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Computational modelling for sports injury prevention research: Proposing a new simulation paradigm
Abstract   Peer reviewed

Computational modelling for sports injury prevention research: Proposing a new simulation paradigm

Adam Hulme, J Thompson, Gemma J M Read, R Nielsen and Paul M Salmon
Journal of Science and Medicine in Sport, Vol.21(Supplement 1), p.S20
Sports Medicine Australia Conference, 2018 (Perth, Australia, 10-Oct-2018–13-Oct-2018)
2018
DOI: https://doi.org/10.1016/j.jsams.2018.09.047
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https://doi.org/10.1016/j.jsams.2018.09.047View
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Abstract

Human Movement and Sports Science Medical Physiology Public Health and Health Services
Objectives: There have been recent calls for the application of the 'complex systems approach' in sports injury research. However, beyond theoretical description and static models of complexity, little progress has been made towards formalising this approach in way that is practical to sports injury scientists and clinicians. The objective of this study was to use a computational systems science modelling method and develop a dynamic simulation in sports injury research. Methods: Agent-Based Modelling (ABM) was applied in the context of distance running-related injury (RRI). The primary aim of the model was to demonstrate the method and simulate the dynamic relationship between weekly running distances and RRI through the manipulation of various 'athlete management tools'. The ABM was developed based on sports injury and RRI causal theory, and incorporates evidence gathered from studies using the acute: chronic workload ratio (ACWR). Results: Building weekly running distances over time, even within the reported ACWR 'sweet spot', will eventually result in RRI as athletes reach and surpass their individual physical workload limits. Introducing training-related error into the simulation and the modelling of a hard ceiling dynamic resulted in a higher RRI incidence proportion across the population at higher absolute workloads. Discussion: Whilst this simulation was modelled on understanding RRI occurrence in a general population, the implications of this dynamic indicated fragility at the extremities of performance for the more serious runner who might aim to participate in competitive events. Athletes, running coaches, and healthcare practitioners are reminded that although it is necessary to progressively and systematically increase external workloads over time, it is as equally important to continuously monitor and measure internal physiological and psychological responses to that load. Importantly, the presented simulation offers a practical starting point to further apply more sophisticated computational models that can account for the complex nature of sports injury aetiology. Alongside traditional forms of scientific inquiry, the use of ABM (and other simulation-based techniques) could be considered as a complementary and alternative methodological approach in sports injury research.

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