Abstract
BackgroundRegular physical activity is known to be beneficial for people with type 2 diabetes. Nevertheless, most of the people who have diabetes lead a sedentary lifestyle. Smartphones create new possibilities for helping people to adhere to their physical activity goals through continuous monitoring and communication, coupled with personalized feedback.ObjectiveThe aim of this study was to help type 2 diabetes patients increase the level of their physical activity.MethodsWe provided 27 sedentary type 2 diabetes patients with a smartphone-based pedometer and a personal plan for physical activity. Patients were sent short message service messages to encourage physical activity between once a day and once per week. Messages were personalized through a Reinforcement Learning algorithm so as to improve each participant’s compliance with the activity regimen. The algorithm was compared with a static policy for sending messages and weekly reminders.ResultsOur results show that participants who received messages generated by the learning algorithm increased the amount of activity and pace of walking, whereas the control group patients did not. Patients assigned to the learning algorithm group experienced a superior reduction in blood glucose levels (glycated hemoglobin [HbA1c]) compared with control policies, and longer participation caused greater reductions in blood glucose levels. The learning algorithm improved gradually in predicting which messages would lead participants to exercise.ConclusionsMobile phone apps coupled with a learning algorithm can improve adherence to exercise in diabetic patients. This algorithm can be used in large populations of diabetic patients to improve health and glycemic control. Our results can be expanded to other areas where computer-led health coaching of humans may have a positive impact. Summary of a part of this manuscript has been previously published as a letter in Diabetes Care, 2016.
Highlights
Physical activity is highly recommended to patients with diabetes, as it is known that such activity leads to better control of glucose and other metabolic risk factors and improved quality of life [1]
Mobile phone apps coupled with a learning algorithm can improve adherence to exercise in diabetic patients
We report the characteristics of patients and their participation in the experiment, the effect of individual messages on user behavior, how the algorithm changed over time, and the two experimental outcomes—the change in activity made by participants during the experiment and the change in HbA1c during the experiment
Summary
Physical activity is highly recommended to patients with diabetes, as it is known that such activity leads to better control of glucose and other metabolic risk factors and improved quality of life [1]. There have been multiple studies of mobile phone interventions using short message service (SMS) messages to improve health-related behaviors (reviewed in De Jongh et al [7]), and there are several previous studies that have tried to assess the effect of mobile phone apps in encouraging physical activity (reviewed in Bort-Roig et al [8]). These studies use random messages or a display that quantifies the amount of activity performed. Smartphones create new possibilities for helping people to adhere to their physical activity goals through continuous monitoring and communication, coupled with personalized feedback
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