Evidence map›Paper›PMID 42221128›Full record

SynthesisFrontiers in medicine2026

Effectiveness of AI-enhanced virtual patients for psychiatric interview training in health professions education: a meta-analysis.

Senay Kilincel, Furkan Bulut, Pelin Goksel, Mirac Baris Usta, Tuba Mutluer, Oguzhan Kilincel

Erratum issuedAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Senay KilincelDepartment of Child and Adolescent Psychiatry, School of Medicine, Istanbul Aydin University, Istanbul, Türkiye.
Furkan BulutPrivate Practice, Psychotherapy Institute, Sakarya, Türkiye.
Pelin GokselDepartment of Adult Psychiatry, School of Medicine, Ondokuz Mayis University, Samsun, Türkiye.
Mirac Baris UstaDepartment of Child and Adolescent Psychiatry, School of Medicine, Ondokuz Mayıs University, Samsun, Türkiye.
Tuba MutluerDepartment of Child and Adolescent Psychiatry, Koc University, Istanbul, Türkiye.
Oguzhan KilincelDepartment of Child Development, Istanbul Gelisim University, Istanbul, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Artificial intelligence (AI)-enhanced virtual patient simulations are increasingly used in health professions education to improve clinical communication and diagnostic reasoning. However, the effectiveness of these technologies for psychiatric interview training has not been systematically quantified. This study aimed to systematically review and meta-analyze the existing literature evaluating the impact of AI-enhanced virtual patients on psychiatric interview performance, knowledge acquisition, and learner confidence in health professions education. Materials and methods: A systematic review and meta-analysis was conducted following the PRISMA 2020 guidelines. Electronic database searches were performed in PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar to identify relevant studies published between January 2000 and March 2026. Studies were included if they evaluated AI-enhanced virtual patient simulations for psychiatric interview training among medical students, psychiatry residents, clinicians, or other health professions trainees. Data extraction included study characteristics, participant populations, intervention types, and educational outcomes. Risk of bias was assessed using the Cochrane Risk of Bias Tool. Quantitative synthesis was performed using random-effects meta-analysis models, and effect sizes were calculated as standardized mean differences (SMD) with 95% confidence intervals (CI) using R statistical software. Results: A total of 560 records were identified through database searches and additional sources. After removal of duplicates and screening procedures, 10 studies met the inclusion criteria and were included in the final analysis. The studies involved approximately 450 participants, including medical students, psychiatry residents, clinicians, nursing students, and psychology trainees. AI-enhanced virtual patient interventions included conversational AI systems, virtual human simulations, large language model-based simulated patients, and AI-virtual reality training environments. The pooled analyses indicated improvements in psychiatric interview performance, knowledge acquisition, and learner confidence following AI-supported virtual patient training. Subgroup analysis demonstrated positive educational outcomes across both student and clinician populations. Risk-of-bias assessment revealed variable methodological quality across studies, with several pilot and non-randomized designs. Conclusion: AI-enhanced virtual patient simulations appear to be effective educational tools for improving psychiatric interview training in health professions education. These technologies provide scalable and standardized simulation environments that support communication skill development, diagnostic reasoning, and learner confidence. Although the findings suggest promising educational benefits, further large-scale randomized controlled trials and standardized outcome assessments are needed to confirm the long-term educational impact of AI-supported virtual patient training in psychiatry.

Indexed as

artificial intelligenceclinical communication skillshealth professions educationmedical educationmeta-analysispsychiatric interview trainingsimulation-based learningvirtual patients

Identifiers

PMID42221128
PMCPMC13215799

What OpenQuestion holds

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LicenceCC BY
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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.