Main outcomes and measures: The coprimary outcomes included change in overall surgical performance across practice resections and skill transfer to a complex realistic scenario, measured by artificial intelligence-calculated composite expertise score (range, -1.00 [novice] to 1.00 [expert]). Secondary outcomes included emotional and cognitive demands, measured via questionnaires.
Results: In this randomized clinical trial, the final analysis included 87 medical students (46 [53%] women; mean [SD] age, 22.7 [4.0] years), with 30, 29, and 28 participants in groups 1, 2, and 3, respectively. Group 3 achieved significantly higher scores than group 1 across several trials, including trial 5 (mean difference, 0.26; 95% CI, 0.09-0.43; P = .01) and the realistic task (mean difference, 0.20; 95% CI, 0.06-0.34; P = .02). Group 3 also achieved significantly better scores than the other 2 groups in certain metrics, such as bleeding and injury risk. Emotions and cognitive load demonstrated significant differences.
Conclusions and relevance: In this randomized clinical trial, personalized expert instruction resulted in enhanced surgical performance and skill transfer compared with intelligent tutor instruction, highlighting the importance of human input and participation in artificial intelligence-based surgical training.