Screening for Intimate Partner Violence: Emergency Physicians’ Experiences in Atlantic Canada \nSeptember 2016 – May 2018
Bibliographic record
Abstract
Abstract \nBACKGROUND: Intimate partner violence (IPV) results in poorer health outcomes and greater system costs. IPV screening protocols are recommended in emergency departments (EDs) where intervention is critical, yet there is limited literature investigating ED-specific IPV screening health outcomes. This study aims to identify trends in emergency physicians' experiences screening women for IPV and to investigate associated IPV screening outcomes. \nMETHODS: This was a qualitative research design with ethics approval. An emergency physician who had performed at least one IPV screen on a woman of childbearing age presenting to the ED was eligible for interview. Each participant was asked eight predetermined questions addressing their IPV screening experiences with allotted time for discussion. Recorded interviews were transcribed and underwent Braun and Clarke’s six phases of thematic analysis. \nRESULTS: There are no official IPV screening protocols in place at the investigated hospitals. IPV is often missed and perceived incidence may vary by gender or experience. Allied health professionals are crucial to IPV patient care. Outcomes are predicted to not improve post current interventions. The greatest challenge to IPV management is eliciting disclosure of abuse. \nCONCLUSION: These findings indicate that physicians believe formal ED screening protocols would likely help IPV victims. Unfortunately, there are none currently in place at three EDs in Atlantic Canada. The incidence of patients who present to the ED due to IPV should be determined. The identified population could be analyzed for common features. These features could be used as indicators for formal, evidence-based, IPV screening protocols, which may increase identification of victims.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".