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The goal of the project is  to  study  and  develop  a computational  persuasion-based methodology  for  personalized  eHealth interventions targeting behavioral change. The usage of persuasion technologies will be fundamental toraise the effectiveness of eHealth interventions, which can be applied in different scenarios. They can help modelling personalized motivation and self-efficacy boosting interactions, or scheduling periodic micro-interventions based on the trajectory of a patient. This methodology will  rely  on  the  exploitation  of  patientpersuadee  models, persuasion  goals  and  behaviors,  encapsulated  in  a  multi-agent architecture.

This project aims to study  and  develop  a computational  persuasion-basedmethodology  that  actually  allows  to influence and induce behavioral change in the context of a specific health program. Beyond theanalysis of profile trends, this  project  will  aim  at exploring different motivation,  self-efficacy,and  goal-setting  factorsthat  can  help to  increasethe effectiveness of health-related interventions. These persuasion techniques can differ according tothe trajectory of a patient, which  characterizes previous  events  and  interventions, andfeedback  on  the  appropriateness  of  previous  advice  or counseling. The proposed methodology will rely on the use of multi-agent systems to act as persuasion entities, managing patient knowledge, goals, expectations, motivations,and feedback, to establish strategies that aim at maximizing the impact of  the  eHealth  support  activities.The  methodology  should  also  allow definingmetrics  that  will  be  used  to  evaluate  the persuasionprocess, according to expected outcomes and goals. The project defines the following specific objectives:O1:Study the state-of-the-art and current limitations and challenges of computational persuasion for behavior change in e-Health personalized applications. O2:Develop a methodology for modelingcomputational persuasion agentsso that they can be used to guide personalized behavioral changewith explicable outcomes. O3:Implement  aprototype  of  a multi-agentarchitecture  for  computational  persuasion, integrating the  provision  of personalized interventionsthrough conversational technologies. O4:Deploy  the  prototype  and  apply  the  methodology  in  two  different  use  cases requiringpersonalized  interventions according to trajectory analysis. One use case will be focused on physical therapy and the other onbehavior change. O5:Evaluate  the  technical  prototype  developed  in  the  project,  and  the  methodology  proposed,  with  the  use  cases  as validation scenarios.O6:Document the results, including the technologies developed, andthe scientific contributions to the state of the art.