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Enregistrement W4309655531 · doi:10.1177/20543581221136402

Involving Patient Partners in the KRESCENT Peer Review: Intent, Process, Challenges, and Opportunities

2022· article· en· W4309655531 sur OpenAlexaffabout
Elisabeth Fowler, Karin Bell, Kevin D. Burns, Angela Chiazzese, Sacha A. DeSerres, Bethany J. Foster, Sunny Hartwig, Gwen Herrington, Matthew T. James, Victor L. Jensen, Nina Jones, Sandi Kidston, Serge Lemay, Adeera Levin, Anne MacPhee, Shanda McCutcheon, Pietro Ravani, Susan Samuel, James W. Scholey, Tomoko Takano, Navdeep Tangri, Nancy Verdin, R. Todd Alexander, Catherine M. Clase

Notice bibliographique

RevueCanadian Journal of Kidney Health and Disease · 2022
Typearticle
Langueen
DomaineHealth Professions
ThématiqueMental Health and Patient Involvement
Établissements canadiensMcMaster UniversityImpactUniversity of AlbertaSt. Joseph’s Healthcare HamiltonUniversity of ManitobaUniversity of TorontoKidney Foundation of CanadaUniversity of British ColumbiaUniversity of GuelphUniversity of CalgaryUniversity of Prince Edward IslandUniversity of OttawaMcGill University Health CentreSimon Fraser UniversityOttawa HospitalUniversité Laval
Organismes subventionnairesnon disponible
Mots-clésMedicineMedical educationPeer reviewKidney diseaseFamily medicinePublic relationsPolitical scienceInternal medicine

Résumé

récupéré en direct d'OpenAlex

Purpose of review: The Kidney Research Scientist Core Education and National Training (KRESCENT) is a national Canadian training program for kidney scientists, funded by the Kidney Foundation of Canada (KFOC), the Canadian Institutes of Health Research (CIHR), and the Canadian Society of Nephrology (CSN). We describe our first year of incorporating patient partners into a scientific peer-review committee, the 2017 committee to select senior research trainees and early-career kidney researchers for funding and training, in the hope that it will be helpful to others who wish to integrate the perspective of people with lived experience into the peer-review process. Sources of information: Other peer-review committees, websites, journal articles, patient partners, Kidney Foundation of Canada Research Council, Canadians Seeking Solutions and Innovations to Overcome Chronic Kidney Disease (Can-SOLVE CKD) Patient Council, participants in the 2017 Kidney Foundation of Canada KRESCENT peer-review panel. Methods: We describe our motivation, rationale, guiding principles, plans, feedback, implementation, and response. Key findings: We disseminated a "call for patient partners" 8 weeks before the meeting, seeking patients or their care givers to partner with the KRESCENT peer-review panel; we defined these people with lived experience of kidney disease as patient partners. Eight patient partners came forward and all participated as reviewers. Patient partners first participated in a webinar to learn about the function, structure, and processes of a peer-review committee. They practiced reviewing plain language summaries and giving feedback. In a subsequent teleconference, they shared and discussed their reviews. Plain language summaries were scored, overall, on the same 0-5 quality scale used by scientific reviewers. Three patient reviewers participated in some or all of the 6-hour meeting, which was conducted as usual, for this panel, by teleconference (initially audio only; from 2020 onwards by videoconference). In the meeting, the 2 assigned scientific reviewers first gave their scores, followed by the patient reviewers giving their scores, and discussion (mostly scientific, and conducted in usual scientific language). Scientific reviewers then negotiated a consensus score based on their initial scores, the discussion, patient reviewers' scores and statements, and the scientific officer's notes. Patient reviewers, scientific reviewers, and the Kidney Foundation of Canada (KFOC) were generally positive about the process. The increased length of the meeting (estimated at 1 hour) was generally thought to be acceptable. Patient reviewers also provided feedback on the methods used to incorporate patients into the research under review. These comments were concrete, insightful, and helpful. The patients did not uniformly recommend that basic scientists involve patients in their work. We did not detect bias against preclinical science, work that did not involve patients, or rarer diseases. Some patients found participation inspiring and enlightening. All participants appreciated the idea of patient partners as community witnesses to a group process committed to fairness and supportiveness. We discussed assigning formal meaningful weight to patient reviewers' assessments. Most, but not all, patients thought that the scientific reviewers were ultimately the best judges of the allocation of scarce research resources. Limitations: Patient participants tended to be Caucasian, middle class, and well educated. Because of the difficulties of travel for some people living with or supporting those living with kidney disease, our findings may not generalize fully to peer-review meetings that are conducted face to face. This is explicitly a supportive panel, committed to reviewing junior scientists with kindness as well as rigor; our findings may not generalize to panels conducted differently. We did not use formal qualitative methodology. Implications: Inclusion of patient partners as patient reviewers for the KRESCENT program peer-review panel was feasible, added value for scientific and patient reviewers, and for the funding stakeholders (CIHR, KFOC, and CSN). We were glad that we had taken this step and continue to refine the process with each successive competition.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,498
score de la tête « metaresearch » (Gemma)0,744
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesMétarecherche
DomaineSignal candidat: Évaluation · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,502
Score d'incertitude au seuil0,619

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,4980,744
Méta-épidémiologie (sens strict)0,0010,002
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0030,003
Études des sciences et des technologies0,0220,014
Communication savante0,0210,016
Science ouverte0,0070,024
Intégrité de la recherche0,0080,015
Charge utile insuffisante (le modèle a refusé de juger)0,0080,006

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.

Tête enseignante Opus0,338
Tête enseignante GPT0,423
Écart entre enseignants0,085 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.

Devis d'étudeQualitatif
DomaineÉvaluation
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2022
Routes d'admission2
Résumé présentoui

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