Cancer Survivors’ Adherence to Lifestyle Behavior Recommendations and Associations With Health-Related Quality of Life: Results From the American Cancer Society's SCS-II
Bibliographic record
Abstract
PURPOSE: To examine the prevalence and clustering of physical activity (PA), fruit and vegetable consumption (5-A-Day), and smoking across six major cancer survivor groups and to identify any associations with health-related quality of life (HRQoL). METHODS: A total of 9,105 survivors of six different cancers completed a national cross-sectional survey that included the lifestyle behavior questions and the RAND-36 Health Status Inventory. RESULTS: Only a minority of cancer survivors were meeting the 5-A-Day (14.8% to 19.1%) or PA (29.6% to 47.3%) recommendations, whereas most were meeting the smoking recommendation (82.6% to 91.6%). In terms of the lifestyle behavior clusters, only 5% of cancer survivors were meeting all three recommendations. Analyses of covariance generally showed higher HRQoL in survivors who were meeting versus not meeting each lifestyle behavior recommendation with the strongest associations emerging for PA. Trend analyses showed a steep positive association between the number of lifestyle behavior recommendations being met and HRQoL for breast (P < .001), prostate (P < .001), colorectal (P < .001), bladder (P < .001), uterine (P < .001), and skin melanoma (P < .001) cancer survivors. CONCLUSION: Few cancer survivors are meeting the PA or 5-A-Day recommendations, and even fewer are meeting all three lifestyle recommendations. The association between the current lifestyle recommendations and HRQoL in cancer survivors appears to be cumulative. Interventions to increase PA and fruit and vegetable consumption and reduce smoking are warranted and may have additive effects on the HRQoL of cancer survivors.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".