Impact of depression and anxiety on cancer patients' perceptions of lifestyle behaviors.
Bibliographic record
Abstract
141 Background: Health behaviors including tobacco use, alcohol consumption, and physical activity (PA) can impact outcomes in cancer survivors. While the peri-diagnostic period can be a "teachable moment" for behavior change, patients may face barriers including mental health comorbidities. We have previously identified that patient perceptions of behaviors can influence behavior change. Here, we evaluated the impact of anxiety and depression on patient perceptions of these behaviors. Methods: Cancer patients from all disease sites were surveyed (2016-17) on their smoking, alcohol habits, and PA, and perceptions of the impact of these behaviors on fatigue, survival, and quality of life (QofL). Survey data were linked with same day Edmonton Symptom Assessment Symptom (ESAS) anxiety and depression scores. Logistic regression models evaluated the impact of anxiety and depression on patient perceptions. Results: Of 496, 53% were male; median age, 60 years. At diagnosis, 20% were current smokers, 47% were current drinkers, and 67% were not meeting PA guidelines. 30% screened positive for anxiety (ESAS anxiety > 3) and 34% screened positive for depression (ESAS depression > 2); mean [standard deviation] scores were 1.9 [2.3] for anxiety and 1.5 [2.2] for depression. Most current smokers (> 80%) perceived smoking to negatively impact fatigue, survival and QofL. Smokers screening positive for anxiety were more likely to perceive smoking as harmful on survival (OR=9.09, 95% CI (1.15-100), P=0.04); greater ESAS anxiety scores were associated with perceiving smoking to worsen survival (OR=1.51 per point, 95% CI (1.04-2.17), P=0.03). While those less physically active at diagnosis (> 65%) felt that PA improves fatigue, survival and QofL and half of current drinkers (45%-50%) felt that alcohol worsens outcomes, anxiety and depression were not found associated with perceptions (P > 0.10). Conclusions: Among current smokers, greater anxiety scores and those screening positive for anxiety were more likely to perceive continued smoking as harmful to survival. Mental health comorbidities were not found to have an impact on patient perceptions of the effect of alcohol consumption and PA on fatigue, survival, and QofL.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".