Factors Influencing Pregnant Womenʼs Perceptions of Risk
Bibliographic record
Abstract
PURPOSE: To explore factors women consider in determining their perceptions of pregnancy risk, and to compare and contrast factors considered by women with complicated and uncomplicated pregnancies. STUDY DESIGN AND METHODS: Descriptive qualitative study in which women described factors they considered in making personal risk assessments. Of the 205 women in the study, half (n = 103) had pregnancy complications, while the other half (n = 102) had no known complications. Written responses to three open-ended questions were used to determine factors women considered in assessing their risks. A qualitative content analysis approach was used to interpret the data. RESULTS: Four major themes emerged that influenced perception of risk for both groups: self image, history, healthcare, and "the unknown." Women with complications voiced greater risk perceptions and identified specific risks, while women with no complications mentioned potential risks that were diffuse and hypothetical.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".