ReviewSports medicine (Auckland, N.Z.)2020
Sports Injury Forecasting and Complexity: A Synergetic Approach.
Review in Sports medicine (Auckland, N.Z.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05430581 (Prediction of Knee Injuries Through System Dynamics Modeling), which is not on this map. Cited by 33 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Prediction of Knee Injuries Through System Dynamics Modeling
Who cites it
33 citing papers in PubMed.
- Universal prevention through a digital health platform reduces injury incidence in youth athletics (track and field): a cluster randomised controlled trial.British journal of sports medicine · 2023Trial
- When evidence fails in real life: Rethinking sports injury rehabilitation and prevention.Brazilian journal of physical therapy · 2026Review
- Application of Artificial Intelligence for Predicting Sports Injuries and Customizing Personalized Prevention Strategies: A Scoping Review.Bioengineering (Basel, Switzerland) · 2026Review
- Development and validation of a machine learning model for non-contact injury prediction based on lower limb strength asymmetry in professional football.Scientific reports · 2026Article
- Multifactorial background of acute sports injuries in young Japanese athletes-a semi-structured interview study.Frontiers in sports and active living · 2026Article
- Time-variability of muscle oxygen saturation during graded maximal exercise.European journal of applied physiology · 2026Article
- Interdependent Effect of Intrinsic Risk Factors on Non-Contact Lower Limb Injuries in Male Football Players: A Structural Equation Modeling Approach.Medicina (Kaunas, Lithuania) · 2025Article
- A Field-Based Screening Protocol for Hamstring Injury Risk in Football Players: Evaluating Its Functionality Using Exploratory Factor Analysis.Sports (Basel, Switzerland) · 2025Article
- Knee strength balance ratios are not affected by aging among male runners.Journal of exercise science and fitness · 2025Article
- Challenges and Opportunities for Injury Reduction and Performance Development in Elite Youth Team Sport Schools: A Practice-Based Opinion.International journal of sports physical therapy · 2025Article
- Comprehensive 1-year multilevel study of sports injuries in para athletes: impact of season timing, years of sports experience, impairment and sports type.BMJ open sport & exercise medicine · 2025Article
- Critical Fluctuations as an Early Warning Signal of Sports Injuries? A Proof of Concept Using Football Monitoring Data.Sports medicine - open · 2024Article
- Running Gait Complexity During an Overground, Mass-Participation Five-Kilometre Run.Sensors (Basel, Switzerland) · 2024Article
- Comparison of Inter-Rater and Intra-Rater Reliability of Raters with Different Levels of Experience When Using Landing Error Scoring System (LESS) in Field-Based Screening of Professional Football Players.Sports (Basel, Switzerland) · 2024Article
- ACL Injury Etiology in Its Context: A Systems Thinking, Group Model Building Approach.Journal of clinical medicine · 2024Article
- Real-time sports injury monitoring system based on the deep learning algorithm.BMC medical imaging · 2024Article
- Periodic health evaluation in Para athletes: a position statement based on expert consensus.BMJ open sport & exercise medicine · 2024Article
- Resilience in sports: a multidisciplinary, dynamic, and personalized perspective.International review of sport and exercise psychology · 2024Article
- Changes to balance dynamics following a high-intensity run are associated with future injury occurrence in recreational runners.Frontiers in network physiology · 2023Article
- Towards the Development of a System Dynamics Model for the Prediction of Lower Extremity Injuries.International journal of exercise science · 2023Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.