Measurement invariance of the University of Rhode Island Change Assessment Scale in Project MATCH: An exploratory structural equation modeling approach.

BACKGROUND: Progression through the stages of change is a proposed mechanism underlying the effects of treatment for alcohol use disorder (AUD). However, examining stages of change as a mechanism of treatment effects requires that the measure be invariant across patient subgroups, treatment conditions, and time. In this study, we examined measurement invariance of the University of Rhode Island Change Assessment Scale (URICA) in Project MATCH using an exploratory structural equation modeling (ESEM) approach. METHODS: We conducted a secondary analysis of data from Project MATCH (N = 1726; Mage  = 40.2, SD = 10.9; 75.7% male; 80% non-Hispanic white), a multisite randomized clinical trial that tested three AUD treatments: Motivational Enhancement Therapy, Cognitive-Behavioral Therapy, or Twelve-Step Facilitation. Participants completed the 24-item URICA for assessing the stages of change in relation to drinking at baseline and post-treatment (3 months after baseline). RESULTS: A 4-factor ESEM provided a good fit to the data and a better fit to the data than a conventional 4-factor confirmatory factor analysis model. Further, the URICA demonstrated scalar invariance across each patient subgroup at baseline (sex, ethnicity, marital status, education, and parental history of AUD) and treatment condition at follow-up. However, the URICA was not longitudinally invariant as the metric model resulted in a significant decrement in model fit. CONCLUSIONS: Measurement invariance of the URICA over time was not supported. Longitudinally invariant measures of the stages of change are needed to test the proposal that progression through the stages explains treatment effects.

Using Decision Trees to Identify Salient Predictors of Cannabis-Related Outcomes.

Cannabis use continues to escalate among emerging adults and college attendance may be a risk factor for use. Severe cases of cannabis use can escalate to a cannabis use disorder, which is associated with worse psychosocial functioning. Predictors of cannabis use consequences and cannabis use disorder symptom severity have been identified; however, they typically employ a narrow set of predictors and rely on linear models. Machine learning is well suited for exploratory data analyses of high-dimensional data. This study applied decision tree learning to identify predictors of cannabis user status, negative cannabis-related consequences, and cannabis use disorder symptoms. Undergraduate college students (N = 7000) were recruited from nine universities in nine states across the U.S. Among the 7 trees, 24 splits created by 15 distinct predictors were identified. Consistent with prior research, one's beliefs about cannabis were strong predictors of user status. Negative reinforcement cannabis use motives were the most consistent predictors of cannabis use disorder symptoms, and past month cannabis use was the most consistent predictor of probable cannabis use disorder. Typical frequency of cannabis use was the only predictor of negative cannabis-related consequences. Our results demonstrate that decision trees are a useful methodological tool for identifying targets for future clinical research.

Examining Cross-Country and Sex Differences on a Comprehensive Assessment of Protective Behavioral Strategies for Alcohol.

OBJECTIVE: Use of protective behavioral strategies (PBS) has been associated with reduced alcohol-related harms among college students. However, most of this research has been conducted among U.S. samples. The present study examines the use of PBS in an international context. METHOD: Participants (n = 1512) were recruited from universities in Spain (n = 298), Argentina (n = 439), and the U.S. (n = 775) to determine if there are differences in PBS use across countries and/or across sex. Further, we examined whether the association between PBS use and negative consequences differ across country and sex. RESULTS: We found that U.S. students reported the most frequent use of Stopping/Limiting Drinking PBS (M = 3.32, SD = 1.23) compared to Argentine (M = 2.89, SD = 0.97) and Spanish (M = 2.83, SD = 0.94) students. Argentine students reported the least frequent use of Serious Harm Reduction PBS (M = 4.57, SD = 0.99) compared to U.S. (M = 5.09, SD = 0.98) and Spanish (M = 5.03, SD = 0.78) students. Elastic net regression analyses stratified by country indicated most individual PBS predicted decreased negative alcohol-related consequences, although two items consistently predicted increased consequences and we observed some variability in the most predictive specific strategies in each country. Across each subscale and for 32 of 40 individual items, females reported more frequent use of PBS than males (ps<.05). CONCLUSIONS: From the perspective of developing and adapting interventions, we recommend the cultural context in which PBS are used is taken into account. Although future work is needed to delineate cultural factors underlying the country-level differences we found, these findings have implications for the most promising PBS to target for college students in each country.