Barriers to accessing health care of older Chinese immigrants in Canada: a scoping review
Bibliographic record
Abstract
Background This scoping review aims to examine the extant literature and summarize findings related to barriers to accessing health care faced by older Chinese immigrants in Canada. Methods We conducted a search of electronic databases for peer-reviewed articles using a comprehensive set of keywords without limiting the search to a specific time period. To be included in our review, articles had to meet the following criteria: (a) published in a peer-reviewed journal, (b) written in English, (c) provide a clear description of the methods used, and (d) respond to our research question, which focuses on identifying barriers to accessing healthcare for older Chinese immigrants living in Canada. Results Fifteen papers were selected based on the criteria, and five main barriers were identified, which are ranked in descending order according to the number of times they were mentioned: culture and health beliefs (N = 13), language and communication (N = 7), structural and circumstances (N = 2), health literacy and information (N = 2), and demographic, social, and economic factors (N = 2). Conclusions The issue of accessing healthcare for older Chinese immigrants in Canada is complex, as it involves multiple aspects that are relevant to both patients and healthcare providers. Our research findings suggest that the culturally and linguistically sensitive education programs, inter-sectoral coordination, and social support should be improved for older Chinese immigrants and those of other ethnic backgrounds.
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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 | 0.011 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.020 | 0.029 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".