Cultural concordant care: insights from international medical graduate family physicians in Canadian practice
Bibliographic record
Abstract
Within Canada, 25% of physicians are international medical graduates (IMGs) who completed medical school outside of Canada. While they may share similar cultural backgrounds with Canada's multi-cultural population, they have been trained abroad. The purpose of this study was to identify the rewards and challenges experienced by IMG family physicians when caring for patients of the same cultural background as the physician. Using a descriptive qualitative approach, we conducted in-depth, semi-structured interviews with 18 practicing, licenced IMG family physicians in Edmonton and Calgary, Alberta, Canada. The interview questions addressed the rewards and challenges of providing culturally concordant care. Audiotaped interviews were transcribed and subject to qualitative latent content analysis. The study findings revealed that the rewards of caring for patients of the same cultural background as the IMG family physician included: shared cultural values; a common language; and establishment of patient rapport and trust. The challenges associated with caring for patients of the same cultural background as the IMG physician included: concerns with patients crossing boundaries; communication challenges; and perception of appointments being longer. Understanding these dynamics can help better prepare IMGs for family practice, particularly in navigating professional boundaries, which should be emphasised during IMG training and induction into the healthcare system.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.031 | 0.015 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".