Rural breast cancer survivors: exercise preferences and their determinants
Bibliographic record
Abstract
OBJECTIVE: As a first step in planning interventions to promote exercise in rural breast cancer survivors (BCS), we sought to determine the exercise preferences of rural BCS and to identify the major determinants of these preferences. METHODS: Self-administered mail survey to a population-based sample from a state cancer registry. RESULTS: Among the 483 respondents, 96% were White with mean education of 13+/-2.5 years and mean months since diagnosis of 39.0+/-21.5. Only 19% reported >or=150 min of moderate to vigorous physical activity per week. Although up to half were open to various counseling options, the most popular options were counseling after treatment (36%), face-to-face (47%), and from an exercise specialist (40%). Rural BCS preferred home-based (63%), unsupervised (47%), moderate intensity exercise (65%) that was primarily walking. The strongest preference correlates include higher education with exercise specialist, higher environment score with outdoors, more comorbidities with low intensity and counseling after cancer treatment, higher social support with exercising with friends or family, sedentary or insufficient physical activity with low intensity, and lower household income with preferring supervised exercise. CONCLUSIONS: Interventions designed to promote exercise among rural BCS are needed. Such interventions should consider the environmental aspects of this population and include multiple options based on the preferences of targeted subgroups.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".