Emotional and Physical Child Abuse in the Aftermath of Natural Disasters: a Focus on Haiti
Bibliographic record
Abstract
Background: Child abuse remains a public health and human rights issue with severe consequences. Natural disasters can cause physical, social, and psychological stressors, which may lead to an increase in child directed abuse. Objective: The aim of this study was to i) investigate the social and living conditions of households in Haiti pre- and post 2010 Haiti earthquake, ii) to determine the household prevalence of emotional, physical, and severe physical abuse in children aged 2-14 post-earthquake, and iii) to explore the association between earthquake-related loss and experiences of emotional, physical, and severe physical child abuse in the household. Methods: A nationally representative sample of Haitian households from the 2005/6 (n=9888) and 2012 (n=13181) cycle of the Demographic and Health Survey (DHS) was used. Descriptive analysis was summarized using frequencies and measures of central tendency. Chi-squared and independent T-tests were used to compare data that was available pre-and post-earthquake. Associations between earthquake-related loss and emotional, physical, and severe physical child abuse was assessed using multivariate log-binomial regression models. Results: Comparing pre-post-earthquake, noteworthy improvements were observed in the educational attainment of the household head (9.1% decrease in “no education” category) and in possession of the following household items: electricity, television, mobile-phone, and radio. The prevalence estimates of emotional, physical, and severe physical abuse, in the month prior to the 2012 survey, was 78.5%, 77.0%, and 15.4% respectively. Two years following the earthquake, death of a household member was associated with a higher likelihood of a child being victim to emotional (RR=1.11, 95% CI: 1.05-1.17) and severe physical abuse (RR=1.49, 95% CI: 1.14-1.94). Conversely, injury of a household member was associated with a lower likelihood of a child experiencing emotional abuse (RR=0.67, 95% CI: 0.52-0.87). Visual mapping revealed that the prevalence of severe physical abuse in settlement camps was notably higher (25.0%) compared to the overall prevalence in Haiti (15.4%). Conclusions: Results of this study highlight a need to better protect children in Haiti from abuse. We found associations between some forms of earthquake related loss and child abuse patterns that would warrant further study and consideration in other contexts of natural disaster.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".