Navigating primary care in Ontario: a qualitative study investigating the perceptions of Chinese newcomers to Canada
Bibliographic record
Abstract
Abstract Newcomers to Canada often encounter challenges navigating a novel healthcare system. Some of these challenges may be related to differences between the healthcare system in their home country and the Canadian system. Few studies have addressed how Chinese newcomers to Canada understand the role of primary care; this study addresses this gap. The primary objective was to explore how Chinese newcomers perceive the role of primary care in Ontario. Secondary objectives explored how they learned about primary care, their understanding of continuity of care, and their perceptions of preventive healthcare. This qualitative study used individual interviews conducted with residents of Ontario who immigrated from mainland China in the last 5 years. Transcripts from 10 interviews were analyzed using thematic analysis and demographic data were analyzed descriptively. Main themes included: barriers to accessing care, differences between healthcare systems, the importance of continuity of care, understanding the family doctor’s role, the significance of preventive healthcare, and healthcare system information needs. Given the substantial differences in how healthcare is provided in China compared to Canada, there is a need to improve newcomer education and orientation regarding the role of primary care in Ontario. Improved understanding of the Canadian healthcare system would help newcomers address barriers and assist with system navigation. Study findings also have broader implications for understanding the experiences and perceptions of newcomers from other countries as they navigate primary care in a new setting.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".