Physicians’ Knowledge of Alcohol, Tobacco and Folic Acid in Pregnancy
Bibliographic record
Abstract
OBJECTIVE: To assess: (1) physicians' knowledge and clinical confidence regarding problematic substance use in pregnancy compared to folic acid, and (2) physicians' desire for education in this area and their preferred learning modalitiestools. DESIGN: Self-administered survey. SETTING: Family Medicine Forum 2004 in Toronto, Canada. PARTICIPANTS: Physicians attending Family Medicine Forum 2004 in Toronto who provide antenatal care. MAIN OUTCOME MEASURES: Knowledge of folic acid, smoking and alcohol in pregnancy. Clinical confidence and interest in resources regarding problematic substance use in pregnancy. RESULTS: Sixty-six surveys completed. Physicians answered 92.3% of folic acid questions correctly, compared to 82.0% for nicotine and 57.1% for alcohol. Scores were higher on questions about effects of nicotine and alcohol use in pregnancy than on questions about treatment options. A perceived inability to influence clinical outcomes and a lack of professional resources regarding substance use in pregnancy were also identified. Physicians were interested in learning more about problematic substance use in pregnancy, particularly from continuing medical education events, websites and pocket cards. CONCLUSION: Participants' level of knowledge regarding substance use in pregnancy was significantly lower than their knowledge of folic acid, as was their clinical confidence. This lack of knowledge was not attributable to disinterest and clearly more educational resources are needed to address this topic.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.004 | 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".