COVID-19 and family violence: A rapid review of literature published up to 1 year after the pandemic declaration
Bibliographic record
Abstract
Background: After the World Health Organization declared COVID-19 a pandemic on March 11, 2020, public health restrictions were introduced to slow COVID-19 transmission and prevent health systems overload globally. Work-from-home requirements, online schooling, and social isolation measures required adaptations that may have exposed parents and children to family violence, including intimate partner violence and child abuse and neglect, especially in the early days of the pandemic. Thus, we sought to: (1) examine the occurrence of family violence; (2) identify factors associated with family violence; and (3) identify relevant recommendations, from COVID-19 literature published up to 1 year after the pandemic declaration. Methods: This review was registered on PROSPERO (CRD42021241622), employed rapid review methods, and extracted data from eligible papers in medical and health databases published between December 1, 2019 and March 11, 2021 in MEDLINE, PsycINFO, CINAHL, and Embase. Findings: 28 articles including 29 studies were included in the rapid review. While many studies of families/households revealed rises in family violence incidence, official justice, police, and emergency department records noted declines during the pandemic. Parental stress, burnout, mental distress (i.e. depression), difficulty managing COVID-19 measures, social isolation, and financial and occupational losses were related to increases in family violence. Health services should adopt approaches to prevent family violence, treat victims in the context of public health restrictions, and increase training for digital service usage by health and educational professionals. Interpretation: Globally, restrictions aimed to limit the spread of COVID-19 may have increased the risk factors and incidence of family violence in communities. Official records of family violence may be biased toward under-reporting in the context of pandemics and should be interpreted with caution. Funding: RESOLVE Alberta, Canada and the Emerging Leaders in the Americas Program (ELAP), Global Affairs Canada.
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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 | 0.014 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.031 | 0.029 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".