Depressive symptoms and their mechanisms An investigation of long-term patterns of interaction through a panel-network approach

Open Access
Authors
Publication date 09-2024
Journal Clinical Psychological Science
Volume | Issue number 12 | 5
Pages (from-to) 903-916
Organisations
  • Faculty of Social and Behavioural Sciences (FMG) - Amsterdam School of Communication Research (ASCoR)
  • Faculty of Social and Behavioural Sciences (FMG) - Psychology Research Institute (PsyRes)
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.
Document type Article
Note With supplemental material
Language English
Published at https://doi.org/10.1177/21677026231208172
Other links https://www.scopus.com/pages/publications/85176913463
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Depressive symptoms and their mechanisms (Final published version)
Supplementary materials
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