Experiences of physical and emotional intimate partner violence during the COVID-19 pandemic: a comparison of prepandemic and pandemic data in a longitudinal study of Australian mothers
Bibliographic record
Abstract
OBJECTIVE: There is a lack of longitudinal population-based research comparing women's experiences of intimate partner violence (IPV) prior to and during the COVID-19 pandemic. Using data from the Mothers' and Young People's Study, the prevalence of physical and emotional IPV in the first year of the pandemic is compared with earlier waves of data. DESIGN: A prospective pregnancy cohort of first-time mothers in Melbourne, Australia was followed up over the first decade of motherhood, with a quick response study conducted during the COVID-19 pandemic. 422 women completed the primary exposure measure (IPV; Composite Abuse Scale) in the 1st, 4th and 10th year postpartum and the additional pandemic survey (June 2020-April 2021). OUTCOME MEASURES: Depressive symptoms; anxiety symptoms; IPV disclosure to a doctor, friends or family, or someone else. RESULTS: Maternal report of emotional IPV alone was higher during the pandemic (14.4%, 95% CI 11.4% to 18.2%) than in the 10th (9.5%, 95% CI 7.0% to 12.7%), 4th (9.2%, 95% CI 6.8% to 12.4%) and 1st year after the birth of their first child (5.9%, 95% CI 4.0% to 8.6%). Conversely, physical IPV was lowest during the pandemic (3.1%, 95% CI 1.8% to 5.0%). Of women experiencing IPV during the pandemic: 29.7% were reporting IPV for the first time, 52.7% reported concurrent depressive symptoms and just 6.8% had told their doctor. CONCLUSIONS: Findings suggest that the spike in IPV-related crime statistics following the onset of the pandemic (typically incidents of physical violence) is the tip of the iceberg for women's IPV experiences. There is a need to increase the capacity of health practitioners to recognise emotional as well as physical IPV, and IPV ought to be considered where women present with mental health problems.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".