Does Unit-Dose Packaging Influence Understanding of Serving Size Information for Cannabis Edibles?
Bibliographic record
Abstract
OBJECTIVE: Edible cannabis products have increased in popularity, particularly in jurisdictions that have legalized nonmedical cannabis. Rates of adverse events from cannabis edibles have also increased, in part because of difficulties identifying and titrating tetrahydrocannabinol (THC) levels. The current study tested whether packaging cannabis in separate units enhances consumer understanding of serving sizes. METHOD: An experimental task was conducted as part of the 2018 International Cannabis Policy Study online survey. Participants were recruited from the Nielsen Global Insights Consumer Panel. A total of 26,894 participants (61.5% female) ages 16-65 years from Canada and the United States were randomly assigned to view a cannabis brownie packaged according to one of three conditions: (a) multiserving edible ("control condition"), (b) single-serving edible, and (c) single-serving edible packaged separately ("unit-dose packaging"). Participants were asked to identify a standard serving based on information on the product label. Logistic regression was used to test the influence of packaging condition on the likelihood of a correct response, adjusting for key covariates. RESULTS: Compared with the multiserving edible control (50.6%), participants were significantly more likely to correctly identify the serving size in the single-serving edible condition (55.3%; adjusted odds ratio = 1.22, CI [1.15, 1.29], p < .001) and the unit-dose packaging condition (54.3%; adjusted odds ratio = 1.17, CI [1.10, 1.24], p < .001). CONCLUSIONS: Packaging in which each product unit contained one dose of THC enhanced consumers' ability to identify how much of a product constitutes a standard serving or dose. Packaging products as individual doses eliminates the need for mental math and could reduce the risk of accidental overconsumption of cannabis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| 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".