Best Evidence Summary for Management of Older People With Type 2 Diabetes Mellitus Using ‘Internet Plus Nursing Services’
Notice bibliographique
Résumé
AIM: To evaluate and summarise the evidence for the management of older people with Type 2 diabetes mellitus (T2DM) using 'Internet Plus nursing services (IPNS)'. DESIGN: This study was conducted as an evidence summary, adhering strictly to the evidence summary reporting standards established by Fudan University Center for Evidence-based Nursing. METHODS: We systematically searched for the best available evidence pertaining to the management of older people with T2DM using the IPNS. The literature types encompassed clinical guidelines, expert consensuses, systematic reviews, evidence summaries and original research studies. DATA SOURCES: In order to gather pertinent information, we conducted a comprehensive search across various databases, including UpToDate, BMJ Best Practice, Joanna Briggs Institute, Guidelines International Network, National Institute for Health and Care Excellence, Registered Nurses Association of Ontario, Scottish Intercollegiate Guidelines Network, the Cochrane Library, PubMed, Web of Science, Yi Maitong Guidelines Network, SinoMed, CNKI, WanFang database, Chinese Biomedical Literature Database and China Science and Technology Journal Database. The search spanned from the inception of each database up to July 2023, ensuring an extensive coverage of relevant resources. RESULT: After rigorous screening and evaluation, our study ultimately identified 19 articles with high-quality research outcomes. These articles consisted of three guidelines, two expert consensus documents, three systematic reviews and eleven original research studies. Through collaborative and in-depth discussions, we extracted and synthesised 27 pieces of evidence related to the application of the IPNS to enhance the T2DM management for older people. We categorised the evidence into five primary themes: mobile terminal design, team building, health education design, interaction and social support, and information feedback. CONCLUSION: In designing the IPNS for older people with T2DM, utmost attention should be paid to the intricacies of Internet module development preceded by comprehensive guidance. It is imperative to establish multidisciplinary teams to oversee the curation of patient educational content, ensuring its relevance and effectiveness. Leveraging Internet-based information feedback mechanisms is crucial for fostering peer support, assisting in blood glucose control, enhancing self-management capabilities and ultimately improving overall quality of life. Healthcare professionals are supposed to customise the IPNS for this vulnerable population, taking into account institutional resources and local contextual realities. FOR THE PROFESSIONAL FIELD AND PATIENT CARE IMPLICATIONS: It is highly recommended that clinical medical personnel worldwide adhere to the evidence-based recommendations for better care of older people with T2DM using the IPNS. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution was incorporated in this study. IMPLICATIONS FOR PRACTICE: Our study provides structured ideas for the application of IPNS in T2DM management, provides practicable new ways for IPNS to improve self-management of older people with T2DM, and encourages the provision of Internet-based nursing services based on the needs and characteristics of older people, and jointly solves the challenges of T2DM management in order to enhance the effectiveness of nursing services.
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 | 0,020 | 0,087 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,009 |
| Bibliométrie | 0,018 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,005 | 0,003 |
| 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 ».