Accepted for/Published in: JMIR Medical Education
Date Submitted: Jul 27, 2023
Open Peer Review Period: Jul 27, 2023 - Sep 21, 2023
Date Accepted: Dec 11, 2023
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited.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.
Medical Student Experiences and Perceptions of ChatGPT and Artificial Intelligence: A Cross-Sectional Study
ABSTRACT
Background:
Artificial intelligence (AI) has the potential to revolutionize the way medicine is learned, taught, and practiced, and medical education must prepare learners for these inevitable changes. Academic medicine has, however, been slow to embrace innovation. Since its launch in November 2022, ChatGPT (Chat Generative Pre-trained Transformer) has emerged as a fast and user-friendly large language model that can assist healthcare professionals, medical educators, students/trainees, and patients. While many studies focus on the technology’s capabilities, potential, and risks, there is a gap in studying the perspective of end users.
Objective:
The aim of this study was to gauge the experiences and perspectives of graduating medical students on ChatGPT and AI in their training and future careers.
Methods:
A cross-sectional web-based survey of recently graduated medical students in an international academic medical center was conducted between May 5, 2023 and June 13, 2023. Descriptive statistics were used to tabulate variable frequencies.
Results:
Of 325 applicants to the residency programs, 265 completed the survey (81.5% response rate). The vast majority of respondents denied using ChatGPT in medical school, with 20.4% (n=54) using it to help complete written assessments and only 9.4% using the technology in their clinical work (n=25). More students planned to use it during residency, primarily for exploring new medical topics and research (n=168, 63.4%) and exam preparation (n=151, 57.0%). Male students were significantly more likely to believe that AI will improve diagnostic accuracy (51.65% vs. 39.66%; P=.001), reduce medical error (58.24% vs. 40.8%; P=.002), and improve patient care (65.9% vs. 54.6%; P=.007).
Conclusions:
Surveyed medical students have had minimal formal and informal experience with AI tools and a limited understanding of the potential impact of the technology on their medical education and career journey, but were overall positive and optimistic about the future of AI in medical education and healthcare. Structured curricula and formal policies and guidelines are needed to adequately prepare medical learners for the forthcoming integration of AI in medicine.
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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.