Exploring Peer Support Services for Youth Experiencing Multiple Health and Social Challenges in Canada: A Hybrid Realist-Participatory Evaluation Model
Bibliographic record
Abstract
The Canadian youth services system is fragmented with less than one third of youth accessing the mental health services they need. Experts have called for systems transformation that will increase the integration of youth services and take advantage of complementary services, such as peer supports. Further, researchers have suggested that there is a need to identify the unique contribution and underlying mechanisms that support client recovery within youth peer support interventions. This paper describes the steps taken to implement a hybrid realist and participatory evaluation examining peer support services for youth (14–26 years old) with mental health, physical health and/or substance use challenges. We describe the procedures followed to engage peers in the design of the study and how this was integrated with a realist approach. We also provide a detailed description of the related adaptations to the methods applied within the second stage of the study. Lessons learned through the integration of the two methods are provided as well as potential implications for the findings and related research.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".