Elevated Behavioral Economic Demand for Alcohol in Co-Users of Alcohol and Cannabis
Bibliographic record
Abstract
OBJECTIVE: Co-use of cannabis and alcohol is associated with increased drinking and other negative consequences relative to use of alcohol alone. One potential explanation for these differences is overvaluation of alcohol (e.g., alcohol demand) among co-users, similar to established overvaluation of alcohol among tobacco and alcohol co-users. This study examined differences in alcohol demand between an alcohol and cannabis co-user group and an alcohol-only group. METHOD: A large sample of adult drinkers (n = 1,643, 54% female) was recruited through an online crowdsourcing site (Amazon Mechanical Turk). Of the full sample, 476 participants reported weekly or greater cannabis use in the past 6 months (co-user group); 888 reported never using cannabis in the past 6 months (alcohol-only group). Assessments included a validated alcohol purchase task and self-report measures of alcohol and cannabis use. RESULTS: Co-users reported significantly higher alcohol consumption across the elastic portion of the alcohol demand curve (i.e., $1.50-$9.00/drink). Analyses of covariance controlling for alcohol use and demographics revealed significantly higher breakpoint (p = .025) and Omax (p = .002) and significantly lower elasticity (p < .003) in the co-user group. Intensity and Pmax did not significantly differ between groups. CONCLUSIONS: Co-users of cannabis and alcohol overvalue alcohol compared with individuals who drink alcohol but do not use cannabis. This study is generally consistent with prior studies on alcohol and tobacco co-users, providing converging evidence that polysubstance use is associated with overvaluation of alcohol. These findings have important implications for treatment and prevention, particularly in the context of changes in cannabis legalization.
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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 | 0.001 |
| 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".