Many patients with Type 2 Diabetes (T2D) have difficulty in controlling their disease despite wide-spread availability of high-quality guidelines, T2D education programs and primary care follow-up programs. Current diabetes education and treatment programs translate knowledge from bench to bedside well, but underperform on the 'last-mile' of converting that knowledge into action (KTA). Two innovations to the last-mile problem in management of patients with T2D are introduced. 1) Design of a platform for peer-to-peer groups where patients can solve KTA problems together in a structured and psychologically safe environment using all the elements of the Action Cycle phase of the KTA framework. The platform uses Self-Determination Theory as the behavior change theory. 2) A novel patient segmentation method to enable the formation of groups of patients who have similar behavioral characteristics and therefore who are more likely to find common cause in the fight against diabetes.

Design for a Virtual Peer-to-Peer Knowledge to Action Platform for Type 2 Diabetes

Paglialonga A;
2022

Abstract

Many patients with Type 2 Diabetes (T2D) have difficulty in controlling their disease despite wide-spread availability of high-quality guidelines, T2D education programs and primary care follow-up programs. Current diabetes education and treatment programs translate knowledge from bench to bedside well, but underperform on the 'last-mile' of converting that knowledge into action (KTA). Two innovations to the last-mile problem in management of patients with T2D are introduced. 1) Design of a platform for peer-to-peer groups where patients can solve KTA problems together in a structured and psychologically safe environment using all the elements of the Action Cycle phase of the KTA framework. The platform uses Self-Determination Theory as the behavior change theory. 2) A novel patient segmentation method to enable the formation of groups of patients who have similar behavioral characteristics and therefore who are more likely to find common cause in the fight against diabetes.
2022
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
predictive analytics
AI
diabetes prevention
patient segmentation
behavioral intervention
type 2 diabetes
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/412555
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