Prevalence and Factors Associated with Domestic Violence During Pregnancy in Arua District, Uganda, 2015
Bibliographic record
Abstract
Background: Domestic violence during pregnancy is a serious public health challenge threatening maternal and fetal health outcomes. In Uganda, 16% of women experienced domestic abuse during pregnancy (UDHS 2011). Objective: To investigate the prevalence and factors associated with domestic violence during pregnancy in Arua district so as to identify the magnitude of the problem, inform policy so as to protect pregnant women. Methods: A cross-sectional study was conducted. Multi stage sampling technique was applied. Interviewer administered questionnaires were used. Binary and multi variable logistic regression analyses were carried out to identify strongest factors associated with domestic violence. Results: A total of 459 pregnant women were sampled. Prevalence of domestic violence during pregnancy was 48%. Emotional violence was the most prevalent form of violence (40%) followed by physical abuse contributing 29% and sexual violence 28%. Pregnant women reported husbands as their most perpetrators. Partner’s alcohol consumption was the strongest risk factor associated with domestic violence during pregnancy (AOR 12.20 CI 2.25-65.92) followed by number of wives (AOR 2.16 C.I 1.08-4.32), wanting to be pregnant (AOR 0.26 C.I 0.14-0.48) and occupation too (AOR 2.22 C.I 1.12-4.42). Conclusions: Domestic violence against pregnant women was quite high. Almost five in ten women experienced domestic violence. Partner’s alcohol consumption and number of wives were the strongest factors. Partner involvement during antenatal period is important. Increased attention to this vulnerable group is needed to improve maternal and child health. Antenatal care is known to be an important window of opportunity in providing support.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".