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Record W2336828550 · doi:10.1177/1087054715622016

Comparing Executive Functioning in Children and Adolescents With Fetal Alcohol Spectrum Disorders and ADHD: A Meta-Analysis

2016· review· en· W2336828550 on OpenAlexaff
Jennifer E. Khoury, Karen Milligan

Bibliographic record

VenueJournal of Attention Disorders · 2016
Typereview
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFetal alcoholPsychologyMeta-analysisExecutive functionsClinical psychologyAttention deficit hyperactivity disorderFetal Alcohol Spectrum DisorderPsychiatryDevelopmental psychologyCognitionAlcoholMedicinePregnancyInternal medicine

Abstract

fetched live from OpenAlex

Objective: Fetal alcohol spectrum disorders (FASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are associated with a range of neurocognitive impairments. Executive functioning deficits are a hallmark feature of both disorders. Method: The present meta-analysis was undertaken to disentangle the behavioral phenotype of FASD and ADHD by quantitatively differentiating executive functioning differences between these two groups. The current meta-analysis reviews 15 studies comparing children and adolescents with FASD and ADHD to typically developing (TD) samples, on a variety of executive function measures. Results: Results indicate that when compared with TD samples, FASD and ADHD samples demonstrate significant executive function deficits ( d = 0.82 and d = 0.55, respectively). In addition, FASD samples experience significantly greater deficits when compared with ADHD samples ( d = 0.25). Results were moderated by IQ and socioeconomic status. Conclusion: These findings further our understanding of the cognitive differences between FASD and ADHD samples and have the potential to influence future basic research, assessment, and intervention.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0110.030
Bibliometrics0.0050.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.031
GPT teacher head0.299
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations29
Published2016
Admission routes1
Has abstractyes

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