Effects of Home Visits to Vulnerable Young Families
Bibliographic record
Abstract
PURPOSE: Nurses' home visits to new parents have been replaced in many high-need communities by nonprofessional visits without clear evidence of effectiveness. Previous reviews of home visiting research have combined nurse and non-nurse interventions and have pooled studies from the US, where home visiting is mainly limited to low-income families, with those from nations where home visiting is a universal service. This integrative review was focused on nurse-delivered interventions in the US and Canada to identify the nursing-specific models with the greatest effect in this cultural context. Evaluation of support for social ecology theory was a secondary aim. DESIGN: The sample consisted of 20 experimental and quasi-experimental studies of home nursing interventions for families of newborn infants who were vulnerable because of poverty, social risks, or prematurity. METHODS: Each report was examined systematically using specific rules of inference and a scoring system for methodological quality. Intervention effects on five outcome domains were described. FINDINGS: Maternal outcomes, maternal-infant interaction, and parenting were more often influenced than was child development, except in preterm infants. Well-child health care did not improve. Effective programs generally began in pregnancy, included frequent visits for more than a year, had well-educated nurses, and were focused on building a trusting relationship and coaching maternal-infant interaction. Social ecology theory was partially supported. CONCLUSIONS: Future nurse home-visiting research should test a combination of these effective components. Nurses can use this information to seek funding of nurse-delivered interventions for vulnerable families.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".