Search Results (231)

Background/Objectives: While artificial intelligence (AI) is rapidly transforming education, its specific effectiveness for students with learning disabilities (LD) requires rigorous evaluation. This systematic review aims to assess the efficacy of AI-based educational interventions for students with LD, with a specific focus on the methodological quality and risk of bias of the available evidence. Methods: A systematic search was conducted across seven major databases (Google Scholar, ScienceDirect, APA PsycInfo, ERIC, Scopus, PubMed) for experimental studies published between 2022 and 2025. This review followed PRISMA guidelines, using the PICOS framework for inclusion criteria. A formal risk of bias assessment was performed using the ROBINS-I and JBI critical appraisal tools. Results: Eleven studies (representing 10 independent experiments), encompassing 3033 participants, met the inclusion criteria. The most studied disabilities were dyslexia (six studies) and other specific learning disorders (three studies). Personalized/adaptive learning systems and game-based learning were the most common AI interventions. All 11 studies reported positive outcomes. However, the risk of bias assessment revealed significant methodological limitations: no studies were rated as having a low risk of bias, with most presenting a moderate (70%) to high/serious (30%) risk. Despite these limitations, quantitative results from the stronger studies showed large effect sizes, such as in arithmetic fluency (d = 1.63) and reading comprehension (d = −1.66). Conclusions: AI-based interventions demonstrate significant potential for supporting students with learning disabilities, with unanimously positive reported outcomes. However, this conclusion must be tempered by the considerable risk of bias and methodological weaknesses prevalent in the current literature. The limited and potentially biased evidence base warrants cautious interpretation. Future research must prioritize high-quality randomized controlled trials (RCTs) and longitudinal assessments to establish a definitive evidence base and investigate long-term effects, including the risk of cognitive offloading. Full article

Background/Objectives: The use of digital technologies among children and adolescents has been increasing exponentially, raising concerns about the potential impacts on physical, mental, cognitive, educational, and social development. Understanding these effects is key to informing clinical and educational practices and public policies that promote digital wellbeing in childhood and adolescence. The main objective of this study was to map the latest available scientific evidence on the patterns of digital technology use by children and adolescents and its main impact, identifying risk factors, opportunities, and strategies for promoting digital wellbeing. Methods: A rapid review was carried out following the Joanna Briggs Institute (JBI) guidelines. Quantitative, qualitative, and mixed studies published between 2020 and 2025, in Portuguese or English, that addressed the use of digital technologies by children and adolescents were included. The assessment of methodological quality was based on JBI’s Critical Appraisal Tools. Results: Ten studies from diverse contexts showed an association between excessive screen time and risks of sedentary lifestyles, sleep disorders, anxiety, depression, attention difficulties, and low academic performance. Occasional benefits arose with adult mediation and educational use; parental mediation and socioeconomic background were key factors. Conclusions: The use of digital technologies is a complex and multifactorial phenomenon that requires integrated approaches; the promotion of digital literacy, public policies for equitable access to quality digital resources, and longitudinal and intercultural studies are recommended to clarify causal relationships and adapt interventions to local contexts. Full article

Background: Depression is a mental disorder characterized by a combination of somatic and cognitive disturbances, in which a predominantly sad or irritable mood significantly interferes with the patient’s functioning. This condition can affect individuals of all ages and socioeconomic backgrounds. Currently, various studies are exploring a possible association between oral dysbiosis and depression—an increasingly relevant topic, as confirmation of such a relationship could position the oral microbiota as a potential etiological or diagnostic factor for depression, given its accessibility and ease of analysis. Aim: To present a qualitative synthesis of studies addressing how oral dysbiosis influences the onset of depression, as well as the importance of controlling this alteration of the oral microbiota to aid in the prevention of the disease. Materials and Methods: The PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) outline the procedures to be followed for conducting this systematic review. The article search was carried out on 22 May 2025, across the PubMed, Scopus, Scielo, and The Cochrane Library databases, using terms related to “depression” and “oral dysbiosis”. Studies published within the last 10 years that addressed the potential association between oral dysbiosis, and depression were included. Furthermore, the quality of the studies was assessed using various tools depending on their design: the Newcastle–Ottawa Scale (NOS) was applied to case-control and cohort studies; the Joanna Briggs Institute (JBI) critical appraisal checklist was used for cross-sectional studies; and experimental studies were evaluated using SYRCLE’s Risk of Bias Tool. Results: A total of eleven studies were included in this systematic review. The findings suggest the presence of alterations in the oral microbiota of patients with depression, particularly in terms of composition, structure, and diversity. A reduction in alpha diversity—an indicator of local microbial balance—was observed, along with an increase in beta diversity, indicating greater inter-individual variability, which may be associated with inflammatory processes or immunological dysfunctions. Some studies reported differing results, which may be attributable to methodological variability regarding study design, or the populations sampled. Conclusions: This systematic review suggests that the oral microbiome could be considered a diagnostic biomarker and therapeutic target for depression, as the analyzed studies demonstrate a significant association between oral microbiome dysbiosis and this mental disorder. However, the methodological heterogeneity among the studies highlights the need for further research to confirm this potential relationship. Full article

Introduction: Huntington’s disease (HD) disrupts cortico-striato-thalamocortical circuits decades before clinical onset. Electroencephalography (EEG) offers millisecond temporal resolution, low cost, and broad accessibility, yet its mechanistic and biomarker potential in HD remains underexplored. We conducted a mechanistic review to synthesize half a century of EEG findings, identify reproducible electrophysiological signatures, and outline translational next steps. Methods: Two independent reviewers searched PubMed, Scopus, Google Scholar, ResearchGate, and the Cochrane Library (January 1970–April 2025) using the terms “EEG” OR “electroencephalography” AND “Huntington’s disease”. Clinical trials published in English that reported raw EEG (not ERP-only) in human HD gene carriers were eligible. Abstract/title screening, full-text appraisal, and cross-reference mining yielded 22 studies (~700 HD recordings, ~600 controls). We extracted sample characteristics, acquisition protocols, spectral/connectivity metrics, and neuroclinical correlations. Results: Across diverse platforms, a consistent spectral trajectory emerged: (i) presymptomatic carriers show a focal 7–9 Hz (low-alpha) power loss that scales with CAG repeat length; (ii) early-manifest patients exhibit widespread alpha attenuation, delta–theta excess, and a flattened anterior-posterior gradient; (iii) advanced disease is characterized by global slow-wave dominance and low-voltage tracings. Source-resolved studies reveal early alpha hypocoherence and progressive delta/high-beta hypersynchrony, microstate shifts (A/B ↑, C/D ↓), and rising omega complexity. These electrophysiological changes correlate with motor burden, cognitive slowing, sleep fragmentation, and neurovascular uncoupling, and achieve 80–90% diagnostic accuracy in shallow machine-learning pipelines. Conclusions: EEG offers a coherent, stage-sensitive window on HD pathophysiology—from early thalamocortical disinhibition to late network fragmentation—and fulfills key biomarker criteria. Translation now depends on large, longitudinal, multi-center cohorts with harmonized high-density protocols, rigorous artifact control, and linkage to clinical milestones. Such infrastructure will enable the qualification of alpha-band restoration, delta-band hypersynchrony, and neurovascular coupling as pharmacodynamic readouts, fostering precision monitoring and network-targeted therapy in Huntington’s disease. Full article

Background. Cognitive-behavioral theories suggest that obsessions in obsessive-compulsive disorder (OCD) develop from maladaptive misinterpretations and coping strategies of unwanted intrusive thoughts (UITs). Models of Body Dysmorphic Disorder (BDD) and Illness Anxiety Disorder (IAD) propose that these symptoms stem from similar misinterpretations of common UITs relating to perceived defects in appearance and illness. This study examines whether maladaptive misinterpretations and control strategies leading to the escalation of obsessional UITs to OCD symptoms also have a similar effect on the development of BDD and IAD. More specifically, we examined whether misinterpretations and neutralizing responses mediate the associations between the frequency of disorder-specific UITs and symptoms of these disorders. Method. A total of 625 non-clinical participants from four countries completed the Questionnaire of Unpleasant Intrusive Thoughts (QUIT) that assesses OCD, BDD and IAD-related UITs and their associated misinterpretations and neutralizing strategies, as well as self-report measures of OCD, BDD, and IAD symptoms. Parallel multiple mediation models were conducted. Results. The frequency of OCD, BDD and IAD-related UITs predicted symptoms of each disorder. Dysfunctional appraisals and neutralizing behaviors mediated the associations between disorder-specific UITs and symptoms in OCD and IAD. The IAD model accounted for a smaller proportion of variance than the OCD model. No mediating effects were found for BDD symptoms. Conclusions. Experiencing disturbing UITs is a transdiagnostic risk factor of OCD, BDD and IAD, and is associated with symptoms of these disorders. Maladaptive interpretation of UITs and neutralizing strategies should be specific targets in the assessment and treatment of OCD and IAD. The absence of mediation effects for BDD could be due to the limitations observed on the self-report used to assess BDD symptoms and/or the low relevance of the misinterpretations and control strategies assessed by the QUIT, which are more typically endorsed by individuals with OCD. Full article

As digital technology evolves rapidly, smart tourism has become a significant trend in the modernization of the industry, relying on advanced tools like big data and cloud computing to improve travelers’ experiences. Despite the growing use of human–computer interaction in museums, there remains a lack of in-depth academic investigation into its impact on visitors’ behavioral intentions regarding museum engagement. This paper employs Cognitive Appraisal Theory, considers human–computer interaction experience as the independent variable, and introduces destination image and satisfaction as mediators to examine their impact on destination loyalty. Based on a survey of 537 participants, the research shows that human–computer interaction experience has a significant positive impact on destination image, satisfaction, and loyalty. Destination image and satisfaction play a partial and sequential mediating role in this relationship. This paper explores the influence mechanism of human–computer interaction experience on destination loyalty and proposes practical interactive solutions for museums, aiming to offer insights for smart tourism research and practice. Full article

Background/Objectives: In contemporary nursing education, clinical competence and psychological resilience are both essential; however, they are often treated as separate outcomes. Clinical placements are a central component of nursing education, and often expose students to high levels of stress, emotional challenges, and complex clinical demands. Building both clinical competence and psychological resilience during this phase is crucial to preparing students for the realities of professional practice. This narrative review, grounded in Bandura’s social cognitive theory (SCT), explores how educator behaviors, teaching strategies, and learning environments interact to influence both domains in undergraduate nursing students. Methods: A comprehensive search was conducted in PubMed, CINAHL, and PsycINFO for peer-reviewed articles published between 1 January 2000 and 2 May 2025. Relevant studies were thematically analyzed and were guided by Bandura’s SCT constructs, including observational learning, self-efficacy, and reciprocal determinism. No formal study appraisal was conducted due to the narrative nature of the review. Findings: Nineteen studies were included in the review. The findings highlight that reflective practices, structured feedback, peer learning, and strategies to build self-efficacy are central to building resilience and competence. Supportive educator behaviors such as mentoring, emotional support, and professional role modeling, were strongly associated with increased student confidence, emotional regulation, and adaptability. Psychologically safe clinical learning environments further enhanced self-efficacy and active engagement. In contrast, unsupportive or inconsistent environments were linked to student stress, disengagement, and reduced performance. Conclusions: This review highlights the need to move beyond traditional competency-based models toward an integrated approach that equally values psychological preparedness and resilience. Findings suggest a shift toward emotionally and socially integrated clinical education. Full article

This study examines how employees perceive technology-based demands during the digital transformation process and how these perceptions affect job performance. The research utilized data obtained from 388 experts in the accounting and financial reporting profession, a knowledge-intensive field that heavily employs new technologies (e.g., ERP systems, digital audit tools). The data collected through a convenience sampling method was analyzed using SPSS 27 and SmartPLS 4 software. The findings reveal that the direct effect of technostress on job performance is not significant; however, this stress indirectly contributes to performance through techno-eustress. In this study, techno-eustress refers to the cognitive appraisal of technology-related demands as development-enhancing challenges rather than threats. This concept is theoretically grounded in the broader eustress framework, which views stressors as potentially motivating and growth-promoting when positively interpreted. The model is based on Cognitive Evaluation Theory, the Job Demands–Resources Model, and Self-Determination Theory. This study demonstrates that digital transformation can promote not only operational improvements but also organizational resilience by enhancing employees’ psychological resources and adaptive capacities. By highlighting the mediating role of techno-eustress, this research offers a nuanced perspective on how human-centered cognitive mechanisms can strategically support performance and sustainability in the face of technological disruption—an increasingly relevant area for organizations striving to thrive amid uncertainty. Full article

Amid AI-driven organizational transformation, employees’ subjective evaluations of AI technologies—referred to as AI awareness—have become a critical psychological factor influencing innovation behavior. This study aims to uncover how AI awareness affects employee innovation performance through behavioral pathways and examines the moderating role of individual achievement motivation in this process. Grounded in Cognitive Appraisal Theory and the Dual Pathway Model, we construct a dual-path mediation model, in which proactive and withdrawal behaviors act as mediators, and achievement motivation serves as a boundary condition. Based on a two-wave survey of 413 knowledge workers in China’s high-tech sector, the proposed model was empirically tested using moderated mediation analysis (PROCESS macro). The results reveal that AI awareness has a significant dual-path effect on innovation behavior: on the one hand, it promotes innovation by stimulating proactive behavior; on the other hand, it may suppress innovation by inducing withdrawal behavior. Moreover, achievement motivation plays a crucial moderating role in this mechanism by strengthening the positive mediating effect of proactive behavior and weakening the negative mediating effect of withdrawal behavior. This study conceptualizes AI awareness as a psychological input encompassing both perceived opportunity and perceived threat, clarifies the behavioral response mechanisms of employees facing AI, and highlights the boundary-regulating role of individual motivation in organizational adaptability. Practically, the study suggests designing differentiated HR interventions based on employees’ cognitive appraisals and motivational profiles to enhance human–AI collaboration, foster innovation resilience, and improve organizational adaptability amid digital transformation. Full article

Background: The onset and persistence of Long COVID can lead to cognitive and functional impairment, contributing to illness-induced employment and work disparities. Understanding how social support influences these issues can inform care strategies and support continued workforce participation. Objectives: This study explored perceptions of social support among patients with Long COVID. Methods: Semi-structured interviews were conducted with 21 patients receiving care at a post-COVID recovery clinic. Patient perspectives on social support in their work and personal lives were analyzed using both inductive and deductive thematic analysis. Findings were organized under the following five dimensions of social support theory: tangible support, emotional support, informational support, appraisal support, and belonging support. Results: Patients received positive tangible, emotional, and informational support from family, friends, and credible sources. However, patients also described receiving negative appraisal support from their personal lives and workplaces when others misunderstood the scope and duration of their limitations due to Long COVID. This negative appraisal support often labeled them as lazy or underperforming, leading to both personal and professional challenges to their self-esteem. Regarding companionship support, participants reported challenges keeping in touch with others and being less social. Conclusions: Social support impacts Long COVID patients’ abilities to cope with the trauma of their experiences. Understanding the sources of and barriers to social support for Long COVID patients may inform strategies to enhance their care and well-being. Future interventions should offer opportunities for family, friends, and employers of Long COVID patients to learn about what it means to live with the illness. Full article

Background/Objectives: Borderline personality disorder (BPD) is a complex psychiatric condition marked by emotional dysregulation, interpersonal instability, and impulsivity. Despite the advances in psychotherapy and pharmacotherapy, many patients show a partial or unstable response. Recent research suggests that oxytocin, a neuropeptide involved in social cognition and emotional regulation, may offer novel therapeutic avenues. Methods: We systematically synthesize evidence from PubMed, PsycINFO, Web of Science, and Google Scholar on oxytocin’s role in BPD, prioritizing studies on neurobiology, emotion regulation, clinical interventions, and adjunctive therapy models. Thirty studies were included and critically appraised using PRISMA and Cochrane’s tools. Due to methodological heterogeneity, no meta-analysis was conducted; instead, the findings were integrated through a narrative synthesis approach. Results: Evidence supports oxytocin’s modulatory effects on amygdala reactivity, prefrontal–limbic connectivity, and hypothalamic–pituitary–adrenal axis function. Intranasal oxytocin appears beneficial for emotional regulation and interpersonal sensitivity, particularly in individuals with early trauma. The reported effect sizes ranged from small (Cohen’s d ≈ 0.40) to large (d ≈ 0.83), though some trials reported null or adverse effects, such as increased hypermentalization. Heterogeneous responses were influenced by factors such as sex, trauma history, and OXTR gene variants. Conclusions: Although intranasal oxytocin shows promise in modulating core neurobiological systems implicated in BPD and enhancing emotion regulation and social cognition, its clinical effects remain variable and context-dependent. The evidence supports cautious exploration of oxytocin as an adjunct to psychotherapeutic interventions rather than as a standalone treatment. Future research should focus on biomarker-informed, stratified trials that account for trauma history, genetic variation, and sex differences to clarify its therapeutic potential. Full article

Background and Objectives: Adolescence is a critical yet vulnerable developmental stage, characterized by increased exposure to stressful life events (SLEs), which are strongly linked to the onset and progression of depression. Although mindfulness has been consistently associated with lower depressive symptoms, the mechanisms underlying this relationship—particularly in adolescents—remain underexplored. Prior research suggests that mindfulness operates through cognitive mechanisms, such as reduced rumination, enhanced emotional regulation, and greater cognitive flexibility. However, much of this work is cross-sectional, limiting causal interpretation and often overlooking distinctions between direct and indirect effects. This study aimed to clarify two proposed pathways through which trait mindfulness may reduce depressive symptoms in adolescents: (1) a direct pathway involving core cognitive–emotional processes, and (2) an indirect pathway, where mindfulness supports more adaptive stress appraisal. A secondary objective was to assess whether these indirect effects vary across different types of stressful life events. Materials and Methods: We analyzed longitudinal data from 3897 adolescents (M_age = 15.9; 51.2% female) across four waves spaced approximately six months apart. Structural equation modeling (AMOS) was used to evaluate both direct and indirect effects of trait mindfulness on depression, with stress domains included in separate analyses. Results: Trait mindfulness was strongly negatively correlated with depression (r = –0.39 to –0.56). The direct effect of mindfulness on depression was substantial (β = –0.60 to –0.74), while indirect effects via cognitive reappraisal were smaller (β = –0.10 to –0.26 for stress reduction; up to –0.17 for depression). Indirect effects varied across stress domains and were generally modest. Conclusions: Mindfulness appears to reduce adolescent depressive symptoms through both direct and indirect pathways. The more pronounced direct effect likely reflects underlying mechanisms, such as reduced rumination and enhanced emotional regulation. Although weaker, the indirect pathway—mediated by more adaptive stress appraisal—adds meaningful explanatory value. Together, these findings underscore mindfulness as a key protective factor and highlight its potential for informing targeted, resilience-based interventions in adolescent mental health. Full article

Iodine deficiency remains one of the most serious global public health challenges, recognised as the leading cause of preventable brain damage worldwide. It is widely accepted as the primary aetiological factor underlying iodine deficiency disorders (IDD). Inadequate maternal iodine intake reduces thyroxine synthesis, impairing foetal brain development and leading to long-term deficits in cognitive function across childhood and adulthood. However, emerging evidence also suggests that excessive iodine intake may disrupt thyroid function, particularly in individuals with underlying thyroid autoimmunity, potentially leading to adverse neurodevelopmental outcomes. In this state-of-the-art review, we examine the effects of iodine nutrition during pregnancy and lactation on child cognitive outcomes. We provide an overview of the recent global iodine status, critically appraise the current evidence linking both iodine deficiency and excess to neurodevelopmental outcomes, and offer expert interpretation of the key findings. We further highlight areas of uncertainty, introduce emerging evidence from contemporary studies, and propose directions for future research to inform and optimise public health policies and clinical practice. Our findings highlight a U-shaped association, whereby both insufficient and excessive iodine exposure during pregnancy and lactation may impair optimal brain development in the offspring. Full article

Background: The increasing prevalence of dementia and mild cognitive impairment (MCI) among the elderly population is a global health issue. Information and Communication Technology (ICT)-based interventions hold promises for maintaining cognition, but their viability is affected by several challenges. Objectives: This study aimed to significantly assess the effectiveness of ICT-based cognitive and memory aid technology for individuals with MCI or dementia, identify adoption drivers, and develop an implementation model to inform practice. Methods: A PRISMA-based systematic literature review, with the protocol registered in PROSPERO (CRD420251051515), was conducted using seven electronic databases published between January 2015 and January 2025 following the PECOS framework. Random effects models were used for meta-analysis, and risk of bias was assessed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklists. Results: A total of ten forms of ICT interventions that had proved effective to support older adults with MCI and dementia. Barriers to adoption included digital literacy differences, usability issues, privacy concerns, and the lack of caregiver support. Facilitators were individualized design, caregiver involvement, and culturally appropriate implementation. ICT-based interventions showed moderate improvements in cognitive outcomes (pooled Cohen’s d = 0.49, 95% CI: 0.14–1.03). A sensitivity analysis excluding high-risk studies yielded a comparable effect size (Cohen’s d = 0.50), indicating robust findings. However, trim-and-fill analysis suggested a slightly reduced corrected effect (Cohen’s d = 0.39, 95% CI: 0.28–0.49), reflecting potential small-study bias. Heterogeneity was moderate (I² = 46%) and increased to 55% after excluding high-risk studies. Subgroup analysis showed that tablet-based interventions tended to produce higher effect sizes. Conclusions: ICT-based interventions considerably enhance cognition status, autonomy, and social interaction in older adults with MCI and dementia. To ensure long-term scalability, future initiatives must prioritize user-centered design, caregiver education, equitable access to technology, accessible infrastructure and supportive policy frameworks. Full article

This paper provides a conceptual framework for soundscape appraisal as a key outcome of the hearing process. Sound appraisal involves auditory sense-making and produces the soundscape as the perceived and understood acoustic environment. The soundscape exists in the experiential domain and involves meaning-giving. Soundscape research has reached a consensus about the relevance of two experiential dimensions—pleasure and eventfulness—which give rise to four appraisal quadrants: calm, lively/vibrant, chaotic, and boring/monotonous. Requirements for and constraints on the hearing and appraisal processes follow from the demands of living in a complex world, the specific properties of source and transmission physics, and the need for auditory events and streams of single-source information. These lead to several core features and functions of the hearing process, such as prioritizing the auditory channel (loudness), forming auditory streams (audibility, primitive auditory scene analysis), prioritizing auditory streams (audible safety, noise sensitivity), and initial meaning-giving (auditory gist and perceptual layers). Combined, this leads to a model of soundscape appraisal yielding the ISO quadrant structure. Long-term aggregated appraisals lead to a sonic climate that allows for an insightful comparison of different locations. The resulting system needs additional validation and optimization to comply in detail with human appraisal and evaluation. Full article