Health-Related Maternal Decision-Making Among Perinatal Women in the Context of Intimate Partner Violence: A Scoping Review
Bibliographic record
Abstract
Globally, it is estimated that 245 million women and girls aged 15 and over have experienced intimate partner violence (IPV) in the past 12 months. Moreover, research has highlighted the disproportionately high prevalence of IPV victimization among pregnant women. IPV can have serious health implications for women and their infants, yet little is known about maternal health-related decision-making by mothers exposed to IPV. To this end, the purpose of this scoping review was to examine what is known regarding health-related maternal decision-making among perinatal women in the context of IPV. Using Arksey and O'Malley's framework, five electronic databases were searched, resulting in 630 articles. Eligible articles were primary studies written in English, included participants who experienced IPV at any time in their life, and reported results focused on maternal health-related decision-making in the context of IPV. Thirty-six articles were screened by the review team, resulting in seven included articles. Three main themes emerged regarding health-related maternal decision-making by mothers experiencing IPV, including suboptimal breastfeeding practices, under-utilization of maternal and child health services, and poor adherence to medical recommendations/regimens that impact health-related outcomes for mother and child. The well-established risk of poorer health outcomes among women experiencing IPV, alongside the findings of this scoping review, calls for further research specifically addressing health-related decision-making among perinatal women who experience IPV.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".