F. Gutiérrez, J. Peri, A. Aluja, E. Baillés, B. Sureda, A. Gutiérrez-Zotes, Gemma Vall, N. Calvo, M. Ferrer, M. Cavero, Aida Mallorquí, Silvia Edo Villamón, Amanda Meliá de Alba, M. Á. R. Rodríguez
{"title":"区分多维空间中的异常、正常和理想人格特征","authors":"F. Gutiérrez, J. Peri, A. Aluja, E. Baillés, B. Sureda, A. Gutiérrez-Zotes, Gemma Vall, N. Calvo, M. Ferrer, M. Cavero, Aida Mallorquí, Silvia Edo Villamón, Amanda Meliá de Alba, M. Á. R. Rodríguez","doi":"10.1027/1614-0001/a000395","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":47049,"journal":{"name":"Journal of Individual Differences","volume":" ","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Differentiating Abnormal, Normal, and Ideal Personality Profiles in Multidimensional Spaces\",\"authors\":\"F. Gutiérrez, J. Peri, A. Aluja, E. Baillés, B. Sureda, A. Gutiérrez-Zotes, Gemma Vall, N. Calvo, M. Ferrer, M. Cavero, Aida Mallorquí, Silvia Edo Villamón, Amanda Meliá de Alba, M. Á. R. 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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. 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Differentiating Abnormal, Normal, and Ideal Personality Profiles in Multidimensional Spaces
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.
期刊介绍:
Researchers, teachers, and students interested in all areas of individual differences (e.g., gender, temperament, personality, intelligence) and their assessment in human and animal research will find the Journal of Individual Differences useful. The Journal of Individual Differences publishes manuscripts dealing with individual differences in behavior, emotion, cognition, and their developmental aspects. This includes human as well as animal research. The Journal of Individual Differences is conceptualized to bring together researchers working in different areas ranging from, for example, molecular genetics to theories of complex behavior.