Function Definition and Clinical Validation of Digital Health App: Using Weight Management as An Example
- Conditions
- Body Fat Rate LossWeight LossBody Composition Change
- Interventions
- Device: "AI Mindful Eating" AppBehavioral: Outpatient regular follow-up
- Registration Number
- NCT06380920
- Lead Sponsor
- National Cheng-Kung University Hospital
- Brief Summary
This project anticipates addressing the obesity epidemics problem which has caused unhealthy lifestyle in billions of obesities and overweight people worldwide. The investigators propose on digital health solution in providing healthcare-on-demand, for personalized health, healthy lifestyle and weight management. This study proposes on using Cognitive Behavior Therapy (CBT) in decreasing individual's food craving, which is administered through AI (Assistive Intelligence) tracking. As with any new medicine, uncertain long-term effects and high costs of these new drugs are also critical factors considered by physicians and policy makers worldwide. Researchers have also reported on 85% of people re-gaining premedication weight after 5 years. There is no easily available self-controlled monitoring strategy/intervention for the unhealthy lifestyle is believed to be one of the main problems. Therefore, the investigators propose on the research and development of self-managing digital health APP (application) for 12 months over two phases, with three months to design APP and nine months to confirm the clinical validation. During the first phase, the investigators propose on design of an "AI Mindful Eating" App, to enhance individual's healthy lifestyle with subsequent weight-loss. Based on "gut-brain-axis", this is anticipated to be achieved by using CBT and AI is used to recognize nutrition and mood within mobile images. This facilitates fulfilling lifestyle and long-term weight-loss. Finally, the study proposes to complete function definition and clinical validation for our AI Humanity APP. By scheduled check-up program by monitoring and analyzing body weight, body fat, anthropometric and metabolic change data between case and control groups. The investigators intend to disclose the effect of the AI assistant APP in weight management and metabolic disease prevention.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- NOT_YET_RECRUITING
- Sex
- All
- Target Recruitment
- 100
- Obese subjects (BMI>= >= 27 kg/m2) with age 18 year-old and less than 65 y/o over will be considered (M/F= 1:1)
- Any history of cancer
- Unstable mental status
- Uncooperative subject
- Complex clinical comorbidities, such as heart failure, end-stage renal disease, etc.
- Severe physical disability
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Arm && Interventions
Group Intervention Description Case Outpatient regular follow-up intervened with App/CBT/MB-EAT groups by a randomized control trial design for 9 months and periodically surveyed as well as 0, 3, and 6 months after intervened Case "AI Mindful Eating" App intervened with App/CBT/MB-EAT groups by a randomized control trial design for 9 months and periodically surveyed as well as 0, 3, and 6 months after intervened Control Outpatient regular follow-up intervened without App/CBT/MB-EAT groups by a randomized control trial design for 9 months and periodically surveyed as well as 0, 3, and 6 months after intervened
- Primary Outcome Measures
Name Time Method weight change 0, 3 and 6 months after intervened Body composition measured by BIA or DXA
- Secondary Outcome Measures
Name Time Method Parameters of Metabolic syndrome 0, 3 and 6 months after intervened Waist circumference was measured at mid-way of abdomen during end-expiratory phase