Digital Mental Health Research Priorities, Revisited for the AI and Large Language Model Era.

Authors

Max Valentin Birk, Shruti Kochhar, Keris Myrick, Stephen M Schueller, John Torous

Published in

JMIR mental health. Volume 13. Pages e104118. Jul 10, 2026. Epub Jul 10, 2026.

Abstract

Digital mental health has become an established part of mental health care, but the rapid arrival of large language models and other artificial intelligence (AI) tools has refocused attention on the evidence needed to guide the field. This editorial updates the research priorities articulated by JMIR Mental Health in 2023, while reaffirming their emphasis on equity, replicability, privacy, efficacy, and engagement. While the importance of these priorities has not changed in recent years, the urgency with which they must now be applied has. As digital tools become more clinically consequential, research must move beyond demonstrating that a technology is feasible, usable, or novel. The field now needs studies that clarify how these tools work, for whom they are beneficial, under what conditions they may cause harm, and how they can be ethically integrated into care. We call for research that is transparent about the technologies being studied, grounded in meaningful clinical questions, attentive to safety, and designed to produce knowledge that remains useful as specific products and models change.

PMID:
42430722
Bibliographic data and abstract were imported from PubMed on 11 Jul 2026.

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