Reviewer ’s report  
 
Title: Mediating Effects of Depression on Anxiety and Leisure Cons traints in Patients with 
Breast Cancer  
 
Version: 0 Date: 03 Jul 2019  
 
Reviewer: Stewart J Anderson  
 
Reviewer's report:  
 
&lt;B&gt;Overview &lt;/B&gt; 
 
Retrospective cross -sectional data from 106 breast cancer patients obtained as a convenience 
sample were analyzed by the authors via PCA and path analysis to assess the relati onship among 
depression and anxiety between each other and as mediators of leisure time.   The leisure time is 
important because as the authors indicate, more leisure time and exercise may indicate for a 
better prognosis in breast cancer patients.  
 
Even th ough the study population comes from a non -randomized, convenience sample, the 
authors provide an intriguing analysis.  The manuscript is well written and the use of Principle 
Components Analysis within the path analysis framework seems to be well thought out and 
appropriately interpreted with the caveat that the data come from a cross -sectional dataset.   The 
authors also have stated study limitations well with the exception of the fact that probably the 
nature of the convenience sample a weak link to maki ng statistical inference and one or two 
other issues that I have listed below.  
 
 
&lt;B&gt;Comments/Suggestions:  
 
Major &lt;/B&gt; 
 
* The cross -sectional nature of the study makes the claim of the mediating effects of 
depression and anxiety to be somewhat ques tionable as its possible that those with high 
depression and anxiety levels may had already perceived that their leisure time was 
limited even before they had a cancer diagnosis.   The authors use a very old definition of 
mediation is based on a very old d efinition given in the classic paper by Baron and 
Kenny.  Newer research into the areas of mediation and moderation have brought forth a 
more modern understanding of those phenomena [see, e.g., Kraemer, et al. "How and 
Why Criteria Defining Moderators and Mediators Differ Between the Baron &amp;  
Kenny and MacArthur Approaches". Health Psychol. 2008 March; 27(2 Suppl): S101 -
S108].  
 
* The study would have been more interesting and methodologically stronger if the authors 
had figured out a way to bring the clin ical and treatment characteristics into the path 
analysis. Adjustment is also important because of the fact that the data is from a non -
randomized, convenience sample.  
 
* The statistical methods seem mostly OK although the authors do not explain details of  
their path analysis very well. They employ an SPSS add -on program called "PROCESS" 
but are really sparse in providing details of what is really being done.  Also, it's not clear 
how the directions of the arrows in the Figure are established within the lab eled paths.  
Furthermore, the distinction between path c and path c' and the differences in the 
magnitude between those two paths are not clear from the description of methods and 
results.   Establishing a clear description of all aspects of this model is key because most 
of the readers of this journal will not be familiar with these models and hence, cannot 
fairly judge possible clinical implications of this research.  
 
* The models the authors don't seem to be adjusted for stage of cancer and whether or not  
patients were on chemotherapy.  These are key variables to adjust for because, as the 
authors point out, the anxiety, depression and leisure time variables all are related to 
clinical status and treatment.  Furthermore, variation in clinical status and tr eatment may 
result in different relationships among the three variables.    
 
 
&lt;B&gt;Minor &lt;/B&gt; 
 
* Table 4: First, since the adjusted R &lt;sup&gt;2&lt;/sup&gt; and simple 
R&lt;sup&gt;2&lt;/sup&gt; are very similar, one of those two columns could be 
eliminated.  It would probably be best to replace the deleted column with 95% confidence 
intervals for the β estimates.  Also, the p -values in the last column with the " &lt; .000" 
entries look like they might be a result of the page being truncated and were probably 
were meant to be " &lt;0.0001".  Obviously, a p -value cannot be negative as " &lt;.000" 
would indicate so the entries with that information should be fixed.  
 
* The authors should indicate that the ß estimates associated with their models represent 
regression coefficients.  
 
Please overwrite this text when adding your comments to the authors.  
 
Are the methods appropriate and well described?  
If not, please speci fy what is required in your comments to the authors.  
 
No 
 
Does the work include the necessary controls?  
If not, please specify which controls are required in your comments to the authors.  
 
No 
 
Are the conclusions drawn adequately supported by the data shown?  
If not, please explain in your comments to the authors.  
 
Yes 
 
Are you able to assess any statistics in the manus cript or would you recommend an 
additional statistical review?  
If an additional statistical review is recommended, please speci fy what aspects require further 
assessment in your comments to the editors.  
 
I am able to assess the statistics  
 
Quality of written English  
Please indicate the quality of language in the manuscr ipt: 
 
Acceptable  
 
Declaration of competing interests  
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