Detecting personality disorders in a nonclinical population. Application of a 2-stage procedure for case identification

Arch Gen Psychiatry. 1997 Apr;54(4):345-51. doi: 10.1001/archpsyc.1997.01830160073010.

Abstract

Background: There is no epidemiology of personality disorders (PDs) comparable with that currently available for most other mental disorders. One reason for this is that an Axis II diagnosis usually requires considerable clinical sophistication and it is expensive to deploy clinicians rather than trained laypersons to examine large community samples. This study explores the feasibility of using a 2-stage method in which only subjects who were screened as positive for PD would be interviewed by clinicians.

Methods: University students were screened with a self-administered Axis II inventory and subsequently interviewed by clinicians with the use of the International Personality Disorder Examination.

Results: The screen detected all individuals who subsequently received a definite diagnosis on the interview, and a specificity rate of detection was 61%. The point-prevalence estimate for diagnosable PD in this nonclinical population was 11.01% (95% confidence interval, 7.57%-14.52%).

Conclusion: If these results can be replicated in a more representative community sample, this 2-stage method might substantially reduce the number of persons who needed to be interviewed in a major epidemiological study of PDs, with little or no loss in diagnostic accuracy, while presumably lowering the cost of such an investigation.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Confidence Intervals
  • Data Collection / economics
  • Educational Status
  • Female
  • Health Surveys
  • Humans
  • Male
  • Mental Disorders / diagnosis
  • Mental Disorders / epidemiology
  • Personality Disorders / diagnosis*
  • Personality Disorders / epidemiology*
  • Personality Inventory
  • Prevalence
  • Psychiatric Status Rating Scales / statistics & numerical data
  • Random Allocation
  • Sampling Studies