Search Results (1,017)

This paper presents a scientometric review that provides a quantitative perspective on the evolution of Automation in Construction Journal (AICJ) research, emphasizing its developmental paths and emerging trends. The study aims to analyze the journal’s growth and citation impact over time. It also seeks to identify the most influential publications and the cooperation patterns among key contributors. Furthermore, the study explores the journal’s primary research themes and their evolution. Accordingly, 4084 articles were identified using the Web of Science (WoS) database and subjected to a multistep analysis using VOsviewer version 1.6.18 and Biblioshiny as software tools. First, the growth and citation of the publications over time are inspected and evaluated, in addition to ranking the most influential documents. Second, the co-authorship analysis method is applied to visualize the cooperation patterns between countries, organizations, and authors. Finally, the publications are analyzed using keyword co-occurrence and keyword thematic evolution analyses, revealing five major research clusters: (i) foundational optimization, (ii) deep learning and computer vision, (iii) building information modeling, (iv) 3D printing and robotics, and (v) machine learning. Additionally, the analysis reveals significant growth in publications (54.5%) and citations (78.0%) from 2018 to 2023, indicating the journal’s increasing global influence. This period also highlights the accelerated adoption of digitalization (e.g., BIM, computational design), increased integration of AI and machine learning for automation and predictive analytics, and rapid growth of robotics and 3D printing, driving sustainable and innovative construction practices. The paper’s findings can help readers and researchers gain a thorough understanding of the AICJ’s published work, aid research groups in planning and optimizing their research efforts, and inform editorial boards on the most promising areas in the existing body of knowledge for further investigation and development. Full article

Background: Concerns over women’s mental health have intensified globally, especially among mothers managing dual careers and family responsibilities. Positive Psychology Interventions (PPIs), such as gratitude journaling and well-being workshops, have demonstrated promise in enhancing mental health; however, their applicability in Arab contexts remains underexplored. This study aims to investigate the effectiveness of PPIs on mothers’ well-being, gratitude, depression, anxiety, and stress in Saudi Arabia. Methods: This quasi-experimental, one-group pretest–posttest study assessed the effects of a four-week PPI on 37 Saudi working mothers (aged 21–50 years) employed at a private school in Riyadh. The intervention included guided gratitude journaling thrice weekly and two workshops on positive psychology and gratitude. Pre- and post-intervention assessments used validated Arabic versions of the Depression Anxiety Stress Scale (DASS-21), WHO-5 Well-being Index, and Gratitude Questionnaire (GQ-6). Results: Significant improvements were found post-intervention: depression, anxiety, and stress scores decreased (p < 0.001), while well-being and gratitude increased (p = 0.001). However, participants with lower household income (<50,000 SAR) showed less improvement, indicating a potential moderating effect of socioeconomic status. Conclusions: The intervention demonstrated promising short-term improvements in mental health and well-being among Saudi mothers. The findings underscore the importance of culturally appropriate PPIs and highlight the need for further research using controlled, long-term designs. Limitations include the small, non-random sample, absence of a control group, and restriction to a single geographic region. Full article

The integration of artificial intelligence (AI) in education offers novel opportunities to enhance critical thinking while also posing challenges to independent cognitive development. In particular, Human-Centered Artificial Intelligence (HCAI) in education aims to enhance human experience by providing a supportive and collaborative learning environment. Rather than replacing the educator, HCAI serves as a tool that empowers both students and teachers, fostering critical thinking and autonomy in learning. This study investigates the potential for AI to become a collaborative partner that assists learning and enriches academic engagement. The research was conducted during the 2024–2025 winter semester within the Pedagogical and Teaching Sufficiency Program offered by the Audio and Visual Arts Department, Ionian University, Corfu, Greece. The research employs a hybrid ethnographic methodology that blends digital interactions—where students use AI tools to create artistic representations—with physical classroom engagement. Data was collected through student projects, reflective journals, and questionnaires, revealing that structured dialog with AI not only facilitates deeper critical inquiry and analytical reasoning but also induces a state of flow, characterized by intense focus and heightened creativity. The findings highlight a dialectic between individual agency and collaborative co-agency, demonstrating that while automated AI responses may diminish active cognitive engagement, meaningful interactions can transform AI into an intellectual partner that enriches the learning experience. These insights suggest promising directions for future pedagogical strategies that balance digital innovation with traditional teaching methods, ultimately enhancing the overall quality of education. Furthermore, the study underscores the importance of integrating reflective practices and adaptive frameworks to support evolving student needs, ensuring a sustainable model. Full article

Small news media organizations are increasingly reshaping the news media system in Latin America. They are stepping into the role of watchdogs by investigating issues such as corruption scandals that larger outlets sometimes overlook. However, this journalistic work exposes both journalists and their organizations to a range of security threats, including physical violence, legal pressure, and digital attacks. In response, these outlets have developed coping strategies to manage and mitigate such risks. This article presents an exploratory study of the approaches adopted to protect information and data, ensure the safety and well-being of journalists, and maintain organizational continuity. Based on a series of in-depth interviews with leaders of award-winning news organizations for their investigative reporting, the study examines a shift from a competitive newsroom model to a collaborative approach in which information is shared—sometimes across borders—to support investigative reporting and strengthen security practices. We identify strategies implemented by small news organizations to safeguard their journalistic work and propose an integrative model of news safety encompassing the following three areas of security: physical, legal, and digital. This study contributes to the development of the newsafety framework and sheds light on safety practices that support media freedom. Full article

Background: The biological mediators for the epidemiologic overlap between osteoporosis and dementia are unclear. We undertook a scoping review of clinical studies to identify genetic and biological factors linked with these degenerative conditions, exploring the mechanisms and pathways connecting both conditions. Methods: Studies selected (1) involved clinical research investigating genetic factors or biomarkers associated with dementia or osteoporosis, and (2) were published in English in a peer-reviewed journal between July 1993 and March 2025. We searched Medline Ovid, Embase, PsycINFO, the Cochrane Library, the Web of Science databases, Google Scholar, and the reference lists of studies following the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR). Results: Twenty-three studies were included in this review. These explored the role of the APOE polymorphism (n = 2) and the APOE4 allele (n = 13), associations between TREM2 mutation and late onset AD (n = 1), and associations between amyloid beta and bone remodeling (n = 1); bone-related biomarkers like DKK1, OPG, and TRAIL as predictors of cognitive change (n = 2); extracellular vesicles as bone–brain communication pathways (1); and the role of dementia-related genes (n = 1), AD-related CSF biomarkers (n = 1), and parathyroid hormone (PTH) (n = 1) in osteoporosis–dementia pathophysiology. Conclusions: Bone-related biomarkers active in the Wnt/β-Catenin pathway (Dkk1 and sclerostin) and the RANKL/RANK/OPG pathway (OPG/TRAIL ratio) present consistent evidence of involvement in AD and osteoporosis development. Reports proposing APOE4 as a causal genetic link for both osteoporosis and AD in women are not corroborated by newer observational studies. The role of Aβ toxicity in osteoporosis development is unverified in a large clinical study. Full article

Inclusive Education aims to ensure equitable learning opportunities for all students, including those with special educational needs (SEN) and disabilities, by promoting accessible teaching practices and supportive learning environments. Although its importance for fostering the academic and social development of diverse learners has been widely recognized in international policy and research, its practical implementation is still under investigation, particularly within the Greek primary education system. This study investigates (a) Greek primary school teachers’ perspectives, focusing on their attitudes, knowledge, challenges, and perceived needs in Inclusive Education for SEN students and (b) research trends relating to these perspectives, focusing on publication trends and methodological characteristics, through a systematic literature review using the PRISMA methodology. The analysis revealed a shift in Greek primary teachers’ attitudes towards Inclusive Education for SEN students, trending towards neutral or negative responses, alongside limited knowledge, various challenges, and an absence of targeted support mechanisms. The analysis also highlighted chronological gaps between the identified studies in international journals and a variability in methodological approaches and sample characteristics. These insights point to a pressing need for further targeted and ongoing research on Greek primary teachers’ perspectives and professional development initiatives to enable effective and inclusive practices for SEN students in Greek primary education. Full article

Background/Objectives: The role of environmental modifications and design in mitigating behavioural symptoms is increasingly being recognised as a way to address the psychosocial needs of individuals with dementia. This study aims to investigate various nature-based interventions for reducing agitation in people with dementia in long-term residential care environments. Methods: Database searches were conducted on MEDLINE, PsycINFO, Scopus, and Web of Science. A literature search was conducted with the following inclusion criteria: (i) peer-reviewed journal publication written in English; (ii) random controlled trials (RCTs) and quasi-experimental design with results for pre- and post-testing reported; (iii) interventions using natural elements, where the effectiveness of the reduction in agitation was measured using a validated instrument; and (iv) participants aged 65 and older with dementia residing in long-term care facilities. Results: This meta-analysis included 29 studies with 733 participants. The results showed that such interventions had a significant negative mean effect on lowering agitation in this population. Additionally, intervention settings (indoor vs. outdoor) and the presence of social interaction were significant predictors of the effect size for agitation reduction. At the same time, no significant differences in effect size were observed between the types of experiences with nature (indirect vs. direct) or the duration of the interventions. Conclusions: This study demonstrates that, when thoughtfully applied, nature-based interventions can significantly alleviate agitation in patients with dementia residing in long-term residential care facilities. This review lays the groundwork for future research aimed at developing design guidelines and planning strategies to integrate natural elements into dementia-friendly environments effectively. Full article

Background: Femoral neck fractures (FNF) have high mortality rates. Surgical delay likely contributes. Dynamic hip screw (DHS) fixation is common for FNF, and the tip–apex distance (TAD) measures screw position in the femoral head. A TAD >20–25 mm is considered a risk factor for screw cut-out. This study investigated the association between (1) surgical delay and complication/mortality rates within two years post-surgery and (2) TAD and postoperative complications following DHS in FNF. Methods: This retrospective study included 325 FNF patients who underwent DHS osteosynthesis at Regional Hospital Randers, Denmark from 2015–2021. The primary composite outcome included complications measured on radiographs (e.g., screw cut-out, avascular necrosis), reoperation, or death within 2 years. Radiographs were evaluated for TAD and postoperative complications/reoperations. Surgical delay was defined as the time from the diagnostic radiograph to the start of the operation. TAD was measured based on radiographs. Electronic patient journals and national SSN registers were used to assess reoperation and death rates. Results: The mortality rate was 16% within 1 year and 26% within 2 years. The complication rate was 16% within 2 years. The median surgical delay was 7.9 h (IQR 5; 14). Surgical delay was significantly associated with the 1-year mortality rate (p < 0.01), but not with the 1-year complication rate (p = 0.77). Surgical delay was associated with complication rates 2 years post-surgery only for undisplaced fractures, p = 0.046. The median TAD was 16.3 mm (13.8; 18.7); no association with complications <1 year (p = 0.56) or <2 years (p = 0.99) was observed. There were 59/325 patients with TAD >20 mm, six of whom had complications, and 6/59 with TAD >25 mm, none of whom had complications. Conclusions: We report a significant association between surgical delay and mortality rates in FNF, despite surgical delays <24 h. Additionally, there was a significant association between surgical delay and risk of complication/reoperation 2 years post-surgery for undisplaced fractures. No association was found between TAD and complication rates following DHS fixation for FNF; however, only a few TAD outliers were observed. Full article

As artificial intelligence (AI) becomes ubiquitous across various fields, understanding people’s acceptance and trust in AI systems becomes essential. This review aims to identify quantitative measures used to measure trust in AI and the associated studied elements. Following the PRISMA guidelines, three databases were consulted, selecting articles published before December 2023. Ultimately, 45 articles out of 1283 were selected. Articles were included if they were peer-reviewed journal publications in English reporting empirical studies measuring trust in AI systems with multi-item questionnaires. Studies were analyzed through the lenses of cognitive and affective trust. We investigated trust definitions, questionnaires employed, types of AI systems, and trust-related constructs. Results reveal diverse trust conceptualizations and measurements. In addition, the studies covered a wide range of AI system types, including virtual assistants, content detection tools, chatbots, medical AI, robots, and educational AI. Overall, the studies show compatibility of cognitive or affective trust focus between theorization, items, experimental stimuli, and level of anthropomorphism of the systems. The review underlines the need to adapt measurement of trust in the specific characteristics of human–AI interaction, accounting for both the cognitive and affective sides. Trust definitions and measurement could be chosen depending also on the level of anthropomorphism of the systems and the context of application. Full article

This study presents a comprehensive bibliometric analysis of the evolving landscape of data protection in medicine, examining research trends, thematic developments, and scholarly contributions from the 1960s to 2024. By analyzing 2159 publications indexed in the Scopus database using the Bibliometrix R package (v.4.3.2), based on R (v.4.4.3), this paper maps key research areas, leading journals, and international collaboration patterns. Our findings reveal a significant shift in focus over time, from early concerns centered on data privacy and management to contemporary themes involving advanced technologies such as artificial intelligence, blockchain, and big data analytics. This transition reflects the increasing complexity of balancing data accessibility with security, ethical, and regulatory requirements in healthcare. This analysis also highlights persistent challenges, including fragmented research efforts, disparities in global contributions, and the ongoing need for interdisciplinary collaboration. These insights offer a valuable foundation for future investigations into medical data governance and emphasize the importance of ethical and responsible innovation in an increasingly digital healthcare environment. Full article

This study investigates the evolution and prospective directions of big data applications within the global digital economy over the past twelve years. A comprehensive bibliometric analysis was conducted using Biblioshiny and included 752 documents authored by 1748 scholars and published in 416 specialized journals and academic books between 2013 and 2024. The findings reveal that scholarly interest in this area peaked in 2024. Co-occurrence network mapping highlights three dominant thematic trends in the applicability of big data within the digital economy: technological innovations, conceptual frameworks, and the role of China. Influential academic publications—such as Sustainability, PLoS ONE, and the proceedings of the 8th International Conference on Information Technology and Quantitative Management—have played a pivotal role in advancing research in this domain. Moreover, leading institutions, including the University of the Chinese Academy of Sciences, Shenzhen University, and Guizhou University, have emerged as pivotal contributors to advancing research in this field. China is the primary driving force and key player in reshaping the digital economy through big data, a role that is expected to contribute to global technological advancement in the future. Full article

Traffic congestion constitutes a substantial global issue, adversely impacting economic productivity and quality of life, with associated costs estimated at approximately 2% of GDP in various nations. This systematic review investigates the application of machine learning (ML) in traffic congestion forecasting from 2010 to 2024, adhering to the PRISMA 2020 guidelines. A comprehensive search of three major databases (IEEE Xplore, SpringerLink, and ScienceDirect) yielded 9695 initial records, with 115 studies meeting the inclusion criteria following rigorous screening. Data extraction encompassed methodological approaches, ML techniques, traffic characteristics, and forecasting periods, with quality assessment achieving near-perfect inter-rater reliability (Cohen’s $\kappa$ = 0.89). Deep Neural Networks were the predominant technical approach (47%), with supervised learning being the most prevalent (57%). Classification tasks were the most common (42%), primarily addressing recurrent congestion scenarios (76%) and passenger vehicles (90%). The quality of publications was notably high, with 85% appearing in Q1-ranked journals, demonstrating exponential growth from minimal activity in 2010 to 18 studies in 2022. Significant research gaps persist: reinforcement learning is underutilized (8%), rural road networks are underrepresented (2%), and industry–academia collaboration is limited (3%). Future research should prioritize multimodal transportation systems, real-time adaptation mechanisms, and enhanced practical implementation to advance intelligent transportation systems (ITSs). This review was not registered because it focused on mapping the research landscape rather than intervention effects. Full article

Although open innovation is not novel within the business sector, it has recently garnered increasing scholarly interest. However, empirical investigations applying this concept to the tourism industry remain scarce. Despite tourism being one of the most significant contributors to the global economy, it continues to face persistent challenges, including political standpoints. Within this context, implementing open innovation emerges as a potentially transformative strategy. This study examines the application of open innovation to the tourism industry. Drawing upon a detailed analysis of 35 peer-reviewed articles retrieved from the Scopus database, the study adopts the PRISMA methodology to ensure methodological rigor and transparency. Articles were retrieved using a predefined search string: “Open innovation” AND “tourism industry” OR “tourism” OR “hospitality” OR “hotels” OR “leisure”. The selection process followed the PRISMA guidelines and included only peer-reviewed journal articles in English within Business and Economics. The findings reveal that open innovation enables stakeholder collaboration, supports service and experience co-creation, and facilitates digital and organizational transformation across diverse tourism contexts. The analysis shows that recent contributions in this field tend to converge around four key thematic areas: the role of open innovation in enhancing destination branding and experiential value; the importance of stakeholder collaboration and co-creation; the internal dynamics of employee empowerment and innovation culture within tourism firms; and the strategic use of digital technologies to drive transformation and resilience in the face of industry challenges. Full article

This study investigates how pre-service Earth science teachers used ChatGPT in designing lessons based on the 5E instructional model and what educational opportunities and challenges emerged. As generative AI tools gain traction in education, understanding their integration into science lesson planning is increasingly important. Eight pre-service teachers from a South Korean university participated in a four-week instructional design project. They developed 5E-aligned Earth science lessons while interacting with ChatGPT for idea generation, explanation, activity development, and assessment. Data sources included lesson plans, ChatGPT interaction logs, reflective journals, and interviews. Thematic analysis was used to examine instructional uses of AI and the adaptations required during the process. Findings showed that ChatGPT supported different phases of the 5E model—providing metaphors and analogies in Engage, activity ideas in Explore, draft explanations in Explain, task prompts in Elaborate, and assessment questions in Evaluate. However, participants frequently revised or rejected AI-generated content to match inquiry goals, student readiness, and curriculum standards. The study highlights the importance of pedagogical reasoning in AI-supported lesson design. It contributes to the growing literature on teacher education and AI by offering a phase-specific view of GenAI use and underscoring the instructional mediation needed for effective application. Full article

This research examined the domain of intelligent transportation systems (ITS) by analyzing the impact of scholarly work and thematic prevalence, as well as focusing attention on vehicles, their technologies, cybersecurity, and related scholarly technologies. This was performed by examining the scientific literature indexed in the Scopus database. This study analysed 2919 documents published between 2018 and 2025. The findings indicated that the highest and most significant journal was derived from IEEE Transactions on Vehicular Technology, with significant standing to the growth of communication and computing on vehicles with edge computing and AI optimization of vehicular systems. In addition, important PST research conferences highlighted the growing interest in academic research in cybersecurity for vehicle networks. Sensor networks, pose forensics, and privacy-preserving communication frameworks were some of the significant contributing fields marking the significance of the interdisciplinary nature of this research. Employing bibliometric analysis, the literature illustrated the multiple channels integrating knowledge creation and innovation in ITS through citation analysis. The outcome suggested an increasingly sophisticated research area, weighing technical progress and increasing concern about security and privacy measures. Further studies must investigate edge computing integrated with AI, advanced privacy-preserving linguistic protocols, and new vehicular network intrusion detection systems. Full article