R project software version 4

Descriptive variables are presented using means (and standard deviations) for the continuous variables and frequencies (and percentages) for the categorical variables. Parametric and non-parametric statistics (t-tests, McNemar’s test, and Wilcoxon signed-rank test) were used for within- and between-subject paired and independent comparisons. IBM SPSS Statistical Analysis System Version 25 (2019) and R Project software version 4.0.3 (2020) were used to conduct data analysis.

Initially, the data distribution was assessed by implementing the Shapiro–Wilk normality test. Data found to be normally distributed were expressed as the mean alongside the 95% confidence interval (95% CI), while non-normally distributed data were represented as the median coupled with the interquartile range (IQR). To compare more than two groups of non-parametric data, we applied the Kruskal–Wallis test, followed by pairwise comparisons using the Wilcoxon rank-sum test with continuity correction for further exploration of specific group differences. For normally distributed data, we conducted an analysis of variance (ANOVA) for comparison across multiple groups, and if they were deemed significant, we followed them up with t-tests for pairwise comparisons. All statistical analyses were performed utilizing R-project software, version 4.0.3 (R-project, http://www.r-project.org; accessed on 12 March 2023), with a significance level set at p < 0.05 for all tests.