Community education on preterm birth. Does it change practice?
Bibliographic record
Abstract
OBJECTIVE: To evaluate how well physicians and other prenatal care providers educate women about early recognition of and appropriate response to the signs and symptoms of preterm labour (PTL). To assess use of antenatal steroids for babies born at less than 34 weeks' gestation. DESIGN: Before-after study using a population-based approach. SETTING: Health care providers' offices, hospitals, and prenatal classes in Ottawa, Ont. PARTICIPANTS: Prenatal care providers, women in hospital after giving birth, prenatal class participants. INTERVENTIONS: Prenatal care providers received information and educational materials on PTL and preterm birth (PTB). They passed this information on to pregnant women at their 18- to 20-week prenatal visits. Teachers of prenatal classes gave the same information in early-series classes. Clinical practice guidelines were developed, and hospital staff received education on appropriate response to PTL. MAIN OUTCOME MEASURES: Use of educational materials and steroid treatment. RESULTS: Statistically significant increases were seen in the numbers of care providers who had educational material about PTL and PTB, who reported giving the educational material to all women, and who reported discussing signs and symptoms of PTL and PTB with all women; women who reported that their care providers talked with them about PTL and PTB, and women delivering preterm (< 34 weeks) babies who received steroids. CONCLUSION: Providing knowledge and standardized educational materials to health care providers can help improve preventive practice for PTL and educate women about PTL.
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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 | 0.007 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".