Date Approved

8-15-2023

Embargo Period

8-16-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Psychology

College

College of Science & Mathematics

Advisor

Bethany Raiff, Ph.D.

Committee Member 1

Chelsie Young, Ph.D.

Committee Member 2

Steven Brunwasser, Ph.D.

Committee Member 3

Mikhail Koffarnus, Ph.D.

Keywords

COVID-19, coping strategies, alcohol use, reinforcement pathology

Subject(s)

Alcoholism

Disciplines

Psychology | Social and Behavioral Sciences

Abstract

The COVID-19 pandemic is the largest global public health challenge of this century. Concerns were raised that the rapid changes associated with daily life during the initial months of the pandemic would increase depression and alcohol use. However, changes in population-level alcohol use have been mixed. Behavioral economic theories of addiction, such as the Reinforcer Pathology (RP) model, have been proposed as well suited to identify individuals, and inform interventions, to address these concerns. However, no quantitative research has validated this claim in a sample recruited during the pandemic. The current study extended upon existing research by examining patterns of RP measures in predicting alcohol use and related outcomes from a sample (n=788) recruited from social media websites during June and July 2020. Latent profile analysis revealed that a three-profile solution provided the best fit to the data, with participants from the profile best resembling the theorized RP characteristics of high demand and delay discounting showing significantly greater alcohol consumption, alcohol use disorder symptoms, alcohol-related problems, and symptoms of alcohol use disorder than those in the other two classes. These results lend support to the RP model of addiction and potentially the use of assessment and intervention approaches based on RP principles in a context where there is restricted access to reinforcers, social and otherwise

Available for download on Saturday, August 16, 2025

Included in

Psychology Commons

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