1. Artificial neural network model for predicting child sexual offending: role of cognitive distortions, sexual coping, and attitudes.
- Author
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Baúto, Ricardo Ventura, Cardoso, Jorge, and Leal, Isabel
- Subjects
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CRIMES against children , *ARTIFICIAL neural networks , *SEX crimes , *HUMAN sexuality , *ATTITUDES toward sex , *CHILD sexual abuse - Abstract
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. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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