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Towards a complex systems approach in sports injury research: simulating running-related injury development with agent-based modelling
  1. Adam Hulme1,
  2. Jason Thompson2,
  3. Rasmus Oestergaard Nielsen3,
  4. Gemma J M Read1,
  5. Paul M Salmon1
  1. 1 Faculty of Arts, Business and Law, Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore DC, Queensland, Australia
  2. 2 Faculty of Architecture, Building and Planning, Melbourne School of Design, Transport, Health and Urban Design (THUD) Research Hub, University of Melbourne, Melbourne, Victoria, Australia
  3. 3 Department of Public Health, Section for Sports Science, RunSafe Research Group, Aarhus University, Aarhus, Denmark
  1. Correspondence to Dr Adam Hulme, Faculty of Arts, Business and Law, Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore DC, QLD 4556, Australia; ahulme{at}


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. Therefore, our objective was to use a computational modelling method and develop a dynamic simulation in sports injury research.

Methods Agent-based modelling (ABM) was used to model the occurrence of sports injury in a synthetic athlete population. The ABM was developed based on sports injury causal frameworks and was applied in the context of distance running-related injury (RRI). Using the acute:chronic workload ratio (ACWR), we simulated the dynamic relationship between changes in weekly running distance and RRI through the manipulation of various ‘athlete management tools’.

Results The findings confirmed that 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.

Conclusions 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.

  • agent-based modelling
  • complex systems
  • sports injury
  • distance running

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  • Contributors AH was responsible for the concept, ABM development, methods, results interpretation and write-up. JT was primarily responsible for developing the ABM, contributed to the methods write-up and had editorial input into the manuscript. RON, GJMR and PMS had editorial input into the manuscript and contributed to the write-up. PMS’s contribution to this work was funded by the Australian Research Council (FT140100681).

  • Funding Australian Research Council (grant number: FT140100681).

  • Competing interests None declared.

  • Patient consent Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.