88 Variables that Impact the Diagnosis of Fetal Alcohol Spectrum Disorder in Ontario
Bibliographic record
Abstract
In Canada, the incidence of Fetal Alcohol Spectrum Disorder (FASD) is estimated to be one in 100 live births. FASD is the leading cause of developmental and cognitive disabilities among Ontario’s children. FASD remains a complex diagnosis that requires meticulous gathering of prenatal alcohol exposure history, and extensive neuro-psychological testing. To determine what variables are associated with receiving or not receiving a diagnosis of FASD on initial diagnostic assessment. Cross-sectional study design was used. One-thousand and one (1,001) participants including caregivers of individuals with FASD, ages 3 to 25 years, living in urban and rural communities throughout Ontario. Participants completed a structured interviewer-administered questionnaire which elicited information such as clarity of prenatal alcohol exposure history, age at diagnosis, physical signs of FASD identified on diagnosis, history of FASD in the biological family, severity of the condition, co-morbidities, relationship of the individual to the caregiver (biological, adoptive, foster). A stepwise multiple regression analysis was used to identify significant variables which were associated with receiving or not receiving a diagnosis. Having 2 or more facial features consistent with FASD, clarity of prenatal alcohol history, and age under 6 years positively impacted on receiving the diagnosis (p<0.01) of FASD on initial diagnostic assessment. Age between the range of 13 to 18 years (p<0.01), and co-morbidities of depression with a manic component, personality disorder, and autism negatively impacted on making the diagnosis (p<0.001). Despite their age and co-morbidities, these children and youth had clear prenatal alcohol exposure, and met 4 neuro-psychological criteria of Fetal Alcohol Spectrum Disorder. All children in this study eventually received a diagnosis within 2 to 6 years of the initial diagnostic assessment. Better understanding of why the FASD teams withheld diagnosis in children who met diagnostic criteria is needed. Implications for practice, policy, and research are discussed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".