Participation as a Predictor of Quality of Life among Japanese Children with Neurodevelopmental Disorders Analyzed Using a Machine Learning Algorithm.
Autor: | Shiozu, Hiroyasu, Kimura, Daisuke, Iwanaga, Ryoichiro, Kurasawa, Shigeki |
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Předmět: |
DIAGNOSIS of autism
CROSS-sectional method RANDOM forest algorithms CHILD psychopathology PREDICTION models RESEARCH funding ATTENTION-deficit hyperactivity disorder QUESTIONNAIRES DESCRIPTIVE statistics MANN Whitney U Test SURVEYS QUALITY of life MACHINE learning DECISION trees DATA analysis software SOCIAL participation ALGORITHMS REGRESSION analysis CHILDREN |
Zdroj: | Children; May2024, Vol. 11 Issue 5, p603, 10p |
Abstrakt: | Participation is important for children's quality of life (QOL). This study aimed to identify participation factors that influence QOL among Japanese children with neurodevelopmental disorders. Ninety-two Japanese parents of children with neurodevelopmental disorders participated in this study. The parents completed the parent version of the Kid- and Kiddo-KINDL health-related QOL questionnaire and the Participation and Environment Measure for Children and Youth. The data were examined using the random forest algorithm to analyze the participation factors that affected the children's QOL. The analyses revealed that school and community environmental factors that affected participation were the most important predictors of QOL among children. As school and community environments can significantly impact the QOL of children with neurodevelopmental disorders, greater focus should be placed on participation in environmental contexts. [ABSTRACT FROM AUTHOR] |
Databáze: | Complementary Index |
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