User Experiences of Well-Being Chatbots
Abstract
Objective: The current paper conducted two parallel studies to explore user experiences of well-being conversational agents (CAs) and identify important features for engagement. Background: Students transitioning into university life take on greater responsibility, yet tend to sacrifice healthy behaviors to strive for academic and financial gain. Additionally, students faced an unprecedented pandemic, leading to remote courses and reduced access to healthcare services. One tool designed to improve healthcare accessibility is well-being CAs. CAs have addressed mental health support in the general population but have yet to address physical well-being support and accessibility to those in disadvantaged socio-economic backgrounds where healthcare access is further limited. Method: Study One comprised a thematic analysis of mental health applications featuring CAs from the public forum, Reddit. Study Two explored emerging usability themes of an SMS-based CA designed to improve accessibility to well-being services alongside a commercially available CA, Woebot. Results: Study One identified several themes, including accessibility and availability, communication style, and anthropomorphism as important features. Study Two identified themes such as user response modality, perceived CA role, question specificity, and conversation flow control as critical for user engagement. Conclusion: Various themes emerged from individuals’ experiences regarding CA features, functionality, and responses. The mixed experiences relevant to the communication and conversational styles between the CA and the user suggest varied motivations for using CAs for mental and physical well-being. Application: Practical recommendations to encourage continued use include providing dynamic response modalities, anthropomorphizing the chatbot, and calibrating expectations early.
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Rule-based chatbot apps have more promising user engagement, with positive app store ratings and qualitative studies finding that users appreciate the human-like interaction and social support.
“Rule-based chatbot apps have more promising user engagement, with positive app store ratings19,20 and qualitative studies finding that users appreciate the human-like interaction and social support19–23.”
From “It happened to be the perfect thing”: experiences of generative AI chatbots for mental health (2024) · cites this paper as [23]
Qualitative studies published so far include thematic analyses of user forum comments on both generative AI and rule-based DMHIs, student survey responses on companion-focused generative AI chatbots, and semi-structured interviews with hospital outpatients who were asked to try ChatGPT for mental health support.
“Qualitative studies published so far include thematic analyses of user forum comments on both generative AI and rule-based DMHIs23, student survey responses on companion-focused generative AI chatbots48, and semi-structured interviews with hospital outpatients who were asked to try ChatGPT for mental health support49.”
From “It happened to be the perfect thing”: experiences of generative AI chatbots for mental health (2024) · cites this paper as [23]
Cites
Using thematic analysis in psychology
Braun, V., & Clarke, V. (2006) · Qualitative Research in Psychology · doi:10.1191/1478088706qp063oa · Cited by 194,414 · see citing works
Effects of COVID-19 on College Students’ Mental Health in the United States: Interview Survey Study
Son, C., Hegde, S., Smith, A., Wang, X., & Sasangohar, F. (2020) · Journal of Medical Internet Research · doi:10.2196/21279 · Cited by 2,822 · see citing works
Fitzpatrick, K. K., Darcy, A., & Vierhile, M. (2017) · JMIR Mental Health · doi:10.2196/mental.7785 · Cited by 2,730 · cited 3× · see citing works
“…comments including helpfulness, usefulness, ease of use, conversation repetition, limitations in natural conversation and chatbot understanding, content length, and communication style of the chatbot (Fitzpatrick et al., 2017; Gardiner et al., 2017; Hudlicka, 2013; Inkster et al., 2018).”
BackgroundWang, X., Hegde, S., Son, C., Keller, B., Smith, A., & Sasangohar, F. (2020) · Journal of Medical Internet Research · doi:10.2196/22817 · Cited by 1,463 · see citing works
Inkster, B., Sarda, S., & Subramanian, V. (2018) · doi:10.2196/preprints.12106 · Cited by 1,063 · see citing works
Mental health problems in college freshmen: Prevalence and academic functioning
Bruffaerts, R., Mortier, P., Kiekens, G., Auerbach, R. P., Cuijpers, P., Demyttenaere, K., Green, J. G., Nock, M. K., & Kessler, R. C. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.07.044 · Cited by 1,047 · see citing works
Lattie, E. G., Adkins, E. C., Winquist, N., Stiles-Shields, C., Wafford, Q. E., & Graham, A. K. (2019) · Journal of Medical Internet Research · doi:10.2196/12869 · Cited by 843 · see citing works
Mobile Text Messaging for Health: A Systematic Review of Reviews
Hall, A. K., Cole-Lewis, H., & Bernhardt, J. M. (2015) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-031914-122855 · Cited by 815 · see citing works
Spotting fake reviewer groups in consumer reviews
Mukherjee, A., Liu, B., & Glance, N. (2012) · Proceedings of the 21st international conference on World Wide Web · doi:10.1145/2187836.2187863 · Cited by 773 · see citing works
College Students and Eating Habits: A Study Using An Ecological Model for Healthy Behavior
Sogari, G., Velez-Argumedo, C., Gomez, M. I., & Mora, C. (2018) · Nutrients · doi:10.3390/nu10121823 · Cited by 646 · see citing works
Establishing the computer-patient working alliance in automated health behavior change interventions
Bickmore, T., Gruber, A., & Picard, R. (2005) · Patient Education and Counseling · doi:10.1016/j.pec.2004.09.008 · Cited by 494 · see citing works
User Experiences of Social Support From Companion Chatbots in Everyday Contexts: Thematic Analysis
Ta, V., Griffith, C., Boatfield, C., Wang, X., Civitello, M., Bader, H., DeCero, E., & Loggarakis, A. (2020) · Journal of Medical Internet Research · doi:10.2196/16235 · Cited by 461 · cited 2× · see citing works
“For instance, Ta et al. (2020) identi fi ed four themes: in-formational, emotional, appraisal, and companion support.”
BackgroundResultFox, M. C., Ericsson, K. A., & Best, R. (2011) · Psychological bulletin · doi:10.1037/a0021663 · Cited by 442 · see citing works
Deliens, T., Deforche, B. I., Bourdeaudhuij, I. D., & Clarys, P. (2015) · BMC Public Health · doi:10.1186/s12889-015-1553-4 · Cited by 415 · see citing works
D’Alfonso, S. (2020) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2020.04.005 · Cited by 408 · see citing works
Ebert, D. D., Mortier, P., Kaehlke, F., Bruffaerts, R., Baumeister, H., Auerbach, R. P., Alonso, J., Vilagut, G., Martínez, K. U., Lochner, C., et al. (2019) · International Journal of Methods in Psychiatric Research · doi:10.1002/mpr.1782 · Cited by 407 · see citing works
PHILLIPS, P. B. (1965) · American Journal of Psychiatry · doi:10.1176/ajp.121.10.1027-a · Cited by 392 · see citing works
Prins, M. A., Verhaak, P. F. M., Bensing, J. M., & van der Meer, K. (2008) · Clinical Psychology Review · doi:10.1016/j.cpr.2008.02.009 · Cited by 271 · cited 1× · see citing works
“…black or Hispanic individuals, and younger adults, smartphones are sometimes the only means to access reliable internet at home (Anderson & Horrigan, 2016), yet are also the same individuals that are less likely to receive or even seek treatment for mental health issues (Prins et al., 2008).”
BackgroundDarcy, A., Daniels, J., Salinger, D., Wicks, P., & Robinson, A. (2021) · JMIR Formative Research · doi:10.2196/27868 · Cited by 260 · see citing works
Torous, J., Chan, S. R., Yee-Marie Tan, S., Behrens, J., Mathew, I., Conrad, E. J., Hinton, L., Yellowlees, P., & Keshavan, M. (2014) · JMIR Mental Health · doi:10.2196/mental.4004 · Cited by 228 · see citing works
Using Health Chatbots for Behavior Change: A Mapping Study
Pereira, J., & Díaz, Ó. (2019) · Journal of Medical Systems · doi:10.1007/s10916-019-1237-1 · Cited by 199 · see citing works
Stawarz, K., Preist, C., Tallon, D., Wiles, N., & Coyle, D. (2018) · Journal of Medical Internet Research · doi:10.2196/10120 · Cited by 198 · see citing works
Optimizing Students’ Mental Health and Academic Performance: AI-Enhanced Life Crafting
Dekker, I., De Jong, E. M., Schippers, M. C., De Bruijn-Smolders, M., Alexiou, A., & Giesbers, B. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01063 · Cited by 176 · see citing works
Nicholas, J., Fogarty, A. S., Boydell, K., & Christensen, H. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.7273 · Cited by 158 · see citing works
An Overview of Machine Learning in Chatbots
Suta, P., Lan, X., Wu, B., Mongkolnam, P., & Chan, J. H. (2020) · International Journal of Mechanical Engineering and Robotics Research · doi:10.18178/ijmerr.9.4.502-510 · Cited by 152 · see citing works
Gardiner, P. M., McCue, K. D., Negash, L. M., Cheng, T., White, L. F., Yinusa-Nyahkoon, L., Jack, B. W., & Bickmore, T. W. (2017) · Patient Education and Counseling · doi:10.1016/j.pec.2017.04.015 · Cited by 139 · see citing works
Towards understanding and detecting fake reviews in app stores
Martens, D., & Maalej, W. (2019) · Empirical Software Engineering · doi:10.1007/s10664-019-09706-9 · Cited by 137 · see citing works
Blanchard, C. M., Fisher, J., Sparling, P. B., Hunt-Shanks, T. T., Nehl, E. J., Rhodes, R. E., Courneya, K. S., & Baker, F. (2009) · Journal of Nutrition Education and Behavior · doi:10.1016/j.jneb.2007.12.006 · Cited by 136 · see citing works
Gabrielli, S., Rizzi, S., Bassi, G., Carbone, S., Maimone, R., Marchesoni, M., & Forti, S. (2021) · JMIR mHealth and uHealth · doi:10.2196/27965 · Cited by 125 · cited 1× · see citing works
“Recent studies showed that users considered CAs effective and supportive, suggesting that CAs are an ideal tool for addressing health-related behavioral improvements (Daley et al., 2020; Dekker et al., 2020; Gabrielli et al., 2021; Lattie et al., 2019).”
MethodCadigan, J. M., Lee, C. M., & Larimer, M. E. (2018) · Prevention Science · doi:10.1007/s11121-018-0875-8 · Cited by 119 · see citing works
Ethical implications of conversational agents in global public health
Luxton, D. D. (2020) · Bulletin of the World Health Organization · doi:10.2471/blt.19.237636 · Cited by 108 · see citing works
Virtual training and coaching of health behavior: Example from mindfulness meditation training
Hudlicka, E. (2013) · Patient Education and Counseling · doi:10.1016/j.pec.2013.05.007 · Cited by 104 · see citing works
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Bice, K. C., & Lewis, C. (1989) · Cited by 103 · see citing works
Preliminary Evaluation of the Engagement and Effectiveness of a Mental Health Chatbot
Daley, K., Hungerbuehler, I., Cavanagh, K., Claro, H. G., Swinton, P. A., & Kapps, M. (2020) · Frontiers in Digital Health · doi:10.3389/fdgth.2020.576361 · Cited by 101 · cited 3× · see citing works
“Study one yielded a high quantity of broad comments, with many out-of-scope comments, yet captured experiences that would not have been observed in a laboratory setting (eg Daley et al., 2020; Fitzpatrick et al., 2017; Inkster et al., 2018).”
BackgroundMethodBoard on Human-Systems Integration, Education, D. O. B. A. S. S. A., & National Academies of Sciences, E. (2021) · National Academies Press eBooks · doi:10.17226/26355 · Cited by 99 · see citing works
Digital Health Solutions for Mental Health Disorders During COVID-19
Chew, A., Ong, R., Lei, H.-H., Rajendram, M., Grisan, K. V., Verma, S. K., Fung, D. S. S., Leong, J.-Y., & Gunasekeran, D. V. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.582007 · Cited by 64 · see citing works
Ford, E. M., Shepherd, S., Jones, K. H., & Hassan, L. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2020.592237 · Cited by 59 · see citing works
La santé mentale et les comportements alimentaires: Une relation bidirectionnelle
Polivy, J., & Herman, C. P. (2005) · Canadian Journal of Public Health · doi:10.1007/bf03405201 · Cited by 50 · see citing works
Natural Language Processing for Industry
Quarteroni, S. (2018) · Informatik-Spektrum · doi:10.1007/s00287-018-1094-1 · Cited by 45 · see citing works
User Perspectives of Mood-Monitoring Apps Available to Young People: Qualitative Content Analysis
Widnall, E., Grant, C., Wang, T., Cross, L., Velupillai, S. U., Roberts, A., Stewart, R. J., Simonoff, E. A., & Downs, J. M. (2020) · JMIR mhealth and uhealth · doi:10.2196/18140 · Cited by 43 · see citing works
Mason, A., Jang, K., Morley, K. C., Scarf, D., Collings, S. C., & Riordan, B. C. (2021) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2020.0521 · Cited by 25 · see citing works
Riordan, B. C., Conner, T. S., Flett, J. A. M., & Scarf, D. (2017) · Digital Health · doi:10.1177/2055207617707627 · Cited by 24 · see citing works
Lietaer, G., & Brodley, B. T. (2003) · Person-Centered & Experiential Psychotherapies · doi:10.1080/14779757.2003.9688320 · Cited by 9 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
“It happened to be the perfect thing”: experiences of generative AI chatbots for mental health
Siddals, S., Torous, J., & Coxon, A. (2024) · npj Mental Health Research · doi:10.1038/s44184-024-00097-4 · Cited by 241 · see citing works
Does the Digital Therapeutic Alliance Exist? Integrative Review
Malouin-Lachance, A., Capolupo, J., Laplante, C., & Hudon, A. (2025) · JMIR Mental Health · doi:10.2196/69294 · Cited by 103 · see citing works
User perceptions and experiences of an AI-driven conversational agent for mental health support
Chaudry, B., & Debi, H. R. (2024) · mHealth · doi:10.21037/mhealth-23-55 · Cited by 78 · see citing works
The Digital Therapeutic Alliance With Mental Health Chatbots: Diary Study and Thematic Analysis
Xu, Z., Lee, Y., Stasiak, K., Warren, J., & Lottridge, D. M. (2025) · JMIR Mental Health · doi:10.2196/76642 · Cited by 50 · see citing works
Self-citationA New Research Model for Artificial Intelligence–Based Well-Being Chatbot Engagement: Survey Study
Yang, Y., Tavares, J., & Oliveira, T. (2024) · JMIR Human Factors · doi:10.2196/59908 · Cited by 42 · see citing works
Chen, T. H., Chu, G., Pan, R.-H., & Ma, W. (2025) · Expert Review of Medical Devices · doi:10.1080/17434440.2025.2466742 · Cited by 16 · see citing works
Wygnańska, J. (2023) · Qualitative Sociology Review · doi:10.18778/1733-8077.19.4.05 · Cited by 12 · see citing works
Chatbots in Psychology: Revolutionizing Clinical Support and Mental Health Care
de Filippis, R., & Foysal, A. A. (2024) · Voice of the Publisher · doi:10.4236/vp.2024.103025 · Cited by 15 · see citing works
Generative AI and the profession of genetic counseling
Meekins‐Doherty, L., Dive, L. L., McEwen, A., & Sexton, A. (2025) · Journal of Genetic Counseling · doi:10.1002/jgc4.2009 · Cited by 9 · see citing works
Dechant, M., Lash, E., Shokr, S., & O’Driscoll, C. (2025) · JMIR Formative Research · doi:10.2196/74411 · Cited by 9 · see citing works
Gupta, S., Saxena, S., & Kataria, S. (2025) · Psychology and Marketing · doi:10.1002/mar.70093 · Cited by 7 · see citing works
Félix, B., Braga, C., Ntinga, X., Till, S. C., Meoli, L., van Heerden, A. C., Melo, R., Verdezoto, N. X., Densmore, M., & Nunes, F. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3661504 · Cited by 6 · see citing works
Meadows, R. P., & Hine, C. (2024) · Culture Medicine and Psychiatry · doi:10.1007/s11013-024-09876-2 · Cited by 5 · see citing works
Allen, A., Young, A. H., Jellesma, F. C., Vorobev, A., Ivanova, E., Babakov, N., Gisnarian, A., & Kannis‐Dymand, L. (2026) · Journal of Affective Disorders · doi:10.1016/j.jad.2026.121275 · Cited by 5 · see citing works
Navigating relationships with GenAI chatbots: User attitudes, acceptability, and potential
Vowels, L. M., Francois‐Walcott, R. R. R., Grandjean, M., Darwiche, J., & Vowels, M. J. (2025) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2025.100183 · Cited by 4 · see citing works
Arjanto, P., & Senduk, F. F. W. (2024) · Journal of Community Mental Health and Public Policy · doi:10.51602/cmhp.v6i2.144 · Cited by 4 · see citing works
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Porna, S. B., Ahmad, M., Vallejo, R. G., Shahzadi, I., & Rahman, M. A. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-9173-0.ch011 · Cited by 4 · see citing works
Kettle, L., Herrera, K. M. G., Pithayarungsarit, P., Simpson, K. L., & Lee, Y. (2023) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/21695067231192927 · Cited by 2 · see citing works
Self-citationDando, C. J., & Adam, C. E. (2025) · Scientific Reports · doi:10.1038/s41598-025-93281-1 · Cited by 3 · see citing works
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Yang, Y., Tavares, J., & Oliveira, T. (2026) · International Journal of Telemedicine and Applications · doi:10.1155/ijta/9055091 · Cited by 2 · see citing works
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Liu, Q., Liu, S., Si, G., & Cui, K. (2025) · Industrial Management & Data Systems · doi:10.1108/imds-05-2025-0643 · Cited by 1 · see citing works
Hwang, L. J., Li, H., & Feng, B. (2026) · Behaviour and Information Technology · doi:10.1080/0144929x.2026.2633768 · Cited by 1 · see citing works
Xu, Z., Lee, Y., Stasiak, K., Warren, J., & Lottridge, D. M. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791614 · Cited by 1 · see citing works
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Li, J., Li, H., Zhu, H., Walter, H., Banaschewski, T., Li, C., Li, X., & Zhang, Y. (2026) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2026.106460 · Cited by 1 · see citing works
Xu, Z., Warren, J., & Lottridge, D. M. (2025) · International Conference on Human-Engaged Computing (ICHEC) · doi:10.1145/3786995.3787059 · Cited by 1 · see citing works
Future Me: Promoting a future-oriented outlook through conversation with our future self.Preprint
Lash, E., Dechant, M., & O’Driscoll, C. (2024) · doi:10.31219/osf.io/eh62p · Cited by 1 · see citing works
Dechant, M., Lash, E., Shokr, S., & O’Driscoll, C. (2025) · doi:10.2196/preprints.74411
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Garg, M., Punia, B. K., Bansal, G., & Punia, V. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8612-6.ch008
Lan, Y., Liu, S., Liu, C., & Chen, H. (2026) · doi:10.2196/preprints.94129
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Park, S., Song, Y., Cho, S., & Yun, M. H. (2026) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3772363.3798485
Yang, Y., Tavares, J., & Oliveira, T. (2026) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2026.100413
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Wut, T. M., Low, M. P., & Tam, K.-W. (2026) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2026.102956
Bartali, V., Croes, E. A. J., Antheunis, M. L., Bosse, T., & de Groot, R. H. M. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2677759 · Cited by 1 · see citing works
Bartali, V., Croes, E. A. J., Bosse, T., de Groot, R. H. M., & Antheunis, M. L. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-26717-7_3
Park, S., Song, Y., & Cho, S. (2026) · IEEE Access · doi:10.1109/access.2026.3724790
Kettle, L., Pithayarungsarit, P., Herrera, K. M. G., Simpson, K. L., Sharifi, K., & Lee, Y. (2026) · Safety · doi:10.3390/safety12040109
Self-citationThe Use of Artificial Intelligence Systems in Mental Health Treatment: A Thematic Review
Frankenfield, J., Sobel, B. M., & Chaparro, B. (2026) · Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care · doi:10.1177/2327857926151127
Shah, M. N. B. M., & Zaharim, M. Z. A. (2026) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2026.100403
Salazar-Altamirano, M. A., Martínez-Arvizu, O. J., Coronil, A. G., & Ravina-Ripoll, R. (2026) · Journal of Manufacturing Technology Management · doi:10.1108/jmtm-02-2026-0178
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Bui, T. (2026) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3776574.3828965
Bu, Y., 张, 震., 黎, 雨., & Wang, S. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2739771
Apablaza-Noe, J. J., Cano, S. P., & Osega, J. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2739757
- Authors
- Kettle, L., & Lee, Y.-C.
- Affiliations
- George Mason University (US)
- Corresponding author
- Kettle, Liam
- Venue
- Human Factors: The Journal of the Human Factors and Ergonomics Society
- Publisher
- SAGE Publications
- Published
- 2023-03-14
- Volume
- 66
- Issue
- 6
- Pages
- 1703-1723
- ISSN
- 0018-7208 (ISSN-L)
- 1547-8181
- OpenAlex
- W4324129961
- Cited by
- 45
- References
- 43
- Citations by year
- 2026: 20 · 2025: 13 · 2024: 10 · 2023: 2
- FWCI
- 11.62
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Human Factors The Journal of the Human Factors and Ergonomics Society (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- chatbots, user experience, mental health support, physical well-being, anthropomorphism, Woebot, user engagement, health care access, university students, COVID-19 pandemic, socioeconomic deprivation
- MeSH terms
- Adult, Communication, Female, Health Services Accessibility, Humans, Male, Students, Universities, Young Adult
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