Association between personality profiles and symptomatology patterns based on TCI and MMPI-2-RF in a transdiagnostic psychiatric sample: A person-centered approach

Abstract

BackgroundThe temperament and character dimensions of personality appear to be networking structures that interact nonlinearly. Previous studies have attempted to classify temperament and character subtypes using a person-centered approach but have been unable to explore the relationship between the combination of temperament and character and psychopathology patterns in a transdiagnostic sample. The purpose of this study was to examine how symptomatology patterns differ according to individuals' personality profiles, employing a psychobiological model in a transdiagnostic psychiatric sample. MethodsParticipants were 1881 patients who visited the psychiatry department of a major medical hospital in Seoul, Korea, and completed both the Temperament Character Inventory (TCI) and the Minnesota Multiphasic Personality Inventory-2-Restructed Form (MMPI-2-RF) as part of their psychological evaluation. We performed two separate latent profile analyses using four temperament and four character indicators of the TCI to identify personality profiles and nine restructured clinical scales of the MMPI-2-RF to identify symptom patterns. ResultsFive personality classes emerged: “vulnerable-maladaptive,” “stable-adaptive,” “average,” “inhibited-neurotic,” and “impulsive-irrational.” Moreover, six symptom classes emerged: “non-distressed,” “depressed,” “emotionally-distressed,” “average,” “dysfunctional thoughts,” and “confused.” The personality profiles comprising a combination of rigid temperament and immature character were related to patterns of more severe subjective pain and symptoms. However, profiles with less rigid temperament and less immature character exhibited more diverse symptom patterns. ConclusionsThis study examined the relationship between personality profiles and symptomatology patterns, suggesting that understanding patients' personality profiles may be helpful in predicting symptom manifestation and establishing treatment plans.