The time has come to stop rotations for the identification of structures in the Hamilton Depression Scale (HAM-D₁₇)

To use principal component analysis (PCA) to test the hypothesis that the items of the Hamilton Depression Scale (HAM-D₁₇) have been selected to reflect depression disability, whereas some of the items are specific for sub-typing depression into typical vs. atypical depression. Our previous study us...

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Published inRevista brasileira de psiquiatria Vol. 35; no. 4; pp. 360 - 363
Main Authors Bech, Per, Csillag, Claudio, Hellström, Lone, Fleck, Marcelo Pio de Almeida
Format Journal Article
LanguageEnglish
Portuguese
Published Brazil Associação Brasileira de Psiquiatria 01.12.2013
Associação Brasileira de Psiquiatria (ABP)
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Summary:To use principal component analysis (PCA) to test the hypothesis that the items of the Hamilton Depression Scale (HAM-D₁₇) have been selected to reflect depression disability, whereas some of the items are specific for sub-typing depression into typical vs. atypical depression. Our previous study using exploratory factor analysis on HAM-D₁₇ has been re-analyzed with PCA and the results have been compared to a dataset from another randomized prospective study. PCA showed that the first principal component was a general factor covering depression disability with factor loadings very similar to those obtained in the STAR*D study. The second principal component was a bi-directional factor contrasting typical vs. atypical depression symptoms. Varimax rotation gave no new insight into the factor structure of HAM-D₁₇. With scales like the HAM-D₁₇, it is very important to make a proper clinical interpretation of the PCA before attempting any form of exploratory factor analysis. For the HAM-D₁₇, our results indicate that profile scores are needed because the total score of all 17 items in the HAM-D₁₇ does not give sufficient information.
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ISSN:1516-4446
1809-452X
1809-452X
1516-4446
DOI:10.1590/1516-4446-2013-1116