Healthy Immigrant Effect and Immigrant Women’s Health Issues in Canada: A Scoping Review of Health Measures
Bibliographic record
Abstract
The healthy immigrant effect describes a phenomenon in which immigrants lose health advantage overtime as they reside longer in their migrated country. A scoping review was conducted to observe whether this phenomenon is also observable in the Canadian immigrant demographic specific to women’s health issues. A search strategy was used to collect relevant quantitative studies from MEDLINE, Embase, PsycINFO, Healthstar, and CINAHL databases. The studies examined the relationship between duration of residence in Canada and cervical screening rates, intimate partner violence, help seeking rates for intimate partner violence, and a range of obstetrical outcomes including antenatal and postpartum depression, maternal placental syndrome, illness and hospitalization during pregnancy, and preterm birth. The studies reported gradual approximation of immigrant health status and behaviours to long-term resident or Canadian-born patterns. However, the direction of the effect varied for each health measure. Immigrants were less likely to experience intimate partner violence, maternal placental syndrome, illness or hospitalization during pregnancy, and preterm birth, but were more likely to suffer from antenatal and postpartum depression and less cervical screening. Ethnic background and country of origin seem to modulate these effects. Clinical implications of the study encourage the health care system to consider the unique needs and risk factors of the recent immigrant population including economic, language, and social challenges, while discouraging acculturation of immigrants to harmful lifestyles and behaviours. The researchers recommend future studies to account for specific dynamics within ethnic and language groups and to utilize more longitudinal designs.
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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 | 0.019 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.027 | 0.042 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 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".