Literature DB >> 29179144

The centrality of DSM and non-DSM depressive symptoms in Han Chinese women with major depression.

Kenneth S Kendler1, Steven H Aggen2, Jonathan Flint3, Denny Borsboom4, Eiko I Fried4.   

Abstract

INTRODUCTION: We compared DSM-IV criteria for major depression (MD) with clinically selected non-DSM criteria in their ability to represent clinical features of depression.
METHOD: We conducted network analyses of 19 DSM and non-DSM symptoms of MD assessed at personal interview in 5952 Han Chinese women meeting DSM-IV criteria for recurrent MD. We estimated an Ising model (the state-of-the-art network model for binary data), compared the centrality (interconnectedness) of DSM-IV and non-DSM symptoms, and investigated the community structure (symptoms strongly clustered together).
RESULTS: The DSM and non-DSM criteria were intermingled within the same symptom network. In both the DSM-IV and non-DSM criteria sets, some symptoms were central (highly interconnected) while others were more peripheral. The mean centrality of the DSM and non-DSM criteria sets did not significantly differ. In at least two cases, non-DSM criteria were more central than symptomatically related DSM criteria: lowered libido vs. sleep and appetite changes, and hopelessness versus worthlessness. The overall network had three sub-clusters reflecting neurovegetative/mood symptoms, cognitive changes and anxiety/irritability. LIMITATIONS: The sample were severely ill Han Chinese females limiting generalizability.
CONCLUSIONS: Consistent with prior historical reviews, our results suggest that the DSM-IV criteria for MD reflect one possible sub-set of a larger pool of plausible depressive symptoms and signs. While the DSM criteria on average perform well, they are not unique and may not be optimal in their ability to describe the depressive syndrome.
Copyright © 2017. Published by Elsevier B.V.

Entities:  

Keywords:  Diagnostic and Statistical Manual 3rd Edition; Major depression; Network analysis

Mesh:

Year:  2017        PMID: 29179144      PMCID: PMC5815309          DOI: 10.1016/j.jad.2017.11.032

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


  15 in total

1.  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

2.  Robust symptom networks in recurrent major depression across different levels of genetic and environmental risk.

Authors:  H M van Loo; C D Van Borkulo; R E Peterson; E I Fried; S H Aggen; D Borsboom; K S Kendler
Journal:  J Affect Disord       Date:  2017-10-29       Impact factor: 4.839

3.  The influence of sample selection on the structure of psychopathology symptom networks: An example with alcohol use disorder.

Authors:  Michaela Hoffman; Douglas Steinley; Timothy J Trull; Sean P Lane; Phillip K Wood; Kenneth J Sher
Journal:  J Abnorm Psychol       Date:  2019-06-13

Review 4.  Challenges and Strategies for Current Classifications of Depressive Disorders: Proposal for Future Diagnostic Standards.

Authors:  Seon-Cheol Park; Yong-Ku Kim
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

5.  Phenotype Network and Brain Structural Covariance Network of Major Depression.

Authors:  Je-Yeon Yun; Yong-Ku Kim
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

6.  Adolescent depression beyond DSM definition: a network analysis.

Authors:  Pedro H Manfro; Rivka B Pereira; Martha Rosa; Hugo Cogo-Moreira; Helen L Fisher; Brandon A Kohrt; Valeria Mondelli; Christian Kieling
Journal:  Eur Child Adolesc Psychiatry       Date:  2021-12-02       Impact factor: 4.785

7.  A comparison of logistic regression methods for Ising model estimation.

Authors:  Michael J Brusco; Douglas Steinley; Ashley L Watts
Journal:  Behav Res Methods       Date:  2022-10-20

8.  The symptom-specific efficacy of antidepressant medication vs. cognitive behavioral therapy in the treatment of depression: results from an individual patient data meta-analysis.

Authors:  Lynn Boschloo; Ella Bekhuis; Erica S Weitz; Mirjam Reijnders; Robert J DeRubeis; Sona Dimidjian; David L Dunner; Boadie W Dunlop; Ulrich Hegerl; Steven D Hollon; Robin B Jarrett; Sidney H Kennedy; Jeanne Miranda; David C Mohr; Anne D Simons; Gordon Parker; Frank Petrak; Stephan Herpertz; Lena C Quilty; A John Rush; Zindel V Segal; Jeffrey R Vittengl; Robert A Schoevers; Pim Cuijpers
Journal:  World Psychiatry       Date:  2019-06       Impact factor: 49.548

Review 9.  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

10.  Problems with Centrality Measures in Psychopathology Symptom Networks: Why Network Psychometrics Cannot Escape Psychometric Theory.

Authors:  Michael N Hallquist; Aidan G C Wright; Peter C M Molenaar
Journal:  Multivariate Behav Res       Date:  2019-08-12       Impact factor: 5.923

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