Document Type : Original Article
Authors
1
Medical Biochemistry department, Faculty of Medicine, Tanta University, Egypt.
2
medical biochemistry department, faculty of medicine, tanta university
3
Medical Biochemistry Department, Faculty of Medicine, Tanta University, Egypt
4
Medical Biochemistry Department, Faculty of Medicine, Tanta University, Egypt.
5
Department of Emergency Medicine, Faculty of Medicine, Tanta University, Egypt. Department of public Health, school of Medicine, Kyoto University, Japan.
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Department of Medical Education, Faculty of Medicine, Tanta University, Egypt.
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Member of Medical Education Department, Faculty of Medicine, Tanta University, El-Geesh St, Tanta, Egypt. Assistant Professor of Medical Biochemistry & Molecular Biology
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Histology and cell biology , Faculty of Medicine, Tanta University
Abstract
There is a recent rise in the application of AI in medical education research and development. We aim to assess the effects of AI tools on the workload and well-being of preclinical medical students, concentrating on their views, acceptance, and satisfaction with these technologies. A cross-sectional survey was conducted between September and October 2024. A total of 926 preclinical medical students from Tanta University, Egypt, were involved. Data were gathered using a validated online questionnaire that included sections on demographic data, perception of AI tools, the impact of AI on medical education and willingness to use it, and the impact of AI on workload and well-being. Descriptive statistical analyses of questionnaire sections were done. A logistic regression model was used to assess the association of 13 predictor questions with the effect of AI on students' well-being and their willingness to use AI. A significant P-value (P < 0.001) suggests a strong association between computer literacy and willingness to use AI. Among all predictor questions, the strongest association for a'strongly agree' response was observed for the statement 'I'm aware of AI applications in different aspects of life' (Adjusted Odds Ratios [AORs]: 3.19 [95% CI: 1.96–5.26]). Additionally, the statement 'I assume AI could replace traditional teaching methods' showed significant associations in improving well-being for both'strongly agree' (AOR: 2.24 [95% CI: 1.38–3.68]) and 'agree' (AOR: 1.55 [95% CI: 1.04–2.37]). This study highlights the significance of integrating AI technologies into medical education to improve students’ well-being and decrease workload.
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