Translating Physical Activity Interventions for Breast Cancer Survivors into Practice: An Evaluation of Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: Although physical activity (PA) interventions have been effective for improving health outcomes in breast cancer survivors, little is known relative to their potential for translation into practice. PURPOSE: This review was designed to provide a quantitative estimate of the reporting of both internal and external validity in recent studies of PA in breast cancer survivors (BCS). METHODS: The Reach, Efficacy/Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework was utilized to assess the reporting of internal and external validity in 25 randomized controlled trials (RCTs) of PA and BCS published between 1998 and 2008. Each trial was evaluated relative to the degree it met criteria for each of the above dimensions. RESULTS: The majority of studies in this review reported dimensions reflecting internal validity. The overall level of detail relative to external validity of PA interventions was rarely reported, limiting the generalizability of study findings. CONCLUSIONS: As with many RCTs of health behavior change, detail relative to contextual elements of published PA interventions in BCS is limited. It is recommended that future physical activity interventions in BCS be designed to facilitate scalable and sustainable interventions for improving health outcomes in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.103 | 0.226 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".