Mobilizing the Power of Lived/Living Experiences to Improve Health Outcomes for all
Notice bibliographique
Résumé
INTRODUCTION: Health Equity Assessments (HEAs) are decision-support frameworks or tools used to evaluate the equity impacts of policies, programmes and initiatives. However, HEAs are often conducted without meaningful engagement from the individuals and communities most affected by health inequities. This lack of social participation limits the relevance and effectiveness of HEAs, leaving systemic inequities unaddressed and opportunities for impactful change unrealized. An alternative is to involve people with diverse lived/living experiences in conducting and offering HEAs-so that people most impacted, and most excluded by decision-making can offer recommendations to improve the way they access and utilise care. METHODS: Equity Mobilizing Partnerships in Community (EMPaCT) is a scalable, participatory citizen engagement model that integrates lived/living experiences into the HEA process. EMPaCT's Five Steps to a Community-Engaged Health Equity Assessment (CEn-HEA) was co-designed with community members typically excluded from decision-making. This process fosters psychological safety, trust-building, and power-sharing between underserved communities and decision-makers. The CEn-HEA systematically analyzes inequities across downstream (individual), midstream (community), and upstream (structural) levels to generate actionable, equity-focused recommendations. RESULTS: The EMPaCT CEn-HEA framework produces context-specific recommendations that address immediate project needs while advancing long-term, systemic change. The framework is a participatory process that centres community voices, builds trust, amplifies lived/living expertise, and fosters equity-driven decision-making that can lead to measurable improvements in healthcare policies, programmes, and practices. CONCLUSION: In this paper, we examine the challenges and opportunities associated HEAs; introduce EMPaCT's CEn-HEA framework as a co-designed, innovative, and community-engaged approach to health equity analysis; and discuss methods for measuring and evaluating the health equity impacts of these efforts. PATIENT OR PUBLIC CONTRIBUTION: Patient and community involvement were central to the design, development and implementation of this project and resulting manuscript. Equity Mobilizing Partnerships in Community (EMPaCT), including its Community-Engaged Health Equity Assessment (CEn-HEA) framework, was co-created with diverse patient partners who have lived/living experiences of health inequities. In the preparation of this manuscript, patient partners were involved in codesign sessions to define the focus, structure and language of the manuscript. They collaborated in discussions to refine key concepts, articulate challenges and highlight solutions that are grounded in their lived realities. In the preparation of this manuscript, patient partners reviewed early drafts, contributed feedback to ensure accessibility and relevance of the content and shaped the actionable recommendations. This manuscript reflects EMPaCT's commitment to justice, inclusion and meaningful change.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».