Re-Envisioning the Canadian Nephrology Trials Network: A Can-SOLVE-CKD Stakeholder Meeting of Patient Partners and Researchers
Notice bibliographique
Résumé
PURPOSE: The Canadian Nephrology Trials Network (CNTN) was formed in 2014 to support Canadian researchers in developing, designing, and conducting prospective studies in nephrology. In response to the changing landscape and needs within the Canadian nephrology research community, an interest in further growth and development of the network was identified. In the following report, we describe the process undertaken to re-envision the network through the creation of 3 new committees and how the committees are facilitating change and growth within the CNTN for future sustainability. SOURCES OF INFORMATION: To understand areas for improvement and capacity building, the organization charged with overseeing the CNTN, Canadians Seeking Solutions and Innovations to Overcome Chronic Kidney Disease (Can-SOLVE CKD), began by conducting an environmental scan. As well, 2 informal surveys were sent to nephrology professionals (who were members of the CNTN and the Canadian Society of Nephrology) and patient partners (from Can-SOLVE CKD). METHODS: In September 2018, 44 CNTN members and other stakeholders from across Canada (including patient partners and representatives from research funding agencies) convened for a 2-day visioning workshop in Mississauga, Ontario. The agenda for this workshop was largely based on the results from the informal surveys. CNTN leadership participated and chose other workshop participants through informal stakeholder mapping and purposeful recruitment. Patient partners were recruited to participate in the workshop through advertisement within the Can-SOLVE-CKD patient council. The survey results and discussion questions were presented to participants at the workshop who, in turn, discussed in large- and small-group session ways in which the CNTN might be expanded. RESULTS: Surveys of patient partners indicated that they would like to see greater involvement of patients in the research process. Surveys of researchers indicated that they wanted more support and resources for coordinating prospective trials. The themes which emerged from the workshop discussions were peer review, engagement, and training. These themes were broadened and formally re-named to Scientific Operations, Communications and Engagement, and Capacity Building. A working committee, each co-led by a nephrologist with research experience and a patient partner, was created to advance each of these identified themes. An executive committee was created to provide overall strategic leadership and governance to the network. The Scientific Operations Committee conducts peer reviews; provides letters of endorsement after peer review; and holds semi-annual in-person meetings where researchers can present their proposals and obtain feedback from multiple stakeholders, including patients. The Communications and Engagement Committee publishes a quarterly newsletter, engages the community on Twitter, and reaches out to community sites and new nephrologists to engage them in research. The Capacity Building Committee conducts webinars to encourage patient partners to develop their own research questions and is developing a hub-and-spoke model to improve research collaboration. LIMITATIONS: We did not conduct formal stakeholder mapping. Only attendees of the visioning workshop provided input, and not everyone's comment or opinion was included in the workshop report. Perspectives were limited to the sample of people who attended the workshop or were surveyed and may not reflect perspectives of all stakeholders in nephrology research in Canada. We did not use formal qualitative methodology to summarize the workshops. IMPLICATIONS: Renewed areas of focus and related committees within the CNTN could lead to an increased capacity for nephrology research, increased engagement and collaboration with researchers, a higher likelihood of funding with rigorous peer review, and more clinical trials and multicenter collaborative prospective research being conducted in Canada.
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 | 0,193 | 0,133 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,052 | 0,015 |
| Communication savante | 0,020 | 0,011 |
| Science ouverte | 0,008 | 0,032 |
| Intégrité de la recherche | 0,015 | 0,027 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,002 |
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; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».