A natural conversational interface that allows longitudinal symptom tracking would be extremely valuable in health wellness applications. However, the task of designing emotionally-aware agents for behavior change is still poorly understood. In this paper, we present the design and evaluation of an emotion-aware chatbot that conducts experience sampling in an empathetic manner. We evaluate it through a human-subject experiment with N=39 participants over the course of a week. Our results show that extraverts preferred the emotion-aware chatbot significantly more than introverts. Also, participants reported a higher percentage of positive mood reports when interacting with the empathetic bot. Finally, we provide guidelines for the design of emotion-aware chatbots for potential use in mHealth contexts.
@cite_10: Twenty professionals, half men and half women, half above and half below the age of thirty, were signaled at random during their normal waking hours by an electronic paging device or "beeper" over the course of a week. Self reports on seven cognitive and affective measures were analyzed using multivariate analysis of variance. Environment was demonstrated to have a highly significant impact on respondents' reports. Age and sex within age group effects as well as significant interactions between environment and age and sex appeared. A characteristic profile of life experiences of professionals emerged in which there appeared significant contrasts in cognitive and affective states, particularly at home and work, but in recreation and transportation as well. The research is introduced as a new method for examining personality in the normal range of environments which persons typically inhabit. The results serve to reinforce the belief that personality is not expressed consistently across environments, and underscores the limitations of measuring personality in a single and often atypical testing situation. The introduction of this new method provides some promise for advancing personality research through providing a more representative picture of persons' typical experience than has been possible previously.
@cite_6: Lee Sailer Department of Anthropology, University of Pittsburgh, Pittsburgh, Pennsylvania 15260 "A measurement whose accuracy is completely unknown has no use whatever" [Wilson ( 1 07. p. 232)]. "A serious obstacle in the use of replications for increasing accuracy is the tendency to get closely agreeing repetitions for irrelevant reasons" [Wilson (107. p. 253)1. "My people don't lie to me" (Anonymous Anthropologist).
@cite_12: To understand the dynamics of mental health, it is essential to develop measures for the frequency and the patterning of mental processes in every-day-life situations. The Experience-Sampling Method (ESM) is an attempt to provide a valid instrument to describe variations in self-reports of mental processes. It can be used to obtain empirical data on the following types of variables: (a) frequency and patterning of daily activity, social interaction, and changes in location; (b) frequency, intensity, and patterning of psychological states, i.e., emotional, cognitive, and conative dimensions of experience; (c) frequency and patterning of thoughts, including quality and intensity of thought disturbance. The article reviews practical and methodological issues of the ESM and presents evidence for its short-and long-term reliability when used as an instrument for assessing the variables outlined above.
The experience sampling method (ESM) @cite_10 was born in 1970s with the advent of pagers. It is a validated technique used for capturing frequency, intensity, and overall patterns of one's emotional experience @cite_12 . ESM alleviates people's inability to provide accurate retrospective information on their daily behavior and experience by capturing such information in the moment @cite_6 .