About this trial
In Taiwan, an estimated 2.3 million individuals have diabetes, with a 44% increase observed among young adults and adolescents. Poor dietary habits and sedentary lifestyles are major risk factors for type 2 diabetes. The widespread use of smartphones has facilitated the development of digital health technologies, including digital food photography and artificial intelligence (AI), which show promise for personalized nutrition care and health promotion. While such technologies have demonstrated short-term success in diabetes management, their long-term effectiveness remains uncertain.
This study aims to evaluate the effectiveness of a digital eHealth care intervention for individuals with diabetes. Participants will be recruited from the Diabetes Shared Care Network and community care centers in Taiwan and followed for 12 months. Eligible participants will be randomly assigned by computer to either a control or an eHealth care group.
• eHealth Group: Receives a 10-minute digital nutrition education session using the lab-developed "3D/AR MetaFood food portion education platform" (https://sketchfab.com/susanlab108/collections) and is required to submit weekly dietary records through food images using the "Formosa FoodAPP." Participants will receive immediate dietary feedback from nutritionists, followed by AI-generated personalized feedback on the glycemic index (GI) and glycemic load (GL) of their meals. They will also be provided with educational videos on healthy eating, physical activity, and selecting low-GI/GL foods.
Anthropometric measurements and baseline questionnaires will be collected at enrollment. Blood biochemistry, including HbA1c, will be measured at baseline, and at 3, 6, 9, and 12 months. Collected food image data will be used to train AI systems for real-time dietary feedback and to explore the relationship between nutrient intake and long-term glycemic control.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
20 years old or older
Pre-diabetes or diabetes
Taiwan nationality or fluent in Mandarin or Taiwanese
Not pregnant or breastfeeding
Disqualifiers
Eating disorders
Undergoing treatment for severe illnesses that could affect normal dietary intake (e.g., cancer)
Unable to use a smartphone to take photos and record food intake.
Trial design
Single group
Treatments tested in this trial
Real-Time Personalized Dietary Feedback (via AI and Nutritionist)
Behavioral* Behavioral: "3D/AR MetaFood" Portion Size and Nutrition Education * Behavioral: Nutrition and Physical Activity Educational Videos
conventional nutrition education by dietitian
BehavioralThe participants receive conventional health and nutrition education from state registered dietitian.
Treatment groups
Trial outcomes
Primary outcomes
HbA1c
the change of HbA1c
Fasting glucose
the change of Fasting glucose
Secondary outcomes
Triglyceride (TG)
the change of Triglyceride (TG)
Total cholesterol (TC)
the change of total cholesterol (TC)
Low-density lipoprotein-cholesterol (LDL-C)
the change of low-density lipoprotein-cholesterol (LDL-C)
Triglyceride-glucose (TyG)
the change of triglyceride-glucose (TyG)
Sponsors and contacts
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