Literature DB >> 28067191

New insights into the correlation structure of DSM-IV depression symptoms in the general population v. subsamples of depressed individuals.

S Foster1, M Mohler-Kuo1.   

Abstract

AIMS: Previous research failed to uncover a replicable dimensional structure underlying the symptoms of depression. We aimed to examine two neglected methodological issues in this research: (a) adjusting symptom correlations for overall depression severity; and (b) analysing general population samples v. subsamples of currently depressed individuals.
METHODS: Using population-based cross-sectional and longitudinal data from two nations (Switzerland, 5883 young men; USA, 2174 young men and 2244 young women) we assessed the dimensions of the nine DSM-IV depression symptoms in young adults. In each general-population sample and each subsample of currently depressed participants, we conducted a standardised process of three analytical steps, based on exploratory and confirmatory factor and bifactor analysis, to reveal any replicable dimensional structure underlying symptom correlations while controlling for overall depression severity.
RESULTS: We found no evidence of a replicable dimensional structure across samples when adjusting symptom correlations for overall depression severity. In the general-population samples, symptoms correlated strongly and a single dimension of depression severity was revealed. Among depressed participants, symptom correlations were surprisingly weak and no replicable dimensions were identified, regardless of severity-adjustment.
CONCLUSIONS: First, caution is warranted when considering studies assessing dimensions of depression because general population-based studies and studies of depressed individuals generate different data that can lead to different conclusions. This problem likely generalises to other models based on the symptoms' inter-relationships such as network models. Second, whereas the overall severity aligns individuals on a continuum of disorder intensity that allows non-affected individuals to be distinguished from affected individuals, the clinical evaluation and treatment of depressed individuals should focus directly on each individual's symptom profile.

Entities:  

Keywords:  Classification; depressive disorder; diagnosis; epidemiology; factor analysis

Mesh:

Year:  2017        PMID: 28067191      PMCID: PMC6998857          DOI: 10.1017/S2045796016001086

Source DB:  PubMed          Journal:  Epidemiol Psychiatr Sci        ISSN: 2045-7960            Impact factor:   6.892


  66 in total

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4.  The sensitivity and specificity of the Major Depression Inventory, using the Present State Examination as the index of diagnostic validity.

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5.  The differential influence of life stress on individual symptoms of depression.

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6.  The long-term stability of depressive subtypes.

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7.  Subtypes of depression in a nationally representative sample.

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8.  The predictive power of subgroups: an empirical approach to identify depressive symptom patterns that predict response to treatment.

Authors:  Joël Bühler; Florian Seemüller; Damian Läge
Journal:  J Affect Disord       Date:  2014-04-08       Impact factor: 4.839

9.  A network view on psychiatric disorders: network clusters of symptoms as elementary syndromes of psychopathology.

Authors:  Rutger Goekoop; Jaap G Goekoop
Journal:  PLoS One       Date:  2014-11-26       Impact factor: 3.240

10.  Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010.

Authors:  Alize J Ferrari; Fiona J Charlson; Rosana E Norman; Scott B Patten; Greg Freedman; Christopher J L Murray; Theo Vos; Harvey A Whiteford
Journal:  PLoS Med       Date:  2013-11-05       Impact factor: 11.069

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  1 in total

1.  Physical and social anhedonia in female adolescents: A factor analysis of self-report measures.

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