Patient-Identified Solutions to Primary Care Access Barriers in Canada: The Viewpoints of Nepalese Immigrant Community Members
Bibliographic record
Abstract
BACKGROUND: Accessing healthcare for immigrants in Canada is complicated by many difficulties. With the continued and upward trend of immigration to Canada, it is crucial to identify the solutions to the barriers from the perspectives of different immigrant communities as they encounter them including the relatively smaller and less studied population groups of immigrants. As such, Nepalese immigrants in Canada are a South Asian ethnic group who have their own distinct language, culture, and socio-economic backgrounds, however, their experience with accessing healthcare in Canada is scarce in the literature. METHODS: We conducted 12 focus group discussions with first-generation Nepalese immigrants who had experiences with primary care use in Canada. Informed consent and demographic information were obtained before each focus group discussion. The verbatim transcription of the focus groups was analyzed using thematic analysis. RESULTS: The participants expressed a range of potential solutions to overcome the barriers, which we presented using the socio-ecological framework into 4 different levels. This includes individual-, community-, service provider-, and government/policy-levels. Individual-level actions included improving self-awareness and knowledge of health in general and navigating the healthcare system and proactively improving the language skills and assimilating into the Canadian culture. Examples of community-level actions included community events to share health information with immigrants, health literacy programs, and driving/carpooling to clinics or hospitals. Actions at the service provider level were mainly focused on enhancing communications, cultural competency training for providers, and ensuring to hire primary care workforce representing various ethnocultural backgrounds. Overall, focus group participants believed that the provincial and federal government, as appropriate, should increase support for dental and vision care support and take actions to increase the healthcare capacity, particularly by employing internationally graduated health professionals. CONCLUSIONS: Access to primary care is essential for the health of immigrant populations in Canada. Individuals, community organizations, health service providers, and governments need to work both individually and collaboratively to improve immigrants' primary care access.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".