Title of article :
Factor structure and dimensionality of the two depression scales in STAR*D using level 1 datasets
Author/Authors :
Bech، نويسنده , , P. and Fava، نويسنده , , M. and Trivedi، نويسنده , , M.H. and Wisniewski، نويسنده , , S.R. and Rush، نويسنده , , A.J.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
Abstract :
Background
ctor structure and dimensionality of the HAM-D17 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).
s
rst 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.
s
th 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-C6 were found to be unidimensional scales, i.e., their total scores are each a sufficient statistic for the measurement of depressive states.
tions
used only one medication in Level 1.
sions
idimensional 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.
Keywords :
Principal component analysis , Item response theory analysis , Hamilton depression scale , Inventory of Depressive Symptomatology
Journal title :
Journal of Affective Disorders
Journal title :
Journal of Affective Disorders