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Innovative Approaches in Diabetes Care

NCT05687968 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 39

Last updated 2025-07-30

No results posted yet for this study

Summary

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.

Conditions

Interventions

BEHAVIORAL

Real-Time Personalized Dietary Feedback (via AI and Nutritionist)

* Behavioral: "3D/AR MetaFood" Portion Size and Nutrition Education * Behavioral: Nutrition and Physical Activity Educational Videos

BEHAVIORAL

conventional nutrition education by dietitian

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

Sponsors & Collaborators

  • Taipei Medical University

    lead OTHER

Principal Investigators

  • Jung-Su Chang, PhD. · College of Nutrition, Taipei Medical University

Study Design

Allocation
NA
Purpose
SUPPORTIVE_CARE
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
20 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-10-19
Primary Completion
2025-10-01
Completion
2025-10-01

Countries

  • Taiwan

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05687968 on ClinicalTrials.gov