Transition to adult healthcare for immigrant youth: Practice recommendations
Bibliographic record
Abstract
The transition from pediatric to adult healthcare is challenging for adolescents and young adults (AYA) with pediatric-onset chronic health conditions. Although barriers faced by AYA during transition are well-documented, previous studies have not considered how migration and settlement impact patient and family experiences. To fill this gap, we conducted a qualitative descriptive study to explore the recommendations for policy and practice from the perspectives of immigrant and refugee AYA living with chronic health conditions in Canada as they transition from pediatric to adult healthcare. We also sought the perspectives of their parents/caregivers and service providers. Semi-structured individual interviews and focus groups were conducted with 20 AYA, 14 caregivers, and 5 service providers. AYA were 1st or 2nd generation immigrants to Canada, aged 16–25, with childhood-onset chronic health conditions. Parents or caregivers were 1st generation immigrants, having children with chronic health conditions. Service providers delivered healthcare or other services to immigrant populations. Recommendations to improve the transition process and mitigate barriers to care included providing more accessible information about patients’ health conditions prior to transition, moving the age of transfer beyond age 18, establishing a centralized online health portal for patients who are transitioning to the adult system, providing family case workers, increasing language support, and increasing cross-sector support. A broad range of recommendations aimed at improving the transition process were provided. Future interventions to support transition from pediatric to adult care for immigrants and refugees should incorporate these recommendations. • Immigrant youth living chronic health conditions face major transition hurdles • Barriers to transition include language barriers, discrimination, and finances • Recommendations include providing increased information about patients’ health conditions prior to transition, moving the age of transition later, a centralized online health portal for patients who are transitioning to the adult system, the provision of family case workers, increasing language support, and increasing cross-sector support
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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 | 0.018 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".