A Description of the Medical Cannabis Use in Ontario, Canada
Bibliographic record
Abstract
Abstract Objectives: Despite the approval of medical cannabis in Canada, there remains a significant knowledge gap for physicians to provide informed health care to these patients. Thus, we provide relevant demographic, economic, and clinical data from one of the largest known databases of patients seeking cannabis as a medical therapy. Materials and Method(s): Self-reported outcomes were collected from 10,269 adults authorized for cannabis in Ontario, Canada. Sociodemographics, primary complaints, and several validated questionnaires, including the Generalized Anxiety Disorder 7-item (GAD-7) scale, the Patient Health Questionnaire (PHQ-9), and the CAGE Questionnaire Adapted to Include Drugs (CAGE-AID), were collected. All data are expressed descriptively using means (standard deviations) or proportions as appropriate. Results: 54.3% of patients seeking cannabis were male with a mean age of 51.2±14.6 years. Of these, 46.1% were above the mean income of the province of Ontario. The majority of patients (66.0%) sought medical cannabis for chronic general or musculoskeletal pain. Consistent with chronic pain being associated with a higher incidence of anxiety and depression, 50.7% of the patients completing the GAD-7 questionnaire ( n =6783) were categorized as having moderate to severe anxiety while 32.6% of those patients completing the PHQ-9 questionnaire ( n =7150) had moderate to severe depression. Few patients reported a history of cocaine use, while 17% indicated previous opioid use and 16.4% had a positive response to the CAGE-AID. Conclusion: Our findings show that medical cannabis is largely sought by a population who has a high incidence of chronic pain as well as comorbid anxiety and depression.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".