Research‐based interventions for children and youth with a Fetal Alcohol Spectrum Disorder: revealing the gap
Bibliographic record
Abstract
BACKGROUND: Alcohol use during pregnancy can result in a continuum of effects including growth deficits, dysmorphology and/or complex patterns of behavioural and cognitive difficulties that influence an individual's functioning throughout their lifespan. We conducted a systematic review to identify research-based interventions for children and youth with a Fetal Alcohol Spectrum Disorder and areas for future study. METHODS: We identified the substantive literature by searching 40 peer-reviewed and 23 grey literature databases, as well as reference lists. We hand-searched eight relevant journals, and undertook a systematic search of Internet sites and review of reports and documents received from key stakeholders. Two reviewers independently assessed eligibility and quality, and extracted data. Given the small number of studies that met all inclusion criteria, both experimental and quasi-experimental studies were included. RESULTS: Ten intervention studies were identified, of which three were experimental or quasi-experimental, and four were non-experimental. Despite multiple attempts, three studies (two in foreign languages and one unpublished) could not be acquired. A meta-analysis could not be undertaken because the included studies examined different interventions or outcomes. Interventions targeted in the included studies were as follows: (i) psychostimulant medications (methyphenidate, pemoline and dextroamphetamine); and (ii) Cognitive Control Therapy. The identified studies were limited by very small sample sizes and weak designs. CONCLUSION: There is limited scientific evidence upon which to draw recommendations regarding efficacious interventions for children and youth with a Fetal Alcohol Spectrum Disorder. Clinicians, researchers, service providers, educators, policy makers, affected children and youth and their families, and others need to urgently collaborate to develop a comprehensive research agenda for this population.
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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 | 0.063 | 0.215 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".