Prediction of injury risk in sports

• Sport injuries are a major problem associated with sport participation. To develop preventive strategies and programs, it is important to identify factors that will increase the likelihood of sport injuries. In most sport injury risk factor research, statistical analyses are performed; however, many of the most common statistical analyses provide limited information about predictors of sport injury risk. The common analyses used in previous studies do not acknowledge the complexity associated with investigating risk factors for sport injuries. To better capture this complexity, suggested in most theoretical frameworks, more appropriate of statistical approaches should be used. In this article we present how latent profile analysis, latent change score analysis, and latent growth curve analysis can be used to overcome some of the limitations with more traditional analyses. Lastly, we also elaborate on future directions for analyses in sport injury risk factor research. More specifically, we present how advanced statistical models, such as classification and regression trees (CART) analysis and random forest analysis, can be used to provide researchers and clinicians with results that are more clinically meaningful.

Ämnesord

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)

NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)

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