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Record W3120116246 · doi:10.1111/add.15530

Alcohol consumption during the COVID‐19 pandemic in Europe: a large‐scale cross‐sectional study in 21 countries

2021· article· en· W3120116246 on OpenAlexaff
Carolin Kilian, Jürgen Rehm, Peter Alle­beck, Fleur Braddick, Antoni Gual, Miroslav Barták, Kim Bloomfield, Artyom Gil, Maria Neufeld, Amy O’Donnell, Benjamin Petruželka, Vladimír Rogalewicz, Bernd Schulte, Jakob Manthey

Bibliographic record

VenueAddiction · 2021
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
FundersUniversitat de BarcelonaHáskóli ÍslandsUniversity of CreteNorwegian Institute of Public HealthNational Institute for Health and Care ResearchHelsingin YliopistoNational Research CentreBudapesti Corvinus EgyetemMinistry of Health of the Russian FederationWorld Health Organization
KeywordsCross-sectional studyCoronavirus disease 2019 (COVID-19)PandemicAlcohol consumptionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakEnvironmental healthScale (ratio)MedicineGeographyVirologyAlcoholOutbreakCartographyBiology

Abstract

fetched live from OpenAlex

AIMS: To investigate changes in alcohol consumption during the first months of the COVID-19 pandemic in Europe as well as its associations with income and experiences of distress related to the pandemic. DESIGN: Cross-sectional on-line survey conducted between 24 April and 22 July 2020. SETTING: Twenty-one European countries. PARTICIPANTS: A total of 31 964 adults reporting past-year drinking. MEASUREMENTS: Changes in alcohol consumption were measured by asking respondents about changes over the previous month in their drinking frequency, the quantity they consumed and incidence of heavy episodic drinking events. Individual indicators were combined into an aggregated consumption-change score and scaled to a possible range of -1 to +1. Using this score as the outcome, multi-level linear regressions tested changes in overall drinking, taking into account sampling weights and baseline alcohol consumption [Alcohol Use Disorder Identification Test (AUDIT-C)] and country of residence serving as random intercept. Similar models were conducted for each single consumption-change indicator. FINDINGS: The aggregated consumption-change score indicated an average decrease in alcohol consumption of -0.14 [95% confidence interval (CI) = -0.18, -0.10]. Statistically significant decreases in consumption were found in all countries, except Ireland (-0.08, 95% CI = -0.17, 0.01) and the United Kingdom (+0.10, 95% CI = 0.03, 0.17). Decreases in drinking were mainly driven by a reduced frequency of heavy episodic drinking events (-0.17, 95% CI = -0.20, -0.14). Declines in consumption were less marked among those with low- or average incomes and those experiencing distress. CONCLUSIONS: On average, alcohol consumption appears to have declined during the first months of the COVID-19 pandemic in Europe. Both reduced availability of alcohol and increased distress may have affected consumption, although the former seems to have had a greater impact in terms of immediate effects.

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)0.002
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
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 integrity0.0010.000
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 head0.085
GPT teacher head0.430
Teacher spread0.345 · 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

Citations182
Published2021
Admission routes1
Has abstractyes

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