ArticleFrontiers in medicine2026
Preparing tomorrow's physicians for AI-driven healthcare: insights from a study on medical students', interns', and residents' knowledge, attitudes, and educational needs.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) is increasingly embedded in healthcare delivery, influencing clinical practice, medical education, and research. Despite rapid technological advancement, limited empirical evidence exists on how medical trainees across training levels perceive AI, their readiness to use it, and the educational, ethical, and system-level conditions required for responsible AI integration. Objective: This study aimed to examine medical and dental trainees' knowledge, attitudes, real-world experiences, and educational needs related to AI in healthcare, with particular attention to trust, workflow integration, human oversight, and institutional governance. Methods: An explanatory sequential mixed-methods design was employed. A structured online survey was distributed to undergraduate and postgraduate medical and dental trainees across the United Arab Emirates (UAE) ( Results: Survey responses ( Conclusion: Trainees recognize the transformative potential of AI but emphasize the need for longitudinal, clinically relevant education, robust ethical governance, institutional support, and continued human oversight. These findings suggest that preparing future physicians for AI-enabled healthcare may require human-centered, ethically grounded, and system-ready approaches that align education, workflow integration, and governance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.