Comparison of the application of elastic bandage and medical tape in pain reduction in primary and secondary teachers
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The convolutions generated on the patient’s skin with the application of the elastic bandage reduce the pressure on the mechanoreceptors and thus, the nociceptive stimulus. The objective of this study was to compare the effect of the elastic bandage application with the application of the medical tape in myofascial pain in the region of the upper fibers of the trapezius muscle in teachers. METHODS: Participants were assessed using the McGill-Melzack Pain questionnaire and the numeric pain rating scale, palpation for the detection of trigger points, goniometry for shoulder abduction and lateral neck flexion, and the upper trapezius muscle strength test. Participants were randomly divided into two groups. In the first moment, the participants of group A received an application of elastic bandage, with the “Y” technique, and those belonging to group B received the application of the same technique, however, using the medical tape. Both groups were reassessed after teaching class and after 24 hours. Two weeks later, there was the inversion of the materials used. RESULTS: The sample consisted of 16 teachers. Group A had a significant statistical pain reduction, according to the numeric pain rating scale, between the initial assessment and post-application at the first moment (p=0.00) and at the second moment (p=0.02). A similar result was found in group B, according to the numeric pain rating scale, both at the first moment (p=0.01) and at the second moment (p=0.03). In both groups, there was pain attenuation with no significance on the effect of the elastic bandage or the medical tape. CONCLUSION: The application of elastic bandage has the same effect that the medical tape in reducing pain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".