Journal of Gambling Studies

, 22:289 | Cite as

Flow and Dissociation: Examination of Mean Levels, Cross-links, and Links to Emotional Well-Being across Sports and Recreational and Pathological Gambling

  • Brigitte WannerEmail author
  • Robert Ladouceur
  • Amélie V. Auclair
  • Frank Vitaro
Original Paper


To examine whether flow (Csikszentmihalyi (1990). Flow: The psychology of optimal experience. NY: Harper & Row) and dissociation (Jacobs (1986). Journal of Gambling Behavior, 2, 15–31) are experienced across sports and recreational and pathological gambling, we assessed a sample of 511 college students (256 females and 255 males, M age = 19.54) that was comprised of 14 pathological gamblers, 21 non-addicted gamblers, and 476 athletes. The findings showed that both flow and dissociation lay on a continuum of subjective experiences across activity groups. Specifically, pathological gamblers experienced lower levels of flow than athletes, whereas recreational gamblers lay in between the previous groups in this regard. In contrast, pathological gamblers experienced higher mean levels of dissociation than athletes and recreational gamblers who, in turn, were similar in this regard. A LISREL model showed that flow was positively associated with general emotional well-being, whereas dissociation was negatively associated with well-being.


Dissociation Flow Pathological gambling Recreational gambling Sports 



This research was made possible by a grant from the Fonds Québécois pour la Recherche Sociale. We wish to thank the authorities and directors of the School Board of the participating Colleges as well as the participating students. Finally, Geneviève Mailloux, Marie-Josée Perron and François Mathieu deserve our thanks for their assistance in data collection.


  1. American Psychiatric Association (1994). Diagnostic and statistical manual of mental disorders. (4th ed.). Washington, DC: Author.Google Scholar
  2. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W. H. Freeman.Google Scholar
  3. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588–506.CrossRefGoogle Scholar
  4. Bernstein, E. M., & Putnam, F. W. (1986). Development, reliability, and validity of a dissociation scale. The Journal of Nervous and Mental Disease, 174, 727–735.Google Scholar
  5. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Beverly Hills: Sage.Google Scholar
  6. Brunet, A., Holowka, D. W., & Laurence, J. R. (2001). In M. J. Aminoff & R. B. Daroff (Eds.), Dissociation. Encyclopedia of the Neurological Sciences. San Diego: Academic Press.Google Scholar
  7. Cancio, L. C. (1991). Stress and trance in freefall parachuting: A pilot study. American Journal of Clinical Hypnosis, 33, 225–234.Google Scholar
  8. Crockford, D. N. & el-Guebaly, N. (1998). Psychiatric comorbidity in pathological gambling: A critical review. Canadian Journal of Psychiatry – Review of Canadian Psychiatry, 43, 43–50.Google Scholar
  9. Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco: Jossey-Bass.Google Scholar
  10. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. NY: Harper & Row.Google Scholar
  11. Csikszentmihalyi, M., & Csikszentmihalyi, I. (1988). Optimal experience: Psychological studies of flow in consciousness. NY: Cambridge Press.Google Scholar
  12. Derevensky, J. L., Gupta, R., & Winters, K. (2003). Prevalence rates of youth gambling problems: Are the current rates inflated? Journal of Gambling Studies, 19, 405–425.CrossRefGoogle Scholar
  13. Diener, E., & Emmons, R. A. (1984). The independence of positive and negative affect. Journal of Personality and Social Psychology, 47, 1105–1117.CrossRefGoogle Scholar
  14. Diskin, K. M., & Hodgins, D. C. (1999). Narrowing of attention and dissociation in pathological video lottery gamblers. Journal of Gambling Studies, 15, 17–28.CrossRefGoogle Scholar
  15. Diskin, K. M., & Hodgins, D. C. (2001). Narrowed focus and dissociative experiences in a community sample of experienced video lottery gamblers. Canadian Journal of Behavioural Science, 33, 58–64.Google Scholar
  16. Dixon, M. R., Hayes, L. J., & Ebbs, R. E. (1998). Engaging in ‘illusory control’ during repeated risk-taking. Psychological Reports, 83, 959–962.CrossRefGoogle Scholar
  17. Grant, J. E., & Kim, S. W. (2003). Dissociative symptoms in pathological gambling. Psychopathology, 36, 200–203.CrossRefGoogle Scholar
  18. Gupta, R., & Derevensky, J. L. (1998a). An empirical examination of Jacobs’ General Theory of Addictions: Do adolescent gamblers fit the theory? Journal of Gambling Studies, 14, 17–49.CrossRefGoogle Scholar
  19. Gupta, R., & Derevensky, J. L. (1998b). Adolescent gambling behavior: A prevalence study and examination of the correlates associated with problem gambling. Journal of Gambling Studies, 14, 319–345.CrossRefGoogle Scholar
  20. Han, S. (1988). The relationship between life satisfaction and flow in elderly Korean immigrants. In M. Csikszentmihalyi & I. Csikszentmihalyi (Eds.), Optimal experience: Psychological studies of flow in consciousness (pp. 138–149). New York: Cambridge University.Google Scholar
  21. Hausenblas, H. A., & Downs, D. S. (2002). Exercise dependence: A systematic review. Psychology of Sport and Exercise, 3, 89–123.CrossRefGoogle Scholar
  22. Hull, R. B. (1991). Mood as a product of leisure: Causes and consequences. In: B. L. Driver, P. J. Brown & G. L. Peterson (Eds.), Benefits of leisure (pp. 250–262). State College, PA: Venture Publishing.Google Scholar
  23. Jackson, S. A., & Marsh, H. W. (1996). Development and validation of a scale to measure optimal experience: The Flow State Scale. Journal of Sport and Exercise Psychology, 18, 17–35.Google Scholar
  24. Jacobs , D. F. (1986). A general theory of addictions: a new theoretical model. Journal of Gambling Behavior, 2, 15–31.CrossRefGoogle Scholar
  25. Jacobs, D. F. (1988). Evidence for a common dissociative-like reaction among addicts. The Journal of Gambling Behavior, 4, 27–37.CrossRefGoogle Scholar
  26. Jacobs, D. F. (1989). A general theory of addictions: Rationale for and evidence supporting a new approach for understanding and treating addictive behaviors. In: H. J. Shaffer, S. A. Stein, B. Gambino, & T. N. Cummings (Eds.), Compulsive gambling: Theory, research, and practice (pp. 35–64). Lexington, UK: Lexington Books.Google Scholar
  27. Jöreskog, K. G., & Sörbom, D. (1996). LISREL 8: User’s reference guide. Chicago: Scientific Software International.Google Scholar
  28. Kishton, J. M., & Widaman K. F. (1994). Unidimensional versus domain representative parceling of questionnaire items: an empirical example. Educational and Psychological Measurement, 54, 757–765.Google Scholar
  29. Ladouceur, R. (1996). The prevalence of pathological gambling in Canada. Journal of Gambling Behavior, 12, 129–142.CrossRefGoogle Scholar
  30. Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32, 311–328.CrossRefGoogle Scholar
  31. Lesieur, H. R., & Blume, S. B. (1987). The South Oaks Gambling Screen (the SOGS): A new instrument for pathological gambling in a combined alcohol, substance abuse and pathological gambling treatment unit using the Addiction Severity Index. British Journal of Addiction, 86, 1017-1028. CrossRefGoogle Scholar
  32. Mannell, R. C. (1979). A conceptual and experimental basis for research in the psychology of leisure. Loisir & Societe, 2, 179–196.Google Scholar
  33. Marsh, H. W., & Jackson, S. A. (1999). Flow experience in sport: construct validation of multidimensional, hierarchical state and trait responses. Structural Equation Modeling, 6, 343–371.CrossRefGoogle Scholar
  34. Marshall, K. (1998). The gambling industry: raising the stakes. Perspect. Labour Income, 10, 7–11.Google Scholar
  35. Massimini F., & Carli, M. (1988). The systematic assessment of low in daily life. In M. Moore, S. M., & K. Ohtsuka (1999). Beliefs about control over gambling among young people, and their relation to problem gambling. Psychology of Addictive Behaviors, 13, 339–347.Google Scholar
  36. Mayer, K. U., & Baltes, P. B. (1996). Die Berliner Altersstudie: Viele Gesichter des Alterns. Berlin: Akademie Verlag.Google Scholar
  37. McArdle, J. J. (1996). Current directions in structural factor analysis. Current Directions, 5, 11–18.CrossRefGoogle Scholar
  38. National Research Council, (1999). Pathological gambling: A critical review. Washington, DC: National Academic Press.Google Scholar
  39. Platz, L., & Millar, M. (2001). Gambling in the context of other recreation activity: A quantitative comparison of casual and pathological student gamblers. Journal of Leisure Research, 33, 383–395.Google Scholar
  40. Ross, C. A., Joshi, S., & Currie, R. (1990). Dissociative experiences in the general population. American Journal of Psychiatry, 147, 1547–1552.Google Scholar
  41. Shaffer, H. J., & Hall, M. N. (1996). Estimating the prevalence of adolescent gambling disorders: a quantitative synthesis and guide toward standard gambling nomenclature. Journal of Gambling Studies, 12, 193–214.CrossRefGoogle Scholar
  42. Sterlini, G. L., & Bryant, R. A. (2002). Hyperarousal and dissociation: A study of novice skydivers. Behaviour Research and Therapy, 40, 431–437.CrossRefGoogle Scholar
  43. Volberg, R. (1996). Prevalence studies of problem gambling in the United States. Journal of Gambling Behavior, 12, 111–128.CrossRefGoogle Scholar
  44. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of Positive and Negative Affectivity: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Brigitte Wanner
    • 1
    Email author
  • Robert Ladouceur
    • 2
  • Amélie V. Auclair
    • 2
  • Frank Vitaro
    • 1
  1. 1.Research Unit on Children’s Psychosocial Maladjustment University of MontrealMontrealCanada
  2. 2.Laval UniversitySte-FoyCanada

Personalised recommendations