# Examining the Impact of Stress on the Emotionally Reinforcing Properties of Alcohol in Heavy Social Drinkers: A Multimodal Investigation Integrating Laboratory and Ambulatory Methods

> **NIH NIH R01** · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · 2023 · $523,246

## Abstract

Alcohol’s ability to improve mood in the face of stress is among its most prized reinforcing properties, long held
by researchers to be of critical importance for the understanding of the etiology of alcohol use disorder (AUD).
Drinkers overwhelmingly report that the mood-enhancement they gain from alcohol is most pronounced in the
context of stress, and individuals who report higher levels of stress relief from alcohol are at risk for developing
AUD. But attempts to capture this key element of alcohol reinforcement using experimental methods have
yielded strikingly inconsistent results. One remarkable feature of the extant experimental literature is that, in
attempting to capture alcohol’s stress-relieving effects, researchers have strayed far outside the range of
stressors typically encountered in everyday drinking settings, contexts that are overwhelmingly social in
nature. Here, we harness the power of stressful stimuli that emerge naturally within everyday contexts,
focusing on social novelty as a compound stress-trigger ubiquitous to real-world heavy drinking settings.
Building on our prior work indicating enhanced alcohol reward in novel compared with familiar social context,
together with pilot findings pointing to potential links between social novelty and hazardous patterns of
drinking, we draw on innovative methods and measures to further build the understanding of social-contextual
factors driving consumption. Specifically, we leverage multi-participant neuroimaging recording arrays (i.e.,
hyperscanning) to pinpoint both inter- and intra-brain processes underlying alcohol reinforcement, a
mechanistic analysis we complement with ambulatory and longitudinal methods for tracing real world patterns
of consumption. Participants (N=240) will attend two experimental laboratory sessions, on one of which they
will consume alcohol and on the other a control beverage. Participants will complete tasks in the company of
either a stranger or familiar individual while EEG is recorded from both participants simultaneously.
Participants will also engage in a 14-day ambulatory assessment period during which drinking will be assessed
continuously via transdermal alcohol biosensor while social context is explored via in-vivo photographic image-
capture methods. Finally, longitudinal changes in hazardous drinking and AUD symptoms will be assessed for
24 months post-baseline. The aims of the project are to: 1) Explore diminished threat sensitivity and enhanced
social engagement as mechanisms driving alcohol reward in novel social context; 2) Examine social reward-
attentive processes as well as social-contextual novelty as predictors of hazardous drinking and AUD. The
proposed research contributes to the understanding of AUD by addressing one of the most fundamental
questions in the alcohol literature—the question of why people drink. Further, representing a critical step
towards building a contextually-informed, mechanistically precise model of AUD etiolo...

## Key facts

- **NIH application ID:** 10735704
- **Project number:** 2R01AA025969-06
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
- **Principal Investigator:** Catharine Fairbairn
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $523,246
- **Award type:** 2
- **Project period:** 2023-08-15 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10735704

## Citation

> US National Institutes of Health, RePORTER application 10735704, Examining the Impact of Stress on the Emotionally Reinforcing Properties of Alcohol in Heavy Social Drinkers: A Multimodal Investigation Integrating Laboratory and Ambulatory Methods (2R01AA025969-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10735704. Licensed CC0.

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