Specific Learning Disorder in Children and Adolescents, a Scoping Review on Motor Impairments and Their Potential Impacts

Blanchet, Mariève; Assaïante, Christine

doi:10.3390/children9060892

Cited by 13 publications

(9 citation statements)

References 126 publications

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“…A growing body of recent literature supports these findings. For example, a review by Blanchet and Assaiante [ 25 ] cited 36 studies reporting on motor impairments in students with SLD. These studies used a variety of qualitative motor tests, which identified minor to severe levels of motor impairment (fine motor, gross motor, and postural skills) in children with SLD.…”

Section: Introductionmentioning

confidence: 99%

“…These studies used a variety of qualitative motor tests, which identified minor to severe levels of motor impairment (fine motor, gross motor, and postural skills) in children with SLD. Children and adolescents with SLDs also showed significant impairments in bilateral coordination, balance, and manual dexterity [ 25 ]. Furthermore, children with SLD displayed poorer performance in timing precision of motor coordination, demonstrated significant deficits in bimanual tasks, and made more sequential errors [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

“…Children and adolescents with SLDs also showed significant impairments in bilateral coordination, balance, and manual dexterity [ 25 ]. Furthermore, children with SLD displayed poorer performance in timing precision of motor coordination, demonstrated significant deficits in bimanual tasks, and made more sequential errors [ 25 ]. In a recent cross-sectional study of 200 children (100 with SLD and 100 without SLD), researchers assessed motor performance using the second edition of the Bruininks-Oseretsky Test of Motor Skills (BOT-2) [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

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Associations between Executive Functions and Sensorimotor Performance in Children at Risk for Learning Disabilities

Tószegi,

Zsido,

Lábadi

2023

Occupational Therapy International

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Executive functions (EF) and sensorimotor skills play a critical role in children’s goal-directed behavior and school readiness. The aim of the current study is to provide new insights into the relationship between executive functions and sensorimotor development by considering the risks associated with learning difficulties. Therefore, we investigate the predictive role of EF and sensorimotor skills in the development of learning difficulties during preschool years. Ninety-five preschool children (5–7 years old) were tested, comparing the performance of children that are at risk of learning difficulties ( n = 55 ) to the performance of typically developing children ( n = 40 ). Participants completed a battery for the assessment of sensorimotor skills (i.e., Southern California Sensory Integration Test: postural imitation, body midline crossing, bilateral motor coordination, and standing balance with eyes open) and executive functions (i.e., inhibition, cognitive flexibility, and verbal working memory). Our results show that children at risk for learning difficulties exhibited more impairments on sensorimotor and EF measures (inhibition and verbal working memory) when compared with TD children. We ran three separate binary logistic regression analyses to assess the relative influence of EF and sensorimotor functions on predicting risk for learning difficulties. Our findings demonstrated that verbal working memory as EF function (odd ratio OR = 0.91 , 95% CI 0.78-0.91, P = 0.05 ) and standing balance skills as a sensorimotor skill (odd ratio OR = 0.86 , 95% CI 0.81-0.98, P = 0.01 ) were the strongest predictors of risk for learning difficulties. The findings point to the importance of supporting children’s executive function development and promoting sensorimotor development, as both fundamentally influence school readiness.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Associations between Executive Functions and Sensorimotor Performance in Children at Risk for Learning Disabilities

Tószegi,

Zsido,

Lábadi

2023

Occupational Therapy International

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“…This is related, as shown in this study, to the fact that the main research topic is the influence of motor skills on academic performance. The publication carried out by Blanchet et al [ 64 ] in 2022, in which they analyzed how students with specific learning disabilities may have impaired motor skills, stands out. Thus, they concluded that out of the 36 studies analyzed, all reported motor impairments, which can be seen to increase in subjects with ADHD and coordination problems.…”

Section: Discussionmentioning

confidence: 99%

Citation Network Analysis on the Influence of Vision on Academic Performance

et al. 2023

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Background: Proper vision is absolutely critical to children’s academic performance, as vision problems can drastically affect learning ability. Currently, the existing literature in this field is somewhat inconsistent and carries several controversies about the influence of vision on academic performance. In this study, citation networks were utilized in order to analyze the relationship between publications and authors, the most-cited publication, and the different research areas. Additionally, the most commonly utilized publication sources along with the most common research areas were also pinpointed. Methods: The aforementioned search was executed in the Web of Science database, with a time range beginning in 1941 and ending in 2022. In order to scrutinize the publications, VOSviewer, CiteSpace software, and the Citation Network Explorer were utilized for analysis about the most-cited publication and the different research areas. Results: Overall, 1342 papers were found in all fields along with 2187 citation networks. Moreover, 2020 was the year with the most publications, including 127 publications and 4 citation networks. Bull et al., published in 2008, was the most-cited work, reaching a citation index of 975. The clustering function managed to identity four groups with the most engaging research topics from researchers: motor visual skills, visual memory, the influence of vision on the different learning styles, and abnormal development of the visual system. Conclusions: In the end, the topic with the greatest interest was the influence of visual motor skills on academic performance. Ideally, this paper will assist fellow researchers in quickly noting which topics are of greatest interest and how research in this area has evolved.

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“…As a result, less invasive devices are available (i.e., eye-trackers), which provide the child with a computer interaction community and allow understanding of how children engage with digital technologies, letting novel insights into their visual and cognitive processing [18]. Eye tracking is a method for identifying diagnostic biomarkers with evidence in children with ASD [19][20][21], ADHD [22][23][24][25], ID [26][27][28], SLD [29,30], and CD [24,27]. The role of the autonomic nervous system has earned consideration for many types of neurophysiological features of NDs, such as ASD [31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Employing Classification Techniques on SmartSpeech Biometric Data towards Identification of Neurodevelopmental Disorders

Toki

Tatsis

et al. 2023

Signals

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Early detection and evaluation of children at risk of neurodevelopmental disorders and/or communication deficits is critical. While the current literature indicates a high prevalence of neurodevelopmental disorders, many children remain undiagnosed, resulting in missed opportunities for effective interventions that could have had a greater impact if administered earlier. Clinicians face a variety of complications during neurodevelopmental disorders’ evaluation procedures and must elevate their use of digital tools to aid in early detection efficiently. Artificial intelligence enables novelty in taking decisions, classification, and diagnosis. The current research investigates the efficacy of various machine learning approaches on the biometric SmartSpeech datasets. These datasets come from a new innovative system that includes a serious game which gathers children’s responses to specifically designed speech and language activities and their manifestations, intending to assist during the clinical evaluation of neurodevelopmental disorders. The machine learning approaches were used by utilizing the algorithms Radial Basis Function, Neural Network, Deep Learning Neural Networks, and a variation of Grammatical Evolution (GenClass). The most significant results show improved accuracy (%) when using the eye tracking dataset; more specifically: (i) for the class Disorder with GenClass (92.83%), (ii) for the class Autism Spectrum Disorders with Deep Learning Neural Networks layer 4 (86.33%), (iii) for the class Attention Deficit Hyperactivity Disorder with Deep Learning Neural Networks layer 4 (87.44%), (iv) for the class Intellectual Disability with GenClass (86.93%), (v) for the class Specific Learning Disorder with GenClass (88.88%), and (vi) for the class Communication Disorders with GenClass (88.70%). Overall, the results indicated GenClass to be nearly the top competitor, opening up additional probes for future studies toward automatically classifying and assisting clinical assessments for children with neurodevelopmental disorders.

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Specific Learning Disorder in Children and Adolescents, a Scoping Review on Motor Impairments and Their Potential Impacts

Cited by 13 publications

References 126 publications

Associations between Executive Functions and Sensorimotor Performance in Children at Risk for Learning Disabilities

Associations between Executive Functions and Sensorimotor Performance in Children at Risk for Learning Disabilities

Citation Network Analysis on the Influence of Vision on Academic Performance

Employing Classification Techniques on SmartSpeech Biometric Data towards Identification of Neurodevelopmental Disorders

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