Large language models as mental health providers
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Surveys show that the rates of individuals using LLMs for mental health range from 24% to 48.7% of users.
“Surveys show that the rates of individuals using LLMs for mental health range from 24% to 48.7% of users8–12.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [10]
The opening section (page not provided) says independent surveys indicate extensive mental-health use of LLMs. It gives neither a 24% nor a 48.7% rate, so the claimed numerical range is not supported by this paper's text. (LLM, conf=0.86)
Experimental — accuracy not yet measuredPeople increasingly bring mental-health concerns to general-purpose LLMs, often in moments of acute distress and outside any clinical pathway.
“People increasingly bring mental-health concerns to general-purpose LLMs, often in moments of acute distress and outside any clinical pathway (Bodner et al., 2026;Rousmaniere et al., 2026).”
From HealthBench-Psych: A Mental Health Subset of OpenAI's HealthBench (2026) · cites this paper as Rousmaniere et al., 2026
The opening section (page unavailable) says general-purpose chatbots are routinely used for mental-health questions, including by people in crisis situations, and describes a progression toward psychotherapeutic use. It does not establish that use in acute distress is frequent, or state that these interactions occur outside any clinical pathway. (LLM, conf=0.85)
Experimental — accuracy not yet measuredLLM-CBs find increasing use as mental health support tools, both for the general public and for patients in clinical interventions.
“LLM-CBs find increasing use as mental health support tools, both for the general public8–12 and for patients in clinical interventions13,14.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [10]
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Cites
Stade, E. C., Stirman, S. W., Ungar, L. H., Boland, C. L., Schwartz, H. A., Yaden, D. B., Sedoc, J., DeRubeis, R. J., Willer, R., & Eichstaedt, J. C. (2024) · npj Mental Health Research · doi:10.1038/s44184-024-00056-z · Cited by 391 · see citing works
Goldberg, S. B., Lam, S. U., Simonsson, O., Torous, J., & Sun, S. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000002 · Cited by 237 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 7
- [1]Rousmaniere T, Zhang Y, Li X, Shah S. Large language models as mental health resources: patterns of use in the United States. Practice Innovations 2025; published online July 7. 10.1037/pri0000292. · DOI
- [3]Hua Y, Na H, Li Z, A scoping review of large language models for generative tasks in mental health care. NPJ Digit Med 2025; 8: 230. 40307331 PMC12043943
- [4]Jin Y, Liu J, Li P, The applications of large language models in mental health: scoping review. J Med Internet Res 2025; 27: e69284. 40324177 PMC12089884
- [5]Moore J, Grabb D, Agnew W, Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers. In: Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency; June 23–26, 2025 (599– 627).
- [6]McBain RK, Cantor JH, Zhang LA, Competency of large language models in evaluating appropriate responses to suicidal ideation: comparative study. J Med Internet Res 2025; 27: e67891. 40053817 PMC11928068
- [8]Wampold BE, Imel ZE. The great psychotherapy debate: the evidence for what makes psychotherapy work. London, UK: Routledge; 2015.
- [9]Obradovich N, Khalsa SS, Khan W, Opportunities and risks of large language models in psychiatry. NPP Digit Psychiatry Neurosci 2024; 2: 8. 39554888 PMC11566298
Cited by
Sorted by citations
A scoping review on the mental health harms of LLM-based chatbots
Diel, A., Torous, J., Cuijpers, P., Kleesiek, J., Nensa, F., Weber, N., Faust, F., Lalgi, T. J., Mellis, F. S., Teufel, M., et al. (2026) · npj Digital Medicine · doi:10.1038/s41746-026-03054-x · Cited by 4 · see citing works
Self-citationHealthBench-Psych: A Mental Health Subset of OpenAI's HealthBench
Flathers, M., Nguyen, P. A., Noorily, J., Herpertz, J., Chen, M., Multani, J., Powell, S., Granof, M., Kalinch, M., & Torous, J. (2026) · arXiv · doi:10.48550/arxiv.2608.25071
Self-citation
- Authors
- Rousmaniere, T., Goldberg, S. B., & Torous, J.
- Affiliations
- American Psychological Association (US)
- Beth Israel Deaconess Medical Center (US)
- Corresponding author
- Rousmaniere, Tony
- Venue
- The Lancet Psychiatry
- Publisher
- Elsevier BV
- Published
- 2026-01
- Volume
- 13
- Issue
- 1
- Pages
- 7-9
- ISSN
- 2215-0366 (ISSN-L)
- PMC
- PMC12462653
- OpenAlex
- W4414112829
- Cited by
- 22
- References
- 2
- Citations by year
- 2026: 21 · 2025: 1
- FWCI
- 17.60
- Type
- journal article
- Language
- en
- Open access
- green
- pmc.ncbi.nlm.nih.gov
- Licence
- Locations
- The Lancet Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion)
- Funders
- National Institute of Mental Health (R01MH139512)
- National Center for Complementary and Integrative Health (K23AT010879, R24AT012845)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Keywords
- large language models, mental health services, chatbots, AI-assisted therapy, digital mental health
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