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The validation of Five Facets Mindfulness Questionnaire (FFMQ) - short version was performed in a general population of a city in a region of Galicia (Spain), the sample was composed of randomly selected Spanish Health Care patients (N = 845). The results on the goodness of fit of the non-hierarchical, five-dimensional factorial model met the criteria for good and acceptable model adjustment (after eliminating item 18 and despite the correlations detected among the errors included in the model), explaining a 55.5%.of the variance. As the second objective has been analysed the association between the scores obtained in the different facets of the FFMQ-SF and the risk of suffering an episode of depression. (The Odd Ratio, the Hosmer-Lemeshow test and the ROC curve were calculated.) Participants who were currently suffering from an episode of depression were more likely to have low scores in "describing" facet of Mindfulness (adjusted OR = 1.58, 95% CI = 1.04-2.40, linear trend: χ2 = 3.74, df = 1, p = 0.053) as well as low scores on "acting with awareness" (adjusted OR = 2.19, 95% CI = 1.461-3.30, linear trend: χ2 = 9.52, df = 1; = 0.002) and "non judging" (adjusted OR = 2.05, 95% CI = 1.36-3.09, linear trend: χ2 = 143.21, df = 1; p <0.001). Participants with a previous episode of depression were more likely to have low scores on the subscale "acting with awareness" (adjusted OR = 2.37, 95% CI = 1.43-3.93, linear trend: χ2 = 9.62, df = 1, p = 0.002) and "non-reactivity" (adjusted OR = 2.14, 95% CI = 1.28-3.56, linear trend: χ2 = 8.30 ; df = 1; p = 0.004. Questionnaire FFMQ-SF is an adequate questionnaire for the evaluation of mindfulness in non-clinical multi- occupational population.

To validate the FFMQ-SF questionnaire in the general, non-clinical, multi- occupational population, the 5-dimensional model described previously was proposed [46]. We calculated means (standard deviations), medians (interquartile intervals) and frequencies (percentages) for sociodemographic data. The asymmetry, kurtosis and Mardia coefficients [58] have been analyzed to evaluate the distribution of the items. We use polymorphic matrices to estimate a more real correlation between the theoretical continuous latent variables of the ordinal items observed, and we estimate the characteristics of the matrices by the determinant of the correlation matrix, the KMO index and the Bartlett sphericity test [59]. The determinant of the correlation matrix shows the extent to which the variables are related and is zero when they are linearly dependent. The KMO index of sampling adequacy predicts whether the data is likely to have a good factor (KMO must be ≥0.70 to continue factor analysis). We use the goodness-of-fit index (GFI) and the adjusted goodness-of-fit index (AGFI), which refer to the explained variance of the model, and values> 0.90 are acceptable [54]; also the standardized mean square residual (RMSR), which is the standardized difference between the observed and predicted covariance, and the square root of the mean squared error (RMSEA), which indicate good adjustment values ​​when they score <0.08 [54]; the standardized adjustment index (NFI) that measures the proportional reduction in the adjustment function when going from null to the proposed model, and the comparative adjustment index (CFI), in both is considered a good fit of the model when they are> 0.90 [60]. To analyze the relationship between the scores obtained in the different facets of the FFMQ-SF and the suffering or not, a current or past episode of depression, the Odd Ratio, the Hosmer-Lemeshow test and the ROC curve were calculated. The data from the questionnaires were analyzed statistically with the statistical package SPSS 20 and AMOS v20. The cases that presented data misings were eliminated.

Response Rates: the sample was composed of randomly selected Spanish Health Care patients (N = 845)

Presence of Common Scales:
Five Facets of Mindfulness Questionnaire short form (FFMQ-SF)

the Goldberg Anxiety and Depression Scale