Brand Preferences of Underage Drinkers Who Report Alcohol-Related Fights and Injuries
Bibliographic record
Abstract
BACKGROUND: A significant body of research has demonstrated an association between adolescent alcohol consumption and subsequent fights and injuries. To date, however, no research has identified which brands are associated with alcohol-related fights and injuries among underage drinkers. OBJECTIVES: We aimed to: (1) report the prevalence of alcohol-related fights and injuries among a national sample of underage drinkers in the U.S. and (2) describe the relationship between specific alcohol brand consumption and these alcohol-related negative consequences. METHODS: We recruited 1,031 self-reported drinkers (ages 13-20 years) via an internet panel maintained by Knowledge Networks to complete an online survey. Respondents reported their past-month overall and brand-specific alcohol consumption, risky drinking behavior, and past-year alcohol-related fights and injuries. RESULTS: Over one-quarter of the respondents (26.7%, N = 232) reported at least one alcohol-related fight or injury in the past year. Heavy episodic drinkers were over six times more likely to report one of these negative alcohol-related consequences (AOR: 6.4, 95% CI: 4.1-9.9). Respondents of black race and those from higher-income households were also significantly more likely to report that experience (AOR: 2.2, 95% CI: 1.3-3.7; AOR: 1.8, 95% CI: 1.1-3.0 and 1.1-3.2, respectively). We identified eight alcohol brands that were significantly associated with alcohol-related fights and injuries. CONCLUSIONS/IMPORTANCE: Alcohol-related fights and injuries were frequently reported by adolescent respondents. Eight alcohol brands were significantly more popular among drinkers who experienced these adverse consequences. These results point to the need for further research on brand-specific correlates of underage drinking and negative health outcomes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".