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Differentiating Abnormal, Normal, and Ideal Personality Profiles in Multidimensional Spaces
dc.contributor.author | Gutiérrez, Fernando | |
dc.contributor.author | Peri, Josep Maria | |
dc.contributor.author | Aluja, Anton | |
dc.contributor.author | Bailles, Eva | |
dc.contributor.author | Sureda, Barbara | |
dc.contributor.author | Gutiérrez-Zotes, Alfonso | |
dc.contributor.author | Vall, Gemma | |
dc.contributor.author | Calvo, Natalia | |
dc.contributor.author | Ferrer, Marc | |
dc.contributor.author | Cavero, Myriam | |
dc.contributor.author | Mallorquí, Aida | |
dc.contributor.author | Edo Villamón, Silvia | |
dc.contributor.author | Meliá de Alba, Amanda | |
dc.contributor.author | Ruipérez Rodríguez, María Ángeles | |
dc.date.accessioned | 2023-07-20T07:56:02Z | |
dc.date.available | 2023-07-20T07:56:02Z | |
dc.date.issued | 2023-03-15 | |
dc.identifier.citation | Gutiérrez, F., Peri, J. M., Aluja, A., Baillés, E., Sureda, B., Gutiérrez-Zotes, A., ... & Rodríguez, M. (2023). Differentiating abnormal, normal, and ideal personality profiles in multidimensional spaces. Journal of Individual Differences. | ca_CA |
dc.identifier.issn | 1614-0001 | |
dc.identifier.issn | 2151-2299 | |
dc.identifier.uri | http://hdl.handle.net/10234/203405 | |
dc.description.abstract | Current dimensional taxonomies of personality disorder (PD) establish that intense traits do not suffice to diagnose a disorder, and additional constructs reflecting dysfunction are required. However, traits appear able to predict maladaptation by themselves, which might avoid duplications and simplify diagnosis. On the other hand, if trait-based diagnoses are feasible, it is the whole personality profile that should be considered, rather than individual traits. This takes us into multidimensional spaces, which have their own particular – but poorly understood – logic. The present study examines how profile-level differences between normal and disordered subjects can be used for diagnosis. The Dimensional Assessment of Personality Pathology – Basic Questionnaire (DAPP-BQ) and the Personality Inventory for DSM-5 (PID-5) were administered to a community and a clinical sample each (total n = 1,925 and 3,543 respectively). Intense traits proved to be common in the general population, so empirically-based thresholds are indispensable not to take as abnormal what is at most unideal. Profile-level parameters such as Euclidean and Mahalanobis distances outperformed individual traits in predicting mental problems and equaled the performance of published measures of dysfunction or severity. Personality profiles can play a more central role in identifying disorders than is currently acknowledged, provided that adequate metrics are used. | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Hogrefe | ca_CA |
dc.rights | © 2023 Hogrefe. All rights reserved. | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | ca_CA |
dc.subject | personality disorders | ca_CA |
dc.subject | personality dysfunction | ca_CA |
dc.subject | dimensional classification | ca_CA |
dc.subject | multidimensional space | ca_CA |
dc.title | Differentiating Abnormal, Normal, and Ideal Personality Profiles in Multidimensional Spaces | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1027/1614-0001/a000395 | |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | ca_CA |
dc.relation.publisherVersion | https://econtent.hogrefe.com/doi/full/10.1027/1614-0001/a000395 | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
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