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Record W3124063765 · doi:10.1111/add.15408

A new perspective on European drinking cultures: a model‐based approach to determine variations in drinking practices among 19 European countries

2021· article· en· W3124063765 on OpenAlexaff
Carolin Kilian, Jakob Manthey, Ludwig Kraus, Pia Mäkelä, Jacek Moskalewicz, Janusz Sierosławski, Jürgen Rehm

Bibliographic record

VenueAddiction · 2021
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental Health
FundersThird Health ProgrammeConsumers, Health, Agriculture and Food Executive AgencyEuropean Commission
KeywordsLatent class modelEnvironmental healthDemographyHeavy drinkingInjury preventionEuropean unionMedicineSuicide preventionPoison controlOccupational safety and healthHuman factors and ergonomicsConfidence intervalPsychology

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: In recent decades, alcohol drinking in the European Union has been characterized by increasing homogenization of levels of drinking coupled with an overall decrease. This study examined whether we can still distinguish distinct practices of drinking by addressing two research questions: (1) are drinking practices still characterized by the choice of a certain alcoholic beverage; and (2) how do drinking practices vary across countries? DESIGN: Cross-sectional study: latent-class analyses of drinking variables and fractional response regression analyses of individual characteristics for individual-level class endorsement probabilities, respectively. SETTING: Nineteen European countries and one autonomous community. PARTICIPANTS: A total of 27 170 past-year drinkers aged 18-65 years in 2015. MEASUREMENTS: Data were collected through the Standardized European Alcohol Survey included frequency of past-year drinking, pure alcohol intake per drink day, occurrence of monthly risky single-occasion drinking and preferred beverage, together with socio-demographic data. FINDINGS: Three latent classes were identified: (1) light to moderate drinking without risky single-occasion drinking [prevalence: 68.0%, 95% confidence interval (CI) = 66.7-69.3], (2) infrequent heavy drinking (prevalence: 12.6%, 95% CI = 11.5-13.7) and (3) regular drinking with at least monthly risky single-occasion drinking (prevalence: 19.4%, 95% CI = 18.1-20.9). Drinking classes differed considerably in beverage preference, with women reporting a generally higher share of wine and men of beer drinking. Light to moderate drinking without risky single-occasion drinking was the predominant drinking practice in all locations except for Lithuania, where infrequent heavy drinking (class 2) was equally popular. Socio-demographic factors and individual alcohol harm experiences (rapid alcohol on-line screen) explained up to 20.5% of the variability in class endorsement. CONCLUSIONS: Beverage preference appears to remain a decisive indicator for distinguishing Europeans' drinking practices. In most European countries, multiple drinking practices appear to be present.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.346
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

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

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 head0.303
Teacher spread0.266 · 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 teacher head, 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

Citations23
Published2021
Admission routes1
Has abstractyes

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