Pandemic-related prenatal maternal stress, model of maternity care and postpartum mental health: The Australian BITTOC study
Bibliographic record
Abstract
PROBLEM: Women pregnant during the COVID-19 pandemic may be at risk of elevated postpartum mental health problems. BACKGROUND: Social support protects maternal mental health during a pandemic. It is possible that formal supports, such as continuity maternity models of care, may also support maternal wellbeing. AIM: To investigate whether model of care moderates the association between prenatal maternal stress from the COVID-19 pandemic, and postpartum (a) depression and (b) anxiety. METHODS: Women in Australia, pregnant during the COVID-19 pandemic (n = 3048), completed a survey detailing their COVID-19-related objective hardship and subjective distress during pregnancy and completed depression and anxiety measures at birth to six weeks ("Early"), seven to 21 weeks ("Moderate"), and/or 22-30 weeks ("Late") postpartum. FINDINGS: Higher subjective distress was associated with elevated depression and anxiety at all timepoints. Model of care did not moderate the association of objective hardship or subjective distress and depression or anxiety at any timepoint. Compared with Standard Care, women receiving private midwifery care had a 74 % reduction in the odds of elevated anxiety in early postpartum. DISCUSSION: Women receiving private midwifery may have experienced lower anxiety due to a greater duration of postpartum in-home care, fewer changes to service delivery, and the option of homebirth. Women pregnant during a pandemic should be screened for higher subjective distress about the event. CONCLUSION: These results suggest that continuity of private midwifery care may be beneficial for supporting postpartum mental health during a pandemic, with implications for practice and policy for the current and future pandemics.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".