Currently submitted to: JMIR Human Factors
Date Submitted: May 12, 2026
Open Peer Review Period: May 25, 2026 - Jul 20, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Knowledge, Attitudes, and Practices of Medical Students Toward Artificial Intelligence in Healthcare: Cross-Sectional Survey at a Bulgarian Medical University
ABSTRACT
Background:
Artificial intelligence (AI) is rapidly transforming healthcare, yet medical students’ perspectives in Eastern European contexts remain underexplored. Understanding their knowledge, attitudes, and practices is essential to guide curriculum reform and ensure that future healthcare professionals are prepared to use AI safely and effectively.
Objective:
This study assessed the knowledge, attitudes, and practices related to AI integration among students at the Medical University of Plovdiv, Bulgaria.
Methods:
A cross-sectional survey was conducted in May 2025 among 732 medical students (240 international, 492 Bulgarian) using a 20-item anonymous questionnaire covering AI familiarity, attitudes, ethical concerns, and educational needs. Analyses were performed in R Statistical Software (v4.5.3); P<.05 was considered statistically significant.
Results:
Approximately 88-90% of students reported AI familiarity with no significant between-group difference. Social media was the dominant information source (55% international, 65% Bulgarian), with university education cited by only 10-15%. International students showed significantly higher AI tool usage for studying (69.6% vs 44.1%), stronger belief in AI’s transformative potential (70.0% vs 56.1%), and greater ethical concern levels (P=.03). Both groups equally supported AI curriculum integration (~51%) and identified loss of the human element (~70%) as the primary ethical concern. Roughly one-third of all students felt unprepared for clinical AI applications.
Conclusions:
Students demonstrate broad AI awareness but significant gaps persist in formal education and practical readiness. Systematic integration of AI into medical curricula – emphasizing hands-on training, ethical considerations, and critical evaluation skills – is needed to bridge the gap between awareness and clinical competence.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.