Evidence map›Paper›PMID 42222491›Full record

ArticlePeerJ2026

A comparison of modeling approaches when estimating tibial loading during running with different foot strike patterns.

Sanghyuk Han, Matthew Ellison, Akbar Javadi, Dominic J Farris, Hannah Margaret Rice

Abstract readComparative Study
In one paragraph

Article in PeerJ, 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. Article
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

5 authors.

Sanghyuk HanPublic Health and Sport Sciences, University of Exeter, Exeter, United Kingdom.
Matthew EllisonPublic Health and Sport Sciences, University of Exeter, Exeter, United Kingdom.
Akbar JavadiDepartment of Engineering, University of Exeter, Exeter, United Kingdom.
Dominic J FarrisPublic Health and Sport Sciences, University of Exeter, Exeter, United Kingdom.
Hannah Margaret RiceDepartment of Physical Performance, Norwegian School of Sport Sciences, Oslo, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Foot strike can alter internal tibial loading, a mechanical factor linked to tibial stress injury. Participant-specific models are essential for evaluating these loads, but detailed tibial geometry typically requires medical imaging. Open-source statistical shape modeling (SSM) enables geometric reconstruction of the tibia from external landmarks without imaging. However, the reconstruction accuracy achievable using only four anatomical markers commonly used in motion capture, relative to imaging-based reference geometries, is unknown. It also remains unclear whether simplified 2D beam theory and detailed 3D finite element analyses produce consistent internal tibial loading responses across altered running conditions. This study (1) quantified reconstruction errors using a 4-marker SSM configuration; and (2) evaluated the consistency of tibial loading estimates across modeling approaches under different foot strike conditions. Methods: An open-source anatomical dataset ( Results: The 4-marker configuration showed a 17.1% lower Jaccard index than the 9-marker configuration. Reconstructed tibial lengths correlated with marker-based measurements (Spearman's Conclusion: Relative changes in internal tibial loading showed consistent directional trends between approaches across foot strike conditions, indicating that simplified 2D beam theory may provide a practical alternative for estimating within-participant or within-group changes in healthy runners when medical imaging is unavailable.

Indexed as

FootRunningTibiaWeight-BearingAdultBiomechanical PhenomenaFemaleFinite Element AnalysisHumansImaging, Three-DimensionalMagnetic Resonance ImagingMale2D Beam theory3D Finite element analysisFoot strike patternInternal tibial loadingStatistical shape modeling

Identifiers

PMID42222491
PMCPMC13218341

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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.