Effect Of Klapp’s Exercises Through Telerehabilitation on The Health-Related Quality of Life of Patients with Scoliosis
Bibliographic record
Abstract
Aim: This study determined the effect of Klapp’s exercises through telerehabilitation on the health-related quality of life of patients with scoliosis. Methods: This study used one-group pretest-posttest design to determine if there is a significant difference between the pretest and posttest of patients with scoliosis with respect to intensity and quality of pain experienced by participants using the McGill short form pain questionnaire, extent of curvature of the spine using the Cobb angle measurement and health- related quality of life (HRQoL) using the quality-of-life profile for spine deformities. The Klapp’s exercise was recorded, stored and forwarded to the patients. The Klapp’s exercise was done for 20 sessions, five times a week. Results: Klapp’s exercises delivered through tele-rehabilitation decreases the degree of curvature of the spine (p = 0.05) and increase the quality of life (p = 0.000) of patients with scoliosis but there is no significant difference in terms of intensity of pain (p = 0.257). Conclusion and Implications: Based on the findings of the study, Klapp’s exercises delivered through telerehabilitation can improve the health-related quality of life of patients with scoliosis; given the patients have good internet connection, appropriate gadgets, consistent monitoring of patients and expert instructions for the intervention from the therapist. Results of this study may use as guidelines in implementing telerehabilitation as mode of physical therapy interventions.
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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 | 0.001 |
| 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) | 0.004 | 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".