SynthesisBMC medical education2026
The impact of generative artificial intelligence on clinical skills and knowledge acquisition in medical undergraduates: a systematic review and meta-analysis.
Synthesis in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
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Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundCurrently, there is a growing body of research examining the role of generative Artificial Intelligence (GenAI) in medical undergraduate education. However, the findings of these studies exhibit considerable variability. Therefore, this review was designed to systematically evaluate the effectiveness of GenAI tools in improving basic knowledge and clinical skills among undergraduate medical students compared to conventional pedagogy.
methodEleven online databases were systematically searched (e.g., Medline, Embase, CINAHL, APA PsycArticle, APA PsycInfo, ERIC, Scopus, CNKI, WanFang Database, VIP, and SinoMed), from inception to 30 Oct, 2025, and updated to April 24, 2026. Risk assessment was conducted using the Cochrane Risk of Bias tool (ROB 2) and the Medical Education Research Study Quality Instrument (MERSQI). Data were analyzed using RevMan 5.3 and Stata 15.0. Overall effects were estimated using either the fixed effects model or the random effects model. The quality of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework.
resultsThis systematic review and meta-analysis included 31 studies involving 2615 medical undergraduates. It found no significant difference in clinical medicine students' knowledge exam score between GenAI and control groups with a small effect size (n = 1592, P = 0.22, I
conclusionGenAI's educational benefits are context- and domain-dependent. Its efficacy is concentrated in cognitive clinical skills, academic writing, and nursing education, while its advantage over high-fidelity video instruction for fine procedural skills remains uncertain. These findings support a differentiated integration strategy rather than uniform adoption. Future high-quality, multi-center, large-sample, and long-term RCTs are still required to robustly confirm its effects on medical undergraduates' knowledge acquisition, clinical skills, and academic writing performance.
trial registrationThe protocol was registered on the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) and the registration number is INPLASY2025120075.
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