Psychometric properties of the state Probability and Consequences Questionnaire for social anxiety disorder

Nadia L. Shnier, Amy L. Burton*, Ronald M. Rapee, Matthew Modini, Maree J. Abbott

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    1 Citation (Scopus)
    24 Downloads (Pure)

    Abstract

    Cognitive models of social anxiety propose that overestimation of the probability and cost of negative evaluation plays a central role in maintaining the disorder. However, there are currently no self-report state-based measures of probability and cost appraisals. The current paper examines the psychometric properties of the Probability and Consequences Questionnaire for social anxiety (PCQ-SA), which measures probability and consequence appraisals both in anticipation of, and in response to, an impromptu speech task. A total of 532 participants were recruited for the present study, consisting of 409 participants with a principal diagnosis of Social Anxiety Disorder (SAD), and 123 non-clinical controls. Results of exploratory and confirmatory factor analyses supported a two-factor solution for the PCQ-SA. The PCQ-SA demonstrated excellent internal consistency, excellent test-retest reliability, good convergent validity at both time points (i.e., pre and post speech task), and sensitivity to treatment. Finally, using Receiver Operating Characteristic Curve Analysis, clinical cut-off scores were calculated for probability and consequences at both time points, with the PCQ-SA scales showing good sensitivity, specificity, and positive and negative predictive values. Overall, the results provide evidence that the PCQ-SA possesses excellent psychometric properties. The PCQ-SA is suitable for use in clinical and research settings to assess key cognitive maintaining factors for SAD.

    Original languageEnglish
    Article number102636
    Pages (from-to)1-10
    Number of pages10
    JournalJournal of Anxiety Disorders
    Volume92
    DOIs
    Publication statusPublished - Dec 2022

    Keywords

    • social anxiety
    • self-report
    • probability and consequences questionnaire
    • psychometric properties
    • factor analysis

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