Neuromechanical response to spinal manipulation therapy: effects of a constant rate of force application
Bibliographic record
Abstract
BACKGROUND: Neuromechanical responses to spinal manipulation therapy (SMT) have been shown to be modulated through the variation of SMT biomechanical parameters: peak force, time to peak force, and preload force. Although rate of force application was modulated by the variation of these parameters, the assumption that neuromuscular responses are modulated by the rate of force application remains to be confirmed. Therefore, the purpose of the present study was to evaluate the effect of a constant rate of force application in neuromechanical responses to SMT in healthy adults. METHODS: Four SMT force-time profiles presenting different time to peak force and peak force, but with a constant rate of force application were applied on 25 healthy participants' T7 transverse processes. Muscular responses were recorded through surface electromyography electrodes (T6 and T8 levels), while vertebral displacements were assessed through pasted kinematic markers on T6 to T8 spinous processes. Effects of SMT force-time profiles on neuromechanical responses were assessed using repeated-measures ANOVAs. RESULTS: There was no main effect of SMT force-time profile modulation on muscular responses (ps > .05) except for the left T8 (F (3, 72) = 3.23, p = .03) and left T6 (F (3, 72) = 2.94, p = .04). Muscular responses were significantly lower for the lowest peak force condition than the highest (for T8) or second highest (for T6). Analysis showed that increasing the SMT peak force (and concomitantly time to peak force) led to a significant vertebral displacement increase for the contacted vertebra (F T7 (1, 17) = 354.80, p < .001) and both adjacent vertebras (F T6 (1, 12) = 104.71, p < .001 and F T8 (1, 19) = 468.68, p < .001). CONCLUSION: This study showed that peak force modulation using constant rate of force application leads to similar neuromuscular responses. Coupled with previous investigations of SMT peak force and duration effects, the results suggest that neuromuscular responses to SMT are mostly influenced by the rate of force application, while peak force modulation yields changes in the vertebral displacement. Rate of force application should therefore be defined in future studies. Clinical implications of various SMT dosages in patients with spine related pain should also be investigated. TRIAL REGISTRATION: ClinicalTrials.gov NCT02550132 . Registered 8 September 2015.
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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) | 0.000 | 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".