Life dissatisfaction in Canadians aged 40 and above with cancer and mental health disorders: A cross‐sectional study using the Canadian Community Health Survey
Bibliographic record
Abstract
BACKGROUND: Life dissatisfaction varies with different factors--particularly in the presence of chronic conditions, such as cancer. The combination of cancer and mental health disorders may increase life dissatisfaction due to lowered resilience against stress. We sought to determine if life dissatisfaction is higher in Canadians aged 40 and above with cancer compared to the cancer-free population and if there is a synergistic effect between cancer and mental health disorder on life dissatisfaction. METHODS: We conducted a cross-sectional study using the 2015-2016 Canadian Community Health Survey. We included 67,294 subjects aged 40+, and evaluated the association between cancer, mental health disorders, and life dissatisfaction using logistic regression and odds ratios (ORs) while adjusting for age, sex, marital status, education level, and chronic conditions. Relative excess risk due to interaction (RERI), attributional proportion due to interaction (AP), and Synergy index (S-index), were calculated to determine the significance of additive interaction. RESULTS: Compared to the cancer-free population, life dissatisfaction was higher in patients with cancer (OR 2.44, 95% CI: 1.88-3.16) and mental health disorders (OR 5.17, 95% CI: 4.56-5.85). The adjusted ORs for life dissatisfaction were 2.45 (95% CI: 1.74-3.43) and 5.17 (95% CI: 4.55-5.87) for cancer and mental health disorders, respectively, but when both conditions were present, the OR increased to 12.50 (95% CI: 8.40-18.62). The results suggested a synergistic interaction (RERI: 5.89 [95% CI: 0.91-10.87]; AP: 0.47 [95% CI: 0.25-0.69]; and S-index: 2.05 [95% CI: 1.30-3.23]). CONCLUSION: This study showed higher life dissatisfaction in cancer and mental health disorder patients. A synergistic effect was detected between cancer and mental health disorder on life dissatisfaction. These results suggest cancer patients with mental health disorders require additional support and psychological resources to improve their quality of life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".