Seeking prescription opioids from physicians for nonmedical use among people who inject drugs in a Canadian setting
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Despite the high prevalence of prescription opioid (PO) misuse, little is known about the phenomenon of seeking POs for nonmedical use among high-risk populations, such as people who inject drugs (PWID). We therefore sought to examine the prevalence and correlates of seeking POs from a physician for nonmedical use among PWID in Vancouver, Canada. METHODS: Cross-sectional data from two open prospective cohort studies of PWID in Vancouver were collected between June 2013 and May 2014 (n = 1252). Multivariable logistic regression was used to identify factors associated with seeking POs from physicians for nonmedical use. RESULTS: Of 1252 participants, 458 individuals (36.6%) reported ever trying to get a PO prescription from a physician for nonmedical use and, of these, 343 (74.9%, comprising 27.4% of the total sample) reported ever being successful. Variables independently and positively associated with PO-seeking behavior included older age (adjusted odds ratio [AOR] = 1.02), Caucasian ethnicity (AOR = 1.38), having ever overdosed (AOR = 1.32), having ever participated in methadone maintenance therapy (AOR = 1.90), having ever dealt drugs (AOR = 1.65), and having ever been refused a prescription for pain medication (AOR = 2.02) (all p < .05). DISCUSSION AND CONCLUSIONS: We observed that PO-seeking behavior was common among this sample of PWID and associated with several markers of higher intensity drug use. SCIENTIFIC SIGNIFICANCE: Our findings highlight the need to identify evidence-based public health and clinical strategies to mitigate PO misuse among PWID without compromising care for PWID with legitimate medical concerns. (Am J Addict 2016;25:275-282).
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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 it