Chronic Neck Pain Influence on Oculomotor Performance During Near Point Convergence and Fitts’s Tasks: a cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to quantify the influence of musculoskeletal dysfunction on oculomotor performance by evaluating oculomotor convergence and volitional gaze performance in participants with chronic neck pain compared with controls. METHODS: Twelve participants with chronic neck pain were age/sex matched to 12 asymptomatic participants. All participants completed a series of tests in neutral, trunk rotated right, and trunk rotated left positions. A Royal Air Force ruler was used to measure near point convergence (NPC), a convergence insufficiency (CI) measurement. Oculomotor performance was assessed using an oculomotor Fitts's Law task. Questionnaire data included the neck disability index (NDI) and CI symptom survey (CISS). RESULTS: A significant reduction in NPC was found in participants with neck pain for the neutral and rotated left positions. Movement time increased for targets at farther amplitudes for both groups. Reaction time increased for targets at shorter amplitudes for the symptomatic group, indicating motor planning challenges. Significant correlations were found between CISS and NPC scores, as well as between CISS and NDI scores, indicating CISS scores are associated with convergence performance deficits. Greater NDI scores related to larger CISS scores, correlating to increased CI symptoms. CONCLUSION: Significant differences between groups were found for NPC suggesting that symptomatic participants have difficulties controlling convergent eye movements compared with asymptomatic participants. Reaction time was found to be longer for index of difficulty at a shorter amplitude for the symptomatic group. Correlations between CISS scores with NPC and NDI scores respectively were found, providing evidence of a relationship between CI and neck disability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".