Activity Tracker to Prescribe Various Exercise Intensities in Breast Cancer Survivors
Bibliographic record
Abstract
PURPOSE: To prescribe different physical activity (PA) intensities using activity trackers to increase PA, reduce sedentary time, and improve health outcomes among breast cancer survivors. The maintenance effect of the interventions on study outcomes was also assessed. METHODS: The Breast Cancer and Physical Activity Level pilot trial randomized 45 breast cancer survivors to a home-based, 12-wk lower (300 min·wk at 40%-59% of HR reserve) or higher-intensity PA (150 min·wk at 60%-80% of HR reserve), or no PA intervention/control. Both intervention groups received Polar A360® activity trackers. Study outcomes assessed at baseline, 12 and 24 wk included PA and sedentary time (ActiGraph GT3X+), health-related fitness (e.g., body composition, cardiopulmonary fitness/V˙O2max), and patient-reported outcomes (e.g., quality of life). Intention-to-treat analyses were conducted using linear mixed models and adjusted for baseline outcomes. RESULTS: Increases in moderate-vigorous intensity PA (least squares adjusted group difference [LSAGD], 0.6; 95% confidence interval [CI], 0.1-1.0) and decreases in sedentary time (LSAGD, -1.2; 95% CI, -2.2 to -0.2) were significantly greater in the lower-intensity PA group versus control at 12 wk. Increases in V˙O2max at 12 wk in both interventions groups were significantly greater than changes in the control group (lower-intensity PA group LSAGD, 4.2; 95% CI, 0.5-8.0 mL·kg·min; higher-intensity PA group LSAGD, 5.4; 95% CI, 1.7-9.1 mL·kg·min). Changes in PA and V˙O2max remained at 24 wk, but differences between the intervention and control groups were no longer statistically significant. CONCLUSIONS: Increases in PA time and cardiopulmonary fitness/V˙O2max can be achieved with both lower- and higher-intensity PA interventions in breast cancer survivors. Reductions in sedentary time were also noted in the lower-intensity PA group.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".