“I’ve never asked one question.” Understanding the barriers among orthopedic surgery residents to screening female patients for intimate partner violence
Bibliographic record
Abstract
BACKGROUND: Intimate partner violence (IPV) is a global public health problem. Orthopedic surgery residents may identify IPV among injured patients treated in fracture clinics. Yet, these residents face a number of barriers to recognizing and discussing IPV with patients. We sought to explore orthopedic surgery residents' knowledge of IPV and their preparedness to screen patients for IPV in academic fracture clinic settings with a view to developing targeted IPV education and training. METHODS: We conducted focus groups with junior and intermediate residents. Discussions explored residents' knowledge of and experiences with IPV screening and preparedness for screening and responding to IPV among orthopedic patients. Data were analyzed iteratively using an inductive approach. RESULTS: Residents were aware of the issue of abuse generally, but had received no specific information or training on IPV in orthopedics. Residents did not see orthopedics faculty screen patients for IPV or advocate for screening. They did not view IPV screening or intervention as part of the orthopedic surgeon's role. Residents' clinical experiences emphasized time management and surgical intervention by effectively "getting through clinic" and "dealing with the surgical problem." Communication with patients about other health issues was minimal or nonexistent. CONCLUSION: Orthopedic surgery residents are entering a career path where IPV is well documented. They encounter cultural and structural barriers preventing the incorporation of IPV screening into their clinical and educational experiences. Hospitals and academic programs must collaborate in efforts to build capacity for sustainable IPV screening programs among these trainees.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".