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Paper Type
ERF
Description
The COVID-19 outbreak has witnessed a significant increase in the development and testing of healthcare chatbots. However, this could raise ethical concerns and pose challenges for responsible research in sensitive healthcare areas such as mental health. Our study focuses on the application of the Social Presence theory to mental-health chatbots. We use quantitative content analysis to determine if users in high-risk mental-health situations require a higher level of social presence from chatbots. Our research contributes to designing improved mental-health chatbots.
Paper Number
1679
Recommended Citation
THIMMANAYAKANAPALYA, Sagarika Suresh; Singh, Raghvendra; Mulgund, Pavankumar; Sun, Ying-Chih; and Sharman, Raj, "The Effect of Varying User Risk Levels on Perceived Social Presence in Mental Health Chatbots" (2023). AMCIS 2023 Proceedings. 19.
https://aisel.aisnet.org/amcis2023/sig_odis/sig_odis/19
The Effect of Varying User Risk Levels on Perceived Social Presence in Mental Health Chatbots
The COVID-19 outbreak has witnessed a significant increase in the development and testing of healthcare chatbots. However, this could raise ethical concerns and pose challenges for responsible research in sensitive healthcare areas such as mental health. Our study focuses on the application of the Social Presence theory to mental-health chatbots. We use quantitative content analysis to determine if users in high-risk mental-health situations require a higher level of social presence from chatbots. Our research contributes to designing improved mental-health chatbots.
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