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Record W4409336932 · doi:10.5334/ijic.icic24457

Developing evidence-based practice guidelines for delivering and monitoring youth-centred opioid agonist treatment

2025· article· en· W4409336932 on OpenAlexaboutno aff
Roxanne Turuba, Kirsten Marchand, Skye Barbic

Bibliographic record

VenueInternational Journal of Integrated Care · 2025
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOpioidAgonistNursingPsychology

Abstract

fetched live from OpenAlex

Background: Opioid use disorder (OUD) is a chronic health condition that impacts over 26 million people worldwide and is one of the largest contributor of global disease burden (e.g., blood-borne infections, unintentional injuries, overdose deaths, suicide). Opioid agonist treatment (OAT) is widely recognized as the safest and most effective treatment for people with OUD. Yet, youth encounter substantial structural barriers to engage with OAT (e.g., age-based eligibility criteria, misinformation, and stigma). Further, youths’ treatment goals, preferences, and needs often do not align with how OAT is currently delivered (e.g., daily dispensation). Thus, this life-saving treatment remains underutilized among youth, further exacerbating opioid-related harms (e.g., mental and physical morbidity, social exclusion, mortality) in North America and many nations globally. Objective: This project aims to develop evidence-based practice guidelines for the delivery and monitoring of youth-centred OAT. These guidelines will help service providers deliver OAT and measure outcomes that are relevant and informed by youth. Methods: In the first phase of this study (completed), we conducted a scoping review to identify and summarize peer-reviewed literature published between 2015 and 2023 on the full range of evidence-based interventions and health-related services for youth (ages 12-25) who use unregulated opioids in North America. In the second phase (December 2023 – January 2024), we will conduct semi-structured interviews with four expert groups (youth, caregivers, service providers, and policy makers) who have experience receiving, delivering, or making decisions on the implementation and monitoring of OAT for youth. Interviews will collect data on their perspectives of the optimal principles, characteristics, settings, and outcomes of a youth-centred OAT model of care, as well as their recommendations for implementing a best practice across diverse healthcare settings. The interviews will be audio-recorded, transcribed, and analyzed using a directed content analysis approach. We will share the findings from the analysis at the conference and use them to inform the implementation of youth-centred OAT across Foundry, a network of integrated youth services in British Columbia. Results/Implications: Twenty-five articles were included in the scoping review. The findings show that OAT leads to improved substance use outcomes among youth, however treatment effects were not as strong as in adults. Few studies in the scoping review were conducted in healthcare settings that were tailored to youth or in integrated care settings where youth could engage with comprehensive and individualized care. The results of the review support the need for developing youth-centred OAT practice guidelines. The practice guidelines will improve the quality and monitoring of OAT for youth, and thus, reduce the adverse harms associated with opioid use. While these guidelines will be developed from the perspective of experts in British Columbia, they can provide direction for pan-Canadian and international guidelines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.263
metaresearch head score (Gemma)0.504
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.263
Threshold uncertainty score0.909

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2630.504
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0070.012
Bibliometrics0.0260.018
Science and technology studies0.0050.004
Scholarly communication0.0140.015
Open science0.0180.014
Research integrity0.0150.012
Insufficient payload (model declined to judge)0.0080.005

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.

Opus teacher head0.095
GPT teacher head0.405
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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