Cargando…

Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care

BACKGROUND: The aim of this study was to examine the symptomatic dimensions of depression in a large sample of patients with major depressive disorder (MDD) in the primary care (PC) setting by means of a factor analysis of the Zung self-rating depression scale (ZSDS). METHODS: A factor analysis was...

Descripción completa

Detalles Bibliográficos
Autores principales: Romera, Irene, Delgado-Cohen, Helena, Perez, Teresa, Caballero, Luis, Gilaberte, Immaculada
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2257949/
https://www.ncbi.nlm.nih.gov/pubmed/18194524
http://dx.doi.org/10.1186/1471-244X-8-4
_version_ 1782151291445706752
author Romera, Irene
Delgado-Cohen, Helena
Perez, Teresa
Caballero, Luis
Gilaberte, Immaculada
author_facet Romera, Irene
Delgado-Cohen, Helena
Perez, Teresa
Caballero, Luis
Gilaberte, Immaculada
author_sort Romera, Irene
collection PubMed
description BACKGROUND: The aim of this study was to examine the symptomatic dimensions of depression in a large sample of patients with major depressive disorder (MDD) in the primary care (PC) setting by means of a factor analysis of the Zung self-rating depression scale (ZSDS). METHODS: A factor analysis was performed, based on the polychoric correlations matrix, between ZSDS items using promax oblique rotation in 1049 PC patients with a diagnosis of MDD (DSM-IV). RESULTS: A clinical interpretable four-factor solution consisting of a core depressive factor (I); a cognitive factor (II); an anxiety factor (III) and a somatic factor (IV) was extracted. These factors accounted for 36.9% of the variance on the ZSDS. The 4-factor structure was validated and high coefficients of congruence were obtained (0.98, 0.95, 0.92 and 0.87 for factors I, II, III and IV, respectively). The model seemed to fit the data well with fit indexes within recommended ranges (GFI = 0.9330, AGFI = 0.9112 and RMR = 0.0843). CONCLUSION: Our findings suggest that depressive symptoms in patients with MDD in the PC setting cluster into four dimensions: core depressive, cognitive, anxiety and somatic, by means of a factor analysis of the ZSDS. Further research is needed to identify possible diagnostic, therapeutic or prognostic implications of the different depressive symptomatic profiles.
format Text
id pubmed-2257949
institution National Center for Biotechnology Information
language English
publishDate 2008
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-22579492008-02-28 Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care Romera, Irene Delgado-Cohen, Helena Perez, Teresa Caballero, Luis Gilaberte, Immaculada BMC Psychiatry Research Article BACKGROUND: The aim of this study was to examine the symptomatic dimensions of depression in a large sample of patients with major depressive disorder (MDD) in the primary care (PC) setting by means of a factor analysis of the Zung self-rating depression scale (ZSDS). METHODS: A factor analysis was performed, based on the polychoric correlations matrix, between ZSDS items using promax oblique rotation in 1049 PC patients with a diagnosis of MDD (DSM-IV). RESULTS: A clinical interpretable four-factor solution consisting of a core depressive factor (I); a cognitive factor (II); an anxiety factor (III) and a somatic factor (IV) was extracted. These factors accounted for 36.9% of the variance on the ZSDS. The 4-factor structure was validated and high coefficients of congruence were obtained (0.98, 0.95, 0.92 and 0.87 for factors I, II, III and IV, respectively). The model seemed to fit the data well with fit indexes within recommended ranges (GFI = 0.9330, AGFI = 0.9112 and RMR = 0.0843). CONCLUSION: Our findings suggest that depressive symptoms in patients with MDD in the PC setting cluster into four dimensions: core depressive, cognitive, anxiety and somatic, by means of a factor analysis of the ZSDS. Further research is needed to identify possible diagnostic, therapeutic or prognostic implications of the different depressive symptomatic profiles. BioMed Central 2008-01-14 /pmc/articles/PMC2257949/ /pubmed/18194524 http://dx.doi.org/10.1186/1471-244X-8-4 Text en Copyright © 2008 Romera et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Romera, Irene
Delgado-Cohen, Helena
Perez, Teresa
Caballero, Luis
Gilaberte, Immaculada
Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care
title Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care
title_full Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care
title_fullStr Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care
title_full_unstemmed Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care
title_short Factor analysis of the Zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care
title_sort factor analysis of the zung self-rating depression scale in a large sample of patients with major depressive disorder in primary care
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2257949/
https://www.ncbi.nlm.nih.gov/pubmed/18194524
http://dx.doi.org/10.1186/1471-244X-8-4
work_keys_str_mv AT romerairene factoranalysisofthezungselfratingdepressionscaleinalargesampleofpatientswithmajordepressivedisorderinprimarycare
AT delgadocohenhelena factoranalysisofthezungselfratingdepressionscaleinalargesampleofpatientswithmajordepressivedisorderinprimarycare
AT perezteresa factoranalysisofthezungselfratingdepressionscaleinalargesampleofpatientswithmajordepressivedisorderinprimarycare
AT caballeroluis factoranalysisofthezungselfratingdepressionscaleinalargesampleofpatientswithmajordepressivedisorderinprimarycare
AT gilaberteimmaculada factoranalysisofthezungselfratingdepressionscaleinalargesampleofpatientswithmajordepressivedisorderinprimarycare