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Record W2125275261 · doi:10.3109/17518423.2010.511421

Investigating the efficacy of an attention training programme in children with foetal alcohol spectrum disorder

2010· article· en· W2125275261 on OpenAlexaff
Kimberly A. Kerns, Jennifer MacSween, Shelly Vander Wekken, Vincenza Gruppuso

Bibliographic record

VenueDevelopmental Neurorehabilitation · 2010
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsUniversity of Victoria
FundersSvenska Forskningsrådet Formas
KeywordsIntervention (counseling)FluencyPsychologyCognitionFetal Alcohol Spectrum DisorderClinical psychologyCognitive trainingFetal alcoholVerbal fluency testDevelopmental psychologyPsychiatryNeuropsychologyAlcohol

Abstract

fetched live from OpenAlex

OBJECTIVE: The current study investigated the efficacy of a direct intervention programme aimed at improving attention abilities in children with foetal alcohol spectrum disorder (FASD). METHODS: The Computerized Progressive Attention Training (CPAT) program is an intervention which targets proposed attention networks. CPAT task difficulty automatically adjusts based on participant performance. Ten children aged 6-15 with FASD completed an average of 16 hours of intervention over ~9 weeks at school, aided by a research assistant providing metacognitive strategies and support. RESULTS: Pre- and post-intervention assessments indicate significant improvement on several attention measures including sustained attention and selective attention. In addition, several measures of spatial working memory, math fluency, and reading fluency also significantly increased, suggesting that better attention leads to better cognitive performance. CONCLUSION: Results provide support for the use of computerized attention training materials as part of an effective intervention for cognitive performance in children 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.257
Teacher spread0.242 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations68
Published2010
Admission routes1
Has abstractyes

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