
doi: 10.1002/pmh.1336
pmid: 27120419
AbstractAimThe ICD‐11 Personality Disorders Committee has proposed five personality domains: Detached, Anankastic, Negative Affective, Dissocial and Disinhibited. We attempted to validate these proposed domains in a large sample of patients with major depression.MethodsParticipants from five treatment studies received a SCID assessment interview to assess DSM‐5 personality disorder symptoms. Personality disorder symptoms were assigned to the five proposed domains. Confirmatory factor analysis in an exploratory framework was used to test the hypothesized domain structure.ResultsA total of 606 patients were included in the analysis. A series of models were tested on the data set. The best fitting model produced five domains. Three domains detached, anankastic and negative affective were similar to the ICD‐11 proposed domains. The Disinhibited domain did not emerge as a distinct factor but loaded onto a single Dissocial/Disinhibited factor. The model was improved by adding a separate Antisocial domain. The remaining domain incorporating borderline, histrionic and narcissistic symptoms is tentatively labelled Borderline to retain continuity with clinical practice and research.ConclusionsThe proposed ICD‐11 personality disorder domains were partially validated. We have five domains currently labelled Detached, Anankastic, Negative Emotional, Antisocial and Borderline. The sample studied limits the generalizability of our findings. In particular, the broad domain we have called Borderline requires further study. Copyright © 2016 John Wiley & Sons, Ltd.
Adult, Male, Psychiatric Status Rating Scales, Reproducibility of Results, Personality Assessment, Personality Disorders, Diagnostic and Statistical Manual of Mental Disorders, International Classification of Diseases, Humans, Female, Factor Analysis, Statistical
Adult, Male, Psychiatric Status Rating Scales, Reproducibility of Results, Personality Assessment, Personality Disorders, Diagnostic and Statistical Manual of Mental Disorders, International Classification of Diseases, Humans, Female, Factor Analysis, Statistical
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