Clinical correlates of fetal alcohol spectrum disorder among diagnosed individuals in a rural diagnostic clinic.
Bibliographic record
Abstract
BACKGROUND: Diagnosis of fetal alcohol spectrum disorder (FASD) is relevant for the reduction of long term adverse sequalae. However, the diagnostic guidelines require a multidisciplinary approach which may hinder access to diagnostic and management services. Most diagnostic clinics are located in urban areas. There is less emphasis on the operations, capacities, and outcomes from rural diagnostic clinics. METHODS: Over a ten and half years of clinic operations to diagnose children and subsequently adults, all consenting adults provided answers to interviews, participated in measurements and other diagnostic procedures. Information was collected on their contact with mental health services. Comparison of the findings with those from other established clinics included variables relevant to outcome measures. RESULTS: 375 individuals were referred, assessed and diagnosed according to the existing guidelines for FASD diagnosis. Alcohol-related neurodevelopmental disorder (ARND), which was closely associated with age, was the most prevalent FASD diagnosis. One third of those diagnosed had IQ above the average range and ADHD was the most relevant clinical correlate. The diagnostic clinic was able to complete diagnosis on potentially 37.5% of likely affected individuals. CONCLUSION: FASD can be diagnosed in children and adults in a rural setting. ADHD and other mental disorders should be a focus for treatment in affected individuals especially adults. It is important to consider the impact of age on the outcome of FASD. To increase diagnostic capacity, clinic operations could be modelled similarly.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".