A Multi-Method Study of Extreme Alcohol Drinkers in the Lab and in Real-Life: Increasing Precision of Assessments of Extreme Drinking Determinants

Authors: Bruce D. Bartholow, Timothy J. Trull, Ian R. Gizer, Paige DeGennaro, Caroline C. Boyd-Rogers, Julia L. Smith, Shuo Yan, Denis M. McCarthy, Kenneth Shur, Yi Shang, Thomas Piasecki, Derek D. Morgan
Cited by: 0

Abstract

This study seeks to provide some of the first comprehensive data about influences on the extreme drinking phenotype, and to compare them with those for the typical binge drinking phenotype. We will leverage new technologies in a multi-method, intensive longitudinal study that can overcome many of the limitations of assessing extreme drinking by retrospective self-report. The project combines laboratory alcohol administration, ecological momentary assessment (EMA), and real-time BAC assessment (via portable breathalyzer) to predict binge (drinking to a BAC of .08-.159) and extreme drinking (BAC ≥ .16) and their consequences. Integrating these methods will allow us to test the structural associations among inter- (e.g., personality, genotype) and intra-individual (e.g., mood variability, craving) influences, across multiple levels of environmental influences (macro (outlet density) to micro (drinking situation)). The current study aims to: 1. Evaluate the validity and utility of real-time assessments for predicting High Intensity Drinking (HID) episodes and related behaviors. 2. Characterize the structural influence of stable individual differences, transient intra-individual factors, and environmental variables on risky, binge, and HID drinking occasions and alcohol negative consequences through use of environmental, genetic, neural, physiological, and psychological assessments and self-report. 3. Identify multidimensional profiles associated with stable or highly variable binge and HID drinking behavior.

Fields of Study & Subjects

Substance Abuse Treatment and Outcomes Alcohol Consumption and Health Effects Mental Health Research Topics

Publication details

Journal / source
OSF Preprints (OSF Preprints)
Publication date
13 February 2026
Language
EN
Document type
Preprint