Search Results (417)

Introduction: Growing evidence indicates that diet quality significantly influences metabolic parameters and cognitive functioning. In healthy individuals, higher consumption of minimally processed foods and products rich in omega-3 fatty acids is associated with a more favorable lipid profile and better cognitive performance. Patients with schizophrenia present an increased risk of metabolic disturbances and reduced cognitive functioning. This suggests that this group may be particularly sensitive to nutritional factors. However, relatively few studies have simultaneously examined the relationships between diet, metabolism, and cognitive profile in patients with schizophrenia and healthy individuals. Aim: The aim of the study was to compare the relationships between the frequency of consumption of selected food categories and metabolic parameters (glycemia, lipid profile, and insulin resistance), as well as cognitive functions (Stroop Test, Trail Making Test, and verbal fluency), in patients with schizophrenia and healthy men. Methods: The study included 21 patients with schizophrenia and 20 healthy men. All participants completed a questionnaire assessing the frequency of food consumption. Blood samples were collected to determine glucose, insulin, HDL, LDL, and triglyceride levels, and the HOMA-IR index was calculated. Cognitive functioning was assessed using the Stroop Test (RCNb, NCWd) and the Trail Making Test (TMT-A and TMT-B), which measure psychomotor speed and visuospatial working memory, respectively, and the verbal fluency test (semantic and phonological). Correlation analyses were performed separately in both groups. Due to the small sample size, all correlations are treated as exploratory and are analyzed with correction for multiple comparisons. Results: Exploratory analyses identified several patterns of associations between the frequency of consumption of selected food categories, metabolic parameters, and cognitive performance in both healthy men and patients with schizophrenia. The observed patterns differed between groups, suggesting that clinical status and treatment-related factors may modify diet–metabolism–cognition relationships. These findings highlight potential pathways linking dietary habits with metabolic and cognitive outcomes and provide a basis for further hypothesis-driven research. Conclusions: Diet quality may be related to metabolic status and cognitive functioning. However, the pattern of these associations differs between patients with schizophrenia and healthy individuals. The findings suggest that diet may play a role in metabolic health and cognitive functioning, particularly in clinical populations. Full article

Background: Language impairment is a core feature of Major Neurocognitive Disorder (MND), yet the domain-specific relationship between language functioning and everyday functional status remains insufficiently characterized. Methods: We conducted a retrospective observational study in 125 older adults diagnosed with MND according to DSM-5 criteria with mild-to-moderate cognitive impairment measured with Mini-Mental State Examination (MMSE). Language performance was assessed using semantic, phonemic verbal fluency and confrontation naming. Functional status was evaluated using basic (BADL) and instrumental activities of daily living (IADL). Ordinal logistic regression models examined associations between language domains and functional outcomes, adjusting for global cognitive status (MMSE), demographic variables, multimorbidity, and depressive symptoms. Model fit was evaluated using the Akaike Information Criterion. Results: Semantic fluency emerged as the best-performing predictor of BADL across all hierarchical models, remaining statistically significant after full adjustment for MMSE and clinical covariates (β ≈ 0.60, p < 0.05). Phonemic fluency showed the most robust association with IADL, with a stable effect across models, reaching a trend toward statistical significance in the fully adjusted analyses (β ≈ 0.22–0.27, p = 0.069). Naming ability did not influence functional outcomes. All observed associations persisted after controlling for MMSE, demographic variables, multimorbidity, and depressive symptoms. Conclusions: Language abilities showed differential associations across language domains with functional status in this sample of patients with MND. Semantic fluency was associated with basic self-care, while phonemic fluency showed a trend toward association with instrumental daily activities. These relationships remained observable after adjustment for global cognitive impairment, suggesting verbal fluency as a potentially sensitive marker of functional vulnerability. Full article

Vagus nerve stimulation (VNS) may improve cognition and promote underlying brain health through various mechanisms including the noradrenaline and cholinergic pathways. Whilst early human studies used invasive devices (iVNS), recent decades have seen the emergence of non-invasive devices that stimulate the vagus nerve transcutaneously (tVNS) via either the cervical branches in the neck (tcVNS) or the auricular branch in the ear (taVNS). With this increase in more accessible devices, tVNS is gaining interest as a novel therapy in mild cognitive impairment (MCI) and Alzheimer’s disease (AD). This targeted review aims to understand the current evidence in human trials in this specific population. PubMed, Cochrane, EMBASE, MEDLINE, and Google Scholar were searched. Six human interventional studies were found (one iVNS; five taVNS). VNS is well tolerated and study designs demonstrate feasibility within this population for future blinded and appropriately powered long-term studies with participants applying tVNS at home. However, protocols and tVNS settings remain variable. Working memory domains such as verbal fluency and 3D processing show the most promise but global cognitive scores were also sensitive in some cases. The role of biomarkers of tVNS activity and its effect on AD markers and neuroinflammation should be considered in the design of future studies. Full article

Alzheimer’s disease (AD), the most common cause of dementia, is characterized by progressive memory and cognitive decline. Conventional genome-wide association studies (GWAS) comparing AD cases and controls may miss genetic influences that act along a continuum of cognitive function. Using data from 3007 participants in the National Institute on Aging Late-Onset Alzheimer’s Disease Family Study (NIA-LOAD GWAS), we conducted a family-based GWAS of eight quantitative cognitive phenotypes encompassing episodic memory (Logical Memory IA and IIA), working memory (Digit Span Forward, Backward, and Ordering), and semantic fluency (Animal, Fruit and Vegetable, and Vegetable Fluency). Family-based association testing in PLINK v1.9 identified numerous single nucleotide polymorphisms (SNPs) associated with cognitive phenotypes at genome-wide significant (p < 5 × 10⁻⁸) levels. Notably, genome-wide significant variants with cognatic functions were localized to genes implicated in synaptic function, neurodevelopment, and neurodegeneration, including TOMM40 (rs2075650), ERBB4 (rs1521543), APLP2 (rs12281267, rs959354), PTPRD (rs1353983, rs970347, rs1392511), NCAM2 (rs2826728), GRM7 (rs6788201), PAX5 (rs2988003, rs2381595), NRG1 (rs16875655), and NRG3 (rs1937957). Furthermore, the TOMM40 (rs2075650) was significantly associated with AD as a binary outcome (p = 4.60 × 10⁻²⁴) and APLP2 (rs12281267, rs959354), APOE (rs405509), PTPRD (rs1353983, rs970347, rs1392511) were associated with AD (p < 0.001). Additionally, several pathways including the ERBB4 signaling pathway (adjusted p = 2.82 × 10⁻³), driven by ERBB4, NRG1, and NRG3 may contribute to cognitive impairments. This study provides a comprehensive resource of cognitive endophenotype associations in AD families, advancing understanding of the genetic architecture underlying memory, executive function, and cognitive aging, and highlights new therapeutic targets for replication and functional follow-up. Full article

This paper argues that the most significant challenge artificial intelligence poses to theological anthropology is not ontological but epistemic. Rather than asking whether machines can think, feel, or bear the image of God, this paper redirects attention to the prior question of what happens to the human when core epistemic capacities, judgment, discernment, interpretive authority, and moral reasoning are progressively delegated to computational systems. Drawing on the concept of epistemic automation, understood as the systematic transfer of knowledge-producing functions from human agents to algorithmic processes, this paper develops a threefold analytical framework. First, it distinguishes epistemic authority from ontological status as the more productive locus for theological anthropological inquiry. Second, it introduces the distinction between fluency and understanding as an anthropological boundary condition that AI renders newly visible. Third, it analyses delegated cognition as a form of agency deformation with theological significance. The paper concludes that theological anthropology must move beyond reactive commentary on AI and instead generate a theory of the human under conditions of epistemic transformation. The argument engages constructively with philosophy of technology, social epistemology, and Christian theological traditions to offer a framework applicable across confessional boundaries. Full article

The identification of gifted students with learning disabilities (GLD) remains theoretically and methodologically contested. The present study examined cognitive and reading profiles of 150 Greek students in Grades 4–6, classified as gifted with learning disabilities (GLD) (n = 36), gifted (n = 31), or dyslexic of average intellectual ability (n = 83). Gifted classification was based on National Association for Gifted Children guidelines issued in 2018, using reasoning-based WISC-VIndices (FSIQ, GAI, EGAI, NVI, VECI ≥ 120), while learning disability was determined through formal multidisciplinary diagnosis. Cognitive performance was assessed with the WISC-V and reading with the standardized DADA battery (decoding, fluency, and comprehension). One-way ANOVAs and ROC analyses were conducted. GLD students demonstrated reasoning abilities and processing speed abilities comparable to gifted peers, but working memory deficits compared to gifted peers. In reading, GLD students showed decoding deficits like dyslexic peers and fluency impairments indistinguishable from them, yet significantly stronger comprehension. These findings reveal a differentiated literacy profile in which higher-order reasoning appears to support meaning construction despite persistent efficiency-based constraints in decoding and fluency. Overall, the results indicate that twice-exceptionality reflects a structurally uneven cognitive–academic configuration, underscoring the importance of multidimensional assessment approaches that simultaneously evaluate reasoning strengths and reading-specific vulnerabilities. Full article

Background/Objectives: Cognitive impairment is a major concern in aging populations. Early detection through validated neuropsychological tests is essential for dementia risk stratification and preventive interventions. This scoping review (PRISMA-ScR, 2013–2023, registration protocol: 10.17605/OSF.IO/8NHJF) evaluated cognitive testing trends in aging research and identified the most frequently used neuropsychological screening tests in Spanish populations. Methods: Searches in PubMed and Web of Science (March 2024) yielded 730 records; 156 were reviewed in full, and 15 met inclusion criteria for Spanish adults ≥65 years. Results: The Mini-Mental State Examination was the most-used test, followed by verbal fluency and Trail Making Test. No test covered all six DSM-5 cognitive domains, and social cognition was never assessed in any of the studies. The Montreal Cognitive Assessment was underused despite its superior sensitivity. Conclusions: Findings support developing a tailored, multidomain battery combining global and domain-specific tests. Social cognition assessments should be included to ensure a complete cognitive domain coverage. Full article

Mathematics is a diverse discipline that requires a variety of cognitive abilities and presents varying levels of difficulty. Understanding how different cognitive profiles relate to specific patterns of mathematical performance is important for developing effective educational interventions. This study extends our previous research, in which we identified subgroups of children with mathematical difficulties based on their cognitive abilities. We examined 146 Israeli elementary school children in grades 3 and 4, classified into four subgroups: Reading Accuracy Difficulties (RAD), Mild Mathematical Difficulties (MMD), Non-Verbal Reasoning Difficulties (NVRD), and Typically Developing children (TD). Participants were assessed on arithmetic facts, computational fluency, procedural skills, estimation, and numeration. We observed varied performance patterns among subgroups. The RAD group showed the most severe impairments across all mathematical domains, along with reading comorbidity and cognitive difficulties. The MMD group, which maintained intact cognitive skills, faced notable challenges in computation, performing significantly below the TD group but better than the RAD group. The NVRD group, despite limitations in nonverbal reasoning, outperformed other difficulty groups on fact retrieval and estimation. Performance on multiplication and division tasks consistently followed a hierarchical pattern across all difficulty groups, with the RAD group facing the greatest challenges. These findings demonstrate that mathematical difficulties vary across cognitive profiles and that distinguishing between profiles through targeted assessment enables the development of differentiated interventions tailored to each learner’s specific cognitive profile. Full article

Singing-Oriented Language and Music Education (SOLME) is an accessible, low-resource pedagogical and cognitive framework in which singing serves as the primary interface through which musical activities support both first and foreign language acquisition processes. Early vocalizations in infancy make the overlap between singing and speech highly perceptible, forming a continuum rather than clearly separable domains. Child-directed speech similarly shares key features with singing—such as repetition, emotional engagement, exaggerated pitch variation and rhythm—and both input forms inherently combine musical and linguistic elements. Research has shown that the overlap between singing and language abilities persists throughout the lifespan, positioning singing as a valuable facilitator of language learning processes. Singing, integrated as a musical tool, has proven effective in enhancing key abilities for (foreign) language learning—including phonological awareness, pronunciation, and verbal memory, among others—and in supporting language functioning across diverse communication disorders, from developmental fluency challenges to acquired impairments. This entry outlines the benefits of singing as an integrated means to support musical development as well as first and second language acquisition processes. It outlines functional and structural similarities between singing and language development, from early caregiver–infant interaction to formal foreign-language instruction, and then discusses the many advantages of embedding singing as a musical tool in the (foreign) language learning process. Full article

Background/Objectives: Stuttering is a neurodevelopmental disorder of speech fluency. It emerges most commonly between 2 and 5 years old, often causing social exclusion and stigma. In Latin America, cultural misconceptions regarding its causes exacerbate these psychosocial challenges. This study validated a culturally adapted instrument for Chile to measure public attitudes toward stuttering. The instrument provides a psychometrically sound method to assess and address stigma within educational and community settings. Methods: A total of 756 Chilean adults (mean age = 36.7 years, SD = 15.8; 64% women, 36% men) were recruited using stratified probability sampling to reflect the national demographics. Ethical approval and informed consent were obtained. The subsection underwent rigorous cross-cultural adaptation (translation, expert review, cognitive debriefing n = 30, pre-testing n = 50). Analysis employed polychoric matrices, EFA, CFA with WLSMV, and multiple reliability/validity indices. Results: Joint analysis showed poor fit (CFI = 0.72, RMSEA = 0.12), confirming independence. Beliefs (14 items): three-factor CFA fit excellent (CFI = 0.993, RMSEA = 0.034); factors: competence/normality (α = 0.85), psychological causes (α = 0.78), and help/support (α = 0.72). Reactions (11 items): four-factor fit adequate (CFI = 0.97, RMSEA = 0.043); factors: distant concern (α = 0.82), personal concern (α = 0.79), media sources (α = 0.75), and formal sources (α = 0.77). Validity was supported; bifactor models favored multidimensionality. Conclusions: The adapted subsection is psychometrically robust and effectively captures Chilean-specific attitudes toward childhood stuttering. It provides a reliable tool for quantifying public stigma and misconceptions, particularly in educational and school contexts, thereby supporting the design of targeted school-based policies and interventions to reduce bullying, promote inclusion, and safeguard the psychosocial well-being of children and adolescents who stutter. Full article

Detecting unnatural pauses is a critical component of automated quality assessment (AQA) in interpreter training, as pause patterns directly reflect an interpreter’s cognitive load and fluency. Traditional pause detection methods rely on static temporal thresholds (e.g., 1.0 s), which often fail to account for segment-specific speech rate variability and individual speaking styles. This study proposes a context-adaptive pause detection framework that integrates unsupervised anomaly detection using Isolation Forest (iForest) with a sliding window technique. To enhance pedagogical validity, we specifically focused on intra-sentential pauses by delineating sentence boundaries using a specialized segmentation model. The proposed model was evaluated against ground-truth labels annotated by professional interpreting experts. Our results demonstrate that the sliding window–based contextual anomaly detection model significantly outperforms the conventional static baseline, particularly in terms of recall and Cohen’s kappa. Furthermore, by applying a weighted F3-score and the “Recognition-over-Recall” principle, we confirmed that the proposed model substantially reduces the instructor’s total operational burden by shifting the workload from de novo annotation creation to more efficient corrective pruning. These findings suggest that speech-adaptive modeling provides a more reliable and labor-saving framework for automated interpreting assessment and feedback. Specifically, this study makes three main contributions: (1) the proposal of a context-adaptive pause detection framework using anomaly detection, (2) the integration of sliding window–based local contextual modeling for speech-rate–aware analysis, and (3) the introduction of an evaluation strategy based on the Recognition-over-Recall principle to reduce instructor workload in interpreter training. Full article

Executive function (EF) impairments are common in children with intellectual and developmental disabilities and have a significant impact on learning and daily life. Cognitive training programs aimed at strengthening EFs may show limited feasibility and generalization. However, recent studies suggest that ecological, curriculum-embedded problem-solving activities may be more promising. This multiple-baseline single-case study tested the feasibility and efficacy of a short computational thinking and coding intervention based on problem-solving for children with sickle cell disease, a hemoglobinopathy associated with cognitive decline and EF deficits. The trial followed the What Works Clearinghouse (WWC) Version 5 guidelines for single-case research. Three 7–8-year-old children with lower-range IQ (71–82) and EF impairments completed 11 coding sessions over 5–6 weeks using code.org, with pre/post assessments of non-verbal EF (planning, inhibition, and switching), and verbal EF skills (verbal working memory, phonological fluency and semantic fluency). Results showed 100% adherence to the intervention, significant improvement in coding (IRD range = 0.69–0.79), with positive transfer effects on nonverbal planning skills (gains > 2 z-scores) and also verbal fluency (z-score gains ranging from 0.47 to 1.04). Inter-individual variability in effects was related to the child’s individual cognitive profile. Findings suggest that problem-solving, coding-based activities can be feasible and potentially beneficial for children with significant EF impairments. Full article

Human–robot interaction (HRI) takes place in dynamic environments where both humans and robots act as active agents, making the system inherently unpredictable. Abrupt movements can originate from either side and include human reflexes, fatigue, or unexpected reactions, as well as robot malfunctions, control errors, or task changes. These unpredictable events generate significant risks for both interaction fluency and safety, affecting not only the physical domain (e.g., collisions, excessive forces) but also cognitive aspects such as trust and predictability. Although different application areas present domain-specific challenges, a comprehensive overview of abrupt movements in HRI is still lacking, especially in the industrial scenario. This review aims to consolidate current knowledge regarding how abrupt phenomena are analyzed, prevented, and mitigated across various contexts and to offer new insights for researchers. In detail, after describing the literature search and the screening process, the review categorizes abrupt events, highlights key methodological approaches, and identifies gaps and future directions. By providing a structured synthesis of existing strategies, this work guides researchers in developing safer and more adaptive HRI frameworks capable of handling unpredictability. Full article

Background/Objectives: As life expectancy increases, chronic diseases have become more prevalent, often leading to poorer health in later years. Maintaining cognitive functioning is therefore essential for preserving independence in older adulthood. Within the framework of cognitive enrichment, research highlights the protective role of healthy lifestyles and engagement in social and intellectual activities on cognitive functioning. This study aimed to provide evidence of the moderator effect of diagnosis group (including healthy condition, dementia, Parkinson’s, and stroke) on a predictive model of cognitive function. Methods: Data employed in this study came from the 9th wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) project, including 17,105 individuals aged 50 years and older from 27 European countries. Cognitive functioning was assessed through numeracy, temporal orientation, verbal fluency, and memory. Physical inactivity, social participation, intellectual activities, age, gender, and education were included as predictors. A measurement invariance routine across diagnostic groups was tested. Results: The model demonstrated excellent fit in the general sample and partial invariance across groups. Physical inactivity was negatively associated with numeracy in all groups, with stronger effects in clinical populations, particularly stroke and dementia. Intellectual activities were positively associated with numeracy across groups, with the largest effects observed in dementia. Temporal orientation, physical inactivity and intellectual activities showed significant associations mainly in clinical groups, whereas age demonstrated a consistent negative effect across all groups. Conclusions: Lifestyle factors show differential associations with cognitive domains depending on diagnostic condition. These findings support the heterogeneity of cognitive aging and highlight the importance of tailored, person-centered intervention strategies. Full article

The rapid adoption of generative artificial intelligence tools such as ChatGPT in educational settings has generated both enthusiasm and concern regarding their influence on student learning. While several studies report improvements in efficiency, confidence, and perceived understanding, evidence for durable conceptual learning and knowledge transfer remains mixed. This article examines these tensions through the concept of fluency illusion, a cognitive phenomenon in which information that is easy to process is mistakenly judged as being well understood. Using a narrative conceptual review approach, this study synthesizes findings from 41 publications identified through searches of Google Scholar, Scopus, Web of Science, and ERIC covering the period from 2022 to early 2026. The reviewed literature includes 28 empirical studies, nine conceptual or theoretical analyses, and four review articles addressing the use of ChatGPT in educational contexts. Across domains such as writing and language learning, STEM problem solving, feedback and tutoring, and assessment, the literature shows a recurring pattern in which fluent AI-generated responses increase learners’ confidence without consistently improving deeper conceptual understanding. Drawing on research from cognitive psychology and metacognition, this review proposes an integrative conceptual account of how fluent AI output may shape learners’ judgments of understanding and influence their engagement with learning tasks. The paper concludes by discussing implications for instructional design, assessment practices, and metacognitive scaffolding, and outlines directions for future research aimed at empirically examining the proposed framework and identifying strategies to reduce fluency-driven misjudgments while preserving the potential benefits of generative AI in education. Full article