Exploring Effects of Chatbot-based Social Contact on Reducing Mental Illness Stigma

要旨

Chatbots have been designed to provide interventions in mental healthcare. However, how chatbot-based social contact can mitigate social stigma in mental illness remains under-explored. We designed two chatbots that deliver either first-person or third-person narratives about mental illness and evaluated them using a mixed methods study. Compared to a web survey group, participants in both chatbot groups decreased their beliefs that individuals are personally responsible for their mental illnesses, and increased their intentions to help. Additionally, participants in the first-person chatbot group showed a reduced level of fear, and a lower desire for social distance from people with mental illness. Many in the first-person chatbot group also reported a feeling of relationship with the chatbot, and chose to phrase their responses empathetically. Results demonstrated that chatbot-based social contact has promising potential for mitigating mental illness stigma. Implications for designing chatbot-based social contact are discussed.

著者
YI-CHIEH LEE
National University of Singapore, Singapore, Singapore
Yichao Cui
Cornell Tech, New York City, New York, United States
Jack Jamieson
NTT, Keihanna, Japan
Wayne Fu
Google, Seattle, Washington, United States
Naomi Yamashita
NTT, Keihanna, Japan
論文URL

https://doi.org/10.1145/3544548.3581384

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Mental Health and Care Work

Room Y05+Y06
6 件の発表
2023-04-27 01:35:00
2023-04-27 03:00:00