392 Co-design of a patient navigator intervention for migrant children and youth with special healthcare needs for the MiNav RCT
Bibliographic record
Abstract
Abstract PTH 9: Miscellaneous 2, B302 (FCSH), September 5, 2025, 11:30 - 12:24 Aim Families of migrant children and youth with special healthcare needs (CYSHCN) frequently report unmet needs and barriers to obtaining appropriate healthcare. Our objectives were to co-design with families of migrant CYSHCN a patient navigator intervention aimed at decreasing barriers to care, for future testing in a randomized controlled trial (RCT). Methods For the co-design process, we used 1) the National Institute of Health Research (UK) guidance on co-producing research projects; 2) a tool by Moll et al. (2020) to foster reflexivity in co-design with marginalized populations; 3) two Community Advisory Boards (CABs; in Montreal and Toronto, Canada), including 10 migrant CYSHCN parents with lived experiences (different genders, race, ethnicity, language), 4 health and social services professionals caring for migrant families. We conducted 14 virtual CAB meetings over 16 months to co-develop: 1) roles, competencies, and training of the navigator (building off previous published work and our pilot program); 2) care coordination tools; 3) implementation and evaluation of the intervention. Results Parents and healthcare professionals shared experiences with navigating complex health and social service systems. The CABs determined that the patient navigator’s role was to: 1) support migrant families with CYSHCN to navigate transitions within and across the healthcare and social services systems; 2) facilitate communication between service providers and families; 3) support care coordination; 4) connect families to resources; 5) empower families; 6) provide effective and culturally safe communication and active listening; 7) complete administrative tasks. Navigator competencies prioritized included: knowledge of services and funding, empathy, communication skills, professionalism, parental empowerment, and advocacy. The CABs provided feedback on tools and outcomes, which were integrated into the planned RCT. Conclusion Through co-design, parents and providers developed a patient navigator intervention for migrant CYSHCN that integrated existing models and lived experiences. The CABs continue to contribute to the currently recruiting RCT.
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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 | 0.037 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 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".