OBJECTIVE: Past research assessing the factor structure of the Alcohol Use Disorders Identification Test (AUDIT) with various exploratory and confirmatory factor analytic techniques has identified one-, two-, and three-factor solutions. Because different factor analytic procedures may result in dissimilar findings, we examined the factor structure of the AUDIT using the same factor analytic technique on two new large clinical samples and on archival data from six samples studied in previous reports. METHOD: Responses to the AUDIT were obtained from participants who met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), criteria for alcohol dependence in two large randomized clinical trials: the COMBINE (Combining Medications and Behavioral Interventions) Study (N = 1,337; 69% men) and Project MATCH (Matching Alcoholism Treatments to Client Heterogeneity; N = 1,711; 76% men). Supplementary analyses involved six correlation matrices of AUDIT data obtained from five previously published articles. Confirmatory factor analyses based on one-, two-, and three-factor models were conducted on the eight correlation matrices to assess the factor structure of the AUDIT. RESULTS: Across samples, analyses supported a correlated, two-factor solution representing alcohol consumption and alcohol-related consequences. The three-factor solution fit the data equally well, but two factors (alcohol dependence and harmful alcohol use) were highly correlated. The one-factor solution did not provide a good fit to the data. CONCLUSIONS: These findings support a two-factor solution for the AUDIT (alcohol consumption and alcohol-related consequences). The results contradict the original three-factor design of the AUDIT and the prevalent use of the AUDIT as a one-factor screening instrument with a single cutoff score.
OBJECTIVE: Past research assessing the factor structure of the Alcohol Use Disorders Identification Test (AUDIT) with various exploratory and confirmatory factor analytic techniques has identified one-, two-, and three-factor solutions. Because different factor analytic procedures may result in dissimilar findings, we examined the factor structure of the AUDIT using the same factor analytic technique on two new large clinical samples and on archival data from six samples studied in previous reports. METHOD: Responses to the AUDIT were obtained from participants who met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), criteria for alcohol dependence in two large randomized clinical trials: the COMBINE (Combining Medications and Behavioral Interventions) Study (N = 1,337; 69% men) and Project MATCH (Matching Alcoholism Treatments to Client Heterogeneity; N = 1,711; 76% men). Supplementary analyses involved six correlation matrices of AUDIT data obtained from five previously published articles. Confirmatory factor analyses based on one-, two-, and three-factor models were conducted on the eight correlation matrices to assess the factor structure of the AUDIT. RESULTS: Across samples, analyses supported a correlated, two-factor solution representing alcohol consumption and alcohol-related consequences. The three-factor solution fit the data equally well, but two factors (alcohol dependence and harmful alcohol use) were highly correlated. The one-factor solution did not provide a good fit to the data. CONCLUSIONS: These findings support a two-factor solution for the AUDIT (alcohol consumption and alcohol-related consequences). The results contradict the original three-factor design of the AUDIT and the prevalent use of the AUDIT as a one-factor screening instrument with a single cutoff score.
Authors: Chun-Zi Peng; Richard W Wilsnack; Arlinda F Kristjanson; Perry Benson; Sharon C Wilsnack Journal: Drug Alcohol Depend Date: 2012-01-10 Impact factor: 4.492
Authors: Patrick D Quinn; Erik Pettersson; Sebastian Lundström; Henrik Anckarsäter; Niklas Långström; Clara Hellner Gumpert; Henrik Larsson; Paul Lichtenstein; Brian M D'Onofrio Journal: Am J Med Genet B Neuropsychiatr Genet Date: 2015-12-30 Impact factor: 3.568
Authors: Lisa R LaRowe; Jessica M Powers; Lorra Garey; Andrew H Rogers; Michael J Zvolensky; Joseph W Ditre Journal: Drug Alcohol Depend Date: 2020-07-10 Impact factor: 4.492