The effect of a whole body exercise programme and dragon boat training on arm volume and arm circumference in women treated for breast cancer
Bibliographic record
Abstract
The purpose of this study was to examine the effect of a whole body exercise programme and dragon boat training on changes in arm volume in breast cancer survivors. A total of 16 female breast cancer survivors with no clinical history of lymphoedema volunteered. The 20-week exercise programme consisted of resistance and aerobic exercise with the addition of dragon boat training at week 8. Arm circumference at two sites (CIRC10, CIRC15), arm volume (VOL), and upper body strength (1-RM) were measured at baseline (T1), week 8 (T2), and week 20 (T3). All statistical tests were two-sided (alpha < or = 0.05). No significant differences between the ipsilateral and contralateral upper extremities at any of the three time points were found. All variables significantly increased from T1 to T3 (CIRC10: difference, d = 0.49 cm, 95% confidence interval, CI = 0.25-0.73, P = 0.000; CIRC15: d = 1.33 cm, CI = 0.78-1.88, P = 0.000; VOL: d = 100 mL, CI = 69-130, P = 0.000). As well, 1-RM significantly increased from T1 to T3 (d = 10.8 kg, CI = 5.6-16.1; P = 0.000). In summary, participation in a whole body exercise programme and dragon boat training resulted in a significant increase in upper extremity volume over time. However, the changes were consistent for both arms and the significant gain in upper body muscular strength likely accounted for the increase in arm volume.
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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".