Predictors of fertility awareness-based method use among women trying to conceive and women contemplating pregnancy: a prospective cohort study.
Bibliographic record
Abstract
Objective: To identify predictors of fertility awareness-based method use. Design: Ongoing, prospective internet-based cohort study. Setting: Nurses living in the United States and Canada. Population: Women trying to become pregnant or contemplating pregnancy. Methods: Multivariable negative binomial regression. Main Outcome Measures: Fertility awareness-based methods. Results: Among the 23,418 women with pregnancy intention, 955 were trying to conceive and 2,282 were contemplating pregnancy. The ongoing duration of pregnancy attempt and gravidity were associated with the number of fertility awareness-based methods used among women actively trying to conceive. Compared to women who had been trying for two months or less, the number of methods was 29% (95% CI, 1.11—1.51), 45% (95% CI, 1.27—1.66) and 38% (95% CI, 1.21—1.58) higher for women who had been trying for 3-5 months, 6-12 months, or more than 1 year, respectively. Compared to nulligravid women, the number of fertility-awareness based methods was 17% (95% CI, 0.70—0.98) lower for women with a history of two or more pregnancies. Among women contemplating pregnancy, those who were married or in a domestic partnership used on average 39% (95% CI, 1.23—1.57) more fertility awareness-based methods than unpartnered women. Conclusion(s): Duration of ongoing pregnancy attempt and gravidity were the only significant predictors for number of fertility awareness-based method use among women trying to conceive, whereas partnership was the only significant predictor among women contemplating pregnancy.Funding: Supported by grants R24ES028521 and U01HL145386 from the National Institutes of Health. Keywords: pre-conception, pregnancy planning, fertility awareness-based methods.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".