Acute effects of aerobic exercise and relaxation training on fatigue in breast cancer survivors: A feasibility trial
Bibliographic record
Abstract
OBJECTIVE: This three-armed randomized controlled feasibility trial tested the acceptability and acute effects of aerobic exercise and technology-guided mindfulness training (relative to standalone interventions) on cancer-related fatigue among breast cancer survivors (BCS). METHODS: BCS recruited from Central Illinois completed pre- and post-testing using established measures and were randomized to one of three groups (combined aerobic exercise with guided-mindfulness relaxation, aerobic exercise only, and relaxation only), conducted in three 90 min sessions over the course of 7 days in a fitness room and research office on a university campus. RESULTS: = 4.56 ± 1.81 as measured by the Piper Fatigue Scale. More favorable post-intervention evaluations were reported by the combined group, compared to aerobic exercise or relaxation only (p < 0.05). Reductions in fatigue favoring the combined group (p = 0.05) showed a modest effect size (Cohen's d = 0.91) compared to aerobic exercise only. CONCLUSIONS: These findings provide preliminary evidence for the feasibility of combining evidence-based techniques to address fatigue among BCS. The combined approach, incorporating mobile health technology, presents an efficacious and well-received design. If replicated in longer trials, the approach could provide a promising opportunity to deliver broad-reaching interventions for improved outcomes in BCS. Preregistered-ClinicalTrials NCT03702712.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".