Testing a Hierarchical Model of Distress Tolerance

  • Joseph R. BardeenEmail author
  • Thomas A. Fergus
  • Holly K. Orcutt


Distress tolerance (DT) has been suggested as an individual difference factor with transdiagnostic importance. To date, determining the transdiagnostic status of DT has been limited due to the lack of consensus regarding the construct’s conceptualization. Zvolensky et al. (Current Directions in Psychological Science 19:406–410, 2010) developed a hierarchical model of DT that seeks to unify different conceptualizations of DT that have emerged across literatures (i.e., intolerance of uncertainty, ambiguity, frustration, physical sensations, and negative emotional states). Through exploratory and confirmatory factor analyses, the present study provided the first known empirical test of Zvolensky et al.’s hierarchical experiential distress (in)tolerance model in a large community sample of adults (N = 830). Results indicated that the five lower-order DT constructs are factorially distinct. The magnitude of the latent relations among the DT constructs is consistent with the proposition that all five lower-order constructs belong to the same domain. The fit of Zvolensky et al.’s five-factor higher-order model suggests that a higher-order DT construct accounts for the interrelations among the latent factors. Overall, results are consistent with Zvolensky et al.’s hierarchical DT model. Findings provide an important step in clarifying the nature of DT and provide a platform from which cross-study comparisons may be made.


Distress tolerance Assessment Uncertainty Ambiguity Frustration Discomfort Negative emotions 


  1. Anestis, M. D., Fink, E. L., Smith, A. R., Selby, E. A., & Joiner, T. E. (2011). Eating disorders. In M. Zvolensky, A. Bernstein, & A. Vujanovic (Eds.), Distress tolerance: Theory, research, and clinical applications (pp. 245–260). New York: Guilford Press.Google Scholar
  2. Arbuckle, J. L. (2010). Amos (Version 19.0) [Computer software]. Chicago, IL: SPSS.Google Scholar
  3. Bardeen, J. R. Fergus, T. A., & Orcutt, H. K. (in press). Experiential avoidance as a moderator of the relationship between anxiety sensitivity and perceived stress. Behavior Therapy.Google Scholar
  4. Barlow, D. H., Allen, L. B., & Choate, M. L. (2004). Toward a unified treatment for emotional disorders. Behavior Therapy, 35, 205–230.CrossRefGoogle Scholar
  5. Barsky, A. J., Wyshak, G., & Klerman, G. L. (1990). The somatosensory amplification scale and its relationship to hypochondriasis. Journal of Psychiatric Research, 24, 323–334.PubMedCrossRefGoogle Scholar
  6. Behrend, T. S., Sharek, D. J., Meade, A. W., & Wiebe, E. N. (2011). The viability of crowdsourcing for survey research. Behavior Research Methods, 43, 1–14.CrossRefGoogle Scholar
  7. Bentler, P. M. (1990). Comparative fit indices in structural models. Psychological Bulletin, 107, 238–246.PubMedCrossRefGoogle Scholar
  8. Bonn-Miller, M. O., Zvolensky, M. J., & Bernstein, A. (2009). Discomfort intolerance: evaluation of incremental validity for panic-relevant symptoms using 10% carbon dioxide-enriched air provocation. Journal of Anxiety Disorders, 23, 197–203.PubMedCrossRefGoogle Scholar
  9. Bornovalova, M. A., Gratz, K. L., Daughters, S. B., Hunt, E. D., & Lejuez, C. W. (2012). Initial RCT of a distress tolerance treatment for individuals with substance use disorders. Drug and Alcohol Dependence, 122, 70–76.PubMedCrossRefGoogle Scholar
  10. Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: Guilford Press.Google Scholar
  11. Brown, R. A., Lejuez, C. W., Kahler, C. W., Strong, D. R., & Zvolensky, M. J. (2005). Distress tolerance and early smoking lapse. Clinical Psychology Review, 25, 713–733.PubMedCrossRefGoogle Scholar
  12. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. Bollen & J. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage.Google Scholar
  13. Buckner, J. D., Keough, M. E., & Schmidt, N. B. (2007). Problematic alcohol and cannabis use among young adults: the roles of depression and discomfort and distress tolerance. Addictive Behaviors, 32, 1957–1963.PubMedCrossRefGoogle Scholar
  14. Budner, S. (1962). Intolerance of ambiguity as a personality variable. Journal of Personality, 30, 29–50.PubMedCrossRefGoogle Scholar
  15. Buhr, K., & Dugas, M. J. (2002). The intolerance of uncertainty scale: psychometric properties of the English version. Behaviour Research and Therapy, 40, 931–945.PubMedCrossRefGoogle Scholar
  16. Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon’s Mechanical Turk: a new source of inexpensive, yet high quality, data? Perspectives on Psychological Science, 6, 3–5.CrossRefGoogle Scholar
  17. Carleton, R. N., Gosselin, P., & Asmundson, G. J. G. (2010). The intolerance of uncertainty index: replication and extension with an English sample. Psychological Assessment, 22, 396–406.PubMedCrossRefGoogle Scholar
  18. Carleton, R. N., Mulvogue, M. K., Thibodeau, M. A., McCabe, R., Antony, M. M., & Asmundson, G. J. G. (2012). Increasingly certain about uncertainty: intolerance of uncertainty across anxiety and depression. Journal of Anxiety Disorders, 26, 468–479.PubMedCrossRefGoogle Scholar
  19. Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9, 233–255.CrossRefGoogle Scholar
  20. Comrey, A. L., & Lee, H. B. (1992). A first course in factor analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  21. Dugas, M. J., & Robichaud, M. (2007). Cognitive-behavioral treatment for generalized anxiety disorder: From science to practice. New York: Routledge.Google Scholar
  22. Dugas, M. J., Buhr, K., & Ladouceur, R. (2004). The role of intolerance of uncertainty in the etiology and maintenance of generalized anxiety disorder. In R. Heimberg, C. Turk, & D. Mennin (Eds.), Generalized anxiety disorder: advances in research and practice (pp. 143–163). New York: Guilford Press.Google Scholar
  23. Fergus, T. A., & Valentiner, D. P. (2010). Disease phobia and disease conviction are separate dimensions underlying hypochondriasis. Journal of Behavior Therapy and Experimental Psychiatry, 41, 438–444.PubMedCrossRefGoogle Scholar
  24. Freeston, M. H., Rheaume, J., Letarte, H., Dugas, M. J., & Ladouceur, R. (1994). Why do people worry? Personality and Individual Differences, 17, 791–802.CrossRefGoogle Scholar
  25. Gosselin, P., Ladouceur, R., Evers, A., Laverdiere, A., Routhier, S., & Tremblay-Picard, M. (2008). Evaluation of intolerance of uncertainty: development and validation of a new self-report measure. Journal of Anxiety Disorders, 22, 1427–1439.PubMedCrossRefGoogle Scholar
  26. Gratz, K. L., Rosenthal, M. Z., Tull, M. T., Lejuez, C. W., & Gunderson, J. G. (2006). An experimental investigation of emotion dysregulation in borderline personality disorder. Journal of Abnormal Psychology, 115, 850–855.PubMedCrossRefGoogle Scholar
  27. Grenier, S., Barrette, A., & Ladouceur, R. (2005). Intolerance of uncertainty and intolerance of ambiguity: similarities and differences. Personality and Individual Differences, 39, 593–600.CrossRefGoogle Scholar
  28. Harrington, N. (2005). The frustration discomfort scale: development and psychometric properties. Clinical Psychology & Psychotherapy, 12, 374–387.CrossRefGoogle Scholar
  29. Hayes, S. C., Strosahl, K., & Wilson, K. G. (1999). Acceptance and commitment therapy: An experiential approach to behavior change. New York, NY: Guilford Press.Google Scholar
  30. Herman, J. L., Stevens, M. J., Bird, A., Mendenhall, M., & Oddou, G. (2010). The tolerance for ambiguity scale: towards a more refined measure for international management research. International Journal of Intercultural Relations, 34, 58–65.CrossRefGoogle Scholar
  31. Jolliffe, I. T. (2002). Principal component analysis (2nd ed.). New York: Springer.Google Scholar
  32. Jöreskog, K. G., Sörbom, D., du Toit, S., & du Toit, M. (2000). LISEREL 8: new statistical features (2nd ed.). Chicago, IL: Scientific Software International.Google Scholar
  33. Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: Guilford Press.Google Scholar
  34. Leyro, T. M., Zvolesnky, M. J., & Bernstein, A. (2010). Distress tolerance and psychopathological symptoms and disorders: a review of the empirical literature among adults. Psychological Bulletin, 136, 576–600.PubMedCrossRefGoogle Scholar
  35. Linehan, M. M. (1993). Cognitive-behavioral treatment of borderline personality disorder. New York, NY: Guilford Press.Google Scholar
  36. McHugh, K. R., & Otto, M. W. (2012). Refining the measurement of distress intolerance. Behavior Therapy, 43, 641–651.PubMedCrossRefGoogle Scholar
  37. McLain, D. L. (1993). The MSTAT-I: a new measure of an individual’s tolerance for ambiguity. Educational and Psychological Measurement, 53, 183–189.CrossRefGoogle Scholar
  38. Meade, A. W., Johnson, E. C., & Braddy, P. W. (2008). Power and sensitivity of alternative fit indices in tests of measurement invariance. Journal of Applied Psychology, 93, 568–592.PubMedCrossRefGoogle Scholar
  39. Meyers, L. S., Gamst, G., & Guarino, A. (2006). Applied multivariate research: Design and interpretation. Thousand Oaks, CA: Sage Publishers.Google Scholar
  40. Oppenheimer, D. M., Meyvis, T., & Davidenko, N. (2009). Instructional manipulation checks: detecting satisficing to increase statistical power. Journal of Experimental Social Psychology, 45, 867–872.CrossRefGoogle Scholar
  41. Paolacci, G., Chandler, J., & Ipeirotis, P. G. (2010). Running experiments on Amazon Mechanical Turk. Judgment and Decision Making, 5, 411–419.Google Scholar
  42. Richards, J. M., Daughters, S. B., Bornovalova, M. A., Brown, R. A., & Lejuez, C. W. (2011). Substance use disorders. In M. Zvolensky, A. Bernstein, & A. Vujanovic (Eds.), Distress tolerance: Theory, research, and clinical applications (pp. 171–197). New York: Guilford Press.Google Scholar
  43. Schmidt, N. B., Richey, J. A., & Fitzpatrick, K. K. (2006). Discomfort intolerance: development of a construct and measure relevant to panic disorder. Journal of Anxiety Disorders, 20, 263–280.PubMedCrossRefGoogle Scholar
  44. Sexton, K., & Dugas, M. J. (2009). Defining distinct negative beliefs about uncertainty: validating the factor structure of the intolerance of uncertainty scale. Psychological Assessment, 21, 176–186.PubMedCrossRefGoogle Scholar
  45. Simons, J., & Gaher, R. (2005). The distress tolerance scale: development and validation of a self-report measure. Motivation and Emotion, 29, 83–102.CrossRefGoogle Scholar
  46. Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Boston: Allyn & Bacon.Google Scholar
  47. Wang, M., & Russell, S. S. (2005). Measurement equivalence of the job descriptive index across Chinese and American workers: results from confirmatory factor analysis and item response theory. Educational and Psychological Measurement, 65, 709–732.CrossRefGoogle Scholar
  48. Zvolensky, M. J., Marshall, E. C., Johnson, K., Hogan, J., Bernstein, A., & Bonn-Miller, M. O. (2009). Relations between anxiety sensitivity, distress tolerance, and fear reactivity to bodily sensations to coping and conformity marijuana use motives among young adult marijuana users. Experimental and Clinical Psychopharmacology, 17, 31–42.PubMedCrossRefGoogle Scholar
  49. Zvolensky, M. J., Vujanovic, A. A., Bernstein, A., & Leyro, T. (2010). Distress tolerance: theory, measurement, and relations to psychopathology. Current Directions in Psychological Science, 19, 406–410.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Joseph R. Bardeen
    • 1
    • 2
    • 3
    Email author
  • Thomas A. Fergus
    • 4
  • Holly K. Orcutt
    • 1
  1. 1.Department of PsychologyNorthern Illinois UniversityDeKalbUSA
  2. 2.Department of Psychiatry and Human BehaviorUniversity of Mississippi Medical CenterJacksonUSA
  3. 3.G.V. (Sonny) Montgomery VA Medical CenterJacksonUSA
  4. 4.Department of Psychology and NeuroscienceBaylor UniversityWacoUSA

Personalised recommendations