Effect of Deep Slow Breathing on Pain‐Related Variables in Osteoarthritis
Bibliographic record
Abstract
This study evaluated the effect of a six‐week deep slow breathing (DSB) program on pain, physical function, and heart rate variability (HRV) in subjects with lower extremity joint pain. Twenty subjects were assigned into training (n=10) and control (n=10) groups. The training group participated in a six‐week DSB program consisting of weekly training sessions and at‐home breathing exercises. DSB exercises focused on prolonging the exhalation and the pause following exhalation. The Western Ontario and McMaster Osteoarthritis Index (WOMAC) was used to assess pain and physical function and HRV data were obtained pre‐ and post‐intervention. Results revealed no significant interactions between group and time for any of the variables. There was no significant main effect for group, but there was a significant main effect (p < 0.025) and a large effect size for time on both pain (training pre 148 ± 94, post 84 ± 89; control pre 123 ± 87, post 92 ± 73; group η p 2 = 0.003, time η p 2 = 0.454) and physical function (training pre 434 ± 268, post 276 ± 287; control pre 482 ± 346, post 338 ± 274; group η p 2 = 0.010, time η p 2 = 0.506). There were no significant main effects (p > 0.017) for group and time on LF power (training pre 179.30 ± 562.1 ms 2 , post 9.82 ± 28.84 ms 2 ; control pre 32.08 ± 66.55 ms 2 , post 0.74 ± 0.73 ms 2 ; group η p 2 = 0.039, time η p 2 = 0.061), HF power (training pre 14.04 ± 39.76 ms 2 , post 7.02 ± 19.24 ms 2 ; control pre 7.43 ± 9.99 ms 2 , post 1.50 ± 1.87 ms 2 ; group η p 2 = 0.039, time η p 2 = 0.039), and LF/HF ratio (training pre 5.64 ± 10.03, post 2.13 ± 3.72; control pre 2.38 ± 3.79, post 0.97 ± 0.69; group η p 2 = 0.036, time η p 2 = 0.169). Results indicated that the six‐week DSB program was not sufficient to improve pain or physical function in subjects with lower extremity joint pain. The significant improvements in pain and physical function from pre‐to post‐intervention for both groups may be the result of an increase in perceived social support during the study. As this is the first study to examine the use of DSB for lower extremity joint pain and dysfunction, further research is needed to investigate the efficacy and applicability of DSB. Support or Funding Information none
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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 | 0.000 | 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) | 0.001 | 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".