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

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.

Keywords: biomechanics; foot strike; gait; running; running shoe.

Figure 1

STROBE study flow diagram for observational studies.

Figure 2

Sample ground reaction force (GRF) curves shown for a runner in each of the five groups during stance (A1) Rearfoot accurate, (A2) Rearfoot non-accurate, (B3) Non-rearfoot accurate, (B4) Non-rearfoot non-accurate and (C) Don't know.) GRF are expressed in N. The serial panels beneath each GRF trace are joint motion curves during an entire gait cycle. GRF and motion values were sampled at 100 Hz.

Figure 3

Accurate self-report detection of habitual foot strike type. Values are expressed as% correct based on actual foot strike pattern. *denotes different than rearfoot strikers at p < 0.05.

Figure 4

Prevalence of reported running-related injuries (RRI) by accuracy of self-report foot strike detection. Values are shown as percent of the group for total RRI, soft tissue injuries and bone injuries. Soft tissue injuries include: Achilles tendinopathy, Iliotibial band syndrome, hamstring strain pain, patellofemoral pain, plantar foot pain, flexor hallucis longus tendinopathy, posterior tibialis tendinopathy, low back pain, and Hoffa's fat pad inflammation. Bone injuries included: medial tibial stress syndrome, stress fractures of the tibia, fibula, metatarsals, cuneiforms, navicular, femur, and pelvis.