DOI: 10.32322/jhsm.1957946 ISSN: 2636-8579
Multidimensional attitudes toward Artificial Intelligence among medical students and faculty: associations with knowledge, perspectives, and usage patterns
Fulden Cantaş Türkiş, Arda Kaan Cingöz, Çağrı Ergin, Elif Yağmur Kayhan, Serhat Tan 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.
More from our Archive
-
DOI: 10.68381/jca02008 2026
Proximal Smoothness and the Lower-C
2
Property F. H. Clarke, R. J. Stern, P. R. Wolenski
-
DOI: 10.68381/jca13044 2026
Characterizations of Prox-Regular Sets in Uniformly Convex Banach Spaces Frédéric Bernard, Lionel Thibault, Nadia Zlateva
-
DOI: 10.68381/jca15047 2026
Brøndsted-Rockafellar Property and Maximality of Monotone Operators Representable by Convex Functions in Non-Reflexive Banach Spaces Maicon Marques Alves, Benar Fux Svaiter
-
DOI: 10.68381/jca16027 2026
Proximal Smoothness and the Exterior Sphere Condition Chadi Nour, Ron J. Stern, Jean Takche
-
DOI: 10.68381/jca16053 2026
A New Old Class of Maximal Monotone Operators Maicon Marques Alves, Benar Fux Svaiter
-
DOI: 10.68381/jca13045 2026
Maximal Monotonicity via Convex Analysis Jonathan Borwein
-
DOI: 10.68381/jca08009 2026
Variational Inequalities and Regularity Properties of Closed Sets in Hilbert Spaces Giovanni Colombo, Vladimir V. Goncharov
-
DOI: 10.68381/jca17060 2026
Existence and Uniqueness of Solutions for Non-Autonomous Complementarity Dynamical Systems Bernard Brogliato, Lionel Thibault
-
DOI: 10.68381/jca01001 2026
Variational Sum of Monotone Operators H. Attouch, J.-B. Baillon, M. Théra
-
DOI: 10.68381/jca22017 2026
Weak Convexity of Sets and Functions in a Banach Space Grigorii E. Ivanov