Violence against Women by Their Intimate Partners in Shahroud in Northeastern Region of Iran
Bibliographic record
Abstract
BACKGROUND: Violence against women is one of the worst consequences of cultural, political, and socio-economic inequalities between men and women. Intimate Partner Violence (IPV) has been identified as an important cause of morbidity from multiple mental, physical, sexual, and reproductive health outcomes. Nonetheless, the prevalence and related factors of this international problem have not been investigated extensively in some parts of the world. The aims of this research were to determine the prevalence of physical and mental violence perpetrated by men against their intimate partners and to assess the associated factors of partner violence among women in Shahroud in northeastern region of Iran in 2010. METHODS: This Cross-Sectional study was conducted in Shahroud, in northeast of Iran in 2010. Cluster sampling was done from primary health service institutions, universities, public schools and governmental organizations throughout the city and six hundred married women completed the study. A structured questionnaire with 34 items was designed in three parts to assess the physically (10 items) and mentally (15 items) violent acts by a current intimate male partner and identify collative behaviors (9 items) of victims. The Logistic regression analysis was applied to determine the net effect of background variables on the IPV occurrence within the past year. RESULTS: About 20% of the participants experienced at least one type of physical violence. Increased risk of physical violence was positively associated with the younger age of the couple (OR=3.08, P<0.05), lower education (OR=2.28, P<0.01) and having a semi-manual skilled occupation of husband (OR=3.62, P<0.05), husband's heavy cigarette smoking (OR=2.62, P<0.01), and his drug abuse (OR=2.1, P<0.05). About 85% of the women had experienced mental harassment within the past twelve months. Logistic Regression Analysis found that lower education (OR=3.06, P<0.01) and having semi-manual skilled occupation (OR=3.8, P<0.05) of husband, increasing years of marriage (OR=2.8, P<0.01), husband's heavy cigarette smoking (OR=2.3, P<0.01) and his abusing the use of drugs (OR=3.4, P<0.01) had significant associations with women's experience of mental violence. CONCLUSIONS: Some socioeconomic characteristics such as educational level, occupational status of men, heavy smoking and drug abusing are associated with the occurrence of violence against one's intimate partner. Since IPV is usually unreported, healthcare providers should be aware of the risk factors associated with domestic violence to be able to design preventive measures against its negative health outcomes in 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 | 0.001 | 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) | 0.001 | 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".