What is it about?
The AUDIT (Alcohol Use Disorders Identification Test) is the most widely used alcohol screening tool in clinical and research settings, yet debate existed about whether it measures a single underlying construct of hazardous alcohol use or multiple distinct dimensions. This study used data from a nationally representative stratified multi-stage random sample of 7,849 adults in Great Britain who completed the AUDIT as part of a computer-assisted interview. Confirmatory factor analyses tested one-, two- and three-factor models of the AUDIT's structure to determine which best fit the data. The factors in each model were then correlated with demographic variables, perceived wellbeing, verbal IQ, and neurotic and psychotic symptom scores to assess the construct validity of each solution, establishing how well the AUDIT dimensions map onto clinically and theoretically meaningful external variables.
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Why is it important?
The psychometric properties of the AUDIT have fundamental implications for how alcohol screening results are interpreted, how populations are classified in research, and how scores should be used in clinical decision-making. A nationally representative UK sample provides a much stronger basis for conclusions about AUDIT structure than the clinical or student samples used in many prior validation studies. Establishing whether the AUDIT captures one or multiple distinct dimensions matters for clinical practice: a multidimensional structure means that total scores can mask important differences between people with high consumption but low dependence and those with the reverse profile. This study laid important groundwork for the subsequent structural equation modelling work examining demographic and clinical correlates of each AUDIT dimension in the same dataset.
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This page is a summary of: The factor structure and concurrent validity of the alcohol use disorder identification test based on a nationally representative UK sample, Alcohol and Alcoholism, July 2007, Oxford University Press (OUP),
DOI: 10.1093/alcalc/agm045.
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