Family violence screening and disclosure in a large metropolitan hospital: A health service users’ survey
Bibliographic record
Abstract
OBJECTIVES: Assisting patients who are experiencing family violence is an important issue for health services. Rates of screening for family violence in general hospital settings in Australia are unclear. This study was conducted to obtain data on hospital family violence screening rates and health service users' perceptions of the screening process, in a large metropolitan hospital in Australia. METHODS: Clients from the clinical caseloads of social work and psychology staff were invited to participate in a tablet administered, online survey of their family violence screening experiences, within the health service. RESULTS: A total of 59 surveys were completed by hospital users, who had been treated in areas including the emergency department, acute inpatient wards, sub-acute and rehabilitation units, and outpatient clinics. Less than half the sample reported being screened for family violence at the health service. One-quarter of the respondents reported disclosing family violence concerns, with one-fifth wanting to disclose, but not feeling comfortable to do so. The majority of respondents who disclosed family violence felt supported by the response of the staff member and were provided with information they found helpful. However, further work could be done to improve screening rates, environmental and organizational factors to promote users feeling comfortable to disclose, and staff responses to disclosures. CONCLUSION: The results of the survey will be used to inform the development of a hospital-wide family violence training initiative aimed to improve staff knowledge, confidence, rates of screening, and clinical responses to family violence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".