The association between disrespect and abuse of women during childbirth and postpartum depression: Findings from the 2015 Pelotas birth cohort study
Bibliographic record
Abstract
BACKGROUND: This study examined the association between disrespect and abuse of women during facility-based childbirth and postpartum depression (PD) occurrence. METHODS: We used data from the 2015 Pelotas (Brazil) Birth Cohort, a population-based cohort of all live births in the city. We assessed 3065 mothers at pregnancy and 3-months after birth. Self-reported disrespect and abuse experiences included physical abuse, verbal abuse, denial of care, and undesired procedures. We estimate the occurrence of each disrespect and abuse type, one or more types and disrespect and abuse score. The Edinburgh Postnatal Depression Scale (EPDS) was used to assess PD. EPDS scores ≥13 and ≥15 indicated at least moderate PD and marked/severe. Odds ratios (OR) were calculated by logistic regression. RESULTS: The prevalence of at least moderate PD and marked/severe PD was 9.4% and 5.7%, respectively. 18% of the women experienced at least one type of disrespect and abuse. Verbal abuse increased the odds of having at least moderate PD (OR = 1.58; 95%CI 1.06-2.33) and marked/severe PD (OR = 1.69; 95%CI 1.06-2.70) and the effect among women who did not experience antenatal depressive symptoms was greater in comparison to those who did (OR = 2.51; 95%CI 1.26-5.04 and OR = 4.27; 95%CI 1.80-10.12). Physical abuse increased the odds of having marked/severe PD (OR = 2.28; 95%CI 1.26-4.12). Having experienced three or more mistreatment types increased the odds of at least moderate PD (OR = 2.90; 95%CI 1.30 - 35.74) and marked/severe PD (OR=3.86; 95%CI 1.58-9.42). LIMITATIONS: Disrespect and abuse experiences during childbirth were self-reported. CONCLUSIONS: Disrespect and abuse during childbirth increased the odds of PD three months after birth. Strategies to promote high quality and respectful maternal health care are needed to prevent mother-child adverse outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".