Status
Conditions
Treatments
About
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.
Full description
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.
Enrollment
Sex
Ages
Volunteers
Inclusion criteria
Exclusion criteria
Primary purpose
Allocation
Interventional model
Masking
300 participants in 2 patient groups
Loading...
Data sourced from clinicaltrials.gov
Clinical trials
Research sites
Resources
Legal