A case study of using community-based consensus methods to facilitate shared decision-making among a spinal cord injury network
Notice bibliographique
Résumé
Spinal cord injury (SCI) research and policy decisions are rarely made in partnership with people with SCI, making them less relevant, applicable, and used by those whom the decisions are intended to support. Across disciplines, consensus methods have been promoted as a viable solution for supporting shared research and policy-based decision-making. In this paper, we describe a partnered approach between academic researchers and the Ontario SCI Alliance, a non-profit, SCI community mobilization network to co-develop and co-disseminate a community-based consensus exercise. The community-based consensus exercise included two modified Delphi surveys and one in-person retreat. The partnership's goal with this exercise was to facilitate shared decision-making for the development of their upcoming strategic plan. We then interviewed partners and participants from the Delphi and in-person retreat to discuss successes, challenges, and lessons learned from the exercise. Survey 1 was disseminated to over 2,500 members of the Ontario SCI community and received 374 responses (276 coming from people with SCI). Survey 2 had 118 responses, with 87 coming from people with SCI. The retreat had 73 attendees, including people with SCI, family/friends of people with SCI, clinicians, researchers, and SCI community and research organization staff/volunteers. The retreat included a presentation of the survey results, a clinician/researcher panel, and externally-facilitated working groups. All survey responses and retreat materials were synthesized. Using the synthesized feedback, the Ontario SCI Alliance was able to implement several changes for the Ontario SCI community, including higher-quality primary care experiences (reduced wait times, more accessible examining rooms), the development of a wound care strategy with the Ontario government, and an advocacy campaign for public coverage for catheters and urinary care supplies. From the five interviews conducted, five themes were co-constructed regarding the successes, challenges, and lessons learned from the exercise: (1) Inclusion, Diversity, Equity, and Accessibility; (2) Partnership; (3) Design Considerations; (4) Transparency and Clarity in Communication; and (5) Sustainability. Findings from this community case study demonstrate the feasibility of conducting a community-level consensus exercise among an equity-deserving group while providing detailed guidance for how to ensure future research and policy-based decision-making is shared across diverse knowledge users.
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 | 0,048 | 0,082 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,033 | 0,012 |
| Communication savante | 0,007 | 0,009 |
| Science ouverte | 0,006 | 0,013 |
| Intégrité de la recherche | 0,007 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».