Trajectories and predictors of emotional exhaustion in clinical nurses in the context of healthcare crisis: a case study in Xi’an, China

Abstract

AbstractThis study investigated the growth trajectory of emotional exhaustion and its predictors in clinical nurses in the context of healthcare crisis in the post pandemic era. A total of 422 Chinese clinical nurses were followed up three times over two months from December 2022 to January 2023, and data from the final 358 clinical nurses were analyzed. The growth mixed model was used to identify the trajectory categories, and the predictive factors of the trajectory types were analyzed by logistic regression. The relationship of the trajectory types of emotional exhaustion with psychological capital were analyzed by variance analysis. The best-fit growth mixture modeling revealed three class models: Class 1 characterized by high and increasing levels of emotional exhaustion, Class 2 characterized by moderate and decreasing levels of emotional exhaustion, and Class 3 characterized by low and decreasing levels of emotional exhaustion. These classes accounted for 9.78%, 83.52%, and 6.70% of clinical nurses, respectively. The results of the univariate analysis indicated that age, years of working experience, gender, past participation in emergency public health event rescue, and sleep quality were associated with the trajectory of emotional exhaustion. Logistic regression analysis revealed that gender, past participation in emergency public health event rescue, and sleep quality were independent predictors of the emotional exhaustion trajectory. The variance analysis of the four dimensions of psychological capital showed that there were statistically significant differences in scores of self-efficacy and hope dimensions among the three groups of emotionally exhausted individuals. Our study demonstrated the heterogeneity of emotional exhaustion among clinical nursing personnel in coping with healthcare system overload. The psychological capital of nursing staff with different categories of emotional exhaustion varies. Managers should actively pay attention to the predictive role of gender, past participation in emergency public health event rescue, and sleep quality on the development of emotional exhaustion in clinical nurses.