BACKGROUND: Adolescent and adult samples have shown that the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) abuse and dependence criteria lie on a continuum of alcohol problem severity, but information on criteria functioning in college students is lacking. Prior factor analyses in a college sample (Beseler et al., 2010) indicated that a 2-factor solution fit the data better than a single-factor solution after a binge drinking criterion was included. The second dimension may indicate a clustering of criteria related to excessive alcohol use in this college sample. METHODS: The present study was an analysis of data from an anonymous, online survey of undergraduates (N = 361) that included items pertaining to the DSM-IV alcohol use disorder (AUD) diagnostic criteria and binge drinking. Latent class analysis (LCA) was used to determine whether the criteria best fit a categorical model, with and without a binge drinking criterion. RESULTS: In an LCA including the AUD criteria only, a 3-class solution was the best fit. Binge drinking worsened the fit of the models. The largest class (class 1, n = 217) primarily endorsed tolerance (18.4%); none were alcohol dependent. The middle class (class 2, n = 114) endorsed primarily tolerance (81.6%) and drinking more than intended (74.6%); 34.2% met criteria for dependence. The smallest class (class 3, n = 30) endorsed all criteria with high probabilities (30 to 100%); all met criteria for dependence. Alcohol consumption patterns did not differ significantly between classes 2 and 3. Class 3 was characterized by higher levels on several variables thought to predict risk of alcohol-related problems (e.g., enhancement motives for drinking, impulsivity, and aggression). CONCLUSIONS: Two classes of heavy-drinking college students were identified, one of which appeared to be at higher risk than the other. The highest risk group may be less likely to "mature out" of high-risk drinking after college.
BACKGROUND: Adolescent and adult samples have shown that the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) abuse and dependence criteria lie on a continuum of alcohol problem severity, but information on criteria functioning in college students is lacking. Prior factor analyses in a college sample (Beseler et al., 2010) indicated that a 2-factor solution fit the data better than a single-factor solution after a binge drinking criterion was included. The second dimension may indicate a clustering of criteria related to excessive alcohol use in this college sample. METHODS: The present study was an analysis of data from an anonymous, online survey of undergraduates (N = 361) that included items pertaining to the DSM-IV alcohol use disorder (AUD) diagnostic criteria and binge drinking. Latent class analysis (LCA) was used to determine whether the criteria best fit a categorical model, with and without a binge drinking criterion. RESULTS: In an LCA including the AUD criteria only, a 3-class solution was the best fit. Binge drinking worsened the fit of the models. The largest class (class 1, n = 217) primarily endorsed tolerance (18.4%); none were alcohol dependent. The middle class (class 2, n = 114) endorsed primarily tolerance (81.6%) and drinking more than intended (74.6%); 34.2% met criteria for dependence. The smallest class (class 3, n = 30) endorsed all criteria with high probabilities (30 to 100%); all met criteria for dependence. Alcohol consumption patterns did not differ significantly between classes 2 and 3. Class 3 was characterized by higher levels on several variables thought to predict risk of alcohol-related problems (e.g., enhancement motives for drinking, impulsivity, and aggression). CONCLUSIONS: Two classes of heavy-drinking college students were identified, one of which appeared to be at higher risk than the other. The highest risk group may be less likely to "mature out" of high-risk drinking after college.
Authors: Nicholas J Kuvaas; Robert D Dvorak; Matthew R Pearson; Dorian A Lamis; Emily M Sargent Journal: Addict Behav Date: 2013-10-02 Impact factor: 3.913
Authors: Leah Wetherill; Manav Kapoor; Arpana Agrawal; Kathleen Bucholz; Daniel Koller; Sarah E Bertelsen; Nhung Le; Jen-Chyong Wang; Laura Almasy; Victor Hesselbrock; John Kramer; John I Nurnberger; Marc Schuckit; Jay A Tischfield; Xiaoling Xuei; Bernice Porjesz; Howard J Edenberg; Alison M Goate; Tatiana Foroud Journal: Alcohol Clin Exp Res Date: 2013-09-09 Impact factor: 3.455