Objective: The present study meta-analyzed studies examining changes in alcohol consumption during the coronavirus disease (COVID-19) pandemic and systematically reviewed contextual and individual difference factors related to these changes. Method: Following the preferred reporting items for systematic reviews and meta-analysis (PRISMA) protocol, studies were gathered via PsycINFO, PubMed/MEDLINE, and preprint databases (published April 29, 2021) that examined individual-level changes in consumption during the initial COVID-19 mitigation measures (before October 2020). Next, sample proportion increases and decreases in consumption, in addition to mean change in consumption variables from pre-to during-COVID, were meta-analyzed, and contextual and individual difference variables related to consumption changes during the pandemic were summarized. Results: One hundred and twenty-eight studies provided data from 58 countries (M n = 3,876; Mdn n = 1,092; aggregate sample n = 492,235). The average mean change in alcohol consumption was nonsignificant (Cohen's d = −0.01, p = .68); however, meta-analysis revealed that 23% of participants reported increases in consumption and 23% reported decreases. These changes were moderated by per capita gross domestic product and country. Narrative synthesis revealed multiple predictors of increased drinking, including contextual changes (e.g., children at home, income loss, working remotely), individual difference variables (being female, a young-to-middle aged adult, or Black), and mental health/alcohol-related risk factors (e.g., depression). Conclusions: The identified factors associated with increased alcohol consumption should be considered in planning behavioral health services during future crisis events that abruptly alter everyday environments in ways that increase stress and decrease access to naturally occurring rewards. Public Health Significance StatementThroughout the early months of the first wave of COVID-19, about one-fourth of study samples reported increases in alcohol consumption, and one-fourth reported decreases in consumption. The review suggested that the pandemic differentially affected drinking based on multiple individual and contextual variables. In light of the emergence of mutant strains and the prediction of similar future pandemics, these results provide an empirical basis for a behavioral health pandemic preparedness plan that could reduce the likelihood of pandemic-related drinking increases.

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Background and Aims Reinforcing value, an index of motivation for a drug, is commonly measured using behavioral economic purchase tasks. State‐oriented purchase tasks are sensitive to phasic manipulations, but with heterogeneous methods and findings. The aim of this meta‐analysis was to characterize the literature examining manipulations of reinforcing value, as measured by purchase tasks and multiple‐choice procedures, to inform etiological models and treatment approaches Methods A random‐effects meta‐analysis of published findings in peer‐reviewed articles. Following the Preferred Reporting Items for Systematic Reviews and Meta‐Analysis (PRISMA) protocol, studies were gathered through searches in PsycINFO and PubMed/MEDLINE (published 22 May 2018). Searches returned 34 unique studies (aggregate sample n = 2402; average sample size = 68.94) yielding 126 effect sizes. Measurements included change (i.e. Cohen's d) in six behavioral economic indices (intensity, breakpoint, Omax, Pmax, elasticity, cross‐over point) in relation to six experimental manipulations (cue exposure, stress/negative affect, reinforcer magnitude, pharmacotherapy, behavioral interventions, opportunity cost). Results Cue exposure (d range = 0.25–0.44, all Ps < 0.05) and reinforcer magnitude [d = 0.60; 95% confidence interval (CI) = 0.18, 1.01; P < 0.005] manipulations resulted in significant increases in behavioral economic demand across studies. Stress/negative affect manipulations also resulted in a small, significant increase in Omax (d = 0.18; 95% CI = 0.01, 0.34; P = 0.03); all other effect sizes for negative affect/stress were non‐significant, albeit similar in size (d range = 0.14–0.18). In contrast, pharmacotherapy (d range = −0.37 to −0.49; Ps < 0.04), behavioral intervention (d = −0.36 to −1.13) and external contingency (d = −1.42; CI = −2.30, −0.54; P = 0.002) manipulations resulted in a significant decrease in intensity. Moderators (substance type) explained some of the heterogeneity in findings across meta‐analyses. Conclusions In behavioral economic studies, purchase tasks and multiple‐choice procedures appear to provide indices that are sensitive to manipulations found to influence motivation to consume addictive substances in field experiments.

Our results support the validity of the behavioral economic reinforcer pathology model as applied to young adult heavy drinking.

Demand, or the amount of a substance consumed as a function of price, is a central dependent measure in behavioral economic research and represents the relative valuation of a substance. Although demand is often utilized as an index of substance use severity and is assumed to be relatively stable, recent experimental and clinical research has identified conditions in which demand can be manipulated, such as through craving and stress inductions, and treatment. Our study examines the 1-month reliability of the alcohol purchase task in a sample of heavy drinking college students. We also analyzed reliability in subgroup of individuals whose consumption decreased, increased, or stayed the same over the 1-month period, and in individuals with moderate/severe Alcohol Use Disorder (AUD) vs. those with no/mild AUD. Reliability was moderate in the full sample, high in the group with stable consumption, and did not differ appreciably between AUD groups. Observed indices and indices derived from an exponentiated equation (Koffarnus et al., 2015) were generally comparable, although Pmax observed had very low reliability. Area under the curve, Omax derived, and essential value showed the greatest reliability in the full sample (rs = .75–.77). These results provide evidence for relative stability over time and across AUD groups, particularly in those whose consumption remains stable.