The Effect of a Course of Swiss Ball Training and Ear Acupuncture on Pain and Endurance of Trunk Muscles in People with Low Back Pain
Bibliographic record
Abstract
Background: Low back pain is one of the most common health problems worldwide, but there is no agreement on the most appropriate treatment intervention. Objectives: The aim of this study was to evaluate the effect of Swiss ball training and ear acupuncture on pain and central muscle endurance in women with chronic non-specific low back pain. Methods: In this quasi-experimental study, 45 patients with non-specific chronic low back pain participated voluntarily. They were divided into three equal groups (Swiss ball, ear acupuncture, and control) based on random sampling, g each group consisted of 15 people. The Swiss ball and ear acupuncture groups underwent treatment for six weeks. The control group was asked to continue their daily activities before and after six weeks of the intervention. Pain and central muscle endurance were measured using visual analog scale (VAS) and McGill tests, respectively. Analysis of variance (ANOVA) and paired t-tests were used to analyze the data of inter-group and intra-group, respectively. Results: The results of the present study showed that pain intensity and disability were significantly reduced in both groups of ear acupuncture, Swiss ball, and central muscle endurance increased (P = 0.001); however, no significant difference was observed between the two post-tests (P > 0.05). Conclusions: According to the results of the present study, it seems that both interventions, including ear acupuncture and Swiss ball, can reduce the severity of pain and also increase central muscle endurance in women with non-specific chronic low back pain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".