Abstract
Characterized by excess adipose tissue in the body, obesity is a significant public health problem in today's world. Among the various causes that lead to the development of obesity, endocrine, genetic, behavioural, psychological, economic-social, emotional, environmental, and cultural factors stand out. Although not considered a mental disorder, obesity may be associated with several psychological disorders, such as Eating Disorders, Anxiety Disorders; Obsessive–Compulsive Disorders; Depressive disorders; Sleep–wake Disorders. Obesity can also be the cause of many other diseases such as diabetes, hypertension, infertility, and strokes of the brain and heart diseases. Because of these factors and causes, governments of various countries have been implementing public health programs in their respective populations that include socio-educational and treatment measures. However, despite advances in the knowledge of obesity, treatment solutions do not show significant progress, since there is still a considerable portion of the population, obese. Furthermore, the present study aims to indicate factors that need to be considered in the decision-making process by health professionals in the definition of treatment, as well as by public managers in the implementation of public policies. For this, a hybrid model structured in decision-making methodologies (Multicriteria Decision Analysis) will be used, associated with a specialist system with representations based on knowledge of rules and production probabilities using Artificial Intelligence.
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Pinheiro, P.R. et al. (2021). A Hybrid Model to Support Public Obesity Treatment Policies. In: Visvizi, A., Lytras, M.D., Aljohani, N.R. (eds) Research and Innovation Forum 2020. RIIFORUM 2020. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-62066-0_45
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DOI: https://doi.org/10.1007/978-3-030-62066-0_45
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