Experience of pregnancy during family medicine residency
Bibliographic record
Abstract
OBJECTIVE: To explore the challenges that childbearing family medicine residents encounter during postgraduate training and to understand the available support systems. DESIGN: Descriptive qualitative research study. SETTING: British Columbia, Canada. PARTICIPANTS: Nine University of British Columbia family medicine residents who experienced pregnancy during their residencies between 2014 and 2018. METHODS: Semistructured telephone interviews with family medicine residents were conducted until data reached saturation. Audiorecorded interviews were transcribed and analyzed using content analysis with an iterative approach to elucidate themes. Member checking and peer debriefing were used to ensure the rigour of the findings. MAIN FINDINGS: The participants reported various unique challenges during pregnancy, maternity leave, and return to work. Residents during pregnancy tended to prioritize work over one's own well-being and reported an increased level of perceived adverse symptoms. During maternity leave, residents reported postpartum depression, anxiety, and conflict between the roles of parent and physician. Upon return to work, participants perceived a decrease in their clinical function and reported feelings of guilt and anxiety because of the shared burden of residency with family. Residents found their programs supportive throughout pregnancy and maternity leave; however, a decrease in support upon return to work was a recurring theme in responses. CONCLUSION: Pregnancy during family medicine residency has unique challenges, necessitating support from programs, preceptors, and colleagues. Further resources and incentives are needed to facilitate the transition back to work after maternity leave.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".