Long-term treatment outcomes in a First Nations high school population with opioid use disorder
Bibliographic record
Abstract
Abstract Objective To assess for long-term positive effects of buprenorphine treatment (BT) on opioid use disorder (OUD) at a Nishnawbe Aski Nation high school clinic. Design Postgraduation telephone survey of high school students between March 2017 and January 2018. Setting Dennis Franklin Cromarty High School in Thunder Bay, Ont. Participants All 44 students who had received BT in the high school clinic during its operation from 2011 to 2013 were eligible to participate. Main outcome measures Current substance use, BT status, and social and employment status. Results Thirty-eight of the 44 students who had received BT in the high school clinic were located and approached; 32 consented to participate in the survey. A descriptive analysis of the surveyed indicators was undertaken. Almost two-thirds (n = 20, 62.5%) of the cohort had graduated from high school, more than one-third (n = 12, 37.5%) were employed full time, and most (n = 29, 90.6%) rated their health as “good” or “OK.” A greater percentage of participants who continued taking BT after high school (n = 19, 61.3%) were employed full time (n = 8, 42.1% vs n = 4, 33.3%) and were abstinent from alcohol (n = 12, 63.2% vs n = 4, 33.3%). Participants still taking BT were significantly more likely to have obtained addiction counseling in the past year than those participants not in treatment (n = 9, 47.4% vs n = 1, 8.3%; P = .0464). Conclusion The study results suggest that offering OUD treatment to youth in the form of BT in a high school clinic might be an effective strategy for promoting positive long-term health and social outcomes. Clinical treatment guidelines currently recommend long-term opioid agonist treatment as the treatment of choice for OUD in the general population; they should consider adding youth to the population that might also benefit.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".