Subclinical Neck Pain Alters Gaze Stability During the Vestibulo-Ocular Reflex
Bibliographic record
Abstract
(1) Background: Subclinical neck pain is mild-to-moderate neck pain that has not yet been treated, and where individuals experience pain-free days. Alterations in sensorimotor integration, motor control, proprioception, and cerebellar inhibition have been observed in individuals with subclinical neck pain. Upregulation of the cervico-ocular reflex is documented in subclinical neck pain, with no difference in the gain of the vestibulo-ocular reflex. Vestibulo-ocular reflex gain adaptation and associated differences in visuo-motor control have not been successfully measured in this population. This study aims to investigate the vestibulo-ocular reflex gain adaptation and visuo-motor control in individuals with subclinical neck pain. (2) Methods: 30 right-hand-dominant participants (19 healthy controls: 10 male and 9 female; 16 subclinical neck pain: 6 male and 10 female) aged 18 to 35 performed an eye tracking task. Participants were seated 90cm away from a monitor and instructed to hold their gaze on a stationary or moving target projected onto a screen while performing active head rotations. Trials were divided into 12 blocks (pre-adaptation, 10 adaptation, and post-adaptation) for a total of 192 trials. During adaptation, the target would move at increasing speeds during each block, increasing by 10% of active head velocity up to a maximum of 100%. (3) Results: The subclinical neck pain group demonstrated significantly higher total saccades (p = 0.006, ƞ2 = 0.240) and overt catch-up saccades (p = 0.041, ƞ2 = 0.141) than the healthy control group. (4) Conclusion: Subclinical neck pain alters the visual–vestibular interaction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".