Jornal de Depressão e Ansiedade
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Abstrato

An Algorithm for Creating Alternate CES-D Composite Scores: Advancing Research through Methodological Clarity

Carlos Siordia

The Center for Epidemiologic Studies Depression Scale (CES-D) is a widely used screening test for depression symptomatology in population studies. Publications have dealt with the psychometric properties of the instrument. Until now, no published work has examined the how questionnaire items are handled in data processing protocols. This technical report introduces the “CESD-Flag” macro algorithm using SAS® 9.3 syntax. The main contribution of the statistical program in this report is to provide data managers with a program that creates five CES-D flag variables to help identify the level and location of missingness in CES-D related data. The paper highlights implications from how data editing algorithms handle missing or inconclusive responses to CES-D questions. If absolute transparency should be encouraged as a desirable goal, then the methodology used to “clean” CES-D data should be provided along descriptive statistics for the five flag variables (measure of item incompleteness) created by the CESD-Flag program. The assignment of responses through non-evidence based algorithms merits further attention as the use of CES-D continues to proliferate internationally.