Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Oct 2, 2024
Date Accepted: Feb 25, 2025
An Expert, Interdisciplinary Analysis of AI Driven Chatbots for Mental Health Support: A Mixed-Methods Study
ABSTRACT
Background:
Background:
Recent years have seen an immense surge in the creation and adoption of Mental Health Chatbots — artificially intelligent systems which attempt to mimic human conversation through text and voice. Their aim; to provide empathic responses in support of the delivery of personalised mental health support. These tools are often presented as offering immense potential; however it is also essential that we understand the risks of their deployment, including their potential adverse impacts on users' mental well-being.
Objective:
Objective:
While several studies within Human-Computer Interaction and related fields have examined users’ perceptions of such systems, few studies have engaged mental health professionals in critical analysis of their conduct as mental health support tools. This paper comprises, in turn, an effort to assess the ethical and pragmatic, clinical implications of employing chatbots for therapeutic ends.
Methods:
Methods:
By engaging 11 multidisciplinary participants in a mixed-methods and hands-on analysis, an in-depth assessment of therapeutic chatbots’ features and implications for mental health support is uncovered.
Results:
Results:
The findings of this work highlight how the financial and organisational fragmentation of equitable care creates opportunities for novel digital solutions, how therapeutic intervention - while conversational - involves more than chat, and the promise of designing for therapeutic relationships which yet invites numerous risks.
Conclusions:
Conclusions:
Through this work, we contribute insight into the expert perspective on mental health chatbot design and underscore the necessity for ongoing critical assessment and iterative refinement to maximise the benefits and minimise the risks associated with integrating AI into mental health support — providing researchers and designers alike with new knowledge of the needs and perspectives of expert professional users essential to the ethical and effective design of mental health chatbots.
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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.