Health, social and legal outcomes of individuals with diagnosed or at risk for fetal alcohol spectrum disorder: Canadian example
Bibliographic record
Abstract
BACKGROUND: Fetal Alcohol Spectrum Disorder (FASD) is a leading cause of lifelong developmental and physical disabilities and behavioural problems. This study describes the characteristics of individuals diagnosed with or at risk for FASD in British Columbia, Canada. METHODS: A retrospective chart review and cross-sectional analysis were conducted on records of individuals diagnosed or at risk for FASD at the Asante Centre from January 2015 to July 2019. Descriptive statistics results were stratified by age, sex, and involvement with the criminal justice and child welfare systems. Logistic regression was used to investigate potential associations. RESULTS: 161 individuals with diagnosed or at risk for FASD, (53 % male; mean age = 15.7 years, SD = 9.1) were included in the analysis. High levels of psychological/developmental disabilities (78 %), physical comorbidities (38 %), substance use (50 %), and involvement in child welfare (75 %) and criminal justice systems (30 %) were found across the entire group. Individuals over 20 reported the greatest proportion of any past substance (60.9 %), alcohol use (39.1 %) and stimulant use (30.4 %), compared to individuals aged 10-19 (41.3 %; 12.0 %; 14.1 %, respectively). Involvement with the child welfare system was associated with higher chances of having anxiety (OR 4.1; 95 % CI: 1.25-15.00). Involvement with the criminal justice system was associated with higher rates of past substance and cannabis use. CONCLUSION: Individuals with FASD demonstrate a significant need for access to mental health and addiction services, especially among those with involvement in the child welfare and criminal justice systems. These findings point to the importance of improving policies to support the unique needs of individuals with FASD.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".