Cluster analysis of multiple impairment measures in evidence-based classification for para-alpine sit skiers.

Scand J Med Sci Sports

State Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing, China.

Published: January 2024

AI Article Synopsis

  • * A study with 38 para-alpine sit skiers evaluated various tests, including isometric trunk strength and simulated skiing performance, to understand how these measures relate to skiing ability.
  • * Results showed significant correlations among tests, and the use of cluster analysis helped identify four distinct athlete groups based on their activity limitations, indicating a potential for improved classification accuracy and transparency in para-alpine skiing.

Article Abstract

The International Paralympic Committee has been promoting the development of evidence-based classification to reduce the subjectivity in current decision-making systems. The current study aimed to evaluate the validity of the impairment and performance tests for para-alpine sit skiing classification, and whether cluster analysis of the measures would produce a valid classification structure. Thirty-eight para-alpine sit skiers with different disabilities completed seven tests. During these tests, isometric trunk strength, trunk muscle excitation, trunk range of movement (ROM), and simulated skiing performance (board tilt angle) were assessed. Correlations between the measures and the board tilt angle were calculated. To group athletes, K-means cluster analysis was performed according to how much the impairment measures affected the board tilting. There were significant correlations between all measures and the maximal board tilt angle (r = 0.35-0.81, p < 0.05). The cluster analysis revealed that the introduction of ROM and muscle excitation was an effective supplement to strength measures in improving the classification accuracy (53%-79%). It produced four clusters with strong structures (mean silhouette coefficient = 0.81) and large and significant inter-cluster differences in most measures and performance between clusters (p < 0.05). The cluster analysis produced classes comprising athletes with similar degrees of activity limitation. All tests reported can help establish a more transparent classification system for para-alpine sit skiers. This study also provides a reference for evidence-based classification systems in other Para sports.

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Source
http://dx.doi.org/10.1111/sms.14514DOI Listing

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