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Status unknownNCT05363033Updated May 5, 2022

Evaluation of a Sarcopenia Prediction Model and Development and Effectiveness of a Nursing Guidance Mobile App

An observational study in Prediction of High-risk Populations for Sarcopenia, sponsored by National Taipei University of Nursing and Health Sciences. Status unknown at 1 site in Taiwan. Open to participants aged 20 Years to 80 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2022-05-05.

Sponsored by National Taipei University of Nursing and Health Sciences · Observational

The sponsor has not verified this record recently (last verified May 2022), so the status shown — last known as Enrolling by invitation — may be out of date.
Study type
Observational
Model
Case-only
Time perspective
Prospective
Enrollment
120
Ages
20 Years to 80 Years
Sex
All
01

Study 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.

02

Conditions studied

  • Prediction of High-risk Populations for Sarcopenia

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Keywords

  • artificial intelligence, nursing, nursing guidance mobile application, prediction model, sarcopenia
03

In context

Sarcopenia

1,240 studies on the registry are indexed under Sarcopenia; 405 are open to participants now.

This study's planned enrollment of 120 is close to the median of 120 across 433 observational studies indexed under Sarcopenia.

Browse Sarcopenia studies →

Lead sponsor

National Taipei University of Nursing and Health Sciences is the lead sponsor of 123 studies on the registry; 23 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
20 Years to 80 Years
Sexes eligible
All
Accepts healthy volunteers
Yes
Sampling method
Non-probability sample

Study population

We adopted the convenient sampling method to recruit 120 participants-those who visited the hospital regularly and their accompanying family members

Eligibility criteria

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.

05

Study design

Observational model
Case-only
Time perspective
Prospective
Enrollment
120 participants (estimated)
Patient registry
No

Groups and cohorts

  • one group

    Using a one-group pretest-posttest design

    Device: sarcopenia nursing guidance mobile application was developed

Interventions

  • Devicesarcopenia nursing guidance mobile application was developed

    The application enhanced participants' sarcopenia-related knowledge and awareness regarding self-care

06

What researchers measure

Primary outcomes

  1. changes in sarcopenia-related knowledge and awareness regarding self-care

    In this study, the mobile app significantly improved sarcopenia-related knowledge and awareness regarding self-care among the participants

    Time frame: 2019~2022

07

Study locations

1 site
  • Cheng Hsin General Hospital
    Taipei County, 112, Taiwan
08

References and documents

Publications

  • Liao PH, Huang YJ, Ho CS, Chu W. Application of machine learning and its effects on the development of a nursing guidance mobile app for sarcopenia. BMC Nurs. 2023 Oct 9;22(1):369. doi: 10.1186/s12912-023-01545-w. PubMed 37814285 ↗

Individual participant data

Plan to share: Undecided

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on May 5, 2022, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT05363033
Responsible party
Pei-Hung Liao (Assistant Professor, National Taipei University of Nursing and Health Sciences) — Principal investigator
First posted
May 5, 2022
Start date
Jul 1, 2019
Primary completion
Dec 2022 (estimated)
Completion
Dec 2022 (estimated)
Last update
May 5, 2022

Oversight

FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is status unknown, as verified in May 2022. You cannot join it, but the record below documents what was studied.

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