Identifying central negative thoughts through experience sampling and network analysis: Longitudinal Observational Study (Preprint)

Author:

Marian StefanORCID,Sava Florin AlinORCID

Abstract

UNSTRUCTURED

Network analysis has promised to inform clinical practice about what should be prioritised in the treatment of different psychological disorders. However, the pure phenomenological approach that network analysis has adopted didn’t help make considerable advancements towards this goal. We propose a theoretical approach based on the cognitive model of psychopathology. More specifically, we identified the most common negative thoughts in a preliminary study and then monitored them alongside symptoms of anxiety and depression in a sample of undergraduate students 3 times per day for 3 weeks. Results indicated that negative thoughts have a high bridge outdegree in the temporal network (predict the occurrence of symptoms), while symptoms have a high bridge outdegree (are predicted by thoughts). Adopting a theoretical approach has proven useful in providing concrete targets for therapy instead of just identifying central symptoms, as it is typically done in network studies. Thoughts related to self-criticism, like “There’s something wrong with me”, were the most central both for anxiety and depression and could be considered priority targets for cognitive interventions. Future network studies could also consider adopting an approach based on a psychotherapeutic theory about the aetiology of psychopathology.

Publisher

JMIR Publications Inc.

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