Literature DB >> 26561400

Association of Symptom Network Structure With the Course of [corrected] Depression.

Claudia van Borkulo1, Lynn Boschloo2, Denny Borsboom3, Brenda W J H Penninx4, Lourens J Waldorp3, Robert A Schoevers2.   

Abstract

IMPORTANCE: Major depressive disorder (MDD) is a heterogeneous condition in terms of symptoms, course, and underlying disease mechanisms. Current classifications do not adequately address this complexity. In novel network approaches to psychopathology, psychiatric disorders are conceptualized as complex dynamic systems of mutually interacting symptoms. This perspective implies that a more densely connected network of symptoms is indicative of a poorer prognosis, but, to date, no previous study has examined whether network structure is indeed associated with the longitudinal course of MDD.
OBJECTIVE: To examine whether the baseline network structure of MDD symptoms is associated with the longitudinal course of MDD. DESIGN, SETTING, AND PARTICIPANTS: In this prospective study, in which remittent and persistent MDD was defined on the basis of a follow-up assessment after 2 years, 515 patients from the Netherlands Study of Depression and Anxiety with past-year MDD (established with the Composite International Diagnostic Interview) and at least moderate depressive symptoms (assessed with the Inventory of Depressive Symptomatology [IDS]) at baseline were studied. Baseline starting and ending dates were September 1, 2004, through February 28, 2007. Follow-up starting and ending dates were September 1, 2006, through February 28, 2009. Analysis was conducted August 2015. The MDD was considered persistent if patients had at least moderate depressive symptoms (IDS) at 2-year follow-up; otherwise, the MDD was considered remitted. MAIN OUTCOMES AND MEASURES: Sparse network structures of baseline MDD symptoms assessed via IDS were computed. Global and local connectivity of network structures were compared across persisters and remitters using a permutation test.
RESULTS: Among the 515 patients, 335 (65.1%) were female, mead (SD) age was 40.9 (12.1) years, and 253 (49.1%) had persistent MDD at 2-year follow-up. Persisters (n = 253) had a higher baseline IDS sum score than remitters (n = 262) (mean [SD] score, 40.2 [8.9] vs 35.1 [7.1]; the test statistic for the difference in IDS sum score was 22 027; P < .001). The test statistic for the difference in network connectivity was 1.79 (P = .01) for the original data, 1.55 for data matched on IDS sum score (P = .04), and 1.65 for partialed out data (P = .02). At the symptom level, fatigue or loss of energy and feeling guilty had the largest difference in importance in persisters' network compared with that of remitters (Cohen d = 1.13 and 1.18, respectively). CONCLUSIONS AND RELEVANCE: This study reports that symptom networks of patients with MDD are related to longitudinal course: persisters exhibited a more densely connected network at baseline than remitters. More pronounced associations between symptoms may be an important determinant of persistence in MDD.

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Year:  2015        PMID: 26561400     DOI: 10.1001/jamapsychiatry.2015.2079

Source DB:  PubMed          Journal:  JAMA Psychiatry        ISSN: 2168-622X            Impact factor:   21.596


  147 in total

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2.  Network models of DSM-5 posttraumatic stress disorder: Implications for ICD-11.

Authors:  Karen S Mitchell; Erika J Wolf; Michelle J Bovin; Lewina O Lee; Jonathan D Green; Raymond C Rosen; Terence M Keane; Brian P Marx
Journal:  J Abnorm Psychol       Date:  2017-02-13

3.  A comparative network analysis of eating disorder psychopathology and co-occurring depression and anxiety symptoms before and after treatment.

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4.  The network approach to psychopathology: a review of the literature 2008-2018 and an agenda for future research.

Authors:  Donald J Robinaugh; Ria H A Hoekstra; Emma R Toner; Denny Borsboom
Journal:  Psychol Med       Date:  2019-12-26       Impact factor: 7.723

5.  A Network Approach to Psychosis: Pathways Between Childhood Trauma and Psychotic Symptoms.

Authors:  Adela-Maria Isvoranu; Claudia D van Borkulo; Lindy-Lou Boyette; Johanna T W Wigman; Christiaan H Vinkers; Denny Borsboom
Journal:  Schizophr Bull       Date:  2016-05-10       Impact factor: 9.306

6.  ICD-11 PTSD and complex PTSD: structural validation using network analysis.

Authors:  Eoin McElroy; Mark Shevlin; Siobhan Murphy; Bayard Roberts; Nino Makhashvili; Jana Javakhishvili; Jonathan Bisson; Menachem Ben-Ezra; Philip Hyland
Journal:  World Psychiatry       Date:  2019-06       Impact factor: 49.548

7.  A network theory of mental disorders.

Authors:  Denny Borsboom
Journal:  World Psychiatry       Date:  2017-02       Impact factor: 49.548

8.  Can We Jump from Cross-Sectional to Dynamic Interpretations of Networks? Implications for the Network Perspective in Psychiatry.

Authors:  Fionneke M Bos; Evelien Snippe; Stijn de Vos; Jessica A Hartmann; Claudia J P Simons; Lian van der Krieke; Peter de Jonge; Marieke Wichers
Journal:  Psychother Psychosom       Date:  2017-05-11       Impact factor: 17.659

9.  Generalized Network Psychometrics: Combining Network and Latent Variable Models.

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Review 10.  Network Analysis as an Alternative Approach to Conceptualizing Eating Disorders: Implications for Research and Treatment.

Authors:  Cheri A Levinson; Irina A Vanzhula; Leigh C Brosof; Kelsie Forbush
Journal:  Curr Psychiatry Rep       Date:  2018-08-06       Impact factor: 5.285

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