Lessons Learned About the Education Needs of Kidney Transplant Recipients: A Mixed-Method Study
Notice bibliographique
Résumé
Background: Much of the literature on kidney transplant education focuses on educating recipients prior to transplant or in the early postoperative period. It is unknown whether the information provided is meaningful to patients or whether the importance of education topics changes with time. Objective: We sought to identify the learning needs of patients post-kidney transplant. Design: Our multidisciplinary team conducted a mixed-method study to better understand the learning needs of patients; what is important to them in the early postoperative period and a year after transplant. Setting: One urban academic hospital performing kidney transplant in Ontario, Canada. Data were collected between September 2019 and March 2021, including during the COVID-19 pandemic. Participants: A convenience sample of 20 participants in the post-kidney transplant clinic. Participants’ mean age was 56 (SD ± 11) with 75% of participants male gender. Methods: Twenty kidney transplant patients were recruited between 3 and 6 months post-transplant. Participants completed an initial demographic questionnaire. They completed the Learning Needs Inventory (LNI) and a one-on-one semi-structured interview at 2 time points: 3 to 6 months post-transplant and 12 to 18 months post-transplant. Results: Patient interviews revealed that their access to a trustworthy health care team, support system, and reported challenges post-transplant shaped their ability to engage in learning. Patients shared that each aspect influences when and what topics were important to them, which allowed patients to obtain personalized education. A multidisciplinary team extending beyond physicians and nurses to include professionals such as pharmacists, dietitians, and social workers can best address patient-specific education needs post-transplant was highlighted in patients’ comments. Patients revealed that their support system helps to develop self-reliance and support their transition after transplant to allow them to recover and manage challenges after transplant. Support systems varied from family, friends, colleagues and included social media and community organizations were helpful. Our study identified 3 realms of challenges post-transplant including: emotional, physical, and financial. Quantitative data showed significant findings on the level of importance regarding the use of alcohol, demonstrating a shift in median rating of “not important at all” to “not very important” ( P = .016). A significant effect ( P = .031) shifting the median rating of post-transplant dental care from of “a little important” to “very important.” Limitations: The small convenience sample with only English-speaking patients used in this study may have affected our ability for generalizable results. Part of this study was completed during the COVID-19 pandemic, which may have led to individual responses to vary, as priorities may have been different during the pandemic. Conclusion: Only 2 topics (dental care and use of alcohol) shifted in importance. Most education topics (ie, rejection, infection) covered in 3 to 6 months post-transplant continued to be important for those that have had their transplant for more than a year suggesting the need for ongoing education post-transplant. Multidisciplinary care teams play an important role in providing personalized education to patients and help to address emotional, physical, and financial challenges after transplant. This study showed the importance of social media and community organizations in patients’ education offering an additional avenue of support and to hear others, lived experiences. Trial registration: Not registered.
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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 | 0,022 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,002 | 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 ».