Statistical methods

The quantitative variables were characterised by the arithmetic mean of standard deviation, median, and max/min (range). The qualitative variables were presented with the use of count and percentage. In order to check whether a quantitative variable derived from a population with a normal distribution, the W Shapiro-Wilk test was used. To prove the hypotheses on homogeneity of variances, the Leven (Brown-Forsythe) test was used. Statistical significance of differences between the two groups was tested with Student’s t-test or U Mann-Whitney test. The significance of differences between more than two groups was assessed with the F test. In the case of statistically significant differences between two groups, post hoc tests were used (Tukey test for F or Dunn for Friedman). c² tests for independence were used for qualitative variables. In order to determine dependence, strength, and direction between variables, correlation analysis was used by determining the Pearson or Spearman correlation coefficients. In all the calculations a statistical significance level of a = 0.05 was used. Statistical analyses were performed using TIBCO (Software Inc., 2017), Statistica v. 13 (Palo Alto, CA, USA, 2017, http://statistica.io), and Excel.