Improving the Nurse–Family Partnership in Community Practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Evidence-based preventive interventions are rarely final products. They have reached a stage of development that warrant public investment but require additional research and development to strengthen their effects. The Nurse-Family Partnership (NFP), a program of nurse home visiting, is grounded in findings from replicated randomized controlled trials. OBJECTIVE: Evidence-based programs require replication in accordance with the models tested in the original randomized controlled trials in order to achieve impacts comparable to those found in those trials, and yet they must be changed in order to improve their impacts, given that interventions require continuous improvement. This article provides a framework and illustrations of work our team members have developed to address this tension. METHODS: Because the NFP is delivered in communities outside of research contexts, we used quantitative and qualitative research to identify challenges with the NFP program model and its implementation, as well as promising approaches for addressing them. RESULTS: We describe a framework used to address these issues and illustrate its use in improving nurses' skills in retaining participants, reducing closely spaced subsequent pregnancies, responding to intimate partner violence, observing and promoting caregivers' care of their children, addressing parents' mental health problems, classifying families' risks and strengths as a guide for program implementation, and collaborating with indigenous health organizations to adapt and evaluate the program for their populations. We identify common challenges encountered in conducting research in practice settings and translating findings from these studies into ongoing program implementation. CONCLUSIONS: The conduct of research focused on quality improvement, model improvement, and implementation in NFP practice settings is challenging, but feasible, and holds promise for improving the impact of the NFP.
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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 | 0.004 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.010 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it