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

Artificial Intelligence (2162) AI Language Models in Health Care (208) Generative Language Models Including ChatGPT (725) Psychiatry (97)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69910, first published .
Assessing the Accuracy and Reliability of Large Language Models in Psychiatry Using Standardized Multiple-Choice Questions: Cross-Sectional Study

Assessing the Accuracy and Reliability of Large Language Models in Psychiatry Using Standardized Multiple-Choice Questions: Cross-Sectional Study

Assessing the Accuracy and Reliability of Large Language Models in Psychiatry Using Standardized Multiple-Choice Questions: Cross-Sectional Study

Authors of this article:

Kaitlin Hanss1 Author Orcid Image ;   Karthik V Sarma1 Author Orcid Image ;   Anne L Glowinski1 Author Orcid Image ;   Andrew Krystal1 Author Orcid Image ;   Ramotse Saunders1 Author Orcid Image ;   Andrew Halls1 Author Orcid Image ;   Sasha Gorrell1 Author Orcid Image ;   Erin Reilly1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Cassim E, Prewitt M, Walsh D. Medical Apps for Physicians. Medical Clinics of North America 2025 View
  2. Ohu F, Burrell D, Jones L. Public Health Risk Management, Policy, and Ethical Imperatives in the Use of AI Tools for Mental Health Therapy. Healthcare 2025;13(21):2721 View
  3. Böke A, Hacker H, Chakraborty M, Baumeister-Lingens L, Vöckel J, Koenig J, Vogel D, Lichtenstein T, Vogeley K, Kambeitz-Ilankovic L, Kambeitz J. Observer-Independent Assessment of Content Overlap in Mental Health Questionnaires: Large Language Model–Based Study. JMIR AI 2025;4:e79868 View