Modeling the value-based decision to consume alcohol in response to emotional experiences

Abstract

Evidence for negative reinforcement of alcohol use is mixed; one possible explanation for this is that people make value-based decisions whether to regulate their emotions via alcohol or an alternative, and only drink-to-cope when alcohol’s reinforcing value is larger than that of available alternatives. If this is the case, immediately following a negative emotional event, the value for alcohol should increase primarily in heavy drinkers, whereas in light drinkers, alternative ways of coping should be valued. We conducted a preregistered online experiment (N = 200) with a mixed design (between - heavy vs. light drinker; within - negative/neutral/positive mood induction). In each of three experimental sessions, participants first provided value ratings for a set of alcohol and food stimuli. Second, they were subjected to a mood induction. Third, they made forced choices between either two alcohol or food stimuli. We then applied a drift-diffusion model to these data and tested whether alcohol- and food-related decision-making parameters are differentially affected following the mood inductions in heavy and light drinkers. In preregistered analyses, we found that heavy drinkers did not value alcohol more but valued food less after the negative mood induction. Exploratory analyses uncovered that both heavy- and light-drinking participants valued alcohol more following the negative mood induction if they reported high alcohol craving at the start of the session. Collectively, these results provide some evidence for the idea that drinking-to-cope might be a value-based decision-making process.

Publication
In Experimental and Clinical Psychopharmacology
Click the Cite button above to demo the feature to enable visitors to import publication metadata into their reference management software.
Create your slides in Markdown - click the Slides button to check out the example.

Supplementary notes can be added here, including code, math, and images.

Jonas Dora
Jonas Dora
Postdoc

Dr. Jonas Dora is a postdoc at the University of Washington.