Predrinking, alcohol use, and breath alcohol concentration: A study of young adult bargoers.
Bibliographic record
Abstract
Predrinking (preloading, pregaming) has been found to be related to alcohol use and intoxication. However, most research relies on estimates of blood alcohol concentration and does not control for usual drinking pattern. We assessed whether predrinking was associated with subsequent alcohol consumption and breath alcohol concentration (BrAC) among 287 young adult bargoers (173 men [60.3%], Mage = 21.86 years, SD = 2.55 years) who were recruited in groups in an entertainment district of a midsized city in Ontario, Canada. We also examined whether predrinking by other group members interacted with individual predrinking in relation to amount consumed/BrAC. Adjusting for nesting of individuals within groups in hierarchical linear models, predrinkers were found to consume more drinks in the bar district and over the entire night compared to nonpredrinkers and had higher BrACs at the end of the night controlling for drinking pattern. A group- by individual-level interaction revealed that individual predrinking predicted higher BrACs for members of groups in which at least half of the group had been predrinking but not for members of groups in which less than half had been predrinking. This study confirms a direct link of predrinking with greater alcohol consumption and higher intoxication levels. Group- by individual-level effects suggest that group dynamics may have an important impact on individual drinking. Given that predrinking is associated with heavier consumption rather than reduced consumption at the bar, initiatives to address predrinking should include more effective policies to prevent intoxicated people from entering bars and being served once admitted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".