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

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Authors: Max Valentin Birk, Shruti Kochhar, Keris Myrick, Stephen Matthew Schueller, John Blake Torous
Cited by: 1
References: 38

Abstract

Unlabelled: 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.

Fields of Study & Subjects

Digital Mental Health Interventions Mental Health via Writing Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
JMIR Mental Health
Volume
13
Pages
e104118–e104118
Publication date
10 July 2026
Language
EN