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An item response theory based analysis of the Hamilton depression rating scale-an Indian perspective
Published online by Cambridge University Press: 23 March 2020
Abstract
Hamilton Depression Rating Scale (HAMD) remains the most widely used outcome measure though many consider the scale to have many defects.
To use IRT analysis to identify HDRS items which are problematic in terms of IRT parameters, thus suggest changes to the scale.
Patients attending psychiatric OPD meeting DSM-5 criteria for unipolar depression were selected for the study. Patients were between 18-65 years of age, had no major medical problems and were not on any medicines at present. 17 item HDRS was administered using the anchors developed by William Guy as part of the ECDEU NIMH Collaborative Study To determine the relationship between scores on the individual HAMD items and overall depressive severity in an outpatient population Option Characteristic Curve (OCC) which is a graphical representation of the probability of endorsing the different options for a given item across the range of depressive severity) and Item Characteristic Curve (ICC) which is a graphical representation of the mean item score (expected value) and confidence interval as a function of depressive severity was used.
Results showed that Items Depressed Mood, Work and Activities show good relationship between item responses and overall depressive severity. Items Hypochondriasis, somatic symptoms general and retardation appeared to be more problematic with regard to their ability to discriminate over the full range of depression severity.
Further studies are needed to critically review one of the most commonly used scale for one of the commonest malady of humans.
The authors have not supplied their declaration of competing interest.
- Type
- e-Poster viewing: Cultural psychiatry
- Information
- European Psychiatry , Volume 41 , Issue S1: Abstract of the 25th European Congress of Psychiatry , April 2017 , pp. S541
- Copyright
- Copyright © European Psychiatric Association 2017
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