Patient and Family Financial Burden in Cancer: A Focus on Differences across Four Provinces, and Reduced Spending Including Decisions to Forego Care in Canada
Bibliographic record
Abstract
GOAL: This study aimed to examine provincial differences in patient spending for cancer care and reductions in household spending including decisions to forego care in Canada. METHODS: Nine-hundred and one patients with cancer, from twenty cancer centers across Canada, completed a self-administered questionnaire (P-SAFE version 7.2.4) (344 breast, 183 colorectal, 158 lung, and 216 prostate) measuring direct and indirect costs and spending changes. RESULTS: Provincial variations showed a high mean out-of-pocket cost (OOPC) of CAD 938 (Alberta) and a low of CAD 280 (Manitoba). Differences were influenced by age and income. Income loss was highest for Alberta (CAD 2399) and lowest for Manitoba (CAD 1126). Travel costs were highest for Alberta (CAD 294) and lowest for British Columbia (CAD 67). Parking costs were highest for Ontario (CAD 103) and lowest for Manitoba (CAD 53). A total of 41% of patients reported reducing spending, but this increased to 52% for families earning <CAD 50,000 per year. The highest national rates of decisions to forego care were in relation to vitamins/supplements, the selection made by 21.3% of those who indicated spending reductions. Reductions for complementary and alternative medicine (CAM) were made by 16.3%, and for drugs, by 12.8%. Most cost categories had higher proportions of individuals who decided to forego care when family income was
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".