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Factor mixture modeling of anxiety sensitivity: a three-class structure.

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Anxiety sensitivity (AS) is a dimensional-categorical construct. This study identified three distinct classes of AS, impacting anxiety and depression symptoms, with implications for clinical assessment.

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Area of Science:

  • Psychology
  • Clinical Psychology
  • Psychometrics

Background:

  • Anxiety sensitivity (AS) is a multidimensional construct linked to anxiety and depression.
  • Recent research suggests AS may be a dimensional-categorical construct, not purely dimensional.
  • Understanding AS's latent structure is crucial for its role in psychopathology.

Purpose of the Study:

  • To examine the latent structure of anxiety sensitivity (AS) using factor mixture modeling.
  • To identify distinct classes of individuals based on AS factor levels and relations.
  • To investigate the relationship between identified AS classes and anxiety/depression symptoms.

Main Methods:

  • Factor mixture modeling was applied to a sample of 1,151 college students.
  • Latent classes of anxiety sensitivity were identified based on factor analysis.
  • Mean levels of anxiety and depression symptoms were compared across identified AS classes.

Main Results:

  • The best-fitting model identified three distinct classes of anxiety sensitivity: normative, moderate, and high.
  • Relations between AS factors differed across classes, being strongest in the normative class.
  • Significant differences in anxiety and depression symptoms were observed across classes, excluding social anxiety disorder.

Conclusions:

  • This study provides empirical support for anxiety sensitivity as a dimensional-categorical construct with three distinct classes.
  • Findings suggest tailored clinical approaches may be beneficial for individuals in different AS classes.
  • The identification of a third AS class has implications for developing specific assessment cut-scores and targeted interventions.