Exercise Prescription and Adherence for Breast Cancer
Bibliographic record
Abstract
PURPOSE: To prospectively assess adherence to oncologist-referred, exercise programming consistent with current recommendations for cancer survivors among women with early breast cancer across the trajectory of adjuvant treatment. METHODS: Sixty-eight women participated in supervised, hour-long, moderate-intensity, aerobic, and resistance exercise thrice per week during adjuvant chemotherapy ± radiation, with a step-down in frequency for 20 additional weeks. Adherence to exercise frequency (i.e., attendance), intensity, and time/duration, and barriers to adherence were tracked and compared during chemotherapy versus radiation, and during treatment (chemotherapy plus radiation, if received) versus after treatment. RESULTS: Attendance decreased with cumulative chemotherapy dose (cycles 1-2 vs cycles 3-8, cycle 3 vs cycles 7-8, all P ≤ 0.05) and was lower during chemotherapy than radiation (64% ± 25% vs 71% ± 32%, P = 0.02) and after treatment than during treatment (P < 0.01). Adherence to exercise intensity trended toward being higher during chemotherapy than radiation (69% ± 23% vs 51% ± 38%, P = 0.06) and was higher during than after treatment (P = 0.01). Adherence to duration did not differ with treatment. Overall adherence to the resistance prescription was poor, but was higher during chemotherapy than radiation (57% ± 23% vs 34% ± 39%, P < 0.01) and was not different during than after treatment. The most common barriers to attendance during treatment were cancer-related (e.g., symptoms, appointments), and after treatment were life-related (e.g., vacation, work). CONCLUSIONS: Adherence to supervised exercise delivered in a real-world clinical setting varies among breast cancer patients and across the treatment trajectory. Behavioral strategies and individualization in exercise prescriptions to improve adherence are especially important for later chemotherapy cycles, after treatment, and for resistance exercise.
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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 | 0.004 |
| 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 | 0.001 |
| 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".