MétaCan
Menu
Retour à la cohorte
Enregistrement W4390956991 · doi:10.5334/ijic.icic23237

Assessing the Scalability of a Community-Based Self-Management Intervention for Older Adults with Diabetes and other Chronic Conditions – The Aging, Community and Health Research Unit Community Partnership Program (ACHRU-CPP)

2023· article· en· W4390956991 sur OpenAlexaffabout
Melissa Northwood, Maureen Markle‐Reid, Rebecca Ganann, Kathryn Fisher

Notice bibliographique

RevueInternational Journal of Integrated Care · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueDiabetes Management and Education
Établissements canadiensMcMaster UniversityHamilton Health Sciences
Organismes subventionnairesnon disponible
Mots-clésMedicineNursingGeneral partnershipAging in placeIntervention (counseling)Integrated careCommunity healthGerontologyHealth carePublic health

Résumé

récupéré en direct d'OpenAlex

Background: A multi-pronged approach was undertaken to assess the scalability of the Aging, Community and Health Research Unit – Community Partnership Program (ACHRU-CPP), a complex, integrated 6-month self-management program for community-living older adults with diabetes and multimorbidity and their caregivers, in two Canadian provinces. The ACHRU-CPP was co-designed by patients, caregivers, home and community-care providers, and researchers, in response to a gap identified by older adults in the self-management of their diabetes and other conditions. The intervention was tested in a feasibility study and an earlier pragmatic trial found that older adults who received the ACHRU-CPP experienced greater improvements in quality of life and self-management, and greater reduction in depressive symptoms, compared to those who received usual diabetes care, at no additional cost to society. Delivered by a collaborative team of primary care providers (registered nurses, registered dietitians) and a community program coordinator, key components include home visits, group wellness sessions, team-based case conferences, caregiver support, interprofessional collaboration, and nurse-led care coordination. Scalability assessment is an integral phase of the current research program, which evaluated the effectiveness and implementation of the ACHRU-CPP in four settings in Ontario (ON) and Prince Edward Island (PEI). Methods: Multiple methods were used to assess scalability of the ACHRU-CPP in ON and PEI: an environmental scan, individual key informant interviews, and qualitative and quantitative data from both the foundational studies and the current trial of ACHRU-CPP implementation and effectiveness. The Intervention Scalability Assessment Tool (ISAT) guided data collection and analysis. The environmental scan was conducted with strategic input from Scalability Working Groups in ON and PEI. These groups were comprised of members of the program’s governance structure, including patient and public research partners, researchers, primary care and community service providers and administrators, and policy- and decision-makers. These partners advised on relevant research and policy documents, identified potential key informants (i.e., policy- and decision-makers at the local, provincial, and national levels), and will participate in scalability assessment workshops in ON and PEI in late 2022, to finalize the scalability assessment, and identify components of the intervention to be strengthened, and barriers to be addressed to enhance the scalability of the program, in each province. Results: To date, the results of the scalability assessment have identified areas of strength and limitations within the program, most notably issues with health human resources, mixed results regarding the effectiveness of the program, and other resource gaps. Conclusion: This study has evaluated the scalability of a community-based program for older adults with diabetes and multiple chronic conditions that integrates primary and community care. It also provides valuable insight on the usefulness and feasibility of the ISAT for assessing scalability, as well as strategies to engage strategic practice, policy, and public partners in the process. Next steps: While scale-up of the ACHRU-CPP may be merited due to the prevalence of diabetes and multimorbidity among older adults, and alignment of this program with health policy, several barriers need to be addressed before scale-up can be recommended.

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)0,007
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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,333
Score d'incertitude au seuil0,612

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0070,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
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 Opus0,124
Tête enseignante GPT0,466
Écart entre enseignants0,343 · 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

Citations2
Publié2023
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueInternational Journal of Integrated CareMême sujetDiabetes Management and EducationTravaux en français237 207