The Diabetes Connections Initiative: Co-designing models of care for diabetes with First Nations through empowerment, autonomy, and ownership for health
Notice bibliographique
Résumé
Introduction: Diabetes has a high prevalence and high morbidity among First Nations communities, exacerbated by a complex history of intersectional determinants of health, including intergenerational trauma from colonization and structural racism. Thus, our team chose a co-design approach to developing a model of care to help to reorient diabetes care in our region to support community empowerment, autonomy, and ownership. Background: Diabetes has reached a high prevalence with high morbidity among Indigenous people living in Canada today, with a complex history of intersectional determinants of health, including intergenerational trauma from colonization and structural racism at its root. This is exemplified through Indian Residential School experiences of physical and sexual abuse, disconnection from land and traditional lifestyles, and resultant mental health and addictions challenges, as well as the socioeconomic factors of decreased access to adequate and affordable housing, nutrition, education & employment options, and accessible & culturally safe health care. The ‘60’s Scoop’ and overrepresentation in child welfare and justice systems have also resulted in further family separation. Ongoing colonization and marginalization also play a critical role, as many interventions aimed at Indigenous communities fail due to limitations of Western health system structures to adapt and respond to the cultural contexts of Indigenous people. Objectives: The purpose of our work is to improve diabetes prevention and treatment for First Nations communities in the Sioux Lookout area by strengthening the capacity at a local level to help achieve a shared vision of “community-empowered diabetes care that is wholistic and sustainable”. We do this in partnership with community members, leaders, local health authorities, and health care providers, as well as provincial government and academic collaborators. Methods: Our team co-created the Diabetes Connections Initiative, an integrated, evidence-based, customized, community-owned model of diabetes care and support, which we are scaling up implementation among 33 on-reserve First Nations communities in the Sioux Lookout area in Northwestern Ontario (population ~40,000). Our approach to developing the model of care prioritized collaborative community engagement, which centres on building reciprocal trust, maintaining relationships over time, and consistent open dialogue. Results: Our model of care includes four strategic areas: 1) Supporting community health workers to have the capacity to assist with the delivery of diabetes prevention and care close to people’s own homes as valued members of a primary health care team; 2) Improving the quality of care throughout a person’s life course with a focus on trauma-informed and culturally-appropriate care; 3) Enhancing integration of health information systems and community-relevant data sharing to support evidence based decision making; and 4) Increasing community ownership through integrated knowledge translation. Conclusion: This approach to co-developing a model of care, which includes collaborative community engagement at its core, has potential to have great impact on not just diabetes, but also for addressing other chronic conditions including cardiovascular disease, cancer, and reproductive health, especially where access to care is limited through geographic, sociocultural and socioeconomic, or other structural barriers.
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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 | 0,021 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,005 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,003 | 0,013 |
| Intégrité de la recherche | 0,001 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».