Intimate Partner Violence (IPV) - Associated Ophthalmologic Injuries among Women: A Systematic Review
Bibliographic record
Abstract
Objectives: This study aims to describe patterns of IPV-associated ophthalmic injuries among women: Specifically, it seeks to identify factors associated with ophthalmic injuries in women secondary to IPV, determine practices and/or protocols in identifying IPV-associated ophthalmic injuries, and to examine practices in referral to ancillary services for IPV survivors with such injuries. Methods: A systematic literature search was conducted for observational studies published from 2009 to 2022 using PubMed, Google Scholar, HERDIN, and the Cochrane Library. Studies were screened and appraised using the Newcastle-Ottawa Quality Assessment Scale (NOS) for risk of bias. Relevant data on injury types, screening protocols, and referral practices were extracted and synthesized. Analysis of risk of bias (ROB) for each study utilizing the NOS scale indicated that four studies exhibited a good ROB. Results: A total of 567 female patients with IPV-related facial injuries were included in the selected studies. Of these, 98 cases (17.28%) involved ophthalmic injuries, including orbital fractures, subconjunctival hemorrhages, and contusions. Factors associated with these injuries included delayed healthcare-seeking behavior, bilateral and recurrent trauma, and psychological distress. Current practices in IPV identification were found to be inconsistent, with a lack of standardized screening protocols, especially in ophthalmology settings. Referral to ancillary services was often suboptimal due to poor interdepartmental coordination and absence of formal pathways. Conclusion: There is a significant gap in the recognition and management of IPV-associated ophthalmic injuries among women. Establishing standardized screening protocols and improving referral systems can enhance care outcomes and provide holistic support for survivors, particularly in low-resource settings.
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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 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".