Diabetes self-management education (DSME) for older persons in Western countries: A scoping review
Notice bibliographique
Résumé
Diabetes mellitus is a chronic metabolic health condition affecting millions globally. Diabetes is a growing concern among aging societies, with its prevalence increasing among those aged 65 and above. Enabling disease self-management via relevant education is part of high-quality care to improve health outcomes and minimize complications for individuals living with diabetes. Successful diabetes self-management education (DSME) programs usually require tailoring for the intended audience; however, there is limited literature about the preferences of older persons in Western countries concerning DSME. As such, a broad overview of DSME for older persons was an identified need. To map the available evidence on DSME for persons aged 65 years and older in Western countries, the JBI methodology for conducting and reporting scoping reviews was used. In this scoping review, we considered all studies about DSME for older persons with T1D and T2D in Western countries where lifestyles, risks, prevention, treatment of diabetes, and approaches to self-management and DSME are similar (e.g., North America, Western and Northern Europe and Australasia). Systematic keyword and subject heading searches were conducted in 10 databases (e.g., MEDLINE, JBI EBP) to identify relevant English language papers published from 2000 to 2022. Titles and abstracts were screened to select eligible papers for full-text reading. Full-text screening was done by four independent reviewers to select studies for the final analysis. The review identified 2,397 studies, of which 1,250 full texts were screened for eligibility. Of the final 44 papers included in the review, only one included participants' understanding of DSME. The education programs differed in their context, design, delivery mode, theoretical underpinnings, and duration. Type of research designs, outcome measures used to determine the effectiveness of DSME, and knowledge gaps were also detailed. Overall, most interventions were effective and improved clinical and behavioural outcomes. Many of the programs led to improvements in clinical outcomes and participants' quality of life; however, the content needs to be adapted to older persons according to their culture, different degrees of health literacy, preference of education (e.g., individualized or group), preference of setting, degree of frailty and independence, and comorbidities. Few studies included the voices of older persons in the design, implementation, and evaluation of DSME programs. Such experiential knowledge is vital in developing educational programs to ensure alignment with this population's preferred learning styles, literacy levels, culture, and needs-such an approach could manifest more substantive, sustained results.
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 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 | 0,011 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,005 |
| Bibliométrie | 0,013 | 0,016 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».