Generative Artificial Intelligence Use Among Medical Students: Learner Perspectives for Clinical Educators
Background: Generative artificial intelligence (AI) is readily available to medical students, yet educators may not know how students use these tools or what guidance students perceive as missing. We examined student-reported AI use, confidence, concerns and institutional support to inform practical guidance. Methods: We conducted an online survey of medical students recruited primarily through US allopathic medical school peer networks from 15 July to 1 September 2025. We used non-probability sampling; because…
Medical students use generative AI often, yet only about half feel confident evaluating its output, few have institution-sponsored tools, and most want clearer guidance and report integrity or ethical concerns.
The study used a non-probability convenience sample with no calculable response rate, so the findings are not national prevalence estimates.
Evidence
- Peer-reviewedThe Clinical Teacher2026-12-01
How should this claim be treated?
Truvace Impact Record TRV-2026-1345, v1: “Generative Artificial Intelligence Use Among Medical Students: Learner Perspectives for Clinical Educators.” Truvace, 2026-10-14. /record/TRV-2026-1345 (accessed at citation time). sha256 c2d6571e2ba41ca1…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1345 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.
ace