FLOURISHING DESPITE A CANCER DIAGNOSIS: FINDINGS FROM A NATIONALLY REPRESENTATIVE STUDY
Bibliographic record
Abstract
This study investigated the association between cancer and complete mental health (CMH). CMH has three elements: 1) absence of mental illness, addictions and suicidal thoughts in the past year; 2) almost daily happiness or life satisfaction in the past month; 3) psychosocial well-being. Control variables included socio-demographics, health behaviours, current physical health and lifetime history of mental illness and childhood maltreatment. The nationally representative 2012 Canadian Community Health Survey-Mental Health was analyzed. This study used bivariate and logistic regression analyses to estimate the odds ratios of CMH among community dwellers aged 50 and older with current cancer (n=438), previous cancer (n=1,174) and no cancer history (n=9,279). Our analyses suggested that adults aged 50 and over with current cancer had a much lower prevalence of CMH (66.1%) than those with previous cancer (77.5%) and those with no cancer history (76.8%). After adjusting for 17 variables, the odds of CMH among those with current cancer remained substantially lower (OR=0.63; 95% CI=0.49–0.79) than those without cancer. Among those who had ever had cancer, the odds of CMH were higher for female, White, married, and older respondents, as well as those with higher socioeconomic status, and no history of childhood physical abuse, substance abuse, depression or anxiety disorder. These findings have a hopeful message for patients and clinicians. Two-thirds of current cancer patients have CMH. Former cancer patients are comparable to those without a cancer history, suggesting substantial resilience.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".