Connecting breast cancer survivors for exercise: protocol for a two-arm randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Peer-based exercise interventions that cultivate new opportunities for support with a fellow cancer survivor may result in increased exercise volume. It is not clear whether adding qualified exercise professional (QEP) support to peer-based interventions improves health outcomes. Therefore, the purpose of this study is to determine whether breast cancer survivor (BCS) dyads who receive 10 weekly sessions of virtually delivered QEP support have improved outcomes compared to BCS dyads who do not receive QEP support. METHODS: Participants Adult BCS with medical clearance for exercise, who have an internet-connected device, and currently engage in < 150 min of moderate-intensity exercise per week. Intervention BCS will be matched using evidence-based criteria. The intervention group will receive dyadic exercise information sessions and a program tailored by a QEP for 10 weeks (intervention period) and have access to the QEP for an additional 4 weeks (tapering period). The control will not receive any QEP support. Outcomes The primary outcome is post-intervention self-reported exercise volume. Secondary outcomes include device-assessed exercise volume (i.e., Fitbit), social support, and health-related quality of life. Randomization 108 participants, matched in dyads, will be randomized 1:1 to the MatchQEP or Match groups using a web-based scheme. Statistical analysis Outcomes will be measured at baseline, post-intervention, post-tapering, and at 12 weeks post-intervention follow-up. DISCUSSION: The findings from this RCT will determine if matched BCS dyads who receive 10 weeks of virtually delivered QEP support have higher levels of self-report and device-measured exercise, social support, and health related quality of life compared to matched dyads without QEP-delivered exercise guidance. To our knowledge this will be the first study to assess the combined effect of peer- and QEP support on exercise volume. Project findings will inform and optimize intervention methods aimed to increase exercise among BCS through accessible exercise supports. TRIAL REGISTRATION: The study is registered on ClinicalTrials.gov (study identifier: NCT04771975, protocol Version Number: 2, date: July 22, 2021).
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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 | 0.031 | 0.030 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.019 | 0.007 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.113 | 0.017 |
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".