scholarly journals Construct Validity and Diagnostic Utility of the Woodcock Johnson Tests of Cognitive Abilities and Clinical Clusters for Children with Attention Deficit/ Hyperactivity Disorder: A Preliminary Investigation

2021 ◽  
Vol 4 (1) ◽  
pp. 37-49
Author(s):  
Linda A.
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Construct Validity ◽  
Attention Deficit ◽  
Cognitive Abilities ◽  
Preliminary Investigation ◽  
Diagnostic Utility ◽  
Hyperactivity Disorder ◽  
Woodcock Johnson

scholarly journals Mapping the neuroanatomic substrates of cognition in familial attention deficit hyperactivity disorder

2018 ◽  
Vol 49 (4) ◽  
pp. 590-597 ◽  
Author(s):  
Rachel Muster ◽  
Saadia Choudhury ◽  
Wendy Sharp ◽  
Steven Kasparek ◽  
Gustavo Sudre ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Working Memory ◽  
Information Processing ◽  
Attention Deficit ◽  
Cognitive Abilities ◽  
Cognitive Skills ◽  
Spatial Working Memory ◽  
Medication History ◽  
Hyperactivity Disorder ◽  
Psychostimulant Medication

AbstractBackgroundWhile the neuroanatomic substrates of symptoms of attention deficit hyperactivity disorder (ADHD) have been investigated, less is known about the neuroanatomic correlates of cognitive abilities pertinent to the disorder, particularly in adults. Here we define the neuroanatomic correlates of key cognitive abilities and determine if there are associations with histories of psychostimulant medication.MethodsWe acquired neuroanatomic magnetic resonance imaging data from 264 members of 60 families (mean age 29.5; s.d. 18.4, 116 with ADHD). Using linear mixed model regression, we tested for associations between cognitive abilities (working memory, information processing, intelligence, and attention), symptoms and both cortical and subcortical volumes.ResultsSymptom severity was associated with spatial working memory (t = −3.77, p = 0.0002), processing speed (t = −2.95, p = 0.004) and a measure of impulsive responding (t = 2.19, p = 0.03); these associations did not vary with age (all p > 0.1). Neuroanatomic associations of cognition varied by task but centered on prefrontal, lateral parietal and temporal cortical regions, the thalamus and putamen. The neuroanatomic correlates of ADHD symptoms overlapped significantly with those of working memory (Dice's overlap coefficient: spatial, p = 0.003; verbal, p = 0.001) and information processing (p = 0.02). Psychostimulant medication history was associated with neither cognitive skills nor with a brain–cognition relationships.ConclusionsDiagnostic differences in the cognitive profile of ADHD does not vary significantly with age; nor were cognitive differences associated with psychostimulant medication history. The neuroanatomic substrates of working memory and information overlapped with those for symptoms within these extended families, consistent with a pathophysiological role for these cognitive skills in familial ADHD.

Attention-deficit hyperactivity disorder (ADHD): progress and controversy in diagnosis and treatment

2018 ◽  
Vol 35 (3) ◽  
pp. 251-257
Author(s):  
D. M. Foreman ◽  
S. Timimi
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Construct Validity ◽  
Patient Outcomes ◽  
Attention Deficit ◽  
Power Relationships ◽  
Social Construct ◽  
Adhd Diagnosis ◽  
Hyperactivity Disorder ◽  
Drug Treatments ◽  
Definition Of

Knowledge about attention-deficit hyperactivity disorder (ADHD) is rapidly accumulating. Recent advances in diagnosis, genetics, neuroimaging, drug and non-drug treatments are considered, and the results are related to the critical attack on the ADHD diagnosis, which argues it a medicalising social construct, unhelpfully sustaining power relationships. The advances reviewed suggest that, while this attack can be conclusively dismissed as wrong and misleading, the phenomenological definition of ADHD is no longer sufficient for construct validity, though continues to be valuable as a guide for clinicians. The humanising and individualising concerns underlying the attack on the diagnosis could usefully be redirected to improving effective measurement of patient outcomes.

Diagnostic utility of brain activity flow patterns analysis in attention deficit hyperactivity disorder

2017 ◽  
Vol 47 (7) ◽  
pp. 1259-1270 ◽  
Author(s):  
J. Biederman ◽  
P. Hammerness ◽  
B. Sadeh ◽  
Z. Peremen ◽  
A. Amit ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Learning Algorithm ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Brain Network ◽  
Diagnostic Utility ◽  
Hyperactivity Disorder ◽  
Network Activation ◽  
Eeg Data

BackgroundA previous small study suggested that Brain Network Activation (BNA), a novel ERP-based brain network analysis, may have diagnostic utility in attention deficit hyperactivity disorder (ADHD). In this study we examined the diagnostic capability of a new advanced version of the BNA methodology on a larger population of adults with and without ADHD.MethodSubjects were unmedicated right-handed 18- to 55-year-old adults of both sexes with and without a DSM-IV diagnosis of ADHD. We collected EEG while the subjects were performing a response inhibition task (Go/NoGo) and then applied a spatio-temporal Brain Network Activation (BNA) analysis of the EEG data. This analysis produced a display of qualitative measures of brain states (BNA scores) providing information on cortical connectivity. This complex set of scores was then fed into a machine learning algorithm.ResultsThe BNA analysis of the EEG data recorded during the Go/NoGo task demonstrated a high discriminative capacity between ADHD patients and controls (AUC = 0.92, specificity = 0.95, sensitivity = 0.86 for the Go condition; AUC = 0.84, specificity = 0.91, sensitivity = 0.76 for the NoGo condition).ConclusionsBNA methodology can help differentiate between ADHD and healthy controls based on functional brain connectivity. The data support the utility of the tool to augment clinical examinations by objective evaluation of electrophysiological changes associated with ADHD. Results also support a network-based approach to the study of ADHD.

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