Sarah Dillon is a PhD candidate at DCU. Image: Sarah Dillon
DCU PhD candidate Sarah Dillon is trying to better understand how running injuries occur and how to bring this data to the masses.
Sarah Dillon is a chartered physiotherapist and a PhD candidate at Dublin City University (DCU). Her work, funded by the SFI Insight Centre for Data Analytics, uses 3D motion analysis technology to model the ‘whys’ of running injuries, with an aim to understand the risk factors for injuries and how they might be avoided.
What inspired you to become a researcher?
I wasn’t one of those people who dreamed of hypotheses and randomised controlled trials from the time I was in nappies. For me, this journey began with my desire to help people and my love of biology.
When it came time to choose what I would do after school, physiotherapy seemed like the perfect fit. Helping someone to manage their injury is a bit like putting a puzzle together, requiring information from subjective and objective assessments, a strong patient-practitioner relationship and a wealth of research to inform your practice.
As an undergraduate in the University of Limerick, a lot of emphasis was placed on evidence-based practice. That ethos naturally leads me to become more inquisitive as a physiotherapist. As I started to question what we did in practice I began to see how many questions are still left unanswered and the value of contributing to gaps in the research.
That’s when I knew that I would love to be one of those people at the coalface of developing our knowledge. I jumped at the opportunity to work on some fantastic research in DCU.
Can you tell us about the research you’re currently working on?
The project I am working on, called the DCU Running Injury Surveillance Centre study, has now collected motion analysis and clinical information of more than 300 runners.
We have taken a snapshot of running technique in the lab using state-of-the-art 3D motion analysis technology and have also tracked their movement using small inertial measurement units which are attached to the legs.
These inertial measurement units are like ‘Fitbits for the legs’ and let us know how hard someone is impacting the ground each time they take a step. We have tracked these runners for injury for 18 months and are hoping to see if there is a relationship between these baseline measurements and running-related injury.
Another interesting part of our research is that we are investigating the rare group of never-injured runners to explore what may make them resistant to injuries.
In your opinion, why is your research important?
This is an exciting area of research as we already know that there is a gap in our knowledge in understanding what causes running injuries. Every year, up to 79pc of recreational runners can experience a running-related injury, often forcing them to stop running for substantial periods of time.
This can be really frustrating and detrimental to their health. We know that injury can be caused by loading which exceeds the capability of the body’s tissues. In layman’s terms, this means that we overload our muscles, tendons and ligaments, causing injury.
Our research takes on a novel approach by using these initial measurement units to track loading, as well as collecting information about clinical factors that may be involved in injury, such as strength, flexibility and foot type, all on a large scale. This will hopefully allow us to have a clearer understanding as to the reasons why so many runners get injured.
What commercial applications do you foresee for your research?
Over the course of a run, a person impacts the ground thousands of times. The sensors in our study have allowed us to measure how hard these runners hit the ground over numerous foot strikes to see if this relates to injury.
In the future, runners may be able to use inertial measurement units themselves to give feedback on their running style via a phone app. The inertial measurement units are small and portable, so they potentially could be used outdoors in a runner’s typical training environment, unlike a lot of other methods of biomechanical analysis.
What are some of the biggest challenges you face as a researcher in your field?
The difficulty with ascertaining what causes running injuries – and injuries as a whole – is that there are many factors that may contribute to sustaining an injury. We can’t control for every factor which may potentially affect whether someone gets injured.
These may include things like sleep, stress, emotional wellbeing or even attitude. For now, we have selected a large amount of potentially valuable variables, some of which are already currently widely used in clinical practice by physiotherapists and certified athletic therapists.
Another thing which has long been known to be difficult when doing a prospective study is maintaining contact with participants. Luckily, so far, we have been very fortunate with the response to our study, so a big thank you to our wonderful participants!
Are there any common misconceptions about this area of research?
When people think of biomechanics, an image of lab-based research springs to mind with information that might not necessarily be applicable to them. However, this area of research is growing and becoming more accessible to the average runner who keeps on getting a niggling injury. What we are hoping to do with our study of recreational runners, is to find potentially useful information that we can all use, not just the elite.
What are some of the areas of research you’d like to see tackled in the years ahead?
I would like to see more research into training load with relation to running injuries specifically. There is research emerging that has found associations between over and under-training injury, but more clarity could be useful.
It would also be particularly interesting to widen our scope of testing to include not just runners, but also athletes such as footballers, rugby players etc. Also, more research aimed at investigating psychosocial factors related to running injuries could be useful in a thorough understanding of this area.
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