Bridging the Artificial Intelligence (AI) Divide: Do Postgraduate Medical Students Outshine Undergraduate Medical Students in AI Readiness?

Autor:	Gandhi R; Community and Family Medicine, Shri M. P. Shah Government Medical College, Jamnagar, IND., Parmar A; Public Health, Shri M. P. Shah Government Medical College, Jamnagar, IND., Kagathara J; Community Medicine, Smt. B. K. Shah Medical Institute & Research Centre, Vadodara, IND., Lakkad D; Internal Medicine, Shri M. P. Shah Government Medical College, Jamnagar, IND., Kakadiya J; Internal Medicine, Shri M. P. Shah Government Medical College, Jamnagar, IND., Murugan Y; Family Medicine, Guru Gobind Singh Government Hospital, Jamnagar, IND.
Jazyk:	angličtina
Zdroj:	Cureus [Cureus] 2024 Aug 20; Vol. 16 (8), pp. e67288. Date of Electronic Publication: 2024 Aug 20 (Print Publication: 2024).
DOI:	10.7759/cureus.67288
Abstrakt:	Introduction: As artificial intelligence (AI) transforms healthcare, medical education must adapt to equip future physicians with the necessary competencies. However, little is known about the differences in AI knowledge, attitudes, and practices between undergraduate and postgraduate medical students. This study aims to assess and compare AI knowledge, attitudes, and practices among undergraduate and postgraduate medical students, and to explore the associated factors and qualitative themes. Methods: A mixed-methods study was conducted, involving 605 medical students (404 undergraduates, 201 postgraduates) from a tertiary care center. Participants completed a survey assessing AI knowledge, attitudes, and practices. Semi-structured interviews and focus group discussions were conducted to explore qualitative themes. Quantitative data were analyzed using descriptive statistics, t-tests, chi-square tests, and regression analyses. Qualitative data underwent thematic analysis. Results: Postgraduate students demonstrated significantly higher AI knowledge scores than undergraduates (38.9±4.9 vs. 29.6±6.8, p<0.001). Both groups held positive attitudes, but postgraduates showed greater confidence in AI's potential (p<0.001). Postgraduates reported more extensive AI-related practices (p<0.001). Key qualitative themes included excitement about AI's potential, concerns about job security, and the need for AI education. AI knowledge, attitudes, and practices were positively correlated (p<0.01). Conclusions: This study reveals a significant AI knowledge gap between undergraduate and postgraduate medical students, highlighting the need for targeted AI education. The findings can inform curriculum development and policies to prepare medical students for the AI-driven future of healthcare. Further research should explore the long-term impact of AI education on clinical practice. Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Institutional Review Board, Shri M. P. Shah Government Medical College and Guru Gobind Singh Government Hospital issued approval 02/01/2023. Informed consent was obtained from all participants. Data anonymization and confidentiality measures were implemented. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work. (Copyright © 2024, Gandhi et al.)
Databáze:	MEDLINE
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