Exploring Canadian Physicians' Experiences With Type 2 Diabetes Care for Adult Indigenous Patients
Bibliographic record
Abstract
OBJECTIVES: The perspectives of physicians caring for Indigenous patients with diabetes offer important insights into the provision of health-care services. The purpose of this study was to describe Canadian physicians' perspectives on diabetes care of Indigenous patients, a preliminary step in developing a continuing medical education intervention described elsewhere. METHODS: Through in-depth semistructured interviews, Canadian family physicians and specialists with sizeable proportions of Indigenous clientele shared their experiences of working with Indigenous patients who have type 2 diabetes. Recruitment involved a purposive and convenience sampling strategy, identifying participants through existing research and the professional relationships of team members in the provinces of British Columbia, Alberta and Ontario. Participants addressed their understanding of factors contributing to the disease, approaches to care and recommendations for medical education. The research team framed a thematic analysis through a collaborative, decolonizing lens. RESULTS: The participants (n=28) included 3 Indigenous physicians, 21 non-Indigenous physicians and 4 non-Indigenous diabetes specialists. They practised in urban, reserve and rural adjacent-to-reserve contexts in 5 Canadian provinces. The physicians constructed a socially framed understanding of the complex contexts influencing Indigenous patients with diabetes in tension with structural barriers to providing diabetes care. As a result, physicians adapted care focusing on social factors and conditions that take into account the multigenerational impacts of colonization and the current social contexts of Indigenous peoples in Canada. CONCLUSIONS: Adaptations in diabetes care by physicians grounded in the historical, social and cultural contexts of their Indigenous patients offer opportunities for improving care quality, but policy and health system supports and structural competency are needed.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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".