title: A profile analysis of personality disorders: beyond multiple diagnoses.
abstract: The authors applied cluster analysis and multidimensional scaling to the analyses of 59 patients with personality pathology. Cluster analysis yielded eight typologies of patients: detached, anankastic, phobic, dramatic, erratic, emotional, milder emotional, and masochistic negativistic. Multidimensional scaling identified the dimensions of classifying patients: anxious rumination versus behavioural acting out, overall severity of personality pathology, and assertiveness versus withdrawal. Considering the distinction between personality disorder (dysfunctional personality) and abnormal personality (extreme personality), the following changes in current classification system are proposed: use of a hierarchy and exclusion criteria in a categorical-type model or use of a personality profile in a dimensional-trait model, in either case, with a dimensional rating for severity of psychopathology to define personality 'disorder'.
authors.affiliation: Department of Psychiatry, Osaka University Medical School, Japan. nakao@psy.med.osaka-u.ac.jp
authors.forename: K
authors.initials: K
authors.lastname: Nakao
authors.forename: J
authors.initials: J
authors.lastname: Takaishi
authors.forename: K
authors.initials: K
authors.lastname: Tatsuta
authors.forename: H
authors.initials: H
authors.lastname: Katayama
authors.forename: M
authors.initials: M
authors.lastname: Iwase
authors.forename: K
authors.initials: K
authors.lastname: Yorifuji
authors.forename: K
authors.initials: K
authors.lastname: Shinosaki
authors.forename: M
authors.initials: M
authors.lastname: Takeda
mesh_terms: D000328:Adult; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D007564:Japan; D008297:Male; D010552:Personality Assessment / Q000706:statistics & numerical data; D010554:Personality Disorders / Q000145:classification / Q000175:diagnosis* / Q000523:psychology; D011569:Psychiatric Status Rating Scales / Q000706:statistics & numerical data*; D011594:Psychometrics