Statistical software package of social science

For each variable descriptive statistics (percentages, means, and standard deviations (SD), medians, and interquartile ranges) were calculated. Mann–Whitney-U tests and Chi-square tests were utilized to calculate differences between two groups (patients with and without current or lifetime mental disorder).
Statistical significance was set at p < .05. All statistical analyses were performed using IBM® Statistical Software Package of Social Science (SPSS®, Chicago, IL, USA) version 26.

Statistical analysis was performed using IBM® Statistical Software Package of Social Science (SPSS®, Chicago, IL, USA) version 26. For all analyzes, significance levels were set at p < 0.05 (two-tailed). Descriptive statistics were calculated and depicted as percentage, mean and standard deviation or median and range. Data distribution was evaluated using Shapiro–Wilk and Kolmogorov–Smirnov tests. As not all data were distributed normally and considering the small number of participants, we chose non-parametric statistics. A Mann–Whitney U test for independent samples was used to determine differences between groups of dichotomous variables. All data were checked for outliers and, if present, analyses were repeated without them. Correlation was studied by means of Spearman rank correlation and, if suitable, linear regression was used to model the relationship between two metric variables. To evaluate outcome measures longitudinally, a two-way analysis of variance by ranks (Friedman’s test) for dependent samples was applied.
This study report was structured following the reporting guidelines to strengthening the Reporting of Observational Studies in Epidemiology (STROBE) [43 (link)].

Statistical analysis was conducted using IBM^® Statistical Software Package of Social Science (SPSS^®, Chicago, IL, USA) version 26. Variables were summarized and provided in percent (%), as mean and standard deviation (SD) or median and range. Comparisons between groups were performed with the Mann–Whitney U test. Distributions of categorical variables were compared using the two-sided Fisher’s exact test. Statistical significance was two-tailed and set at p ≤ 0.05.

Questionnaire scores were calculated for the entire sample and separately for patients with and without cognitive impairment. For each variable descriptive statistics (percentage or mean and standard deviation) were calculated.
We used Shapiro-Wilk test and Kolmogorov-Smirnov test to evaluate data distribution. As our data were not normally distributed, Mann-Whitney U tests were used for comparison of continuous data between the sample with cognitive impairment and the sample without cognitive impairment. Chi-square tests were used for categorical data.
Binary logistic regression analysis with the DemTect (dichotomous) as the dependent variable and variables that were significant in the univariate tests as the independent variable were conducted. All patients with complete data sets (n = 552) were included in this analysis.
For all analyses, P < 0.05 was considered statistically significant. All statistical analyses were performed using IBM^® Statistical Software Package of Social Science (SPSS^®, Chicago, IL, USA) version 25.

We performed the statistical analysis using IBM^® Statistical Software Package of Social Science (SPSS^®, Chicago, IL, USA) version 28. Normality of data was determined using Shapiro–Wilk and Kolmogorov–Smirnov test. Considering the small number of included participants we used non-parametric statistics. The differences between baseline and examined timepoints (month 10, 22 and 30 of nusinersen treatment) were examined using Wilcoxon rank sum test and Fisher’s exact test. Correlations were determined with Spearman’s rank (correlation) coefficient. In the subgroup analysis, we used Mann–Whitney U test for independent samples. We included only the patients with SMA type 2 and 3, due to the small number of patients with SMA type 1 and type 4. Level of statistical significance was set at 0.05 and 0.01.