*2.5. Data Analysis*

After fulfilment of the requirements of normality and homoscedasticity was verified, we examined the distribution of the data for a univariate normality analysis. The results showed asymmetry and kurtosis values lower than 1.2. Next, we calculated the reliability coefficients (Cronbach's alpha, composite reliability, average variance extracted and McDonald's omega coefficient) to obtain reliability evidence. Then, to determine the impact of the programme, descriptive analyses (mean and SD) and analyses of variance (ANOVA) were performed with the scores collected in the pre-test stage. Subsequently, descriptive analyses and analyses of covariance (ANCOVA) were used with post-test scores to determine the impact of the programme on each of the variables. Bonferroni correction was applied for multiple comparisons. For all analyses, a *p*-value <0.05 was considered to indicate statistical significance. After application of Bonferroni correction, a *p*-value <0.012 was considered significant.

The effect size (μ2) of the differences was calculated using partial eta-squared [72]. The effect size was analysed based on four ranges: 0–0.009, negligible; 0.010–0.089, low-effect size; 0.090–0.249, medium-effect size; and >0.250, big-effect size [72]. The data were analysed with SPSS version 24.0 (IBM Corp., Armonk, NY, USA).
