Predicting Personality Disorder Functioning Styles by the Five-Factor Nonverbal Personality Questionnaire in Healthy Volunteers and Personality Disorder Patients

Psychopathology. 2016;49(1):5-12. doi: 10.1159/000443838. Epub 2016 Feb 24.

Abstract

Background: Detecting personality disorders in the illiterate population is a challenge, but nonverbal tools measuring personality traits such as the Five-Factor Nonverbal Personality Questionnaire (FFNPQ) might help. We hypothesized that FFNPQ traits are associated with personality disorder functioning styles in a predictable way, especially in a sample of personality disorder patients.

Methods: We therefore invited 106 personality disorder patients and 205 healthy volunteers to answer the FFNPQ and the Parker Personality Measure (PERM) which measures 11 personality disorder functioning styles.

Results: Patients scored significantly higher on the FFNPQ neuroticism and conscientiousness traits and all 11 PERM styles. In both groups, the 5 FFNPQ traits displayed extensive associations with the 11 PERM styles, respectively, and the associations were more specific in patients. Associations between neuroticism, extraversion and agreeableness traits and most PERM styles were less exclusive, but conscientiousness was associated with antisocial (-) and obsessive-compulsive styles, and openness to experience with schizotypal and dependent (-) styles.

Conclusions: Our study has demonstrated correlations between FFNPQ traits and PERM styles, and implies the nonverbal measure of personality traits is capable of aiding the diagnoses of personality disorders in the illiterate population. Enlarging sample size and including the illiterate might make for more stable results.

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Female
  • Healthy Volunteers
  • Humans
  • Male
  • Middle Aged
  • Personality / classification*
  • Personality Disorders / diagnosis*
  • Personality Inventory / statistics & numerical data
  • Regression Analysis
  • Surveys and Questionnaires / standards*