Investigating the network ties between affect, attachment, and psychopathology

Recent years have seen an increased interest regarding theoretical and empirical associations of adult attachment security and primary affective traits concerning psychiatric disorders. In this study, network analysis technique is applied to dissect the links between both psychodynamic personality constructs and an array of psychopathological symptoms. A total sample of 921 (69.9 % female) participants from the general population was investigated. A regularized cross-sectional partial correlation network between attachment (Experiences in Close Relationships-Revised [ECR-RD8]), primary affective traits (Brief Affective Neuroscience Personality Scales [BANPS-GL]) and psychopathological symptoms (ICD-10-Symptom-Rating Questionnaire [ISR]) was estimated via the EBICglasso algorithm. Node centrality, predictability and bridge centrality were analyzed. To evaluate the stability of the network and evaluate the significance of differences, we employed bootstrap techniques. The network was found to be stable, allowing reliable interpretations. We observed SADNESS, as well as depressive, PTSD and anxiety symptoms as the most influential nodes within the investigated network. Attachment AV and SADNESS were observed as nodes with the highest bridge centrality. The results provide a data-driven in-depth look into the complex dynamics between psychopathological symptoms, attachment security and basic affective traits. Results underscore the critical interconnections between affect, attachment, and psychopathology, advocating for a psychodynamically informed systems approach in psychological research that considers the affective dimensions underlying human mental health.