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Record W4407253140 · doi:10.1038/s41598-025-87413-w

A comprehensive scoping review and meta-analysis of upper limb strength asymmetry

2025· review· en· W4407253140 on OpenAlexafffund
Ryan C. A. Foley, Danny H. Callaghan, Garrick N. Forman, Jeffrey D. Graham, Michael W.R. Holmes, Nicholas J. La Delfa

Bibliographic record

VenueScientific Reports · 2025
Typereview
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsBrock UniversityOntario Tech University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ontario Institute of Technology
KeywordsAsymmetryUpper limbPhysical medicine and rehabilitationLower limbRehabilitationMeta-analysisExertionPsychologyGrip strengthHand strengthPhysical therapyMedicineSurgeryPhysicsInternal medicine

Abstract

fetched live from OpenAlex

The "10% rule" of handedness asserts the dominant hand is 10% stronger than the non-dominant hand. Primarily derived from handgrip data, it is unclear if a generalized asymmetry exists across the upper limb. Understanding how strength asymmetry may be affected by handedness, sex, and exertion type has important implications for ergonomics design, sports performance, and clinical rehabilitation. The purpose of this study was to systematically synthesize currently available evidence examining upper limb strength asymmetry. 10,061 results were retrieved, and 174 studies remained after title/abstract screening. 87 studies were synthesized. Results are compiled by exertion type and manner of asymmetry comparison (i.e. right/left, dominant/non-dominant). Asymmetry ratios were calculated to examine the effects of handedness, exertion side, arm region, and sex. Strength differences were most frequently reported for grip exertions (n = 49). 25 studies reported other joint strength asymmetries. Overall, the right limb was 6.7% stronger than the left limb (n = 9342) and the dominant limb was 11.6% stronger than the non-dominant limb (n = 9327), though strength asymmetry varied across joints and movements (2.1% to 19.5%). This research demonstrates that the 10% rule is a good approximation for upper limb strength asymmetry. However, several factors, including joint, movement type, and sex, can affect this relationship.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.800
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.004
Bibliometrics0.0010.015
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.132
GPT teacher head0.401
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2025
Admission routes2
Has abstractyes

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