Do Canadian prenatal record forms integrate evidence-based guidelines for the diagnosis of a FASD?
Bibliographic record
Abstract
OBJECTIVES: Prenatal alcohol exposure is a significant public health issue with lifelong psychological, emotional and financial costs associated with caring for an affected individual. In 2005, the Public Health Agency of Canada and Health Canada's First Nations and Inuit Health Branch developed evidence-based guidelines for the diagnosis of a Fetal Alcohol Spectrum Disorder (FASD). We examined the extent to which prenatal records across Canadian provinces and territories currently integrate key recommendations from these guidelines. METHODS: A content analysis of prenatal record forms retrieved from each Canadian province and territory (N = 12) was conducted to identify all questions or intervention prompts related to prenatal screening, exposure assessment, counseling or referral for maternal alcohol use during pregnancy. Findings were reviewed in relation to recommendations extrapolated from the Canadian guidelines and the FASD literature. RESULTS: All the prenatal record forms contained questions to assess maternal alcohol use during pregnancy. However, the dimensions of alcohol consumption assessed and the format, wording and number of items related to each dimension varied markedly across provinces/territories. Only five prenatal record forms included a validated screening tool to identify risky alcohol drinking behaviour. Most of the forms lacked prompts to encourage providers to intervene or refer pregnant clients with high-risk drinking behaviour. CONCLUSION: Integration of the Canadian recommendations into Canadian prenatal record forms may be an effective public health strategy for helping identify pregnancies at high risk for alcohol exposure, reducing the incidence of a FASD through appropriate prenatal intervention and referral, and facilitating early diagnosis of a FASD.
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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 | 0.033 | 0.274 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.019 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".