Examining the latent structure of anxiety sensitivity in adolescents using factor mixture modeling

Psychol Assess. 2014 Sep;26(3):741-51. doi: 10.1037/a0036744. Epub 2014 Apr 21.

Abstract

Anxiety sensitivity has been implicated as an important risk factor, generalizable to most anxiety disorders. In adults, factor mixture modeling has been used to demonstrate that anxiety sensitivity is best conceptualized as categorical between individuals. That is, whereas most adults appear to possess normative levels of anxiety sensitivity, a small subset of the population appears to possess abnormally high levels of anxiety sensitivity. Further, those in the high anxiety sensitivity group are at increased risk of having high levels of anxiety and of having an anxiety disorder. This study was designed to determine whether these findings extend to adolescents. Factor mixture modeling was used to examine the best fitting model of anxiety sensitivity in a sample of 277 adolescents (M age = 11.0 years, SD = 0.81). Consistent with research in adults, the best fitting model consisted of 2 classes, 1 containing adolescents with high levels of anxiety sensitivity (n = 25) and another containing adolescents with normative levels of anxiety sensitivity (n = 252). Examination of anxiety sensitivity subscales revealed that the social concerns subscale was not important for classification of individuals. Convergent and discriminant validity of anxiety sensitivity classes were found in that membership in the high anxiety sensitivity class was associated with higher mean levels of anxiety symptoms, controlling for depression and externalizing problems, and was not associated with higher mean levels of depression or externalizing symptoms controlling for anxiety problems.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Anxiety / psychology*
  • Anxiety Disorders / psychology*
  • Child
  • Depression / psychology*
  • Female
  • Humans
  • Male
  • Models, Psychological
  • Reproducibility of Results
  • Risk Factors