Child Neuropsychology最新文献

Research consistently shows that autistic children often exhibit cognitive challenges, particularly in executive functions (EFs), since the preschool years. EFs are cognitive abilities that help regulate impulses, manage information, filter distractions, and shift focus between tasks. Various performance-based measures have been developed to assess EFs in autistic children. However, inconsistencies in findings have raised concerns about the ability of traditional EF measures to capture the real-life challenges these children face, largely due to reductionist approaches and the overlooked issue of task impurity. Here, we employed a broader comprehensive battery - the Measures of Executive Attention - to assess EFs in 43 autistic children aged 8-14 years, compared to 43 neurotypicals matched for age, sex, and fluid reasoning index. The results revealed that neurotypicals outperformed autistic children in most tasks. Specifically, autistic children showed lower performance in cognitive flexibility and generative thinking in a graphical task, as well as in working memory capacity under novel and emotionally stressful conditions. However, when fine motor and verbal skills were excluded from the composite score calculation, no group differences emerged in certain tasks, such as visual search and working memory capacity in a familiar exercise. Our findings highlight the importance of assessing executive attention through multidimensional and context-sensitive tools and offer new insights into cognitive variability in autism.

This study examines the direct and indirect effects of working memory on reading comprehension in a sample of 395 Chilean fourth-grade students (Mean age 9.97, SD = 0.51; 46% are females) within the context of Spanish, a transparent orthographic system. Using both linear and non-linear approaches, the research investigates the relation between working memory and reading comprehension, as well as whether this relation is mediated by a set of linguistic variables. The linear component was analyzed using path analysis, and the results showed that working memory has a significant direct effect on reading comprehension, as well as indirect effects through vocabulary, word reading, and reading speed. The indirect effect via vocabulary was the most substantial. The non-linear component was assessed using latent profile analysis, and the results revealed three distinct working memory cognitive profiles defined by child performance, which were associated with significantly different outcomes in reading comprehension and its predictors. These findings suggest that working memory is not only foundational for the development of fluent and meaningful reading but also interacts with language-related skills to support comprehension. The study highlights the importance of considering both inter and intra-individual differences in cognitive functioning to understand better the mechanisms underlying reading development in transparent orthographies.

The growing fields of genetics and neurogenetics have brought increased attention to developmental and epileptic encephalopathies (DEEs), a group of rare epilepsy disorders that span genetic and neurological pathology. Among the genetic causes of DEEs, single-gene variants represent a significant and increasingly recognized category. These variants often lead to complex and distinct clinical presentations, including variable seizure types, neurocognitive profiles, and developmental trajectories. Foundational knowledge about these disorders, including their molecular and cellular etiologies, accompanying clinical symptoms, and developmental trajectories, can better inform neuropsychological practice, especially in guiding test selection and recommendations as well as highlighting limitations for evaluation. The primary objective of this paper is to provide an evidence-based primer on single-gene developmental epileptic encephalopathies for pediatric neuropsychologists working with these growing clinical and research populations. The manuscript begins with a broad overview of definitions relevant to the care of those with single-gene epilepsies. The paper then describes the clinical features and neurocognitive outcomes associated with the eight most common single-gene pediatric-onset epilepsies, which is subsequently followed by a brief overview of 13 additional single-gene pediatric-onset epilepsies. The paper concludes with a summary of the treatment landscape and discusses current considerations for neuropsychological assessment with this population.

This study evaluated the psychometric properties of the Swedish version of the Behavior Rating Inventory of Executive Function - Second Edition (BRIEF2) across self-, parent-, and teacher-report forms in a gender- and age-balanced community sample of Swedish youth. We examined factor structure, internal consistency, inter-rater reliability, measurement invariance, and age- and gender-related differences in behavioral executive functioning (EF). Participants included 1,257 adolescents (51.8% girls, aged 11-18) who completed the self-report version, 1,340 parents who completed parent reports on their children (46.7% girls, aged 5-18), and 38 teachers who provided teacher reports for 510 adolescents (58.4% girls, aged 13-18). Results supported the original three-factor model (Behavioral, Emotional, and Cognitive Regulation) across all informants, although model fit was somewhat weaker for teacher ratings. Internal consistency ranged from acceptable to excellent. Measurement invariance across age and gender was largely supported, though some scalar non-invariance was observed. Patterns of age- and gender-related differences varied by informant. Specifically, adolescents reported more EF difficulties with increasing age, whereas parents and teachers reported fewer EF difficulties in older youth. Girls self-reported greater EF difficulties, while parents and teachers generally rated girls as having less difficulty - except in the domain of Emotional Control. However, all observed gender and age differences across informants were small in magnitude. Overall, the findings support the Swedish BRIEF2 as having solid psychometric properties across the self-, parent-, and teacher-report forms. However, minor structural inconsistencies, informant discrepancies, the small teacher sample, and signs of item redundancy suggest areas for future improvement and refinement.

Purpose: The Preschool Activity Ranking (PACS) is a tool that measures preschool children's activity participation by focusing on the frequency and extent of their participation. This study aims to assess the validity and reliability of the Preschool Activity Card Sort (PACS) by conducting a Turkish cultural adaptation of the scale in children diagnosed with autism spectrum disorder (ASD).

Methods: This study was conducted with a prospective cross-sectional study design. Participants included parents of 70 children with ASD (study group) and 27 typically developing children (control group) aged between 3 and 6 years old. Validity was analyzed using construct validity, while reliability was examined through internal consistency and test-retest methods.

Results: Results showed that the control group scored significantly higher than the study group in all sub-scales of the PACS (p < 0.01). Additionally, a statistically significant correlation was found between the PACS and the Canadian Occupational Performance Measure (COPM) in all sub-domains except for the household chores sub-domain. The PACS demonstrated high internal consistency (Cronbach Alpha's = 0.94) and excellent time invariance ICC coefficients for the self-care, social mobility, leisure time (low physical requirement), social interaction, housework, and education sub-domains. For the leisure time (high physical requirement) subdomain, the PACS demonstrated good reliability (ICC = 0.85).

Conclusion: Overall, the Turkish version of the PACS was found to be a valid and reliable tool for evaluating activity participation in children with ASD.

Traumatic brain injury (TBI) is associated with disinhibition, impulsivity, and other sequelae which may make adolescent TBI survivors more likely to engage in health risk behaviors though this has not yet been comprehensively investigated. Extant literature on TBI-related health risk behaviors is limited by a dearth of studies on adolescents, reliance on self-report of TBI, lack of an orthopedic injury (OI) control group, and the fact that TBI's effects on various health risk behavior domains are generally examined separately. The current study clarifies the impact of TBI on health risk behaviors among adolescents, specifically those related to 1) unintentional injury and violence (including aggression- and suicide-related behaviors); 2) tobacco use; and 3) alcohol and other drug use in an analytic sample of 74 adolescents (n = 43 for youth with a complicated mild to severe TBI, n = 31 for youth with an OI). Results indicate youth with a TBI exhibited more suicide-related health risk behaviors at 12-month follow-up (F = 6.063; p = .016; η_p² = .079), as well as a nonsignificant trend toward greater marijuana use (F = 3.747; p = .057; η_p² = .050), compared to youth with an OI while controlling for age. Youth with an OI exhibited greater increases in violence and victimization over the 12-month post-injury period compared to youth with a TBI (F = 4.243; p = .044; η_p² = .067) while controlling for age. Interventions to reduce psychological distress and improve social connectedness, problem-solving, coping, and emotion regulation skills may be most relevant for youth who receive a TBI. Emotion regulation and anger management skills may be relevant for youth who receive an OI.

The relationship between writing and math achievement is not well understood. Phonological awareness (PA), working memory (WM), and fine motor skills (FMS) have been individually linked to theories of writing and math, yet are rarely considered together. The current study evaluates the shared cognitive factors underlying writing and math performance, both timed (e.g. fluency/automaticity) and untimed (e.g. spelling and math computation). It does so among third- through fifth-graders (n = 677) who vary in academic abilities. Results revealed differential relationships. WM had a stronger effect on writing than math for timed but not untimed outcomes. PA had a stronger effect on writing compared to math for both timed and untimed outcomes. PA also had a stronger effect on untimed math compared to timed math. Further, WM fully mediated the relationship between FMS and untimed writing but only partially mediated the relationship between FMS and other academic outcomes. Additionally, PA partially mediated the relationship between WM and all writing and math skills These findings underscore the relevance of FMS, WM, and PA in both writing and math achievement, separately and together. These findings additionally provide guidance for developing a firmer theoretical and empirical understanding of the interrelations of writing and math.

Demand for telehealth services has increased in many settings as a means of reducing patient burden and increasing access to care. It is therefore critical to understand if clinical tools validated for in-person use are feasible to administer via telehealth and, if so, how results may vary from those obtained in-person. The Revised Physical and Neurological Examination of Subtle Signs (PANESS) is a validated assessment of pediatric neuromotor functioning that is sensitive to detecting motor dysfunction in youth. The Timed Motor section of the PANESS is an ideal candidate for telehealth administration given its strong inter-rater reliability when scored via video review. Here, we preliminarily examined the feasibility of administering the Timed Motor section of PANESS via videoconferencing and its equivalence with in-person administration. We administered the Timed Motor section of the PANESS in-person and via videoconferencing in 25 typically developing youth ages 10-18 (including n = 11 who had clinically recovered from concussion). All were able to complete the assessment via videoconference. We observed moderate to excellent reliability of scores obtained in-person and via videoconference (intraclass correlations ranging from .743 to .971). Results suggest that the Timed Motor Section of the PANESS can be administered remotely in typically developing youth (including those with a history of concussion) and that the scores obtained are stable with in-person scores. Future work is needed to examine the feasibility and equivalence of telehealth-based PANESS administration in clinical settings and patient populations.

Pediatric central nervous system (CNS) tumors represent one of the most intricate challenges faced by children and their families in the context of cancer illness. In Italy, the psychosocial working group (GDL) of the AIEOP, composed by professionals (psycho-oncologists/neuropsychologists) involved in the care pathways of patients with CNS tumors, has initiated a consensus process regarding the psychological/neuropsychological assessment of CNS patients to improve accessibility to standardized and shared protocols. Standardized psychological and neuropsychological instruments are proposed in the document, which provides for a selection in a tailor-made approach that is simultaneously shared by various centers.

Artificial intelligence (AI) is reshaping the landscape of attention deficit hyperactivity disorder (ADHD) diagnosis through data-driven and technology-enhanced methodologies. This scoping review, conducted in accordance with PRISMA guidelines, systematically analyzed 54 studies published over the past two decades to assess AI's role in ADHD detection and evaluation. The included studies primarily explored AI applications in brain imaging (MRI), brain activity monitoring (EEG and ECG), behavioral assessments, virtual reality-based testing, and motion-tracking sensors. Among the AI technologies examined, machine learning (ML) and deep learning (DL) algorithms demonstrated promising diagnostic accuracy, with performance rates ranging from 70% to 95%. Convolutional neural networks (CNNs) and support vector machines (SVMs) were particularly effective in image and signal analysis, while natural language processing (NLP) models showed potential in behavioral and cognitive assessments. Despite these advancements, challenges such as algorithmic bias, inconsistent data quality, and the need for extensive, diverse datasets remain barriers to widespread clinical integration. Moreover, while AI models enhance speed and precision in ADHD detection, their applicability in treatment monitoring and personalized intervention remains an area for future research. This review underscores the transformative potential of AI in ADHD diagnosis and advocates for a hybrid approach that integrates AI-driven tools with traditional clinical assessments to enhance diagnostic reliability and patient outcomes.