BRIEF RESEARCH REPORT article
Front. Psychiatry
Sec. Digital Mental Health
Facts Label for Transparent Communication of AI Risks in Mental Health Technology
- KM
Khatiya Moon 1
- MT
Matthew Tamura 2
- JR
J. R. Redmond 3
- GC
Gerry Craigen 2,4
- ZH
Zuhal Haidari 5
- BT
Brooke Trainum 5
- DK
Darlene King 6,7
1. Northwell Health, New Hyde Park, United States
2. University of Toronto, Toronto, Canada
3. new york university, New York, United States
4. University of Toronto Temerty Faculty of Medicine, Toronto, Canada
5. American Psychiatric Association, Washington, United States
6. University of Texas Southwestern Medical Center, Dallas, United States
7. Parkland Health, Dallas, United States
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Abstract
With interest in the adoption of artificial intelligence (AI)-enabled digital mental health technologies (AI-DMHTs) among the general population ceaselessly escalating, mental health clinicians are obliged to confront questions about their utility and safety for their practice. However, little guidance exists for developers on how to communicate risks to clinicians who may need to evaluate products for individuals with mental health concerns, individuals who are frequently vulnerable to such risks. We propose a standardized facts label for AI-DMHTs designed to enhance transparency and awareness about these tools and their risks to users, patients, and clinicians. This framework was developed by a multidisciplinary team from the American Psychiatric Association Committee on Mental Health Information Technology through iterative expert review and external clinician consultation, drawing upon existing scholarship in risk communication and informed consent, as well as international AI governance frameworks. The resulting facts label framework is composed of 8 sections: key identifying information, intended use, warnings, risks and limitations, model information, clinical evidence, accessibility and usability considerations, and privacy and security. This research represents a practical step toward responsible utilization of AI-DMHTs and aims to serve as a foundation for continued multidisciplinary collaboration regarding the development and governance of AI risk communication in the domain of mental health and healthcare more broadly.
Summary
Keywords
AI Governance, artificial intelligence, health technology, Mental Health, Risk Communication, Transparency
Received
21 May 2026
Accepted
15 July 2026
Copyright
© 2026 Moon, Tamura, Redmond, Craigen, Haidari, Trainum and King. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Darlene King
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.