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This paper is in the following e-collection/theme issue:

Applications of AI (1084) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (3351) Depression and Mood Disorders; Suicide Prevention (2518) Chatbots and Conversational Agents (1231) Artificial Intelligence (5001) Generative Language Models Including ChatGPT (1627)

Published on in Vol 5 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/92817, first published .
Woman looking stressed at her phone on a bed

AI Chatbot Suicide Risk Detection and Response: Human Validation Study of the Open-Source VERA-MH Safety Evaluation

AI Chatbot Suicide Risk Detection and Response: Human Validation Study of the Open-Source VERA-MH Safety Evaluation

Authors of this article:

Kate H Bentley1, 2 Author Orcid Image ;   Luca Belli1, 3 Author Orcid Image ;   Adam M Chekroud1, 4 Author Orcid Image ;   Emily J Ward1 Author Orcid Image ;   Emily R Dworkin1 Author Orcid Image ;   Emily Van Ark1 Author Orcid Image ;   Kelly M Johnston1 Author Orcid Image ;   Will Alexander1 Author Orcid Image ;   Millard Brown1 Author Orcid Image ;   Matt Hawrilenko1 Author Orcid Image
Article Authors Cited by (4) Tweetations (5) Metrics

Journals

  1. Wu C, Lou N. Optimising AI-mediated wellness interventions’ design, engagement, and adaptation: Introducing the AI-DEA framework for mental health support and psychological change. Journal of Psychology and AI 2026;2(1) View
  2. McBain R, Huang E, Figueroa C, Zhang L, Cantor J. Making medical AI benchmarks clinically interpretable: the case of mental health. BMJ Mental Health 2026;29(1):e302921 View
  3. Pichowicz W, Kotas M, Kalka N, Dembowska J, Karska J, Piotrowski P, Misiak B. Responses of AI chatbots to escalating suicide risk: A simulation study of repeated interactions. Journal of Affective Disorders 2027;416:122586 View

Conference Proceedings

  1. A. Safaei A, M. Vowels L, J. Vowels M, Jha A, Rahimi S. Proceedings of the ACM/IEEE 29th International Conference on Model Driven Engineering Languages and Systems. Quantifying the Relationship Between Clinical Safety and Environmental Impact in Therapeutic LLMs View