Acceptance of AI-based clinical decision support systems among registered nurses: psychological safety and the mediating role of professional identity in a cross-sectional study

Abstract

Background : AI-based clinical decision support systems are increasingly used to support clinical decision-making, patient safety, and evidence-based nursing practice. However, nurses' acceptance may be influenced by psychological and professional factors. Aim : This study examined the relationship between psychological safety and acceptance of AI-based clinical decision support systems among registered nurses and tested whether professional identity mediated this relationship. Methods : A descriptive cross-sectional correlational design was used. The study included 320 registered nurses from Kafr El-Sheikh University Hospitals, Egypt. Data were collected using Edmondson's Team Psychological Safety Scale, the Professional Identity in Nursing Scale 2.0, and an adapted modified UTAUT questionnaire. Data were analyzed using descriptive statistics, Pearson's correlation, multiple linear regression, and Hayes' PROCESS macro-Model 4. Results : Nurses reported moderate-to-high levels of psychological safety, professional identity, and acceptance. Acceptance was positively correlated with professional identity and psychological safety. Psychological safety was the strongest direct predictor of acceptance, whereas professional identity was not significant after controlling psychological safety. Professional identity did not mediate the relationship between psychological safety and acceptance. Conclusion : Psychological safety is central to nurses' acceptance of AI-based clinical decision support systems. Creating psychologically safe clinical environments may enhance nurses' engagement with AI-enabled decision support technologies.