50 Co-designing an intervention with asylum seeking youth to improve access to healthcare in Canada using human-centered design
Bibliographic record
Abstract
Abstract Background Asylum seeking youth in Canada and the United States face multiple barriers to accessing healthcare, leaving them at greater risk of worse health outcomes. In a previous study, we found that limited knowledge of the Canadian health care system and few navigation supports were a key barrier to care for asylum seeking youth, yet no youth-developed intervention existed to support this population. Human-centered design (HCD) develops meaningful interventions with communities who have been historically marginalized. Objectives This study sought to co-design an intervention to increase youth empowerment and access to health care for asylum seeking youth in Canada. Design/Methods This was a community-based participatory-action research (CBPAR) study, and combined human-centered design (HCD) methodologies. We obtained research ethics board approval for this study (#SMH REB 22-117). In partnership with two community organizations that supported asylum seeking youth in a large Canadian city, a youth advisory board was created. In multiple co-creation sessions over a calendar year, an intervention was developed in rapid prototyping sessions and refined with feedback, to develop a final pilot intervention. Results A total of 7 asylum-seeking youth participated in the youth advisory board, ranging in age from 12-19, representing 3 different languages and included youth who self-identified with chronic medical conditions. Over a 15-month period, they participated in 6 co-creation sessions to develop a multi-lingual, web-based tool; youth specifically stated they did not believe an app would be helpful, but rather a resource that could be easily accessed. The youth advisory board shared they had limited understanding of the Canadian healthcare system, as well as interim and provincial health insurance. Youth felt the tool should answer questions about how health insurance worked, be brightly colored, use dyslexia-friendly font and be easily saved on a smartphone as an image. A multi-lingual wallet card was developed for youth to easily present at healthcare encounters, particularly if they did not have provincial health insurance, to help youth communicate their coverage, language and needs. Conclusion To our knowledge, we developed the first co-designed tool in Canada for youth asylum seekers, by youth, to improve and empower youth to receive health care services they are entitled to through navigation support. Given the high degree of marginalization faced by asylum seeking youth, this intervention has the promise to improve health outcomes. Feasibility and acceptability of this study will be evaluated in subsequent studies.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".