Factors Influencing Prenatal Screening for Down’s Syndrome
Bibliographic record
Abstract
This article attempts to identify the factors that influence prenatal screening uptake. About 1400 postdelivery, still-hospitalized women in 15 hospitals in Zhejiang Province were surveyed from November to December 2007. Univariate analysis was used to describe screening uptake and compare respondents with different characteristics. Stepwise logistic regression (forward) was then used to assess the relative strength of those influencing factors. It was found that 49.7% of the respondents received maternal serum prenatal screening. The factors that influenced prenatal screening service utilization included place of residence (urban vs countryside), migrant versus nonmigrant status, attitudes toward screening, frequency of routine prenatal checkups, and doctor's advice. Migrants had a lower probability of getting screened than permanent residents (odds ratio = 0.456; 95% confidence interval [CI] = 0.31, 0.68). The screening uptake probability of women with doctor's advice was 12 times as great as that of women without doctor's advice (95% CI = 7.91, 18.69).
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".