Adam Hulme

From monocausality to systems thinking: a complementary and alternative conceptual approach for better understanding the development and prevention of sports injury

The science of sports injury control, including both its cause and prevention, has largely been informed by a biomedical and mechanistic model of health. Traditional scientific practice in sports injury research has routinely involved collapsing the broader socioecological landscape down in order to analyse individual-level determinants of injury - whether biomechanical and/or behavioural. This approach has made key gains for sports injury prevention research and should be further encouraged and allowed to evolve naturally. However, the public health, Applied Human Factors and Ergonomics, and injury epidemiological literature more broadly, has accepted the value of a socioecological paradigm for better understanding disease and injury processes, and sports injury research will fall further behind unless it does the same. A complementary and alternative conceptual approach towards injury control known as systems thinking that builds on socioecological science, both methodologically and analytically, is readily available and fast developing in other research areas. This review outlines the historical progression of causal concepts in the field of epidemiology over the course of the modern scientific era. From here, causal concepts in injury epidemiology, and models of aetiology as found in the context of sports injury research are presented. The paper finishes by proposing a new research agenda that considers the potential for a systems thinking approach to further enhance sports injury aetiological understanding. A complementary systems paradigm, however, will require that sports injury epidemiologists bring their knowledge and skillsets forwards in an attempt to use, adapt, and even refine existing systems-based approaches. Alongside the natural development of conventional scientific methodologies and analyses in sports injury research, progressing forwards to a systems paradigm is now required.

A framework for the etiology of running-related injuries.

The etiology of running‐related injury is important to consider as the effectiveness of a given running‐related injury prevention intervention is dependent on whether etiologic factors are readily modifiable and consistent with a biologically plausible causal mechanism. Therefore, the purpose of the present article was to present an evidence‐informed conceptual framework outlining the multifactorial nature of running‐related injury etiology. In the framework, four mutually exclusive parts are presented: (a) Structure‐specific capacity when entering a running session; (b) structure‐specific cumulative load per running session; (c) reduction in the structure‐specific capacity during a running session; and (d) exceeding the structure‐specific capacity. The framework can then be used to inform the design of future running‐related injury prevention studies, including the formation of research questions and hypotheses, as well as the monitoring of participation‐related and non‐participation‐related exposures. In addition, future research applications should focus on addressing how changes in one or more exposures influence the risk of running‐related injury. This necessitates the investigation of how different factors affect the structure‐specific load and/or the load capacity, and the dose‐response relationship between running participation and injury risk. Ultimately, this direction allows researchers to move beyond traditional risk factor identification to produce research findings that are not only reliably reported in terms of the observed cause‐effect association, but also translatable in practice.

Closing Pandora's Box: adapting a systems ergonomics methodology for better understanding the ecological complexity underpinning the development and prevention of running-related injury

ABSTRACT The popularity of running as a form of exercise continues to increase dramatically worldwide. Alongside this participation growth is the burden of running-related injury (RRI). Over the past four decades, traditional scientific research applications have primarily attempted to isolate discrete risk factors for RRI using observational study designs as commonly used in public health epidemiology. Unfortunately, only very few randomised controlled trials have evaluated the efficacy associated with a well-specified RRI prevention intervention. Even though the knowledge about risk factors as generated in observational studies is valuable for better understanding why RRI develops, it nonetheless means that there remains a major knowledge gap about how best to prevent it, especially in a way that fully addresses all causal factors. Alongside the continuing use of traditional scientific approaches, a particular systems ergonomics methodology should also be considered in light of its potential to visualise the complete distance running system. This article adapts the Systems Theoretic Accident Mapping and Processes (STAMP) model to the RRI research prevention context. The direct application of STAMP might offer new knowledge about how to prevent RRI, such as exposing questions around the feasibility of adopting novel injury prevention interventions that do not directly target runners themselves.

The epistemic basis of distance running injury research: A historical perspective

For both recreational and competitive purposes, distance running is an ideal activity for increasing endurance capacity and improving cardiovascular health. Running is an accessible and relatively simple form of exercise that is performed by able bodied individuals in a variety of locations worldwide. Accordingly, the popularity of running in developed countries has increased dramatically in recent times, demonstrated by the growth in fun runs, marathons, and fundraising events. Unfortunately, musculoskeletal injuries are a common side effect of participation, particularly for novice exercisers who are at greatest risk.1 In order to reduce the incidence of distance running injury, the identification of risk factors and injury mechanisms is a necessary step for effectuating preventative interventions.2 Aetiological research, however, requires a multidisciplinary approach encompassing epidemiological data, biomechanical analyses, clinical research, and behavioral studies.2 Recent calls for more experimental and observational research to better understand the aetiology of distance running injury are certainly justified.3 In particular, scientific study designs located higher on the evidence hierarchy, such as the randomised controlled trial and prospective cohort, are capable of reducing methodological biases to establish cause–effect relationships reliably. Irrespective of the need for more analytical research, the scientific literature is replete with aetiologically-focused distance running injury investigations. With consideration for what is now a significant body of research, the purpose of this opinion piece is to present the epistemological basis underpinning distance running injury epidemiological research. Exploring the historical context of the literature from an epistemic perspective presents the opportunity to reflect on past developments and current practice. From here, opportunities are identified, and complementary and alternative conceptual and methodological directions for future research are recommended.

When is a study result important for athletes, clinicians and team coaches/staff?

How do you know if the results of a particular study are important to your team, your patients or your community? A result that is statistically significant is not necessarily a meaningful target for sports injury prevention or a treatment strategy.1–3 And if statistical significance is not enough to determine ‘importance’ or meaningfulness, then what is? ### Box 1 Definition: Minimal important difference (MID) Minimal important difference (MID) is the smallest change in sports injury risk or treatment outcome that an athlete, a player, a coach, a clinician and/or team staff would identify as important. The size of MID is context-specific and a study result may be identified as important for some and non-important for others. We aim to shed light on this important topic in the first of a series of editorials that will help clinicians and team staff interpret studies more critically and confidently. First, a measure of association (eg, a relative risk or an absolute risk difference) and its precision (eg, 95% CIs) allows for appropriate evaluation of study results.1 Next, a size of an association should be equal to or exceed a minimal important difference (MID) (box 1) that would affect practice. In this light, the question remains: is it possible to identify a MID in sports injury articles regardless of the measure of association used? In this editorial, we argue that the choice of measure has consequences for the ability to …

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

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.

Applying systems ergonomics methods in sport: A systematic review

INTRODUCTION As sports systems become increasingly more complex, competitive, and technology-centric, there is a greater need for systems ergonomics methods to consider the performance, health, and safety of athletes in context with the wider settings in which they operate. Therefore, the purpose of this systematic review was to identify and critically evaluate studies which have applied a systems ergonomics research approach in the context of sports performance and injury management. MATERIAL AND METHODS Five databases (PubMed, Scopus, ScienceDirect, Web of Science, and SPORTDiscus) were searched for the dates 01 January 1990 to 01 August 2017, inclusive, for original peer-reviewed journal articles and conference papers. Reported analyses were underpinned by a recognised systems ergonomics method, and study aims were related to the optimisation of sports performance (e.g. communication, playing style, technique, tactics, or equipment), and/or the management of sports injury (i.e. identification, prevention, or treatment). RESULTS A total of seven articles were identified. Two articles were focussed on understanding and optimising sports performance, whereas five examined sports injury management. The methods used were the Event Analysis of Systemic Teamwork, Cognitive Work Analysis (the Work Domain Analysis Abstraction Hierarchy), Rasmussens Risk Management Framework, and the Systems Theoretic Accident Model and Processes method. The individual sport application was distance running, whereas the team sports contexts examined were cycling, football, Australian Football League, and rugby union. CONCLUSIONS The included systems ergonomics applications were highly flexible, covering both amateur and elite sports contexts. The studies were rated as valuable, providing descriptions of injury controls and causation, the factors influencing injury management, the allocation of responsibilities for injury prevention, as well as the factors and their interactions underpinning sports performance. Implications and future directions for research are described.

Are prevalence measures better than incidence measures in sports injury research

Prevalence and incidence are terms commonly used to describe the number, proportion and rate of sports injury in the epidemiological and clinical literature. Indeed, scientific articles have discussed the practical implications of choosing one of these measures over another in relation to better understanding the burden of injury as well as sports injury aetiology, prevention and treatment.1–3 Recently, the use of prevalence and not incidence has been promoted to demonstrate a relationship between training load and overuse sports injury.2 However, there is a need to further elaborate on the circumstances in which prevalence and incidence are used as both measures are relevant and depend on the goals of the researcher and study. Therefore, the purpose of this editorial is to explain the differences between prevalence-based and incidence-based measures, and promote when they should be used by drawing on available data from an existing 1-year, 933-person running injury cohort study (DANORUN4). Why do sports injuries develop? What we can do to prevent them? Which treatment options should be offered to injured athletes? These are arguably some of the most important questions facing coaches and clinicians. Fortunately, incidence-based measures can help to provide answers given that they relate to the occurrence of new sports injury in an athletic population within a specified period or how many injured athletes recover over time. ### Incident cases The number of incident cases can facilitate the identification of when injuries occur. This allows coaches and clinicians to carefully consider whether there have been any noticeable and …