Measuring the Effect of Mental Health Chatbot Personality on User Engagement
Moilanen, Joonas; Visuri, Aku; Suryanarayana, Sharadhi Alape; Alorwu, Andy; Yatani, Koji; Hosio, Simo (2022-12-29)
ACM
29.12.2022
Joonas Moilanen, Aku Visuri, Sharadhi Alape Suryanarayana, Andy Alorwu, Koji Yatani, and Simo Hosio. 2022. Measuring the Effect of Mental Health Chatbot Personality on User Engagement. In Proceedings of the 21st International Conference on Mobile and Ubiquitous Multimedia (MUM '22). Association for Computing Machinery, New York, NY, USA, 138–150. https://doi.org/10.1145/3568444.3568464
https://creativecommons.org/licenses/by/4.0/
© 2022 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.
https://creativecommons.org/licenses/by/4.0/
© 2022 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.
https://creativecommons.org/licenses/by/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202508045209
https://urn.fi/URN:NBN:fi:oulu-202508045209
Tiivistelmä
Abstract
Artificial Intelligence is seen as humanity’s current best bet to solve the looming crisis in healthcare. Conversational Agents, or chatbots, rely on advances in AI and are increasingly investigated in the context of digital mental health care. Given how they are end-user-facing and interactive communication tools, the user engagement felt when interacting with the bots is a critical consideration. In this work, we examine the effects of chatbot personalities on the experienced user engagement with the bot. We employed personalities that rely on the Big-5 Personality Theory. Among other findings, our quantitative results indicate that a highly conscientious chatbot is likely to foster the highest user engagement. Our qualitative and content analysis also reveals desired and undesired personality features for future mental health chatbots. We discuss our findings in light of digital mental health and propose novel research directions.
Artificial Intelligence is seen as humanity’s current best bet to solve the looming crisis in healthcare. Conversational Agents, or chatbots, rely on advances in AI and are increasingly investigated in the context of digital mental health care. Given how they are end-user-facing and interactive communication tools, the user engagement felt when interacting with the bots is a critical consideration. In this work, we examine the effects of chatbot personalities on the experienced user engagement with the bot. We employed personalities that rely on the Big-5 Personality Theory. Among other findings, our quantitative results indicate that a highly conscientious chatbot is likely to foster the highest user engagement. Our qualitative and content analysis also reveals desired and undesired personality features for future mental health chatbots. We discuss our findings in light of digital mental health and propose novel research directions.
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