Moms Are Not OK: COVID-19 and Maternal Mental Health
Bibliographic record
Abstract
Introduction: Depression and anxiety affect one in seven women during the perinatal period, and are associated with increased risk of preterm delivery, reduced mother-infant bonding, and delays in cognitive/emotional development of the infant. With this survey we aimed to rapidly assess the influence of the COVID-19 pandemic and subsequent physical distancing/isolation measures on the mental health and physical activity of pregnant and postpartum women. Methods: Between April 14 – May 8, 2020, we recruited women who were pregnant or within the first year after delivery to participate in an online survey. This included questionnaires on self-reported levels of depression/depressive symptoms (Edinburgh Postnatal Depression Survey; EPDS), anxiety (State-Trait Anxiety Inventory; STAI-State), and physical activity. Current and pre-pandemic values were assessed for each. Results: Of 900 eligible women, 520 (58%) were pregnant and 380 (42%) were in the first year after delivery. Sixty-four percent of women reported reduced physical activity with the onset of isolation measures, while 15% increased, and 21% had no change to their physical activity. An EPDS score ≥13 (indicative of depression) was self-identified in 15% of respondents pre-pandemic and in 40.7% currently (mean±SD; 7.5±4.9 vs. 11.2±6.3, respectively; P<0.01, moderate effect). Moderate to high anxiety (STAI-state score ≥40) was identified in 29% of women before the pandemic (mean STAI = 34.5±11.4) versus 72% of women currently (mean STAI = 48.1±13.6; p<0.01, large effect). However, women engaging in at least 150 minutes of moderate intensity physical activity (meeting current guidelines) during the pandemic had significantly lower scores for both anxiety and depression than those who did not (p<0.01, large and small effect, respectively). Discussion: This rapid response survey identifies a substantial increase in the likelihood of maternal depression and anxiety during the COVID-19 pandemic. This highlights the strong need for heightened assessment and treatment of maternal mental health. However, these data also suggest that physical activity, which has previously been shown to reduce depression and depressive symptoms in pregnancy, may be associated with better mental health during the pandemic.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".