How much THC is in that joint? A daily diary study of young adults’ knowledge of the cannabinoid content of cannabis products
Bibliographic record
Abstract
OBJECTIVE: Many young adults report frequent cannabis use and are at risk for cannabis harms. Knowledge of the tetrahydrocannabinol (THC) and cannabidiol (CBD) concentrations of cannabis products may promote harm reduction, but few studies have characterized cannabinoid concentration knowledge in this population. This study used day-level data to examine predictors of cannabinoid concentration knowledge and associations of cannabinoid concentration knowledge with substance-related consequences among young adults. METHOD: = 131; mean age = 22.11 years; 64.12% female) from a larger study of cannabis and alcohol co-use completed daily surveys over 21 days assessing knowledge of the cannabinoid concentrations of cannabis used, forms of cannabis used, motives for cannabis use (medicinal, nonmedicinal, both), and substance-related consequences. RESULTS: On average, participants reported at least some knowledge of the THC and CBD concentrations of their cannabis on 48% and 32% of their cannabis use days, respectively. Generalized linear mixed models revealed that participants with a greater propensity to use nonflower (relative to flower) cannabis products and to report medicinal (relative to exclusively nonmedicinal) motives for cannabis use reported greater cannabinoid concentration knowledge overall across days, controlling for sociodemographic factors and level of cannabis involvement. Participants with greater overall cannabinoid concentration knowledge reported positive substance-related consequences more often. In addition, participants were more likely to report negative substance-related consequences on days during which cannabinoid concentrations were known versus unknown. CONCLUSIONS: Findings suggest that cannabinoid concentration knowledge may be higher among young adults who report primarily nonflower and medicinally motivated cannabis use, although cannabinoid concentration knowledge, alone, may not protect against negative substance-related consequences at the day level.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".