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Enregistrement W4411501273 · doi:10.3389/ijph.2025.1607763

Empowering Indigenous Health: A Call for Equity and Innovation in Public Health

2025· editorial· en· W4411501273 sur OpenAlexaboutno aff
Nurul Athirah Naserrudin, Pauline Yong Pau Lin

Notice bibliographique

RevueInternational Journal of Public Health · 2025
Typeeditorial
Langueen
DomaineSocial Sciences
ThématiqueIndigenous Health, Education, and Rights
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPublic healthHealth equityIndigenousEquity (law)BusinessEnvironmental healthHealth promotionPublic relationsMedicineNursingPolitical science

Résumé

récupéré en direct d'OpenAlex

The WHO's Sustainable Development Goals and the Global Roadmap for Healthy Longevity emphasise diversity, equity, and inclusivity (DEI) in public health strategies (1). Governments must offer tailored, sustainable solutions to health inequities while building resilience (2). For indigenous populations, which disproportionately face health inequity, DEI depends on integrating participatory approaches, traditional knowledge, and equitable policies into public health initiatives, centering the voices and experiences of indigenous communities.In participatory approaches such as Community-Based Participatory Research (CBPR) and citizen science, indigenous populations are actively involved in shaping and implementing health interventions. CBPR focuses communities on the issues they identify and promotes shared decision-making and co-creation throughout the research process (2). In citizen science, researchers often define questions, and community members collect and help analyse data, creating opportunities for ownership, collaboration, and inter-generational knowledge exchange (3). Indigenous participation ensures that health initiatives are inclusive, culturally relevant, meet community needs, and align with community values and priorities. For example, in Canada, the Outdoor Adventure Leadership Experience Incorporating traditional knowledge into public health strategies can enhance cultural relevance, community trust and effectiveness. Indigenous elders, healers, and midwives, hold a wealth of knowledge about culturally grounded practices, kinship systems, and intergenerational caregiving that are important to community well-being (5) Systematic reviews have highlighted the potential for such knowledge systems to improve health outcomes when integrated through respectful, reciprocal, and community-led processes (6). Traditional midwifery has improved safe childbirth practices in many indigenous settings, demonstrating how culturally tailored practices can complement modern healthcare systems (5). Structured mechanisms, such as advisory platforms that include indigenous representatives, capacity-building programs for health professionals and policymakers, and equitable resource allocation, can facilitate the integration of traditional knowledge into formal health systems (6).Despite their potential, these approaches face barriers. Policymakers often lack an understanding of the cultural practices central to indigenous health, and the process of standardising diverse traditional practices remains a complex challenge (9). Overcoming these barriers requires consistent dialogue between indigenous communities and stakeholders, developing collaboration through mutual respect and shared goals. Collaborative platforms that document and disseminate traditional practices can help policymakers appreciate their value, enhancing their visibility and utility in health systems, while piloting programs for the evaluation and refinement of culturally appropriate interventions before scaling nationally (9). Improving community health infrastructure plays an important role in tackling health inequalities. Services such as mobile clinics, telehealth, access to clean water, and financial support have shown positive outcomes in reaching underserved populations (3)(4)6). For ageing Indigenous communities, especially during health emergencies like the COVID-19 pandemic, healthcare must be shaped by local knowledge and cultural practices. In countries like the United States, Canada, and Australia, indigenous groups experienced greater risks due to long-standing structural barriers and a lack of culturally safe services. Despite these challenges, many communities took action through their own systems of care, highlighting the value of indigenous leadership and decision-making (7). Building trust, ensuring cultural safety, and involving local leaders have been shown to support better ageing experiences. Creating person-centred, community-based health systems that draw on indigenous knowledge and involve local health workers is one way to reduce ongoing service gaps (10). These examples point to the importance of healthcare models that are culturally relevant, fair, and led by the communities they aim to serve.The evidence highlights that achieving healthy longevity for indigenous populations requires a shift toward holistic models of care that incorporate participatory methods, respect traditional knowledge and are guided by equityfocused policies. These strategies address immediate health needs and contribute to building resilient health systems capable of supporting indigenous communities through future challenges. By prioritising collaboration, equitable resource allocation, and culturally sensitive practices, public health professionals and policymakers can create inclusive health systems that support healthier, more fulfilling lives for indigenous populations as they age. Sustained commitment to these approaches will ensure that public health initiatives are effective, equitable, and reflective of the unique needs of indigenous communities.

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)0,068
score de la tête « metaresearch » (Gemma)0,051
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,068
Score d'incertitude au seuil0,360

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0680,051
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0030,002
Études des sciences et des technologies0,0090,036
Communication savante0,0160,027
Science ouverte0,0060,038
Intégrité de la recherche0,0190,020
Charge utile insuffisante (le modèle a refusé de juger)0,0180,002

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 Opus0,095
Tête enseignante GPT0,475
Écart entre enseignants0,380 · 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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

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

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

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