Literature DB >> 33638252

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

Jan Scott1,2, Jacob J Crouse1, Nicholas Ho1, Joanne Carpenter1, Nicholas Martin3, Sarah Medland3,4, Richard Parker3, Enda Byrne4, Baptiste Couvy-Duchesne3,4,5, Brittany Mitchell3,6, Kathleen Merikangas7, Nathan A Gillespie8, Ian Hickie1.   

Abstract

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.
© 2021 The Authors. Bipolar Disorders published by John Wiley & Sons Ltd.

Entities:  

Keywords:  activation; bipolar disorder; network analysis; risk factors; sleep-wake cycle

Mesh:

Year:  2021        PMID: 33638252      PMCID: PMC8387492          DOI: 10.1111/bdi.13067

Source DB:  PubMed          Journal:  Bipolar Disord        ISSN: 1398-5647            Impact factor:   5.345


  41 in total

1.  Clinical calibration of DSM-IV diagnoses in the World Mental Health (WMH) version of the World Health Organization (WHO) Composite International Diagnostic Interview (WMHCIDI).

Authors:  Ronald C Kessler; Jamie Abelson; Olga Demler; Javier I Escobar; Miriam Gibbon; Margaret E Guyer; Mary J Howes; Robert Jin; William A Vega; Ellen E Walters; Philip Wang; Alan Zaslavsky; Hui Zheng
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Review 2.  The architecture of complex weighted networks.

Authors:  A Barrat; M Barthélemy; R Pastor-Satorras; A Vespignani
Journal:  Proc Natl Acad Sci U S A       Date:  2004-03-08       Impact factor: 11.205

3.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.

Authors:  Erik von Elm; Douglas G Altman; Matthias Egger; Stuart J Pocock; Peter C Gøtzsche; Jan P Vandenbroucke
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4.  Sparse inverse covariance estimation with the graphical lasso.

Authors:  Jerome Friedman; Trevor Hastie; Robert Tibshirani
Journal:  Biostatistics       Date:  2007-12-12       Impact factor: 5.899

5.  Psychometric perspectives on diagnostic systems.

Authors:  Denny Borsboom
Journal:  J Clin Psychol       Date:  2008-09

6.  The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review.

Authors:  Alba Contreras; Ines Nieto; Carmen Valiente; Regina Espinosa; Carmelo Vazquez
Journal:  Psychother Psychosom       Date:  2019-03-19       Impact factor: 17.659

7.  A Prospective Study on How Symptoms in a Network Predict the Onset of Depression.

Authors:  Lynn Boschloo; Claudia D van Borkulo; Denny Borsboom; Robert A Schoevers
Journal:  Psychother Psychosom       Date:  2016-04-05       Impact factor: 17.659

Review 8.  Can network analysis transform psychopathology?

Authors:  Richard J McNally
Journal:  Behav Res Ther       Date:  2016-07-01

9.  Symptom networks in acute depression across bipolar and major depressive disorders: A network analysis on a large, international, observational study.

Authors:  Filippo Corponi; Gerard Anmella; Norma Verdolini; Isabella Pacchiarotti; Ludovic Samalin; Dina Popovic; Jean-Michel Azorin; Jules Angst; Charles L Bowden; Sergey Mosolov; Allan H Young; Giulio Perugi; Eduard Vieta; Andrea Murru
Journal:  Eur Neuropsychopharmacol       Date:  2020-05-12       Impact factor: 4.600

10.  Estimating psychological networks and their accuracy: A tutorial paper.

Authors:  Sacha Epskamp; Denny Borsboom; Eiko I Fried
Journal:  Behav Res Methods       Date:  2018-02
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  2 in total

1.  Dynamic networks of psychological symptoms, impairment, substance use, and social support: The evolution of psychopathology among emerging adults.

Authors:  Jacob J Crouse; Nicholas Ho; Jan Scott; Richard Parker; Shin Ho Park; Baptiste Couvy-Duchesne; Brittany L Mitchell; Enda M Byrne; Daniel F Hermens; Sarah E Medland; Nicholas G Martin; Nathan A Gillespie; Ian B Hickie
Journal:  Eur Psychiatry       Date:  2022-06-13       Impact factor: 7.156

2.  Days out of role and somatic, anxious-depressive, hypo-manic, and psychotic-like symptom dimensions in a community sample of young adults.

Authors:  Jacob J Crouse; Nicholas Ho; Jan Scott; Nicholas G Martin; Baptiste Couvy-Duchesne; Daniel F Hermens; Richard Parker; Nathan A Gillespie; Sarah E Medland; Ian B Hickie
Journal:  Transl Psychiatry       Date:  2021-05-13       Impact factor: 6.222

  2 in total

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