The purpose of this study is to understand how certain interventions help people reduce or quit their drinking and how certain interventions may help best at certain points in time in the change process.

Problem drinkers (PDs) represent a majority of the estimated 32 million Americans with alcohol problems that spans a spectrum of severity from individuals who drink excessively and experience of occasional negative consequences to those with moderate Alcohol Dependence (AD) and intact psychosocial functioning. PDs can benefit from relatively brief treatment that could be delivered in mainstream healthcare, but less than 5% receive such care. In addition, PD treatment is only modestly effective, and there is a surprising absence of empirical research to guide PD treatment selection. Adaptive Interventions (AI) are a novel approach to treatment development that may have significant advantages over fixed treatments in improving efficacy and fostering adoption of Evidence Based Practices in mainstream healthcare. If study aims are achieved, a set of empirically-derived decision support tools will be created to guide Alcohol Use Disorders (AUD) care similar to tools that exist for other chronic diseases. In addition, new knowledge will be gained about Mechanisms of Behavior Change of AUD that can guide future AUD treatment research. Finally, important progress will be made in methods that capitalize on the remarkable advances in sensor technologies, advanced mathematics, and engineering to create a new type of tailored, near-real time feedback, adaptive behavior therapies.

Primary Inclusion Criteria: Adults who have heavy weekly alcohol consumption (and/or an alcohol use disorder) and are willing to reduce their drinking.

Primary Exclusion Criteria: Adults for whom the level of treatment provided is not appropriate and/or who require more intensive substance use or psychiatric treatment.