Impaired Control over Alcohol Consumption: Laboratory and Field Investigations

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Abstract Excessive alcohol use remains a significant public health problem in the US. A better understanding of the psychological processes underlying excessive drinking is needed so that more effective interventions can be developed. Recent research has focused on impaired control, manifest as a failure to avoid drinking or to limit consumption once it has begun. To better understand the processes underlying impaired control, we developed a novel human laboratory model (Resist CASE) that assesses actual consumption behavior indicative of impaired control. If Resist CASE is a good model, it could be used to evaluate whether impaired control can be modified by psychological or pharmacological manipulations. In the proposed study, we compare self-administration of alcohol in the laboratory model against actual drinking behavior in the field using ecological momentary assessment (EMA). The Sponsor and Co-Sponsor have expertise in laboratory and field assessments respectively. EMA will include assessment of current motivation to abstain and recent drinking. Heavy drinkers (N=37) will complete two Resist CASE sessions, one with a priming alcohol exposure and one without. At each session the ability to resist self-administering alcohol will be assessed (“Resist”), as well as self-administration during an open bar (“Lab Consumption”). Participants will complete six weeks of EMA to assess motivation and drinking. The overall goal is to examine the validity of the laboratory model. The specific aims are 1) To examine the association between ability to resist alcohol self- administration in the lab (Resist) and the ability to abstain from drinking in the real-world, assessed using EMA; 2) To examine the association between alcohol self-administration in the lab during open bar (Lab Consumption) and drinking behavior in the real-world, assessed using EMA; and 3) To examine predictors of resisting and drinking in the lab and field. Laboratory and EMA data from this study may ultimately help to develop algorithms that can predict when an individual is at risk of drinking, and to develop interventions, administered in the field, to reduce the risk of poor outcomes associated with drinking.