Psychopathy is not a diagnostic category, however theories of psychopathy have been discussed throughout psychological history. While the construct of psychopathy is associated with important psychological outcomes, there are inconsistencies in the literature with regard to correlates, etiology and treatment. These inconsistencies suggest that there may be several subtypes of psychopathy. This paper discusses the heterogeneity of psychopathy and considers the existence of psychopathic traits in nonclinical populations. Measures of etiology (Behavioral Activation System and Behavioral Inhibition System; Gray, 1985), psychopathy (Levenson's psychopathy measure; Levenson, Keihl, & Fitzpatrick, 1995) and anxiety (State Trait Anxiety Inventory; Speilberger, Gorsuch & Lushene, 1970) were used in Model based cluster analysis to investigate the existence of subtypes analogous to primary and secondary psychopathy in college students. Four clusters emerged with cluster profiles differing in theoretically coherent ways. Two of the clusters were representative of subclinical primary and secondary psychopathy and the other two represented non-psychopathic groups. Research (Buss, 1961, Dodge, 1991) regarding aggression discriminates between two types of aggression: instrumental and hostile. The current study considered whether the subjects in clusters created by psychopathy data differ in terms of the types of aggression used. As expected, the Psychopathic Traits groups used more aggression than the Non-psychopathic Traits groups, and the Primary Psychopathic Traits group used more instrumental aggression than the Secondary Psychopathic Traits group. Overall, these results support the existence of subclinical subtypes of psychopathy that resemble, in meaningful ways, hypothetical clinical variants. The results also suggest that subtyping may have clinical and forensic utility in risk assessment.

Submitted by Milena Rubi (milenarubi@ufscar.br) on 2016-10-25T22:08:51Z No. of bitstreams: 1 PIANTONI_Jane_2016.pdf: 14171171 bytes, checksum: dff7166cfad97d46b01738a24a184b1c (MD5) / Approved for entry into archive by Milena Rubi (milenarubi@ufscar.br) on 2016-10-25T22:09:03Z (GMT) No. of bitstreams: 1 PIANTONI_Jane_2016.pdf: 14171171 bytes, checksum: dff7166cfad97d46b01738a24a184b1c (MD5) / Approved for entry into archive by Milena Rubi (milenarubi@ufscar.br) on 2016-10-25T22:09:18Z (GMT) No. of bitstreams: 1 PIANTONI_Jane_2016.pdf: 14171171 bytes, checksum: dff7166cfad97d46b01738a24a184b1c (MD5) / Made available in DSpace on 2016-10-25T22:09:29Z (GMT). No. of bitstreams: 1 PIANTONI_Jane_2016.pdf: 14171171 bytes, checksum: dff7166cfad97d46b01738a24a184b1c (MD5) Previous issue date: 2016-01-29 / Não recebi financiamento / The goal of this study is to investigate the characteristics of the new data clustering approaches, carrying out a comparative study of clustering techniques that combine or select multiple solutions, analyzing these latest techniques in relation to variety and completeness of knowledge that can be extracted with your application. Studies have been conducted related to the influence of partitions based on traditional ensembles and multi-objective ensemble. The performance of the methods was evaluated by applying them to different sets of base partitions, in order to evaluate them with respect to their ability to identify quality partitions from different initial scenarios. The other study, was conducted to evaluate the ability of the techniques in relation to recover the information available in the data. And for this, investigations were carried out in two contexts: partitions, which is the traditional form of analysis and clusters to internally verify that the recovered partitions contains more relevant information than the partition analysis shows. And to undertake such analyzes were observed the quality of partitions and clusters, the percentage of actual information (partitions and clusters) really recovered, in both contexts, and the volume of irrelevant information that each technique produces. Among the analyzes are the search for novel partitions and more robust than the sets of base partitions assembly used in the experiments, analysis of the influence of the partitions based on ensembles, the capacity analysis techniques in obtaining multiple partitions, and the analysis of the clusters extracted. / Este trabalho tem como objetivo investigar as características das novas abordagens de agrupamento de dados, realizando um estudo comparativo das técnicas de agrupamento que combinam ou selecionam múltiplas soluções, analisando essas técnicas mais recentes em relação a variedade e completude do conhecimento que pode ser extraído com sua aplicação. Foram realizados estudos relacionados a influência das partições base nos ensembles tradicionais e ensemble multi-objetivo. O desempenho dos métodos foi avaliado, aplicando-os em diferentes conjuntos de partições base, com o objetivo de avaliá-los com respeito a sua capacidade de identificar partições de qualidade a partir de diferentes cenários iniciais. O outro estudo realizado teve como objetivo avaliar a capacidade das técnicas em relação a recuperar as informações existentes nos dados. Para isto, foram realizadas investigações nos dois contextos: partições, que é a forma tradicional de análise e clusters para verificar internamente se as partições recuperadas contém mais informações relevantes do que a análise de partições demonstra. Para realizar tais análises, foram observadas a qualidade das partições e dos clusters, a porcentagem de informações reais (partições e clusters) realmente recuperadas, nos dois contextos, e o volume de informações irrelevantes que cada técnica produz. Dentre as análises realizadas, estão a busca por partições inéditas e mais robustas que o conjunto de partições base utilizados nos experimentos, a análise da influência das partições base nos ensembles, a análise da capacidade das técnicas na obtenção de múltiplas partições e a análise dos clusters extraídos.