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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".