Search Results (1,421)

Background/Objective: The use of immersive virtual reality (VR) for cognitive training in older adults has shown promising results in recent years. However, the number of well-designed studies remains limited, and variability in methodologies makes it difficult to draw generalizable conclusions. This systematic review aims to examine the effects of VR-based cognitive training in older adults, describe the technological characteristics of these interventions, identify current gaps in the literature, and suggest future research directions. Methods: Following PRISMA guidelines, a search was conducted across major databases (PubMed, PsycINFO, Scopus, ProQuest, ACM, and Web of Science) from 2018 to 2025. The database search identified 156 studies, of which 12 met the inclusion criteria after screening and eligibility assessment. Across these studies, a total of 3202 older adult participants (aged 60 years or older) were included. Interventions varied in duration from 4 to 36 sessions, targeting domains such as memory, executive function, attention, and global cognition. Most interventions were based on cognitive training, with a few employing cognitive stimulation or cognitive rehabilitation approaches. Quality was assessed using the Effective Public Health Practice Project tool. Results: Most studies reported positive effects of VR interventions on cognitive domains such as attention, executive functions, and global cognition. Fewer studies showed improvements in memory. The majority used head-mounted displays connected to computers and custom-built software, often without public access. Sample sizes were generally small, and blinding procedures were often unclear. The average methodological quality was moderate. Conclusions: Immersive VR has potential as an effective tool for cognitive training in older adults. Future research should include larger randomized controlled trials, long-term follow-up, standardized intervention protocols, and the development of accessible software to enable replication and broader application in clinical and community settings. Full article

The scientific study of emotion remains fraught with conceptual ambiguity, methodological limitations, and epistemological blind spots. This theoretical paper argues that existing paradigms frequently capture synthetic rather than natural emotional states—those shaped by social expectations, cognitive scripting, and performance under observation. We propose a conceptual framework that distinguishes natural emotion—spontaneous, embodied, and interoceptively grounded—from synthetic forms that are adaptive, context-driven, and often unconsciously rehearsed. These reactions often involve emotional scripts rather than genuine, spontaneous affective experiences. Drawing on insights from affective neuroscience, psychological measurement, artificial intelligence, and neurodiversity, we examine how widely used tools such as EEG, polygraphy, and self-report instruments may capture emotional conformity rather than authenticity. We further explore how affective AI systems trained on socially filtered datasets risk replicating emotional performance rather than emotional truth. By recognizing neurodivergent expression as a potential site of emotional transparency, we challenge dominant models of emotional normalcy and propose a five-step agenda for reorienting emotion research toward authenticity, ecological validity, and inclusivity. This post-synthetic framework invites a redefinition of emotion that is conceptually rigorous, methodologically nuanced, and ethically inclusive of human affective diversity. Full article

Introduction: Pain is highly prevalent among community-dwelling older adults and can undermine their ability to perform Instrumental Activities of Daily Living (IADL), which are essential for independent living. This systematic review aimed to summarize existing research to clarify the relationship between pain and IADL disability in community-dwelling older adults. Methods: We conducted a search of PubMed on 27 July 2025. Eligible studies met the following criteria: (1) assessed the association between pain and IADL disability; (2) included community-dwelling older adults aged 60 and older; and (3) were published in English. Results: Of the 400 records screened, 29 studies met the inclusion criteria. Of these, 23 studies (18 cross-sectional and 5 cohort studies) reported a significant association between pain and IADL disability, while 6 cross-sectional studies did not. Pain was assessed using diverse instruments across varying recall periods and thresholds, and IADL disability was measured using multiple scales. Such methodological heterogeneity precluded quantitative synthesis. Conclusions: In community-dwelling older adults, pain consistently predicts IADL disability across designs and settings. However, the lack of standardized, multidimensional measures and incomplete adjustment for treatment, multimorbidity, and polypharmacy limits precise effect estimation. Future research should adopt harmonized assessment tools, control comprehensively for relevant confounders, and perform meta-analyses where data permit to clarify pain’s true impact on functional independence. Full article

The Internet of Things (IoT) has emerged as a transformative technology in managing Alzheimer’s Disease (AD), offering novel solutions for early diagnosis, continuous patient monitoring, and assistive care. This review presents a comprehensive analysis of iot-enabled systems tailored to ad care, focusing on wearable biosensors, cognitive monitoring tools, smart home automation, and Artificial Intelligence (AI)-driven analytics. A systematic literature survey was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify, screen, and synthesize 236 relevant studies primarily published between 2020 and 2025 across IEEE Xplore, PubMed, Scopus and Web of Science. The inclusion criteria targeted peer-reviewed articles that proposed or evaluated iot-based solutions for ad detection, progression monitoring, or patient assistance. Key findings highlight the effectiveness of the iot in detecting behavioral and cognitive changes, enhancing safety through real-time alerts, and improving patient autonomy. The review also explores integration challenges such as data privacy, system interoperability, and clinical adoption. The study reveals critical gaps in real-world deployment, clinical validation, and ethical integration of iot-based systems for Alzheimer’s care. This study aims to serve as a definitive reference for researchers, clinicians, and developers working at the intersection of the iot and neurodegenerative healthcare. Full article

Wildlife rescue centres face considerable challenges in promoting animal welfare and enhancing the care and housing conditions of animals under professional supervision. These challenges are further compounded by the diversity of species admitted, each with distinct specific needs. In Colombia and other Latin American countries, primates are among the most frequently rescued and behaviourally complex mammalian taxa, requiring particular attention. In response, this study aimed to assess the content validity of proposed animal welfare indicators for Cebus albifrons through a Delphi consultation process and to develop two species-specific assessment protocols: a daily-use tool for keepers and a comprehensive protocol for professional audits. A panel of 23 experts in primate care and rehabilitation participated in two consultation rounds to evaluate and prioritise the indicators based on their content validity, perceived reliability, and practicality. Indicators were classified as either animal-based (direct measures) or resource- and management-based (indirect measures). After each round, experts received summarised feedback to refine their responses and facilitate consensus building. Of the 39 initially proposed indicators, 28 were validated for inclusion in the extended protocol and 10 selected for the daily-use checklist. Among these, 20 indicators in the extended protocol and 6 in the daily protocol were resource- or management-based—such as adequate food provision, physical enrichment, and habitat dimensions—highlighting their practical applicability and relevance in identifying welfare issues and risk factors. Although these indirect indicators were more numerous, the top-ranked indicators in both protocols were animal-based, including signs of pain, affiliative behaviours, and abnormal repetitive behaviours. These are essential for accurately reflecting the animals’ welfare state and are therefore critical components of welfare assessment in captive non-human primates. This study demonstrates that welfare assessment tools can be effectively tailored to the specific needs of wildlife rescue centres, providing a robust foundation for enhancing welfare practices. These protocols not only offer practical approaches for assessing welfare but also underscore the importance of embedding animal welfare as a priority alongside conservation efforts. Future research should aim to refine these tools further, assess their implementation, and evaluate inter- and intra-observer reliability to ensure consistency across different settings. Full article

Artificial intelligence (AI) for placemaking holds the potential to revolutionize how we conceptualize, design, and manage urban spaces to create more vibrant, resilient, and people-centered cities. In this context, integrating Human-Centered AI (HCAI) into public infrastructure presents an exciting opportunity to reimagine the role of urban amenities and furniture in shaping inclusive, responsive, and technologically enhanced public spaces. This review examines the state-of-the-art in HCAI for placemaking, focusing on some of the main factors that must be analyzed to guide future technological research and development, such as (a) AI-driven tools for community engagement in the placemaking process, including sentiment analysis, participatory design platforms, and virtual reality simulations; (b) AI sensors and image recognition technology for analyzing user behaviors within public spaces to inform evidence-based urban design decisions; (c) the role of HCAI in enhancing community engagement in the placemaking process, focusing on tools and approaches that facilitate more inclusive and participatory design practices; and (d) the utilization of AI in analyzing and understanding user behaviors within public spaces, highlighting how these insights can inform more responsive and user-centric design decisions. The review identifies current innovations, implementation challenges, and emerging opportunities at the intersection of artificial intelligence, urban design, and human experience. Full article

Streptococcus pneumoniae remains a leading cause of invasive diseases, particularly affecting young children and the elderly. Currently, two main types of pneumococcal vaccines are commercially available: polysaccharide vaccine (PPSV23) and conjugate vaccines (e.g., PCV20). Of over 100 identified pneumococcal serotypes, vaccines targeting 24 serotypes covered by PPSV23 and PCV20 (19 serotypes overlap between the two vaccines) have been developed, with serotype distribution varying by geography, age, and time. The immune response to pneumococcal vaccines differs across serotypes, vaccine types (polysaccharide vs. conjugate), and host factors. Quantitative methods for antibody assessment—particularly newer high-throughput assays—have emerged since 2000 to address limitations in conventional approaches. However, these methods have not been comprehensively reviewed. This scoping review aimed to systematically map the existing literature on quantitative methods used to assess antibody responses to pneumococcal vaccines. Specific objectives included the following: 1. summarizing conventional and novel quantitative immunoassays; 2. evaluating the current state of validation and application of these methods; 3. identifying knowledge gaps and methodological challenges. We followed the PRISMA-ScR guidelines. We included the following: 1. peer-reviewed, open-access papers related to immunoassays used for pneumococcal antibody assessment; 2. articles written in English; 3. Studies published between 2000 and 2023. We excluded the following: 4. studies focusing on other pathogens, employing different analytical methods, or using animal models. Articles meeting the eligibility criteria were primarily retrieved from PubMed and Scopus. If free full-text versions were unavailable there, Google Scholar or the original journal databases were consulted. All references were exported to EndNote 20 for further management. At the beginning of the review, a data-charting form was developed based on prior studies and commonly addressed themes. Additional charts were created to accommodate newly identified variables during the review. All charting tools were reviewed and finalized through discussion among all research team members. The included studies were classified into five thematic groups: 1. general descriptions of quantitative assessment methods, 2. assay development and validation, 3. comparative studies, 4. technical details of assay development, 5. interpretation of assay application findings. Of 1469 articles from PubMed and 2946 articles from Scopus initially identified, 55 articles met the inclusion criteria. The earliest methods included radioimmunoassays, later replaced by WHO-standardized ELISA. While ELISA remains the gold standard, it is limited by labor, cost, and throughput. Multiplex immunoassays (MIAs), including Luminex-based platforms, have demonstrated advantages in efficiency and scalability. However, many MIAs did not initially meet WHO validation criteria. More recent assays show an improved performance, yet interlaboratory variability and lack of standardized protective thresholds remain major limitations. This review provides the first comprehensive mapping of quantitative antibody assessment methods for pneumococcal vaccines. Although ELISA continues to serve as the benchmark, MIAs represent a promising next-generation approach. Continued efforts are needed to harmonize assay validation protocols and establish global standards for protective thresholds, which will enhance the reliability of vaccine efficacy monitoring across diverse populations. Full article

Background/Objectives: Gastric, oesophageal, and pancreatic cancers are common worldwide, with low but improving survival rates due to advances in curative treatments. However, these treatments often cause long-term nutrition impact symptoms that are frequently overlooked, leading to malnutrition and poorer health outcomes. This review explored the types of nutrition impact symptoms following curative-intent treatment for upper gastrointestinal (UGI) cancers and assessed their impact on nutrition status. Methods: A systematic search of four electronic databases identified studies involving adults treated with curative intent for UGI cancers. Included studies reported both nutrition impact symptoms and nutrition outcomes using validated tools. Study quality was assessed, and results were synthesised narratively. Results: Eleven studies (n = 953 participants), predominantly from the Asia–Pacific region, met the inclusion criteria. Participants were mostly male (68%), with surgery as the primary treatment (91%). Most studies (n = 10) used validated assessment tools to identify nutrition impact symptoms. Reflux was the most commonly reported symptom (n = eight studies), followed by abdominal pain and diarrhoea. Nutrition status was assessed using various validated tools: Patient-Generated Subjective Global Assessment (n = six studies, 55%), Mini Nutritional Assessment (n = two studies, 18%), and Global Leadership Initiative on Malnutrition as well as Subjective Global Assessment and Prognostic Nutritional Index (both n = one study, 9%). Malnutrition prevalence was up to 87% one year post-treatment. Conclusions: Nutrition impact symptoms are common and persistent after curative-intent treatment for UGI cancers. Future research should incorporate validated assessment tools and extend follow-up beyond 12 months. Integrating long-term, tailored dietetic support to identify and manage symptoms post-treatment is vital to improve outcomes for patients. Full article

Positron emission tomography (PET) has become a powerful tool in Alzheimer’s disease (AD) research by enabling in vivo visualization of pathological biomarkers. Recent efforts have aimed to integrate PET-derived imaging phenotypes with genome-wide association studies (GWASs) to better elucidate the genetic architecture underlying AD. This systematic review examines studies that leverage PET imaging in the context of GWASs (PET-GWASs) to identify genetic variants associated with disease risk, progression, and brain region-specific pathology. A comprehensive search of PubMed and Embase databases was performed on 18 February 2025, yielding 210 articles, of which 10 met pre-defined inclusion criteria and were included in the final synthesis. Studies were eligible if they included AD populations, employed PET imaging alongside GWASs, and reported original full-text findings in English. No formal protocol was registered, and the risk of bias was not independently assessed. The included studies consistently identified APOE as the strongest genetic determinant of amyloid burden, while revealing additional significant loci including ABCA7 (involved in lipid metabolism and amyloid clearance), FERMT2 (cell adhesion), CR1 (immune response), TOMM40 (mitochondrial function), and FGL2 (protective against amyloid deposition in Korean populations). The included studies suggest that PET-GWAS approaches can uncover genetic loci involved in processes such as lipid metabolism, immune response, and synaptic regulation. Despite limitations including modest cohort sizes and methodological variability, this integrated approach offers valuable insight into the biological pathways driving AD pathology. Expanding PET-genomic datasets, improving study power, and applying advanced computational tools may further clarify genetic mechanisms and contribute to precision medicine efforts in AD. Full article

The integration of Artificial Intelligence (AI) in education has raised important questions about its role in supporting inclusive practices, particularly in special education. This qualitative-dominant study with quantitative support examines how special education teachers in inclusive primary classrooms in Greece use ChatGPT to design Individualized Education Programs (IEPs) for students with learning disabilities. Six teachers participated, with some employing ChatGPT and others relying on traditional methods. The quality of IEP goals was described using the Revised IEP/IFSP Goals and Objectives Rating Instrument (R-GORI), while in-depth teacher perspectives were explored through thematic analysis. Findings suggest that ChatGPT contributed to clearer goal-setting, generation of diverse instructional resources, and more structured lesson planning. However, teachers emphasized the need for critical oversight, adaptation to real-world classroom conditions, and safeguarding the relational and emotional aspects of teaching. Participants expressed cautious optimism, viewing ChatGPT as a valuable support tool when integrated thoughtfully and ethically. These context-specific, exploratory results offer preliminary guidance for educators, policymakers, and researchers seeking to integrate AI tools into special education. They highlight the importance of targeted professional development, ethical safeguards, and further large-scale research to evaluate the broader applicability of AI-assisted IEP planning. Full article

Polypharmacy in older adults increases risks of adverse drug reactions (ADRs), hospitalisations, and mortality. Pharmacist-led interventions using validated tools (e.g., STOPP/START, MAI, STOPPFrail) aim to optimise prescribing, yet their impact on clinical and economic outcomes in UK/Ireland health systems remains underexplored. This systematic review aimed to critically assess the impact of pharmacist-led deprescribing interventions on PIP, clinical outcomes, and costs in older adults (≥65 years) across the UK and Ireland. Following PRISMA 2020 guidelines, four databases (PubMed, Scopus, Web of Science, Cochrane Library) were searched for studies (2010–2024). Eligible studies included randomised trials, observational designs, and intervention studies in hospitals, care homes, community pharmacies, and intermediate care settings. Fourteen studies met the inclusion criteria. The risk of bias was assessed using CASP checklists. Narrative syntheses and heat maps summarised the findings. Twelve of fourteen studies reported positive outcomes: reductions in potentially inappropriate medications, ADRs, medication burdens, and falls/fall risks. Medication appropriateness improved significantly in 35% of studies using the MAI. STOPPFrail reduced PIMs in care homes, while the MAI enhanced complex hospital reviews. Community interventions improved adherence and reduced the use of fall risk drugs. No studies demonstrated a reduction in hospitalisations, mortality, or the length of stays. Economic analyses showed mixed cost-effectiveness. Key barriers included low uptake of pharmacist recommendations and short follow-up periods. Pharmacist-led interventions have significantly improved the prescribing quality and reduced medication-related risks, but they fail to impact hospitalisations or mortality due to implementation gaps. Context-specific tools and policy reforms—including expanded pharmacist roles and electronic decision support—are critical for sustainability. Future research should focus on long-term outcomes, cost-effectiveness, and multidisciplinary integration. Full article

Background/Objectives: Patient-reported outcome measures (PROMs) are widely used tools in orthopedic surgery for evaluating clinical outcomes, guiding research, and supporting value-based care. However, the optimal timing for collecting baseline PROMs, whether in clinic prior to surgery or on the day of surgery, remains uncertain. This study investigated whether the clinical setting (preoperative clinic vs. day of surgery) affects baseline PROMs in patients undergoing anterior cervical discectomy and fusion (ACDF). Methods: Patients undergoing elective, primary ACDF at a single institution between August 2019 and June 2021 were prospectively enrolled. Inclusion criteria included age over 18, English literacy, and eligibility for primary ACDF. Participants completed PROMIS domains, Neck Disability Index (NDI), Modified Japanese Orthopaedic Association (mJOA) score, and Visual Analog Scale (VAS) at two time points: during the preoperative clinic visit and again in the perioperative area on the day of surgery. A subgroup analysis was performed for patients with anxiety, defined as a PROMIS anxiety score ≥ 59.4. Results: A total of 63 patients were enrolled, with 48 completing both sets of surveys. The average time between the two assessments was 7.9 days (95% CI: 6.4–9.3). After Bonferroni correction (α = 0.005), no significant differences were observed in any PROMs across the two time points, including PROMIS physical function (p = 0.398), pain interference (p = 0.682), fatigue (p = 0.019), social satisfaction (p = 0.331), anxiety (p = 0.047), depression (p = 0.042), NDI (p = 0.072), mJOA (p = 0.566), VAS neck pain (p = 0.054), or VAS overall pain (p = 0.335). Subgroup analysis of anxious patients similarly revealed no statistically significant changes between settings. Conclusions: PROM scores were not meaningfully different between the preoperative clinic and the day of surgery in patients undergoing ACDF. These results are most applicable when baseline PROMs are collected within about one week of ACDF. These findings support flexibility in workflow design for PROM collection, as the timing and setting do not significantly impact baseline responses. Full article

Objectives: This scoping review aims to synthesize the methodological characteristics of weight-cutting strategies, summarize their effects on sleep, recovery, and injury outcomes, and identify research gaps. Methods: Following the PRISMA guidelines, searches were conducted on 20 May 2025, across PubMed, Scopus, and Web of Science, with snowball citation tracking and expert consultation to enhance retrieval. Inclusion criteria targeted peer-reviewed studies involving competitive or recreational combat sport athletes (all ages and sexes) undergoing weight-cutting practices, reporting outcomes on sleep (e.g., quality and duration), recovery (e.g., perceived fatigue and biomarkers), or injury incidence (e.g., reported injuries and odds ratios). Studies included randomized controlled trials, non-randomized trials, or cohort studies with or without comparator groups. The risk of bias was assessed using the RoB 2 tool for randomized trials and the ROBINS-I tool for non-randomized studies. Results: From 2784 records, 17 studies met the inclusion criteria. Participant ages ranged from 17.79 ± 0.75 to 30.1 ± 7.5 years, predominantly national-level combat sport athletes (wrestling, judo, taekwondo, and MMA). Rapid weight loss (RWL, 2–10% body mass loss over 1–7 days) via food/fluid restriction, sauna use, and caloric deficits consistently increased creatine kinase (peaking at 713.4 ± 194.6 U/L), perceived fatigue (41.8 ± 0.9 to 51.3 ± 2.0 A.U.), and injury rates (45.62 injuries/1000 athletic exposures in females). Cortisol responses showed increases in some studies (from 499.9 ± 107.8 to 731.6 ± 80.2 nmol/L) and decreases in others (from 603.2 ± 146.8 to 505.8 ± 118.4 nmol/L). Sleep quality showed mild worsening (5.15 ± 1.83 to 5.52 ± 1.71 A.U.), and perceived recovery declined post-RWL (101.40 ± 2.52 to 87.63 ± 2.47 A.U.). Conclusions: RWL in combat sports consistently impairs recovery, increases muscle damage and fatigue, and increases injury risk, though sleep quality effects are less pronounced. Variability in weight-cutting protocols, outcome measures, and study designs shows the need for standardized methodologies, broader inclusion of female athletes, and longitudinal studies to assess long-term impacts. Full article

This review synthesizes research on smart insole prototypes and their designs, focusing on those incorporating artificial intelligence (AI) and a wireless communication/transmission system. The main objective of this work is to summarize existing studies, identify key trends, evaluate the performance of these innovative biomechanical tools, and recognize the factors that could lead to optimization. This comprehensive analysis includes studies from PubMed, Scopus, and Web of Science databases and other investigations on the critical themes to consider. It follows strict inclusion and exclusion criteria, ensuring the quality and accuracy of the overview. The findings emphasize significant progress in smart insoles, particularly in AI-enhanced prototypes, while addressing existing challenges and problems. This review helps guide potential future research and define practical application directions. The growing importance of biomechanics, especially on smart insoles, underscores the considerable potential of these innovations to monitor and improve human movement in both clinical and non-clinical settings, promising a future of more effective and personalized health and performance interventions. This protocol was registered with the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) on 6 February 2025 and was last updated on 6 February 2025. Full article

This study aims to explore the effectiveness of a problem-solving method, grounded in Pólya’s methodological proposal and complemented by a STEM electronic educational kit, in strengthening the research competences of newly admitted nursing students at a public university in Peru. The research followed a quantitative approach using a quasi-experimental design with pre- and post-test measurements applied to a group of students who addressed real community health issues in their local context. The intervention was structured into four phases: understanding the problem, planning activities, execution, and reviewing the solution. The results showed significant improvements across all phases, particularly in problem analysis, autonomous planning, technological application, and critical thinking. The Wilcoxon test yielded p-values < 0.05 in all evaluated dimensions, allowing the rejection of the null hypothesis and confirming the effectiveness of the intervention. It is concluded that the problem-solving method, when integrated with relevant technological tools, is an effective strategy to promote formative research in vulnerable educational contexts. Moreover, it aligns with the Sustainable Development Goals—specifically SDG 4 (Quality Education) and SDG 10 (Reduced Inequalities)—by fostering inclusive, equitable, and contextually relevant education through socially and technologically meaningful innovation. Full article