Study Habits and Attitudes Toward Artificial Intelligence Tools Among Anesthesia Trainees in Türkiye: A Descriptive Survey

Study Habits of Anesthesia Trainees

Abstract

Objective: To describe the study habits and attitudes toward the use of artificial intelligence (AI) tools for studying among anesthesia trainees in Türkiye, and to explore the associations between these factors and performance in national in-training examinations.
Methods: A cross-sectional online survey was administered to anesthesia trainees in Türkiye between April and June 2025. The questionnaire addressed study frequency and duration, preferred resources, AI use patterns, and 5-point Likert ratings for reliability and usefulness. Performance in the national online trainee assessment examination (ÇADS) was analyzed using Kruskal-Wallis tests and Spearman correlation, with ÇADS scores encoded as ordinal ranks (1-4).
Results: A total of 148 responses were analyzed. Study sessions were reported as “occasional” by 60.1%, with typical sessions lasting 1-2 hours (48.6%). Although 96.6% of the respondents perceived a need to study more, the main barriers were fatigue and burnout (46.9%) and time constraints due to clinical duties (29.4%). The most commonly used resources were textbooks (92.6%), spaced repetition (60.8%), and online journals (52.7%). AI tools were rated as useful (mean 3.89 ± 0.99) but only moderately reliable (3.22 ± 0.97). Two-thirds of the respondents participated regularly in ÇADS (66.2%). Among the 130 participants who had completed at least one ÇADS examination, the most frequently reported score category was 60-79 (73.1%). Frequent AI use was significantly associated with higher ÇADS performance (p = 0.003). No associations were found between ÇADS performance and study frequency or specific study techniques.
Conclusion: Anesthesia trainees in Türkiye display irregular, brief study patterns, with fatigue and burnout as the main problems. AI tool adoption remains low, likely due to moderate trust and a lack of guidance. Frequent AI use and higher self-confidence were associated with better examination performance in exploratory univariable analyses. Educational programs may benefit from addressing workload and burnout while providing structured guidance for the appropriate integration of AI tools.