Risk Factors and Health Profiles of Recent Migrant Women Who Experienced Violence Associated with Pregnancy
Bibliographic record
Abstract
BACKGROUND: Violence associated with pregnancy is a major public health concern, but little is known about it in recent migrant women. This study looked at (1) risk factors for violence associated with pregnancy among newly arrived migrant women in Canada and (2) if those who experienced violence associated with pregnancy had a different health profile or use of healthcare services for themselves or their infants during pregnancy and up to 4 months postpartum compared to other childbearing migrant women. METHODS: Pregnant migrant women in Canada <5 years were recruited in 12 hospitals in 3 large cities between 2006 and 2009 and followed to 4 months postpartum. Data were collected on maternal background, migration history, violence associated with pregnancy, maternal and infant physical and mental health, and services used. RESULTS: Of a total of 774 pregnant migrant women, 59 (7.6%) women reported violence associated with pregnancy. Migrant women who experienced violence, compared to those who did not, were at increased risk of violence if they lived without a partner, were asylum seekers, migrated <2 years ago, or had less than high school education. Women who reported violence were less likely to have up-to-date vaccinations, take folic acid before pregnancy, more likely to commence prenatal care after 3 months gestation and to not use contraceptives after birth. They were also more likely to have a history of miscarriage and report more postpartum pain and increased bleeding. They were also more likely to have inadequate social support and report more depression, anxiety, somatization, and posttraumatic stress disorder (PTSD) on standardized tests. No differences were found in the health status of the infants of women who experienced violence compared to those who did not. CONCLUSIONS: Clinicians should sensitively ask recent migrant women (asylum seekers, refugees, and nonrefugee immigrants) about violence associated with pregnancy and appropriately assess, treat, and refer them.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".