Cannabis legalization and hospitalizations in Alberta: Interrupted time series analysis by age and sex
Bibliographic record
Abstract
OBJECTIVES: Recent research has focused on the effects of legalization on cannabis-related emergency department visits, but the considerable healthcare costs of cannabis-related hospitalizations merit attention. We will examine the association between recreational cannabis legalization and cannabis-related hospitalizations. METHODS: A cohort of 3,493,864 adults from Alberta was examined (October 2015-May 2021) over three periods: pre-legalization, post-legalization of flowers and herbs (phase one), and post-legalization of edibles, extracts, and topicals (phase two). Interrupted time series analyses were used to detect changes. RESULTS: The study found an increase in hospitalization rates among younger adults (18-24) before legalization, yet no increased risk was associated with cannabis legalization, for either younger (18-24) or older adults (25+). CONCLUSIONS: Clinicians should be aware of the increased risk in younger groups and may benefit from early identification and intervention strategies, including screening and brief interventions in primary care settings.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".