Modifiable lifestyle behaviours impact the health‐related quality of life of bladder cancer survivors
Bibliographic record
Abstract
OBJECTIVE: To examine health behaviours in bladder cancer survivors including physical activity (PA), body mass index, diet quality, smoking and alcohol consumption, and to explore their relationship with health-related quality of life (HRQoL). SUBJECTS/PATIENTS AND METHODS: Cross-sectional questionnaire packages were distributed to bladder cancer survivors (muscle-invasive bladder cancer [MIBC] and non-muscle-invasive bladder cancer [NMIBC]) aged >18 years, and proficient in English. Lifestyle behaviours were measured using established measures/questions, and reported using descriptive statistics. HRQoL was assessed using the validated Bladder Utility Symptom Scale, and its association with lifestyle behaviours was evaluated using analysis of covariance (ancova) and multivariate regression analyses. RESULTS: A total of 586 participants completed the questionnaire (52% response rate). The mean (SD) age was 67.3 (10.2) years, and 68% were male. PA guidelines were met by 20% (n = 117) and 22.7% (n = 133) met dietary guidelines. In all, 60.9% (n = 357) were overweight/obese, and the vast majority met alcohol recommendations (n = 521, 92.5%) and were current non-smokers (n = 535, 91.0%). Health behaviours did not differ between MIBC and NMIBC, and cancer treatment stages. Sufficient PA, healthy diet, and non-smoking were significantly associated with HRQoL, and the number of health behaviours participants engaged in was positively associated with HRQoL (P < 0.001). CONCLUSION: Bladder cancer survivors are not meeting guidelines for important lifestyle behaviours that may improve their overall HRQoL. Future research should investigate the impact of behavioural and educational interventions for health behaviours on HRQoL in this population.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".