Nurses' Knowledge, Communication Needs, and Future Directions in Neonatal Research
Bibliographic record
Abstract
BACKGROUND: Preterm birth is a significant contributor to neonatal morbidity and mortality. Despite legislative efforts to increase pediatric drug development, neonatal clinical trials continue to be infrequent. The International Neonatal Consortium (INC) includes nurses as key stakeholders in their mission to accelerate safe and effective therapies for neonates. PURPOSE: INC developed a survey for nurses, physicians, and parents to explore communication practices and stakeholders' perceptions and knowledge regarding clinical trials in neonatal intensive care units (NICUs). METHODS: A stepwise consensus approach was used to solicit responses to an online survey. The convenience sample was drawn from INC organizations representing the stakeholder groups. Representatives from the National Association of Neonatal Nurses and the Council of International Neonatal Nurses, Inc, participated in all stages of the survey development process, results analysis, and publication of results. RESULTS: Participants included 188 nurses or nurse practitioners, mainly from the United States, Canada, the European Union, and Japan; 68% indicated some level of research involvement. Nurses expressed a lack of effective education to prepare them for participation in research. Results indicated a lack of a central information source for staff and systematic approaches to inform families of studies. The majority of nurses indicated they were not asked to provide input into clinical trials. Nurses were uncertain about research consent and result disclosure processes. IMPLICATIONS FOR PRACTICE AND RESEARCH: This study indicates the need to educate nurses in research, improve NICU research communication through standardized, systematic pathways, and leverage nurse involvement to enhance research communication.
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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 | 0.041 | 0.090 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| 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".