Towards the Development of a System Dynamics Model for the Prediction of Lower Extremity Injuries

Abstract

Acute noncontact Lower Extremity (LE) injuries constitute a significant problem in team sports. Despite extensive research, current knowledge on the risk factors of LE injuries is limited to static simplistic models of instantaneous cause and effect relationships ignoring the time dimension and the embedded complexity of LE injuries. Even though complex systems approaches have been used in various cases to improve policy and intervention effectiveness, there is limited research on predicting and managing LE injuries. This creates an opportunity to fill the gap in the current literature by applying the System Dynamics (SD) methodology to model LE injuries. The proposed approach allows for synthesizing risk factors and examining their interaction. This paper makes the first step towards such an approach by developing a causal loop model revealing the etiology of LE injuries. A causal loop model for LE injuries is developed via an extensive literature review and brainstorming with experts. In contrast to the traditional static approaches, the proposed model reveals some of the complexity and nonlinear relationships of the various sports injury risk factors. The derived causal loop model may then be used to quantify these interactions and develop a simulation model. This will be achieved by operationalizing and incorporating the main risk factors that impact LE injuries in an integrated sports injury prediction model. In this way, plausible strategies for preventing LE injuries can be tested prior implementation and thereby achieve optimization of intervention programs.

Keywords: Complex systems; noncontact lower extremity injuries; sports injury prevention; system dynamics; team management.

Figure 1

Multiple causalities for sports injuries

Figure 2

A Causal Loop Diagram example of Risk factors interactions and complexity for acute noncontact LE injuries. B and R with circular arrows represent the balancing and reinforcing feedback loops, respectively. Green arrows represent the internal and red arrows the external risk factors.

Figure 3

Feedback loops creating due to injury.

Figure 4

Quality of movement causes tree.