Search Results (342)

Introduction: Cystic fibrosis (CF) is a genetic condition affecting several organs and systems, including the pancreas, colon, respiratory system, and reproductive system. The detection of a growing number of CFTR variants and genotypes has contributed to an increase in the CF population which, in turn, has had an impact on the overall statistics regarding the prognosis and outcome of the condition. Given the increase in life expectancy, it is critical to better predict outcomes and prognosticate in CF. Thus, each person’s choice to aggressively treat specific disease components can be more appropriate and tailored, further increasing survival. The objective of our narrative review is to summarize the most recent information concerning the value and significance of clinical parameters in predicting outcomes, such as gender, diabetes, liver and pancreatic status, lung function, radiography, bacteriology, and blood and sputum biomarkers of inflammation and disease, and how variations in these parameters affect prognosis from the prenatal stage to maturity. Materials and methods: A methodological search of the available data was performed with regard to prognostic factors in the evolution of CF in children and young adults. We evaluated articles from the PubMed academic search engine using the following search terms: prognostic factors AND children AND cystic fibrosis OR mucoviscidosis. Results: We found that it is crucial to customize CF patients’ care based on their unique clinical and biological parameters, genetics, and related comorbidities. Conclusions: The predictive significance of more dynamic clinical condition markers provides more realistic future objectives to center treatment and targets for each patient. Over the past ten years, improvements in care, diagnostics, and treatment have impacted the prognosis for CF. Although genotyping offers a way to categorize CF to direct research and treatment, it is crucial to understand that a variety of other factors, such as epigenetics, genetic modifiers, environmental factors, and socioeconomic status, can affect CF outcomes. The long-term management of this complicated multisystem condition has been made easier for patients, their families, and physicians by earlier and more accurate identification techniques, evidence-based research, and centralized expert multidisciplinary care. Full article

The purpose of the present research is to analyse the negative outcomes associated with the excessive Instagram dependency of those users that access the application through their smartphones. An empirical study was conducted through online interviews using structured questionnaires, resulting in 342 valid responses, with the target population being young users over 18 years old who access Instagram daily. Research shows that dependency on Instagram is primarily driven by individuals’ need for orientation and understanding, with entertainment being a secondary motivation. The results indicate that dependency on the social network is positively associated with excessive use, addiction, and Instastress. Furthermore, excessive use contributes to personal and social problems and increases both stress levels and mindfulness related to the platform. In turn, this excessive use intensifies addiction, which functions as a mediating variable between overuse and Instastress, mindfulness, and emotional exhaustion. This study offers valuable insights for academics, mental health professionals, and marketers by emphasizing the importance of fostering healthier digital habits and developing targeted interventions. Full article

The influence of social media personalities has grown significantly, especially among youth audiences who spend substantial time on platforms like TikTok. The emergence and popularity of different types of social media influencers accelerated during the COVID-19 pandemic in many countries, including South Africa. In turn, this period also saw a surge in youth audiences following these influencers. This rapid growth of influencer followings among young people is largely driven by specific types of content that resonate with them, thus encouraging continued engagement. However, the benefits that these young followers gain from engaging with various influencers and the factors driving their preferences for specific influencers remain underexplored, particularly within the context of South African students within higher education. Therefore, this study explores the types of social media influencers most followed by university students at a South African University and investigates the key factors that drive their preferences. A structured online questionnaire was distributed, gathering both multiple-choice and open-ended responses from students. The data were analyzed using categorical frequency counts and thematic analysis. The data highlight how students actively turn to influencers as emotional anchors, role models, and sources of practical guidance. Their engagement reflects a deep need for connection, inspiration, and identity formation in a challenging academic and social environment. These patterns show that influencer content is not just entertainment but plays a critical developmental role. Understanding these motivations helps educators, policymakers, and brands to align better with youth values. The significance of these results lies in how influencer content is now coming in to fill the emotional, cultural, and educational gaps left by traditional systems among the young South African university students in this modern era. Full article

Given that participating in or spectating sports events plays a vital role in enhancing individuals’ mental health, understanding the key factors that promote continued participation and attendance in sports events is of significant theoretical and practical importance within the context of sports tourism. From this perspective, the service quality of sports events and the image of the host destination have been identified as major determinants of sustained engagement among sports tourists. However, a review of the literature reveals that findings on the influence of sports event service quality and host destination image on the behavioral intentions of sports tourists have been inconsistent. Therefore, the purpose of this study is to employ a meta-analytic structural equation modeling (MASEM) approach to synthesize data from 39 independent studies comprising 16,335 participants, which were collected up to 30 September 2024, thereby providing generalizable conclusions. The results indicate that, first, host destination image is the most critical factor in enhancing visitor satisfaction. Additionally, the service quality of sports events significantly influences visitor satisfaction, which in turn impacts their future behavioral intentions. Second, tourist satisfaction fully mediates the relationship between event service quality and behavioral intentions, and it partially mediates the relationship between host destination image and behavioral intentions. Third, under the moderating effect of event scale (small scale vs. mega scale), host destination image and physical environment quality are more important in small-scale sports events than in mega-scale sports events. Furthermore, under the moderating effect of cultural context (Eastern vs. Western), service quality dimensions are more influential in Western cultural settings, whereas host destination image is more important in Eastern cultural settings. The significance of this study lies in its integration of previously disparate findings into a unified model, offering a more comprehensive understanding of the relationships among the variables. The results provide broad implications for future academic research and practical insights for sports tourism practitioners. Full article

The development of stock markets is pivotal for economic growth, particularly through the mobilization of idle resources into productive investments. Despite recent reforms to enhance Uzbekistan’s capital market, public engagement remains limited. This study examines the behavioral determinants of stock market investment intention and participation among university students, employing the Theory of Planned Behavior (TPB) and Partial Least Squares Structural Equation Modeling (PLS-SEM). The model investigates the influence of digital literacy, financial literacy, social interaction, herding behavior, overconfidence bias, risk tolerance, and financial well-being on investment intention and behavior. A survey of 369 university students was conducted to assess the proposed relationships. The results reveal that risk tolerance, overconfidence bias, and herding behavior significantly and positively affect investment intention, while digital literacy demonstrates a notable negative effect, suggesting caution in assuming technology readiness automatically translates to investment readiness. Investment intention, in turn, strongly predicts actual participation and mediates several of these effects. Conversely, financial literacy, financial well-being, and social interaction showed no significant direct or mediating influence. Additionally, differences according to gender and academic background were observed in how intention translates into behavior. The findings underscore the need for integrated financial and behavioral education to enhance market participation and contribute to policy discourse on youth financial engagement in emerging economies. Full article

Modern financial practices introduce complex risks, which in turn force financial institutions to rely increasingly on computational risk analytics (CRA). The purpose of our research is to attempt to systematically explore the evolution and intellectual structure of CRA in banking using a detailed bibliometric analysis of the literature sourced from Web of Science from 2000 to 2025. A comprehensive search in the Web of Science (WoS) Core Collection yielded 1083 peer-reviewed publications, which we analyzed using analytical tools like VOSviewer 1.6.20 and Bibliometrix (Biblioshiny 5.0) so as to examine the dataset and uncover bibliometric characteristics like citation patterns, keyword occurrences, and thematic clustering. Our initial analysis results uncover the presence of key research clusters focusing on bankruptcy prediction, AI integration in financial services, and advanced deep learning applications. Furthermore, our findings note a transition of CRA from an emerging to an expanding domain, especially after 2019, with terms like machine learning (ML), artificial intelligence (AI), and deep learning (DL) being identified as prominent keywords and a recent shift towards blockchain, explainability, and financial stability being present. We believe that this study tries to address the need for an updated mapping of CRA, providing valuable insights for future academic inquiry and practical financial risk management applications. Full article

The current study examines the determinants influencing preparatory year (PY) students’ intentions to adopt AI-powered natural language processing (NLP) models, such as Copilot, ChatGPT, and Gemini, and how these intentions shape their conceptions of digital sustainability. Additionally, the extended unified theory of acceptance and use of technology (UTAUT) was integrated with a diversity of educational constructs, including content availability (CA), learning engagement (LE), learning motivation (LM), learner involvement (LI), and AI satisfaction (AS). Furthermore, responses of 274 PY students from Saudi Universities were analysed using partial least squares structural equation modelling (PLS-SEM) to evaluate both the measurement and structural models. Likewise, the findings indicated CA (β = 0.25), LE (β = 0.22), LM (β = 0.20), and LI (β = 0.18) significantly predicted user intention (UI), explaining 52.2% of its variance (R² = 0.522). In turn, UI significantly predicted students’ digital sustainability conceptions (DSC) (β = 0.35, R² = 0.451). However, AI satisfaction (AS) did not exhibit a moderating effect, suggesting uniformly high satisfaction levels among students. Hence, the study concluded that AI-powered NLP models are being adopted as learning assistant technologies and are also essential catalysts in promoting sustainable digital conceptions. Similarly, this study contributes both theoretically and practically by conceptualising digital sustainability as a learner-driven construct and linking educational technology adoption to its advancement. This aligns with global frameworks such as Sustainable Development Goals (SDGs) 4 and 9. The study highlights AI’s transformative potential in higher education by examining how user intention (UI) influences digital sustainability conceptions (DSC) among preparatory year students in Saudi Arabia. Given the demographic focus of the study, further research is recommended, particularly longitudinal studies, to track changes over time across diverse genders, academic specialisations, and cultural contexts. Full article

Mental health is an increasing concern, particularly among the younger population. Given that university life is a critical stage in the personal and academic development of some young individuals, identifying the factors that contribute to their well-being is essential. This study focused on exploring the role of emotional intelligence and resilience in the perceived stress of a sample of 338 university students from the University of Alicante. To this end, a structural equation analysis was used to evaluate the direct and indirect effects of the variables included in the model. The instruments used were the Trait Meta-Mood Scale, the Connor–Davidson Resilience Scale, and the Perceived Stress Scale. Based on the dimensions of the cascading model of emotional intelligence, the results indicate that emotional attention had a direct and positive effect on stress, while both emotional clarity and emotional repair influenced resilience directly and positively. In turn, resilience had a direct and negative effect on stress, acting as a mediator between the dimensions of emotional intelligence and stress. The final proposed model explained 49.3% of the variance in stress. This study provides empirical evidence regarding how these variables interact and underscores the importance of emotional abilities in stress regulation in the university setting. Full article

Crowdsourcing has become increasingly relevant in academic research due to its role in the evolving digital landscape, where information is a key driver of organizational performance. In a context dominated by emerging technologies and digital platforms, organizations are turning to external sources for data and idea generation. This paper offers a comprehensive review of the literature on crowdsourcing and digital information, using bibliometric techniques and qualitative analysis to identify major trends. The findings reveal several shifts in focus: from conceptual frameworks to practical applications; from customer participation to broader stakeholder involvement; and from general technological and managerial approaches to specific technologies and emerging perspectives in entrepreneurship and finance. The primary contributing disciplines are Computer Science, Engineering, and Information Science. Recent research (post 2023) emphasizes constructs such as “crowdfunding”, “digital platforms”, and “machine learning”, moving beyond earlier focuses like “citizen science” and “social media.” This review also reveals growing interest in managerial, medical, and cultural heritage applications, alongside a decline in research related to geography and crisis management over the past two years. This study enhances our understanding of current research directions and practical implications in crowdsourcing and digital information, offering valuable insights for both academics and practitioners. Full article

This essay serves as an expansive, conceptual anchor and scholarly argument that demonstrates the modality of “reflexive extractivist” religious studies and also orients the Special Issue on Religion in Extractive Zones. We demonstrate that critical religious and theological scholarship have existing tools and methods for deepening the study of extraction in the environmental humanities and related discourses. We make two interconnected arguments: that religion has been and continues to be produced out of extractive zones in the conflicts, negotiations, and strategic alliances of contact zones and that the complex production of sacred and secular in these zones can be fruitfully analyzed as imaginaries and counter-imaginaries of extraction. We present these arguments through a dialogical and critically integrative methodology, in which arguments from theorists across several disciplines are put into conversation and from which our insights emerge. This methodology leads to a final section of the essay that sets a framework for, and invites further dialogical and integrative scholarship on, the practical ethics of non- or counter-extractive academic research, scholarship, and publishing. Offering theoretical, methodological, and practical suggestions, we call for a turn toward reflexive extractivist religious studies, articulate the specific conceptual and methodological approaches linking religion and extraction, and thus set the framework and tone for the Special Issue. Full article

Teachers’ beliefs on issues of multilingualism shape their classroom practices, which in turn affect their multilingual students’ learning opportunities and academic achievement. Examining these beliefs is therefore crucial for teacher educators who strive to equip pre- and in-service teachers with the appropriate mindset that is necessary in the context of an educational landscape characterized by linguistic diversity. In this study, we examine German pre-service teachers’ knowledge of and beliefs toward multilingualism and their perceived preparedness for a multilingual classroom. We use a questionnaire that includes an internationally recognized scale to measure beliefs toward multilingualism Additionally, we investigate how a semester-long lecture on German as a second language (GSL) and language-sensitive teaching influences pre-service teachers’ beliefs. The results indicate that while German pre-service teachers demonstrate knowledge and awareness of multilingualism, there remains potential for fostering a more open belief system—one that is essential for effectively engaging with diverse student groups and should be systematically addressed during university education. Pre-service teachers who participated in the semester-long lecture showed slightly more multilingual beliefs. These findings provide a basis for discussing curricular opportunities aimed at promoting multilingualism and supporting language learning in educational settings. Full article

Public speaking anxiety, which is closely related to social anxiety, is a crucial factor in the development of adolescents. It affects their ability to regulate their emotions and irrational beliefs, which in turn shapes their relationships and academic success. The purpose of this present study is two-fold: (a) to develop a valid and reliable measurement tool for public speaking anxiety for adolescents, and (b) to determine the mediating role of dysfunctional emotion regulation on the effect of irrational beliefs on public speaking anxiety. To achieve this, data were collected through face-to-face interviews from a total of 1231 adolescent students, including 642 girls (age, $\overline{X}$ = 14.96) and 589 boys ($\overline{X}$ = 14.99), aged between 12 and 17 years old in five stages. Data collection was based on the Public Speaking Anxiety Scale (PSAS) (developed in the current study), the Irrational Beliefs Scale (IBS), the Regulation of Emotions Questionnaire (REQ) and the Social Anxiety Scale for Adolescents (SAS-A). Data were analysed through SPSS, AMOS, JAMOVI, G-POWER and Microsoft Excel programmes. This study concludes that the Public Speaking Anxiety Scale (PSAS) has demonstrated both valid and reliable psychometric properties. The findings of this study further reveal that internal dysfunctional emotion regulation plays a partial mediating role in the effect of irrational beliefs on public speaking anxiety, and that external dysfunctional emotion regulation, on the contrary, did not have a mediating role in the effect of irrational beliefs on public speaking anxiety. Full article

Over the past few years, there has been a need to discuss the strengthening of academic contributions to the 2030 Agenda as a vital facilitator for planning and evaluating sustainable goals. However, managing information in this field has become an internal institutional challenge for higher education organizations. Identifying the aspects of sustainable development goals within research projects is crucial for developing strategies and policies that promote collaboration in joint projects, ultimately strengthening research in SDGs. Recent advancements in computational methods have emerged as powerful tools to address the difficulties associated with utilizing information related to academic contributions to the 2030 Agenda. These methods offer innovative ways to process, analyze, and visualize data, enabling decision-makers to gain valuable insights and make informed decisions. This paper proposes a computational model to facilitate the identification of the 2030 Agenda for Sustainable Development within teaching, research, and extension projects at a Brazilian University. The model aims to align academic research and institutional actions with the 17 Sustainable Development Goals (SDGs) established by the United Nations. The developed model can extract and categorize SDG-related text data by employing keywords and natural language processing techniques. The development of this tool is driven by the need for universities to adapt their curricula and contribute to the 2030 Agenda. The model helps identify the potential impact of projects on the SDGs, assessing the alignment of research or actions with specific goals, and improving data governance. By utilizing the proposed model, educational institutions can efficiently manage their research, organize their work around the SDGs, foster collaboration internally and with external partners, and enhance their internationalization efforts. The model has the potential to increase the capabilities of educational institutes as vital mobilizing agents, reducing costs and streamlining the analysis of information related to the 2030 Agenda. This, in turn, enables more effective academic actions to integrate sustainable goals. Full article

This article examines the interplay between study demands, institutional resources, and individual resources, specifically resilience, with the perceived stress, study engagement, and dropout intentions of student teachers using the Study Demands–Resources model. The aim is to describe the relevance of these variables in relation to student teachers’ intention to drop out of their studies as an indicator of student success. Further, we aim to explore whether the correlation structures can also be confirmed under different conditions, particularly in the context of the COVID-19 pandemic. To answer these questions, data collected under pandemic study conditions (N_LA1 = 510) and post-pandemic study conditions (N_LA2 = 433) are used and analysed by SEM. The results show that the Study Demands–Resources model is applicable in the two different contexts based on its validation in both study contexts. In line with the model, in both contexts, perceived stress and student engagement were significantly related to student teachers’ dropout intentions. Furthermore, study demands and resilience influenced perceived stress, which in turn affected dropout intentions, whereas institutional resources were associated with dropout intentions via student engagement. This article contextualises the findings within the existing research landscape. Based on the results, theoretical implications are discussed and approaches to reduce perceived stress in a sustainable manner to support student teachers and their academic success are described. Full article

This study explores the impact of educational technology on student success within higher education institutions (HEIs). Faced with pressures to improve enrollment, retention, and graduation rates, HEIs have increasingly turned to technology solutions. This article examines a pilot initiative at a large midwestern university, which implemented a collaborative studying software platform across multiple campuses. The research employed a Strategic Academic Research and Development (SARD) framework, triangulating data sources, methods, and interpreters to assess the effectiveness of the technology in improving student outcomes. This study utilized both quantitative and qualitative methodologies. Quantitative data included pass rates, grade-point averages, instructor fidelity, and software usage metrics, analyzed using Chi-square tests, analysis of variance, and linear mixed-effects models. Qualitative data were gathered from instructor reflections and student surveys, providing insights into changes in student engagement and performance. Pass rates and average GPAs increased following the intervention, but gains were similar across usage levels. Instructor fidelity was significantly associated with student performance, and results varied by discipline and campus, emphasizing the importance of context. This study also revealed challenges related to student adoption and instructor engagement with the technology. Overall, the findings suggest that while educational technology can enhance student success, its effectiveness depends on thoughtful integration and continuous assessment. The SARD framework proved valuable in guiding the evaluation process, emphasizing the need for comprehensive and collaborative approaches to educational technology assessment. Full article