Dark Triad Traits and Risky Behaviours: Identifying Risk Profiles from a Person-Centred Approach

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The relationship between Dark Triad traits and risky behaviours has been shown in recent years. However, few studies have attempted to disentangle this relationship using a person-centred approach. The goal of the current study was to identify subgroups of individuals on the basis of their scores on Machiavellianism, psychopathy, and narcissism and analyse the differences between them in a set of risky behaviours (i.e., frequency of substance use, reactive and proactive aggression, risk perception and risk engagement, and problematic internet use). The sample consisted of 317 undergraduates aged 18–34 (46% males). The results of the latent profile analysis showed five subgroups of individuals that were identified based on their scores on the Dark Triad traits: low-Dark Triad, narcissistic, Machiavellian/narcissistic, psychopathic, and Machiavellian/psychopathic. Overall, the Machiavellian/narcissistic and Machiavellian/psychopathic subgroups showed higher scores for most risky behaviours. The low-Dark Triad scored higher for risk perception. No significant differences between subgroups were found as regards frequency of alcohol, tobacco, and cannabis use. These findings suggest that the combination of the Dark Triad traits lead to more negative outcomes as regards risky behaviour than individual components. Moreover, they highlight the relevance of using a person-centred approach in the study of dark personalities

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Maneiro, L.; Navas, M.P.; Van Geel, M.; Cutrín, O.; Vedder, P. Dark Triad Traits and Risky Behaviours: Identifying Risk Profiles from a Person-Centred Approach. Int. J. Environ. Res. Public Health 2020, 17, 6194

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This research was partially funded by Xunta de Galicia under the program Axudas á etapa posdoutoral (Consellería de Cultura, Educación e Ordenación Universitaria) and the consolidation and structuring of competitive research units and other promotional actions in the universities of the SUG; GRC, 2018

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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
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