Dispositions Toward Flow and Mindfulness Predict Dispositional Insight
- 158 Downloads
This study aimed to investigate whether dispositions to positive affect (PA), mindfulness, and flow states predict a disposition toward insight. Using a sample of 1069 participants, two structural equation models (SEMs) were performed; the first included positive affect, mindfulness, and flow as the predictors. The second SEM repeated this, but with the nine components of flow included separately. In the first model, mindfulness and flow significantly predicted insight; PA showed no effect. In the second model, PA and mindfulness showed an effect. The subcomponents of flow—merging of action and awareness, unambiguous feedback, and transformation of time—had the strongest effect on insight, followed by autotelic experience. Clear goals negatively affected insight.
KeywordsInsight Flow Mindfulness Positive affect Disposition Structural equation modeling
This work was funded under an Australian Government Research Training Program Scholarship. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors. We thank the Charles Sturt University Writing Circle for providing insightful comments on the content and expression of ideas.
LO: designed and executed the study, and conducted the analyses of the data, and wrote the paper. AS: collaborated on the design of the study, writing, and editing of the manuscript. JG: collaborated on the design of the study, writing, and editing of the manuscript.
Compliance with Ethical Standards
The study was approved by the Charles Sturt University, Faculty of Arts Ethics Committee. All procedures performed in the study were in accordance with the ethical standards of the institution and with the 1964 Helsinki declaration and its later amendments. Participants gave informed consent through accessing the study online via a link in an email inviting potential respondents to participate.
Conflict of Interest
The authors declare that they have no competing interests.
- Baumann, N., Kaschel, R., & Kuhl, J. (2005). Striving for unwanted goals: stress-dependent discrepancies between explicit and implicit achievement motives reduce subjective well-being and increase psychosomatic symptoms. Journal of Personality and Social Psychology, 89(5), 781.CrossRefPubMedGoogle Scholar
- Begley, S. (2007). Train your mind, change your brain: how a new science reveals our extraordinary potential to transform ourselves. New York: Random House Digital, Inc..Google Scholar
- Bishop, S. R., Lau, M., Shapiro, S., Carlson, L., Anderson, N. D., Carmody, J.,... Velting, D. (2004). Mindfulness: a proposed operational definition. Clinical Psychology: Science and Practice, 11(3), 230–241.Google Scholar
- Bodner, T. E. (2000). On the assessment of individual differences in mindful information processing. (PhD Thesis), Harvard University, Cambridge, United States. Retrieved from https://elibrary.ru/item.asp?id=5317264
- 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). Newbury Park: Sage.Google Scholar
- Chen, F., Curran, P. J., Bollen, K. A., Kirby, J., & Paxton, P. (2008). An empirical evaluation of the use of fixed cutoff points in RMSEA test statistic in structural equation models. Sociological Methods and Research, 36(4), 462–494. https://doi.org/10.1177/0049124108314720.CrossRefPubMedPubMedCentralGoogle Scholar
- Cohen, J. (1988). Statistical power analysis for the behavioral sciencies (2nd ed.). New York: Routledge.Google Scholar
- Cortina, J. M., & Landis, R. S. (2009). When small effect sizes tell a big story, and when large effect sizes don’t. In C. E. Lance & R. J. Vandenberg (Eds.), Statistical and methodological myths and urban legends: doctrine, verity and fable in the organizational and social sciences (pp. 287–308). New York: Routledge.Google Scholar
- Csikszentmihalyi, M. (1991). Flow: the psychology of optimal experience. New York: Harper Perennial.Google Scholar
- Csikszentmihalyi, M. (2000). Beyond boredom and anxiety: experiencing flow in work and play. San Francisco: Jossey-Bass.Google Scholar
- Csikszentmihalyi, M. (2014). Toward a psychology of optimal experience. In M. Csikszentmihalyi (Ed.), Flow and the foundations of positive psychology (pp. 209–226). Dordrecht: Springer.Google Scholar
- Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60.Google Scholar
- Jung-Beeman, M., Bowden, E. M., Haberman, J., Frymiare, J. L., Arambel-Liu, S., Greenblatt, R.,... Kounios, J. (2004). Neural activity when people solve verbal problems with insight. PLoS Biology, 2(4), 500–510.Google Scholar
- Kounios, J., & Beeman, M. J. (2015). The Eureka factor: creative insights and the brain. London: Random House.Google Scholar
- Langer, E. J. (1997). The power of mindful learning. Boston: Da Capo Press.Google Scholar
- Lau, M. A., Bishop, S. R., Segal, Z. V., Buis, T., Anderson, N. D., Carlson, L.,... Devins, G. (2006). The Toronto mindfulness scale: development and validation. Journal of Clinical Psychology, 62(12), 1445–1468.Google Scholar
- Løvstad, M., Funderud, I., Meling, T., Krämer, U. M., Voytek, B., Due-Tønnessen, P.,... Solbakk, A. K. (2012). Anterior cingulate cortex and cognitive control: neuropsychological and electrophysiological findings in two patients with lesions to dorsomedial prefrontal cortex. Brain and Cognition, 80(2), 237–249. https://doi.org/10.1016/j.bandc.2012.07.008.
- Maruyama, G. M. (1997). Basics of structural equation modeling. London: Sage Publications.Google Scholar
- 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 University Press.Google Scholar
- Oaksford, M., Morris, F., Grainger, B., & Williams, J. M. G. (1996). Mood, reasoning, and central executive processes. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(2), 476–492.Google Scholar
- Ovington, L. A., Saliba, A. J., Moran, C. C., Goldring, J., & MacDonald, J. B. (2015). Do people really have insights in the shower? The when, where and who of the aha! moment. The Journal of Creative Behavior, In Press. https://doi.org/10.1002/jocb.126.
- Sakaki, M., & Niki, K. (2011). Effects of the brief viewing of emotional stimuli on understanding of insight solutions. Cognitive, Affective, & Behavioral Neuroscience, 11(4), 1–15.Google Scholar
- Smith, S. M. (1995a). Fixation, incubation, and insight in memory and creative thinking. In S. M. Smith, T. B. Ward, & R. A. Finke (Eds.), The creative cognition approach (pp. 135–156). London: The MIT Press.Google Scholar
- Smith, S. M. (1995b). Getting into and out of mental ruts. In R. J. Sternberg & J. E. Davidson (Eds.), The nature of insight (pp. 229–251). London: The MIT Press.Google Scholar
- Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics. Michigan: Allyn and Bacon.Google Scholar