The Inclusion of Patients’ Reported Outcomes to Inform Treatment Effectiveness Measures in Opioid Use Disorder. A Systematic Review
Bibliographic record
Abstract
Introduction: Patient centred care is needed now more than ever in the treatment of opioid use disorder. Trials, policy makers, and service providers have most often used treatment retention and opioid urine screens as measures of treatment effectiveness. However, patients receiving medication for opioid use disorder treatment (MOUD) may prioritise the use of different ways to assess treatment success. Objective: The aim of this review is to synthesize literature examining the self-reported goals patients would like to achieve in MOUD for opioid use disorder. Methods: We searched MEDLINE, EMBASE, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Web of Science, Cochrane Library, Cochrane Clinical Trials Registry, the National Institutes for Health Clinical Trials Registry, and the WHO International Clinical Trials Registry Platform from inception until April 30th, 2021. No restrictions were placed on language, age, or type of MOUD. A qualitative synthesis is presented given that a meta-analysis was not possible. Results: The search yielded a total of 21,082 records from which 8 met criteria for inclusion in the qualitative synthesis. We identified a total of 43 patient-reported treatment goals from the 8 studies. Twelve domains were created from the 43 goals reported. These domains cover a range of important areas for patients' goals related to living a normal life, physical health, mental health, treatment, and substance use specific areas. Conclusion: This review highlights several patient goals that they would like to achieve during treatment for opioid use disorder that are not commonly considered as markers of treatment effectiveness. Goals related to health, living a normal life, and overall substance use concerns by patients should be taken into consideration by clinical trialists, researchers, policy makers, service providers, patients, and communities engaged in developing and tailoring treatment plans for opioid use disorder. Systematic Review Registration: PROSPERO CRD42018095553.
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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 | 0.062 | 0.211 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".