Assessing the Prevalence of Nonmedical Prescription Opioid Use in the General Canadian Population: Methodological Issues and Questions
Bibliographic record
Abstract
OBJECTIVE: To assess the prevalence of nonmedical prescription opioid use (NMPOU) in the Canadian general adult population in the context of rising overall prescription opioid (PO) consumption and related problems in North America. METHOD: The prevalence of NMPOU was assessed as a multiitem construct in the Canadian Alcohol and Drug Use Monitoring Survey (CADUMS; n = 16 672), an ongoing cross-sectional monthly random digit dialing telephone survey representative of the general Canadian population, aged 15 years and older. CADUMS data were collected between April and December of 2008 with a response rate of 43.5%. RESULTS: About 22% of CADUMS respondents reported PO use in the last year, while 0.5% reported NMPOU during the same time frame. PO use was significantly higher among women than among men, and highest in the group aged 25 to 54 years. NMPOU was similar among men and women, and highest in the group aged 15 to 24 years. CONCLUSIONS: CADUMS data indicate an extremely low rate of NMPOU, especially given the levels of overall PO use, other PO-use related problems, and NMPOU levels estimated in the general US population where NMPOU has been assessed to be 10 times higher than in Canada. NMPOU survey item construction and response rates appear to strongly influence and potentially compromise NMPOU survey data. Existing NMPOU data and survey methods need to be validated for this important indicator in Canada, where increasing PO use and problem levels have been recognized as a significant and rising public health problem.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".