Evaluation of the Medical Artificial Intelligence Readiness Status of Medical Faculty Students

Abstract

Aim: This study aims to evaluate the readiness status of medical faculty students regarding medical artificial intelligence and to determine whether it varies according to demographic characteristics. Materials and Methods: The study population consists of medical faculty students in Kayseri province. Accordingly, 368 medical faculty students voluntarily participated in the cross-sectional study conducted between June 1 and July 15, 2024. The “Medical Artificial Intelligence Readiness Scale” consisting of 22 items, was used in the study, and data were collected through a survey technique. The SPSS software package was used for the analysis of the collected data, employing descriptive analysis, correlation analysis, t test, and ANOVA. Results: The study revealed that medical school students' level of readiness for medical artificial intelligence and their mean scores in the skill, foresight and ethical sub dimensions were high, while their mean scores in the cognitive sub dimension were low. In addition, medical faculty students' medical artificial intelligence readiness levels and cognitive, skill, foresight and ethical sub dimension averages significantly differed according to demographic characteristics (gender, age and class). Conclusion: The research findings indicate that medical school students have above-average readiness for medical artificial intelligence. This study is considered to guide the development of a new curriculum in medical education and to provide significant practical contributions to the medical education literature.

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