College Students’ Trust in Generative AI for Mental Health

OBJECTIVE: This study aimed to examine college students' trust in generative artificial intelligence (AI) for mental health information and decisions. METHODS: Among 926 undergraduates at two institutions in the 2024-2025 Healthy Minds Study, demographic and clinical correlates of dichotomized trust ratings were examined. RESULTS: Overall, 31% trusted AI for mental health information, and 13% trusted AI for mental health decisions. Severe depression, anxiety, and therapy history were not significantly associated with trust. Students with (vs. without) a lifetime psychiatric diagnosis trusted AI less for information (28% vs. 34%). Lesbian, gay, bisexual, and queer (LGBQ; vs. non-LGBQ) students trusted AI less for information (21% vs. 38%) and decisions (7% vs. 17%). International (vs. domestic) students trusted AI more for information (52% vs. 29%), and Asian (vs. White) students trusted AI more for decisions (17% vs. 11%). CONCLUSIONS: Trust varied by identity but not by most clinical characteristics. Clinicians should ask patients about AI use.

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Publication Details

Journal
Psychiatric Services
Published
2026-07-30
DOI
https://doi.org/10.1176/appi.ps.20260116
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

College Students’ Trust in Generative AI for Mental Health

Tiffany Yip, Cindy H. Liu
Psychiatric Services
Artificial Intelligence in Healthcare and Education
article

College Students’ Trust in Generative AI for Mental Health

Tiffany Yip, Cindy H. Liu
article en

Abstract

OBJECTIVE: This study aimed to examine college students' trust in generative artificial intelligence (AI) for mental health information and decisions. METHODS: Among 926 undergraduates at two institutions in the 2024-2025 Healthy Minds Study, demographic and clinical correlates of dichotomized trust ratings were examined. RESULTS: Overall, 31% trusted AI for mental health information, and 13% trusted AI for mental health decisions. Severe depression, anxiety, and therapy history were not significantly associated with trust. Students with (vs. without) a lifetime psychiatric diagnosis trusted AI less for information (28% vs. 34%). Lesbian, gay, bisexual, and queer (LGBQ; vs. non-LGBQ) students trusted AI less for information (21% vs. 38%) and decisions (7% vs. 17%). International (vs. domestic) students trusted AI more for information (52% vs. 29%), and Asian (vs. White) students trusted AI more for decisions (17% vs. 11%). CONCLUSIONS: Trust varied by identity but not by most clinical characteristics. Clinicians should ask patients about AI use.

Psychiatric Services
Brigham and Women's Hospital (US), Harvard University (US), Fordham University (US)
Quality Education
Openalex Percentile: Top 12%
Artificial Intelligence in Healthcare and Education
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