Coping styles, strategies and psychological distress amongst perinatal individuals during the COVID-19 pandemic: a rapid review
Bibliographic record
Abstract
Introduction: Perinatal individuals are at an increased risk of experiencing psychological distress, which often manifests in a combination of co-occurring symptoms of anxiety, depression, and stress. During the COVID-19 pandemic, the rates of psychological distress experienced by perinatal women dramatically increased, in some cases doubling or even tripling. This increase is concerning as psychological distress can impact the health and wellbeing of mothers and their offspring, including an offspring's neurocognitive, physical, mental, and socio-emotional development. The strategies a perinatal individual uses to cope with psychological distress are modifiable and, therefore, can be targeted to help improve outcomes for mothers and their offspring. Methods: This rapid review describes and synthesizes the literature related to coping with perinatal psychological distress during the COVID-19 pandemic. This review included twenty-four cross-sectional studies. Results: Perinatal individuals reported using various coping strategies to deal with the COVID-19 pandemic, including social strategies (e.g., connecting with others); physical strategies (e.g., exercising); cognitive strategies (e.g., positive re-appraisal); and spiritual strategies (e.g., prayer). An avoidant style of coping and its accompanying behaviours, including disengagement, substance use, and distraction via screen time/social media use, were significantly associated with higher levels of psychological distress. Strategies associated with lower levels of psychological distress included sleep and social support. Discussion: Future studies should address the impact of technology on coping and the long-term impact of coping styles used during the COVID-19 pandemic on the wellbeing of mothers and their offspring. Although this rapid review centered on the COVID-19 context, its findings are broadly relevant to women worldwide who continue to experience prolonged stressors such as climate change, poverty, and conflict.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".