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.