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

Methods and New Tools in Mental Health Research (504) Artificial Intelligence (1786) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1850) Machine Learning (1780) Natural Language Processing (812) Chatbots and Conversational Agents (648)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59479, first published .
The Opportunities and Risks of Large Language Models in Mental Health

The Opportunities and Risks of Large Language Models in Mental Health

The Opportunities and Risks of Large Language Models in Mental Health

Authors of this article:

Hannah R Lawrence1 Author Orcid Image ;   Renee A Schneider2 Author Orcid Image ;   Susan B Rubin1 Author Orcid Image ;   Maja J Matarić2 Author Orcid Image ;   Daniel J McDuff2 Author Orcid Image ;   Megan Jones Bell2 Author Orcid Image
Article Authors Cited by (21) Tweetations (13) Metrics

Journals

  1. Mansoor M, Ansari K. Early Detection of Mental Health Crises through Artificial-Intelligence-Powered Social Media Analysis: A Prospective Observational Study. Journal of Personalized Medicine 2024;14(9):958 View
  2. Ma Y, Zeng Y, Liu T, Sun R, Xiao M, Wang J. Integrating large language models in mental health practice: a qualitative descriptive study based on expert interviews. Frontiers in Public Health 2024;12 View
  3. Ferrara E. Large Language Models for Wearable Sensor-Based Human Activity Recognition, Health Monitoring, and Behavioral Modeling: A Survey of Early Trends, Datasets, and Challenges. Sensors 2024;24(15):5045 View
  4. Van Meter A, Wheaton M, Cosgrove V, Andreadis K, Robertson R, Laroia G. The Goldilocks Zone: Finding the right balance of user and institutional risk for suicide-related generative AI queries. PLOS Digital Health 2025;4(1):e0000711 View
  5. Levkovich I. Evaluating Diagnostic Accuracy and Treatment Efficacy in Mental Health: A Comparative Analysis of Large Language Model Tools and Mental Health Professionals. European Journal of Investigation in Health, Psychology and Education 2025;15(1):9 View
  6. Miller T, Durlik I, Kostecka E, Łobodzińska A, Łazuga K, Kozlovska P. Leveraging Large Language Models for Enhancing Safety in Maritime Operations. Applied Sciences 2025;15(3):1666 View
  7. A. Rutter L, Edinger A, Lorenzo-Luaces L, ten Thij M, Valdez D, Bollen J. Anxiety and Depression are Associated with More Distorted Thinking on Social Media: A Longitudinal Multi-Method Study. Cognitive Therapy and Research 2025 View
  8. Creswell Báez J, Victor B, Dysart C, Goldkind L. “I Don’t Understand It, but Okay”: An Empirical Study of Mental Health Practitioners’ Readiness to Use Large Language Models. Journal of Technology in Human Services 2025:1 View
  9. Kirkeby-Hinrup A, Stenseke J. The psychology of LLM interactions: the uncanny valley and other minds. Journal of Psychology and AI 2025;1(1) View
  10. Bunge E, Desage C. A Framework for Evaluating Mental Health Artificial Intelligence-based Conversational Agents. Journal of Technology in Behavioral Science 2025 View
  11. Jin Y, Liu J, Li P, Wang B, Yan Y, Zhang H, Ni C, Wang J, Li Y, Bu Y, Wang Y. The Applications of Large Language Models in Mental Health: Scoping Review. Journal of Medical Internet Research 2025;27:e69284 View
  12. Torous J, Linardon J, Goldberg S, Sun S, Bell I, Nicholas J, Hassan L, Hua Y, Milton A, Firth J. The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality. World Psychiatry 2025;24(2):156 View
  13. Swinger N, Baseman C, Ryu M, Abdullah S, Wiese C, Sherrill A, Arriaga R. There's No "I" in TEAMMAIT: Impacts of Domain and Expertise on Trust in AI Teammates for Mental Health Work. Proceedings of the ACM on Human-Computer Interaction 2025;9(2):1 View
  14. Scholich T, Barr M, Wiltsey Stirman S, Raj S. A Comparison of Responses from Human Therapists and Large Language Model–Based Chatbots to Assess Therapeutic Communication: Mixed Methods Study. JMIR Mental Health 2025;12:e69709 View
  15. Ni Y, Jia F. A Scoping Review of AI-Driven Digital Interventions in Mental Health Care: Mapping Applications Across Screening, Support, Monitoring, Prevention, and Clinical Education. Healthcare 2025;13(10):1205 View
  16. Kim M, Hwang G, Jang J, Chang S, Roh H, Park R. Performance of Open-Source Large language Models in Psychiatry: A Comparative Analysis of Non-English Records and English Translations (Preprint). Journal of Medical Internet Research 2024 View
  17. Su H, Sun Y, Li R, Zhang A, Yang Y, Xiao F, Duan Z, Chen J, Hu Q, Yang T, Xu B, Zhang Q, Zhao J, Li Y, Li H. Large Language Models in Medical Diagnostics: Scoping Review With Bibliometric Analysis. Journal of Medical Internet Research 2025;27:e72062 View
  18. Linardon J, Messer M, Anderson C, Liu C, McClure Z, Jarman H, Goldberg S, Torous J. Role of large language models in mental health research: an international survey of researchers’ practices and perspectives. BMJ Mental Health 2025;28(1):e301787 View

Conference Proceedings

  1. Lim M, Ku J, Oh G, Lee S, Kang Y, Kim J. 2024 15th International Conference on Information and Communication Technology Convergence (ICTC). A Family-History Based Conversational AI System Using LLM View
  2. Meng H. Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. Leveraging Human-AI Partnership Approach to Unravel Human Psychological Constructs View
  3. Skeggs A, Mehta A, Yap V, Ibrahim S, Rhodes C, Gross J, Munson S, Klasnja P, Orben A, Slovak P. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. Micro-narratives: A Scalable Method for Eliciting Stories of People’s Lived Experience View