Clinical Research With Pregnant Women: Perspectives of Pregnant Women, Health Care Providers, and Researchers
Bibliographic record
Abstract
Limited clinical research with pregnant women has resulted in insufficient data to promote evidence-informed prenatal care. Charmaz's constructivist grounded theory methodology was used to explore how research with pregnant women would be determined ethically acceptable from the perspectives of pregnant women, health care providers, and researchers in reproductive sciences. Semistructured interviews were conducted with a purposive sample of 12 pregnant women, 10 health care providers, and nine reproductive science researchers. All three groups suggested the importance of informed consent and that permissible risk would be very limited and complex, being dependent on the personal benefits and risks of each particular study. Pregnant women, clinicians, and researchers shared concerns about the well-being of the woman and her fetus, and expressed a dilemma between promoting research for evidence-informed prenatal care while securing the safety in the course of research participation.
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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 | 0.082 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.026 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.012 |
| 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".