Individual and Situational Factors Related to the Experience of Flow in Adolescence

A Multilevel Approach
  • Jennifer A. Schmidt
  • David J. Shernoff
  • Mihaly Csikszentmihalyi


A fundamental issue pursued by researchers in positive psychology involves defining what constitutes a good life and understanding how individuals can create one. From the perspective of flow theory, “a good life is one that is characterized by complete absorption in what one does” (Nakamura and Csikszentmihalyi in Handbook of positive psychology. Oxford, New York, 2002). Born out of a desire to understand intrinsically motivated activity, flow refers to a state of optimal experience characterized by total absorption in the task at hand: a merging of action and awareness in which the individual loses track of both time and self, The flow state is experientially positive, and out of the flow experience emerges a desire to replicate the experience. Over the past three decades, Csikszentmihalyi and colleagues have developed theoretical constructs and empirical research tools to better understand the nature, origins, and consequences of this state of optimal experience called flow. In this chapter, we describe the flow model and then present data analyses in which we explore the personal traits and contextual conditions associated with the experience of flow among adolescents in the United States. We demonstrate the utility of hierarchical linear modeling (HLM) for exploring flow using a complex data set characterized by repeated measures.


Positive Psychology Flow Experience Hierarchical Linear Modeling Internal Dimension External Dimension 
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  1. Adlal-Gail, W. (1994). Exploring the autotelic personality. Unpublished doctoral dissertation, University of Chicago.Google Scholar
  2. Cowen, E. L., & Kilmer, R. P. (2002). “Positive psychology”: Some plusses and some open issues. Journal of Community Psychology 30, 449–460.CrossRefGoogle Scholar
  3. Csikszentmihalyi, M. (1985). Emergent motivation and the evolution of the self. Advances in Motivation and Achievement 4, 93–119.Google Scholar
  4. Csikszentmihalyi, M. (1990). Flow. New York: Harper and Row.Google Scholar
  5. Csikszentmihalyi, M. (1996). Creativity. New York: HarperCollins,Google Scholar
  6. Csikszentmihalyi, M. (2000). Beyond boredom and anxiety. San Francisco: Jossey-Bass (Original work published 1975)Google Scholar
  7. Csikszentmihalyi, M., Csikszentmihalyi, I. S. (Eds.) (1988). Optimal experience. Cambridge: Cambridge University Press.Google Scholar
  8. Csikszentmihalyi, M., Larson, R. (1984). Being adolescent. New York: Basic Books.Google Scholar
  9. Csikszentmihalyi, M., Larson, R. (1987). Validity and reliability of the experience-sampling method. Journal of Nervous and Mental Disease, 175(9), 525–536.CrossRefGoogle Scholar
  10. Csikszentmihalyi, M., Larson, R., Prescott, S. (1977). The ecology of adolescent activity and experience. Journal of Youth and Adolescence, 6, 281–294CrossRefPubMedGoogle Scholar
  11. Csikszentmihalyi, M., Rathunde, K., & Whalen, S. (1993). Talented teenagers. New York: Cambridge University Press.Google Scholar
  12. Csikszentmihalyi, M., & Schneider, Β. (2000). Becoming adult. New York: Basic Books.Google Scholar
  13. Delle Fave, Α., & Massimini, F. (1988). Modernization and the changing contexts of flow in work and leisure. In M. Csikszentmihalyi & I. S. Csikszentmihalyi (Eds.), Optimal experience (pp. 193–213). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  14. Delle Fave, Α., & Massimini, F. (1992). The ESM and the measurement of clinical change: A case of anxiety disorder. In MW deVries (Ed.) The experience of psychopathology (pp. 280–289). Cambridge: Cambridge University Press.Google Scholar
  15. Eccles, J., & Gootman, J. A. (2002). Community programs to promote youth development. Washington, DC: National Academy Press.Google Scholar
  16. Finn, J. D., & Cox, D. (1992). Participation and withdrawal among fourth-grade pupils. American Educational Research Journal 29, 141–162CrossRefGoogle Scholar
  17. Fredricks, J. Α., Blumenfeld, P. C., & Paris, A. H. (2004) School engagement: potential of the concept, state of the evidence. Review of Educational Research, 74, 59–109CrossRefGoogle Scholar
  18. Hektner, J. (1996). Exploring optimal personality development: A longitudinal study of adolescents. Unpublished doctoral dissertation, University of Chicago.Google Scholar
  19. Hektner, J. M., Schmidt, J. Α., & Csikszentmihalyi, M. (2006). Measuring the quality of everyday life: The ESM handbook. Thousand Oaks: Sage.Google Scholar
  20. Hox, J. (2002). Multilevel analysis: Techniques and applications. Mahwah: Erlbaum.Google Scholar
  21. Jackson, S. (1995). Factors influencing the occurrence of flow state in elite athletes. Journal of Applied Sport Psychology, 7, 138–166CrossRefGoogle Scholar
  22. Jackson, S. (1996). Toward a conceptual understanding of the flow experience in elite athletes. Research Quarterly for Exercise and Sport, 67, 76–90CrossRefPubMedGoogle Scholar
  23. Jackson, S., & 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, 17–35CrossRefGoogle Scholar
  24. LeFevre, J. (1988). Flow and the quality of experience during work and leisure. In M. Csikszentmihalyi & I. S. Csikszentmihalyi (Eds.), Optimal experience (pp. pp 307–326). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  25. Logan, R. (1985). The “flow experience” in solitary ordeals. Journal of Humanistic Psychology, 25, 79–89CrossRefGoogle Scholar
  26. Magnusson, D, & Stattin, H. (1998) .Person-context interaction theories. In R. M. Lerner (Ed.), Handbook of child psychology (Vol 1, pp. 685–759). New York: WileyGoogle Scholar
  27. Marks, H. M. (2000). Student engagement in instructional activity: Patterns in the elementary, middle and high school years. American Educational Research Journal, 37,153–184CrossRefGoogle Scholar
  28. Massimini, F., Carli, M. (1988). The systematic assessment of flow in daily experience. In M. Csikszentmihalyi, I. S. Csikszentmihalyi (Eds.), Optimal experience (pp. 266–287). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  29. Massimini, F., Csikszentmihalyi, M., & Carli, M. (1992). The monitoring of optimal experience: a tool for psychiatric rehabilitation. In M. W. deVries (Ed.) ,The experience of psychopathology (pp. 270–279). Cambridge: Cambridge University Press.Google Scholar
  30. Mayers, P. (1978). Flow in adolescence and its relation to school experience. Unpublished doctoral dissertation, University of Chicago.Google Scholar
  31. Moneta, G., & Csikszentmihalyi, M. (1996) .The effect of perceived challenges and skills on the quality of subjective experience. Journal of Personality, 64, 275–310CrossRefPubMedGoogle Scholar
  32. Nakamura, J., & Csikszentmihalyi, M. (2002). The concept of flow. In C. R. Snyder & S. J. Lopez (Eds.) Handbook of positive psychology (pp. 89–105). New York: Oxford.Google Scholar
  33. Parks, B. (1996). “Flow”, boredom, and anxiety in therapeutic work. Unpublished doctoral dissertation, University of ChicagoGoogle Scholar
  34. Perry, S. K. (1999). Writing in flow. Cincinnati: Writer’s Digest BooksGoogle Scholar
  35. Rathunde, K. (1996). Family context and talented adolescents’ optimal experience in school-related activities. Journal of Research on Adolescence, 6, 605–628Google Scholar
  36. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models (2nd ed). Thousand Oaks: Sage.Google Scholar
  37. Rosenberg, M. (1965). Society and the adolescent self-image. Princeton: Princeton University Press.CrossRefGoogle Scholar
  38. Shernoff, D. J. (2001). The experience of student engagement in high school classrooms: a phenomenological perspective. Unpublished doctoral dissertation, University of ChicagoGoogle Scholar
  39. Shemoff, D. J., Csikszentmihalyi, M., Schnelder, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18(2), 158–176Google Scholar
  40. Snijders, T. A. B., & Bosker, R. (1999). Multilevel analysis: An introduction to bask and advanced multilevel modeling. Thousand Oaks, CA: Sage.Google Scholar
  41. Van Der Poel, E. G. T., & Delespaul, P. A. E. G. (1992). The applicability of ESM in personalized rehabilitation. In M. W. deVries (Ed.), The experience of psychopalhology (pp. 290–303). Cambridge, UK: Cambridge University Press.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Jennifer A. Schmidt
    • 1
  • David J. Shernoff
    • 1
  • Mihaly Csikszentmihalyi
    • 1
  1. 1.Claremont Graduate UniversityClaremontUSA

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