Publication: Feasibility of an Activity Control System in Patients with Diabetes: A Study Protocol of a Randomised Controlled Trial.
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2022-09-02
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Abstract
Patients with diabetes mellitus have an increased risk of developing various serious health problems that could be life-threatening. These problems are associated with the difficulty of these patients in managing their lifestyle, which may even lead to the abandonment of treatment. The present study was designed to evaluate the feasibility of a multipurpose activity control solution for home activity (home activity control system), which will provide information on the activities of daily living carried out outside in real time, to improve adherence to each of the therapeutic objectives agreed on with the diabetic patient. A pilot randomised controlled feasibility study will be carried out to evaluate a home activity control system (Beprevent) in managing patients with type 2 diabetes mellitus. Twenty patients with type 2 diabetes mellitus will be included (10 in the intervention group and 10 in the control group). Data on satisfaction with the tool will be collected from professionals and patients, as well as other clinical/epidemiological data from their digital health records and several questionnaires, at baseline and six months. In addition, data will also be recorded regarding the degree of adherence to the behaviors agreed on with the patients before starting the study to assess changes throughout the study and their relationship with clinical results (glycosylated haemoglobin (HbA1c), cholesterol, etc), and to compare these outcomes between two study groups. This project involves the incorporation of telemedicine in the management of patients with diabetes. Thus, according to the currently published bibliography, the use of smart devices in this population could help improve the quality of life of these people, reduce medical visits and improve adherence to home care patterns for diabetes mellitus. There are currently no published clinical trials or protocols that monitor activities of daily living in patients with diabetes individually using artificial intelligence (AI) devices.