Perceptions of Community-Dwelling Patients and Their Physicians on OxyContin® Discontinuation and the Impact on Chronic Pain Management
Bibliographic record
Abstract
OxyContin, formerly one of the most commonly prescribed medications for chronic pain in Canada, was discontinued, delisted from the Ontario Drug Formulary, and replaced by a tamper-resistant formulation in 2012. The impact of discontinuing OxyContin on patients formerly prescribed it to treat chronic pain was unreported. Patients with chronic pain aged 45 years and over ( n=13 ) were recruited from two primary care and one specialty practice sites and interviewed using a semistructured guide to capture their experiences with discontinuing OxyContin, the efficacy of alternate medications, and relationships with physicians. Additional interviews were conducted with their physicians ( n=7 ) to obtain physician perceptions on discontinuation and to expand understanding of the patients’ experiences. Aspects of patients’ pain and medical care through the discontinuation process revealed emergent themes that both converge and diverge from that of treating physicians. Areas of divergence include the motive for discontinuation, which was condemned by most patients but supported by all physicians, and the perceived impact of discontinuance on pain control, with the majority of patients experiencing a negative impact and most physicians describing it as insignificant. Perceptions of patients and physicians coincided on the need to optimize pain management practices.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".