Knowledge of Tetrahydrocannabinol and Cannabidiol Levels Among Cannabis Consumers in the United States and Canada
Bibliographic record
Abstract
Objective: This study aimed to examine consumer knowledge of tetrahydrocannabinol (THC) and cannabidiol (CBD) levels for usual cannabis products. Methods: Data are from the International Cannabis Policy Study conducted online in August–September 2018. Respondents included 6471 past 12-month cannabis users, aged 16–65 years, recruited from the Nielsen Global Insights Consumer Panel using nonprobability methods. Respondents were recruited from Canada, which had not yet legalized nonmedical cannabis ( n =2354), and US states that had ( n =2160) and had not ( n =1957) legalized nonmedical cannabis. Results: Participants reported descriptive THC:CBD ratios (e.g., high THC, low CBD) and numeric THC and CBD levels (mg or %) for products they usually use in each of nine product categories. Few consumers knew and were able to report the numeric THC or CBD levels of their usual cannabis products. For example, only 10% of dried herb consumers reported the THC level, approximately 30% of whom reported implausible values. A greater proportion of consumers reported a descriptive THC:CBD ratio of their usual product, ranging from 50.9% of edible users to 78.2% of orally ingested oil users. Consumers were substantially more likely to report products high in THC versus low in THC for all products except topicals and tinctures, whereas similar proportions reported using products high and low in CBD. Despite some evidence of greater knowledge in legal jurisdictions, knowledge was still low in states with legal cannabis markets. Conclusions: Consumer knowledge of THC and CBD levels was low, with only modest differences between consumers living in jurisdictions that had and had not legalized nonmedical cannabis. The findings cast doubt on the validity of self-reported cannabinoid levels.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".