Partner Disengagement from Pregnancy and Adverse Maternal and Infant Outcomes
Bibliographic record
Abstract
OBJECTIVE: To assess whether partner disengagement from pregnancy is associated with adverse maternal and infant outcomes. MATERIALS AND METHODS: We analyzed data from the 2006-2007 Canadian Maternity Experiences Survey, comprising a cross-sectional representative sample of 6,421 childbearing women. Multiple logistic regression assessed the association between adverse outcomes and three indicators of partner disengagement: (1) partner did not want the pregnancy, (2) partner argued more than usual in the year prior to the baby's birth, and (3) partner was absent at the delivery. RESULTS: Of all respondents, 3.8% had partners who did not want the pregnancy, 16.1% argued more than usual with their partner in the past year, and 7.6% had partners who were absent at the delivery. Women whose partner did not want the pregnancy were more likely to report intimate partner violence (IPV) (adjusted odds ratio [AOR] 3.55; 95% confidence interval [95% CI] 2.36-5.14), elevated depressive symptoms in the extended postpartum period (AOR 2.56, 95% CI 1.70-3.83), and nonroutine child healthcare visits after birth (AOR 1.54, 95% CI 1.13-2.11). Women whose partner argued more in the past year had higher odds of IPV (AOR 4.82, 95% CI 3.69-6.30), elevated depressive symptoms in the extended postpartum period (AOR 3.63; 95% CI 2.84-4.64), and nonroutine child healthcare visits (AOR 1.49, 95% CI 1.26-1.77), after adjustment for potential confounders. CONCLUSIONS: Partner disengagement is common and is associated with adverse maternal and infant outcomes. Affected women may benefit from special assistance during pregnancy and after delivery.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".