Using an AI-assisted tool to predict the behavior of children with type 1 diabetes for optimal use of sensor technology in Oman
| ISRCTN | ISRCTN15827616 |
|---|---|
| DOI | https://doi.org/10.1186/ISRCTN15827616 |
- Submission date
- 03/04/2025
- Registration date
- 22/04/2025
- Last edited
- 22/04/2025
- Recruitment status
- Not yet recruiting
- Overall study status
- Ongoing
- Condition category
- Nutritional, Metabolic, Endocrine
Plain English summary of protocol
Background and study aims
This pilot study investigates the effectiveness of the OMNIdiasense, an AI-assisted assessment tool, designed to predict and enhance adherence to continuous glucose monitor (CGM) use among children (under 18 years of age) with type 1 diabetes mellitus (T1DM) in Oman. Building on prior research highlighting AI's role in improving self-management and glycemic control, the study aims to develop and evaluate predictive models that generate personalized behavioral insights and adherence strategies to optimize diabetes care.
Who can participate?
Children diagnosed with T1DM in Oman, including CGM sub-users identified from previous formative studies and newly recruited participants.
What does the study involve?
Two groups of participants will be recruited. The first group (Questi-experimental study) will involve existing children with T1DM identified as CGMs sub-optimizers from formative cross-sectional studies who will be assigned to use the OMNIdiasense tool before reintroducing CGMs, with tailored motivational interviewing (MI)-based consultations provided at baseline, 3, and 6 months. The second group involves new prospective participants who will be randomly allocated to either the intervention or control groups. The intervention group will use the OMNIdiasense tool before applying the CGMs with MI-based consultations provided at baseline, 3, and 6 months. The control group will continue standard CGM use without the OMNIdiasense tool. All participants from both studies will be monitored over one year with follow-ups at 6 and 12 months. The study also involves predictive model development using machine learning, training sessions for healthcare teams, and real-time feedback mechanisms.
What are the possible benefits and risks of participating?
Benefits include improved adherence to CGMs, personalized diabetes management, and potential enhancement in glycemic control and quality of life. Risks are minimal and primarily pertain to data privacy and standard risks associated with CGM use.
Where is the study run from?
The study is coordinated from Muscat, Oman, involving regional polyclinics and diabetes care providers.
When is the study starting and how long will it run?
February 2025 to May 2027
Who is funding the study?
Ministry of Higher Education, Research and Innovation, Oman
Who is the main contact?
Dr Thamra Said Al Ghafri, t.alghafri@squ.edu.om
Contact information
Public, Scientific, Principal Investigator
Ministry of Health Sultanate of Oman
P O box
Muscat
113
Oman
 ORCID ID |
0000-0002-4818-9565 |
|---|---|
| Phone | +968-99376455 |
| t.alghafri@squ.edu.om |
Study information
| Study design | Quasi-experimental single-arm pilot followed by a randomized controlled trial |
|---|---|
| Primary study design | Interventional |
| Secondary study design | Randomised controlled trial |
| Study setting(s) | GP practice, Hospital, Medical and other records |
| Study type | Prevention, Screening |
| Participant information sheet | Not available in web format, please use the contact details to request a participant information sheet |
| Scientific title | Utilizing an AI-assisted tool to predict the behavior of children with type 1 diabetes for optimal use of sensor technology in Oman: a multi-phase translational research project Effectiveness of an AI-assisted assessment tool (the OMNIdiasense) to predict the behavior of adherence to CGMs use in children with T1DM in Oman: A pilot study |
| Study objectives | A newly developed AI-assisted tool is effective in predicting the behavior of children with type 1 diabetes in adhering to the use of the continuous glucose monitors |
| Ethics approval(s) |
Approved 12/02/2025, Health Studies and Research Approval Committee (HSRAC) Ministry of Health, Sultanate of Oman (P O Box 393, Muscat, PC 100, Oman; +968-22357280; admin@mohcsr.gov.om), ref: MoH/CSR/25/29506 |
| Health condition(s) or problem(s) studied | Improve the glycemic control and quality of life for children with type 1 diabetes |
| Intervention | The phases/sub-studies associated with this project as background are: Sub-study 1: The characteristics of children with T1DM who received the CGMs in Oman (data from the Al Shifa system). All children who received CGMS from July 2024 to February 2025 will be included (n=1500). Data on their glycemic control will be compared at least 3 months from baseline. Sub-study 2: Correlates of adherence to Continuous Use of CGMs in Children with T1DM in Oman: A Mixed-Design Study Based on face-to-face interviews with randomly selected children of T1DM (10-18 years of age from Sub-study 1). Demographic, psycho-social, dietary and physical activity factors influencing their CGMs use will be identified. Results from this study will inform the development of a smart AI tool that can predict the behaviour/adherence to CGMs. This study relates to the pilot and randomised controlled trial below: Sub-study 3: Effectiveness of an AI-assisted assessment tool in predicting adherence to CGMs in children with T1DM in Muscat. Two approaches will be used to test the effectiveness of the AI-predictive tool. First, a quasi-experimental (single-arm) study will be conducted on 100 children with T1DM from Phase 2, identified as CGM sub-users. These children will be randomly selected using random number generation in SPSS to ensure unbiased allocation of participants, and the OMNIdiasense will be used prior to the reintroduction of CGMs. Simultaneously, another group of 50 children will be recruited across the regions of Oman. Of these, 25 will be randomized to undergo the OMNIdiasense assessment to predict their adherence to CGMs, while the remaining 25 (control group) will receive CGMs as usual care without exposure to the assessment tool. Scores from the AI tool will determine the accompanied intervention (face-to-face consultations guided by motivational interviewing methods at baseline, 3 months and 6 months) to improve compliance with the use of CGMs. Scores will be reassessed at 6 and 12 months and compared to the baseline scores. All recruited children (both intervention and control groups) will be followed for one year and assessed at 6-month and 12-month follow-ups. |
| Intervention type | Behavioural |
| Primary outcome measure | Effectiveness of the AI-assisted tool to predict the optimal use of CGMs in children with T1DM measured using 1. (OMNIdiasense) scores at baseline, 3, 6, and 12 months 2. Recordings from the CGMs at baseline, 3, 6, and 12 months 3. Motivational interviewing-guided behavior change consultations at baseline, 6 and 12 months |
| Secondary outcome measures | The following variables were assessed using data collected from a study questionnaire at baseline: 1. Demographic characteristics 2. Medical history of the disease 3. Family history of DM and type 4. History of co-morbidities The following variables were assessed using data collected from patient health information records at baseline, 6 and 12 months follow-up: 1. Drug/treatment history 2. Anthropometric measures: Weight, BMI 3. Blood pressure 4. Cholesterol testing, liver function tests (LFT), and renal function tests (RFT) 5. HbA1c |
| Overall study start date | 12/02/2025 |
| Completion date | 01/05/2027 |
Eligibility
| Participant type(s) | Patient |
|---|---|
| Age group | Child |
| Lower age limit | 1 Year |
| Upper age limit | 18 Years |
| Sex | Both |
| Target number of participants | 1500 |
| Key inclusion criteria | All children with type 1 diabetes willing to participate |
| Key exclusion criteria | Refusal to participate |
| Date of first enrolment | 01/12/2025 |
| Date of final enrolment | 01/05/2026 |
Locations
Countries of recruitment
- Oman
Study participating centre
Muscat
113
Oman
Sponsor information
Government
P O box
Muscat
113
Oman
| Website | https://www.mohcsr.gov.om/ |
|---|
Funders
Funder type
Government
Government organisation / National government
- Alternative name(s)
- Ministry of Higher Education - Oman, Oman Ministry of Higher Education, Research and Innovation, Oman, Ministry of Higher Education, Research and Innovation, Minister for Higher Education, Research and Innovation, Ministry of Higher Education, Research and Innovation of the Sultanate of Oman, وزارة التعليم العالي, MoHERI
- Location
- Oman
Results and Publications
| Intention to publish date | 15/12/2027 |
|---|---|
| Individual participant data (IPD) Intention to share | Yes |
| IPD sharing plan summary | Available on request |
| Publication and dissemination plan | Planned publication in a peer-reviewed journal |
| IPD sharing plan | The datasets generated during and/or analysed during the current study will be available upon request to the PI, Dr Thamra Alghafri, thamra74@yahoo.com, t.alghafri@squ.edu.om, and official approval from the Ministry of Health, Oman. • The type of data that will be shared: The Type of data will include characteristics of participants and measures of adherence to CGMs. • Timing for availability: December 2027 • Whether consent from participants was required and obtained: Consent is required from the participants and is included in the consent form • Comments on data anonymization: All data will be anonymized, which means personal details like name or contact information will not be included, instead, participant will be coded according to their regions and health institutes. • Any ethical or legal restrictions: Ethical approval was obtained. This is a low risk study with no major ethical or legal restrictions expected. • Any additional comments: None |
Editorial Notes
22/04/2025: Study's existence confirmed by the Health Studies and Research Approval Committee (HSRAC), Ministry of Health, Sultanate of Oman.
