Effect of Spinal Manipulation on Eye and Head Movement Performance in Participants With Chronic Neck Pain: An Observational Study
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine the immediate effects of spinal manipulation (SM) on motor performance of eye and head movement tasks in symptomatic and asymptomatic participants with chronic neck pain. METHODS: This observational study utilized a between and within group analyses to assess the effects of cervical SM in symptomatic (n = 20) and asymptomatic (n = 20) groups. Participants performed goal-directed eye and head movement tasks before and after cervical SM, to identify changes in eye and head motor performance. Eye and head movement time (MT) was analyzed as a primary outcome. Secondary outcomes included eye and head peak velocity and time to peak velocity. RESULTS: During the eye movement task, there was no significant effect of SM on MT. During the head movement task, there was a significant SM by group interaction for MT and significant effect of SM on MT during the amplitude and width conditions within the symptomatic group indicating that head MTs were reduced in both analyses. CONCLUSION: There was no effect of SM on eye MTs. However, the significant effect of SM on head MT provides evidence for changes in head control following SM. Given the SM targeted the cervical spine, the changes in MT were only present for head movements, we propose the observed changes may result from both neuromuscular and sensorimotor adaptations following SM.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".