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Article

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

1
Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119077, Singapore
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Department of Paediatrics, Khoo Teck Puat-National University Children’s Medical Institute, National University Health System, Singapore 119228, Singapore
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Singapore Institute of Clinical Sciences, Agency of Science, Technology and Research, Singapore 117609, Singapore
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ICCTR, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
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Department of Primary Education, National and Kapodistrian University of Athens, 157 72 Athens, Greece
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Department of Psychology, College of Arts, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
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Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC 27599, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Paul B. Tchounwou
Int. J. Environ. Res. Public Health 2022, 19(15), 9195; https://doi.org/10.3390/ijerph19159195
Received: 22 June 2022 / Revised: 26 July 2022 / Accepted: 26 July 2022 / Published: 27 July 2022
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. View Full-Text
Keywords: attention-deficit/hyperactivity disorder; SES; preschool attention-deficit/hyperactivity disorder; SES; preschool
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MDPI and ACS Style

Law, E.; Sideridis, G.; Alkhadim, G.; Snyder, J.; Sheridan, M. Classifying Young Children with Attention-Deficit/Hyperactivity Disorder Based on Child, Parent, and Family Characteristics: A Cross-Validation Study. Int. J. Environ. Res. Public Health 2022, 19, 9195. https://doi.org/10.3390/ijerph19159195

AMA Style

Law E, Sideridis G, Alkhadim G, Snyder J, Sheridan M. Classifying Young Children with Attention-Deficit/Hyperactivity Disorder Based on Child, Parent, and Family Characteristics: A Cross-Validation Study. International Journal of Environmental Research and Public Health. 2022; 19(15):9195. https://doi.org/10.3390/ijerph19159195

Chicago/Turabian Style

Law, Evelyn, Georgios Sideridis, Ghadah Alkhadim, Jenna Snyder, and Margaret Sheridan. 2022. "Classifying Young Children with Attention-Deficit/Hyperactivity Disorder Based on Child, Parent, and Family Characteristics: A Cross-Validation Study" International Journal of Environmental Research and Public Health 19, no. 15: 9195. https://doi.org/10.3390/ijerph19159195

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