ICRE TOP RESEARCH ABSTRACTS 2024
Bibliographic record
Abstract
Background: 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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".