Daily Order of Alcohol and Cannabis Use Predicts Drinking Quantity on Simultaneous Use Days, but Substance Use Motives do not Moderate
Bibliographic record
Abstract
The present study examined whether using alcohol versus cannabis first when simultaneously using predicts levels of alcohol consumption on a given day, while focusing on daily levels of coping and enhancement motives for simultaneous alcohol and cannabis (SAM) use.Undergraduate student drinkers (n=370) participated in a 14weekend diary study in Fall 2021, completing surveys on Friday, Saturday, and Sunday mornings (n=2,826 responses) assessing their SAM use, alcohol consumption, and motives for SAM use the previous day.Findings from multilevel models showed that students consumed a greater number of drinks on SAM use days than alcohol-only.Students reported consuming less alcohol on SAM use days when they used cannabis versus alcohol first, and no moderating effects of daily coping or enhancement motives were found.Results suggest that college and university students may not drink heavily on all SAM use days, and students may strategically use cannabis first to reduce their drinking.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".