Resonance massage tool effects in non-migraine headache management
Bibliographic record
Abstract
BACKGROUND: This study examines the feasibility of preventative and acute treatment of chronic cluster headaches using vibration as a potential intervention to warrant a large-scale clinical trial. METHODS: The paper reports a study on sixty individuals suffering from tension or cluster-type headaches. The experimental group of 30 individuals received vibratory treatment at set frequencies, and the control received sham treatment. All individuals were evaluated prior to and immediately after the intervention, and at six and eight weeks after the conclusion of treatment. RESULTS: Significant improvement was noted in the experimental group as rated by the Headache Impact Test-6, Rivermead Persistent Post-Concussive Syndrome (PPCS) Questionnaire, Montreal Cognitive Assessment, Participant Health Questionnaire-9, Generalized Anxiety Disorder Scale-7, and/or the Post Traumatic Stress Disorder Checklist. CONCLUSIONS: The use of vibration and resonance-type devices significantly reduces mean pain ratings over time, pointing to their effectiveness as a potential maintenance or preventative type of therapy. This study contributes to the development and design of larger randomized controlled trials that could further evaluate the effectiveness of vibration and resonance with oscillating expiratory pressure on headache. CLINICAL TRIAL REGISTRATION: ISRCTN37415803.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.006 | 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".