Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Effects of Mobility-Fit, a tailored multicomponent physical activity program with upper-limb emphasis, on strength, mobility and fall risk among older adults in long-term care: a cluster randomised controlled trial.

Age and ageing·2025
Same author

Development of the CHILD-SHOE Reporting Checklist: A Scoping Review and Modified Delphi Study to Support Reporting in Children's Footwear Research.

Journal of foot and ankle research·2025
Same author

Diffusion models enable zero-shot pose estimation for lower-limb prosthetic users.

PLOS digital health·2025
Same author

Identifying the Problem Side with Single-Leg Squat and Hamstrings Flexibility for Non-Specific Chronic Low Back Pain.

Medicina (Kaunas, Lithuania)·2024
Same author

Biomechanics of step-off drop landings are affected by limb dominance and lead limb in task initiation.

Journal of sports sciences·2024
Same author

Smaller Biceps Femoris Aponeurosis Size in Legs with a History of Hamstring Strain Injury.

International journal of sports medicine·2024

Related Experiment Video

Updated: Jan 17, 2026

Comparative Analysis of Lower Limb Kinematics between the Initial and Terminal Phase of 5km Treadmill Running
08:26

Comparative Analysis of Lower Limb Kinematics between the Initial and Terminal Phase of 5km Treadmill Running

Published on: July 17, 2020

6.4K

Predicting Running-Related Injuries from Functional, Kinetic and Kinematic Data.

Ray Ban Chuan Loh1,2, Jing Wen Pan1, Muhammad Nur Shahril Iskandar1

  • 1Physical Education and Sports Science Department, National Institute of Education, Nanyang Technological Univerrsity, Singapore.

International Journal of Sports Medicine
|September 20, 2025
PubMed
Summary

Current prediction models struggle to forecast running injuries, even with complex biomechanical data. Accessible screening tools are insufficient for accurately predicting future running-related injuries in recreational runners.

More Related Videos

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
06:52

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

8.5K
3D Kinematic Analysis for the Functional Evaluation in the Rat Model of Sciatic Nerve Crush Injury
08:20

3D Kinematic Analysis for the Functional Evaluation in the Rat Model of Sciatic Nerve Crush Injury

Published on: February 12, 2020

9.3K

Related Experiment Videos

Last Updated: Jan 17, 2026

Comparative Analysis of Lower Limb Kinematics between the Initial and Terminal Phase of 5km Treadmill Running
08:26

Comparative Analysis of Lower Limb Kinematics between the Initial and Terminal Phase of 5km Treadmill Running

Published on: July 17, 2020

6.4K
An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
06:52

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

8.5K
3D Kinematic Analysis for the Functional Evaluation in the Rat Model of Sciatic Nerve Crush Injury
08:20

3D Kinematic Analysis for the Functional Evaluation in the Rat Model of Sciatic Nerve Crush Injury

Published on: February 12, 2020

9.3K

Area of Science:

  • Sports Medicine
  • Biomechanics
  • Injury Prevention

Background:

  • Inconsistent biomechanical risk factors for running-related injuries are documented.
  • Limited research exists on the interaction between biomechanics and other injury risk factors.
  • Predicting running injuries remains a challenge for recreational runners.

Purpose of the Study:

  • To develop and compare prediction models for running-related injuries over 12 months.
  • To assess the predictive capability of various model complexities using accessible tools.
  • To investigate interactions between biomechanical and other risk factors for running injuries.

Main Methods:

  • Prospective cohort study with 83 recreational runners.
  • Baseline assessments included the Functional Movement Screen and biomechanical analysis (in-shoe force sensors, 2D kinematic analysis).
  • 12-month follow-up to record running-related injuries; statistical analysis using Mann-Whitney U-test and binary logistic regression.

Main Results:

  • No statistically significant prediction models were identified, regardless of complexity (p-values 0.106–0.972).
  • Neither simple (single variable) nor complex (multiple variables) models accurately predicted running injuries.
  • Accessible biomechanical and functional screening tools did not yield significant predictive power.

Conclusions:

  • Prediction models using accessible tools cannot accurately forecast future running-related injuries.
  • Researchers and practitioners should exercise caution regarding the over-reliance on simple screening measures for injury risk.
  • Further research is needed to identify reliable predictors for running-related injuries.