Developing a model for predicting safety performance of nurses based on psychosocial safety climate and role of job demands and resources, job satisfaction, and emotional exhaustion as mediators

BACKGROUND: The present study aimed to develop a model for predicting the safety performance of nurses based on psychosocial safety climate (PSC) and the role of job demands and resources, job satisfaction, and emotional exhaustion as mediators. METHODS: A cross-sectional study using structural equation modeling (SEM) was carried out among nurses in Iran. Data were collected using the Psychosocial Safety Climate questionnaire, Neal and Griffin’s Safety Performance Scale, the Management Standards Indicator Tool, the Effort-Reward Imbalance questionnaire, the Michigan Organizational Assessment Job Satisfaction subscale and the Maslach Burnout Inventory. RESULTS: Surveys were distributed to 340 nurses provided informed consent. After removing incplete surveys, data from 280 partipants were analysed. The completion rate was 82.35%. The SEM results indicated that PSC can directly and indirectly predict nurses’ safety performance. The final model showed an acceptable goodness of fit (p = 0.023). It indicated that PSC, job demands, and job satisfaction were directly related to safety performance, and also that PSC, emotional exhaustion, job resources, and job demands were all indirectly related to safety performance. Also, PSC had a significant relationship with all mediator variables, and job demands had direct effect on emotional exhaustion. CONCLUSIONS: The current study presented a new model for predicting safety performance in nurses in which PSC, both directly and indirectly, plays an important role. In addition to paying attention to the physical aspects of the workplace, healthcare organizations should also take into account PSC to improve safety. Next steps in reducing safety issues in nursing is to develop intervention studies using this new evidence-based model as a framework.