Sarcopenic ObesityNCT07782320
Generative AI-Based Health Education for Older Adults With Sarcopenic Obesity
A study testing Generative AI-based text materials, Generative AI-based video materials and Generative AI-based images materials in people with Sarcopenic Obesity, run by Taipei Medical University at 1 site in Taiwan.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 50 to 99 yearsHealthy volunteers can take part
- Conditions the study is for
- Sarcopenic Obesity
- What is being tested?
- Generative AI-based text materials, Generative AI-based video materials and Generative AI-based images materials
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 500 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Oct 2026to 31 Dec 2029
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 50 to 99 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- . 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.
Who cannot join
- . Functional dependency
- . Current residence in long-term care facilities or hospitals
- . Presence of serious diagnosed diseases, disabilities, or mental health issues requiring medical treatment that might influence the study process.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Taiwan1 site
Taipei Medical University
Taipei, 110
Hsin-Yen Yen, PhD, 886-2-2736-166 ext. 27749, kenji@tmu.edu.tw
About this study
Official title: 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.
- Conditions
- Sarcopenic Obesity
- Being tested
- Generative AI-based text materials, Generative AI-based video materials, Generative AI-based images materials, Generative AI-based voice materials, Non-Personalized Gen-AI MHE
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Generative AI-based text materialsBehavioural
Participants receive a text message regarding the health education topic.
Generative AI-based video materialsBehavioural
Participants receive a video message , accompanied by AI-generated background music at the beginning and end. Male avatars are used for PA and SO education, and female avatars are used for HD education.
Generative AI-based images materialsBehavioural
Participants receive one Gen-AI-generated image concerning the health education topic, formatted as a health poster.
Generative AI-based voice materialsBehavioural
Participants receive a podcast-style voice message regarding the health education topic. The recording incorporates AI-generated background voice. Male voices are utilized for physical activity (PA) education, while female voices are used for healthy diet (HD) and sarcopenic obesity (SO) education.
Non-Personalized Gen-AI MHEBehavioural
Participants receive non-personalized multimodal health education generated by generative AI.
Personalized Gen-AI MHEBehavioural
Participants receive personalized multimodal health education tailored through generative AI.
| Study group | Role | What they receive |
|---|---|---|
| No Intervention | No intervention | Not described |
| Generative Artificial Intelligence (AI)-based text materials | Active comparator | Not described Receives: Behavioral: Generative AI-based text materials |
| Generative AI-based video materials | Experimental | Not described Receives: Behavioral: Generative AI-based video materials |
| Generative AI-based images materials | Experimental | Not described Receives: Behavioral: Generative AI-based images materials |
| Generative AI-based voice materials | Experimental | Not described Receives: Behavioral: Generative AI-based voice materials |
| Comparator Group | No intervention | Not described |
| Non-Personalized Gen-AI MHE | Experimental | Not described Receives: Behavioral: Non-Personalized Gen-AI MHE |
| Personalized Gen-AI MHE | Experimental | Not described Receives: Behavioral: Personalized Gen-AI MHE |
What is being measured
The primary outcome is the main question the study is designed to answer.
The Chinese version of the Physical Activity Scale for the Elderly
This questionnaire consists of 12 items assessing physical activity (PA) over the past 7 days, including leisure-time, household, and occupational activities. Total, light-, moderate-, and vigorous-intensity PA can be calculated in metabolic equivalents of task-minutes per week (MET-min/week).
Measured: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
General Dietary Behavior Inventory
A total of 16 items measure participants' healthy behaviors using a 5-point bipolar scale.The score of each item is summed up to a total score, with a higher score representing healthier dietary behavior.
Measured: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
The skeletal muscle index (SMI)
A body composition analyzer using bioelectrical impedance analysis technology is conducted. A higher score (kg/m2) of the skeletal muscle index (SMI) indicates greater muscle mass for sarcopenic indicators.
Measured: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
Muscle Strength
Muscle strength is assessed using a handheld grip device (SANKA, Japan). Participants are asked to stand, allow the wrist and arm of the dominant hand to hang straight down, and maintain maximum strength for more than 3 seconds. This measurement is repeated three times, and the maximum value (kg) is used as the muscle strength.
Measured: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
Secondary outcomes (2)
The Health-Promoting Lifestyle Profile II
The Health-Promoting Lifestyle Profile II consists of 29 items measuring participants' engagement in healthy lifestyles. A 4-point Likert scale is used (1 never, 2 sometimes, 3 frequently, and 4 regularly).
Measured: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
World Health Organization (WHO)- Quality of Life Scale
A shorter version with 28 questions. The scale evaluates various aspects of life, including physical health, psychological state, social relationships, and environmental factors, scored between 1 and 5.
Measured: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Aug 2026
- Study start1 Oct 2026 (estimated)
- Primary completion31 Dec 2029 (estimated)
- Study completion31 Dec 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Sarcopenic ObesityStudies 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Taipei Medical University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07782320
- Sponsor's protocol ID
- N202404120
- Status last verified
- Jan 2026
- First submitted
- 16 Aug 2026
- Last updated
- 24 Aug 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 24 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- An Exploration of Health-Promoting Effects of Personalized AI-Generated Multimedia Health Education in Community-Dwelling Older Adults With Sarcopenic Obesity
- ClinicalTrials.gov ID
- NCT07782320
- Acronym / sponsor ID
- N202404120
- Conditions
- Sarcopenic Obesity
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 500 participants (estimated)
- Lead sponsor
- Taipei Medical UniversityUniversity, hospital or other
- Study start
- 1 Oct 2026 (estimated)
- Primary completion
- 31 Dec 2029 (estimated)
- Study completion
- 31 Dec 2029 (estimated)
- First posted
- 24 Aug 2026 (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.
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.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 8
| Arm | Type | Receives |
|---|---|---|
| No Intervention | No intervention | – |
| Generative Artificial Intelligence (AI)-based text materials | Active comparator | Behavioral: Generative AI-based text materials |
| Generative AI-based video materials | Experimental | Behavioral: Generative AI-based video materials |
| Generative AI-based images materials | Experimental | Behavioral: Generative AI-based images materials |
| Generative AI-based voice materials | Experimental | Behavioral: Generative AI-based voice materials |
| Comparator Group | No intervention | – |
| Non-Personalized Gen-AI MHE | Experimental | Behavioral: Non-Personalized Gen-AI MHE |
| Personalized Gen-AI MHE | Experimental | Behavioral: Personalized Gen-AI MHE |
Who may qualify
- Ages
- 50 to 99 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- . 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.
Key exclusion criteria (3 listed)
- . Functional dependency
- . Current residence in long-term care facilities or hospitals
- . Presence of serious diagnosed diseases, disabilities, or mental health issues requiring medical treatment that might influence the study process.
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 |
|---|---|---|
| Generative AI-based text materialsParticipants receive a text message regarding the health education topic. | Behavioural | Generative Artificial Intelligence (AI)-based text materials |
| Generative AI-based video materialsParticipants receive a video message , accompanied by AI-generated background music at the beginning and end. Male avatars are used for PA and SO education, and female avatars are used for HD education. | Behavioural | Generative AI-based video materials |
| Generative AI-based images materialsParticipants receive one Gen-AI-generated image concerning the health education topic, formatted as a health poster. | Behavioural | Generative AI-based images materials |
| Generative AI-based voice materialsParticipants receive a podcast-style voice message regarding the health education topic. The recording incorporates AI-generated background voice. Male voices are utilized for physical activity (PA) education, while female voices are used for healthy diet (HD) and sarcopenic obesity (SO) education. | Behavioural | Generative AI-based voice materials |
| Non-Personalized Gen-AI MHEParticipants receive non-personalized multimodal health education generated by generative AI. | Behavioural | Non-Personalized Gen-AI MHE |
| Personalized Gen-AI MHEParticipants receive personalized multimodal health education tailored through generative AI. | Behavioural | Personalized Gen-AI MHE |
Primary outcome
The Chinese version of the Physical Activity Scale for the Elderly
Time frame: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
This questionnaire consists of 12 items assessing physical activity (PA) over the past 7 days, including leisure-time, household, and occupational activities. Total, light-, moderate-, and vigorous-intensity PA can be calculated in metabolic equivalents of task-minutes per week (MET-min/week).
General Dietary Behavior Inventory
Time frame: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
A total of 16 items measure participants' healthy behaviors using a 5-point bipolar scale.The score of each item is summed up to a total score, with a higher score representing healthier dietary behavior.
The skeletal muscle index (SMI)
Time frame: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
A body composition analyzer using bioelectrical impedance analysis technology is conducted. A higher score (kg/m2) of the skeletal muscle index (SMI) indicates greater muscle mass for sarcopenic indicators.
Muscle Strength
Time frame: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
Muscle strength is assessed using a handheld grip device (SANKA, Japan). Participants are asked to stand, allow the wrist and arm of the dominant hand to hang straight down, and maintain maximum strength for more than 3 seconds. This measurement is repeated three times, and the maximum value (kg) is used as the muscle strength.
2 secondary outcomes
The Health-Promoting Lifestyle Profile II
Time frame: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
World Health Organization (WHO)- Quality of Life Scale
Time frame: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Aug 2026.
Related trials for Sarcopenic Obesity
Not yet recruiting
Effects of the EatWelLog App on Enhancing Diet Management for Older Adults With Sarcopenic Obesity
Sacropenic Obesity
RecruitingObservational study
GLP-1 Receptor Agonist Use and Sarcopenia in Obese Individuals Without Diabetes
Obesity, Sarcopenia
Enrolling by invitation
Whole-body Vibration Training on the Elderly With Combined Bilateral Knee Osteoarthritis
Knee OA, Sarcopenic Obesity
Active, not recruiting
The Effect of Acupuncture on Sarcopenia and Obesity in Patients With Sarcopenic Obesity.
Sarcopenic Obesity, Acupuncture Treatment
RecruitingPhase 4
GLP-1R Actions on Muscle and the Skeleton
Musculoskeletal Abnormalities, Obesity
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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Generative AI-based text materials, Generative AI-based video materials and Generative AI-based images materials in people with Sarcopenic Obesity, run by Taipei Medical University 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?
The sponsor lists 4 inclusion and 3 exclusion criteria. 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: opening soon, as of the sponsor's last update on 24 Aug 2026. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Hsin-Yen Yen, PhD (886-2-2736-1661 ext. 27749, kenji@tmu.edu.tw), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The Chinese version of the Physical Activity Scale for the Elderly (time frame: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 24 Aug 2026.