Impact of <scp>COVID</scp>‐19 restrictions on the postpartum experience of women living in Eastern Canada during the early pandemic period: A cross‐sectional study
Bibliographic record
Abstract
OBJECTIVES: To (1) compare changes in parenting self-efficacy, social support, postpartum anxiety, and postpartum depression in Canadian women before and during the early COVID-19 pandemic; (2) explore how women with a newborn felt during the pandemic; (3) explore ways that women coped with challenges faced. METHODS: A cross-sectional design was used. Prior to the pandemic, an online survey was conducted with women who an infant 6 months old or less in one of the three Eastern Canadian Maritime provinces. A similar survey was conducted during the pandemic in mid-2020. RESULTS: Pre-COVID, 561 women completed the survey, and 331 women during the pandemic. There were no significant differences in parenting self-efficacy, social support, postpartum anxiety, and depression between the cohorts. Difficulties that women reported because of COVID-19 restrictions included lack of support from family and friends, fear of COVID-19 exposure, feeling isolated and uncertain, negative impact on perinatal care experience, and hospital restrictions. Having support from partners and families, in-person/virtual support, as well as engaging in self-care and the low prevalence of COVID-19 during the summer of 2020 helped women cope. CLINICAL RELEVANCE: Women identified challenges and negative impacts due to the COVID-19 pandemic, although no differences in psychosocial outcomes were found. Consideration of public health policy during the postpartum period for the ongoing COVID-19 pandemic is needed. CONCLUSION: While there were no significant differences in psychosocial outcomes, there were still challenges and negative impacts that women identified.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".