Implementing exercise and self-management for women with breast cancer during treatment: results of the NEXT-BRCA randomized controlled trial
Bibliographic record
Abstract
The purpose of this study was to determine the feasibility (recruitment, retention, and adherence rates) and effectiveness of institution-based exercise and self-management (SM) on physical activity (PA) level, exercise knowledge and intention, health status, functional capacity, patient engagement, and lower extremity strength for individuals with breast cancer receiving treatment. We conducted a hybrid implementation-effectiveness trial (type 1), including female participants with a current diagnosis of breast cancer undergoing treatment. Participants were randomized to (1) exercise and SM (EXSM; 8 in person exercise sessions and SM education), (2) SM only (8 sessions of SM), or (3) usual care (UC; no intervention). The RE-AIM model was used to explore the interventions success. The primary outcome was PA level at post-intervention. An ANCOVA determined effectiveness of the intervention at each timepoint. Eighty-five participants were included in the study. Study recruitment was 72%. Both the EXSM and SM interventions had high levels of retention (EXSM: 72%; SM: 93%) and adherence (EXSM: 76%; SM: 93%). A significant effect of group was found between EXSM and UC for PA level at post-intervention timepoint (adjusted mean difference: 9.28 (95% CI 6.45, 12.10); p < 0.001), and was maintained at 6- and 12-month follow-ups (11.78 (8.93, 14.64); p < 0.001; 11.10 (8.28, 13.92); p < 0.001). Exercise and SM using strategies that maximize availability and accessibility of exercise and SM services for survivors of breast cancer can successfully be implemented during treatment within the cancer institution in Canada. Future research should explore implementation of this program at multiple centers, maximizing referral of diverse participants from diverse providers, and consider cost-effectiveness of the interventions provided over the long term in order to facilitate sustained implementation across cancer centers.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".