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Record W2418321488 · doi:10.1177/1087054716652617

Potential Social and Neurocognitive Benefits of Aerobic Exercise as Adjunct Treatment for Patients With ADHD

2016· review· en· W2418321488 on OpenAlexaff
Sivan Klil‐Drori, Lily Hechtman

Bibliographic record

VenueJournal of Attention Disorders · 2016
Typereview
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsMcGill University
Fundersnot available
KeywordsAdjunctAerobic exerciseNeurocognitiveMethylphenidatePsychosocialPsychologyStimulantGuanfacineClinical trialClinical psychologyAttention deficit hyperactivity disorderCognitionPsychiatryPhysical therapyMedicineClonidineInternal medicine

Abstract

fetched live from OpenAlex

Objective: The aim of the article is to review the evidence that aerobic exercise may be a useful adjunct treatment for ADHD. Method: Studies on physical, cognitive, and psychosocial aspects of aerobic exercise that are relevant to ADHD are reviewed and evaluated. Results: Stimulant medication, the main pharmacotherapy for ADHD, and aerobic exercise both act on catecholamine pathways. Aerobic exercise has been shown to be beneficial in preclinical studies on spontaneous hypertensive rats, an animal model of ADHD, and in clinical trials of children with ADHD, as an adjunct treatment to medication. Social and neurocognitive function in children and adults seem to be positively affected by exercise as well. Nevertheless, no controlled clinical trials in adults with ADHD have been conducted. Conclusion: Aerobic exercise may be a useful non-medication adjunct therapy for ADHD. The clinical effectiveness of aerobic exercise for ADHD in children and adults warrants further clinical studies.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.343
Teacher spread0.301 · 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 designNot applicable
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

Citations10
Published2016
Admission routes1
Has abstractyes

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