<p>Estimado Consejo Editorial</p>
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<p>Esta carta acompaña nuestro manuscrito “<em>Intolerance of uncertainty over COVID-19 pandemic and its effect on anxiety and depressive symptoms</em>”, considerado para ser publicado en la revista. Hemos leído cuidadosamente los comentarios hechos por el revisor y realizado las modificaciones pertinentes.</p>
<p>Los cambios en el manuscrito fueron indicados con resaltador amarillo. También acompañamos esta carta con el listado de los comentarios del revisor y la respuesta punto por punto a cada uno de ellos.</p>
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<p>Muchas gracias por su consideración. Sinceramente,</p>
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<p><strong>Macarena del Valle y colaboradores.</strong></p>
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<p><strong><em># Reviewer 1</em></strong></p>
<p><strong><em>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.</em></strong></p>
<p><em>&nbsp;</em><strong><em><u>Comment 1:</u></em></strong><strong><em> Some statistical tests should include, in addition to the effect size, power, which would also help interpret the results with a little more precision. </em></strong></p>
<p>Reply: power (1-β) was added for t-test. Effect size (f<sup>2</sup>) and power (1-β) were added for regressions.</p>
<p><em>&nbsp;</em><strong><em><u>Comment 2: </u>In addition, the option of using non-parametric statistics instead of standardizing variables should be considered. </em></strong><strong><em>Understanding that in regression models normality is almost a must, it is homocedasticity that really matters. </em></strong></p>
<p><em>&nbsp;</em>Reply: As both anxiety and intolerance of uncertainty showed normal distributions, the authors decided that normalizing depression data was the best choice. This way, all the analysis were performed with the same statistic, instead of using parametric statistics for some variables and non-parametric statistics for another one. In addition, scartterplots of both models were explored, showing homoscedasticity. This information was included in the “data analysis” section, along with the residual analysis information.</p>
<p><strong><em><u>Comment 3: </u>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. </em></strong></p>
<p><strong><em>&nbsp;</em></strong>Reply: After the reviewer's suggestion, we incorporated the Levene statistics in the ANOVAs we carried out. The results indicated non-compliance with the assumption of homocedasticity in all cases. However, the number of participants (n = 3805) may have an effect over the significance levels. We understand that the ANOVA analysis is sufficiently robust, even in the face of non-compliance with some of its assumptions (e.g., Blanca, Alarcón, Arnau, Bono, &amp; Bendayan, 2017). For the reader's clarity, we specify the non-compliance with homogeneity in the “data analysis” section.</p>
<p>Given that the authors' objective in applying factorial ANOVA was to explore the existence of interactions, and despite the absence of such interactions, we decided to show the results in the paper so we could illustrate the variables’ behavior. If the reviewer (or the editor) so wishes, we can remove the ANOVAs from the paper, as well as the corresponding graphs.</p>
<p><strong><em><u>Comment 4: </u>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)</em></strong></p>
<p><strong><em>&nbsp;</em></strong>Reply: Regarding to this comment, we would like to highlight a few points. First, the comparison with other studies that have used the IU scale is not simple, because the scale was adapted relatively recently (2015), so there are not many studies that have used it yet. Second, the IU scale version used in this study was modified (to assess the pandemic situation), so comparing it with other versions would be inaccurate. Regarding STAI (anxiety), there are no Argentinean adaptation of the scale and no paper has explore its psychometric properties in our country. Although there are some previous studies in Argentina that have used the STAI, they focus on specific populations (e.g., clinical patients, university students), and also generally work with a much more limited number of participants (200, 300). Similarly, the Argentinian adaptation of the BDI-II in general population was carried out on a sample of 472 people, all of whom resided in the city of Buenos Aires (our sample included a larger number of participants, who also came from different Argentine cities). Unfortunately, we also do not have a pre-pandemic measure that allows us to make accurate comparisons. Despite these limitations, we incorporated into the “discussion” section some comments with comparisons to previous studies that have explored these variables, and some new studies that have explored this problem. We believe that the modifications introduced in this section respond to the reviewer's suggestions.</p>
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