Improving executive functioning in children with fetal alcohol spectrum disorders
Bibliographic record
Abstract
An extensive body of literature has documented executive function (EF) impairments in children with fetal alcohol spectrum disorders (FASD); however, few studies have aimed specifically at improving EF. One treatment program that shows promise for children with FASD is the Alert Program for Self-Regulation®, which is a 12-week treatment specifically designed to target self-regulation, a component of EF. The present study sought to examine if Alert would produce improvements in self-regulation that would generalize to other aspects of EF, behavior, and social skills in children with FASD. Twenty-five children aged 8-12 years diagnosed with an FASD were assigned in alternating sequence to either an immediate treatment (TXT) or a delayed treatment control (DTC) group. Both groups received a comprehensive evaluation of EF at baseline and upon completing therapy (TXT), or after a 12- to 14-week interval from baseline (DTC). Parents also completed questionnaires assessing EF and behavior at both time points. For the TXT group only, parent questionnaires were readministered at 6-month follow-up. At the 12-week follow-up, the TXT group displayed significant improvements in inhibitory control and social cognition. Parents of children in the TXT group reported improved behavioral and emotional regulation, as well as reduced externalizing behavior problems. These behavioral improvements along with further improved parent-rated inhibitory control was maintained at the 6-month follow-up. The EF disabilities in children with FASD can be remediated through a targeted treatment approach aimed at facilitating self-regulation skills.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".