Attitudes and Beliefs Toward Cannabis Before Recreational Legalization: A Cross-Sectional Study of Community Adults in Ontario
Bibliographic record
Abstract
Objectives: To characterize attitudes and perceptions regarding risks and benefits of cannabis before Canadian legalization for recreational use, both in general and between cannabis users and nonusers. Methods: A cross-sectional sample of community adults assessed in the month before legalization (September 17 to October 17, 2018). Overall, 1,480 individuals (60% female) of an average age of 34.5 years (±13.92) were included in the analysis; 48% reported cannabis use in the past 6 months. Attitudes and perceptions were assessed using a subset of items from the Canadian Cannabis Survey, the National Survey on Drug Use and Health, and the Risks and Benefits of Cannabis Use. Results: Most commonly identified risks of cannabis were impaired memory (67%) and legal problems (54%). Most also identified addiction as a risk (52%), although 25% reported that cannabis was not addictive. The most commonly identified benefits were for pain relief (94%) and management of stress, anxiety, or depression (80%). Active cannabis users systematically reported lower endorsement of risks and higher endorsement of benefits. Only 6% of respondents anticipated increasing cannabis use postlegalization. Among other legal substances, medical cannabis was considered the most socially acceptable, followed by alcohol, recreational cannabis, electronic cigarettes, and then combustible cigarettes. Conclusion: Before legalization, attitudes toward cannabis in this sample of Canadian adults were generally favorable, particularly for medical cannabis. Perceptions of risk were often compatible with existing evidence, but notable proportions underendorsed risk of cannabis use disorder and overendorsed benefits for mental health. These results suggest priorities for public health messaging and provide benchmarks for understanding attitudinal changes postlegalization.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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".