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Evaluating the Factor Structure of Each Facet of the Five Facet Mindfulness Questionnaire

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Abstract

Objective

Nearly all studies treat the Five Facet Mindfulness Questionnaire as five independent scales (one measuring each of the five facets), yet almost no methodological work has examined the psychometric structure of the facets independently. We address this issue using factor analytic methods.

Methods

Exploratory and confirmatory factor models were fit to item response data from a sample of 522 adults recruited online. Findings were replicated in a sample of 454 adults receiving aftercare for substance use disorder.

Results

Parallel analysis suggested multiple factors for all five facets, in both samples. Exploratory factor models suggested the presence of method factors on the acting with awareness (items using the term “distraction”) and describing facets (items that were reverse-scored). Confirmatory factor models fit poorly for all facets, in both samples. In follow-up analyses, model fit improved substantially on the acting with awareness and describing facets when method factors were included in a bifactor model. Model fit was also better for the facets of FFMQ short forms than for the full-length facets. The short-form facets and original facets correlated similarly with external criteria in both samples.

Conclusions

None of the FFMQ facets fit a unidimensional factor model; yet, follow-up analyses suggested that each can be considered substantively unidimensional. Initial tests suggest that the facets’ multidimensionality did not materially impact their relation to other psychological constructs, suggesting that multidimensionality can be ignored for some purposes. The use of short-form facets or latent variable models (e.g., bifactor specifications) are both viable solutions for addressing multidimensionality when desired.

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References

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin, 103, 411–423.

    Article  Google Scholar 

  • Baer, R. A., Smith, G. T., & Allen, K. B. (2004). Assessment of mindfulness by self-report: the Kentucky Inventory of Mindfulness Skills. Assessment, 11, 191–206.

    Article  PubMed  Google Scholar 

  • 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.

    Article  PubMed  Google Scholar 

  • Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57, 289–300.

    Article  Google Scholar 

  • Bohlmeijer, E., ten Klooster, P. M., Fledderus, M., Veehof, M., & Baer, R. (2011). Psychometric properties of the five facet mindfulness questionnaire in depressed adults and development of a short form. Assessment, 18, 308–320.

    Article  PubMed  Google Scholar 

  • Bowen, S., Chawla, N., Collins, S. E., Witkiewitz, K., Hsu, S. H., Grow, J., et al. (2009). Mindfulness-based relapse prevention for substance use disorders: a pilot efficacy trial. Substance Abuse, 30, 295–305.

    Article  PubMed  Google Scholar 

  • Bowen, S., Witkiewitz, K., Clifasefi, S. L., Grow, J., et al. (2014). Relative efficacy of mindfulness-based relapse prevention, standard relapse prevention, and treatment as usual for substance use disorders: a randomized clinical trial. JAMA Psychiatry, 71, 547–556.

    Article  PubMed  PubMed Central  Google Scholar 

  • Brown, K. W., & Ryan, R. M. (2003). The benefits of being present: mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology, 84, 822–848.

    Article  PubMed  Google Scholar 

  • Buchheld, N., Grossman, P., & Walach, H. (2001). Measuring mindfulness in insight meditation (Vipassana) and meditation-based psychotherapy: the development of the Freiburg mindfulness inventory (FMI). Journal for Meditation and Meditation Research, 1, 11–34.

    Google Scholar 

  • Burzler, M. A., Voracek, M., Hos, M., & Tran, U. S. (2019). Mechanisms of mindfulness in the general population. Mindfulness, 10, 469–480.

    Article  Google Scholar 

  • Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: the BIS/BAS scales. Journal of Personality and Social Psychology, 67, 319–333.

    Article  Google Scholar 

  • Chadwick, P., Hember, M., Symes, J., Peters, E., Kuipers, E., & Dagnan, D. (2008). Responding mindfully to unpleasant thoughts and images: Reliability and validity of the Southampton Mindfulness Questionnaire (SMQ). British Journal of Clinical Psychology, 47, 451–455.

  • Chen, F. F., West, S. G., & Sousa, K. H. (2006). A comparison of bifactor and second-order models of quality of life. Multivariate Behavioral Research, 41, 189–225.

    Article  PubMed  Google Scholar 

  • Christopher, M. S., Neuser, N. J., Michael, P. G., & Baitmangalkar, A. (2012). Exploring the psychometric properties of the five facet mindfulness questionnaire. Mindfulness, 3, 124–131.

    Article  Google Scholar 

  • Clerkin, E. M., Sarfan, L. D., et al. (2017). Mindfulness facets, social anxiety, and drinking to cope with social anxiety: testing mediators of drinking problems. Mindfulness, 8, 159–170.

    Article  PubMed  Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale: Lawrence Erlbaum Associates.

    Google Scholar 

  • Crawford, A. V., Green, S. B., Levy, R., Lo, W.-J., Scott, L., Svetina, D., & Thompson, M. S. (2010). Evaluation of parallel analysis methods for determining the number of factors. Educational and Psychological Measurement, 70, 885–901.

    Article  Google Scholar 

  • Curtiss, J., & Klemanski, D. (2014). Factor analysis of the five facet mindfulness in a heterogeneous clinical sample. Journal of Psychopathology and Behavioral Assessment, 36, 683–694.

    Article  Google Scholar 

  • Diedenhofen, B., & Musch, J. (2015). cocor: A comprehensive solution for the statistical comparison of correlations. PLoS One, 10, e0121945.

    Article  PubMed  PubMed Central  Google Scholar 

  • Edwards, M. C., Houts, C. R., & Cai, L. (2017). A diagnostic procedure to detect departures from local independence in item response theory models. Psychological Methods, 23, 138–149.

    Article  PubMed  PubMed Central  Google Scholar 

  • Eisenberg, I. W., Bissett, P. G., Canning, J. R., Dallery, J., Enkavi, A. Z., Whitfield-Gabrieli, S., et al. (2018). Applying novel technologies and methods to inform the ontology of self-regulation. Behaviour Research and Therapy, 101, 46–57.

    Article  PubMed  Google Scholar 

  • Eisenberg, I. W., Bissett, P. G., Enkavi, A. Z., Li, J., MacKinnon, D. P., Marsch, L. A., & Poldrack, R. A. (2019). Uncovering the structure of self-regulation through data-driven ontology discovery. Nature Communications, 10, 2319.

    Article  PubMed  PubMed Central  Google Scholar 

  • Enkavi, A. Z., Eisenberg, I. W., Bissett, P. G., Mazza, G. L., MacKinnon, D. P., Marsch, L. A., & Poldrack, R. A. (2019). Large-scale analysis of test–retest reliabilities of self-regulation measures. Proceedings of the National Academy of Sciences, 116, 5472–5477.

    Article  Google Scholar 

  • Feldman, G. C., Hayes, A. M., Kumar, S. M., & Greeson, J. M. (2004). Development, factor structure, and initial validation of the cognitive and affective mindfulness scale.

  • Fiske, D. W. (1971). Measuring the concepts of personality. Oxford: Aldine.

    Google Scholar 

  • Gosling, S. D., Rentfrow, P. J., & Swann, W. B. (2003). A very brief measure of the big-five personality domains. Journal of Research in Personality, 37, 504–528.

    Article  Google Scholar 

  • Green, S. B., & Yang, Y. (2009). Commentary on coefficient alpha: a cautionary tale. Psychometrika, 74, 121–135.

    Article  Google Scholar 

  • Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30, 179–185.

    Article  PubMed  Google Scholar 

  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 1–55.

    Article  Google Scholar 

  • Karyadi, K. A., VanderVeen, J. D., & Cyders, M. A. (2014). A meta-analysis of the relationship between trait mindfulness and substance use behaviors. Drug and Alcohol Dependence, 143, 1–10.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kessler, R. C., Andrews, G., Colpe, L. J., Hiripi, E., Mroczek, D. K., Normand, S.-L. T., et al. (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine, 32, 959–976.

    Article  PubMed  Google Scholar 

  • Lai, K., & Green, S. B. (2016). The problem with having two watches: assessment of fit when RMSEA and CFI disagree. Multivariate Behavioral Research, 51, 220–239.

    Article  PubMed  Google Scholar 

  • Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002). To parcel or not to parcel: exploring the question, weighing the merits. Structural Equation Modeling: A Multidisciplinary Journal, 9, 151–173.

    Article  Google Scholar 

  • Lubinski, D. (2004). Introduction to the special section on cognitive abilities: 100 years after Spearman’s (1904) “‘General intelligence,’ objectively determined and measured”. Journal of Personality and Social Psychology, 86, 96–111.

    Article  PubMed  Google Scholar 

  • Lynam, D., Smith, G., Whiteside, S., & Cyders, M. (2006). The UPPS-P: assessing five personality pathways to impulsive behavior. West Lafayette: Purdue University.

    Google Scholar 

  • MacDonald, H. Z., & Price, J. L. (2017). Emotional understanding: examining alexithymia as a mediator of the relationship between mindfulness and empathy. Mindfulness, 8, 1644–1652.

    Article  Google Scholar 

  • Medvedev, O. N., Siegert, R. J., Kersten, P., & Krägeloh, C. U. (2017). Improving the precision of the five facet mindfulness questionnaire using a Rasch approach. Mindfulness, 8, 995–1008.

    Article  Google Scholar 

  • Millsap, R. E. (2007). Structural equation modeling made difficult. Personality and Individual Differences, 42, 875–881.

    Article  Google Scholar 

  • Millsap, R. E., & Olivera-Aguilar, M. (2015). Investigating measurement invariance using confirmatory factor analysis. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (pp. 380–392). New York: Guilford Press.

    Google Scholar 

  • Muthén, L. K., & Muthén, B. (2015). Mplus user’s guide (7th ed.). Los Angeles: Muthén & Muthén.

    Google Scholar 

  • Neal, D. J., & Carey, K. B. (2005). A follow-up psychometric analysis of the self-regulation questionnaire. Psychology of Addictive Behaviors, 19, 414–422.

    Article  PubMed  PubMed Central  Google Scholar 

  • Pelham, W. E., III, Gonzalez, O., Metcalf, S. A., Whicker, C. L., Scherer, E. A., Witkiewitz, K., et al. (2019). Item response theory analysis of the five facet mindfulness questionnaire and its short forms. Mindfulness, 10, 1615–1628.

    Article  PubMed  PubMed Central  Google Scholar 

  • Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88, 879–903.

    Article  PubMed  Google Scholar 

  • Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–569.

  • R Core Team. (2019). R: A language and environment for statistical computing. Vienna, Austria: R Foundating for Statistical Computing.

    Google Scholar 

  • Reise, S. P., Bonifay, W. E., & Haviland, M. G. (2013a). Scoring and modeling psychological measures in the presence of multidimensionality. Journal of Personality Assessment, 95, 129–140.

    Article  PubMed  Google Scholar 

  • Reise, S. P., Scheines, R., Widaman, K. F., & Haviland, M. G. (2013b). Multidimensionality and structural coefficient bias in structural equation modeling: a bifactor perspective. Educational and Psychological Measurement, 73, 5–26.

    Article  Google Scholar 

  • Revelle, W. R. (2017). Psych: procedures for personality and psychological research. Evanston: Northwestern University.

    Google Scholar 

  • Saunders, J. B., Aasland, O. G., Babor, T. F., Fuente, J. R. D. L., & Grant, M. (1993). Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption-II. Addiction, 88, 791–804.

    Article  PubMed  Google Scholar 

  • Smith, G. T., McCarthy, D. M., & Anderson, K. G. (2000). On the sins of short-form development. Psychological Assessment, 12, 102–111.

    Article  PubMed  Google Scholar 

  • Sochat, V. V., Eisenberg, I. W., Enkavi, A. Z., Li, J., Bissett, P. G., & Poldrack, R. A. (2016). The experiment factory: Standardizing behavioral experiments. Frontiers in Psychology, 7, 610.

    Article  PubMed  PubMed Central  Google Scholar 

  • Tangney, J. P., Baumeister, R. F., & Boone, A. L. (2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72, 271–324.

    Article  PubMed  Google Scholar 

  • Tran, U. S., Glück, T. M., & Nader, I. W. (2013). Investigating the five facet mindfulness questionnaire (FFMQ): construction of a short form and evidence of a two-factor higher order structure of mindfulness. Journal of Clinical Psychology, 69, 951–965.

    Article  PubMed  Google Scholar 

  • van Dam, N. T., Hobkirk, A. L., Danoff-Burg, S., & Earleywine, M. (2012). Mind your words: positive and negative items create method effects on the five facet mindfulness questionnaire. Assessment, 19, 198–204.

    Article  PubMed  Google Scholar 

  • Veehof, M. M., ten Klooster, P. M., Taal, E., Westerhof, G. J., & Bohlmeijer, E. T. (2011). Psychometric properties of the Dutch Five Facet Mindfulness Questionnaire (FFMQ) in patients with fibromyalgia. Clinical Rheumatology, 30, 1045–1054.

    Article  PubMed  PubMed Central  Google Scholar 

  • West, S. G., Taylor, A. B. & Wu, W. (2012). Model fit and model selection in structural equation modeling. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (pp. 209-231). New York, NY: Guilford.

  • Williams, E. J. (1959). The comparison of regression variables. Journal of the Royal Statistical Society. Series B (Methodological), 21, 396–399.

    Article  Google Scholar 

  • Williams, M. J., Dalgleish, T., Karl, A., & Kuyken, W. (2014). Examining the factor structures of the five facet mindfulness questionnaire and the self-compassion scale. Psychological Assessment, 26, 407–418.

    Article  PubMed  Google Scholar 

  • Yen, W. M. (1993). Scaling performance assessments: Strategies for managing local item dependence. Journal of Educational Measurement, 30, 187–213.

    Article  Google Scholar 

  • Yu, C. Y. (2002). Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes (doctoral dissertation). University of California. Los Angeles.

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Funding

This work was supported by the National Institutes of Health (NIH) Science of Behavior Change Common Fund Program through an award administered by the National Institute on Drug Abuse (NIDA) UH2 DA041713. Additional support was provided by NIDA P30 DA029926 and R37 DA009757, National Science Foundation grant DGE-1311230, and National Institute on Alcohol Abuse and Alcoholism grant F31 AA026768. Finally, data for the replication sample were collected using support from NIDA R21 DA010562 and R01 DA025764.

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Contributions

LM and DM designed and executed the study from which data for the primary sample were drawn. KW designed and executed the larger study from which data for the secondary sample were drawn. WP, OG, and DM conceptualized the current research question and planned analyses. WP and OG carried out analyses and wrote the first draft of the manuscript. SM, CW, KW, LM, and DM critically reviewed and revised the manuscript. All authors approved the final version of the manuscript for submission.

Corresponding author

Correspondence to William E. Pelham III.

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The authors declare that they have no conflicts of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. IRB approval for the primary sample study was received at Stanford University. IRB approval for the secondary sample studies was received at the University of Washington.

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Pelham, W.E., Gonzalez, O., Metcalf, S.A. et al. Evaluating the Factor Structure of Each Facet of the Five Facet Mindfulness Questionnaire. Mindfulness 10, 2629–2646 (2019). https://doi.org/10.1007/s12671-019-01235-2

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