Bereaved Parents: Insights for the Antenatal Consultation
Bibliographic record
Abstract
OBJECTIVE: The study aimed to explore experiences of extremely preterm infant loss in the delivery room and perspectives about antenatal consultation. STUDY DESIGN: Bereaved participants were interviewed, following a semi-structured protocol. Personal narratives were analyzed with a mixed-methods approach. RESULTS: In total, 13 participants, reflecting on 17 pregnancies, shared positive, healing and negative, harmful interactions with clinicians and institutions: feeling cared for or abandoned, doubted or believed, being treated rigidly or flexibly, and feeling that infant's life was valued or not. Participants stressed their need for personalized information, individualized approaches, and affective support. Their decision processes varied; some wanted different things for themselves than what they recommended for others. These interactions shaped their immediate experiences, long-term well-being, healing, and regrets. All had successful subsequent pregnancies; few returned to institutions where they felt poorly treated. CONCLUSION: Antenatal consultations can be strengthened by personalizing them, within a strong caregiver relationship and supportive institutional practices. KEY POINTS: · Personalized antenatal consultations should strive to balance cognitive and affective needs.. · Including perspectives from bereaved parents can strengthen antenatal consultations.. · Trusting provider-parent partnerships are pivotal for risk 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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".