The socioemotional impact of the COVID-19 pandemic on pregnant and postpartum people: a qualitative study
Bibliographic record
Abstract
BACKGROUND: The social isolation and safety measures imposed during the COVID-19 pandemic differentially burdened pregnant and postpartum people, disrupting health care and social support systems. We sought to understand the experiences of people navigating pre- and postnatal care, from pregnancy through to the early postpartum period, during the pandemic. METHODS: In this qualitative investigation, we conducted semistructured interviews with people residing in British Columbia and Alberta, Canada, during the second half of pregnancy and again at 4-6 weeks' post partum between June 2020 and July 2021. Interviews were conducted remotely (via Zoom or telephone) and focused on the impact of the COVID-19 pandemic on pre- and postnatal care, birth and labour planning, and the birthing experience. We used content and thematic analysis to analyze the data, and checked patterns using NVivo. RESULTS: We interviewed 19 people during the second half of pregnancy and 18 of these people at 4-6 weeks' post partum. We identified 7 themes/subthemes describing how the COVID-19 pandemic affected their experiences: disrupted support systems, isolation, disrupted health care experiences (pre- and postnatal care, and labour and birth/hospital protocols), violated social norms (including typical rituals such as baby showers), impact on mental health and unexpected benefits (such as a no-visitor policy in hospitals after the birth, which provided a quiet period to bond with baby). INTERPRETATION: Pregnant and postpartum people were uniquely vulnerable during the COVID-19 pandemic and would have benefited from increased access to support in both health care and social settings. Future work should investigate maternal and infant/child functioning and behaviour to assess the long-term impact of the pandemic on Canadian families and developing children, with an aim to increase support where necessary.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".