Characteristics of Complex Systems in Sports Injury Rehabilitation: Examples and Implications for Practice
Yung, Kate K ORCID: 0000-0003-1906-4111, Ardern, Clare L ORCID: 0000-0001-8102-3631, Serpiello, Fabio ORCID: 0000-0001-8919-3053 and Robertson, Samuel ORCID: 0000-0002-8330-0011 (2022) Characteristics of Complex Systems in Sports Injury Rehabilitation: Examples and Implications for Practice. Sports Medicine - Open, 8. ISSN 2199-1170
Abstract
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.
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Item type | Article |
URI | https://vuir.vu.edu.au/id/eprint/45080 |
DOI | 10.1186/s40798-021-00405-8 |
Official URL | https://sportsmedicine-open.springeropen.com/artic... |
Subjects | Current > FOR (2020) Classification > 4207 Sports science and exercise Current > Division/Research > Institute for Health and Sport |
Keywords | complexity, return to sport, return to play, decision making, machine learning, Bayesian network |
Citations in Scopus | 10 - View on Scopus |
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