Patient and Provider Emergency Care Experiences Related to Intimate Partner Violence: A Systematic Review of the Existing Evidence
Bibliographic record
Abstract
Intimate partner violence (IPV) is a public health problem that has devastating physical, psychological, and economic consequences. The emergency department (ED) is an important point of contact for individuals experiencing IPV. However, there are few studies synthesizing interactions between patients experiencing IPV and providers. We aimed to summarize the existing evidence regarding (1) ED care experiences of patients with a history of IPV and (2) experiences of ED providers interacting with them. The secondary aim of this review was to evaluate high-quality care barriers and facilitators and to elucidate common causes of care avoidance. A literature search of peer-reviewed electronic databases was undertaken. Inclusion criteria consisted of studies detailing IPV-related patient or provider experiences surrounding ED visits. Articles published before 2000 or unavailable in English/French were excluded. A total of 772 studies were screened, yielding a final number of 41 studies. Negative patient experiences arose from individual-, institutional-, and system-level issues, commonly including adverse provider behavior. Negative provider experiences stemmed from individual-, institutional-, and system-level issues, such as a lack of knowledge and lack of infrastructure. Facilitators to positive patient experiences included interacting with empathetic providers, having privacy, and receiving timely specialized care. Facilitators to positive provider experiences included feeling well-equipped to manage IPV and having policies leading to appropriate care. Negative ED care experiences reveal inadequate care quality, ultimately leading to secondary victimization of individuals experiencing IPV. This review also uncovered important literature gaps regarding experiences of those who identify as equity-deserving.
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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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".