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

2023Journal article Restricted access
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dc.contributor.authorBaúto, R.V.
dc.contributor.authorCardoso, Jorge
dc.contributor.authorLeal, I.
dc.date.accessioned2024-04-23T16:05:57Z
dc.date.available2024-04-23T16:05:57Z
dc.date.issued2023
dc.description.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 contextpt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBaúto, 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/10.1080/24732850.2023.2249518pt_PT
dc.identifier.doi10.1080/24732850.2023.2249518pt_PT
dc.identifier.issn24732842
dc.identifier.urihttp://hdl.handle.net/10400.12/9737
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherRoutledgept_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectSexual offensespt_PT
dc.subjectChild sexual abusespt_PT
dc.subjectArtificial neural networkspt_PT
dc.subjectCognitive distortionspt_PT
dc.titleArtificial neural network model for predicting child sexual offending: Role of cognitive distortions, sexual coping, and attitudespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceUnited Kingdompt_PT
oaire.citation.endPage19pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleJournal of Forensic Psychology Research and Practicept_PT
person.familyNameVentura Baúto
person.familyNameCardoso
person.familyNameMaria Pereira Leal
person.givenNameRicardo
person.givenNameJorge
person.givenNameIsabel
person.identifier.ciencia-idAE16-BF9D-2729
person.identifier.ciencia-idED13-65EC-0486
person.identifier.ciencia-id9116-1A09-8BE5
person.identifier.orcid0000-0002-7255-2256
person.identifier.orcid0000-0001-6037-3210
person.identifier.orcid0000-0002-1672-7912
person.identifier.scopus-author-id54985518100
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationb85a60b2-28c8-4a23-b7a1-35e0714ec2f6
relation.isAuthorOfPublicationb83c0ab3-80da-485f-8d92-06f94e0d0ff9
relation.isAuthorOfPublication7302fd27-17cc-49a3-a25d-5388723e5733
relation.isAuthorOfPublication.latestForDiscovery7302fd27-17cc-49a3-a25d-5388723e5733

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