Depressive Symptoms and Their Mechanisms: An Investigation of Long-Term Patterns of Interaction Through a Panel-Network Approach

Abstract

The dynamic interaction between depressive symptoms, mechanisms proposed in the metacognitive-therapy model, and loneliness across a 9-month period was investigated. Four data waves 2 months apart were delivered by a representative population sample of 4,361 participants during the COVID-19 pandemic in Norway. Networks were estimated using the newly developed panel graphical vector-autoregression method. In the temporal network, use of substance to cope with negative feelings or thoughts positively predicted threat monitoring and depressed mood. In turn, threat monitoring positively predicted suicidal ideation. Metacognitive beliefs that thoughts and feelings are dangerous positively predicted anhedonia. Suicidal ideation positively predicted sleep problems and worthlessness. Loneliness was positively predicted by depressed mood. In turn, more loneliness predicted more control of emotions. The findings point at the theory-derived variables, threat monitoring, beliefs that thoughts and feelings are dangerous, and use of substance to cope, as potential targets for intervention to alleviate long-term depressive symptoms.