Predicting Intent to Leave Using Structural Equation Modeling of Burnout, Moral Distress, and Psychological Resilience Among Critical Care Nurses

Abstract

Background: Critical care nurses work in demanding environments where workload and ethical conflict undermine workforce stability. Understanding how burnout, moral distress and psychological resilience shape intention to leave is essential for targeted retention strategies in Saudi hospitals.

Purpose: To test and confirm a structural equation model of intent to leave among the critical care nurses using burnout, moral distress and psychological resilience.

Methods: Cross-sectional survey was done on 362 nurses that work in the ICU, CCU, PICU, and NICU units of three tertiary hospitals in Riyadh, Jeddah and Dammam. The data were gathered by means of Maslach Burnout Inventory-Human Services Survey, the Moral Distress Scale-Revised, the 10-item Connor-Davidson Resilience Scale and a three-item turnover intention scale. The SPSS was used to carry out descriptive analyses and partial least squares structural equation modelling was done in SmartPLS 4.

Results: The final model showed adequate reliability and convergent and discriminant validity. Burnout and moral distress were positively associated with intent to leave, whereas resilience showed a direct negative association. The model explained 57% of the variance in turnover intention. Resilience was also negatively related to burnout and moral distress, with significant indirect effects on intent to leave, and it attenuated the impact of burnout on turnover intention.

Conclusion: Burnout, moral distress and resilience jointly explain critical care nurses’ intent to leave in Saudi tertiary hospitals. Interventions that reduce workload and ethical strain, while strengthening resilience, are likely to be central to sustainable retention.