Racial Background and Health Behaviors Among Adults With Cancer in Canada: Results of a National Survey
Bibliographic record
Abstract
BACKGROUND: This study was an assessment of the impact of racial background on health behaviors among Canadian adults with a concurrent or past history of a cancer diagnosis. METHODS: The Canadian Community Health Survey datasets (2015-2018) were accessed, and adults (age ≥18 years) with cancer were reviewed. Information about the racial background, socioeconomic status, and different health behaviors was reviewed. Multivariable logistic regression analyses for factors associated with different health behaviors were conducted. RESULTS: A total of 20,514 participants with a history of cancer were considered eligible and were included in the analysis. Compared with individuals who self-identified as White, those who self-identified as indigenous were less likely to have received an influenza vaccination in the past year (odds ratio [OR], 1.253; 95% CI, 1.084-1.448), less likely to have drunk alcohol in the past 12 months (OR, 0.641; 95% CI, 0.546-0.752), more likely to be current smokers (OR, 2.245; 95% CI, 1.917-2.630), and more likely to have used recreational drugs in the past 12 years (OR, 1.488; 95% CI, 1.076-2.057). Compared with individuals who self-identified as White, those who self-identified as non-White and nonindigenous were less likely to have received an influenza vaccination in the past year (OR, 1.207; 95% CI, 1.035-1.408), less likely to have drunk alcohol in the past 12 months (OR, 0.557; 95% CI, 0.463-0.671), and less likely to be current smokers (OR, 0.605; 95% CI, 0.476-0.769). CONCLUSIONS: Within the Canadian context, there is a considerable variability in the health behaviors of adults with cancer according to their racial background. There is a need to tailor the survivorship care planning of patients with cancer based on socioeconomic context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".