Evidence map›Paper›PMID 40133891›Full record

ArticleBMC medical education2025

The role of generative artificial intelligence in psychiatric education- a scoping review.

Qin Yuan Lee, Michelle Chen, Chi Wei Ong, Cyrus Su Hui Ho

Abstract readScoping Review
In one paragraph

Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
  4. Strengths and Potential Pitfalls of the Use of Artificial Intelligence in Psychiatric Education and Practice.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026
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  5. Artificial Intelligence in Psychiatric Graduate Medical Education.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Qin Yuan LeeSchool of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore, Singapore.
Michelle ChenSchool of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore, Singapore.
Chi Wei OngSchool of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, Singapore, Singapore.
Cyrus Su Hui HoDepartment of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. pcmhsh@nus.edu.sg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe growing prevalence of mental health conditions, worsened by the COVID-19 pandemic, highlights the urgent need for enhanced psychiatric education. The distinctive nature of psychiatry- which is heavily centred on communication skills, interpersonal skills, and interviewing techniques- indicates a necessity for further research into the use of GenAI in psychiatric education.

objectiveGiven GenAI has shown promising outcomes in medical education, this study aims to discuss the possible roles of GenAI in psychiatric education.

methodsWe conducted a scoping review to identify the role of GenAI in psychiatric education based on the educational framework of the Canadian Medical Education Directives for Specialists (CanMEDS).

resultsOf the 12,594 papers identified, five studies met the inclusion criteria, revealing key roles for GenAI in case-based learning, simulation, content synthesis, and assessments. Despite these promising applications, limitations such as content accuracy, biases, and concerns regarding security and privacy were highlighted.

conclusionsDespite these promising applications, limitations such as content accuracy, biases, and concerns regarding security and privacy have been highlighted. This study contributes to understanding how GenAI can enhance psychiatric education and suggests future research directions to refine its use in training medical students and primary care physicians. GenAI has significant potential to address the growing demand for mental health professionals, provided its limitations are carefully managed.

Indexed as

Artificial IntelligenceEducation, MedicalPsychiatryCanadaCOVID-19Generative Artificial IntelligenceHumansSARS-CoV-2AssessmentCanMEDSCase-based learningContent synthesisGenerative AIPsychiatric educationSimulation

Identifiers

PMID40133891
PMCPMC11938615

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.