Personalized message emission in a mobile application for supporting therapeutic adherence

Often chronic patients fail to follow all the recommendations in their treatments. This affects their health and increases the costs associated with their care. To help these patients to follow their therapy this paper proposes a recall and guide system implemented on a mobile device. The system emits custom messages according to the patient's inferred mental state with the intention of persuading him to adhere to his medical prescriptions. To achieve personalization, the system uses ontologies to classify the messages and to model the user. When it is necessary to issue a reminder, the selection of the message is obtained by querying the relationships between the patient's current model and the discourse ontology.