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Maladaptive Behaviours Associated with Generalized Anxiety Disorder: An Item Response Theory Analysis

Published online by Cambridge University Press:  19 March 2018

Alison E.J. Mahoney*
Affiliation:
Clinical Research Unit for Anxiety and Depression, University of New South Wales at St Vincent's Hospital, Sydney, NSW, Australia
Megan J. Hobbs
Affiliation:
Clinical Research Unit for Anxiety and Depression, University of New South Wales at St Vincent's Hospital, Sydney, NSW, Australia
Jill M. Newby
Affiliation:
Department of Psychology, University of New South Wales, Sydney, NSW, Australia
Alishia D. Williams
Affiliation:
Department of Clinical and Health Psychology, Utrecht University, The Netherlands
Gavin Andrews
Affiliation:
Clinical Research Unit for Anxiety and Depression, University of New South Wales at St Vincent's Hospital, Sydney, NSW, Australia
*
*Correspondence to Dr Alison Mahoney, Clinical Research Unit for Anxiety and Depression, University of New South Wales at St Vincent's Hospital, Level 4 O'Brien Centre, 394–404 Victoria Street, Darlinghurst, NSW, Australia, 2010. E-mail: Alison.Mahoney@svha.org.au

Abstract

Background: Cognitive models of generalized anxiety disorder (GAD) suggest that maladaptive behaviours may contribute to the maintenance of the disorder; however, little research has concentrated on identifying and measuring these behaviours. To address this gap, the Worry Behaviors Inventory (WBI) was developed and has been evaluated within a classical test theory (CTT) approach. Aims: As CTT is limited in several important respects, this study examined the psychometric properties of the WBI using an Item Response Theory approach. Method: A large sample of adults commencing treatment for their symptoms of GAD (n = 537) completed the WBI in addition to measures of GAD and depression symptom severity. Results: Patients with a probable diagnosis of GAD typically engaged in four or five maladaptive behaviours most or all of the time in an attempt to prevent, control or avoid worrying about everyday concerns. The two-factor structure of the WBI was confirmed, and the WBI scales demonstrated good reliability across a broad range of the respective scales. Together with previous findings, our results suggested that hypervigilance and checking behaviours, as well as avoidance of saying or doing things that are worrisome, were the most relevant maladaptive behaviours associated with GAD, and discriminated well between adults with low, moderate and high degrees of the respective WBI scales. Conclusions: Our results support the importance of maladaptive behaviours to GAD and the utility of the WBI to index these behaviours. Ramifications for the classification, theoretical conceptualization and treatment of GAD are discussed.

Type
Research Article
Copyright
Copyright © British Association for Behavioural and Cognitive Psychotherapies 2018 

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References

Andrews, G., Hobbs, M. J., Borkovec, T. D., Beesdo, K., Craske, M. G., Heimberg, R. G. et al. (2010). Generalised worry disorder: a review of DSM-IV generalised anxiety disorder and options for DSM-V. Depression and Anxiety, 27, 134147.Google Scholar
Andrews, G., Mahoney, A. E. J, Hobbs, M. J. and Genderson, M. (2016). Treatment of Generalized Anxiety Disorder: Therapist Guides and Patient Manual. Oxford: Oxford University Press.Google Scholar
Andrews, G. and Williams, A. D. (2015). Up-scaling internet-based cognitive behavioral therapy (iCBT) for depression: a model for dissemination into primary care. Clinical Psychology Review, 41, 4048.Google Scholar
American Psychiatric Association (1987). Diagnostic and Statistical Manual for Mental Disorders (3rd edn). Washington, DC.Google Scholar
American Psychiatric Association (2013). Diagnostic and Statistical Manual for Mental Disorders (5th edn). Washington, DC.Google Scholar
Australian Bureau of Statistics (2013). Australian Statistical Geography Standard (ASGS) (vol. 4). Canberra, Australia: Australian Bureau of Statistics.Google Scholar
Beard, C., Hsu, K. J., Rifkin, L. S., Busch, A. B. and Björgvinsson, T. (2016). Validation of the PHQ-9 in a psychiatric sample. Journal of Affective Disorders, 193, 267273.Google Scholar
Beesdo-Baum, K., Jenjahn, E., Hofler, M., Lueken, U., Becker, E. S. and Hoyer, J. (2012). Avoidance, safety behavior, and reassurance-seeking in generalized anxiety disorder. Depression and Anxiety, 29, 948957.Google Scholar
Cai, L. (2017). flexMIRTR version 3.51: Flexible multilevel multidimensional item analysis and test scoring [computer software]. Chapel Hill, NC: Vector Psychometric Group.Google Scholar
Coleman, S. L., Pieterfesa, A. S., Holaway, R. M., Coles, M. E. and Heimberg, R. G. (2011). Content and correlates of checking related to symptoms of obsessive compulsive disorder and generalised anxiety disorder. Journal of Anxiety Disorders, 25, 293301.Google Scholar
Dugas, M. J., Gagnon, F., Ladouceur, R. and Freeston, M. H. (1998). Generalized anxiety disorder: a preliminary test of a conceptual model. Behavior Research and Therapy, 36, 215226.Google Scholar
Furukawa, T. A., Kessler, R. C., Slade, T. and Andrews, G. (2003). The performance of the K6 and K10 screening scales for psychological distress in the Australian National Survey of Mental Health and Well-Being. Psychological Medicine, 33, 357362.Google Scholar
Hu, L. T. and Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3, 424453.Google Scholar
Kang, T. and Chen, T. T. (2011). Performance of the generalized S-X2 item fit index for the graded response model. Asia Pacific Educational Review, 12, 8996.Google Scholar
Kessler, R. C., Andrews, G., Colpe, L. J., Hiripi, E., Mroczek, D. K., Normand, S. T. et al. (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine, 32, 959976.Google Scholar
Kroenke, K., Spitzer, R. and Williams, J. B. (2001). The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine, 16, 606613.Google Scholar
Kroenke, K., Spitzer, R., Williams, J. B. and Löwe, B. (2010). The Patient Health Questionnaire Somatic, Anxiety, and Depressive Symptom Scales: a systematic review. General Hospital Psychiatry, 32, 345359.Google Scholar
Löwe, B., Decker, O., Müller, S., Brähler, E., Schellberg, D., Herzog, W. et al. (2008). Validation and standardization of the Generalized Anxiety Disorder Screener (GAD-7) in the general population. Medical Care, 46, 266274.Google Scholar
MacCallum, R. C., Browne, M. W. and Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1, 130149.Google Scholar
Mahoney, A., Hobbs, M. J., Newby, J. M., Williams, A. D., Sunderland, M. and Andrews, G. (2016). The Worry Behaviors Inventory: assessing the behavioral avoidance associated with generalized anxiety disorder. Journal of Affective Disorders, 203, 256264.Google Scholar
Mahoney, A., Hobbs, M. J., Newby, J. M., Williams, A. D. and Andrews, G. (2018). Psychometric properties of the Worry Behaviors Inventory: replication and extension in a large clinical and community sample. Behavioral and Cognitive Psychotherapy, 46, 84100.Google Scholar
Mewton, L., Wong, N. and Andrews, G. (2012). The effectiveness of internet cognitive behavioral therapy for generalized anxiety disorder in clinical practice. Depression and Anxiety, 29, 843849.Google Scholar
Muthén, B. (2001). Statmodel discussion: comment 16 July 2001, 1035 regarding the converting MPlus output for polytonomous items to item response theory parameters of Samejima's graded response model. Available at: http://www.statmodel.com/discussion/messages/23/35.html (accessed 21 August 2017).Google Scholar
Muthén, L. K. and Muthén, B. O. (1998– 2015). Mplus User's Guide, 7th edn. Los Angeles, CA: Muthén and Muthén.Google Scholar
Newby, J. M., Mewton, L. and Andrews, G. (2017). Transdiagnostic versus disorder-specific internet-delivered cognitive behavior therapy for anxiety and depression in primary care. Journal of Anxiety Disorders, 46, 2534.Google Scholar
Orlando, M. and Thissen, D. (2000). Likelihood-based item-fit indices for dichotomous item response theory models. Applied Psychological Measurement, 24, 5064.Google Scholar
Reckase, M. D. (2009). Multidimensional Item Response Theory. New York, NY: Springer.Google Scholar
Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F., Crane, P. K., Teresi, J. A. et al. (2007). Psychometric evaluation and calibration of health-related quality of life item banks: plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Medical Care, 45 (suppl 1), S22–31.Google Scholar
Reise, S. P., Ainsworth, A. T. and Haviland, M. G. (2005). Item response theory: fundamentals, application, and promise in psychological research. Current Directions in Psychological Science, 14, 95101.Google Scholar
Reise, S. P. and Waller, N. G. (2009). Item response theory and clinical measurement. Annual Review of Clinical Psychology, 5, 2748.Google Scholar
Robichaud, M. (2013). Cognitive behavior therapy targeting intolerance of uncertainty: application to a clinical case of generalized anxiety disorder. Cognitive and Behavioral Practice, 20, 251263.Google Scholar
Robinson, E., Titov, N., Andrews, G., McIntyre, K., Schwencke, G. and Solley, K. (2010). Internet treatment for generalised anxiety disorder: a randomized controlled trial comparing clinician vs. technician assistance. PLoS ONE, 5, e10942.Google Scholar
Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometric Monograph No. 17. Psychometric Society: Richmond, VA.Google Scholar
Santor, D. A. and Ramsay, J. O. (1998). Progress in the technology of measurement: Application of item response theory. Psychological Assessment, 10, 345359.Google Scholar
Schut, A. J., Castonguay, L. G. and Borkovec, T. D. (2001). Compulsive checking behaviors in generalised anxiety disorder. Journal of Clinical Psychology, 57, 705715.Google Scholar
Spitzer, R. L., Kroenke, K., Williams, J. B. and Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of Internal Medicine, 166, 10921097.Google Scholar
Sunderland, M., Mahoney, A. and Andrews, G. (2012). Investigating the factor structure of the Kessler 10 Psychological Distress Scale in community and clinical samples of the Australian population. Journal of Psychopathology and Behavioral Assessment, 34, 253259.Google Scholar
Tallis, F. and de Silva, P. (1992). Worry and obsessional symptoms: a correlational analysis. Behavior Research and Therapy, 30, 103105.Google Scholar
Thissen, D. and Wainer, H. (eds) (2001). Test Scoring. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Titov, N., Andrews, G., Robinson, E., Schwencke, E., Johnston, L., Solley, K. and Choi, I. (2009). Clinician-assisted Internet-based treatment is effective for generalized anxiety disorder: a randomized controlled trial. Australian and New Zealand Journal of Psychiatry, 43, 905912.Google Scholar
Townsend, M. H., Weissbecker, K. A., Barbee, J. G., Peña, J. M., Snider, L. M., Tynes, L. L. et al. (1999). Compulsive behaviors in generalised anxiety disorder. Journal of Nervous and Mental Disease, 187, 697699.Google Scholar
Wells, A. (1995). Meta-cognition and worry: a cognitive model of generalized anxiety disorder. Behavioral and Cognitive Psychotherapy, 23, 301320.Google Scholar
Wells, A. (1999). A metacognitive model and therapy for generalized anxiety disorder. Clinical Psychology and Psychotherapy, 6, 8695.Google Scholar
Zbozinek, T. D., Rose, R. D., Wolitzky-Taylor, K. B., Sherbourne, C., Sullivan, G., Stein, M. B. et al. (2012). Diagnostic overlap of generalized anxiety disorder and major depressive disorder in a primary care sample. Depression and Anxiety, 29, 10651071.Google Scholar
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