Issues Related to Delivering an Early Childhood Home-Visiting Program
Bibliographic record
Abstract
PURPOSE: To describe the issues related to delivering an early childhood home visiting program, BabyFirst, from the perspective of public health nurses and lay home visitors (paraprofessionals). STUDY DESIGN AND METHODS: This descriptive, qualitative interpretive study had a sample of 24 public health nurses and 14 lay home visitors. One in-depth, semi-structured, audio-taped interview was conducted with each participant. Transcribed data were analyzed using content analysis techniques. RESULTS: Public health nurses and lay home visitors identified several issues associated specifically with the use of lay home visitors and more broadly with the delivery of the BabyFirst program. These are discussed in the following categories: issues related to (a) the lay home visitors, (b) the BabyFirst families, and (c) the general administration of the program. CLINICAL IMPLICATIONS: Findings from this study provide information about the issues related to providing home-visiting services delivered by lay home visitors that can be applied to policy and practice development. The findings suggest that in addition to careful selection of prospective applicants, considerable resources should be provided in preparing public health nurses and home visitors for their respective roles. The concerns identified by nurses and home visitors suggest the need to target the following three areas: (a) training and retention of nurses and home visitors, (b) program delivery, and (c) enrollment of families. Attention to the issues discussed in this article has implications for improving the BabyFirst home-visiting program and other similar early childhood programs.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".