Can Gross Motor Skills Be Trained Through Telehealth-Based Training? Insights From a Randomized Controlled Trial of Creative Movement and Play-Based Interventions in Children With Autism Spectrum Disorder
Notice bibliographique
Résumé
Background The motor trajectories of children with autism spectrum disorder (ASD) are often compromised, leading to difficulties in gross motor performance and locomotor skills by late childhood. Our past work has suggested that whole-body movement interventions using rhythmic contexts can facilitate gross motor skills in children with ASD. Objective This study compares the effects of whole-body movement interventions delivered face-to-face (F2F) versus via telehealth (TH) and compares these effects to those of a standard-of-care, seated play (SP) intervention on the gross motor performance of children with ASD. Methods A total of 45 children with ASD aged between 5 and 14 years were seen for 10 weeks, with pretests and posttests conducted during the first and 10th weeks. Children were matched based on age, gender, and level of functioning and then randomly assigned to the general movement (GM), creative movement (CM), or SP groups. An equal number of children in each group received the training via F2F and TH modes. Training was provided in 2 sessions per week for 8 weeks, with sessions lasting from 1 to 1.15 hours. The CM and GM groups received whole-body movement training, whereas the SP group engaged in tabletop activities. The gross and fine motor subtests (fine motor precision, fine motor integration, balance, bilateral coordination, running speed and agility, and strength) of the Bruininks-Oseretsky Test of Motor Proficiency were administered at pre- and posttest. We reported standard scores on body coordination, strength and agility, and fine manual control composites. Results The CM and GM groups showed significant improvements on the body coordination composite (CM group’s scores—pretest: mean 35.3, SE 2.1; posttest: mean 40.5, SE 2.7; P<.005; GM group’s scores—pretest: mean 38.1, SE 3.2; posttest: mean 44.7, SE 3.3; P<.005). The GM group’s scores (pretest: mean 36.1, SE 2.6; posttest: mean 40.9, SE 3.1; P<.001) also improved on the strength and agility composite, and a trend for similar improvements was observed in the CM group’s scores (pretest: mean 32.5, SE 2.4; posttest: mean 34.5, SE 2.7; P=.09). The SP group did not show any improvements on the gross motor composites. The SP group’s scores instead showed significant improvements on the fine manual control composite (pretest: mean 36.4, SE 2.3; posttest: mean 41.6, SE 2.5; P<.005). Fine motor skills remained unchanged in the CM and GM groups. In each of the 3 groups, there were no significant differences in the amount of improvements (posttest − pretest) observed for children seen F2F versus via TH for the body coordination (CM group—F2F: mean 4.1, SE 2.6; TH: mean 5.4, SE 1.6; P=.70; GM group—F2F: mean 6.5, SE 2.7; TH: mean 5.6, SE 2.5; P=.80), strength and agility (CM group—F2F: mean 1.3, SE 1.4; TH: mean 2, SE 1.1; P=.70; GM group—F2F: mean 3.7, SE 1.3; TH: mean 5.6, SE 1.5; P=.40), and fine manual control composite standard scores (SP group—F2F: mean 2.2, SE 2.8; TH: mean 1.9, SE 1.2; P=.80). Conclusions The findings of our pilot study emphasize the importance of training gross and fine motor skills in children with ASD and suggest that virtual modes of intervention delivery can be used by movement clinicians to train these skills. Conflicts of Interest None declared.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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.
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