Between- and Within-Person Correlates of Alcohol-Impaired Driving in First-Year University Students: The Roles of Impulsivity, Binge Drinking, Depression, and Anxiety
Bibliographic record
Abstract
OBJECTIVE: University students are a high-risk demographic for alcohol-impaired driving (AID), a leading contributor to death and injury on Canadian roads. Although between-person correlates of AID are well established, little research has identified within-person correlates that elucidate when AID occurs. Accordingly, this study investigated whether between- and within-person variability in impulsivity, binge drinking, depression, and anxiety are associated with AID in university students. METHOD: = 0.76]) from a Canadian university who completed seven monthly surveys. Multilevel models disaggregated between- and within-person associations. RESULTS: Between-person elevations in negative and positive urgency, sensation seeking, lack of premeditation, binge drinking, and depression were associated with greater odds of AID. Within-person elevations in negative urgency, sensation seeking, and binge drinking were associated with greater odds of AID, whereas within-person elevations in depression were associated with lower odds of AID. CONCLUSIONS: These results support existing research regarding who is most likely to engage in AID (students with elevated impulsivity, binge drinking, and depression) and extend this research by identifying under what conditions AID is likeliest to occur (when impulsivity and binge drinking are higher than usual, and depression is lower than usual). The opposing between- and within-person associations of depression with AID highlight the need for careful specification of hypotheses, as findings at the between-person level may not generalize to the within-person level. Moving forward, research that elucidates not only for whom but also when AID occurs may be best positioned to inform intervention and prevention efforts among university students.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".