Psychological Distress and Behavioural Changes in Pregnant and Postpartum Individuals During the COVID-19 Pandemic
Bibliographic record
Abstract
OBJECTIVES: To determine the psychological and behavioural effects of the COVID-19 pandemic on a Canadian cohort of individuals during pregnancy and the postpartum period. METHODS: In 2020, individuals between 20 weeks gestation and 3 months postpartum receiving maternity care from an urban Canadian clinic were invited to complete a questionnaire. The purpose-built questionnaire used validated scales including the Medical Outcomes Study Social Support Survey (MOS), Depression, Anxiety, and Stress Scale (DASS-21), Edinburgh Postnatal Depression Scale (EPDS), and questions from a SARS study. RESULTS: One hundred nine people completed the questionnaire (response rate, 55%) of whom 57% (n = 62) were postpartum. Most respondents (107, 98%) were married and had completed post-secondary education (104, 95%). Despite these protective factors, moderate to severe levels of depression (22%), anxiety (19%) and stress (27%), were recorded using the DASS-21, and 25% of participants (26) had depression (score ≥11) using the EPDS. Despite high social support in all MOS domains (median scores 84-100), a majority of participants reported loneliness (69, 67%) and were nearly or totally housebound (65, 64%). About half of participants worried about themselves (50, 46.3%) or their baby (59, 54%) contracting COVID-19, while the majority postponed (80, 74.1%) and cancelled (79, 73.2%) prenatal appointments. Being homebound or feeling lonely / lacking support were significant risk factors for psychological distress (P = 0.02) whereas exercise and strong social support were protective (P < 0.05). CONCLUSION: Pregnant and postpartum individuals experienced moderate to severe depression, anxiety, and stress during the COVID-19 pandemic. Exercise and strong social support were protective. Health care provider enquiry of home circumstances and activity may identify individuals needing enhanced supports.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".