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07-10-2019 | ORIGINAL PAPER | Uitgave 12/2019

Mindfulness 12/2019

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

Mindfulness > Uitgave 12/2019
William E. Pelham III, Oscar Gonzalez, Stephen A. Metcalf, Cady L. Whicker, Katie Witkiewitz, Lisa A. Marsch, David P. Mackinnon
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The online version of this article (https://​doi.​org/​10.​1007/​s12671-019-01235-2) contains supplementary material, which is available to authorized users.

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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.


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.


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.


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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