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Record W3181298093 · doi:10.1055/s-0041-1731651

Bereaved Parents: Insights for the Antenatal Consultation

2021· article· en· W3181298093 on OpenAlexaff
Marlyse F. Haward, John M. Lorenz, Annie Janvier, Baruch Fischhoff

Bibliographic record

VenueAmerican Journal of Perinatology · 2021
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsFeelingMedicineNursingCognitionNarrativeFamily medicinePsychiatryPsychologySocial psychology

Abstract

fetched live from OpenAlex

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..

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.352
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of PerinatologySame topicGrief, Bereavement, and Mental HealthFrench-language works237,207