Effects of an oncologist’s recommendation to exercise on self-reported exercise behavior in newly diagnosed breast cancer survivors: a single-blind, randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Increased attention has focused on exercise as a quality of life intervention for breast cancer survivors during and after adjuvant therapy. PURPOSE: Our objective was to examine the effects of an oncologist's recommendation to exercise on self-reported exercise behavior in newly diagnosed breast cancer survivors attending their first adjuvant therapy consultation. METHODS: Using a single-blinded, 3-armed, randomized controlled trial, 450 breast cancer survivors were randomly assigned to receive an oncologist exercise recommendation only, an oncologist exercise recommendation plus referral to an exercise specialist, or usual care. The primary outcome was self-reported total exercise (in metabolic equivalent [MET] hours per week) at 5 weeks postconsultation. RESULTS: The follow-up assessment rate was 73% (329 of 450). Intention-to-treat analysis based on participants with follow-up data indicated a significant difference in total exercise in favor of the recommendation-only group over the usual care group (mean difference, 3.4 MET hr per week; 95% confidence interval [CI], 0.7-6.1 MET hr per week; p = .011). There was no significant difference between the recommendation-plus-referral group and the usual care group (mean difference, 1.5 MET hr per week; 95% CI, -1.0 to 4.0 MET hr per week; p = .244). Ancillary "on-treatment" analyzes showed that participants who recalled an exercise recommendation reported significantly more total exercise than participants who did not recall an exercise recommendation (mean difference, 4.1 MET hr per week: 95% CI, 1.9-6.4 MET hr per week; p < .001). CONCLUSIONS: Our findings suggest that an oncologist recommendation may increase exercise behavior in newly diagnosed breast cancer survivors, particularly if it is recalled 1 week after the recommendation.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| 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 | 0.004 | 0.003 |
| 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".