Agreement Between Prospective and Retrospective Reports of Maternal Exposure to Chemicals During Pregnancy
Bibliographic record
Abstract
Learning Objectives Compare how well, in previous studies, retrospectively and prospectively collected information on exposure of mothers to chemicals or drugs have agreed with medical records data. Recall the reported agreement—or lack thereof—between self-reported exposure to organic solvents at the time of pregnancy and at follow-up 3 to 7 years later. Describe the implications of these findings and how more valid maternal exposure data might be acquired. As part of a prospective study of solvent exposure and child behavior, it occurred that women’s responses about exposure history during pregnancy differed from the information documented during the postpartum period. The objective of the study was to examine the levels of agreement in 29 self-reports of exposure information obtained before and 3- to 7-years after pregnancy. Percent agreement was low for duration of exposure (41%), protective barrier use (48%), and symptomatology (41%). When reports were not in perfect agreement, women tended to report longer durations of exposure (r = 0.67), increased use of protective barriers (r = 0.39), and more symptoms at time of follow-up (r = 0.57). Agreement of report was not substantially associated with time since pregnancy or concurrent child behavior. Low levels of agreement may reflect response biases in the data collected at time of pregnancy or recall biases at time of follow-up. These variations in self-reports are of concern because they can severely affect estimates of human teratological risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 | 0.104 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".