Factor structure and dimensionality of the two depression scales in STAR*D using level 1 datasets

P. Bech, M. Fava, M. H. Trivedi, S. R. Wisniewski, A. J. Rush

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Background: The factor structure and dimensionality of the HAM-D 17 and the IDS-C30 are as yet uncertain, because psychometric analyses of these scales have been performed without a clear separation between factor structure profile and dimensionality (total scores being a sufficient statistic). Methods: The first treatment step (Level 1) in the STAR*D study provided a dataset of 4041 outpatients with DSM-IV nonpsychotic major depression. The HAM-D17 and IDS-C30 were evaluated by principal component analysis (PCA) without rotation. Mokken analysis tested the unidimensionality of the IDS-C6, which corresponds to the unidimensional HAM-D6. Results: For both the HAM-D17 and IDS-C30, PCA identified a bi-directional factor contrasting the depressive symptoms versus the neurovegetative symptoms. The HAM-D6 and the corresponding IDS-C6 symptoms all emerged in the depression factor. Both the HAM-D6 and IDS-C 6 were found to be unidimensional scales, i.e., their total scores are each a sufficient statistic for the measurement of depressive states. Limitations: STAR*D used only one medication in Level 1. Conclusions: The unidimensional HAM-D6 and IDS-C6 should be used when evaluating the pure clinical effect of antidepressive treatment, whereas the multidimensional HAM-D17 and IDS-C30 should be considered when selecting antidepressant treatment.

Original languageEnglish (US)
Pages (from-to)396-400
Number of pages5
JournalJournal of affective disorders
Volume132
Issue number3
DOIs
StatePublished - Aug 2011

Keywords

  • Hamilton depression scale
  • Inventory of Depressive Symptomatology
  • Item response theory analysis
  • Principal component analysis

ASJC Scopus subject areas

  • Clinical Psychology
  • Psychiatry and Mental health

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