Statistical analysis
SE, disability, pain
The statistical analysis was performed using the statistical program SPSS v22, and the intention-to-treat analysis was performed with an alpha of 0.05. Quantitative variables were described using the mean, standard deviation (SD), standard error (SE), median, and interquartile range.Sociodemographic baseline characteristics were compared using the chi-square tests of independence for categorical data and the Student’s t-test for continuous data.A two-way mixed ANOVA was used to determine whether there was an interaction effect between the two independent variables, treatment (control and experimental) and time (pre- and post-test). The mean difference (MD) with 95% confidence interval (CI) was calculated to analyze continuous outcomes. We corrected p-value comparisons using Bonferroni. We used the partial Eta squared (η2) to measure the effect size. We considered a partial η2 > 0.009 as a small effect size, partial η2 > 0.058 as a medium effect size, and partial η2 > 0.137 as a large effect size [We used the Pearson bivariate correlation analysis to investigate the relationship between the TrA activation measured with the PBU and pain and disability.