Search Results (1,264)

In individuals exposed to relatively mild methylmercury, even if they appeared to be independent in activities of daily living (ADL), slower judgment and motor responses in daily activities were observed, suggesting potential cognitive impairment. To quantitatively assess this impairment, we measured reaction time (RT) in a visual search test, as a visual cognitive ability test. The study participants included 24 residents from contaminated areas with sensory impairments in the limbs but no visual field defects (E group), as well as 12 individuals from non-contaminated areas (Group C). The 24 participants from contaminated areas were further divided into two groups: 12 without hand motor coordination disorders (Group E-HA) and 12 with such disorders (Group E+HA). Participants were instructed to search for the target letter “Z” on a computer screen, and the visual stimuli consisted of two, six, or ten alphabet letters. An equal number of trials contained “Z” and did not contain “Z,” for a total of thirty trials, which were conducted twice. RT was significantly longer in Group E+HA, followed by Group E-HA, and then Group C. However, in the second test, RT decreased in all cases, with a greater reduction in the exposed groups compared to the control group. These results suggest that methylmercury exposure may cause cognitive impairment, yet it also possesses plasticity. Full article

Introduction: Asthma is a chronic respiratory disease affecting approximately 5 million children in the US, but little is known about whether asthma alters children’s attention and memory functions. Most studies on this topic focus on psychiatric and QoL outcomes rather than cognitive functions, leaving a gap in the literature. We aimed to conduct a systematic review and meta-analysis to evaluate the attention deficit and memory function outcomes in children with bronchial asthma. Methods: A systematic search was conducted in PubMed, Web of Science, and Cochrane Library from inception to 28 February 2025 for studies evaluating attention deficit and memory function in children with bronchial asthma. Outcomes of interest included attention deficit and memory function. Statistical analysis was performed with R 4.3.1. Heterogeneity was accessed using the I² statistics and Cochrane Q test. The standardized mean difference (SMD) with restricted maximum-likelihood estimator random-effects method was computed for all outcomes. Results: A total of seven studies were included in the final meta-analysis, comprising 104,975 patients, of whom 10,200 (9.7%) had bronchial asthma (mean age ± 8.98 years, mean 45% females). In the pooled analysis, children with asthma had a worsened attention deficit compared to the healthy group (SMD 0.29; 95% CI [0.07; 0.51]; p = 0.01; I² = 92%). However, no statistically significant difference was found in memory function between groups (SMD −0.24; 95% CI [−1.81; 1.33]; p = 0.77; I² = 96%). Conclusions: Children with asthma showed significantly higher attention deficit scores compared to healthy children. No statistically significant differences were observed in memory function between the groups. These findings may have implications for early cognitive screening in pediatric asthma management. Full article

Background/Objectives: Heart transplantation is a life-saving procedure for patients with end-stage heart failure, yet it involves significant psychological and emotional challenges throughout its various stages. International guidelines recommend a multi-professional approach to the care of these patients and a psycho-social assessment for listing. The recommendations focus on content aspects, but not on the psychometric measure to be administered to patients as part of the assessment. Therefore, the purpose of this study is to provide the preliminary results of administering the protocol used by our center, measuring coping strategies, cognitive functioning, quality of life, and psychological distress in a sample of patients who are candidates for and undergo cardiac transplantation, and to observe any variations after the procedure. Methods: We conducted a comprehensive psychological-clinical assessment involving 40 patients, focusing on psychosocial functioning, cognitive reserves, mental health, and coping strategies. Tools such as the Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT), Beck Depression Inventory-II (BDI-II), Montreal Cognitive Assessment (MoCA), General Anxiety Disorder 7 (GAD-7), and Medical Outcomes Survey Short Form 36 (SF-36) were employed to evaluate readiness for transplantation and post-transplant adaptation. Results: Results showed high levels of clinical anxiety (52.5%) and low perceived physical health (98%) before the transplant, while post-operative evaluations indicated reduced anxiety (13.51%) and depressive symptoms (10.81%), along with improved psychological well-being and reintegration into daily life. Conclusions: These results show improvement in physical and cognitive levels, accompanied by a state of enhanced psychological well-being after transplantation. A longitudinal psychological approach, from pre-transplant screening to post-discharge follow-up, is needed to address distress, improve coping mechanisms, and promote treatment adherence. This integrative strategy is critical to improving the quality of life and long-term outcomes for heart transplant recipients. Full article

Optimal sensorimotor control depends on response timing. With age, it is broadly assumed that reaction time (RT) increases as cognitive function declines. However, it is not clear if the literature supports this assumption. The purpose of this work was to review the association between cognition and upper extremity RT in older adults. We conducted a search using Scopus database with four inclusion criteria: (1) healthy, community-dwelling adults over 60 years old, (2) upper extremity movement, (3) cognitive assessment, and (4) RT measure. Twenty-five of the 1608 articles screened met the inclusion criteria. Only nine studies directly or indirectly assessed the association between cognition and RT. Our interpretation of the literature was further limited by inconsistency in test selection and measurement interdependence that could be addressed by future studies. We present a conceptual framework to guide research assessing the influence of cognition on sensorimotor control with age. Full article

Background/Objectives: Frailty is a multifactorial clinical syndrome characterized by diminished physiological reserves and increased vulnerability to stressors. It is increasingly recognized as a predictor of poor outcomes in cardiac rehabilitation (CR). However, how frailty is defined, assessed, and addressed across outpatient CR programmes remains unclear. This scoping review aimed to map the extent, range, and nature of research examining frailty in the context of outpatient CR, including how frailty is measured, its impact on CR participation and outcomes, and whether sex and gender considerations or participation barriers are reported. Methods: Following the PRISMA-ScR guidelines, we conducted a comprehensive search across six electronic databases (from inception to 15 May 2025). Eligible peer-reviewed studies included adult participants assessed for frailty using validated tools and enrolled in outpatient CR programmes. Two reviewers independently screened citations and extracted data. Results were synthesized descriptively and narratively across three domains: frailty assessment, sex and gender considerations, and barriers to CR participation. The protocol was registered with the Open Science Framework. Results: Thirty-nine studies met inclusion criteria, all conducted in the Americas, Western Pacific, or Europe. Frailty was assessed using 26 distinct tools, most commonly the Kihon Checklist, Fried’s Frailty Criteria, and Frailty Index. The median pre-CR frailty prevalence was 33.5%. Few studies (n = 15; 38.5%) re-assessed frailty post-CR. Sixteen studies reported sex or gender data, but none applied sex- or gender-based analysis (SGBA) frameworks. Only eight studies examined barriers to CR participation, identifying physical limitations, emotional distress, cognitive concerns, healthcare system-related factors, personal and social factors, and transportation as key barriers. Conclusions: The literature on frailty in CR remains fragmented, with heterogeneous assessment methods, limited global representation, and inconsistent attention to sex, gender, and participation barriers. Standardized frailty assessments and individualized CR programme adaptations are urgently needed to improve accessibility, adherence, and outcomes for frail individuals. Full article

Background/Objectives: Dystonia, traditionally regarded as a purely motor disorder, is now increasingly recognized as involving clinically significant non-motor symptoms (NMSs) that can adversely affect patients’ health-related quality of life (HRQoL). This study aimed to assess HRQoL in Romanian patients with isolated dystonia and to evaluate the impact of two key NMSs, depression and cognitive impairment, on their HRQoL. We hypothesized that depression would have a greater adverse effect on HRQoL than cognitive impairment. Methods: A cross-sectional study was conducted involving 65 adult Romanian patients with isolated dystonia. HRQoL was measured using the Short Form-36 Health Survey (SF-36), including the physical component summary (PCS) and mental component summary (MCS). Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), and cognitive impairment was assessed using the Montreal Cognitive Assessment (MoCA). Descriptive statistics, correlation analysis, and parametric and non-parametric tests were used. Multiple regression analysis was employed to evaluate associations between NMS and HRQoL. Results: The mean (SD) age was 56.6 (14.3) years, and 80% of participants were female. Depression and cognitive function were significantly associated with PCS (0.33 and −0.51, respectively) and MCS (0.26 and −0.78, respectively). Multiple regression analysis showed that the two NMS explained 38% of the variance in PCS and 58% of the variance in MCS. Depression had a greater impact on PCS and MCS than cognitive impairment (−0.47 vs. 0.33 and −0.72 vs. 0.16, respectively). Cognitive impairment (MoCA < 26) was present in 35.4% of patients, while 46.2% had at least mild depressive symptoms (PHQ-9 ≥ 5); 23.1% met criteria for moderate-to-severe depression (PHQ-9 ≥ 10). Depressive symptoms showed strong negative correlations with all SF-36 domains, while cognitive performance correlated modestly. Conclusions: Both depression and cognitive impairment have a significant negative impact on HRQoL in dystonia, with depression having a stronger effect, as we hypothesized. Routine screening for non-motor symptoms is essential to support better clinical outcomes and enhance patients’ quality of life. Full article

Background: Mild Cognitive Impairment (MCI) represents an intermediate stage between normal cognitive aging and Alzheimer’s Disease (AD). Early and accurate identification of MCI is crucial for implementing interventions that may delay or prevent further cognitive decline. This study aims to develop a machine learning-based model for differentiating between Cognitively Normal (CN) individuals and MCI patients using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Methods: An ensemble classification approach was designed by integrating Extra Trees, Random Forest, and Light Gradient Boosting Machine (LightGBM) algorithms. Feature selection emphasized clinically relevant biomarkers, including Amyloid-β 42, phosphorylated tau, diastolic blood pressure, age, and gender. The dataset was split into training and held-out test sets. A probability thresholding strategy was employed to flag uncertain predictions for potential deferral, enhancing model reliability in borderline cases. Results: The final ensemble model achieved an accuracy of 83.2%, a recall of 80.2%, and a precision of 86.3% on the independent test set. The probability thresholding mechanism flagged 23.3% of cases as uncertain, allowing the system to abstain from low-confidence predictions. This strategy improved clinical interpretability and minimized the risk of misclassification in ambiguous cases. Conclusions: The proposed AI-driven ensemble model demonstrates strong performance in classifying MCI versus CN individuals using multimodal ADNI data. Incorporating a deferral mechanism through uncertainty estimation further enhances the model’s clinical utility. These findings support the integration of machine learning tools into early screening workflows for cognitive impairment. Full article

Background and Objectives: General-purpose multimodal large language models (LLMs) are increasingly used for medical image interpretation despite lacking clinical validation. This study evaluates the diagnostic reliability of ChatGPT-4o and Claude 2 in photographic assessment of adolescent idiopathic scoliosis (AIS) against radiological standards. This study examines two critical questions: whether families can derive reliable preliminary assessments from LLMs through analysis of clinical photographs and whether LLMs exhibit cognitive fidelity in their visuospatial reasoning capabilities for AIS assessment. Materials and Methods: A prospective diagnostic accuracy study (STARD-compliant) analyzed 97 adolescents (74 with AIS and 23 with postural asymmetry). Standardized clinical photographs (nine views/patient) were assessed by two LLMs and two orthopedic residents against reference radiological measurements. Primary outcomes included diagnostic accuracy (sensitivity/specificity), Cobb angle concordance (Lin’s CCC), inter-rater reliability (Cohen’s κ), and measurement agreement (Bland–Altman LoA). Results: The LLMs exhibited hazardous diagnostic inaccuracy: ChatGPT misclassified all non-AIS cases (specificity 0% [95% CI: 0.0–14.8]), while Claude 2 generated 78.3% false positives. Systematic measurement errors exceeded clinical tolerance: ChatGPT overestimated thoracic curves by +10.74° (LoA: −21.45° to +42.92°), exceeding tolerance by >800%. Both LLMs showed inverse biomechanical concordance in thoracolumbar curves (CCC ≤ −0.106). Inter-rater reliability fell below random chance (ChatGPT κ = −0.039). Universal proportional bias (slopes ≈ −1.0) caused severe curve underestimation (e.g., 10–15° error for 50° deformities). Human evaluators demonstrated superior bias control (0.3–2.8° vs. 2.6–10.7°) but suboptimal specificity (21.7–26.1%) and hazardous lumbar concordance (CCC: −0.123). Conclusions: General-purpose LLMs demonstrate clinically unacceptable inaccuracy in photographic AIS assessment, contraindicating clinical deployment. Catastrophic false positives, systematic measurement errors exceeding tolerance by 480–1074%, and inverse diagnostic concordance necessitate urgent regulatory safeguards under frameworks like the EU AI Act. Neither LLMs nor photographic human assessment achieve reliability thresholds for standalone screening, mandating domain-specific algorithm development and integration of 3D modalities. Full article

As digital marketing becomes more targeted and interactive, it is more critical to understand how young audiences perceive and react to compelling content. This research examines the extent to which consumer responses are affected by neuromarketing knowledge, interest, and screen-based advert exposure for middle school kids. Based on responses from 244 Greek adolescents aged 12–15 years, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to investigate direct and mediated influences on purchase intentions with advertisement skepticism and persuasion knowledge as mediating factors. Results indicate that exposure and recognition have a significant influence on intentions both by means of cognitive as well as attitudinal processes, while interest only increases skepticism but not interaction. Multi-group analysis yielded significant differences according to age and experience, referring to the development path of advertising literacy. The results provide strong cues to educators, policymakers, and marketers who want to develop media-critical competencies among adolescents in an ever-shaping digital age. Full article

This study proposes an interpretable hybrid deep learning framework for classifying attention deficit hyperactivity disorder (ADHD) using EEG signals recorded during cognitively demanding tasks. The core architecture integrates convolutional neural networks (CNNs), gated recurrent units (GRUs), and long short-term memory (LSTM) layers to jointly capture spatial and temporal dynamics. In addition to the final hybrid architecture, the CNN–GRU–LSTM model alone demonstrates excellent accuracy (99.63%) with minimal variance, making it a strong baseline for clinical applications. To evaluate the role of global attention mechanisms, transformer encoder models with two and three attention blocks, along with a spatiotemporal transformer employing 2D positional encoding, are benchmarked. A hybrid CNN–RNN–transformer model is introduced, combining convolutional, recurrent, and transformer-based modules into a unified architecture. To enhance interpretability, SHapley Additive exPlanations (SHAP) are employed to identify key EEG channels contributing to classification outcomes. Experimental evaluation using stratified five-fold cross-validation demonstrates that the proposed hybrid model achieves superior performance, with average accuracy exceeding 99.98%, F1-scores above 0.9999, and near-perfect AUC and Matthews correlation coefficients. In contrast, transformer-only models, despite high training accuracy, exhibit reduced generalization. SHAP-based analysis confirms the hybrid model’s clinical relevance. This work advances the development of transparent and reliable EEG-based tools for pediatric ADHD screening. 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: This review explores the influence of eco-anxiety on sustainable consumption, with a specific focus on the urban context. While the literature on green consumerism continues to expand, the role of emotional and psychological factors, especially eco-anxiety, in shaping sustainable consumption decisions remains underexplored. Most existing studies emphasize cognitive, social, or contextual drivers, often overlooking affective dimensions that may significantly influence consumer behavior. Addressing this gap, the review examines how emotional responses to climate change, such as eco-anxiety, inform and potentially motivate eco-friendly consumption patterns. Understanding these affective pathways offers valuable insights on how individuals and urban communities can effectively adapt to climate change and establish a sustainable consumption culture. Methods: A systematic literature search was conducted in Scopus and Web of Sciences databases, following a predefined keyword strategy, resulting in 56 initial records. We further implemented a supplementary search of gray literature on Google Scholar to search for additional reports. The full-text screening process identified 12 eligible studies based on the following inclusion criteria: quantitative or mixed-methods studies focusing on adult and young adult individuals, including both measures of eco-anxiety and green consumption and assessing their direct or indirect relationship. Results: Findings suggest that eco-anxiety functions as a cognitive–affective motivator for sustainable consumer choices; however, the strength and direction of this influence appear contingent on moderating emotional and psychological variables and cross-cultural and demographic moderators. Discussion: This review highlights the need for urban-focused intervention tailored communication, marketing, and business strategies that address the emotional dimensions of climate change. Policymakers and businesses are encouraged to consider affective drivers as eco-anxiety to promote sustainable consumption stewardship within urban communities. By addressing these psychological responses, urban societies can become more resilient and proactive in confronting climate change challenges. Full article

Background: Psychological problems post-stroke can negatively impact stroke survivors. Although general psychological services exist (e.g., NHS Talking Therapies), access remains limited, particularly for individuals with post-stroke communication and cognitive impairments. Stroke service staff report low confidence in managing psychological distress. This study is the first to explore the barriers and facilitators to implementing a novel intervention package comprising a cross-service care pathway and staff training to enhance post-stroke psychological provision. Methods: Staff from stroke and mental health services in four UK regions, recruited through purposive sampling to ensure diversity of services and professional roles, participated in semi-structured interviews or focus groups, guided by the Theoretical Domains Framework (TDF), before and after implementation of the intervention package. Pre-implementation interviews/groups identified anticipated barriers and facilitators to implementation and training needs, informing the development of site-specific intervention packages; post-implementation interviews/groups explored experienced barriers, facilitators and perceptions of the intervention. Interviews underwent thematic analysis using the TDF. Results: Fifty-five staff participated pre-implementation and seventeen post-implementation, representing stroke (e.g., nurse, physiotherapist, consultant) and psychology (e.g., counsellor, psychological therapist) roles across acute, rehabilitation, community, and voluntary services. Challenges anticipated pre-implementation included: limited specialist post-stroke psychological support; low staff confidence; and fragmented service pathways. Post-implementation findings indicated increased staff knowledge and confidence, enhanced screening and referral processes, and stronger inter-service collaboration. Implementation success varied across sites (with some sites showing greater ownership and sustainability of the intervention) and across staff roles (with therapy staff more likely than nursing staff to have received training). Conclusions: Effective implementation of an intervention package to increase psychological provision post-stroke requires staff engagement at all levels across all services. Staff investment influenced ownership of the intervention package, beliefs about priorities and overall enhancement of service capability. Full article

Background: Cognitive impairment (CI) is a common and disabling symptom in patients with relapsing–remitting multiple sclerosis (RRMS), potentially emerging at any stage, including preclinical phases. Despite its impact on quality of life, CI often goes unrecognized, as clinical follow-up typically focuses on motor and sensory symptoms. Validated tools, such as the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) and patient-reported outcomes (PROs), should be integrated into routine evaluations beyond the Expanded Disability Status Scale (EDSS). Objective: The objective of this study was to evaluate cognitive impairment and quality of life in patients with RRMS using the BICAMS and PROs. Methods: This cross-sectional, descriptive study included patients with RRMS under follow-up at a tertiary hospital in San Luis Potosí, Mexico. Participants underwent cognitive screening with the BICAMS battery and completed the MSQoL-54 (quality of life), FSMC (fatigue), and MSIS-29 (functional impact) scales. Statistical analyses included ANOVA, the Kruskal–Wallis test, and Pearson correlations. Results: Nineteen patients were evaluated (73.7% female, mean age 36.5 ± 8.9 years). BICAMS results showed variable cognitive performance, with no significant differences across treatment groups for processing speed (p = 0.222), verbal memory (p = 0.082), or visuospatial memory (p = 0.311). A significant correlation was found between verbal and visuospatial memory (r = 0.668, p = 0.002). Total quality of life differed significantly across treatments (F = 8.007, p = 0.029), with a strong correlation between overall quality of life and general health perception (r = 0.793, p < 0.001). Fatigue and MSIS scores showed no association with treatment. Conclusions: Cognitive impairment is common in RRMS and can be detected using brief assessment tools, such as the BICAMS. Incorporating cognitive screening and PROs into clinical practice is essential to guide comprehensive management. Full article

Genetic factors play an important role in the risk of developing lung cancer, a disease that disproportionately affects African American (AA) individuals who smoke. Accumulating evidence suggests that specific ancestry-informative genetic markers are predictive of lung cancer risk in AA individuals who smoke. Although testing for, and communication of, genetic risk to patients should impact health and screening, results are mixed. The goal of this study was to evaluate the effects of genetic risk communication that also included ancestry-specific risk information among African American individuals who smoke. Using an experimental design, African American individuals who smoke (n = 166) were assigned randomly to receive hypothetical genetic test results that indicated (1) low vs. high genetic risk for lung cancer (“Risk”) and (2) European vs. African Ancestry (“Ancestry”). We hypothesized that participants who had been told that they were both at high risk for lung cancer based on genetic markers prominent in African persons at risk of lung cancer, and that they have African ancestry, would exhibit increases in cognitive (perceived lung cancer risk), emotional (cancer worry and psychological distress), and motivational (motivation to quit smoking) factors shown to predict longer-term health behavior change. Results revealed significant and moderate-to-large effects of Risk for all outcomes. There was also a significant Ancestry effect on perceived lung cancer risk: increased risk perceptions among participants who learned that they have high African genetic heritage. Path analytic modeling revealed that cognitive and emotional factors mediated the effects of both Risk and Ancestry feedback on motivation to quit smoking. Findings further highlight the importance of incorporating ancestry-specific genetic risk information into genetic counseling sessions, especially in underserved populations, as doing so may impact key cognitive, emotional, and motivational factors critical to behavior change. Full article