Ggplot2

The studied sample was divided into 2 groups to address anxiety and depression, mild and significative symptoms (instead of using the classic grades of none, mild, moderate, moderate-severe, and severe), using a score of 10 as cut point. Continuous variables were represented by mean ± standard deviation and median [interquartile range], and the categorical variables were presented as percentages. To identify the variable distribution type, they were analyzed using the Kolmogorov-Smirnov test. The differences between the non-parametric quantitative variables were evaluated with the Mann-Whitney U statistical test and the qualitative variables were evaluated using with the χ² test or Fisher's exact test. Spearman's correlation was used to evaluate the correlation between variables and a significative staging of depression and anxiety. A binary logistic regression was done to identify the association between the variables and the significative staging of depression and anxiety using the variables that previously had a correlation with a P-value < .01. Statistical analysis was conducted in IBM-Statistical Package for Social Sciences version 23 (IBM Corp., USA)²⁵ , and the figure was produced using R version 4.0.2 (R Core Team, Austria)²⁶ with the package ggplot2 version 3.3.2 (Wickham, USA).²⁷

The studied sample was divided into 2 groups to address anxiety and depression, mild and significative symptoms (instead of using the classic grades of none, mild, moderate, moderate-severe, and severe), using a score of 10 as cut point. Continuous variables were represented by mean ± standard deviation and median [interquartile range], and the categorical variables were presented as percentages. To identify the variable distribution type, they were analyzed using the Kolmogorov-Smirnov test. The differences between the non-parametric quantitative variables were evaluated with the Mann-Whitney U statistical test and the qualitative variables were evaluated using with the χ² test or Fisher's exact test. Spearman's correlation was used to evaluate the correlation between variables and a significative staging of depression and anxiety. A binary logistic regression was done to identify the association between the variables and the significative staging of depression and anxiety using the variables that previously had a correlation with a P-value < .01. Statistical analysis was conducted in IBM-Statistical Package for Social Sciences version 23 (IBM Corp., USA)²⁵ , and the figure was produced using R version 4.0.2 (R Core Team, Austria)²⁶ with the package ggplot2 version 3.3.2 (Wickham, USA).²⁷