Spss vs 28.0 program for windows

Descriptive analysis was performed using measures of central tendency, dispersion, and position (median and interquartile range (P75–P25)) for quantitative variables and frequency distribution for qualitative variables. To assess differences between study groups (absence vs. presence of hydrotherapy), the chi-squared test (or Fisher’s exact test if expected frequencies were less than 5) was used for qualitative variables, while Student’s t-test (or Mann–Whitney U test if the distribution was non-normal) was used for quantitative variables. Multivariate logistic regressions were performed between the following variables: postpartum haemorrhage, postpartum perineal status (comparing intact vs. first-degree tear, second-degree tear, third-degree tear, and episiotomy), foetal complications, neonatal admission, abnormal RCTGF signs, maternal arterial hypotension, and maternal fever. Each model was adjusted for age and number of pregnancies (1, 2 and 3 or more).
For all analyses, the level of statistical significance was set at p < 0.05. The analysis was performed using SPSS vs. 28.0 program for Windows (IBM Corporation, Armonk, NY, USA) statistical software.

The SPSS vs. 28.0 program for Windows (IBM Corporation, Armonk, NY, USA) was used for statistical analysis. The Student’s t test or the Mann–Whitney U test was used for the study of quantitative variables and the Chi-square test (or Fisher’s test if necessary) for the comparison of proportions. The results are expressed as mean, standard deviation, number, and/or percentage.

Descriptive analyses were conducted using measures of the central tendency and dispersion (mean and standard deviation) for quantitative variables, and the frequency distribution for qualitative variables. To evaluate differences between the study groups (no hydrotherapy use vs. use of hydrotherapy), the chi-square test (or Fisher’s exact test in case of expected frequencies less than 5) was used for the categorical variables, and the Student’s t-test was used for the quantitative variables. Using pain as the outcome variable, a multivariate linear regression model was employed, including unbalanced independent variables from the previous bivariate analysis, selecting variables with a criterion of p < 0.05, and describing the beta coefficient (β) with respective 95% confidence intervals (CI95%). This involved checking for normality, homoscedasticity, and multicollinearity.
For all analyses, the level of statistical significance was set at p < 0.05. These analyses were performed using SPSS vs. 28.0 program for Windows (IBM Corporation, Armonk, NY, USA) statistical software.