Predictive factors of anxiety and depression among nurses fighting coronavirus disease 2019 in China

Abstract

Anxiety and depression are common mental illnesses among nurses fighting coronavirus disease 2019 (COVID-19). However, the precise factors that affect anxiety and depression in this population require further evaluation. This study aimed to explore factors associated with anxiety and depression among nurses fighting COVID-19 in China. We used convenience sampling to recruit 282 nurses fighting COVID-19 in three hospitals. Participants were questioned about demographic characteristics, daily working time, daily sleep duration, sleep quality, anxiety, depression, resilience, and coping styles. Linear regression analysis indicated that resilience (β = −0.217, P < 0.001), positive coping style (β = −0.281, P < 0.001), negative coping style (β = 0.395, P < 0.001), and sleep quality (β = 0.153, P = 0.010) were predictive factors for anxiety, and the model explained 44.20% (P < 0.001) of variability. Resilience (β = −0.239, P < 0.001), positive coping style (β = −0.222, P < 0.001), negative coping style (β = 0.152, P < 0.001), and sleep quality (β = 0.104, P = 0.003) were identified as explanatory factors for depression, and the model explained 34.50% (P < 0.001) of variability. The present study suggested that resilience, coping styles, and sleep quality could account for an individual’s levels of anxiety and depression.