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      A multistate framework for the analysis of subsequent injury in sport (M-FASIS) : M-FASIS

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          A structural approach to selection bias.

          The term "selection bias" encompasses various biases in epidemiology. We describe examples of selection bias in case-control studies (eg, inappropriate selection of controls) and cohort studies (eg, informative censoring). We argue that the causal structure underlying the bias in each example is essentially the same: conditioning on a common effect of 2 variables, one of which is either exposure or a cause of exposure and the other is either the outcome or a cause of the outcome. This structure is shared by other biases (eg, adjustment for variables affected by prior exposure). A structural classification of bias distinguishes between biases resulting from conditioning on common effects ("selection bias") and those resulting from the existence of common causes of exposure and outcome ("confounding"). This classification also leads to a unified approach to adjust for selection bias.
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            Understanding injury mechanisms: a key component of preventing injuries in sport.

            Anterior cruciate ligament (ACL) injuries are a growing cause of concern, as these injuries can have serious consequences for the athlete with a greatly increased risk of early osteoarthrosis. Using specific training programmes, it may be possible to reduce the incidence of knee and ankle injuries. However, it is not known which programme components are the key to preventing knee and ankle injuries or how the exercises work to reduce injury risk. Our ability to design specific prevention programmes, whether through training or other preventive measures, is currently limited by an incomplete understanding of the causes of injuries. A multifactorial approach should be used to account for all the factors involved-that is, the internal and external risk factors as well as the inciting event (the injury mechanism). Although such models have been presented previously, we emphasise the need to use a comprehensive model, which accounts for the events leading to the injury situation (playing situation, player and opponent behaviour), as well as to include a description of whole body and joint biomechanics at the time of injury.
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              A dynamic model of etiology in sport injury: the recursive nature of risk and causation.

              The purpose of this manuscript is to outline a new model representing a dynamic approach that incorporates the consequences of repeated participation in sport, both with and without injury. This model builds on the previous work, while emphasizing the fact that adaptations occur within the context of sport (both in the presence and absence of injury) that alter risk and affect etiology in a dynamic, recursive fashion. Regardless of the type of injury, it is often preceded by a chain of shifting circumstances that, when they come together, constitute sufficient cause to result in an injury. If we are to truly understand the etiology of injury and target appropriate prevention strategies, we must look beyond the initial set of risk factors that are thought to precede an injury and take into consideration how those risk factors may have changed through preceding cycles of participation, whether associated with prior injury or not. This model considers the implications of repeated exposure, whether such exposure produces adaptation, maladaptation, injury or complete/incomplete recovery from injury. When feasible, future studies on sport injury prevention should adopt a methodology and analysis strategy that takes the cyclic nature of changing risk factors into account to create a dynamic, recursive picture of etiology.
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                Author and article information

                Journal
                Scandinavian Journal of Medicine & Science in Sports
                Scand J Med Sci Sports
                Wiley-Blackwell
                09057188
                February 2016
                February 03 2016
                : 26
                : 2
                : 128-139
                Article
                10.1111/sms.12493
                9abc600b-67e4-4d72-a40d-d2efe6e3161f
                © 2016

                http://doi.wiley.com/10.1002/tdm_license_1.1

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