Patient perspectives of methadone formulation change in British Columbia, Canada: outcomes of a provincial survey
Bibliographic record
Abstract
BACKGROUND: In British Columbia, Canada, methadone maintenance treatment formulation transitioned from the oral liquid compound Tang™-flavoured methadone to the ten-times more concentrated cherry-flavoured Methadose™ in February 2014. We quantitatively describe perceptions and reported consequences among a sample of patients on methadone maintenance treatment following this transition. METHODS: A province-wide survey was used. Bivariable analyses utilized independent samples t-tests, Phi associations, and Chi-square tests. Multivariable logistic regression analyses evaluated factors related to dependent variables - namely, increases in dose, pain, dope sickness, and the need to supplement with additional opioids. RESULTS: Four hundred five methadone maintenance treatment patients from fifty harm reduction sites across British Columbia reported transitioning to Methadose™ in February 2014. The majority (n = 258; 73.1 %) heard about the formulation change from their methadone provider or pharmacist. Adjusted models show worse taste was positively associated with reporting an increasing dose (OR = 2.46; CI:1.31-4.61), feeling more dope sick (OR = 3.39; CI:1.88-6.12), and worsening pain (OR = 4.65; CI:2.45-8.80). Feeling more dope sick was positively associated with dose increase (OR = 2.24; CI:1.37-3.66), and supplementing with opioids (OR = 8.81; CI:5.16-15.05). CONCLUSIONS: Methadone maintenance treatment policy changes in British Columbia affect a structurally vulnerable population who may be less able to cope with transitions and loss of autonomy. There may be a psychosocial component contributing to the perception of Methadose™ tasting worse, and increased dope sickness, pain, and dose. Our study shows the pronounced negative impacts medication changes can have on patients without informed, coordinated efforts. We stress the need to engage all stakeholders allowing for communication about the reasons, risks and consequences of medication policy changes and provision of additional psychosocial support.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".