NCT06783907

Technological-based Personalized Care Intervention for Supporting Older People With Diabetes Mellitus

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 60 (actual)
• Sponsor: Hong Kong Metropolitan University · Academic / Other
• Sex: All
• Age: 60 Years
• Healthy volunteers: Not accepted

Summary

The objectives of this project are (1) to develop a new model of DM management using non-invasive healthcare technology for continuous glucose monitoring; (2) to use health apps to give timely personalized care intervention for enhancing compliance rate of DM self-management; \& (3) to compare the DM management using non-invasive healthcare technology to traditional invasive blood glucose monitoring method. The proposed study will adopt a RCT with two treatment arms to clarify the effects of non-invasive blood glucose device on blood glucose monitoring. The two arms will be the non-invasive blood glucose monitoring (arm 1) and traditional self-monitoring (arm 2) as a control. A block randomisation and a single-blind design will be used. The inclusion criteria are (1) aged ≥ 60 years old; (2) patients diagnosed with Type II DM; (3) patients experienced hypo (histix \< 4.0 mmol/L) or hyperglycemia (histix ≥16.0 mmol/L); \& (iv) the Abbreviated Mental Test (AMT) ≥ 6. Participants fitting the inclusion criteria will be selected by convenience sampling. They will join a two-arm RCT and will be allocated into the intervention or control group in a 1:1 ratio. The primary outcomes will be the point of care test (POCT) of HbA1C level and the secondary outcomes will be the fasting blood glucose, total cholesterol, blood pressure, basic anthropometric measurement, breath and blood ketone and Diabetes Self-Care activities questionnaire. The outcome measurements will be recorded before the intervention (T0) and immediately after the 8-week intervention (T1). The required sample size would be 30 participants per group (with a ratio of 1:1) for testing the feasibility of the study.

Detailed description

Research aim 1\. This study will aim to develop a new model of DM management using non- invasive healthcare technology for continuous glucose monitoring. 2 To use health apps to give timely personalized care intervention for enhancing compliance rate of DM self-management. 3. To compare the DM management using non-invasive healthcare technology to traditional invasive blood glucose monitoring method. 4. To improve self-management skills, decrease hospital admissions, and save medical. Our DM project integrates personalized care intervention with a non-invasive continuous glucose monitoring (CGM) device for diabetes patients. The use of mHealth (Mobile health) ensures timely care without time or location constraints, while Just-in-Time Adaptive Intervention (JITAI) provides instant, personalized support. The painless, non-invasive CGM device offers an alternative to traditional finger-prick methods, improving compliance with self-management. This approach is particularly beneficial for patients who struggle with conventional monitoring and aims to enhance both patient outcomes and healthcare efficiency, especially for older people at high risk of hypo- or hyperglycemia.

Conditions

• Diabetes Mellitus

Interventions

Type	Name	Description
BEHAVIORAL	Non-invasive blood glucose monitoring	Non-invasive wearable glucose monitoring device for capturing participants' blood glucose. The intervention will include: 1. Training for self-management of diabetes and phone consultation. 2. Follow-up through phone calls or WhatsApp for hypoglycaemic or hyperglycaemic events. 3. Personalized care guided by sensor data. The Investigator will monitor the health data from the device regularly. A mobile app will track and record compliance with blood glucose monitoring.
BEHAVIORAL	Traditional blood glucose monitoring	Traditional blood glucose monitoring Participants will engage in traditional self-monitoring of blood glucose at home over the course of 8 weeks. They are recommended to check their blood glucose levels one to two times per week and record all results. This will allow for the collection of data using traditional monitoring methods.

Timeline

• Start date: 2023-12-01
• Primary completion: 2025-06-10
• Completion: 2025-06-10
• First posted: 2025-01-20
• Last updated: 2025-09-11

Locations

1 site across 1 country: Hong Kong