Search Results (4,384)

The emergence of generative AI has led to significant transformations, reshaping media organizations’ workflows and facilitating new forms of participation in the news. This scoping review aims to map the existing literature on the role of generative AI in enhancing audience participation and engagement in journalism. It investigates the theories and methods employed in relevant studies, emerging areas of focus and AI applications used by media organizations to foster audience involvement with the news. The data collection was conducted using online sources (Scopus, EBSCO, ProQuest, and Google Scholar) and a total of 30 studies, published between 2022 and 2024, were selected based on the following criteria: English-language, peer-reviewed, and (hybrid) open-access publications relevant to the research objectives and aligned to the search keywords. The results reveal different theoretical and empirical approaches to studying generative AI in journalism, emphasizing emerging focus areas regarding the adoption of relevant tools and the legal and ethical challenges associated with the credibility of news content. Additionally, generative AI applications in journalism primarily serve to facilitate participation and engagement through personalization, accessibility and interactive storytelling. Lastly, this study highlights the potential of generative AI to enhance audience participation in the news, underscoring the ethical and practical challenges it poses as well as existing research gaps, setting the stage for further research. Full article

This study empirically examines how information technology (IT) governance and digital financial transformation interact to influence economic sustainability performance. The research instrument used in the current study is a questionnaire survey. The data were collected from different government authorities in Oman. The study used convenience and snowball sampling to collect the data. Online questionnaire platforms, such as Google Forms, were used to collect data for the current study. The data collected for the current study were from 104 respondents. The results indicate that IT governance has a significant positive effect on digital financial transformation. Further, digital financial transformation has effectively and significantly enhanced the level of economic sustainability performance. However, IT governance does not have a direct effect on economic sustainability performance; rather, it has an indirect effect on economic sustainability performance through the mediating effect of digital financial transformation. These findings provide actionable implications for policymakers and practitioners to enhance awareness and integration of governance across different aspects in the context of digital financial transformation. The present study contributes to the literature and offers a unique perspective to the existing body of knowledge by highlighting the importance of IT governance as a key driver for digital financial transformation and economic sustainability performance. Full article

Background/aim: Medical students often face intense pressure to excel, which can lead to imposterism, characterized by persistent self-doubt and fear of being exposed as inadequate, alongside high levels of perfectionism. This study aims to assess the prevalence of imposterism and perfectionism among medical students in Saudi Arabia and explore their potential implications for student well-being. Methods: A cross-sectional analytical study was conducted between October and December 2024 among female medical students in Saudi Arabia. Data were collected via an online survey, which included demographic questions, the validated Arabic versions of the Clance Impostor Phenomenon Scale (Ar-CIPS), the short form of the Big Three Perfectionism Scale (BTPS-SF), and the General Self-Efficacy Scale (GSES). Results: A total of 265 medical students (mean age 20.96 ± 1.44 years) participated. Most reported a monthly income of less than 2000 SR, and the majority had a GPA above 4.5. A 74.3% expressed moderate impostor experiences. The BTPS-SF revealed the highest scores in self-critical perfectionism, followed by narcissistic and rigid perfectionism. Higher impostor scores were significantly associated with greater perfectionism and lower self-efficacy (p < 0.05). In multivariable analysis, BTPS-SF scores positively predicted CIPS scores (β = 0.52, p < 0.001), whereas GSE scores predicted lower CIPS scores (β = −0.47, p = 0.001). Conclusions: This study revealed a high prevalence of impostor phenomenon and perfectionism among female medical students, with self-critical perfectionism being the most prominent. Imposterism was significantly associated with higher perfectionism and lower self-efficacy. Full article

Introduction: The anonymisation of Personal Data (PD) and its release as Open Data (OD) hold considerable potential for innovation across health, research, public administration, and the economy. However, practical experiences regarding data anonymisation and OD publication remain underexplored in Germany. This study empirically investigates the current state of anonymised data practices, the barriers to implementation, and the desired support mechanisms for publishing formerly PD as OD. Methods: Embedded in a mixed-methods approach, this cross-sectional study examines research interest in the collection, processing, and use of anonymised data, as well as potential barriers and support services for the anonymisation and publication of former PD. A nationwide online survey was conducted in October–November 2024 via LimeSurvey. A total of 215 responses were included in the descriptive analysis. Results: The findings indicate limited experience with PD anonymisation and OD publication across industries. The potential added value of these processes was often not fully recognised, and data-handling responsibilities were rarely standardised. Data collectors, data protection officers, and IT departments were identified as the most frequently involved parties in these processes. Technical and educational support were the most desired forms of assistance. Discussion: To foster broader OD utilisation, stakeholders require comprehensive support. According to the sample, specific training and further education on the anonymisation and publishing process, as well as the desired software, are most important. Developing standardised process descriptions that integrate ethical and legal considerations, supported by national networks or governmental institutions, could significantly enhance the responsible and effective use of anonymised OD in Germany. Full article

The aim of this study is to analyze how public and private museums adopt digital innovations and to evaluate their contribution to sustainability strategies. The study explores the reasons for implementing digital innovation in museums, how digital innovation contributes to museums’ sustainability, and how museums’ governance model (state-funded or private) influences their capacity for digital innovation and sustainability. The analysis uses a multiple-case study in Lithuania, focusing on the following three museums in Vilnius: the state-funded Lithuanian National Museum, the privately managed MO Museum, and the Lithuanian Art Centre TARTLE. Empirical insights come from semi-structured interviews with museum representatives. Data are collected through online interaction and included in the study dataset. The findings show a clear tendency among museums to adopt digital innovations both to make the visitor experience more interactive and immersive, and to enhance internal management. The results suggest that the adoption of such innovations depends less on the museum’s form (public or private) and more on its size and related financial capacities. Large museums—whether public or private—have more financial capacity to implement digital innovations than smaller ones. Still, the results show that the lack of funds for technological innovations does not prevent museums from achieving sustainability. This research contributes to the field of sustainability by reviewing the scientific literature on the aspects of sustainability (economic, social, environmental, cultural, communicative) in museums’ digital innovation, and by offering exploratory insights from the Lithuanian context into the strategies that museums use to implement digital innovation and promote sustainable development. Full article

Background/Objectives: Seasonal influenza is a global public health issue, and influenza vaccination is the most effective preventive measure. Nursing students are at a higher risk of contracting it due to clinical exposure. However, vaccination uptake among nursing students remains low. This study examines seasonal influenza vaccination uptake rates and the predictors of nursing students’ willingness to receive this vaccine. Methods: A cross-sectional online study was conducted using a well-validated questionnaire in order to collect data from a convenience sample of nursing students in Hong Kong from early November to early December 2024. Results: Out of the 461 valid responses received, 67.5% were from females, with a mean age of 20.53 (SD = 2.16) years. Vaccination history was diverse: 34.3% reported that they underwent influenza vaccination in the most recent season, 49.7% reported that they were vaccinated one to two times over the preceding five years, and only 5% reported that they undergo vaccination annually. A logistic regression model showed that the respondents who had been vaccinated against influenza in the most recent years (OR = 2.881, 95% CI: 1.773–4.680) had been vaccinated against influenza 1–2 times (OR = 3.239, 95% CI: 1.750–5.993), had been vaccinated 3–4 times (OR = 3.984, 95% CI: 1.773–8.957), had been vaccinated every year (OR = 10.353, 95% CI: 3.025–35.436) in the past five years, and had a higher score of perceived susceptibility (OR = 2.244, 95% CI: 1.302–3.867) were more likely to intend to be vaccinated with an influenza vaccine in the coming year. Conclusions: Annual seasonal influenza vaccination rates among nursing students remain low, though they have improved. We recommend that the Hong Kong government, healthcare organizations, and universities develop effective strategies for promoting annual seasonal influenza vaccination to safeguard both patients’ health and the health of future nursing professionals. Full article

Digital transformation in government services represents a strategic shift that leverages digital technologies to enhance efficiency, accessibility, convenience, and user-centricity. In the wake of the COVID-19 pandemic, many governments accelerated the digitisation of services to support remote access and social distancing. Governments typically progress from digitisation (converting physical processes into digital formats) to digitalisation (automating service delivery and improving process efficiency), and ultimately to full digital transformation, where services are completed instantly and entirely online. However, varying levels of maturity across countries influence service outcomes differently, and indicators related to service quality, convenience, and security remain underexamined, particularly in developing contexts. This study addresses these gaps by examining Kuwait’s progress along the digitalisation–digital transformation continuum. It investigates current trends and user preferences in the use of digital government services based on empirical quantitative data collected from users in Kuwait. Specifically, the research objectives are fourfold: (i) to identify crucial outcome metrics for the success of digital government services, (ii) to assess user evaluations of these services according to these metrics, (iii) to examine significant differences between digital transformation and digitalisation services, and (iv) to develop and empirically test a model for evaluating digital transformation success. Drawing on established Information Systems’ (ISs’) success perspectives, a customised conceptual model incorporating six outcome metrics in three domains—service-related (user satisfaction, service quality), convenience-related (accessibility, ease of use), and security-related (perceived security, perceived trust)—was developed. A survey of 378 users of digital government services in Kuwait was conducted to compare perceptions across service types using independent-samples t-tests and linear regression analyses. The study found that users primarily accessed government services through smartphones and dedicated applications, highlighting the importance of mobile optimisation, and showed a clear preference for real-time, fully automated services over those requiring extended approval processes. The results indicate that digital transformation services significantly outperform digitalisation services across five outcome metrics—satisfaction, service quality, accessibility, ease of use, and perceived security—while trust remains consistent across both. These findings underscore the importance of advancing comprehensive digital transformation to enhance public service delivery. Practical recommendations are provided to support Kuwait’s digital government strategy. Given the purposive sampling and cross-sectional, comparative design, the findings should be interpreted with caution, and future studies are encouraged to apply probability-based sampling and more advanced multivariate techniques (e.g., structural equation modelling) to validate and extend the proposed model. Full article

Background/Objectives: Sleep disturbances, particularly insomnia, are increasingly recognized as important determinants of health. Previous studies have shown bidirectional associations between sleep quality and obesity. Limited evidence exists on the modifying role of age in the relationship between insomnia symptoms and body mass index (BMI) among women. This study aimed to evaluate the association between insomnia symptoms and BMI in women, with a specific focus on the potential effect of age. Methods: A cross-sectional study was conducted among 72 female nursing students aged 21–48 years. Data were collected via an online questionnaire including demographic, occupational, and anthropometric variables, as well as the Athens Insomnia Scale (AIS) to assess insomnia symptoms. BMI was calculated based on self-reported weight and height. Logistic and multiple linear regression models were used to evaluate the relationship between AIS scores and BMI and age. Results: Overall, insomnia severity was not directly associated with BMI in the full sample (p = 0.55). However, a significant interaction between insomnia symptoms and age was observed (p = 0.02). Among women aged ≥37 years, higher AIS scores were positively associated with BMI (β = 0.59; p = 0.06), whereas this association was absent in younger participants. Conclusions: Insomnia symptoms showed a trend toward a positive association with higher BMI, primarily among older women, suggesting an age-dependent relationship between sleep disturbances and body weight. Screening for sleep problems and promoting sleep hygiene could serve as simple, low-cost preventive strategies for maintaining metabolic health in women. Full article

Sustainable digital marketing in the United Arab Emeritus (UAE) faces challenges in terms of balancing rapid technological adoption with long-term environmental goals. Many firms struggle to integrate eco-friendly practices into fast-growing online platforms. Limited consumer awareness and inconsistent regulatory frameworks further hinder the shift toward truly sustainable digital strategies. The current study addressed this problem in artificial intelligence (AI) adoption, which has rarely been addressed in sustainable digital marketing among the telecommunication companies working in the UAE. Therefore, the objective of this study is to examine the role of AI adoption in sustainable digital marketing through the promotion of smart distribution channels (SDCs), sustainable employee intention, and employee behavior. Primary data was collected using a structured questionnaire distributed among the employees of Etisalat and du in the UAE. Three hundred (300) valid responses were received, which were used for data analysis via PLS-SEM. Findings of the study proposed that AI adoption is key to promoting sustainable digital marketing through the promotion of SDCs, sustainable employee intention, and employee behavior. These results provide valuable insights for the policymakers to address the problem of sustainable digital marketing. Full article

Background: Many biological drugs have a rival version produced from different cell lines by other manufacturers; these drugs are referred to as biosimilars. By providing accurate information, encouraging patient and medical community acceptance, and advocating for their appropriate usage, pharmacists can play a crucial role in supporting the uptake of biosimilar medicines. Aim: This study aimed to assess pharmacists’ knowledge and attitudes toward biosimilar medicines in the Aseer region in Saudi Arabia. Methods: The study employed a descriptive, cross-sectional design using an anonymous online self-administered questionnaire. The questionnaire was developed by adapting a previously validated instrument and consisted of three sections: demographic data, knowledge about biosimilars, and attitudes toward biosimilars. Two non-probability sampling approaches, i.e., convenience and snowball sampling, were using for data collection. Results: A total of 298 pharmacists participated in the current study. Overall, a total of 135 (45.3%) demonstrated good knowledge of biosimilar medicines, while 163 (54.7%) exhibited poor knowledge. The median knowledge score among the study participants was 5 (5–6). Only 26.2% of pharmacists in the current study correctly identified that biosimilars were not generics and not interchangeable with reference biologics. More experienced pharmacists and those working in industry-related sectors demonstrated greater knowledge of biosimilars (p < 0.05). Pharmacists in the current study demonstrated generally favorable attitudes toward biosimilar medicines. Conclusions: The current study revealed knowledge gaps regarding biosimilar medicines among pharmacists. Targeted educational initiatives, continuing professional development opportunities, and enhanced curricular content could be implemented to address these gaps. Full article

Wireless sensor networks (WSNs) consist of distributed nodes to monitor various physical and environmental parameters. The sensor nodes (SNs) are usually resource constrained such as power source, communication, and computation capacity. In WSN, energy consumption varies depending on the distance between sender and receiver SNs. Communication among SNs having long distance requires significantly additional energy that negatively affects network longevity. To address these issues, WSNs are deployed using multi-hop routing. Using multi-hop routing solves various problems like reduced communication and communication cost but finding an optimal cluster head (CH) and route remain an issue. An optimal CH reduces energy consumption and maintains reliable data transmission throughout the network. To improve the performance of multi-hop routing in WSN, we propose a model that combines Multi-Objective Particle Swarm Optimization (MOPSO) and a Decision Tree for dynamic CH selection. The proposed model consists of two phases, namely, the offline phase and the online phase. In the offline phase, various network scenarios with node densities, initial energy levels, and BS positions are simulated, required features are collected, and MOPSO is applied to the collected features to generate a Pareto front of optimal CH nodes to optimize energy efficiency, coverage, and load balancing. Each node is labeled as selected CH or not by the MOPSO, and the labelled dataset is then used to train a Decision Tree classifier, which generates a lightweight and interpretable model for CH prediction. In the online phase, the trained model is used in the deployed network to quickly and adaptively select CHs using features of each node and classifying them as a CH or non-CH. The predicted nodes broadcast the information and manage the intra-cluster communication, data aggregation, and routing to the base station. CH selection is re-initiated based on residual energy drop below a threshold, load saturation, and coverage degradation. The simulation results demonstrate that the proposed model outperforms protocols such as LEACH, HEED, and standard PSO regarding energy efficiency and network lifetime, making it highly suitable for applications in green computing, environmental monitoring, precision agriculture, healthcare, and industrial IoT. Full article

Insects constitute a vital component of terrestrial ecosystems, yet their ongoing global decline underscores the urgency of identifying the factors that facilitate or hinder public engagement in their conservation. This study identifies the key psychological drivers of insect-related conservation behavior within a Romanian context, an understudied geographical and sociocultural setting. Using data collected from 346 adult respondents via an online questionnaire, the predictive performance of the Value–Belief–Norm (VBN) theory, the Theory of Planned Behavior (TPB), and an integrated VBN–TPB framework was examined through Partial Least Squares Structural Equation Modeling (PLS-SEM). The VBN model exhibited superior explanatory power relative to TPB, with biospheric values, ecological worldviews, and personal moral norms emerging as the most influential determinants of behavioral intention and self-reported action. Although participants demonstrated moderate levels of general entomological knowledge, awareness of specific insect-friendly practices was notably limited and frequently characterized by misconceptions. Perceived barriers, particularly informational deficits, time constraints, and financial considerations, exerted significant inhibitory effects on conservation engagement. The findings indicate that effective interventions must extend beyond knowledge transmission, incorporating strategies that activate moral norms, strengthen affective and identity-based motivations, and reduce structural barriers to action. Full article

The teacher–student relationship is often more strongly associated with learning outcomes than the family relationship during emerging adulthood, primarily through self-efficacy. However, most of these findings are based on offline contexts, where teachers interact with students face-to-face and families remain relatively distant. Online learning may involve different dynamics, especially during the COVID-19 pandemic, when families became more engaged and teacher–student interactions were digitally mediated. These shifts may also reshape the traditionally blurred boundaries between parental and teacher roles in China, where teachers are often regarded as quasi-parental figures. Therefore, it is necessary to re-examine and compare the relative contributions of family and teacher–student relationships to online learning outcomes. Data were collected from 1793 university students (Mage = 21.28, SD = 2.26; 50.08% male) across 32 provinces in China. Structural equation modeling with bootstrapping was used to test mediation and compare direct and indirect effects. The results showed that (a) both family and teacher–student relationships were positively associated with online learning outcomes via self-efficacy, and (b) although total effects were similar, the teacher–student relationship exhibited a stronger indirect effect. These findings suggest that family relationships primarily offer emotional and environmental support, maintaining background stability, whereas teacher–student relationships foster the cognitive–motivational processes underlying autonomous learning. They may play complementary roles in online learning within the Chinese higher education, where schools retain instructional authority even in digital environments and families continue to act as educational mediators. Full article

The purpose of this study was to examine the relationships among coursework demand, course value, learning engagement, and mental fatigue among online undergraduate students in the United States. Data was collected through a panel survey involving 415 online student complete responses across the study variables. Structural Equation Modeling (SEM) was employed to analyze the relationships between the variables of interest. The findings revealed that coursework demand exerted a direct positive effect on mental fatigue, meaning higher demand leads to more fatigue. In contrast, course value indirectly reduced mental fatigue by positively enhancing learning engagement. Furthermore, learning engagement had a direct negative impact on mental fatigue, suggesting that higher levels of engagement may function as a potential buffer against the negative effects of increased coursework demand. While the variables in the current model have been examined individually in prior research, this study explored the mechanisms of the relevant variables and the pathways through which they affect mental fatigue, particularly among online learning populations who are more susceptible to experiencing online learning fatigue. The current findings therefore have significant implications for public health and higher education, suggesting that interventions focused on carefully adjusting coursework demand, increasing course value, and boosting learning engagement could be an effective strategy to mitigate mental fatigue and promote the overall well-being of college students. Full article

This study examines two primary research objectives: (1) to investigate the roles of work stress, logistics infrastructure, financial stress, and environmental stress as antecedent factors influencing the wellbeing of truck drivers in Thailand, and (2) to explore the mediating roles of driver fatigue, cognitive impairment, and accident risk in the relationship between antecedent factors and wellbeing. Data were collected from 534 Thai truck drivers through voluntary participation in an online survey utilizing a validated five-point Likert scale instrument with established reliability and validity. The data collected was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings demonstrate that Work Stress, Financial Stress, and Environmental Stress constitute antecedent factors with direct effects on wellbeing. Driver fatigue, cognitive impairment, and accident risk function as complementary partial mediators in the relationships between work stress, environmental stress and wellbeing, while simultaneously serving as competitive partial mediators in the relationship between financial stress and wellbeing. Moreover, these three mediating variables collectively operate as full serial mediators in the relationship between logistic infrastructure and wellbeing. The results show that all antecedent factors significantly affect wellbeing, with financial stress having the strongest impact, followed by environmental stress. Together, these factors explain a substantial portion of wellbeing variance among Thai truck drivers. Full article