Youth Residential Treatment Options in \nNewfoundland & Labrador
Bibliographic record
Abstract
The Issue \nIn 2009, the Government of Newfoundland & Labrador announced the creation of two youth residential treatment (YRT) centres for youth with complex needs. YRT is a multifaceted form of care that requires programming in the areas of treatment, milieu (i.e., plans to manage group interactions among clients and staff), and the residence itself. \nA broad range of multi-disciplinary research-based evidence can inform the design and implementation of these YRT centres. For this evidence to be useful to decision makers, it needs to be interpreted in the context of Newfoundland & Labrador. Providing health decision makers with the best available evidence that is attuned to the capacities and characteristics of the province is the goal of the Contextualized Health Research Synthesis Program (CHRSP). \nThe Results \nThe Research Team, led by Dr. John Lyons, synthesized and contextualized the systematic review research literature related to several areas of interest: 1) YRT as a generic treatment program; 2) treating youth with addictions; 3) treating youth with disruptive behaviours; 4) treating sexually aggressive youth; 5) treating Aboriginal youth; 6) YRT site design, staffing and governance; and 7) the health economics of YRT. \nDespite a long history, YRT does not have a robust base of systematic review evidence due to methodological challenges. Nonetheless, there was evidence indicating that: \n• YRT is most useful for those youth with elevated levels of complex needs. \n• Some established treatments for youth with addictions and youth with disruptive behaviours can produce statistically significant, but clinically small, effects in clients. \n• There are significant gaps in evidence concerning Aboriginal youth with complex needs and several indications that they may need specialized programming in order for treatments to be effective. \n• YRT centres may benefit significantly from an autonomous intake system and they are most efficient if they operate within an integrated continuum of child care services including less intensive options. \n• The costs of not treating youth with complex needs greatly exceeds the costs of treatment, although community-based services are more cost efficient than residential services.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".