A Network Analysis of the Five Facets Mindfulness Questionnaire (FFMQ)

Abstract

Objectives The Five Facet Mindfulness Questionnaire (FFMQ) is a popular self-report instrument for mindfulness assessment. However, several studies report mixed evidence regarding its reliability and validity. While recent replication studies have shown several issues regarding its latent structure, first-order facets seemed to replicate successfully. This study proposes an exploratory approach to these facets on an item level in one sample, with cross-validation in another sample. Methods Using a snowball sampling, 1008 participants were recruited in the first sample. Psychometric networks were applied to explore relations between items and item clusters. We compared these exploratory latent variable proposals with previous literature. A second sample of 1210 participants was collected from an FFMQ validation study, and confirmatory factor analyses were applied to cross-validate findings on the first sample. Results The FFMQ showed a positively correlated network. Exploratory analyses suggested the 5-facet structure as stable with alternatives of 4-facet (merging Observe and Non-Judging) and 6-facet (splitting Acting with Awareness in two) solutions. However, the CFAs in the second sample did not provide clear support to any solution. Conclusions The FFMQ showed unclear evidence on its latent structure. We propose researchers and users of the FFMQ to use the most fitting solution between the 5 and 6-facet solutions in their data, since the 4-facet solution is difficult to interpret. We also propose cautionary notes and guidelines for researchers and applied users of the FFMQ and regarding this instrument. We conclude that more research is needed in mindfulness assessment to provide robust measurements.

A Network Analysis of the Fear of COVID-19 Scale (FCV-19S): A Large-Scale Cross-Cultural Study in Iran, Bangladesh, and Norway

“…This allows one to explore and model complex sets of multivariate data, flexibly and robustly, without needing strong theoretical models [ 58 ]. Some applied examples are present in psychopathology [ 59 ], personality [ 60 ], social psychology [ 61 ], and psychometric research [ 62 , 63 ]. Therefore, a network analysis can help researchers quickly understand the relationships between variables and provide exploratory interactive models [ 64 ].…”

Unraveling Heterogeneities in Mindfulness Profiles: a Review and Latent Profile Analysis of the Five Facet Mindfulness Questionnaire Short-Form (FFMQ-SF) in the Spanish Population

“…Most validation studies featured sub-optimal practices, while an attempt to replicate the latent structure of the FFMQ required several modifications. Nevertheless, recent contributions showed the five facets as stable in some contexts, whereas they also propose alternative structures (i.e., six facets without an overall mindfulness factor; Karl et al, 2020;Lecuona et al, 2021). In addition, the Observe facet has shown mixed properties in prior literature, showing negative relations with other facets in clinical and nonmeditators (e.g., Carpenter et al, 2019;Diehl et al, 2021).…”

The psychometric properties of the Vietnamese Version of the Five Facet Mindfulness Questionnaire

“…Specifically, the FFMQ conceptualizes mindfulness as a psychological construct with five latent facets: Observe (i.e., attending to internal and external experiences), Describe (i.e., labeling internal experiences with words), Actaware (i.e., attending to one’s activities of the moment), Nonjudge (i.e., taking a nonevaluative stance toward thoughts and feelings), and Nonreact (i.e., not getting caught up in thoughts and feelings). Although the FFMQ offered a psychologically interpretable model of mindfulness, many researchers [ 19 – 21 ] disagreed on the latent structure of the FFMQ in the general population and several authors [ 19 – 22 ] also called attention to the lack of the FFMQ research in non-Western countries. In the following paragraphs, we examined each of these points in details.…”

“…To add more nuances to the current discussion on the FFMQ structure, a recent study by Lecuona et al [ 21 ] that used a recently developed psychometric method (i.e., the exploratory graph analysis (EGA) [ 33 – 35 ]) made several contributions to the understanding of the FFMQ structure. Specifically, using the EGA, which was shown to be comparable to standard parallel analysis [ 35 ], Lecuona et al [ 21 ] offered a six-facet model with the Actaware split into two facets, which was deemed a competitive alternative to the regular five-facet model. These results corresponded to Karl et al [ 20 ]’s findings that in many cultures, the six-factor model with a split Actaware facet provided the best fit model for the FFMQ.…”