MACHINE LEARNING MODEL PROPOSAL THAT ASSOCIATES THE MAIN EPIDEMIOLOGICAL AND SOCIODEMOGRAPHIC CHARACTERISTICS OF HIGH-RISK PREGNANT WOMEN TO PREDICT THE LEVEL OF ANXIETY

  • Michele Freire Seixas UNIR
  • Aníbal Monteiro de Magalhães-Neto UFMT
  • Talles Paul Leandro Mota UFMT
  • Márcio Vinícius de Abreu Verli UFMT
  • Luis Carlos Oliveira Gonçalves UFMT
  • Ivete de Aquino Freire UNIR
  • Ramon Núñez Cárdenas UNIR
Palavras-chave: Mental health, Clinical-epidemiological profile, Social characteristics, Public health

Resumo

The mental health of pregnant women includes preexisting and current factors that can increase their anxiety, especially in high-risk pregnancies. The stratification of intervening variables aims to understand the multidimensionalities in which pregnant women are inserted and can contribute to a favorable outcome for the mother and baby binomial. The objective was to describe the clinical-epidemiological profile and sociodemographic characteristics of high-risk pregnant women and to analyze the association of these variables with the level of anxiety through a descriptive, quantitative and documentary study, with 339 pregnant women. For data collection, the Aaron Beck Anxiety Questionnaire and two instruments authored by the author were used. In the analysis of sociodemographic and epidemiological variables with the level of anxiety, it was observed that there is statistical evidence of a significant association between the level of anxiety and the variables presented, suggesting a new model to predict anxiety in public health..

Publicado
2025-07-04
Seção
Ciências da Saúde