Search Results (886)

The global maritime sector is undergoing rapid transformation, creating an urgent need to align digital port technologies with a sustainable development framework. However, existing research on smart ports and the blue economy is fragmented and predominantly driven by deterministic approaches that overlook systemic complexity and uncertainty. This study develops a smart port system model grounded in blue economy principles, using a Bayesian network to analyze causal relationships among operational, environmental, and governance variables under uncertainty. The model incorporates key factors including port operational efficiency, logistics reliability, environmental compliance systems, coastal employment, and regulatory enforcement. The findings indicate that operational and logistical factors are the primary drivers of the system, while environmental and socioeconomic variables strongly shape sustainability outcomes. Scenario analysis shows that coordinated interventions targeting these key variables generate the greatest improvements in Smart Port–Blue Economy integration. Sensitivity analysis further identifies coastal economic output, regional competitiveness, and marine ecosystem health as the most responsive outcome variables. The research offers lessons for policymakers to enhance port management by integrating logistics and technological considerations with blue economy principles to design adaptive and resilient policies, particularly in island regions. Full article

This study presents a Markov chain-based metric called the Reliability Reserve (τ), designed to estimate the time available for operator intervention during the ayran fermentation process. This indicator can be integrated into a digital twin forecast management system. The fermentation process was obtained using a DTMC (discrete-time Markov chain) and divided into five states according to pH (S1–S5). Laboratory samples were prepared from premium-grade cow’s milk sourced from the Zher-Ana farm and divided into three experimental groups: Control (without additives), Opt1 (3% additive), and Opt2 (4% additive). A sequence of states was created for the three studied groups (Control, Opt1, and Opt2), and the transition states of the matrix were calculated. The Reliability Reserve quantifies how much time is left before the system transitions from the target state to the acidification state. For the first group, P₄₅ was 0.200, corresponding to τ = 26.9 min. The incorporation of functional additives increased P₄₅ to 0.250, reducing τ to 20.9 min and shortening the operator intervention window by approximately 6 min. Markov chains were constructed using 101 interpolated time points obtained from five experimental pH measurements for each group. The original pH values were recorded at 2, 4, 6, 8, and 10 h of fermentation and linearly interpolated with a step size of 0.1 h to improve temporal resolution. Model robustness was evaluated using sensitivity analysis (±0.05 pH boundary shifts) and bootstrap resampling (n = 1000, 95% confidence intervals). The concept of Reliability Reserve is a practical decision-making tool in real time. It offers an alternative to traditional reliability indicators such as MTTF and allows integration into digital twin-based control systems. Full article

Dental caries remains one of the most prevalent yet preventable non-communicable diseases worldwide, disproportionately affecting populations with limited access to dental care and persistent socioeconomic inequalities. Early-stage lesions frequently remain undetected because of their asymptomatic nature, inadequate screening infrastructure, and the absence of continuous monitoring technologies, resulting in preventable complications and increased healthcare costs. To address these challenges, this study proposes an Internet of Things (IoT)-enabled intraoral wearable sensing device (I-OWSD) for continuous, quantitative, real-time monitoring of biomarkers associated with caries progression. The proposed framework integrates intraoral wearable sensing, cloud-based telemedicine services, and artificial intelligence (AI)-assisted analytics to support preventive oral healthcare and remote clinical decision-making. Two primary contributions are presented. First, a fractional-order delay-type model (FODM) based on the Caputo–Fabrizio derivative is proposed to capture the memory-dependent and nonlocal dynamics of caries progression. Mathematical analysis establishes the model’s non-negativity, boundedness, existence, uniqueness, and stability properties. Second, a biocompatible intraoral sensor interface is designed to enable continuous data acquisition and secure wireless communication with digital health platforms. Simulation results based on the proposed FODM suggest that, under an estimated adoption rate of 67.49%, the I-OWSD framework could reduce caries prevalence by approximately 15% while improving opportunities for early intervention and preventive care. The findings demonstrate the potential of combining fractional-order modelling, wearable sensing, and AI-driven teledentistry to advance continuous oral health monitoring and preventive dental care. Full article

Dynamic testing (DT) aims to overcome a limitation of static assessment by providing learning opportunities as part of the test procedure so as to allow an individual’s latent potential to be evaluated rather than relying on a mere snapshot of their performance. Despite strong theoretical support, DT remains underutilized in research and applied settings. Thus, this study analyzes whether the Figural Analogies Learning Test (FALT), a newly developed short-term learning test (a DT procedure), is suitable for the assessment of latent potential in school-aged children. Mode of delivery for learning opportunities (i.e., feedback) was experimentally manipulated to investigate whether a digital or social modality results in differential effects on learning gains. A further aim was to establish whether—by capturing test takers’ latent potential—the FALT has incremental predictive utility in relation to academic achievement. The study randomly assigned 279 Swiss schoolchildren to one of three conditions: digital FALT, social FALT, or a static analogies task, all based on the same item set. Intervention effectiveness was evaluated using a static retest two weeks later. In both FALT conditions (digital and social), children achieved higher scores at the repeated assessment than in the static control condition. Moreover, socially mediated feedback produced significantly larger score gains than digitalized feedback. The three conditions did not differ in their ability to predict academic achievement and, thus, showed no incremental predictive utility for the FALT. However, an explorative exclusion of children with high grade averages indicated an advantage for the digital FALT relative to its static counterpart. The results provide tentative evidence that while both digitally and socially mediated feedback enhance learning performance, the latter is more effective. We discuss the absence of incremental predictive utility, specifically in the context of self-regulated learning, as well as implications for the design and diagnostic use of learning tests in educational contexts. Full article

Background: The COVID-19 pandemic was accompanied by an infodemic that promoted the use of so-called “miracle products” lacking scientific evidence, posing significant public health risks. Despite increasing concern, evidence on effective educational strategies to counteract this misinformation remains limited, particularly in Latin America. Methods: A quasi-experimental pre–post study without a control group was conducted among university students in Mexico City between February and June 2021. Participants were recruited via Facebook using a snowball sampling approach. A validated nine-item questionnaire assessed knowledge about miracle products before and after exposure to an educational video intervention. Paired statistical analyses were performed to evaluate changes in knowledge. Results: A total of 157 participants completed the pre-test, and 103 completed the post-test. The intervention resulted in a significant increase in knowledge scores, from a mean of 5.98 (SD = 1.73) to 9.05 (SD = 1.54) (p < 0.001). Significant improvements were observed in eight of nine items, with the largest increases in knowledge related to high-risk substances and reporting mechanisms. No significant baseline differences were found between participants who completed and those who did not complete the post-test. Conclusions: The video-based educational intervention was effective in improving knowledge about miracle products during COVID-19. These findings support the use of digital health education strategies as scalable tools to combat misinformation, particularly in resource-constrained settings. However, further research using controlled designs is needed to assess long-term effects and behavioral outcomes. Full article

As digital beauty filters have become widespread among young people, their links with self-image cognition and behavioral responses have attracted growing attention. However, existing studies largely focus on Western samples or linear approaches, leaving Chinese youth underexplored in their cultural context. Using mixed methods combining grounded theory and fsQCA, this study examines the mechanisms shaping self-image cognition and behavioral responses among Chinese youth in the context of digital beauty filter use. Semi-structured interviews and three-stage coding identified four core categories: Beauty Filter Use Habits, Beauty Filter Use Motivations, Beauty Filter Use Preferences, and Psychological Responses to Beauty Filter Use. Building on this, fsQCA identified five configurational pathways. The psychological-response–motivation and psychological-response–preference core coexistence configurations were linked to high Self-Image Cognition; the three non-high Self-Image Cognition pathways formed two patterns: dual absence of psychological responses and motivations, and motivational-core absence with coexisting habits and preferences. Different self-image cognition outcomes may relate to adaptive behaviors, such as moderate retouching and naturalized self-presentation, or risk-related behaviors, such as avoidance of original images and overdependence on beauty filters. This study offers a new perspective on youth authentic self-construction and technological adaptation in the digital visual era, with implications for media literacy education, platform design, and mental health intervention. Full article

Background: Admission to an intensive care unit (ICU) exposes family members of adult patients to substantial informational, emotional, and decisional burden. In recent years, digital tools have increasingly been used to support communication, information delivery, virtual visiting, psychological support, diary writing, and surrogate decision making in ICU settings, although the available literature remains heterogeneous in terms of intervention type, purpose, timing, and outcomes assessed. Methods: A scoping review was conducted according to Joanna Briggs Institute methodology and reported following PRISMA-ScR. The literature search was performed between January and March 2026 in PubMed/MEDLINE, Scopus, and CINAHL. After duplicate removal, title/abstract screening, and full-text assessment, 32 studies were included in the qualitative synthesis. Results: The included studies were published between 2016 and 2026, used heterogeneous methodological designs, and originated from different international contexts. Six main categories of digital tools were identified: educational websites and online information resources; decision aids and tablet-based tools; virtual visiting and video communication systems; digital diaries and writing practices; psychological support or self-management applications; and digital assessment or family-engagement platforms. Overall, informational and communication-oriented tools appeared to provide the clearest signals of usefulness for family orientation, information access, communication, and relational continuity, whereas evidence regarding psychological and decisional outcomes remained more variable and largely preliminary. Conclusions: Digital tools for family members of adult ICU patients represent a relevant and evolving component of family-centered critical care. Their value appears to depend on the family need addressed, the timing of implementation, and their integration into clinical workflows. Overall, the available literature suggests that digital tools may be particularly useful for family orientation, information access, and communication, whereas their impact on psychological and decisional outcomes remains less certain and requires further investigation. Full article

Digital transformation and artificial intelligence are reshaping nursing education by changing how students access information, complete academic tasks, and engage with technology-mediated learning. However, evidence on digital competencies, AI-related constructs, mediating mechanisms, and academic performance remains fragmented and methodologically uneven. This systematic review of empirical studies synthesized how digital competencies and AI-related constructs are associated with academic performance and learning-related outcomes in nursing education. Following PRISMA 2020 guidelines adapted to social science research, searches were conducted in Scopus and Web of Science Core Collection in March 2026, covering 2022–2026. Twenty-five empirical studies were included: 18 quantitative, 4 qualitative, and 3 mixed-methods studies. The evidence was concentrated in the Middle East and North Africa, Asia, and Europe. Findings suggest that digital competencies are associated with academic and learning-related outcomes mainly through self-efficacy, academic motivation, cognitive presence, and learning flow. AI-related evidence remains emerging, mixed, and context-dependent. Although some AI-assisted interventions reported favorable outcomes, one experimental study found greater knowledge gains with traditional text-based study than with ChatGPT-assisted learning. Therefore, AI integration should not be considered universally beneficial, but contingent on pedagogical design, task type, teacher guidance, AI literacy, responsible use, and critical verification. Full article

This article examines the maturation of the Astana Hub technology park and its association with Kazakhstan’s national digital competitiveness during the country’s transition from resource dependency toward a higher value-added digital economy. As Central Asia’s largest international technology park, Astana Hub provides a policy-relevant case of a state-initiated open-innovation ecosystem. To proxy the national enabling environment, we construct the Kazakhstan Digital Performance Index (KDPI), a composite measure that normalizes and aggregates three publicly available global indices: the UN E-Government Development Index (EGDI), the Global Innovation Index (GII, WIPO), and the Network Readiness Index (NRI, Portulans Institute). Using an Interrupted Time Series (ITS) design over 2010–2024, we estimate the change in the level and slope of national IT service exports associated with the establishment of the Hub in 2018. The analysis identifies a statistically significant post-2018 increase in the export-growth slope of approximately $112.8 million per year relative to the pre-intervention trend, alongside a near 20-fold rise in IT service exports between 2020 and 2024. By contrast, the composite KDPI shows no comparable acceleration, and an exploratory correlation analysis over the short post-2018 window indicates a positive association between Hub growth and e-government infrastructure but a negative association with the GII. We interpret these patterns cautiously as descriptive evidence consistent with a temporary “island of efficiency,” in which commercial scaling has outpaced economy-wide innovation diffusion, rather than as confirmation of a bidirectional feedback loop or of causal national-level human-capital effects, which the single-country quasi-experimental design cannot establish. The paper discusses policy options for diffusing Hub capabilities into the wider economy and sets out the limitations of the design. Full article

Background: In recent years, there has been a growing concern regarding social media driving the decline of mental health, especially among adolescents. However, scientific consensus remains mixed, with many studies reporting only small or inconsistent associations. Aims: This paper aims to present the latest and most influential findings in the field of social media, with a focus on understanding the impact it has on adolescents’ mental health by looking at clinical versus non-clinical populations. Method: We conducted a comprehensive search through Scopus, looking for scientific articles and reviews published from January 2020 to March 2026 that include social media and adolescents with mental health conditions. We examined social media use patterns, affordances, mechanisms of impact, and clinical versus non-clinical populations. Results: There is limited literature comparing clinical versus non-clinical adolescent populations. Adolescents with mental health disorders spend more time online, teens with internalizing conditions report being more prone to social comparison and more sensitive to digital feedback, while those with externalizing conditions report a lack of control over how much time they spend on social media. Screen time alone is not sufficient to determine the impact on mental health. Among the features that might be associated with mental health problems are sharing personal content and scrolling through others’ posts. Conclusions: The impact of social media could be shaped by pre-existing vulnerabilities. There is a need for longitudinal study designs to test temporal associations and more research to cover the gap on clinical populations to develop better policies and interventions. Full article

Background: Malnutrition is common among older adults aged 65 years and over and is associated with physical and mental health risks. Malnutrition is a complex condition; supporting older adults in achieving healthy, sustainable dietary behaviors remains a challenge for care professionals. Assistive technologies to support malnutrition care, such as monitoring tools, social robots, or smart spoons, are often poorly adapted to real-world contexts and fail to sustain long-term engagement. Method: A design research approach was used to understand care practices better and explore design opportunities for assistive technologies. Eight in-depth, qualitative interviews were conducted with dietitians treating older adults with malnutrition. Interviews were transcribed and analyzed through thematic analysis. A five-phase patient journey was created as a visual tool to identify where assistive technologies could improve the care process and define design requirements. Results: Dietitians face challenges due to the dynamic nature of patient journeys, limited time for personalized care, difficulty in monitoring progress, and unclear collaboration with other care providers. Conclusions: This study contributed by reframing malnutrition as a dynamic, multi-actor patient journey in which assistive technology can play a supportive role at different phases, supporting collaboration, facilitating relationship-building, and involving the larger care network. Full article

Human factors remain the dominant contributor to cybersecurity incidents, yet awareness training produces only moderate and often non-durable behaviour change, and most evaluated programs are either purely digital or evaluated only at the framework level. This study addresses two gaps: the scarcity of empirical and demographically stratified evidence for multi-modal community-facing awareness programs, and the lack of an explicit account of how artificial intelligence (AI) should be integrated into such programs rather than treated as an optional add-on. We evaluate Cyber4Me, a four-stage individual-awareness intervention (community roadshows, structured training, a hackathon, and a physical–digital escape room) that is wrapped in a cross-cutting AI adaptive layer built entirely on structured performance and behaviour data baseline competency tiering, awareness–behaviour gap detection, predictive early-warning, and personalised recommendation, with no reliance on free text. Using a single-group pre–post design with 130 participants in the UK Black Country region and a multi-dimensional Likert instrument, all four competency domains (confidence, familiarity, GDPR knowledge, incident-response preparedness) improved significantly (paired-t, all $p<0.001$; large within-participant effects, Cohen’s $d\ge 1.0$). Improvement was strongly moderated by demographics: older adults gained most in familiarity, undergraduates in confidence, and lower-education participants in regulatory knowledge. The contributions are as follows: transparent and demographically stratified pre–post evidence for a multi-modal awareness program with effect sizes reported; a fitness-for-purpose comparison against contemporary analogs (KnowBe4, Proofpoint, CyberPatriot, iCAT, CAT-RWE, GPT-CSAT, escape-room studies) that treats AI as a first-class design dimension; and an articulated AI integration architecture for the framework, demonstrated offline on the cohort using only structured performance and behaviour data (no free text). In this architecture, a gradient-boosted classifier assigns participants to three baseline competency tiers at 93.1% cross-validated accuracy; these tiers differ sharply in measured improvement (ANOVA $F=68.8$, $p<0.001$; Foundational $+1.79$ vs. Applied $+0.30$ scale points), an awareness–behaviour gap segment is detected and predicted from intake signals alone (AUC $=0.73$), and a recommender routes participants to personalised follow-on tracks. As the design is single-group and self-reported, results are reported as evidence of within-participant change associated with the intervention rather than as a causal efficacy estimate, and the AI layer is demonstrated for feasibility rather than being evaluated as a separate trial arm; the scope is explicitly individual security awareness and behaviour, not technical network, IIoT, or cloud security. Full article

Access to authentic clinical learning experiences is often limited for undergraduate Health Sciences students. Immersive technologies such as 360-degree video may help bridge this gap, yet evidence regarding their use in home care education and Problem-Based Learning (PBL) remains scarce. To address this gap, we used a Design-Based Research (DBR) approach to develop and implement a 360-degree video-based home care learning experience and evaluated students’ perceptions of the video, VR headsets, and associated educational formats across three curricular tracks. The experiences of 251 undergraduate Health Sciences students across three different tracks (Policy, Mental Health and Digital) at Maastricht University were studied. Each track offered a different educational format using the 360-degree video as part of its Problem-Based Learning (PBL) curriculum. Students responded once to a combination of self-developed and standardized questionnaires, which included subscales from the Technology Acceptance Model 3 (TAM3) and the Video Transportation Scale (VTS). A DBR approach facilitated the iterative development and implementation of a 360-degree video-based home care learning experience embedded within a Problem-Based Learning curriculum. The intervention was successfully integrated across three tracks without compromising key PBL principles. Students generally perceived the 360-degree video and associated educational formats positively, particularly appreciating the opportunities for interaction and contextualized learning. The findings suggest that immersive 360-degree video delivered through VR headsets is a feasible and acceptable educational approach for undergraduate Health Sciences students and may provide meaningful exposure to clinical practice when access to placements is limited. Full article

As hybrid work arrangements become more established in organisations, the need for effective design and implementation strategies has grown significantly. Evidence indicates that employee wellbeing and engagement in hybrid work environments are declining and this presents a critical challenge for human resource management (HRM) professionals. This presents HRM professionals with a critical imperative of improving wellbeing, while maintaining engagement and productivity at work. This aligns closely with the United Nations’ 17 Sustainable Development Goals, particularly those that promote wellbeing and decent work. Through a systematic synthesis of 78 studies, this research investigates the key determinants of employee engagement and wellbeing in hybrid work contexts. The conceptual framework for this study is grounded in existing theoretical perspectives from the Job Demands–Resources model, Saks Frameworks and wellbeing perspective presented by Guest. The analysis identifies five critical factors that influence engagement and wellbeing outcomes in hybrid work, accompanied by evidence-based propositions for practice. These recommendations encompass: establishing well-equipped workspaces with appropriate flexibility in both location and time; developing organisational culture and leadership through enhanced communication and collaboration mechanisms; strategically allocating jobs and tasks whilst fostering effective networks and collaboration tools and implementing targeted training interventions to mitigate technostress and burnout associated with digital workloads. We advocate for future research to develop comprehensive models, frameworks and wellbeing interventions to guide HRM professionals in addressing these challenges at both the local and global levels. Full article

Urban historic districts often present archaeological sites and historic buildings in a fragmented way, posing significant challenges for public understanding and enhancing heritage value. Solely physical conservation fails to fully communicate their cultural significance, while excessive commercialization often results in the erosion of cultural authenticity and the displacement of local communities. Drawing from cultural capital theory in sociology and cultural economics, this study redefines historical districts as sustainable urban cultural capital, comprising habituated, objectified, and institutionalized components. A Value Chain Model of Cultural Capital (VCMCC) is developed, consisting of three stages: cultural resource excavation, cultural asset cultivation, and cultural capital management. This model aims to empower heritage adaptive reuse and foster synergy between cultural heritage and economic development. Utilizing an embedded single-case design with longitudinal ethnography, the research focuses on the Western Han Archaeological Sites Historical District (WHAS HD) in Hanzhong, China. It involves multiple rounds of mixed-data collection from 2023 to 2025, on which design-based research is performed. This study operationalizes VCMCC through a series of spatially and socially grounded strategies. In the cultural resource excavation stage, superior resources are identified through a systematic review of historical archives, archaeological reports, and local gazetteers, along with surveys of architectural remains and spatial mapping. In the cultural asset cultivation stage, these resources are transformed into experiential and communicable cultural assets via a “one courtyard, one strategy” approach for activating courtyard functions, developing dual-theme heritage routes, and deploying digital interpretation tools. In the cultural capital management stage, a multi-stakeholder community committee is established, and binding institutional safeguards are integrated to ensure sustainable heritage adaptive reuse. Concurrently, a baseline indicator system covering three dimensions, cultural, social, and economic benefits, is developed to provide benchmarks for future post-intervention benefit evaluation and verification. The proposed and implemented VCMCC model translates cultural capital theory from an abstract explanatory framework into an actionable pathway for heritage adaptive reuse, offering theoretical and methodological guidance for the adaptive reuse of similar small and medium-sized historic districts. Full article