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Enregistrement W4411426729 · doi:10.1016/j.ard.2025.05.359

OP0357-HPR A Syndemic Care Model for the Management of Rheumatic and Musculoskeletal Diseases in Indigenous Maya-Yucatec Populations: A Mixed-Methods Study

2025· article· en· W4411426729 sur OpenAlexaff
Cinthya Cadena-Trejo, E. Motte Garcia, Alfonso Gastelum‐Strozzi, Adalberto Loyola‐Sánchez, N. Facio-Escalona, V. Fernández-García, J.F. Moctezuma, Arturo Recabarren Lozada, David López Aguilar, Kenia Nayrobi López-Herrera, P. Loeza-Magaña, Hugo Laviada‐Molina, Ingris Peláez‐Ballestas

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueMusculoskeletal Disorders and Rehabilitation
Établissements canadiensAlberta HealthAlberta Health Services
Organismes subventionnairesnon disponible
Mots-clésMedicineSyndemicIndigenousFamily medicineTraditional medicineHuman immunodeficiency virus (HIV)

Résumé

récupéré en direct d'OpenAlex

Background: Rheumatic and Musculoskeletal Diseases (RMSDs) in the Maya-Yucatec population generate a syndemic when interacting with the most common Non-Communicable Chronic Diseases (NCDs), such as diabetes, hypertension, and obesity, leading to disability and a decrease in quality of life. A syndemic refers to the negative synergy between two or more diseases within an unfavorable context, resulting in worst health outcomes. The Syndemic Care Model (SCM) is an intervention designed to address the syndemia between RMSDs and NCDs, considering the structural factors that hinder adequate healthcare for marginalized populations. Using a Community-Based Participatory Research (CBPR) strategy, partnerships are established between researchers, communities, and authorities to address specific health needs. Objectives: To co-design and Syndemic Care Model in collaboration with the community to address health needs related to the syndemic produced by the interaction between RMSDs and NCDs. Methods: A parallel-convergent mixed-methods study following the phases of CBPR in three Maya-Yucatec communities. The quantitative component was a cross-sectional study, and the qualitative component was an ethnographic study. Phase 1: Census using the COPCORD methodology to identify RMSDs/NCDs. The following questionnaires were administered: HAQ-Di, EuroQoL 5D-3L, and service utilization, all validated in Maya and Spanish. Semi-structured interviews with patients and healthcare professionals and ethnographic records/field notes were made. Phase 2: Identifying and prioritizing health needs with community leaders and patients. Quantitative analysis: descriptive analysis of continuous and categorical variables using RStudio 4.4.2. Qualitative analysis: inductive coding using Atlas.ti and thematic analysis. The project was approved by the Ethics and Research Committee of the General Hospital of Mexico (DI/23/404-B/05/22). Results: A total of 508 people participated in the census, 69% were women, with an average age of 49 years; 53% reported being homemakers. 42% of participants were from Xkalakdzonot, 33% from Xcopteil, and the rest from Yaxunah. The prevalence of RMSDs was 8%. Eleven patients with RMSDs and six healthcare professionals were interviewed. Two focus groups, multiple community assemblies, and meetings with health and municipal authorities were conducted to strengthen collaborations. Barriers and facilitators to accessing healthcare services were identified, and the health needs expressed by the communities were prioritized (see Table 1). Based on the findings, the elements of the SCM were established, including, 1) building connections between local and regional healthcare systems to address NCDs, 2) collaborating with the municipality for the provision of medications and transportation, 3) caring for RMSDs through rheumatology and rehabilitation consultations in each community, and 4) educating to address and prevent NCDs complications (see Figure 1). Conclusion: We co-designed a culturally sensitive SCM through the implementation of a mixed methods research study that allowed us to identify and prioritize the health needs of the participant Mayan Communities. Therefore, we anticipate that the future implementation of this model will result in improved health outcomes for those living with RMSDs/NCDs. REFERENCES: [1] Singer M, Bulled N, Ostrach B, Mendenhall E. Syndemics and the biosocial conception of health. The Lancet. 2017;389(10072):941-950. [2] Ramírez-Flores MF, Cadena-Trejo C, Motte-García E, Juárez-Cruz ID, Fernández-García MF, Gastelum-Strozzi A, et al. A Mixed-Methods Systematic Review on Syndemics in Rheumatology. J Clin Rheumatol. 2023 Apr 1;29(3):113-1. Acknowledgements: Partial funding from the Marista University of Merida. CONAHCYT (CVU 671018 and CVU1145201). Disclosure of Interests: None declared . © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,783
Score d'incertitude au seuil0,505

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,030
Tête enseignante GPT0,412
Écart entre enseignants0,382 · 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 tête enseignante, pas un consensus.

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

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

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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Même revueAnnals of the Rheumatic DiseasesMême sujetMusculoskeletal Disorders and RehabilitationTravaux en français237 207