Evaluation of a Health Navigator Pilot Program for Youth in Foster Care
Bibliographic record
Abstract
The Health Navigator Program (HNP) was a pilot health mentor intervention program for youth in British Columbia, Canada, with connections to the provincial child welfare system. In this article, youth participants are referred to as “independent youth” as they are independent of traditional familial care. Children and youth in the foster care system face increased prevalence and risk of physical and mental health challenges with lasting implications throughout adulthood. The cumulative effect of childhood trauma, lack of connections to supportive adults, and structural obstacles such as poverty, racism, and sexism all contribute to creating significant barriers for independent youth navigating the health care system. The HNP was created to address these obstacles and facilitate improved health outcomes for independent youth. Youth from 2 program sites were paired with medical student volunteers who provided advocacy and mentorship. A qualitative process evaluation was undertaken to assess the effectiveness of the HNP in achieving the intended program outcomes. Findings revealed that the independent youth participants increased awareness of their own health needs, gained confidence in navigating the health care system, and had improved short-term health outcomes. Relationship building with a caring adult, outside of a paid professional role, was shown to be the most significant factor in achieving these positive outcomes.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".