Clinical trial NCT06380920: Function Definition and Clinical Validation of Digital Health App: Using Weight Management as An Example
Official title: Function Definition and Clinical Validation of Digital Health App: Using Weight Management as An Example
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Weight Loss
Body Fat Rate Loss
Body Composition Change
Keywords: obesity
assistive intelligence
APP
weight control
cognitive behavior therapy
Lead sponsor: National Cheng-Kung University Hospital
Sponsor class: OTHER
First posted: 2024-04-24
Enrollment: 100
Sex: ALL
Minimum age (years): 18
Maximum age (years): 65
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: TREATMENT

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.


Eligibility criteria: 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

Primary outcomes:
measure: weight change
timeFrame: 0, 3 and 6 months after intervened
Secondary outcomes:
measure: Parameters of Metabolic syndrome
timeFrame: 0, 3 and 6 months after intervened
Other outcomes:
Locations:
Study officials:
affiliation: Department of Family Medicine, National Cheng Kung Univ Hosp
name: Chih-Hsing Wu, MD
role: STUDY_DIRECTOR
References: