AI Article Synopsis

  • Regular physical activity is crucial for managing type 2 diabetes, but many patients remain inactive; smartphones offer tools for improving adherence through monitoring and personalized feedback.
  • This study provided 27 sedentary diabetes patients with smartphone pedometers and tailored activity plans, supported by personalized motivational messages using a learning algorithm.
  • Results showed that participants using the algorithm increased physical activity and improved blood glucose levels more than those receiving standard messages, highlighting the potential of tech-based health coaching for diabetes management and other health areas.

Article Abstract

Background: Regular 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.

Objective: The aim of this study was to help type 2 diabetes patients increase the level of their physical activity.

Methods: We 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.

Results: Our 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.

Conclusions: Mobile 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5654735PMC
http://dx.doi.org/10.2196/jmir.7994DOI Listing

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