The article is certainly interesting. The subject matter is relevant, the sources are updated, and the results provide information for a new area of study that includes everything related to COVID-19.
 Some statistical tests should include, in addition to the effect size, power, which would also help interpret the results with a little more precision. In addition, the option of using non-parametric statistics instead of standardizing variables should be considered. Understanding that in regression models normality is almost a must, it is homocedasticity that really matters. The ANOVA tests presented do not mention the results of the analysis of variance, which makes the reader assume that the assumption of homogeneous variances is fulfilled. As these are also widely used instruments, the results obtained could be discussed in contrast to other studies that use the same instruments to weigh how large the effect of quarantine is, and hypothesize it or seek to delineate it as a variable in itself (understanding that this is a novel and exploratory study)
