Changes in daily dose in open-label compared to double-blind: The role of clients’ expectations in injectable opioid agonist treatment
Bibliographic record
Abstract
Introduction: Though double-blind studies have indicated that hydromorphone and diacetylmorphine produce similar effects when administered through injectable opioid agonist treatment (iOAT) programs, participant preference may influence some aspects of medication dispensation such as dose. Methods: This is a retrospective longitudinal analysis. Participants (n = 131) were previously enrolled in a double-blind clinical trial for iOAT who continued to receive treatment in an open-label follow up study. Data included medication dispensation records from 2012 to 2020. Using linear regression and paired t-tests, average daily dose totals of hydromorphone and diacetylmorphine were examined comparatively between double-blind and open-label periods. A subgroup analysis explored dose difference by preference using the proxy, blinding guess, a variable used to facilitate the measurement of treatment masking during the clinical trial by asking which medication the participant thought they received. Results: During the open-label period, participants prescribed diacetylmorphine received 49.5 mg less than during the double-blind period (95% CI -12.6,-86.4). Participants receiving hydromorphone did not see a significant dose decrease. Participants who guessed they received hydromorphone during the clinical trial, but learned they were on diacetylmorphine during the open-label period, saw a decrease in total daily dose of 78.3 mg less (95% CI -134.3,-22.4) during the open-label period. Conclusion: If client preference is considered in the treatment of chronic opioid use disorder, clients may be able to better moderate their dose to suit their individual needs. Together with their healthcare providers, clients can participate in their treatment trajectories collaboratively to optimize client outcomes and promote person-centered treatment options.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".