Salus: um modelo para assistência educacional ubíqua em doenças crônicas não transmissíveis

Abstract

Noncommunicable Chronic Diseases (NCDs) are the leading cause of death worldwide, meaning 41 million people die each year, accounting for 74% of all deaths. These chronic diseases need long-term and continuous treatment that requires knowledge about diseases, requires adaptation to treatment needs, incurs cost and delays or hinders the development, especially of low- and middle-income families. Actions for the prevention and monitoring of NCDs should be promoted through the use of ubiquitous computing technologies to provide services to individuals that assist in health education, including self-management and self-care of their health conditions. Through ubiquitous computing it is possible to integrate technologies to the daily life of individuals, making use of smartphones and tablets. In turn, ubiquitous education makes possible the integration of the individual with their context, helping in continuous and contextualized learning. In this sense, this thesis proposes SALUS, a computational model that uses context histories of individuals' as a mechanism to assist in ubiquitous educational assistance in the prevention and monitoring of NCDs. These technologies allow SALUS to adapt to available resources and provide personalized services to assist individuals in improving their specific health conditions. The model uses an ontology to represent knowledge in the domain of ubiquitous educational assistance in NCDs. In addition, it explores elements of the context of individuals that are used in the composition of context histories. Finally, the analysis of context histories is used to customize services that deliver useful information for the health education of individuals. These characteristics are the contributions of SALUS in the area of ubiquitous education applied to NCDs. In order to evaluate the model, a prototype with services for recommending content and place for individuals with or without a diagnosis of cardiovascular diseases was created. The evaluation aimed to assess the correctness of the content and place recommendations indicated by the service. A public database containing data from 4239 individuals was used in the evaluation, with results showing an occurrence of 28.8% where content recommendation is between high (score >60 and ≤80) and very high (score >80) ranges, where 96.18% of these records have a score of risk for nominal cardiovascular disease (CVD) between elevated and risk>30% (classification indicated by calculating the 10-year risk score for CVD, defined in the Framingham Heart Study). Regarding the place recommendation score, 25.4% of the records had a value between high and very high, where 100% of these records had a nominal CVD risk score between elevated and risk>30%. The results obtained reinforce the hypothesis that it is possible to define a computational model to support ubiquitous assistance in the education of an individual aimed at the prevention and monitoring of NCDs.