Psychological distress associated with the COVID-19 lockdown: A two-wave network analysis

Abstract

Background: Although preliminary research has evidenced negative psychological consequences of the COVID-19 pandemic among the general population, little research has been carried out examining the interplay among the broader dimensions and correlates of individual distress. Via network analysis, the current study investigated the pathways that underlie some components of psychological distress and their changes over time (during and post COVID-19-related lockdown). Methods: 1,129 adult participants (79.1% women) completed a two-wave online survey during and after the lockdown, and reported on variables such as depression, anxiety, stress, fear of COVID, intolerance of uncertainty, emotion regulation and social support. The networks were estimated via Gaussian Graphical Models and their temporal changes were compared through the centrality measures. Results: Depression, stress, anxiety and fear of COVID formed a spatially contiguous pattern, which remained unchanged in both the two waves. After the lockdown, the fear of COVID node reduced its strength in the network, whereas inhibitory intolerance of uncertainty and emotion suppression were associated with depression. Emotion regulation was connected to depression, but not to stress and anxiety during both waves. Perceived emotional support had few connections to the other nodes. Limitations: Only 32.7% of participants provided complete responses for both waves. Conclusion: The COVID-19 outbreak has had a significant psychosocial impact on adults. In the context of the network approach, depressive symptoms had the highest strength and their associations to other dimensions of individual distress may be key factors in understanding the influence of exposure to the COVID-19 outbreak on mental health.