Bibliographic record
Abstract
Purpose: The purpose of this study was to investigate the effect of manual lymphatic drainage (MLD) methods on muscle tone, pain, and depression in patients with breast cancer. Methods: The study had a two-group pretest-posttest design. A total of 24 patients with breast cancer voluntarily participated in the study. Subjects were randomly assigned to the MLD (n=12) and control (n=12) groups. Measurements of muscle tone, pain, and depression were taken prior to starting the intervention and after completing the 4 week program. The muscle tone, pain, and depression were measured using noninvasive muscle tone measuring equipment, the short-form McGill pain questionnaire, and the Beck depression inventory, respectively. The intervention was performed for 20 minutes a day, three times a week, for four weeks. A paired t-test was used to compare pretest and posttest values within each group, and an independent t-test was used to compare to pretest and posttest changes between the groups. Results: Comparison of the effects within the groups revealed significant reductions in muscle tone, pain, and depression in the MLD group after 4 weeks (p<.05), whereas the control group showed no differences. Comparison of the effects between the groups revealed significantly better reductions in muscle tone, pain, and depression in the MLD group than in the control group after 4 weeks (p<.05). Conclusion: These results suggest that MLD is an effective method for reducing muscle tone, pain, and depression in patients with breast cancer.
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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) | 0.002 | 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".