Measuring euthymia within the Neuroticism Scale from the NEO Personality Inventory: A Mokken analysis of the Norwegian general population study for scalability

J Affect Disord. 2016 Mar 15:193:99-102. doi: 10.1016/j.jad.2015.12.039. Epub 2015 Dec 29.

Abstract

Background: Whereas the Eysenck Neuroticism Scale only contains items covering negative mental health to measure dysthymia, the NEO Personality Inventory (NEO-PI) contains neuroticism items covering both negative mental health and positive mental health (or euthymia). The consequence of wording items both positively and negatively within the NEO-PI has never been psychometrically investigated. The aim of this study was to perform a validation analysis of the NEO-PI neuroticism scale.

Methods: Using a Norwegian general population study we examined the structure of the negatively and positively formulated items by principal component analysis (PCA). The scalability of the identified two groups of euthymia versus dysthymia items was examined by Mokken analysis.

Results: With a response rate of 90%, 1082 individuals with a completed NEO-PI were available. The PCA identified the neuroticism scale as the most distinct where 14 items had acceptable loadings for the euthymia subscale, another 14 items for the dysthymia subscale. However, the Mokken analysis coefficient of homogeneity only found acceptable scalability for the euthymia subscale.

Limitations: A comparison with the Eysenck Neuroticism Scale was not performed.

Conclusion: The NEO-PI neuroticism scale contains two subscales consisting of items worded in an opposite direction where only the positive euthymia items have an acceptable scalability.

Keywords: Dysthymia; Euthymia; Mokken analysis; NEO Personality Inventory.

MeSH terms

  • Anxiety Disorders / diagnosis
  • Anxiety Disorders / psychology
  • Cyclothymic Disorder / diagnosis*
  • Cyclothymic Disorder / psychology
  • Dysthymic Disorder / diagnosis
  • Dysthymic Disorder / psychology
  • Humans
  • Neuroticism
  • Norway
  • Personality Inventory*
  • Principal Component Analysis
  • Psychiatric Status Rating Scales*
  • Psychometrics
  • Reproducibility of Results