Predictors of women's physical health problems after childbirth
Bibliographic record
Abstract
The objectives of this study were to document the extent and the correlates of common physical health symptoms in women two months after childbirth. Of special interest was determining whether violence and depression histories increase the risk for experiencing these symptoms. Participants were recruited in six Toronto-area hospitals and were interviewed by telephone 8-10 weeks later. Two hundred of the 332 (60.2%) women who were approached completed the study. Most women (96%) reported at least one physical health symptom 2 months postnatally (Mean = 3.4, SD = 2.0). Stepwise logistic regression was conducted for each outcome. Antenatal depression was a significant predictor of excessive fatigue and bad headaches. Sick leave during pregnancy predicted postpartum backaches. Adult emotional abuse and household income were associated with bowel problems. Episiotomy, maternal complications, and planned pregnancy predicted perineal pain. Finally, being Canadian born and having an assisted vaginal delivery increased the risk for hemorrhoids while cesarean section decreased the risk. A high prevalence of physical symptoms was found in women after childbirth. History of depression and violence were implicated in the occurrence of some of these symptoms. Other important predictors included demographic, maternal, and delivery-related factors.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".