Fuzzy Logic: vulnerability of women who have sex with women to sexually transmitted infections

Objective: To describe the possibility of applying Fuzzy Logic in analyzing the vulnerability of Women Who Have Sex with Women to Sexually Transmitted Infections/HIV/AIDS. Methods: We developed a Fuzzy Logic system with 17 input variables and one output variable, using data related to vulnerability...

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Bibliographic Details
Authors: Andrade, Juliane [UNESP], Santos, Kendra Yanne da Silva, de Freitas, Ana Paula Freneda [UNESP], Ignácio, Mariana Alice Oliveira [UNESP], Godinho, Emmanuel Zullo, Duarte, Marli Teresinha Cassamassimo [UNESP]
Format: article
Status:Published version
Publication Date:2024
Country:Brasil
Institution:Universidade Estadual Paulista (UNESP)
Repository:Repositório Institucional da UNESP
Language:English
Portuguese
OAI Identifier:oai:repositorio.unesp.br:11449/299134
Online Access:http://dx.doi.org/10.1590/0034-7167-2023-0271
https://hdl.handle.net/11449/299134
Access Level:Open access
Keyword:Fuzzy Logic
Health Vulnerability
Reproductive Health
Sexually Transmitted Diseases
Women Who Have Sex With Women
Description
Summary:Objective: To describe the possibility of applying Fuzzy Logic in analyzing the vulnerability of Women Who Have Sex with Women to Sexually Transmitted Infections/HIV/AIDS. Methods: We developed a Fuzzy Logic system with 17 input variables and one output variable, using data related to vulnerability in a municipality located in the Midwest region of the State of São Paulo, Brazil. Results: The factor with the greatest positive impact was the confirmation that a low understanding of Sexually Transmitted Infections/HIV/AIDS is associated with higher vulnerability. Conversely, the statement “Not disclosing sexual activity to healthcare professionals,” where individuals do not admit to having sex with women, had the least impact. Conclusions: Fuzzy Logic facilitates the identification of vulnerability, expressed through the analysis of interaction between variables in each dimension. This makes it a promising method to assist in analyzing the vulnerability of specific populations.