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The latent structure of social anxiety disorder and the performance only specifier: a taxometric analysis.

Grace B BoyersJoshua J Broman-FulksDavid P ValentinerKathleen McCrawLisa CurtinKurt D Michael
Published in: Cognitive behaviour therapy (2017)
Social anxiety disorder (SAD) is often treated as a discrete diagnostic entity that represents a naturally occurring class, though empirical evidence largely supports a dimensional conceptualization of social fears. Further, the inclusion of a "performance only" specifier in the DSM-5 implies that individuals who experience intense social anxiety exclusively in performance situations are distinct from those with broader social fears. The purpose of the present research was to examine the latent structure of SAD and the DSM-5 "performance only" specifier in a large nonclinical sample (n = 2019). Three taxometric procedures (MAXCOV, MAMBAC, and L-Mode) were applied to indicators derived from two commonly used measures of social anxiety. Results yielded convergent evidence indicating that social anxiety exhibits a dimensional latent structure. Further, social performance anxiety demonstrates continuous relationships with milder social fears, suggesting that the "performance only" specifier may not represent a discrete entity. The implications of these findings for the assessment, diagnosis, classification, and treatment of social anxiety are discussed.
Keyphrases
  • healthcare
  • mental health
  • machine learning
  • depressive symptoms
  • deep learning
  • data analysis