Breast cancer survivors’ barriers and motives for participating in a group-based physical activity program offered in the community
Bibliographic record
Abstract
PURPOSE: The purpose of this qualitative study was to explore the barriers and motives experienced by women attending an 8-week group-based physical activity program offered in the community following treatment for breast cancer. METHODS: Seven women were interviewed during the first and last week of the program. Data were analyzed using thematic analysis. RESULTS: Factors that hindered women's continued participation could be subdivided into situational barriers, which encompassed community (i.e., distance of center and traffic) and institutional factors (i.e., competing roles and responsibilities), and internal barriers, which consisted of cancer-specific limitations. Motives for initial and continued participation were situational (i.e., gaining social support, networking, and being around similar others) and internal (i.e., feeling a sense of personal fulfillment, acquiring health benefits, and recovering from cancer). CONCLUSIONS: The findings contribute to a deeper understanding of women's motives to engage in a group-based physical activity program after treatment for breast cancer. Further, they underscore the necessity of considering situational and internal barriers when developing group-based physical activity programs to increase regular participation, optimize adherence, and reduce drop-out.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".