Search Results (671)

This study aims to understand the meaning nursing professionals attribute to their lived experiences of providing humanized care within a public hospital setting. Grounded in Jean Watson’s theory of human caring, the research adopts a qualitative, descriptive phenomenological design to capture the perceptions and emotions of nurses regarding humanized care. Data were collected through semi-structured interviews with nine experienced nurses, selected through purposive sampling. The interviews, conducted virtually between July and December 2024, were analyzed using Colaizzi’s method and supported by Atlas.ti software. Four main thematic categories emerged: institutional health policies, professional image and identity, strengths and challenges in care, and essential competencies for humanized care. The findings highlight the critical role of empathy, cultural sensitivity, ethical commitment, and emotional presence in delivering compassionate care. Participants emphasized that, beyond clinical procedures, humanized care requires relational and contextual sensitivity, often hindered by institutional limitations and excessive administrative burdens. The study concludes that nursing professionals are key agents in promoting ethical, empathetic, and culturally respectful practices that humanize health services. These insights offer valuable contributions for designing policies and training strategies aimed at strengthening humanized care as a cornerstone of quality healthcare systems. Full article

Deep Federated Learning (DFL) revolutionizes machine learning (ML) by enabling collaborative model training across diverse, decentralized data sources without direct data sharing, emphasizing user privacy and data sovereignty. Despite its potential, DFL’s application in sensitive sectors is hindered by challenges in meeting rigorous standards like the GDPR, with traditional setups struggling to ensure compliance and maintain trust. Addressing these issues, our research introduces an innovative Zero Trust-based DFL architecture designed for GDPR compliant systems, integrating advanced security and privacy mechanisms to ensure safe and transparent cross-node data processing. Our base paper proposed the basic GDPR-Compliant DFL Architecture. Now we validate the previously proposed architecture by formally verifying it using High-Level Petri Nets (HLPNs). This Zero Trust-based framework facilitates secure, decentralized model training without direct data sharing. Furthermore, we have also implemented a case study using the MNIST and CIFAR-10 datasets to evaluate the existing approach with the proposed Zero Trust-based DFL methodology. Our experiments confirmed its effectiveness in enhancing trust, complying with GDPR, and promoting DFL adoption in privacy-sensitive areas, achieving secure, ethical Artificial Intelligence (AI) with transparent and efficient data processing. Full article

In an era where digitalization shapes economic and social landscapes, the intersection of digital skills, ethics, and integrity plays a crucial role in understanding the vulnerability of youth classified as NEET (Not in Education, Employment, or Training). This study explores how risky internet use and digital skill gaps contribute to socio-economic exclusion, integrating a multivariate and spatial approach to assess regional disparities in Europe. This study adopts a systems thinking perspective to explore digital exclusion as an emergent outcome of multiple interrelated subsystems. The research employs logistic regression, Principal Component Analysis (PCA) with Promax rotation, and Geographic Information Systems (GIS) to examine the impact of digital behaviors on NEET status. Using Eurostat data aggregated at the country level for the period (2000–2023) across 28 European countries, this study evaluates 24 digital indicators covering social media usage, instant messaging, daily internet access, data protection awareness, and digital literacy levels. The findings reveal that low digital skills significantly increase the likelihood of being NEET, while excessive social media and internet use show mixed effects depending on socio-economic context. A strong negative correlation between digital security practices and NEET status suggests that youths with a higher awareness of online risks are less prone to socio-economic exclusion. The GIS analysis highlights regional disparities, where countries with limited digital access and lower literacy levels exhibit higher NEET rates. Digital exclusion is not merely a technological issue but a multidimensional socio-economic challenge. To reduce the NEET rate, policies must focus on enhancing digital skills, fostering online security awareness, and addressing regional disparities. Integrating GIS methods allows for the identification of territorial clusters with heightened digital vulnerabilities, guiding targeted interventions for improving youth employability in the digital economy. Full article

Compassion is a critical competence for university students in the healthcare field when dealing with the suffering of patients and relatives. However, there are no tools that measure compassionate capacity during students’ training. Recently, the Compassion Capacity Scale (CCS) was developed for health professionals, exhibiting good psychometric properties. The aim of this study was to translate, culturally adapt, and validate the CCS for Portuguese university students in the healthcare field. The study was divided into two phases: (1) translation and adaptation of the CCS for Portuguese university students in the healthcare field; (2) validation and analysis of psychometric properties. The CCS-PHS showed good internal consistency (Cronbach’s α = 0.886), temporal stability (rho = 0.703), and content validity (CVI-i = 1). Criterion validity analysis showed strong correlations between all of the CCS-PHS’s dimensions and the chosen reference criteria scale. Construct validity analysis revealed that the CCS-PHS is composed of 17 items, classified into four factors. The differences found in the exploratory factor analysis in relation to the original scale may be due to the differences in the life experiences of healthcare professionals when compared to those of students. Our psychometric analysis suggests that the CCS-PHS is a reliable and valid tool to assess compassionate capacity in healthcare students. Knowing the compassionate competence of students is vital for guiding educational strategies, implementing compassion training programs and evaluating their effectiveness, as well as reinforcing key attitudes and behaviors for humanized and ethical healthcare. Full article

Surgery remains a healthcare intervention with significant risks for patients. Novel technologies can now enhance the peri-operative workflow, with artificial intelligence (AI) and extended reality (XR) to assist with pre-operative planning. This review focuses on innovation in AI, XR and imaging for hepato-biliary surgery planning. The clinical challenges in hepato-biliary surgery arise from heterogeneity of clinical presentations, the need for multiple imaging modalities and highly variable local anatomy. AI-based models have been developed for risk prediction and multi-disciplinary tumor (MDT) board meetings. The future could involve an on-demand and highly accurate AI-powered decision tool for hepato-biliary surgery, assisting the surgeon to make the most informed decision on the treatment plan, conferring the best possible outcome for individual patients. Advances in AI can also be used to automate image interpretation and 3D modelling, enabling fast and accurate 3D reconstructions of patient anatomy. Surgical navigation systems utilizing XR are already in development, showing an early signal towards improved patient outcomes when used for hepato-biliary surgery. Live visualization of hepato-biliary anatomy in the operating theatre is likely to improve operative safety and performance. The technological advances in AI and XR provide new applications in pre-operative planning with potential for patient benefit. Their use in surgical simulation could accelerate learning curves for surgeons in training. Future research must focus on standardization of AI and XR study reporting, robust databases that are ethically and data protection-compliant, and development of inter-disciplinary tools for various healthcare applications and systems. Full article

Background/Objectives: Emotional intelligence has emerged as a key factor in shaping nursing performance and care quality, yet its specific mechanisms and impact within the Greek public healthcare context remain underexplored. This study aimed to investigate the role of emotional intelligence in ethical behavior, crisis management, and the perceived quality of care among nurses working in Greek public hospitals. Methods: A cross-sectional survey was conducted among practicing nurses using validated instruments to assess emotional intelligence, ethical compliance, crisis management skills, and care quality. Data were analyzed using covariance-based structural equation modeling (CB SEM) to examine both direct and indirect relationships among variables. Results: The results indicated that emotional intelligence training had a strong and significant effect on nurses’ ethical behavior and their ability to manage critical situations. However, the direct effect of emotional intelligence on the perceived quality of care was not significant; instead, its influence was mediated through improvements in ethics and crisis management. Conclusions: These findings suggest that the benefits of emotional intelligence in nursing are most evident when integrated with supportive organizational practices and ongoing professional development. Overall, this study highlights the need for comprehensive emotional intelligence training and a supportive workplace culture to enhance ethical standards, resilience, and patient care quality in Greek healthcare settings. Full article

This study explores the potential of Intelligent Geographic Information Systems (GISs) in advancing educational practices through the integration of real-time data models. The objective is to investigate how GIS technology can enhance teaching and learning by providing interactive and dynamic learning environments. The research employs a bibliometric analysis based on the Scopus database, covering the period from 2000 to 2024, to identify key trends, the evolution of GIS applications in education, and their pedagogical impact. Findings reveal that GISs, particularly when incorporating real-time data, enable a more immersive learning experience, facilitate data-driven decision-making, and promote student engagement through project-based learning. However, challenges such as the lack of specialized training for educators and limitations in technological infrastructure remain significant barriers to widespread adoption. The study concludes that Intelligent GISs have the potential to transform education by fostering personalized, interdisciplinary learning and enhancing educational management. It emphasizes the need for further research aimed at developing user-friendly systems and addressing ethical concerns to ensure the benefits of GIS technology are accessible to all students. Future studies should examine the long-term effects of GISs on student outcomes and explore their integration into diverse educational contexts. Full article

Artificial intelligence (AI) holds considerable promise to transform education, from personalizing learning to enhancing teaching efficiency, yet it simultaneously introduces significant concerns regarding ethical implications and responsible implementation. This exploratory survey investigated the perceptions of 376 teachers, university students, and future educators from the University of Salerno area concerning AI integration in education. Data were collected via a comprehensive digital questionnaire, divided into sections on personal data, AI’s perceived impact, its usefulness, and specific applications in education. Descriptive and inferential statistical analyses, including mean, mode, standard deviation, and 95% confidence intervals, were applied to the Likert scale responses. Results indicated a general openness to AI as a supportive tool for personalized learning and efficiency. However, significant reservations emerged regarding AI’s capacity to replace the human role. For instance, 69% of participants disagreed that AI tutors could match human feedback efficiency, and strong opposition was found against AI replacing textbooks (81% disagreement) or face-to-face lessons (87% disagreement). Conversely, there was an overwhelming consensus on the necessity of careful and conscious AI use (98% agreement). Participants also exhibited skepticism regarding AI’s utility for younger learners (e.g., 80% disagreement for ages 0–6), while largely agreeing on its benefit for adult learning. Strong support was observed for AI’s role in providing simulations and virtual labs (89% agreement) and developing interactive educational content (94% agreement). This study underscores a positive inclination towards AI as an enhancement tool, balanced by a strong insistence on preserving human interaction in education, highlighting the need for thoughtful integration and training. Full article

Media organizations are experiencing ongoing transformation, increasingly driven by the advancement of AI technologies. This development has begun to link journalists with generative systems and synthetic technologies. Although newsrooms worldwide are exploring AI adoption to improve information sourcing, news production, and distribution, a gap exists between resource-rich organizations and those with limited means. Since ChatGPT 3.5 was released on 30 November 2022, Greek media and journalists have gained the ability to use and explore AI technology. In this study, we examine the use of AI in Greek newsrooms, as well as journalists’ reflections and concerns. Through qualitative analysis, our findings indicate that the adoption and integration of these tools in Greek newsrooms is marked by the lack of formal institutional policies, leading to a predominantly self-directed and individualized use of these technologies by journalists. Greek journalists engage with AI tools both professionally and personally, often without organizational guidance or formal training. This issue may compromise the quality of journalism due to the absence of established guidelines. Consequently, individuals may produce content that is inconsistent with the media outlet’s identity or that disseminates misinformation. Age, gender, and newsroom roles do not constitute limiting factors for this “experimentation”, as survey participants showed familiarity with this technology. In addition, in some cases, the disadvantages of specific tools regarding qualitative results in Greek are inhibiting factors for further exploration and use. All these points to the need for immediate training, literacy, and ethical frameworks. Full article

Background: Artificial intelligence (AI) is being increasingly promoted as a means to enhance diagnostic accuracy, to streamline workflows, and to improve overall care quality in primary care. However, empirical evidence on how primary care physicians (PCPs) perceive, engage with, and emotionally respond to AI technologies in everyday clinical settings remains limited. Concerns persist regarding AI’s usability, transparency, and potential impact on professional identity, workload, and the physician–patient relationship. Methods: This qualitative study investigated the lived experiences and perceptions of 28 PCPs practicing in diverse outpatient settings across Germany. Participants were purposively sampled to ensure variation in age, practice characteristics, and digital proficiency. Data were collected through in-depth, semi-structured interviews, which were audio-recorded, transcribed verbatim, and subjected to rigorous thematic analysis employing Mayring’s qualitative content analysis framework. Results: Participants demonstrated a fundamentally ambivalent stance toward AI integration in primary care. Perceived advantages included enhanced diagnostic support, relief from administrative burdens, and facilitation of preventive care. Conversely, physicians reported concerns about workflow disruption due to excessive system prompts, lack of algorithmic transparency, increased cognitive and emotional strain, and perceived threats to clinical autonomy and accountability. The implications for the physician–patient relationship were seen as double-edged: while some believed AI could foster trust through transparent use, others feared depersonalization of care. Crucial prerequisites for successful implementation included transparent and explainable systems, structured training opportunities, clinician involvement in design processes, and seamless integration into clinical routines. Conclusions: Primary care physicians’ engagement with AI is marked by cautious optimism, shaped by both perceived utility and significant concerns. Effective and ethically sound implementation requires co-design approaches that embed clinical expertise, ensure algorithmic transparency, and align AI applications with the realities of primary care workflows. Moreover, foundational AI literacy should be incorporated into undergraduate health professional curricula to equip future clinicians with the competencies necessary for responsible and confident use. These strategies are essential to safeguard professional integrity, support clinician well-being, and maintain the humanistic core of primary care. Full article

This research analyzed university students’ perceptions of the use of generative artificial intelligence (hereafter Gen-AI) in a higher education context. Specifically, it addressed the potential benefits and challenges related to the application of these web-based resources. A mixed method was adopted and the sample consisted of 407 teacher training students enrolled in the Early Childhood and Primary Education Degrees in the Region of Murcia in Spain. The results indicated a clear recognition of the relevance of these technological tools for teaching and learning. Respondents highlighted the potential to engage them in academic tasks, increase their motivation, and personalize their learning pathways. However, participants identified some challenges related to technology dependency, ethical issues, and privacy concerns. By understanding learners’ beliefs and assumptions, educators and educational administrations can adapt Gen-AI according to learners’ needs and preferences to improve their academic performance. In learning practice, these adaptations could involve evidence-based interventions, such as AI literacy modules or hybrid assessment frameworks, to translate findings into practice. In addition, it is necessary to adjust materials, methodologies, and the assessment of the academic curriculum to facilitate student learning and ensure that all students have access to quality education and the adequate development of digital skills. Full article

The evolution of Industry 4.0 and the emerging paradigm of Industry 5.0 have introduced disruptive technologies that are reshaping modern manufacturing environments. Among these, Digital Twin (DT) and Industrial Metaverse (IM) technologies are increasingly recognized for their potential to enhance Occupational Health and Safety (OHS). However, a comprehensive understanding of how these technologies integrate to support OHS in manufacturing remains limited. This study systematically explores the transformative role of DT and IM in creating immersive, intelligent, and human-centric safety ecosystems. Following the PRISMA guidelines, a Systematic Literature Review (SLR) of 75 peer-reviewed studies from the SCOPUS and Web of Science databases was conducted. The review identifies key enabling technologies such as Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), Internet of Things (IoT), Artificial Intelligence (AI), Cyber-Physical Systems (CPS), and Collaborative Robots (COBOTS), and highlights their applications in real-time monitoring, immersive safety training, and predictive hazard mitigation. A conceptual framework is proposed, illustrating a synergistic digital ecosystem that integrates predictive analytics, real-time monitoring, and immersive training to enhance the OHS. The findings highlight both the transformative benefits and the key adoption challenges of these technologies, including technical complexities, data security, privacy, ethical concerns, and organizational resistance. This study provides a foundational framework for future research and practical implementation in Industry 5.0. Full article

The integration of extended reality (XR) technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), is transforming forensic investigation by empowering processes such as crime scene reconstruction, evidence analysis, and professional training. This manuscript presents a systematic review of technological advances in XR technologies developed and employed for forensic investigation, their impacts, challenges, and prospects for the future. A systematic review was carried out based on the PRISMA^® methodology and considering articles published in repositories and scientific databases such as SCOPUS, Science Direct, PubMed, Web of Science, Taylor and Francis, and IEEE Xplore. Two observers carried out the selection of articles and a Cohen’s Kappa coefficient of 0.7226 (substantial agreement) was evaluated. The results show that XR technologies contribute to improving accuracy, efficiency, and collaboration in forensic investigation processes. In addition, they facilitate the preservation of crime scene data and reduce training costs. Technological limitations, implementation costs, ethical aspects, and challenges persist in the acceptability of these devices. XR technologies have significant transformative potential in forensic investigations, although additional research is required to overcome current barriers and establish standardized protocols that enable their effective integration. Full article

Formative research is an essential component of higher education, aimed at developing research competencies in students, with an emphasis on critical thinking, academic autonomy, and analytical capacity. Its purpose is not the production of original knowledge but the systematic preparation for research activity. Within this framework, the objective of this study is to analyze how conceptual appropriation, which encompasses theoretical, methodological, procedural, and normative knowledge, is related to students’ perceived research skills. This study is grounded in the imperative of fostering higher education that cultivates critical, autonomous, and ethically responsible researchers. For this purpose, a quantitative methodology was used, with a non-experimental and correlational design, applying a census sampling to 10,536 students from a higher education institution. Data were collected through a structured survey on conceptual appropriation and perceived research skills. After the removal of inconsistent records, the data were processed statistically using non-parametric tests, particularly Spearman’s correlation, due to the non-normal distribution of the variables. The results reveal strong and significant correlations between conceptual appropriation and key research skills such as hypothesis formulation, critical thinking, and motivation for research, demonstrating that greater conceptual mastery promotes a more solid and engaged research training. These findings reinforce the need to systematically and progressively integrate research content into the university curriculum, fostering an authentic, reflective, and contextualized education. Full article

Generative AI (GenAI) tools, including ChatGPT, Microsoft Copilot, and Google Gemini, are rapidly reshaping higher education by transforming how students, educators, and researchers engage with learning, teaching, and academic work. Despite their growing presence, the adoption of GenAI remains inconsistent, largely due to the absence of universal guidelines and trust-related concerns. This study examines how trust, defined across three key dimensions (accuracy and relevance, privacy protection, and nonmaliciousness), influences the adoption and use of GenAI tools in academic environments. Using survey data from 823 participants across different academic roles, this study employs multiple regression analysis to explore the relationship between trust, user characteristics, and behavioral intention. The results reveal that trust is primarily experience-driven. Frequency of use, duration of use, and self-assessed proficiency significantly predict trust, whereas demographic factors, such as gender and academic role, have no significant influence. Furthermore, trust emerges as a strong predictor of behavioral intention to adopt GenAI tools. These findings reinforce trust calibration theory and extend the UTAUT2 framework to the context of GenAI in education. This study highlights that fostering appropriate trust through transparent policies, privacy safeguards, and practical training is critical for enabling responsible, ethical, and effective integration of GenAI into higher education. Full article