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Translation and adaptation of the Zung Self- Rating Depression Scale for application in the bilingual Azerbaijani population

Published online by Cambridge University Press:  15 April 2020

F. Mammadova*
Affiliation:
Baku Psycho-Neurological Dispensary, Baku Azerbaijan
M. Sultanov
Affiliation:
Republic Psychiatric Hospital, Baku Azerbaijan
A. Hajiyeva
Affiliation:
Baku Psycho-Neurological Dispensary, Baku Azerbaijan
M. Aichberger
Affiliation:
Department of Psychiatry and Psychotherapy, Charité – Berlin, Germany
A. Heinz
Affiliation:
Department of Psychiatry and Psychotherapy, Charité – Berlin, Germany
*
*Corresponding Author. E-mail address:[email protected] (F. Mammadova)
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Abstract

Background

A self-reported Zung Self-Rating Depression Scale (ZSDS) is recognized as a reliable and valid measure for assessment of depressive symptoms, applicable cross-culturally. The aim of the study was to adapt ZSDS for application in the bilingual Azerbaijani population.

Methods

ZSDS was translated into Azerbaijani and Russian. Two pilot studies on small samples (n = 30 and n = 45) were conducted to improve the scale's acceptability. A readability study was conducted on a bigger sample of depressed subjects (n = 55) and healthy controls (n = 120). Chronbach's alpha for the total scale, item-test correlations, alpha if item deleted, and sensitivity and specificity at various cut-off levels were calculated.

Results

The drop-out rate was 83.3% at the first pilot study due to problems of comprehension of item 5 and culturally unacceptable wording of item 6. After rewording of the items drop-out reduced to 20%. On the reliability study Chronbach's alpha for the total scale was 0.8727, and item-test correlations for the most individual items were satisfactory. An optimal cut-off point was 45 points with sensitivity=90.91%, specificity=80.83%.

Conclusions

Adaptation of the Zung Self-Reported Depression Scale improved cultural acceptability of the scale in the context of the Azerbaijani study population.

Type
Research Article
Copyright
Copyright © 2012 Elsevier Masson SAS

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