Socio‐economic and psychosocial factors in the management and prevention of preterm labour
Why this work is in the frame
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Bibliographic record
Abstract
Socio-economic factors associated with preterm labour include social class, (usually assessed by earnings and education), working conditions (professional status, ergonomic environment, working hours), physical and travelling activities, daily life activities, lifestyle, family status and psychosocial state as related to past and current pregnancy history together with current stress factors. A review of the association of these factors with preterm birth will be reported with an emphasis of the biological plausibility linking mostly emotional, and at a lesser degree, physical and psychological stress to the occurrence of preterm labour. A case control study, carried out in Quebec City among 101 women in preterm labour and 202 matched pregnancies for parity and gestational age, identified 7 risk factors in an explanatory multivariate model among 117 variables: Body mass index (BMI) <20 (OR; 95% CI: 3.96; 2.61-7.09), previous preterm labour (OR; 95% CI: 3.61; 1.12-11.65) previous low birth weight (OR; 95% CI: 2.24; 1.05-7.71), standing at work >2 hours (OR; 95% CI: 3.90; 1.53-9.91), Abruptio placentae (OR; 95% CI: 5.88; 1.20-28.76), urinary tract infection (UTI) (OR; 95% CI: 4.4.3; 1.47-13.34), and stress score >5 (OR; 95% CI: 2.56; 1.20-5.54). The most stressful events were related to family illness, mortality, disruption, violence or financial distress. Some risk factors cannot be modified (previous preterm labour, low birth weight and UTI), while preventive efforts should be directed towards attaining BMI >20 before conception, modifying working conditions during current pregnancy and appropriate management of acute emotional stress.
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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 it