Health care and social service professionals' perceptions of a home-visit program for young, first-time mothers
Bibliographic record
Abstract
INTRODUCTION: Little is known about health care and social service professionals' perspective on the acceptability of long-term home-visit programs serving low-income, first-time mothers. This study describes the experiences and perspectives of these community care providers involved with program referrals or service delivery to mothers who participated in the Nurse-Family Partnership (NFP), a targeted nurse home-visit program. METHODS: The study included two phases. Phase I was a secondary qualitative data analysis used to analyze a purposeful sample of 24 individual interviews of community care providers. This was part of a larger case study examining adaptations required to increase acceptability of the NFP in Hamilton, Ontario, Canada. In Phase II (n = 4), themes identified from Phase I were further explored through individual, semi-structured interviews with community health care and social service providers, giving qualitative description. RESULTS: Overall, the NFP was viewed as addressing an important service gap for first-time mothers. Providers suggested that frequent communication between the NFP and community agencies serving these mothers could help improve the referral process, avoid service duplication, and streamline the flow of service access. The findings can help determine key components required to enhance the success of integrating a home-visit program into an existing network of community services. CONCLUSION: The function of home-visit programs should not be viewed in isolation. Rather, their potential can be maximized when they collaborate and share information with other agencies to provide better services for first-time mothers.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".