Stress and quality of life of intensive care nurses during the COVID-19 pandemic: Self-efficacy and resilience as resources

Abstract

Background: Health care workers employed in the COVID-19 emergency are at a high risk of stress. Aims and objectives: To explore the mediating roles of self-efficacy and resilience between stress and both physical and mental quality-of-life components in intensive care nurses during the COVID-19 pandemic. Design: Cross-sectional survey design. Methods: The stress subscale (depression, anxiety, and stress scale in Spanish Scale, DASS-21), the summary components (physical and mental) of health-related quality of life (SF-36), the general self-efficacy scale (GSES), and the resilience scale (RS-14) were administered in 308 intensive care nurses. Serial multiple mediator models were used. Results: There was a significant indirect effect of levels of perceived stress on both physical and mental health components through self-efficacy and resilience. Specifically, greater perception of self-efficacy was associated with a lower perception of stress and greater resilience, while higher resilience was associated with greater physical and mental health (B = −0.03; SE = 0.02; 95% confidence interval [CI] = [−0.07, −0.01]; B = −0.03, SE = 0.01, 95% CI = [−0.07, −0.01], respectively). It was observed that self-efficacy alone also mediates the relationship of the perception of stress on the components of physical and mental health (B = −0.07; SE = 0.05; 95% CI = [−0.18, −0.03]; B = −0.09; SE = 0.04; 95% CI = [−0.17, −0.24], respectively). However, resilience alone was not a significant mediator of these associations. Conclusions: It can be concluded that stress is linked to the physical and mental health components related to quality of life through self-efficacy and resilience. Relevance to clinical practice: These psychological resources would allow the nursing staff to maintain a good quality of life despite high levels of stress. These findings have implications for future research in terms of both model testing and clinical application.