Comorbidity Network Analysis of Depression, Anxiety and Stress During the COVID-19 Pandemic (preprint)

ABSTRACT

Background: Stress caused by the COVID-19 pandemic is highly correlated with depression and anxiety disorders, and there is currently a lack of understanding of the comorbidity network of these disorders. The purpose of this study is to explore the comorbidity network of depression, anxiety and stress during the COVID-19 pandemic through network analysis.Method: 887 participants are conducted a DASS 21 mental state survey across the country from February 18 to 22 in the outbreak of the COVID-19 pandemic in China. The network analysis method was used to explore the network relationship between these disorders, including the use of indicators of expected influence and bridge expected influence to explain the centrality of the network.Results: The strongest six edges were the connections between the symptoms within each group, including three depressive symptom edges initiative-anhedonia, hopeless-meaningless and worthless-meaningless, one anxiety symptom edge dyspneic-heart sick and two stress symptom edges over reactive-touchy and agitated-relax. Centrality indicators show that symptoms blue, relax, and intolerable have the strongest expected influence centrality. The results show that symptoms intolerable, sad mood and blue have the strongest bridge expected influence centrality.Conclusion: We found that symptoms blue, intolerable and relax are the core ones in the network, while dry and heartsick are less important ones. In addition, symptoms intolerable, sad mood and blue were also found to have the strongest bridge symptoms. Interventions against the core symptoms in this study will be more precise.