Characterizing Landing Strategies during the Drop Jump Task: A Proposed Data-Driven Approach to Identify Increased Exposure to Noncontact Anterior Cruciate Ligament Injury

PURPOSE: To determine if distinct landing strategies could be delineated that could inform higher exposure to anterior cruciate ligament (ACL) injury. We also sought to determine whether a greater proportion of females would be assigned to a higher exposure cluster. METHODS: Kinematic and kinetic data from 74 healthy athletes (31 males and 43 females) were obtained during a drop jump task. Variables of interest included those previously shown in prospective studies to be predictive of future ACL injury. K-means clustering (k = 2) was used to determine if two (or more) distinct strategies could be delineated. Independent t tests were used to assess between-cluster differences for each biomechanical variable of interest. A chi-square test was utilized to explore the distribution of males and females across the two clusters. RESULTS: K-means clustering categorized participants into two groups (Cluster 1: N = 36; Cluster 2: N = 38). Two distinct landing strategies were identified as evident by the finding of statistically significant between-cluster differences in seven of the eight biomechanical variables evaluated. Of these differences, six have been identified in the literature as being predictive of future ACL injury. The proportion of females assigned to Cluster 1 was 69.4% ( N = 25), compared with 30.6% males ( N = 11). CONCLUSIONS: The results of this study revealed that the drop jump task can be used to characterize distinct landing strategies. Based on the coexistence of suspected risk factors, an argument could be made that Cluster 1 may be representative of a landing strategy representative of elevated exposure to ACL injury.