A survey of physicians knowledge regarding awareness of maternal alcohol use and the diagnosis of FAS.
Bibliographic record
Abstract
BACKGROUND: Alcohol is the most widely used drug in the world that is a human teratogen whose use among women of childbearing age has been steadily increasing. It is also probable that Fetal Alcohol Syndrome is under diagnosed by physicians. The objectives of this study were twofold: 1) to evaluate the experience, knowledge and confidence of family physicians with respect to the diagnosis of FAS and 2) to evaluate physicians awareness of maternal drinking patterns. METHODS AND PARTICIPANTS: A multiple choice anonymous questionnaire was sent to a randomly selected group of family physicians in the Metropolitan Toronto area. RESULTS: There was a 73% (75/103) total response rate; Overall, 6/75 (8%) of family physicians reported that they had actually diagnosed a child with FAS. 17.9% had suspicions but did not make a diagnosis and 12.7% reported making a referral to confirm the diagnosis. Physician rated confidence in the ability to diagnosis FAS was low, with 49% feeling they had very little confidence. 75% reported counselling pregnant women and 60.8% reported counselling childbearing women in general on the use of alcohol. When asked what screening test they used to detect the use of alcohol, 75% described frequency/quantity. Not a single respondent identified using the current accepted screening method for alcohol use (TWEAK) which is recommended by The Centre for Addiction and Mental Health. CONCLUSIONS: Family physicians do not feel confident about diagnosing FAS. None of the physicians were aware of the current screening methods to accurately gage alcohol use in pregnant and childbearing women.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".