Artificial neural network model for predicting child sexual offending: role of cognitive distortions, sexual coping, and attitudes

Abstract

ABSTRACTThis 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.KEYWORDS: Sexual offenseschild sexual abuseartificial neural networkscognitive distortions Disclosure statementNo potential conflict of interest was reported by the author(s).