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Can network analysis of self-reported psychopathology shed light on the core phenomenology of bipolar disorders in adolescents and young adults?

Lookup NU author(s): Emeritus Professor Jan Scott



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2021 The Authors. Bipolar Disorders published by John Wiley & Sons Ltd. Objectives: Network analysis is increasingly applied to psychopathology research. We used it to examine the core phenomenology of emerging bipolar disorder (BD I and II) and ‘at risk’ presentations (major depression with a family history of BD). Methodology: The study sample comprised a community cohort of 1867 twin and nontwin siblings (57% female; mean age ~26) who had completed self-report ratings of (i) depression-like, hypomanic-like and psychotic-like experiences; (ii) family history of BD; and (iii) were assessed for mood and psychotic syndromes using the Composite International Diagnostic Interview (CIDI). Symptom networks were compared for recent onset BD versus other cohort members and then for individuals at risk of BD (depression with/without a family history of BD). Results: The four key symptoms that differentiated recent onset BD from other cohort members were: anergia, psychomotor speed, hypersomnia and (less) loss of confidence. The four key symptoms that differentiated individuals at high risk of BD from unipolar depression were anergia, psychomotor speed, impaired concentration and hopelessness. However, the latter network was less stable and more error prone. Conclusions: We are encouraged by the overlaps between our findings and those from two recent publications reporting network analyses of BD psychopathology, especially as the studies recruited from different populations and employed different network models. However, the advantages of applying network analysis to youth mental health cohorts (which include many individuals with multimorbidity) must be weighed against the disadvantages including basic issues such as judgements regarding the selection of items for inclusion in network models.

Publication metadata

Author(s): Scott J, Crouse JJ, Ho N, Carpenter J, Martin N, Medland S, Parker R, Byrne E, Couvy-Duchesne B, Mitchell B, Merikangas K, Gillespie NA, Hickie I

Publication type: Article

Publication status: Published

Journal: Bipolar Disorders

Year: 2021

Volume: 23

Issue: 6

Pages: 584-594

Print publication date: 01/09/2021

Online publication date: 26/02/2021

Acceptance date: 21/02/2021

Date deposited: 04/08/2022

ISSN (print): 1398-5647

ISSN (electronic): 1399-5618

Publisher: John Wiley and Sons Inc.


DOI: 10.1111/bdi.13067

PubMed id: 33638252


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