Informing youth‐centred opioid agonist treatment: Findings from a retrospective chart review of youths' characteristics and patterns of opioid agonist treatment engagement in a novel integrated youth services program
Bibliographic record
Abstract
AIM: Youth ages 12-24 account for approximately 20% of overdoses and yet are poorly reached by opioid agonist treatment (OAT), the most widely recommended treatment for opioid use disorder (OUD). This study contributes to understanding this critical gap by describing youths' patterns of OAT engagement at a novel integrated youth-specific OAT program. METHODS: A retrospective chart review was carried out on electronic medical records of n = 23 youth with OUD accessing a community-based integrated youth services (IYS) centre. Data abstraction focused on four domains: sociodemographic, social determinants of health, patterns of OAT engagement, and other services utilized. RESULTS: Youths' mean age was 22.6 years (SD = 2.1), with a mean age of first opioid use of 17.4 (SD = 2.7). Youth reported extensive histories of adverse childhood experiences, concurrent mental and physical health complications, and poly-substance use. All youth were offered OAT and 83% initiated treatment with buprenorphine/naloxone, methadone, or slow-release oral morphine. Among those initiating OAT, 42.1% were considered stable on OAT. CONCLUSIONS: To our knowledge, this is the first empirical study to describe youths' OAT engagement in an integrated youth-specific OAT program. Our findings demonstrated that a high proportion of youth with OUD initiated OAT in this novel program with varying degrees of OAT stability. These findings can be used to inform the development and implementation of youth-specific and integrated OAT. To account for the novelty of this area of study and small sample sizes, future collaborative efforts across IYS initiatives should be considered, including mixed method approaches to understand outcomes and experiences.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".