The network structure of psychopathological and resilient responses to the pandemic: A multicountry general population study of depression and anxiety

Commonly identified patterns of psychological distress in response to adverse events are characterized by resilience (i.e., little to no distress), delayed (i.e., distress that increases over time), recovery (i.e., distress followed by a gradual decrease over time), and sustained (i.e., distress remaining stable over time). This study aimed to examine these response patterns during the COVID-19 pandemic. Anxiety and depressive symptom data collected across four European countries over the first year of the pandemic were analyzed (N = 3,594). Participants were first categorized into groups based on the four described patterns. Network connectivity and symptom clustering were then estimated for each group and compared. Two thirds (63.6%) of the sample displayed a resilience pattern. The sustained distress network (16.3%) showed higher connectivity than the recovery network (10.0%) group, p = .031; however, the resilient network showed higher connectivity than the delayed network (10.1%) group, p = .016. Regarding symptom clustering, more clusters emerged in the recovery network (i.e., three) than the sustained network (i.e., two). These results replicate findings that resilience was the most common mental health pattern over the first pandemic year. Moreover, they suggest that high network connectivity may be indicative of a stable mental health response over time, whereas fewer clusters may be indicative of a sustained distress pattern. Although exploratory, the network perspective provides a useful tool for examining the complexity of psychological responses to adverse events and, if replicated, could be useful in identifying indicators of protection against or vulnerability to future psychological distress.