Patient Opinions of Screening for Intimate Partner Violence in a Fracture Clinic Setting
Bibliographic record
Abstract
BACKGROUND: Approximately one-third of injured women presenting to fracture clinics have experienced some form of intimate partner violence in the past year. The aim of the current study was to determine patients' perceptions on screening for intimate partner violence during visits to a surgical fracture clinic. METHODS: We conducted a cross-sectional study to evaluate patients' perceptions and opinions on screening for intimate partner violence in an orthopaedic fracture clinic. Eligible patients anonymously completed a self-reported written questionnaire, which included questions on patient demographics, attitudes toward intimate partner violence in general, the acceptability of screening for intimate partner violence in an orthopaedic fracture clinic, and opinions on how, when, and by whom the screening should be conducted. RESULTS: The study included 750 patients (421 male and 329 female) at five clinical sites in Canada and the Netherlands. The majority (554, 73.9%) of the respondents either "agreed" or "strongly agreed" that the fracture clinic was a good place for health-care providers to ask about intimate partner violence. The majority (671, 89.5%) also agreed that health-care providers should screen for intimate partner violence by means of face-to-face interactions rather than other, more passive methods. Increased openness to screening was significantly associated with female sex, higher income, and higher education (F₃₅₉₅ = 21.950, p < 0.001). CONCLUSIONS: Our findings demonstrated that the majority of patients endorse active screening for intimate partner violence in orthopaedic fracture clinics.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".