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

Published online by Cambridge University Press:  09 January 2013

M. G. Kushner*
Affiliation:
Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
R. F. Krueger
Affiliation:
Department of Psychology, University of Minnesota, Minneapolis, MN, USA
M. M. Wall
Affiliation:
Departments of Psychiatry and Biostatistics, Columbia University, New York City, NY, USA
E. W. Maurer
Affiliation:
Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
J. S. Menk
Affiliation:
Biostatistical Design and Analysis Center, Clinical and Translational Science Institute, University of Minnesota, Minneapolis, MN, USA
K. R. Menary
Affiliation:
Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
*
*Address for correspondence: M. G. Kushner, Ph.D., 282-2A West, 2450 Riverside Avenue, Minneapolis, MN 55454, USA. (Email: [email protected])

Abstract

Background

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.

Method

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.

Results

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.

Conclusions

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.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2013 

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References

Andrews, G, Goldberg, DP, Krueger, RF, Carpenter, WT, Hyman, SE, Sachdev, P, Pine, DS (2009). Exploring the feasibility of a meta-structure for DSM-V and ICD-11: could it improve utility and validity? Psychological Medicine 39, 19932000.CrossRefGoogle ScholarPubMed
Andrews, G, Slade, T, Issakidis, C (2002). Deconstructing current comorbidity: data from the Australian National Survey of Mental Health and Well-Being. British Journal of Psychiatry 181, 306314.CrossRefGoogle ScholarPubMed
APA (1980). Diagnostic and Statistical Manual of Mental Disorders, 3rd edn.American Psychiatric Association: Washington, DC.Google Scholar
Barlow, DH, Allen, LB, Choate, ML (2004). Toward a unified treatment for emotional disorders. Behavior Therapy 35, 205230.CrossRefGoogle Scholar
Barlow, DH, Craske, MG, Cerny, JA, Klosko, JS (1989). Behavioral treatment of panic disorder. Behavior Therapy 20, 261282.CrossRefGoogle Scholar
Beck, AT (1976). Cognitive Therapy and the Emotional Disorders. International Universities Press: New York.Google Scholar
Beck, AT, Rush, AJ, Shaw, BF, Emery, G (1979). Cognitive Therapy of Depression. Guilford Press: New York.Google Scholar
Beck, AT, Ward, CH, Mendelson, M, Mock, J, Erbaugh, J (1961). An inventory for measuring depression. Archives of General Psychiatry 4, 5363.CrossRefGoogle ScholarPubMed
Beekman, AT, de Beurs, E, van Balkom, AJ, Deeg, DJ, van Dyck, R, van Tilburg, W (2000). Anxiety and depression in later life: co-occurrence and communality of risk factors. American Journal of Psychiatry 157, 8995.CrossRefGoogle ScholarPubMed
Bernstein, DA, Borkovec, TD (1973). Progressive Relaxation Training. A Manual for the Helping Professions. Research Press: Champaign, IL.Google Scholar
Borsboom, D, Mellenbergh, G, van Heerden, J (2003). The theoretical status of latent variables. Psychological Review 110, 203219.CrossRefGoogle ScholarPubMed
Brown, EJ, Turovsky, J, Heimberg, RG, Juster, HR, Brown, TA, Barlow, DH (1997). Validation of the Social Interaction Anxiety Scale and the Social Phobia Scale across the anxiety disorders. Psychological Assessment 9, 2127.CrossRefGoogle Scholar
Brown, SA, Irwin, M, Schuckit, MA (1991). Changes in anxiety among abstinent male alcoholics. Journal of Studies on Alcohol 52, 5561.CrossRefGoogle ScholarPubMed
Brown, TA, Campbell, LA, Lehman, CL, Grisham, JR, Mancill, RB (2001). Current and lifetime comorbidity of the DSM-IV anxiety and mood disorders in a large clinical sample. Journal of Abnormal Psychology 110, 585599.CrossRefGoogle Scholar
Chambless, DL, Caputo, GC, Jasin, SE, Gracely, EJ, Williams, C (1985). The Mobility Inventory for Agoraphobia. Behaviour Research and Therapy 23, 3544.CrossRefGoogle ScholarPubMed
Eaton, NR, Krueger, RF, Oltmanns, TF (2011). Aging and the structure and the long-term stability of the internalizing spectrum of personality and psychopathology. Psychology and Aging 26, 987993.CrossRefGoogle ScholarPubMed
Ellard, KK, Fairholme, CP, Boisseau, CL, Farchione, TJ, Barlow, DH (2010). Unified protocol for the transdiagnostic treatment of emotional disorders: protocol development and initial outcome data. Cognitive Behavioral Practice 17, 88101.CrossRefGoogle ScholarPubMed
Ellis, A, Harper, RO (1975). A New Guide to Rational Living. Prentice-Hall: Oxford, UK.Google Scholar
Foa, EB, Kozak, MJ (1986). Emotional processing of fear: exposure to corrective information. Psychological Bulletin 99, 2035.CrossRefGoogle ScholarPubMed
First, MB, Spitzer, R, Gibbon, M, Williams, J (1989). Structural Clinical Interview for Axis-I DSM-IV Disorders Patient Edition (SCID-I/P Version 2.0). New York State Psychiatric Institution: New York, NY.Google Scholar
Heimberg, RG, Dodge, CS, Hope, DA, Kennedy, CR, Zollo, LJ, Becker, RE (1990). Cognitive behavioral group treatment for social phobia: comparison with a credible placebo control. Cognitive Therapy and Research 14, 123.CrossRefGoogle Scholar
Houck, PR, Spiegel, DA, Shear, MK, Rucci, P (2002). Reliability of the self-report version of the Panic Disorder Severity Scale. Depression and Anxiety 15, 183185.CrossRefGoogle ScholarPubMed
Hu, L, Bentler, PM (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling 6, 155.CrossRefGoogle Scholar
Jacobson, E (1938). Progressive Relaxation, 2nd edn.University of Chicago Press: Oxford, UK.Google Scholar
Kendler, KS, Prescott, CA, Myers, J, Neale, MC (2003). The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Archives of General Psychiatry 60, 929937.CrossRefGoogle ScholarPubMed
Kessler, RC, Chiu, W, Demler, O, Walters, E (2005). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 62, 617627.CrossRefGoogle ScholarPubMed
Kessler, RC, Ormel, J, Petukhova, M, McLaughlin, KA, Green, JG, Russo, LJ, Stein, DJ, Zaslavsky, AM, Aguilar-Gaxiola, S, Alonso, J, Andrade, L, Benjet, C, de Girolamo, G, de Graaf, R, Demyttenaere, K, Fayyad, J, Haro, JM, Hu, CY, Karam, A, Lee, S, Lepine, J, Matchsinger, H, Mihaescu-Pintia, C, Posada-Villa, J, Sagar, R, Üstün, TB (2011). Development of lifetime comorbidity in the World Health Organization World Mental Health Surveys. Archives of General Psychiatry 68, 90100.CrossRefGoogle ScholarPubMed
Kline, RB (2010). Principles and Practice of Structural Equation Modeling. Guilford Press: New York.Google Scholar
Krueger, RF (1999). The structure of common mental disorders. Archives of General Psychiatry 56, 921926.CrossRefGoogle ScholarPubMed
Krueger, RF, Finger, MS (2001). Using item response theory to understand comorbidity among anxiety and unipolar mood disorders. Psychological Assessment 13, 140151.CrossRefGoogle ScholarPubMed
Krueger, RF, Goldman, D (2010). The need for dimensional approaches in discerning the origins of psychopathology. In Causality and Psychopathology: Finding the Determinants of Disorders and their Cures (ed. Shrout, P., Keyes, K. and Ornstein, K.), pp. 338351. Oxford University Press: New York.Google Scholar
Krueger, RF, Markon, KE (2006). Reinterpreting comorbidity: a model-based approach to understanding and classifying psychopathology. Annual Review of Clinical Psychology 2, 111133.CrossRefGoogle ScholarPubMed
Kushner, MG, Abrams, K, Thuras, P, Hanson, KL, Brekke, M, Sletten, S (2005). Follow-up study of anxiety disorder and alcohol dependence in comorbid alcoholism treatment patients. Alcoholism: Clinical and Experimental Research 29, 14321443.CrossRefGoogle ScholarPubMed
Kushner, MG, Maurer, EW, Thuras, P, Donahue, C, Frye, B, Menary, KR, Hobbs, J, Haeny, AM, Van Demark, J (in press). Hybrid cognitive-behavioral therapy versus relaxation training for co-occurring anxiety and alcohol disorder: a randomized clinical trial. Journal of Consulting and Clinical Psychology.Google Scholar
Kushner, MG, Wall, MM, Krueger, RF, Sher, KJ, Maurer, E, Thuras, P, Lee, S (2012). Alcohol dependence is related to overall internalizing psychopathology load rather than to particular internalizing disorders: evidence from a national sample. Alcoholism: Clinical and Experimental Research 36, 325331.CrossRefGoogle ScholarPubMed
Little, RJA, Rubin, DB (2002). Statistical Analysis with Missing Data, 2nd edn.John Wiley & Sons: New York.CrossRefGoogle Scholar
Mansell, W, Harvey, A, Watkins, ER, Shafran, R (2008). Cognitive behavioral processes across psychological disorders: a review of the utility and validity of the transdiagnostic approach. International Journal of Cognitive Therapy 1, 181191.CrossRefGoogle Scholar
Mansell, W, Harvey, A, Watkins, E, Shafran, R (2009). Conceptual foundations of the transdiagnostic approach to CBT. Journal of Cognitive Psychotherapy 23, 619.CrossRefGoogle Scholar
Markon, KE (2010). Modeling psychopathology structure: a symptom-level analysis of Axis I and II disorders. Psychological Medicine 40, 273288.CrossRefGoogle ScholarPubMed
Marsh, HW, Muthén, B, Asparouhov, T, Lüdtke, O, Robitzsch, A, Morin, AJS, Trautwein, U (2009). Exploratory structural equation modeling, integrating CFA and EFA: application to students' evaluations of university teaching. Structural Equation Modeling 16, 439476.CrossRefGoogle Scholar
McGlinchey, JB, Zimmerman, M (2007). Examining a dimensional representation of depression and anxiety disorders' comorbidity in psychiatric outpatients with item response modeling. Journal of Abnormal Psychology 116, 464474.CrossRefGoogle ScholarPubMed
Meredith, W (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika 58, 525543.CrossRefGoogle Scholar
Meyer, TJ, Miller, ML, Metzger, RL, Borkovec, TD (1990). Development and validation of the Penn State Worry Questionnaire. Behaviour Research and Therapy 28, 487495.CrossRefGoogle ScholarPubMed
Millsap, RE, Hartog, SB (1988). Alpha, beta and gamma change in evaluation research: a structural equation approach. Journal of Applied Psychology 73, 574584.CrossRefGoogle Scholar
Mineka, S, Watson, D, Clark, LA (1998). Comorbidity of anxiety and unipolar mood disorders. Annual Review of Psychology 49, 377412.CrossRefGoogle ScholarPubMed
Moffitt, TE, Harrington, H, Caspi, A, Kim-Cohen, J, Goldberg, D, Gregory, AM, Poulton, R (2007). Depression and generalized anxiety disorder: cumulative and sequential comorbidity in a birth cohort followed prospectively to age 32 years. Archives of General Psychiatry 64, 651660.CrossRefGoogle Scholar
Muthén, LK, Muthén, BO (2011). Mplus User's Guide, 6th edn.Muthén & Muthén: Los Angeles, CA.Google Scholar
Simms, LJ, Prisciandaro, JJ, Kruger, RF, Goldberg, DP (2012). The structure of depression, anxiety and somatic symptoms in primary care. Psychological Medicine 42, 1528.CrossRefGoogle ScholarPubMed
Spielberger, CD, Sydeman, SJ, Owen, AE, Marsh, BJ (1999). Measuring anxiety and anger with the State-Trait Anxiety Inventory (STAI) and State-Trait Anger Expression Inventory (STAXI). In The Use of Psychological Testing for Treatment Planning and Outcome Assessment, 2nd edn (ed. Maruish, M. E.), pp. 295300. Lawrence Erlbaum Associates: Mahwah, NJ.Google Scholar
Vrieze, SI (2012). Model selection and psychological theory: a discussion of the differences between the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). Psychological Methods 17, 228243.CrossRefGoogle ScholarPubMed
Watson, D (2009). Differentiating the mood and anxiety disorders: a quadripartite model. Annual Review of Clinical Psychology 5, 221247.CrossRefGoogle ScholarPubMed