Association between current lifestyle behaviors and health-related quality of life in breast, colorectal, and prostate cancer survivors
Bibliographic record
Abstract
The purpose of the present study was to compare cancer survivors on three different lifestyle behaviors (i.e., physical activity, fruit and vegetable (F&V) consumption, and smoking) and examine the association between these lifestyle behaviors and health-related quality of life (HRQOL). Breast (n = 123), colorectal (n = 86), and prostate (n = 107) cancer survivors completed a survey that included lifestyle behavior questions and the RAND-36 Health Status Inventory (HSI). Results showed that similar percentages of breast, colorectal, and prostate cancer survivors met the lifestyle behavior recommendations. Overall, 69.9 and 26.3% reported meeting the recommendations for physical activity and F&V consumption while 94.3% did not smoke. In addition, survivors who met the physical activity recommendation had significantly higher HRQOL than those who did not, however, meeting the F&V recommendation was not related to HRQOL. Nonetheless, survivors who met more than one lifestyle behavior recommendation had significantly higher HRQOL than those who only met one recommendation. Therefore, although it appears that F&V interventions are needed, it may be important to target more than one lifestyle behavior to obtain optimal HRQOL benefits. Importantly, results suggest that physical activity may be the key lifestyle behavior to include in multibehavioral interventions aimed at improving HRQOL.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".