Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/70141

TítuloCan the triarchic model of psychopathy predict youth offender recidivism?
Autor(es)Pechorro, Pedro Fernandes Santos
Quintas, Jorge
DeLisi, Matt
Gonçalves, Rui Abrunhosa
Palavras-chavecrime
detention
triarchic model of psychopathy
youth offenders
recidivism
Data2021
EditoraTaylor & Francis
RevistaPsychology, Crime & Law
CitaçãoPedro Pechorro, Jorge Quintas, Matt DeLisi & Rui Abrunhosa Gonçalves (2021) Can the triarchic model of psychopathy predict youth offender recidivism?, Psychology, Crime & Law, DOI: 10.1080/1068316X.2020.1818237
Resumo(s)The triarchic model of psychopathy is one of the most influential models of psychopathy developed in recent years. The current aim is to investigate the utility of a self-report measure of the triarchic model of psychopathy in predicting criminal recidivism among a sample of incarcerated juvenile offenders. Male youth participants (N=228, M=16.38 years, SD=1.26 years) from the Detention Centers managed nation-wide by the Ministry of Justice of Portugal were followed during a two-year period and categorized as recidivists or non-recidivists. The Area Under the Curve (AUC) results showed that only the Disinhibition dimension of the triarchic model of psychopathy was able to significantly predict general recidivism. The binary logistic regression models controlling for relevant variables (e.g. age of first detention, past frequency of crimes, conduct disorder symptoms) found that the boldness, meanness, and disinhibition dimensions failed to predict general or violent recidivism. The overall findings suggest that the triarchic model of psychopathy demonstrates limited utility in terms of predicting recidivism among juvenile offenders.
TipoArtigo
URIhttps://hdl.handle.net/1822/70141
DOI10.1080/1068316X.2020.1818237
ISSN1068-316X
e-ISSN1477-2744
Versão da editorahttps://www.tandfonline.com/doi/full/10.1080/1068316X.2020.1818237
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CIPsi - Artigos (Papers)

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