Search Results (609)

Pediatric palliative care (PPC) aims to enhance the quality of life of children with life-limiting conditions and their families through individualized, interdisciplinary support. Among this population, children with neurological diseases represent a substantial and growing group, often facing prolonged disease courses, cognitive impairment, and high prognostic uncertainty. Effective communication is central to PPC; however, it remains deeply influenced by cultural, religious, and spiritual frameworks that shape family perceptions of illness, suffering, and decision-making. This narrative review explores communication strategies in PPC, with a specific focus on children with neurological conditions, highlighting conceptual foundations, cross-cultural variations, and emerging best practices. Key findings highlight the importance of culturally humble approaches, family-centered communication models, and structured tools, such as co-designed advance care planning and dignity therapy, to enhance communication. Additionally, the review highlights the presence of ethical and interdisciplinary challenges, particularly in neonatal and neurology settings, where misaligned team messaging and institutional hesitancy may compromise trust and timely referral to palliative care. Future research, policy, and clinical education priorities should advocate for models that are inclusive, ethically grounded, and tailored to the unique trajectories of neurologically ill children. Integrating cultural competence, team alignment, and family voices is essential for delivering equitable and compassionate PPC across diverse care settings. Full article

Floods pose a growing threat globally, causing tragic loss of life, billions in economic damage annually, and disproportionately affecting socio-economically vulnerable populations. This paper aims to improve flood-risk communication for community leaders by exploring the application of artificial intelligence. We categorize U.S. flood information sources, review communication modalities and channels, synthesize the literature on community leaders’ roles in risk communication, and analyze existing technological tools. Our analysis reveals three key challenges: the fragmentation of flood information, information overload that impedes decision-making, and the absence of a unified communication platform to address these issues. We find that AI techniques can organize data and significantly enhance communication effectiveness, particularly when delivered through infographics and social media channels. Based on these findings, we propose FLAI (Flood Language AI), an AI-driven flood communication platform that unifies fragmented flood data sources. FLAI employs knowledge graphs to structure fragmented data sources and utilizes a retrieval-augmented generation (RAG) framework to enable large language models (LLMs) to produce contextualized narratives, including infographics, maps, and cost–benefit analyses. Beyond flood management, FLAI’s framework demonstrates how AI can transform public service data management and institutional AI readiness. By centralizing and organizing information, FLAI can significantly reduce the cognitive burden on community leaders, helping them communicate timely, actionable insights to save lives and build flood resilience. Full article

Today, ‘social sustainability’ is a key feature of many organisations’ environmental, social, and governance strategies, as well as underpinning sustainable development goals. The term refers to the implementation of targets such as reduced societal inequalities, the promotion of social well-being, and the practice of positive community relations. Building a meaningful, accountable, and quantifiable evidence-base from which to translate these high-level concepts into tangible and achievable goals is, however, challenging. The complexities of measuring social capital—often described as a building block of social sustainability—have been documented. The challenge lies in measuring the person, group, or collective in interaction with the context under investigation, whether that be a climate goal, an institution, or a national policy. Social identity theory is a social psychological approach that articulates the processes through which an individual internalises the values, norms, and behaviours of their contexts. Levels of social identification—a concept capturing the state of internalisation—have been shown to be predictive of outcomes as diverse as communication and cognition, trust and citizenship, leadership and compliance, and health and well-being. Applying this perspective to the articulation and measurement of social sustainability provides an opportunity to build an empirical approach with which to reliably translate this high-level concept into achievable outcomes. Full article

Background/Objectives: Predicting comprehensive patient characteristics is essential for optimal individualized rehabilitation plans for acute stroke patients. However, current models primarily predict single outcomes. This study aimed to assess the applicability of latent class analysis (LCA) in rehabilitation practice by identifying comprehensive characteristics and associated predictors in acute stroke patients. Methods: We conducted a retrospective observational study using the Japan Association of Rehabilitation Database, including 10,270 stroke patients admitted to 37 acute-care hospitals between January 2005 and March 2016. Patients were classified using LCA based on outcomes at discharge, including Functional Independence Measure (FIM), National Institutes of Health Stroke Scale (NIHSS) subscales for upper-extremity function, length of hospitalization, and discharge destination. Predictor variables at admission included age, FIM scores, NIHSS subscales for upper-extremity function, stroke type, and daily rehabilitation volume. Results: 6881 patients were classified into nine distinct classes (class size: 4–29%). Class 1, representing the mildest cases, was noted for independent ambulation and good upper limb function. Class 2 comprised those with the most severe clinical outcome. Other classes exhibited a gradient of severity, commonly encountered in clinical practice. For instance, Class 7 included right-sided paralysis with preserved motor activities of daily living (ADLs) and modified dependence in cognitive functions, such as communication. All predictors at admission were significantly associated with class membership at discharge (p < 0.001). Conclusions: LCA effectively identified unique clinical subgroups among acute stroke patients and demonstrated that key admission variables could predict class membership. This approach offers a promising insight into targeted, personalized rehabilitation practice for acute stroke patients. Full article

This study conducts a systematic qualitative review of empirical research on sense of place within housing contexts, employing the tripartite model of place identity, place attachment, and place dependence. The study employs an expanded model that captures the internal complexity of each indicator by integrating its cognitive, affective, and conative components, which represent the dimensions of human–place interaction. This model conceptualizes sense of place as a multidimensional construct, facilitating thematic synthesis and cross-study comparisons. A structured search of Scopus and Web of Science identified 10 studies that met predefined inclusion criteria. Additionally, eight studies with divergent conceptualizations of sense of place were narratively analyzed to explore the diversity of interpretations across disciplinary perspectives in housing research. The review yields three key findings: (1) The expanded tripartite model provides a framework for understanding the relationships between residents and housing. (2) Sense of place is both a criterion and a catalyst for housing sustainability. (3) The development of a sense of place is influenced by the interaction of physical, spatial, environmental, social, cultural, economic, and institutional housing factors. Sense of place provides insight into how housing becomes home, informing context-dependent strategies that enhance place-based connections and contribute to housing sustainability. Full article

The willingness to pay (WTP) for green energy consumption not only indicates the public’s green energy consumption practices, but also affects the realization of China’s “dual carbon” goals and global green development. Based on data from the 2018 Chinese General Social Survey (CGSS), this study describes the WTP for green energy consumption of Chinese urban and rural residents in the context of “dual carbon”. Moreover, it provides an in-depth interpretation from the perspectives of capital endowment and energy cognition, guided by social practice theory (SPT). This study found that, firstly, the public’s WTP for green energy consumption needs to be strengthened urgently, and the percentage of the refusal to participate group reaches 41.44%, and shows significant urban–rural differences. Compared with rural residents, the proportion and amount of WTP for urban residents are 7.5% and 4.016 CNY/month higher, respectively. Secondly, capital endowment and energy cognition are important influencing factors. Among them, economic capital (β = 0.647, p < 0.01) and cultural capital (β = 0.358, p < 0.05) play a significant role for urban residents, while rural residents depend on the government support cognition of energy (β = 7.678, p < 0.001). Finally, the urban–rural divergence in WTP for green energy consumption mainly stems from the gap in capital endowment, which contributes 29.08%, significantly higher than the contribution of energy cognition (8.34%). Therefore, efforts should be made to enhance the capital endowment levels of urban and rural residents, implement a targeted energy knowledge dissemination system, build a comprehensive government support system, and break down institutional barriers through urban–rural integration to guard against the disadvantages of rural residents. 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

Although career choice is a kind of individual behavior, as the gatekeeper of the discipline, doctoral students’ academic career intention reflects the attractiveness of the academic labor market and determines the sustainable development of academic careers. An analysis of data (N = 1322) from a survey among Chinese doctoral students reveals that (1) environmental factors, such as departmental atmosphere and advisor support, cognitive factors like academic interest and research self-efficacy, as well as behavioral factors including research engagement and publication rates, significantly promote doctoral students’ academic career intentions; (2) female doctoral students and those from prestigious institutions show stronger academic career aspirations; (3) the influence of interest factors on doctoral students’ commitment to an academic career is particularly pronounced, especially in the field of fundamental science; (4) a clear understanding of career paths positively moderates the effect of interest on academic career intentions. Within increasingly severe competition in the global academic labor market, it is necessary to provide more support for doctoral students who are willing to engage in academic careers by enhancing career planning guidance for doctoral students and supporting them in making rational career plans and adequate preparations. Full article

Workforce transformation is one of the most pressing challenges in the AI-driven construction industry, as traditional skilled labour roles are rapidly evolving into more interdisciplinary, digitally enabled positions. This study aims to investigate how AI is fundamentally reshaping skill requirements within the construction sector, to analyse stakeholder perceptions and adaptive responses to workforce transformation, and to explore strategies for optimizing construction workforce development to facilitate the critical transition from traditional “skilled workers” to contemporary “smart talent.” It employs phenomenological qualitative research methodology to conduct in-depth interviews with 20 stakeholders in Chongqing, and uses NVivo 14 to conduct thematic analysis of the data. The findings indicate that AI has penetrated all areas of the construction process and is transforming jobs to more likely be digitalized, collaborative, and multi-faceted. However, significant cognitive disparities and varying adaptive capacities among different stakeholder groups have created structural imbalances within the workforce development ecosystem. Based on these key findings, a four-pillar talent development strategy is proposed, encompassing institutional support, educational reform, enterprise engagement, and group development, while stressing the necessity for systemic-orchestrated coordination to reimagine a smart talent ecosystem. This study advances theoretical understanding of digital transformation within construction labour markets, while offering real pathways and institutional contexts for developing regions that desire to pursue workforce transformation and sustainable industrial development in the AI era. Full article

Generative AI tools are becoming increasingly common in education. They make many tasks easier, but they also raise questions about how students interact with information and whether their ability to think critically might be affected. Although these tools are now part of many learning processes, we still do not fully understand how they influence cognitive behavior or digital maturity. This study proposes a model to help identify different user profiles based on how they engage with AI in educational contexts. The approach combines fuzzy clustering, the Analytic Hierarchy Process (AHP), and explainable AI techniques (SHAP and LIME). It focuses on five dimensions: how AI is used, how users verify information, the cognitive effort involved, decision-making strategies, and reflective behavior. The model was tested on data from 1273 users, revealing three main types of profiles, from users who are highly dependent on automation to more autonomous and critical users. The classification was validated with XGBoost, achieving over 99% accuracy. The explainability analysis helped us understand what factors most influenced each profile. Overall, this framework offers practical insight for educators and institutions looking to promote more responsible and thoughtful use of AI in learning. Full article

Background/Objectives: Childhood cancer leads to significant physical, cognitive, and psychosocial consequences that adversely affect the development and quality of life. Occupational Therapy (OT) has the potential to mitigate these effects. However, its integration into pediatric oncology care in Spain remains limited and underexplored. This study aims to examine the availability, characteristics, and perceived impact of OT services within pediatric oncology units across Spain and to identify key barriers to their implementation. Methods: A descriptive, cross-sectional study using a mixed-methods approach was conducted. An online questionnaire was distributed to healthcare professionals working in pediatric oncology units nationwide. Quantitative data were analyzed using descriptive statistics, Fisher’s exact test, and odds ratios with 95% confidence intervals to explore associations. Effect sizes were calculated using Cramér’s V where applicable. Qualitative responses underwent inductive thematic analysis. Results: A total of 42 hospital centers from 12 autonomous communities participated. Only 16 reported having OT services in pediatric oncology, with notable regional disparities. A significant proportion of respondents were unaware of the integration of OT in their institutions. Identified barriers included lack of resources, insufficient specialized training, and limited institutional recognition of OT. Nonetheless, professionals familiar with OT interventions reported positive outcomes, particularly in improving patients’ functional autonomy, emotional well-being, and social participation. Conclusions: OT remains insufficiently integrated into pediatric oncology care in Spain. To optimize the quality of care, it is essential to address educational, structural, and institutional challenges and promote OT as a key component of multidisciplinary teams. Full article

Biophilic design has emerged as a multidimensional response to growing concerns about health, well-being, and ecological balance in the built environment. Despite its rising prominence, research on the topic remains fragmented across building typologies, user groups, and geographic contexts. This study presents a comprehensive review of the biophilic design literature, employing a hybrid methodology combining structured content analysis and bibliometric mapping. All peer-reviewed studies indexed in the Web of Science and Scopus were manually screened for architectural relevance and systematically coded. A total of 435 studies were analysed to identify key trends, thematic patterns, and research gaps in the biophilic design discipline. This review categorises the literature by methodological strategies, building typologies, spatial scales, population groups, and specific biophilic design parameters. It also examines geographic and cultural dimensions, including climate responsiveness, heritage buildings, policy frameworks, theory development, pedagogy, and COVID-19-related research. The findings show a strong emphasis on institutional contexts, particularly workplaces, schools, and healthcare, and a reliance on perception-based methods such as surveys and experiments. In contrast, advanced tools like artificial intelligence, simulation, and VR are notably underused. Few studies engage with neuroarchitecture or neuroscience-informed approaches, despite growing recognition of how spatial design can influence cognitive and emotional responses. Experimental and biometric methods remain scarce among the few relevant contributions, revealing a missed opportunity to connect biophilic strategies with empirical evidence. Regarding biophilic parameters, greenery, daylight, and sensory experience are the most studied parameters, while psychological parameters remain underexplored. Cultural and climate-specific considerations appear in relatively few studies, and many fail to define a user group or building typology. This review highlights the need for more inclusive, context-responsive, and methodologically diverse research. By bridging macro-scale bibliometric patterns with fine-grained thematic insights, this study provides a replicable review model and valuable reference for advancing biophilic design as an evidence-based, adaptable, and human-centred approach to sustainable architecture. Full article

International students are an important group at German higher education institutions. Yet few studies have considered the psychosocial situation of these students. The present study combines the study demands-resources model (SD-R model) and the acculturation framework to adapt the former to the specific situation of international students, and examines the effects of study demands, institutional resources, individual resources (acculturation orientations, i.e., affective and cognitive orientations towards the home and host country), stress, and engagement on their life satisfaction as one indicator of well-being. We used cross-sectional survey data from 503 international students across more than 20 higher education institutions. Latent structural equation models showed that lower study demands were associated with lower stress and higher student engagement, which in turn predicted greater life satisfaction. Although higher institutional resources also related to increased engagement and, thus, higher life satisfaction, they were unexpectedly linked to increased stress, which was in turn associated with lower life satisfaction. Additionally, the expected positive effect of affective host country orientation on life satisfaction, mediated through perceived stress and engagement, was confirmed. The consideration of acculturation orientations in the SD-R model helps to understand the specific conditions of well-being amongst international students in Germany. Full article

Robotics has emerged as a transformative discipline at the intersection of the engineering, computer science, and cognitive sciences. This state-of-the-art review explores the current trends, methodologies, and challenges in both robotics research and education. This paper presents a comprehensive review of the evolution of robotics, tracing its development from early automation to intelligent, autonomous systems. Key enabling technologies, such as Artificial Intelligence (AI), soft robotics, the Internet of Things (IoT), and swarm intelligence, are examined along with real-world applications in healthcare, manufacturing, agriculture, and sustainable smart cities. A central focus is placed on robotics education, where hands-on, interdisciplinary learning is reshaping curricula from K–12 to postgraduate levels. This paper analyzes instructional models including project-based learning, laboratory work, capstone design courses, and robotics competitions, highlighting their effectiveness in developing both technical and creative competencies. Widely adopted platforms such as the Robot Operating System (ROS) are briefly discussed in the context of their educational value and real-world alignment. Through case studies, institutional insights, and synthesis of academic and industry practices, this review underscores the vital role of robotics education in fostering innovation, systems thinking, and workforce readiness. The paper concludes by identifying the key challenges and future directions to guide researchers, educators, industry stakeholders, and policymakers in advancing robotics as both technological and educational frontiers. Full article