Spss statistical software version 23 for mac

The SPSS statistical software version 23 for MAC (IBM SPSS, Chicago, IL, USA) was used to process the data. Firstly, the Kolmogorov–Smirnov test was employed to check normality in the continuous variables’ data distribution; as this assumption was not met, nonparametric statistical tests were chosen. Spearman’s Rho test was used to analyse the relationship between the MBSRQ and IFIS dimensions. Thus, to interpret correlation coefficients, thresholds proposed by Mondragón-Barrera [57 (link)] were followed: from 0.01 to 0.10 (low correlation), from 0.11 to 0.50 (medium correlation), from 0.51 to 0.75 (strong correlation), from 0.76 to 0.90 (very high correlation) and from 0.91 to 1.00 (perfect correlation). Cronbach’s alpha was used to analyse the reliability of each instrument; to interpret the values, Nunally and Bernstein criteria were chosen [58 ]: <0.70 (low), 0.71 to 0.90 (satisfactory) and >0.91 (excellent).

SPSS statistical software version 23 for MAC (IBM SPSS, Chicago, IL, USA) was used to process the collected data. First, the Kolmogorov-Smirnov test was used to explore the assumption of normality in the distribution of continuous variable data. It was found that this assumption was not met, so nonparametric statistical tests were used. Spearman’s Rho test was used to analyze the relationship between each of the ECIPQ dimensions and the E-AEM scores. To interpret the correlation coefficients, the thresholds proposed by Mondragón Barrera (2014) , were followed: rom 0.01 to 0.10 (low correlation), from 0.11 to 0.50 (medium correlation), from 0.51 to 0.75 (considerable correlation), from 0.76 to 0.90 (very high correlation) and from 0.91 to 1.00 (perfect correlation). Cronbach’s alpha and McDonalds omega were used to analyze the reliability of each instrument. To interpret the values of the reliability test, we took as a reference those set out by Nunnally and Bernstein (1994) : <0.70 (low), 0.71–0.90 (satisfactory) and >0.91 (excellent). To ensure the integrity and quality of the data, to give robustness to the accuracy of trends and patterns within our study sample, an outlier study was conducted that involved detailed inspection of extreme values for all items in individual responses. Those responses whose values in all items of the scale (32) were extreme were eliminated.

First, the Kolmogorov–Smirnov test was used to check whether the data of the continuous variables followed a normal distribution. This was not the case, so we proceeded to use nonparametric statistical tests. The Mann–Whitney U-test was used to analyze possible differences in the scores of the dimensions of the EBIPQ questionnaire and the AF-5 scale as a function of sex, school location, and educational stage. Spearman’s Rho test was used to explore the correlations between the scores of each of the dimensions of the questionnaires. The thresholds proposed by Mondragón-Barrera [30 (link)] were taken into account to interpret the following correlation coefficients: from 0.01 to 0.10 (low correlation), from 0.11 to 0.50 (medium correlation), from 0.51 to 0.75 (considerable correlation), from 0.76 to 0.90 (very high correlation), and from 0.91 to 1.00 (perfect correlation). In addition, in order to analyze the reliability of each of the instruments, Cronbach’s alpha, McDonald’s omega, and composite reliability were used. The values cited by Nunnally Berstein [31 ] were used as a reference to interpret the values resulting from the reliability test: <0.70 (low), 0.71 to 0.90 (satisfactory), and >0.91 (excellent). The SPSS statistical software version 23 for MAC (IBM SPSS, Chicago, IL, USA) was used to process the data collected.