A Scoping Review of Evidence-Based Interventions and Health-Related Services for Youth Who Use Nonmedical Opioids in Canada and the United States
Bibliographic record
Abstract
PURPOSE: This scoping review synthesizes the characteristics and outcomes of recent evidence-based treatments and services for youth with nonmedical opioid use/opioid use disorder in the context of the ongoing opioid crisis in Canada and the United States. METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses - Extension for Scoping Reviews guidelines, empirical health databases were searched for literature describing treatments or health-related services for nonmedical opioid use/opioid use disorder among youth (ages 12-25). Two independent reviewers conducted study screening, selection, and data extraction. A deductive content analysis further synthesized the interventions' characteristics following the Consolidated Framework for Implementation Research and an inductive content analysis synthesized the interventions' efficacy/effectiveness outcomes. RESULTS: Twenty-five articles met inclusion from 2,761 screened; 88% described opioid agonist treatment (alone or in combination with nonpharmacological treatment). Following the Consolidated Framework for Implementation Research, commonly identified adaptable characteristics included treatment decision-making processes, integrated health and social services, and treatment settings. Efficacy/effectiveness outcomes most frequently included substance use and treatment engagement. DISCUSSION: This study informs future development, implementation, and evaluation of practices and policies that could be tailored to improve the quality of opioid agonist treatment for youth at risk of significant harms from nonmedical opioid use.
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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 | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".