Expressive Interviewing: A Conversational System for Coping with COVID -19 (2020)

Abstract: The ongoing COVID-19 pandemic has raised concerns for many regarding personal and public health implications, financial security and economic stability. Alongside many other unprecedented challenges, there are increasing concerns over social isolation and mental health. We introduce Expressive Interviewing – an interview-style conversational system that draws on ideas from motivational interviewing and expressive writing. Expressive Interviewing seeks to encourage users to express their thoughts and feelings through writing by asking them questions about how COVID-19 has impacted their lives. We present relevant aspects of the system’s design and implementation as well as quantitative and qualitative analyses of user interactions with the system. In addition, we conduct a comparative evaluation with a general purpose dialogue system for mental health that shows our system potential in helping users to cope with COVID-19 issues.

## introduction the covid-19 pandemic has changed our world in unimaginable ways, dramatically challenging our health system and drastically changing our daily lives. as we learned from recent large-scale analyses that were performed on social media datasets and extensive surveys, many people are currently experiencing increased anxiety, loneliness, depression, concerns for the health of family and themselves, unexpected unemployment, increased child care or homeschooling, and general concern with what the future might look like. 1 research in expressive writing @xcite and motivational interviewing @xcite has shown that even simple interactions where people talk about one particular experience can have significant psychological value. numerous studies have demonstrated their effectiveness in improving people's mental and physical health @xcite @xcite . both expressive writing and motivational interviewing rely on the fundamental idea that by putting emotional upheavals into words, one can start to understand them better and therefore gain a sense of agency and coherence of the thoughts and emotions surrounding their experience. in this paper, we introduce a new interview-style dialogue paradigm called expressive interviewing that unites strategies from expressive writing and motivational interviewing through a system that guides an individual to reflect on, express, and better understand their own thoughts and feelings during the pandemic. by encouraging introspection and selfexpression, the dialogue aims to reduce stress and anxiety. our system is currently online at https://expressiveinterviewing.org and available for anyone to try anonymously. ## expressive interviewing our system conducts an interview-style interaction with the users about how the covid-19 pandemic has been affecting them. the system's goal is to encourage users to write as much as possible about themselves, building upon previous findings regarding the psychological value of writing about personal upheavals and the use of reflective listening for behavioral change @xcite . the interview consists of a set of writing prompts in the form of questions about specific issues related to the pandemic. the system guides the interaction based on users responses, and provides reflective feedback and asks additional questions whenever appropriate. in order to provide reflective feedback, the system automatically detects the topics being discussed (e.g., work, family) or emotions being expressed (e.g., anger, anxiety), and responds with reflective statements that ask the user to elaborate or to answer a related question to explore that concept more deeply. for instance, if the system detects work as a topic of interest, it responds with "how has work changed under covid? what might you be able to do to keep your career moving during these difficult times?" after the interaction ends, i.e., all prompts have been answered by the user, the system provides detailed visual and textual feedback. ## analysis of user interactions after the system was launched (and up to when we conducted this analysis), we had 174 users interact with the system. we analyze these interactions to evaluate system usefulness, user engagement, and reflection effectiveness. ## comparative evaluations to assess the extent to which our expressive interviewing system delivers an engaging user experience, we conduct a comparative study between our system and the conversational mental health app woebot @xcite . we chose woebot over wysa as it was more widely available for covid-19 mental support at the time we were conducting our experiments and also for its use of predefined prompts, which was similar to our own strategies. we recruited 12 participants and asked them to interact independently with each system to discuss their covid-19 related concerns. participants include graduate and undergraduate students in our lab, 4 female and 8 male and with ages ranging between 22 to 35 years. more specifically, we asked them to use each system during 10-15 minutes and provide evaluative feedback pre-and postinteraction. the interaction with our system ended whenever the participant responded the four main prompts and reached the feedback page. while interacting with woebot, participants stopped after they interacted with the system for at least 10 minutes. to avoid cognitive bias, we randomized the order in which each participant evaluated the systems. in addition, we randomized the order in which the questions are shown in the evaluation form. to protect participant's privacy we did not link their interaction logs with each system with their evaluation responses. before interacting with either system, participants rated their life satisfaction and their stress level. after the interaction, participants reported again their stress level and rated several aspects of their interaction with the system, including ease of use, usefulness (in terms of discussing covid-19 related issues and motivation to write about it), overall experience, and satisfaction using mainly binary scales. for example, the questions "@xmath0 woebot expressive interviewing stress bef ore 91% 91% stress af ter 73% 64% overall, participants reported that expressive interviewing was easier to use, more useful to discuss their covid concerns and motivated them to write more than woebot. similarly, users reported a more meaningful interaction and a better overall experience. while these results are encouraging, it is important to note that this study has been conducted with a small pool of participants and that woebot was not specifically designed for discussing covid-19 concerns and it is of more general purpose than our system. nonetheless, our analysis suggests that a dialogue system such as expressive interviewing can be effective in helping users cope with covid-19 issues as compared to a general purpose dialogue system for mental health. ## ethical and privacy considerations during development, we followed suggestions of previous research on automated mental health counseling and adopted the goals of being respectful of user privacy, following evidence based methods, ensuring user safety, and being transparent in system capabilities @xcite . however, there are a number of open questions surrounding the use of conversational agents in healthcare and we need to continue to evaluate our system to ensure that it benefits users @xcite . the practices of motivational interviewing and expressive writing have numerous studies supporting their efficacy @xcite . the combination of these methods in an interviewing format has not previously been studied and we intend to continue publishing our findings as the user population expands and becomes more diverse. we will also continue to improve our system and assessment. in addition, we have taken efforts to secure users' data. for instance, we do not ask for identifiers and data is stored anonymously by session id. the website is secured with ssl. furthermore, the collected data is only accessible to researchers directly involved with our study. our study has been approved by the university of michigan irb (hum00182586). ## conclusion in this paper, we introduced an interview-style dialogue system called expressive interviewing to help people cope with the effects of the covid-19 pandemic. we provided a detailed description on how the system is designed and implemented. we analyzed a sample of 174 user interactions with our system and conducted analyses on aspects such as system usefulness, user engagement and reflection effectiveness. we also conducted a comparative evaluation study between our system and woebot, a general purpose dialogue system for mental health. our main findings suggest that users benefited from the reflective strategies used by our system and experienced meaningful interactions leading to reduced stress levels. furthermore, our system was judged to be easier to use and more useful than woebot when discussing covid-19 related concerns. in future work we intend to explore the applicability of the developed system to other healthrelated domains.