Locked down, locked out: a cross-sectional study on experiences of intimate partner violence (IPV) and barriers to formal and informal support during COVID-19 lockdowns in Ontario
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic intensified pre-existing social and health inequities, with individuals actively experiencing intimate partner violence (IPV) facing heightened risks and barriers to support. While lockdowns were necessary for public health, they also increased isolation and limited access to essential formal and informal supports. This study explores the association between IPV experienced during Ontario’s COVID-19 lockdowns (March 2020–June 2021) and barriers to both formal (e.g., health, legal, housing) and informal (e.g., friends, family) support systems. METHODS: A cross-sectional online survey was conducted with 1,344 participants, 18 years or older, who were in an adult relationship and residing in Ontario, Canada during the lockdowns. Participants were recruited through non-probability convenience, quota-based sampling from a pre-existing online panel (Leger Opinion, LEO). Data were analyzed using descriptive statistics, chi-square tests, and multivariable logistic regression to examine associations between IPV and support barriers, controlling for demographic, relational, and health-related factors. RESULTS: Nearly one in four participants (23.4%) self-identified as experiencing IPV (i.e., emotional, sexual, physical, mental, financial, coercive, spiritual and/or technology-based abuse) during the lockdowns. IPV survivors had over three times greater odds of facing multiple barriers to formal supports (aOR = 3.4; 95% CI: 2.16–5.38) and 1.6 times higher odds of decreased communication with friends or family (aOR = 1.6; 95% CI: 1.06–2.31). Risk factors for reduced access included low household income, informal caregiving responsibilities, and perceived community violence. Poor physical and mental health were also significant predictors of reduced access to formal and informal supports. CONCLUSIONS: This study highlights how COVID-19 lockdowns compounded access barriers for participants who self-identified as IPV survivors, limiting both formal services and informal networks. Emergency preparedness plans should maintain IPV service capacity during lockdowns through essential service designations, implement technology-based interventions such as discreet online platforms and text-based safety planning, and create targeted outreach for high-risk groups including low-income households and caregivers. More inclusive frameworks are also needed to ensure that supports are responsive to all survivors—particularly as men and women in this study reported similar IPV experiences and outcomes during lockdowns. Future pandemic responses must proactively fund IPV services rather than rely on reactive, underfunded crisis interventions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 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) | 0.003 | 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".