Innovative Approaches in Diabetes Care

Study Overview
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Brief Summary
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It is estimated that 2.3 million Taiwanese have diabetes and there is a 44% increased rate among young adults and adolescents. Poor dietary habits and sedentary lifestyle are the major risk factors for type 2 diabetes. The growing availability of smartphones has boosted the development of new technologies that incorporate the use of digital food photography as health promotion and individualized nutrition care. Digital health technology is also used to prevent and treat diabetes with good degree of successes in the short term but the long term effect remains unknown. The broad aim of this study is to evaluate the effectiveness of digital technology eHealth care for diabetic patients. A total of 300 diabetic patients will be recruited from Diabetes Shared Care Network and community care center in Taiwan and follow up 12 months. A simple randomization by computer system will be used to randomly allocate subjects into 2 groups: control group and eHealth care. The control group (n=100) of diabetic patients will receive conventional health and nutrition education from state registered dietitian. The eHealth care group (n=200) of diabetic patients will receive a 10 mins of food portion size nutrition education using  3D/AR MetaFood platform and is required to record their consume meal by food image once a week using Taiwan FoodAPP. Patients in the eHealth group will receive instant feedback from the nutritionists or artificial intelligence (AI) for the information of glycemic index (GI) and glycemic load (GL), and educational video related to healthy eating or how to select GI/GL food. Anthropometry, and baseline questionnaires will be collected at baseline. Blood biochemistry (e.g. HbA1c) and body weight will be collected at baseline, 3, 6, 9, and 12 months. The collected food image data will be used for AI training to identify the relationship between the patient's diet and blood glucose changes over time.

Official Title
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Innovative Approaches in Diabetes Care

Conditions
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M-health, Diabetes Mellitus, Mobile Application, Dietary Assessment

Intervention / Treatment
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* Behavioral: 3D/AR MetaFood  nutrition education, and receive instant feedback from the nutritionists or AI after recording their dietary food image.
* Behavioral: conventional nutrition education by dietitian


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: ≧20 years old pre-diabetes or diabetes Taiwan nationality or people who can speak Chinese fluently Currently not pregnant or breastfeeding Available to use smartphone to take photos and record food Exclusion Criteria: Eating disorders

Ages Eligible for Study
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Minimum Age: 20 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Supportive Care
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: eHealth care group<br>The eHealth group will receive instant feedback from the nutritionists and/or AI after recording their dietary food image, and receive 3D/AR MetaFood food portion and nutrition education. | Behavioral: 3D/AR MetaFood  nutrition education, and receive instant feedback from the nutritionists or AI after recording their dietary food image.<br>* The participants record diet images by using Taiwan FoodAPP and receive instant feedback from the nutritionists or AI after recording their dietary food image. The dietitian will use 3D/AR MetaFood food nutrition education platform to do nutrition education for patients.<br>|
| Experimental: control group<br>The control receive conventional health and nutrition education from state registered dietitian. | Behavioral: conventional nutrition education by dietitian<br>* The participants receive conventional health and nutrition education from state registered dietitian.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| HbA1c | the change of HbA1c | baseline, 3 month, 6 month, 9 month, 12 month | 
| Fasting glucose | the change of Fasting glucose | baseline, 3 month, 6 month, 9 month, 12 month | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Body mass index (kg/m2) | the change of Body mass index | baseline, 3 month, 6 month, 9 month, 12 month | 
| body weight | the change of body weight | baseline, 3 month, 6 month, 9 month, 12 month | 
| Triglyceride (TG) | the change of Triglyceride (TG) | baseline, 3 month, 6 month, 9 month, 12 month |