Statistical Analysis
The Statistical Package for Social Science program (v23; SPSS, Chicago, IL) was used for statistical analysis. Data were expressed as mean ± standard deviation or percentages. The Kolmogorov–Smirnov test was used to analyze the normality of the variables, all parameters were non-normally distributed. The Wilcoxon signed rank test used for the comparison of menstrual symptoms, menstrual pain severity, and fatigue severity of individuals before and after COVID-19. Inter correlations between the changes ((post COVID-19) - (pre-COVID)) in MSQ, MSQ subgroup scores, fatigue and menstrual pain and coronavirus anxiety were computed using Spearman correlation. Independent variables based on univariate analysis were analyzed by multiple linear regression analysis to determine the multivariate influence of the predictors of the Δ MSQ scores. The adjusted R2 was used to explain the total variance. Subjects’ the Δ MSQ scores and subgroup scores compared based on demographic features and prolonged COVID-19 symptoms using Mann Whitney-U test or Kruskal-Wallis test. Statistical significance was set at p < 0.05 for all analysis.