Data encoding and data processing were carried out using the SPSS 25.0 statistical package (SPSS Inc., Chicago, IL, USA). The normality of the variables has been analyzed with the Kolmogorov–Smirnov statistic. After a descriptive analysis (means and standard deviations), a comparison test was performed by the analysis of covariance (ANCOVA). Age and BMI were used as covariables because of their influence in the HRV parameters and the inter-individual variability [42 (link)]. TTM, WAI, and PSS groups were treated as factors, and RMSSD, %Recovery, and %Stress as dependent variables. A Bonferroni post-hoc test was used for pairwise comparisons. In addition, the confidence interval and effect size (ES; Cohen’s d) have been included. The ES was evaluated as follows: 0–0.2 = trivial; 0.2−0.5 = small; 0.5−0.8 = moderate; and >0.8 high. Finally, several regression estimations were performed to analyze the influence of TTM, WAI, and PSS classifications on the different physiological stress variables. All models were also controlled by sex, age, and BMI. The regression did not present normality or heteroscedasticity problems. Moreover, the Variance Inflation Factor (VIF) did not report any multicollinearity problems. The statistical significance criterion was established at p < 0.05.
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