Should AI Have Humanlike Self-disclosure in the Mental Health Intervention? The Moderated Mediation Effect of Negative Emotion

With the increasing concerns about psychological issues and limited mental healthcare resources, chatbots have emerged as a promising therapeutic solution. This study investigates the psychological mechanisms underlying human-chatbot interactions in mental healthcare, focusing on the roles of self-disclosure strategies, emotion recognition, and users' negative emotions. Through a 2 × 3 between-group factorial design involving 197 subjects, this research explores how chatbot self-disclosure strategies and emotion recognition capabilities influence users' perceived empathy and authenticity, with users' negative emotions as a moderating factor. By examining how different chatbot therapeutic interventions influence user perceptions across negative emotion states, this research provides practical insights for designing personalized therapeutic chatbot interventions in mental healthcare.

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Publication Details

Journal
ScholarSpace (University of Hawaii at Manoa)
Published
2025-12-23
Primary Topic
Digital Mental Health Interventions
Type
article
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article

Should AI Have Humanlike Self-disclosure in the Mental Health Intervention? The Moderated Mediation Effect of Negative Emotion

Zixuan Meng, Jianing Gao, Jingjun (David) Xu
ScholarSpace (University of Hawaii at Manoa)
Digital Mental Health Interventions
article

Should AI Have Humanlike Self-disclosure in the Mental Health Intervention? The Moderated Mediation Effect of Negative Emotion

Zixuan Meng, Jianing Gao, Jingjun (David) Xu
article en

Abstract

With the increasing concerns about psychological issues and limited mental healthcare resources, chatbots have emerged as a promising therapeutic solution. This study investigates the psychological mechanisms underlying human-chatbot interactions in mental healthcare, focusing on the roles of self-disclosure strategies, emotion recognition, and users' negative emotions. Through a 2 × 3 between-group factorial design involving 197 subjects, this research explores how chatbot self-disclosure strategies and emotion recognition capabilities influence users' perceived empathy and authenticity, with users' negative emotions as a moderating factor. By examining how different chatbot therapeutic interventions influence user perceptions across negative emotion states, this research provides practical insights for designing personalized therapeutic chatbot interventions in mental healthcare.

ScholarSpace (University of Hawaii at Manoa)
Openalex Percentile: Top 30%
Digital Mental Health Interventions
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