Short term effects of kinesio taping on pain and functional disability in young females with menstrual low back pain: A randomised control trial study
Bibliographic record
Abstract
BACKGROUND: Menstrual low back pain (LBP) in young females can reduce daily activity and cause functional disability, while the progressive application of kinesio-taping (KT) on pain reduction and functional correction has been stated. OBJECTIVE: This study has been designed to investigate the efficacy of the lumbar vertebral column KT in young female with menstrual LBP. METHODS: Thirty-two young females with menstrual LBP participated in this crossover study and were assigned randomly in two separate groups. The first group received KT during their first menstrual cycle and No-KT in their next menstrual, while the other group had no KT during the first mentrual cycle and received KT during the next menstrual cycle. The primary outcome measurements included the visual analogue scale (VAS) of pain, Oswestry disability index and McGill pain questionnaire score which were planned to collect at the end of the third day of the menstrual cycle. RESULTS: Comparing pain and disability between two conditions, of menstrual cycle with KT and menstrual cycle without KT, revealed significant reduction in VAS (mean change = 1.7; 95%CI = 0.6 to 2.8; P= 0.005), McGill pain score (mean change = 20.1; 95%CI = 8.7 to 31.3; P= 0.001) and functional disability (mean change = 12.3; 95%CI = 7.2 to 17.5; P< 0.0001) by using KT during menstrual cycle. CONCLUSIONS: Results showed that KT may effectively reduce pain and disability. The findings may support the clinical application of kinesiotaping in young females with menstrual LBP.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".