Service provider perspectives on how COVID-19 and pandemic restrictions have affected intimate partner and sexual violence survivors in Canada: a qualitative study
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic may increase risk of intimate partner and sexual violence and make relevant services less accessible. This study explored the perspectives of intimate partner and sexual violence workers across Canada on how the COVID-19 pandemic has affected the survivors with whom they work. METHODS: Using a qualitative descriptive design, we interviewed 17 management and frontline staff of organizations supporting survivors of intimate partner and sexual violence across Canada. RESULTS: We identified 4 themes that describe the impacts of COVID-19 on intimate partner and sexual violence survivors, from the perspective of service providers: (1) No escape; (2) Isolation; (3) Tough decisions; and (4) Heightened vulnerability. These narrative findings are presented first, followed by an analysis within a social determinants of health framework. Interpreting our findings against such a framework revealed a complex interplay of social determinants, notably social support, access to services, and poverty, that produced several challenges for intimate partner and sexual violence survivors during COVID-19. CONCLUSION: According to service providers, intimate partner and sexual violence survivors in Canada faced several challenges during the pandemic, including reduced ability to escape their situations, increased isolation, increasingly complex decisions, and heightened vulnerability. Our findings demonstrate the critical need to adopt a broader, more holistic approach in tackling intimate partner and sexual violence by also addressing socioeconomic issues such as poverty and marginalization.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.024 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".