Evidence map›Paper›PMID 29915127›Full record

ReviewBritish journal of sports medicine2019

Towards a complex systems approach in sports injury research: simulating running-related injury development with agent-based modelling.

Adam Hulme, Jason Thompson, Rasmus Oestergaard Nielsen, Gemma J M Read, Paul M Salmon

Registry-linked trialOpen access · bronzeAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in British journal of sports medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05430581 (Prediction of Knee Injuries Through System Dynamics Modeling), which is not on this map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
6.7field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05430581 unknown statusnot on this mapstarted 2022, after this paper: background citation

Prediction of Knee Injuries Through System Dynamics Modeling

TypeobservationalSponsorUniversity of PatrasRan2022 to 2024Enrolled99ConditionsSport Injury, Sports Physical Therapy
3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 2 syntheses or guidelines pooled it, 63 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 4 countries.

Adam HulmeFaculty of Arts, Business and Law, Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore DC, Queensland, Australia.ORCID http://orcid.org/0000-0002-3305-8538
Jason ThompsonFaculty of Architecture, Building and Planning, Melbourne School of Design, Transport, Health and Urban Design (THUD) Research Hub, University of Melbourne, Melbourne, Victoria, Australia.
Rasmus Oestergaard NielsenDepartment of Public Health, Section for Sports Science, RunSafe Research Group, Aarhus University, Aarhus, Denmark.ORCID http://orcid.org/0000-0001-5757-1806
Gemma J M ReadFaculty of Arts, Business and Law, Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore DC, Queensland, Australia.
Paul M SalmonFaculty of Arts, Business and Law, Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Maroochydore DC, Queensland, Australia.
University of the Sunshine Coast · AUAarhus University · DKThe University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThere 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.

methodsAgent-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'.

resultsThe 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.

conclusionsThe 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.

Indexed as

Computer SimulationSystems AnalysisAthletesAthletic InjuriesHumansRunningWorkloadagent-based modellingcomplex systemsdistance runningsports injury

Identifiers

PMID29915127
PMCPMC6579554
OpenAlexW2809062899

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.