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.