The impacts of alcohol marketing and advertising, and the alcohol industry's views on marketing regulations: Systematic reviews of systematic reviews
Bibliographic record
Abstract
ISSUES: Advertising and marketing affect alcohol use; however, no single systematic review has covered all aspects of how they affect alcohol use, and how the alcohol industry views alcohol marketing restrictions. APPROACH: Two systematic reviews of reviews were performed according to the Preferred Reporting Items on 2 February 2023. Results were analysed using a narrative synthesis approach. KEY FINDINGS: Twenty-three reviews were included in the systematic reviews. The first systematic review examined youth and adolescents (11 reviews), digital or internet marketing (3 reviews), alcohol marketing's impact on cognition (3 reviews), and alcohol marketing and policy options (2 reviews). The second systematic review focused on alcohol industry (i.e., importers, producers, distributors, retailers and advertising firms) response to advertising restrictions (four reviews). The reviews indicated that there is evidence that alcohol marketing (including digital marketing) is associated with increased intentions to drink, levels of consumption and harmful drinking among youth and young adults. Studies on cognition indicate that advertisements focusing on appealing contexts and outcomes may be more readily accepted by adolescents, and may be less easily extinguished in this population. The review of the alcohol industry found a strong desire to self-regulate alcohol advertising. IMPLICATIONS: We found alcohol advertising and marketing is associated with increased drinking intentions, consumption and harmful drinking. Thus, policies which restrict advertising may be an effective way to reduce alcohol use. CONCLUSION: More research is needed to assess all aspects of the observed associations, especially as to how marketing policies impact women and people with alcohol dependence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".