Recommendations from a consensus development workshop on the diagnosis of fetal alcohol spectrum disorders in Australia
Bibliographic record
Abstract
BACKGROUND: Fetal alcohol spectrum disorders (FASD) are underdiagnosed in Australia, and health professionals have endorsed the need for national guidelines for diagnosis. The aim of this study was to develop consensus recommendations for the diagnosis of FASD in Australia. METHODS: A panel of 13 health professionals, researchers, and consumer and community representatives with relevant expertise attended a 2-day consensus development workshop to review evidence on the screening and diagnosis of FASD obtained from a systematic literature review, a national survey of health professionals and community group discussions. The nominal group technique and facilitated discussion were used to review the evidence on screening and diagnosis, and to develop consensus recommendations for the diagnosis of FASD in Australia. RESULTS: The use of population-based screening for FASD was not recommended. However, there was consensus support for the development of standard criteria for referral for specialist diagnostic assessment. Participants developed consensus recommendations for diagnostic categories, criteria and assessment methods, based on the adaption of elements from both the University of Washington 4-Digit Diagnostic Code and the Canadian guidelines for FASD diagnosis. Panel members also recommended the development of resources to: facilitate consistency in referral and diagnostic practices, including comprehensive clinical guidelines and assessment instruments; and to support individuals undergoing assessment and their parents or carers. CONCLUSIONS: These consensus recommendations provide a foundation for the development of guidelines and other resources to promote consistency in the diagnosis of FASD in Australia. Guidelines for diagnosis will require review and evaluation in the Australian context prior to national implementation as well as periodic review to incorporate new knowledge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.239 | 0.321 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.010 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.012 | 0.021 |
| Research integrity | 0.018 | 0.024 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".