Teaching critical appraisal to large classes of undergraduate medical students using team-based learning versus group discussions: a randomized controlled trial

BMC MEDICAL EDUCATION(2022)

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摘要
Background Evidence on the effectiveness of team-based learning in teaching critical appraisal to large classes of preclinical medical students is scarce. This study investigated whether team-based learning is effective in teaching critical appraisal to large classes of preclinical medical students. Methods Between April 2018 and May 2019, 107 first-year medical students were randomly allocated to receive instruction in critical appraisal using team-based learning or traditional group discussions as teaching methods. The primary outcome was students’ performance on the Berlin Questionnaire administered at the end of second year. Results Students’ mean (SD) age was 22.0 (0.7) years. Baseline characteristics of the two groups were similar (all p values > 0.05). The mean (SD) Berlin scores of both groups were 80.4 (11.6) and 80.1 (12.1) for team-based learning and group discussions, respectively. Multivariate stepwise linear regression analysis revealed that the student’s academic achievement in medical school was the sole predictor of performance on the Berlin Questionnaire ( ß = 1.079, p < 0.001), adjusting for gender, Medical College Admission Test score, student’s self-reported preferred teaching method, rank upon admission to medical school, score on the Epidemiology and Biostatistics course, and teaching method (team-based learning versus group discussions). Conclusions Team-based learning and group discussions were equally effective instructional strategies to teach critical appraisal to large classes of undergraduate medical students. Replication of our findings is needed in other educational settings. Trial Registration Current Controlled Trials ISRCTN15430424 , retrospectively registered on December 30, 2021.
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关键词
Critical appraisal, Evidence-based medicine, Preclinical medical education, Small group discussions, Team-based learning
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