Applied Psychophysiology and Biofeedback

, Volume 36, Issue 2, pp 101–112 | Cite as

Exploring the Effectiveness of a Computer-Based Heart Rate Variability Biofeedback Program in Reducing Anxiety in College Students

  • Gregg Henriques
  • Steven Keffer
  • Craig Abrahamson
  • S. Jeanne Horst
Article

Abstract

Given the pervasiveness of stress and anxiety in our culture it is important to develop and implement interventions that can be easily utilized by large numbers of people that are readily available, inexpensive and have minimal side effects. Two studies explored the effectiveness of a computer-based heart rate variability biofeedback program on reducing anxiety and negative mood in college students. A pilot project (n = 9) of highly anxious students revealed sizable decreases in anxiety and negative mood following utilizing the program for 4 weeks. A second study (n = 35) employing an immediate versus delayed treatment design replicated the results, although the magnitude of the impact was not quite as strong. Despite observing decreases in anxiety, the expected changes in psychophysiological coherence were not observed.

Keywords

Anxiety Biofeedback Heart rate variability Heart rhythm coherence 

References

  1. Allison, P. D. (2002). Missing data. (Sage University Papers Series on Quantitative Applications in the Social Sciences, series no. 07–136). Thousand Oaks, CA: Sage.Google Scholar
  2. American College Health Association National College Health Assessment Spring. (2006). Reference group data report (abridged). (January/February 2007). Journal of American College Health, 55(4), 195–206.Google Scholar
  3. Bradley, R. T., McCraty, R., Atkinson, M., Arguelles, L., Rees, R. A., & Tomasino, D. (2007). Reducing test anxiety and improving test performance in America’s schools: results from the TestEdge national demonstration study. Boulder Creek, CA: HeartMath Research Center, Institute of HeartMath. Report no. 07–04-01.Google Scholar
  4. Cohen, H., Matar, M. A., Kaplan, Z., & Kotler, M. (1999). Power spectral analysis of heart rate variability in psychiatry. Psychotherapy and Psychosomatics, 68, 59–66.PubMedCrossRefGoogle Scholar
  5. Friedman, B. H. (2007). An autonomic flexibility-neurovisceral integration model of anxiety and cardiac vagal tone. Biological Psychology, 74(2), 185–199.PubMedCrossRefGoogle Scholar
  6. Giardino, H. D., Chan, L., & Borson, S. (2004). Combined heart rate variability and pulse oximetry biofeedback for chronic obstructive pulmonary disease: Preliminary findings. Applied Psychophysiology and Biofeedback, 29, 121–133.PubMedCrossRefGoogle Scholar
  7. Hair, J. F., Andersen, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  8. Hassett, A. L., Radvanski, D. C., Vaschillo, E. G., Vaschillo, B., Sigal, L. H., Karavidas, M. K., et al. (2007). A pilot study of the efficacy of heart rate variability (HRV) biofeedback in patients with fibromyalgia. Applied Psychophysiology and Biofeedback, 32, 1–10.PubMedCrossRefGoogle Scholar
  9. Karavidas, M. (2005). Heart rate variability biofeedback in the treatment of major depressive disorder. Applied Psychophysiology and Biofeedback, 30, 397–423.CrossRefGoogle Scholar
  10. Lehrer, P. M., Vaschillo, E., Vaschillo, B., Lu, S.-E., Eckberg, D. L., Edelberg, R., et al. (2003). Heart rate variability biofeedback increases baroreflex gain and peak expiratory flow. Psychosomatic Medicine, 65, 796–805.PubMedCrossRefGoogle Scholar
  11. McCraty, R., Atkinson, M., & Lipsenthal, L. (2000). Emotional self-regulation program enhances psychological health and quality of life in patients with diabetes. Boulder Creek, CA: HeartMath Research Center, Institute of HeartMath. Publication No. 00–006.Google Scholar
  12. McCraty, R., Atkinson, M., & Tomasino, D. (2003). Impact of a workplace stress reduction program on blood pressure and emotional health in hypertensive employees. Journal of Alternative and Complementary Medicine, 9, 355–359.CrossRefGoogle Scholar
  13. McCraty, R., Atkinson, M., Tomasino, D., & Bradley, R. T. (2006). The coherent heart: heart-brain interactions, psychophysiological coherence, and the emergence of system-wide order. HeartMath Research Center, Institute of HeartMath, Publication No. 06-022, Boulder Creek, CA. 64 pages.Google Scholar
  14. Reger, M. A., & Gahm, G. A. (2009). A meta-analysis of the effects of internet- and computer-based cognitive-behavioral treatments for anxiety. Journal of Clinical Psychology, 65, 53–75.PubMedCrossRefGoogle Scholar
  15. Reiner, R. (2008). Integrating a portable biofeedback device into clinical practice for patients with anxiety disorders: Results of a pilot study. Applied Psychophysiology and Biofeedback, 33, 55–61.PubMedCrossRefGoogle Scholar
  16. Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. Journal of Personality and Social Psychology, 57, 1069–1081.CrossRefGoogle Scholar
  17. Ryff, C. D., & Keyes, L. M. (1995). The structure of psychological well-being revisited. Journal of Personality and Social Psychology, 69(4), 719–727.PubMedCrossRefGoogle Scholar
  18. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. New York: Houghton Mifflin Company.Google Scholar
  19. Spielberger, C. D. (1970). Manual for the state-trait anxiety inventory. Palo Alto, CA: Consulting Psychologists Press.Google Scholar
  20. Stein, P. K., & Kleiger, R. E. (1999). Insights from the study of heart rate variability. Annual Review of Medicine, 50, 249–261.PubMedCrossRefGoogle Scholar
  21. Task Force of the European Society of Cardiology, & The North American Society of Pacing Electrophysiology. (1996). Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. Circulation, 93, 1043–1065.Google Scholar
  22. Thayer, J. F., & Lane, R. D. (2009). Claude Bernard and the heart-brain connection: Further elaboration of a model of neurovisceral integration. Neuroscience and Biobehavioral Reviews, 33, 81–88.PubMedCrossRefGoogle Scholar
  23. Thayer, J. F., & Sternberg, E. M. (2006). Beyond heart rate variability: Vagal regulation of allostatic systems. Annals of the New York Academy of Sciences, 1088, 361–372.PubMedCrossRefGoogle Scholar
  24. Tiller, W. A., McCraty, R., & Atkinson, M. (1996). Cardiac coherence: A new, noninvasive measure of autonomic nervous system order. Alternative Therapies, 2, 52–65.Google Scholar
  25. Twenge, J. M. (2000). The age of anxiety? Birth cohort change in anxiety and neuroticism, 1952–1993. Journal of Personality and Social Psychology, 79, 1007–1021.PubMedCrossRefGoogle Scholar
  26. Watson, D., & Clark, L. (1991). The Mood and Anxiety Symptom Questionnaire. Unpublished Manuscript.Google Scholar
  27. Watson, D., Weber, K., Assenheimer, J. M., Clark, L., Strauss, M. E., & McCormick, R. A. (1995). Testing a tripartite model: I. Evaluating the convergent and discriminant validity of anxiety and depression symptom scales. Journal of Abnormal Psychology, 104, 3–14.PubMedCrossRefGoogle Scholar
  28. Zetterqvist, K., Maanmies, J., Strom, L., & Andersson, G. (2003). Randomized controlled trial of internet-based stress management. Cognitive Behaviour Therapy, 32(3), 151–160.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Gregg Henriques
    • 1
  • Steven Keffer
    • 2
  • Craig Abrahamson
    • 3
  • S. Jeanne Horst
    • 4
  1. 1.Graduate PsychologyJames Madison UniversityHarrisonburgUSA
  2. 2.Department of BiologyJames Madison UniversityHarrisonburgUSA
  3. 3.Department of PsychologyJames Madison UniversityHarrisonburgUSA
  4. 4.Department of PsychologyEastern Mennonite UniversityHarrisonburgUSA

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