2.4. Statistical analysis
The study data were analysed statistically using SPSS v. 25.0 software (IBM SPSS Statistics, IBM Corporation, Armonk, NY, USA). Continuous variables were stated as mean ± standard deviation (SD) values, and categorical variables as number (n) and percentage (%). Conformity of the data to normal distribution was assessed with the Shapiro-Wilk test. In the examinations of independent groups, one-way variance analysis (posthoc: Tukey test) and the Significance of the difference between two means test were applied to variables meeting parametric test assumptions. When variables did not meet the parametric test assumptions, Kruskal-Wallis variance analysis (posthoc: Bonferroni corrected Mann-Whitney U test) and the Mann-Whitney U test were applied. In the comparisons of differences between measurements, the paired samples t-test was applied to parametric data and the Wilcoxon paired samples t-test when parametric assumptions were not met. The chi-square test was applied to examine differences between categorical variables. A value of p < 0.05 was accepted as statistically significant. Bonferroni correction was used to avoid type 1 error, and the level of significance was defined by dividing the p-value (0.05) into the number of pairwise comparisons. Spearman correlation analysis was used to evaluate the relationship between continuous variables.