Dataset Information

Estimating biological accuracy of DSM for attention deficit/hyperactivity disorder based on multivariate analysis for small samples.

ABSTRACT:

Objective

To estimate whether the "Diagnostic and Statistical Manual of Mental Disorders" (DSM) is biologically accurate for the diagnosis of Attention Deficit/ Hyperactivity Disorder (ADHD) using a biological-based classifier built by a special method of multivariate analysis of a large dataset of a small sample (much more variables than subjects), holding neurophysiological, behavioral, and psychological variables.

Methods

Twenty typically developing boys and 19 boys diagnosed with ADHD, aged 10-13 years, were examined using the Attentional Network Test (ANT) with recordings of event-related potentials (ERPs). From 774 variables, a reduced number of latent variables (LVs) were extracted with a clustering of variables method (CLV), for further reclassification of subjects using the k-means method. This approach allowed a multivariate analysis to be applied to a significantly larger number of variables than the number of cases.

Results

From datasets including ERPs from the mid-frontal, mid-parietal, right frontal, and central scalp areas, we found 82% of agreement between DSM and biological-based classifications. The kappa index between DSM and behavioral/psychological/neurophysiological data was 0.75, which is regarded as a "substantial level of agreement".

Discussion

The CLV is a useful method for multivariate analysis of datasets with much less subjects than variables. In this study, a correlation is found between the biological-based classifier and the DSM outputs for the classification of subjects as either ADHD or not. This result suggests that DSM clinically describes a biological condition, supporting its validity for ADHD diagnostics.

SUBMITTER: Abramov DM

PROVIDER: S-EPMC6571005 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Estimating biological accuracy of DSM for attention deficit/hyperactivity disorder based on multivariate analysis for small samples.

Abramov Dimitri M DM Lazarev Vladimir V VV Gomes Junior Saint Clair SC Mourao-Junior Carlos Alberto CA Castro-Pontes Monique M Cunha Carla Q CQ deAzevedo Leonardo C LC Vigneau Evelyne E

PeerJ 20190612

<h4>Objective</h4>To estimate whether the "Diagnostic and Statistical Manual of Mental Disorders" (DSM) is biologically accurate for the diagnosis of Attention Deficit/ Hyperactivity Disorder (ADHD) using a biological-based classifier built by a special method of multivariate analysis of a large dataset of a small sample (much more variables than subjects), holding neurophysiological, behavioral, and psychological variables.<h4>Methods</h4>Twenty typically developing boys and 19 boys diagnosed w ...[more]

PMID: 31223531

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Project description:Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) criteria for attention deficit/hyperactivity disorder (ADHD) specify two dimensions of inattention and hyperactivity-impulsivity symptoms that are used to define three nominal subtypes: predominantly hyperactive-impulsive type (ADHD-H), predominantly inattentive type (ADHD-I), and combined type (ADHD-C). To aid decision making for DSM-5 and other future diagnostic systems, a comprehensive literature review and meta-analysis of 546 studies was completed to evaluate the validity of the DSM-IV model of ADHD. Results indicated that DSM-IV criteria identify individuals with significant and persistent impairment in social, academic, occupational, and adaptive functioning when intelligence, demographic factors, and concurrent psychopathology are controlled. Available data overwhelmingly support the concurrent, predictive, and discriminant validity of the distinction between inattention and hyperactivity-impulsivity symptoms, and indicate that nearly all differences among the nominal subtypes are consistent with the relative levels of inattention and hyperactivity-impulsivity symptoms that define the subtypes. In contrast, the DSM-IV subtype model is compromised by weak evidence for the validity of ADHD-H after first grade, minimal support for the distinction between ADHD-I and ADHD-C in studies of etiological influences, academic and cognitive functioning, and treatment response, and the marked longitudinal instability of all three subtypes. Overall, we conclude that the DSM-IV ADHD subtypes provide a convenient clinical shorthand to describe the functional and behavioral correlates of current levels of inattention and hyperactivity-impulsivity symptoms, but do not identify discrete subgroups with sufficient long-term stability to justify the classification of distinct forms of the disorder. Empirical support is stronger for an alternative model that would replace the subtypes with dimensional modifiers that reflect the number of inattention and hyperactivity-impulsivity symptoms at the time of assessment. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Dataset Information

Estimating biological accuracy of DSM for attention deficit/hyperactivity disorder based on multivariate analysis for small samples.

Objective

Methods

Results

Discussion

Publications

Estimating biological accuracy of DSM for attention deficit/hyperactivity disorder based on multivariate analysis for small samples.

Similar Datasets

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