Prediction of High-risk Populations for SarcopeniaNCT05363033
Evaluation of a Sarcopenia Prediction Model and Development and Effectiveness of a Nursing Guidance Mobile App
An observational study of Prediction of High-risk Populations for Sarcopenia, run by National Taipei University of Nursing and Health Sciences at 1 site in Taiwan.
Trial 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. Read more about this study
- Who is it for?
- Ages 20 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Prediction of High-risk Populations for Sarcopenia
- What is being tested?
- sarcopenia nursing guidance mobile application was developed
- Type of treatment
- Medical device
- How many people
- 120 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Jul 2019to Dec 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: We adopted the convenient sampling method to recruit 120 participants-those who visited the hospital regularly and their accompanying family members
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.
Trial locations and contacts
1 site in 1 country.
About this study
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.
- Being tested
- sarcopenia nursing guidance mobile application was developed
- Keywords
- artificial intelligence, nursing, nursing guidance mobile application, prediction model, sarcopenia
- Medical subject headings
- Sarcopenia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
sarcopenia nursing guidance mobile application was developedDevice
The application enhanced participants' sarcopenia-related knowledge and awareness regarding self-care
| Study group | Role | What they receive |
|---|---|---|
| one group | Using a one-group pretest-posttest design Receives: Device: sarcopenia nursing guidance mobile application was developed |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: 2019~2022
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 May 2022
- Study start1 Jul 2019
- Primary completionDec 2022 (estimated)
- Study completionDec 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Prediction of High-risk Populations for SarcopeniaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 120 participants (estimated)
Sponsor and investigators
- Lead sponsor
- National Taipei University of Nursing and Health Sciences
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Pei-Hung Liao, National Taipei University of Nursing and Health Sciences
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05363033
- Sponsor's protocol ID
- 108A-06
- Status last verified
- May 2022
- First submitted
- 2 May 2022
- Last updated
- 5 May 2022
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
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
Study at a glance
From the registry record, last updated by the sponsor on 5 May 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of a Sarcopenia Prediction Model and Development and Effectiveness of a Nursing Guidance Mobile App
- ClinicalTrials.gov ID
- NCT05363033
- Acronym / sponsor ID
- 108A-06
- Keywords
- artificial intelligence, nursing, nursing guidance mobile application, prediction model, sarcopenia
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 120 participants (estimated)
- Lead sponsor
- National Taipei University of Nursing and Health SciencesUniversity, hospital or other
- Study start
- 1 Jul 2019 (actual)
- Primary completion
- Dec 2022 (estimated)
- Study completion
- Dec 2022 (estimated)
- First posted
- 5 May 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| one group | – | Device: sarcopenia nursing guidance mobile application was developedUsing a one-group pretest-posttest design |
Who may qualify
- Ages
- 20 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- We adopted the convenient sampling method to recruit 120 participants-those who visited the hospital regularly and their accompanying family members
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| sarcopenia nursing guidance mobile application was developedThe application enhanced participants' sarcopenia-related knowledge and awareness regarding self-care | Device | one group |
Primary outcome
changes in sarcopenia-related knowledge and awareness regarding self-care
Time frame: 2019~2022
In this study, the mobile app significantly improved sarcopenia-related knowledge and awareness regarding self-care among the participants
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 May 2022.
- Derived from this study: PubMed 37814285Liao 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.
- Individual participant dataSharing planned: Undecided
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Prediction of High-risk Populations for Sarcopenia, run by National Taipei University of Nursing and Health Sciences at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 5 May 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
changes in sarcopenia-related knowledge and awareness regarding self-care (time frame: 2019~2022). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05363033, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 May 2022.