Applied Neuropsychology: Child最新文献

This study aimed to explore the implementation of an AI-enhanced motor and cognitive intervention for a 7-year-old child with developmental delay. A case study design was employed using an A-B framework (pre-test, intervention, post-test) over 12 weeks. The intervention incorporated AI-based tools such as Lumosity, Just Dance, and Cogmed for tailored motor and cognitive activities. The Bruininks-Oseretsky Test of Motor Proficiency-2 Brief Form (BOT-2 BF) and the Dynamic Occupational Therapy Cognitive Assessment for Children (DOTCA-Ch) were used to evaluate outcomes. Post-intervention, significant improvements were observed in BOT-2 BF and DOTCA-Ch scores, indicating enhanced motor coordination, and cognitive abilities. AI-enhanced interventions demonstrated the potential to address developmental delays by providing adaptive, engaging, and effective therapeutic activities. The findings highlight the feasibility of integrating AI tools into therapy, with implications for broader adoption in addressing developmental challenges. Further research is recommended to explore generalizability and long-term effects.

Objective: This study examined neurocognitive deficits in Cognitive Flexibility (CF) and Visual-Motor Search (VMS) among children with Frontal Lobe Epilepsy (FLE), Temporal Lobe Epilepsy (TLE), and Non-Epileptic (NE) controls to inform subtype-specific interventions.

Methods: We assessed 90 children (30 FLE, 30 TLE, 30 NE; ages 7-12), matched on key demographics, using the Wisconsin Card Sorting Test (WCST) to assess CF and Trail Making Tests (TMT-A/B) to evaluate VMS. Group differences were analyzed using MANOVA with Bonferroni post-hoc comparisons.

Results: MANOVA revealed significant group differences with a large effect size (F (12, 164) = 28.43, p < .001, ηp² = .68). Post-hoc tests confirmed a hierarchy of impairment: children with FLE performed worse than those with TLE on both CF and VMS measures, and the TLE group scored lower than NE controls on all tasks. Significant differences were found on all TMT and WCST sub-measures.

Discussion: The findings indicate hierarchical CF and VMS impairments in pediatric epilepsy, likely linked to frontal-parietal and hippocampal-temporal dysfunction. This suggests a need for tailored interventions, such as metacognitive training for FLE and contextual cueing for TLE. Future research should use neuroimaging and more diverse populations.

Objectives: The aim was to investigate the impact of mindfulness-based intervention on repetitive and stereotypical behaviors in children with autism spectrum disorder (ASD).

Methods: This study is a quasi-experimental pretest-post-test design with a control group, in which the effect of a mindfulness-based intervention program on the level of stereotypical behaviors of children with ASD is examined. Children with ASD aged 7 to 12 who were receiving education and services in special centers for children with ASD in Jeddah in 2024-2025. To select the sample group, two of the autism centers in Jeddah were referred, and 60 children from the center were selected using purposive sampling and randomly divided into two groups of 30 experimental and 30 control subjects. In the study, covariance analysis (ANCOVA) was used.

Results: The results showed that the mindfulness-based intervention program was effective on all subscales of stereotypical behaviors of children with ASD.

Conclusions: These findings suggest great promise for the use of mindfulness-based intervention with students with ASD to improve their stereotypical behaviors.

Working memory is widely acknowledged as a core and essential executive functions. The aim was to examine the mediating role of self concept in hierarchical relationship between working memory and executive functions. This cross-sectional descriptive-analytical study was conducted. A sample of 120 intellectually gifted children (mean age = 10.77 years, SD = 0.89, 80 females; 66% and 60 males, 44%) participated in the study. A mediation model, was examined, proposing the existence of interrelations between executive functions, working memory capacity and academic performance of highly able students, and a mediated path of self-concept. Structural equation modeling (SEM), with full information maximum likelihood estimation (FIML) was used to examine bivariate correlations and the mediation model. Multiple fit indices in addition to the chi-square test statistic were used to assess model fit. The results of the full mediation structural model fit indicated that the model fit the data well, with Chi-square = 733.041, p = 0.000, Relative Chi-Sq = 1.773; GFI = 0.825, CFI = 0.917, IFI = 0.910, RMSEA = 0.052. The Goodness of-fit indices of the structural model indicated that the GFI, CFI, and IFI approached or exceeded the cutoff value of 0.90.

There is a pressing need for well-defined phonological assessment protocols and the development of valid, reliable, and clinician-friendly tools tailored to the unique linguistic contexts of each country. This study reports the initial phase of establishing normative data on phonological development in Persian-speaking children aged 24-84 months. The objective was to develop a robust set of single words varying in length and syllabic structure for use in speech sound assessment. Using a content analysis approach, 108 words were selected, ranging from one to six syllables (35 monosyllabic, 26 disyllabic, and 47 polysyllabic). Word selection was guided by psycholinguistic principles, including phoneme frequency, phonotactic diversity, syllabic complexity, and lexical familiarity. Criteria ensured cultural appropriateness, absence of repeated phonemes, diverse syllable structures, and inclusion of all consonants across positions. The stimuli are designed to probe underlying speech motor planning and phonological encoding processes in children. These words were organized into 18 semantically related image sets, each containing six words. Monosyllabic and disyllabic items included at least two Persian consonants in both initial and final syllable positions, and each consonant was represented by at least one polysyllabic word. Eight clinically-experienced adults evaluated name-image agreement, while 10 children aged 30-54 months demonstrated over 50% spontaneous naming and over 70% familiarity with the words. The final stimulus set includes a substantial number of polysyllabic words and appears suitable for analyzing phonetic and phonemic inventories, and phonological error patterns in Persian-speaking children.

Objective: Mental health (MH) and attention deficit hyperactivity disorder (ADHD) are inextricably linked, having the same symptoms and complications. The goal of this research is to pinpoint the precise brain areas that cause ADHD in children and to make it possible to diagnose the disorder early. The study intends to provide a trustworthy diagnosis framework that enables prompt intervention using cutting-edge electroencephalogram (EEG) data analysis and machine learning (ML) approaches.

Method: This study uses EEG decomposition for improved ADHD detection. Decomposition techniques, such as the discrete cosine transform (DCT), short-time Fourier transform (STFT), and empirical mode decomposition (EMD), are used to break down EEG signals into sub-bases. As STFT demonstrated the highest accuracy, in further studies ML algorithms use STFT sub-bands on various combinations of brain regions as feed-ins to detect ADHD.

Result: The results demonstrate that STFT methods outperform DCT and EMD. The trial outcomes revealed that, when utilizing a combination of 19 electrode sites, the STFT approach achieved the best accuracies, specifically 96% with light gradient-boosting machine (LightGBM) models. However, when utilizing STFT with LightGBM, the combination of Fp1F3C3C4P4 (5 electrode placements) yields 91% accuracy and 93% on Fp1F3C3C4P4 as well as Fp1F3C3C4F8.

Novelty: While our previous research has separately investigated the efficacy of EMD and STFT/DCT, this presents the first comprehensive, head-to-head comparison of all three techniques within a unified framework. We conclusively demonstrate that STFT-based features, when paired with a LightGBM classifier, achieve a new state-of-the-art accuracy of 96%. Building on this superior model, we conduct a novel and granular electrode-reduction analysis to identify a minimal 5-channel configuration that maintains over 91% accuracy, directly addressing the need for scalable and cost-effective diagnostic systems and establishing a clear pathway for their development.

Specific learning disorder (SLD) is a neurodevelopmental disorder that affects 5-15% of school-aged children worldwide. Often, difficulties in reading (SLD-RD) and mathematics (SLD-MD) occur together. Deficits in phonological awareness (PA) have been identified as the common factor between the two difficulties. Intervention in PA has been shown to be effective in SLD-RD; however, it is not clear whether it is also effective in SLD-MD. Neuropsychological intervention is usually conducted face-to-face, but when the patient is in a remote location or during extraordinary situations such as the COVID-19 pandemic, tele neuropsychology (TeleNP) may be a suitable alternative. The objective of this study was to evaluate the efficacy of a telerehabilitation program for PA to improve math skills in children with SLD-RD/SLD-MD. The study had an N-of-1 SCED design, and included six children aged 10-12 years with SLD-RD/SLD-MD. After four baseline measurements with an arithmetic verification paradigm, they were treated with TeleNP-PA. The effect on each participant was evaluated using visual analysis and the reliable change index. After the intervention, all participants showed improvement in arithmetic tasks, suggesting that the PA intervention had a positive influence on these skills.

The Teenage Executive Functioning Inventory (TEXI) is a newly developed, reliable, and valid measure to assess deficits in executive functioning. The present study aimed to adapt and evaluate the psychometric properties and factor structure of the Bangla version of the TEXI in a sample of Bangladeshi adolescents. The cross-sectional research on 360 Bangladeshi adolescents aged between 12 and 18 years was carried out. Initially, the 20-item TEXI was translated into Bangla and pretested. Confirmatory factor analysis (CFA) was used to test factor structure and measurement invariance across genders. The CFA identified a two-factor solution, including working memory and inhibition, thereby replicating the original model. Multi-group CFA further suggested configural, metric, scaler, and residual measurement invariance between genders in a Bangladeshi sample. The internal consistency reliability of the TEXI was adequate. Construct and criterion-related validity were confirmed by establishing substantial and statistically significant correlations between the two factors within the TEXI and the associations between academic performance and the overall TEXI score. The Bangla version of the TEXI is a valuable measurement tool for evaluating executive dysfunction among adolescents. This study opens the door to future research on adolescents' executive functioning deficits and their relationship with other real-life behaviors.

The present study aimed to identify autistic traits as a mediator between visual working memory capacity and enhanced performance in visual-perceptual tasks in children with ASD. One hundred-forty children, ages 4-6 years, participated in this study (mean age = 5.34 ± 4.11, 98 males). They were recruited from Taiba Specialized Centers for the Care of People with Special Needs in Saudi Arabia. A correlational design was used to identify the mediating role of autistic traits in the relationship between visual working memory capacity and enhanced performance in visual-perceptual tasks in children with ASD. The present study developed a theoretical model that incorporated autistic traits as a mediator between visual working memory capacity and enhanced performance in visual-perceptual tasks in children with ASD. The study findings indicate that: (1) A significant positive correlation exists between autistic traits and visual working memory capacity; (2) A significant positive correlation exists between autistic traits and enhanced performance in visual-perceptual tasks; (3) The relationship between visual working memory capacity and enhanced performance is mediated by autistic traits.

Adolescents with Fetal Alcohol Spectrum Disorder (FASD) often have challenges with executive functioning (EF), which impacts their ability to self-regulate. In this study, 23 adolescents with FASD completed a self-regulation intervention. The intervention was a manualized Teen Adaptation of the Alert Program®. A nonrandomized waitlist control design was used, and participants completed pre- and post-testing using performance-based measures of EF, and rating scales of EF were completed by caregivers. Results were analyzed three ways; 1) intervention and waitlist control group comparison, 2) whole sample pre-and post- test comparison, and 3) using Reliable Change Indexes to examine individual-level clinically relevant changes. No significant intervention effects were found when comparing the intervention and waitlist control groups. A significant difference was found on a measure of verbal inhibition when total sample pre-and post-test scores were compared. Using Reliable Change Index analysis, 30% participants showed reliable change in the direction of improvement on direct measures of EF, and 57% demonstrated reliable change in the direction of improvement on rating scales. This research study underscores the importance of investigating both individual and group level changes when analyzing data, as well as using reliable change to understand clinically meaningful effects that may be otherwise masked. These findings highlight the potential of the SR intervention to positively impact EF in adolescents with FASD. This study contributes to the growing literature that demonstrates the potential of individuals with FASD to benefit from direct intervention.