Feasibility and Effectiveness of an AI-Powered Carbohydrate Counting Educational Platform to Support Parents of Children With Type 1 Diabetes

NCT07671053 | Not Yet Recruiting

• 1 other identifier: SultanQU-PEDU-002
• Study Type: interventional
• Target: 80
• Locations: 2 countries
• Sites: 3

Brief Summary

The goal of this clinical trial is to learn whether an AI-powered carbohydrate counting educational platform can help parents of children with type 1 diabetes improve their carbohydrate counting skills and diabetes management. The study will include parents or primary caregivers of children aged 2-12 years with type 1 diabetes. The main questions it aims to answer are:

• Is the AI-powered educational platform feasible, acceptable, and easy for parents to use?
• Can the platform improve carbohydrate counting accuracy, parental confidence in diabetes management, and diabetes outcomes compared with usual education alone? Researchers will compare parents who receive access to the AI-powered carbohydrate counting educational platform plus usual diabetes education with parents who receive usual diabetes education alone to see whether the AI-supported approach provides additional benefits. Participants will:
• Complete baseline assessments, including questionnaires and a carbohydrate counting test.
• Be randomly assigned to either the AI-supported education group or the usual education group.
• Use the assigned educational resources for 12 weeks.
• Complete a follow-up assessment at 6 weeks and a final assessment at 12 weeks.
• Provide information about their child's diabetes management, including HbA1c and glucose monitoring data.
• Complete questionnaires about confidence, usability, and satisfaction with the educational support they receive. The AI platform is designed to provide educational support only and does not replace medical advice, insulin dosing decisions, or routine diabetes care provided by healthcare professionals.

Conditions

Type 1 Diabetes Mellitus

Keywords

Type 1 Diabetes; Carbohydrate Counting; Artificial Intelligence; AI-Powered Education; Digital Health

Outcome Measures

Primary Outcomes (4)

• Recruitment Rate

  Number and proportion of eligible participants recruited into the study across participating sites.

  12 months

• Retention Rate

  Proportion of enrolled participants who complete the 12-week follow-up assessment.

  12 weeks

• Intervention Adherence

  Proportion of participants in the intervention group who engage with the AI-powered carbohydrate counting educational platform for at least 10 sessions during the study period.

  12 weeks

• Data Completeness

  Proportion of participants with complete primary outcome data collected at baseline and 12-week follow-up assessments.

  12 weeks

Secondary Outcomes (6)

• Acceptability of Intervention Measure

  12 weeks

• System Usability Scale

  12 weeks

• Net Promoter Score

  12 weeks

• Carbohydrate Counting Accuracy

  Baseline and 12 weeks

• Time in Range (70-180 mg/dL)

  Baseline and 12 weeks

Study Arms (2)

AI-Powered Carbohydrate Counting Educational Platform + Enhanced Usual Care

EXPERIMENTAL

Participants receive access to an AI-powered carbohydrate counting educational platform in addition to enhanced usual diabetes care. The platform provides interactive educational support, carbohydrate counting practice, personalized feedback, scenario-based learning, and educational guidance under dietitian and diabetes specialist oversight. Participants also receive standard diabetes education materials and routine clinical care for 12 weeks.

Behavioral: AI-Powered Carbohydrate Counting Educational Platform

Enhanced Usual Care Alone

NO INTERVENTION

Participants receive enhanced usual diabetes care consisting of standard diabetes education provided by their clinical care team, printed carbohydrate counting educational materials, portion size reference materials, educational PDF resources, and routine clinical care. Participants do not receive access to the AI-powered carbohydrate counting educational platform

Interventions

AI-Powered Carbohydrate Counting Educational Platform BEHAVIORAL

Participants will receive access to an AI-powered carbohydrate counting educational platform designed for parents of children with type 1 diabetes. The platform provides interactive carbohydrate counting education, personalized educational guidance, carbohydrate estimation practice, natural-language question answering, and scenario-based learning. Participants will use the platform for 12 weeks in addition to enhanced usual diabetes care. All educational content is developed and supervised by pediatric endocrinologists, certified diabetes educators, and registered dietitians. The platform functions as an educational support tool only and does not provide medical advice or insulin dosing recommendations.

AI-Powered Carbohydrate Counting Educational Platform + Enhanced Usual Care

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• Primary responsibility for carbohydrate counting and insulin dosing decisions for the child
• English-speaking
• Access to a smartphone (iOS or Android) with internet connectivity
• Willing and able to provide informed consent and complete study procedures
• Diagnosis of type 1 diabetes for at least 1 month
• Receiving intensive insulin therapy (multiple daily injections or insulin pump)
• Using carbohydrate counting for insulin dosing

You may not qualify if:

• Child has significant developmental delay or a medical condition that substantially alters nutritional requirements or carbohydrate metabolism (e.g., celiac disease, cystic fibrosis)
• Parent or caregiver has significant cognitive impairment that would preclude participation
• Family plans to relocate from the study area during the study period
• Participation in another diabetes intervention study

Sponsors & Collaborators

• Sultan Qaboos University: lead
• Applied Science Private University: collaborator
• Al Jalila Children's Specialty Hospital: collaborator

Study Sites (3)

Sultan Qaboos University Hospital

Muscat, 123, Oman

Location

Al Jalila Children's Hospital

Dubai, United Arab Emirates

Location

Al Qasimi Hospital

Sharjah city, United Arab Emirates

Location

MeSH Terms

Conditions

Diabetes Mellitus, Type 1

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Autoimmune Diseases; Immune System Diseases

Study Officials

• Moez AlIslam Faris, PhD

  Applied Science Private University

  STUDY CHAIR

Central Study Contacts

Zainab Al-Abadla, BSN, MSc, BC-ADM

CONTACT

00971554001640; Zainab.alabadla@dubaihealth.ae

Hussain Alsaffar, FACE, MSc, FRCPCH

CONTACT

+96896399402; hussaina@squ.edu.om

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Purpose: SUPPORTIVE CARE
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Consultant Pediatric Endocrinologist

Model Details: Participants will be randomized in a 1:1 ratio to either an AI-powered carbohydrate counting educational platform plus enhanced usual care or enhanced usual care alone. The two groups will be followed in parallel for 12 weeks to evaluate feasibility, acceptability, usability, and preliminary effectiveness outcomes

Study Record Dates

• First Submitted: June 22, 2026
• First Posted: June 26, 2026
• Study Start (Estimated): September 1, 2026
• Primary Completion (Estimated): August 31, 2027
• Study Completion (Estimated): December 31, 2027
• Last Updated: June 30, 2026

Record last verified: 2026-06

Data Sharing

• IPD Sharing: Will not share

Locations

OM (1); AE (2)