108.6: Implementation of evidence-based best practices in patient, family, and donor engagement in deceased organ donation research.
Bibliographic record
Abstract
International Donation and Transplantation Legislative and Policy Forum. Canadian Donation and Transplantation Research Program. Introduction: While every donation and transplantation system strives to satisfy the needs of its population, there are a diverse array of challenges to do so. To address common global challenges, we organized the International Donation and Transplantation Legislative and Policy Forum (the Forum) to create a consensus description of laws and policies for an ideal system. This guidance was designed for stakeholders who aspire to link evidence and ethical concepts for legislative and policy reform. Colleagues from around the world, including researchers, clinicians, ODO administrators, and experts in law, social sciences, and bioethics, were joined by partners with lived experience as pre-or-post transplant patients, family and caregivers, living donors, and deceased donor families, to co-develop recommendations in seven domains through the nominal group technique. The Research and Innovation domain focused on ethical recommendations for research practice. Method: As a national research network, the Canadian Donation and Transplantation Research Program (CDTRP) is positioned to support the implementation of Forum recommendations related to research and innovation. The CDTRP is taking a practical approach to supporting researchers in implementing these practices in their research programs. Results: The key Forum recommendation regarding PFD involvement in deceased donation research is that it must be based on the principles of inclusiveness, support, mutual respect, and co-building. Specific recommended practices include (1) dedicating sufficient funding to remunerate PFD partners for their roles and expertise, (2) establishing infrastructure to support, (3) providing training for researchers and PFD partners, (4) developing an approach to matching patient expertise with specific research goals, (5) establishing a patient engagement plan that outlines the project’s values and defines the scope of engagement, time commitments, and roles, and (6) developing an evaluation framework to measure outcomes of engaging patients. The CDTRP is building core resources, processes, and/or expertise related to all six recommendations, which researchers can draw on to improve the quality of their research. We have seen a consistently high proportion of support requests related to PFD engagement from 2021-2025, as well as an increasing number of registered PFD partners wishing to participate in research. Conclusion: Integrating the experiences and priorities of PFD partners is the only way to ensure that donation and transplant research serves this population in the way that is most meaningful to them. The CDTRP provides a framework to assist researchers and patient, family, and donor partners to increase the uptake of ethical recommendations into research projects, improving research’s quality and relevance. This work offers a model for teams, institutions, and national/international bodies who wish to support the enhanced integration of these voices into research programs.
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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 | 0.483 | 0.464 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.013 | 0.022 |
| Research integrity | 0.021 | 0.020 |
| Insufficient payload (model declined to judge) | 0.012 | 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".