Prediction of High-risk Populations for Sarcopenia
Conditions
Keywords
artificial intelligence, nursing, nursing guidance mobile application, prediction model, sarcopenia
Brief summary
We evaluated a model for the prediction of high-risk populations for sarcopenia in home settings, developed a sarcopenia nursing guidance mobile application, and assessed the effectiveness of this application in influencing sarcopenia-related knowledge and self-care behavior among participants.
Interventions
DEVICEsarcopenia nursing guidance mobile application was developed
The application enhanced participants' sarcopenia-related knowledge and awareness regarding self-care
Sponsors
National Taipei University of Nursing and Health Sciences
Study design
Observational model
CASE_ONLY
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
20 Years to 80 Years
Healthy volunteers
Yes
Inclusion criteria
were being a member of the public, aged ≥20 years and \<80 years, and having experience using mobile devices or smartphones.
Exclusion criteria
were not belonging to a high-risk population for sarcopenia and/or being unable to use the application platform.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| changes in sarcopenia-related knowledge and awareness regarding self-care | 2019~2022 | In this study, the mobile app significantly improved sarcopenia-related knowledge and awareness regarding self-care among the participants |
Countries
Taiwan
Outcome results
None listed