A Systematic Review of Interventions to Improve Mental Health and Substance Use Outcomes for Individuals with Prenatal Alcohol Exposure and Fetal Alcohol Spectrum Disorder
Bibliographic record
Abstract
Individuals with fetal alcohol spectrum disorder (FASD) experience remarkably high rates of mental health and substance use challenges, beginning early in life and extending throughout adulthood. Proactive intervention can help to mitigate some of these negative experiences. Although the literature on FASD intervention is growing, there is currently a lack of consolidated evidence on interventions that may improve mental health and substance use outcomes in this population. Informed by a life course perspective, we undertook a systematic review of the literature to identify interventions that improve mental wellness through all developmental stages for people with prenatal alcohol exposure (PAE) and FASD. A total of 33 articles were identified, most of which were focused on building skills or strategies that underlie the well-being of children with PAE and FASD and their families. Other interventions were geared toward supporting child and family wellness and responding to risk or reducing harm. There was a notable lack of interventions that directly targeted mental health and substance use challenges, and a major gap was also noted in terms of interventions for adolescents and adults. Combined, these studies provide preliminary and emerging evidence for a range of intervention approaches that may support positive outcomes for individuals with FASD across the life course.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".