Developing a Model of Risk Factors of Injury in Track and Field Athletes

Abstract

This work aimed to develop a model to assess the likelihood of injury in track and field athletes, and to establish which factors have the greatest impact. Tests verifying their significance were also reviewed, as well as the method for selecting variables. The key element was to confirm the quality of the classification system and to test the impact of individual factors on the likelihood of injury. The survey was carried out among physically active participants who take part in track and field sporting disciplines. The Cronbach’s alpha was 0.73, which can be considered an acceptable value for the survey. The seven most important factors influencing the risk of injury were selected from a group of twenty-four and were used to create the model. The Nagelkerke’s R2 reached 0.630 for the logit model, which indicates a good effect of the independent variables. The data suggested that the largest factor influencing the risk of injury was the number of prior injuries.