Towards a complex systems approach in sports injury research: simulating running-related injury development with agent-based modelling. Issue 9 (18th June 2018)

• Record Type: Journal Article
• Authors: Hulme, Adam; Thompson, Jason; Nielsen, Rasmus Oestergaard; Read, Gemma J M; Salmon, Paul M
• Is Part Of: British journal of sports medicine. Volume 53:Issue 9(2019)
• Page Start: 560
• Page End: 569
• Publication Date: 2018-06-18
• Subjects: agent-based modelling -- complex systems -- sports injury -- distance running; Sports medicine -- Periodicals; 617.1027
• DOI: 10.1136/bjsports-2017-098871
• Languages: English
• ISSNs: 0306-3674

Abstract

Abstract : 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.