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Record W2146175308 · doi:10.1177/1087054710379735

A Physical Activity Program Improves Behavior and Cognitive Functions in Children With ADHD

2010· article· en· W2146175308 on OpenAlexaff
Claudia Verret, Marie‐Claude Guay, Claude Berthiaume, Phillip F. Gardiner, Louise Béliveau

Bibliographic record

VenueJournal of Attention Disorders · 2010
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of ManitobaUniversité du Québec à MontréalUniversité de MontréalHôpital Rivière-des-Prairies
Fundersnot available
KeywordsPsychologyCognitionMotor skillPopulationPhysical fitnessDevelopmental psychologyPhysical activityEffects of sleep deprivation on cognitive performanceClinical psychologyPhysical medicine and rehabilitationPhysical therapyPsychiatryMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study is to explore the effects of a moderate- to high-intensity physical activity program on fitness, cognitive functions, and ADHD-related behavior in children with ADHD. METHOD: Fitness level, motor skills, behaviors, and cognitive functions are assessed by standardized tests before and after a 10-week training or control period. RESULTS: Findings show that participation in a physical activity program improves muscular capacities, motor skills, behavior reports by parents and teachers, and level of information processing. CONCLUSION: A structured physical activity program may have clinical relevance in the functional adaptation of children with ADHD. This supports the need for further research in the area of physical activity with this population.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.323
Teacher spread0.308 · 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 designNon-randomized trial
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

Citations291
Published2010
Admission routes1
Has abstractyes

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Same venueJournal of Attention DisordersSame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207