Adolescent Drinking Patterns Across Countries: Associations with Alcohol Policies
Bibliographic record
Abstract
Early consumption of full servings of alcohol and early experience of drunkenness have been linked with alcohol-related harmful effects in adolescence, as well as adult health and social problems. On the basis of secondary analysis of county-level prevalence data, the present study explored the current pattern of drinking and drunkenness among 15- and 16-year-old adolescents in 40 European and North American countries. Data from the 2006 Health Behavior in School Children survey and the European School Survey Project on Alcohol and other Drugs were used. The potential role of alcohol control and policy measures in explaining variance in drinking patterns across countries was also examined. Policy measures and data on adult consumption patterns were taken from the WHO Global Information System on Alcohol and Health, Eurostat and the indicator of alcohol control policy strength developed by Brand DA, Saisana M, Rynn LA et al. [(2007) Comparative analysis of alcohol control policies in 30 countries. PLoS Med 4:e151.]. We found that a non-significant trend existed whereby higher prices and stronger alcohol controls were associated with a lower proportion of weekly drinking but a higher proportion of drunkenness. It is important that future research explores the causal relationships between alcohol policy measures and alcohol consumption patterns to determine whether strict policies do in fact have any beneficial effect on drinking patterns, or rather, lead to rebellion and an increased prevalence of binge drinking.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".