Development of a conceptual framework for understanding financial barriers to care among patients with cardiovascular-related chronic disease: a protocol for a qualitative (grounded theory) study
Bibliographic record
Abstract
BACKGROUND: Patients with cardiovascular-related chronic diseases may face financial barriers to accessing health care, even in Canada, where universal health care insurance is in place. No current theory or framework is adequate for understanding the impact of financial barriers to care on these patients or how they experience financial barriers. The overall objective of this study is to develop a framework for understanding the role of financial barriers to care in the lives of patients with cardiovascular-related chronic diseases and the impact of such barriers on their health. METHODS: We will perform an inductive qualitative grounded theory study to develop a framework to understand the effect of financial barriers to care on patients with cardiovascular-related chronic diseases. We will use semistructured interviews (face-to-face and telephone) with a purposive sample of adult patients from Alberta with at least 1 of hypertension, diabetes, heart disease or stroke. We will analyze interview transcripts in triplicate using grounded theory coding techniques, including open, focused and axial coding, following the principle of constant comparison. Interviews and analysis will be done iteratively to theoretical saturation. Member checking will be used to enhance rigour. INTERPRETATION: A comprehensive framework for understanding financial barriers to accessing health care is instrumental for both researchers and clinicians who care for patients with chronic diseases. Such a framework would enable a better understanding of patient behaviour and nonadherence to recommended medical therapies and lifestyle modifications.
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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 | 0.092 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".