Development and pilot testing of a health education program to improve immigrants’ access to Canadian health services
Bibliographic record
Abstract
BACKGROUND: In Canada's increasing immigrant population, a phenomenon called the "healthy immigrant effect" has arisen in which health declines after four years of settling. Access to healthcare is an important consideration. There is strong evidence that immigrants lack confidence and knowledge for navigating health services. The aim of this study was to develop and pilot test the Accessing Canadian Healthcare for Immigrants: Empowerment, Voice & Enablement (ACHIEVE) program. METHOD: The study employed an exploratory sequential mixed methods design. A qualitative study was completed. Program content was developed based on a scoping review and refined in a formative evaluation. Then, a pilot test of the program measured participants' perceived efficacy in improving confidence in healthcare navigation, program satisfaction, and learning in individual sessions. RESULTS: Researchers found significantly higher rates of health navigation and an increase in knowledge about the Canadian health system post-program. CONCLUSIONS: Results provide promising evidence that ACHIEVE may improve confidence in healthcare access among immigrants, demonstrating potential for dispersion on a larger scale.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".