108.6: Implementation of evidence-based best practices in patient, family, and donor engagement in deceased organ donation research.
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,483 | 0,464 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,003 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,010 | 0,005 |
| Études des sciences et des technologies | 0,009 | 0,009 |
| Communication savante | 0,013 | 0,009 |
| Science ouverte | 0,013 | 0,022 |
| Intégrité de la recherche | 0,021 | 0,020 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,004 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».