Bibliographic record
Abstract
BACKGROUND: Violence against women is a worldwide issue. Emotional abuse of women is the second most common form of abuse after physical abuse. Thus, this issue needs focus and attention especially among disadvantaged communities such as refugees.OBJECTIVE: This study aimed to investigate the prevalence of emotional abuse among Syrian refugee women in Jordan.METHODS: A descriptive cross-sectional study was conducted using a convenient sample of 182 Syrian refugee women residing in Mafraq Governorate. Participants were recruited from Maternal & Child Health Centers (MCHC) across the governorate. A validated Arabic version of the NorVold Domestic Abuse Questionnaire (NORAQ) was used to collect data from the study participants.RESULTS: Participants’ ages ranged from 19 to 55 years, (mean age ± 30.2; SD ± 8.9 years). Forty four percent of the participants reported experiencing emotional abuse in the preceding year prior the evaluation. The lifetime prevalence of emotional abuse was 51.6%. About 21.4% of married refugees surveyed reported emotional abuse from their husbands. Thirteen percent of the married participant reported being emotionally abused by their brothers. Twelve of the unmarried participants reported that the perpetrators were family members (4 fathers, 7 brothers, and 1 mother). Logistic regression model revealed that Syrian refugee women who are married, live within large families, reside in urban areas, and have lower educational levels are more likely to suffer emotional abuse. A significant association was found between exposure to emotional abuse and poor mental health, including depression, insomnia and feelings of anguish.CONCLUSION: High prevalence rate of life time abuse was revealed by this study. Overall, findings suggest that improving socio-demographic circumstances (i e education) would reduce their vulnerability to emotional abuse. This study may guide both future research and current efforts to combat emotional violence amongst Syrian refugee women.
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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 | 0.000 |
| 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".