, Volume 7, Issue 2, pp 420–432 | Cite as

Getting Personal with Mindfulness: a Latent Profile Analysis of Mindfulness and Psychological Outcomes

  • Adrian J. Bravo
  • Laura G. Boothe
  • Matthew R. PearsonEmail author


Variable-centered analyses demonstrate that most facets of mindfulness are associated with improved psychological well-being. Person-centered analyses provide the ability to identify distinct subpopulations defined by individuals’ full response profiles on mindfulness facets. Previous research has used latent profile analysis (LPA) to distinguish four subgroups of college students based on five facets of mindfulness: high mindfulness group, low mindfulness group, judgmentally observing group, and non-judgmentally aware group. On emotional outcomes, they found the judgmentally observing group had the most maladaptive emotional outcomes followed by the low mindfulness group. However, they did not examine experience with mindfulness meditation, other mindfulness-related constructs, or psychological well-being. In a sample of 688 college students (481 non-meditators, 200 meditators), we used LPA to identify distinct subgroups defined by their scores on the Five Facet Mindfulness Questionnaire (FFMQ). Using the Lo-Mendell-Rubin Likelihood Ratio Test, we found that a 4-class solution fits optimally for the entire sample as well as subsamples of meditation-naïve and meditation-experienced participants. We substantially replicated previous findings in all samples with regard to emotional outcomes. Further, the high mindfulness group demonstrated the highest levels of psychological well-being, decentering, self-regulation, and psychological flexibility. Overall, our results demonstrate the utility of person-centered analyses to examine mindfulness in unique ways.


Mindfulness Emotional health Psychological flexibility Psychological well-being Latent profile analysis Person-centered analysis 


Compliance with Ethical Standards


Although no direct funding was provided for the present study, the corresponding author is supported by a career development award from the National Institute on Alcohol Abuse and Alcoholism (K01-AA023233).

Ethical Approval

All procedures performed in our study were approved by the institutional review board at the participating university and in accordance with the ethical standards of the 1964 Helsinki declaration and its later amendments.

Informed Consent

Informed consent was obtained from all individual participants included in the present study.


  1. Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrov & F. Casaki (Eds.), Second International Symposium on Information Theory (pp. 267–281). Budapest: Academiai Kiado.Google Scholar
  2. Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716–723. doi: 10.1109/TAC.1974.1100705.CrossRefGoogle Scholar
  3. American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.Google Scholar
  4. Asparouhov, T., & Muthén, B. (2007). Computationally efficient estimation of multilevel high-dimensional latent variable models. Proceedings of the 2007 Joint Statistical Meetings, Section on Statistics in Epidemiology (2531–2535). Alexandria, VA: American Statistical Association.Google Scholar
  5. Baer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J., & Toney, L. (2006). Using self-report assessment methods to explore facets of mindfulness. Assessment, 13, 27–45. doi: 10.1177/1073191105283504.CrossRefPubMedGoogle Scholar
  6. Baer, R. A., Smith, G. T., Lykins, E., Button, D., Krietemeyer, J., Sauer, S., & Williams, J. M. G. (2008). Construct validity of the five facet mindfulness questionnaire in meditating and nonmeditating samples. Assessment, 15, 329–342. doi: 10.1177/1073191107313003.CrossRefPubMedGoogle Scholar
  7. Bishop, S. R., Lau, M., Shapiro, S., Carlson, L., Anderson, N. D., Carmody, J., Segal, Z. V., Abbey, S., Speca, M., Velting, D., & Devins, G. (2004). Mindfulness: a proposed operational definition. Clinical Psychology: Science and Practice, 11, 230–241. doi: 10.1093/clipsy/bph007.Google Scholar
  8. Brinker, J. K., & Dozois, D. J. A. (2009). Ruminative thought style and depressed mood. Journal of Clinical Psychology, 65, 1–19. doi: 10.1002/jclp.20542.CrossRefPubMedGoogle Scholar
  9. Brown, D. B., Bravo, A. J., Roos, C. R., & Pearson, M. R. (2015). Five facets of mindfulness and psychological symptoms: evaluating a psychological model of the mechanism of mindfulness. Mindfulness, 6, 1021–1032. doi: 10.1007/s12671-014-0349-4.CrossRefPubMedGoogle Scholar
  10. Carey, K. B., Neal, D. J., & Collins, S. E. (2004). A psychometric analysis of the self-regulation questionnaire. Addictive Behaviors, 29, 253–260. doi: 10.1016/j.addbeh.2007.05.004.CrossRefPubMedGoogle Scholar
  11. Carmody, J., & Baer, R. A. (2008). Relationships between mindfulness practice and levels of mindfulness, medical and psychological symptoms and well-being in a mindfulness-based stress reduction program. Journal of Behavioral Medicine, 31, 23–33. doi: 10.1007/s10865-007-9130-7.CrossRefPubMedGoogle Scholar
  12. Clark, S. L., & Muthén, B. (2009). Relating latent class analysis results to variables not included in the analysis. Submitted for publication. Available from
  13. Collins, L. M., & Lanza, S. T. (2010). Latent class and latent transition analysis with applications in the social, behavioural, and health sciences. Hoboken: John Wiley & Sons, Inc.Google Scholar
  14. Eaton, W. W., Muntaner, C., Smith, C., Tien, A., & Ybarra, M. (2004). Center for Epidemiologic Studies Depression Scale: review and revision (CESD and CESD-R). In M. E. Maruish (Ed.), The use of psychological testing for treatment planning and outcomes assessment (3rd ed., pp. 363–377). Mahwah: Lawrence Erlbaum.Google Scholar
  15. Fernandez, A. C., Wood, M. D., Stein, L. A. R., & Rossi, J. S. (2010). Measuring mindfulness and examining its relationship with alcohol use and negative consequences. Psychology of Addictive Behaviors, 24, 608–616. doi: 10.1037/a0021742.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Fresco, D. M., Moore, M. T., van Dulmen, M. H., Segal, Z. V., Ma, S. H., Teasdale, J. D., & Williams, J. M. (2007). Initial psychometric properties of the experiences questionnaire: validation of a self-report measure of decentering. Behavior Therapy, 38, 234–246. doi: 10.1016/j.beth.2006.08.003.CrossRefPubMedGoogle Scholar
  17. Godfrey, K. M., Gallo, L. C., & Afari, N. (2015). Mindfulness-based interventions for binge eating: a systematic review and meta-analysis. Journal of Behavioral Medicine, 38, 348–362.CrossRefPubMedGoogle Scholar
  18. Gu, J., Strauss, C., Bond, R., & Cavanah, K. (2015). How do mindfulness-based cognitive therapy and mindfulness-based stress reduction improve mental health and wellbeing? A systematic review and meta-analysis of mediation studies. Clinical Psychology Review, 37, 1–12.CrossRefPubMedGoogle Scholar
  19. Hayes, S. C., Strosahl, K. D., Wilson, K. G., Bissett, R. T., Pistorello, J., Toarmino, D., et al. (2004). Measuring experiential avoidance: a preliminary test of a working model. The Psychological Record, 54, 553–578.Google Scholar
  20. Henson, J. M., Reise, S. P., & Kim, K. H. (2007). Detecting mixtures from structural model differences using latent variable mixture modeling: a comparison of relative model fit statistics. Structural Equation Modeling, 14, 202–226. doi: 10.1080/10705510709336744.CrossRefGoogle Scholar
  21. Kabat-Zinn, J. (1982). An outpatient program in behavioral medicine for chronic pain patients based on the practice of mindfulness meditation: theoretical considerations and preliminary results. General Hospital Psychiatry, 4, 33–47.CrossRefPubMedGoogle Scholar
  22. Kabat-Zinn, J. (1994). Wherever you go, there you are: mindfulness meditation in everyday life. New York: Hyperion Books.Google Scholar
  23. Lilja, J. L., Lundh, L.-G., Josefsson, T., & Falkenstӧm, F. (2013). Observing as an essential facet of mindfulness: a comparison of FFMQ patterns in meditating and non-meditating individuals. Mindfulness, 4, 203–2012. doi: 10.1007/s12671-012-0111-8.CrossRefGoogle Scholar
  24. Lo, Y., Mendell, N., & Rubin, D. (2001). Testing the number of components in a normal mixture. Biometrika, 88, 767–778. doi: 10.1093/biomet/88.3.767.CrossRefGoogle Scholar
  25. Marsh, H. W., Lüdtke, O., Trautwein, U., & Morin, A. J. (2009). Classical latent profile analysis of academic self-concept dimensions: synergy of person-and variable-centered approaches to theoretical models of self-concept. Structural Equation Modeling, 16, 191–225. doi: 10.1080/10705510902751010.CrossRefGoogle Scholar
  26. Meyer, T. J., Miller, M. L., Metzger, R. L., & Borkovec, T. D. (1990). Development and validation of the Penn state worry questionnaire. Behavior Research and Therapy, 28, 487–495. doi: 10.1016/0005-7967(90)90135-6.CrossRefGoogle Scholar
  27. Muthén, L. K., & Muthén, B. O. (1998–2012). Mplus user’s guide (7th ed.). Los Angeles: Muthén & Muthén.Google Scholar
  28. Pearson, M. R., Brown, D. B., Bravo, A. J., & Witkiewitz, K. (2015a). Staying in the moment and finding purpose: the associations of trait mindfulness, decentering, and purpose in life with depressive symptoms, anxiety symptoms, and alcohol-related problems. Mindfulness, 6, 645–653. doi: 10.1007/s12671-014-0300-8.CrossRefGoogle Scholar
  29. Pearson, M. R., Lawless, A. K., Brown, D. B., & Bravo, A. J. (2015b). Mindfulness and emotional outcomes: identifying subgroups of college students using latent profile analysis. Personality and Individual Differences, 76, 33–38. doi: 10.1016/j.paid.2014.11.009.CrossRefPubMedGoogle Scholar
  30. Roos, C. R., Pearson, M. R., & Brown, D. B. (2015). Drinking motives mediate the negative associations between mindfulness facets and alcohol outcomes among college students. Psychology of Addictive Behaviors, 29, 176–183. doi: 10.1037/a0038529.CrossRefPubMedPubMedCentralGoogle Scholar
  31. Ryff, C. (1989). Happiness is everything, or is it? Explorations on the meaning of psychological well-being. Journal of Personality and Social Psychology, 57, 1069–1081. doi: 10.1037/0022-3514.57.6.1069.CrossRefGoogle Scholar
  32. Sakamoto, Y., Ishiguro, M., & Kitagawa, G. (1986). Akaike information criterion statistics. Dordrecht, The Netherlands: D. Reidel.Google Scholar
  33. Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461–464. doi: 10.1214/aos/1176344136.CrossRefGoogle Scholar
  34. Shapiro, S. L., Carlson, L. E., Astin, J. A., & Freedman, B. (2006). Mechanisms of mindfulness. Journal of Clinical Psychology, 62, 373–386. doi: 10.1002/jclp.20237.CrossRefPubMedGoogle Scholar
  35. Shonin, E., Van Gordon, W., Compare, A., Zangeneh, M., & Griffiths, M. D. (2015). Buddhist-derived loving-kindness and compassion meditation for the treatment of psychopathology: a systematic review. Mindfulness, 6, 1161–1180.CrossRefGoogle Scholar
  36. Simons, J. S., & Gaher, R. M. (2005). The distress tolerance scale: development and validation of a self-report measure. Motivation and Emotion, 29, 83–102. doi: 10.1007/s11031-005-7955-3.CrossRefGoogle Scholar
  37. Van Dam, N. T., & Earleywine, M. (2011). Validation of the center for epidemiologic studies depression scale—revised (CESD-R): Pragmatic depression assessment in the general population. Psychiatry Research186, 128-132. doi: 10.1016/j.psychres.2010.08.018.
  38. Vuong, Q. (1989). Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica, 57, 307–333. doi: 10.2307/1912557.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Adrian J. Bravo
    • 1
  • Laura G. Boothe
    • 2
  • Matthew R. Pearson
    • 3
    Email author
  1. 1.Department of PsychologyOld Dominion UniversityNorfolkUSA
  2. 2.Department of PsychologyUniversity of VirginiaCharlottesvilleUSA
  3. 3.Center on Alcoholism, Substance Abuse, & AddictionsUniversity of New MexicoAlbuquerqueUSA

Personalised recommendations