The use of AI scribes across medical fields and why psychiatry is lagging behind: A scoping review.

Authors

Chloé Daignault, Justine Audelin-Rinfret, Marie Désilets, Arash Bahremand, André Do

Published in

Sante mentale au Quebec. Volume 51. Issue 2. Pages 53-83.

Abstract

Objective This scoping review aimed to examine the current available literature on the use of artificial intelligence (AI) scribes across all medical fields compared to their use in psychiatry. Methods A scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Five electronic databases (PubMed, MEDLINE, EMBASE, PsycINFO, and CINAHL) were systematically searched for studies published up to June 2025. Two reviewers independently screened titles and abstracts according to pre-established eligibility criteria using the PICOS framework. Full-text articles were then assessed for inclusion. Results A total of 1896 records were identified, of which 15 met the inclusion criteria. Most studies were conducted in outpatient, primary care, and procedural settings. Across studies, clinicians generally reported favorable acceptance and perceptions of AI scribes. Findings also suggested improved clinician well-being, reduced documentation time, better workflow efficiency, and positive patient experience. Results on documentation accuracy and quality were mixed. Critically, no eligible studies evaluated the use of AI scribes in psychiatry. Limitations included study heterogeneity, with wide variations in study design, sample size, and evaluation metrics. Conclusion The absence of empirical studies in psychiatry highlights a significant gap in the literature, particularly in contrast to the growing body of research across other medical specialties. Because of its unique clinical, ethical, and relational dimensions, dedicated research is needed to evaluate the feasibility, safety, and ethical implications of implementing AI scribes in psychiatric care.

PMID:
42550434
Bibliographic data and abstract were imported from PubMed on 04 Aug 2026.

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