Predictors of Anxiety and Depression in Medical Professionals During the Time of COVID-19 Outbreak

Abstract

ABSTRACT Objectives: The aim of this study was to investigate the influences of sociodemographic data, mental disorder history, confusion and somatic discomfort triggered by social media on anxiety and depression symptoms among medical professionals during COVID-19 outbreak. Methods: 460 participants completed online questionnaires that included sociodemographic data, mental health disorder history, an assessment of confusion and somatic discomfort triggered by social media, and psychological disturbance. Hierarchical linear regression model was adopted to analysis the data. Results: The hierarchical linear regression model was able to explain 41.7% of variance in depression symptoms. Including: comorbidity with one mental disorder (B= 0.296, P < .001), confusion (B= 0.174, P < .001) and somatic discomfort (B=0.358, P<.001) triggered by social media. The hierarchical linear regression model was able to explain 41.7% of variance in anxiety symptoms, including: sex (B = -0.08, P < .005), comorbidity with one mental health disorder (B= 0.242, P < .001), confusion (B= 0.228, P < .001) and somatic discomfort (B=0.436, P<.001) triggered by social media. Conclusions: These results suggest that it is important to provide adequate psychological assistance for medical professionals with mental health problems in COVID-19 to buffer the negative impact of social media.