The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Psychiatrists’ experiences and opinions of generative artificial intelligence in mental healthcare: An online mixed methods survey
Open accessAbstract
Following the launch of ChatGPT in November 2022, interest in large language model (LLM)-powered chatbots has surged with increasing focus on the clinical potential of these tools. Missing from this discussion, however, are the perspectives of physicians. The current study aimed to explore psychiatrists' experiences and opinions on this new generation of chatbots in mental health care. An online survey including both quantitative and qualitative responses was distributed to a non-probability sample of psychiatrists affiliated with the American Psychiatric Association. Findings revealed 44 % of psychiatrists had used OpenAI's ChatGPT-3.5 and 33 % had used GPT-4.0 "to assist with answering clinical questions." Administrative tasks were cited as a major benefit of these tools: 70 % somewhat agreed/agreed "documentation will be/is more efficient". Three in four psychiatrists (75 %) somewhat agreed/agreed "the majority of their patients will consult these tools before first seeing a doctor". Nine in ten somewhat agreed/agreed that clinicians need more support/training in understanding these tools. Open-ended responses reflected these opinions but respondents also expressed divergent opinions on the value of generative AI in clinical practice, including its impact on the future of the profession.
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“The mental health support potential of LLM-CBs has been noted by both patients149,152,153 and practitioners153–155”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [154]
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“It is worth emphasizing that physicians also exhibit unwanted prejudicial biases in clinical practice, and whether algorithmic biases are worse than what already exists in human mediated care is unknown (FitzGerald and Hurst, 2017; Takeshita et al., 2020).”
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AI-Generated Medical Advice—GPT and Beyond
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AI Chatbots, Health Privacy, and Challenges to HIPAA Compliance
Marks, M., & Haupt, C. E. (2023) · JAMA · doi:10.1001/jama.2023.9458 · Cited by 174
What ChatGPT Tells Us about Gender: A Cautionary Tale about Performativity and Gender Biases in AI
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Privacy is an essentially contested concept: a multi-dimensional analytic for mapping privacy
Mulligan, D. K., Koopman, C., & Doty, N. (2016) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2016.0118 · Cited by 149 · cited 1×
“We suggest that in the era of LLMs in healthcare, fundamental issues pertaining to privacy will need to be considered (Mulligan et al., 2016), including whether individual patient privacy can be considered a relic of the past or whether technological advances can effectively guard sensitive data…”
Blease, C., Locher, C., Leon-Carlyle, M., & Doraiswamy, M. (2020) · DIGITAL HEALTH · doi:10.1177/2055207620968355 · Cited by 121
Self-citationChatGPT's Ability to Assist with Clinical Documentation: A Randomized Controlled Trial
Baker, H. P., Dwyer, E., Kalidoss, S., Hynes, K., Wolf, J., & Strelzow, J. A. (2024) · Journal of the American Academy of Orthopaedic Surgeons · doi:10.5435/jaaos-d-23-00474 · Cited by 115
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Open AI meets open notes: surveillance capitalism, patient privacy and online record access
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Self-citationSharing notes with mental health patients: balancing risks with respect
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Self-citationGarbage in, Garbage out—Words of Caution on Big Data and Machine Learning in Medical Practice
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Harmful biases in artificial intelligence
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Research works printed but not linked: 1
- AMA, 2023. ChatGPT and generative AI: what physicians should consider. American Medical Association. https://www.ama-assn.org/system/files/chatgpt-what-physicians-should-consider.pdf (Accessed 11 September 2023).
Cited by
Sorted by citations
Torous, J., Linardon, J., Goldberg, S. B., Sun, S., Bell, I., Nicholas, J., Hassan, L., Hua, Y., Milton, A., & Firth, J. (2025) · World Psychiatry · doi:10.1002/wps.21299 · Cited by 323
Self-citationLarge Language Models for Mental Health Applications: Systematic Review
Guo, Z., Lai, A., Thygesen, J. H., Farrington, J., Keen, T., & Li, K. (2024) · JMIR Mental Health · doi:10.2196/57400 · Cited by 269
Ning, Y., Teixayavong, S., Shang, Y., Savulescu, J., Nagaraj, V., Miao, D., Mertens, M., Ting, D. S. W., Ong, J. C. L., Liu, M., et al. (2024) · The Lancet Digital Health · doi:10.1016/s2589-7500(24)00143-2 · Cited by 212
Generative artificial intelligence in primary care: an online survey of UK general practitioners
Blease, C., Locher, C., Gaab, J., Hägglund, M., & Mandl, K. D. (2024) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2024-101102 · Cited by 169
Self-citationKolding, S., Lundin, R. M., Hansen, L., & Østergaard, S. D. (2024) · Acta Neuropsychiatrica · doi:10.1017/neu.2024.50 · Cited by 97
Metadata
- Authors
- Blease, C., Worthen, A., & Torous, J.
- Affiliations
- Uppsala University (SE)
- American Psychiatric Association (US)
- Beth Israel Deaconess Medical Center (US)
- Corresponding author
- Blease, Charlotte
- Venue
- Psychiatry Research
- Publisher
- Elsevier BV
- Published
- 2024-03
- Volume
- 333
- Pages
- 115724
- ISSN
- 0165-1781 (ISSN-L)
- OpenAlex
- W4390749717
- Cited by
- 113
- References
- 20
- Citations by year
- 2026: 44 · 2025: 50 · 2024: 19
- FWCI
- 10.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Psychiatry Research (publishedVersion, cc-by)
- PubMed (publishedVersion)
- KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- generative AI, large language models, psychiatrists' perspectives, ChatGPT, GPT-4, mental health services, administrative efficiency, clinical documentation, clinician training, future of psychiatry, physician attitudes
- MeSH terms
- Psychiatrists, Artificial Intelligence, Humans, Mental Health Services, Psychiatry, Surveys and Questionnaires
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