Recording a history of alcohol use in pregnancy: an audit of knowledge, attitudes and practice at a child development service.
Bibliographic record
Abstract
AIMS: To assess the effectiveness of alcohol documentation, examining medical correspondence and medical files of patients referred to the State Child Development Service (SCDS) and (ii) To measure the knowledge, attitudes and clinical practice of health practitioners working at the child development service (CDS) in relation to asking about alcohol use in pregnancy. METHODS: Written documentation for children attending the State Child Development Centre (SCDC) in Western Australia were examined for documentation of alcohol use during pregnancy; a random sample of 40 medical records were examined and all correspondence authored by every paediatrician for the calendar year 2006 (n=210) were reviewed. (ii) A survey was completed of staff at the CDS, to assess their knowledge, attitudes, and clinical practice and their perceived importance of asking about alcohol and other drug use. RESULTS: Review of all written documentation, of both files and paediatric correspondence, found only three letters recording alcohol use in pregnancy; two of the letters recorded the index child displaying stigmata consistent with prenatal alcohol exposure, yet Fetal Alcohol Spectrum Disorders (FASD) were not considered within the concluding differential diagnoses. 56% of responding CDS staff (73% response) agreed it was important to ask about alcohol use when taking a pregnancy history, 20% indicated they routinely asked about alcohol exposure and 35% of staff said they never asked about alcohol use. 60% of the CDS staff completing the survey would welcome a proven technique to ask about alcohol use. CONCLUSIONS: There is a gap in clinical practice within this CDS in asking and/or recording information about alcohol use in pregnancy. The majority of CDS staff who completed the survey agreed that asking about alcohol use in pregnancy was important and welcomed a proven technique to do so.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".