Biopsychosocial determinants of pregnancy length and fetal growth
Bibliographic record
Abstract
The causes and mechanisms related to preterm delivery and intrauterine growth restriction are poorly understood. Our objective was to assess the direct and indirect effects of psychosocial and biomedical factors on the duration of pregnancy and fetal growth. A self-administered questionnaire was distributed to pregnant women attending prenatal ultrasound clinics in nine hospitals in the Montérégie region in the province of Quebec, Canada, from November 1997 to May 1998. Prenatal questionnaires were linked with birth certificates. Theoretical models explaining pregnancy length and fetal growth were developed and tested, using path analysis. In order to reduce the number of variables from the questionnaire, a principal component analysis was performed, and the three most important new dimensions were retained as explanatory variables in the final models. Data were available for 1602 singleton pregnancies. The biophysical score, covering both maternal age and the pre-pregnancy body mass index, was the only variable statistically associated with pregnancy length. Smoking, obstetric history, maternal health and biophysical indices were direct predictors of fetal growth. Perceived stress, social support and self-esteem were not directly related to pregnancy outcomes, but were determinants of smoking and the above-mentioned biomedical variables. More studies are needed to identify the mechanisms by which adverse psychosocial factors are translated into adverse biological effects.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".