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Modeling and treating internalizing psychopathology in a clinical trial: a latent variable structural equation modeling approach

  • M. G. Kushner (a1), R. F. Krueger (a2), M. M. Wall (a3), E. W. Maurer (a1), J. S. Menk (a4) and K. R. Menary (a1)...

Clinical trials are typically designed to test the effect of a specific treatment on a single diagnostic entity. However, because common internalizing disorders are highly correlated (‘co-morbid’), we sought to establish a practical and parsimonious method to characterize and quantify changes in a broad spectrum of internalizing psychopathology targeted for treatment in a clinical trial contrasting two transdiagnostic psychosocial interventions.


Alcohol dependence treatment patients who had any of several common internalizing disorders were randomized to a six-session cognitive-behavioral therapy (CBT) experimental treatment condition or a progressive muscle relaxation training (PMRT) comparison treatment condition. Internalizing psychopathology was characterized at baseline and 4 months following treatment in terms of the latent structure of six distinct internalizing symptom domain surveys.


Exploratory structural equation modeling (ESEM) identified a two-factor solution at both baseline and the 4-month follow-up: Distress (measures of depression, trait anxiety and worry) and Fear (measures of panic anxiety, social anxiety and agoraphobia). Although confirmatory factor analysis (CFA) demonstrated measurement invariance between the time-points, structural models showed that the latent means of Fear and Distress decreased substantially from baseline to follow-up for both groups, with a small but statistically significant advantage for the CBT group in terms of Distress (but not Fear) reduction.


The approach demonstrated in this study provides a practical solution to modeling co-morbidity in a clinical trial and is consistent with converging evidence pointing to the dimensional structure of internalizing psychopathology.

Corresponding author
*Address for correspondence: M. G. Kushner, Ph.D., 282-2A West, 2450 Riverside Avenue, Minneapolis, MN 55454, USA. (Email:
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Psychological Medicine
  • ISSN: 0033-2917
  • EISSN: 1469-8978
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