<scp>H</scp>istory of being in government care associated with younger age at injection initiation among a cohort of street‐involved youth
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Compared to the general population of youth, health-related disparities experienced by youth exposed to the child welfare system are well documented. Amongst these vulnerabilities are elevated rates of substance use, including injection drug use; however, less is known about when these youth transition to this high-risk behaviour. We sought to assess whether having a history of government care is associated with initiating injection drug use before age 18. DESIGN AND METHODS: Between September 2005 and May 2014, data were derived from the At-Risk Youth Study, a cohort of street-involved youth who use illicit drugs in Vancouver, Canada. Multivariable logistic regression analysis was employed to examine the relationship between early initiation of injection drug use and having a history of being in government care. RESULTS: Among the 581 injecting street-involved youth included, 229 (39%) reported initiating injection drug use before 18 years of age. In multivariable analysis, despite controlling for a range of potential confounders, having a history of government care remained significantly associated with initiating injection drug use before age 18 (adjusted odds ratio = 1.69; 95% confidence interval: 1.15-2.48). DISCUSSION AND CONCLUSIONS: Youth with a history of being in government care were significantly more likely to initiate injection drug use before age 18 than street-involved youth without a history of being in care. These findings imply that youth in the child welfare system are at higher risk and suggest that interventions are needed to prevent transitions into high-risk substance use among this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".