Leveraging policy to reduce chronic opioid use by educating and empowering community dwelling adults: a study protocol for the TAPERING randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Opioid use has risen to epidemic proportions across Canada, with increasing evidence of harms including accidental overdose and death. Policy-makers have called for effective approaches to promote opioid reduction. One promising method from deprescribing randomized trials is to empower patients through direct-to-patient education. The current trial will evaluate the effectiveness of a government-led mail-out of educational information to adult community-dwelling, chronic opioid users on the reduction of opioids compared to usual care. METHODS: This is a pragmatic, prospective, cluster randomized, parallel-arm controlled trial, comparing mailed distribution of a direct-to-patient educational brochure for chronic opioid use (intervention arm) to usual care (control arm). Eligible participants from across Manitoba, Canada, will be identified by the Provincial Drug Programs Branch within the Manitoba Health, Seniors and Active Living Department of the Manitoba Government, allocated to primary care providers, and the latter will be randomized in clusters of family medicine practices to achieve a 1:1 ratio. The primary outcome is complete cessation of opioids after 6 months assessed using Drug Program Information Network data. Secondary outcomes include ≥ 25% dose reduction in the mean morphine milligram equivalent (MME) daily dose, reduction of daily dose to < 90 mg MME, or therapeutic switch to another opioid or non-opioid medication. Data will be analyzed using intent-to-treat generalized estimating equations. DISCUSSION: This trial will test the efficacy of a population-based, wide-scale, government-led direct-to-patient educational initiative to drive reductions in chronic opioid use by community-dwelling adults across Manitoba. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT03400384 . Registered on 18 January 2018.
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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 | 0.080 | 0.071 |
| Meta-epidemiology (narrow) | 0.009 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.008 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.083 | 0.016 |
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".