Meta-analyses and reviews have demonstrated the efficacy and effectiveness of many interventions preventing alcohol use in adolescents and young adults (Foxcroft et al. 2003; Smit et al. 2008; Tobler et al. 2000). Particularly, many interventions with randomized control trials (RCTs) have been shown to reduce the rates of growth of alcohol use during adolescence (e.g., Mason et al. 2003; Taylor et al. 2000). However, intervention impacts generally have modest effect size, especially with regard to long term effects. To better allocate limited intervention resources and to achieve optimal and long-term outcomes, research has begun to prioritize the identification of subgroups of the population that respond differentially to interventions, as well as individual characteristics that identify these subgroups (Bakermans-Kranenburg and van Ijzendoorn 2015; Bloom and Michalopoulos 2013). These individual characteristics can provide potential markers or targets for future adaptive and tailored interventions to maximize the fit between individuals and intervention programs to strengthen and bolster intervention effects.
