Opting Out and Offers of ‘Alibis’ for Potential Living Kidney Donors in US Transplant Centers
Notice bibliographique
Résumé
Purpose 1) To delineate rates of and reasons for opting out of living kidney donation in the US. 2) To determine if and how transplant centers offer alibis to individuals who opt out. 3) To assess transplant professional attitudes regarding policy about offers of alibis. Methods We interviewed independent living donor advocates (ILDAs) and medical program directors from US transplant centers with the highest volume living kidney donor (LKD) programs. The semi-structured interviews inquired about rates of withdrawal from donation for non-medical reasons; reasons potential donors report for opting out; personal experiences interacting with individuals who opted out; and attitudes towards alibi policy. The data were analyzed using standard qualitative coding techniques in NVivo. Results 38 centers participated in the study (76% response rate). No transplant center systematically tracked rates of opting out. The most commonly reported reasons for LKDs to opt out included: fear of impact on health or surgical risks (50%), pressure or coercion from family or the intended recipient (42%) financial problems (34%), change in life circumstances (32%), increased awareness of donation's complexities (32%), and other care-taking responsibilities (29%). 74% of centers sometimes or always offered alibis to all potential donors while 21% of centers do not and 5% were unsure. Most centers offered non-specific statements of ineligibility to donate, whereas 18% of occasionally provided alibis included false or exaggerated medical information. Few participants had ever personally offered an alibi. Those who had been involved rarely knew if the alibi had been used or how it had been received by the intended recipient. Most centers do not recontact those who opted out, though a few ILDAs had followed up with individuals who they thought were at especially high risk for emotional distress. The majority (78%) of participants were unaware of any UNOS/OPTN policy about alibis; one individual (2%) correctly stated that there was no such UNOS/OPTN policy. Two-thirds (67%) were in favor of introducing either policies or guidelines regarding the use of alibis, while 27% opposed, 2% unsure, and 4% who believed that alibis should be prohibited. Discussion We found that most US transplant centers do not know much about the population of individuals who opt out of living kidney donation. Our study reveals a range of practices for use of and attitudes regarding alibis. At present, there is no OPTN/OPTN policy regarding alibi offers for LKDs who opt out. Further work should be done to identify best practices that help preserve potential LKD autonomy and welfare. Conclusion Our results highlight the need for further study of individuals who opt out of living kidney donation. They also suggest avenues for transplant centers and policy makers to develop guidance to help improve support for those who opt out.
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 | 0,016 | 0,052 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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 ».