Violence against women during pregnancy and its dimensions in COVID-19 pandemic: A systematic review and meta-analysis
Bibliographic record
Abstract
This systematic review and meta-analysis investigated the prevalence of violence against pregnant women during COVID-19 pandemic based on the available evidence. Medline, Scopus, Web of Science, and Google Scholar were searched. All published observational articles from December 2019 to December 2022 were assessed by two independent authors using the "violence, pregnancy, COVID-19" keywords. The quality appraisal of primary studies conducted using the Newcastle - Ottawa Quality Assessment Scale checklist and 10 eligible articles were included in this review. After reviewing the articles, the prevalence of violence among pregnant women during the COVID-19 pandemic was estimated to be 23% [95% confidence interval (CI) =18 to 29%] using the random effect model. Of them, 59% (95% CI = 13 to 105%) was attributed to verbal-behavioral violence, 30% (95% CI = 17 to 42%) emotional violence, 14% (95% CI = 8 to 20%) sexual violence, and 11% physical violence (95% CI = 6 to 17%). The results indicated that the violence prevalence among pregnant women was not different during and before the start of the COVID-19 pandemic. However, the behavioral-verbal, emotional, physical, and sexual violence were the most common forms of violence.
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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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.031 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".