Examination of Non-Specific Low Back Pain, Pain Perceptions and Disability Between Brazilian Jiu Jitsu, Muay Thai and Boxing Athletes
Bibliographic record
Abstract
Background: Non-specific low back pain is the leading cause of years lived with disability worldwide. The present study investigates non-specific low back pain, pain perceptions and disability due to pain among Brazilian Jiu Jitsu, Muay Thai and Boxing athletes. Methods: The study included 90 amateur athletes (aged 18–45 years; M = 28.97, SD = 5.88). The athletes completed the valid and reliable Pain Beliefs Perceptions Inventory (PBPI), the Quebec Pain Disability Scale (QPDS) and the Short-Form McGill Pain Questionnaire (SF-MPQ) which includes the Visual Analogue Scale (10 cm VAS 0–10 rating system) and the Present Pain Intensity index (PPI). Results: The results revealed that the majority of athletes rated their pain as low (SF-MPQ: M = 12.34, SD = 8.91; VAS: M = 1.65, SD = 1.82; PPI: M = 2.10, SD = 1.08) with low disability due to pain (QPDS: M = 18.98, SD = 22.71). Also, the majority of athletes disagreed that their pain was mysterious or persistent with high duration (PBPI: M = 1.43, SD = 2.23). Between the three martial arts, Brazilian Jiu Jitsu athletes showed statistically significantly (a) higher emotional and sensational pain intensity (x2(2) = 15.73; p < 0.001; x2(2) = 19.34; p < 0.001), (b) higher disability due to pain (x2(2)= 25.30; p < 0.001) and (c) more mysterious, more persistent pain with more duration (x2(2)= 9.32; p < 0.05) than Muay Thai and Boxing athletes. Also, a few correlations were found between age and pain perception only in Brazilian Jiu Jitsu and Boxing martial arts athletes. Conclusions: Further research is required to elucidate the biomechanical and psychological factors contributing to these differences between martial arts athletes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 teacher head, 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".