Related Experiment Videos
Knowledge and perception of artificial intelligence among operating room staff in educational hospitals: a
Farzaneh Nekuei Manesh1, Zahra Eydizadeh2, Mohammad Reza Sohrabi3
1Department of Operating Room, Nursing and Midwifery Care Research Center, School of Nursing and Midwifery, Isfahan University of Medical Sciences, Isfahan,Iran.
Background:
Successful implementation of artificial intelligence (AI) in healthcare depends not only on technological performance but also on the readiness of healthcare professionals to understand, trust, and appropriately use AI-enabled systems. Evidence regarding AI knowledge among multidisciplinary operating room (OR) staff remains limited, particularly in low- and middle-income healthcare settings.
Objective:
To assess AI-related knowledge and perceptions among OR personnel and examine demographic factors associated with workforce preparedness for AI implementation in clinical practice.
Methods:
An analytical cross-sectional survey was conducted among 200 OR healthcare professionals, including nurses, OR technicians, and anesthesiology personnel, working in four educational hospitals affiliated with Isfahan University of Medical Sciences, Iran. Data were collected using a researcher-developed questionnaire, validated for content and construct validity, consisting of demographic characteristics, seven knowledge items, and twenty-five perception items. Because the data were not normally distributed, Mann-Whitney U, Kruskal-Wallis, and Spearman correlation tests were used for statistical analysis.
Results:
Participants demonstrated limited AI knowledge (mean score: 2.11 ± 0.76 out of 7; 30.1% of the maximum possible score), whereas perceptions toward AI were generally positive (mean score: 76.8 ± 14.5 out of 125). Knowledge scores differed significantly according to educational level (P < 0.001), employment status (P < 0.001), professional discipline (P = 0.026), work experience (P = 0.015), and gender (P = 0.036). Perception scores were significantly associated only with educational level (P = 0.010). Knowledge and perception showed a moderate positive correlation (Spearman's r = 0.421, P < 0.001), while age was weakly negatively correlated with knowledge (r = - 0.156, P = 0.027).
Conclusions:
Despite favorable attitudes toward AI, OR staff demonstrated substantial deficiencies in AI knowledge. Further research and targeted educational initiatives may be warranted to improve AI knowledge among perioperative healthcare professionals and support the safe integration of clinical informatics.