The Addictive Behaviors and Health Studies Group and the Center for Behavioral Economic Health Research at the University of Florida welcome you to our research project titled “Digital Motivational Behavioral Economic Intervention to Reduce Risky Drinking Among Community-Dwelling Emerging Adults Research Project.”



This study will be the first to test a web-based alcohol risk reduction intervention to reach community-dwelling emerging adults using behavioral economic principles and digital respondent-driven sampling. The 5-year project is funded by the National Institute of Alcohol Abuse and Alcoholism, National Institutes of Health, and the Principal Investigator is Professor Jalie A. Tucker, Ph.D., M.P.H.

Project Narrative

Digital Motivational Behavioral Economic Intervention to Reduce Risky Drinking Among Community-Dwelling Emerging Adults Research Project.

Preventive interventions for college student risky drinkers are well established, but the needs of emerging adult risky drinkers who live in disadvantaged communities and are not fulltime college students have been neglected, and they often have more limited access to rewarding opportunities, activities, and adult roles that present alternatives to heavy drinking. Guided by behavioral economics, this randomized controlled trial will address their needs by evaluating an evidence-based behavioral intervention aimed at increasing future orientation and engagement in pro-social alternatives to drinking and will be delivered using a peer-driven sampling method and digital platform well suited for accessing emerging adult social networks. The study will be the first to test a web-based alcohol reduction intervention focused on behavioral economic principles and has high potential for reach and scalability with under-served community risk groups.

This study aims to: (1) Evaluate intervention efficacy, which is predicted to reduce risky drinking and negative alcohol-related consequences. (2) Evaluate intervention change mechanisms and boundary conditions. (3) Use a network ego approach to assess how network members are arranged around each participant and how network features are associated with participant drinking.