Discordant indigenous and provider frames explain challenges in improving access to arthritis care: a qualitative study using constructivist grounded theory
Bibliographic record
Abstract
INTRODUCTION: Access to health services is a determinant of population health and is known to be reduced for a variety of specialist services for Indigenous populations in Canada. With arthritis being the most common chronic condition experienced by Indigenous populations and causing high levels of disability, it is critical to resolve access disparities through an understanding of barriers and facilitators to care. The objective of this study was to inform future health services reform by investigating health care access from the perspective of Aboriginal people with arthritis and health professionals. METHODS: Using constructivist grounded theory methodology we investigated Indigenous peoples' experiences in accessing arthritis care through the reports of 16 patients and 15 healthcare providers in Alberta, Canada. Semi-structured interviews were conducted between July 2012 and February 2013 and transcribed verbatim. The patient and provider data were first analyzed separately by two team members then brought together to form a framework. The framework was refined through further analysis following the multidisciplinary research team's discussions. Once the framework was developed, reports on the patient and provider data were shared with each participant group independently and participants were interviewed to assess validity of the summary. RESULTS: In the resulting theoretical framework Indigenous participants framed their experience with arthritis as 'toughing it out' and spoke of racism encountered in the healthcare setting as a deterrent to pursuing care. Healthcare providers were frustrated by high disease severity and missed appointments, and framed Indigenous patients as lacking 'buy-in'. Constraints imposed by complex healthcare systems contributed to tensions between Indigenous peoples and providers. CONCLUSION: Low specialist care utilization rates among Indigenous people cannot be attributed to cultural and social preferences. Further, the assumptions made by providers lead to stereotyping and racism and reinforce rejection of healthcare by patients. Examples of 'working around' the system were revealed and showed potential for improved utilization of specialist services. This framework has significant implications for health policy and indicates that culturally safe services are a priority in addressing chronic disease management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".