Adaptation and implementation of an intervention to identify and respond to intimate partner violence in the family nurse partnership Northern Ireland program
Bibliographic record
Abstract
BACKGROUND: A need to adapt and implement an intimate partner violence (IPV) intervention, developed for the Nurse-Family Partnership (United States) program, was identified in the Northern Ireland Family Nurse Partnership (FNP) program. OBJECTIVES: To describe the: 1) IPV intervention adaptation process and outputs, and 2) feasibility to implement the intervention with fidelity and its acceptability to FNP nurses and supervisors in Northern Ireland. PARTICIPANTS AND SETTING: 260 women enrolled in, and 19 nurses and 5 supervisors delivering, the FNP/NFP program in Northern Ireland. METHODS: A team-based, project management approach was used to adapt the intervention. A convergent mixed methods regional service evaluation was conducted to describe feasibility, fidelity, and acceptability. RESULTS: The adapted IPV intervention was feasible and acceptable to implement. Moderate to high levels of fidelity to the clinical pathway were reported, dependent on intervention phase, with highest rates of fidelity related to a universal assessment of safety. Overall, 20 % of clients disclosed IPV; with most clients reporting multiple forms of abuse. Multiple factors positively influenced implementation and acceptability, including intervention alignment with FNP/NFP program content, practices and structure, the provision of wraparound clinical and reflective supervision, and the delivery of care within a system of integrated health and social care services. CONCLUSIONS: The adapted IPV intervention demonstrated potential to increase nurse knowledge and confidence to assess for, identify and classify IPV and to educate and support FNP/NFP clients with tailored plans of care. Future adaptations could include stratification of future training and education for new and more experienced nurses.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".