Evidence on the Ability of a Pneumatic Decompression Belt to Restore Spinal Height Following an Acute Bout of Exercise
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to evaluate the ability of a pneumatic decompression belt to restore spinal height lost following an acute bout of exercise that induced compression. METHODS: This study implemented a test-retest repeated measures design in which twelve participants (male = 10, female = 2) age, 21.5 ± 1.0 years; height, 179.0 ± 7.70 cm; weight, 84.0 ±11.5 kg; were recruited from a university population and acted as their own control. All participants were healthy with no previous history of disabling back pain, and were frequent weight trainers. A stadiometer was used to measure spinal height at baseline, then following an acute bout of exercise and then again following the intervention (use of a pneumatic decompression belt for 20 minutes) or control (lying supine for 20 minutes). A 2-way repeated measures ANOVA was performed on the change in spinal height in order to evaluate differences between measurement phases and intervention conditions. RESULTS: The use of the decompression belt increased spinal height gain (4.3 ± 3.0 mm) significantly more than the control condition (1.8 ± 1.2 mm) following an acute bout of weightlifting exercises known to elicit high compressive loads on the lumbar spine. CONCLUSION: The pneumatic decompression belt restored spinal height faster than a non-belt wearing condition in young healthy asymptomatic participants.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".