Caifeng Chen,Xiaoying Wang,Han Xu,Yuhong Li
Effectiveness of digital psychological interventions in reducing perinatal depression: a systematic review of meta-analyses
Perinatal depression,Digital,Psychological interventions,Systematic review,Meta-analysis
Digital psychological interventions have been widely used clinically in recent years, but the methodological quality and quality of evidence of related studies are unclear, thus interfering with the translation of practice outcomes and the application of clinical decisions. We searched for meta-analyses of randomized controlled trials in the PubMed, Web of Science, Embase, Cochrane Library, JBI Database, CINAHL, and PsycINFO databases as well as some databases containing gray literature up to 27 April 2022 using a combination of keywords. After two researchers independently screened and extracted data from the literature, the methodological quality of the included literature was evaluated by the AMSTAR 2 scale, and the evidence quality of the outcome index was graded by the Grading of Recommendations, Assessment, Development, and Evaluation system. A total of 12 meta-analyses reporting the positive impact of digital psychological interventions in the prevention and/or treatment of depressive symptoms in perinatal women were included, but the methodological quality and evidence level of the included studies were low. Digital psychological interventions are effective in reducing perinatal depression, but the methodological quality and reliability of outcome indicators are mostly low. Improving study designs, using higher-quality clinical evidence, conducting systematic evaluation studies strictly following the procedures, and standardizing the reporting of study results are recommended.
Effectiveness of digital psychological interventions in reducing perinatal depression: a systematic review of meta-analyses

Digital psychological interventions have been widely used clinically in recent years, but the methodological quality and quality of evidence of related studies are unclear, thus interfering with the translation of practice outcomes and the application of clinical decisions. We searched for meta-analyses of randomized controlled trials in the PubMed, Web of Science, Embase, Cochrane Library, JBI Database, CINAHL, and PsycINFO databases as well as some databases containing gray literature up to 27 April 2022 using a combination of keywords. After two researchers independently screened and extracted data from the literature, the methodological quality of the included literature was evaluated by the AMSTAR 2 scale, and the evidence quality of the outcome index was graded by the Grading of Recommendations, Assessment, Development, and Evaluation system. A total of 12 meta-analyses reporting the positive impact of digital psychological interventions in the prevention and/or treatment of depressive symptoms in perinatal women were included, but the methodological quality and evidence level of the included studies were low. Digital psychological interventions are effective in reducing perinatal depression, but the methodological quality and reliability of outcome indicators are mostly low. Improving study designs, using higher-quality clinical evidence, conducting systematic evaluation studies strictly following the procedures, and standardizing the reporting of study results are recommended.

The World Health Organization (WHO) reports that approximately 140 million women worldwide give birth each year (World Health Organization 2018). During pregnancy, childbirth, and lactation, women undergo tremendous physical, psychological, social, familial, and role changes, and these changes may affect psychological and physical resources, leading to an increased susceptibility to psychological problems, such as major depressive disorder (MDD), anxiety disorders, and psychotic disorders (Howard and Khalifeh 2020; van Ravesteyn et al. 2017). Perinatal depression (PND) refers to depressive episodes of different degrees occurring from pregnancy to 12 months after delivery, including prenatal and postnatal depression, which mainly manifests as depressed mood, sadness, agitation, and irritability. In severe cases, psychotic symptoms such as hallucinations or suicidal thoughts may occur (Simas et al. 2018). The incidence of perinatal depression ranges from 5 to 38.8% (Lara et al. 2014; Silveira et al. 2015; Huang et al. 2019), the incidence of perinatal depression is as high as 40% in high-risk women (e.g., family history of depression, major life events, or socioeconomically disadvantaged groups) (Parameswaran et al. 2022), and the recurrence rate of postpartum depression is as high as 30–50% in women with a second pregnancy and delivery (Josefsson et al. 2002). The harms of perinatal depression are multifaceted; it affects not only maternal quality of life, marital relationships, and social functioning status (Wonch et al. 2016) but also pregnancy outcomes (e.g., preterm birth, low birth weight) (Jarde et al. 2016); the emotional, intellectual, cognitive, and behavioral development of infants and children (Herba et al. 2016; Hannigan et al. 2018; Duan et al. 2019); and in severe cases, even suicidal or infanticidal behavior (Khalifeh et al. 2016). In addition, the children of women with perinatal depression also suffer from depression in childhood to adulthood that is more difficult to treat, has a longer duration, and can even last for multiple generations, which is known as intergenerational transmission (Grundwald and Brunton 2015; Bowers and Yehuda 2016). Perinatal depression has a high incidence and is harmful, and effective interventions are the key to reducing perinatal depression. Studies have shown that pharmacotherapy is only indicated for moderate to severe illness, whereas behavioral interventions are recommended for the initial treatment of mild to moderate depression (Ladyman et al. 2022). Generally, non-pharmacological treatments to reduce depression, such as psychological interventions, are preferred by those who are pregnant (Zhang et al. 2021), possibly due to the adverse effects of antidepressants, which impact the gastrointestinal, cardiovascular, and central nervous systems (Lei et al. 2019). These adverse effects may affect patient tolerance and compliance, and antidepressant exposure during pregnancy is associated with adverse pregnancy outcomes and offspring development (Rommel et al. 2020, 2022). Psychological intervention is a planned and step-by-step process guided by psychological theories to influence the mental activities, personality characteristics, or psychological problems of certain subjects so that patients progress toward the desired goal. Psychological interventions are performed in a variety of ways (e.g., cognitive behavioral therapy (CBT), interpersonal therapy (IPT), mindfulness intervention, behavioral activation (BA), and psychological education intervention) (Martín-Gómez et al. 2020). Studies have shown that psychological interventions have a positive impact on perinatal depression (Dolan et al. 2022; Sockol 2018), but previous psychological interventions were mostly face-to-face (individual or group) (Sangsawang et al. 2019), and some women were unable to access psychotherapy due to temporal and financial barriers, stigma, and self-stigma (Cacciola and Psouni 2020). With the rapid development of networked information technology, digital health is revolutionizing the delivery of medical services and has rapidly become an important tool for providing care during the COVID-19 pandemic (Meyer 2020). Digital psychological interventions are being increasingly examined. Psychological interventions are considered digital when they are delivered by methods, including the internet, computers, mobile phones or tablets, and short message services (SMSs) (Fu et al. 2020). Digital psychological interventions (a) overcome spatial and temporal constraints and increase access and convenience (Brearly et al. 2017), (b) improve the connectivity and flexibility of psychological interventions (Gordon et al. 2016), (c) reduce personnel costs (Osborne et al. 2019), and (d) benefit individuals who are reluctant to seek help due to the stigma of mental illness (Mannarini and Rossi 2018). Studies have shown that digital psychological interventions can significantly reduce the degree of depression in affected individuals (Gilbody et al. 2017). Several meta-analyses have examined the efficacy of digital psychological interventions in reducing perinatal depressive symptoms, and these meta-analyses varied in terms of purpose, type of intervention, and study quality, hindering overall findings. A systematic re-evaluation is a new approach to synthesizing high-quality evidence based on the same or similar interventions, which supports summing up treatment effects in a broader context (Smith et al. 2011) and can provide useful and up-to-date evidence for practitioners and clinicians. Currently, there are no systematic reviews of meta-analyses and/or systematic reviews on the effectiveness of digital psychological interventions to reduce perinatal depression. Therefore, we aimed to (a) comprehensively evaluate the meta-analyses on the effects of digital psychological interventions on perinatal depression and (b) synthesize results from past meta-analyses to guide health policies and research.

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Page et al. 2021). The study protocol was registered in the PROSPERO database (CRD42022356820).

Studies were selected for review if they fulfilled the following criteria: Population: women aged ≥ 18 years in the perinatal period (during pregnancy and the first 12 months postpartum); Intervention: Intervention conditions must include at least one digital psychological intervention group (e.g., ICBT or IPT); Comparison: any comparison condition (e.g., active control, usual care, or waitlist); Outcomes: perinatal depression (from pregnancy to the first 12 months postpartum); Study design: meta-analyses of the effectiveness of digital psychological interventions in reducing perinatal depression. Studies were excluded for the following reasons: (a) non-English literature, (b) full text was not available, (c) data reporting was incomplete, (d) research content was the development or feasibility evaluation of the telemedicine system, and (e) others (e.g., primary outcome indicator is not depression, non-psychological interventions, conference abstracts).

A systematic search of electronic databases (PubMed, Web of Science, Embase, Cochrane Library, JBI Database, CINAHL, PsycINFO, and some databases containing gray literature) was conducted from the inception of the databases until April 27, 2022. The database search was conducted independently by two authors (CC and XW). The search terms and strategy were as follows: [(postpartum) OR (postnatal) OR (puerper*) OR (pregnan*) OR (antenatal) OR (antepartum) OR (prenatal) OR (perinatal) OR (peripartum) OR (maternal*)] AND [(depress*) OR (“mental health”) OR (“mental disorder*”) OR (“depressive disorder*”)] AND [(m-health) OR (mhealth) OR (e-health) OR (ehealth) OR (telehealth) OR (telemedicine) OR (teleconsultation) OR (“information service”) OR (telephone) OR (“cell phone”) OR (“mobile phone”) OR (“mobile application”) OR (“mobile health”) OR (“text messaging”) OR (telemonitoring) OR (“social media”) OR (“reminder system”) OR (computer*) OR (online) OR (internet) OR (web-based) OR (technolog*)] AND [(“meta-analysis”) OR (“meta synthesis”) OR (“systematic review”)]. In addition, the references of the included literature were traced to supplement the acquisition of relevant literature. The search results were imported to EndNote X9.3.3, and duplicates were deleted. Two authors (CC and XW) independently screened the titles and abstracts according to the inclusion and exclusion criteria; then, potentially eligible articles were screened by full-text reading. Reasons for excluding papers in the full-text screening stage were recorded. Each article was cross-checked after completion, and any disagreements were discussed and resolved or referred to a third author (HX).

Data extraction from the included articles was completed independently by two authors (CC and XW) using a data extraction form. Extracted data included the first author, year of publication, country, aims, type and number of included studies, sample size, intervention description, depression measurement, main findings, funding sources, and risk of bias assessment. If the literature data were missing or could not be extracted, the original author was contacted to obtain the data. Any discrepancies in this process were discussed and resolved with the third author (HX).

The methodological quality and quality of evidence were evaluated independently by two authors (CC and XW) for each meta-analysis included, with a third author (HX) joining to resolve any disagreements.

Evaluation was performed using the AMSTAR 2 assessment tool, which was adapted for both randomized and non-randomized studies of healthcare interventions and provided a more comprehensive assessment of methodological quality (Shea et al. 2017).

With perinatal depression as the evidence body, the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system was used for evaluation (Guyatt et al. 2008). The certainty of the evidence could increase or decrease for several reasons: certainty could be rated lower due to the risk of bias, imprecision, inconsistency, indirectness, or publication bias; certainty could be rated higher for a large magnitude of effect and dose‒response gradient, and all residual confounders would decrease the magnitude of effect (in situations with an effect).

According to the search strategy, a total of 1314 articles were retrieved, and 869 articles remained after removing duplicates. Forty-seven articles were screened after reading the titles and abstracts, and 1 additional article was included after screening the references. A total of 48 papers were rescreened after reading the full text in detail, and 36 papers were excluded. Finally, 12 articles were included in the systematic review of meta-analyses. The literature screening process and results are shown in Fig. 1.

Table 1 presents a summary of the included meta-analyses following the PICO search strategy. All of the studies were conducted between 2017 and 2022; the number of included original studies ranged from 5 to 19 articles; the sample size of one study was not reported completely, and the remaining studies ranged from 567 to 2277. Of the 12 meta-analyses, 7 reviews examined the treatment of perinatal depression, and 5 reviews examined both the prevention and treatment of perinatal depression (Chae and Kim 2021; Nair et al. 2018; Neo et al. 2022; Lau et al. 2020, 2022). Among the 12 meta-analyses, 11 were conducted with article quality evaluation and a description of the quality evaluation tool, and 1 study (Roman et al. 2019) did not mention whether quality evaluation was performed. The quality evaluation tools for each of the 11 articles were as follows: 7 studies (Lau et al. 2017, 2020, 2022; Liu et al. 2022; Loughnan et al. 2019; Neo et al. 2022; Zhao et al. 2021) used the Cochrane Risk of Bias tool (Higgins et al. 2011), 1 study (Chae and Kim 2021) used the Cochrane Risk of Bias 2.0 (Sterne et al. 2019), 2 studies (Nair et al. 2018; Dol et al. 2020) used the JBI (Lockwood et al. 2015), and 1 study (Mu et al. 2021) used the Jadad scale (Jadad et al. 1996). GRADE (Guyatt et al. 2008) was used to evaluate the evidence quality of four articles (Dol et al. 2020; Lau et al. 2020, 2022; Neo et al. 2022). Almost all the included papers, except for three (Liu et al. 2022; Nair et al. 2018; Roman et al. 2019), were supported by grants.

Regarding digital psychological interventions, the studies included a variety of interventions: 7 reviews included BA (Nair et al. 2018; Loughnan et al. 2019; Lau et al. 2020, 2022; Mu et al. 2021; Zhao et al. 2021; Liu et al. 2022), 4 reviews included psychoeducation (Nair et al. 2018; Lau et al. 2020; Chae and Kim 2021; Neo et al. 2022), 4 reviews included problem-solving therapy (Dol et al. 2020; Chae and Kim 2021; Lau et al. 2022; Neo et al. 2022), and all studies included CBT. In addition, interventions such as peer support (Dol et al. 2020; Zhao et al. 2021), mindfulness therapy (Dol et al. 2020; Lau et al. 2020; Neo et al. 2022), mood tracking (Nair et al. 2018), metacognitive therapy and positive psychology (Chae and Kim 2021; Neo et al. 2022), and stress reduction therapy (Lau et al. 2020) have also been described. The studies included different types of intervention delivery formats, with 8 reviews being telephone-based (Chae and Kim 2021; Dol et al. 2020; Lau et al. 2017, 2020, 2022; Loughnan et al. 2019; Roman et al. 2019; Zhao et al. 2021) and 8 reviews being app-based (Nair et al. 2018; Dol et al. 2020; Lau et al. 2020, 2022; Chae and Kim 2021; Zhao et al. 2021; Liu et al. 2022; Neo et al. 2022), and all but 1 review (Dol et al. 2020) reported on the effectiveness of website-based psychological interventions. Of the 12 meta-analyses, five reviews did not report the number of sessions (Nair et al. 2018; Dol et al. 2020; Mu et al. 2021; Zhao et al. 2021; Liu et al. 2022), and seven articles reported the number of sessions to be between 2 and 44 sessions. Among the 7 studies, two had between 3 and 16 sessions (Lau et al. 2020, 2022), and three had between 6 and 12 sessions (Lau et al. 2017; Loughnan et al. 2019; Roman et al. 2019). Regarding the duration of treatment, 4 articles did not report this information (Roman et al. 2019; Mu et al. 2021; Zhao et al. 2021; Liu et al. 2022), and 8 articles reported that the treatment duration was between 2 and 46 weeks. The duration of follow-up ranged from 4 weeks to 16 months. The primary outcome measure in all studies was depression, which was measured by the EPDS in 12 studies. Other frequently reported measures in the reviews were the BDI-II, PHQ-9, and CES-D. The control group mainly used measures such as treatment as usual (TAU), placebo, and waitlist.

All 12 reviews evaluated the effectiveness of digital psychological interventions in the reduction of depressive symptoms. Regarding the type of intervention, both mindfulness therapy (Neo et al. 2022) and CBT (Lau et al. 2017; Roman et al. 2019) significantly improved the depressive symptoms of patients in the intervention group compared with those in the control group postintervention. In one study (Liu et al. 2022), the subgroup analysis of BA intervention and CBT intervention revealed that internet-based CBT had a significant effect on perinatal and postpartum depression (PPD) (standardized mean difference (SMD) = − 1.62; 95% CI: − 2.42 to − 0.80; p < 0.00001), but in the internet behavioral activation group, there was no significant difference in PPD scores after intervention between the experimental group and the control group (SMD = − 0.55; 95% CI: − 0.68 to − 0.43; p = 0.67). In addition, a study by Lau et al. (2020) showed that a website platform with ≥ 8 therapist-guided sessions using the theoretical principle of cognitive behavioral therapy was more effective than other treatments in improving depression symptoms in postnatal women. Regarding the delivery format of intervention, 1 article subgroup analyzed the effect of website-based, application-based, and telephone-based psychological interventions on perinatal depression. The results showed that all three intervention platforms had a positive effect on reducing perinatal depression, and application-based interventions (g = 4.02) were more effective than telephone-based interventions (g = 2.18) and website-based interventions (g = 1.62) (Liu et al. 2022). One article compared website-based interventions with application-based interventions and found that the effect sizes were greater among application-based interventions (g = 1.18) than website-based interventions (g = 0.45) (Lau et al. 2022). Subgroups of 2 studies analyzed the effect of digital psychological interventions on the prevention and treatment of perinatal depression and concluded that digital psychological interventions have a positive impact on the treatment of perinatal depression but differed with regard to the prevention of perinatal depression; however, no significant subgroup differences in prevention or treatment were found in either study (p > 0.05) (Lau et al. 2020, 2022). Regarding the duration of the intervention, studies showed that the postpartum depression scores of the intervention group were reduced at follow-up after 6–8 weeks, 4–7 weeks, and 8–14 weeks (Dol et al. 2020; Neo et al. 2022). The results of Mu et al. (2021) revealed that the effect of internet-based interventions weakened in studies with a follow-up duration over 12 weeks after intervention (0.727, 95% CI: 0.637 to 0.831). Lau et al. (2022) found that preferable features of intervention should be more than eight sessions and longer than 6 weeks in postnatal women.

Table 2 presents an item-by-item quality assessment for each study using the AMSTAR 2 instrument. Of the 12 articles, 2 were rated as low quality (Lau et al. 2017, 2020), and the rest were rated as critically low quality. Critical item 7 and non-critical items 3 and 10 were more frequently reported missing. In addition, some articles did not report and/or discuss the impact of the risk of bias on the results.

Table 3 shows the results of the quality grading of the outcome indicators according to the GRADE, with 2 high-level evidence papers, 1 moderate-level evidence paper, 4 low-level evidence papers, and 5 critically low-level evidence papers. Among the downgrading factors, inconsistency was the main downgrading factor, with most studies showing a high degree of heterogeneity between studies. The next most common downgrading factor was limitations, with 9 articles being downgraded because of limitations. Most of the articles only mentioned randomization but did not describe the method of generating random numbers, and most of the literature did not use blinding and allocation concealment. Finally, funnel plots or tests for publication bias were not produced in parts of the literature, leading to a high risk of publication bias.

The purpose of this study was to conduct a systematic review of previous meta-analyses addressing the effects of digital psychological interventions on PND symptoms. Of the 12 included meta-analyses, one meta-analysis reported that there was no significant difference between the internet behavioral activation and control groups in PPD scores after intervention (Liu et al. 2022). This may have been because only two articles were integrated for analysis in this subgroup, and the results may be somewhat biased. Second, one of the two studies included a population of women meeting Diagnostic and Statistical Manual of Mental Disorders criteria for major depressive disorder and one of women with depressive symptoms. Major depressive disorder requires a combination of formal psychotherapy and pharmacotherapy (Langan and Goodbred 2016), and psychological intervention alone may have little effect in treating major depressive disorder. While postpartum depression mostly occurs within 2 weeks after delivery, the symptoms are obvious 4–6 weeks after delivery (Li 2020), the incidence of perinatal depression decreases and symptoms gradually resolve as the postpartum period progresses (Banti et al. 2011; Underwood et al. 2016), and a longer assessment time (15 weeks) may lead to less pronounced postpartum depressive symptoms. These factors may have caused no obvious difference in the evaluation results between the two groups. In addition, this subgroup of articles analyzed internet-based CBT, and the results showed that internet-based CBT had a significant effect on PPD. The remaining 11 reviews reported the positive effects of digital psychological interventions in reducing perinatal depression. Psychotherapeutic interventions mainly include CBT, IPT, mindfulness intervention, BA, psychoeducational intervention, problem-solving therapy, stress reduction therapy, or a combination of therapies. A meta-analysis integrating 20 randomized controlled trials found that CBT effectively improved the symptoms and progression of postnatal depression (Huang et al. 2018). At present, the role of psychotherapeutic interventions in the prevention and treatment of perinatal depression has been generally verified (Nillnia et al. 2018; Ponting et al. 2020). With the rapid development of information technology, digital psychological intervention has gradually become a research hotspot in technology, psychology, nursing, and other fields. Digital interventions are diverse, with most studies focusing on telephone-based interventions, but recent studies have also demonstrated the superiority and effectiveness of SMS and smartphone applications (Lamont et al. 2016; Sun et al. 2021). The literature included in this study suggests that digital interventions, whether website-based psychological interventions, telephone-based psychological interventions, or application-based psychological interventions, have a positive impact on perinatal depression, but the effect size of other delivery forms of psychological intervention on reducing perinatal depression was not specifically compared. We recommend that this is expanded in future studies to identify the best form of delivery and improve the effectiveness of the intervention. In addition, the effectiveness of digital psychological interventions in preventing perinatal depression needs to be further validated. The effectiveness of the different digital psychological intervention methods varied depending on the duration of the intervention, intensity, intervention provider, and depth of follow-up; however, in general, digital psychological interventions had a positive impact on improving perinatal depression.

The results of the AMSTAR 2 quality evaluation showed that the methodological quality of the 12 included meta-analyses was low, with items 3, 7, and 10 more frequently reported as missing and some articles not reporting and/or discussing the impact of the risk of bias on the results. Our recommendations for further research are as follows: (a) Considering that the inclusion of RCTs alone may result in the inclusion of non-comprehensive studies, the types of included studies should be limited, and the reasons for inclusion should be explained; (b) to avoid researchers being influenced by their preferences when screening and including studies, researchers should make a list of excluded literature and give reasons for exclusion; (c) given the influence of commercial funding, researchers should report whether the included studies receive funding and the source of that funding; (d) note the heterogeneity and impact of the risk of bias (e.g., selection bias, publication bias) of the included literature on the results; subgroup analysis, sensitivity analysis, and detailed discussion and interpretation of the results should be included. The GRADE evaluation showed that the included literature had a low strength of evidence; inconsistency was the main downgrading factor, followed by limitations and publication bias. The above analysis showed that many of the existing studies have deficiencies, such as poor design and incomplete analysis. Therefore, the conclusions of the meta-analysis need to be further validated. More high-quality original studies, especially high-quality randomized controlled trials, need to be conducted in the future to provide better evidence to support the use of digital psychological interventions.

Despite these important findings, this study also had the following limitations. First, the current systematic evaluation and re-evaluation could only descriptively evaluate the elements included in the meta-analysis based on existing studies, and it was difficult to re-evaluate the previous research process comprehensively. The quality of meta-analysis is influenced by the quality of the original article and the quality of the methodology, and bias objectively exists; therefore, large-scale and high-quality research and reviews are needed. Second, the heterogeneity among the included studies was large, which was mainly due to the inconsistency of intervention methods, frequency, duration, and time of measurement (ranging from 2 weeks to 16 months, mostly ≤ 12 weeks) of perinatal depression of digital psychological interventions. Therefore, we did not combine the original articles included in the 12 meta-analyses to provide a pooled effect size of digital psychological interventions on perinatal depression and only performed a descriptive analysis. Finally, the selected meta-analyses included overlapping trials, so these studies were considered more than once in our synthesis, which may have skewed some of the results. We comprehensively examined the original literature in 12 meta-analyses, and a total of 110 original studies were included, leaving 50 remaining after removing duplicates. In the future, large-scale and high-quality studies should be conducted to establish evidence-based digital psychological intervention methods in terms of structure, content, and providers to lay the foundation for the development of scientific, rigorous, and standardized systematic evaluations and promote the development of the evidence-based practice of digital psychological interventions in perinatal depression. Literature included in systematic reviews and meta-analyses should also strictly follow the PRISMA statement to improve the quality of the review and the level of evidence and to provide a scientific basis for advancing the clinical translation of research results.

This study is an early systematic re-evaluation focusing on digital psychological interventions for reducing perinatal depression and provides a reference for promoting an evidence-based practice of digital psychological interventions in women with perinatal depression. This review suggests that digital psychological interventions have a positive effect on reducing perinatal depression, and the use of digital psychological interventions for the treatment and care of women in the perinatal period should be considered in medical practice to increase the accessibility of medical care and reduce women’s sense of stigma. However, the methodological quality and level of evidence of the current meta-analyses are low, the outcome indicators of the studies mostly used scales based on subjective evaluation, and there was a lack of objective quantitative analysis, which may have impacted the reliability and accuracy of the results of this study. Therefore, the effectiveness of digital psychological interventions in reducing perinatal depression needs to be supported by higher-level evidence. More high-quality, large-sample, multicenter clinical trials should be conducted in the future to compare different intervention forms and durations; provide the best level of support; lay the foundation for developing scientific, rigorous, standardized systematic evaluations; maximize long-term effects; and promote the development of evidence-based digital psychological interventions for perinatal depression.