What do justice-involved youth want from integrated youth services? A conjoint analysis.
Bibliographic record
Abstract
Background: Many youth in the criminal justice system are affected by mental health and/or substance use (MHS) challenges, yet only a minority receive treatment. One way to increase access to MHS care is integrated youth services (IYS), a community-based model of service delivery where youth can access evidence-based treatment for their MHS problems and other wellbeing needs, in one location. However, it is unknown what IYS services justice-involved youth prioritize. Objective: This study explored what components of IYS justice-involved youth deem to be the most important in meeting their MHS service needs, in comparison with non-justice-involved youth, by conducting a secondary analysis of data gathered from a larger Ontario-wide study. Method: = 188 non-justice-involved youth, completed thirteen choice tasks representing different combinations of IYS. Results: Both justice-involved and non-justice-involved youth exhibited preferences for a broad range of core health services, including mental health services, substance misuse counseling, medication management, and physical or sexual health services. They also preferred a broad range of additional support services, in addition to fast access to care in a community setting that specializes in mental health services, with the incorporation of e-health services. Justice-involved youth prioritized working with a trained peer support worker to learn life skills and help them with the services they need. The importance of youth playing a leadership role in making decisions within IYS organizations was also a distinguishing preference among justice-involved youth. Conclusions: Tailoring IYS to meet the service preferences of justice-involved youth may enhance service utilization, potentially leading to better outcomes for justice-involved youth and their communities.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".