Comparison of alternative models for personality disorders, II: 6-, 8- and 10-year follow-up

Psychol Med. 2012 Aug;42(8):1705-13. doi: 10.1017/S0033291711002601. Epub 2011 Dec 2.

Abstract

Background: Several conceptual models have been considered for the assessment of personality pathology in DSM-5. This study sought to extend our previous findings to compare the long-term predictive validity of three such models: the five-factor model (FFM), the schedule for nonadaptive and adaptive personality (SNAP), and DSM-IV personality disorders (PDs).

Method: An inception cohort from the Collaborative Longitudinal Personality Disorder Study (CLPS) was followed for 10 years. Baseline data were used to predict long-term outcomes, including functioning, Axis I psychopathology, and medication use.

Results: Each model was significantly valid, predicting a host of important clinical outcomes. Lower-order elements of the FFM system were not more valid than higher-order factors, and DSM-IV diagnostic categories were less valid than dimensional symptom counts. Approaches that integrate normative traits and personality pathology proved to be most predictive, as the SNAP, a system that integrates normal and pathological traits, generally showed the largest validity coefficients overall, and the DSM-IV PD syndromes and FFM traits tended to provide substantial incremental information relative to one another.

Conclusions: DSM-5 PD assessment should involve an integration of personality traits with characteristic features of PDs.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Validation Study

MeSH terms

  • Adolescent
  • Adult
  • Cohort Studies
  • Diagnostic and Statistical Manual of Mental Disorders*
  • Female
  • Follow-Up Studies
  • Humans
  • Interview, Psychological
  • Male
  • Middle Aged
  • Models, Psychological*
  • Personality
  • Personality Assessment / statistics & numerical data*
  • Personality Disorders / classification*
  • Personality Disorders / diagnosis
  • Personality Inventory / statistics & numerical data
  • Predictive Value of Tests
  • Young Adult