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

Year: 2025

Type: conference-paper

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.

Source: ScholarSpace (University of Hawaii at Manoa)

Authors: Meng, Zixuan, Xu, Jingjun (David), Gao, Jianing

Language: English

Topic: Digital Mental Health Interventions

Subfield: Applied Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7117348912

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