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Record W4410051015 · doi:10.1016/j.drugpo.2025.104826

Restrictive and permissive alcohol policies during the COVID-19 pandemic and their association with alcohol consumption in the United States

2025· article· en· W4410051015 on OpenAlexaff
Julia M. Lemp, Carolin Kilian, Sophie Bright, William C. Kerr, Laura Llamosas‐Falcón, Nina Mulia, Jürgen Rehm, Charlotte Probst

Bibliographic record

VenueInternational Journal of Drug Policy · 2025
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsCentre for Addiction and Mental Health
FundersNational Institutes of HealthNational Institute on Alcohol Abuse and AlcoholismMinisterium für Wissenschaft, Forschung und Kunst Baden-WürttembergDeutsche Forschungsgemeinschaft
KeywordsPermissiveCoronavirus disease 2019 (COVID-19)PandemicAlcohol consumptionAssociation (psychology)2019-20 coronavirus outbreakConsumption (sociology)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)AlcoholHuman factors and ergonomicsSuicide preventionPoison controlInjury preventionCriminologyPolitical sciencePsychologyEnvironmental healthMedicineVirologySociologyBiologyOutbreak

Abstract

fetched live from OpenAlex

• Analysis integrates BRFSS survey data with data on alcohol policy measures to disentangle the distinct effects of restrictive and permissive policies on alcohol consumption in 2020 and 2021. • Cross-sectional results support a polarization of alcohol consumption patterns during COVID-19, with varied effects across demographic groups and drinking behaviors. • Restrictive alcohol policies linked to lower overall drinking prevalence, especially among younger adults, but increased daily consumption and heavy episodic drinking (HED) among drinkers. • Permissive alcohol policies linked to higher drinking rates among people with high education. • Women reported a higher relative increase in the frequency of HED compared to men when experiencing additional psychological distress, highlighting possible gendered impacts of the pandemic. Early in the COVID-19 pandemic, alcohol researchers anticipated that psychological distress and changes in alcohol availability would impact alcohol consumption patterns. While psychological distress was expected to increase alcohol use, particularly among vulnerable groups, restrictive alcohol policies might have led to reduced consumption. This study examined the complex relationship between psychological distress, alcohol policies, alcohol consumption, and their interactions with sociodemographic factors during the COVID-19 pandemic in the US. We used 2020–21 US Behavioral Risk Factor Surveillance System Survey (BRFSS, N = 726,962 adults) data to analyze associations between psychological distress, alcohol policy scores, and alcohol consumption, considering age, sex, education, race and ethnicity, and COVID-19 government response as covariates in a zero-inflated multi-level regression. State-level monthly alcohol policy scores derived from Alcohol Policy Information System data reflect the restrictiveness and permissiveness of alcohol policies implemented during the COVID-19 pandemic. Psychological distress and exposure to restrictive policies increased the likelihood of abstaining from alcohol in the past month, although the observed effects were small. Among past-month drinkers, distress and restrictive policies were associated with slightly higher average daily consumption in pure alcohol grams/day. Younger respondents were more likely to abstain from alcohol when exposed to restrictive policies, while permissive policies correlated with higher drinking prevalence and heavy episodic drinking occurrence among those with higher education. Alcohol policies and psychological distress during the COVID-19 pandemic were linked to both lower and higher alcohol consumption in different population subgroups. Restrictive and permissive policies had diverging associations with consumption patterns across subgroups. While effect sizes were modest, they could translate into meaningful changes in alcohol consumption at the population level, especially during prolonged times of crisis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.365
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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