Generative AI-Based Health Education for Older Adults With Sarcopenic Obesity

August 20, 2026 updated by: Taipei Medical University

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.

Study Overview

Study Type

Interventional

Enrollment (Estimated)

500

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

  • Name: Hsin-Yen Yen, PhD
  • Phone Number: 27749 886-2-2736-1661
  • Email: kenji@tmu.edu.tw

Study Locations

      • Taipei, Taiwan, 110
        • Taipei Medical University
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  1. . Age: 60 years or older
  2. . Smartphone ownership with internet connectivity
  3. . 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
  4. . Ability to read, listen, and understand health education materials with normal cognitive function (MMSE score ≥ 25) and normal sensory function.

Exclusion Criteria:

  1. . Functional dependency
  2. . Current residence in long-term care facilities or hospitals
  3. . Presence of serious diagnosed diseases, disabilities, or mental health issues requiring medical treatment that might influence the study process.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Prevention
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
No Intervention: No Intervention
Active Comparator: Generative Artificial Intelligence (AI)-based text materials
Participants receive a text message regarding the health education topic.
Experimental: Generative AI-based video materials
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.
Experimental: Generative AI-based images materials
Participants receive one Gen-AI-generated image concerning the health education topic, formatted as a health poster.
Experimental: Generative AI-based voice materials
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.
No Intervention: Comparator Group
Experimental: Non-Personalized Gen-AI MHE
Participants receive non-personalized multimodal health education generated by generative AI.
Experimental: Personalized Gen-AI MHE
Participants receive personalized multimodal health education tailored through generative AI.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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).
Baseline, midpoint (the 6th week), and post-intervention (the 13rd 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.
Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
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.
Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
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.
Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
The Health-Promoting Lifestyle Profile II
Time Frame: Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)
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).
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)
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.
Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

October 1, 2026

Primary Completion (Estimated)

December 31, 2029

Study Completion (Estimated)

December 31, 2029

Study Registration Dates

First Submitted

August 16, 2026

First Submitted That Met QC Criteria

August 20, 2026

First Posted (Actual)

August 24, 2026

Study Record Updates

Last Update Posted (Actual)

August 24, 2026

Last Update Submitted That Met QC Criteria

August 20, 2026

Last Verified

January 1, 2026

More Information

Terms related to this study

Other Study ID Numbers

  • N202404120

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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