Artificial intelligence use among medical students: an Italian cross-sectional study
Abstract
Background: Artificial Intelligence (AI) is rapidly transforming healthcare and medical education, yet formal instruction remains limited, creating a gap between technological adoption and curricular preparation. Medical students increasingly use AI-supported self-directed learning, raising concerns about ethical literacy, clinical reasoning, and professional readiness. The objective of this study was to assess the use and attitudes toward AI among medical students at a large Italian university.
Methods: A cross-sectional online survey was conducted among medical students at the University of Turin, Italy, from November 2024 to March 2025. The anonymous questionnaire collected sociodemographic data, AI use during studies, perceived learning effects, trust, training exposure, expectations for the medical profession, and support for mandatory AI courses. Descriptive analyses and multivariable logistic regression were performed.
Results: Among 316 students, 70.25% reported using AI tools, mainly ChatGPT (98.6%). Users were younger than non-users, and age was the only independent predictor of use (adjOR 0.90, 95% CI 0.82–0.99, p = 0.027). A clear training gap emerged: 94% reported no formal AI education, yet 75% supported mandatory AI courses. AI users more often perceived benefits for accessing medical information (87.9% vs 63.8%, p < 0.001), whereas non-users were more concerned about dehumanization and weakening of the physician-patient relationship (47.9% vs 29.3%, p = 0.002). Unconditional trust in AI outputs was very low (4.4%).
Conclusions: AI is already embedded in medical learning, but structured education is largely absent. This Italian experience reflects a broader European need for harmonized frameworks that ensure equitable AI literacy across medical schools. To support safe, ethical, and patient-centred care, European medical education should urgently integrate mandatory AI training that strengthens critical appraisal and preserves humanistic practice.
Key messages: • 94% of medical students lack formal AI training despite 70% usage, highlighting an urgent need for standardized European curricular reforms to ensure patient safety and professional competence.
• Strong student support (75%) for mandatory AI courses provides a clear mandate for European institutions to integrate AI literacy, balancing technological innovation with humanistic care.
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BibTeX
@article{capirone2026artificial,
title = {{Artificial intelligence use among medical students: an Italian cross-sectional study}},
author = {F Capirone and G Lo Moro and D Consoli and E Martelli and M Martella and G Scaioli and F Bert and R Siliquini},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.403},
url = {https://doi.org/10.1093/eurpub/ckag169.403},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Artificial intelligence use among medical students: an Italian cross-sectional study
AU - F Capirone
AU - G Lo Moro
AU - D Consoli
AU - E Martelli
AU - M Martella
AU - G Scaioli
AU - F Bert
AU - R Siliquini
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.403
UR - https://doi.org/10.1093/eurpub/ckag169.403
AB - Background: Artificial Intelligence (AI) is rapidly transforming healthcare and medical education, yet formal instruction remains limited, creating a gap between technological adoption and curricular preparation. Medical students increasingly use AI-supported self-directed learning, raising concerns about ethical literacy, clinical reasoning, and professional readiness. The objective of this study was to assess the use and attitudes toward AI among medical students at a large Italian university. Methods: A cross-sectional online survey was conducted among medical students at the University of Turin, Italy, from November 2024 to March 2025. The anonymous questionnaire collected sociodemographic data, AI use during studies, perceived learning effects, trust, training exposure, expectations for the medical profession, and support for mandatory AI courses. Descriptive analyses and multivariable logistic regression were performed. Results: Among 316 students, 70.25% reported using AI tools, mainly ChatGPT (98.6%). Users were younger than non-users, and age was the only independent predictor of use (adjOR 0.90, 95% CI 0.82–0.99, p = 0.027). A clear training gap emerged: 94% reported no formal AI education, yet 75% supported mandatory AI courses. AI users more often perceived benefits for accessing medical information (87.9% vs 63.8%, p < 0.001), whereas non-users were more concerned about dehumanization and weakening of the physician-patient relationship (47.9% vs 29.3%, p = 0.002). Unconditional trust in AI outputs was very low (4.4%). Conclusions: AI is already embedded in medical learning, but structured education is largely absent. This Italian experience reflects a broader European need for harmonized frameworks that ensure equitable AI literacy across medical schools. To support safe, ethical, and patient-centred care, European medical education should urgently integrate mandatory AI training that strengthens critical appraisal and preserves humanistic practice. Key messages: • 94% of medical students lack formal AI training despite 70% usage, highlighting an urgent need for standardized European curricular reforms to ensure patient safety and professional competence. • Strong student support (75%) for mandatory AI courses provides a clear mandate for European institutions to integrate AI literacy, balancing technological innovation with humanistic care.
SN - 1101-1262
SN - 1464-360X
ER -