Paper Type
Complete
Paper Number
PACIS2025-1733
Description
Amid rapid advancements in artificial intelligence (AI) technologies, mental health chatbots (MHCs) have emerged as innovative solutions in healthcare. Yet, our understanding of how users perceive the diverse possibilities enabled by MHCs—termed mental health chatbot affordances (MHCAs)—remains limited. To deepen insights into human-chatbot interaction in this context, we developed the MHCAs scale using a mixed-methods approach that integrates qualitative and quantitative techniques. In the qualitative phase, we conducted a literature review on affordances, and performed grounded theory-based interviews with 8 users and 4 developers/designers. A third-order construct of MHCAs was conceptualized, comprising 4 dimensions and 13 first-order constructs. In the quantitative phase, we conducted two surveys for scale development to generate reliable measurements. Subsequently, drawing on affordance theory and conservation of resources theory, a nomological survey was performed to examine how MHCAs enhance psychological resilience. Theoretical and practical implications are discussed.
Recommended Citation
Jialan, Shan; Deng, Zihao; and Deng, Zhaohua, "Classifying and measuring affordances of mental health chatbots (MHCAs)" (2025). PACIS 2025 Proceedings. 11.
https://aisel.aisnet.org/pacis2025/ishealthcare/ishealthcare/11
Classifying and measuring affordances of mental health chatbots (MHCAs)
Amid rapid advancements in artificial intelligence (AI) technologies, mental health chatbots (MHCs) have emerged as innovative solutions in healthcare. Yet, our understanding of how users perceive the diverse possibilities enabled by MHCs—termed mental health chatbot affordances (MHCAs)—remains limited. To deepen insights into human-chatbot interaction in this context, we developed the MHCAs scale using a mixed-methods approach that integrates qualitative and quantitative techniques. In the qualitative phase, we conducted a literature review on affordances, and performed grounded theory-based interviews with 8 users and 4 developers/designers. A third-order construct of MHCAs was conceptualized, comprising 4 dimensions and 13 first-order constructs. In the quantitative phase, we conducted two surveys for scale development to generate reliable measurements. Subsequently, drawing on affordance theory and conservation of resources theory, a nomological survey was performed to examine how MHCAs enhance psychological resilience. Theoretical and practical implications are discussed.
Comments
Healthcare