Estimating the symptom structure of bipolar disorder via network analysis: Energy dysregulation as a central symptom.

ABSTRACT: Using network analysis, we estimated the structure of relations among manic and depressive symptoms, respectively, in 486 patients (59% women; age: M = 37, SD = 12.1) with bipolar disorder prior to their entering a clinical trial. We computed three types of networks: (a) Gaussian graphical models (GGMs) depicting regularized partial correlations, (b) regression-based GGMs depicting nonregularized partial correlations, and (c) directed acyclic graphs (DAGs) via a Bayesian hill-climbing algorithm. Low energy and elevated energy were consistently identified as central nodes in the GGMs and as key parent nodes in the DAGs. Across analyses, pessimism about the future and depressed mood were the symptoms most strongly associated with suicidal thoughts and behavior. These exploratory analyses pro

SUBMITTER: McNally RJ 

PROVIDER: S-EPMC9168523 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature