Is there a ‘low‐risk’ drinking level for youth? The risk of acute harm as a function of quantity and frequency of drinking
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Drinking guidelines have rarely provided recommendations for different age groups despite evidence of significant age effects on alcohol consumption and related risks. This study attempted to quantify the degree of risk associated with lower levels of consumption for people under 25 years of age, with the broader purpose of informing the development of Canadian low-risk drinking guidelines. DESIGN AND METHODS: A random community-based sample of 540 youth aged 16-23 (54.4% female) completed an interview concerning alcohol consumption patterns and a broad range of acute health and social harms. Logistic regression analyses were designed to test whether there were discernible thresholds of risk as a function of both gender and age. RESULTS: A significant proportion of young people consumed in excess of adult drinking limits recommended by the Centre for Addiction and Mental Health (CAMH) to minimise risk of alcohol-related harm. Compared with abstainers, rates of reported harm increased linearly with increasing frequency and quantity levels. However, problems were most strongly associated with consumption in excess of two drinks per occasion and a frequency of more than once a week. No independent effects of age or gender were identified. DISCUSSION AND CONCLUSIONS: The CAMH guidelines for adult drinkers do not adequately address acute risks for young people. More specific guideline recommendations for young people could be considered with a more prominent focus on drinking quantity (one to two drinks per occasion), and a recommended frequency of consumption (once a week).
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".