Integrating Parents in Neonatal and Pediatric Research
Bibliographic record
Abstract
BACKGROUND: Parents and their infants are the beneficiaries of neonatal and pediatric research, but in the past they have been excluded from most stages of research projects. As a result, many projects may fail to produce the most worthwhile information for parents and families. Lately, veteran resource parents and patients have been increasingly integrated in research initiatives. METHODS: Benchmarking of neonatal and pediatric research initiatives where resource parents and/or ex neonatal patients have helped to optimize pediatric research. We review ways in which resource parents/patients can be involved in research, with examples and practical ideas of how to proceed. RESULTS: Resource parents/patients can be collaborators in research and be integrated in many steps: prioritizing research projects, designing trials, determining the outcomes of interest, ethics review, developing and improving consent procedures, collection and interpretation of data, participation in data safety monitoring committees, publication of results, and presentation to peer groups. Some of the strategies for integration of stakeholders in clinical research are more complex, may involve risk and require more training than others. CONCLUSION: We suggest that groups wanting to involve parents in their research endeavors start with simpler tasks that entail less risk and develop teams of resource parents who have differing interests and abilities. Quality control of programs is essential, such as frequently giving and obtaining feedback from resource parents/patients and researchers. In the future, integration of resource parents/patients into every step of clinical research will be essential to ensure that parent and family important outcomes are examined.
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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 | 0.067 | 0.141 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".