SynthesisBMC medical education2026
Use of artificial intelligence-enhanced virtual patients in educational approaches to medical interview training: a systematic review.
Synthesis in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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.
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Who cites it
3 citing papers in PubMed.
- Effect of Large Language Model-Powered Virtual Standardized Patients on History-Taking Among Undergraduate Medical Students: Propensity-Matched Cohort Study.JMIR medical education · 2026Article
- Augmented reality-supported self-care training and clinical outcomes in patients with major depressive disorder: a retrospective propensity score-matched cohort study.Frontiers in psychiatry · 2026Article
- From information literacy to health literacy: AI-driven transformation in university libraries under digital public health-a perspective.Frontiers in public health · 2026Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEffective communication and empathy are essential for professional–patient relationships, patient care, and the therapeutic alliance. With the increasing use of artificial intelligence-assisted virtual patients (AI-VPs), new opportunities to improve interview training are observed. This systematic review assesses the educational use, benefits, and limitations of AI-VPs in clinical interview training for healthcare professionals and students.
methodsFollowing PRISMA recommendations, the review involved a systematic search in PubMed, Google Scholar, and PsycINFO. Eleven studies met the inclusion criteria. Methodological quality of papers was assessed using the MMAT 2018.
resultsThe findings suggest that AI-VPs can improve empathy, communication, and clinical reasoning, as well as promote perceived self-efficacy, reduce anxiety, and enhance engagement through immersive experiences. However, questions remain about the transferability of these skills to clinical practice. The studies show a lack of consistent theoretical frameworks and standardized outcome measures. While feedback is widely used, it is not formalized. Technical limitations, such as issues with speech recognition and nonverbal communication, can disrupt immersion.
conclusionAI-VPs represent a promising educational tool for initial interview training, as it creates learning environments that are scalable, standardized, and interactive. A step-by-step approach, beginning with standardized patients and progressing to real patients, may optimize skill acquisition. Robust longitudinal studies and cost–benefit analyses are needed to support these findings. Although AI-VPs can improve training in interpersonal and communication skills, further work is needed to validate its clinical impact and educational design.
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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.