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Publication
Artificial neural network model for predicting child sexual offending: Role of cognitive distortions, sexual coping, and attitudes
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Advisor(s)
Abstract(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
Description
Keywords
Sexual offenses Child sexual abuses Artificial neural networks Cognitive distortions
Citation
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
Publisher
Routledge