Top

Open Access 19-02-2025 | ORIGINAL PAPER

Psychometric Properties of the Five Facet Mindfulness Questionnaire Short Version (FFMQ-SF) in the Colombian Population

Auteurs: Diego F. Castañeda, Javier M. Bianchi, Javier A. Villalba-Garzón, Francisco J. Ruiz

Gepubliceerd in: Mindfulness

Abstract

Objectives

The Five Facet Mindfulness Questionnaire (FFMQ) is one of the most widely used instruments for assessing mindfulness and was developed based on previously established mindfulness scales. This study aimed to estimate the psychometric properties of the 24-item version of the FFMQ in a Colombian sample.

Method

Psychometric analyses were performed in a sample of 582 Colombian adults, recruited through non-probabilistic convenience sampling, using classical test theory and the Rasch model. The internal structure was obtained with a confirmatory factor analysis (CFA). The FFMQ-SF scores were correlated with mindfulness, inflexibility, emotional symptomatology, behavioral activation, and environmental reward.

Results

The five-factor structure was confirmed to be invariant with respect to sex and meditation practice. Alpha and McDonald’s omega coefficients ranged from 0.68 for Non-reactivity to inner experience to 0.87 for Acting with awareness. The correlations with emotional symptomatology, mindfulness, and the transdiagnostic variables measured were of expected magnitude and direction. Twenty of the 24 items had good infit and outfit indices, and Items 10 and 13 presented DIF concerning sex.

Conclusions

Findings indicated that the FFMQ-SF exhibited robust psychometric properties for evaluating the five facets of mindfulness in a Colombian sample. Nevertheless, interpreting scores on the “observe” facet should be cautiously approached.

Preregistration

This study was not preregistered.

Supplementary file1 (DOCX 1.29 MB)

Supplementary file2 (DOCX 4.11 MB)

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1007/s12671-025-02533-8.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

By 2010, about 180 mindfulness-related scientific articles were published, while by 2022, more than 1400 (American Mindfulness Research Association, 2023), which shows the growing interest in this field of study. Mindfulness has been described as an awareness focused on the present moment, characterized by openness, receptivity, curiosity, and letting go of judgments (Kabat-Zinn, 2003; Rau & Williams, 2016). Bishop et al. (2004) proposed mindfulness comprises two elements: (a) the self-regulation of attention directed to the present moment and (b) adopting an attitude of curiosity, openness, and acceptance toward ongoing own experiences. Similarly, mindfulness can be considered an effort to intentionally attend to the experiences and sensations of the present moment without judgment for a prolonged time (Segal et al., 2013).

In the clinical field, mindfulness is the core of some intervention programs (e.g., Mindfulness-Based Stress Reduction Program; Kabat-Zinn, 1990) or part of multicomponent therapies, such as Acceptance and Commitment Therapy (ACT; Hayes et al., 1999), Dialectical Behavior Therapy (Linehan et al., 1993) and Mode Deactivation Therapy (Jennings & Apsche, 2014). These strategies conceptualize mindfulness as a set of skills that will facilitate decreasing psychological distress and promote well-being (Baer et al., 2006).

As interest in using mindfulness-based interventions has increased, assessment tools for this construct have been developed. These instruments vary depending on the required degree of familiarity with mindfulness meditation practice needed to respond and the number of dimensions (Ruiz et al., 2016b): from one (e.g., Mindfulness Attention Awareness Scale; Brown & Ryan, 2003) to five (Five Facets Mindfulness Questionnaire; Baer et al., 2006). The FFMQ is one of the most widely used instruments and was designed based on previously developed mindfulness scales: the MAAS, Kentucky Inventory of Mindfulness Skills (KIMS; Baer et al., 2004), Cognitive and Affective Mindfulness Scale (CAMS; Feldman et al., 2004), Mindfulness Questionnaire (MQ; Chadwick et al., 2005), and Freiburg Mindfulness Inventory (FMI; Buchheld et al., 2001). The study conducted by Baer et al. (2006) identified five facets of mindfulness through factor-analytic studies with the MAAS, KIMS, CAMS, MQ, and FMI: (a) Observing: noticing or attending to inner and outer experiences; (b) Describing: labeling inner experiences with words, (c) Acting with awareness: paying attention to the activities taking place; (d) Non-judging of experience: adopting a non-judgmental stance to feelings and thoughts; and (e) Non-reactivity to inner experience: the tendency to allow the flows of thoughts and feelings, without engaging or responding based on them.

The FFMQ is a 39-item instrument with an internal consistency ranging from adequate to good (α values between 0.75 and 0.91) and with significant correlations among the facets, except for Observing and Non-judging of experience. The confirmatory factor analysis (CFA) of the five-factor structure presented an adequate fit (Baer et al., 2006). The FFMQ has been adapted and validated in Spain (Cebolla et al., 2012), Austria (Tran et al., 2013), Holland (Veehof et al., 2011), France (Heeren et al., 2011), China (Hou et al., 2014), Norway (Dundas et al., 2013), and Chile (Schmidt & Vinet, 2015), Colombia (Sosa, 2019), among others.

The study by Sosa (2019) validated the FFMQ in Colombian samples. The author submitted the Spanish version of Cebolla et al. (2012) for evaluation by five expert judges. The inter-judge agreement yielded \({k}_{\text{free}}\) (Randolph, 2005) values between intermediate and good (0.50, 0.91), according to Fleiss (1981), in the following criteria: relevance, semantics, syntax, and coherence. Sosa reported that 12 items were modified for linguistic adjustment to “Colombian” Spanish. Additionally, in a sample of 395 Colombian participants, Sosa (2019) found alpha values between 0.79 (Non-reactivity to inner experience subscale) and 0.87 (Acting with awareness subscale). The author confirmed a five-factor model with relationships between item errors of three dimensions, which showed mixed fit indices, between adequate and poor.

Despite its robust psychometric properties, the 39 items of the FFMQ make it a lengthy questionnaire (Oñate & Calvete, 2018), which has motivated the development of shorter versions. Bohlmeijer et al. (2011) developed the 24-item Five Facet Mindfulness Questionnaire Short-Form (FFMQ-SF-24) by selecting the items that presented better corrected item-total correlations and standardized factor loadings in the CFA model. The internal consistency of the resulting facets ranged between adequate and good (α values between 0.75 and 0.87), and they showed theoretically coherent correlations with symptoms of depression and anxiety.

Subsequently, Oñate and Calvete (2018) analyzed the psychometric properties of the FFMQ-SF-24 in a sample of 265 relatives of people with intellectual and developmental disabilities in Spain. The facets obtained adequate to good internal consistency (α values between 0.71 and 0.82). Spearman’s correlation values between facets were moderate (rho between 0.22 and 0.41). The five-factor model showed acceptable goodness-of-fit indices (RMSEA = 0.08, CFI = 0.93, NNFI = 0.92). However, correlations were not significant between the facets Observing and Acting with awareness (rho = 0.08), Non-judging and Non-reactivity (rho = 0.10), and Non-judging and Describing (rho = 0.01).

Brady et al. (2019) found adequate to good internal consistency for the FFMQ dimensions (α values between 0.72 and 0.85) in Australian and New Zealand older adults. In clinical samples, Fong et al. (2021) and de Gu et al. (2016) reported adequate internal consistency of the FFMQ dimensions (α values between 0.69 and 0.85), and the five-factor structure obtained a good fit to the data in the 20- and 15-item versions, respectively.

Mixed evidence has been found regarding the factor structure of the FFMQ-SF-24 (Fernández Curado et al., 2022; Lecuona et al., 2022). On the one hand, some studies have found a five-factor structure in which the mindfulness facets are correlated, as in the original study (Bohlmeijer et al., 2011). These studies were conducted on Brazilian adults (Fernández Curado et al., 2022), Chinese patients of cancer (Fong et al., 2021), psychiatric patients in the USA (Levin-Aspenson et al., 2023), and Spanish caregivers (Oñate & Calvete, 2018), among others. On the other hand, some studies have found a hierarchical structure in which the five mindfulness facets are part of one or more second-order factors (Brady et al., 2019; Iani et al., 2017), or a bifactor structure (Fernández Curado et al., 2022).

Research on the FFMQ has yielded varying results regarding measurement invariance across different versions and populations. Studies have demonstrated measurement invariance across sex and meditation practice in Argentine university students using the 39-item FFMQ (Correa et al., 2023), and metric invariance across Bhutanese and US populations for the same version (Haas & Akamatsu, 2019). Further studies have shown varying levels of invariance for other FFMQ versions. For example, the 20-item FFMQ demonstrated residual factorial invariance between genders and metric invariance across grades in early Chinese adolescents (Hu et al., 2024). The 15-item version exhibited metric invariance across genders and cultures (Pakistan and Spain), although this invariance was limited to the Non-judgment subscale in the case of cultural comparisons (Iqbal et al., 2023). These findings suggest that the level of measurement invariance may vary depending on the specific FFMQ version and the characteristics of the sample studied. Previous studies have examined the psychometric properties of the FFMQ-SF-24, particularly in relation to sex and meditation practice. However, the search did not yield any evidence of factorial invariance for the FFMQ-SF-24 in relation to sex or meditation practice, suggesting that further research is needed to establish the validity of this shorter version of the FFMQ for these specific groups.

Most of the research on the FFMQ (Correa et al., 2023) and FFMQ-SF-24 (Asensio-Martínez et al., 2019; Lecuona et al., 2022; Oñate & Calvete, 2018) in Spanish-speaking countries has been conducted with the Spanish adaptation by Cebolla et al. (2012). Cebolla et al. (2012) did not report the linguistic adaptation process of the item content. In the current study, we used the version adapted by Sosa (2019), who adjusted the linguistic content of six of the items of the Spanish version of the FFMQ-39 by Cebolla et al. (2012): Items 12 (5 in the FFMQ-SF), 19 (9), 22 (11), 26 (15), 28 (17), and 31 (20). This choice is based on the identification that (a) the social fabric in Colombia is characterized by a network of cultural and ethnic diversity that affects both the construction of psychometric tests and their validation (Zapata-Orozco et al., 2020) and (b) the potential differences in the use of the Spanish language, as well as idiomatic expressions that may affect the accuracy of the measure.

In summary, the FFMQ is a widely accepted tool to measure mindfulness (Asuero et al., 2013; Gracia Gozalo et al., 2019; Salamea et al., 2019) and can be seen as the most comprehensive measure of mindfulness facets. However, it is an extensive tool (i.e., 39 items), which hinders its use in clinical and research settings (Oñate & Calvete, 2018). The FFMQ-SF-24 reduced 15 items and demonstrated psychometric properties similar to those of the long version. Accordingly, this study aimed to analyze the validity evidence of the FFMQ-SF-24 in a Colombian sample regarding its internal structure, factorial invariance testing, and Differential Item Functioning (DIF) detection.

According to previous research, we also collected evidence of the relationships of the FFMQ-SF-24 with other variables, such as dispositional mindfulness and emotional symptoms. Additionally, we explored the relationships between the FFMQ-SF and constructs related to behavioral activation, such as activation, avoidance, and environmental reward, because previous studies have shown that mindfulness training might increase reward experience in adults vulnerable to depression (Geschwind et al., 2011) and participants with kleptomania (Asami et al., 2022). Likewise, after a mindfulness intervention in participants with addictions, Garland (2016) found an increase in the preference for positive environmental rewards instead of substances. Lastly, we included a measure of psychological inflexibility, given the extensive research that has linked this construct with mindfulness (e.g., Latzman & Masuda, 2013; Ruiz, 2014).

Method

Participants

The participants were 582 Colombians between 18 and 87 years old. They were mostly women (74.3%), single (68.0%), and university students (53.2%). The research counted the participation of people from the country’s five regions, most from Bogotá, D.C. (n = 333, 57.22%). Regarding mental health, 241 (41.41%) participants had attended psychological and/or psychiatric services at some point in their lives, 72 (12.37%) in the last month.

Measures

Meditation Practice

The sociodemographic form included questions regarding participants’ experience with mindfulness. First, participants were asked whether they engaged in some sort of meditation practice. If they responded “yes,” they were asked the time they have been practicing meditation (response options: 1 month, 6 months, 1 year, 3 years, or more).

Five Facet Mindfulness Questionnaire (FFMQ)

The FFMQ was developed by Baer et al. (2006), and we used the Spanish version by Sosa (2019). The FFMQ is a 39-item questionnaire that is responded to on a Likert-type scale (1 = never or very rarely true; 5 = very often or always true). It assesses five facets of mindfulness: Observing, Describing, Acting with awareness, Non-judging of experience, and Non-reactivity to inner experience. The higher the score, the higher the mindfulness facet. The Colombian version (Sosa, 2019) presented good internal consistency (α = 0.86) for the total scale and evidence of content validity, internal structure, and its relationship with other variables. The FFMQ has a short form (FFMQ-SF-24; Bohlmeijer et al., 2011) consisting of a selection of 24 items. The FFMQ-SF-24 has shown adequate internal consistency, and its facets have shown similar relationships with related constructs as the long version. In the current study, the FFMQ presented Cronbach’s alpha and McDonald’s omega of 0.91, with a mean score of 128.46 (SD = 20.73).

Mindful Attention Awareness Scale (MAAS)

The MAAS was developed by Brown and Ryan (2003), and we used the Spanish version by Ruiz et al. (2016b). The MAAS evaluates the degree to which individuals pay attention when performing some tasks. It comprises 15 items that are responded to on a 6-point Likert-type scale (1 = almost never; 6 = almost always). High scores indicate a higher level of mindfulness. The Spanish version showed excellent internal consistency (α = 0.92) in Colombian samples, the expected one-factor model, and convergent validity. In the current study, the MAAS showed alpha and omega values of 0.93, with a mean score of 64.12 (SD = 15.31).

Acceptance and Action Questionnaire – II (AAQ-II)

The AAQ-II was developed by Bond et al. (2011), and we used the Spanish version by Ruiz et al. (2013). The AAQ-II is a measure of psychological inflexibility. It comprises 7 items that are responded to on a 7-point Likert-type scale (1 = never true; 7 = always true). The higher the scores, the greater the degree of psychological inflexibility. The Spanish version showed excellent internal consistency (α = 0.91) in Colombian samples, the expected one-factor structure, and convergent and discriminant validity (Ruiz et al., 2016a, 2024). In this study, the AAQ-II obtained alpha and omega values of 0.95, with a mean score of 21.98 (SD = 11.04).

Depression Anxiety Stress Scales – 21 (DASS-21)

The DASS-21 was developed by Lovibond and Lovibond (1995), and we used the Spanish version by Daza et al. (2002). The DASS-21 was designed to evaluate emotional symptoms of Depression, Anxiety, and Stress. It comprises 21 items that are responded to on a 4-point Likert-type scale (0 = did not apply to me at all; 3 = applied to me very much, or most of the time). The higher the score, the greater the degree of symptomatology. The Spanish version showed excellent internal consistency in Colombian samples (Ruiz et al., 2017) and a hierarchical factor structure consisting of three first-order factors and a second-order factor representing a general emotional symptomatology factor. In this study, the DASS-21 showed alpha and omega values of 0.96 for the total scale and mean score of 21.40 (SD = 14.97).

Behavioral Activation for Depression Scale – Short Form (BADS-SF)

The BADS-SF was developed by Manos et al. (2011), and we used a Spanish version by García (2019). It comprises 9 items that are responded to on a 7-point Likert scale (0 = not at all; 6 = completely). It measures two dimensions related to behavioral activation: Avoidance and Activation. The Spanish version of the BADS-SF showed adequate internal consistency, the expected two-factor model, and convergent validity (García, 2019). In this study, the BADS-SF presented alpha and omega values of 0.82 and 0.81, respectively. The mean score was 32.75 (SD = 10.00).

Reward Probability Index (RPI)

The RPI was developed by Carvalho et al. (2011), and we used the Spanish version by Reyes-Buitrago et al. (2023). The RPI is a self-report instrument that was designed to evaluate the magnitude of environmental reward as an approximation of response contingent positive reinforcement (RCPR) through two factors: Reward Probability and Environmental Suppressors. It comprises 20 items that are responded to on a 4-point Likert-type scale. The Spanish version showed good internal consistency, the expected two-factor model, and convergent validity (Reyes-Buitrago et al., 2023). In this study, the RPI showed alpha and omega values of 0.88 and 0.87, respectively. Participants’ mean score was 56.38 (SD = 8.61).

Procedure

Permission to use the instrument was obtained via email from the corresponding author of the FFMQ-SF-24. Participants responded to an anonymous online survey (Microsoft Forms) disseminated through social networks (e.g., Facebook, WhatsApp, and Instagram), including meditation groups. Thus, a snowball sampling procedure was conducted in which the researchers asked their contacts and participants to share the publication of the survey to reach more potential participants. The data collection period was from September to December 2021.

Before accessing the questionnaire package, participants provided informed consent by accepting the conditions explained at the beginning of the survey, including that they were adults. The informed consent emphasized that participation was anonymous, and the participants could stop their participation anytime they wanted. The median time for the completion of the survey was approximately 25 min. Participants were not compensated for their participation.

Data Analyses

A descriptive analysis of the sociodemographic data and scale scores was performed to identify the type of distribution, frequencies, means, standard deviations, and ranges. Following the guidelines proposed in the Standards for Psychological and Educational Tests of the American Educational Research Association, the American Psychological Association, and the National Council on Measurement in Education (AERA, APA & NCME, 2014), the evidence based on the internal structure was collected through CFA and DIF methods between men and women and meditation practice. Three models were compared through CFAs with the Diagonally Weighted Least Squares (DWLS) estimator: (a) a one-factor model, (b) a five-factor model, and (c) a five-factor model with a second-order factor. The following goodness-of-fit indexes were computed: (a) the comparative fit index (CFI), (b) the Tucker-Lewis index (TLI), (c) the normed fit index (NFI), (d) the incremental fit index, (e) the goodness of fit (GFI), (f) the root mean square error of approximation (RMSEA), and (g) the parsimony normed fit index (PNFI). The models were assessed based on χ²/df < 4; CFI ≥ 0.95; TLI, NFI, IFI, and GFI > 0.90; and RMSEA < 0.05. Additionally, higher PNFI values indicate a more parsimonious model (Rial et al., 2006).

Multigroup CFAs were performed to test configural, metric, scalar, and residual factorial invariance regarding sex and the condition of practicing meditation. The analysis was progressive and sequential, starting from a configural invariance model and then imposing restrictions until a model was rejected or the residual model was achieved. To reject models, the criteria suggested by Lippke et al. (2007) (a p-value of ∆χ² < 0.050, and a ∆TLI value > 0.050) and Chen (2007) (∆RMSEA value > 0.015) were adopted. For DIF detection, significance values of χ² < 0.05 and pseudo-R² Nagelkerke index values > 0.010 between compared groups were considered (Choi et al., 2011).

The internal consistency of the instruments was estimated with Cronbach’s alpha (α) and McDonald’s omega (ω) coefficients. Values greater than 0.70 were considered adequate for both internal consistency indices (George & Mallery, 2003; Ventura-León & Caycho-Rodríguez, 2017). Additionally, the discrimination index was calculated with item-total and item-subscale item correlations. The CTT analyses were complemented with estimates of the Rasch model of Item Response Theory (IRT) and the parameters b and θ with their respective standard errors, the INFIT and OUTFIT fit indices, and the Test Information Functions (TIF).

To analyze the evidence based on the relationships of the FFMQ-SF-24 with other variables, correlations between total and subscale scores with FFMQ-39, MAAS, AAQ-II, DASS-21, RPI, and BADS-SF scores were estimated. Spearman’s correlation coefficient (rho) was calculated where values < 0.10 are considered negligible correlations, 0.10 to 0.30 weak, > 0.30 moderate correlations, and > 0.50 strong correlations (Goss-Sampson, 2019).

Student’s t-test was used to identify the differences between the subsamples of meditators and non-meditators. This test allows reporting the data, even if they are not normally distributed, by considering the homogeneity in variances (Goss-Sampson, 2019).

Data analysis was performed with the ULLR Toolbox add-on version 4.0.2 for Windows RStudio (Hernández, 2017). The libraries lavaan (Version 0.6–7; Rosseel, 2012), semTools (Version 0.5–5; Jorgensen et al., 2019), semPlot (Version 1.1.2; Epskamp, 2015), eRm (Version 1.0–6; Mair & Hatzinger, 2007), and lordif (Version 0.3–3; Choi et al., 2011) were used.

Results

Mindfulness Practice

Of the total sample, 22.6% (n = 132) reported engaging to some extent in meditation practices (24.2% were males and 75.70% were females): 21.2% reported formal practice for 6 months to 1 year, 41.7% between 1 and 3 years, and 37.1% for more than 3 years. Of them, 54.1% attended mental health services at some point in their lives. Seventy-eight percent reported university and/or postgraduate studies, and 73.0% were single, followed by 15.0% in a free union. Twenty-seven participants were excluded because they reported that their meditation practice was less than 6 months.

Validity Evidence Based on Internal Structure

Confirmatory Factor Analyses

Three models were analyzed: a one-factor model, the original five-factor model, and a five-factor model with a second-order factor (Table 1). The results showed good goodness-of-fit indices for the five-factor model: \({\chi }^{2}\)/df = 2.302, RMSEA = 0.047 (90% CI [0.042, 0.053]), TLI = 0.962, CFI = 0.967, NFI = 0.943, IFI = 0.976, and GFI = 0.971, which indicate a good fit to the model (Rial et al., 2006).

Table 1

Goodness-of-fit indices for tested models

Models	\({\chi }^{2}\)	df	CFI	TLI	NFI	PNFI	IFI	RMSEA	GFI
One factor	1767.722	252	0.839	0.824	0.818	0.747	0.948	0.102	0.910
One factor	1767.722	252	0.839	0.824	0.818	0.747	0.948	[0.097, 0.106]	0.910
Five factors	557.214	242	0.967	0.962	0.943	0.826	0.967	0.047	0.971
Five factors	557.214	242	0.967	0.962	0.943	0.826	0.967	[0.042, 0.053]	0.971
Five factors + second-order factor	751.221	247	0.946	0.940	0.922	0.826	0.947	0.059	0.962
Five factors + second-order factor	751.221	247	0.946	0.940	0.922	0.826	0.947	[0.054, 0.064]	0.962

Figure 1 shows that 22 of the 24 items presented factor loadings greater than 0.60; in only 2 items (7 and 9), the loadings were less than 0.32. The highest correlation was obtained between the factors Non-judging of experience and Acting with awareness, with a value of 0.64, and the lowest was between Observing and Non-judging of experience, with a value of 0.05. The factor that was most correlated with the others was Describing with a mean correlation of 0.49, while Observing had the lowest mean correlation, with a value of 0.20. The mean correlation among the five factors was 0.39.

Measurement Invariance

The factorial invariance analyses of the five-factor model across the sex and meditation practice variables show no statistically significant differences between men and women or in relation to whether meditation is practiced regularly (Table 2). In other words, no differences were found in the basic configuration of the model and its factor weights (configural and metric invariance), as well as in its intercept values and residual variances/covariances (scalar and residual invariance). The supplementary material of this article presents the figures with the standardized solutions for each of the invariance levels for each comparison group: (a) configural, items loading on the same factors; (b) metric, factor loadings being equivalent across groups; (c) scalar, allowing group comparisons; and (d) strict, the differences found in the comparisons are not attributable to differences in the measurement precision (Putnick & Bornstein, 2016).

Table 2

Factorial invariance across the sex and meditation practice variables

Variable	Invariance	df	\({\chi }^{2}\)	\({\Delta \chi }^{2}\)	∆df	p	ΔRMSEA scaled	ΔCFI scaled	ΔTLI scaled
Sex	Configural	484	709.23
	Metric	503	775.31	24.04	19	0.19	− 0.002	0.002	0.012
	Scalar	522	792.33	24.78	19	0.17	− 0.001	− 0.001	0.003
	Residual	546	822.47	33.84	24	0.09	− 0.001	0.001	0.004
Practice with meditation	Configural	484	705.09
	Metric	503	767.77	20.92	19	0.34	− 0.004	0.007	0.015
	Scalar	522	780.42	19.86	19	0.40	− 0.001	− 0.001	0.004
	Residual	546	801.92	27.04	24	0.30	− 0.001	0.001	0.006

DIF Detection

Items 10 (p = 0.00, 0.00, and 0.19 with R² Nagelkerke = 0.01, 0.01, and 0.00) and 13 (p = 0.00, 0.00, and 0.03 with R² Nagelkerke = 0.01, 0.01, and 0.00) presented differential functioning on the sex variable. Item 13 also presented DIF on the meditation practice variable with p = 0.42, 0.00, and 0.00 with Nagelkerke’s R² = 0.00, 0.01, and 0.01. Item 10 presented uniform DIF with lower probability scores for males in all four categories. In Item 13, the DIF was not uniform because women scored lower probabilities in the low category (1) and men in the high categories (2, 3, and 4). This item had the same type of DIF with people who do not practice meditation because they obtained lower probabilities in Categories 1, 2, and 3 but higher probabilities in Category 4.

Relations of the FFMQ-SF-24 Scores with Meditation Practice

Independent samples Student’s t-test was performed after ensuring compliance with its requirements because the variances were homogeneous (Levene’s test p > 0.05), although there was no normal distribution in all facets. Table 3 shows that the facets Observing (t(580) = 2.85, p = 0.00; d = 0.28) and Non-reactivity to inner experience (t(580) = 2.28, p = 0.02; d = 0.23) presented statistically significant differences in the groups of meditators and non-meditators with small effect sizes.

Table 3

Results of independent samples t-test

	Medit	M	SD	S-W		Levene’s		Student’s t
FFMQ SF	Medit	M	SD	W	p	F	p	t	df	p	Cohen’s d
Observing	Yes	14.19	3.42	0.97	0.003	0	0.98	2.85	580	0.004	0.28
Observing	No	13.21	3.48	0.98	< 0.001	0	0.98	2.85	580	0.004	0.28
Describing	Yes	18.13	3.96	0.98	0.040	0.70	0.40	1.48	580	0.138	0.145
Describing	No	17.52	4.18	0.98	< 0.001	0.70	0.40	1.48	580	0.138	0.145
Acting	Yes	17.56	4.13	0.98	0.037	0.33	0.57	1.28	580	0.203	0.13
Acting	No	17.01	4.44	0.97	< 0.001	0.33	0.57	1.28	580	0.203	0.13
Non-judging	Yes	16.54	4.59	0.98	0.092	0.54	0.46	1.16	580	0.248	0.11
Non-judging	No	16.03	4.35	0.98	< 0.001	0.54	0.46	1.16	580	0.248	0.11
Non-reactivity	Yes	16.30	3.17	0.97	0.012	3.48	0.06	2.28	580	0.023	0.23
Non-reactivity	No	15.51	3.63	0.99	< 0.001	3.48	0.06	2.28	580	0.023	0.23

S-W, Shapiro–Wilk test; Levene’s, homogeneity of variances test

Reliability

Table 4 shows the item-factor correlations ranged from 0.50 to 0.57 for Observing, from 0.52 to 0.67 for Describing, from 0.66 to 0.76 for Acting with awareness, from 0.43 to 0.70 for Non-judging of experience, and from 0.32 to 0.53 for Non-reactivity to inner experience. Thus, all item-factor correlations were above 0.30 (Frías, 2021), which agrees with expectations. The values of alpha and omega coefficients are also presented in Table 4. Both alpha and omega values ranged from 0.68 for Non-reactivity to inner experience to 0.87 for Acting with awareness.

Table 4

Internal consistency coefficients of the FFMQ-SF

Facet ω α [IC95%]	Item	M	SD	Factor
Facet ω α [IC95%]	Item	M	SD	Item-factor correl	ω without the item	α without the item
Observing	6	2.72	1.24	0.50	0.70	0.70
ω = 0.74 [0.71, 0.78]	10	3.29	1.18	0.55	0.68	0.67
α = 0.74 [0.70, 0.77]	15	3.69	1.09	0.51	0.69	0.69
	20	3.72	1.13	0.57	0.67	0.66
	1	3.49	1.06	0.67	0.77	0.76
Describing	2	3.64	1.04	0.62	0.79	0.78
ω = 0.82 [0.79, 0.84]	5R	2.49	1.21	0.67	0.77	0.76
α = 0.82 [0.79, 0.84]	11R	2.41	1.02	0.57	0.79	0.79
	16	3.43	1.11	0.52	0.82	0.81
Acting with awareness	8R	2.38	1.11	0.66	0.86	0.85
Acting with awareness	12R	2.38	1.09	0.72	0.84	0.84
ω = 0.87 [0.86, 0.89]	17R	2.75	1.02	0.66	0.85	0.85
α = 0.87 [0.85, 0.89]	22R	2.52	1.07	0.76	0.83	0.83
	23R	2.84	1.09	0.68	0.85	0.85
	4R	2.59	1.24	0.65	0.77	0.76
Non-judging of experience	7R	3.24	1.11	0.43	0.83	0.83
ω = 0.82 [0.80, 0.85]	14R	2.653	1.16	0.68	0.77	0.76
α = 0.81 [0.79, 0.84]	19R	2.483	1.17	0.70	0.76	0.75
	24R	2.885	1.13	0.57	0.80	0.79
Non-reactivity to inner experience	3	3.091	1.04	0.32	0.67	0.67
Non-reactivity to inner experience	9	3.122	1.18	0.38	0.66	0.65
ω = 0.68 [0.64, 0.72]	13	3.251	1.04	0.51	0.60	0.59
α = 0.68 [0.63, 0.72]	18	2.976	1.02	0.43	0.64	0.63
	21	3.247	1.07	0.53	0.59	0.58

Relations with Mindfulness, Present Moment Awareness, Emotional Symptoms, Psychological Inflexibility, Environmental Reward, and Activation

Table 5 shows that all the correlations of the FFMQ-SF-24 facets with the other variables were statistically significant (p < 0.001), with the exception of the Observing facet. As expected, the FFMQ-SF-24 strongly correlated with the original FFMQ. Likewise, the FFMQ-SF-24 facets showed medium and strong correlations with the MAAS scores. The FFMQ-SF-24 facets showed medium and strong correlations with constructs related to behavioral activation, as expected. Lastly, the FFMQ-SF-24 facets showed theoretically coherent negative correlations with emotional symptoms and psychological inflexibility.

Table 5

Correlations among the FFMQ-SF-24 and other measures

Scale	FFMQ-SF-24
Scale	Observing	Describing	Acting with awareness	Non-judging of experience	Non-reactivity to inner experience
FFMQ-39
Observing	0.88***	0.24***	0.09*	0.03	0.30***
Describing	0.21***	0.97***	0.49***	0.47***	0.47***
Acting	0.05	0.46***	0.95***	0.55***	0.30***
Non-judging	− 0.07	0.42***	0.50***	0.97***	0.24***
Non-reactivity	0.29***	0.43***	0.24***	0.25***	0.95***
MAAS
Total	0.17***	0.48***	0.70***	0.44***	0.28***
RPI
Total	0.13**	0.55***	0.51***	0.570***	0.39***
Reward Prob	0.19***	0.49***	0.42***	0.39***	0.36***
Env. Suppress	− 0.01	− 0.41***	− 0.41***	− 0.53***	− 0.30***
BADS-SF
Total	0.18***	0.51***	0.56***	0.55***	0.38***
Avoidance	− 0.11**	− 0.41***	− 0.50***	− 0.54***	− 0.30***
Activation	0.20***	0.43***	0.41***	0.37***	0.34***
DASS-21
Total	− 0.01	− 0.45***	− 0.57***	− 0.61***	− 0.29***
Depression	− 0.05	− 0.46***	− 0.55***	− 0.59***	− 0.31***
Anxiety	0.01	− 0.41***	− 0.47***	− 0.55***	− 0.28***
Stress	− 0.02	− 0.41***	− 0.55***	− 0.55***	− 0.26***
AAQ-II
Total	− 0.10*	− 0.53***	− 0.56***	− 0.66***	− 0.34***

*p < 0.05, **p < 0.01, ***p < 0.001. AAQ-II, Acceptance and Action Questionnaire – II; BADS-SF, Behavioral Activation for Depression Scale – Short Form; DASS-21, Depression Anxiety and Stress Scale – 21; Env. Suppress, Environmental Suppressors; FFMQ-SF-24, Five Facet Mindfulness Questionnaire – Short Form; MAAS, Mindful Attention Awareness Scale; RPI, Reward Probability Index; Reward Prob., Reward Probability

Psychometric Analyses Based on the Rasch Model

Compliance with the assumption of unidimensionality required by the model was guaranteed when performing the analyses by subscale. The parameters and goodness-of-fit indices were not obtained in the Observing facet because the Rasch model did not converge. According to the criteria of Hodge and Morgan (2017), the model did not fit for Items 1, 14, 19, and 22. In Item 21, there was only a misfit in the OUTFIT, indicating that the model loses prediction in the responses of people with measures θ far from the parameter b of this item. The b parameters of the items were distributed in the following ranges: 7.64 logits (Describe), 13.42 (Acting with awareness), 9.90 (Non-judging of Experience), and 6.53 (Non-reactivity to inner experience). In the θ parameters of the persons, the ranges were 6.05 logits, 8.34, 6.48, and 6.23, respectively. When comparing the ranges of the logit measures of the items and persons, it was identified that 8.42% of the participants had θ parameters below the b parameters of the FFMQ, and 13.40% had outlier measures. Table 6 shows the averages of the b-parameters obtained from the four categories, the average standard error of the parameters, and the INFIT and OUTFIT goodness-of-fit indices.

Table 6

Parameters and goodness-of-fit indices

		Parameter b	Standard error	\({\upchi }^{2}\)	df	p	Infit MSQ	Outfit MSQ
Describing	1	2.89	0.26	373.19	554	1.000	0.67	0.67
	2	2.25	0.26	430.83	554	1.000	0.77	0.78
	5R	2.82	0.26	448.25	554	1.000	0.84	0.81
	11R	2.48	0.26	487.99	554	0.980	0.84	0.88
	16	3.12	0.26	594.59	554	0.113	1.02	1.07
Acting with awareness	8R	3.58	0.30	547.30	556	0.596	0.98	0.98
	12R	3.55	0.30	432.85	556	1.000	0.79	0.78
	17R	5.45	0.32	493.87	556	0.972	0.85	0.89
	22R	4.29	0.31	366.78	556	1.000	0.66	0.66
	23R	5.93	0.33	471.68	556	0.996	0.85	0.85
Non-judging of experience	4R	2.33	0.21	480.64	565	0.996	0.82	0.85
	7R	4.55	0.25	665.12	565	0.002	1.11	1.18
	14R	2.54	0.22	386.95	565	1.000	0.69	0.68
	19R	1.94	0.21	374.43	565	1.000	0.67	0.66
	24R	3.33	0.22	494.43	565	0.985	0.85	0.87
Non-reactivity to inner experience	3	2.34	0.20	565.40	571	0.558	0.94	0.99
	9	2.25	0.20	601.10	571	0.185	1.04	1.05
	13	1.85	0.20	420.04	571	1.000	0.71	0.73
	18	2.70	0.21	451.98	571	1.000	0.77	0.79
	21	1.86	0.20	392.31	571	1.000	0.71	0.69

Regarding the precision of the estimation of the parameters θ, the standard errors reported in Table 6 and the Test Information Functions (TIFs) shown in Fig. 2 provide evidence that the Describe, Non-Judging, and Non-Reactivity facets presented higher precision compared to Acting with awareness. However, the latter maintained the highest level of precision over two logits (between three and five), while the other three only maintained this maximum of information around one logit unit.

Discussion

The current study analyzed the psychometric properties of the FFMQ-SF-24 in a large Colombian sample. Specifically, we analyzed the scale’s reliability, internal structure, relationships with the degree of attention paid when performing tasks (MAAS), the probability of reward (IRP), the level of activation (BADS-SF), psychological inflexibility (AAQ-II), emotional symptomatology (DASS-21), and the condition of practicing meditation.

In the internal structure validity evidence, the five-factor model was confirmed. All items obtained adequate factor loadings with their dimensions (from 0.305 to 0.917). The goodness-of-fit indices were excellent and comparable to the results of Bohlmeijer et al. (2011), and Oñate and Calvete (2018). The five-factor model with a second-order factor presented good fit indices, but the five-factor model showed the best fit. As mentioned above, previous evidence showed that both the model with five correlated factors and the five-factor model with a second-order factor are adequate; however, the five-factor correlated model tends to obtain a better fit (Brady et al., 2019; Levin-Aspenson et al., 2023; Oñate & Calvete, 2018) as in the original study (Bohlmeijer et al., 2011). Additionally, the fit in the present study was better than the study with caregivers by Oñate and Calvete (2018) and similar to that of Asensio-Martínez et al. (2019), who removed Item 18.

We found that the five-factor model was invariant for meditation practice and gender. This is relevant because it means that the FFMQ-SF-24 assesses the same latent/observed construct among these groups and adds evidence to what has been reported in the literature, given that the five-factor model has shown to be longitudinally invariant following ACT interventions (Levin-Aspenson et al., 2023). The current finding adds evidence to the analysis of measurement invariance of alternative versions of the FFMQ. For instance, the five-factor model of the original FFMQ has shown invariance across gender and meditation practice in Argentinian undergraduates (Correa et al., 2023) and across Bhutan and USA samples (Haas & Akamatsu, 2019). Other studies have also found evidence of measurement invariance in different versions of the FFMQ (Fong et al., 2021; Gu et al., 2016; Hu et al., 2024; Iqbal et al., 2023; Raphiphatthana & Jose, 2020).

Items 10, “Generally, I pay attention to sounds, such as clocks ticking, birds chirping, or cars passing”, and 13, “When I have distressing thoughts or images, I feel calm soon after,” presented DIF regarding sex, and Item 13 presented DIF in relation to meditation practice. According to Gómez-Benito et al. (2010), the presence of DIF does not necessarily indicate that the items have a bias between the groups compared; however, this result needs to be verified with further studies to rule out whether this differential functioning can really be explained by some bias that may affect the fairness of the measurement of mindfulness. The evidence collected in this study adds to the previous study conducted by Fernández Curado et al. (2022), who detected some levels of DIF in all subscales except for Acting with awareness. However, the analysis of modification indices of the CFA did not present evidence of DIF for any of the items in the subscales. In summary, it seems necessary to continue the DIF analysis of the FFMQ-SF-24, especially with bigger samples, to allow a more precise analysis of DIF presence.

Meditators presented significantly higher scores compared to the non-meditators group in Observing and Non-reactivity to inner experience, with small effect sizes. Thus, participants who practiced meditation presented higher levels of mindfulness skills compared to non-meditators, which has been reported by Loret de Mola Gubbins (2011). These results might be seen as evidence of the discriminant validity of the FFMQ-SF-24.

The FFMQ-SF-24 items showed adequate item-factor correlations. Alpha and omega values ranged from 0.68 to 0.87 for Non-reacting to inner experience and Acting with awareness, respectively. These values are similar to those reported by Oñate and Calvete (2018) and Brady et al. (2019).

Significant correlations were found between the FFMQ-SF-24 and the DASS-21 (emotional symptoms), its dimensions (depression, anxiety, and stress), the AAQ-II (psychological inflexibility), the avoidance dimension of the BADS-SF-24, and the environmental suppressor’s dimension of the RPI. These results indicate that the greater the ability of mindfulness, the lower the psychological inflexibility, avoidance, environmental suppressors, and clinical symptomatology, which is consistent with previous research (Bohlmeijer et al., 2011; Oñate & Calvete, 2018; Veehof et al., 2011).

The correlations found between the level of Activation (BADS-SF) and environmental reward (RPI) with the dimensions Describe, Acting with awareness, Non-judging, and Non-reactivity are theoretically coherent. In this regard, it has been found that self-compassion, understood as the cultivation of mindfulness in relation to one’s own suffering (Neff, 2003), allows people to overcome avoidance and increase behavioral activation, which increases the RCPR and, concomitantly, decreases depressive symptoms (Adie et al., 2021).

Regarding the results of the Rasch model, some items in the dimensions Non-judging of Experience (14 and 19), Describing (1), and Acting with awareness (22) did not fit. These items (except for Item 1) also presented low discrimination in a clinical sample (Pelham et al., 2019) according to a Graded Response Model. According to Karabatsos (2000), model misfit may indicate problems in the formulation of the items or the presence of multidimensionality, biases, or random responses. However, no problems were identified in the wording of these items. Possible biases were also ruled out because none of these items presented DIF, and there were no low item-factor correlations that would evidence randomness in the responses. In this sense, the most viable hypothesis to explain the mismatch found leans toward the presence of multidimensionality in these items, especially because, in the results of Pelham et al. (2019), the discrimination parameter decreased in the clinical sample.

The Observing facet was not modeled with the Rasch model because the matrix could not be inverted, and some vectors were collinear. The items in this dimension had the lowest discrimination parameter in the clinical sample of the study of Pelham et al. (2019), and none conveyed much information above the logit mean of the latent trait. In general, the results of this study and Pelham et al. (2019) showed that the Observing facet should be deeply analyzed because the IRT models used in both studies evidenced a poor psychometric function. In this sense, the Observing facet also showed low correlations with the remaining mindfulness facets and negligible correlations with the DASS-21 and AAQ-II scores, which coincides with the findings obtained in the FFMQ (de Bruin et al., 2012; Sosa, 2019) and FFMQ-SF-24 (Bohlmeijer et al., 2011; Oñate & Calvete, 2018). These results may be related to either (a) the meaning of the observational experience (de Bruin et al., 2012) in samples of meditators (adaptive ability) and non-meditators (paying attention to internal experience may result in thoughts of criticism and self-criticism), (b) the dimension is not related to emotional awareness (Rudkin et al., 2018), or the Observing facet exhibits limited utility in capturing the mindfulness construct among individuals without prior meditation practice (Aguado et al., 2016).

Limitations and Future Research

Some limitations of this study are worth mentioning. First, the FFMQ-SF-24 performance was evaluated in an adult general population sample, with a small subsample of meditators. Therefore, it is recommended that future studies analyze the psychometric properties of the FFMQ-SF-24 in a larger and more homogeneous sample in terms of representativeness by sex, regions of the country, and meditation practice. Second, no systematic information was obtained on the clinical diagnoses of the participants, which prevented comparison of the clinical relevance of the instrument. Third, all variables were measured through self-reports, and for this type of study, at least one directly measured variable is recommended. Fourth, a convenience sample was recruited, which does not allow for generalizing the results to the whole Colombian population. Thus, the results obtained in this study should be considered cautiously because they could be more a function of the sampling than the actual psychometric properties of the FFMQ-SF-24 in Colombia. In this sense, this sample was composed of a considerably higher percentage of women than men. Further studies with additional Colombian samples are suggested to confirm the results. Lastly, it is necessary to explore the sensitivity of the FFMQ-SF-24 to treatment effects and to analyze whether the instrument scores are sensitive to the effect of psychological interventions aimed at increasing mindfulness.

Based on the present research, the FFMQ-SF-24 can be proposed as an instrument for measuring mindfulness and its five facets in the Colombian population. However, given the psychometric properties found, the Observing facet requires some caution in its interpretations. Overall, the FFMQ-SF-24 is a promising mindfulness instrument for evaluating mindfulness in communal settings.

Declarations

Ethics Approval

This study was part of a master’s thesis in clinical psychology conducted at the Fundación Universitaria Konrad Lorenz. The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board.

Ethical approval was obtained from the Institutional Review Board before data collection. Participants provided informed consent by electronically signing a consent form created using Microsoft Forms, which outlined the study’s purpose, procedures, and potential risks.

Conflict of Interest

The authors declare no competing interests.

Use of Artificial Intelligence Statement

AI was used for editing the manuscript to improve the English language.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Onze productaanbevelingen

BSL Psychologie Totaal

Met BSL Psychologie Totaal blijf je als professional steeds op de hoogte van de nieuwste ontwikkelingen binnen jouw vak. Met het online abonnement heb je toegang tot een groot aantal boeken, protocollen, vaktijdschriften en e-learnings op het gebied van psychologie en psychiatrie. Zo kun je op je gemak en wanneer het jou het beste uitkomt verdiepen in jouw vakgebied.

Meer informatie

BSL Academy Accare GGZ collective

Meer informatie

BSL GOP_opleiding GZ-psycholoog

Meer informatie

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 1.29 MB)

Supplementary file2 (DOCX 4.11 MB)

Adie, T., Steindl, S. R., Kirby, J. N., Kane, R. T., & Mazzucchelli, T. G. (2021). The relationship between self-compassion and depressive symptoms: Avoidance and activation as mediators. Mindfulness, 12(7), 1748–1756. https://doi.org/10.1007/s12671-021-01637-1CrossRef

Aguado, J., Luciano, J. V., Cebolla, A., Serrano-Blanco, A., Soler, J., & García-Campayo, J. (2016). Bifactor analysis and construct validity of the Five Facet Mindfulness Questionnaire (FFMQ) in non-clinical Spanish samples. Frontiers in Psychology, 6, 404. https://doi.org/10.3389/fpsyg.2015.00404CrossRef

American Educational Research Association, the American Psychological Association and the National Council on Measurement in Education (2014). Standards for educational and psychological testing. American Educational Research Association.

American Mindfulness Research Association AMRA (May 11, 2023). Mindfulness journal publications by year, 1980–2022. https://goamra.org/Library

Asami, Y., Nomura, K., Shimada, H., Nakagawa, K., Sugano, M., Koshiba, A., Ohishi, Y., Ohishi, H., & Ohishi, M. (2022). Cognitive behavioural group therapy with mindfulness for kleptomania: An open trial. The Cognitive Behaviour Therapist, 15, e34. https://doi.org/10.1017/S1754470X22000290CrossRef

Asensio-Martínez, Á., Masluk, B., Montero-Marin, J., Olivan-Blázquez, B., Navarro-Gil, M. T., García-Campayo, J., & Magallón-Botaya, R. (2019). Validation of five facets mindfulness questionnaire–short form, in spanish, general health care services patients sample: Prediction of depression through mindfulness scale. PLoS ONE, 14(4), e0214503. https://doi.org/10.1371/journal.pone.0214503

Asuero, A., Rodríguez Blanco, T., Pujol-Ribera, E., Berenguera, A., & Moix Queraltó, J. (2013). Evaluación de la efectividad de un programa de mindfulness en profesionales de atención primaria. Gaceta Sanitaria, 27, 521–528. https://doi.org/10.1016/j.gaceta.2013.04.007CrossRef

Baer, R. A., Smith, G. T., & Allen, K. B. (2004). Assessment of mindfulness by self-report: The Kentucky Inventory of Mindfulness Skills. Assessment, 11(3), 191–206. https://doi.org/10.1177/1073191104268029CrossRefPubMed

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(1), 27–45. https://doi.org/10.1177/1073191105283504CrossRefPubMed

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(3), 230–241. https://doi.org/10.1093/clipsy/bph077CrossRef

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(3), 308–320. https://doi.org/10.1177/1073191111408231CrossRefPubMed

Bond, F. W., Hayes, S. C., Baer, R. A., Carpenter, K. M., Guenole, N., Orcutt, H. K., Waltz, T., & Zettle, R. D. (2011). Preliminary psychometric properties of the Acceptance and Action Questionnaire – II: A revised measure of psychological inflexibility and experiential avoidance. Behavior Therapy, 42, 676–688. https://doi.org/10.1016/j.beth.2011.03.007CrossRefPubMed

Brady, B., Kneebone, I. I., & Bailey, P. E. (2019). Validation of the five facet mindfulness questionnaire among community-dwelling older adults. Mindfulness, 10(3), 529–536. https://doi.org/10.1007/s12671-018-0994-0CrossRef

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(4), 822. https://doi.org/10.1037/0022-3514.84.4.822CrossRefPubMed

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(1), 11–34.

Carvalho, J. P., Gawrysiak, M. J., Hellmuth, J. C., McNulty, J. K., Magidson, J. F., Lejuez, C. W., & Hopko, D. R. (2011). The Reward Probability Index: Design and validation of a scale measuring access to environmental reward. Behavior Therapy, 42(2), 249–262. https://doi.org/10.1016/j.beth.2010.05.004CrossRefPubMed

Cebolla, A., Garcia-Palacios, A., Soler, J., Guillén, V., Baños, R., & Botella, C. (2012). Psychometric properties of the Spanish validation of the Five Facets of Mindfulness Questionnaire (FFMQ). The European Journal of Psychiatry, 26(2), 118–126. https://doi.org/10.4321/S0213-61632012000200005CrossRef

Chadwick, P., Taylor, N. K., & Abba, N. (2005). Mindfulness groups for people with psychosis. Behavioral and Cognitive Psychotherapy, 33, 351–359. https://doi.org/10.1017/S1352465805002158CrossRef

Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 464–504. https://doi.org/10.1080/10705510701301834CrossRef

Choi, S. W., Gibbons, L. E., & Crane, P. K. (2011). Lordif: An R package for detecting differential item functioning using iterative hybrid ordinal logistic regression/item response theory and Monte Carlo simulations. Journal of Statistical Software, 39(8), 1. https://doi.org/10.18637/jss.v039.i08CrossRefPubMedPubMedCentral

Correa, P., Michelini, Y., Bravo, A. J., Mezquita, L., & Pilatti, A. (2023). Validation of the spanish version of the Five Facet Mindfulness Questionnaire in a sample of Argentinian college students. Mindfulness, 14(6), 1479–1492. https://doi.org/10.1007/s12671-023-02152-1CrossRef

Daza, P., Novy, D. M., Stanley, M. A., & Averill, P. (2002). The Depression Anxiety Stress Scale-21: Spanish translation and validation with a Hispanic sample. Journal of Psychopathology and Behavioral Assessment, 24, 195–205. https://doi.org/10.1023/A:1016014818163CrossRef

de Bruin, E. I., Topper, M., Muskens, J. G., Bögels, S. M., & Kamphuis, J. H. (2012). Psychometric properties of the Five Facets Mindfulness Questionnaire (FFMQ) in a meditating and a non-meditating sample. Assessment, 19(2), 187–197. https://doi.org/10.1177/1073191112446654CrossRefPubMed

Dundas, I., Vøllestad, J., Binder, P. E., & Sivertsen, B. (2013). The five factor mindfulness questionnaire in Norway. Scandinavian Journal of Psychology, 54(3), 250–260. https://doi.org/10.1111/sjop.12044CrossRefPubMed

Epskamp, S. (2015). semPlot: Unified visualizations of structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 22(3), 474–483. https://doi.org/10.1080/10705511.2014.937847CrossRef

Feldman, G. C., Hayes, A. M., Kumar, S. M., Greeson, J. M., & Laurenceau, J. P. (2004). Development, factor structure, and initial validation of the Cognitive and Affective Mindfulness Scale. Unpublished Manuscript.

Fernández Curado, D., Gonçalves Gallo, G., Alves Machado, M. P., Vargas de Barros, V., & Noto, A. R. (2022). Psychometric properties of the short version of the Five Facets of Mindfulness Questionnaire in Brazilian Portuguese. Bragança Paulista, 27(3), 489–499. https://doi.org/10.1590/1413-82712028270307CrossRef

Fleiss, J. L. (1981). Statistical methods for rates and proportions. Wiley.

Fong, T. C., Wan, A. H., Wong, V. P., & Ho, R. T. (2021). Psychometric properties of the Chinese version of Five Facet Mindfulness Questionnaire—short form in cancer patients: A Bayesian structural equation modeling approach. Health and Quality of Life Outcomes, 19(1), 1–11. https://doi.org/10.1186/s12955-021-01692-1CrossRef

Frías, D. (2021). Apuntes de consistencia interna de las puntuaciones de un instrumento de medida. Universidad de Valencia. España. AlfaCronbach.pdf (uv.es)

García, D. R. (2019). Propiedades Psicométricas de la Escala BADS Short-Form (BADS-SF) en una Muestra Colombiana [Tesis de Maestría en Psicología Clínica]. Fundación Universitaria Konrad Lorenz.

Garland, E. L. (2016). Restructuring reward processing with Mindfulness-Oriented Recovery Enhancement: Novel therapeutic mechanisms to remediate hedonic dysregulation in addiction, stress, and pain. Annals of the New York Academy of Sciences, 1373(1), 25–37. https://doi.org/10.1111/NYAS.13034CrossRefPubMedPubMedCentral

George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference. 11.0 update (4th ed.). Allyn & Bacon.

Geschwind, N., Peeters, F., Drukker, M., Van Os, J., & Wichers, M. (2011). Mindfulness training increases momentary positive emotions and reward experience in adults vulnerable to depression: A randomized controlled trial. Journal of Consulting and Clinical Psychology, 79(5), 618–628. https://doi.org/10.1037/A0024595CrossRefPubMed

Gómez-Benito, J., Hidalgo, M. D., & Guilera, G. (2010). El sesgo de los instrumentos de medición. Tests Justos. Papeles Del Psicólogo, 31(1), 75–84.

Goss-Sampson, M. A. (2019). Análisis estadístico con JASP: una guía para estudianteshttps://doi.org/10.6084/m9.figshare.9980744

Gracia Gozalo, R. M., Ferrer Tarrés, J. M., Ayora, A., Alonso Herrero, M., Amutio, K. A., & Ferrer Roca, R. (2019). Aplicación de un programa de mindfulness en profesionales de un servicio de medicina intensiva. Efecto sobre el burnout, la empatía y la autocompasión. Medicina Intensiva, 43, 207–216. https://doi.org/10.1016/j.medin.2018.02.005CrossRefPubMed

Gu, J., Strauss, C., Crane, C., Barnhofer, T., Karl, A., Cavanagh, K., & Kuyken, W. (2016). Examining the factor structure of the 39-item and 15-item versions of the Five Facet Mindfulness Questionnaire before and after mindfulness-based cognitive therapy for people with recurrent depression. Psychological Assessment, 28(7), 791–802. https://doi.org/10.1037/pas0000263CrossRefPubMedPubMedCentral

Haas, B. W., & Akamatsu, Y. (2019). Psychometric investigation of the five facets of mindfulness and well-being measures in the kingdom of Bhutan and the USA. Mindfulness, 10, 1339–1351. https://doi.org/10.1007/s12671-018-1089-7CrossRef

Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (1999). Acceptance and Commitment Therapy: An experiential approach to behavior change. Guilford Press.

Heeren, A., Douilliez, C., Peschard, V., Debrauwere, L., & Philippot, P. (2011). Cross-cultural validity of the Five Facets Mindfulness Questionnaire: Adaptation and validation in a French-speaking sample. European Review of Applied Psychology, 61(3), 147–151. https://doi.org/10.1016/j.erap.2011.02.001CrossRef

Hernández, J. (2017). ULLRToolbox for R (Version 1.0). [Software]. https://sites.google.com/site/ullrtoolbox/00-instalacion-windows

Hodge, K. J., & Morgan, G. B. (2017). Stability of INFIT and OUTFIT Compared to Simulated Estimates in Applied Setting. Journal of Applied Measurement, 18(4), 383–392.PubMed

Hou, J., Wong, S. Y. S., Lo, H. H. M., Mak, W. W. S., & Ma, H. S. W. (2014). Validation of a Chinese version of the Five Facet Mindfulness Questionnaire in Hong Kong and development of a short form. Assessment, 21(3), 363–371. https://doi.org/10.1177/1073191113485121CrossRefPubMed

Hu, H., Lyu, R., Dai, X., & Lu, S. (2024). Validating a short-form five facet mindfulness questionnaire among chinese early adolescents. Mindfulness, 15, 2632–2646. https://doi.org/10.1007/s12671-024-02446-yCrossRef

Iani, L., Lauriola, M., & Cafaro, V. (2017). The assessment of mindfulness skills: The “what” and the “how”. Journal of Mental Health, 29(2), 144–151. https://doi.org/10.1080/09638237.2017.1385738

Iqbal, F., Iqbal, F., & Humayun, G. K. (2023). Factor structure of the Five Facets Mindfulness Questionnaire (FFMQ) (15 items) in a collectivist society—Pakistan. Psychology in the Schools, 60(7), 2502–2519. https://doi.org/10.1002/pits.22875CrossRef

Jennings, J. L., & Apsche, J. A. (2014). The evolution of a fundamentally mindfulness-based treatment methodology: From DBT and ACT to MDT and beyond. International Journal of Behavioral Consultation and Therapy, 9(2), 1. https://doi.org/10.1037/h0100990CrossRef

Jorgensen, T. D., Pornprasertmanit, S., & Schoemann, A. M. Rosseel Y. (2019). semTools: Useful tools for structural equation modeling (R package version 0.5–5) [Computer software][Internet].

Kabat-Zinn, J. (1990). Full catastrophe living. Using the wisdom of your body and mind to face stress, pain, and illness. Delta Book Publishing.

Kabat-Zinn, J. (2003). Mindfulness-based interventions in context: Past, present, and future. Clinical Psychology: Science and Practice, 10(2), 144–156. https://doi.org/10.1093/clipsy.bpg016CrossRef

Karabatsos, G. (2000). A critique of Rasch residual fit statistics. Journal of Applied Measurement, 1, 152–176.PubMed

Latzman, R. D., & Masuda, A. (2013). Examining mindfulness and psychological inflexibility within the framework of Big Five personality. Personality and Individual Differences, 55(2), 129–134. https://doi.org/10.1016/j.paid.2013.02.019CrossRef

Lecuona, O., García-Rubio, C., De Rivas, S., Moreno-Jiménez, J. E., & Rodríguez-Carvajal, R. (2022). 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. Mindfulness, 13(8), 2031–2046. https://doi.org/10.1007/s12671-022-01939-yCrossRef

Levin-Aspenson, H. F., Marks, R. M., Dalrymple, K. L., & Zimmerman, M. (2023). Does the Five Facet Mindfulness Questionnaire measure the same constructs before and after ACT-based treatment? Examination of the longitudinal measurement invariance of the 24-item FFMQ-SF. Journal of Contextual Behavioral Science, 29, 131–139. https://doi.org/10.1016/j.jcbs.2023.07.001CrossRef

Linehan, M. M., Heard, H., Clarkin, J., Marziali, E., & Munroe-Blum, H. (1993). Dialectical behavior therapy for borderline personality disorder. Guilford.

Lippke, S., Nigg, C. R., & Maddock, J. E. (2007). The theory of planned behavior within the stages of the transtheoretical model: Latent structural modeling of stage-specific prediction patterns in physical. A Multidisciplinary Journal, 14(4), 649–670. https://doi.org/10.1080/10705510701575586CrossRef

Loret de Mola Gubbins, A. M. (2011). Confiabilidad y validez de constructo del FFMQ en un grupo de meditadores y no meditadores. (Tesis para optar el título de Licenciada en Psicología con mención en Psicología Clínica). Pontifica universidad Católica del Perú.

Lovibond, S., & Lovibond, P. (1995). Manual for the depression anxiety stress scales. Psychology Foundation of Australia.

Mair, P., & Hatzinger, R. (2007). Extended Rasch modeling: The eRm package for the application of IRT models in R. Journal of Statistical Software, 20, 1–20. https://doi.org/10.18637/jss.v020.i09CrossRef

Manos, R. C., Kanter, J. W., & Luo, W. (2011). The Behavioral Activation for Depression Scale-Short Form: Development and Validation. Behavior Therapy, 42(4), 726–739. https://doi.org/10.1016/j.beth.2011.04.004CrossRefPubMed

Neff, K. D. (2003). Self-compassion: An alternative conceptualization of a healthy attitude toward oneself. Self and Identity, 2, 85–102. https://doi.org/10.1080/15298860309032CrossRef

Oñate, L., & Calvete, E. (2018). Adaptation of the Five-Facet Mindfulness Questionnaire-Short Form (FFMQ-SF) to spanish family caregivers of people with intellectual and developmental disabilities. Anales De Psicología, 34(2), 304–312. https://doi.org/10.6018/analesps.34.2.294551CrossRef

Pelham III, W. E., Gonzalez, O., Metcalf, S. A., Whicker, C. L., Scherer, E. A., Witkiewitz, K., Marsch, L. A., & Mackinnon, D. P. (2019). Item response theory analysis of the five facet mindfulness questionnaire and its short forms. Mindfulness, 10(8), 1615–1628. https://doi.org/10.1007/s12671-019-01105-x

Putnick, D. L., & Bornstein, M. H. (2016). Measurement invariance conventions and reporting: The state of the art and future directions for psychological research. Developmental Review, 41, 71–90. https://doi.org/10.1016/j.dr.2016.06.004

Randolph, J. J. (2005). Free-marginal multirater kappa (multirater K [free]): An alternative to fleiss' fixed-marginal multirater kappa. Online submission. https://eric.ed.gov/?id=ED490661

Raphiphatthana, B., & Jose, P. E. (2020). The relationship between dispositional mindfulness and grit moderated by meditation experience and culture. Mindfulness, 11, 587–598. https://doi.org/10.1007/s12671-019-01265-wCrossRef

Rau, H. K., & Williams, P. G. (2016). Dispositional mindfulness: A critical review of construct validation research. Personality and Individual Differences, 93, 32–43. https://doi.org/10.1016/j.paid.2015.09.035CrossRef

Reyes-Buitrago, P. L., Bianchi, J. M., Suárez-Falcón, J. C., & Ruiz, F. J. (2023). Revista Latinoamericana de Psicología. Revista Latinoamericana de Psicología, 55, 1–9. https://doi.org/10.14349/rlp.2023.v55.1CrossRef

Rial, A., Valera, J., Abalo, J., & Lévy, J. (2006). El análisis factorial confirmatorio. In J. Lévy & J. Varela (Eds.), Modelización con Estructuras de Covarianza en Ciencias Sociales (pp. 119–144). Gesbiblo.

Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48, 1–36. https://doi.org/10.18637/jss.v048.i02CrossRef

Rudkin, E., Medvedev, O. N., & Siegert, R. J. (2018). The five-facet mindfulness questionnaire: Why the observing subscale does not predict psychological symptoms. Mindfulness, 9(1), 230–242. https://doi.org/10.1007/s12671-017-0766-2CrossRef

Ruiz, F. J. (2014). The relationship between low levels of mindfulness skills and pathological worry: The mediating role of psychological inflexibility. Anales De Psicología, 30(3), 887–897. https://doi.org/10.6018/analesps.30.3.150651CrossRef

Ruiz, F. J., Langer-Herrera, Á. I., Luciano, C., Cangas, A. J., & Beltrán, I. (2013). Measuring experiential avoidance and psychological inflexibility: The Spanish version of the Acceptance and Action Questionnaire-II. Psicothema, 25, 123–129. https://doi.org/10.7334/psicothema2011.239CrossRefPubMed

Ruiz, F. J., Suárez-Falcón, J. C., Cárdenas-Sierra, S., Durán, Y. A., Guerrero, K., & Riaño-Hernández, D. (2016a). Psychometric properties of the Acceptance and Action Questionnaire – II in Colombia. The Psychological Record, 66, 429–437. https://doi.org/10.1007/s40732-016-0183-2CrossRef

Ruiz, F. J., Suárez-Falcón, J. C., & Riaño-Hernández, D. (2016b). Psychometric properties of the Mindful Attention Awareness Scale in Colombian undergraduates. Suma Psicológica, 23(1), 18–24. https://doi.org/10.1016/j.sumpsi.2016.02.003CrossRef

Ruiz, F. J., García-Martín, M. B., Suárez-Falcón, J. C., & Odriozola-González, P. (2017). The hierarchical factor structure of the Spanish version of Depression Anxiety and Stress Scale - 21. International Journal of Psychology and Psychological Therapy, 17, 97–105.

Ruiz, F. J., Bianchi, J. M., Bastidas-Suárez, D. M., Ramírez, E. S., & Peña-Hernández, V. (2024). Is the Acceptance and Action Questionnaire – II that bad? Journal of Contextual Behavioral Science, 100854. https://doi.org/10.1016/j.jcbs.2024.100854

Salamea, R. M., Fernandez, J. C., & Cedillo, L. F. (2019). Programa de conciencia plena (mindfulness) y compasión para la alimentación consciente en estudiantes universitarios obesos. Revista Espacios, 40(40), 26.

Schmidt, C., & Vinet, E. V. (2015). Atención plena: Validación del five facet mindfulness questionnaire (FFMQ) en estudiantes universitarios chilenos. Terapia Psicológica, 33(2), 93–102. https://doi.org/10.4067/S0718-48082015000200004CrossRef

Segal, Z. V., Williams, J. M. G., & Teasdale, J. D. (2013). Mindfulness-based cognitive therapy for depression (2nd ed.). Guilford Press.

Sosa, M. (2019). Propiedades psicométricas de la Escala Five Factor Mindfulness Questionnaire FFMQ en una muestra colombiana [Tesis de Maestría en Psicología Clínica]. Fundación Universitaria Konrad Lorenz.

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(9), 951–965. https://doi.org/10.1002/jclp.21996CrossRefPubMed

Veehof, M. M., Peter, 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(8), 1045–1054. https://doi.org/10.1007/s10067-011-1690-9CrossRefPubMedPubMedCentral

Ventura-León, J. L., & Caycho-Rodríguez, T. (2017). El coeficiente Omega: Un método alternativo para la estimación de la confiabilidad. Revista Latinoamericana De Ciencias Sociales, Niñez y Juventud, 15(1), 625–627.

Zapata-Orozco, S., Zapata-González, J., Gantiva, C., Suárez-Pico, P., & Barrera-Valencia, M. (2020). Construcción y validación del repositorio de expresiones faciales emocionales colombianas. Suma psicológica, 27(2), 142–149. https://doi.org/10.14349/sumapsi.2020.v27.n2.8

Titel: Psychometric Properties of the Five Facet Mindfulness Questionnaire Short Version (FFMQ-SF) in the Colombian Population
Auteurs: Diego F. Castañeda
Javier M. Bianchi
Javier A. Villalba-Garzón
Francisco J. Ruiz
Publicatiedatum: 19-02-2025
Uitgeverij: Springer US
Gepubliceerd in: Mindfulness
Print ISSN: 1868-8527
Elektronisch ISSN: 1868-8535
DOI: https://doi.org/10.1007/s12671-025-02533-8

Bohn Stafleu van Loghum

Welkom bij THIM Hogeschool voor Fysiotherapie & Bohn Stafleu van Loghum

Registreer

Login

Psychometric Properties of the Five Facet Mindfulness Questionnaire Short Version (FFMQ-SF) in the Colombian Population

Abstract

Objectives

Method

Results

Conclusions

Preregistration

Supplementary Information

Publisher's Note

Method

Participants

Measures

Procedure

Data Analyses

Results

Mindfulness Practice

Validity Evidence Based on Internal Structure

Confirmatory Factor Analyses

Measurement Invariance

DIF Detection

Relations of the FFMQ-SF-24 Scores with Meditation Practice

Reliability

Relations with Mindfulness, Present Moment Awareness, Emotional Symptoms, Psychological Inflexibility, Environmental Reward, and Activation

Psychometric Analyses Based on the Rasch Model

Discussion

Limitations and Future Research

Declarations

Ethics Approval

Conflict of Interest

Use of Artificial Intelligence Statement

Publisher's Note

Onze productaanbevelingen

BSL Psychologie Totaal

BSL Academy Accare GGZ collective

BSL GOP_opleiding GZ-psycholoog

Supplementary Information

Bohn Stafleu van Loghum

Welkom bij THIM Hogeschool voor Fysiotherapie & Bohn Stafleu van Loghum

Registreer

Login

Deel dit onderdeel of sectie (kopieer de link)

Abstract

Objectives

Method

Results

Conclusions

Preregistration

Supplementary Information

Publisher's Note

Method

Participants

Measures

Procedure

Data Analyses

Results

Mindfulness Practice

Validity Evidence Based on Internal Structure

Confirmatory Factor Analyses

Measurement Invariance

DIF Detection

Relations of the FFMQ-SF-24 Scores with Meditation Practice

Reliability

Relations with Mindfulness, Present Moment Awareness, Emotional Symptoms, Psychological Inflexibility, Environmental Reward, and Activation

Psychometric Analyses Based on the Rasch Model

Discussion

Limitations and Future Research

Declarations

Ethics Approval

Informed Consent

Conflict of Interest

Use of Artificial Intelligence Statement

Publisher's Note

Deel dit onderdeel of sectie (kopieer de link)

Onze productaanbevelingen

BSL Psychologie Totaal

BSL Academy Accare GGZ collective

BSL GOP_opleiding GZ-psycholoog

Supplementary Information