A mixed-methods evaluation of a community physical activity program for breast cancer survivors
Bibliographic record
Abstract
BACKGROUND: Given the benefits of physical activity for health and survival, clinicians are seeking opportunities for cancer patients to become more active independent of rehabilitation programs that are small, time-limited, and location specific. This proof-of-concept study evaluated a community-based physical activity program (Curves™) for increasing physical activity among women diagnosed and treated for breast cancer. METHODS: Women were recruited from a breast cancer clinic through physician chart review. In study 1, women (n = 14) received the community physical activity memberships (Curves™), guidelines, and a pedometer. This group was compared to women (n = 16) who received physical activity guidelines and a pedometer on changes in physical activity. In study 2, women (n = 66) completed self-report questionnaires after Curves™ memberships expired to evaluate the program. Study 3 was a qualitative study exploring the benefits and barriers of the physical activity program among women (n = 6) who attended Curves™ regularly. RESULTS: Provision of memberships to a community-based physical activity program did not improve physical activity levels beyond educational and information resources. However, there are a number of advantages to community-based physical activity programs, and the women offer a number of suggestions for improvements for community physical activity opportunities aimed at breast cancer survivors. CONCLUSIONS: Women-only community-based physical activity programs may be a viable option to help introduce women to get active after treatment. Trial registration ISRCTN, ISRCTN14747810. Registered on 18 October 2017-Retrospectively registered, https://doi.org/10.1186/ISRCTN14747810.
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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 | 0.023 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".