COVID-19 and perinatal intimate partner violence: a cross-sectional survey of pregnant and postpartum individuals in the early stages of the COVID-19 pandemic
Bibliographic record
Abstract
OBJECTIVE: The objectives of this study were to: (1) document violent and controlling behaviours within intimate partnerships during the perinatal period; and (2) determine individual, interpersonal and household-level factors influencing the risk of perinatal intimate partner violence (IPV). DESIGN: Cross-sectional survey. SETTING: The Ottawa Hospital, Department of Obstetrics and Gynecology, Ottawa, Ontario, Canada. PARTICIPANTS: Patients who gave birth at The Ottawa Hospital and were >20 days post partum between 17 March and 16 June 2020. MAIN OUTCOMES AND MEASURES: Perinatal IPV was defined as regular controlling behaviours or act-based forms of emotional/physical/sexual abuse in the 12 months before pregnancy, during pregnancy and/or post partum. Log-binomial multivariable regression models were used to compute adjusted risk ratios (aRRs) and 95% CIs to identify potential risk factors for IPV: maternal age, postpartum depression, parity, increase in partner substance use and household income. RESULTS: Among 216 participants, the median maternal age was 33 years (IQR: 30-36). In total, 52 (24.07%) reported some form of perinatal IPV, 37 (17.13%) reported regular controlling behaviour and 9 (4.17%) reported both. Household income below the municipal median was the strongest risk factor for perinatal IPV (aRR: 3.24, 95% CI: 1.87 to 5.59). There was no apparent association between maternal age (aRR: 0.99, 95% CI: 0.94 to 1.04), postpartum depression (aRR: 1.03, 95% CI: 1.00 to 1.07), nulliparity (aRR: 1.18, 95% CI: 0.71 to 1.97) or increases in partner substance use (aRR: 0.73, 95% CI: 0.42 to 1.25) with IPV. CONCLUSION: One in four individuals in this study experienced perinatal IPV. Household income was the strongest risk factor, and surprisingly, many hypothesised risk factors (eg, mental health, partner substance use, etc) were not significantly associated with perinatal IPV in this sample. This highlights the challenges in both measuring IPV and identifying individuals exposed to perinatal IPV during the high stress of the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".