Accuracy of self-reported foot strike pattern detection among endurance runners.

IF 2.3 Q2 SPORT SCIENCES
Frontiers in Sports and Active Living Pub Date : 2024-12-11 eCollection Date: 2024-01-01 DOI:10.3389/fspor.2024.1491486
Heather K Vincent, Kyle Coffey, Aiden Villasuso, Kevin R Vincent, Sharareh Sharififar, Lydia Pezzullo, Ryan M Nixon
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Abstract

Introduction: Foot strike pattern is often associated with running related injury and the focus of training and rehabilitation for athletes. The ability to modify foot strike pattern depends on awareness of foot strike pattern before being able to attempt change the pattern. Accurate foot strike pattern detection may help prevent running related injury (RRI) and facilitate gait modifications and shoe transitions. The purposes of this study were to determine the accuracy of self-reported foot strike pattern among endurance runners, to identify what factors were predictive of accurate foot strike detection and recent RRI.

Methods: This was a retrospective, cross-sectional study which included endurance runners (N = 710; 51.5% female; 35.4 ± 15.5 years; 51.6% were training competitively at the time of testing) with different running injury histories. Runners self-reported foot strike pattern [rearfoot, non-rearfoot (mid or forefoot), or "don't know"] and information about shoewear specifics. All runners performed a single session of running at self-selected speed on an instrumented treadmill with 3D motion capture and high-speed filming that verified actual foot strike. Logistic regression was used to predict accuracy of foot strike detection and RRI.

Results: Overall accuracy of foot strike detection was low (42.7%; p < 0.01). Self-reported foot strike was 28.3% for rearfoot, 47.0% for nonrearfoot forefoot strike and 24.6% did not know. Biomechanical analyses actually showed that 34% of rearfoot strikers accurately detected rearfoot strike, while 69.5% of non-rearfoot strikers self-reported accurate non-rearfoot strike (p < 0.05). Runners who "did not know" their strike had the highest prevalence of RRI compared to runners who self-reported nonrearfoot or rearfoot strike (73% vs. 56% and 58%; p < .001). After accounting for several variables, shoe heel-to-toe drop was a consistent predictor of accurate strike detection [OR = 0.93 (0.88-0.99); p = 0.026] and RRI in last six months [OR = 1. 1 (1.01-1.17); p = 0.018]. RRI were also predicted by recent shoe change [OR = 2.8 (1.7-4.6); p < 0.001].

Discussion: Accurate detection of actual foot strike by endurance runners varies by the actual foot strike type determined during testing and is associated shoe characteristics. These findings demonstrate the importance of accurately identifying foot strike pattern and recommending footwear as a factor if planning to use retraining to alter foot strike pattern.

耐力跑者自我报告的足击模式检测的准确性。
脚部击球方式常与跑步相关损伤有关,是运动员训练和康复的重点。在能够尝试改变脚法之前,修改脚法的能力取决于对脚法的意识。准确的足部撞击模式检测可能有助于预防跑步相关损伤(RRI),促进步态调整和鞋的转换。本研究的目的是确定耐力跑者自我报告的足击模式的准确性,以确定哪些因素可以预测准确的足击检测和最近的RRI。方法:这是一项回顾性横断面研究,包括耐力跑者(N = 710;51.5%的女性;35.4±15.5岁;51.6%的人在测试时进行了竞争性训练,有不同的跑步损伤史。跑步者自述的脚着地模式[后脚,非后脚(中或前脚),或“不知道”]和关于鞋子细节的信息。所有的跑步者都在一个仪器化的跑步机上以自己选择的速度进行一段时间的跑步,该跑步机上有3D动作捕捉和高速拍摄,以验证实际的足部撞击。采用Logistic回归预测足部撞击检测的准确性和RRI。结果:足部撞击检测的总体准确率较低(42.7%;p p p p = 0.026]和近6个月RRI [OR = 1]。1 (1.01 - -1.17);p = 0.018]。最近换鞋也能预测RRI [OR = 2.8 (1.7-4.6);p讨论:耐力跑者对实际脚击的准确检测因测试过程中确定的实际脚击类型和相关的鞋特性而异。这些发现表明,如果计划使用再训练来改变足部打击模式,准确识别足部打击模式和推荐鞋类作为一个因素的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.60
自引率
7.40%
发文量
459
审稿时长
15 weeks
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