Active Learning in Biostatistics Education for Medical Students: A Systematic Review and Meta-Analysis

Biostatistics is an essential part of medical training and evidence-based decision-making. However, many students find it difficult, which can lead to anxiety and poor performance. Hence, this review aimed to evaluate the effectiveness of active learning methodologies compared to traditional teaching methods for undergraduate medical students. A systematic review with meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The study protocol was also registered with the International Prospective Register of Systematic Reviews (PROSPERO) under registration number CRD420261299740. Studies on active methodologies for teaching biostatistics to undergraduate medical students were searched in PubMed/MEDLINE, Web of Science, and Google Scholar (2000-2026). Two reviewers performed study selection and data extraction. The primary outcome was academic performance, and the secondary outcomes were satisfaction and perceived knowledge. Risk of bias was assessed using Risk of Bias 2.0 (RoB-2) and Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I). The meta-analysis used the standardized mean difference (SMD) with a 95% confidence interval (CI), a random effects model, and assessed heterogeneity with I² and Egger's test. A p-value of less than 0.05 was considered significant. A total of 17 studies involving 3,702 medical students were included in the analysis. Active methodologies were found to significantly improve academic performance compared to traditional teaching methods (SMD = 0.83; 95% CI: 0.38-1.27; p = 0.0003; I² = 95%). The effect was also significant by region: America (SMD = 0.51; p = 0.02), Asia (SMD = 1.12; p = 0.02), and Europe (SMD = 0.63; p = 0.0002). In pre-post intervention studies, significant improvements were observed after the intervention (SMD = 2.11; p < 0.0001; I² = 98%). Additionally, higher perceived knowledge (SMD = 0.64; p = 0.009) and student satisfaction (SMD = 0.85; p < 0.00001; I² = 0%) were observed in the intervention group. No evidence of publication bias was detected using Egger's test (p = 0.335). However, several studies presented a moderate to serious risk of bias, and hence, the results should be interpreted with caution. In conclusion, active learning methodologies are effective in improving biostatistics learning.