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

Scott, Jan, Crouse, Jacob J., Ho, Nicholas, Carpenter, Joanne, , , Parker, Richard, Byrne, Enda, Couvy-Duchesne, Baptiste, , Merikangas, Kathleen, Gillespie, Nathan A., & Hickie, Ian (2021) Can network analysis of self-reported psychopathology shed light on the core phenomenology of bipolar disorders in adolescents and young adults? Bipolar Disorders, 23(6), pp. 584-594.

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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.

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ID Code: 231110
Item Type: Contribution to Journal (Journal Article)
Refereed: Yes
Additional Information: Funding Information: Funding information BLTS: National Health and Medical Research Council, Grant/Award Numbers (CI: Martin): 1031119, 1049911, APP10499110; National Institute of Health, Grant/Award Number: K99R00, R00DA02354 (CI: Gillespie). This work was partially supported by grants from the National Health and Medical Research Council including Centre of Research Excellence (No. 1061043) and Australia Fellowship (No. 511921) awarded to Prof Hickie. BDC is supported by a CJ Martin Fellowship, funded by the NHMRC (1161356). We thank the participants and their families for engagement with this longitudinal study.
Measurements or Duration: 11 pages
Keywords: activation, bipolar disorder, network analysis, risk factors, sleep-wake cycle
DOI: 10.1111/bdi.13067
ISSN: 1398-5647
Pure ID: 110194107
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Schools > School of Biomedical Sciences
Funding Information: Funding information BLTS: National Health and Medical Research Council, Grant/Award Numbers (CI: Martin): 1031119, 1049911, APP10499110; National Institute of Health, Grant/Award Number: K99R00, R00DA02354 (CI: Gillespie). This work was partially supported by grants from the National Health and Medical Research Council including Centre of Research Excellence (No. 1061043) and Australia Fellowship (No. 511921) awarded to Prof Hickie. BDC is supported by a CJ Martin Fellowship, funded by the NHMRC (1161356). We thank the participants and their families for engagement with this longitudinal study.
Copyright Owner: 2021 The Authors.
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Deposited On: 19 May 2022 05:01
Last Modified: 14 Mar 2024 21:30