Association Between Fear of COVID-19 and Emotional Distress in Nurses With Mediating Role of Socio-Demographic Features

Objectives: To determine the predictive association between fear of COVID-19 and emotional distress (depression, anxiety, and stress) in frontline and non-frontline nurses. To explore the mediating role of socio-demographic features.Methods: Correlational cross-sectional research design was implied. A total of 500 on-duty male and female, frontline and non-frontline, nurses were included from five major hospitals in Gujrat (Aziz Bhatti Shaheed Hospital, City Hospital, Doctors Hospital, Akram Hospital, and Gujrat Hospital). Fear of COVID-19 scale and the Urdu version of depression, anxiety, and stress scale - 21 (DASS-21) were used to measure variables of interest. Descriptive statistics, structural equation modeling (SEM), linear regression, and t-test were carried out using Statistical Package for Social Sciences (SPSS) 21.Result: Structural equation modeling (SEM) revealed a significant predictive link between fear of COVID-19 and depression, anxiety, and stress (goodness of model fit; NFI = 0.93, GFI = 0.914, AGFI = 0.93, CFI = 0.936, and IFI = 0.936). Furthermore, a significant mediating effect of certain demographic features was discovered by SEM (CMIN/DF = 1.11, NFI = 0.94, TLI = 0.98, GFI = 0.08, AGFI = 0.93, RMSEA = 0.029, CFI = 0.99, and IFI = 0.99). Results of linear regression analysis also revealed a momentous predictive association between fear of COVID-19 and emotional distress (R = 0.860). In comparative analysis, the results of t-test explored the statistical significant difference in fear of COVID-19 and emotional distress between frontline (mean = 25.775, 36.147 and SD = 1.75, 2.23) and non-frontline nurses (mean = 21.702, 27.353 and SD = 4.607, 10.212), with t(130) =7.111, 6.92.Conclusion: Managing the mediating effect of demographic characteristics and reducing the fear of COVID-19 can help nurses to overcome emotional distress, such as depression, anxiety, and stress. Further, this will increase the productivity among nurses.