Nurse Home Visitors’ Perceptions of Mandatory Reporting of Intimate Partner Violence to Law Enforcement Agencies
Bibliographic record
Abstract
In the United States, there is an ongoing debate about requiring health care professionals to report intimate partner violence (IPV) to law enforcement agencies. A comprehensive examination of the perspectives of those required to report abuse is critical, as their roles as mandated reporters often pose legal, practical, moral, and ethical questions. Even so, the perspective of health care professionals who are required to report is often overlooked and research is scarce on mandated reporters who work outside of clinical settings, such as nurses who engage in home visitation with clients. The purpose of this study was to examine nurse home visitors' perspectives regarding the mandatory reporting of IPV, specifically focusing on their attitudes toward reporting, perceived awareness of reporting requirements, and intended reporting behaviors. A web-based survey was administered to nurses in the Nurse-Family Partnership home visitation program across the United States. A total of 532 completed surveys were returned (response rate = 49%). In terms of support for reporting IPV, 40% of nurses indicated that they should "always" be required to report. Almost half of the sample indicated that they would report a case of IPV, yet less than one-third of participants were aware of a legal mandate. Attitudes and support toward reporting as well as the perception of a reporting requirement significantly predicted intention to report. Furthermore, 29% of participants did not know if they were required to report IPV perpetrated against their clients. Comprehensive information about mandatory reporting duties is needed for health care professionals in home visitation settings. The findings of the current study highlight the need to reduce variation among practitioners and establish consistent program practices that are grounded in the program's principals, supported by existing research, and compliant with existing state policies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".