Generalized Anxiety Disorder 7-Item (GAD-7) Scores in Medically Authorized Cannabis Patients—Ontario and Alberta, Canada
Bibliographic record
Abstract
ObjectivesDespite increasing rates of legalization of medical cannabis worldwide, the current evidence available on its effect on mental health outcomes including anxiety is of mixed results. This study assesses the effect of medical cannabis on generalized anxiety disorder 7-item (GAD-7) scores in adult patients between 2014 and 2019 in Ontario and Alberta, Canada.MethodsAn observational cohort study of adults authorized to use medical cannabis. The GAD-7 was administered at the time of the first visit to the clinic and subsequently over the follow-up time period of up to 3.2 years. Overall changes in GAD-7 scores were computed (mean change) and categorized as: no change (<1 point); improvement; or worsening—over time.ResultsA total of 37,303 patients had initial GAD-7 scores recorded and 5,075 (13.6%) patients had subsequent GAD-7 follow-up scores. The average age was 54.2 years (SD 15.7 years), 46.0% were male, and 45.6% noted anxiety symptoms at the baseline. Average GAD-7 scores were 9.11 (SD 6.6) at the baseline and after an average of 282 days of follow-up (SD 264) the average final GAD-7 score recorded was 9.04 (SD 6.6): mean change −0.23 (95% CI, −0.28 to −0.17, t[5,074]: −8.19, p-value <0.001). A total of 4,607 patients (90.8%) had no change in GAD-7 score from their initial to final follow-up, 188 (3.7%) had a clinically significant decrease, and 64 (1.3%) noted a clinically significant increase in their GAD-7 scores.ConclusionsOverall, there was a statistically significant decrease in GAD-7 scores over time (in particular, in the 6–12-month period). However, this change did not meet the threshold to be considered clinically significant. Thus, we did not detect clinical improvements or detriment in GAD-7 scores in medically authorized cannabis patients. However, future well-controlled clinical trials are needed to fully examine risks or benefits associated with using medical cannabis to treat anxiety conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".