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Decision tree model for predicting diagnosis of attention-deficit hyperactivity disorder among preschoolers based on parental questionnaire |
ZHANG Jinsong1,2, PAN Jingxue1,2, SHUAI Lan1, ZHANG Huifeng1,2, XIA Weiping1, WANG Zhouye1, LI Wei1,2 |
1. Department of Medical Psychology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China; 2. Ministry of Education and Shanghai Key Laboratory of Children's Environment Health, Shanghai 200092, China |
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Abstract Objective To discuss the correlation between executive function and attention-deficit hyperactivity disorder (ADHD) symptoms in preschool children, and to establish the ADHD diagnostic prediction model based on clinical data. Methods Parents of kindergarten students (n=105), non-reference clinical patients who were diagnosed as having ADHD (n=263) by the psychiatrists based on Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) and diagnostic infant preschool assessment (DIPA) completed the (Swanson, Nolan, and Pelham Ⅳ Rating Scale,parent version, SNAP-Ⅳ), strengths and difficulties questionnaire (SDQ), and behavior rating scale of executive function-preschool version parent form(BRIEF-P) to evaluate children's symptoms and executive function through different perspectives. Significant factors which contribute to relationship were chosen by correlation analysis, and then whole prediction was made by Logistic regression. To improve the prediction of ADHD, subsections prediction was made using decision tree analysis and Logistic regression conditionally to classify ADHD types. Results ① Factors which were relative to ADHD mainly included inhibition, working memory, inhibitory selfcontrol, emergent metacognition and total BRIEF-P score, hyperactivity, inattention and hyperactivity/impulsivity. ② Logistic regression predicted 88.8% of ADHD, and decision tree analysis showed that the prediction nodes influencing diagnosis of ADHD included inattention, inhibition and inhibitory self-control factors. ③ Logistic regression and decision tree analysis were conducted on ADHD subtype diagnostic prediction and related significant factors. Conclusion The ADHD symptoms and executive function can predict the diagnosis of ADHD in preschool children. Moreover, it predicts the diagnosis of ADHD subtype and comorbidity with oppositional defiant disorder(ODD), providing the references for clinic application.
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