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

NCT06380920 | Active Not Recruiting

• 1 other identifier: Digital Health App
• Study Type: interventional
• Target: 100
• Locations: 1 country
• Sites: 1

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.

Conditions

Weight Loss; Body Fat Rate Loss; Body Composition Change

Keywords

obesity; assistive intelligence; APP; weight control; cognitive behavior therapy

Outcome Measures

Primary Outcomes (1)

• weight change

  Body composition measured by BIA or DXA

  0, 3 and 6 months after intervened

Secondary Outcomes (1)

• Parameters of Metabolic syndrome

  0, 3 and 6 months after intervened

Study Arms (2)

Case

EXPERIMENTAL

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

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

Control

PLACEBO COMPARATOR

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

Behavioral: Outpatient regular follow-up

Interventions

"AI Mindful Eating" App DEVICE

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, in place of medication, to alleviate food addiction and proper nutrition intake during proper metabolic conditions and time, which are coordinated via AI.

Case

Outpatient regular follow-up BEHAVIORAL

Outpatient regular follow-up

Case; Control

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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)

You may not qualify if:

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

Sponsors & Collaborators

• National Cheng-Kung University Hospital: lead

Study Sites (1)

National Cheng Kung University Hospital

Tainan, Taiwan

Location

MeSH Terms

Conditions

Weight Loss; Obesity

Condition Hierarchy (Ancestors)

Body Weight Changes; Body Weight; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Overweight; Overnutrition; Nutrition Disorders; Nutritional and Metabolic Diseases

Study Officials

• Chih-Hsing Wu, MD

  Department of Family Medicine, National Cheng Kung Univ Hosp

  STUDY DIRECTOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: QUADRUPLE
• Who Masked: PARTICIPANT, CARE PROVIDER, INVESTIGATOR, OUTCOMES ASSESSOR
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: April 18, 2024
• First Posted: April 24, 2024
• Study Start: November 20, 2024
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: January 29, 2026

Record last verified: 2025-05

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)