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Health Qual Life Outcomes. 2010 Sep 21;8:105. doi: 10.1186/1477-7525-8-105.

Validation of the Rasch-based Depression Screening in a large scale German general population sample.

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  • 1Institute of Medical Psychology and Medical Sociology, University Hospital of RWTH Aachen, Pauwelsstraße 30, 52074 Aachen, Germany.



The study aimed at presenting normative data for both parallel forms of the "Rasch-based Depression Screening (DESC)", to examine its Rasch model conformity and convergent and divergent validity based on a representative sample of the German general population.


The sample was selected with the assistance of a demographic consulting company applying a face to face interview (N = 2509; mean age = 49.4, SD = 18.2; 55.8% women). Adherence to Rasch model assumptions was determined with analysis of Rasch model fit (infit and outfit), unidimensionality, local independence (principal component factor analysis of the residuals, PCFAR) and differential item functioning (DIF) with regard to participants' age and gender. Norm values were calculated. Convergent and divergent validity was determined through intercorrelations with the depression and anxiety subscales of the Hospital Anxiety and Depression Scale (HADS-D and HADS-A).


Fit statistics were below critical values (< 1.3). There were no signs of DIF. The PCFAR revealed that the Rasch dimension "depression" explained 68.5% (DESC-I) and 69.3% (DESC-II) of the variance, respectively which suggests unidimensionality and local independence of the DESC. Correlations with HADS-D were rDESC-I = .61 and rDESC-II = .60, whereas correlations with HADS-A were rDESC-I = .62 and rDESC-II = .60.


This study provided further support for the psychometric quality of the DESC. Both forms of the DESC adhered to Rasch model assumptions and showed intercorrelations with HADS subscales that are in line with the literature. The presented normative data offer important advancements for the interpretation of the questionnaire scores and enhance its usefulness for clinical and research applications.

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