Cultural adaptation considerations of a comprehensive housing outreach program for Indigenous youth exiting homelessness
Bibliographic record
Abstract
Generalist health interventions that aim to reduce chronic health disparities between Indigenous and non-Indigenous populations can be culturally adapted to better meet the needs of Indigenous people in Canada; however, little is known regarding best practices in implementing these adaptations. The present study first provides a review of the research process used to adapt a previous evidence-based housing initiative for Indigenous youth in Northwestern Ontario. Second, it includes an overview of the adaptations that were made and the associated rationale for such adaptations. Third, it examines the experiences of participants and staff involved in the cultural adaptation of the Housing Outreach Program Collaborative (HOP-C), a health intervention re-designed to improve physical and mental health outcomes, wellbeing, and social support for formerly homeless Indigenous youth as they secure housing. Qualitative feedback from interviews with 15 participants and eight program staff, in addition to one focus group with an additional six frontline workers, described perceived outcomes of the program's cultural adaptations. Modifications to the overall program structure, specific roles within the program (including counseling services, peer mentorship, cultural services, and case management), and adaptations to general implementation within the health organization providing the intervention were described by participants and staff as effective and helpful adaptations. The focus of Indigenous values at an organizational level led to consistent adaptations in counseling and case management to best meet the unique needs of the youth involved. Based upon participant interviews, recommendations to future adaptations are provided.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".