Many model thinking in systems ergonomics: a case study in road safety

The Chartered Institute of Ergonomics and Human Factors at 75: perspectives on contemporary challenges and future directions for Ergonomics and Human Factors

As the UK's Chartered Institute of Ergonomics and Human Factors (CIEHF) celebrates its 75th anniversary, it is worth reflecting on our discipline's contribution, current state, and critical future endeavours. We present the perspectives of 18 EHF professionals who were asked to respond to five questions regarding the impact of EHF, contemporary challenges, and future directions. Co-authors were in agreement that EHF's impact has been only limited to date and that critical issues require resolution, such as increasing the number of suitably qualified practitioners, resolving the research-practice gap, and increasing awareness of EHF and its benefits. Frequently discussed future directions include advanced emerging technologies such as artificial intelligence, the development of new EHF methods, and enhancing the quality and reach of education and training. The majority felt there will be a need for EHF in 75 years; however, many noted that our methods will need to adapt to meet new needs.Practitioner statement: This article provides the perspectives of 18 Ergonomics and Human Factors (EHF) professionals on the impact of EHF, contemporary challenges and critical future directions, and changes that are necessary to ensure EHF remains relevant in future. As such, it provides important guidance on future EHF research and practice.

Contextual design requirements for decision-support tools involved in weaning patients from mechanical ventilation in intensive care units

Weaning patients from ventilation in intensive care units (ICU) is a complex task. There is a growing desire to build decision-support tools to help clinicians during this process, especially those employing Artificial Intelligence (AI). However, tools built for this purpose should fit within and ideally improve the current work environment, to ensure they can successfully integrate into clinical practice. To do so, it is important to identify areas where decision-support tools may aid clinicians, and associated design requirements for such tools. This study analysed the work context surrounding the weaning process from mechanical ventilation in ICU environments, via cognitive task and work domain analyses. In doing so, both what cognitive processes clinicians perform during weaning, and the constraints and affordances of the work environment itself, were described. This study found a number of weaning process tasks where decision-support tools may prove beneficial, and from these a set of contextual design requirements were created. This work benefits researchers interested in creating human-centred decision-support tools for mechanical ventilation that are sensitive to the wider work system.

When tomorrow comes: A prospective risk assessment of a future artificial general intelligence-based uncrewed combat aerial vehicle system

There are concerns that Artificial General Intelligence (AGI) could pose an existential threat to humanity; however, as AGI does not yet exist it is difficult to prospectively identify risks and develop requisite controls. We applied the Work Domain Analysis Broken Nodes (WDA-BN) and Event Analysis of Systemic Teamwork-Broken Links (EAST-BL) methods to identify potential risks in a future 'envisioned world' AGI-based uncrewed combat aerial vehicle system. The findings suggest five main categories of risk in this context: sub-optimal performance risks, goal alignment risks, super-intelligence risks, over-control risks, and enfeeblement risks. Two of these categories, goal alignment risks and super-intelligence risks, have not previously been encountered or dealt with in conventional safety management systems. Whereas most of the identified sub-optimal performance risks can be managed through existing defence design lifecycle processes, we propose that work is required to develop controls to manage the other risks identified. These include controls on AGI developers, controls within the AGI itself, and broader sociotechnical system controls.

Enhancing prediction and analysis of UK road traffic accident severity using AI: Integration of machine learning, econometric techniques, and time series forecasting in public health research

This research project explored into the intricacies of road traffic accidents severity in the UK, employing a potent combination of machine learning algorithms, econometric techniques, and traditional statistical methods to analyse longitudinal historical data. Our robust analysis framework includes descriptive, inferential, bivariate, multivariate methodologies, correlation analysis: Pearson's and Spearman's Rank Correlation Coefficient, multiple logistic regression models, Multicollinearity Assessment, and Model Validation. In addressing heteroscedasticity or autocorrelation in error terms, we've advanced the precision and reliability of our regression analyses using the Generalized Method of Moments (GMM). Additionally, our application of the Vector Autoregressive (VAR) model and the Autoregressive Integrated Moving Average (ARIMA) models have enabled accurate time series forecasting. With this approach, we've achieved superior predictive accuracy and marked by a Mean Absolute Scaled Error (MASE) of 0.800 and a Mean Error (ME) of -73.80 compared to a naive forecast. The project further extends its machine learning application by creating a random forest classifier model with a precision of 73%, a recall of 78%, and an F1-score of 73%. Building on this, we employed the H2O AutoML process to optimize our model selection, resulting in an XGBoost model that exhibits exceptional predictive power as evidenced by an RMSE of 0.1761205782994506 and MAE of 0.0874235576229789. Factor Analysis was leveraged to identify underlying variables or factors that explain the pattern of correlations within a set of observed variables. Scoring history, a tool to observe the model's performance throughout the training process was incorporated to ensure the highest possible performance of our machine learning models. We also incorporated Explainable AI (XAI) techniques, utilizing the SHAP (Shapley Additive Explanations) model to comprehend the contributing factors to accident severity. Features such as Driver_Home_Area_Type, Longitude, Driver_IMD_Decile, Road_Type, Casualty_Home_Area_Type, and Casualty_IMD_Decile were identified as significant influencers. Our research contributes to the nuanced understanding of traffic accident severity and demonstrates the potential of advanced statistical, econometric, machine learning techniques in informing evidence based interventions and policies for enhancing road safety.

Managing the risks associated with technological disruption in the road transport system: a control structure modelling approach

Road transport is experiencing disruptive change from new first-of-a-kind technologies. While such technologies offer safety and operational benefits, they also pose new risks. It is critical to proactively identify risks during the design, development and testing of new technologies. The Systems Theoretic Accident Model and Processes (STAMP) method analyses the dynamic structure in place to manage safety risks. This study applied STAMP to develop a control structure model for emerging technologies in the Australian road transport system and identified control gaps. The control structure shows the actors responsible for managing risks associated with first-of-a-kind technologies and the existing control and feedback mechanisms. Gaps identified related to controls (e.g. legislation) and feedback mechanisms (e.g. monitoring for behavioural adaptation). The study provides an example of how STAMP can be used to identify control structure gaps requiring attention to support the safe introduction of new technologies.

Forecasting emergent risks in advanced AI systems: an analysis of a future road transport management system

Artificial Intelligence (AI) is being increasingly implemented within road transport systems worldwide. Next generation of AI, Artificial General Intelligence (AGI) is imminent, and is anticipated to be more powerful than current AI. AGI systems will have a broad range of abilities and be able to perform multiple cognitive tasks akin to humans that will likely produce many expected benefits, but also potential risks. This study applied the EAST Broken Links approach to forecast the functioning of an AGI system tasked with managing a road transport system and identify potential risks. In total, 363 risks were identified that could have adverse impacts on the stated goals of safety, efficiency, environmental sustainability, and economic performance of the road system. Further, risks beyond the stated goals were identified; removal from human control, mismanaging public relations, and self-preservation. A diverse set of systemic controls will be required when designing, implementing, and operating future advanced technologies.Practitioner summary: This study demonstrated the utility of HFE methods for formally considering risks associated with the design, implementation, and operation of future technologies. This study has implications for AGI research, design, and development to ensure safe and ethical AGI implementation.

From Anti-doping-I to Anti-doping-II: Toward a paradigm shift for doping prevention in sport

Doping remains an intractable issue in sport and occurs in a complex and dynamic environment comprising interactions between individual, situational, and environmental factors. Anti-doping efforts have previously predominantly focused on athlete behaviours and sophisticated detection methods, however, doping issues remain. As such, there is merit in exploring an alternative approach. The aim of this study was to apply a systems thinking approach to model the current anti-doping system for four football codes in Australia, using the Systems Theoretic Accident Model and Processes (STAMP). The STAMP control structure was developed and validated by eighteen subject matter experts across a five-phase validation process. Within the developed model, education was identified as a prominent approach anti-doping authorities use to combat doping. Further, the model suggests that a majority of existing controls are reactive, and hence that there is potential to employ leading indicators to proactively prevent doping and that new incident reporting systems could be developed to capture such information. It is our contention that anti-doping research and practice should consider a shift away from the current reactive and reductionist approach of detection and enforcement to a proactive and systemic approach focused on leading indicators. This will provide anti-doping agencies a new lens to look at doping in sport.

Incident reporting in the outdoors: a systems-based analysis of injury, illness, and psychosocial incidents in led outdoor activities in Australia

Incident reporting systems are a fundamental component of safety management, however, most systems used in practice are not aligned with contemporary accident causation models. This article presents an analysis of a National Incident Dataset (NID) for adverse incidents occurring in the Australian Led Outdoor Activity (LOA) sector. The aim was to investigate the adverse Injury, Illness, and Psychosocial incidents reported to the NID. In total, 1657 injuries, 532 illnesses, and 146 psychosocial incidents were analysed from 357,691 program participation days. The findings show that the rate of incidents per 1000 program participant days in LOAs was 4.6 for injury, 1.5 for illness, and 0.04 for psychosocial incidents, and incident severity was predominately minor. The analysis of systemic contributory factors demonstrates that incidents in LOA are systemic in nature, with multiple levels of the LOA system identified as contributing to adverse incidents. For example, contributory factors were identified across local government (facilities), schools (communication), parents (communication), LOA management (policies and procedures), people involved in the incidents (mental and physical condition), and the environment (terrain) and equipment (clothing). This study presents an assessment of the current state of safety in the Australian LOA sector and demonstrates the utility of applying systems ergonomics methods in practice. Practitioner summary: This article presents an analysis of 1657 injury, 532 illness, and 146 psychosocial incidents occurring in the Australian Led Outdoor Activity (LOA) sector, using a systems ergonomics method. The findings demonstrate the incident charactersitics and how decisions and actions from across the system contribute to adverse incidents in LOAs.

Taking a mixed-methods approach to collision investigation: AcciMap, STAMP-CAST and PCM

Recently, ergonomics and safety researchers have turned their attention towards applying combinations of sociotechnical methods rather than using single methods in isolation. In the current research, a mixed-method approach combining two systems-based methods, Accimaps and the Systems Theoretic Accident Model and Process - Causal Analysis using Systems Theory (STAMP-CAST), and one cognitive approach, the Perceptual Cycle Model (PCM), were employed in analysing a rail-level crossing incident in Bangladesh. Each method was applied individually to investigate the collision, and interventions were proposed corresponding to incident events at different risk management framework levels. The three methods provided different perspectives of the whole picture, together identifying an array of contributory factors. The complementary nature of these methods aided in proposing a comprehensive set of safety recommendations, thereby demonstrating the benefit of a mixed-method approach for collision investigation in low-income settings.

Utilising Human Crash Tolerance to Design an Interim and Ultimate Safe System for Road Safety

Many jurisdictions globally have adopted a zero road trauma target by 2050 and an interim target of a 50% reduction by 2030. The objective of this study was to investigate what the road system will need to look like in order to achieve these respective targets. Utilising human tolerance to injury as the key design factor, this study defined the combination of vehicle, infrastructure, and travel speed requirements to manage crash energy in order to: 1. prevent all fatalities and serious injuries by 2050 in an Ultimate Safe System scenario; and 2. significantly reduce fatalities and severe injuries by 2030 in an Interim Safe System scenario. Victoria, Australia and its Movement and Place (M&P) framework was employed as a case study. With the vehicle and infrastructure countermeasures currently available coupled with appropriate travel speeds it is possible to construct an Ultimate Safe System that can manage crash forces to achieve zero trauma and an Interim Safe System that can significantly reduce the most severe injuries in Victoria. This study has demonstrated a potential pathway from the current situation to 2030 and then 2050 that can achieve safety targets while meeting the core objectives of the transport system.

Fatal and Serious Injury Rates for Different Travel Modes in Victoria, Australia

While absolute injury numbers are widely used as a road safety indicator, they do not fully account for the likelihood of an injury given a certain level of exposure. Adjusting crash and injury rates for travel exposure can measure the magnitude of travel activity leading to crash outcomes and provide a more comprehensive indicator of safety. Fatal and serious injury (FSI) numbers were adjusted by three measures of travel exposure to estimate crash and injury rates across nine travel modes in the Australian state of Victoria. While car drivers accounted for the highest number of injuries across the three modes, their likelihood of being killed or seriously injured was substantially lower than that of motorcyclists across all exposure measures. Cyclists accounted for fewer injuries than car passengers and pedestrians but had a higher risk per exposure. The results varied by both injury severity and exposure measure. The results of this study will assist with high level transport planning by allowing for the investigation of the changes in travel-related FSI resulting from proposed travel mode shifts driven by safety, environmental reasons or other reasons as part of the holistic goal of transforming the transport system to full compliance with Safe System principles.

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.

The impact of power on health care team performance and patient safety: a review of the literature

Communication failure within health care teams is a major cause of patient harm across health care settings. Factors which contribute to communication failure include actual or perceived 'power'. Whilst a great deal of ergonomics research has focussed on teamwork in health care, the role of power in relation to measurable patient safety and performance outcomes remains relatively unknown. This article presents the findings from a review of the literature on power within multidisciplinary health care team settings. Following a systematic literature search, nineteen studies were evaluated in terms of research design, methods and analyses across the included studies. The main impacts resulting from power imbalances include negative effects on team collaboration, decision-making, communication and overall performance. Wider patient safety research, and more specifically the ergonomics discipline, is encouraged to address the complex interplay between power and teamwork in the health care sector.Practitioner Statement: We conducted a review of studies focussed on the influence of power on teamwork in health care. The findings show that power can have negative impacts on collaboration, decision-making, communication, and team performance. We conclude that power represents an important area for ergonomics, both in health care and other settings.Abbreviations: CRM: crew resource management; TEM: threat and error management; SNA: social network analysis; EAST: event analysis of systemic teamwork.

Complexity theory in accident causation: using AcciMap to identify the systems thinking tenets in 11 catastrophes

The quest to explain and understand the cause of accidents is both ever-present and ongoing amongst the safety science community. In an attempt to advance the theory and science of accident causation, researchers have recently formalised a set of '15 systems thinking tenets' that cover the conditions and characteristics of work systems that are believed to contribute to the cause of accidents. The purpose of this study was to attempt to identify the systems thinking tenets across a range of different systems and accidents using the Accident Mapping (AcciMap) method. The findings suggest that the tenets can be attributed to play a role in accident causation, however as a result of this process, the capability of AcciMap has been brought into question. Implications and directions for future research are described. Practitioner Summary: This study is an extension of previous work that suggested there was a need to test for the 'systems thinking tenets of accident causation' in a multi-incident dataset. We used AcciMap to evaluate whether it has the capability to support ongoing accident analysis activities in ergonomics research.

Resolving the differences between system development and system operation using STAMP: a road safety case study in a low-income setting

Road safety strategies adopted worldwide have made significant progress in reducing road trauma, but have stagnated more recently. The situation in low- and middle-income countries is even worse with no significant decrease in fatality rates. Safety researchers have argued that adopting sociotechnical systems approach is necessary to make significant advancements and improvements. The aim of this study was to develop a control structure model of the Bangladesh road safety system by identifying the actors and organisations involved across the system. Expert stakeholders were identified and interviewed, and relevant information was gathered in order to generate the Systems Theoretic Accident Model and Process control structure model. Throughout the analysis of this model, differences in the control and feedback mechanisms of the system were identified, and road safety intervention recommendations were made. Future research should also predict potential risks within the system and propose proactive and preventative countermeasures. Practitioner summary: In this article, a Systems Theoretic Accident Model and Process control structure model of the Bangladesh road safety system is developed, and the involved actors are identified. Based on interviews and workshops with expert stakeholders, differences in the controls and feedback mechanisms in the system were identified, and road safety intervention recommendations were made. Abbreviations: BUET: Bangladesh University of Engineering and Technology.

Human Factors and Ergonomics and the management of existential threats: A work domain analysis of a COVID-19 return from lockdown restrictions system

Following strict "lockdown" restrictions designed to control the spread of the COVID-19 virus, many jurisdictions are now engaged in a process of easing restrictions in an attempt to stimulate economic and social activity while continuing to suppress virus transmission. This is challenging and complex, and in several regions, new outbreaks have emerged. We argue that systems Human Factors and Ergonomics methods can assist in understanding and optimizing the return from lockdown. To demonstrate, we used work domain analysis to develop an abstraction hierarchy model of a generic "return from lockdown restrictions" system. The model was assessed to identify (a) issues preventing a successful return from lockdown; and (b) leverage points that could be exploited to optimize future processes. The findings show that the aim of continuing to suppress virus transmission conflicts with the aims of returning to pre-virus economic and social activity levels. As a result, many functions act against each other, ensuring that the system cannot optimally achieve all three of its primary aims. Potential leverage points include modifying the goals and rules of the system and enhancing communications and feedback. Specifically, it is argued that moderating economic aims and modifying how social and community activities are undertaken will result in longer term suppression of the virus.

Healthcare workers' perspectives on participatory system dynamics modelling and simulation: designing safe and efficient hospital pharmacy dispensing systems together

With increasingly complex safety-critical systems like healthcare being developed and managed, there is a need for a tool that permits decision-makers to better understand the complexity, test various strategies and guide effective changes. System Dynamics (SD) modelling is an effective approach that can aid strategic decision-making in healthcare systems but has been underutilised partly due to the challenge of engaging healthcare stakeholders in the modelling process. This paper, therefore, investigates the applicability of a participatory SD approach based on healthcare workers' perspectives on ease of use (usability) and usefulness (utility). The study developed an interactive simulation dashboard platform which facilitated participatory simulation for exploring various hospital pharmacy staffing level arrangements and their impacts on interruptions, fatigue, workload, rework, productivity and safety. The findings reveal that participatory SD approach can enhance team learning by converging on a shared mental model, aid decision-making and identifying trade-offs. The implications of these findings are discussed as well as experience and lessons learned on modelling facilitation. Practitioner Summary: This paper reports the perspectives of healthcare workers, who were engaged with a participatory system dynamics modelling and simulation process for hospital pharmacy staffing level management. Evaluative feedback revealed that the participatory SD approach can be a valuable tool for participatory ergonomics by helping the participants gain a deeper understanding of the complex dynamic interactions between workload, rework, safety and efficiency. Abbreviations: SD: system dynamics; ETTO: efficiency-thoroughness trade-off.

Computational modelling and systems ergonomics: a system dynamics model of drink driving-related trauma prevention

System dynamics is a computational modelling method that is used to understand the dynamic interactions influencing behaviour in complex systems. In this article we argue that the method provides a useful tool for ergonomists wishing to model the behaviour of complex systems. We present a system dynamics model that simulates the behaviour of a drink driving-related trauma system and explore the potential impact of different road safety policy interventions. The model was simulated over thirty-year periods with different policy interventions. The findings suggest that the greatest reduction in drink driving-related trauma can be achieved by policies that integrate standard road safety interventions (e.g. education and enforcement) with interventions designed to address the societal issue of alcohol misuse and addiction. In closing we discuss the potential use of system dynamics modelling in future ergonomics applications and outline its strengths and weaknesses in relation to existing systems ergonomics methods. Practitioner Summary: The outputs of systems ergonomics methods are typically static and cannot simulate behaviour over time. We propose system dynamics as a useful approach for modelling the behaviour of complex systems. Applied to drink driving-related road trauma, the method was able to dynamically model the potential impacts of different policy interventions.

Ergonomists as designers: computational modelling and simulation of complex socio-technical systems

Contemporary ergonomics problems are increasing in scale, ambition, and complexity. Understanding and creating solutions for these multi-faceted, dynamic, and systemic problems challenges traditional methods. Computational modelling approaches can help address this methodological shortfall. We illustrate this potential by describing applications of computational modelling to: (1) teamworking within a multi-team engineering environment; (2) crowd behaviour in different transport terminals; and (3) performance of engineering supply chains. Our examples highlight the benefits and challenges for multi-disciplinary approaches to computational modelling, demonstrating the need for socio-technical design principles. Our experience highlights opportunities for ergonomists as designers and users of computational models, and the instrumental role that ergonomics can play in developing and enhancing complex socio-technical systems. Recognising the challenges inherent in designing computational models, we reflect on practical issues and lessons learned so that computational modelling and simulation can become a standard and valuable technique in the ergonomists' toolkit. Practitioner summary: This paper argues that computational modelling and simulation is currently underutilised in ergonomics research and practice. Through example applications illustrating the benefits, limitations, and opportunities of such approaches, this paper is a point of reference for researchers and practitioners using computational modelling to explore complex socio-technical systems.

The perils of perfect performance; considering the effects of introducing autonomous vehicles on rates of car vs cyclist conflict

How humans will adapt and respond to the introduction of autonomous vehicles (AVs) is uncertain. This study used an agent-based model to explore how AVs, human-operated vehicles, and cyclists might interact based on the introduction of flawlessly performing AVs. Under two separate experimental conditions, results of experiment 1 showed that, despite no conflicts occurring between cyclists and AVs, modelled conflicts among human-operated cars and cyclists increased with the introduction of AVs due to cyclists' adjusted expectations of the behaviour and capability of human-operated and autonomous cars. Similarly, when human-operated cars were replaced with AVs over time in experiment 2, cyclist conflict rates did not follow a linear reduction consistent with the replacement rate but decreased more slowly in the early stages of replacement before 50% substitution. It is concluded that, although flawlessly performing AVs might reduce total conflicts, the introduction of AVs into a transport system where humans adjust to the behaviour and risk presented by AVs could create new sources of error that offset some of AVs assumed safety benefits. Practitioner summary: Ergonomics is an applied science that studies interactions between humans and other elements of a system, including non-human agents. Agent-Based Modelling (ABM) provides an approach for exploring dynamic and emergent interactions between agents. In this article, we demonstrate ABM through an analysis of how cyclists and pedestrians might interact with Autonomous Vehicles (AVs) in future road transport systems. Abbreviations: ABM: agent-based model; AV: autonomous vehicle; ODD; overview, design concepts and details; RW: rescorla-wagner.

Who is to blame for crashes involving autonomous vehicles? Exploring blame attribution across the road transport system

The introduction of fully autonomous vehicles is approaching. This warrants a re-consideration of road crash liability, given drivers will have diminished control. This study, underpinned by attribution theory, investigated blame attribution to different road transport system actors following crashes involving manually driven, semi-autonomous and fully autonomous vehicles. It also examined whether outcome severity alters blame ratings. 396 participants attributed blame to five actors (vehicle driver/user, pedestrian, vehicle, manufacturer, government) in vehicle-pedestrian crash scenarios. Different and unique patterns of blame were found across actors, according to the three vehicle types. In crashes involving fully autonomous vehicles, vehicle users received low blame, while vehicle manufacturers and government were highly blamed. There was no difference in the level of blame attributed between high and low severity crashes regarding vehicle type. However, the government received more blame in high severity crashes. The findings have implications for policy and legislation surrounding crash liability. Practitioner summary: Public views relating to blame and liability in transport accidents is a vital consideration for the introduction of new technologies such as autonomous vehicles. This study demonstrates how a systems ergonomics framework can assist to identify the implications of changing public opinion on blame for future road transport systems. Abbreviation: ANOVA: analysis of variance; DAT: defensive attribution theory; IV: independent variable.

Integrating complex systems science into road safety research and practice, part 1: review of formative concepts

Many of our most persistent public health problems are complex problems. They arise from a web of factors that interact and change over time and may exhibit resistance to intervention efforts. The domain of systems science provides several tools to help injury prevention researchers and practitioners examine deep, complex and persistent problems and identify opportunities to intervene. Using the increase in pedestrian death rates as an example, we provide (1) an accessible overview of how complex systems science approaches can augment established injury prevention frameworks and (2) a straightforward example of how specific systems science tools can deepen understanding, with a goal of ultimately informing action.

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.