Classifying Young Children with Attention-Deficit/Hyperactivity Disorder Based on Child, Parent, and Family Characteristics: A Cross-Validation Study

Evelyn Law, Georgios Sideridis, Ghadah Alkhadim, Jenna Snyder and Margaret Sheridan
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Evelyn Law: Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
Georgios Sideridis: ICCTR, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
Ghadah Alkhadim: Department of Psychology, College of Arts, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
Jenna Snyder: Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC 27599, USA
Margaret Sheridan: Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC 27599, USA

IJERPH, 2022, vol. 19, issue 15, 1-13

Abstract: We aimed to identify subgroups of young children with differential risks for ADHD, and cross-validate these subgroups with an independent sample of children. All children in Study 1 (N = 120) underwent psychological assessments and were diagnosed with ADHD before age 7. Latent class analysis (LCA) classified children into risk subgroups. Study 2 (N = 168) included an independent sample of children under age 7. A predictive model from Study 1 was applied to Study 2. The latent class analyses in Study 1 indicated preference of a 3-class solution (BIC = 3807.70, p < 0.001). Maternal education, income-to-needs ratio, and family history of psychopathology, defined class membership more strongly than child factors. An almost identical LCA structure from Study 1 was replicated in Study 2 (BIC = 5108.01, p < 0.001). Indices of sensitivity (0.913, 95% C.I. 0.814–0.964) and specificity (0.788, 95% C.I. 0.692–0.861) were high across studies. It is concluded that the classifications represent valid combinations of child, parent, and family characteristics that are predictive of ADHD in young children.

Keywords: attention-deficit/hyperactivity disorder; SES; preschool (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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