The Effects of Concurrent Training on the Body Composition, Quality of Life, and Sleep Quality of Postmenopausal Women with Breast Cancer
Bibliographic record
Abstract
Background: Concurrent training is more effective in developing fitness indicators than doing endurance and resistance training separately. However, there has been limited research to evaluate the effects of this type of exercise training on improvement of body composition and quality of life indicators in postmenopausal women with cancer. Objectives: The present study aimed to determine the effects of eight-week of concurrent training on body composition, quality of life, and sleep quality in postmenopausal women with breast cancer. Methods: This study was conducted on 42 women with breast cancer who were selected randomly and divided into exercise training and control groups. The training group followed eight-week of resistance training (2 - 3 sets, 10 - 18 repetitions, and 50% - 70% 1RM) and aerobic training (50% - 70% maximum heart rate, 12 - 14 Borg scale, and 20 - 40 minutes). Anthropometric characteristics were measured based on body composition (ZEUS 9.9), the sleep quality was measured by the Pittsburgh sleep quality index (PSQI), and the quality of life was measured by the McGill quality of life (MQOL) questionnaire. Two-way repeated measures ANOVA has been used for McGill’s analysis of variance (P < 0.05). Results: The results showed a significant decrease in sleep quality score, weight, fat percentage, BMI, and waist circumference in the training group (P < 0.05), as well as an increase in quality of life index in the training group (P < 0.05). However, no significant changes were observed in the Waist-hip ratio (WHR) values of the training group compared with the control group (P > 0.05). Conclusions: Although the changes in WHR index were not significant after eight weeks of concurrent training, this type of training program could be considered as a beneficial way for improving body composition, quality of life, and sleep quality 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) | 0.001 | 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".