Assessing the impact of Lithuania’s 2018 alcohol marketing ban on adolescent alcohol use by comparing trends with five EU control countries: a study protocol for a secondary data analysis
Bibliographic record
Abstract
INTRODUCTION: Alcohol consumption poses a significant health risk, contributing to 10% of deaths in the WHO European Region. To combat this, the WHO recommends the implementation of its 'best buy' policies-three cost-effective alcohol policies that include higher taxes, restricted availability and marketing bans. While evidence links alcohol marketing to increased consumption, the effectiveness of marketing bans in decreasing alcohol use remains inconclusive. Lithuania's 2018 comprehensive alcohol marketing ban offers a unique opportunity to measure the impact of this particular 'best buy' control policy. METHODS AND ANALYSIS: We will analyse repeated cross-sectional measures of alcohol use among 15-year-old and 16-year-old adolescents from Lithuania and other five European Union countries (Estonia, France, Italy, Latvia and Poland). Data from the European School Survey Project on Alcohol and Other Drugs collected between 2003 and 2019 will be used, as well as longitudinal alcohol policy data meticulously gathered through official records, supplemented by relevant literature and consultations with national authorities. Although all six countries introduced best buy alcohol policies-primarily via excise tax increases implemented at different times-only Lithuania implemented a full marketing ban. Generalised linear mixed models will be employed to assess the impact of national alcohol marketing restrictions on alcohol consumption, controlling for participant characteristics, social behaviours and country-level variables such as other alcohol control policies evaluated through a partial Bridging the Gap (BtG) scale. Sensitivity analyses will explore different outcome time periods and model specifications. ETHICS AND DISSEMINATION: The Research Ethics Board of the primary recipient of the grant has approved the secondary data analyses as outlined in the grant proposal (CAMH REB 050/2020 delegated review, renewed annually). The study results will be published in a peer-reviewed journal, presented at conferences, and shared with policymakers.
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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 | 0.032 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.008 |
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".