Attitudes and Experiences of Probuphine Treatment: A Qualitative Interview Study
Bibliographic record
Abstract
Canada is in the midst of an opioid crisis. Medical treatment of opioid dependence decreases illicit opioid use at a greater rate compared with psychosocial intervention or placebo alone, and reduces associated morbidity and mortality. An implantable formulation of buprenorphine with a 6-month duration of action (brand name: Probuphine was approved by the FDA in 2016 and Health Canada in 2018 for long-term maintenance treatment of opioid use disorder. While taper from medical treatment of opioid dependence is generally not advised due to increased likelihood of relapse, British Colombia Center for Substance Use guidelines suggest “for individuals with a successful and sustained response to agonist treatment desiring medication cessation, consider slow taper (e.g., 12 months).” Given the long duration of action, Probuphine may represent an effective tool for opioid taper. No current studies exist to advise on the use of Probuphine for opioid taper. Using semi structured interviews, the purpose of this study is to assess the experience of patients of a London, Ontario-based practice who have received the Probuphine implant for management of opioid dependence. The team will also observe characteristics of patients who had positive tapering experiences and patients who had negative tapering experiences.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".