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Record W4405364645 · doi:10.4300/jgme-d-24-00931.1

ICRE TOP RESEARCH ABSTRACTS 2024

2024· article· en· W4405364645 on OpenAlexfundno aff

Bibliographic record

VenueJournal of Graduate Medical Education · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Applications
Canadian institutionsnot available
FundersRoyal College of Physicians and Surgeons of Canada
KeywordsMEDLINEMedicineLibrary scienceComputer scienceWorld Wide WebData scienceInformation retrievalBiology

Abstract

fetched live from OpenAlex

From Pregnancy to Postpartum and BeyondBackground: The birth of a child is a pivotal moment in an individual's life.For medical trainees, who work long hours in demanding environments, the road to parenthood often involves additional challenges.With pregnancy during training becoming more common as the number of women in medicine increase, it is imperative to understand the experience of trainees in pregnancy and beyond to inform future research related to this changing workforce.Objective: The aim of this narrative review is to synthesize and assess the available literature describing the experience of pregnant and postpartum trainees in graduate medical education.Methods: The literature on PubMed and Google Scholar was reviewed for the following key words: pregnancy, maternity leave, postpartum, resident, medical training, and breastfeeding.We analyzed 42 articles written from 1990 to 2023 and included studies from all specialties, synthesizing data related to trainees.Results: Our review revealed 5 salient findings: (1) Trainees are at disproportionate risk of pregnancy complications including pregnancy loss, intrauterine growth restriction, and hypertensive disorders of pregnancy; these increased with frequency of night shifts and consecutive hours worked; (2) Maternity leave duration varies among specialties, with a mean length around 6 weeks; (3) A large academic institution found that trainees with leave duration >8 weeks had decreased postpartum depression rates and increased breastfeeding rates; (4) Reported breastfeeding barriers include time constraints and lack of lactation policies and onsite lactation facilities; and (5) Proposed challenges to implementation of extended leave policies and work accommodations include concerns regarding trainee competency, training requirements, the impact on colleagues' workload, and funding leave policies.Conclusions: Our review underlines that pregnancy in training is associated with increased complications and that longer maternity leaves provide benefits for both mother and child.Future research should aim to identify if antepartum work restrictions mitigate adverse pregnancy outcomes and if breastfeeding policies improve breastfeeding rates among trainees.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.581
Threshold uncertainty score0.828

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0140.010
Science and technology studies0.0010.001
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.4190.151

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 head0.148
GPT teacher head0.443
Teacher spread0.295 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

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