Function Definition and Clinical Validation of Digital Health App: Using Weight Management as An Example

National Cheng-Kung University

Status: Active, not recruiting

Conditions: Weight Loss; Body Composition Change; Body Fat Rate Loss

Treatments: Device: "AI Mindful Eating" App; Behavioral: Outpatient regular follow-up

Study type: Interventional

Funder types: Other

Identifiers

NCT06380920

Digital Health App

Details and patient eligibility

About

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.

Enrollment: 100 estimated patients

Sex: All

Ages: 18 to 65 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• 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)

Exclusion criteria

• Any history of cancer
• Unstable mental status
• Uncooperative subject
• Complex clinical comorbidities, such as heart failure, end-stage renal disease, etc.
• Severe physical disability

Trial design

Primary purpose: Treatment

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Quadruple Blind

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100 participants in 2 patient groups, including a placebo group

Case

Experimental group

Description:

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

Treatment:

Behavioral: Outpatient regular follow-up

Device: "AI Mindful Eating" App

Control

Placebo Comparator group

Description:

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

Treatment:

Behavioral: Outpatient regular follow-up