Int J Sports Med
DOI: 10.1055/a-2706-5516

Orthopedics & Biomechanics

Authors Author Affiliations

Ray Ban Chuan Loh

1   Physical Education and Sports Science Department, National Institute of Education, Nanyang Technological Univerrsity, Singapore (Ringgold ID: RIN63238)

2   Sports Medicine and Surgery Clinic, Tan Tock Seng Hospital, Singapore, Singapore (Ringgold ID: RIN63703)

Jing Wen Pan 

1   Physical Education and Sports Science Department, National Institute of Education, Nanyang Technological Univerrsity, Singapore (Ringgold ID: RIN63238)

Muhammad Nur Shahril Iskandar

1   Physical Education and Sports Science Department, National Institute of Education, Nanyang Technological Univerrsity, Singapore (Ringgold ID: RIN63238)

Pui Wah Kong 

1   Physical Education and Sports Science Department, National Institute of Education, Nanyang Technological Univerrsity, Singapore (Ringgold ID: RIN63238)

Supported by: This research is supported by the National Institute of Education, Singapore, under its Research Support for Senior Academic Administrators Grant (RS 2/21 KPW). Further Information(opens Publication History section)Also available at   Buy Article(opens in new window) Permissions and Reprints(opens in new window)

The literature has identified inconsistent biomechanical risk factors for running-related injuries but lacks investigations on interactions between biomechanics and other risk factors. This prospective cohort study aimed to develop and compare prediction models of various levels of complexity to predict running-related injuries over 12 months in recreational runners. The seven-item functional movement screen test was administered at baseline for 83 participants. Running biomechanics were evaluated using clinically friendly tools, including wearable in-shoe force sensors to measure vertical ground reaction forces and 2D video-based kinematic analysis of lower extremities. The participants were subsequently monitored over a 12-month follow-up period to track whether they sustained running-related injuries. Differences between the injured (n=26) and non-injured (n=55) groups were examined using the Mann–Whitney U-test. Binary logistic regression was performed to identify significant indicators for running-related injuries, with six models developed involving different sets of variables. Neither simple (involving one variable) nor complex models (including multiple variables) were statistically significant (p-values ranged from 0.106 to 0.972). In conclusion, prediction models developed using variables obtained from accessible tools are unable to accurately predict future running-related injuries regardless of model complexity. Researchers and practitioners should avoid over-reliance on simple measures for screening injury risks.

Keywords sports - lower extremity - biomechanics - gait - risk factors - prognosis Publication History

Received: 11 June 2025

Accepted after revision: 20 September 2025

Accepted Manuscript online:
20 September 2025

Article published online:
13 October 2025

© 2025. Thieme. All rights reserved.

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Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

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