Intimate Partner Violence, Mental Health Services and the COVID-19 Pandemic in Ontario: What are the differences, if any, in mental health service accessibility and service satisfaction during COVID-19 between women in abusive relationships and women in non-abusive relationships?
Bibliographic record
Abstract
Introduction: Intimate partner violence (IPV) increased during the COVID-19 pandemic in Canada as a result of increased economic pressures and social isolation brought on by stay-at home orders. During the COVID-19 pandemic, women experiencing IPV experienced declines in mental health conditions and unique difficulties in accessing mental health services amid closures, shifts in service delivery, and inconsistent availabilities.\nMethods: An online survey was administered to 44 women living in Ontario (23 who had not experienced IPV and 16 who had not) to explore their satisfaction and access to mental health services during the COVID-19 pandemic. Descriptive statistics were used to explore differences in access and satisfaction between those who had experienced IPV and. Those who had not. An inductive thematic analysis was used to understand the types of barriers being faced by women.\nResults: Women who experienced violence had higher means for satisfaction and demonstrated lower barriers of access. Women indicated using a range of mental health services with primary health care providers and pharmacies being used more frequently. The main barriers to access faced by women were waitlist challenges and the limited availability of healthcare. professionals.\nConclusion: This study highlights the nuances of access and satisfaction while capturing the need for multi-sectoral collaboration in ensuring that women know which services are available to them during global crises. Further research is required to explore the satisfaction and access of women experiencing IPV with specific mental health services.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".