The relationship between cervical spine range of motion and postural sway in mechanical neck pain: A cross-sectional study
Bibliographic record
Abstract
Background: Impairments in postural sway have been identified in people with mechanical neck pain. The influence of cervical spine range of motion (ROM) on postural sway is unclear in mechanical neck pain (MNP). Objective: This study investigated the relationship between cervical spine range of motion (ROM) and postural sway in MNP. Methods: The cervical ROM was measured using the Cervical Range of Motion (CROM) device. Standing postural sway characterised by mean centre of pressure (COP) measurements in the anterior posterior (AP) and medio-lateral direction with eyes closed and feet together condition was recorded on a posturography platform. Pearson product moment correlation coefficient was used to identify the relationship between cervical ROM and postural sway. Results: Seventy-two MNP individuals (Mean age: [Formula: see text]) of either sex (Male: [Formula: see text]) were recruited. Overall, no statistically significant correlations were identified between cervical spine ROM in sagittal and frontal plane and postural sway (r values ranging from 0.00 to [Formula: see text]; p-values [Formula: see text]). However, a weak negative correlation was present between the cervical rotation and AP (r-[Formula: see text]; p-[Formula: see text]) and mediolateral (r-[Formula: see text]; p-[Formula: see text]) COP excursion. Conclusion: The cervical spine ROM was found to have a weak relationship with postural sway in individuals with MNP. This suggests the investigation of other mechanisms especially muscle tension which might be responsible for altered postural sway in MNP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".