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Record W4323035362 · doi:10.1080/15389588.2023.2181664

How does attention deficit hyperactivity disorder affect children’s road-crossing? A case-control study

2023· article· en· W4323035362 on OpenAlexaff
Zahra Tabibi, David C. Schwebel, Mahboobeh Hashemi Juzdani

Bibliographic record

VenueTraffic Injury Prevention · 2023
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversité de Sherbrooke
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentNational Institutes of Health
KeywordsAttention deficit hyperactivity disorderPsychologyExecutive functionsAttention deficitAffect (linguistics)PedestrianCognitionDevelopmental psychologyClinical psychologyAudiologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Objective: Children diagnosed with attention-deficit/hyperactivity disorder (ADHD) may have particularly high pedestrian injury risk given their deficits in attention, inhibition, and concentration. The aims of this study were a) to assess differences in pedestrian skill between children with ADHD and typically-developing children and b) to examine relations between pedestrian skill and attention, inhibition, and executive function among children with ADHD as well as among typically-developing children.Methods: A sample of 50 children with mean age of 9 years participated, 56% of them diagnosed with ADHD. Children completed IVA + Plus, an auditory-visual test evaluating impulse response control and attention and then engaged in a Mobile Virtual Reality (MVR) pedestrian task to assess pedestrian skills. Parents completed the Barkley’s Deficits in Executive Functions Scale-Child & Adolescents (BDEFS-CA) to rate children’s executive function. Children with ADHD engaged in the experiment off any ADHD medications.Results: Independent samples t-tests indicated significant differences between the two groups in all IVA + Plus and BDEFS_CA scores, supporting the clinical diagnoses of ADHD and the distinction between the two groups. Independent samples t-tests also indicated differences in pedestrian behavior: Children in the ADHD group had significantly higher numbers of unsafe crossings in the MVR environment. Partial correlations within samples stratified by ADHD status indicated that for both groups of children, there were positive correlations between unsafe pedestrian crossings and executive dysfunction. There were no relations between IVA + Plus attentional measures and unsafe pedestrian crossings in either group. A linear regression model predicting unsafe crossings was significant, with children with ADHD more likely to cross in a risky manner after controlling for executive dysfunction and child age.Conclusions: ADHD children exhibited riskier street-crossing behavior in the MVR, confirming an increased risk of pedestrian injury among children with ADHD compared to typically-developing children. Risky crossing among the typically-developing children and ADHD was related to deficits in executive function. Implications are discussed in relation to parenting and professional practice.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.317
Teacher spread0.298 · 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.

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

Citations8
Published2023
Admission routes1
Has abstractyes

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