Money is Brain: Financial Barriers and Consequences for Canadian Stroke Patients
Bibliographic record
Abstract
BACKGROUND: Stroke patients of lower socioeconomic status have worse outcomes. It remains poorly understood whether this is due to illness severity or personal or health system barriers. We explored the experiences of stroke patients with financial barriers in a qualitative descriptive pilot study, seeking to capture perceived challenges that interfere with their poststroke health and recovery. METHODS: We interviewed six adults with a history of stroke and financial barriers in Alberta, Canada, inquiring about their: (1) experiences after stroke; (2) experience of financial barriers; (3) perceived reasons for financial barriers; (4) health consequences of financial barriers; and (5) mechanisms for coping with financial barriers. Two reviewers analyzed data using inductive thematic analysis. RESULTS: The participants developed new or worsened financial circumstances as a consequence of stroke-related disability. Poststroke impairments and financial barriers took a toll on their mental health. They struggled to access several aspects of long-term poststroke care, including allied health professional services, medications, and proper nutrition. They described opportunity costs and tradeoffs when accessing health services. In several cases, they were unaware of health resources available to them and were hesitant to disclose their struggles to their physicians and even their families. CONCLUSION: Some patients with financial barriers perceive challenges to accessing various aspects of poststroke care. They may have inadequate knowledge of resources available to them and may not disclose their concerns to their health care team. This suggests that providers themselves might consider asking stroke patients about financial barriers to optimize their long-term poststroke care.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.020 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".