Development and evaluation of a simple, multifactorial model based on landing performance to indicate injury risk in surfing athletes

Document Type

Journal Article

Publisher

Human Kinetics

Place of Publication

Champaign, Illinois, United States

Faculty

Faculty of Health, Engineering and Science

School

School of Medical and Health Sciences

RAS ID

20034

Comments

Lundgren, L. E., Tran, T. T., Nimphius, S., Raymond, E., Secomb, J. L., Farley, O. R. l., ... Sheppard, J. M. (2015). Development and evaluation of a simple, multifactorial model based on landing performance to indicate injury risk in surfing athletes. International Journal of Sports Physiology and Performance, 10(8), 1029-1035. doi: 10.1123/ijspp.2014-0591. Available here

Abstract

Purpose : To develop and evaluate a multifactorial model based on landing performance to estimate injury risk for surfing athletes. Methods : Five measures were collected from 78 competitive surfing athletes and used to create a model to serve as a screening tool for landing tasks and potential injury risk. In the second part of the study, the model was evaluated using junior surfing athletes (n = 32) with a longitudinal follow-up of their injuries over 26 wk. Two models were compared based on the collected data, and magnitude-based inferences were applied to determine the likelihood of differences between injured and noninjured groups. Results : The study resulted in a model based on 5 measures—ankle-dorsiflexion range of motion, isometric midthigh- pull lower-body strength, time to stabilization during a drop-and-stick (DS) landing, relative peak force during a DS landing, and frontal-plane DS-landing video analysis—for male and female professional surfers and male and female junior surfers. Evaluation of the model showed that a scaled probability score was more likely to detect injuries in junior surfing athletes and reported a correlation of r = .66, P = .001, with a model of equal variable importance. The injured (n = 7) surfers had a lower probability score (0.18 ± 0.16) than the noninjured group (n = 25, 0.36 ± 0.15), with 98% likelihood, Cohen d = 1.04. Conclu - sions : The proposed model seems sensitive and easy to implement and interpret. Further research is recommended to show full validity for potential adaptations for other sports.

DOI

10.1123/ijspp.2014-0591

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