Prediction Rules Identify Which Young Adults Have Higher Rates of Heavy Episodic Drinking After Exposure to 12-Week Text Message Interventions.

Background: An alcohol text message intervention recently demonstrated effects in reducing heavy episodic drinking (HED) days at the three month follow-up in young adults with a history of hazardous drinking. An important next step in understanding intervention effects involves identifying baseline participant characteristics that predict who will benefit from intervention exposure to support clinical decision-making and guide further intervention development. To identify baseline characteristics that predict HED, this exploratory study used a prediction rule ensemble (PRE). Compared to more complex decision-tree methods (e.g., random forest), PREs have comparable performance, while generating simpler rules that can directly identify subgroups that do or do not respond to intervention.

Methods: This secondary analysis examined data from 916 young adults who reported HED (68.5% female, mean age = 22.1, SD = 2.1), were enrolled in an alcohol text message randomized clinical trial and who completed baseline assessment and the three month follow-up. A PRE with ten fold cross-validation, which included 21 baseline variables representing sociodemographic characteristics (e.g., sex, age, race, ethnicity, college enrollment), alcohol consumption (frequency of alcohol consumption, quantity consumed on a typical drinking day, frequency of HED), impulsivity subscales (i.e., negative urgency, positive urgency, lack of premeditation, lack of perseverance, sensation seeking), readiness to change, perceived peer drinking and HED-related consequences, and intervention status were used to predict HED at the three month follow-up.

Results: The PRE identified 12 rules that predicted HED at three months (R² = 0.23) using 7 baseline features. Only two cases (0.2%) were not classified by the 12 rules. The most important features for predicting three month HED included baseline alcohol consumption, negative urgency score, and perceived peer drinking.

Conclusions: The rules provide interpretable decision-making tools that predict who has higher alcohol consumption following exposure to alcohol text message interventions using baseline participant characteristics (prior to intervention), which highlight the importance of interventions related to negative urgency and peer alcohol use.