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Record W4413765343 · doi:10.1016/j.spinee.2025.08.331

Passive neck stiffness and range of motion for males and females from early to late adulthood

2025· article· en· W4413765343 on OpenAlexfundno aff
Mingyue Liu, Ryan D. Quarrington, William S. P. Robertson, Baptiste Sandoz, Claire F. Jones

Bibliographic record

VenueThe Spine Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
FundersUniversity of AdelaideProvidence Health CareHospital Research Foundation
KeywordsMedicineRange of motionRange (aeronautics)Physical medicine and rehabilitationSurgeryAerospace engineering

Abstract

fetched live from OpenAlex

BACKGROUND CONTEXT: Understanding human passive neck range of motion (ROM) and stiffness, and their association with age and sex, can be beneficial for clinical assessment, and surrogate and computational modelling. PURPOSE: To assess passive head-neck ROM and stiffness, and to investigate association with age and sex, in flexion, extension, left and right lateral bending, and axial rotation. STUDY DESIGN/SETTING: In-vivo human participant testing. METHODS: A total of 80 participants aged 20 to 79 years (nearly even distribution), who self-reported no history of significant health conditions and with no neck pain, were recruited. Two custom apparatus were used to support participants in relaxed lying. Their head was rotated to maximum ROM; applied moment and head-torso motion were recorded. Muscle activation was monitored in real-time to ensure electromyographic signals from agonist muscles remained below a passive threshold. Stiffness was determined from the moment-angle data within each of three zones, with zone boundaries delineated to maximize moment-angle linearity within each zone. The age and sex effects on passive stiffness and ROM were assessed using generalized linear models for flexion and extension, and linear mixed models for lateral bending and axial rotation. RESULTS: Passive neck ROM decreased by 0.2° per year of age in lateral bending and axial rotation for males and females, and extension ROM for males was 5.8° lower than for females. Passive stiffness in lateral bending (zone 1 and 2: 0.9 and 3.5 Nmm/°/year; zone 3: 3%), axial rotation (zone 1 and 2: 1%; zone 3 for males and females: 1.9 and 0.9 Nmm/°/year) and some zones in extension (zone 2: 0.8 Nmm/°/year; males in zone 3: 2.7 Nmm/°/year) increased with age, and males had higher stiffness than females in lateral bending (zone 1 and 2: 22.3 and 43.9 Nmm/°; zone 3: 35%) and axial rotation (zone 1 and 2: 49% and 35%). CONCLUSIONS: Passive neck ROM decreased with age in lateral bending and axial rotation, while passive neck stiffness tended to increase with age in all motions but flexion. Extension ROM was higher for females, and lateral bending and axial rotation stiffness at lower angles were higher for males. CLINICAL SIGNIFICANCE: The neck ROM, stiffness, and moment-angle corridors developed in this study provide benchmarks for clinical assessment of cervical spine function, and can assist the development of surrogate and computational models incorporating minimal muscle activation, for injury simulation and clinical skill training.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.292
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes1
Has abstractyes

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