In the context of some of the issues that I wrote about yesterday concerning the problems with the “pronation” paradigm as the basis for prescribing running shoes, a number of years ago we decided to do a study looking at how a different parameter might be affected by the so-called ‘motion control design’ features of a running shoe. Unfortunately, the study never really got completed so won’t be published mainly because of the pressures of academic life, workload and other factors having to be given priority especially when a project is unfunded. I have to acknowledge my colleague Dan Bonanno for working on this project as well.
What we decided to do was to see if different running shoes would alter the time that load came off the heel when running. This was based on the hypothesis that perhaps a motion control running shoe would theoretically allow the load to come off the heel sooner. To do this we contacted a number of running shoe companies and asked them to supply what they considered to be their best motion control running shoe and the most neutral running shoe that they had. We used an in-shoe pressure measuring system to determine the percent of the gait cycle that load came off the heel. We collected data from multiple running steps and calculated the mean percent of the stance phase that load came off the heel. We only collected data on eight subjects and as you can see from the table below there were no differences in the timing that the load came off the heel in those eight:
Even though this was probably an inadequate sample size of eight there are clearly no differences between all the different shoes. Even though it was only on eight you would have at least expected to see a hint of a trend if there was to be a difference and there is no hint of a trend.
So much for our hypothesis. This reminds me of a quote from TH Huxley: “The great tragedy of science is the slaying of a beautiful hypothesis by an ugly fact”
But all is not lost. What was interesting about this data, and why I am posting about it, was when you looked at the individual runners; ie the subject specific data. Here is the subject specific data from one runner in the study.
As you can see from the from the data there were very clear differences between the shoes. One particular shoe delayed heel off until 63% of the stance phase whereas with another two shoes, the heel off was at 50% of the stance phase. That is a 13% difference. What does this mean? It could mean a less load going through the tissues if heel off is at 50% as it might have been easier to get the heel of the ground with less effort. This could mean that the forces flowing through the foot are moving forward more easily (terrible terminology). The forces are probably lower and that’s why the heel came off the ground sooner. This could also be a sign of efficiency. Obviously getting the heel off the ground sooner means you probably going to be running faster with less effort. All speculative interpretation, of course.
It was the same for every one of the eight runners that we managed to recruit into the study, as limited as what the sample size was. For each runner there was one or two shoes that appeared to delay heel off and one or two shoes in which heel off occurred earlier. For each runner it was a different shoe or set of shoes that did this. So there was not one particular shoe that brought heel off on earlier or brought heel off on later. It was different for each runner. It was subject specific. When you pool all the data for the eight subjects as in the first table above there are no differences between any of the shoes.
It is interesting to speculate on what these findings may potentially have for the prescribing of running shoes, injury risk reduction, and running performance. The challenge is going to have to be why and what was it about each runner that meant they responded differently to the different design features in each of the shoes and how can we match up the runner to this either in a clinical or a retail setting. This could perhaps be with the use of in-shoe pressure measuring system or an in-shoe sensor to determine the timing of heel off in different shoes to find the right one. However, this is likely to be a very time-consuming process and are certainly not going to be economical at the retail level. Nike have been reported in the media as having committed $2 million to a project for a running shoe for Mo Farah. I have no idea exactly what they did or are doing but can only assume that they will be measuring how he responds to different design features and incorporating those designs into the shoe that best suits him. His shoe will probably not work for anyone else.
It is interesting to speculate the relationship of what we found to what runners often described as the “ride” of a shoe. The comments are things like the ride of the shoe is better then the right of that shoe. Does this mean that they are sensing what we found in the small study? Are they naturally feeling that more efficient forward flow of the forces in some shoes and not in others? … as bad as that terminology is!
As always: I go where the evidence takes me until convinced otherwise … and I really only post this information more to provoke thought rather than present our results as something definitive due to the limited nature of the study that we did. Make of it what you will.