Technological-based Personalized Care Intervention for Supporting Older People With Diabetes Mellitus
NCT ID: NCT06783907
Last Updated: 2025-09-11
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
60 participants
INTERVENTIONAL
2023-12-01
2025-06-10
Brief Summary
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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.
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Detailed Description
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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
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Study Design
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RANDOMIZED
PARALLEL
HEALTH_SERVICES_RESEARCH
NONE
Study Groups
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Non invasive blood glucose monitoring group
Non invasive blood glucose monitoring : Participants will use a non-invasive sensor on the arm for blood glucose monitoring during the first and second weeks, as well as the seventh and eighth weeks. Between the third and sixth weeks, participants will be asked to monitor their blood glucose levels at home using traditional methods.
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.
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.
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.
Interventions
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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.
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.
Eligibility Criteria
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Inclusion Criteria
2. patients diagnosed with Type II DM without insulin injections;
3. patients experienced hypo (histix \< 4.0 mmol/L) or hyperglycemia (histix
* 16.0 mmol/L); \&
2\. The Abbreviated Mental Test (AMT) ≥ 6.
Exclusion Criteria
2. taking ascorbic acid \> 500mg daily or (Not recommended by manufacturer as result may be affected);
3. taking salicylic acid ≥ 650mg single dose or (Not recommended by manufacturer as result may be affected); or
4. scheduled radiological therapy during CGM application (Not recommended by manufacturer as result may be affected).
60 Years
ALL
No
Sponsors
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Hong Kong Metropolitan University
OTHER
Responsible Party
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Dr Queenie Law Pui Sze
Associate Professor
Locations
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LEI FOOK Neighbourhood Elderly Centre
Hong Kong, , Hong Kong
Countries
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References
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Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, Colagiuri S, Guariguata L, Motala AA, Ogurtsova K, Shaw JE, Bright D, Williams R; IDF Diabetes Atlas Committee. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2019 Nov;157:107843. doi: 10.1016/j.diabres.2019.107843. Epub 2019 Sep 10.
2. World Health Organization. (2016). Global Report on Diabetes. In World Health Organization (Vol. 978). https://doi.org/ISBN 978 92 4 156525 7
3. Centre for Health Protection. (2017). Report of Population Health Survey 2014/2015.
Wang L, Miller LC. Just-in-the-Moment Adaptive Interventions (JITAI): A Meta-Analytical Review. Health Commun. 2020 Nov;35(12):1531-1544. doi: 10.1080/10410236.2019.1652388. Epub 2019 Sep 5.
Goldstein SP, Zhang F, Klasnja P, Hoover A, Wing RR, Thomas JG. Optimizing a Just-in-Time Adaptive Intervention to Improve Dietary Adherence in Behavioral Obesity Treatment: Protocol for a Microrandomized Trial. JMIR Res Protoc. 2021 Dec 6;10(12):e33568. doi: 10.2196/33568.
Hardeman W, Houghton J, Lane K, Jones A, Naughton F. A systematic review of just-in-time adaptive interventions (JITAIs) to promote physical activity. Int J Behav Nutr Phys Act. 2019 Apr 3;16(1):31. doi: 10.1186/s12966-019-0792-7.
Teepe GW, Da Fonseca A, Kleim B, Jacobson NC, Salamanca Sanabria A, Tudor Car L, Fleisch E, Kowatsch T. Just-in-Time Adaptive Mechanisms of Popular Mobile Apps for Individuals With Depression: Systematic App Search and Literature Review. J Med Internet Res. 2021 Sep 28;23(9):e29412. doi: 10.2196/29412.
Perski O, Hebert ET, Naughton F, Hekler EB, Brown J, Businelle MS. Technology-mediated just-in-time adaptive interventions (JITAIs) to reduce harmful substance use: a systematic review. Addiction. 2022 May;117(5):1220-1241. doi: 10.1111/add.15687. Epub 2021 Oct 11.
9. Pimenta, N., Félix, I. B., Monteiro, D.
Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Document Type: Informed Consent Form
Other Identifiers
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HE-RD/2023/1.11
Identifier Type: -
Identifier Source: org_study_id
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