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Psychometric Validation of the Diagnostic...
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Psychometric Validation of the Diagnostic Assessment for Research and Treatment for Alcohol Use Disorder

Abstract

Aims: Structured clinical interviewing is considered the gold standard in psychiatric diagnosis. The Diagnostic Assessment and Research Tool (DART) is a novel modularized semi-structured interview; however, no studies have examined the psychometric properties of its alcohol use disorder (AUD) module. The primary aims of this study were: (1) to validate the factor structure of the DART AUD module and (2) to examine measurement invariance across several key demographic and subgroup factors.Methods: Participants were community members in Hamilton, Canada and Boston, USA who self-identified as making a significant recovery attempt from problematic alcohol use (N = 499). Internal reliability was examined via the Kuder-Richardson 20 statistic, and correlations between symptom count and drinking quantity/frequency were examined. Then, symptom-level data were included in a confirmatory factor analysis to examine model fit of a single hypothesized factor structure. Finally, measurement invariance of the factor were conducted for sex, age, ethnicity (White vs. racialized), and study site. Results: This study found evidence for adequate internal reliability (rKR20 = 0.75), and symptom scores correlated with drinking quantity and frequency (r = 0.16 - 0.43). CFA suggested indices of the unidimensional one-factor AUD model were excellent (χ2 = 0.092, CFI = 0.99, TLI = 0.99, SRMR = 0.06, RMSEA = 0.02). Measurement invariance analyses revealed that the factor structure was equivalent between sex, age, ethnicity, and study site. Conclusions: Together, these findings provide strong evidence for psychometric properties of the AUD DART module and provide psychometric evidence supporting its use in research and clinical practice.

Authors

Garber ML; Belisario KL; Levitt E; McCabe RE; Kelly J; MacKillop J

Publication date

September 15, 2024

DOI

10.31234/osf.io/xjsgf

Preprint server

PsyArXiv

Labels

Sustainable Development Goals (SDG)

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