Machine-learning models can assist in diagnosing autism but have biases. We examines the correlates of misclassifications and how training data affect model generalizability. The Social Responsive Scale data were collected from two cohorts in Taiwan: the clinical cohort comprised 1203 autistic participants and 1182 non-autistic comparisons, and…

Language impairment (LI) and attention-deficit/hyperactivity disorder (ADHD) are 2 relatively common developmental disorders that have been shown to have high rates of co-occurrence in a number of studies, and this phenomenon is also commonplace in the experience of many clinicians. Understanding this comorbidity, therefore, is central to building…

To evaluate evidence for motor impairment specificity in autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD). Children completed performance-based assessment of motor functioning (Movement Assessment Battery for Children: MABC-2). Logistic regression models were used to predict group membership. In the models…

The current study examined the incremental utility of rating scales, a structured diagnostic interview, and multiple informants in a comprehensive assessment of attention-deficit/hyperactivity disorder (ADHD). The sample included 185 children with ADHD (M[subscript age] = 9.22, SD = 0.95) and 82 children without ADHD (M[subscript age] = 9.24, SD =…

We examined the phenotypic expression of attention-deficit/hyperactivity disorder (ADHD) across cultures by assessing the factor/latent class structure of its core symptoms. We conducted a systematic review of the literature published from January 1987 to November 2008 using Medline and PsycINFO. We systematically reviewed 2,511 article abstracts,…