Canadian Stakeholders’ Perspectives on Voucher Donation in Kidney Transplantation
Bibliographic record
Abstract
Introduction: Living donation remains the best therapy for people with end-stage kidney disease. Voucher donation allows donation to take place at the time that is most convenient for the donor. In this type of donation, a voucher is issued that can later be exchanged by a person in need of a kidney transplant. Voucher donation raises numerous issues. The objective of this study was to gather the perspectives of patients and transplant professionals on voucher donation. Methods: We conducted interviews with 24 patients and 21 transplant professionals between November 2020 and December 2022. The interviews were digitally recorded, transcribed, and analyzed using the qualitative description approach. Results: Most participants were open-minded about the possibility of implementing voucher donation because it could increase the number of available organs; however, they raised the following ethical concerns: issues of fairness, risks of undue pressure, informed consent, and risks of commodification. Prioritization among voucher holders, the number of vouchers allowed, the transferability of vouchers, and the verification of voucher holder's identity were the logistical issues raised. Actions suggested before implementing this program included the following: a regulatory framework or guidelines, educational tools, patient engagement, and management by a national program. Conclusion: This study describes the perspectives of patients and transplant professionals on ethical and logistical issues related to voucher donation. Strategies to address these issues as well to explore the perspectives of marginalized communities and of the general public are needed.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.035 | 0.009 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".