Executive functions (EFs) are essential for goal-directed behavior and cognitive adaptation in dynamic environments. This study explores the relationship between regular organized indoor soccer training and potential better performance in EFs among preadolescents, a critical period for cognitive development. A sample of 60 preadolescents (30 soccer players and 30 non‑athletes) were assessed using standardized tests: Backward Corsi for visuospatial working memory, New Card Sorting Test (NCST) for cognitive flexibility, Forward and Backward Digit Span for working memory, and Stroop Test for inhibitory control. Statistical analyses involved non-parametric tests with Holm-Bonferroni correction to compare EF performance between groups. Results indicated that soccer players performed significantly better in visuospatial working memory (Backward Corsi: p = 0.042) and reactive cognitive flexibility (NCST categories completed and non-perseverative errors: p < 0.005; perseverative errors: p = .048) compared to controls, with no significant difference in verbal working memory (Forward Digit Span: p = .100) or inhibitory control (Stroop: p = .152). These findings suggest that regular soccer training is associated with enhanced performance in visuospatial working memory and reactive cognitive flexibility in preadolescents, supporting the role of team sports in cognitive development. However, the cross-sectional design, modest sample size (power ∼.48), and lack of assessor blinding limit causal inferences and generalizability. Future longitudinal studies with larger, diverse samples are needed to establish causality and inform targeted sports programs.

This study aims to provide a comprehensive, longitudinal perspective on the evolution of executive functions (EF) in early childhood by examining scientific trends and conceptual transformations from 1997 to 2025. A bibliometric analysis was conducted on 530 peer-reviewed articles indexed in Social Sciences Citation Index (SSCI), Emerging Sources Citation Index (ESCI), and Science Citation Index Expanded (SCI Expanded), retrieved from the Web of Science (WoS) Core Collection. To enhance transparency and reproducibility, a rigorous screening process is detailed through a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. The field’s conceptual structure was revealed through co-occurrence and clustering analyses, resulting in four major thematic clusters: (a) Skills and Early Learning, emphasizing school readiness and academic processes; (b) Family Influences, covering socioeconomic factors and parenting practices; (c) Behavioral Dimension, focusing on EF-related difficulties and standardized assessment tools; and (d) Experimental and Intervention-Based Studies, representing program evaluations and mechanism-oriented approaches. Trend analyses demonstrate a notable increase in EF research particularly after 2015, accompanied by a shift from deficit-oriented perspectives toward more ecological, developmental, and intervention-focused approaches. The visualized maps generated in this study illustrate both the dynamic intellectual growth of the field and the conceptual transitions that have shaped EF research in early childhood over nearly three decades.

Attention deficit hyperactivity disorder (ADHD) is a neurological disorder that primarily develops in early childhood and affects motor development, vision, information processing, memory, and sensory functioning in children. Although many works have been focused on developing machine learning (ML) models to diagnose ADHD from electroencephalography (EEG) data, they lack in interpreting the predictions. This article addresses this gap by proposing an explainable artificial intelligence (AI)–driven approach that computes entropy, mutual information, and transfer entropy from EEG data using the 10–20 system, aggregates electrode-level features into lobe-wise representations, applies ML models, and selects the optimal model for interpretable predictions. Experimental and statistical results show that support vector machine provides better results, 92% accuracy of classification of ADHD and proves to be suitable for clinical screening tasks than other state of the art algorithms. Furthermore, explanations are obtained using Local Interpretable Model-agnostic Explanations (LIME), Shapely Additive Explanations (SHAP), and Partial Dependency Plot (PDP). These reveal that higher values of entropy and transfer entropy in frontal region indicates uncertainty; whereas less participation of occipital region denotes dysfunctionality toward visual perception in children with ADHD. The PDP proves that the maximum values of the three measures in frontal, occipital, and central lobes contribute to the feature importance for the prediction class.

Objective This study evaluated the reliability and validity of the Self-Report Symptom Inventory (SRSI) in adolescents, aiming to determine whether the SRSI effectively distinguishes between valid and distorted symptom reports under different instructed response conditions. Method Eighty-eight adolescents, aged 12 to 17 years, from the Dutch-speaking general population completed the SRSI twice: once under honest instructions, and once under one of four randomly assigned conditions: honest (n = 24), feigning depression (n = 23), feigning pain (n = 22), or careless responding (n = 19). Internal consistency, test-retest reliability, and discriminative validity were analyzed. Exploratory analyses examined the impact of careless responding on SRSI scores and the utility of consistency items (i.e., positive health items) in differentiating between careless and feigned responding. Results The SRSI demonstrated high discriminative validity between honest and feigned responses, with specificity of .90 and sensitivity of .91 at the standard cutoff (> 9). When careless responses were combined with feigned responses – both reflecting distorted symptom presentations – sensitivity decreased to .80. Internal consistency was high for both the genuine (α = .91) and pseudosymptoms (α = .81) scales, and test-retest reliability was high (n = 24; r = .93 and .88, respectively). Among careless responders, approximately 50% scored above the SRSI pseudosymptoms standard cutoff. Exploratory findings suggest that endorsement of multiple consistency items after failing the SRSI may reflect careless rather than feigned responding. Conclusions These initial findings support the potential utility of the SRSI as a symptom validity measure for adolescents. The lower specificity at the standard cutoff than that found in experimental feigning studies in adults (.90 vs. ≥ .95) suggests that the cutoff may need to be raised in youth samples. Further validation in clinical populations is necessary before recommending its use in applied settings.

Children who are deaf or hard hearing (DHH) demonstrate difficulties with working memory (WM), which is associated with language, literacy and academic skills. This feasibility study investigated WM, language and literacy skills and the relationship among them in children who are DHH and whether a low-frequency dosage of Cogmed working memory training (CWMT) program leads to improved performance in WM (trained) and in language (untrained) tasks. Twenty-one children, aged 6–16 years who used hearing aids and/or cochlear implants participated in the assessment study. A battery of 14 subtests spanning cognitive, language, and literacy domains was administered to all children. Ten children participated in approximately 40 sessions of CWMT program, administered two-three times per week at their school. Results showed below-average performance by some children on verbal WM, language, and reading comprehension, with demonstrated strengths in word reading skills. Verbal WM showed significant positive associations with language and literacy variables whereas visual WM did not. Following intervention, children demonstrated significant improvements in WM and in recalling sentences task. Results demonstrated feasibility of administering a low-frequency dosage of CWMT program in public schools and provided preliminary evidence for short-term improvement in WM and far transfer of intervention effects.

This research aimed to analyze the extent to which executive functions (EF) predict changes in Science academic performance (SAP) of primary school students, based on student self-reports and parental perceptions of their children’s executive functioning. Students attending primary school in Medina, Saudi Arabia was selected. A non-probability convenience sample was drawn. This sample consisted of 200 children from 3 schools. The present study corresponds to a non-experimental, quantitative design, with a descriptive-correlational scope. Descriptive analyses were performed, and the mean, standard deviation, and minimum and maximum values of the variables of interest were calculated. For inferential analyses, a correlation analysis was first conducted using Pearson’s correlation coefficient to examine the existence of significant correlations between the variables. The results showed that EF related to planning (PL) and working memory (WM), according to the perceptions of the students and their parents, can explain Science academic performance (SAP). The results provide evidence regarding the potential importance of using self-reports and parental reports of cognitive abilities in analyzing the relationship between executive functioning (EF) and Science academic performance (SAP), and in studying the influence of socioeconomic context on SAP in primary school students. These results regarding EF can inform interventions or policies concerning school performance in academic achievement.

Objective This study aimed to compare adolescents diagnosed with major depressive disorder (MDD) and healthy peers in terms of self-esteem, life satisfaction, executive functions, and cognitive flexibility. Methods The study included 76 adolescents aged 12–18 years (38 with MDD, 38 healthy controls) who completed a standardized assessments: the Rosenberg Self-Esteem Scale, Life Satisfaction Scale, Cognitive Flexibility Scale and the Serial Digit Learning Test (SDLT). Depression severity was measured using the Children’s Depression Rating Scale–Revised. Results Adolescents with MDD showed significantly lower scores in cognitive flexibility (p < 0.001), self-esteem (p < 0.001), life satisfaction (p < 0.001), and executive functioning (p = 0.0102) compared to controls. Conclusion Depression during adolescence is associated with notable deficits in cognitive and psychosocial domains, particularly in self-esteem and cognitive flexibility. These findings emphasize that MDD in adolescents extends beyond affective disturbances and involves disruptions in self-perception, adaptability, and learning-based executive processes. Integrating interventions that simultaneously target emotional regulation, self-esteem, and cognitive flexibility may enhance treatment outcomes and promote long-term psychological well-being in depressed youth.

This study examined auditory processing (AP) and selective attention in adolescents with cognitive disengagement syndrome (CDS), attention-deficit/hyperactivity disorder (ADHD), and controls. Participants were 61 adolescents (CDS: n = 20; ADHD: n = 20; ages 12–18) recruited from a child psychiatry clinic, and 21 controls recruited from other hospital outpatient clinics. AP was assessed with the experimental Auditory Selective Attention Task, which included monaural and dichotic listening trials measuring accuracy and reaction time (RT). Executive and attentional symptoms were evaluated with the Barkley Deficits in Executive Functioning Scale; the Swanson, Nolan, and Pelham, Version IV; and the Barkley Child Attention Scale. Both CDS and ADHD groups showed significantly lower AP accuracy than controls (e.g., dichotic percent correct: H = 18.54, p < .001), with no differences between the clinical groups. However, adolescents with CDS exhibited greater executive dysfunction and inattention than those with ADHD (all ps < .05). Regression analyses controlling for gender and diagnostic group identified significant associations only for dichotic listening: higher inattention and poorer self-restraint predicted lower accuracy and slower RTs. No significant relationships were found for monaural tasks. Preliminary findings suggest that CDS does not involve additional basic AP deficits beyond ADHD but is characterized by broader executive and emotional difficulties. Overall, results support a dimensional view, indicating that difficulties in complex auditory contexts reflect higher-order executive control rather than sensory processing.

Objective Prior findings on anxiety comorbidity and cognition in youth with ADHD are mixed. We tested whether co-occurring anxiety disorders relate to differences in selected cognitive outcomes. Methods Retrospective chart review of 175 treatment-naïve patients aged 6–18 years with primary ADHD (ADHD-only n = 114; ADHD+anxiety n = 61) evaluated 2020–2025 in Turkey. Anxiety disorders (GAD, separation anxiety, social or specific phobia) were diagnosed clinically (DSM-5) and supported by K-SADS-PL screening. Outcomes were grade-standardized oral reading speed, Trail Making Test (TMT) A/B time and errors, and WISC-R full-scale, verbal, and performance IQ. Group differences were tested with (M)ANCOVA adjusting for age; Holm–Bonferroni controlled family-wise error. Results The ADHD+anxiety group was older and had higher clinician-rated global severity (CGI-S). After age adjustment and correction, no group differences were observed in reading speed or TMT outcomes. Verbal IQ was nominally higher in the comorbid group but did not remain significant after correction. Conclusions In this clinic-based sample, anxiety comorbidity was not associated with poorer processing speed or cognitive flexibility on this battery.

EEG-based ADHD diagnosis models suffer from two persistent issues: data leakage and the lack of physiologically grounded interpretability, limiting clinical adoption. To address these, this paper presents 3D ADHD-Net and DeepTrace. Unlike established 1D and 2D studies, 3D ADHD-Net is a topology-aware spatiotemporal model that preserves scalp geometry by projecting raw EEG onto a grid, preventing spatial information loss. DeepTrace is a novel explainability framework that traces diagnostic information from latent representations back to input electrode space using balanced sign-aligned ensemble Spearman correlation. All experiments utilized strict subject-independent 5-fold cross-validation, explicitly mitigating epoch-level, preprocessing, and optimization leakage. Using a public pediatric EEG dataset (61 ADHD, 60 controls), the framework achieved 84.23% mean accuracy and 91.20% fold-averaged ROC–AUC, significantly outperforming replicated baselines ( p < 0.05 ), which suffered substantial performance collapses under the same rigorous evaluation. Importantly, DeepTrace identified a consistent fronto–central hypoactivation signature, which was causally validated via phenotype induction and rescue perturbation experiments, confirming reliance on established neurophysiological biomarkers rather than gradient-based artifacts. This study demonstrates that diagnostic performance and interpretability need not be competing objectives, and that physiologically faithful attribution can be integrated into deep learning pipelines for developing clinically trustworthy EEG-based ADHD assessment support systems.