? It is interesting to note at this stage that medicine is premised upon an etiology/symptomology distinction which closely mirrors that between super-explanatory and secondary properties. For example, people with scurvy tend to share the symptoms (or secondary properties) of scurvy – anaemia, bleeding, myalgia, gum disease – across instances because they share the underlying super-explanatory property of deficient levels of vitamin C. Similarly, Graves’ Disease is an autoimmune disease caused by the immune system producing antibodies that attack cells in the thyroid gland. Because people with Graves’ Disease share this characteristic dysfunctional immune response, they tend to share a number of other secondary properties in common as well, such as weight loss, rapid heartbeat, fatigue and trouble tolerating heat. Or consider infectious diseases. The symptoms of tuberculosis – such as fever, cough, loss of appetite – are all caused by mycobacterium tuberculosis infecting the body’s cells. In this sense, the infection explains the other properties associated with the kind, and thus counts as super-explanatory.
The etiology/symptomology distinction is also reflected in medical nosology, where systems which individuate diseases according to etiology – that is, the super-explanatory cause of the disease – are considered the gold standard. Indeed, where a particular symptom-cluster (say, fever) is later discovered in fact to be causally accounted for by a number of distinct underlying disease processes (tuberculosis, heatstroke, inflammation of the joints etc.), this usually results in calls for its re-classification into more fine-grained disease-types which better reflect the syndrome’s actual causal underpinnings in each kind of case.15 Recall that we are employing a more permissive notion of the kinds of properties which may count as super-explanatory, spanning characteristic interactions and higher-level properties, and so may count a wider range of etiologies (or specific domino dysfunctions) as super-explanatory properties. Given these stipulations, the distinction between super-explanatory and secondary properties seems an apt model for medical kinds in general.
So medical kinds are, often enough, real kinds characterised by shared super-explanatory properties. But are these properties natural? We have defined natural properties as the sorts of properties which feature within the natural, including the biological, sciences. Thus, if a disease kind is characterised by a particular underlying biological property, state or process – such as a disordered neural circuit, peculiar bacterial infection or uncontrolled cell division in the breast tissues – it would qualify as a natural kind. And indeed, the usual case of a disease kind is just such a case.16
Disease kinds as reactive kinds
As we have seen, many disease kinds qualify as natural kinds in virtue of being real property clusters which are caused by super-explanatory biological properties. However, unlike most other natural kinds – gold, Equus caballus – disease kinds are also divisions between people, and as such form an interesting class. Other than disease kinds, there are very few natural divisions within the category of human beings. Homo sapiens is of course a natural kind, but few distinctions within our species form genuine natural, biological kinds of their own (with the possible exception of biological sex).17 The intra-human property clusters which are important tend mostly to be explained, not by super-explanatory natural properties, but rather by cultural, legal and economic factors – teachers, Palestinians, fathers, members of the middle-class, and so on. In that natural disease kinds also map onto human kinds, they have within them enhanced potential to enter into interactive relations with their classifications – just as other human kinds do.18
The claim I shall go on to defend is not that every natural disease kind has an element of reactivity. I do not think we are in a position to make any blanket claims here and, in any case, it is not important for my purposes to do so. Instead, I shall offer four cases – ranging from the biomedical, to the neurological, to the microbial – which, taken as a whole, motivate the position that medical kinds often have a reactive element.
Breast cancer
Let us first consider breast cancer. Those who develop breast cancer share many properties in common due to a particular shared pathophysiological process and its secondary properties. Uncontrolled cell-division in the breast tissues (the super-explanatory property) causes lumps in the breast or lymph nodes, changes to the structure of the skin, changes to the size and shape of the breast, and eventually more serious symptomology, including mortality. In other words, breast cancer is a natural kind (per our permissive view thereof).19 However, this is not the only reason why people with breast cancer share properties in common. People with breast cancer also share properties as a consequence of being classified, conceptualised and treated in a particular way within a particular social context. As is particularly often the case with ‘women’s diseases’, a diagnosis of breast cancer carries particular social meanings and cultural significance – in some respects, it is a category ‘on the move’. Discussing the emergence of the category as an identity in the early 20th Century, Klawiter writes:In addition to the stigmas that adhered to cancer in general, the stigma of breast cancer in particular … was intensified and inflected by the cultural power of women’s breasts. But although gender, heterofemininity, and the cultural significance of women’s breasts were deeply implicated in the stigma of this disease, the stigma itself circulated in the form of discourses that were not “carried” by specific individuals or particular subsets of the female population. With rare exception, no one publicly identified as a woman with breast cancer, as an ex-breast cancer patient, or even as a breast cancer victim. No one claimed these [identities] or had them thrust upon her. For the most part, women with breast cancer histories “passed” as normal women and, as a social formation, breast cancer-related identities did not yet exist. … Whereas people with AIDS and HIV were publicly ‘outed’ and disparaged, women with breast cancer were publicly ‘closeted’ and pitied.
(p 8 - 9, Klawiter, 1999)
Contrast Klawiter’s account of being a person with breast cancer in the early 20th Century with how this label features in our current cultural milieu. Since the Pink Ribbon movement, breast cancer awareness month, cancer screening programmes, breast cancer survivor networks and a multitude of corporate campaigns and sponsorships, the properties associated with instantiations of breast cancer have changed. Breast cancer has taken on a new form, indeed perhaps emerged as a “way of being as person” (p. 303, Hacking, 2007). Women with breast cancer share properties – identities, narratives, stigma, experiences – due to being classified as people with breast cancer. Being thus classified is what explains why all these properties are co-instantiated – it is, in this sense, a super-explanatory factor.20
Nor are the natural facts and the classificatory facts entirely causally unrelated here. Stigma and ‘closeting’ of those affected by the disease may contribute to impoverished knowledge of the condition and a lack of research investment, and deter treatment seeking behaviour. This in turn has implications for the mortality rate of the disease, as well as the stages of pathology the disease is permitted to reach prior to intervention. Our classification – through our knowledge, our experts, our institutions and our conceptions – interacts with the pathophysiology of members of the kind to produce certain outcomes. These effects in turn feed back into what it means to have breast cancer – is it a relatively treatable disease from which you may emerge a noble ‘survivor’, or a shameful death sentence?
Autism
Let us move on to consider a rather different case, one that has featured prominently in Hacking’s later work. High-functioning autism, Hacking contends, predates our classification thereof: “[I]f, as is widely supposed, autism is a congenital neurological deficit, then there were certainly autistic children who were dismissed as retarded, feeble-mind, and so on, a long previous litany of dismissive epithets.” (p 304, 2007). In other words, high-functioning autism existed as a real natural (biological) kind prior to our idea of it as such.21 In our terminology then, unlike MPD, autism is not a nominal reactive kind, a mere consequence of our classification practices; it would have been real regardless.
However, as Hacking goes on to argue, even if high-functioning autism always existed as a mind-independent natural kind – a neurodevelopmental disorder – it did not always exist as a ‘way to be a person’:Before 1950, maybe even before 1975, high-functioning autism was not a way to be a person. There probably were a few individuals who were regarded as retarded and worse, who recovered, retaining the kinds of foibles that high-functioning autistic people have today. But people did not experience themselves in this way, they did not interact with their friends, their families, their employers, their counsellors, in the way they do now. Later this did become a way to be a person, to experience oneself, to live in society … This was a looping effect: a few of those diagnosed with autism developed in such a way as to change the very concept of autism. They brought into being the idea of a high-functioning autistic person.
(p. 303 – 304, Hacking, 2007)
Hacking argues that, even if there were people with the congenital disorder of autism prior to the coining of ‘high-functioning autism’ as a construct, there was no one who was a member of the particular social kind ‘high-functioning autism’.22 The properties associated with that kind are in part explained and impacted upon by our peculiar systems of classification – in this case the classification ‘high-functioning autism’. As such, before that classification existed, nor did the cluster of properties caused by its reactive effects.23
Ischemic stroke
Reactivity in the medical realm can also come in the form of self-fulfilling prophecies, aided by placebo and related effects (the mechanisms of which remain largely mysterious) (Benedetti, 2020; Cavanna et al., 2007). Think of ischemic stroke. Until relatively recently the received view was that the brain was essentially ‘set’ after adolescence, and that if something broke it was therefore doomed to stay broken:Just 50 years ago, the idea that the adult brain could change in any way was heretical. Researchers accepted that the adolescent brain was malleable, but also believed that it gradually hardens, like clay poured into a mould, and, therefore, that any damage or injuries it sustains cannot be fixed.
(p. 2, Costandi, 2016)
However, this consensus had been turned on its head in the past few decades, with increasing evidence that the brain possesses a remarkable neuroplastic ability to reorganize itself in response to injury and novel environmental demands. This finding is also informing our theories of brain damage. Where damage to neural tissues was previously thought to be permanent and immutable, it is now recognised that the plasticity of the brain can be harnessed to regain function and compensate for impairments.24 By encouraging those affected to think of their brains as capable of healing themselves, over time, with the aid of therapeutic exercises, cognitive therapies and increased activity levels, perhaps patients may come to have more of this capacity as well. As noted by researchers, “[M]otivation and attention can be critical modulators of plasticity” (Cramer et al., p. 1603, 2011). As such, patients who see their brains as able to heal, rather than permanently and immutably broken, may be more likely to heal – which in turn informs our understanding of the nature of stroke and its pattern of recovery.25
Covid-19
Finally, let us consider a case which is prima facie rather different. It has been pointed out by various participants in the philosophical debate surrounding reactivity and its relationship to natural kinds that some pathogens, like bacteria or viruses, may in the right circumstances count as reactive. Hacking writes:Microbes, not individually but as a class, may well interact with the way in which we intervene in the life of microbes. We try to kill bad microbes with penicillin derivatives. We cultivate good ones such as the acidophilus and bifidus we grow to make yogurt. In evolutionary terms, it is very good for these benevolent organisms that we like yogurt, and cultivate them. But some of the malevolent organisms ones do pretty well too. Disease microbes that we try to kill may as a class, a species, respond to our murderous onslaught.
(Hacking, p. 106, 1999)
That is, our theories and conceptions and the behavioural, scientific and political implications of our theories and conceptions – broadly, our classifications – can under the right conditions act as selection pressures influencing the evolution of the pathogen, such that the properties of the disease-kind are altered.
Perhaps we are living through one such process right now. Sars-Cov-2, the novel Coronavirus, was discovered in Wuhan in the latter months of 2019, and was quickly identified as a major threat to human life, health and societal functioning. In response, countries locked down and instituted control measures intended to reduce transmission. New strains of the virus emerged that were better able to evade our measures by being more transmissible. It is possible that, in a similar vein to Hacking’s microbes, our classifications are acting as selection pressures in the evolution of the virus such that Covid-19 – this disease kind – is altering in response to our classifications (see Khalidi, 2013).26 We have since produced vaccines against the virus and rolled them out on a large scale. How might Sars-Cov-2 evolve next?
Reactive natural kinds and varieties of dependence
As argued in the previous section, we have reason to believe that many disease kinds satisfy conditions for being natural kinds whilst being, to some extent, reactive in response to our classification practices. This prompts the question: under what conditions is a natural disease kind really a reactive natural biological kind, and when does it simply co-occur or intersect with a corresponding social, reactive kind?
In what follows, I shall argue that we can provide a principled answer to this question which is conditional on the variety of dependence relation which holds between the natural kind and its classification. Where the peculiar pattern of correlating properties within a natural medical kind is partly explained by, or impacted upon, by our practices of classification, there are three varieties of dependence which may obtain. Each has different implications for the metaphysics of the kind in question. In cases of simple dependence, there is simply a natural kind and an associated classificatory kind (assuming that the classification yields a social kind) and no real reactivity. In cases of secondary dependence, there is a natural kind and an intersecting classificatory kind, and thus a limited form of reactivity, but not the kind of reactivity which stands to render the natural kind metaphysically unstable and ‘a moving target’ of scientific inquiry. In cases of essential dependence, the natural kind in question really is an unstable reactive natural kind.27
Simple dependence
Simple dependence is so called because it is ubiquitous and represents no real puzzle. According to my definition, simple dependence obtains between a natural kind and its classification when the classification depends upon the properties of the natural kind. For example, our classification of gold reflects or depends upon the underlying super-explanatory property of the chemical kind gold – i.e. ‘having an atomic number of 79’. This is the sort of dependence relation which obtains in successful science.
In these cases, precisely because our classification (C) reflects the nature of the natural kind (N), it is also the case that if some particular instance as a matter of fact is N then that is going to increase the probability of that instance being labelled as C. For example, the fact that the cufflinks I’ve just handed to a jeweller are made of gold – that is, that they constitute a sample of an element with atomic number 79 – is going to increase the probability that the label ‘gold’ will be applied to them (assuming the jeweller is any good at her job). As such, if the classification C has some secondary effects, then the properties caused by the natural kind (the properties S springing from N, in Fig. 4 below) and the properties caused by our classification thereof (the properties S caused by C) will still correlate – even if there is no reactivity to speak of between the natural kind and our classification thereof. For example, suppose our classification of gold includes some culturally contingent symbolism around marriage and romance, and that this causes samples of gold to be frequently formed into rings. If so, then the secondary properties of the natural kind gold (e.g. having a melting point of 1064 °C) will correlate with the secondary properties caused by our classification of gold (e.g. being moulded into rings) despite there being no interaction of note. As such, the secondary properties of C and N will still cluster, even if there is no real reactivity at play.Fig. 4 Simple dependence between a natural kind and a classificatory kind
Some property clusters in medicine likely constitute just such cases of associations between natural kinds and classificatory kinds, where the nature of the classification depends upon the nature of the kind in a simple sense. A number of properties correlate across instances, some of which are products of our classifications (that is, caused by C) and some of which are products of the underlying natural disease kind (caused by N). In cases that fit this pattern, simple dependence obtains, and the natural kind is not really reactive (in that no properties of the natural kind are changing in response to our classifications) – the natural kind is merely associated with a social phenomenon.
Determining which real-world disease kinds fit this pattern will, in practice, be very complicated but, by way of illustration, let us consider a hypothetical example. Suppose a natural disease kind – let’s call it N1 – causes weakness in the arms and legs and bruising of the skin. Through scientific investigation, we discover that N1 is a particular sexually transmitted pathogen, the presence of which can be established by a simple laboratory test. The classification of N1 – let’s call it C1 – now encompasses this knowledge. Due to N1’s association with sex, people who are classified as having N1 (that is, that have the diagnostic label C1 applied to them) also tend to giggle and be embarrassed. Because C1 reflects N1, those persons that actually instantiate N1 now have an increased likelihood of being classified as such, that is, of having C1 applied to them. Because C1 causes embarrassment and giggling, those identified as infected with N1 now instantiate those properties, in addition to weakness in the arms and legs and bruising of the skin. Thus, the properties of the natural kind and the properties of the classificatory kind come to correlate – and as such (in a sense) form a cluster of properties – without any reactivity in the natural kind. N1 is just correlated with C1.
Simple dependence is represented below. As before, N is a super-explanatory natural property, C is a super-explanatory classificatory property, and the downward arrows represent causal relations between the super-explanatory properties (N, C) and their secondary properties (S). The arrow leading from N to C represents the dependence relation between the nature of the natural kind and the nature of our classification thereof. Assuming that C is super-explanatory, and itself the super-explanatory property at the heart of a classificatory, social kind (in the sense outlined in previous sections) what we now have is a natural kind which is associated with a classificatory, reactive kind.28 Their properties will correlate for this reason, but that does not mean that the natural kind itself is reactive.
Secondary dependence
In The Social Construction of What? and elsewhere, Hacking rather confusingly considers the possibility that some particular kind may count both as an indifferent kind and as an interactive kind. Given that indifferent kinds are defined, by myself but also by Hacking, in opposition to reactive kinds – “All I want is a contrast to interactive kinds. Indifferent will do.” (p. 105, Hacking, 1999) – Hacking’s contentions in this regard have caused some understandable bewilderment in the literature: “Given Hacking’s manner of defining interactive kinds and indifferent kinds as ‘classifications that affect their objects of study’ and ‘classifications that do not affect their objects of study’, respectively, he is not entitled to maintain that a classification such as autism can be both interactive and indifferent.” (Tsou, p. 334, 2007). However, as we shall see, the phenomenon of secondary dependence, which I shall outline in this section, makes good sense of the manner in which a particular (in this case, disease) kind may simultaneously both interact with its classification and not.
Secondary dependence obtains where the classification (C) impacts upon secondary properties (S) which are also caused by the kind’s super-explanatory natural property (N). Let us return to the example of breast cancer. Suppose that there is a great deal of stigma associated with breast cancer, and that this impacts upon the extent and timing of treatment seeking behaviour which, in turn, impacts upon the mortality of the disease. Of course, the mortality of the disease is not solely a product of our classifications. Mortality rates for breast cancer are also products of the pathophysiology of the disease itself – that is, uncontrolled cell division in the breast tissues (N). In this sense, the secondary properties of breast cancer (S) depend both upon the super-explanatory natural property of the disease kind (N) and on our practices of classification (C). In this sense, breast cancer is a case of secondary dependence.
We are now in a position to provide a clear solution to Hacking’s puzzle. How can a disease kind be both indifferent and reactive? The answer is that the secondary properties of the disease kind may be responsive to our classifications, but without any reactivity in the super-explanatory natural property which characterises the natural kind. Some secondary properties of breast cancer may be reactive to our classifications, but the super-explanatory property – the property which characterises the kind and occupies a special, causal-explanatory role in the metaphysical structure of the kind – is not. As such, there is a sense in which breast cancer is both indifferent and reactive. The super-explanatory natural property is indifferent, but some secondary properties of the natural kind in questions are reactive in response to our classifications.29
So, assuming C is a super-explanatory property of a classificatory kind, under conditions of secondary dependence we have a natural kind which intersects with a social kind to produce certain outcomes which are products both of the natural kind and the classificatory kind (see Fig. 5 below). In this sense, the properties associated with the disease will not (as in the case of simple dependence) be entirely reducible to the separate contributions of the natural and the social kind – some properties are influenced by both. As such, there is a sense in which the natural kind N is reactive, but it is a limited form of reactivity which does not threaten its stability in response to our classification.Fig. 5 Secondary dependence between a natural kind and a classificatory kind
Essential dependence
Essential dependence between a natural kind and its classification occurs where the super-explanatory natural property at the heart of the natural disease kind is responsive to our classifications (Fig. 6). In other words, a natural kind is essentially dependent if the property (N) of the relevant disease kind is causally impacted by our practices of classification (C). Let us consider again the novel coronavirus. Sars-Cov-2 is the virus which is responsible for the respiratory disease Covid-19. As I have argued above, it is possible that our classification of Sars-Cov-2 as a major threat to human health and well-being, and the resultant policy measures – are impacting upon the evolution of the virus. As such, the super-explanatory natural property of the disease kind Covid-19 is responsive to our classifications. In this sense, Covid-19 is essentially dependent.Fig. 6 Essential dependence between a natural kind and a classificatory kind
My claim is that conditions of essential dependence are the only conditions under which a natural disease kind is truly reactive in an important sense, with implications for the stability of the kind and our classification thereof. If the super-explanatory natural property underlying the kind changes in response to our classification practices, then there is a fundamental instability at the heart of the natural disease kind in question.30 The special super-explanatory property of the natural kind in question – that which is explanatory and definitional – really does change in response to our classification such that, once classified in a particular way, the phenomenon of interest really is not what it once was prior to classification, in the manner Hacking suggests at his more radical: “[S]ince they are changed, they are not quite the same kind … as before. The target has moved.” (p. 293, 2007). In what follows, I shall offer a hypothesis as to when essential dependence may obtain, and why this may occur more often in neuropsychiatric disorders.
Essential dependence, adaptation and neuropsychiatry: a hypothesis
Tsou has argued, contra Hacking, that neuropsychiatric kinds (like depression, schizophrenia and even suicide) are not as unstable as Hacking suggests, because they are in fact characterised by ‘stable’ neurobiological regularities across instances (Tsou, 2007, 2013; see also 2021). And yet neuropsychiatric kinds of various sorts are often cited, by Hacking and others in this literature, as paradigm cases of reactivity. Psychiatry contrasts with biomedicine in this respect as biomedical kinds – arthritis, myocarditis or sickle cell anaemia – are rarely invoked as examples of reactivity (although, as I have argued, in the limited sense of secondary dependence, they often are). How to explain this apparent disanalogy? In what follows, contra Tsou, I shall offer a hypothesis as to why, even if they are underpinned by biological realities, kinds in psychiatry (and possibly to a lesser extent in neurology) may be more susceptible to essential dependence and thus to instability. This view is motivated not by some spooky dualism about the mental, but by a very real biological disanalogy between the brain and the rest of the physical body – the relative plasticity of the brain.
Under what conditions can essential dependence obtain? Essential dependence can obtain where the super-explanatory natural property is susceptible, via some discernible mechanism, to directed change, en masse, in response to our classification practices. For example, the virus which underlies Covid-19, Sars-Cov-2, is literally evolving and so, when our classification practices act as selection pressures in its evolution, the super-explanatory property at the heart of Covid-19 reacts to our classification. As such, it is an unstable and changeable kind.31 However, this change in no way threatens its status as a natural kind – after all, it is still a real kind explained by the presence of a super-explanatory natural property. It’s just that that this super-explanatory property is susceptible to adaptation. In the same vein, other diseases that are evolving – such as those caused by bacteria, fungi and viruses – may be similarly reactive under the right social conditions.
The primacy of adaptation to essential dependence points to an interesting implication. It may be that neuropsychiatric kinds characterised by dysfunctions in complex or higher-level neural traits are susceptible to essential dependence as well, because they too are susceptible to adaptation.32 The reductionist programme in psychiatry – which optimistically hypothesised that psychiatric disorders would turn out be neatly reducible to simple, basic pathologies (as was the case for, say, neurosyphilis) – has largely given way to a programme according to which, even if psychiatric disorders are brain disorders, many of them are likely to be disruptions in complex neural functions or, as the National Institute of Mental Health’s Research Domain Criteria project would have it: psychiatric illnesses are “neural circuit disorders” (p. 499, Insel & Cuthbert, 2015).
Complex higher level neural processes differ from functions in the rest of the body in some interesting respects. In particular, relative to functions of the biological body beyond the brain (and perhaps some very basic brain functions, such as the internal functioning of neurons), higher level neural processes have a remarkable potential for neuroplastic adaptation to external stimuli and novel environmental demands. When these novel environmental demands include our classification practices, theories and conceptions, it seems possible that the underlying super-explanatory neurobiological property (that is, the dysfunctional neurocircuitry causing the psychiatric disorder) may change, systematically, in response to our practices of classification. That is, like our evolving pathogens in the above, neural circuits are amenable to adaptation (broadly construed).33
Whether and when this in fact occurs in particular cases is going to be difficult to ascertain. However, by way of illustration, let us consider a (hypothetical) example. Suppose Substance Use Disorder is caused by a maladaptive feedback loop between the reward system, the stress system and the executive system in the brain. If so, this characteristic interaction between neural systems is the natural super-explanatory property which causes the secondary properties of addiction, such as neglect of important life goals (as suggested in previous sections). Suppose further that addiction is reconceptualised and reclassified as a disease, rather than as moral deviance (as it was previously understood). Assuming addiction is realised by a dysfunctional neural circuit with the capacity to adapt plastically to environmental factors it seems possible that this change in our classification (which, after all, forms part of the social, political and material environment within which our brains must operate) could affect the super-explanatory neural processes. If the natural property underlying the disease is a neural process with the potential for adaptation in response to environmental (including social) factors, there seems no principled reason to assume that our classification practices could only ever impact upon the kind’s secondary properties (such as behavioural symptomology).34
To be clear, I am not committed to essential dependence obtaining for this, or any other, particular psychiatric disorder. For now, I seek merely to establish that there are principled reasons why psychiatric disorders may be more essentially dependant on our classifications than paradigm somatic disorders, even if they are underpinned by a super-explanatory natural property such as characteristic neurobiology. Establishing that there are biological regularities underpinning particular psychiatric disorders, as Tsou attempts to do, is insufficient grounds to establish that these super-explanatory properties are not the sorts of properties that could be reactive in response to classifications. We must be careful to avoid the fallacious inference that biological equals immutable and psychological equals changeable. Psychiatric disorders are biological; this is not the issue. The question is, rather, what sorts of biological properties underpin psychiatric disorders, and do they have the potential to change systematically in response to our classifications? I believe that we have principled and empirically informed reasons to think the answer here is ‘yes’.
Conclusion
Under what circumstances is a natural disease kind truly reactive in response to our classification, and when is it merely co-instantiated with or intersecting with a corresponding social and reactive kind? I have argued that a disease kind is only really reactive in the sense of being unstable or ‘on the move’ under conditions of ‘essential dependence’, that is, where the super-explanatory natural property characterising the kind is changing systematically in response to our practices of classification. I went on to argue that there are principled theoretical reasons to think that this sort of dependence can only occur in cases where the super-explanatory natural property is amenable to certain forms of directed change or ‘adaptation’ (broadly construed) in response to environmental factors.
In what cases can this occur? I have argued that essential dependence is a possibility in two sets of cases: 1) diseases caused by pathogens which are literally evolving (fungi, bacteria, Sars-Cov-2) and 2) diseases which are caused by dysfunctions in higher level neural processes with the capacity for neuroplastic adaptation to environmental conditions. This implies a possible, and heretofore underappreciated, disanalogy between neuropsychiatric disorders and paradigm biomedical disorders. If the hypothesis advanced in this paper holds, then special sorts of interdependencies may obtain between (certain types of) neuropsychiatric disorders and our classifications of these disorders. These sorts of interdependencies may undermine the prospects for a science of, and a scientific classification system for, psychiatry which is strongly premised on biomedicine.
Acknowledgements
I would like to thank David Papineau, Marion Godman and participants at the workshop ‘Reactivity and Categorisation in the Human Sciences’ for valuable feedback on this research. I am also grateful to participants at Interdisciplinary Philosophy and Medicine Workshop at King’s College London for their insightful comments and questions. This research was conducted while in receipt of a studentship from the London Arts and Humanities Partnership.
Funding
This research was conducted while receiving a studentship from the London Arts and Humanities Partnership (LAHP).
Declarations
Ethical approval
N/A. Work is entirely theoretical and includes no participants.
Informed consent
N/A. Work is entirely theoretical and includes no participants.
Conflict of interest
None.
1 For example, consider the category of ‘round things’, the category of ‘vegetables’ (parts of plants that are edible to humans, and which are not subsumed under the category ‘fruit’), or the category of ‘farm animals’ (presumably spanning from chickens to Patterdale Terriers, with very little uniting the two).
2 As argued persuasively by Godman et al. (2020) and Godman and Papineau (2020), however this is controversial (cf. Devitt, 2008, 2021).
3 According to Godman et al. (2020), super-explanatory properties are special, not just in virtue of their particular causal explanatory relation to the secondary properties, but in that they are (in contrast to the secondary properties) metaphysically necessary. Godman et al. go on to hypothesise that the modal necessity of super-explanatory properties derives from the special causal relation which obtains between the super-explanatory property and the secondary properties of the kind. For my purposes here, it the special causal and definitional role of super-explanatory properties and the conversation this enables which are of importance, and I shall remain agnostic as to the modal issues.
4 In my view, it is not necessary that an interaction has these sorts of effects for it to count as super-explanatory. It is enough that the interaction explains the correlation of the mutually reinforcing properties (and any effects they have individually). However, the interaction should at the very least count as super-explanatory when it has effects which are not straightforwardly reducible to the action of any of the constitutive properties. Thanks to an anonymous reviewer for prompting me to clarify my position in this regard.
5 The DSM-5 (Diagnostic and Statistical Manual of Mental Disorders) recognises eleven criteria for the diagnosis of Substance Use Disorder, including items such as “Continuing to use, even when you know you have a physical or psychological problem that could have been caused or made worse by the substance” (American Psychiatric Association, 2013).
6 I see no reason to deny this, other than an overly restrictive view of which features of a phenomenon rightly count as ‘properties’. One might, for example, think of interactions between properties as complex properties made up of more basic elements (see Cunningham, 2001 for discussion). However, I won’t commit to any particular view of properties here.
7 A number of instances can share a great many properties in common, and as such constitute a very tight and ‘clumpy’ property cluster, for some reason that is super-explanatory, but that is not by any measure a ‘natural’ property. Groups of artefacts may share a great many properties because they descend from some original – for example all the world’s copies of Alice in Wonderland (Millikan, 2017; Godman et al., 2020). Similarly, Godman has argued that specific gender categories – like ‘Japanese Woman’ – are culturally reproduced historical kinds, instances of which share properties due to cultural inheritance (Godman, 2018, Godman et al., 2020).
8 Nor am I committed to the view that ‘natural kinds’ themselves constitute a natural kind (cf. Hacking, 2007).
9 Thanks to Cecily Whiteley for helpful conversations that lead me to think of distinctions between kinds in this way.
10 Similar distinctions can be drawn within the category of real kinds, such as between social kinds (kinds which share some social property, such as a classification, profession or social role) and artefactual kinds (common intended function or deriving from some original design-template) and, still more fine-grained distinctions (see also Millikan, 2017).
11 As the alchemists would have it. Kauffman cites Arnold of Villanova: “[I]t harbours specific virtues which are due to celestial influence. In its stability and permanence, gold is itself like a star of heaven.” (p. 74, Kauffman, 1985).
12 There is naturally some controversy as to whether this story should be believed. I shall just assume Hacking’s account for present purposes. See Hacking (1998) for discussion.
13 There is some reasonable concern, at least in psychiatry, that medical nosology really is off track, but this problem is a relatively peculiar to psychiatry and its ongoing so called ‘crisis of classification’ (see e.g. Poland & Tekin, 2017).
14 That is not to say that all medical kinds are real kinds. Some may turn out to be spurious or overly heterogenous.
15 Of course, the distinction between (super-explanatory) etiology and (secondary) symptomology is salient in medicine for clinical as well as theoretical reasons – ideally, we would intervene medically on the property which is causing all the other properties (the super-explanatory pathoetiology) so as to alleviate all the problematic symptomology with a single ‘silver bullet’ cure, rather than treat each disparate symptom individually in a therapeutic game of whack-a-mole.
16 Are there exceptions to this general rule? An obvious candidate would be MPD or another such transient mental illness where the characteristic symptomology is caused by an extrinsic social property such as a classification. However, whether these cases should count as true disease kinds is plausibly up for debate. We might also wonder about cases where characteristic symptomology appears to be caused by an extrinsic past event such as exposure to trauma (as in traumatic head injury or post-traumatic stress disorder) or past infection (as in the case of ‘Long Covid’). In these cases, there will usually be some intermediate property (say, damage to the neural tissues or inflammation) causing the symptomology in a proximal sense. However, nothing about the framework I have outlined here prohibits extrinsically constituted biological kinds from constituting natural kinds, so I need not rule these cases out entirely.
17 For discussion, see Khalidi (2020).
18 That is not to say unique potential, as we shall see.
19 See Plutynski (2018) for an argument that cancer is not a natural kind. Plutynski appears to assume a rather more reductive and traditionally essentialist position than the one I am proposing here – for example, she entertains the possibility that what defines cancer cells is “their distinctive interactions with neighboring cells” (p. 43, 2018) which would appear to be compatible with my account (if not with hers). In any case, a rebuttal is beyond my scope here.
20 The case of HIV, to which Klawiter alludes, may constitute an analogous case of reactivity.
21 Whether autism constitutes a real, uniform kind – or even a disease – is controversial both philosophically and scientifically (Chapman, 2020). I do not have any particular commitments here.
22 What is the super-explanatory property in this case? We do not know exactly, because there is empirical uncertainty as to what causes autism and, indeed, whether there is a uniform cause (Walsh et al., 2011). The assumption in Hacking’s account, however, appears to be that there is some particular neural dysfunction (‘a congenital neurological deficit’) which causes the symptoms associated with autism.
23 It should be noted that Hacking does not employ the language of ‘social, reactive kind’ versus ‘natural kind’, but I think it is reasonably to infer that this is the metaphysics which would make sense of his insistence that high functioning autistic people did, and yet did not, exist prior to classification.
24 I assume, here, that damage to the neural tissues is the super-explanatory property. Of course, the damage itself is, in a more distal sense, caused by vascular dysfunction. However, the original disruption to the blood supply is no longer causative of the symptoms after it is dissolved. It is the damage caused by the disruption to the oxygen supply which remains, and which causes the symptoms.
25 This is at least a plausible hypothesis. In addition to motivation, neuroplasticity in stroke recovery is modulated by factors such as depression and degree of social engagement, indicating that belief in one’s capacity for recovery could make a difference via these metrics (Chaturvedi et al., 2020; Tracy et al., 2014). Stinear also notes that a stroke patient’s perceived poor prognosis may risk “the outlook becoming a self-fulfilling prophecy” (p. 1230) by lowering investment in therapeutic measures (2010). Moreover, it has also been argued that, in learning contexts, positive narratives may stimulate neuroplasticity, whilst negative thinking may increase stress and decrease plasticity in the brain (Cozolino & Sprokay, 2006).
26 The super-explanatory property of the disease Covid 19 is infection with the Sars-Cov-2 virus. The secondary properties are the symptoms of Covid-19 (e.g. loss of the sense of taste and smell). This case is analogous to the tuberculosis case considered in Sect. 3.1.
27 Although I have focused in this paper on disease kinds, I take this framework to – in principle – have broader application.
28 It is not clear that C will always be super-explanatory in the sense of causing many other secondary properties to be instantiated. If so, it is just the property C which will be correlated with N and the other secondary properties of N.
29 In a critique of Hacking, Tsou makes a distinction between ‘strong’ and ‘weak’ implications of looping effects which bears some relation to my distinction between secondary and essential dependence. The strong implication, according to Tsou, is that the looping effect causes the definitional criteria of a classification to change, where ‘definitional criteria’ are cashed out in terms of law-like biological regularities. The weak implication is that people’s behaviours simply change in response to their classification. Although I am sympathetic to Tsou’s line of argument here, I take my own to offer a higher degree of precision. Firstly, it is not clear that ‘definitional criteria’ are what Tsou is really after – recall that the formal definitional criteria for psychiatric disorders (within ICD and DSM) are generally behavioural rather than biological. Moreover, Tsou makes the curious assumption that biological regularities ipso facto cannot be mutable in response to looping effects: “To establish [that objects of study in psychiatry are unstable], Hacking would need to show that the typical biological or physiological process that leads to abnormal behaviour is changed because of looping effects. There is no good evidence for thinking that this is a possible consequence of looping effects.” (Tsou, 2007, emphasis original; see also Tsou, 2013). As we shall see, this inference does not hold.
30 I have in mind here direct changes to the nature of the super-explanatory natural property in question, not merely changes to its frequency of instantiation in the population (which would not have implications for the stability of our classifications).
31 My claim is not that essential dependence absolutely obtains in the case of Covid-19 or any other particular case. More modestly, I hope to establish the possibility of these sort of dependence relations between our classifications and causes of disease that are, in some sense, subject to adaptation. Thanks to an anonymous reviewer for pushing me on this point.
32 I accept that talk of ‘higher-level’ and ‘complex’ neural functions is somewhat vague. Roughly speaking, what I have in mind are the sorts of complex abstract functions which feature, for example, in the RDoC matrix (Morris & Cuthbert, 2012; see also Hyman, 2000). Although it is beyond my scope here, much can be done to elaborate on this notion.
33 Adaptation needs to be broadly construed here as the mechanisms by which the brain adapts and that through which a virus adapts are rather different (for some relevant discussion, see Garson, 2019).
34 Tsou appears to draw this erroneous inference.
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| 0 | PMC9735059 | NO-CC CODE | 2022-12-14 23:28:32 | no | Eur J Philos Sci. 2022 Dec 7; 12(4):72 | utf-8 | Eur J Philos Sci | 2,022 | 10.1007/s13194-022-00500-x | oa_other |
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Article
Male involvement in randomised trials testing psychotherapy or behavioural interventions for depression: a scoping review
http://orcid.org/0000-0002-0890-9898
Knox James 1
Morgan Philip 234
Kay-Lambkin Frances 5
Wilson Jessica 5
Wallis Kimberley 1
Mallise Carly 1
Barclay Briana 234
Young Myles [email protected]
12
1 grid.266842.c 0000 0000 8831 109X School of Psychological Science, University of Newcastle, University Drive, Callaghan, NSW 2308 Australia
2 grid.413648.c Active Living Research Program, Hunter Medical Research Institute, New Lambton Heights, Australia
3 grid.266842.c 0000 0000 8831 109X School of Education, University of Newcastle, Callaghan, Australia
4 grid.266842.c 0000 0000 8831 109X Centre for Active Living and Learning, University of Newcastle, Callaghan, Australia
5 grid.266842.c 0000 0000 8831 109X School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
5 12 2022
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The prevalence of Major Depressive Disorder in men is half that of women, yet depression affects approximately 109 million men worldwide. Alarmingly, men account for three quarters of suicides in Western countries but are unlikely to seek help for mental health concerns. It is possible that existing mental health treatments are not engaging or accessible to men. The aim of this review was to quantify the number of men involved in randomised trials of psychotherapy or lifestyle behaviour change targeting depression. Results found men represented 26% of participants in 110 eligible articles compared to 73% women. Men’s representation was low across all intervention characteristics (e.g., delivery mode). No studies used a completely male sample, compared to 19 studies targeting women only. Men are substantially underrepresented in research trials targeting depression.
Supplementary information
The online version contains supplementary material available at 10.1007/s12144-022-04017-7.
Keywords
Depression
Men
Help-seeking
Psychotherapy
Lifestyle behaviour change
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pmcMajor depressive disorder (depression) is a chronic mental health condition characterised by persistent low mood, loss of interest in activities, and internalising symptoms of sadness, hopelessness, and guilt (American Psychiatric Association [APA], 2013). Between 1990 and 2017, the worldwide prevalence of depression increased by almost 50% (Liu et al., 2020) affecting approximately 4.4% of the population (World Health Organisation [WHO], 2017). COVID-19 has increased the prevalence of depression globally by approximately 28% (Santomauro et al., 2021). Depression is associated with a range of other mental and physical health conditions including anxiety (Hirschfeld, 2001), substance use (Hasin et al., 2005), diabetes, cardiovascular disease, and arthritis (Lotfaliany et al., 2018; Moussavi et al., 2007), making it a leading cause of disability worldwide (James et al., 2018).
The prevalence of depression, based on diagnosed cases, is higher in women than men; in 2015 global prevalence was 5.1% and 3.6% respectively (WHO, 2017). However, gender plays an important and complex role in depression diagnosis, with research showing both physicians and family members display gender bias towards attributing depression to women rather than men (Bertakis et al., 2001; Brommelhoff et al., 2004). Similarly, men are potentially underdiagnosed with depression due to diagnostic criteria not considering male specific aspects of depression and masculinity leading men to respond to depression by acting out (Martin et al., 2013; Magovcevic & Addis, 2008). Notably, gender sensitive scales which include externalising symptoms of depression have shown greater sensitivity for detecting change in treatment than traditional scales in some groups of men (Rice et al., 2013, Rice et al., 2020). Despite this, approximately 109 million men worldwide are currently experiencing traditional depressive disorders, which highlights the urgent need to support this at-risk subgroup (Global Burden of Disease [GBD], 2022).
Despite increasing access to mental health care in recent decades (Harris et al., 2015), men are less likely than women to seek help for mental health problems, including depression (Liddon et al., 2018; Oliver et al. 2005; Rice et al., 2017). One reason for this difference is stigma associated with mental illness. Some men endorse that mental health problems and help-seeking are signs of weakness (Judd et al., 2008; Lynch et al., 2018), also known as negative self-stigma (Vogel et al., 2006). In part, these views stem from adherence to traditional masculine norms in most Western societies, such as stoicism, emotional restraint, and self-reliance; which are associated with decreased help seeking (Addis & Mahalik, 2003; Seidler et al., 2016), poor mental health status (Primack et al., 2010), and suicidality (Pirkis et al., 2017).
It is also possible that existing mental health treatments may not be engaging or accessible to men (Bilsker et al., 2018; Seidler et al., 2018). When men are diagnosed with depression, they are often referred to psychotherapy for treatment. Psychotherapy is a general term used to describe interventions based on a scientific theoretical background and that use psychological techniques to reduce symptoms through modifying motivational, emotional, cognitive, behavioural, or interpersonal processes (Linde et al., 2015). Although evidence exists supporting the efficacy of various types of psychotherapy (Barth et al., 2016), some men have reported negative attitudes towards treatments (Levant et al., 2011), viewing psychotherapy as unappealing and anti-masculine (Berger et al., 2013; Englar-Carlson & Stevens, 2006). Men may also be deterred from certain aspects of therapy such as personal disclosure, emotional expression, and vulnerability, due to the impact of dominant masculine norms (Mahalik et al., 2003). Further, many services fail to consider gender and structural barriers, such as time and resources, and unappealing service environments are common (Seidler et al., 2018).
According to common wisdom, men are also less likely than women to participate in research testing interventions for depression, meaning that less evidence is available to suggest how interventions or service provision could be tailored to better address their needs. Whilst some psychotherapy reviews for depression neglect reporting gender outcomes (Newby et al., 2016), others have confirmed their samples are predominantly female (Berryhill et al., 2019; Castro et al., 2020; Nieuwsma et al., 2012). In this regard, ‘male gender blindness’ describes how men’s needs are implicitly overlooked (Seager et al., 2014). When studies do report gender data, the understanding gained is limited to the population or intervention investigated (Josephine et al., 2017). As such, the overall representation of men across all depression-focused intervention studies remains unclear, as are the outcomes of these studies in relation to addressing the identified gaps in service delivery for men with depression.
What does engage men
To better engage men, a substantial body of research has sought to understand what is engaging. Several recommendations have been made by clinicians and researchers regarding how to work therapeutically with men, which generally focus on themes such as making services gender-sensitive (APA, 2018; Mahalik et al., 2012). Substantially less is known about what specific intervention characteristics are best practice with men and how this relates to their experience of depression specifically. Research investigating sex differences in preferences for therapy has found that men engage more with treatments that take into account gender-specific preferences (Seidler et al., 2018). For example, men have indicated a preference for practical, action-focused interventions, such as cognitive behaviour therapy (CBT), over other forms of ‘talk therapy’ or emotion-focused therapy (Emslie et al., 2007; Seidler et al., 2016). Men have also indicated a preference for individual over group therapy (Kealy et al., 2021; Sierra Hernandez et al., 2014). eHealth interventions (which rely on end users to self-direct their intervention) have the potential to better engage men because they are confidential, non-confrontational, and promote autonomy and self-sufficiency (Berger et al., 2013; Ellis et al., 2013; Wang et al., 2016). These qualitative differences in gender-based preferences are important, but a gap remains regarding how these preferences reflect study enrolment rates and engagement practices for men on a larger scale.
Depression is associated with several lifestyle behaviours such as physical inactivity (Gianfredi et al., 2020), poor diet (Molendijk et al., 2018), disturbed sleep (Fang, Tu, Sheng, & Shao, 2019), and increased alcohol consumption (Churchill & Farrell, 2017). Multiple reviews have indicated that physical activity is an effective strategy for treating depression (Cooney et al., 2013; Josefsson et al., 2014; Schuch et al., 2016), and the evidence for interventions based on improving diet and sleep is growing (Firth et al., 2019; Gee et al., 2019). Observational evidence suggests men more frequently present with disruptions in these health behaviours rather than the cognitive or emotional symptoms of depression (Proudfoot et al., 2015). It is often these health behaviours that act as a prompt for men to seek help (Addis & Mahalik, 2003). Thus, lifestyle interventions have been highlighted as a promising approach for treating depression in men (Seaton et al., 2017), especially those who conform to traditional masculine norms (Berger et al., 2013) or are reluctant to acknowledge that they have depression (Fields & Cochran, 2011). A recent review of lifestyle programs found no studies with substantive mental health support for men with pre-existing mental health conditions and adequate power to detect changes in mental health outcomes (Drew et al., 2020), indicating a current lack of programs specifically targeting men’s mental health through lifestyle change.
Why it is important to do this review
Although qualitative research exists exploring men’s experience of depression treatment (Seidler et al., 2018), and sex differences in depression prevalence have been reported (Liddon et al., 2018), no study has simultaneously investigated the proportion of males included in intervention trials targeting depression and examined whether men’s involvement is moderated by key study or intervention characteristics. Research has shown that men will engage in treatment when it is accessible, appropriate, and engaging (Seidler et al., 2016). Therefore, it is crucial to understand which interventions men find most appealing (Addis, 2008).
Thus, we conducted this review to investigate the following research questions: (i) what is the number of males engaging in trials targeting major depression, (ii) have there been any published studies targeting males only, or are specifically designed for men, (iii) do male enrolment rates differ across certain intervention and trial design characteristics, (iv) have any attempts been made to increase the involvement of males, (v) are low rates of male involvement identified as a limitation, and (vi) are studies testing for sex differences in outcome?
Method
This review followed the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement (Moher, Liberati, Tetzlaff, & Altman, 2010).
Eligibility criteria
Types of participants: Adults aged 18 and over who scored in a clinical range on a validated measure of depression (e.g., PHQ-9), or were diagnosed with major depression via interview. See Supplemental material 1 for the cut-off scores used.
Types of intervention: Studies were included if they tested at least one psychotherapy or lifestyle intervention. For this review, an intervention was considered psychotherapy if it was based on a scientific theoretical background and used psychological techniques to reduce symptoms and improve general well-being through modifying motivational, emotional, cognitive, behavioural, or interpersonal processes. For inclusion, it needed to have been performed either as a tailored, verbal communication process between a patient (or a group of patients) and a health care professional in direct or remote (e.g., telephone) contact, or as a less intense or self-guided intervention using written information material (e.g., book or computer program) that the patient worked through more or less independently (Linde et al., 2015). Eligible forms of psychotherapy were adapted based on existing reviews (e.g., CBT, behavioural activation therapy, problem solving therapy, psychodynamic therapy, non-directive supporting therapy (e.g., counselling) (Cuijpers et al., 2021; Cuijpers et al., 2008).
Eligible lifestyle interventions provided patients with knowledge and skills to promote meaningful changes to at least one lifestyle behaviour (e.g., physical activity). Mechanistic studies that manipulated health behaviours in a lab environment without a clear intent to create lasting behaviour change were excluded (e.g., acute impact of supervised exercise on depressive symptoms).
Comparator: Psychotherapy or lifestyle intervention arms could be compared to a control group or another intervention.
Outcomes: To be eligible, studies needed to explicitly report a power calculation at 80% to detect a change in the primary outcome related to depression (e.g., symptoms, prevalence, remission rates). Given the large number of depression trials published, this criterion was applied to reduce the number of included articles and to act as a proxy for study quality.
Types of studies: The review included randomized trials published in peer-reviewed, English language journals, from 2011 to 2021.
Information sources and search
An electronic database search of PsycInfo, Medline, Embase, and CINAHL was conducted on April 13th 2021. Search terms were divided into three groups: (a) intervention (e.g., psychotherapy, treatment); (b) study design (e.g., RCT, controlled trial, clinical trial); and (c) depression (e.g., major depression, MDD, depressive disorder). Medical subject heading terms were used when possible (e.g., Counselling/, Major Depression/, Clinical Trials/). Where possible, the following limits were applied: English language, last 10 years, adults (over 18 years of age), and clinical trials. See Supplemental material 2 for search syntax and results for all databases.
Study selection
In the first stage of study selection, one reviewer (JK) screened 8013 title and abstracts. Following this, three reviewers (JK, BB, JW) independently screened 1034 full-text studies. A sample of 50 studies were screened for inclusion or exclusion with excellent interrater reliability (absolute agreement = 0.92). Discrepancies were resolved by the primary author and discussion between reviewers. The final sample included 110 studies (see Fig. 1).
Fig. 1 Participant flowchart
Data extraction
Three coders (JK, KW, CM) extracted the data from the eligible studies using a double-coding method. To improve interrater reliability, three rounds of preliminary coding with a random sample of 20 studies was conducted, and discrepancies were discussed as a group to identify areas of potential concern. Any discrepancies identified during the formal coding process were resolved via discussion. Protocol papers were searched for relevant outcomes where required. Data for research questions 2, 4, and 5 were extracted by one reviewer (JK) reading each article and coding as yes or no, and specific responses were recorded verbatim. The data file for this project is stored in the Centre for Open Science data repository. Link: https://osf.io/4r6zn/?view_only=9ae914f335d34f9baa873fa44eccada6.
Number of participants randomised
Sex of participants
Data were extracted for the sex of participants as male, female, other, or not reported. Interrater agreement on this item was > 99%. In studies that reported sex data for a completer’s sample rather than the entire randomised sample, unidentified participants were categorised as ‘not reported’. A single study used an ‘other’ category for participants who did not identify as male or female. As such, for the purpose of this study, where the number of females was the only sex reported, it was assumed that the rest of the sample was male (and vice versa).
Country
The country each trial was conducted in was coded verbatim (agreement1 = 100%).
Year
Year of publication was coded based on the year the paper was published in a specific issue (agreement = 98%).
Co-occurring physical health condition
Whether or not studies included participants with a specific co-occurring physical health condition, to depression, was coded as yes or no (agreement = 99%).
Co-occurring mental health diagnosis
Whether or not studies included participants with a co-occurring mental health diagnosis, to depression, was coded as yes or no (agreement = 99%).
Depression determination method
The method of diagnosing depression was coded as: screening tool (e.g., PHQ), clinical/diagnostic interview, or both which was a combination of screening tool and interview (agreement = 77%).
Recruitment method
The recruitment method was either classified as direct, indirect, or a combination of each. In studies that used direct recruitment, potential participants were personally invited to participate in the study. In studies that used indirect recruitment, potential participants were exposed to non-specific study information (typically characterised by advertisements) and took initiative to register. A combination of each approach was coded as a separate category (agreement = 77%).
Intervention type
Within each study, individual interventions were categorised as psychotherapy, lifestyle, a combined psychotherapy and lifestyle approach, other therapeutic interventions, or control groups. Other therapeutic interventions were those that did not meet the criteria for being a psychotherapy or lifestyle program, such as medication. All interventions labelled as control groups, including usual care, were coded accordingly (agreement = 92%).
Intervention style
Given the published literature on men’s potential preference for Cognitive Behaviour Therapy over other types of therapy, the intervention style in psychotherapy interventions was coded as either Cognitive Behavioural Therapy or all other types of psychotherapy interventions (e.g., psychodynamic therapy, emotion-focused therapy). Interventions were considered part of the Cognitive Behaviour Therapy umbrella of interventions if they were based on first wave (e.g., behavioural activation), second wave (e.g., CBT) or third wave therapies (e.g., Acceptance and Commitment Therapy). For lifestyle programs, the style was selected from a range of options, such as physical activity or diet. However, physical activity programs were the only style of lifestyle program used outside of those in combined psychotherapy and lifestyle studies or not categorised studies, which used different styles across each arm (agreement = 89%).
Mode of delivery
Delivery mode was coded as face-to-face group, face-to-face individual, distance methods (online/technology/phone calls/printed materials), and unclear/not reported. These data were coded based on the primary mode of delivery, judged by time of contact (agreement = 89%).
Contact
Whether the intervention required contact with other people, including professionals, peers, family members, was coded into four groups: (1) involved contact with others, (2) self-guided with minimal contact (e.g., seeing someone briefly at the beginning or end), and (3) completely self-guided (agreement = 89%).
Sessions per week
The total duration of the intervention was coded in weeks and number of sessions was recorded. Where necessary, sessions were discrete contacts with individuals delivering the program, or in the case of self-guided interventions, modules were considered sessions. These two variables were combined to create sessions/per week (agreement = 75%). Where either number of sessions or length of intervention was unclear/not reported, sessions per week could not be calculated.
Data analysis
All analyses were conducted using IBM SPSS Statistics (version 27) predictive analytics software. Means for quantitative variables and percentages for categorical variables were calculated. To investigate the first research question, the representation of men was examined as a proportion of total participants across all studies, and within studies that allowed males to participate. For the second research question, independent samples t tests and analyses of variance investigated whether the proportion of male participants across the studies varied by key study or intervention characteristics. Because the RCT design precludes participants from choosing a particular intervention arm, studies testing multiple interventions that differed on a particular characteristic (e.g., online mode of delivery vs. face-to-face mode of delivery) were not included in that particular analysis. Similarly, studies that explicitly excluded males or females were also excluded from the moderator analyses.
Results
Most studies were published in the United States (29%), followed by the United Kingdom (16%), The Netherlands (7%), and Germany (6%). The number of studies published has increased over time, with 10% of studies published in 2011–2012 and 29% published between 2019 and 2021. Regarding co-occurring conditions with depression, 21% of studies explicitly recruited participants with a co-occurring physical health condition, but only 2% targeted those with co-occurring mental health condition. Approximately half of the studies diagnosed depression using both a screening tool and diagnostic interview (51%); a quarter used a screening tool only (26%); and a quarter used a diagnostic interview only (23%). The most common recruitment method was direct recruitment (67%), followed by a combination of direct and indirect, (20%) followed by indirect alone (13%).
Regarding intervention characteristics, most studies tested psychotherapy interventions only (82%), followed by integrated interventions that included both psychotherapy and lifestyle components (6%). Only 3% of studies tested lifestyle approaches exclusively and 10% were not categorised, indicating that intervention types were not consistent across study arms (e.g., psychotherapy arm vs. lifestyle arm). In terms of intervention style, the most common was CBT and third wave cognitive therapies (52%), followed by all other types of psychotherapy (20%), followed by physical activity (3%), and 26% were not categorised due to differences across study arms. Most studies tested interventions that were delivered individually face-to-face (49%) compared to remote interventions (26%, e.g., online/tech interventions, phone consultations, printed materials) or face-to-face group sessions (16%). Most studies tested interventions that involved repeated contact with another person (86%) with fewer studies involving one-off contact (6%), or no contact at all (4%). Intervention dose was mostly one session per week (48%), followed by less than one session per week (30%), and greater than one session per week (22%; 0.1-7 per week) (Table 1).
Table 1 Characteristics of included studies
Study characteristic Studies, n Study, %
Country 110 100
United States 32 29
United Kingdom 18 16
Netherlands 8 7
Germany 7 6
Australia 5 5
Othera 40 36
Year
2011–2012 11 10
2013–2014 20 18
2015–2016 24 22
2017–2018 23 21
2019–2021 32 29
Study sample
Female only 19 17
Male only 0 0
Allowed men to participate* 90 82
Sex data not reported 1 1
Co-occurring physical health condition
Yes 23 21
No 87 79
Co-occurring mental health condition
Yes 2 2
No 108 98
Depression determination method
Screening tool 29 26
Clinical/diagnostic interview 25 23
Both screening tool & clinical/diagnostic interview 56 51
Recruitment method
Direct 74 67
Indirect 14 13
Both direct & indirect 22 20
Intervention type
Psychotherapy 90 82
Lifestyle 3 3
Combined 6 6
Not categorised b 11 10
Intervention style
CBT & third wave 57 52
All other types of psychotherapy intervention 22 20
Physical activity 3 3
Not categorised b 28 26
Mode of delivery
Face-to-face Group 18 16
Face-to-face Individual 54 49
Online/tech/phone calls/printed materials 29 26
Unclear/not reported 3 3
Not categorised b 6 5
Contact
Involved contact 95 86
Self-guided with minimal contact 7 6
Completely self-guided 4 4
Not categorised b 4 4
Sessions per week
< 1 23 30
1 37 48
> 1 17 22
a Spain (n = 4), Finland (n = 3), Denmark (n = 3), India (n = 3), Pakistan (n = 3), Brazil (n = 3), Iran (n = 3), Japan (n = 3), South Korea (n = 2), Nigeria (n = 2), Switzerland (n = 2), Turkey (n = 1), Korea (n = 1), Canada (n = 1), Hong Kong (n = 1), Italy (n = 1), New Zealand (n = 1), Sweden (n = 1), Kenya (n = 1), Taiwan (n = 1). b Study included > 1 intervention arm that differed on this characteristic (e.g., online vs. face to face). * Refers to studies which did not restrict eligibility to males or females
Research question 1: what is the representation of males in psychotherapy and lifestyle interventions targeting depression?
Across all 110 eligible studies (n = 24,397), males represented 26% (n = 6,303) of participants, females represented 73% (n = 17,712), 2% (n = 381) were unclear, and a single participant did not identify as male or female. Within the 90 (n = 20,252) studies that allowed both men and women to participate, males represented 31% (n = 6,303) of participants compared to 68% (n = 13,738) female, and 1% (n = 210) were unclear (Table 2).Table 2 Participant representation across all studies
n % (of randomised) % (of reported)
All studies (n = 110) 24,397
Male 6,303 26 26
Female 17,712 73 73
Other 1 0 0
Not reported 381 2 n/a
Studies including both genders (n = 90) 20,252
Male 6,303 31 31
Female 13,738 68 69
Other 1 0 0
Not reported 210 1 n/a
Note. 19 studies either recruited women only as the target group or excluded men from participating. One study didn’t explicitly exclude men, but had a 100% female sample
Research question 2: were any attempts made to increase the involvement or, and if so, what were they?
No studies reported any explicit attempt to increase the involvement of men through targeted strategies.
Research question 3: are males more or less likely to participate in studies with certain characteristics? (Tables 3 and 4)
Table 3 Male representation across study characteristics
Study characteristic N (%) % Male (M, SD) p-value
Year
2011–2015 35 (39) 30 (17)
2016–2018 30 (33) 33 (13)
2019–2021 25 (28) 32 (18) 0.83
Co-occurring physical or mental health condition
Yes 19 (21) 29 (17)
No 71 (79) 32 (15) 0.46
Diagnosis
Screening tool 19 (21) 35 (17)
Clinical/diagnostic interview 23 (25) 32 (20)
Both 48 (54) 30 (12) 0.60
Recruitment method
Direct 58 (64) 34 (17)
Indirect 13 (14) 28 (14)
Both 19 (21) 27 (12) 0.22
Table 4 Male representation across intervention level characteristics
Intervention level N (%) % Male (M, SD) p-value
Intervention type
Psychotherapy 73 (91) 32 (16)
Combined + Lifestyle 7 (9) 24 (10) 0.19
Psychotherapy stylea
CBT/ Third Wave 48 (75) 33 (17)
All other types 16 (25) 30 (13) 0.58
Mode
Face-to-face (group) 14 (17) 28 (13)
Face-to-face (individual) 45 (54) 32 (16)
Online/tech/phone calls/printed materials 24 (29) 30 (12) 0.58
Contact
Involved Contact 76 (88) 32 (16)
Self-guidedb 10 (12) 29 (11) 0.65
Dose (sessions per week)
< 1 18 (28) 30 (10)
1 30 (47) 30 (19)
> 1 16 (25) 33 (16) 0.80
a Refers to types of psychotherapy only. b Includes studies that were self-guided with minimal contact or completely self-guided
Year
Male involvement did not vary significantly over time (F2,87 = 0.19, p = 0.83). To account for the escalating publication rate, studies were analysed in three groups of approximately equal size. Overall, males represented 30%, 33%, and 32% of participants in studies published from 2011 to 2015, 2016 to 2018, and 2019 to 2021, respectively.
Co-occurring physical or mental health condition
There was no significant difference in male involvement between studies targeting participants with a co-occurring physical or mental health condition (29%) or those without a co-occurring condition (32%; t88 = -7.40, p = 0.46). The most common co-occurring physical health conditions targeted were diabetes (4 studies), overweight or obesity (2 studies), and chronic pain (2 studies).
Depression determination method
Male involvement did not differ significantly depending on the method of diagnosing depression (F2,87 = 0.51, p = 0.60). Although trials that used a screening tool only had a higher proportion of males (35%) compared to trials that used an interview only (32%), and trials that used both a screening tool and interview (30%), the difference was not significant.
Recruitment method
Recruitment method did not have a significant influence on male involvement (F2,87 = 1.55, p = 0.22). The highest mean proportion of males were recruited directly (33%), compared to indirect recruitment (28%), and when a combination of methods were used (27%).
Intervention type
In this analysis, studies that tested integrated interventions and lifestyle interventions alone were combined, as only one lifestyle intervention allowed men to participate. The mean proportion of males participating in studies testing psychotherapy interventions (32%) was higher than in studies testing integrated interventions or lifestyle interventions combined (24%), however, the mean difference was not significant (t78 = 1.32, p = 0.19).
Psychotherapy intervention style
Among studies that tested psychotherapy interventions only, male involvement did not differ between studies testing CBT/Third wave cognitive therapies (33%) compared to other types of psychotherapy therapy (30%; t62 = 0.55, p = 0.58).
Mode of delivery
Mode of delivery did not have a significant effect on male involvement (F2,80 = 0.54, p = 0.58). The mean number of males was similar across all three modes: face-to-face group (28%), face-to-face individual (32%), remote delivery (online/technology/phone calls/printed materials; 30%). The various modes included in the remote delivery group were combined because they are conceptually similar in that they require low contact.
Contact
There was no difference in male participation between interventions that involved repeated contacts with intervention or research staff (32%), compared to self-guided or minimal contact interventions (29%; t84 = 0.46, p = 0.65). The self-guided group consisted of studies that involved some contact (e.g., a single face-to-face session followed by 10 online modules), and completely self-guided interventions. These two groups were combined because they are conceptually similar in both requiring low contact and only four studies tested completely self-guided interventions.
Dose (sessions per week)
No association was detected between male participation and the dose of the intervention (F2,61 = 0.23, p = 0.80). Slightly more men participated in studies testing interventions that were delivered using > 1 sessions per week (33%) than < 1 session per week (30%) and 1 session per week (30%).
Research question 4: did any studies specifically target men only, and/or tested gender-tailored interventions designed for men?
No studies targeted men only, and by virtue of this no studies tested interventions that were gender tailored towards men. Both studies with > 90% males were war veteran samples. The next highest representation of men was 67% in alcohol dependent individuals followed by 65% in a prison sample. In contrast, 19 studies explicitly recruited females only (17%) whilst two others consisted of a 100% female sample despite allowing men to participate.
Research Question 5: in studies with < 40% males, did the authors identify the lack of men as a limitation?
Out of 72 studies that had less than 40% males, including two studies that had complete female samples (but had not actually excluded men from participating), ten studies (14%) identified that the underrepresentation of men (or the overrepresentation of women) was a limitation. Consistent with a previous review, underrepresentation was defined as < 40% males (Pagoto et al., 2012).
Research Question 6: how many studies explicitly reported testing for sex differences in study outcome, or reported outcomes for men and women separately?
Out of 90 studies, 12 (13%) explicitly reported testing for sex differences as a moderator or reported primary outcomes for men and women separately. Ten of these studies reported no difference in intervention effect between males and females, one study reported women performed better than men, and one study was unclear due to gender outcomes being reported as part of racial subgroups rather than male and female groups.
Discussion
To our knowledge, this is the first scoping review to quantify the number of males involved in psychotherapy and lifestyle interventions targeting depression and identify any key study characteristics that moderate male involvement. Across all included studies, men represented only 26% of randomised participants. The review did not identify any randomised trials that have tested the efficacy of a psychotherapy or lifestyle-based intervention specifically targeting depression in men. In contrast, 19 studies (17%) specifically targeted females. No study or intervention characteristics moderated the level of male representation, with males underrepresented across all study types. Despite this, only ten studies suggested that the lack of male participants was a limitation.
The principal finding that men represent 26% of participants in RCTs targeting depression confirms a significant translational gap exists in clinical decision making for depression. Our results are similar to a review of psychosocial interventions for suicidal ideation and behaviour, which are both constructs related to depression (Nock et al., 2009). The proportion of men in the trials ranged from 37% in self-harm behaviour follow-up studies to 48% in school-based interventions (Krysinska et al., 2017). Although male depression prevalence is approximately half of female prevalence (WHO, 2017), with some evidence suggesting this is an underestimation of male cases (Martin et al., 2013), our results indicate males represent less than half of participants. Given men are less likely to seek help for depression than women (Addis & Mahalik, 2003), it is not surprising that fewer men are involved in depression trials than women. This gap is likely wider outside of research trials, given the men participating in RCTs are considered ‘help-seekers’ as they have generally attended a health service and been referred to the trial or signed up on their own volition. Previous research has indicated that negative self-stigma associated with help-seeking (Vogel et al., 2006) may contribute to men’s underrepresentation in both treatment services and research (Mahalik & Di Bianca, 2021; Mahalik et al., 2003). Thus, it is unlikely that the identified group of studies for the current review provide a good scope of barriers and facilitators to the engagement of men in the context of depression.
The current review found no studies testing interventions that were specifically designed for men, or studies testing standard interventions in male-only environments. In contrast, 19 studies used completely female samples and generally targeted peri or post-natal depression. Our results are similar to other reviews (Castro et al., 2020). For example, Strokoff, Halford, and Owen (Strokoff et al., 2016) conducted a review of 15 studies employing male-targeted psychotherapy treatment approaches and identified only a single, small (n = 23), randomised study examining a treatment specifically tailored for men (Syzdek et al., 2014). This study tested the effect of single session gender-based motivational interviewing on mental health symptoms, stigma, and help-seeking in a community sample of 23 men with mild to moderate internalising symptoms; none of the findings were significant (Syzdek et al., 2014). Similarly, a review of male-only lifestyle behaviour change interventions retrieved no studies that: (i) targeted pre-existing mental health conditions, or (ii) were powered to detect changes in mental health outcomes, or included substantive mental health support (Drew et al., 2020). Research has shown that men will seek help when it is accessible, appropriate, and engaging (Seidler et al., 2016). However, men remain unlikely to attend a full course of psychotherapy (Zimmermann et al., 2017) and report negative attitudes towards psychotherapy treatments (Levant et al., 2011). In a sample of Australian men who had previously attended therapy, a drop-out rate of 44.8% reflects the current state of services experienced by many men in Western mental healthcare (Harris et al., 2015; Seidler, Rice, Ogrodniczuk, et al., 2018; Seidler et al., 2021). Concerningly, recommendations for large-scaled controlled trials testing tailored treatments for men were made over 15 years ago (Cochran, 2005). Despite some theoretical advancement (Addis, 2008), along with recommendations and guidelines for clinical practice with males (APA, 2018; Mahalik et al., 2012), our results indicate that development of programs targeting men’s mental health remains a key area of future research. Without evidence based programs, men’s mental health will perpetually fall short of policy consideration, clinical attention, and required funding (Seidler et al., 2018).
The representation of men in depression trials has not increased over the past decade. This finding is somewhat surprising given the field of men’s health in general has gained traction in recent years (Addis & Cohane, 2005). Public health approaches (e.g., Real Men Real Depression) (Rochlen et al., 2005) play an important part in increasing men’s uptake of mental health services, and appear to be having some positive effects; men’s help seeking for mental and substance use disorders increased from 32% in 2006–2007 to 40% in 2011–2012 (Harris et al., 2015). However, our results show that an increase in help-seeking is not translating into participation in research trials. More targeted recruitment strategies, such as gender-tailored brochures, are effective for improving men’s attitudes towards help-seeking, but like public campaigns, they do not guarantee men will receive an engaging treatment upon seeking help (Seidler et al., 2018). Indeed, the process of help-seeking does not solely involve the act of ‘reaching out’, but also the treatments that follow (Seidler et al., 2016). As such, lower rates of help-seeking in men may be better attributed to the lack of engaging, relevant or accessible mental health treatments (Bilsker et al., 2018; Seidler et al., 2018).
Men’s representation did not differ depending on the presence of a co-occurring mental or physical health condition. However, targeting men with co-occurring conditions might still be a valuable engagement strategy. Substance use disorders are highly prevalent in men and co-occurrence with depression is common (Burns & Teesson, 2002). Similarly, a reciprocal link exists between depression and overweight or obesity (Luppino et al., 2010), particularly in men (Magovcevic & Addis, 2008). In our review, two of the most common co-occurring physical health conditions targeted were diabetes and overweight or obesity. Although we found men’s representation did not differ based on the presence of co-occurring conditions, it is not surprising given men’s representation was low overall. As such, offering integrated programs targeting multiple conditions remains a potential solution to improving men’s representation in mental health trials (Kingerlee et al., 2014; McGale et al., 2011).
Interestingly, this review found that men were equally likely to participate in psychotherapy interventions compared to lifestyle interventions. Observational data indicates physical activity and healthy eating are two of the top five strategies men with depression use to manage their mental health (Proudfoot et al., 2015). Additionally, mental health promotion can be integrated into lifestyle programs once men are engaged (Sharp et al., 2018; Sharp et al., 2022). Despite the proclaimed utility of lifestyle approaches (Sharp et al., 2018), the low representation of men in these interventions is consistent with a systematic review of male inclusion in lifestyle behaviour change programs finding that men represented only 27% of participants (Pagoto et al., 2012). These findings may be attributed to the lack of male-only studies, as men can be deterred by the presence of women in lifestyle programs (Morgan et al., 2011). To better engage men, ‘gender-tailored’ programs which specifically account for men’s unique preferences and values are being developed and tested (Morgan et al., 2009; Morgan et al., 2011). These programs have provided promising results for both engagement and effectiveness in treating mental and physical health (Sharp et al., 2020; Sharp et al., 2021; Young et al., 2012; Young et al., 2021). Despite this, no gender-tailored lifestyle programs were found in this review. Men’s representation was slightly higher (32%) in psychotherapy interventions compared to lifestyle interventions (24%), but the difference was not significant, and the lack of male-specific approaches limits the conclusions that can be drawn. To properly investigate the question of whether men prefer a lifestyle approach or mental health approach for managing depression, male-only programs of each type must be developed and tested.
Our finding that men’s representation did not differ between CBT and other treatment types is inconsistent with evidence CBT is men’s preferred treatment (Emslie et al., 2007; Liddon et al., 2018; Seidler et al., 2016), and recommendations by researchers supporting its utility with men (Englar-Carlson & Stevens, 2006; Spendelow, 2015). For example, behavioural interventions delivered with the context of CBT, such as behavioural activation (Skärsäter et al., 2003), are dubbed male-friendly due to their practical and tangible nature (Brooks, 2010). Recently, a vignette-based study found gender role socialisation, self-stigma, and attitudes towards professional psychotherapy help negatively predicted willingness to engage in psychotherapy regardless of therapy orientation, including CBT (Cole et al., 2019), suggesting that therapy type is irrelevant for these men. Comparatively, the men in the current sample are largely help-seekers, which may suggest that type of therapy is also irrelevant when help-seeking intentions are present. However, given men’s representation was low across all programs, our ability to draw a definitive conclusion is limited.
This review found men’s representation did not differ across delivery mode, the level of contact with other people in the intervention, or dose. Specifically, the finding that men’s representation was similar for individual and group delivery is inconsistent with previous research suggesting men prefer individual therapy (Kealy et al., 2021; Sierra Hernandez et al., 2014). Moreover, despite recent research suggesting that online interventions may be particularly appealing to men (Berger et al., 2013; Ellis et al., 2013; Wang et al., 2016), our results suggest men were less likely to engage in online studies compared to those testing face-to-face delivery modes. Similarly, they did not appear to prefer self-guided interventions to those which required more regular contact with the intervention team. However, research investigating preferences for therapy type (e.g., CBT) and trial characteristics has typically used survey methods whereby preferences are selected based on vignettes or prior experience (Cole et al., 2019; Kealy et al., 2021; Liddon et al., 2018; Sierra Hernandez et al., 2014). An issue with this approach is that it fails to consider the impact of multiple intervention characteristics on men’s choices. Comparatively, our results must be viewed in context of trials comprising many combinations of type, mode, and length. As such, previous findings regarding preferences that are independent of other trial components are unlikely to be translated into real world representation. Ultimately, our results suggest that men’s preferences are heterogenous and a suite of intervention options are required that provides men the ability to choose (Seaton et al., 2017).
Our review found that men’s representation did not differ between direct or indirect recruitment. Similarly, it did not differ between the method of determining depression status (interview, screening tool, or both). When considered together, these two findings indicate current methods of recruiting and including men into depression trials are inadequate. Further, we found that no attempts were made to increase the involvement of men (e.g., through targeted recruitment). It is important to conduct more research in this area as men are more difficult to recruit, because they are reluctant to admit they have depression (Firth et al., 2019), are less likely to be diagnosed (Cochran & Rabinowitz, 2003; Kessler, 2000; Oliffe & Phillips, 2008), and are affected by social and self-stigma due to rigid masculine norms. Yet, targeted efforts to recruit men in male-only lifestyle programs have demonstrated some success (Seaton et al., 2017). For example, the SHED-IT (Self-Help, Exercise and Diet using Information Technology): Recharge program recruited men with overweight or obesity and depressive symptoms through gender-tailored advertising (e.g., “lose weight without giving up beer”) and using the programs credibility as a university-based intervention for further appeal (Drew et al., 2021) which aligned with insights from other gender-tailored programs (Aguiar et al., 2017; Morgan et al., 2011; Morgan et al., 2016). Similar male-specific recruitment methods, such as using sports language (e.g., ‘mental fitness’) rather than mental illness are useful in the mental health context (Cooper et al., 2015). However, minimal research has been conducted on recruiting men into gender-neutral programs, particularly for psychotherapy, and trials typically do not report details on recruitment strategies making it difficult to know what extent targeted strategies were used. A potential way of increasing male engagement without targeted recruitment efforts is using male-specific psychometric tools to evaluate study eligibility, as men are often less willing to report depressive symptoms using existing diagnostic scales (Fields & Cochran, 2011). Scales such as the Masculine Depression Scale (MDS; Magovcevic & Addis, 2008) and Masculine Depression Risk Scale (MDRS-22; Rice et al., 2013) have been designed to detect externalising symptoms of depression common in men, but are yet to be adopted into mainstream research practices (Rice et al., 2019).
Despite the clear underrepresentation of men in the studies, very few identified that this was a limitation. Similarly, few explicitly reported testing for sex as a potential moderator of intervention effects. These results are similar to a review of psychosocial interventions for suicidal ideation and behaviour which found 18% of 154 trials reported or examined differences in gender subgroups and only a single study used an all-male sample (Krysinska et al., 2017). Although psychotherapy outcomes are largely reported as similar for men and women (Staczan et al., 2017), some studies have had mixed findings (Ogrodniczuk et al., 2001; Parker et al., 2011). Crucially, many studies do not report gender differences in the outcome (Parker et al., 2011), including several meta-analyses of psychotherapy for depression (Cuijpers et al., 2021; Cuijpers et al., 2008; Nieuwsma et al., 2012). This is a considerable limitation (Butler et al., 2006), especially given men represented only a third of participants in this review, and limits generalisability of results. However, substantially more women are diagnosed with depression than men (WHO, 2017). One could therefore expect there to be less men involved in trials of depression. Yet, depressive disorders affect 109 million men worldwide (GBD, 2022). As such, the view that men are underrepresented in research trials due to inherently lower prevalence overlooks the needs of men and reinforces ‘male gender-blindness’ (Seager et al., 2014).
This review had several strengths. To our knowledge, it is the first review to quantify the number of men involved in psychotherapy and lifestyle interventions targeting depression. Regarding methodology, this reviewed considered adequately-powered RCTs only, given these are likely to be given the highest priority for informing evidence-based practice and guidelines. Finally, all data were extracted by two reviewers, and the conduct and reporting of the review adhered to the PRISMA guidelines. This review also has some limitations. Firstly, due to the considerable size of the depression literature, relevant subject headings were used to streamline the search process. Whilst our search was not exhaustive, we believe it was extensive and the included studies were likely representative of other studies that may not have been included. Secondly, by including studies that were explicitly powered at 80% to detect changes in depression, studies with adequate sample size may have been excluded based on not reporting a power calculation. However, power calculations are important for ensuring existing effects are able to be detected, using the appropriate amount of resources, and larger sample sizes provide better population estimates (Field, 2013; Noordzij et al., 2010).
Conclusion
The underrepresentation of men in psychotherapy or lifestyle intervention trials targeting depression is a significant concern given men’s substantial prevalence of depression and low rates of help-seeking (WHO, 2017). The results of this review suggest men are equally underrepresented across all intervention and study characteristics, despite male participants in trials already potentially having overcome many attitudinal and stigma-related barriers to help-seeking. To better understand men’s preferences, programs that are specifically designed for and appeal to men are urgently required, and research carried out to understand what prompts help seeking in men specifically. Continuing to deliver gender-neutral programs fails to recognise the needs of men and implicitly accepting that men participate in depression trials at lower rates than women is stalling the field of men’s mental health. This review highlights the need for a concerted effort from researchers to design and test therapeutic approaches that are engaging and appealing for men.
Supplementary information
Below is the link to the electronic supplementary material.ESM 1 (DOCX 23.4 KB)
ESM 2 (DOCX 26.4 KB)
Acknowledgements
The first author (JK) is supported by the University of Newcastle’s Academic Career Preparation Scholarship.
Data availability
The data file for this project is stored in the Centre for Open Science data repository. Link: https://osf.io/4r6zn/?view_only=9ae914f335d34f9baa873fa44eccada6.
Declarations
Conflict of interest
The authors declare no conflict of interest.
1 Agreement was calculated by dividing the number of discrepancies by the total number of responses on each item.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9735062 | NO-CC CODE | 2022-12-14 23:28:32 | no | Curr Psychol. 2022 Dec 5;:1-16 | utf-8 | Curr Psychol | 2,022 | 10.1007/s12144-022-04017-7 | oa_other |
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J Stat Theory Pract
J Stat Theory Pract
Journal of Statistical Theory and Practice
1559-8608
1559-8616
Springer International Publishing Cham
310
10.1007/s42519-022-00310-7
Original Article
On Fixed Accuracy Confidence Interval in Multivariate Normal Distribution with Order 1 Autoregressive Covariance Structure
Sarkar Pritam 1
Bandyopadhyay Uttam 2
http://orcid.org/0000-0002-3748-717X
Bhattacharya Rahul [email protected]
[email protected]
2
1 grid.411826.8 0000 0001 0559 4125 Department of Statistics, The University of Burdwan, Barddhaman, India
2 grid.59056.3f 0000 0001 0664 9773 Department of Statistics, University of Calcutta, Ballygunge Circular Road, Kolkata, 700019 India
6 12 2022
2023
17 1 139 11 2022
© Grace Scientific Publishing 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
In this paper, stein-type two-stage sampling procedure is carried out for fixed accuracy confidence interval estimation of the common variance (σ2) parameter corresponding to multivariate normal distribution with autoregressive covariance structure of order 1. Related asymptotics are obtained and simulation results are presented.
Keywords
Fixed accuracy confidence interval
Stein two-stage procedure
Auto-regressive model
Asymptotic relative efficiency
Mathematics Subject Classification
62F25
62H10
issue-copyright-statement© Grace Scientific Publishing 2023
==== Body
pmcIntroduction
Multiple observations, taken over time or space, on the same sampling unit induce correlation among the observations. Consequently, a sensible analysis of such data must be based on an appropriate assumption on the structure of the covariance between measures on the same unit. However, analyses based on the usual spherical covariance assumption undermine the validity of the findings. Although appropriate transformations can make the covariance structure close to spherical but analysis based on the transformed data is inadequate in nature as the best transformation is difficult to identify. Recently, linear mixed model-based methodology allows to incorporate correlation into the covariance structure and makes the analysis more appropriate. Thus, in brief, the correlation structure plays an important role in the analysis of correlation data and quality of inference depends on the assumed covariance structure. Autoregressive (AR) covariance structures are useful for linear time series data, where the current observation is linearly related to the past few observations. Applications of such models are found in the fields of psychometry, bio-medical research and signal detection [5, 7, 11]. The AR models have been found applicable in recent years to the analysis of financial time series data depending upon various complicated political issues. As for example, interest rates of different banking sectors or the stock market index values change frequently and it becomes necessary to understand the causes that are responsible behind these changes in order to develop a future plan for investment. This leads to concentrate our focus on the simplest AR model of first order, which is attractive because of its ability to interpret the random nature of the interest rates as a mean reversion process. However, in the current work, we consider the problem of confidence interval (CI) estimation of the common error variance component. Under a multivariate normal setup with complete symmetry, this problem was considered by [2, 3, 6, 12] and many others. Recently, [8] worked on the same problem but with compound multivariate normal model. However, in the current work, we adopt a two-stage sampling technique [9, 10] to derive an expression of the optimum sampling frequency subject to some constraint based on the CI of error variance and hence derive a fixed accuracy interval of such error variance.
Specifically, we assume that X=(X1,X2,⋯,Xd)⊺ is a d component random vector such that1 X∼Nd(μ,Σ);μ=μ1,Σ=σ2R,
where μ and σ2 are common mean and variance of the marginal distributions, 1 is a vector of ones and R={ρij} is the non-singular correlation matrix with elementsρij=ρif|i-j|=1=1if|i-j|=0=ρ|i-j|if|i-j|>1.
The covariance matrix corresponds to autoregressive (AR) model of order 1 (denoted by AR(1)) and σ2 is the common error variance. In the subsequent development we consider μ=0 without loss of generality and focus on finding n such thatPθδ-1<σ^n2σ2<δ≥1-α
holds for every θ=(σ2,ρ):σ2>0,ρ∈(-1,1)andδ>1,α∈(0,1) with σ^n2 as a consistent estimator of σ2. As a result, the corresponding random interval, [σ^n2δ-1,σ^n2δ], will produce fixed accuracy CI for σ2. It is worth mentioning at this point that the conventional fixed width confidence interval for σ2 uses the random interval (σ^n2-d,σ^n2+d) with positive d, which may produce negative bounds even if it is well known that σ2 is always positive. Although certain modifications can be made to overcome this undesirable scenario but at the cost of compromising the asymptotic consistency property (see, [1], for details). In contrast, fixed accuracy confidence interval for σ2 is based on the random interval [σ^n2δ-1,σ^n2δ] for δ>1 and hence always produce positive bounds. Consequently, we concentrate on developing fixed accuracy confidence intervals throughout this work. The layout of the current work is as follows: The derivation of optimum n in connection with the fixed accuracy confidence interval of σ2 by using two different methods is discussed in Sect. 2. The related sampling scheme is developed in Sect. 3. Choice of pilot sample size with various related large sample results are discussed in Sect. 4. Section 5 contains numerical studies and Sect. 6 concludes.
Finding Optimal Sample Size
In this section, we provide two approaches to find the optimal sample size (n0). One approach uses maximum likelihood (ML) estimator and calls it Approach 1. The other approach is based on least square estimator and calls it Approach 2.
Approach 1
LetA=∑i=1n(Xi12+Xid2),B=∑i=1n∑j=2d-1Xij2,andC=2∑i=1n∑j=1d-1XijXij+1
be obtained from the sample of n observations, {X1,X2,…,Xn} corresponding to (1). Then, the associated log-likelihood function, neglecting the additive constant, isL(θ)=-nd2log(σ2)-n2(d-1)log(1-ρ2)-12σ2(1-ρ2)A+(1+ρ2)B-ρC,
where θ=(σ2,ρ)⊺. LetU(θ)=U1(θ),U2(θ)⊺=∂L(θ)∂σ2,∂L(θ)∂ρ⊺
be the associated score vector, whereU1(θ)=-nd2σ2+12σ4(1-ρ2)A+(1+ρ2)B-ρC,U2(θ)=n(d-1)ρ1-ρ2-12σ2(1-ρ2)2(2ρ)A+(4ρ)B-(1+ρ2)C.
The corresponding information matrix is represented byI(θ)=-Eθ∂2L(θ)∂σ4∂2L(θ)∂ρ∂σ2∂2L(θ)∂σ2∂ρ∂2L(θ)∂ρ2=nd2σ4-n(d-1)ρσ2(1-ρ2)-n(d-1)ρσ2(1-ρ2)n(d-1)(1+ρ2)(1-ρ2)2.
The inverse of I(θ) is obtained asJ(θ)=J11(θ)J12(θ)J21(θ)J22(θ)=d-(d-2)ρ2-12σ4n(1+ρ2)2σ4nρ(1-ρ2)2σ4nρ(1-ρ2)d(1-ρ2)2n(d-1).
Let θ^n=(σ^ML2,ρ^ML)⊺ be the maximum likelihood (ML) estimator of θ based on n observations. Then, θ^n is the solution of2 U(θ)=(U1(θ),U2(θ))⊺=0,
which, after straightforward calculation, givesσ^ML2=1nd(1-ρ^ML2)(A+B)-Cρ+Bρ2
with ρ^ML as the solution of2Bρ3(d-1)+ρ2(2C-Cd)-2ρ(Bd+(A+B))+dC=0.
Now from the standard asymptotic theory, we haven(θ^n-θ)→N2(0,J(θ))
in distribution as n→∞, and hence it follows that3 n(log(σ^ML2)-log(σ2))→N(0,2ψ(ρ))
in distribution as n→∞, where ψ(ρ)=1+ρ2d-(d-2)ρ2. Here, our objective is to find n=n0 such that, given (δ,α):δ>0 and α∈(0,1),4 Pθδ-1<σ^ML2σ2<δ≥1-α
holds for all θ: σ2>0 and ρ∈(-1,1). Then, using (3) and (4), we find n0 as5 n10=2u2(ln(δ))2ψ(ρ)+1,
where P(|N(0,1)|<u)=α.
Approach 2
In this approach, we first find the least square (LS) estimator of ρ asρ^LS=∑i=1n∑j=2dXijXij-1∑i=1n∑j=2dXij-12,
which is consistent with ρ. Then, using this estimator, we find6 σ^LS2=1n(d-1)(1-ρ^LS2)∑i=1n∑j=2dXij2-ρ^LS2∑i=1n∑j=2dXij-12
as an estimator of σ2. It can be shown that the asymptotic distribution of n(σ^LS2-σ2) is same as that ofEn=n(d-1)(1-ρ2)(T1-σ2)-ρ2(T2-σ2),
whereT1=1n∑i=1n∑j=2dXij2,T2=1n∑i=1n∑j=2dXij-12.
To study the asymptotic distribution of En, we need to consider first the joint distribution (T1,T2)⊺ for which multivariate CLT yieldsVn=nT1-σ2T2-σ2→N2(0,Σ1)
in distribution, whereΣ1=σ4abba,
witha=2(d-1)+4ρ2(d-2)-(d-1)ρ2+ρ2(d-1)(1-ρ2)2,andb=2ρ22(d-2)-2(d-1)ρ2+ρ(2d-4)(1+ρ4)(1-ρ2)2+2(d-2).
LetL⊺=1(d-1)(1-ρ2),-ρ2(d-1)(1-ρ2).
Then, we get7 L⊺Vn=En→N(0,L⊺Σ1L)
in distribution, where L⊺Σ1L=σ4g(ρ) with. g(ρ)=a(d-1)2(1-ρ2)2(1+ρ4)-2ρ2b(d-1)2(1-ρ2)2. Then, as in the previous case, we find n0 as8 n20=u2g(ρ)(log(δ))2+1
The n10 and n20, given in (5) and (8), are referred to as optimum sample sizes required to get two different fixed width confidence intervals for σ2 using two different estimation procedures. Here, both n10 and n20 are functions of unknown parameter ρ. In the next section, we provide sampling strategy to find plug-in-estimator of n10 and n20.
Sampling Strategy
In this work, to estimate ρ, we opt two stage sampling technique in which we prefix a pilot sample of size n1, say, and will start the procedure with the sample {X1,X2,…,Xn1} corresponding to N(0,σ2R). On the basis of this sample we first find two estimators of ρ, in which one corresponds to Approach 1 and the other corresponds to Approach 2 and then we obtain the plug-in estimators, n^10 and n^20, of n10 and n20. Hence, as in Stein’s two-stage procedure (1945,1949), we find our stopping variables as9 Nk=max{n1,n^k0},
k=1,2, and the associated fixed accuracy confidence intervals for σ2 as10 [σ^Nk2δ-1,σ^Nk2δ],
k=1,2. Next, we suggest a choice for n1 with some asymptotic properties. These are given in the next section.
Choice of Pilot Sample Size and Asymptotic Results
It is very important to choose n1 properly as the performance (average sample size, estimated coverage probability, standard error, etc.) of two stage technique depends upon this. Here, we propose our pilot sample size (see, for example, [4]) as11 n1=max4,ulog(δ)21+γ+1,
where γ>0 and it is not difficult to verify thatlimδ↓1n1nk0=0,k=1,2,
which is a desirable property related to pilot sample size. Now we discuss some asymptotic results associated with our stopping variables.
Theorem 1
For k = 1, 2, we have (i) n^k0nk0→1(a.s.)
(ii) Nknk0→1(a.s.)
(iii) limδ↓1Pθδ-1≤σ^Nk2σ2≤δ=1-α for every θ (asymptotic consistency).
Proof
(i) Here, we prove this for k=1 and the other part is similar. 2u2(log(δ))2ψ(ρ^ML)2u2(log(δ))2ψ(ρ)+1≤n^10n10≤2u2(log(δ))2ψ(ρ^ML)+12u2(log(δ))2ψ(ρ)
and hence the required result follows almost surely when δ↓1.
(ii) Note that n^k0≤Nk≤n^k0+n1,
which implies n^k0nk0≤Nknk0≤n^k0+n1nk0,
and hence the result follows by (i) and limδ↓1n1nk0=0,k=1,2.
(iii) Here, we prove this part of the theorem separately for N1andN2. For N1: We write the above probability statement as 12 PθN1|log(σ^N12)-log(σ2)|2ψ(ρ)≤N1log(δ)2ψ(ρ).
Using (i) we have N1log(δ)2ψ(ρ)→u(a.s).
Hence, by Polya’s theorem, the results follow from (12) provided N1(σ^N12-σ2)2σ4ψ(ρ)→N(0,1)
in distribution. On this matter, using (2) and the representation θ^N1=θ+(θ^n10-θ)+(θ^N1-θ^n10),
it is enough to show 13 n10(σ^N12-σ^n102)→0(in probability).
From (1), using Taylor’s series expansion on U(θ^n) about the true value θ and with some routine steps, we arrive at the approximate relation 14 θ^n≈θ+1n∑i=1nVi(θ)+o(||θ^n-θ||),
where Vi(θ),i=1,2,⋯ are iid according to Vi(θ)=I-1(θ)Ui(θ),E(Vi(θ))=0,E(||Vi(θ)||2)<∞,
and no(||θ^n-θ||)→0(a.s).
Further, it is not difficult to show that for every ϵ>0 and η>0, there exists n∗ and ϵ∗ such that 15 Pmax|m-n|≤nϵ∗∑i=1mVi(θ)-∑i=1nVi(θ)>ϵn<η
for every n≥n∗. Hence, combining (14) and (15), we get 16 Pmax|m-n10|≤n10ϵ∗||θ^m-θ^n10||≥ϵn10≤η
for every δ<δ0<1 with n10=n10(δ). That means , the Anscombe’s condition is satisfied, and hence (13) follows.
For N2 : Here, as in (a), we prove that 17 N2σ^N22-σ2→N(0,1)
in distribution as δ↓1. On this matter, as ρ^n20→ρ(a.s) when δ↓1, it is enough to show that 18 1n20(SN2k-Sn20k)→0(inprobability)
as δ↓1 for k=1,2, where Sn1=∑i=1n{∑j=2d(Xij2-σ2)}andSn2=∑i=1n{∑j=2d(Xij-12-σ2)}. In (18), the proofs for k=1,2 are similar. Hence, we consider k=1 . From Kolmogorov’s inequality for iid random variables and using (i), it follows that lim supδ↓1Pmax|t-n20|<n20ϵ3|St1-Sn201|>ϵn20<aϵ
for every ϵ>0, which implies (18) .
□
Numerical Studies
In this section we carry out simulation to present some numerical results associated with the performances for the stopping variables Nk,k=1,2. On these matters we exhibit how such performances, measured by the triples {Average sample number (E(Nk)^), Standard error (SE^(Nk)) and coverage probability (cp^k)}; k=1,2, are changed with various configurations of θ=(σ2,ρ,γ,δ) and d. We set αat0.05 and make 10000 iterations of each selected value of θ and d in which σ2=2.Table 1 Numerical results associate with performance measure of Approach 1 and Approach 2
Approach 1 Approach 2
d σ2 ρ δ γ n1 n10 E(N1)^ SE^(N1) cp1^ n20 E(N2)^ SE^(N2) cp2^
10 2 -.4 1.15 .7 23 53 53.1611 .0470 .9493 63 64.4145 .0975 .9552
1.5 9 53 53.6416 .0766 .9515 63 67.4823 .1995 .9570
1.09 .7 40 138 138.6314 .0825 .9469 164 166.8175 .1848 .9554
1.5 13 138 138.5213 .1723 .9430 164 172.6389 .3973 .9530
.4 1.15 .7 23 53 53.17 .0464 .9492 63 64.4759 .1857 .9573
1.5 9 53 53.7891 .0781 .9465 63 67.8087 .2157 .9539
1.09 .7 40 138 138.7249 .0931 .9474 164 166.7414 .1832 .9507
1.5 13 138 139.9018 .1674 .9494 164 171.7549 .3798 .9558
.6 1.15 .7 23 76 75.861 .0894 .9474 136 147.3199 .5985 .9721
1.5 9 76 76.0263 .1400 .9424 136 174.14 1.6002 .9684
1.09 .7 40 198 198.6528 .1761 .9477 356 374.4621 1.0885 .9793
1.5 13 198 199.067 .3099 .9451 356 413.768 2.4461 .9709
20 2 -.4 1.15 .7 23 27 27.2196 .0180 .9516 30 30.4067 .0298 .9536
1.5 9 27 27.4008 .0290 .9468 30 31.1011 .0550 .9540
1.09 .7 40 71 70.7241 .0354 .9509 78 78.8227 .0574 .9555
1.5 13 71 70.9761 .0620 .9471 78 80.0152 .1107 .9508
.4 1.15 .7 23 27 27.2584 .0181 .9526 30 30.441 .0301 .9590
1.5 9 27 27.2196 .0289 .9488 30 31.114 .0541 .9576
1.09 .7 40 71 70.7092 .0354 .9525 78 78.8863 .0589 .9489
1.5 13 71 71.0109 .0626 .9518 78 79.8866 .1095 .9533
.6 1.15 .7 23 40 40.1914 .0367 .9598 67 96.8755 .1932 .9773
1.5 9 40 40.3293 .0589 .9452 67 74.3195 .3614 .9721
1.09 .7 40 105 104.7955 .0733 .9455 175 178.8089 .3672 .9796
1.5 13 105 104.6165 .1272 .9489 175 188.9388 .7445 .9779
In Table 1, we demonstrate the numerical figures associated with the performance measures for Approaches 1 and 2 at different (θ,d) to get a comparative view between the two approaches. Towards this we make the following observations : (i) E(N1)^ is uniformly smaller than E(N2)^ for all θ,d,andα that we have considered here. specifically, E(N1)^attains the corresponding optimal value(n10) quite accurately. On the other hand, E(N2)^ exceeds the corresponding optimal value (n20) by a small margin for all the parametric configurations considered here, except for ρ=.6, whereas this margin is not too small.
(ii) cp^1 meets the nominal confidence (= 0.95) quite appropriately for all θ and d. The same scenario is observed for cp^2 except for ρ=0.6, in which case it is higher than 0.95.
(iii) For fixed θ and d considered here, E(Nk)^ decreases with d. The same behavior is also observed for SE^(Nk),k=1,2.
(iv) For fixed θ,δ and α with increasing γ,E(N2)^ increases but E(N1)^ remains unchanged.
(v) As usual, for each fixed ρ,γ and α, E(N)^k increases with δ(k=1,2).
(vi) For all given θ,d and α, SE^(N1)<SE^(N2).
(vii) In Table 3, we have showed the exact value of asymptotic relative efficiency (ARE) of our two proposed estimators For d=3,5 and our proposed values of ρ, every ARE values are more than 1.
Thus, as a whole Approach 1, is uniformly better than Approach 2 with respect to the statistical measures considered here. On the other hand, Approach 2 is relatively easy to execute in practice.
Data Study
In order to envisage the applicability of the developed procedure, we applied our procedure in a real situation-based data. The data set is related to COVID-19 infections in Belgium during 18-4-20 to 16-6-20, which is available at ‘www.ourworldindata.org.’ Although a number of variables are available in the data set, we consider only the variables daily case, daily deaths and daily tests. At the outset, we apply Box-Cox transformation on each variable by taking λ=.1 and perform Mardia’s test on the transformed data to justify tri-variate normality. The p value of the corresponding test of kurtosis comes out as 0.2353, which ensures significant closeness with the assumed tri-variate parent. Thus, we use this data for our purpose noting that the unit of the time point is two months. We computed N adopting both the approaches for different choices of δ and fixed γ=0.7,α=0.05 and the results are given in Table 2.Table 2 Some values of N for different δ
Approach 1 Approach 2
N(δ=1.60)=28 N(δ=1.60)=40
N(δ=1.55)=32 N(δ=1.55)=46
N(δ=1.50)=37 N(δ=1.50)=52
We also compare the lengths of fixed sample confidence interval with this fixed accuracy confidence interval under both approaches for different choices of δ. If we use σ^ML2, then the observed length of fixed sample procedure is19 L=σ^ML22nu2ψ(ρ^ML)(n-2u2ψ(ρ^ML))
Since, for large enough n, σ^ML2 and ρ^ML are close to the corresponding true values, we plot L against ρ for different choices of n and σ2.
In Fig. 1, it is observed that L increases steadily with increase in ρ for every fixed n and σ2. For n=50, L increases more rapidly compared to the other choices of n because for such a choice the denominator of L decreases sharply. Figure 2 depicts the same feature for σ2=130. However, for the data taken for our purpose, σ^ML2=132.4125 and ρ^ML=0.7177 and hence we can say from these figures that L will tend to be higher. However, the lengths of confidence intervals corresponding to fixed sample procedure and two stage procedure are not comparable and hence for comparability, we use the value of stopping variable (N) for a fixed δ in (19). For example, when δ=1.50, N corresponding to Approach 1 is 37 and we used this value and plug in the estimated values of σ2 and ρ in (19). This gave us a comparable length of 128.782. However, for δ=1.5, the length of the fixed accuracy interval is found to be 2log(δ)=0.8765. Hence, the quality of precision is significantly improved under the proposed two stage strategy.Fig. 1 Graph of length for varying n and σ2=125
Fig. 2 Graph of length for varying n and σ2=130
Concluding Remarks
In this work, we have followed the spirit of Stein’s two stage procedure in both approaches by adopting different methods of estimation for the unknown parameters involved in the parent population distribution. Our numerical findings establish superiority of Approach 1 relative to Approach 2. In fact the asymptotic relative efficiency (ARE) of σ^ML2 with respect to σ^LS2 is obtained ase(ρ)=g(ρ)2ψ(ρ)=limδ→1n20n10,
which exceeds unity for all the values of ρ∈(-1,+1) (see Appendix). That is, σ^ML2, as expected, is asymptotically more efficient than σ^LS2 and this fact makes Approach 1 superior to Approach 2 with respect to the present measures of performances (see, for example, the numerical figures in Table 3). Further computation (not shown here) revealed that e is close to 1 for large d when other components in θ remain unaltered. We finally note that the methods considered in this article, can easily be extended to sequential framework. We would like to pursue in this direction further.Table 3 Comparison of ARE of ML and LS estimators corresponding two approaches
d ρ ARE
3 .10 1.000022
.50 1.008333
.07 1.000005
.80 1.019980
.25 1.000766
5 .10 1.000024
.50 1.012562
.07 1.000006
.80 1.048820
.25 1.000899
Appendix
By definition, e(ρ)=g(ρ)2ψ(ρ) is symmetric with respect to 0 as it involves only even powers of ρ. The first order derivative of e(ρ) comes out ase′(ρ)=2(ψ(ρ)g′(ρ)-g(ρ)ψ′(ρ))4ψ2(ρ),
whereψ′(ρ)=4ρ(d-1)(d-1)2(1-ρ2)2andg′(ρ)=(d-1)2(1-ρ2)2(4aρ3+(1+ρ4)∂a∂ρ)-(4ρb+2ρ2∂b∂ρ)(d-1)2(1-ρ2)22.
It is easy to observe that ψ′(0)=0. Again from the structure of a=a(ρ),a′(ρ)=4(1-ρ2)22ρ(d-2)-(d-1)4ρ3+2dρ(2d-1)+ρ2[(d-2)-(d-1)ρ2+ρ(2d-1)]4ρ(1-ρ2)(1-ρ2)4,
which vanishes for ρ=0. Thus, e′(0)=0 and hence 0 is a stationary point of e(ρ). A further routine algebraic manipulation reveals that e(ρ) is strictly increasing for ρ∈(0,1), which together with the symmetry of e(ρ) establishes that e(ρ) is ‘U’ shaped. Hence, we can conclude that ρ=0 is the only point of minimum of e(ρ). Thus, e(ρ)>e(0)=d(d-1)>1 for all ρ∈(-1,1). A simple graph of e(ρ) for d=3 is further added below for brevity (Fig. 3).Fig. 3 Change of ARE with respect to ρ
Acknowledgements
The authors sincerely thank the referees, Editor and the Associate Editor for their insightful suggestions, which led to an improvement over the submitted version.
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Article
Phase angle and cellular health: inflammation and oxidative damage
http://orcid.org/0000-0002-8674-5753
da Silva¹ Bruna Ramos 1
http://orcid.org/0000-0001-5989-0528
Orsso¹ Camila E. 1
http://orcid.org/0000-0002-3901-8182
Gonzalez² Maria Cristina 2
http://orcid.org/0000-0002-7523-953X
Sicchieri³ Juliana Maria Faccioli 3
http://orcid.org/0000-0001-6647-7774
Mialich³ Mirele Savegnago 3
http://orcid.org/0000-0003-1288-0802
Jordao³ Alceu A. 3
http://orcid.org/0000-0002-3609-5641
Prado Carla M. [email protected]
1
1 grid.17089.37 0000 0001 2190 316X Department of Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, Canada
2 grid.411965.e 0000 0001 2296 8774 Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Rio Grande do Sul Brazil
3 grid.11899.38 0000 0004 1937 0722 Department of Health Sciences, Division of Nutrition and Metabolism, School of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil
7 12 2022
120
28 11 2022
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This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
Phase angle is a composite measure that combines two raw bioelectrical impedance analysis measures: resistance and reactance. Phase angle has been considered an indicator of cellular health, integrity, and hydration. As inflammation and oxidative stress can damage cellular structures, phase angle has potential utility in early detecting inflammatory and oxidative status. Herein, we aimed to critically review the current understanding on the determinants of phase angle and its relationship with markers of inflammation and oxidative stress. We also discussed the potential role of phase angle in detecting chronic inflammation and related adverse outcomes. Several factors have been identified as predictors of phase angle, including age, sex, extracellular to intracellular water ratio, and fat-free mass. In addition to these factors, body mass index (BMI) also seems to influence phase angle. Available data also show that lower phase angle values are correlated (negligible to high correlation coefficients) with higher c-reactive protein, tumour necrosis factor-α, interleukin-6, and interleukin-10 in studies involving the general and aging populations, as well as patients with chronic conditions. Although fewer studies have evaluated the relationship between phase angle and markers of oxidative stress, available data also suggest that phase angle has potential to be used as an indicator (for screening) of oxidative damage. Future studies including diverse populations and bioelectrical impedance devices are required to confirm the validity and accuracy of phase angle as a marker of inflammation and oxidative stress for clinical use.
Keywords
Bioelectrical impedance analysis
Phase angle
Chronic diseases
Inflammation
Oxidative stress
==== Body
pmcIntroduction
Inflammation is a critical component of the body’s response to damage, injury, and infection to restore homeostasis [1]. The immune system triggers inflammatory responses as a defense mechanism, usually temporary in acute conditions [2, 3]. Conversely, chronic inflammation is an uncontrolled, prolonged process associated with abnormal proinflammatory cytokine production and its consequential tissue damage and physiological imbalances; this low-grade inflammatory response is often subclinical [4].
Chronic inflammation can contribute to metabolic abnormalities, changes in body composition, and the onset of many chronic diseases, such as sarcopenia, diabetes, metabolic syndrome, cardiovascular disease, neurodegeneration, and cancer [5–8]. Obesity can compound the inflammatory response through an increased production of tumour necrosis factor-α (TNF-α) and interleukin-6 (IL-6), prompting a proinflammatory milieu and oxidative stress [9]. This is particularly important in view of the obesity epidemic worldwide [10]. In more severe cases, chronic inflammation can also result in organ dysfunction and death [11–13].
Given the negative effects of inflammation on health, assessing and monitoring inflammatory status can provide valuable information in clinical practice. In such settings, inflammation is often evaluated by measuring blood biomarkers, such as cellular factors (e.g., lymphocytes), C-reactive protein (CRP), TNF-α, interleukins, and negative acute-phase proteins (e.g., albumin, and transferrin) among others [14, 15]. However, these markers require invasive blood tests and subsequent costly laboratory analyses, delaying the assessment of inflammatory status. Early assessment of inflammation is critical to initiate personalized treatment, evaluate patient prognosis, and screen for diseases [15–17].
Phase angle (PhA) may be a low-cost, real-time alternative approach to measuring blood inflammatory biomarkers. During inflammation and oxidative stress, reactive oxygen species disrupt cell membranes and fluid balance between intracellular and extracellular spaces; this fluid imbalance influences the capacitive effect of membranes and consequently, PhA [18]. PhA is therefore considered a marker of cell membrane integrity and a potential surrogate—yet reliable method—to screen for inflammatory and oxidative abnormalities [18]. Notably, several studies have shown the relationship between PhA and medical issues, prognoses, and mortality [19, 20]. Here, we summarized the literature, outlining the determinants of PhA as well as the relationships between PhA, inflammation, and oxidative damage. We further discuss the utility of PhA in clinical practice and future research on this important topic.
Phase angle and its determinants
PhA is obtained as a ratio between the raw measures resistance (R) and reactance (Xc) from bioelectrical impedance analysis (BIA) at 50 kHz frequency, according to the following formula [21]:\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Phaseangle\left(^\circ \right)=Arctangent\left(\frac{Reactance}{Resistance}\right)\times \left(\frac{180^\circ }{\pi }\right)$$\end{document}
PhA results from the relationship between the body’s resistive behaviour, the opposition offered by the body fluids and electrolytes (i.e., intracellular and extracellular resistance) and cell membrane-specific capacitance / Xc (i.e., membrane’s ability to sustain the electrical potential) to the BIA’s electric current [22, 23]. In other words, the alternating current passing through the body’s tissues is associated with changes in R and Xc, which are the foundation of the PhA concept [24]. Therefore, PhA depends on many parameters, including cellular content and fluids as well as cell membranes’ integrity and permeability [24]. As a result, PhA is regarded as a marker of cell size, hydration, integrity, and death [25]. Decreased cellular structure and increased cell death are associated with lower PhA values, whereas improved overall cell function and health are associated with higher PhA values [26, 27].
Several factors can determine PhA, and the extent of their influence vary with age and health status. For instance, a large cohort study showed that sex and age were the main PhA determinants in heathy adults (n = 214,732), but age and body mass index (BMI) predicted PhA to a greater extent in healthy children and adolescents (n = 15,605) [28]. Although BMI was weakly correlated with PhA in healthy adults, PhA seems to decrease after a BMI of 40 kg/m2 [28]. This inverse association between PhA and BMI > 40 kg/m2 has been confirmed by others [29, 30] and might be explained by factors such as increased tissue hydration [22] and inflammation [28]. At very high BMI values (i.e., ≥ 40 kg/m2), individuals present with fluid overload that is characterized by altered extracellular water (ECW) and intracellular water (ICW) ratio (ECW/ICW) [24, 31], which is negatively related to PhA [24]. As obesity is associated with a chronic proinflammatory status, individuals with higher BMI values may also present with cellular membrane damage, further contributing to fluid imbalance and a lower PhA [28].
In addition to the ECW/ICW ratio, fat-free mass is another strong predictor of PhA. In a study with healthy individuals (N = 1,442), fat-free mass was one of the most critical determinants of PhA, explaining the association between PhA, sex, and age [24]. Variability in PhA has also been explored using a machine learning approach, with ICW and sex having the highest effect on PhA differences, followed by total body water, basal metabolic rate, and age [32]. PhA has also been linked to other health markers, such as frailty, muscle mass quantity and composition, physical function, muscular strength, and cardiorespiratory fitness levels [33–36]. In healthy older adults, Matias et al. reported that PhA predicted body strength and agility independently of sex, age, and skeletal muscle mass [37].
Other factors can impact PhA in the presence of diseases, with patients generally presenting with lower PhA values than healthy individuals [38]. PhA can be affected by specific elements of the disease, infection, inflammation, or oxidative stress [22, 39]. In this sense, PhA has been proposed as an independent predictor of disease severity in clinical conditions, such as malnutrition [40], increased nutritional risk [41], and sarcopenia [42]. These conditions all have inflammation in common [43], which affects tissue electrical properties, body cell mass, cell membrane integrity, and ultimately PhA [44]. Nevertheless, a systematic review of 33 articles could not conclusively indicate that PhA can independently predict malnutrition in clinical populations, as assessed by Subjective Global Assessment [45]. This result could have been impacted by the selected studies failing to account for confounding variables and/or to select proper PhA cut-offs [45]. Hydration is another potential confounder; thus, it is recommended to interpret PhA along with the RXc graph from the bioimpedance vector analysis in clinical populations [44]. Conditions in which malnutrition is prevalent and PhA is considered a prognostic tool include patients with human immunodeficiency virus [46], kidney chronic disease [47, 48], breast [49], colorectal [50], head and neck [51], hepatic cancers and other liver diseases [52], and COVID-19 [53, 54]. Higher ECW/total body water ratio played a significant role in mediating the relationship between PhA and mortality in patients with cancer cachexia even at a low BMI range [55]. Finally, PhA can also be affected by lifestyle factors. For example, smoking negatively affects PhA, primarily due to oxidative stress and inflammatory pathways [56]. Research has additionally shown a positive impact of physical activity intervention programs and antioxidants supplementation (e.g., zinc) on PhA values [57–59].
The biological and medical implications of PhA can be better appreciated in light of technological advancements, such as the field of Proteomics. Proteomics is a cutting-edge application of technologies for identifying and quantifying the total amount of proteins in a cell, tissue, or organism [60]. Huemer et al., 2022 employed proteomics to investigate PhA’s biomedical factors by identifying protein markers and its related biological processes [61]. The authors found that N-terminal prohormone brain natriuretic peptide (a marker of heart failure) was a significant PhA marker. They also indicated that the biological process related to PhA’s protein profile was involved in the protein profile control of cell quantity and growth, supporting the consensus that PhA reflects body cell mass from a biomedical perspective [61].
Phase angle, inflammation and cellular damage
Overview
Inflammation and oxidative stress are intimately related and can be triggered by many factors, including pathogens, diseases, environmental factors (e.g., chemical substances, radiation and pollution), lifestyle factors (e.g., smoking and alcohol consumption), and obesity [62, 63]. Both are also associated with cellular damage and are involved in the onset of several chronic disease through mobilization of immune cells and proinflammatory cytokine production [64].
Chronic inflammation, in a vicious cycle, can promote reactive oxidative species production, which increases inflammatory response and cellular injury [12]. As such, an inflammatory and oxidative environment are associated with constant cell damage. These injuries can cause alterations in diverse cellular structures and organelles (e.g., membranes, mitochondria, and nucleus) by oxidation of various components, such as lipids, protein, and deoxyribonucleic acid, which prompts apoptosis [65]. Consequently, this prolonged process can affect cell structure and integrity, cellular water content distribution, and cellular function, potentially causing tissue damage or illness. For this reason, inflammation is considered as an important etiologic factor of cancer, diabetes, cardiovascular disease, neurodegeneration, aging, and sarcopenia [3, 8, 66].
PhA may indirectly reflect inflammation as it measures cellular integrity and health and is associated with body cell mass and hydration [67, 68]. Lower PhA values are associated with a lower body cell mass and imbalances in cellular water (i.e., expansion of absolute ECW or increased ECW/ICW). This occurs in disease states [3, 69], and might be explained by the more oxidative environment of the extracellular fluid, versus that of the intracellular space [70]. During inflammation, Xc decreases in response to the lower capacitance of damaged cell membranes, and this occurs simultaneously with a reduction in R because of increases in ECW (measured at 50 kHz). As PhA represents the ratio between Xc and R, and the values of the former measure decrease to a greater extent than those of the latter, inflammation causes a decrease in PhA. Lower PhA also implies lower overall health, which might explain why low PhA has been linked to different diseases, muscle wasting [42], low physical performance [34], hospitalization [71], and mortality [53]. In contrast to clinical populations, healthy adults (i.e., athletes) showed positive associations between PhA and ICW but negative association with ECW/ICW ratio in both cross-sectional and longitudinal analyses [72, 73]. Thus, it is reasonable to expect that PhA can also reflect inflammation. Figure 1 provides an overview of the interconnection among inflammation, oxidative stress, low PhA, and adverse health effects.
Fig. 1 The relation between inflammation, oxidative stress, cellular damage, low phase angle, and poor outcomes. Pathogens, environmental factors, high fat mass and lifestyle factors, such as alcohol consumption or smoking, can trigger an inflammatory and oxidative stress responses, and both can promote damage in several cellular structures, prompting cell death. This proinflammatory signaling, when chronically maintained, is related to several diseases, such as cardiovascular, metabolic, neurodegenerative disease, and cancer. Prolonged proinflammatory signaling can also lead to muscle wasting, lower physical function, sarcopenia, and increased length of hospitalization and mortality. Additionally, the cellular damage promoted by the inflammatory response can contribute to a low phase angle. For this reason, phase angle has been associated with several chronic diseases and mortality, including inflammation and oxidative stress. Note that the figure depicts phase angle being measured by a tetrapolar bioelectrical impedance analysis (BIA) device; although other BIA devices can also be used, PhA is always obtained at a frequency of 50 kHz. Images retrieved from smart.servier.com
Literature search
We conducted a non-systematic literature search in PubMed (from database inception to July 2022) to identify studies addressing the associations between PhA, inflammation, and oxidative stress. A combination of the following medical subject headings and keywords was used in the title/abstract field: “inflammation,” “inflammatory,” “low-grade inflammation,” “chronic inflammation,” “inflammatory markers,” “meta-inflammation,” “oxidative stress,” “reactive oxygen species (ROS),” “oxygen metabolites,” “free radicals,” “redox imbalance,” “phase angle,” and “bioelectrical impedance phase angle.” Articles published in English or Portuguese were selected for critical synthesis, and only significant associations are reported.
Main findings of selected studies
Phase angle and inflammation
Seventeen of 60 search results were identified as relevant studies describing the associations between PhA and inflammation (Table 1). These studies were published between 2003 and 2022 and included healthy adults and clinical populations. Overall, PhA was associated with several direct inflammatory markers, such as CRP, TNF-α, IL-6, interleukin 1-β (IL-1β), interleukin-10 (IL-10), and indirect markers (i.e., malnutrition-inflammation score). Studies included patients with: chronic kidney disease [74–79], hospitalized [39], primary care [80], psoriasis [81], Prader–Willi Syndrome [82], COVID-19 [54]; additionally, studies also included older women [83, 84], women with obesity [85], general population [86, 87], and professional soccer players [88].
Table 1 Summary of the main results of the relationship between phase angle, inflammatory and oxidative stress markers
Authors/ year
Country Population Study design Device type, model (manufacturer, country) BIA protocol Marker PhA / R / Xc Association coefficient p-value Main conclusion Adjustments
Inflammation
Johansen et al., 2003 [74]
US
- N = 54 (18 ♀)
- Patients undergoing HD treatment
- Age: 51.5 ± 17 y
Longitudinal SF-BIA, model NR (RJL Systems®, USA) NR IL 1-β 5.3 ± 1.5° / NR / NR NR 0.004 Negative association with IL1-β Age, sex, race, diabetes status, and dialysis vintage
Demirci et al., 2010 [75]
Turkey
- N = 95 (53 ♀)
- Patients undergoing PD treatment
- Age: 50 ± 13 y
- BMI: 26.0 ± 3.9 kg/m2
- Diabetes: 10.5%
Case-control MF-BIA,
QuadScan 4000 (Bodystat®, Isle of Man)
- Empty peritoneal cavity
- ≥ 15 min in supine position prior to test.
CRP, albumin Men: 5.8 ± 1.4° / NR / NR; women: 5.7 ± 1.0° / NR / NR CRP: r = − 0.330
Albumin: r = 0.440
All p < 0.01 Negative association with CRP and positive association with albumin NR
Stobäus., 2012 [39]
Germany
- N = 777 (410 ♀)
- Hospitalized patients
- Age: 53.6 ± 16.7
- OW/OB: 37.8%
- Malnutrition by SGA: 54.8%
- Malignant tumours: 34%
Cross-sectional MF-BIA, Nutrigard M (Data Input®, Germany) - As described in Kyle et al. [97] CRP 4.91 ± 1.17° / NR / NR Unadjusted analysis:
R = − 0.248
Adjusted analysis:
β = −0.003
All p < 0.0001 Negative association with CRP Regression analysis was adjusted for age, sex, BMI, nutritional status, disease, and inflammation
Beberashvili et al., 2014 [76]
Israel
- N = 91 (34 ♀)
- Patients undergoing HD treatment (all clinically stable)
- Age: 64.0 ± 11.5 y
Cohort study MF-BIA, Nutrigard M (Data
Input®, Germany)
- As described in Kyle et al. [97] IL-6 4.7 ± 1.3° / NR / NR Correlations between changes in IL-6 and changes in PhA: r = − 0.32 0.005 PhA changes over time were associated with lower IL-6 levels Partial correlation adjusted for age, sex, diabetes, dialysis vintage, and cardiovascular disease history
Beberashvili et al., 2014 [79]
Israel
- N = 250 (82 ♀)
- Patients undergoing HD treatment
- Age: 68.7 ± 13.6 y
Cohort study (baseline assessment) MF-BIA, Nutrigard M (Data
Input®, Germany)
- As described in Kyle et al. [97] Albumin, IL-6, MIS 4.7 ± 1.3° / NR / NR NR All p < 0.001 Patients in the lowest PhA tertile (≤ 4.0°) had the highest IL-6 concentrations and MIS values but the lowest albumin concentrations NR
Tsigos et al., 2015 [80]
Italy
- Outpatients (routine check-up)
- Group A: N = 10,416 (1,606 ♀); (−)OW/OB/MUS; Age: 35.7 ± 11.0; BMI: 24.3 ± 2.5 kg/m2
- Group B: N = 58,710 (53,129 ♀); (−)OW/OB (+)MUS; Age: 41.2 ± 12.5; BMI: 23.3 ± 2.6 kg/m2
- Group C: N = 30,445 (15,312 ♀); (+)OW/OB
(−)MUS; Age: 43.1 ± 12.7; BMI: 31.6 ± 5.0 kg/m2
Case-control MF-BIA, BIA-ACC®
(Biotekna srl., Italy)
- Supine position
- Standard placement of electrodes
CRP Group A: 4.89 ± 1.82° / NR / NR, group B: 3.26 ± 1.38° / NR / NR, group C: 3.69 ± 1.51° / NR / NR R2 = 0.759 (negative slope) NR Negatively correlation with CRP NR
Barrea el al., 2016 [81]
Italy
- N = 180 (52 ♀)
- Patients with psoriasis
- Age: median (range), 50 (21 − 65) y
- BMI: 30.2 ± 6.1 kg/m2
- OW/OB: 77.8%
- Diabetes: 22.8%
Case-control SF-BIA, BIA 101 (Akern Bioresearch, Italy) - Supine position
- Limbs slightly apart the body
- Fasting and not exercising for 6 h prior test
- No alcohol intake for 24 h prior test
- Without shoes and socks
- Contact areas scrubbed with alcohol
CRP 5.2 ± 1.0° 504.5 ± 85.8 Ω / 45.4 ± 9.2 Ω r = − 0.283 < 0.001 Negatively correlation with CRP BMI
Sarmento-Dias et al., 2017 [77]
Portugal
- Patients undergoing PD treatment
- Cross-sectional: N = 61 (27 ♀); age = 48 ± 13 y; residual renal function: 95%
- Longitudinal: N = 33 (15 ♀); age: 47.8 ± 12 y
Cross-sectional; longitudinal analysis of a subgroup of patients MF-BIA, InBody S10 (Biospace, Korea) NR CRP, albumin NR for cross-sectional analysis
Longitudinal:
PhA at baseline: 5.6 ± 1.4°
PhA at follow-up: 6.0 ± 1.1°
Cross-sectional:
CRP: β = −0.419
Albumin: β = 0.302
Longitudinal:
CRP: r = − 0.426 (correlation between % change of both variables)
Cross-sectional: CRP: p = 0.003
Albumin: p = 0.047
Longitudinal:
CRP: p = 0.021
Cross-sectional: Negative association with CRP and positive with albumin
Longitudinal: PhA change negatively associated with changes in CRP levels
Cross-sectional: Multivariable analysis including age, ultrafiltration volume, serum urea, residual renal function, fat-free mass, Charlson comorbidity index
Longitudinal: NR
Moreto et al., 2017 [86]
Brazil
- N = 417 (341 ♀)
- General population
- Age: 53.9 ± 9.4 y
- OW/OB: 72%
- Metabolic syndrome: 52%
Cross-sectional SF-BIA, Biodynamics 450, (Biodynamics® Corp., USA) - No vigorous exercises for 24 h prior test
- No alcohol/ caffeinated drinks for 72 h prior test
- Emptied bladder
- Not during menstruation (women)
CRP NR / NR / NR OR = 1.62 for CRP ≥ 3.0 mg/L < 0.05 Higher CRP increased the odds of low PhA Age, sex, BMI, and muscle mass index
Tomeleri et al., 2018 [84]
Brazil
- N = 46 ♀
- Older women
- Age, Int: 71.0 ± 5.4 y; Ctr: 68.8 ± 4.6 y
- BMI, Int: 26.8 ± 4.3 kg/m2; Ctr: 26.9 ± 4.1 kg/m2
RCT MF-BIA, Hydra ECF/ICF 4200 (Xitron Technologies, USA) - Supine position for 5 min prior test
- Euhydration by post-voiding first-morning body weights and urine color
IL-10, TNF-α and CRP Int: 5.4 ± 0.6° / 560.3 ± 56.1 Ω/ 53.3 ± 7.9 Ω; Ctr: 5.6 ± 0.5° / 579.8 ± 71.5 Ω / 57.0 ± 9.8 Ω Unadjusted analysis: TNF-α (r = − 0.71); IL-10 (r = 0.46); CRP (r = − 0.65)
(correlation between % change of both variables)
< 0.01 Negative association with TNF-α and CRP, and positive association with IL-10 NR
Tomeleri et al., 2018 [83]
Brazil
- N = 155 ♀
- Older women
- Age: 67.7 ± 5.7 y
- BMI: 27.0 ± 4.4 kg/m2
- 75% of women had up to two diseases
Cross-sectional MF-BIA, Hydra ECF/ICF 4200 (Xitron Technologies, USA) - Supine position
- Voided bladder 30 min prior test
- Fasting for 4 h prior test
- No strenuous exercise for 24 h
- No alcohol/ caffeinated drinks for 48 h prior test
- Euhydration confirmed by post-voiding first-morning body weights and urine color
- Metals removed
- Exam table isolated from electrical conductors
- BIA calibrated
IL-6, TNF-α and CRP 5.7 ± 0.6° / NR / NR Unadjusted analysis: TNF-α (r = −0.63); IL-6 (r = − 0.55); CRP (r = − 0.33)
Adjusted analysis: TNF-α (β = −0.84); IL-6 (β = −0.97); CRP (β = −0.58)
< 0.05 Negative association with TNF-α, CRP and IL-6 Age, trunk fat mas, appendicular lean soft tissue, and comorbidities
Wang et al., 2019 [78]
China
- N = 144 (50 ♀)
- Patients with CKD
- Age, median (IQR): 53 (38 − 63) y
- BMI, median (IQR): 24.8 (22.6 − 27.4) kg/m2
- CVD: 22.2%
- Diabetes: 33.3%
- Hypertension: 75.7%
Cross-sectional BIS-BIA, BCM
(Fresenius Medical Care, Germany)
- Electrodes attached to
hand and foot (nondominant side)
- Supine position for ≥ 5 min prior test
MIS 5.38 ± 1.25° / NR / NR Unadjusted analysis:
r = − 0.475
Adjusted analysis: β = −0.842
< 0.005 Negative association with MIS. Association remained significant in multivariable analysis. Age, sex, diabetes, handgrip strength, BMI, eGFR, overhydration, albumin, IL 6
Barrea et al., 2020 [82]
Italy
- N = 15 (9 ♀)
- Adult patients with Prader–Willi Syndrome
- Age: 28.0 ± 6.8 y
- BMI: 43.8 ± 10.7 kg/m2
Cross-sectional SF-BIA, BIA 101 (Akern Bioresearch, Italy) - As described in Kyle et al. [97] CRP 4.5 ± 0.8° / 445.6 ± 63.7 Ω / 35.1 ± 9.4 Ω r = − 0.69 0.01 Negative association with CRP Sex, BMI, and waist circumference
Barrea et al., 2021 [87]
Italy
- N = 1855 (1175 ♀)
- General population
- Age, ♂: 34.8 ± 11.3 y; ♀: 34.4 ± 11.2 y
- BMI, ♂: 33.8 ± 8.1; ♀: 35.6 ± 8.6
- OW/OB: 84.9%
Cross-sectional SF-BIA, BIA 101 (Akern Bioresearch, Italy) - As described in Kyle et al. [97] CRP ♂: 6.1 ± 0.8° / 471.5 ± 90.2 Ω / 49.9 ± 10.3 Ω;
♀: 5.6 ± 0.7° / 481.2 ± 85.7 Ω / 46.5 ± 9.4 Ω
Unadjusted analysis:
r = − 0.55
Adjusted analysis: β = −0.35
< 0.0001 Negative association with CRP Age, sex, physical activity, BMI, waist circumference, and PREDIMED score
Cornejo-Pareja et al., 2021 [54]
Spain
- N = 127 (52 ♀)
- Patients with COVID-19
- Age, median (IQR): 69 (59 − 80) y
- BMI, median (IQR): 28.2 (25.7 − 31.8) kg/m2
- OW/OB: 60.6%
- Diabetes: 29.1%
- Dyslipidemia: 40.9%
- Hypertension: 59.1%
- CVD: 20.5%
- Lung disease: 16.5%
- Chronic renal failure: 14.2%
- ICU admission: 18.1%
Cohort study SF-BIA, BIA 101 Whole
Body BIVA (Akern Bioresearch, Italy)
- Standard protocol
- Daily check for accuracy of BIA device
CRP, Albumin Median (IQR): 4.4 (3.2 − 5.4)° / R/height: 302.5 (272.2 − 366.3) Ω / Xc/height: 24.7 (16.3 − 31.1) Ω NR < 0.001 Patients in the lowest standardized PhA quartile had increased inflammation (high CRP, low albumin) NR
Moya-Amaya et al., 2021 [88]
Spain
- N = 18 (0 ♀)
- Professional soccer players
Clinical trial MF-BIA, MC-780 MA (Tanita Corp., Japan) - Fasting for 8 h
- Morning of the competitive match and 36 h after the match
- No moderate/ intense exercise 24 h prior test
- Voided bladder
- Metals removed
CRP 7.69 ± 0.38° / NR / NR r = 0.554 0.017 Positive association with CRP NR
Barrea et al., 2022 [85]
Italy
- N = 260 ♀
- Women with OW/OB
- Age: 37.6 ± 14.1 y
- BMI: 35.7 ± 5.4 kg/m2
- OW/OB: 100%
Pilot clinical study SF-BIA, BIA 101 (Akern Bioresearch, Italy) - As described in Kyle et al. [97] CRP At baseline: 5.5 ± 0.8° / 478.0 ± 73.1 Ω / 46.3 ± 9.4 Ω Correlation between changes in PhA and changes in CRP: r = − 0.16 0.024 Negative association with CRP Age, physical activity, BMI and waist circumference
Oxidative stress
Zouridakis et al., 2016 [89]
Greece
- N = 30 (14 ♀)
- Patients with CKD
- Age: 64 ± 14 y
Case-control SF-BIA, BIA 101 using the Bodygram software (Akern Bioresearch, Italy) NR TAC At baseline: 5.9 ± 0.9° / 500.5 ± 102.9 Ω / 50.8 ± 9.9 Ω r = 0.606 < 0.001 Positive correlation with TAC NR
Tomeleri et al., 2018 [84]
Brazil
- N = 46 ♀
- Older women
- Age: 70.6 ± 5.1 y
- BMI: 26.9 ± 4.2 kg/m2
RCT MF-BIA, Hydra ECF/ICF Model 4200 (Xitron Technologies, USA) - Supine position for 5 min
- Euhydration confirmed by post-voiding first-morning body weights and urine color
FOX, AOCC, and CAT Int: 5.4 ± 0.6° / 560.3 ± 56.1 Ω/ 53.3 ± 7.9 Ω; Ctr: 5.6 ± 0.5° / 579.8 ± 71.5 Ω / 57.0 ± 9.8 Ω Unadjusted analysis: Correlation between changes in PhA and changes in oxidative stress markers: FOX (r = − 0.43); AOPP (r = − 0.55); CAT (r = 0.73)
Adjusted analysis:
AOPP (β = −1.84); CAT (β = 2.03)
< 0.01 Negative correlation with AOPP and positive correlation with CAT Skeletal muscle and body fat
Tomeleri et al., 2018 [83]
Brazil
- N = 155 ♀
- Older women
- Age: 67.7 ± 5.7 y
- BMI: 27.0 ± 4.4 kg/m2
- 75% of women had up to two diseases
Cross-sectional MF-BIA, Hydra ECF/ICF 4200 (Xitron Technologies, USA) - Supine position
- Voided bladder 30 min prior test
- Fasting for 4 h prior test
- No strenuous exercise for 24 h
- No alcohol/ caffeinated drinks for 48 h prior test
- Euhydration confirmed by post-voiding first-morning body weights and urine color
- Metals removed
- Exam table isolated from electrical conductors
- BIA calibrated
CAT, SOD and TRAP 5.7 ± 0.6° / NR / NR Partial correlations: CAT (r = 0.48); SOD (r = 0.31) and TRAP (r = 0.30) < 0.01 Positive correlation with CAT, SOD and TRAP Age, trunk fat mass, appendicular lean soft tissue, and comorbidities
Venancio et al., 2021 [90]
Brazil
- N = 39 (32 ♀)
- Patients undergoing bariatric surgery
- Age range: 18 − 60 y
- BMI: ≥35 kg/m2
- Diabetes: 41%
- Hypertension: 61.5%
- Dyslipidemia: 40.9%
Cohort study SF-BIA, Biodynamics 450, (Biodynamics® Corp., USA) - As described for Kyle et al. [97] AOPP Median at baseline: RYGB = 7.0 (6.6–7.5)° /
410.6 (339.2–455.9) Ω / 49.9 (42.9–57.8) Ω;
SG = 6.9 (6.6–7.2)° / 465.8 (456.0–517.2) Ω / 55.6 (51.7–61.0) Ω
Correlations between changes in PhA and AOPP: r = − 0.549 0.041 Negative correlation with AOPP NR
Age, body mass index, and phase angle values are mean ± SD, unless otherwise specified. Abbreviations: (−), without; (+), with; ♀, female; ♂, male; AOPP, advanced oxidation protein products; BIA, bioelectrical impedance analysis; BMI, body mass index; CAT, catalase; CKD, chronic kidney disease; CRP, C-reactive protein; Ctr, control group; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; FOX, ferrous oxidation-xylenol orange; HD, hemodialysis; ICU, intensive care unit; IL-10, Interleukin 10; IL-6, Interleukin-6; IL 1-β, interleukin 1-β; Int, intervention group; IQR, interquartile range; MF-BIA, multi-frequency bioelectrical impedance analysis; MIS, malnutrition inflammation score; MUS: medically unexplained symptoms; N, sample size; NR, not reported; OB, obesity; OR, odd ratio; OW, overweight; PD, peritoneal dialysis; PhA, phase angle; R, resistance; RCT, randomized controlled trial; RYGB, roux-en-y gastric bypass; SF-BIA: single-frequency bioelectrical impedance analysis; SG, sleeve gastrectomy; SGA, Subjective Global Assessment; SOD, superoxide dismutase; SOFA, Sequential Organ Failure Assessment; TAC, total antioxidant capacity; TNF-α, tumor necrosis factor‐α; TRAP, radical-trapping antioxidant potential; Xc, reactance
PhA was negatively associated with CRP in 12 of 13 studies. Strength of these correlations varied among the studies, with coefficients ranging from r = − 0.69 to − 0.16, except for one study reporting a positive correlation (r = 0.55) [88]; higher CRP also increased the odds of low PhA. The most extensive study conducted to date found a high negative correlation between PhA and CRP in 99,571 individuals of varied BMI visiting medical centres for routine check-up with or without medically unexplained symptoms [80]. The linear regression model showed that CRP explained 75.9% of PhA variability [80]. Tomeleri et al. also explored the association of PhA with CRP in two studies in older women. One of these studies was an RCT (N = 46), and percent changes in CRP showed moderate negative correlations with percent changes in PhA [84]. The other study had a cross-sectional design (N = 155) and also showed negative correlations between PhA and CRP; this association was maintained in multivariate analysis controlling for age, trunk fat mass, appendicular lean soft tissue, and comorbidities [83].
In addition to reporting a moderated negative correlation between CRP and PhA in both males and females, another article also proposed PhA threshold values to predict high high-sensitivity CRP levels (hs-CRP, above sex-specific, data-driven median values) in 1855 healthy individuals, with most having overweight or obesity (84.9%) [87]. However, their proposed ROC derived thresholds to predict the highest hs-CRP levels (5.5° for males and 5.4° for females) [87] were notably higher than mean values for older adults, as they are associated with the sex and age distribution of the population. This would overestimate the prevalence of high hs-CRP levels. As such, the use of PhA cut-offs values in this context are discouraged. Other studies confirmed negligible to moderate negative associations between PhA and CRP in adults, mostly with excess body weight [85, 86]. These negative associations of similar strength between PhA and CRP were also found in clinical populations, including peritoneal dialysis [75, 77], hospitalized patients (54.8% with malnutrition, and 34% with cancer) [39], psoriasis [81], Prader-Willi Syndrome [82], and COVID-19 [54].
Unexpected results (i.e., positive correlation) between PhA and CRP were observed in one study in athletes with very high (highest among included studies) PhA values (7.69 ± 0.38°) [88]. Although these athletes (healthy soccer players) experienced post exercise-induced muscle damage as an acute recovery response, they were not actually injured. The study also had a small sample size (N = 18) and differences between pre- and post-matches were not significant, yet mean PhA values decreased and CRP increased [88].
Other inflammatory markers were also consistently associated with PhA values. Four of 5 studies showed that higher interleukin concentrations (IL 1-β and IL-6) were associated with lower PhA in patients undergoing maintenance hemodialysis [74, 76, 79] and older women [83]. In contrast, changes in PhA positively correlated with changes in IL-10 concentration (r = 0.46) in older women, mostly with a high BMI and comorbidities [84]. These studies in older women also reported moderate negative correlations (r = − 0.71 to − 0.63) between TNF-α and PhA [83, 84]. Albumin was another inflammatory marker explored, and 4 of 4 studies found a low positive association between PhA and albumin levels in patients undergoing peritoneal dialysis [75, 77], maintenance hemodialysis [79], and COVID-19 [54] treatment. Furthermore, higher malnutrition inflammation score was associated with lower PhA in patients with chronic kidney disease [78] and undergoing hemodialysis treatment [79].
Phase angle and oxidative stress
Four of 16 search results were identified as relevant studies describing the associations between PhA and markers of oxidative stress (Table 1). Our group published a review on the topic in 2021 [18], and the current updated search revelated that no new studies have been conducted since then. Overall, PhA was significantly associated with markers of oxidative stress, highlighting the link between inflammation and oxidative stress with PhA [18]. For instance, Zouridakis et al. were the first to observe a moderate positive correlation between PhA and total antioxidant capacity in 30 patients with chronic kidney disease [89]. Tomeleri et al. also found that PhA positively correlated with antioxidants, such as catalase (low to high correlations), superoxide dismutase (low correlation), and total radical trapping antioxidant (low correlation) in older women, mostly with high a BMI and comorbidities [83, 84]. Conversely, PhA was negatively correlated with ferric-xylenol orange (low correlation) and advanced oxidation protein products (moderate correlation) [83, 84]. The most recent study also showed a moderate negative correlation between PhA and oxidative protein damage (caused by advanced oxidation protein products) in adults undergoing bariatric surgery [90].
Additional points of included studies
As expected, PhA varied according to the population and disease studied as well as the BIA device used to acquire the bioimpedance data, with mean or median values ranging from 3.26° to 7.69° (Table 1). The lowest mean PhA value was found in outpatients of normal weight with medically unexplained symptoms [80]. Although the study by Cornejo-Pareja et al. did not reported the lowest PhA value among the select studies, it showed that patients with COVID-19 in the intensive care unit (ICU) or hospital ward also had very low PhA values (IQR : 3.2 − 5.4°) [54], 16 of which died. In fact, non-survivors of COVID-19 had lower PhA values than survivors (median difference = − 1.7°, p < 0.001) and PhA predicted mortality in adjusted models for several confounders (Hazard ratio = 3.912, 95% confidence interval = 1.322 − 11.572). As mentioned above, the study conducted in a cohort of professional soccer players reported the highest PhA value (7.69 ± 0.38°) [88].
Some studies (7 of 16) failed to adjust for confounding variables, and there was no standardization of which variables to include when adjustments were considered (Table 1). When conducted, most adjustments included age and/or sex as confounding variables. Additional variables were BMI, handgrip strength, physical activity status, diabetes and overall comorbidities, waist circumference, albumin concentration or body composition parameters (i.e., ECW, muscle mass index, body fat, trunk fat and appendicular lean soft tissue), among others. Although some confounding variables are specific to the study population, others determine PhA, such as age, sex, and body composition parameters, as previously addressed. For instance, in a population of patients with chronic kidney disease, Wang et al. adjusted their analyses for estimated glomerular filtration rate and overhydration, in addition to age, sex, and BMI, handgrip strength and inflammatory markers [78].
As expected, we also observed the use of diverse BIA devices, which ranged from single frequency, dual-frequency, multi-frequency, and spectroscopy, and from different brands (Table 1). This is important given the potential variation in PhA values among devices. For instance, while comparing several BIA devices, Genton et al. found different relationships between PhA and mortality, highlighting the need to standardize device selection [91]. Inconsistencies were also observed regarding the protocol applied for BIA assessment (Table 1). Most studies followed a standardized protocol for BIA assessment (i.e., electrodes and participant position). Only a few described pre-study visit procedures, such as instructions for not performing vigorous physical activity, fasting, avoiding alcohol and/or caffeinated drinks before testing, and previous emptying of the bladder. These are certainly important for reliability [92]. Furthermore, seven studies reported followed The European Society for Clinical Nutrition and Metabolism (ESPEN) guidelines for BIA analysis [25]. Only one study considered participants’ menstrual cycle, one reported previous BIA calibration, and none reported smoking status (Table 1).
Utility of phase angle in interventional studies
In the light of current literature, PhA appears to be a promising inflammatory marker. As such, it may be a relevant clinical outcome and a helpful tool to assess and monitor the effectiveness of interventions to improve inflammation status. Although only a few studies have explored the role of different interventions on PhA and inflammation status, results are promising. Nevertheless, these findings should be interpreted considering the technical variability of the PhA measurement, which is device- and procedure-specific. An overview of interventional studies conducted, and their respective findings are shown in Table 2.
Table 2 Main results of the interventional studies included in the review
Authors/ year
Country Population
Study design Device BIA protocol Intervention Control Intervention effects on PhA Intervention effects on inflammation Conclusion
Roberts et al., 2017 [93]
UK
- N = 14 (6 ♀)
- Physically active individuals
- Age: 31 ± 6 y
Crossover RCT
SF-BIA, Impedimed DF50 (Impedimed, USA)
Reliability NR
- No
strenuous exercise ~ 48 h prior test
- No caffeinated
products ~ 48 h prior test
- ~3–4 h fasting prior test
- Supine
- PROHIGH: 2.9 g. kg− 1.d− 1 of PRO for 10 days
- Resistance exercise on days 8–10 (T1-T3)
- PROMOD: 1.8 g. kg− 1.d− 1 of PRO for 10 days
- Resistance exercise on days 8–10 (T1-T3)
- No difference in PhA change from baseline to follow-up between groups
- PROHIGH had greater PhA at T3 than PROMOD (MD = + 0.18°, p = 0.012)
- No difference in TNF-α change from baseline to follow-up between groups
- No difference in TNF-α between groups at follow-up
PhA values were maintained at T3 for the group with higher protein intake. The exercise protocol and diet did not influence TNF-α values
Tomeleri et al., 2018 [84]
Brazil
- N = 46 ♀
- Older women
- Age: 70.6 ± 5.1 y
BMI: 26.9 ± 4.2 kg/m2
RCT
MF-BIA, Hydra ECF/ICF 4200 (Xitron Technologies, USA)
Reliability NR
- Supine position for 5 min
- Euhydration confirmed by post-voiding first-morning body weights and urine color
- Same technician performing pre-/post-tests
− 12 weeks of resistance training under professional supervision performed 3 times per week (45–50 min per session)(TG) - No physical exercise of any type performed for 12 weeks (CG) - TG had a greater PhA than CG at follow-up (MD = + 0.4°, p < 0.05)
- TG had a greater PhA at follow-up than at baseline (MD = + 0.4°, p < 0.05)
- CG had a decrease in PhA from baseline to follow-up (MD = − 0.2°, p < 0.05)
- TG had a lower TNF- α (MD = − 0.3, p < 0.05), IL-6 (MD = − 1.2, p < 0.05) and CRP (MD = − 2.4, p < 0.05) and a greater IL-10 (MD = + 10.3, p < 0.05) than CG at follow-up
- TG had a decrease in TNF-α (MD = − 0.5, p < 0.05), IL-6 (MD = − 0.5, p < 0.05), and CRP (MD = − 0.7, p < 0.05) and an increase in IL-10 (MD = + 0.5, p < 0.05) from baseline to follow-up
12 weeks of resistance training improved PhA and inflammation
Di Renzo et al., 2019 [94]
Italy
- N = 44 (10 ♀)
- Head and neck squamous carcinoma (stage III)
- Age: 65.48 ± 12.66 y
Clinical trial
SF-BIA, BIA 101 S (Akern/RJL Systems, Italy)
Reliability NR
NR - Enteral standard nutrition for days 0–3 (ESN); 1500 kcal/d, 43% CHO, 27% PRO, 30% fat, 14 g fibre
- Enteral immunonutrition for days 4–8 (EIN); 1500 kcal/d, 53% CHO, 22% PRO, 25% fat, < 3 g fibre, 9.15 MCT)
- Oral standard diet (OD) for 8 days; 2448.45 kcal/d, 50% CHO, 17% PRO, 33% fat, 32–35 g fibre - No difference in PhA change between OD and ESN at day 3
- EIN had a greater PhA than OD at day 8 (MD = + 0.75, p = 0.045)
- No difference in leukocyte, neutrophils, lymphocytes, albumin, transferrin, and CRP change between OD and ESN at day 3 and between OD from days 0–8
- EIN trended towards a lower transferrin (MD = − 30.25, p = 0.050) and CRP (MD = − 6.64, p = 0.066) than OD at day 8, but no difference in leukocyte, neutrophils, lymphocytes and albumin change
- EIN had a higher transferrin than ESN (MD = + 39.25, p < 0.05), but no difference in leukocyte, neutrophils, lymphocytes, albumin, transferrin, and CRP
- ESN had higher lymphocytes at day 3 than day 0 (MD = + 0.33, p < 0.05), but no difference in leukocyte, neutrophils, albumin, transferrin, and CRP
Immunonutrition treatment improves PhA and inflammation more than an oral diet and standard enteral nutrition
Moya-Amaya et al., 2021 [88]
Spain
- N = 18 (0 ♀)
- Professional soccer players
Clinical trial
MF-BIA, MC-780 MA (Tanita Corp., Japan)
Reliability NR
- Overnight fast of ≥ 8 h
- Tests performed between 8am and 10am
- No moderate or intense exercise 24 h prior test
- Voided bladder
- Metals removed
- Standing erect
- Same technician performing pre-/post-tests
- Performed according to manufacturer guidelines
- Players (except goalkeepers) who played > 45 min were evaluated in the morning prior to the start of and 36 h after a competitive match during the first half of the season NA - No difference in PhA change from prior to and 36 h after a match - No difference in CRP and IL-6 changes from prior to and 36 h after a match 36 h of intense exercise did not affect PhA nor CRP
Barrea et al., 2022 [85]
Italy
- N = 260 ♀
- Women with OW/OB
- Age: 37.6 ± 14.1 y
- BMI: 35.7 ± 5.4 kg/m2
- OW/OB: 100%
Pilot clinical trial
SF-BIA, BIA 101 (Akern Bioresearch, Italy)
Reliability for intraday (R < 2%; Xc < 2.5%) and interday (R < 3.3%, Xc < 2.8%) tests assessed using same observer.
Coefficient of variation of repeated measurements at 50 kHz assessed in 10 females using same observer: R = 1.4% and Xc = 1.3%.
- Same device and technician performing pre-/post-tests
- Supine
- Limbs slightly apart
- No food, drink, or exercise 6 h prior to test
- No alcohol 24 h prior to test
- Voided bladder
- Very low-calorie ketogenic diet for 31 d using a commercial weight-loss program, replacement meals with a biological value of 110, a multivitamin, and saline supplements
− 13% CHO (< 30 g/d), 43% PRO (1.2–1.5 g/kg IBW), 44% fat (including 10 g/d of EVOO)
− 30 min of moderate physical activity 3 times per week
NA - Participants had a greater PhA at follow-up than at baseline (MD = + 0.5°, p < 0.001) - Participants had a lower hs-CRP at follow-up than at baseline (MD = − 1.7, p < 0.001) 31 days of a low-calorie ketogenic diet promoted a significant reduction in patient inflammation and improved PhA
Abbreviations: ♀, female; BIA, bioelectrical impedance analysis; BMI, body mass index; CHO, carbohydrates; CG, control group; CRP, C-reactive protein; EIN, enteral immunonutrition; ESN, enteral standard nutrition; EVOO, extra virgin olive oil; hs-CRP, high-sensitivity CRP; IBW, ideal body weight; IL-10, interleukin-10; IL-6, interleukin-6; MCT, medium chain triglycerides; MD, mean/median difference; MF-BIA, multi-frequency BIA; N, sample size; NR, not reported; OD, oral diet; PhA, phase angle; PRO, protein; R, resistance; RCT, randomized controlled trial; SF-BIA, single-frequency BIA; TG, training group; TNF-α, tumor necrosis factor-α; Xc, reactance;
Robert and colleagues conducted the first study evaluating the role of a 10-day high protein diet to support improved markers of muscle damage (i.e., PhA and TNF-α) after extenuating exercise in 14 resistance trained adults [93]. Although PhA was higher in the group receiving 2.9 g∙kg− 1∙d− 1 versus 1.8 g∙kg− 1∙d− 1 at the end of the intervention (mean difference = + 0.18°, p = 0.012), no intervention effect was observed on both PhA and inflammation levels.
Di Renzo et al. explored the effects of immunonutrition compared to a control standard oral diet on PhA and inflammatory response in patients with advanced stage head and neck cancer [94]. At the end of treatment (day 8), participants who received immunonutrition had a greater PhA (median difference = +0.75°, p = 0.045) and higher pre-albumin levels (median difference = 3.35 mg/L, p = 0.048) than controls. From days 4 to 8, the immunonutrition group increased PhA (Δ = +0.3°, p = 0.045), pre-albumin (Δ = +4.5 mg/L, p < 0.05), and transferrin (Δ = +39.3 mg/dL, p < 0.05); no significant changes from baseline or day 3 were observed in the standard oral diet group for these inflammatory markers. Although the intervention had no effect on CRP levels, the authors highlighted the potential use of PhA to monitor nutritional and biochemical status [94].
Using exploratory dietary approaches, Barrea et al. conducted a pilot clinical trial to evaluate the effect of a very low-calorie ketogenic diet in improving PhA and inflammation status in 260 women with overweight or obesity [85]. The diet (< 800 kcal/ day; 1.2–1.5 g∙kg− 1 of ideal body weight∙d− 1 g; 44% lipids, including 10 g/d extra virgin olive oil) was followed for 31 days [85]. The authors reported an improvement in PhA from 5.5 ± 0.8° to 6.0 ± 0.8° and in hs-CRP from 3.5 ± 4.1 to 1.8 ± 2.5 mg/L (p < 0.001) after the intervention (Table 2). This was the only study that reported reliability measures, with a coefficient of variation for repeated measures at 50 kHZ of 1.3% for Xc and 1.4% for R. Although it is unclear how the variations in individual PhA components could have reflected the coefficient of variation for PhA values, it is possible that small changes in PhA could be attributed to measurement errors and not to the true intervention effect per se.
Tomeleri et al. explored the effects of a 12-week resistance training program in a sample of 46 older women [84]. They reported a significant improvement in several inflammatory markers (CRP, IL-6, TNF-α, and IL-10) and in PhA values [84]. Conversely, Moya-Amaya et al. described no effects on PhA and CRP levels after 36 h of a competitive soccer math [88]. Despite expected, increased muscle damage was not observed in the athletes [95]. No changes were observed, although this could be explained by a return to baseline levels after 36 h, likely associated to athletes’ greater muscle mass and strength [37].
Other applications / segmental analysis
An alternative approach of BIA use to detect cellular abnormalities, injury, and therefore inflammation, is its segmental application, which can be potentially used to evaluate cellular health at a localized level. According to Lukaski & Moore., localized BIA is a sensitive technique to determine alterations in bioelectrical components (R, Xc, and PhA), which can be used to assess changes in soft-tissue hydration, cell membrane integrity, and structure in a specific body area [96]. Localized BIA has been used to evaluate specific body segments such as arms, trunk, and legs and has been suggested over whole-body analyzes in the presence of specific conditions, such as cardiac insufficiency, liver or kidney failure, neuromuscular diseases, or limb amputation [97].
To the best of our knowledge, no studies have been conducted to evaluate the presence of localized inflammation using the segmental approach. However, insights related directly or indirectly to inflammation have been explored including muscle lesions, wound healing, and cancer diagnoses or its severity. Lukaski & Moore examined the application of localized single-frequency BIA(Quantum IV; RJL Systems, Clinton Township, MI) for patients with lower leg wounds by placing four electrodes around the wound, and showed PhA as a healing indicator [96]. Additionally, PhA assessed by localized BIA has the potential to detect neuromuscular disease, changes in skeletal muscle, injury and lesions [98–102]. In patients with neuromuscular disease, Rutkove et al. reported very low segmental PhA values (using several electrodes placed in line over the thigh for tetrapolar measures) among those with advanced disease state and values close to the healthy range (control subjects) during illness remission [102]. Freeborn & Fu demonstrated that localized PhA, and its components (R and Xc), reduced with increased exercise induced fatigue, using four electrodes placed on the lateral side of the biceps and a multifrequency BIA (E4990A Impedance Analyzer; Keysight Technologies, Santa Rosa, CA) [100]. Although muscle swelling was not evaluated in this study, the authors speculated that it might have caused R values to drop. Future investigations into the connection between muscle swelling and PhA should also assess potential confounders, such as changes in blood flow, interstitial fluid, and skin blood flow and temperature. Using four electrode placed on the calf and proximal hamstring muscles and a single-frequency BIA (BIA-101; AKERN-Srl, Florence, Italy), localized PhA measures agreed with the diagnosis of muscle injury severity assessed by magnetic resonance imaging [98].
Two studies explored the effectiveness of localized BIA and its PhA as a screening and prognostic tool for patients with prostate cancer [103, 104]. Tyagi et al. demonstrated that low PhA allowed discriminating prostate cancer patients using BIA electrodes on the right upper and right lower limb and a multifrequency BIA (QuadScan 4000 (Bodystat®; Isle of Man) [103]. PhA was lower in patients with prostate cancer (compared to matched controls) and worse comparing more advanced versus earlier disease stages [103]. In the other study, four electrodes were placed around the prostate area and a single frequency BIA (BIA 101 ASE®; Akern Srl, Italy) was used to measure PhA values in individuals with prostate cancer, benign prostatic disease, and healthy volunteers. Although Xc and R values differed between studied groups, PhA had a good sensitivity (0.925) but a poor specificity (0.200) to diagnose patients with prostate cancer [104]. Although none of these studies have evaluated the presence of inflammation, it is well known that the inflammatory state is associated with cancer, muscle damage and wound healing [3, 105, 106]. In that sense, it is expected that segmental PhA could also reflect inflammatory status, assessing localized inflammation. Further research is needed to confirm the role of segmental PhA to screen for inflammation in patients with cancer.
Localized PhA seems to be a potential technique to evaluate the health condition of a specific body part, also reflecting the impact of changes in tissue physiology on changes in tissue’s electrical properties. However, it is still unclear whether localized PhA is superior to whole-body PhA. Obayashi et al. compared segmental and whole-body PhA in adolescent athletes using a multifrequency BIA (Body S10 Body Water Analyzer; InBody Co., Seoul, Korea) with eight electrodes placed on five body segments (right and left arms, trunk, and right and left legs), and found that localized PhA was related to the performance of corresponding parts of the body (except trunk, which was excluded from the analysis), suggesting its use in association with whole-body PhA to assess local physical fitness levels [107]. Conversely, Jiang et al. concluded that PhA in the trunk estimated with a segmental BIA (InBody S10, InBody, Seoul, Korea) was underestimated compared to measures obtained by a tetrapolar, single-frequency BIA (Quantum IV, RJL Systems, Clinton Township, MI) in older adults [108].
Strengths and limitations of current literature
There is consistent evidence suggesting PhA can be used as a screening tool to detect inflammation, and several factors support this association. Studies were conducted in people with various medical conditions (chronic kidney disease, COVID-19, hospitalized and intensive care unit patients, obesity, psoriasis, general population, older people, and athletes), and across the globe (United States, Germany, Brazil, Israel, Italy, Portugal, Spain, Turkey, China, and Greece) (Table 1). The association between PhA and inflammation was explored using different inflammatory markers (CRP, TNF-α, IL-6, IL-1β and IL-10), presented in various designs (cross-section, cohort, case-control and clinical trials), and direction of associations were consistent among studies despite variations in the strength of associations. Furthermore, PhA may also provide supplemental clinical information that could be helpful in health care settings as PhA can be a prognostic marker for a variety of poor outcomes [37, 49, 109, 110].
Unfortunately, results hereby presented are not generalizable. The clinical significance of PhA as a predictor of inflammation and oxidative stress in a more diverse population, particularly with less severe conditions, has yet to be explored. We have also noted the need for standardized procedures during BIA assessment. Although some argue that PhA cut-offs to identify inflammation are needed, these cut-offs would have lower accuracy when used in populations that differ in age, sex, BMI, body composition, and ethnicity. Future research should therefore explore the utility of PhA in evaluating inflammatory changes and in determining the efficacy of nutritional and exercise interventions to improve inflammation and oxidative stress, as results are still scarce. Moreover, future research should assess the biological importance of localized PhA measurement and whether it is superior to the whole-body technique.
Conclusion
Inflammation and oxidative stress are intimately related and can cause tissue damage and lead to several chronic diseases. PhA is a feasible tool for assessing cellular health and integrity and could be a potential marker of inflammation and oxidative stress. Lower PhA was consistently associated with higher levels of CRP, interleukins, and TNF-α as well as lower albumin levels, despite heterogeneity in populations, study designs, and BIA devices. PhA is an affordable assessment, reliable, and non-invasive, which might be an efficient measure to be used in clinical settings to detect inflammation, where faster and simpler alternatives are urgently needed. Future studies should explore the relationship between PhA, inflammation, and oxidative stress using single and other multifrequency devices and standardized BIA protocols. Studies should also include large populations of varied age and health status.
Acknowledgements
The authors acknowledge Leticia Ramos da Silva and Lucas Yoshio Matsuo Hashimoto for their assistance with the graphical illustration, and Anne Caretero for her assistance updating Tables 1 and 2.
Declarations
Competing interests
CEO has received honoraria from Abbott Nutrition. MCG has received paid consultancy from Abbott Nutrition, Nutricia, and Nestlé Brazil. CMP has previously received honoraria and/or paid consultancy from Abbott Nutrition, Nutricia, Nestlé Health Science, AMRA medical, and Pfizer. BRS, JMFS, MSM, and AAJ have nothing to disclose.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 36474107 | PMC9735064 | NO-CC CODE | 2022-12-14 23:28:32 | no | Rev Endocr Metab Disord. 2022 Dec 7;:1-20 | utf-8 | Rev Endocr Metab Disord | 2,022 | 10.1007/s11154-022-09775-0 | oa_other |
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Air Qual Atmos Health
Air Qual Atmos Health
Air Quality, Atmosphere, & Health
1873-9318
1873-9326
Springer Netherlands Dordrecht
1294
10.1007/s11869-022-01294-w
Article
Impact of the COVID-19 pandemic on air pollution from jet engines at airports in central eastern China
Bao Danwen 1
http://orcid.org/0000-0002-0149-6939
Tian Shijia [email protected]
1
Kang Di 2
Zhang Ziqian 1
Zhu Ting 1
1 grid.64938.30 0000 0000 9558 9911 College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Jiangning District, No. 29, Jiangjun Avenue, Nanjing, 211106 Jiangsu Province China
2 grid.17635.36 0000000419368657 Department of Industrial and Systems Engineering, University of Minnesota, 2818 Como Avenue S.E, Minneapolis, MN 55414 USA
5 12 2022
119
14 6 2022
25 11 2022
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Aircraft engine emissions (AEEs) generated during landing and takeoff (LTO) cycles are important air pollutant sources that directly impact the air quality at airports. Although the COVID-19 pandemic triggered an unprecedented collapse in the civil aviation industry, it also relieved some environmental pressure on airports. To quantify the impact of COVID-19 on AEEs, the amounts of three typical air pollutants (i.e., HC, CO, and NOx) from LTO cycles at airports in central eastern China were estimated before and after the pandemic. The study also explored the temporal variation and the spatial autocorrelation of both the emission quantity and the emission intensity, as well as their spatial associations with other socioeconomic factors. The results illustrated that the spatiotemporal distribution pattern of AEEs was significantly influenced by the policies implemented and the severity of COVID-19. The variations of AEEs at airports with similar characteristics and functional positions generally followed similar patterns. The results also showed that the studied air pollutants present positive spatial autocorrelation, and a positive spatial dependence was found between the AEEs and other external socioeconomic factors. Based on the findings, some possible policy directions for building a more sustainable and environment-friendly airport group in the post-pandemic era were proposed. This study provides practical guidance on continuous monitoring of the AEEs from LTO cycles and studying the impact of COVID-19 on the airport environment for other regions or countries.
Keywords
Aircraft engine emission
Coronavirus pandemic
Hydrocarbons
Carbon monoxide
Nitrogen oxides
Spatial dependence
http://dx.doi.org/10.13039/501100012226 Fundamental Research Funds for the Central Universities NS2020047 Bao Danwen http://dx.doi.org/10.13039/501100003405 Foundation of the Graduate Innovation Center, Nanjing University of Aeronautics and Astronautics xcxjh20210705 Tian Shijia
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pmcIntroduction
The civil aviation industry has witnessed decades of steady growth until the outbreak of the novel coronavirus disease 2019 (COVID-19). While air travel has made it possible for passengers to reach more remote destinations in less time and at affordable costs, it has also contributed to the global spread of infectious diseases (Sun et al. 2020; Linka et al. 2021). To slow down the transmission of COVID-19, up to 194 countries have implemented measures to restrict individuals’ mobility in response to the pandemic (Lee et al. 2020). The heavy travel restrictions, together with the unprecedented decrease in passenger demand, have adversely impacted the civil aviation industry (Dube et al. 2021). Airlines have placed numerous aircraft types into temporary storage to avoid significant financial loss from flying empty planes (Adrienne et al. 2020). And many airports had to close their runways to make room for aircraft parking or just significantly limited their operations, awaiting traffic to pick up again. Consequently, there was a substantial decline in domestic and international passenger flights worldwide (Sun et al. 2021). According to International Civil Aviation Organization (ICAO 2020), the overall number of passengers by April had fallen 92% from 2019 levels, an average of a 98% drop-off in international traffic and 87% in domestic air travel. Evidence showed that the decline in air passenger traffic caused by COVID-19 was far more significant than that caused by other effects in literature (Xue et al. 2021b). Although flight suspensions negatively affect many aspects of society, it is expected to have some positive effects on the environment.
One of the most prominent influences that aviation has on the environment is air pollution (Brasseur et al. 2016). Aircraft engines exhaust gases and particles, including carbon monoxide (CO), nitrogen oxides (NOx), sulfur oxide (SOx), hydrocarbons (HC), particulate matter (PM), and so forth (Kurniawan and Khardi 2011). Conventionally, the operations of aircraft are divided into two phases: The landing and takeoff (LTO) phase, which occurs at an altitude below 3000 ft, and the cruise phase, which takes place at an altitude above 3000 ft (Kurniawan and Khardi 2011). Aircraft engine emissions (AEEs) at the cruising altitude are directly released into the upper troposphere and the lower stratosphere, which mainly impact climate change (Brasseur et al. 2016), while AEEs from LTO cycles are primarily associated with the deterioration of air quality at the ground level (Amato et al. 2010; Hsu et al. 2012). Although aircraft emits gases and particles primarily during the cruise phase, AEEs from LTO cycles have aroused increasing public concern in recent years due to the following reasons: (i) In the year 2019, researchers from the Massachusetts Institute of Technology have uncovered that aviation causes twice as much damage to air quality as it does to the climate (Lang 2019); (ii) AEEs from LTO cycles have a more direct effect on human health, local eco-system, and cultural heritage, which are closely related to the living standards of human beings (Song et al. 2019; Aygun and Caliskan 2021; Głowacki et al. 2022). Therefore, the estimation of AEEs from LTO cycles has been recognized as an important issue for developing strategies as future guidelines for airport environmental sustainability.
It is widely acknowledged that 2020 is an unusual year for the civil aviation industry as the COVID-19 outbreak is the first major global pandemic in the era of passenger jet air transportation since the late 1950s (Elias 2020). Accordingly, this study intends to explore the positive environmental impacts of travel restrictions from the perspective of AEEs at the ground level. Although several researches have focused on the estimation and analysis of AEEs from LTO cycles at both the local scale (Yılmaz 2017; Kuzu 2018; Tokuslu 2020) and the regional scale (Kesgin 2006; Hu et al. 2020; Yu et al. 2021), the research on AEEs from LTO cycles in the context of the COVID-19 pandemic is still scarce. Furthermore, there has never been any analysis of the relative change in air pollution at airports between the COVID-19 era and the pre-COVID-19 era, either from a temporal or spatial perspective. In addition, the spatial spillover effect of AEEs and the spatial association with local socioeconomic factors have not been studied yet. Therefore, we explore this area to better comprehend the disparities in the variation patterns of AEEs and its correlations with both COVID-19-related factors and socioeconomic factors.
This paper aims to answer the following research questions: (i) How do the relative changes of the studied AEEs distributed temporally and geographically? And how do the spread of COVID-19 and pertinent policy responses impact the variation patterns? (ii) Does the variation of AEEs at airports with similar characteristics and functional positions follow a specific pattern? (iii) Are AEEs at airports in the studied region spatially dependent? (iv) Does spatial association exist between the socioeconomic status of cities nearby and the AEEs at local airports? To answer these questions, we first analyzed the distribution patterns of relative change on both geographical and temporal scales. Using a modified k-means clustering algorithm, the studied airports were then categorized into groups based on their AEE variation characteristics. Furthermore, some spatial statistical indicators, including univariate and bivariate Moran’s Index (i.e., Moran’s I), were calculated to assess the existence of spatial autocorrelation and spatial association. Based on the results and discussions, the corresponding policy implications were provided.
The remainder of this study is organized as follows. In the second section, relevant literature is briefly reviewed. The third section presents the geographical scope, data sources, variables, and methods. The results are presented and discussed in the fourth section. The fifth section suggests the policy implications. The last section provides the main conclusions and recommendations for future research.
Literature review
A number of studies have investigated the impacts of COVID-19 on transport-related air pollution. Table 1 summarizes the main findings in existing studies on the effects of COVID-19 on traffic-caused air pollution. Compared to road and marine traffic, air pollution caused by air traffic received comparatively less attention. The majority of the studies, which measured the AEEs at airports, were conducted before the outbreak of COVID-19. Yılmaz (2017) estimated the HC, CO, and NOx from the LTO cycle at Kayseri Airport, Turkey. Similar research was also conducted at Los Angeles International Airport (Shirmohammadi et al. 2017), Detroit Metropolitan Airport (Ashok et al. 2017), Atatürk International Airport (Kuzu 2018), and Georgian International Airport (Tokuslu 2021). However, these studies mainly focused on investigating the distribution of total LTO emissions for each operation mode at a single airport. As for the regional multi-airport scale, Song and Shon (2012) calculated the emissions of greenhouse gases at four major international airports in Korea. It was found that monthly and daily emissions do not vary significantly. Yu et al. (2021) analyzed the trend of AEEs at some airports in mainland China from 1970 to 2017 and found that the average emission per passenger has declined for the duration. Bao et al. (2021) revealed some simple regional distribution of AEEs from LTO cycles during the pandemic but failed to thoroughly compare the AEEs at airports in 2020 to the year when the pandemic had not yet occurred. Although these studies have provided valuable insights for investigating the ground-level AEEs from a regional cooperative perspective, they rarely consider the spatial interaction and spatial spillover effects within the region and how their effects on the distribution of emission quantity (EQ) and emission intensity (EI, i.e., emission per passenger). In addition, to the authors’ knowledge, the spatial correlation between AEEs from LTO cycles and other socioeconomic factors has not been examined using spatial econometric methods in any literature.Table 1 Literature on the effects of COVID-19 on traffic-caused air pollution
Study Type of traffic Major finding
Xiang et al. (2020) Road Due to the stay home order (SHO) restriction, the median PM2.5, NOx, and CO levels near the freeway in downtown Seattle significantly declined by 33%, 30%, and 17%, respectively
Wu et al. (2021) Road CO declined by 28.8% at roadside stations in Shanghai due to the COVID-19 lockdown. The decrease in NOx from vehicles led to an increase in ozone on the roadside (30.2%)
Collivignarelli et al. (2020) Road The restriction of mobility led to a significant decrease in the concentration of air pollutants mainly due to vehicular traffic (PM2.5, PM10, BC, benzene, CO, and NOx)
Nakada and Urban (2020) Road During the partial lockdown in São Paulo, Brazil, an increase of approximately 30% in ozone concentration was observed, probably related to NOx decreases influenced by vehicle traffic
Shi and Weng (2021) Water As a result of the strict COVID-19 quarantine measures, the emissions from cargo ship are significantly reduced, while the emissions from the container ships and tankers slightly decreased
Ju and Hargreaves (2021) Water A significant decrease in CO2 occurred from June to August 2020 in Singapore as most of the marine transport of essential goods remained normal despite the COVID-19 epidemic
Xue et al. (2021a, b) Air Since the second quarter of 2020, daily fuel consumption and aircraft emissions have been rising in four Chinese international airports. In the fourth quarter, the ratio of 2020 to 2019 is 0.875
Cui et al. (2022) Air Affected by the epidemic, the average emissions from the climbing, cruising, and descending stages of the routes decreased significantly in South America
Overall, research on AEEs from LTO cycles in the context of the COVID-19 pandemic is still limited. Although several attempts have brought valuable results of emissions from the aircraft engines during each operation mode of a typical LTO, the impact of COVID-19 on the spatiotemporal distribution of EQ, EI, and their relative change still needs further research. The LTO emission data at an individual airport has rarely been viewed as geo-referenced data, which considers the impact of the adjacent areas. Given this, we found it necessary to fill the aforementioned research gaps. With the employment of some other analytical methodologies, the following contributions have been made in this research compared to the previous studies: (i) To better comprehend the COVID-19 impact on airport environment, special attention was devoted to both EQ and EI, as well as their relative changes between the pre-COVID-19 era and the year 2020. (ii) The temporal variation patterns of AEEs during the COVID-19 pandemic were classified, and the potential causes were analyzed. (iii) The spatial dependence effect of both the EQ and EI, and their association with other socioeconomic factors were investigated in this paper.
Materials and methods
Geographical scope
The Yangtze River Delta (YRD), which consists of Jiangsu province, Zhejiang province, Anhui province, and Shanghai municipality, is a major metropolitan area located in the east of China (Fig. 1). Accounting for about 23% of the total gross domestic product (GDP) and 11% of the total population, the YRD is widely recognized as a significant driving force for the nation’s economy. In December 2019, the government issued an outline for the integrated development of the YRD. Tasks specified in the outline include establishing a world-class regional airfield complex. Table 2 shows the basic information of the airports at the YRD. Currently, there are 22 civil airports in the YRD, including 2 airports in Shanghai, 9 airports in Jiangsu, 6 airports in Zhejiang, and 5 airports in Anhui province. And the 4 largest airports, which served more than 100,000 flights in 2020, are the airports in Shanghai, Hangzhou, and Nanjing. The outline pointed out that it is crucial to ensure that the airports are under coordinated management within the region. Despite the region’s outstanding performance in civil aviation, the extensive air pollution related to air traffic is still a challenging problem due to the high volume of flights. The outline also stressed that priority should be given to environmental protection. Therefore, to better understand aviation-related environmental issues, it is necessary to study the spatiotemporal pattern of the AEEs generated during LTO cycles at the airports in the YRD.Fig. 1 The map of the Yangtze River Delta, China
Table 2 The basic information of airports in the Yangtze River Delta
Province Airport name IATA codes City Flight demand of 2020
Shanghai Shanghai Pudong International Airport PVG Shanghai 325,678
Shanghai Hongqiao International Airport SHA Shanghai 219,404
Jiangsu Changzhou Bennou International Airport CZX Changzhou 22,000
Huaian Lianshui International Airport HIA Huaian 34,135
Lianyungang Baita International Airport LYG Lianyungang 11,826
Nantong Xingdong International Airport NTG Nantong 28,454
Sunnan Shuofang International Airport WUX Wuxi 53,901
Xuzhou Guanyin International Airport XUZ Xuzhou 34,568
Yancheng Nanyang International Airport YNZ Yancheng 18,799
Yangzhou Taizhou International Airport YTY Yangzhou 42,154
Nanjing Lukou International Airport NKG Nanjing 181,724
Zhejiang Ningbo Lishe International Airport NGB Ningbo 75,373
Taizhou Luqiao Airport HYN Taizhou 9492
Wenzhou Yongqiang International Airport WNZ Wenzhou 73,717
Yiwu Airport YIW Jinhua 13,677
Zhoushan Putuoshan Airport HSN Zhoushan 20,250
Hangzhou Xiaoshan International Airport HGH Hangzhou 237,362
Anhui Anqing Tianzhushan Airport AQG Anqing 5328
Chizhou Jiuhuashan Airport JUH Chizhou 3034
Fuyang Xiguan Airport FUG Fuyang 13,712
Huangshan Tunxi International Airport TXN Huangshan 5526
Hefei Xinqiao International Airport HFE Hefei 74,391
Data resources
Different types of data are needed for estimating the amount of AEEs released during LTO cycles. Firstly, the information on daily flights at 22 airports in the YRD from January 1, 2019 to December 31, 2020 was obtained from the Official Airline Guide (OAG) company (www.oag.com), the world’s leading travel data provider. With the world’s largest network of flight information data, OAG provides access to the most accurate airline schedules and flight records. The historical flight status database includes records of flight information, which contains the flight number, the operating time, the carrier, the origin airport, the departure airport, the aircraft name, which can be specific to a certain series of an aircraft type, etc. The number of daily LTO cycles and the accurate aircraft type of each flight were collected from those records. The aircraft-engine combination was determined by the information from the official websites of aircraft manufacturers and airlines. In an entire LTO cycle, the power setting (%), the time spent (minutes), fuel flow (kg/s), and the emission indices of the HC, NOx, and CO of a certain engine type for each operation mode (i.e., idle, approach, climb out, and takeoff) were obtained from the ICAO engine emission databank.
Methodology
Aircraft emission calculation model
HC, CO, and NOx are the reference AEEs defined in ICAO standards against which engines are certificated (Nielsen et al. 2019). To best reflect actual emission quantity of HC, CO, and NOx, we employed an advanced approach recommended by ICAO (2016). The equation below shows the formula to calculate the AEEs during LTO cycles.1 EQi=∑j∑m=14LTOj×NEj×FCj,m×TIMj,m60×EIi,j,m
Where i is the type of AEEs (i.e., HC, CO, and NOx); j is the type of aircraft; m is the operation mode in a typical LTO cycle (i.e., idle, approach, takeoff, and climb out); EQi is the total emission of pollutant i , in grams (g); LTOJ is the number of the LTO cycle for aircraft j; NEj is the number of engine of aircraft j;FCj,m is the fuel consumption of aircraft j in mode m , in kilograms per second (kg/s); TIMj,m is the duration (abbreviation of time in mode) of mode m for aircraft j, in minutes (min); EIi,j,m is the emission factor for pollutant i, aircraft j in operating mode m, in grams per pollutant per kilogram of fuel (g/kg of fuel) for each engine on aircraft j.
Clustering algorithm
Clustering analysis can search for correlations among time series data (Wu et al. 2022). To classify the temporal variation pattern of the AEEs, a modified k-means clustering algorithm is used to partition the variations of AEEs at different airports into homogeneous subgroups. Firstly, the percentage of the change in the emissions between every two consecutive months in 2020 was calculated. Then, to best feature the variation of the emission between each consecutive 2 months, we further classify the change of AEEs into five categories: (i) substantial decrease, i.e., a decline that is smaller than − 50%; (ii) moderate decrease, i.e., a decline from − 50 to − 10%; (iii) stability, i.e., a decline from − 10 to 0% and a growth from 0 to 10%; (iv) moderate increase, i.e., a growth from 10 to 50%; (v) substantial increase, i.e., a growth that is larger than 50%. The five variation categories are labeled − 2, − 1, 0, 1, and 2, respectively. Since there are 11 intervals between 12 months, each airport in the YRD can be labeled by 11 numbers based on the variation trend of the AEEs. The series of numbers of different airports are then selected to be the input dataset for the clustering algorithm. And the airports can, therefore, be categorized into clusters using the K-means clustering method. Airports that belong to the same cluster have similar variation trends.
Spatial dependence analysis
Spatial dependence is an essential property within the geographic space: characteristics at adjacent locations tend to be positively or negatively correlated. Such a phenomenon results from several spatial effects, including spatial interaction, spatial hierarchies, and spatial spillover (Cartone et al. 2021).
A spatial weight matrix quantifies the spatial relationships between the observational units in a spatially referenced dataset (Fotheringham and Brunsdon 1999). It is an n×n positive symmetric matrix, denoted as W, with element wij at location i, j for n locations. According to the spatial data type, the spatial weights can be classified into two categories: contiguity-based weights and distance-based weight. Contiguity-based weights are commonly adopted to measure the adjacency of polygons, and contiguity means that two spatial units share a common border of non-zero length. In comparison, distance-based weights are usually adopted for measuring the relative locations between points (Negret et al. 2020). Since the observations of the study are not based on cities (whose shapes are polygons) within the research region but on the airports (which can be seen as separate points) within each city, the distance-based spatial weight matrix is more suitable to represent the spatial structure of the research data. The most widely used distance-based weighting method is inverse distance squared weighting, which is in accordance with the logic of Tobler’s geography law (Musashi et al. 2018). Taking the theory of impedance and distance decay into consideration (Simini et al. 2012), the inverse distance squared weighting assumes that each measured point has a local influence on the others that diminishes with distance, and the superiority of it in modeling autocorrelation function has been demonstrated in several literatures (Ping et al. 2004; Musashi et al. 2018). Therefore, the element in the weight matrix is calculated by the following formula:2 wij=1dij2
Where dU is the distance from the center of unit i to the neighboring unit j
To investigate whether the AEEs from LTO cycles at the studied airports in the YRD are spatially correlated, a spatial autocorrelation analysis is conducted by calculating both the global and the local Moran’s I developed by Moran (1950) and Anselin (1995). The value of Moran’s I ranges from − 1 to 1. A positive Moran’s I indicates the clustering of similar values, while a negative Moran’s I indicates the clustering of dissimilar values (i.e., dispersion). A value of 0 for Moran’s I typically indicates no autocorrelation, which means that the values are randomly distributed. The larger the absolute value of Moran’s I is, the stronger the spatial autocorrelation exists. The global Moran’s I assesses the overall spatial autocorrelation in the research region, as shown in Eq. (3). The local Moran’s I is the statistic for local indicators of spatial association (LISA), which is a localized measure of the spatial aggregation of AEEs around airport i, as shown in Eq. (4).3 IU=n∑i=1n∑j=1nwij∑i=1n∑j=1nwijxi-x¯yi-y¯∑i=1nxi-x¯2
4 IUi=nxi-x¯∑i=1nxi-x¯2∑j=1nwijwj-x¯
where IU refers to the global univariate Moran’s I; IUi represents the local univariate Moran’s I for airport i;∙wij is the element of the spatial weight matrix; xi and xj are the amounts of AEEs at airport i and airport j, respectively; x¯ is the average amount of AEEs; n is the number of airports in the YRD.
To explore how AEEs at airports spatially correlate with other socioeconomic factors in the adjacent areas within the research region, a cross-correlation analysis is conducted by calculating the bivariate Moran’s I. Common bivariate association measures, such as Person’s correlation coefficient, fail to recognize the spatial interaction of the dataset. Tobler (1979) summarizes the first theory of geography as, “Everything is related to everything else, but near things are more related than distant things.” According to this theory, no region is isolated, and each region is continuously developing in accordance with its correlation with other regions (Ma et al. 2015). Therefore, by adopting both the concept of the Person’s correlation and univariate Moran’s I, bivariate Moran’s I was developed to capture bivariate spatial dependence (Lee 2001). In this study, the global bivariate Moran’s I measures the overall spatial dependence between AEEs and other socioeconomic factors, as defined in Eq. (5). In contrast, the bivariate LISA can reveal the spatial disparity of the association at the local level, as defined in Eq. (6). The pseudo-significance of the bivariate Moran’ I statistics is evaluated at the 5% level based on 10,000 randomization permutations, which can reduce the uncertainty to an acceptable level. The bivariate Moran’s I with p-values below 5% indicates that the amount of AEEs at a particular airport is associated with the socioeconomic status in the neighboring regions.5 IBn∑i=1n∑j=1nwij∑i=1n∑j=1nwijxi-x¯yi-y¯∑i=1nxi-x¯2∑j=1nyi-y¯2
6 IBi=nxi-x¯∑j=1nyi-y¯2∑j=1nwijyi-y¯
Where IB refers to the global bivariate Moran’s I; IBi represents the local bivariate Moran’s I for airport i; xi is the amount of AEEs at airport i ;xi is the amount of AEEs at airport i and x¯ is the average amount of AEEs; yi is the value of the socioeconomic factors at city j and y is the average amount of them.
Results and discussions
Analysis of the relative change
The COVID-19 pandemic has inflicted a heavy toll on the civil aviation industry, but it has also eased the environmental pressure on airports in 2020. Table 3 shows the descriptive statistics of EQ and EI at 22 airports in the YRD. Figure 2 shows the spatial distribution of relative changes in EQ and EI at each airport between 2020 and 2019.With the Jenks natural breaks optimization method, the relative changes were classified into 5 degrees and represented by different cycle sizes in Fig. 2. Such a classification method can ensure that the features are divided into classes whose boundaries are set where there are relatively big differences in the data values. Overall, it is evident that there is a decline in EQ of the studied AEEs at all airports. The relative change of EQ ranges from − 47.7 to − 1.13% for HC, − 35.79 to − 0.79% for CO and − 39.55 to − 1.57% for NOx. In general, the EQ emitted at airports in Shanghai, western Jiangsu province, and southern Anhui province decreased more significantly in 2020, indicating that the civil aviation industry in these regions has suffered a greater blow than other regions in the YRD. In contrast, there was an increase in EI at all airports in the YRD, especially for airports located in the middle and southern parts of Zhejiang province and Jiangsu province, southern Anhui province, and Shanghai. Given that the aircraft types on certain routes connecting the airports in the YRD barely changed in 2020 compared to 2019, the impact of aircraft type on the EI could be ignored. The EI of a trip strongly depends on the passenger load factor (Dhital et al. 2022). Defined by the ratio of the passengers onboard to the total number of available seats, the passenger load factor measures how much of the passenger carrying capacity is used. The significant rise in EI at all airports in the YRD indicated the decline in the load factor of passengers during the COVID-19 pandemic, which can be explained by the following two reasons: (i) the collapse in air travel demand caused an oversupply of seats on flights. And it has been reported that some airlines were flying essentially empty aircraft to avoid losing their slots at slot-constrained airports (Sun et al. 2021); (ii) to limit the “touchpoint” opportunities for COVID-19 to spread via close physical proximity between passengers on flights, the CAAC urged that airlines should ensure social distancing when assigning seats onboard in 2020. Therefore, it can be inferred that the decline in the aircraft occupancy rate significantly contributes to EI growth.Table 3 Descriptive statistics of EQ and EI at 22 airports, YRD
Type Period Min Max Mean St.d
Emission Quantity
(t)
HC 2020 1.12 97.30 17.28 26.59
2019 1.21 167.44 23.93 41.15
CO 2020 16.17 1583.54 274.28 408.52
2019 21.57 2391.33 341.84 567.69
NOx 2020 19.76 2578.96 468.22 716.84
2019 32.68 4195.48 614.39 1043.37
Emission Intensity
(g/pax)
HC 2020 1.49 5.48 2.55 1.00
2019 0.97 3.39 2.00 0.52
CO 2020 30.62 73.51 40.58 10.44
2019 25.02 41.27 30.42 4.52
NOx 2020 50.64 89.80 64.40 12.04
2019 40.11 68.84 51.19 7.61
Fig. 2 Spatial distribution of relative changes between 2020 and 2019 in EQ and EI. a Absolute of relative changes of the EQ of HC; b absolute of relative changes of the EQ of CO; c absolute of relative changes of the EQ of NOx; d relative changes of EI of HC; e relative changes of EI of CO; f relative changes of EI of NOx
To study how the COVID-19 pandemic affected the AEEs at airports in the YRD, we further analyzed the relationship between the spread of COVID-19 and the monthly variation of relative changes in the AEEs. Policy responses to the pandemic are also taken into consideration. Figure 3 shows the relative changes in EQ and the number of newly confirmed cases in 2020. Figure 4 demonstrates the daily difference in the new confirmed cases, existing confirmed cases of COVID-19, and the total confirmed cases between different cities in the research region.Fig. 3 Relative changes in EQ of the AEEs between 2019 and 2020, and the number of newly confirmed cases in 2020
Fig. 4 The COVID-19 situation in the YRD, 2020. a Daily new cases of COVID-19 at each province and Shanghai in the YRD, 2020. b The existing cases of COVID-19 at each province and Shanghai in the YRD, 2020. c The total confirmed case at each city in the YRD, 2020
In the YRD, the first confirmed case of COVID-19 was identified in Shanghai on January 20, 2020. Three days later, infections were reported in all provinces of the YRD. At the same time, all regions in the YRD have initiated the highest level of public health emergency responses. The number of daily new cases gradually climbed and peaked during late January and early February. And numerous flights were canceled due to the vigorous restrictions on air transportation services. Consequently, the Chinese New Year Festival (CNYF) of 2020 (from January 24 to February 8) witnessed a sharp decline in flights and the AEEs at all airports in the YRD. The decline was unprecedentedly significant in February as the CNYF was usually a peak season for air traffic. Compared to the same period in 2019, the average EQ of HC, CO, and NOx at airports in the YRD decreased by 30.16%, 16.68%, and 40.66%, respectively. However, as the number of new cases turned zero in the YRD by the end of February, the travel restrictions have been slightly relaxed. Different neighborhoods and townships are categorized into high, medium, or low risk, depending on the number of confirmed cases and whether there are cluster cases, which formed the basis for the gradual easing of lockdown measures. This policy also led to the rise of the AEEs at some airports in the study area since March.
To resolutely contain the increasing risks of imported COVID-19 cases, the information on international flight plans (Phase Five) was released by the Civil Aviation Administration of China (CAAC) on March 12. Two weeks after, notice on further reducing international flights was issued by CAAC. But, still, foreign-imported infections began to account for almost all the resurgence of COVID-19 cases in Shanghai, which made Shanghai the city with the most infections in the research region in 2020. Because of the restricted quarantine policies for the inbound passengers, Shanghai successfully prevented new cases from spreading exponentially in 2020. On April 30, there were no existing infections in the three provinces, indicating that the COVID-19 pandemic had been successfully controlled in the YRD by the end of April. At that time, the relative change of the EQ began to rebound. The post-pandemic reopening of the economy has again boosted the demand for domestic air travel, which significantly offset the reduction in international flights. As a result, the next 2 months witnessed a considerable increase in the AEEs at most airports in the YRD. During the second half of 2020, airlines in China have been restoring flights and regaining passengers for domestic services. The reviving domestic business has slightly boosted the local civil aviation industry. In September, there was a drastic growth in the AEEs. And, for the first time in 2020, the emissions of the studied AEEs surpassed the values in the same period in 2019. The EQ of AEEs continued to climb, and the relative change peaked at around 20% in October, when people in China enjoyed 10 days off to celebrate the National Day and Mid-Autumn Festival. The public holidays stimulated the tourism market, which, in turn, boosted the demand for air transportation. Thus, the amount of AEEs at airports became relatively higher in October, with an average change of 14.43% for HC, 19.49% for CO, and 21.71% for NOx, respectively. However, as the weather turned colder in November and December, the relative change of the three types of AEEs plummeted again because of a growing public fear of COVID-19 infection.
Classification of temporal variation patterns
The EQ of AEEs at different airports experienced different variation patterns in the year 2020. According to the results obtained from the modified k-means clustering algorithm, some common shapes can be used to illustrate the variation patterns of the AEEs during the first half of 2020, including the shape of letters “W,” “U,” and “V.” Fig. 5 shows the classification result of CO for the first half of 2020 (from January to June). And these classification results are similar for the other two AEEs as well.Fig. 5 The classification results of variation patterns during the first half of 2020. a The W-shaped variation patterns of CO; b the U-shaped variation patterns of CO; c the V-shaped variation patterns of CO
A W-shaped pattern refers to the type of variation that resembles the letter “W” when charted. The W-shaped variation pattern of AEEs at an airport indicated that the civil aviation industry in that region began to recover rapidly after the significant decrease during the most challenging period of the COVID-19 pandemic but then turned down into another decline. Such a double-dip variation pattern may exhibit a false sign of recovery at first, but the industry just crashed again in the second round. Four airports are categorized into the W-shape, and three (FUG, AQG, and JUH) experienced a second decline in May, followed by another increase in June (43.88%, 54.99%, and 50.16%, respectively). According to CAAC (2015), the four airports in this category (i.e., HYN, FUG, AQG, and JUH) are all small branch-line airports that serve only domestic and intra-provincial flights, and their annual passenger throughput is less than 2 million. Another similarity is that these airports have a larger portion of tourist traffic as they are in cities with proximity to tourist attractions. Therefore, they are relatively less resilient in the face of the pandemic disruption compared to the airports that serve a large proportion of business passengers who travel regularly. That may explain why these airports show a fluctuated variation of AEEs during the first half of 2020.
A U-shaped pattern refers to the type of variation that takes on the shape of the letter “U” when charted. A U-shaped pattern, in this case, presents that the AEEs at these airports did not begin to increase until April at the earliest, even though the coronavirus cases in the YRD are under control in March and the economies began to be reopened. Airports that experienced a U-shaped variation pattern include two hub airports (SHA and PVG) located in Shanghai with dense international and domestic routes and two mainline airports located at the capital city (NKG and HGH). However, there still exists some disparity in the variations, even for the airports classified in the same category. For example, the growth of AEEs at PVG in May is much smaller than the other U-shaped airports, with an increase of only 23.16% for HC, 12.92% for CO, and 28.38% for NOx. In contrast, the average growth of AEEs at other airports is 43.01% for HC, 37.93% for CO, and 42.04% for NOx. Such disparity is associated with the difference in the functional positions of the airports. As one of the major aviation hubs of East Asia, PVG handles a larger proportion of international flights. In comparison, other airports mainly serve domestic and regional flights. After the five international flight plans (phase five) issued by CAAC, the number of international routes and inbound flights from other nations slumped to an unprecedented low level that has not been experienced for years. And this could explain the more minor increase in AEEs from PVG compared to other airports.
A V-shaped pattern refers to the type of variation that resembles the letter “V.” Nearly half of the airports in the YRD exhibited a V-shaped variation pattern, which was characterized by a quick and sustained increase after the continuous sharp declines in the AEEs. However, for most airports, the variation of AEEs did not always follow a full V-shape, because it was extremely difficult for the right side to peak at the pre-crisis level in such a short time, considering the huge recession that aviation suffered from the COVID-19 pandemic. The greatest difference between V-shaped and U-shaped patterns is that a V-shaped variation does not bump along the bottom. Airports that experienced a V-shaped variation pattern include 5 airports in Jiangsu province, 3 airports in Zhejiang province, and 2 airports in Anhui province. Except for HFE, all the airports that are classified into this category are medium-sized airports located in non-capital cities of the provinces. The strength of the recovery in one certain area is closely associated with the severity of the preceding impact of COVID-19, as well as the airport’s resilience to severe events. For most of the airports, the continuous downward trend ends in April.
The control of the COVID-19 pandemic allowed the recovery of domestic air transportation at most of the airports in the YRD during the second half of 2020. The increasing confidence in air travel also resulted in an upsurge in the AEEs. Generally, there are three types of tendencies for the variation patterns of AEEs in the second half of 2020: upward trend, fluctuation, and downward trend. Figure 6 shows the classification result of CO for the second half of 2020 (from July to December). And this classification result holds true for the other two AEEs as well.Fig. 6 The classification results of variation patterns during the second half of 2020. a The variation patterns of CO with an upward trend; b the variation patterns of CO with a fluctuated trend; c the variation patterns of CO with a downward trend
Airports that presented an upward trend of the variation patterns of the AEEs are small airports (except for PVG) with relatively fewer annual flights in the YRD. The marked surge of AEEs at these airports indicated that smaller airports in the research region were more resilient to the COVID-19 pandemic. As for airports that presented a fluctuation trend, almost all these airports experienced some levels of increase in the AEEs in August 2020. The increase ranged from 8.61 to 45.58% for HC, 4.48 to 33.64% for CO, and 11.58 to 41.3% for NOx, indicating a further recovery of civil aviation in most areas of the research region. From August to December, the amount of AEEs from LTO cycles at these airports slightly fluctuates around the same level as July (the change ranges from − 20 to 20%). And airports that witnessed this type of variation trend are usually intermediate or large airports that are busy for the whole year. In comparison, airports that experienced greater changes are smaller airports (e.g., AQG, JUH, LYG, HIA, and FUG) that relied greatly on the local tourism industry. As for these airports, there are sharp rises in the amount of AEEs in the peak season of tourism and declines in the off-season of tourism. As can be seen in Fig. 6 (c), only JUH and NKG witnessed downward trends of AEEs. JUH was specially built to serve tourists who come to visit Jiuhua Mountain. Because November is one of the worst seasons to travel to Jiuhua Mountain, it is reasonable that the AEEs plummet at that time. As for NKG, the variation patterns of the AEEs experienced a noticeable rise in September, followed by a significant decline in October. Such a phenomenon may be explained by the fact that Nanjing is one of the cities with the most universities and institutes in China. Given that September is the beginning of a new semester, numerous students flied to Nanjing from all over the country at this time, which contributed to the sharp rise in AEEs in September 2020.
Spatial dependence analysis
Spatial autocorrelation analysis
Table 4 shows that the global Moran’s I of EQ, EI, and other socioeconomic factors (i.e., GDP, GDP per capita, population, and population density) are all greater than 0, indicating the presence of positive spatial autocorrelation in the YRD. The Moran’s I of the AEEs is relatively lower compared to the Moran’s I of these socioeconomic indicators. Several reasons may account for this. Firstly, affected by the localized management mechanism of air transportation, the distribution of resources for airports is uneven. For instance, the government of Jiangsu province established the China East Airport Group (EAG) in 2018, which is responsible for the general planning and co-construction of all airports in Jiangsu province except for WUX and NTG. Accordingly, there still exists a large gap between the development of civil aviation in different cities. Some airports received more investments in constructing airport facilities than their neighbors, leading to significant unbalanced development within the studied region. Secondly, the YRD has a well-developed expressway network and a high-speed railway network. As of the end of 2019, 20 high-speed rail lines have opened in the region, making the YRD the region with the highest density of high-speed rail in China. However, superior ground transportation has suppressed the interaction and coordinated development among airports in the study area. Furthermore, the aviation business in the YRD is currently highly concentrated in some major cities due to the disparity in economic development. In 2019, the passenger throughput of 8 major airports in Shanghai, Hangzhou, Nanjing, Ningbo, Wenzhou, Hefei, and Wuxi reached approximately 240 million passengers, accounting for about 90% of the total amount in the YRD. In contrast, the cumulative passenger throughput of the other 14 airports in the research region did not reach the level of 30 million passengers. Some airports are facing the problem of the saturation of operation capacity, while others are challenged by the serious shortage of business volume. The novel findings of the spatial autocorrelation analysis offered the opportunity to explore and disclose the problems behind the coordinated development of the airport group in the research region.Table 4 Univariate global Moran’s I
Variable Global Moran’s I
EQ of AEE HC 0.155841**
CO 0.125544***
NOx 0.169038**
EI of AEE HC 0.128533***
CO 0.119157**
NOx 0.110603***
Economic indicator GDP 0.291022*
GDP per capita 0.579645**
Demographic indicator Population 0.144057*
Population density 0.276255**
*Statistically significant at the 10% level; **significant at the 5% level; ***significant at the 1% level.
Figure 7 is the LISA map of EQ, which demonstrates the classification of the airports with an assessment of significance. In this case, there are three types of clustering patterns with points that are significant (p ≤0.05): (1) high-high clustering (SHA and PVG)- airports with high AEEs are adjacent to airports with high AEEs; (2) low-low clustering (AQG, JUH, and TXN)- airports with low AEEs are adjacent to airports with low AEEs; (3) low–high clustering (WUX, NTG, and HSN)- airports with low AEEs are adjacent to airports with high AEEs. Generally, the high-high and low-low clustering spots, which contribute significantly to the positive global spatial autocorrelation, are polarized in the YRD. The high-high spots are distributed in the east, while the low-low spots are scattered in the west. The two airports in Shanghai belong to the high-high cluster, which indicate a great concentration of the AEEs from LTO cycles in Shanghai. The low-low cluster covers three cities in the southwest of Anhui province, suggesting a less-developed civil aviation industry across this domain. Compared to Jiangsu province and Zhejiang province, Anhui province has fewer air passenger demands, less developed airport construction, and lower airport utilization efficiency. Except for the HFE in the capital city, Hefei, which has more routes and flights, none of the airports in Anhui Province can compete with airports in Jiangsu Province. Therefore, it is reasonable that airports in the low-low cluster are in three adjacent cities in Anhui Province. The airports that belong to the low–high cluster are in Wuxi, Nantong, and Zhoushan, respectively. These cities are all close to Shanghai, which have a relatively larger population density and a higher level of economic development. Because of the high density of airports and extensive air routes in the region, the airspace and time resources of the YRD tend to be saturated (Shi et al. 2021). Airway congestion has become a prominent problem in the research region. Given the fact that Shanghai is the aviation hub in the Asia–Pacific region, the growth of air traffic in the three airports (i.e., WUX, NTG, and HSN) has been greatly suppressed to ensure the normal operation of SHA and PVG in Shanghai. The results of local spatial autocorrelation of the EI with an assessment of significance are presented in Fig. 8. It is noteworthy that airports located in southern Anhui province (i.e., AQG, JUH, and TXN) are categorized as high-high clusters, whereas airports located in the southeast Zhejiang province are identified as low-low clusters. One of the primary causes that may explain this result may be the economies of scale, as the converted throughput per airport in southeast Zhejiang province was much higher than in southern Anhui province.Fig. 7 The results of local spatial autocorrelation of the EQ. a The LISA map; b the significance map
Fig. 8 The results of local spatial autocorrelation of the EI. a The LISA map; b the significance map
Spatial association analysis
The bivariate Moran’s I model is used to address the closely pertinent question: is there any spatial correlation between AEEs and other socioeconomic factors? Table 5 shows the bivariate Moran’s I statistics and the corresponding p-values. The values of bivariate Moran’s I show that GDP, GDP per capita, population, and population density are all spatially correlated with AEEs at airports in a positive way. And the interactions of those factors between the cities with closer geographic positions are relatively significant (all Moran’s I values > 0, p-values ≤ 0.05). An increase in any of these socioeconomic factors would promote the corresponding AEEs at airports for other cities that were geographically nearby at the same time. This result is consistent with extensive literature, which argues that socioeconomic factors have always been the important driving force for the aviation sector (Wang et al. 2020; Liu et al 2021). The strongest spatial correlation is observed between the AEEs and GDP per capita (mean Moran’s I: 0.404), suggesting that the higher the economic welfare and living standard is in the neighboring region, the larger amount of AEEs at local airports is likely to be generated. This situation is probably due to the mutually supportive relationship between the local economy and the civil aviation industry (Addepalli et al. 2018). Generally, the contribution of air transport and related civil aviation industries to local economies includes the output and jobs directly attributable to civil aviation, as well as the multiplier or ripple effect upon other industries throughout the economy. Meanwhile, the local economy contributes to the aviation industry by boosting passenger demand for the transport of passengers, mail, freight, and other services. Since AEEs from LTO cycles are highly reliant on flight demand, the strong positive spatial relationship between AEEs and local economic conditions is, therefore, reasonable.Table 5 Bivariate global Moran’s I in the YRD
First variable (X) Second variable (Y) Moran’s I
HC GDP 0.244632**
CO GDP 0.231359**
NOx GDP 0.248902**
HC GDP per capita 0.406193***
CO GDP per capita 0.396324***
NOx GDP per capita 0.409726***
HC Population 0.163799*
CO Population 0.154004*
NOx Population 0.167640*
HC Population density 0.242420**
CO Population density 0.239702*
NOx Population density 0.247184**
*Statistically significant at the 10% level; **significant at the 5% level; ***significant at the 1% level.
The Bi-LISA cluster map (Fig. 9) depicts the spatial clustering and spatial outliers of the studied AEEs by the lagged values of GDP per capita, GDP, population, and population density. Similar to the univariate LISA map mentioned above, it can be observed that AQG, JUH, and TXN also appeared in the low-low region on all the Bi-LISA cluster maps, indicating that the three airports, which have a relatively smaller amount of AEEs, are surrounded by cities with poorer economic performance, smaller population, and smaller population density. Being the financial center of the YRD, the two airports in Shanghai are again identified as the significant high-high region, which is consistent with the fact that Shanghai has apparent economic externalities and a spatial spillover effect on its neighboring cities in terms of many socioeconomic aspects. Besides, slight differences can be found between the clustering patterns of GDP and per capita GDP. On the Bi-LISA map for the AEEs and GDP per capita, more spatial units are included in the high-high and low–high regions. NKG is identified as a high-high cluster, indicating that NKG has AEEs more than the average amount, and the contiguous cities also present a higher per capita GDP value than the average. In contrast, NKG is not significant on the Bi-LISA mapr for the AEEs and GDP. Besides, except for WUX and NTG, CZX and YTY are also classified as the low–high spatial outliers when using per capita GDP as the second variable. This can be explained by the fact that these airports are all close to the airports classified as high-high clusters. The Bi-LISA maps for the AEEs and population and population density present the same distribution pattern. In general, regions predominantly from the west of the YRD are relatively less developed in terms of civil aviation and other socioeconomic aspects, which, in turn, resulted in fewer AEEs released from LTO cycles.Fig. 9 The bivariate LISA map for the YRD. a AEEs and GDP; b AEEs and GDP per capita; c AEEs and population; d AEEs and population density
Policy implications
Based on the results and discussion above, we provide recommendations for building a more sustainable and environment-friendly airport group in the YRD.
Reducing the aircraft taxiing time with integrated methods
The air pollutant emissions released during a typical LTO cycle are closely related to the time spent in each mode of the operation (i.e., idle, approach, takeoff, and climb out). From the perspective of the airport authorities, the most feasible way to cut the AEEs at the ground level is to reduce the operation time of the aircraft at the airport. Previous studies have suggested that the taxi mode of the aircraft contributes the biggest portion of the total LTO emissions (Song and Shon 2012; Yılmaz 2017). It has also been estimated that fuel burned during taxiing accounts for up to 6% of the total fuel consumption by an airline fleet for short-haul flights (Brownlee et al. 2018), and a shorter taxiing time can potentially save one-third of the fuel (Hao et al. 2017). Therefore, reducing the aircraft taxiing time should be considered a critical issue in alleviating aircraft emissions at airports. With this aim, the optimization of the ground movement of aircraft on the taxiway has been the focus of extensive studies over the past decades, which involves the routing problems and the scheduling problems (Adacher et al. 2018). With the development of computer science, different algorithms are capable of solving the problems, such as the adapted heuristic algorithm (Zhang et al. 2018) and modified Dijkstra’s short-path algorithms (Brownlee et al. 2018). Some other integrated approaches to optimizing the ground movement of aircraft include optimizing gate allocation (Chow et al. 2022; Jiang et al. 2022a, b) and runway sequencing (Jiang et al. 2022a, b). In addition, potential approaches to increase the taxi efficiency of the aircraft may include increasing the airport capacity, using more advanced automation and information management system to improve the performance of air traffic control (ATC) and so forth. By adopting these approaches at the airports, the idling time of aircraft on the taxiway can be minimized, and, thus, the pollutant emissions from aircraft at ground levels can be hopefully reduced.
Improving demand management and air traffic management
The occurrence of severe public emergencies, such as COVID-19, led to unpredictable fluctuations in the demand for air transportation. The plunge in air passengers, as well as the stringent social distancing standards during flights, has forced the airlines to cut down the seating capacity, which consequently resulted in the surge of emission intensity per passenger at the airports. Traditionally, each air route is designated with a certain type of aircraft based on the historical average demand. However, this strategy does not fit the ever-changing civil aviation market. During the post-COVID-19 era, airlines should be encouraged to enhance the ability to predict passenger demand and increase the flexibility when assigning aircraft to a specific route to avoid the huge oversupply of seats onboard. It would be more environment-friendly so that the capacity of the designated aircraft can better match the demands of specific air routes. Furthermore, the ever-changing air traffic level during the COVID-19 pandemic has also brought great challenges to air traffic management (ATM), as the system and air traffic controllers had to respond quickly to variable situations and simultaneously maintain efficiency and performance. Previous studies have argued that the performance of air traffic controllers was negatively impacted by the COVID-19 pandemic, leading to rising concerns about longer flight delays and more aircraft emissions (Vink 2021). Hopefully, the application of advanced air traffic management technologies may greatly reduce human errors and provide tactical decision support (Xue et al. 2021a). Aiming at increasing flight efficiency, ICAO has been proposing the Communication, Navigation, and Surveillance for ATM (CNS/ATM) (2). As a key component, the Automatic Dependent Surveillance-Broadcast (ADS-B) can offer accurate and reliable real-time aircraft positions (Xue et al. 2021a) and, thus, improve ATM efficiency. Besides, switching the traditional ground navigation system to a satellite navigation system should be encouraged to strike a balance between flight demands and airport capacity (Xue et al. 2022). In addition, the arrival manager (AMAN) and the departure manager (DMAN) are useful sequencing tools that can help air traffic controllers to improve their situational awareness and to anticipate the flow of traffic (Insaurralde and Blasch 2022). The adoption of coupled AMAN-DMAN allows for optimization of the arrival and departure sequence, and, thus, helps ensure efficient demand coordination and reduce the fuel burn of aircraft (Liang et al. 2018). Other technologies that can be adopted by the airport to improve ATM and reduce the AEEs include terminal flight data manager (TFDM), airport surveillance radar (ASR-11), trajectory-based operations (TBO), and so forth. By improving demand management and air traffic management, airports and airlines would be able to look beyond the pandemic and adapt to the long-term realities of COVID-19.
Enhancing coordinated development of civil aviation in the YRD
The development of civil aviation in the YRD is highly unbalanced, which can be reflected by the spatial clustering patterns of the AEEs at airports in the YRD. Currently, a great number of airports in the YRD are challenged by a shortage of flights, while airports in megacities (e.g., Shanghai, Hangzhou, Nanjing) are facing severe problems of capacity saturation. Consequently, extensive delays and longer operation time on the ground are caused by capacity saturation, resulting in the escalation of air pollutant emissions from the aircraft. Therefore, airports with larger traffic need to make better use of airport resources and improve the ability to manage airflow so that emissions caused by congestion and delays can be reduced. Besides, communication and cooperation between different airports should also be encouraged as the shared information is beneficial for building a more sustainable airport group. In addition, the regional government should be encouraged to seek a balance between unified management strategies and differentiated policies based on the functional position of the airports and the according local development characteristics. The recommendations above for building a more sustainable airport group can all be achieved by implementing collaborative decision making (CDM). As a joint government and industry initiative, CDM aims to improve traffic flow and capacity management performance by encouraging different aviation stakeholders to work together and make decisions based on shared information (Corrigan et al. 2015). The successful implementation of CDM at many airports in the world has proved its advantages in improving the efficiency and quality of airport operation, assisting the decision-making process of aviation community stakeholders, and enhancing the collaboration between different aviation stakeholders (Okwir et al. 2017).
Conclusions
The dramatic drop in the demand for air travel, together with the traffic restrictions, led to the decline in AEEs from LTO cycles at airports. Compared to 2019, the EQ of HC, CO, and NOx decreased greatly at airports in the YRD in 2020. However, there was a significant rise in the EI, mainly due to the decline of passenger load factors during the COVID-19 pandemic. The temporal variation patterns of the studied AEEs were significantly influenced by the policy responses to the epidemic and the severity of the COVID-19. The monthly variation pattern of the AEEs during the first half of 2020 was classified into W-shaped, U-shaped, and V-shaped patterns. During the second half of 2020, three types of tendencies for the variation patterns were observed, including upward trend, fluctuation, and downward trend. The positive spatial autocorrelation was found in both the EQ and EI of AEEs at airports in the YRD. As for EQ, the high-high cluster and low-low clusters were polarized in the YRD. The high-high cluster was located in the east, while the low-low cluster was located in the west. As for EI, airports distributed in the southern YRD presented stronger spatial dependence. The positive spatial association was found between the AEEs and the external socioeconomic factors (i.e., GDP, GDP per capita, population, and population density) of the cities in close proximity. The strongest spatial association was observed between the AEEs and GDP per capita, indicating that the higher the economic welfare and living standard is in the neighboring, the more AEEs from LTO cycles are likely to be generated.
Several limitations exist in this study. Firstly, it should be noted that the engine performance can be affected by airport meteorological conditions. Therefore, it would be valuable to include the meteorological factor when calculating the amount AEEs in the future. Moreover, due to limited data access and permission, this research only took the Yangtze River Delta located in central eastern China as an example to study the variations of AEEs and their relationship with other external factors. Further research can expand the study area to the whole nation and other countries.
Author contribution
DB: conceptualization, funding acquisition, methodology, formal analysis, writing—original draft, resources, and supervision. ST: conceptualization, funding acquisition, methodology, formal analysis, and writing—original draft. DK: writing, review, editing, and supervision. ZZ: data curation. TZ: visualization.
Funding
This work was supported by the Fundamental Research Funds for the Central Universities, (NO. NS2020047) and the Foundation of the Graduate Innovation Center, Nanjing University of Aeronautics and Astronautics (NO. xcxjh20210705).
Data availability
The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval
Not applicable.
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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| 0 | PMC9735065 | NO-CC CODE | 2022-12-14 23:28:32 | no | Air Qual Atmos Health. 2022 Dec 5;:1-19 | utf-8 | Air Qual Atmos Health | 2,022 | 10.1007/s11869-022-01294-w | oa_other |
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