View clinical trials related to Sport Injury.
Filter by:The primary aim of this observational cohort study is to assess sports specialization, sports performance, history of injuries (prevalence, types, areas, duration) and quality of life in young healthy athletes aged 8-16 from Poland. Athlete profiles will be created based on the variables (explained in detailed description) examined. Furthermore, the investigators will perform one-year injury follow-up. The main questions it aims to answer are: - Do athletes with a specific profile (lower values in athletic performance tests, low values in quality of life) evaluated at one time point, suffer injury in the future in annual observation? - Do athletes with high sports specialization will sustain injury in one-year follow-up? - Does sports specialization have a relationship with sports performance tests, and quality of life? - Does sport specialisation, training volume, geographical factor relate to injury history? - Does sports specialisation, injury history differ between sports (individual and team sports)? - Does value of the specific muscle (lower limb) isometric strength will be associated with the dynamic balance scores in young healthy athletes?
The large number of studies in the recent decade dealing with knee injury prevention seems not effective enough to cause a decline in knee injury rates. Thus, it has been proposed to use non-linear mathematical models that simulate the operation of complex and dynamic systems. The present study aims to analyze the dynamic relationships of the risk factors for knee injuries through system dynamics modeling to effectively predict and prevent knee injury. The first part of this project includes a qualitative study informing the theoretical non-linear interrelationships among the risk factors. The aim is to examine the initial hypothetical model formulated in the first part of the project through statistical analysis such as factor analysis and structural equation modeling. Pre-season and in-season data from questionnaires and biomechanical measurements for risk factors will be collected from at least 100 athletes who participate in high-risk sports. The athletes will be monitored for injuries during one season, and these data will be used in the next part of the research plan. The next part of the project aims to develop a dynamic simulation model for predicting knee injuries using specific equations. The function of the simulation model will predict the propensity of knee injuries over time. The next step includes the validation and calibration of the model based on the knee injuries that occurred during the season. The validated and calibrated model will then provide implications for effective policy decisions in knee injury prevention.
Despite the extensive research on prevention and prediction strategies, hamstrings strains injury (HSI) persists at a high rate in team sports and specifically in football. An initial injury increases the risk for re-injury and affects performance, whereas the financial cost for athletes and teams is crucial due to the time needed for appropriate rehabilitation. For that reason, it is critical to formulate better strategies in order to predict and prevent HSI. This study aims to develop a system dynamics (SD) model to evaluate HSI risk. First, a literature review will be carried out on the current approaches and identification of intrinsic and extrinsic risk factors of hamstrings strain injuries. Second, co-creation workshops based on the method of Group Modeling Building (GMB) will be applied to develop the SD for the HSI model. This co-creation process will involve stakeholders such as sports physiotherapists, doctors, and sports scientists. After creating the SD for HSI model, a one-year prospective cohort study will be performed to validate the model with real data and evaluate the ability of the model to predict HSIs. Sports teams will be invited to take part in the validation of the model. Multiple biomechanical parameters and other personal characteristics will be collected. Then, athletes will be monitored for the occurrence of injury and their exposure to injury risk during training and games. The factors' non-linear interaction will be assessed with the statistical method of structural equation modeling and factor analysis. In this way, the factors' interactions extracted for the qualitative phase of the study (group modeling building process) will be quantitatively evaluated. Validating the model with real data will provide a computer simulation platform to test plausible strategies for preventing hamstrings strain injuries prior to implementation and optimize intervention programs.
This study aims to precisely describe epidemiology of injuries than occur during practice of crossfit. Each participant will complete questionnaires in order to identify injuries. The first questionnaire will be completed at the moment of the inclusion and the second questionnaire will be completed if participant has injuries every 3 months until month 12.