Accepted for/Published in: JMIR Human Factors
Date Submitted: Jan 9, 2025
Open Peer Review Period: Feb 4, 2025 - Apr 1, 2025
Date Accepted: Aug 10, 2025
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Preferred Uses of Generative AI Chatbots in Mental Health Care: Exploring Practitioners’ Perspectives
ABSTRACT
Background:
Generative Artificial Intelligence (AI) chatbots have the potential to improve mental health care for practitioners and clients. Evidence demonstrates that AI chatbots can assist with tasks such as documentation, research, counselling, and therapeutic exercises. However, research examining practitioners’ perspectives is limited.
Objective:
Drawing on qualitative and quantitative data, this mixed-methods study investigates: (1) practitioners’ perspectives on different uses of Generative AI chatbots; (2) their likelihood of recommending chatbots to clients; and (3) whether recommendation likelihood increases after viewing a demonstration.
Methods:
Participants were 23 mental health practitioners (17 female, 6 male; M age = 39.39, SD = 16.20). In forty-five-minute interviews, participants selected their three most helpful uses of chatbots from 11 options and rated their likelihood of recommending chatbots to clients on a Likert-scale before and after a 11-minute chatbot demonstration.
Results:
Binomial tests found that Generating Case Notes was selected at greater-than-chance levels (p = .001), while Support with Session Planning (p = .863) and Identifying and Suggesting Literature (p = .096) were not. Although 55% (n = 12) were likely to recommend chatbots to clients, a binomial test found no significant difference from the 50% threshold (p = .738). A paired samples t-test found that recommendation likelihood increased significantly (p = .002) from pre-demonstration to post-demonstration.
Conclusions:
Findings suggest practitioners favour administrative uses of Generative AI and are more likely to recommend chatbots to clients after exposure. This study highlights the need for practitioner education and guidelines to support safe and effective AI integration in mental health care.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.