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TRUVACE RECORD VERSION
record: TRV-2026-1345
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-14T18:13:19.627977Z
status: published
lens: p_space
sector: health
headline: Generative Artificial Intelligence Use Among Medical Students: Learner Perspectives for Clinical Educators
dek: 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…
gain_title: (none)
problem_title: 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.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: 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.
problem_evidence: Only 50.3% were moderately or extremely confident evaluating AI-generated content | 64.2% wanted more training or clearer guidance | 78.7% reported academic integrity and/or ethical concerns
quick_read: A survey of medical students, recruited mainly through US allopathic school peer networks in July to September 2025, asked how they use generative AI. Most reported using text-based tools and many used them at least weekly, and a majority found them useful.

The results suggest educators cannot assume AI is absent from informal learning, and that students want clearer expectations on privacy, disclosure and appraising AI output. The sample was a voluntary convenience sample, so the figures cannot be read as national prevalence and the study cannot show how widely these patterns apply.
limitation: The study used a non-probability convenience sample with no calculable response rate, so the findings are not national prevalence estimates.
tag: Evidence-backed problem
key_points: 552 students from at least 37 institutions answered at least one item, and 517 answered the AI-use and frequency items. | 87.0% used text-based generative AI and 74.7% used AI tools at least weekly. | 67.8% rated AI tools moderately or extremely useful. | Only 12.2% reported using an institution-sponsored generative AI tool. | Authors suggest clarifying expectations, privacy boundaries, disclosure norms and AI-output appraisal strategies.
rundown: The online survey ran from 15 July to 1 September 2025 and used non-probability sampling, with dissemination through voluntary forwarding among medical student peer networks. Outcomes covered AI use, frequency, usefulness, confidence, concerns and institutional support, analyzed with descriptive statistics and Wilson 95% confidence intervals.

Use was common and perceived as useful, but confidence in evaluating AI-generated content was much lower than uptake. Institution-sponsored tools were rarely used, indicating most use likely occurs through other channels.

Guidance needs were widespread, with most respondents wanting more training or clearer rules and most voicing academic integrity or ethical concerns. The authors frame these as learner perspectives to inform practical guidance by clinical educators.
sources:
- peer_reviewed | The Clinical Teacher | https://doi.org/10.1111/tct.70531 | 2026-12-01
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