How do patients receiving radiotherapy in a Dutch hospital value their time? A contingent valuation study
Bibliographic record
Abstract
Abstract Aim Cancer patients spend a lot of time receiving medical care. Our study investigates patients’ preferences regarding reducing the time involved in non-palliative radiotherapy care. Methods A total of 142 Dutch patients were included in our study. Using a contingent valuation survey, we measured the proportion of patients who preferred to reduce their patients’ time, splitting it into five different categories, and, for those who did, whether and how much they were willing to pay for this to happen. Results About 50% of the patients preferred to reduce their time waiting for admission by 1 week and their travel time by half; 20 and 62% wanted to reduce their waiting time by half and their treatment time from 20 to 5 minutes, respectively; 36% preferred to be treated 7 instead of 5 days a week; and 20% of those wishing to reduce their patients’ time were willing to pay, and their mean willingness to pay (WTP) ranged from £0·32 to £18·1 per hour’s reduction of their time. Conclusion Half of the patients seem to assess their patients’ time as reasonable. The other half preferred to reduce it, but only about 20% of them were willing to pay for it to happen and their mean WTP was low.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".