Driving under the influence behaviours among high school students who mix alcohol with energy drinks
Bibliographic record
Abstract
Alcohol and energy drinks are commonly used substances by youth in Canada, and are often mixed (AmED). While several studies have shown that AmED can have dangerous effects, less well understood is how AmED is associated with driving under the influence of either alcohol or drugs. This study sought to determine whether youth who use AmED were more likely to engage in driving, or being a passenger of a driver, under the influence of alcohol or cannabis compared to youth who use either alcohol or energy drinks alone. This study used data from grade 10-12 students who took part in the 2014/2015 Canadian Student Tobacco, Alcohol and Drugs Survey (N=17,450). The association of past-year AmED use with past-30day: driving under the influence of alcohol or cannabis, and riding with an alcohol- or cannabis-influenced driver, was assessed using logistic regression. One in four youth had consumed AmED in the previous 12months. AmED users were more likely to engage in all risk behaviours except riding with a drinking driver, relative to youth who only consumed alcohol. No association was observed for youth who consumed alcohol and energy drinks on separate occasions. Youth who use AmED demonstrate a higher risk profile for driving under the influence of alcohol or cannabis, than youth who use alcohol alone. Future research should explore the biopsychosocial pathways that may explain why using energy drinks enhances the already heightened risk posed by alcohol on other health-related behaviours such as driving under the influence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; a candidate call from one teacher head, 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".