Developing and Validating a Computerized Adaptive Test to Measure Broad and Specific Factors of Internalizing in a Community Sample

Matthew Sunderland*, Philip Batterham, Natacha Carragher, Alison Calear, Tim Slade

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    18 Citations (Scopus)

    Abstract

    Highly efficient assessments that better account for comorbidity between mood and anxiety disorders (internalizing) are required to identify individuals who are most at risk of psychopathology in the community. The current study examined the efficiency and validity associated with a multidimensional computerized adaptive test (CAT) to measure broad and specific levels of internalizing psychopathology. The sample comprised 3,175 respondents to an online survey. Items from five banks (generalized anxiety, depression, obsessive–compulsive disorder, panic disorder, social anxiety disorder) were jointly calibrated using a bifactor item response theory model. Simulations indicated that an adaptive algorithm could accurately (rs ≥ 0.90) estimate general internalizing and specific disorder scores using on average 44 items in comparison with the full 133-item bank (67% reduction in items). Scores on the CAT demonstrate convergent and divergent validity with previously validated short severity scales and could significantly differentiate cases of DSM-5 disorder. As such, the CAT validly measures both broad and specific constructs of internalizing disorders in a manner similar to the full item bank and a static brief form but with greater gains in efficiency and, therefore, a reduced degree of respondent burden.

    Original languageEnglish
    Pages (from-to)1030-1045
    Number of pages16
    JournalAssessment
    Volume26
    Issue number6
    DOIs
    Publication statusPublished - 1 Sept 2019

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