Engaging Everyone: Co-building diverse and inclusive patient partnerships to promote health equity.
Notice bibliographique
Résumé
Background: To address the challenge of engaging diverse people, discover a novel model of engagement where diverse members of community bring a health equity lens to healthcare projects, policies and research. Workshop description: This workshop is designed to introduce participants to challenges and opportunities in diverse patient engagement. Participants will learn about the Equity-Mobilizing Partnerships in Community (EMPaCT) model. Through group discussions, participants will explore how they can adapt the EMPaCT approach to their own settings. Through tools and resources developed by EMPaCT, participants will learn how to co-design sustainable and scalable models of patient engagement to promote health equity. In particular, participants will learn about: 1.Conceptual frameworks that make explicit the relationships between social, political and economic inequities and health outcomes; 2.Strategies to involve communities experiencing the most inequities in policy and decision-making; and 3.Methods to design programs that are scalable. Intended audience: Anyone who is: 1.interested in learning how to engage in patient partnerships that promote health equity; 2.interested in engaging with diverse and seldom-heard communities for practice, research or policy development; 3.involved in system-level healthcare redesign and resourcing. Workshop overview & agenda (90 mins workshop) 1.Introductions (10 mins) – Alies, Ambreen, Emily 2.Section: Getting to know the audience (10 mins ) – Emily Approach: Interactive polls. Responses reviewed in real-time. Outcome: Understand which stakeholder category participants identify with and their experiences in patient engagement including engagement with diverse voices as well as level of decision-making authority. 3.Section: Introduction to the challenges and opportunities in diverse patient engagement and the need for scalable equity-oriented patient partnerships (10 mins) – Ambreen Approach: Presentation by workshop facilitators. Outcome: Participants will have foundational knowledge needed to engage in interactive workshop. 4.Section: Identifying and using conceptual frameworks that recognize how health inequities drive health outcomes (15 mins) – Emily Approach: Overview of frameworks and interactive discussion using Padlet-based questions. Outcome: Participants will engage in learning and discussion about health and social inequities. 5.Section: Involving communities experiencing the most inequities in policy and decision-making (15 mins) – Alies Approach: Facilitators will share how EMPaCT was co-designed using an equity-oriented lens to patient engagement. Participants will learn how to apply the same lens to their setting using interactive group discussion through Padlet. Outcome: Participants will learn about different ways to involve communities experiencing the most inequities in policy and decision-making. 6.Section: Designing programs that are scalable and sustainable (15 mins) – Ambreen Approach: Facilitators will share how EMPaCT was co-developed as a scalable unit. Participants will engage in interactive discussions through Padlet to identify the resources available to them to co-create a scalable unit in their setting. Outcome: Participants will learn about different ways to scale and sustain patient engagement activities that promote health equity. 7.Closing summary (15 mins) – Alies
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 | 0,025 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,008 | 0,005 |
| Communication savante | 0,008 | 0,012 |
| Science ouverte | 0,003 | 0,030 |
| Intégrité de la recherche | 0,006 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,028 | 0,006 |
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.
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 ».