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Record W4316810843 · doi:10.1186/s12984-023-01133-8

Kinematic analysis of sensorimotor control during the craniocervical flexion movement in patients with neck pain and asymptomatic individuals: a cross-sectional study

2023· article· en· W4316810843 on OpenAlexaff
Elena Bocos-Corredor, Filippo Moggioli, Tomás Pérez-Fernández, Susan Armijo‐Olivo, Cristina Sánchez, Juan Nicolás Cuenca‐Zaldívar, Josué Fernández‐Carnero, Aitor Martín‐Pintado‐Zugasti

Bibliographic record

VenueJournal of NeuroEngineering and Rehabilitation · 2023
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Alberta
FundersAgencia Estatal de InvestigaciónMinisterio de Ciencia, Innovación y Universidades
KeywordsMedicinePhysical medicine and rehabilitationNeck painSupine positionPhysical therapyAsymptomaticRange of motionContext (archaeology)Cross-sectional studySittingMotor controlObservational studyAnesthesiaSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Patients with craniocervical pain have shown reduced performance in the craniocervical flexion test (CCFT). However, there is limited evidence of other possible kinematic alterations not assessed in the context of the CCFT. Previous studies on other functional or planar movements have reported alterations in sensorimotor control (e.g., range of motion [ROM], velocity, or smoothness) in subjects with neck pain. The objective of this study was to explore the association between sensorimotor control variables associated with craniocervical flexion movement and different characteristics related to pain, age, disability, and fear of movement in individuals with non-traumatic chronic neck pain and asymptomatic controls. METHODS: This was an observational, cross-sectional study in patients with non-traumatic neck pain and asymptomatic participants. Regression models were used to assess whether descriptive characteristics of the sample, including: (a) age, (b) intensity of pain, (c) neck disability, (d) chronicity of pain, and (e) fear of movement could explain sensorimotor control variables such as ROM, velocity, jerk, head repositioning accuracy, and conjunct motion. All these variables were recorded by means of light inertial measurement unit sensors during the performance of three maximal repetitions of full range craniocervical flexion in the supine position. RESULTS: A total of 211 individuals were screened and 192 participants finished the protocol and were included in the analyses. Participants had an average age of 34.55 ± 13.93 years and included 124 patients with non-traumatic neck pain and 68 asymptomatic subjects. Kinesiophobia partially explained lower craniocervical flexion ROM (p = .01) and lower peak velocity in flexion (P < .001). Age partially explained increased craniocervical extension ROM (P < .001) and lower peak velocity in flexion (P = .03). Chronicity partially explained increased lateral flexion conjunct motion (P = .008). All models showed low values of explained variance (< 32%) and low absolute values of regression coefficients. CONCLUSIONS: This study did not find a clear relationship between population characteristics and sensorimotor control variables associated with the craniocervical flexion movement. Kinesiophobia might have some association with reduced ROM in craniocervical flexion, but further research in this field is needed in large samples of patients with higher levels of kinesiophobia pain or disability.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.004
GPT teacher head0.245
Teacher spread0.241 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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