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A Content Analysis of Self-report Child Anxiety Measures

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Abstract

A clear understanding of the item content of psychological assessments is critical but often overlooked. This study describes the content overlap of seven commonly used and psychometrically validated measures of anxiety among children and adolescents. Symptom codes were created for all items across measures and items were sorted by these codes, which all fell into specific symptom categories. We conducted two analyses of all items: a “bottom-up” content categorization approach, which used symptom categories that were developed during this study, and a “top-down” DSM-5 categorization which mapped items onto symptoms of anxiety disorders in the DSM-5. Findings reveal a weak mean overlap across the included measures of youth anxiety. This suggests that the scope of anxiety measures should be carefully considered when designing studies, interpreting research, or assessing youth in clinical practice. Further research is needed to develop and establish a coding scheme for a more objective, comprehensive content analysis.

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Funding

Research reported in this publication was supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health under Award Number P50HD103555 for use of the Clinical and Translational Core facilities. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Correspondence to Andrew G. Guzick.

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ES received royalties from Elsevier Publications, Springer Publications, American Psychological Association, Oxford, Kingsley, Wiley, Inc., and Lawrence Erlbaum. He holds stock in NView, where he serves on the clinical advisory board. He was a consultant for Levo Therapeutics and is currently a consultant for Biohaven Pharmaceuticals and Brainsway. He co-founded and receives payment from Rethinking Behavioral Health, which is a consulting firm that provides support for implementing evidence-based psychological treatment strategies. AG receives grant support from the Texas Higher Education Coordinating Board and the Milken Institute/REAM Foundation. MK, JC, EL, SS declare that they have no conflict of interest.

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Kook, M., Clinger, J.W., Lee, E. et al. A Content Analysis of Self-report Child Anxiety Measures. Child Psychiatry Hum Dev (2022). https://doi.org/10.1007/s10578-022-01455-z

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