Estimating DSM accuracy for Attention Deficit Hyperactivity Disorder Based on Neurophysiological, Psychological, and Behavioral Correlates
Background.Psychiatric nosology lacks objective biological foundation, as well as typical biomarkers for diagnoses, which raises questions about its validity. The problem is particularly evident concerning Attention Deficit/Hyperactivity Disorder (ADHD). The objective of this study is to estimate whether the \"Diagnostic and Statistical Manual of Mental Disorders\" (DSM) is biologically valid for ADHD diagnosis using a multivariate analysis for small samples from a large dataset concerning neurophysiological, behavioral, and psychological variables.\n\nMethodsTwenty typically developing boys and 19 boys diagnosed with ADHD, aged 10-13 years, were examined using the Attentional Network Test (ANT) with records of event-related potentials (ERPs). From 815 variables, a reduced number of latent variables (LVs) were extracted with a clustering method, for further reclassification of subjects using the k-means method. This approach allowed multivariate analysis to be applied to a significantly larger number of variables than the number of cases (E. Wigneau et al., 2003, 2015)\n\nResultsFrom datasets including ERPs from the mid-frontal, mid-parietal, right frontal, and central channels, only seven subjects were miss-reclassified by the LVs. An estimated specificity of 75.00% and sensitivity of 89.47% for DSM were found in the reclassification. The kappa index between DSM and behavioral/psychological/neurophysiological data was 0.75, which is regarded as a \"substantial level of agreement\".\n\nDiscussionResults showed that CLV is a useful method for diagnostic classification using a large dataset of small samples, suggesting the biological validity of DSM for ADHD diagnosis, in accordance to alterations in fronto-striatal networks previously related to ADHD.