Safer opioid supply clients’ values and preferences: a systematic review and thematic synthesis of qualitative research
Bibliographic record
Abstract
QUESTION: What are the values and preferences of safer opioid supply clients? STUDY SELECTION AND ANALYSIS: We conducted a systematic review of qualitative studies on safer opioid supply client experiences published between January 2016 and August 2024. Searches were conducted across seven databases-MEDLINE, Embase, PsycINFO, CINAHL, EBM Reviews, Web of Science and Scopus-and supplemented with searches in Google Scholar and relevant repositories. Study quality was assessed using the Critical Appraisal Skills Programme. Data analysis was guided by Thomas and Harden's thematic synthesis approach and confidence in review findings was evaluated using Grading of Recommendations Assessment, Development and Evaluation-Confidence in the Evidence from Reviews of Qualitative research. The review was registered with PROSPERO (CRD42022384447). FINDINGS: Our thematic synthesis included 19 peer-reviewed original research articles involving 459 study participants from British Columbia and Ontario, of whom 60.1% were men and 36.1% were women. Our findings centred on four cross-cutting analytic themes: (1) client-relevant goals and outcomes (withdrawal management, pain management, socioeconomic improvements), (2) the right medications to optimise client-relevant outcomes (multiple medication and formulation options, flexible dosage), (3) supportive, client-centred care environment (safe, welcoming and non-judgmental spaces, coordinating access to health and social support services, shared decision-making) and (4) complex adaptive systems approach to clinical policies (understanding the complexity of clients' living circumstances, flexible dose schedules, non-punitive policies). Confidence in findings ranged from moderate to high. CONCLUSIONS: Safer opioid supply's success depends on providing individualised opioid medications, fostering person-centred care and implementing adaptive clinical policies. A supportive and flexible model enhances client satisfaction, sustains programme participation and optimises client-relevant outcomes.
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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 | 0.138 | 0.176 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".