Exploring the impact of intimate partner violence on children’s behavior in urban slums of Dhaka City, Bangladesh
Bibliographic record
Abstract
Background & Aim: Intimate partner violence (IPV) is highly prevalent in Bangladesh especially in lower socioeconomic groups. The aim of this research was to identify the prevalence and nature of IPV and determine its association with young children‟s behavior in urban slums. Methods & Materials: This cross-sectional survey was conducted on married women with at least one child aged 4-5 years and living with the father of that child (n = 182). The socioeconomic status (SES) questionnaire, the Strengths and Difficulties Questionnaire (SDQ), and IPV questionnaire were used to collect data. The SDQ consists of 4 subscales of difficulties and 1 prosocial subscale. Bivariate correlations and multiple regression analysis were conducted to determine the association of SDQ with IPV. Results: Almost 90% of women had at least once experienced any type of IPV. Some married women had experienced all types of physical, emotional, and sexual violence by their husband throughout their married life. Children, whose mothers experienced IPV, had higher scores of total difficulties on SDQ as well as emotional symptoms and conduct problems compared to those whose mothers did not experience IPV. The study showed that 1 unit increase in emotional violence by the intimate partner independently led to the increase of the total difficulties score by 0.60 units and the emotional symptom problems by 0.28 units (P ≤ 0.05). The regression models showed the 1 unit increase in physical violence by the intimate partner predicted an increase of 0.59 units in the child‟s total difficulties scores (P ≤ 0.05). Conclusion: IPV is widely prevalent in Bangladesh and affects children‟s behavior. The implications for developing policy to educate and intervene are immense and emphasis must be placed on the age appropriate development of exposed children.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".