Young adult concurrent use and simultaneous use of alcohol and marijuana: A cross-national examination among college students in seven countries
Bibliographic record
Abstract
INTRODUCTION: Many young adults report frequent co-use of alcohol and marijuana, with some individuals engaging in simultaneous use (SAM; use of both substances within the same occasion resulting in an overlap of their effects) and others in concurrent use (CAM; use of both substances during a similar time period [e.g., past 30 days] but not within the same occasion). Emerging work demonstrates that SAM relative to CAM use places individuals at a greater risk for substance-related harms; however, these results primarily rely on U.S. samples. The goal of the present multi-country study was to examine prevalence rates of CAM and SAM use and examine differences in past 30-day SAM/CAM use on alcohol/marijuana substance-related outcomes among college students from seven countries. METHODS: = 3.96) college students participated in the cross-sectional online survey study. RESULTS: Among students who endorsed use of both alcohol and marijuana in the past 30-days (n = 2124), SAM use (75.8%) was far more prevalent than CAM use (24.2%). Moreover, ∼75% of students endorsed SAM use within each country subsample. Regression models showed that SAM vs. CAM use was associated with greater alcohol and marijuana use and negative consequences. CONCLUSIONS: College students from around the world endorse high rates of SAM use, and this pattern of co-use is associated with greater frequency of use and substance-related harms. On college campuses, SAM use should be a target of clinical prevention/intervention efforts and the mechanisms underpinning the unique harms of SAM need to be clarified.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".