Innovative Approaches in Diabetes Care

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age20+
SponsorTaipei Medical University

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 volunteers

Qualifiers

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

Design model

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

    Behavioral

    The participants receive conventional health and nutrition education from state registered dietitian.

Treatment groups

39 Participants
are divided into 1 treatment group
Group A: eHealth groupExperimental treatment 2 interventions

Trial outcomes

Primary outcomes

1

HbA1c

the change of HbA1c

Time frame
baseline, 3 month, 6 month, 9 month, 12 month
2

Fasting glucose

the change of Fasting glucose

Time frame
baseline, 3 month, 6 month, 9 month, 12 month

Secondary outcomes

1

Triglyceride (TG)

the change of Triglyceride (TG)

Time frame
baseline, 3 month, 6 month, 9 month, 12 month
2

Total cholesterol (TC)

the change of total cholesterol (TC)

Time frame
baseline, 3 month, 6 month, 9 month, 12 month
3

Low-density lipoprotein-cholesterol (LDL-C)

the change of low-density lipoprotein-cholesterol (LDL-C)

Time frame
baseline, 3 month, 6 month, 9 month, 12 month
4

Triglyceride-glucose (TyG)

the change of triglyceride-glucose (TyG)

Time frame
baseline, 3 month, 6 month, 9 month, 12 month

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.