Equitable Access Challenges for Primary Healthcare Faced by Egyptian Immigrant Women in Canada
Bibliographic record
Abstract
Background: Primary healthcare services are often the first services accessed when one experiences a health issue and where inequities in healthcare access are likely to appear. To date, there is a scarcity of health-related research that has been conducted among Egyptian-Canadian immigrant women. The primary objective of this study is thus to gain a deeper understanding of the nature of primary healthcare access barriers among Egyptian immigrant women residing in Calgary. Methods: Using a community-engaged research approach, we conducted three focus group discussions (FGDs) among first-generation Egyptian-Canadian women in Calgary. Community-engaged research is a collaborative research approach engaging researchers, community members, and community stakeholders in identifying societal inequities throughout every step of the research process. The recorded FGDs will be analyzed using thematic analysis by generating codes and defining key themes. Results: There were 14 participants in the 3 FGDs with an average age of 38.1 years. Among the participants, 64.3% were married, and all had university-level education. As the study is currently ongoing, we conducted a preliminary analysis with the three FGD transcripts. Based on preliminary data from conducted FGDs, it is anticipated that barriers will include wait times, communication barriers, and lack of trust based on prior negative experiences with the Canadian healthcare system. Conclusion: This project focuses on studying equitable healthcare access within an underrepresented immigrant population, with the goal of promoting more research in the field of immigrant health. This project has implications for health policy, as this may help inform and raise awareness about the barriers immigrant women may face when accessing primary healthcare and potential solutions.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".