AI-Made Health Lessons for Older Adults With Muscle Loss and Excess Fat
Tests personalized AI health lessons in older adults with sarcopenic obesity.
Plain-language title generated from the registry record
Registry title: Generative AI-Based Health Education for Older Adults With Sarcopenic Obesity
Key facts
- Where
- Taipei, TaiwanSee the site
AI summary: who the study is looking for
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The trial is looking for community-dwelling adults aged 60 or older with sarcopenic obesity who have a smartphone with internet. They get AI-made health education.
- Age
- 60 years or older (the record also lists a registry range of 50 to 99 years).
- Sex
- All sexes can join.
- Disease stage
- Sarcopenic obesity, defined by a low appendicular fat-free mass (AFFM) calculation (residual of 3.4 or less in the equation).
Main reasons for not taking part
- Functional dependency
- Living in a long-term care facility or hospital
- Serious diagnosed disease, disability or mental health problem needing medical treatment that might affect the study
- Cannot read, listen to and understand the materials, or MMSE score below 25
- No smartphone with internet
Read by machine on 12 November 2026.
Could this be for you?
Answer for yourself. This is not a decision: only the study team can say whether you can take part.
- Are you between 50 and 99 years old?
Source: NCT07782320, who can take part
Where in Taiwan
- Taipei Medical UniversityTaipei, TaiwanContact: Hsin-Yen Yen, PhDNo longer taking part
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Contact the study team: see the registry record → Contacts and Locations
Print a page for my doctorTrial details
- Who runs it
- Taipei Medical University
- Trial code
- NCT07782320
- Record updated
- 24 August 2026
- Original description
Sarcopenic obesity is a major public health concern among community-dwelling older adult populations.Encouraging healthy behavior modification through health education emerges as an effective strategy for preventing and treating sarcopenic obesity. Generative Artificial Intelligence (AI) offers an innovative opportunity to tailor health education for aging populations. This study aims to explore the effectiveness of Personalized AI-generated Multimedia Health Education in community-dwelling older adults with sarcopenic obesity. The study comprises two phases, with 280 participants in Study 1 and 180 in Study 2.Study 1, a cluster randomized controlled trial, explores the feasibility, acceptability, and efficacy of different AI-generated multimedia, including images, sounds, and videos. Study 2 employs a three-armed,individually randomized controlled trial design, creating Personalized AI-generated Multimedia Health Education based on participant preferences. All materials focus on behavioral risk factors, delivered by social media-based AI chatbots. The intervention is conducted once a day, five days a week for 12 weeks.Structured questionnaires and objective instruments collect data before and after the intervention. The study outcome includes behavioral and psychological factors, quality of life, and sarcopenic obesity indicators. Statistical analyses include descriptive analyses, Chi-square tests, t-tests, One-way analysis of variance, path models, and generalized estimating equations. This study anticipates that Personalized AI-generated Multimedia Health Education will be a feasible, acceptable, and effective intervention for older adults. The study results are expected to demonstrate a significant improvement in study outcomes in the experimental group. Personalized AI-generated multimedia health education could be an easy-to-use,enjoyable, and effective strategy for health promotion and sarcopenic obesity prevention.Read full original descriptionShow less
An Exploration of Health-Promoting Effects of Personalized AI-Generated Multimedia Health Education in Community-Dwelling Older Adults With Sarcopenic Obesity
Sarcopenic obesity is a major public health concern among community-dwelling older adult populations.Encouraging healthy behavior modification through health education emerges as an effective strategy for preventing and treating sarcopenic obesity. Generative Artificial Intelligence (AI) offers an innovative opportunity to tailor health education for aging populations. This study aims to explore the effectiveness of Personalized AI-generated Multimedia Health Education in community-dwelling older adults with sarcopenic obesity. The study comprises two phases, with 280 participants in Study 1 and 180 in Study 2.Study 1, a cluster randomized controlled trial, explores the feasibility, acceptability, and efficacy of different AI-generated multimedia, including images, sounds, and videos. Study 2 employs a three-armed,individually randomized controlled trial design, creating Personalized AI-generated Multimedia Health Education based on participant preferences. All materials focus on behavioral risk factors, delivered by social media-based AI chatbots. The intervention is conducted once a day, five days a week for 12 weeks.Structured questionnaires and objective instruments collect data before and after the intervention. The study outcome includes behavioral and psychological factors, quality of life, and sarcopenic obesity indicators. Statistical analyses include descriptive analyses, Chi-square tests, t-tests, One-way analysis of variance, path models, and generalized estimating equations. This study anticipates that Personalized AI-generated Multimedia Health Education will be a feasible, acceptable, and effective intervention for older adults. The study results are expected to demonstrate a significant improvement in study outcomes in the experimental group. Personalized AI-generated multimedia health education could be an easy-to-use,enjoyable, and effective strategy for health promotion and sarcopenic obesity prevention.
Inclusion: . Age: 60 years or older; . Smartphone ownership with internet connectivity; . Appendicular fat-free mass (AFFM) calculated by the equation: AFFM = 14.529 + (17.989 * height)+ (0.1307 * fat mass). The cut-off value corresponds to a residual ≤ 3.4 in the equation; . Ability to read, listen, and understand health education materials with normal cognitive function (MMSE score ≥ 25) and normal sensory function.
Exclusion: . Presence of serious diagnosed diseases, disabilities, or mental health issues requiring medical treatment that might influence the study process; . Functional dependency; . Current residence in long-term care facilities or hospitals.