Proprioceptive Neuromuscular Facilitation Neck Pattern and Trunk Specific Exercise on Trunk Control and Balance—an Experimental Study
Bibliographic record
Abstract
Background: Most stroke survivors continue to live with disabilities and may require physical rehabilitation to control the trunk and balance during the post-stroke period. The cause of lack of trunk control and balance among stroke patients is the weakened trunk muscle strength. Purpose: To study the effect of proprioceptive neuromuscular facilitation (PNF) neck pattern and trunk-specific exercise on trunk control and balance among stroke patients. Setting: The study was conducted at the medical wards of Saveetha Medical College and Hospital, Chennai, India. Participants: Sixty patients with stroke who met the inclusion criteria participated in the study. Research Design: This is a quasi-experimental study. Intervention: PNF trunk-specific exercise was administered to the experimental group for 45 min of 28 sessions, which contained 15 min of stretching exercise and 30 min trunk-specific exercise. The control group received routine hospital care services. Main Outcome Measures: The study's primary outcome was balance and trunk control, measured by the Berg Balance Scale (BBS) and Trunk Impairment Scale (TIS) before the intervention and at the end of the intervention of 28 days. Results: < .001). Between-group analysis, both the experimental and control group post-test mean score of TIS (15.03±0.96 &13.70±1.15) and BBS (27.07±1.48 & 25.30±1.73) showed significant difference (p < .001). Conclusion: PNF neck pattern and trunk-specific exercise used in this study effectively improved balance and trunk control among patients with stroke.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".