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The authors have addressed all of the reviewers' comments and the manuscript seems ready for publication.
[# PeerJ Staff Note - this decision was reviewed and approved by Mike Climstein, a PeerJ Section Editor covering this Section #]
A few minor remaining still to address from the reviewers.
In the main, I am satisfied that the authors have addressed my previous comments regarding basic reporting. I respectfully disagree with the rationale presented for including data repeated in both table 1 and figures 1-3, but I don’t feel that there is sufficient need to demand that the authors move either of those formats to the supplementary files unless the academic editor strongly that should be the case.
Again, I am generally satisfied with the changes that have been made in response to my previous suggestions in this section. However, I feel that some of the points that were made within the rebuttal to the editors and reviewers should be included in the manuscript itself. This can be done around lines 144-146, where the citations to the work of Rodrigo-Carranza and colleagues are made. Specifically, reference should be made to your own supplementary data, and to the Willwacher et al. preprint, that both support the case the extending the analysis back to 2010 would have no effect on the analysis.
As a minor follow up point, I also respectfully disagree with the point about the large data set and the difficulties of presenting it being a reason to curtail the analysis. Again, I am not asking for this to be changed within the manuscript, but I feel that the analysis and reporting should be driven by the data and the questions being asked, not by the challenges or complexities of data visualisation, especially with things having advanced so much in that area in recent years.
I am happy with the response given by the authors and the changes made to the manuscript as a result in relation to all of my previous comments in this section.
I have no further comments.
All my concerns have been properly addressed
All my concerns have been properly addressed
All my concerns have been properly addressed
All my concerns have been properly addressed, two final suggestions:
L78 (tracked changes document) "1896-2008 indicating" change to "1896-2008 indicate"
L339 (tracked changes document) "which do not directly investigate midsole thickness" consider briefly discussing the findings of Barrons et al (https://doi.org/10.1080/19424280.2023.2218321) here, who observed no improvements in running economy from increased midsole thickness.
Both reviewers raised important points that I think all need to be addressed in revisions to the manuscript (not just rebuttals to the reviews). In particular:
- Both reviewers had concerns over the seemingly arbitrary choice of 2016 as the starting point for the data. The basis for this choice should be justified and the question of whether categorically different results are achieved if a different starting point is used should be addressed.
- Consistent with Reviewer #2, I was unclear on why paired tests were used. This seems appropriate only if it is the same athletes being compared to themselves, which is presumably not the case unless I misunderstood what was done exactly (e.g. the top 20 athletes in different years are not the same 20 athletes).
**PeerJ Staff Note:** Please ensure that all review, editorial, and staff comments are addressed in a response letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate.
[# PeerJ Staff Note: Reviewer 1 declared a potential Conflict of Interest, and the Editor was aware of this when making their decision #]
Overall, the manuscript was clear, well written and easy to follow. There was one overly long paragraph in the discussion (starting on line 273), which the authors should consider breaking up to aid flow and readability. Referencing was generally good throughout, although the Healey et al (2022) study cited on line 122 and elsewhere was not included within the reference list. Please cross-check the in-text citations with the reference list throughout the manuscript.
It seemed to me that there was some repetition in the data presentation between table 1 and figures 1-3, to the extent that I’m not certain that both the table and the figure are required. Please consider condensing the information contained across these two formats in to one that best summarises the intended overall message. Further, the ordering of events was different between tables 1 & 3, which could potentially cause confusion to the reader. I suggest using a consistent ordering throughout.
All appropriate raw data appears to have been shared, and in my opinion the submission is sufficiently self-contained and represents an appropriate unit of publication.
As far as I am aware, this is original primary research, and it is within the scope of the journal. The aims and hypotheses that are presented are relevant and meaningful, and the research has clear potential to fill an identified knowledge gap.
I have no queries about the ethical standards of the work. I am a little unsure, however, about some of the specifics of the research design, and would appreciate some further clarification here. A major premise of the analysis is that performances in the analysed events have reached a plateau. Whilst a case is made for this within the introduction, and additionally based on the data analysed form 2016-2019, I feel that further explanation and evidence is required. I note that in the supplementary data files, data for the top 100 times have been provided going back to 2010, yet only the data to 2016 have been included in the manuscript. This appears to be something of an arbitrary cut-off, and I wonder if by including the data back to 2010 in the analysis the findings about the timing of the plateau may be different. On what basis was the 2016 cut-off chosen?
Additionally, have the authors considered the potential effect of the type of global competition that is held within each year (Olympics v World Championships), and the differences in qualification that may or may not have some influence on the top times in any given year. Further, some years don’t have a major global championship (e.g. 2018). Please comment on the potential impact of this within your study design.
The introduction section (line 76) mentions the plateau in some women’s events since 1994, but doesn’t mention the potential link to this of the introduction of more routine drug testing not long prior to that date. This point is picked up a little in the discussion, but I feel is also important to raise regarding the initial context of the study.
Overall, I found the description of the methods to contain sufficient information to be reproducible.
All necessary underlying data have been provided and appear to be robust. I do have a query regarding the statistical approach, however. On line 169 it is stated that the normal distribution assumption was verified. However, aren’t the data being analysed almost by definition being taken from a very specific part of that normal distribution – i.e. from the very tail at the extreme elite end of performance? This is then represented in the shapes of the curves presented in Figures 1-3. Please clarify.
I felt that in places throughout the manuscript that the findings and conclusions were at times overly confidently or strongly stated. It felt to me that the phrasing from line 260 that “our results provide initial evidence that along with the technological innovation there is meaningful advancement in sprint performances” gave a more appropriate reflection of the likely contribution to the advancement of knowledge of the current study. I suggest that this tone is adopted throughout.
I also felt that some of the explanations for the reasons behind the findings could do with more explanation in a couple of instances; Firstly, the differences in findings between the male and female athletes could potentially do with further explanation – is it possible to provide any theoretical predictions of the likely magnitude of the effects of the mechanisms that you propose for explaining these differences? Secondly, can you comment further on the inconsistency in the findings from 2021 and 2022 compared to pre-ATF? i.e. if the ATF were to have such a clear effect after their adoption, would we expect those effects to be consistent across both years in which they have been worn? Please comment on these points.
The wording on line 118 appears to include some unintended repetition, which makes its meaning hard to follow. Please clarify.
Overall, this paper was a great read and a nice extension to the referenced papers on road running performances and AFT. While the introduction could use a little polishing the content was all there, and a lot of thought was clearly put into the discussion.
Meets all the check boxes.
I have one concern about the statistical approach (see below), otherwise robust.
My post-doc Zach Barrons, PhD assisted me with this review.
Overall
The purpose of this paper was to determine if the introduction of AFT spikes have meaningfully impacted sprint event performances and to determine whether they affect one sex mores so than the other.
Overall, this paper was a great read and a nice extension to the referenced paper on road running performances and AFT. While the introduction could use a little polishing the content was all there, and a lot of thought was clearly put into the discussion.
We have several important concerns that we would like to see addressed:
Our main concern is whether the use of paired t-tests is appropriate in this case. There is no reason why data points between years should be considered pairs, and since all the data is ranked (top 20, top 100), this probably makes the use of paired t-tests even less appropriate. Consider the following example. Year 1, top 100: 10.01s – 11.00s; year 2, top 100: 10:00s – 10.99s (let’s say 1 athlete improves from 11:00 to 10:00s). Paired t-test based on rank would suggest a significant improvement (p<0.0000001), as there’s 100 ‘pairs’ where year 2 is 0.01 faster. However, if these are considered 2 independent samples (which they are), these are not significantly different (p=0.8).
Secondly, a rationale should be provided for starting the analyses with the year 2016.
Another concern involves the examination of the top 20 and top 100 performers. As written, for the first half of the paper it appeared to me that you set off from to start to look at these two distinct groups however, it is unclear whether the top 100 analysis includes the top 20 performers as well. Based on the methods I think the focus on 2 groups may have been the result of an inability to identify footwear. Please clarify when you say top 100 vs top 20, does the top 100 contain the top 20? As written, that’s how I would interpret it but that seems like a flawed approach, when aiming to evaluate groups with different performance levels.
Finally, a preprint addressing similar questions using similar methodology is available ( https://sportrxiv.org/index.php/server/preprint/view/297 ) and should be discussed here.
Abstract
Line 32 – We are unsure what you mean by “emphatic performance benefits” perhaps consider the use of a different word.
Line 33 – please change “has” to “have”
Line 35 – Perhaps consider being more specific. It is not clear based on what whether AFT spikes work.
Line 37 – please clarify that you’re looking at improvements in athletes’ performance (I assume)
Line 43 – the structure of this sentence is a little awkward, please consider revising. Specifically “between the years each year for each event”.
Line 47 – please remove “for”
Introduction
Line 65 – “The” can be removed.
Line 71 – please specify the end of the time period referenced or the additional decades in question. “the decades from the 1990s” until when?
Line 72 – please consider rearranging the sentence to state that sprint times are plateauing.
Line 76 – please change “had” to “has”
Line 76 – it might be good to reiterate the changes in drug testing in the early 90s (many would consider the late 80, early 90 women’s sprint performances suspicious)
Line 84 – the shoe characteristics that define AFT are not mentioned until Line 91, and come too late. I can see it would break the flow to add this definition here, but please reorder things, to not leave the reader hanging…
Line 95 – please change “to track spikes” to “in track spikes”
Line 97 – “The” can be removed.
Line 113 – please remove “the” from “the AFT sprint spikes”
Line 115 – please consider changing “AFT to sprint spikes”. Previously you’ve used AFT to describe footwear that incorporate key features and on first read its confusing if you’re talking about the key features or the footwear. Maybe change “AFT to sprint spikes” to “AFT to sprinting”.
Line 117 – please change “throws” to “throwing” or “throw”
Line 118 – please delete “gold medals in athletics throws events”; change “Olympic” to “Olympics”
Line 120 – please consider altering this sentence “Despite…”. The structure of the sentence is a little awkward. Also please change “is” to “ has” on Line 122.
Line 123- aim 1: I’m currently wondering why you specify top 100 and top 20. Are the top 20 not part of the top 100? I think I’m missing something. As specified for line 37, please clarify that you’re looking at improvement in performance of the athletes.
Line 125- please considering changing the line from “the advent and thus extensive use” to “the introduction” (or something similar). I think it may clarify what you mean.
Line 126 – please clarify if you mean all recent performances or recent improvement in performance?
Line 127 – please consider changing “level-specific” to “experience” or something similar to enhance clarity.
Materials and Methods
Database search and data selection
Line 138 – Why did you choose the years 2016 – 2019 as your pre-AFT period? Please consider justifying.
Definition and identification of AFT
Line 153 – please change “uses” to “incorporates” or something similar
Line 155 – would it be possible to provide a list of models identified as AFT in the supplementary materials
Line 156:161 - please consider moving these lines to follow line 147.
Data analysis and statistics
Line 164 – Please consider removing this sentence. I think that goes without saying.
Line 166 – pairwise, see main concern above
Results
Line 194 – since one-sided t-tests were performed, “differences” should be specified as “improvements”
Discussion
Line 251 – When you compared the performances of the top 100 athletes to the top 20, did you remove the top 20 or were they still included in the top 100?
Line 253 – “influencing” is too strong here, given the correlational analysis
Line 259 – please change “distance” to “distances”
Line 273:326 – although the authors should be commended for discussing potential mechanisms explaining their findings. There’s currently too much speculation that is presented with too much confidence. Please add more clearly that this is all speculative based on observations from studies not addressing midsole thickness per se.
Line 282 – alternatively, they might as well create less beneficial lever arms, as for a similar hip torque production a longer effective leg length will result in a smaller propulsive force… basically the opposite of the suggested mechanism… so the same citations can be used for the opposite argument…
Line 293 – observations of reduced leg length resulting in slower speed, do not necessarily mean that increases in leg length result in higher speed…
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