Computational methods to model complex systems in sports injury research: agent-based modelling (ABM) and systems dynamics (SD) modelling

Using systems thinking-based risk assessment methods to assess hazardous manual tasks: a comparison of Net-HARMS, EAST-BL, FRAM and STPA

Formal risk assessment is a component of safety management relating to hazardous manual tasks (HMT). Systems thinking approaches are currently gaining interest for supporting safety management. Existing HMT risk assessment methods have been found to be limited in their ability to identify risks across the whole work system; however, systems thinking-based risk assessment (STBRA) methods were not designed for the HMT context and have not been tested in this area. The aim of this study was to compare the performance of four state-of-the-art STBRA methods: Net-HARMS, EAST-BL, FRAM and STPA to determine which would be most useful for identifying HMT risks. Each method was independently applied by one of four analysts to assess the risks associated with a hypothetical HMT system. The outcomes were assessed for alignment with a benchmark analysis. Using signal detection theory (SDT), overall STPA was found to be the best performing method having the highest hit rate, second lowest false alarm rate and highest Matthews Correlation Coefficient of the four methods.Practitioner summary: A comparison of four systems thinking risk assessment methods found that STPA had the highest level of agreement with the benchmark analysis and is the most suitable for practitioners to use to identify the risks associated with HMT systems.

Cost-benefit analysis of construction waste source reduction: a system dynamics approach

Construction waste (CW) source reduction is a crucial strategy to address the sustainability issue of the construction industry. The economic benefit is a key factor affecting project decision-makers on whether to implement this strategy. However, limited studies analysed the cost-benefit of CW source reduction from a system dynamic perspective. Therefore, by considering the design and construction phase as a whole, this study constructed a system dynamics (SD) model based on the identification of the factors affecting the cost-benefit of CW source reduction to analyse the cost-benefit of CW source reduction. A residential building project in China's Chengdu was used for the study case. The results show that the net benefit of CW source reduction is positive, and BIM implementation, design for standard material size, and building material storage are the three strategies to effectively improve the economic benefits of CW source reduction. Furthermore, the best investment level of CW source reduction was also determined. This study provides a model which can be used to simulate the cost-benefit under different implementation levels of reduction strategies and different investment levels in advance, thereby providing a reference for project decision-makers to plan CW source reduction.

The need for a complex systems approach in rural health research

On a global scale, many major rural health issues have persisted for decades despite the introduction of new health interventions and public health policies. Although research efforts have generated valuable new knowledge about the aetiology of health, disease and health inequities in rural communities, rural health systems remain to be some of the most deprived and challenged in both the developing and developed world. While the reasons for this are many, a significant factor contributing to the current state of play is the pressing need for methodological innovation and relevant scientific approaches that have the capacity to support the translation of novel solutions into 'real world' rural contexts. Fortunately, complex systems approaches, which have seen an increase in popularity in the wider public health literature, could provide answers to some of the most resilient rural health problems in recent times. The purpose of this article is to promote the value and utility of a complex systems approach in rural health research. We explain the benefits of a complex systems approach and provide a background to the complexity sciences, including the main characteristics of complex systems. Two popular computational methods are described. The next step for rural health research involves exploring how a complex systems approach can help with the identification and evaluation of new and existing solutions to policy-resistant rural health issues. This includes generating awareness around the analytical trade-offs that occur between the use of traditional scientific methods and complex systems approaches.

Scar formation from the perspective of complexity science: a new look at the biological system as a whole

A burn wound is a complex systemic disease at multiple levels. Current knowledge of scar formation after burn injury has come from traditional biological and clinical studies. These are normally focused on just a small part of the entire process, which has limited our ability to sufficiently understand the underlying mechanisms and to predict systems behaviour. Scar formation after burn injury is a result of a complex biological system-wound healing. It is a part of a larger whole. In this self-organising system, many components form networks of interactions with each other. These networks of interactions are typically non-linear and change their states dynamically, responding to the environment and showing emergent long-term behaviour. How molecular and cellular data relate to clinical phenomena, especially regarding effective therapies of burn wounds to achieve minimal scarring, is difficult to unravel and comprehend. Complexity science can help bridge this gap by integrating small parts into a larger whole, such that relevant biological mechanisms and data are combined in a computational model to better understand the complexity of the entire biological system. A better understanding of the complex biological system of post-burn scar formation could bring research and treatment regimens to the next level. The aim of this review/position paper is to create more awareness of complexity in scar formation after burn injury by describing the basic principles of complexity science and its potential for burn care professionals.

A Systems Analysis Critique of Sport-Science Research

PURPOSE

The broad aim of sport-science research is to enhance the performance of coaches and athletes. Despite decades of such research, it is well documented that sport-science research lacks empirical evidence, and critics have questioned its scientific methods. Moreover, many have pointed to a research-practice gap, whereby the work undertaken by researchers is not readily applied by practitioners. The aim of this study was to use a systems thinking analysis method, causal loop diagrams, to understand the systemic issues that interact to influence the quality of sport-science research.

METHODS

A group model-building process was utilized to develop the causal loop diagram based on data obtained from relevant peer-reviewed literature and subject-matter experts.

RESULTS

The findings demonstrate the panoply of systemic influences associated with sport-science research, including the existence of silos, a focus on quantitative research, archaic practices, and an academic system that is incongruous with what it actually purports to achieve.

CONCLUSIONS

The emergent outcome of the interacting components is the creation of an underperforming sport-science research system, as indicated by a lack of ecological validity, translation to practice, and, ultimately, a research-practice gap.

Sports Injury Forecasting and Complexity: A Synergetic Approach

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.

Does an Optimal Relationship Between Injury Risk and Workload Represented by the "Sweet Spot" Really Exist? An Example From Elite French Soccer Players and Pentathletes

Objective

To examine the relationships between the occurrence and severity of injuries using three workload ratios (ACWR, EWMA, REDI) in elite female soccer players and international male and female pentathletes.

Materials and Methods

Female soccer players in the U16 to U18 national French teams (n = 24) and international athletes (n = 12, 4 women and 8 men) in the French modern pentathlon team were monitored throughout an entire season. The Acute Chronic Workload Ratio (ACWR), the Exponentially Weighted Moving Averages (EWMA), and the Robust Exponential Decreasing Index (REDI) were calculated for internal load by the ROE method in soccer and external load in pentathlon. The occurrence and severity of injuries (determined according to time-loss) were quantified in the sweet spot zone [0.8; 1.3] and compared to the other zones of load variation: [0; 0.8], [1.3; 1.5], [1.5; +8], using the three ratios.

Results

Over the study period, a total of sixty-six injuries (2.75 per athlete) were reported in the soccer players and twelve in pentathletes (1 per athlete). The cumulative severity of all injuries was 788 days lost in soccer and 36 in pentathlon: respectively, 11.9 days lost per injury in soccer player and 3.0 per pentathlete. The mean values across the three methods in soccer showed a higher number of injuries detected in the [0; 0.8] workload ratio zone: 22.3 ± 6.4. They were 17.3 ± 3.5 in the sweet spot ([0.8-1.3] zone) and 17.6 ± 5.5 in the [1.5; +8] zone. In comparison to the [1.5; +8] zone, soccer players reported a higher number of days lost to injuries in the presumed sweet spot and in the [0-0.8] zone: 204.7 ± 28.7 and 275.0 ± 120.7 days, respectively. In pentathletes, ten of the twelve injuries (83.3%) occurred in the presumed sweet spot. REDI was the only method capable of tracking workloads over all-time series.

Conclusion

In the present cohort of elite soccer players and pentathletes, acute chronic workload calculations showed an association with injury occurrence and severity but did not provide evidence supporting existence of a sweet spot diminishing injury risk.

Beyond the Tip of the Iceberg: Using Systems Archetypes to Understand Common and Recurring Issues in Sports Coaching

Background: Systems thinking, a fundamental approach for understanding complexity, is beginning to gain traction in sports science. Systems archetypes (SAs) describe common recurring patterns of system behaviors and have been used extensively in other domains to explain the system wide influences on behavior. SAs look at the deeper levels of systemic structure by identifying what creates system behaviors, which supports the development of interventions to identify and resolve problem sources. Methods: Four commonly used SAs were used to explain the dynamics underpinning recurring issues for coaching in football: (1) Fixes that fail, (2) Shifting the burden, (3) Drifting goals, and (4) Success to the successful. The SAs models were built, refined and validated by seven subject matter experts (SMEs) including experienced football researchers, systems thinking experts, an international football coach, a skill acquisition specialist, and an experienced exercise scientist. Results: The findings show that the SAs fit well in the football coaching context, providing further evidence that a complex system thinking approach is required when considering football performance and its optimization. The developed SAs identify the factors that play a role in recurring issues in football coaching and highlight the systemic structures that contribute to the issues. The developed SAs identify the appropriate leverage points in the system where sustainable change can be made to improve coaching practice and subsequent performance of players. Discussion: A common theme emerging across the analyses was that systemic problems often arise in football when quick fixes are attempted. Whereas, improvements to system behavior usually require a delay after the implementation of the appropriate corrective action. The SAs developed in the current study also provide practical templates of common problems in football that can be used to prompt discussions around how to avoid ineffective interventions and instead make sustainable improvements across multiple aspects of football performance.