Impact of immigration status on health behaviors and perceptions in cancer survivors.
Bibliographic record
Abstract
27 Background: Health behaviors including smoking cessation, physical activity (PA) and alcohol moderation are key aspects of cancer survivorship. Disparities in health literacy and cancer screening behaviors have been reported between immigrant and native-born cancer patients. However, disparities in health behaviors in cancer survivorship has not been explored. We compared health behaviors and perceptions about these behaviors between immigrant and native-born cancer survivors. Methods: Adult cancer patients from Princess Margaret Cancer Centre (Toronto, Canada) were surveyed on their smoking, PA, and alcohol habits and perceptions of the effects of these behaviors on quality of life (QoL), 5-year survival, and fatigue. Multivariable models evaluated the effect of immigration status on behaviors and perceptions. The effect of originating from a Western vs. non-Western country was also evaluated. Results: Of 1275 patients, 27% self-identified as foreign-born. At 1 year before diagnosis (baseline), 17% smoked, 69% were physically inactive, and 58% consumed alcohol. Although immigration status was not associated with smoking at baseline (P > 0.05), immigrants were less likely to perceive that smoking was harmful on QoL (adjusted odds ratio [aOR] 0.58, P = 0.008), survival (aOR 0.56, P = 0.002), and less so for fatigue (aOR 0.75, P = 0.11). Immigrants were less likely to meet PA guidelines at baseline (aOR = 0.70, P = 0.08), and perceive that PA improved fatigue (aOR 0.62, P = 0.04) and survival (aOR 0.64, P = 0.08). Immigrants were also less likely to drink alcohol at baseline (aOR = 0.47, P = 0.001), but alcohol perceptions did not differ between immigrants and native-born. Those from non-Western countries were less likely to smoke (aOR 0.63, P = 0.03), drink alcohol (aOR 0.48, P = 0.006), or meet PA guidelines at baseline (aOR 0.44, P = 0.006). Conclusions: Immigrants were less likely to perceive continued smoking as harmful and less likely to be aware of the benefits of PA. Patients from non-Western countries were less likely to meet PA guidelines, but were also less likely to smoke or drink at baseline. Culturally tailored counselling should be considered for immigrants who smoke or are physically inactive at baseline.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".