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Medicine (Baltimore) ; 101(33): e30056, 2022 Aug 19.
Article in English | MEDLINE | ID: covidwho-2001503

ABSTRACT

During the coronavirus disease 2019 pandemic, we considered the case of a child with developmental language disorder (DLD) who could not go to the hospital on time to receive timely rehabilitation treatment due to disrupted hospital operations. The application of cloud-based rehabilitation platforms has provided significant advantages and convenience for children with DLD in-home remote rehabilitation. Among them, the JingYun Rehab Cloud Platform is the most widely used in mainland China. It is an interactive telerehabilitation system developed by Weixin Huang that delivers personalized home rehabilitation for special education children. In this study, we used the JingYun Rehab Cloud Platform to investigate the extent to which cloud-based rehabilitation is effective for children with DLD in terms of language and cognitive outcomes. This was a prospective cohort study including all children who were evaluated and diagnosed with DLD through Sign-Significant Relations and were followed up at the rehabilitation clinic of our institute. We followed 162 children with DLD for 3 months, including 84 children with DLD who participated in remote cloud-based rehabilitation on the JingYun Rehab Cloud Platform and 78 children with DLD as the control group who underwent home-based rehabilitation. Language abilities of both groups were assessed using the Chinese version of the Peabody Picture Vocabulary Test-Revised. Several measures of training performance (language, memory, and cognition tasks) were assessed before and after cloud-based rehabilitation in the remote cloud-based rehabilitation group. Children with DLD in the cloud-based rehabilitation group performed significantly better in language abilities, as assessed by the Peabody Picture Vocabulary Test-Revised, than children with DLD in the control group. Furthermore, for children who participated in remote cloud-based rehabilitation, the frequency of training sessions was proportional to their performance on language, memory, and cognition tasks. This study demonstrated the effectiveness of cloud-based rehabilitation on the JingYun Rehab Cloud Platform in treating children with DLD.


Subject(s)
COVID-19 , Language Development Disorders , Child , Cloud Computing , Humans , Language Development Disorders/diagnosis , Language Tests , Pandemics , Prospective Studies
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