Date on Master's Thesis/Doctoral Dissertation

5-2024

Document Type

Doctoral Dissertation

Degree Name

Ph. D.

Department

Mechanical Engineering

Degree Program

Mechanical Engineering, PhD

Committee Chair

Quesada, Peter

Committee Co-Chair (if applicable)

Murphy, Kevin

Committee Member

Murphy, Kevin

Committee Member

Rahman, Md Jahidur

Committee Member

Caruso, John

Author's Keywords

ACWR; injury likelihood; sport injury; GPS workload metrics; athlete monitoring; workload management

Abstract

The use of the acute:chronic workload ratio (ACWR) is a strategy presented as a means of mitigating the injury risk athletes are exposed to from their regular participation in sport. However, the current literature is inconclusive towards its effectiveness at actually mitigating injuries. The purpose of this dissertation was to determine if ACWR should be integrated into an injury mitigation strategy of a sport organization and, if so, what input, computation, and injury-related methodologies should be used with it. Retrospective injury data and velocity-based distances from training and competition demands from collegiate women’s field hockey athletes were used to investigate the significance of ACWR methodologies within the context of ACWR computation, injury likelihood profiling, and injury mitigation strategy (IMS) performance. Factors included injury definition and lag period, input, averaging and coupling method, and acute and chronic time frame. Levels within each factor were based on methods from the literature. A case study was also presented investigating the accuracy, sensitivity, and specificity of all configurations using a threshold optimized for peak accuracy. A selected configuration was then used to evaluate the performance of an IMS using varied thresholds, the injury likelihood profile, and flagged injuries relative to a seasonal timeline and injury type. Within each application, the effects of a given factor should not be interpreted without considering its interactions with other factors and factor levels. The impact of each factor fell within a hierarchical order where considerations for injury criterion factors were more important than input and considerations for input were more important than factors within the ACWR computation model. The injury likelihood profile, performance curves, and flagged injuries should be used to evaluate the development of the ACWR criteria. This dissertation concluded the use of ACWR provides information that supports injury mitigation decisions and efforts. However, the utility of ACWR depends on how it is applied, and there is not a universal configuration for its implementation. Further research should be directed at backtesting and optimizing injury mitigation strategies to maximize their practical impact.

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