Assessing ADHD symptoms in children and adults: evaluating the role of objective measures

• DOI: 10.1186/s12993-018-0143-x
• Publication Date: 2018-05-17T22:18:42Z
• Authors: Theresa S. Emser; Blair A. Johnston; J. Douglas Steele; Sandra Kooij; Lisa Thorell; Hanna Christiansen
• Keywords: Adult; ddc:610; Support vector machines; Support Vector Machine; Research; Middle Aged; Neuropsychological Tests; Classification; 3. Good health; 03 medical and health sciences; 0302 clinical medicine; Children/adults; Attention Deficit Disorder with Hyperactivity; Objective assessment; ADHD; Humans; Neurology. Diseases of the nervous system; Symptom Assessment; RC346-429; Child

Diagnostic guidelines recommend using a variety of methods to assess and diagnose ADHD. Applying subjective measures always incorporates risks such as informant biases or large differences between ratings obtained from diverse sources. Furthermore, it has been demonstrated that tests seem somewhat different constructs. The use objective might thus yield valuable information for diagnosing This study aims at evaluating the role when trying distinguish individuals with ADHD controls. Our sample consisted children (n = 60) adults 76) diagnosed matched controls who completed self- observer well tasks. Diagnosis was primarily based on clinical interviews. A popular pattern recognition approach, support vector machines, used predict diagnosis.We observed relatively high accuracy 79% (adults) 78% (children) applying solely measures. Predicting an diagnosis both exceeded (89.5%) (86.7%), variables proving be most relevant.We argue are more robust against rater bias errors inherent in may replicable. Considering only, we found our study, think they should incorporated diagnostic procedures assessing