Statistical analysis

Data are expressed as mean and standard deviation (SD). Normality was tested using the Shapiro-Wilk test. To compare subjects’ characteristics between groups, as well as the mean, highest, and lowest affective response, affective response at the highest RPE, and the mean HR during the HIIE bout, the independent-samples t test was used. Cohen’s d was used to calculate the effect size of these analyses. A two-factor, group (active and insufficiently active) x time (work bouts 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10), mixed-model repeated measures ANOVA analysis was conducted to compare HR, affective responses, and RPE during the HIIE bout. Whenever the sphericity assumption was violated, the degrees of freedom were adjusted and reported using the Greenhouse-Geisser épsilon correction. Partial eta squared (η²_p) was used to determine the effect size of these analyses. If necessary, Tukey’s pos hoc test was used to determine where the significant differences occurred. The chi-squared test was used to verify a possible difference in the distribution of subjects that presented the mean FS score as positive or negative in each group, which were categorized as “unpleasant HIIE” or “pleasant HIIE”; moreover, the frequency of the positive and negative affective responses in the beginning (work bouts 1 to 3), in the middle (work bouts 4 to 7), and in the end (work bouts 8 to 10) of the HIIE bout between the groups was compared using chi-squared test. Pearson product-moment correlation coefficient was used to examine a possible relationship between the affective and RPE responses in both groups. For the analyses, the significance level was set at 5% (p < 0.05). All data were analyzed using SPSS^® 20.0 for Windows (SPSS, Inc., Chicago, IL). A post hoc statistical power analysis was conducted using G*Power version 3.1.9.2.