Honesty, Trust, and Respect During Consent Discussions in Neonatal Clinical Trials
Bibliographic record
Abstract
“Participating in the study provided an avenue for a premature baby like mine to receive an outstanding level of care and extra support from the research nurse that may not otherwise be available outside research. It was also fulfilling knowing that from this research may come the help that others with this same condition may need. It played a significant role in our education about improving and maintaining his health. ”—Parents of a neonatal clinical trial participant Participation in neonatal clinical trials is often viewed as risky, ethically challenging, burdensome for parents, and a favor that altruistic families are performing for future generations of babies.1,2 Views such as “valid consent in the antenatal/perinatal population is difficult, if not impossible, to obtain” are common.3 However, neonatal research need not be viewed through such a negative lens. Parents who have participated in clinical trials may view their research involvement very differently, as an exciting opportunity rather than a burden.4 Participation can have benefits for the newborn child and the family, even if the infant is not assigned by chance to a therapy that proves to be superior after completion of the trial.5,6 Collectively, as a group of research nurses and clinical investigators, we have discussed research participation with >900 families. We have found that when done well, conversations about consent to research can empower and support families at a time of crisis and reassure them that health care professionals are … Address correspondence to Sara B. DeMauro, MD, MSCE, The Children’s Hospital of Philadelphia, 34th Street and Civic Center Boulevard, Division of Neonatology, 2 Main, Philadelphia, PA 19104. E-mail: demauro{at}email.chop.edu
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.465 | 0.602 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.021 | 0.042 |
| Scholarly communication | 0.016 | 0.027 |
| Open science | 0.005 | 0.022 |
| Research integrity | 0.029 | 0.048 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".