Implementing Family-Integrated Care in the NICU
Bibliographic record
Abstract
The purpose of this study was to develop, implement, and evaluate a parent education and support program that enhances family-integrated care in a Canadian neonatal intensive care unit (NICU). A total of 39 mothers of infants born at 35 or fewer weeks' gestation were enrolled in the pilot program. We examined the development, implementation, and qualitative assessment of the education component of a family-integrated care program. We enrolled in groups of 4 or 5, the study mothers agreed to attend daily educational sessions, provide care for their infants for at least 8 hours daily, and participate in medical rounds. The educational sessions were provided by staff and veteran parents to assist parents' development of confidence in providing caregiving skills and assuming the role of a primary caregiver for their infants as they moved closer to discharge. Effectiveness of the program was evaluated through anecdotal feedback and a formal evaluation process at discharge. The results indicated that the mothers were provided with the tools to parent their infants in the NICU, recognize their own strengths, increase their problem-solving strategies, and emotionally prepare them to take their infant home. Feedback from the participants provided direction to adapt the program to provide optimal parent support and education. Parental education is a valued and vital component of family-integrated care in the NICU.
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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 | 0.004 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".