Child Neuropsychology最新文献

The Developmental Neuropsychological Assessment - II (NEPSY-II) is a widely used assessment battery in pediatric settings, but its internal structure has not been adequately examined. This study employed a rational, empirical approach to examine the construct validity of 23 NEPSY-II subtest scores from children ages 7-12 (M = 9.99, SD = 2.76) in the NEPSY-II norming sample (N = 600; 50% girls). Competing higher-order models based on prior research, hypothesized NEPSY-II domains, and conceptual subtest classifications were evaluated via confirmatory factor analysis and a sequential approach to model comparisons. The results supported the multidimensionality of NEPSY-II subtests and the organization of subtests by hypothesized neuropsychological domains. The best fitting model included a general factor and four first-order factors. Factor loadings from the general factor to first-order factors were very strong. However, general factor loadings for most subtests were less than .50 (range = .21-.69, M = .44), and domain-specific effects for all subtests, independent of the general factor, were even lower (range = .00-.45, M = .44). Interestingly, all subtests demonstrated strong subtest-specific effects, but it is not clear what construct(s) the subtest-specific effects represent. Findings support NEPSY-II authors' emphasis on subtest-level interpretations rather than composite-level interpretations and highlight that NEPSY-II subtest scores should be interpreted carefully and with caution.

Children and adolescents with neurodevelopmental disorders demonstrate extensive cognitive heterogeneity that is not adequately captured by traditional diagnostic systems, emphasizing the need for alternative assessment and classification techniques. Using a transdiagnostic approach, a retrospective cohort study of cognitive functioning was conducted using a large heterogenous sample (n = 1529) of children and adolescents 7 to 18 years of age with neurodevelopmental disorders. Measures of short-term memory, verbal ability, and reasoning were administered to participants with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), comorbid ADHD/ASD, and participants without neurodevelopmental disorders (non-NDD) using a 12-task, web-based neurocognitive testing battery. Unsupervised machine learning techniques were used to create a self-organizing map, an artificial neural network, in conjunction with k-means clustering to identify data-driven subgroups. The study aims were to: 1) identify cognitive profiles in the sample using a data-driven approach, and 2) determine their correspondence with traditional diagnostic statuses. Six clusters representing different cognitive profiles were identified, including participants with varying forms of cognitive impairment. Diagnostic status did not correspond with cluster-membership, providing evidence for the application of transdiagnostic approaches to understanding cognitive heterogeneity in children and adolescents with neurodevelopmental disorders. Additionally, the findings suggest that many typically developing participants may have undiagnosed learning difficulties, emphasizing the need for accessible cognitive assessment tools in school-based settings.

The Pediatric Quality of Life Inventory-Cognitive Functioning Scale (PedsQL^TM-CFS) was developed as a brief, general, symptom-specific tool to measure cognitive function. The 6-item PedsQL™ Cognitive Functioning Scale and PedsQL 3.0 Cancer Module answered 369 parents and 330 children with 5-18 years. Parents also completed Behavior Rating Inventory of Executive Function (BRIEF). The PedsQL™ Cognitive Functioning Scale evidenced excellent reliability (parent proxy-report α = 0.980/Fleiss Kappa: 0.794; children self-report α = 0.963/Fleiss Kappa: 0.790). Both child self-report and parent proxy-report PedsQL™ Cognitive Functioning Scale scores exhibited significant correlations with all parent-report BRIEF summary and subscale scores (p < .05). Both child self-report and parent proxy-report PedsQL™ Cognitive Functioning Scale scores exhibited significant correlations with PedsQL 3.0 Cancer Module total score and subscale scores (p < .05). The PedsQL^TM-CFS can be used in high-risk populations with substantial to perfect reliability, both in regards to total/subcategory scores as well as in children with cancer.

The Tower of London, Drexel Version, Second Edition (TOL-DX) is purported to measure multiple aspects of executive functions, although it also possesses inherent non-executive demands. Such complexity makes it useful in detecting impairment but difficult in interpreting the neurocognitive cause of impairment, particularly in children. This study investigated the developmental, neurocognitive, and symptom correlates of the TOL-DX in children and adolescents with neuropsychiatric disorders. Two-hundred and thirty-three children and adolescents (7-21 years old) completed the TOL-DX during a neuropsychological evaluation as part of clinical care within a children's psychiatric hospital. Pearson correlation, regression models, and receiver operating characteristic curve (ROC) analyses examined the association among variables. Visuospatial and executive functions (EF) were most consistently related to total moves, execution time, and violations. TOL-DX variables were associated with attention in younger participants and EF in older participants. No TOL-DX scores were related to parent-reported symptoms. The TOL-DX possesses inherent visuospatial and attention/executive demands in children and adolescents which are difficult to differentiate, differ by age group, and not associated to clinical symptoms. Taken together, the TOL-DX is complex to interpret, but psychometrically sound and sensitive to neurocognitive impairment in children and adolescents with transdiagnostic neuropsychiatric disorders.

This study aimed to determine some of the factors that influence performance on a comprehensive test of verbal and visual memory in children, the Child and Adolescent Memory Profile (ChAMP) in a mixed clinical sample (n = 178; 56% male, 67% White, median age 12 years). We used hierarchical linear regression analyses with ChAMP standard scores as the dependent variable, and parental education as well as Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) factor index scores as the independent variables. WISC-V Processing Speed and (to a lesser extent) Working Memory were statistically significant predictors of most ChAMP Index scores. In addition, WISC-V Verbal Comprehension contributed to the model for ChAMP Verbal Memory, and WISC-V Visual Spatial to the model for ChAMP Visual Memory. In each case better performance on the WISC-V was predictive of higher scores on the ChAMP, with large effect sizes. WISC-V variables also mediated the positive effect of parental education on ChAMP scores. We conclude that clinicians should consider performance on measures of speed of processing, working memory, language and visual-spatial skills as potential influences on ChAMP results that may suggest a specific memory deficit.

Electroencephalogram (EEG) abnormalities could be seen in up to 60% of non-epileptic children with autism spectrum disorder (ASD). They have been used as biomarkers of ASD severity. The objective of our study is to identify EEG abnormalities in children with different degrees of ASD severity based on the Autism Treatment Evaluation Checklist (ATEC). We also want to assess the quality of life for children with ASD. All of the children underwent at least one hour of sleep-deprived EEG. Forty-five children were enrolled, of whom 42 were male. EEG abnormalities were found in 10 (22.2%) children, predominantly in the bilateral frontal areas. There were no differences in EEG findings among the mild, moderate, and severe ASD groups. The severity of ASD was associated with female sex (p-value = 0.013), ASD with attention deficit hyperactivity disorder (ADHD) (p-value = 0.032), ASD children taking medications (p-value = 0.048), and a lower Pediatric Quality of Life Inventory (PedsQL) (p-value <0.001). Social and emotional domains were the most problematic for health-related quality of life in ASD children, according to parent reports of PedsQL. Further studies with a larger sample size will help to clarify the potential associations between EEG abnormalities and the severity of ASD, as well as the impact on quality of life.

This study uses fNIRS to determine whether there is a difference in the relationship between intra-individual variability and frontal lobe activity between ADHD patients and typically developing children. A total of 28 subjects (14 in ADHD patient group and 14 in control group) participated in this study. The subjects were tested for K-SADS and intelligence, and then the frontal lobe activity of the subjects was measured by continuous performance test, using functional near-infrared spectroscopy (NIRSIT). Processing speed index was significantly lower in the ADHD patient group than in the control group (p = .04). The CPT test results showed a positive correlation in the activity of the right dorsolateral prefrontal region in the patient group, but not at a statistically significant level. In the control group, activity showed a significant level of negative correlation with commission and hit reaction time standard deviation (p = .023; p = .063 respectively). In contrary to ADHD patient group, activation of the right dorsolateral prefrontal area was significantly correlated with reduction of intra-individual variability. This result showing that the relationship between activation of the right dorsolateral prefrontal area of the ADHD patient group and intra-individual variability shows a different pattern from typically developing children.

Learning to read and write are essential academic skills that children develop during their early years of primary school. These skills are supported by various predictive indices that emerge in early childhood. This review has three main goals: to identify which factors are closely examined as predictors for reading and writing, specifically decoding and encoding skills, in different populations and languages (Objective 1); to assess the longitudinal relationship between these predictors and reading and writing skills (Objective 2), considering difficulties or disorders in these areas (Objective 3), during school-age. Using the PRISMA methodology, 81 articles were reviewed. As a first result, there is a significant difference in the number of studies investigating the relationship between predictors and reading (n = 75) compared to writing (n = 18). The most extensively studied predictors for both skills are phonological awareness, language skills, executive functions, rapid automatized naming, and non-verbal cognitive skills. English is the most studied language. Results indicated variability in the relationship between predictors and reading/writing, possibly due to differences in the analyzed populations, chosen outcome measures, and statistical analyses. Additionally, few studies explored the long-term connection between predictors and learning difficulties. In summary, recognizing the multifaceted nature of predictive factors for reading and writing is crucial, and early screening is important for tailored preventive interventions in case of early deficiencies. Future research should delve into writing, conduct cross-cultural studies with diverse languages, and explore the role of predictive factors in understanding reading and writing difficulties or disorders.

Short duration of sleep and poor sleep quality have been linked to poor attention and impulse control in children. We aimed to determine the longitudinal predictive value of sleep quantity and quality during early childhood on objective and caregiver-report measures of attention, impulse control, and executive function in children at age 8 years. We used data from the Health Outcomes and Measures of the Environment (HOME) Study, a pregnancy and birth cohort. Caregivers reported on their child's sleep at ages 2, 2.5, 3, 4, and 5 years. Analysis included 410 participants. We used longitudinal growth curve models of early childhood sleep patterns to predict neurobehavioral functioning at age 8 years. Sleep problems did not predict any of our outcome measures at age 8 years. Sleep duration trended shorter as children matured, so predictive models examined both intercept and slope. Children with the least decline in sleep duration across early childhood had fewer impulsive errors at age 8 years on a continuous performance test (unadjusted p = .013; adjusted p = .013). Children with shorter duration of sleep across early childhood had worse caregiver-reported behavioral regulation at age 8 years (unadjusted p = .002; adjusted p = .043). Neither sleep duration slope nor intercept predicted inattention or metacognitive skills at age 8 years (p > .05). Total sleep time across early childhood predicts behavior regulation difficulties in school-aged children. Inadequate sleep during early childhood may be a marker for, or contribute to, poor development of a child's self-regulatory skills.