VALIDATION AND APPLICATION OF AN ALCOHOL-RELATED PROBLEM SCALE FOR AMERICAN INDIAN ADOLESCENTS: RACE MODERATING THE RELATIONSHIP BETWEEN ALCOHOL CONSUMPTION AND ALCOHOLRELATED PROBLEMS

American Indian (AI) communities and researchers have identified alcohol as a primary concern for AI, acknowledging the severity of alcohol-related consequences experienced by individuals, families, and whole communities (Stanley, Harness, Swaim, & Beauvais, 2014; Yuan et al., 2010) as well as the long-term damaging effects (Radin et al., 2015). Though extant research has shown varied results regarding actual prevalence rates of alcohol use among AI adolescents (Lynne-Landsman, Komro, Kominsky, Boyd, & Maldonado-Molina, 2016; Whitbeck et al., 2014), there is strong agreement that AI youth suffer disproportionate negative consequences associated with alcohol use (Landen, Roeber, Naimi, Nielsen, & Sewell, 2014; Prevention, 2008; Indian Health Services, 2018; Szlemko, Wood, & Thurman, 2006). Despite this, there are few to no measures of alcohol-related consequences that have been validated with AI/AN samples. Thus, the purpose of this study is to evaluate the psychometric properties of the American Drug and Alcohol Survey’s (ADASTM) alcohol-related problem scale for AI adolescents, and to examine how race (AI and non-Hispanic White) moderates the relationship between alcohol consumption and alcohol-related problems. The current study (n = 2,214, 52.1% female) is a secondary data analysis study of a large population-based sample that included youth between the ages of 15-21 drawn from a large sample of adolescents living on or near a reservation. The scale had good internal consistency, Cronbach’s alpha = . 834. Results from the principal component analysis suggested one-factor and confirmatory factor analysis confirmed a one-factor model. Multiple group confirmatory factor analysis found the ADAS’sTM alcohol-related problem scale was invariant across race (AI and non-Hispanic white) and sex (female and male), suggesting that the scale is appropriate for use to compare across groups (race and sex) with little to no measurement bias. However, a multi-group confirmatory factor analysis was conducted with all four groups and that model failed to reach convergence. Pointbiserial correlations revealed a significant positive association between frequency of endorsing drinking over the past-12 months (r(2076) = . 435, p < . 001) and frequency of endorsing being drunk over the past-12 months (r(2017) = . 535, p < . 001) and alcohol-related problems, suggesting this scale can be considered valid. Next, two multilevel regression analyses to evaluate the effects of age, sex, alcohol use and race (level 1 variables) and accounted for nesting with community location (level 2), on alcohol-related problems. A significant main effect was found for race (b = -0.559, SE = 0.102, t = -5.485, p <.001, 95% CI [-0.759, -0.359]), and frequency of drinking over 12-months (b = 0.524, SE = 0.054, t = 9.671, p <.001, 95% CI [0.418, 0.631]), on alcohol-related problems, as well as for race (b = -0.513, SE = 0.102, t = -5.01, p <.001, 95% CI [-0.714, -0.312], and frequency of being drunk over 12-months on alcohol-related problems (b = 0.562, SE = 0.053, t = 10.700, p <.001, 95% CI [0.459, 0.666]). A significant main effect was found between the association of alcoholrelated problems and drinking, and alcohol-related problems and being drunk, for both AI and non-Hispanic white adolescents. Though, simple slopes revealed these relationships were stronger for AI adolescents. Results from this study aid in the alcohol-related health disparity literature for AI adolescents and emphasize the importance of using cross-culturally validated measures with use among AI.