Intimate Partner Violence During Pregnancy among Postnatal Mothers Attending Health Centers in Lalitpur District, Nepal: An Observational Study
Bibliographic record
Abstract
Introduction: Any form of intimate partner violence during pregnancy can push women into critical situations. It may result in inadequate prenatal care, poor nutrition, depression, and even death, which are all preventable maternal outcomes. For the neonate, the effect can be low birth weight, preterm birth, and even neonatal death. Therefore, this study aims to assess the prevalence of intimate partner violence among postnatal mothers attending Health Centres. Methods: A descriptive cross-sectional design with a probability cluster sampling technique was used for the study. The data was collected using interview schedules from 325 postnatal mothers using a modified form of the domestic violence tool from the Nepal Demographic Health Survey. Results: A total of 92 (28.30%) of mothers experienced some form of violence. Specifically, 62 (19.08%) endured psychological abuse, 49 (15.08%) suffered actual physical violence, and 52 (16.00%) were victims of sexual violence. Conclusions: This study reveals a significant prevalence of intimate partner violence, with over a quarter of postnatal mothers experiencing some form of abuse. These findings highlight a critical public health issue in Nepal, indicating that a substantial number of mothers and their infants are at risk of severe health consequences due to violence from an intimate partner.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".