Prevalence of and Sociodemographic Factors Associated with Prescription Opioid Misuse among Canadian Adults
Bibliographic record
Abstract
ABSTRACT Objectives: There remains a lack of research on prescription opioid misuse in Canada, and definitions of misuse vary across studies. Consequently, more research is needed on the prevalence of and sociodemographic factors associated with prescription opioid misuse. Methods: The current study examines the prevalence of and sociodemographic factors associated with prescription opioid misuse among Canadian adults aged 25 and older using the 2019 Canadian Alcohol and Drug Survey and logistic regression. Results: The findings showed that 1.9% of Canadian adults reported past-year prescription opioid misuse. Logistic regression analyses found that residents of provinces in the Prairies had significantly higher odds of misuse compared with persons living in Central Canadian provinces. Unpartnered and currently employed individuals were significantly more likely to report misuse compared with their counterparts. Persons with household incomes between $20k and $39,999k were significantly less likely to report misuse compared with those in the poorest household income category of <$20k. Conclusions: Additional research is needed to further identify the prevalence and sociodemographic characteristics associated with prescription opioid misuse in Canada. Objectifs: La recherche sur l’usage abusif des opioïdes de prescription au Canada demeure insuffisante et les définitions d’usage abusif varient d'une étude à l'autre. Par conséquent, il est nécessaire d'effectuer davantage de recherches sur la prévalence et les facteurs sociodémographiques associés à l’usage abusive des opioïdes d'ordonnance. Méthodes: La présente étude examine la prévalence et les facteurs sociodémographiques associés à l’usage abusif d'opioïdes sur ordonnance chez les adultes canadiens âgés de 25 ans et plus à l'aide de l'Enquête Canadienne sur l'alcool et les drogues de 2019 et d'une régression logistique. Résultats: Les résultats montrent que 1,9 % des adultes canadiens ont déclaré avoir fait un usage abusif d'opioïdes sur ordonnance au cours de l'année écoulée. Les analyses de régression logistique ont révélé que les résidents des provinces des Prairies avaient des probabilités significativement plus élevées de faire un usage abusif que les personnes vivant dans les provinces du centre du Canada. Les personnes sans partenaire et celles qui ont un emploi étaient significativement plus susceptibles de déclarer un usage abusif que leurs homologues. Les personnes dont le revenu du ménage se situe entre 20 000$ et 39 999$ étaient nettement moins susceptibles de déclarer un usage abusif que celles dont le revenu du ménage était inférieur à 20 000$, la catégorie la plus pauvre. Conclusion: Des recherches supplémentaires sont nécessaires pour mieux identifier la prévalence et les caractéristiques socio-démographiques associées à l’usage abusif des opioïdes de prescription au Canada.
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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 | 0.000 | 0.000 |
| 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".