MétaCan
Menu
Back to cohort
Record W2170743500 · doi:10.1177/0883073807309244

Handwriting Performance in Children With Attention Deficit Hyperactivity Disorder (ADHD)

2008· review· en· W2170743500 on OpenAlexafffund
Marie Brossard Racine, Annette Majnemer, Michael Shevell, Laurie Snider

Bibliographic record

VenueJournal of Child Neurology · 2008
Typereview
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsMcGill University Health CentreMontreal Children's HospitalMcGill University
FundersHospital for Sick ChildrenCanadian Occupational Therapy Foundation
KeywordsHandwritingAttention deficit hyperactivity disorderPsychologyPopulationDevelopmental psychologySocializationClinical psychologyPsychiatryMedicineComputer science

Abstract

fetched live from OpenAlex

Attention deficit hyperactivity disorder (ADHD) is the most common neurobehavioral condition of childhood. Consequences are multifaceted and include activity limitations in daily-living skills, academic challenges, diminished socialization skills, and motor difficulties. Poor handwriting performance is an example of an affected life skill that has been anecdotally observed by educators and clinicians for this population and can negatively impact academic performance and self-esteem. To guide health and educational service delivery needs, the authors reviewed the evidence in the literature on handwriting difficulties in children with ADHD. Existing evidence would suggest that children with ADHD have impaired handwriting performance, characterized by illegible written material and/or inappropriate speed of execution compared to children without ADHD. Studies with larger sample sizes using standardized measures of handwriting performance are needed to evaluate the prevalence of the problem and to better understand the nature of handwriting difficulties and their impact in 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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.317
Teacher spread0.291 · 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 designSystematic review
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

Citations146
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Child NeurologySame topicWriting and Handwriting EducationFrench-language works237,207