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The use of social simulation modelling to understand adherence to diabetic retinopathy screening programs.
Pereira, Andreia Penso; Macedo, João; Afonso, Ana; Laureano, Raul M S; de Lima Neto, Fernando Buarque.
Afiliación
  • Pereira AP; Information Sciences, Technologies and Architecture Research Center (ISTAR-IUL), Instituto Universitário de Lisboa (ISCTE-IUL), Av. das Forças Armadas, 1649-026, Lisboa, Portugal. andreia_marisa_pereira@iscte-iul.pt.
  • Macedo J; Escola Politécnica, Computer Engineering, (POLI/EComp), Universidade de Pernambuco (UPE), Recife, 50720-001, Brazil.
  • Afonso A; Global Health and Tropical Medicine, GHTM, Associate Laboratory in Translation and Innovation Towards Global Health, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, 1349-008, Lisboa, Portugal.
  • Laureano RMS; Information Sciences, Technologies and Architecture Research Center (ISTAR-IUL), Instituto Universitário de Lisboa (ISCTE-IUL), Av. das Forças Armadas, 1649-026, Lisboa, Portugal. raul.laureano@iscte-iul.pt.
  • de Lima Neto FB; Business Research Unit (BRU-IUL), Instituto Universitário de Lisboa (ISCTE-IUL), Av. das Forças Armadas, 1649-026, Lisboa, Portugal. raul.laureano@iscte-iul.pt.
Sci Rep ; 14(1): 4963, 2024 02 29.
Article en En | MEDLINE | ID: mdl-38424187
ABSTRACT
The success of screening programs depends to a large extent on the adherence of the target population, so it is therefore of fundamental importance to develop computer simulation models that make it possible to understand the factors that correlate with this adherence, as well as to identify population groups with low adherence to define public health strategies that promote behavioral change. Our aim is to demonstrate that it is possible to simulate screening adherence behavior using computer simulations. Three versions of an agent-based model are presented using different methods to determine the agent's individual decision to adhere to screening (a) logistic regression; (b) fuzzy logic components and (c) a combination of the previous. All versions were based on real data from 271,867 calls for diabetic retinopathy screening. The results obtained are statistically very close to the real ones, which allows us to conclude that despite having a high degree of abstraction from the real data, the simulations are very valid and useful as a tool to support decisions in health planning, while evaluating multiple scenarios and accounting for emergent behavior.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Diabetes Mellitus / Retinopatía Diabética Límite: Humans Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Portugal Pais de publicación: Reino Unido
Texto completo
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XML
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Diabetes Mellitus / Retinopatía Diabética Límite: Humans Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Portugal Pais de publicación: Reino Unido