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Assessing the dimensionality of the CES-D using multi-dimensional multi-level Rasch models

OBJECTIVES: The CES-D is a widely used depression screening instrument. While numerous studies have analysed its psychometric properties using exploratory and various kinds of confirmatory factor analyses, only few studies used Rasch models and none a multidimensional one. METHODS: The present study...

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Detalles Bibliográficos
Autores principales: Alexandrowicz, Rainer W., Jahn, Rebecca, Wancata, Johannes
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5969764/
https://www.ncbi.nlm.nih.gov/pubmed/29799866
http://dx.doi.org/10.1371/journal.pone.0197908
Descripción
Sumario:OBJECTIVES: The CES-D is a widely used depression screening instrument. While numerous studies have analysed its psychometric properties using exploratory and various kinds of confirmatory factor analyses, only few studies used Rasch models and none a multidimensional one. METHODS: The present study applies a multidimensional Rasch model using a sample of 518 respondents representative for the Austrian general population aged 18 to 65. A one-dimensional model, a four-dimensional model reflecting the subscale structure suggested by [1], and a four-dimensional model with the background variables gender and age were applied. RESULTS: While the one-dimensional model showed relatively good fit, the four-dimensional model fitted much better. EAP reliability indices were generally satisfying and the latent correlations varied between 0.31 and 0.88. In the analysis involving background variables, we found a limited effect of the participants’ gender. DIF effects were found unveiling some peculiarities. The two-items subscale Interpersonal Difficulties showed severe weaknesses and the Positive Affect subscale with the reversed item wordings also showed unexpected results. CONCLUSIONS: While a one-dimensional over-all score might still contain helpful information, the differentiation according to the latent dimension is strongly preferable. Altogether, the CES-D can be recommended as a screening instrument, however, some modifications seem indicated.