The impact of generative artificial intelligence on clinical skills and knowledge acquisition in medical undergraduates: a systematic review and meta-analysis
Abstract
Background: Currently, 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.
Method: Eleven 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.
Results: This 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, I2 = 92%, SMD = 0.22, 95%CI: - 0. 13 to 0.56, 14 studies, random-effect model). However, nursing…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 1,592 participants or records.
Read the paper
Related studies
- Learning from First-Generation Qualitative Approaches in the IS Discipline: An Evolutionary View and Some Implications for Authors and Evaluators (PART 1/2)
- Commentary on the clinical and preclinical dosage limits of interstitially administered magnetic fluids for therapeutic hyperthermia based on current practice and efficacy models
- Prosthesis: New Technological Opportunities and Innovative Biomedical Devices
- The history and future of neural modeling for cochlear implants
- Ryanodine receptors: waking up from refractoriness
- Novel Transgenic Rabbit Model Sheds Light on the Puzzling Role of Matrix Metalloproteinase-12 in Atherosclerosis
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.