Generative AI-Based Health Education for Older Adults With Sarcopenic Obesity
ConditionSarcopenic Obesity
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age50-99
SponsorTaipei Medical University
About this trial
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.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
. 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.
Disqualifiers
. 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 design
Design model
Parallel
Treatments tested in this trial
Generative AI-based text materials
BehavioralParticipants receive a text message regarding the health education topic.
Generative AI-based video materials
BehavioralParticipants 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 materials
BehavioralParticipants receive one Gen-AI-generated image concerning the health education topic, formatted as a health poster.
Generative AI-based voice materials
BehavioralParticipants 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 MHE
BehavioralParticipants receive non-personalized multimodal health education generated by generative AI.
Personalized Gen-AI MHE
BehavioralParticipants receive personalized multimodal health education tailored through generative AI.
Treatment groups
500 Participants
are divided into 8 treatment groups8
Treatment groupsSee each treatment group below.
Group A: No InterventionNo intervention 0 interventions
Group B: Generative Artificial Intelligence (AI)-based text materialsActive comparator 1 intervention
Group C: Generative AI-based video materialsExperimental treatment 1 intervention
Group D: Generative AI-based images materialsExperimental treatment 1 intervention
Group E: Generative AI-based voice materialsExperimental treatment 1 intervention
Group F: Comparator GroupNo intervention 0 interventions
Group G: Non-Personalized Gen-AI MHEExperimental treatment 1 intervention
Group H: Personalized Gen-AI MHEExperimental treatment 1 intervention
Trial outcomes
Primary outcomes
1
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).
Time frame
Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)2
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.
Time frame
Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)3
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.
Time frame
Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)4
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.
Time frame
Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)Secondary outcomes
1
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).
Time frame
Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)2
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.
Time frame
Baseline, midpoint (the 6th week), and post-intervention (the 13rd week)Sponsors and contacts
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Source ClinicalTrials.gov
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