Stata 14.1 se software

Categorical variables were presented as absolute numbers and percentages, while quantitative variables were presented as mean values (standard deviation). Inter-observer concordance was evaluated with Fleiss’ Kappa. Correlation between groups for the categorical variables was obtained using the chi-square test or the exact Fisher test if at least one cell had an expected value <5. For quantitative variables, the Shapiro-Wilk normality test was used and the test between groups was performed using variance analysis and t-test if the variables were normally distributed, otherwise we used the respective non-parametric tests of Kruskal–Wallis and Mann–Whitney. In the case of multiple comparisons, the Bonferroni correction was used.
All tests were performed at two-tail, with a significance level (α) at 5%. All the analyses were made using the STATA 14.1 SE software (STATACorp, College Station, TX, USA).

The Shapiro–Wilk test was used to test for normality of the distribution of age (continuous variable). In the presence of symmetry of the distributions, the variable is represented with the mean and standard deviation, and comparisons were assessed using Student’s t-tests. In the case of a nonnormal distribution, the variables are represented with the median value and interquartile range (IQR), and comparisons were assessed using the Wilcoxon–Mann–Whitney test for two independent samples. Categorical data (gender, age, education level, marital status, number of children, distance from family, and type of employment in the hospital) are expressed as total numbers and percentages. Statistical comparisons of categorical variables were assessed using Pearson’s χ² test or Fisher’s exact test, depending on the minimal expected count in each crosstab. The relationships between PPS, PHQ, GAD scale, socio-demographic characteristics, and type of employment in the hospital (health, administrative, or technical) were assessed by the χ² test. A multivariate logistic regression analysis was performed to estimate the Odds Ratios (ORs) for the total sample and stratified by gender. All analyses were performed using the Stata 14.1 SE software (Stata Corporation, College Station, TX, USA). A two-sided p-value < 0.05 was defined as statistically significant.