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 da...

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Publicado en:Medicine & Science in Sports & Exercise Vol. 58; no. 6; pp. 1132 - 1140
Autores principales: SMITH, STANLEY E., SIGWARD, SUSAN M., SCHWEIGHOFER, NICOLAS, STRAUB, RACHEL K., POWERS, CHRISTOPHER M.
Formato: research tables/charts Journal Article
Publicado: Lippincott Williams & Wilkins Jun2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2026
      vid: 58
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      pub: Lippincott Williams & Wilkins
      place: Baltimore, Maryland
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        10.1249/MSS.0000000000003946
        193817391
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        atl: Characterizing Landing Strategies during the Drop Jump Task: A Proposed Data-Driven Approach to Identify Increased Exposure to Noncontact Anterior Cruciate Ligament Injury.
      aug:
        au:
          SMITH, STANLEY E.
          SIGWARD, SUSAN M.
          SCHWEIGHOFER, NICOLAS
          STRAUB, RACHEL K.
          POWERS, CHRISTOPHER M.
        affil: Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA
      sug:
        subj:
          Task Performance and Analysis
          Athletic Performance
          Anterior Cruciate Ligament Injuries Risk Factors
          Risk Assessment
          Jumping
          Biomechanics
          Sex Factors
          Human
          Male
          Female
          Adolescence
          Adult
          Secondary Analysis
          Motion Analysis Systems
          Motion Capture
          Kinematics
          Acceleration Physiology
          Machine Learning
          T-Tests
          Chi Square Test
          Cluster Analysis
          Factor Analysis
          Data Analysis Software
          Descriptive Statistics
          Athletic Injuries Prevention and Control
          Adolescent: 13-18 years
          Adult: 19-44 years
          Male
          Female
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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