From stigma to comfort: examining stress and disclosure pathways in gay men’s interactions with AI chatbots

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Authors: Bilal Mazhar, Bolin Cao, Zhuoheng Yin, W M Tang
Cited by: 1
References: 37

Abstract

Artificial intelligence (AI) chatbots are increasingly used to provide mental health support, but their effectiveness depends on users' willingness to disclose personal information. How gay men develop comfort in sharing sensitive information about sexual orientation and sexual health with AI chatbots remains underexplined. Drawing on the Minority Stress Model and Communication Privacy Management theory, this study surveyed 1023 Chinese gay men to examine how perceived sexual stigma shapes comfort with sensitive self-disclosure to AI chatbots. Using Partial Least Squares Structural Equation Modelling, the study found that perceived sexual stigma did not directly predict disclosure comfort. Instead, its influence operated indirectly through a sequential pathway: stigma increased perceived stress, which promoted general emotional disclosure, and this in turn enhanced comfort with sensitive disclosure. Privacy concerns weakened this positive relationship. Fuzzy-set Qualitative Comparative Analysis further showed that general emotional disclosure was a core condition across multiple pathways leading to high disclosure comfort. These findings highlight a progressive disclosure pathway and position AI chatbots as a potential digital coping resource for stigmatized populations.

Fields of Study & Subjects

AI in Service Interactions Social Robot Interaction and HRI Digital Mental Health Interventions

Publication details

Journal / source
AIDS Care
Publisher
Informa UK Limited
Pages
1–13
Publication date
8 June 2026
Language
EN