A Comparative Study of Neuro-cognitive Functioning of Children with and without ADHD on Cognitive Assessment System (original) (raw)
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Construct Validity and Diagnostic Utility of the Cognitive Assessment System for ADHD
Journal of Attention Disorders, 2013
ADHD is one of the most common disorders of childhood with prevalence estimates ranging from 3% to 7% according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR; American Psychiatric Association [APA], 2000) and the Centers for Disease Control and Prevention (2005). ADHD is a disorder that includes developmentally inappropriate impulsivity, inattention, and overactivity. Frazier, Youngstrom, Glutting, and Watkins (2007) reported on the significant impact ADHD can have on the academic and occupational achievement. School psychologists are often involved in assessments where attention problems, impulsivity, and overactivity are key features of children's learning and behavioral difficulties. Assessments for ADHD may include structured diagnostic interviews, teacher and parent report behavior rating scales, direct observations, neuropsychological tests, and cognitive tests. The American Academy of Child & Adolescent Psychiatry (2007) noted the use of structured diagnostic interviews and behavior rating scales as best practices in clinical assessment of ADHD. Cognitive ability or intelligence tests and their resulting profiles have been recommended in assessment of ADHD (
Iranian journal of psychiatry, 2014
The aim of this study was to examine the differences between ADHD subtypes in executive function tasks compared to themselves and normal controls. In this study, 45 school aged children with Attention Deficit Hyperactivity Disorder (ADHD) and 30 normal children who were matched based on age and IQ score in Wechsler Intelligence Scale for Children-Revised (WISC-R) were compared in terms of executive function. We used Wisconsin Sorting Card Test to assess executive function in both groups. We also used children's scores in Children Symptom Inventory-4 (CSI-4) for diagnosing ADHD and specifying ADHD subtypes. Data were entered in SPSS-17 and analyzed by T-test and ANOVA static tests to clarify the differences between ADHD and controls and between ADHD subtypes. Scheffe's test was also used to identify which groups were different from one another. The mean and standard divisions (SD) were used for descriptive analysis. ADHD subtypes are significantly different in terms of persev...
Neurocognitive Predictors of ADHD Outcome: a 6-Year Follow-up Study
Journal of abnormal child psychology, 2016
Although a broad array of neurocognitive dysfunctions are associated with ADHD, it is unknown whether these dysfunctions play a role in the course of ADHD symptoms. The present longitudinal study investigated whether neurocognitive functions assessed at study-entry (mean age = 11.5 years, SD = 2.7) predicted ADHD symptom severity and overall functioning 6 years later (mean age = 17.4 years, 82.6 % = male) in a carefully phenotyped large sample of 226 Caucasian participants from 182 families diagnosed with ADHD-combined type. Outcome measures were dimensional measures of ADHD symptom severity and the Kiddie-Global Assessment Scale (K-GAS) for overall functioning. Predictors were derived from component scores for 8 domains of neurocognitive functioning: working memory, motor inhibition, cognitive inhibition, reaction time variability, timing, information processing speed, motor control, intelligence. Effects of age, gender, and pharmacological treatment were considered. Results showed...
Profiles of cognitive ability domains in children with and without ADHD symptoms
Baltic Journal of Psychology
Studies to date have most often compared the mean scores of an ADHD and control group to see if there are differences between them. Various cluster or linear data processing methods have also been used in studies to group children into certain subgroups according to various characteristics, but so far we have not found any study that has succeeded in dividing both ADHD and control group children into such subgroups. Results vary from study to study. Therefore, the aim of this study was to investigate and compare the heterogeneity of different cognitive ability domains in children with and without ADHD symptoms with qualitative data analysis methods - creating unique profiles of cognitive ability domains for each child. In this study participated 76 children aged 8–13 and were divided into two groups: ADHD group – 46 children (M = 10.08; SD = 1.67), control group – 30 children (M = 9.41; SD = 1.60). Four methods were used to calculate cognitive ability domain scores: Stroop’s Word an...
Universal Journal of Psychology, 2017
Objective: The current study explores whether WISC-IV cognitive profiles could allow to differentiate between presentations of ADHD. Method: A clinical sample of 216 subjects aged between 6 and 16 years and distributed into 2 subgroups (ADHD inattentive type group aged M = 8.5, SD = 2.4; and ADHD combined group M = 10.1, SD = 2.6) was recruited for the study. Results: Processing Speed Index mean score was significantly higher (F (1,214) = 14.7, p< .001, d = 0.52) in ADHD-Inattentive group (M = 90.7; SD = 12.1) than ADHD-Combined group (M = 97.7; SD = 14.7). Furthermore, PSI was negatively associated with "Inattention" dimension (β =-.21, p< .001 family and β =-.19, p< .001 teachers) while it was positively associated with "Hyperactivity/Impulsivity" dimension (β = .27, p< .001 family and β = .33, p< .001 teachers). Conclusions: The higher inattentiveness the lower PSI mean score, while a higher hyperactivity/impulsivity mean score would reduce the impact caused for inattentiveness. Thus, ADHD-I profile would tend to show a significant lower PSI mean score than ADHD-C.
2014
SUMMARY Objective: The aim of this study was to evaluate the predictive value of Intelligence Quotient scores (IQs), subtests of Wechsler Intelligence Scale for Children-Revised (WISC-R), and the Kaufman’s and Bannatyne’s categories scores in attention deficit hyperactivity disorder (ADHD). In addition, this study was designed to examine the difference of some neurocognitive skills for children with ADHD and their unaffected peers using the WISC-R subtests. Method: WISC-R’s subtest and IQ scores, and scores of Kaufman’s and Bannatyne’s categories of the children who were diagnosed with only ADHD were compared with the same scores of the children in the healthy control group (N= 111) and the ADHD with comorbid group (N= 82). Results: It was found that the subtest scores (vocabulary, comprehension, digit span, picture completion, and block design) of the children with only ADHD and ADHD with comorbidity were significantly lower than the healthy group. In addition, object assembly subt...
Journal of Applied School Psychology, 2012
Index have been advanced as possible diagnostic markers of attention deficit hyperactivity disorder. This hypothesis was tested with a hospital sample with attention deficit hyperactivity disorder (n = 78), a referred but nondiagnosed hospital sample (n = 66), a school sample with attention deficit hyperactivity disorder (n = 196), a school matched comparison sample (n = 196), and a simulated standardization sample (n = 2,200). On the basis of receiver operating characteristic analyses, the General Abilities Index-Cognitive Proficiency Index discrepancy method had an area under the curve of (a) .64, 95% CI [0.58, 0.71] for the hospital attention deficit hyperactivity disorder sample compared with the simulated normative sample, (b) .46, 95% CI [0.37, 0.56] for the hospital attention deficit hyperactivity disorder sample compared with the referred but nondiagnosed hospital sample, (c) .63, 95% CI [0.59, 0.67] for the school attention deficit hyperactivity disorder sample compared with the simulated sample, and (d) .50, 95% CI [0.45, 0.56] for the school attention deficit hyperactivity disorder sample compared with the matched comparison sample. These area-under-the-curve values indicate that the General Abilities Index-Cognitive Proficiency Index discrepancy method has low accuracy in identifying children with attention deficit hyperactivity disorder.
Cognitive Abilities in Children with ADHD, Comorbid Epilepsy and Typically Developed Children
Human, Technologies and Quality of Education, 2022
The aim of the study was to assess the differences in cognitive abilities compared across clinical and control groups. It was hypothesized that differences between groups would be small or non-existant, due to rather heterogeneous clinical profiles. And they could be partially explained by participants’ age as cognitive abilities develope over time. Further analysis of the sample was performed by creating cognitive ability profiles of the participants. The study used data from the project “Development of a Screening Method for Children with ADHD and CSWS in Children aged 7–15”, and included data from 97 children, which were divided into 3 groups: ADHD, combined ADHD and epilepsy and control group. For assessing cognitive abilities an extended battery of executive and other cognitive computerized tests were used: Stroop Color and Word Test, Digit Span Test, Symbol Digit Modalities Test, and Continious Performance Test. The analysis of cognitive ability profiles reveals a wide range o...