Evaluating comparative effectiveness of psychosocial interventions for persons receiving opioid agonist therapy for opioid use disorder: protocol for a systematic review
Bibliographic record
Abstract
INTRODUCTION: The opioid crisis has resulted in increasing rates of death caused by problematic opioid use. Current clinical guidelines recommend that individuals with persons with opioid use disorder (OUD) receive pharmacological (eg, opioid agonist therapy) and psychosocial (eg, cognitive behavioural therapy) therapy; however, the best combination of pharmacologic and psychosocial components is not known. Our objective of the planned study is to conduct a comprehensive systematic review to assess the relative benefits of psychosocial interventions as an adjunct to opioid agonist therapy among persons with OUD. METHODS AND ANALYSIS: A comprehensive search for randomised controlled trials published in English or French will be conducted from database inception to March 2018. The search will be conducted in MEDLINE and translated for Embase, PsycINFO and the Cochrane Central Register of Controlled Trials. Two independent reviewers will screen, extract and assess risk of bias of eligible articles. Primary outcomes of interest will be treatment retention and opioid use (based on urinalysis results). Secondary outcomes will include self-reported opioid use, abstinence from illicit drugs, adherence to psychosocial therapy and opioid agonist therapy, risk for sexually transmitted disease, risk for blood borne pathogens, changes in mental health symptoms (eg, depression), measures of craving and changes in patients' quality of life and relevant adverse events. If sufficient data and adequate homogeneity exists, network meta-analyses (NMA) will be performed. ETHICS AND DISSEMINATION: This will be the first systematic review to incorporate NMA to compare psychosocial treatments used as an adjunct to opioid agonist therapy for OUD. Results of this review will inform clinical management of persons with OUD. TRIAL REGISTRATION NUMBER: CRD42018090761.
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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 | 0.071 | 0.079 |
| Meta-epidemiology (narrow) | 0.008 | 0.006 |
| Meta-epidemiology (broad) | 0.028 | 0.028 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.062 | 0.007 |
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".