Do public expenditures on health and families relate to alcohol abstaining in adolescents? Multilevel study of adolescents in 24 countries
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Several European countries have observed an increase in the proportion of adolescents that abstain from drinking alcohol in the last decade. The reasons for this trend remain underexplored. We hypothesised that more generous government expenditures on health services and benefits to families with children relate to a positive trend in abstainers. DESIGN AND METHODS: We used data on 15-year-olds in four successive cycles of the World Health Organization Health Behaviour in School-aged Children study (2002 to 2014) in 24 North American and European countries (pooled n = 175 331). Generalised linear mixed-effects models were tested to analyse trends in alcohol abstinence and to investigate whether cross-country differences in these trends relate to public expenditures on health and families with children (in proportion to gross domestic product). RESULTS: Overall, we observed an increase in the proportion of abstainers from 21% in 2002 to 35% in 2014. An exception was Greece where abstaining had decreased from 20% to 15%. Similar results were found in boys and girls. The upward trend in abstinence related to larger government expenditures on health and families. DISCUSSIONS AND CONCLUSIONS: More generous expenditures on health services and family benefits relate to more adolescents abstaining from alcohol.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".