Literature DB >> 24402210

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

Per Bech1, Claudio Csillag1, Lone Hellström1, Marcelo Pio de Almeida Fleck2.   

Abstract

OBJECTIVE: 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.
METHOD: 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.
RESULTS: 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.
CONCLUSION: 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.

Entities:  

Mesh:

Year:  2013        PMID: 24402210     DOI: 10.1590/1516-4446-2013-1116

Source DB:  PubMed          Journal:  Braz J Psychiatry        ISSN: 1516-4446            Impact factor:   2.697


  2 in total

1.  The challenge of measurement in psychiatry: the lifetime accomplishments of Per Bech (1942-2018).

Authors:  Marcelo P Fleck; Danilo Carrozzino; Giovanni A Fava
Journal:  Braz J Psychiatry       Date:  2019-10-17       Impact factor: 2.697

2.  The bi-factor structure of the 17-item Hamilton Depression Rating Scale in persistent major depression; dimensional measurement of outcome.

Authors:  Neil Nixon; Boliang Guo; Anne Garland; Catherine Kaylor-Hughes; Elena Nixon; Richard Morriss
Journal:  PLoS One       Date:  2020-10-26       Impact factor: 3.240

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.