Effectiveness of digital health exercise interventions on muscle function and physical performance in older adults with possible, confirmed or severe sarcopenia: a protocol for a systematic review.


Journal

BMJ open
ISSN: 2044-6055
Titre abrégé: BMJ Open
Pays: England
ID NLM: 101552874

Informations de publication

Date de publication:
21 Oct 2024
Historique:
medline: 22 10 2024
pubmed: 22 10 2024
entrez: 21 10 2024
Statut: epublish

Résumé

Sarcopenia is characterised by the progressive weakening of muscle function that occurs with age. This condition frequently leads to frailty, disability and even death. Research on sarcopenia prevention is growing. Digital health exercise interventions are increasingly gaining attention in this field, with the rapid advancement of the internet and the influence of the COVID-19. However, there is a lack of empirical support for their effectiveness. Our study aims to assess the effect of digital health exercise intervention on sarcopenia in older persons, specifically focusing on its ability to improve muscle strength, muscle mass and physical performance. Searching will be performed in the following 11 databases (Medline, Embase, Cochrane Central Register of Controlled Trials, CINAHL, PsycINFO, WOS, Scopus, CBM, CNKI, WANFANG and VIP) for published trials and 2 trial registries (ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform) for unpublished trials. Google Scholar will be used to find grey literature. The criterion of inclusion will be clinical trials involving digital health exercise interventions in older adults (≥60 years) diagnosed with sarcopenia (possible, confirmed or severe sarcopenia). For data synthesis, we will use a summary table to show the major characteristics of selected trials and a summary graph to demonstrate the risk of bias for each outcome using RoB 2, which will be further discussed in a narrative synthesis. The possibility of meta-analysis for quantitative data will be assessed according to the homogeneity analysis of the trials, using the methods of fixed or random effects model. If meta-analysis is possible, subgroup analysis and sensitivity analysis will be performed as well. Publication bias will be assessed through the use of the funnel plot and Egger's linear regression test when an adequate number of trials are available. Finally, the Grading of Recommendations, Assessment, Development and Evaluation approach will be used to classify the certainty of evidence body into four categories (high, moderate, low and very low). The findings of the systematic review will be shared through publishing in a peer-reviewed journal and presentation at appropriate conferences. Since we will not be using specific patient data, ethical approval is unnecessary. CRD42024516930.

Identifiants

pubmed: 39433420
pii: bmjopen-2024-086124
doi: 10.1136/bmjopen-2024-086124
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e086124

Informations de copyright

© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

Auteurs

Ya Shi (Y)

School of Health Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK ya.shi@postgrad.manchester.ac.uk.
School of Nursing & School of Public Health, Yangzhou University, Yangzhou, Jiangsu province, China.

Emma Stanmore (E)

School of Health Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK.
Manchester Academic Health Science Centre, Manchester, UK.
Manchester University NHS Foundation Trust, Manchester, UK.

Lisa McGarrigle (L)

School of Health Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK.
Manchester Academic Health Science Centre, Manchester, UK.

Chris Todd (C)

School of Health Sciences, Faculty of Biology, Medicine & Health, The University of Manchester, Manchester, UK.
Manchester Academic Health Science Centre, Manchester, UK.
Manchester University NHS Foundation Trust, Manchester, UK.

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