INYBI: A New Tool for Self-Myofascial Release of the Suboccipital Muscles in Patients With Chronic Non-Specific Neck Pain
Bibliographic record
Abstract
STUDY DESIGN: A randomized, single-blinded (the outcome assessor was unaware of participants' allocation group) controlled clinical trial. OBJECTIVE: To investigate the effects of myofascial release therapy (MRT) over the suboccipital muscles, compared with self-MRT using a novel device, the INYBI tool, on pain-related outcomes, active cervical mobility, and vertical mouth opening, in adults with chronic non-specific neck pain (NSNP). SUMMARY OF BACKGROUND DATA: MRT is used to manage chronic musculoskeletal pain conditions, with purported positive effects. The efficacy of self-MRT, compared with MRT, has been scarcely evaluated. METHODS: Fifty-eight participants (mean age of 34.6 ± 4.7 yrs; range 21-40 yrs; 77.6% females, 22.4% males) with persistent NSNP agreed to participate, and were equally distributed into an INYBI (n = 29) or a control group (n = 29). Both groups underwent a single 5-minutes intervention session. For participants in the control group, MRT of the suboccipital muscles was performed using the suboccipital muscle inhibition technique, while those in the INYBI group underwent a self-MRT intervention using the INYBI device. Primary measurements were taken of pain intensity (visual analogue scale), local pressure pain sensitivity, as assessed with an algometer, and active cervical range-of-movement. Secondary outcomes included pain-free vertical mouth opening. Outcomes were collected at baseline, immediately after intervention and 45 minutes later. RESULTS: The analysis of variance (ANOVAs) demonstrated no significant between-groups effect for any variable (all, P > 0.05). In the within-groups comparison, all participants significantly improved pain-related outcomes, and showed similar positive changes for mouth opening. Cervical range-of-movement- mainly increased after intervention for participants in the control group. CONCLUSION: Both, MRT and self-MRT using the INYBI, are equally effective to enhance self-reported pain intensity, and local pressure pain sensitivity in chronic NSNP patients. For cervical mobility, MRT appears to be slighlty superior, compared with the INYBI, to achieve improvements in this population. LEVEL OF EVIDENCE: 2.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".