Spss for windows version v 26

Continuous variables were expressed as mean values ± standard deviation (SD). The Kolmogorov–Smirnov test was applied to determine data normality. Differences between student groups were analyzed with independent t-tests. A comparison between pre-test and post-test simulation scores was completed using Student’s t-test paired and a Wilcoxon signed rank test for normal and non-normal distribution variables, respectively. Bivariate correlations were used to assess associations between physiological, pupillary metrics, and workload variables and CPR quality parameters. Testing was conducted on several multiple linear regression models in which differences in pupil variations were considered as dependent variables and the rest of the variables (physiological and workload dimensions) as predictors. The software package SPSS for Windows version v.26 (IBM SPSS, Inc., Chicago, IL, USA) was used for data analysis. A p-value of <0.05 was set as representing statistical significance for all analyses.

Continuous variables were expressed as mean values ± standard deviation (SD). The Kolmogorov–Smirnov test was applied to determine data normality. Differences between student groups were analyzed with independent t-tests. A comparison between pre-test and post-test simulation scores was completed using Student’s t-test paired and a Wilcoxon-signed rank test for normal and non-normal distribution variables, respectively. Bivariate correlations were used to assess associations between physiological, psychological, socio-emotional variables and CPR quality parameters. Testing was conducted on several multiple linear-regression models in which CPR effectiveness, workload dimensions or self-efficacy scores were considered as dependent variables with the rest of the variables as predictors. The software package SPSS for Windows version v.26 (IBM SPSS, Inc., Chicago, IL, USA) was used for data analysis. A p-value of < 0.05 was set as Statistical for all analyses.

Continuous variables were expressed as mean values ± standard deviation (SD). The Kolmogorov–Smirnov test was applied to determine data normality. Differences between zone regions were analyzed using One-way ANOVA and Kruskal–Wallis tests for normal and non-normal distribution variables, respectively. The influence of pH on the MICs values was assessed with the Kruskal–Wallis test. The software package SPSS for Windows version v.26, (IBM SPSS, Inc., Chicago, IL, USA) was used for data analysis. A p-value of <0.05 was set as representing statistical significance for all analyses.