‘Complex systems model’ of running-related injury development and prevention

NewsBot · Aug 5, 2017

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From control to causation: Validating a ‘complex systems model’ of running-related injury development and prevention
A. Hulme et al
Applied Ergonomics; Volume 65, November 2017, Pages 345–354

Highlights
•Distance running is popular form of exercise that promotes numerous physical and psychological health-related benefits.
•One of the main barriers preventing continued adherence to a running program is musculoskeletal running-related injury (RRI).
•Alongside traditional scientific applications, a systems thinking perspective can facilitate an enhanced understanding about RRI development and prevention.
•This study draws on the feedback from a range of subject matter experts to validate an existing prototype systems ergonomics model of the Australian distance running system.
•The validated model shows that multiple people and organisations ‘control’ and influence runners’ behaviours in relation to RRI risk.
•This study demonstrates that ‘faulty’ biomechanics and maladaptive running practices are not wholly responsible for the aetiology of RRI. Future research should continue to utilise a complex systems approach in this space.
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Introduction
There is a need for an ecological and complex systems approach for better understanding the development and prevention of running-related injury (RRI). In a previous article, we proposed a prototype model of the Australian recreational distance running system which was based on the Systems Theoretic Accident Mapping and Processes (STAMP) method. That model included the influence of political, organisational, managerial, and sociocultural determinants alongside individual-level factors in relation to RRI development. The purpose of this study was to validate that prototype model by drawing on the expertise of both systems thinking and distance running experts.

Materials and methods
This study used a modified Delphi technique involving a series of online surveys (December 2016- March 2017). The initial survey was divided into four sections containing a total of seven questions pertaining to different features associated with the prototype model. Consensus in opinion about the validity of the prototype model was reached when the number of experts who agreed or disagreed with survey statement was ≥75% of the total number of respondents.

Results
A total of two Delphi rounds was needed to validate the prototype model. Out of a total of 51 experts who were initially contacted, 50.9% (n = 26) completed the first round of the Delphi, and 92.3% (n = 24) of those in the first round participated in the second. Most of the 24 full participants considered themselves to be a running expert (66.7%), and approximately a third indicated their expertise as a systems thinker (33.3%). After the second round, 91.7% of the experts agreed that the prototype model was a valid description of the Australian distance running system.

Conclusion
This is the first study to formally examine the development and prevention of RRI from an ecological and complex systems perspective. The validated model of the Australian distance running system facilitates theoretical advancement in terms of identifying practical system-wide opportunities for the implementation of sustainable RRI prevention interventions. This ‘big picture’ perspective represents the first step required when thinking about the range of contributory causal factors that affect other system elements, as well as runners' behaviours in relation to RRI risk.
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Craig Payne · Aug 5, 2017

Cool! I was part of the delphi group for this one. massive project.

NewsBot · Jul 13, 2018

Modeling Overuse Injuries in Sport as a Mechanical Fatigue Phenomenon
Brent Edwards, W.
Exercise and Sport Sciences Reviews: July 11, 2018 - Volume Publish Ahead of Print - Issue - p

This paper postulates that overuse injury in sport is a biomechanical event resulting from the mechanical fatigue of biological tissue. A theoretical foundation and operational framework necessary to model overuse injury as a mechanical fatigue phenomenon is introduced. Adopting this framework may provide a more mechanistic understanding of overuse injury, and inform training and preventive strategies to reduce their occurrence.
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NewsBot · Oct 20, 2019

A conceptual model and detailed framework for stress-related, strain-related, and overuse athletic injury
Judd Kalkhoven Mark Watsford Franco Impellizzeri
Source

A multitude of athletic injuries occur when the various tissues that make up the human body experience stresses and strains that exceed their material strength. The precise amount of stress and strain that any given tissue can withstand is determined by the mechanical properties and resultant strength of that particular tissue. These mechanical properties are directly determined by an individual’s physiology and acute regulation of these properties. A number of theoretical frameworks for athletic injury occurrence have been proposed, however, a detailed conceptual framework for injury aetiology that considers the interplay between the physiological and mechanical factors and outlines the causal pathways to injury is needed. This will guide injury research towards a more thorough investigation of causal mechanisms and understanding of risk factors. Further, it is important to take into account the considerable differences in loading patterns which can result in varying injury outcomes such as acute stress-related, strain-related, or overuse injury. Within this article a simplified conceptual model of athletic injury is proposed along with a detailed, evidence-informed, conceptual framework for athletic injury aetiology that focuses on stress-related, strain-related, and overuse injury.
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NewsBot · Nov 19, 2019

Sports Injury Prevention is Complex: We Need to Invest in Better Processes, Not Singular Solutions
Jason C. TeeShaun J. McLarenBen Jones
18 November 2019

In recent years, an understanding has developed that sports injuries are the emergent outcomes of complex, dynamic systems. Thus, the influence of local contextual factors on injury outcomes is increasingly being acknowledged. These realisations place injury prevention research at a crossroads. Currently, injury prevention researchers develop universally applicable injury prevention solutions, but the adoption of these solutions in practice is low. This occurs because implementation contexts are both unique and dynamic in nature, and as a result singular, static solutions are often incompatible. In contrast, practitioners address injury prevention through iterative cycles of trial and error, aiming to optimise the injury prevention process within their own unique contexts. The purpose of this critical review is to draw attention to the misalignment between research and practice-based approaches to injury prevention. In light of this, we propose alternative research approaches that acknowledge the process-driven nature of injury prevention in practice. We propose that a core focus of sport injury prevention research should be to provide practitioners with useful and relevant information to support their decision making around their localised injury prevention practice. Through this approach, injury prevention research ceases to be about what works, and begins to engage with understanding what works in what contexts and why?
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NewsBot · Feb 14, 2020

A conceptual model and detailed framework for stress-related, strain-related, and overuse athletic injury
Judd T. Kalkhoven et al
Source

A multitude of athletic injuries occur when the various tissues that make up the human body experience stresses and strains that exceed their material strength. The precise amount of stress and strain that any given tissue can withstand is determined by the mechanical properties and resultant strength of that particular tissue. These mechanical properties are directly determined by an individual’s physiology and acute regulation of these properties. A number of theoretical frameworks for athletic injury occurrence have been proposed, however, a detailed conceptual framework for injury aetiology that considers the interplay between the physiological and mechanical factors and outlines the causal pathways to tissue damage and injury is needed. This will guide injury research towards a more thorough investigation of causal mechanisms and understanding of risk factors. Further, it is important to take into account the considerable differences in loading patterns which can result in varying injury outcomes such as acute stress-related, strain-related, or overuse injury. Within this article a simplified conceptual model of athletic injury is proposed along with a detailed, evidence-informed, conceptual framework for athletic injury aetiology that focuses on stress-related, strain-related, and overuse injury.
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NewsBot · Aug 7, 2020

Sports Injury Forecasting and Complexity: A Synergetic Approach
Sergio T. Fonseca, Thales R. Souza, Evert Verhagen, Richard van Emmerik, Natalia F. N. Bittencourt, Luciana D. M. Mendonça, André G. P. Andrade, Renan A. Resende & Juliana M. Ocarino
Sports Medicine (2020)

The understanding that sports injury is the result of the interaction among many factors and that specific profiles could increase the risk of the occurrence of a given injury was a significant step in establishing programs for injury prevention. However, injury forecasting is far from being attained. To be able to estimate future states of a complex system (forecasting), it is necessary to understand its nature and comply with the methods usually used to analyze such a system. In this sense, sports injury forecasting must implement the concepts and tools used to study the behavior of self-organizing systems, since it is by self-organizing that systems (i.e., athletes) evolve and adapt (or not) to a constantly changing environment. Instead of concentrating on the identification of factors related to the injury occurrence (i.e., risk factors), a complex systems approach looks for the high-order variables (order parameters) that describe the macroscopic dynamic behavior of the athlete. The time evolution of this order parameter informs on the state of the athlete and may warn about upcoming events, such as injury. In this article, we describe the fundamental concepts related to complexity based on physical principles of self-organization and the consequence of accepting sports injury as a complex phenomenon. In the end, we will present the four steps necessary to formulate a synergetics approach based on self-organization and phase transition to sports injuries. Future studies based on this experimental paradigm may help sports professionals to forecast sports injuries occurrence.
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NewsBot · Jan 27, 2021

State Dependence: Does a Prior Injury Predict a Future Injury?
Benjamin D.SternPT et al
Physical Therapy in Sport; 27 January 2021

Highlights
•Relationships between variables in nonlinear systems are not constant and as the state of the system changes, the effects of the variables on that system and each other also change.
•Depending on the time period we capture, a factor can have different and sometimes opposite effects, helpful and harmful, on a system that is state dependent like the human athlete.
•Variables and relationships that play a role in injury risk may be overlooked by not considering state-dependence.
•By nudging one factor in a state dependent system we can change relationships between other factors.
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The sports medicine literature is filled with associations between injury and causal factors. However, those results have been inconsistent. We’re left wondering which of our athletes might need more attention and where our efforts might be best spent? Resistance to injury is the result of interaction between many variables. These variables are interdependent with dynamic relationships which can be sometimes correlated, at times anti-correlated and from time to time show no relationship with injury risk. Relationships we may have seen yesterday do not necessarily hold true for today and we should not use those to infer what will happen. This perspective piece builds on prior works and explain how the complex interaction of injury determinants presents in other systems, why determinants are not stable and instead vary over time due to internal and external forcing and why our prediction ability remains limited even when determinants are identified. Patterns built from frequent time series data in conjunction with nonlinear dynamical methods can offer us a new approach to thinking about injury prediction.
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NewsBot · Feb 24, 2022

Characteristics of Complex Systems in Sports Injury Rehabilitation: Examples and Implications for Practice
Kate K. Yung, Clare L. Ardern, Fabio R. Serpiello & Sam Robertson
Sports Medicine - Open volume 8, Article number: 24 (2022)

Complex systems are open systems consisting of many components that can interact among themselves and the environment. New forms of behaviours and patterns often emerge as a result. There is a growing recognition that most sporting environments are complex adaptive systems. This acknowledgement extends to sports injury and is reflected in the individual responses of athletes to both injury and rehabilitation protocols. Consequently, practitioners involved in return to sport decision making (RTS) are encouraged to view return to sport decisions through the complex systems lens to improve decision-making in rehabilitation. It is important to clarify the characteristics of this theoretical framework and provide concrete examples to which practitioners can easily relate. This review builds on previous literature by providing an overview of the hallmark features of complex systems and their relevance to RTS research and daily practice. An example of how characteristics of complex systems are exhibited is provided through a case of anterior cruciate ligament injury rehabilitation. Alternative forms of scientific inquiry, such as the use of computational and simulation-based techniques, are also discussed—to move the complex systems approach from the theoretical to the practical level.

Key Points
Complex systems have distinct properties, such as nonlinearity, emergence and adaptation. Sixteen features of complex systems have been identified in sports injury rehabilitation.

Rehabilitation practitioners may connect complex systems theory with their operations in the sports setting.
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NewsBot · Nov 2, 2023

The Effects of Exercise-Based Injury Prevention Programmes on Injury Risk in Adult Recreational Athletes: A Systematic Review and Meta-Analysis
Nathan Liddle, Jonathan M. Taylor, Paul Chesterton & Greg Atkinson
Sports Medicine (2023)

Background
Injuries are common in adult recreational athletes. Exercise-based injury prevention programmes offer the potential to reduce the risk of injury and have been a popular research topic. Yet, syntheses and meta-analyses on the effects of exercise-based injury prevention programmes for adult recreational athletes are lacking.

Objectives
We aimed to synthesise and quantify the pooled intervention effects of exercise-based injury prevention programmes delivered to adults who participate in recreation sports.

Methods
Studies were eligible for inclusion if they included adult recreational athletes (aged > 16 years), an exercise-based intervention and used a randomised controlled trial design. Exclusion criteria were studies without a control group, studies using a non-randomised design and studies including participants who were undertaking activity mandatory for their occupation. Eleven literature databases were searched from earliest record, up to 9 June, 2022. The Physiotherapy Evidence Database (PEDro) scale was used to assess the risk of bias in all included studies. Reported risk statistics were synthesised in a random-effects meta-analysis to quantify pooled treatment effects and associated 95% confidence intervals and prediction intervals.

Results
Sixteen studies met the criteria. Risk statistics were reported as risk ratios [RRs] (n = 12) or hazard ratios [HRs] (n = 4). Pooled estimates of RRs and HRs were 0.94 (95% confidence interval 0.80–1.09) and 0.65 (95% confidence interval 0.39–1.08), respectively. Prediction intervals were 0.80–1.09 and 0.16–2.70 for RR and HR, respectively. Heterogeneity was very low for RR studies, but high for HR studies (tau = 0.29, I2 = 81%). There was evidence of small study effects for RR studies, evidenced by funnel plot asymmetry and Egger’s test for small study bias: − 0.99 (CI − 2.08 to 0.10, p = 0.07).

Conclusions
Pooled point estimates were suggestive of a reduced risk of injury in intervention groups. Nevertheless, these risk estimates were insufficiently precise, too heterogeneous and potentially compromised by small study effects to arrive at any robust conclusion. More large-scale studies are required to clarify whether exercise-based injury prevention programmes are effective in adult recreational athletes.
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