Depression has a huge societal impact, making accurate measurement paramount. While there are several available measures, the Center for Epidemiological Studies Depression Scale (CESD) is a popular assessment tool that has wide applicability in the general population. In order to reflect modern diagnostic criteria and improve upon psychometric limitations of its predecessor, the Center for Epidemiologic Studies Depression Scale--Revised (CESD-R) was recently created, but has yet to be publicized. This study explored psychometric properties of the CESD-R across a large community sample (N=7389) and smaller student sample (N=245). A newly proposed algorithmic classification method yielded base-rates of depression consistent with epidemiological results. Factor analysis suggested a unidimensional factor structure, but important utility for two separate symptom clusters. The CESD-R exhibited good psychometric properties, including high internal consistency, strong factor loadings, and theoretically consistent convergent and divergent validity with anxiety, schizotypy, and positive and negative affect. Results suggest the CESD-R is an accurate and valid measure of depression in the general population with advantages such as free distribution and an atheoretical basis.
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