Clinical significance of exercise‐induced hypoalgesia in individuals with temporomandibular disorders and neck pain: A clinical trial protocol
Bibliographic record
Abstract
Evidence reports positive effects of neck motor control and aerobic exercises (AEs) to improve pain in individuals with temporomandibular disorders (TMD) and neck pain. A single bout of exercise typically leads to an increase in pain thresholds up to 30 min post-exercise, known as exercise-induced hypoalgesia (EIH). Studies evaluating the effects of aerobic and neck motor control exercises on EIH in individuals with chronic neck pain and TMD are limited. Measuring treatment effects and determining the clinical significance based on exercise types and loads and EIH response can improve clinical outcomes and adherence to exercise programmes. This study was designed to determine the clinical significance of EIH after neck motor control and aerobic training in participants with TMD and neck pain. Participants between 18 and 60 years with neck pain and/or TMD will be randomized to neck motor control or aerobic training groups. Participants will be assessed before, immediately after and 15 min after three treatment sessions within a 12-week exercise programme. Assessments will include pain intensity, pressure pain thresholds and tolerance of masticatory and neck muscles, and the Global Rating of Change Scale. EIH response will be calculated in absolute and relative changes by subtracting the post- from the pre-exercise values. Distribution-based (e.g., effect size) and anchor-based (e.g., receiver operating characteristics) methods will be performed to determine the clinical significance of EIH (minimal important difference).
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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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.048 | 0.009 |
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".