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A prototype approach to personality disorder diagnosis.

Drew Westen1, Jonathan Shedler, Rebekah Bradley

  • 1Department of Psychology, Emory University, 532 N. Kilgo Cir., Atlanta, GA 30322, USA. dwesten@emory.edu

The American Journal of Psychiatry
|May 2, 2006
PubMed
Summary

A new prototype matching method simplifies personality disorder diagnosis, reducing comorbidity and improving clinical utility compared to the traditional count/cutoff method. This approach offers a viable alternative for clinical practice.

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Area of Science:

  • Psychiatry
  • Clinical Psychology
  • Mental Health Diagnostics

Background:

  • Current diagnostic methods for personality disorders, established since DSM-III, rely on a count/cutoff approach for symptom presence/absence.
  • Limited research has explored alternative diagnostic procedures to simplify the process.

Purpose of the Study:

  • To test a prototype matching procedure as a simplified alternative to the traditional count/cutoff method for diagnosing personality disorders.
  • To evaluate the clinical utility and diagnostic accuracy of prototype matching compared to existing DSM-IV criteria.

Main Methods:

  • A national sample of 291 psychiatrists and psychologists diagnosed a patient using either a prototype matching system or standard DSM-IV criteria.
  • Diagnostic data included categorical and dimensional assessments of personality disorders.

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Main Results:

  • Prototype diagnosis resulted in lower comorbidity than DSM-IV diagnosis.
  • Prototype matching showed comparable validity in predicting adaptive functioning, treatment response, and etiology.
  • Prototype diagnosis was rated higher for clinical utility and ease of use.
  • Incorporating a personality health prototype enhanced predictive accuracy.

Conclusions:

  • A simple prototype matching procedure offers a practical and effective alternative for diagnosing personality disorders in clinical settings.
  • This method simplifies diagnosis, reduces artifactual comorbidity, aligns with cognitive processes, and supports both categorical and dimensional diagnostic outputs.