Feasibility of a Healthy Relationships Program with Youth at a Child Protective Services Agency
Bibliographic record
Abstract
Abstract Youth involved in child welfare may benefit from programming that enhances their relationship skills given their susceptibility to engaging in high-risk interpersonal behaviors that can lead to challenges such as, engaging in or experiencing violence, housing and job insecurity, and poor physical and mental health. This research explored the feasibility of implementing an evidence-based healthy relationships program, the Healthy Relationships Plus Program - Enhanced (HRP-E), with youth involved in child welfare. Over 9 months, four HRP-E groups were facilitated at a Children’s Aid Society in Ontario, Canada, involving 28 youth. Interviews were conducted with facilitators (n = 5) and youth (n = 13) to examine their views of the program. Facilitators also completed surveys that evaluated the facilitation of each session and overall program implementation. A thematic analysis of the data was conducted and results indicated that the HRP-E was perceived as a valuable program that is relevant and useful for youth involved in child welfare. Participants highlighted trauma-informed practices and organizational resources that are required when facilitating the HRP-E within a child welfare context. The present findings address the theory-to-practice gap by illustrating the practical application of trauma-informed program facilitation. The outcomes of this study contribute to understanding considerations and best practices for implementing a healthy relationships program with youth involved in child welfare.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".