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| Name | Class |
|---|---|
| European Union | OTHER |
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The topic of diet and physical activity are of great importance in the treatment of T2D. In the daily routine of a practice or clinic, a doctor has an average of eight minutes per patient, leaving little time for lifestyle issues (Irving et al. 2017). An individualised procedure requires more time and therefore more resources. Currently, an app can be programmed with evidence-based information so that it provides appropriate personalised behavioural recommendations via machine learning. The user gets direct feedback and can make a behavioural change himself. On the one hand, this approach allows better use of doctor-patient time and, on the other hand, the patient learns through positive reinforcement in such a way that his or her behaviour change is supported and reinforced in the longer term and potentially sustainably.
The aim of this intervention pilot study within the scope of the EU-Horizon 2020 project is to investigate lifestyle support through a mobile app and wearables to improve lifestyle (personalised nutrition) and important metabolic outcomes in patients with type 2 diabetes or prediabetes. In addition, exploratory genetic and microbiome data will be explored to answer the question of personalisation of the recommendations.
An inadequate diet and increasing sedentary lifestyle are major contributors to the rise of non-communicable diseases. Individualized recommendations can lead to a healthier lifestyle. The scientific evidence of the effectiveness of health apps offering personalized recommendations is limited.
The aim of this intervention pilot study within the scope of the EU-Horizon 2020 project is to investigate lifestyle support through a mobile app and wearables to improve lifestyle (personalised nutrition) and important metabolic outcomes in patients with type 2 diabetes or prediabetes. The Investigators want to asess whether the use of this mobile application that incorporates information of wearables (continuous glucose monitoring and fitness tracker), improves lifestyle and metabolic outcomes in patients with type 2 diabetes (T2D) or prediabetes. Our primary outcome is to improve time in range (TIR) by 5%.
It is a prospective randomized control pilot trial with an intervention period of 12 weeks. Participants will use the Protein app, a continuous glucose monitoring system (CGM) and an activity tracker to collect real world data to enable personalisation.
In order to identify the effect of the PROTEIN-Application, 300 participants with T2DM or prediabetes will be randomly allocated into two groups: the (1) start-group or the (2) wait-group. The start-group will use an activity tracker, a CGM and the PROTEIN app for 12 weeks followed by a six-week period without the app, but they will use the wearables. The wait-group will use an activity tracker and a CGM, but not the PROTEIN app for six weeks followed by a period of 12 weeks using the PROTEIN app. This study design allowed us to have a control group within the whole cohort and clearly see the influence of the PROTEIN app.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Start-Group | Experimental | The Start-Group starts with the Protein-Application and wereables for 3 Months and afterwards uses only wereables for 6 Weeks. |
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| Wait-Group | Experimental | The Wait-Group starts with 6 Weeks of using only wereables and afterwards adds the usage of the Protein-Application. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Usage of the PROTEIN-Application | Other | Participants were randomly distributed into 2 groups: (1) Start-Group used the developed Application and wereables to investigate the effect of this support. Participants used the devices and the App for 3 Months followed by a 6-Weeks time of only using wereables and no app, to be able to compare the effects of the Application. (2) The Wait-Group used wereables for 6 Weeks before adding the Protein-App for also 3 Months. |
| Measure | Description | Time Frame |
|---|---|---|
| Improvement of Time In Range (TIR) by 5% | Our primary objective is to increase the time in range (TIR) of the study participants by 5% | 12 Weeks |
| Improve eating behavior towards healthier choices | Improve eating behaviour towards healthier choices during the intervention time | 12 Weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Adherence to dietary recommendations of the app | Adherence to dietary recommendations of the PROTEIN-App | 12 Weeks |
| Improvement of glycaemic metabolism | Fasting glucose, HbA1c, HOMA-IR |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Lazaros Gymnopoulos, Dr | Information Technologies Institute, Centre for Research and Technology Hellas | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Charité Univesitätsmedizin Berlin | Berlin | State of Berlin | 12203 | Germany |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 42342244 | Derived | Lalama E, Csanalosi M, Kabisch S, Wilson-Barnes S, Gymnopoulos LP, Dimitropoulos K, Rouskas K, Anagnostis A, Oikonomidis I, Hadjileontiadis L, Cornelissen V, Hassapidou M, Pagkalos I, Balula Dias S, Hart K, Pfeiffer AFH. Effect of a Personalized Mobile App on Glucose Control in Adults With Prediabetes and Type 2 Diabetes: Exploratory Pilot Randomized Controlled Trial. JMIR Hum Factors. 2026 Jun 24;13:e87692. doi: 10.2196/87692. |
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| ID | Term |
|---|---|
| D003924 | Diabetes Mellitus, Type 2 |
| D011236 | Prediabetic State |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| 12 Weeks |
| Reduction in sedentary time | Reduction in sedentary time, defined as: Activity time through fitness trackers or increase in physical activity or increase in steps per day | 12 Weeks |
| Aproximation of the energy intake | Approximation of the energy intake (calorie intake and distribution of macronutrients) towards the agreed goals | 12 Weeks |
| Measurable change in the faecal microbiome | Measurable change in the faecal microbiome by extraction of DNA and its analysis to identify the relevant species of bacteria | 12 Weeks |
| Calculation of the Polygenic Risk Score | Calculation of the Polygenic Risk Score by Isolation of DNA from whole blood | 12 Weeks |
| D004700 | Endocrine System Diseases |