ArticleThe clinical teacher2026
Improving Resident Knowledge of Artificial Intelligence Ethics and Prompting for Clinical Use.
Article in The clinical teacher, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
backgroundThe rapid introduction of AI into clinical practice shifts how we must teach resident trainees so they may become ethical patient-facing clinicians in an AI-integrated healthcare system. Currently, few published innovations assess outcomes beyond learner attitudes. We developed a pilot curricular innovation to equip postgraduate Internal Medicine resident trainees with the attitudes and knowledge needed to responsibly integrate AI tools into patient care decisions. APPROACH: In the 2025-2026 academic year, we piloted a curricular innovation to teach resident physicians the basics of prompting strategies for AI-assisted clinical reasoning, ethical AI use and legal considerations. The innovation consisted of an initial didactic followed by a hands-on, interactive session integrating AI prompts and outputs into clinical vignettes, thereby leveraging near-peer teaching and situated learning to achieve session objectives. EVALUATION: We assessed perceived knowledge and knowledge using a pre-post intervention strategy using the Wilcoxon Rank-Sum test. Fifty-nine/96 (61.5%) and 52/96 (54.2%) of residents participated in the presession and post-session survey, respectively. Perceived knowledge increased significantly across all five learning objectives with a moderate to large effect size. Fifty-one residents participated in the pre- and post-session knowledge test. The median pre-session score was 6/8 (interquartile range [IQR] 4-8), and the median post-session score was 7/8 (IQR: 5-8); p < 0.001, with a moderate effect size = 0.33. IMPLICATIONS: A combined didactic and small-group interaction session improved residents' perceived understanding and knowledge of ethical and legal considerations related to clinical AI use. Future work developing clinical assessments of trainee skills using AI tools is needed.
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