How does attention deficit hyperactivity disorder affect children’s road-crossing? A case-control study
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».