Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Reimagining Therapy

Consumer Perceptions of Generative AI in Mental Health

Bibliographic Data

ID22411017
AuthorsKaiwen Xue (0000-0002-5434-1340, Faculty of Business and Law, School of Advertising, Marketing and Public Relations Queensland University of Technology Brisbane Queensland Australia, corresponding author), Sven Tuzovic (0000-0002-4043-9275, Faculty of Business and Law, School of Advertising, Marketing and Public Relations Queensland University of Technology Brisbane Queensland Australia), Udo Gottlieb (0000-0002-1439-4341, Faculty of Business and Law, School of Advertising, Marketing and Public Relations Queensland University of Technology Brisbane Queensland Australia)
Year2026
Volume60
Issue3
Publication date2026-09-01
Open AccessYes
TypeARTICLE
VenueJournal of Consumer Affairs (JOURNAL)
Journal identifiersISSN: 0022-0078 • E-ISSN: 1745-6606
PublisherWiley (PUBLISHER • GB)
DOI10.1111/joca.70066
OpenAlexW7168052546
LanguageEN
References cited50

Growing numbers of consumers are turning to Generative AI (GenAI) for mental health support, yet the psychological engagement processes underlying consumer–GenAI therapy interactions remain insufficiently understood. This gap limits our ability to explain why consumer experiences diverge, particularly in emotionally sensitive contexts requiring high levels of engagement. To address that, we examine why these experiences vary and what mechanisms contribute to these conflicting outcomes. Drawing on 30 semi‐structured interviews, we develop an integrative framework outlining an engagement process between consumers and GenAI therapy. Grounded in cognitive appraisal theory, the framework shows that GenAI operates simultaneously as a functional service and a relational agent, meaning that consumer decisions are shaped by both utilitarian and relational evaluations. By explaining how consumers appraise, reappraise, and cope with GenAI therapy, the framework clarifies the mechanisms underlying divergent outcomes and offers insights for identifying potential risks in GenAI mental health services.

Cognition · Cognitive appraisal · Generative grammar · Meaning (existential) · Mental health · Perception · Process (computing) · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Digital Mental Health Interventions

  • Emotion And Adaptation

    Richard S Lazarus•Emotion and adaptation•1991

  • An Empathy-Driven, Conversational Artificial Intelligence Agent (Wysa) for Digital Mental Well-Being

    Open Access•Becky Inkster, Shubhankar Sarda et al.•JMIR mHealth and uHealth•2018

  • The generalizability of the psychoanalytic concept of the working alliance.

    Edward S Bordin•Psychotherapy•1979

  • User Acceptance of Information Technology

    Viswanath Venkatesh, Venkatesh Venkatesh et al.•MIS Quarterly•2003

  • Humans Mindlessly Treat AI Virtual Agents as Social Beings, but This Tendency Diminishes Among the Young

    Open Access•Jianan Zhou, Talya Porat et al.•Human Behavior and Emerging…•2024

  • Social presence

    Open Access•Kate M Xu, Lijia Lin et al.•British Journal of Educational…•2026

  • Ensuring patient and public involvement in the transition to AI‐assisted mental health care

    Open Access•Teodor Zidaru, Elizabeth Morrow et al.•Health Expectations•2021

  • Systematic Review of Cultural Aspects of Stigma and Mental Illness among Racial and Ethnic Minority Groups in the United States

    Open Access•Misra, Supriya Misra et al.•American Journal of Community…•2021

  • AI aversion or appreciation? A capability–personalization framework and a meta-analytic review

    Xin Qin, Xiang Zhou et al.•Psychological Bulletin•2025

  • Abductive Coding

    Open Access•Luis Vila‐henninger, Claire Dupuy et al.•Sociological Methods & Research•2024

  • AI Companions Reduce Loneliness

    Open Access•Julian De Freitas, Zeliha Oğuz-Uğuralp et al.•Journal of Consumer Research•2025

  • The GenAI Future of Consumer Research

    Open Access•Min-Hsiung Huang, Roland T Rust et al.•Journal of Consumer Research•2025

Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae