A prospective cohort study on changes in psychosocial distress and preterm birth among pregnant Pakistani women
Bibliographic record
Abstract
Changes in mental health during pregnancy may better predict preterm birth (PTB) as assessment at one time point are inconsistently associated with this outcome. Our prospective cohort study of 1225 pregnant Pakistani women determined whether (a) changes in psychosocial distress (i.e., pregnancy-related anxiety, state anxiety, depressive symptoms) between 10 to 19 and 22 to 29 weeks’ gestational age influenced the risk of PTB; and (b) social determinants of health and chronic stress influenced this relationship. The individual effect of changes in (a) pregnancy-related anxiety on PTB was significant only among women with low social support from family (OR = 0.85, 95% CI 0.74–0.97, p = 0.017); and (b) depressive symptoms on PTB were significantly modified by education (p = 0.011), number of previous children (p = 0.028) and life-time interpersonal trauma (p = 0.073). The average aggregate change score was associated with PTB among women with low family support (OR = 0.79, 95% CI 0.67–0.93, p = 0.005), after adjusting for confounders. The collective effect, assessed using multiple logistic regression, was not significant. Chronic stress did not alter any findings. An intersectional approach will enable exploration of the disparate burden of psychosocial distress during pregnancy on PTB.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".