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Artificial neural network model for predicting child sexual offending: Role of cognitive distortions, sexual coping, and attitudes
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Orientador(es)
Resumo(s)
This research aims to present additional knowledge about individuals
with a history of sexual offenses against children in
Portugal. Although the international literature mentions the
presence of cognitive distortions as a common element for
child sexual offending, it is known that another cognitive pathway
developed since childhood and adolescence will have
a significant weight in the definition of disruptive sexual behaviors.
In this article, we focused on sexual attitudes and sex as
a strategy for sexual coping and assayed to appreciate the
relevance of these variables as predictors of Child Sexual
Abuse (CSA). This research mainly aims to analyze
a hierarchical and predictive model of these variables and cognitive
distortion in the CSA. With resources to Artificial Neural
Networks (ANN), we conclude that these variables, when associated,
have a predictive accuracy of 82.3% in a sample that
included individuals with a history of sexual offenses against
children (N = 59) and the general community (N = 82). New
future approaches can benefit from integrating coping strategies
and sexual attitudes into CSA, adapted to the Portuguese
context
Descrição
Palavras-chave
Sexual offenses Child sexual abuses Artificial neural networks Cognitive distortions
Contexto Educativo
Citação
Baúto, R. V., Cardoso, J., & Leal, I. (2023). Artificial neural network model for predicting child sexual offending: role of cognitive distortions, sexual coping, and attitudes. Journal of Forensic Psychology Research and Practice. https://doi.org/10.1080/24732850.2023.2249518
Editora
Routledge