Evidence map›Paper›PMID 42258473›Full record

ArticlePloS one2026

Strategy to step on obstacle during cross-country race to minimize overuse injury risk.

Emanuela H Kang, David G Wilson, Jan K Petric, Sophia Ulman

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Emanuela H KangHockaday School, Dallas, Texas, United States of America.
David G WilsonDepartment of Prosthetics-Orthotics, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.ORCID https://orcid.org/0000-0002-3314-9130
Jan K PetricDepartment of Prosthetics-Orthotics, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.
Sophia UlmanOrthopaedic and Sports Medicine Center, Scottish Rite for Children, Frisco, Texas, United States of America.ORCID https://orcid.org/0000-0002-6262-2054

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOveruse injuries are a major concern in high school endurance sports such as cross-country running.

methodsThis study explores how joint laxity, foot placement, and surface friction affect ligament strain during obstacle interaction, using an in-silico computer model simulating a "stepping on obstacle" scenario. Incorporating ground reaction forces and muscle activation, the model evaluates soft tissue responses across 27 cases-varying three levels each of joint laxity (none, medium, high), foot placement (central, medial, lateral), and surface friction (low, medium, high). Ligament strain was recorded at every millisecond and analyzed statistically.

resultsFoot placement is the dominant factor in minimizing ligament strain, with medial foot strikes yielding the lowest anterior tibiotalar ligament strain (11.5%), which increased by 1.75× and 1.73× in central and lateral strikes, respectively. Friction level showed a negative correlation with strain, reducing anterior tibiotalar stress from low to high friction. Joint laxity positively correlated with plantar fascia strain, with the medium laxity group experiencing more strain than the no-laxity group.

conclusionThese findings suggest that medial foot placement and higher surface friction significantly reduce injury risk, providing biomechanical insight and practical guidance for safer running techniques in young endurance athletes.

Indexed as

Athletic InjuriesCumulative Trauma DisordersRunningBiomechanical PhenomenaComputer SimulationFootFrictionHumansJoint InstabilityLigaments

Identifiers

PMID42258473
PMCPMC13245758

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.