Fulden CANTAŞ TÜRKİŞ, Arda Kaan CİNGÖZ, Çağrı ERGİN, Elif Yağmur KAYHAN, Serhat TAN
Journal of Health Sciences and Medicine - 2026;9(5):1225-1234
Aims: This study aimed to evaluate Artificial Intelligence (AI)-related knowledge, healthcare-oriented AI perspectives, and multidimensional attitudes toward AI among medical students and faculty members in a Turkish medical school. Methods: This analytical cross-sectional study was conducted during the 2025-2026 academic year at a faculty of medicine. A total of 467 participants, including 356 medical students and 111 faculty members, were included. Data were collected using an online survey. Participants completed questionnaires regarding sociodemographic characteristics and AI usage habits, together with the AI Knowledge Scale, AI Perspective Scale, and AI Attitude Scale consisting of hope, anxiety, and adaptation subdimensions. Statistical analyses included Mann-Whitney U test, ANOVA/Kruskal-Wallis tests, and multiple linear regression analysis. Results: Faculty members demonstrated significantly higher hope and overall attitude scores than medical students, although the corresponding effect sizes were small (rank-biserial correlations=-0.154 and -0.166, respectively). Male participants had higher self-reported AI knowledge, AI perspective, and hope scores. Participants using premium AI tools and those with longer AI use duration generally demonstrated higher self-reported AI knowledge scores and more favorable scores in several attitude subdimensions. In the multivariable model, medical student status was associated with a lower overall AI attitude score (B=-1.856; 95% CI: -3.594 to -0.119), whereas higher self-reported AI knowledge (B=0.156; 95% CI: 0.017 to 0.296) and AI perspective scores (B=0.140; 95% CI: 0.032 to 0.249) were associated with more favorable overall AI attitudes. In an age-adjusted sensitivity analysis, the associations involving self-reported AI knowledge and AI perspective remained significant, whereas the association with participant group was attenuated. Conclusion: More favorable overall AI attitude scores were independently associated with higher self-reported AI knowledge and more positive healthcare-oriented AI perspectives, whereas AI use duration and premium AI use showed no independent association. The assessment of hope, anxiety, and adaptation highlights the multidimensional nature of AI-related attitudes. These findings may help inform hypotheses and priorities for future educational research rather than provide direct evidence for the effectiveness of specific curricular interventions.
