Transnational Healthcare Practices Among Afghan, Syrian, and Ukrainian Refugee Older Adults in the Greater Toronto Area: A Study Protocol
Bibliographic record
Abstract
The global population of older adults is growing rapidly, and refugees are now a significant proportion of the older adult population in Canada. Transnational healthcare practices (THPs)—seeking health information or services from the country of origin—may be an essential strategy used by refugee older adults in Canada, but few studies have explored this phenomenon. This is a protocol for a study, which is aimed at developing a comprehensive understanding of the role THPs play in the lives of older adults from three refugee groups (Afghan, Syrian and Ukrainian) (re)settled in the Greater Toronto Area (GTA), Canada. It will be informed by Constructivist Grounded Theory and will consist of three phases. Phase 1 will involve semi-structured individual interviews with Afghan, Syrian, and Ukrainian refugee older adults living in the GTA (n = 75–90) to explore their perspectives and experiences with various types of THP. Phase 2 will also involve semi-structured interviews with 75–90 refugee older adults from the three communities to examine the role of THP in stress, coping, and resilience in the context of health promotion, illness diagnosis, and disease management as well as the individual and contextual factors driving the use of THPs. Phase 3 will involve six focus groups (n = 36–48) with refugee older adults from these communities to explore what information, care, supports, technology, and services are needed to manage their health and illnesses locally. This project will advance knowledge in the areas of (re)settlement and integration, aging, local healthcare access, and THPs among refugee older adults in Canada. The findings will inform more effective integration policies and the delivery of efficient and equitable health information, care, support, technology, and services that address the healthcare needs of refugee older adults, enabling them to age well and age in place.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.029 | 0.006 |
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".