Early childhood home visiting programme: factors contributing to success
Bibliographic record
Abstract
AIM: This paper reports a study of the factors that public health nurses, home visitors and parents consider important for the success of an early childhood home visiting programme. BACKGROUND: The primary aim of early child home visiting programmes is to promote healthy and safe growth and development of infants and children in at-risk families. Few studies have focused on actual programme components which foster this outcome. METHODS: The research was a descriptive, qualitative evaluation. Success of the programme was defined as positive changes in families which were seen as directly related to participation. The 58 participants were 24 public health nurses, 14 home visitors and 20 parents. One in-depth semistructured audio-taped interview was conducted with each participant between October 2003 and February 2004. All interviews were transcribed and analysed using open coding; themes and categories were developed and reviewed for congruence of coding. FINDINGS: Participants discussed several factors that they considered important for the success of the programme: its particular characteristics, the programme activities and the healthcare providers. CONCLUSION: Components contributing to the success of early childhood home visiting programmes include a strength-based philosophy, voluntary enrollment of parents, regularly scheduled home visits, a curriculum to structure the home visitor's interventions, and careful attention to the selection, training, and supervision of home visitors.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".