The Psychological Impact of COVID-19 Pandemic on Women’s Mental Health during Pregnancy: A Rapid Evidence Review
Bibliographic record
Abstract
BACKGROUND: The perinatal period is a particularly vulnerable period in women's lives that implies significant physiological and psychological changes that can place women at higher risk for depression and anxiety symptoms. In addition, the ongoing pandemic of coronavirus disease 2019 (COVID-19) is likely to increase this vulnerability and the prevalence of mental health problems. This review aimed to investigate the existing literature on the psychological impact of the COVID-19 pandemic on women during pregnancy and the first year postpartum. METHOD: The literature search was conducted using the following databases: Pubmed, Scopus, WOS-web of science, PsycInfo and Google Scholar. Out of the total of 116 initially selected papers, 17 have been included in the final work, according to the inclusion criteria. RESULTS: The reviewed contributions report a moderate to severe impact of the COVID-19 outbreak on the mental health of pregnant women, mainly in the form of a significant increase in depression-up to 58% in Spain-and anxiety symptoms-up to 72% in Canada. In addition to the common psychological symptoms, COVID-19-specific worries emerged with respect to its potential effects on pregnancy and the well-being of the unborn child. Social support and being engaged in regular physical activities appear to be protective factors able to buffer against the effects of the pandemic on maternal mental health. CONCLUSIONS: Despite the limitations of the study design, the evidence suggests that it is essential to provide appropriate psychological support to pregnant women during the emergency in order to protect their mental health and to minimize the risks of long-term effects on child development.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".