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.
A history of previous injury was associated with an increased risk of both general and specific RRI. The use of oral contraceptives was found to be associated with a decreased risk of skeletal stress fracture. Conversely, irregular and/or absent menstruation was associated with an increased risk. The varied effect directions and/or a number of statistically insignificant results associated with the majority of factors hindered our ability to draw any definitive conclusions about their relationship to RRI risk.
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.
Introduction: This systemic review examines and reports on peer reviewed studies that have applied systems thinking accident analysis methods to better understand the cause of accidents in a diverse range of sociotechnical systems contexts.Methods: Four databases (PubMed, ScienceDirect, Scopus, Web of Science) were searched for published articles during the dates 01 January 1990 to 31 July 2018, inclusive, for original peer reviewed journal articles. Eligible studies applied AcciMap, the Human Factors Analysis and Classification System (HFACS), the Systems Theoretic Accident Model and Processes (STAMP) method, including Causal Analysis based on STAMP (CAST), and the Functional Resonance Analysis Method (FRAM). Outcomes included accidents ranging from major events to minor incidents.Results: A total of 73 articles were included. There were 20, 43, six, and four studies in the Accimap, HFACS, STAMP-CAST, and FRAM methods categories, respectively. The most popular accident contexts were aviation, maritime, rail, public health, and mining. A greater number of contributory factors were found at the lower end of the sociotechnical systems analysed, including the equipment/technology, human/staff, and operating processes levels. A majority of studies used supplementary approaches to enhance the analytical capacity of base applications.Conclusions: Systems thinking accident analysis methods have been popular for close to two decades and have been applied in a diverse range of sociotechnical systems contexts. A number of researchbased recommendations are proposed, including the need to upgrade incident reporting systems and further explore opportunities around the development of novel accident analysis approaches.
Netball is a newly professional women’s sport, as such there has been little research conducted investigating performance analysis (PA) in elite netball. The aim of this study was to develop a model of the elite netball performance system to identify the complex relationships among key performance indicators. Eleven elite subject matter experts (SMEs) participated in workshops to produce a systems model of the netball match performance. The model was developed using the work domain analysis (WDA) method. A model of the netball match performance system was produced showing the interrelated objects, processes, functions, values, and purposes involved in elite level netball matches. The model identified the components of elite level netball performance and the interactions and relationships between them. The output of this research has identified novel PA measures including passing and possession measures, measures of cognitive performance, and measures related to physical activity. Netball is a complex sport, involving multiple dynamic and interrelated components. Consequently, there is an opportunity to develop holistic PA measures that focus on interacting components, as opposed to components in isolation.
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