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      The Revised Child Anxiety and Depression Scale-Short Version: scale reduction via exploratory bifactor modeling of the broad anxiety factor.

      Psychological Assessment
      Adolescent, Anxiety Disorders, diagnosis, Child, Depressive Disorder, Factor Analysis, Statistical, Female, Humans, Male, Psychiatric Status Rating Scales, standards, Psychometrics, instrumentation, Reproducibility of Results

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          Abstract

          Using a school-based (N = 1,060) and clinic-referred (N = 303) youth sample, the authors developed a 25-item shortened version of the Revised Child Anxiety and Depression Scale (RCADS) using Schmid-Leiman exploratory bifactor analysis to reduce client burden and administration time and thus improve the transportability characteristics of this youth anxiety and depression measure. Results revealed that all anxiety items primarily reflected a single "broad anxiety" dimension, which informed the development of a reduced 15-item Anxiety Total scale. Although specific DSM-oriented anxiety subscales were not included in this version, the items comprising the Anxiety Total scale were evenly pulled from the 5 anxiety-related content domains from the original RCADS. The resultant 15-item Anxiety Total scale evidenced significant correspondence with anxiety diagnostic groups based on structured clinical interviews. The scores from the 10-item Depression Total scale (retained from the original version) were also associated with acceptable reliability in the clinic-referred and school-based samples (α = .80 and .79, respectively); this is in contrast to the alternate 5-item shortened RCADS Depression Total scale previously developed by Muris, Meesters, and Schouten (2002), which evidenced depression scores of unacceptable reliability (α = .63). The shortened RCADS developed in the present study thus balances efficiency, breadth, and scale score reliability in a way that is potentially useful for repeated measurement in clinical settings as well as wide-scale screenings that assess anxiety and depressive problems. These future applications are discussed, as are recommendations for continued use of exploratory bifactor modeling in scale development.

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