Use of Prescription Opioids and Impact of Replacing Oxycontin With Oxyneo On Opioid Use Among Metis Citizens, 2013-2018
Bibliographic record
Abstract
IntroductionCanada has one of the highest rates of prescription opioid consumption globally. Little is known about the prevalence and determinants of opioid use among citizens of the Metis nation – one of three Aboriginal groups recognized by the Canadian constitution. Objectives and ApproachOur objectives were to (i) identify trends in prescription opioid use among Metis citizens from 2006 to 2018 and (ii) identify whether replacing OxyContin with OxyNeo in February 2012 differentially impacted prevalence of opioid use among Metis when compared with all other Manitobans. The Manitoba Metis Federation and the University of Manitoba partnered on this research. We identified prescription opioid use using dispensation records from the province’s drug database, which includes records for all prescription drugs dispensed in community. We defined acute prescription opioid use as ≤28 days prescription and chronic use as ≥ 29 days’ prescription. We tested for differences in annual trends in acute and chronic prescription opioid use between Metis and all other Manitobans. We used an interrupted time series design to test whether replacing OxyContin differentially impacted prevalence of acute and chronic opioid use among Metis when compared with all other Manitobans. We used generalized linear models to test for trends and the impact of replacing OxyContin. ResultsAcross all years (2006-2018) acute prescription and chronic opioid use was higher among Metis than all other Manitobans. Acute and chronic use decreased in both groups, non-differentially. Replacing OxyContin with OxyNeo was associated with decreased acute opioid use in both Metis and all other Manitobans and had a greater impact on chronic opioid use among Metis than among all other Manitobans. Conclusion / Implications: Findings highlight the differential experiences arising from the historic and ongoing colonial project in Canada, which need to be considered when working to prevent and treat inappropriate Opioid use among Metis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".