Proprioceptive-neuromuscular-facilitation Stretching Affected Pain, Moments,and Gait During Stepping-over-crossing Among Adults With Knee Osteoarthritis
Bibliographic record
Abstract
PURPOSE: The purpose of the project was to investigate the effects of proprioceptive neuromuscular facilitation stretching (PNF) on pain, joint moments, and gait patterns during stepping over obstacles among older people with knee osteoarthritis (KOA). METHODS: Thirty-two older adults were enrolled and randomly assigned to the PNF or control group. Those who were in the PNF group received PNF intervention, while others received lecture series for 1 hour, 3 times a week for 8 weeks. At weeks 0 and 9, the participants step over an obstacle of 20% of their leg length. Pain scores were measured using the Western Ontario and McMaster Universities Arthritis Index (WOMAC), and joint moments and gait variables were collected by a twelve-camera motion capture system (Vicon, Oxford Metrics Ltd., UK) and two force plates (AMTI, BP600900, USA). A Two-way ANOVA (group-by-intervention) with repeated measures was used to analyze data. RESULTS: Thirteen participants in the PNF group (8 females, 68.5 ± 2.1 years, 164.8 ± 6.8 cm, and 69.9 ± 5.3 kg) and fourteen participants in the control group (7 females, 67.9 ± 1.4 years, 160.9 ± 6.8 cm, and 67.9 ± 7.7 kg) completed the intervention. Significant group-by-intervention interactions were detected in pain scores (p = 0.048, η2p = 0.147), crossing velocity (p = 0.043, η2p = 0.154), foot clearance (p = 0.004, η2p = 0.284), maximum knee internal rotation angle (p = 0.039, η2p = 0.159), first (p = 0.006, η2p = 0.263) and second (p = 0.001, η2p = 0.354) peaks of the knee abduction moment. The post-hoc tests indicated that the pain score (p < 0.001, d = 1.831), foot clearance (week0 = 0.18 ± 0.02, week9 = 0.17 ± 0.02, p = 0.001, d = 0.500), maximum knee internal rotation angle (week0 = 16.14 ± 7.80, week9 = 11.08 ± 7.86, p = 0.017, d = 0.646), first (p < 0.001, d = 1.600) and second peaks (p < 0.001, d = 1.583) of the knee abduction moments were significantly decreased in the PNF group; the crossing velocity (week0 = 0.30 ± 0.04, week9 = 0.33 ± 0.03, p = 0.003, d = 0.832) was increased in PNF group, while no change observed in the control group. CONCLUSION: PNF stretching could be used to relieve pain, increase muscle strength, balance knee loadings and improve gait patterns while stepping over obstacles.Funding was provided by Shandong Province Young Innovative Talent Introduction and Cultivation Program (2019-183).
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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".