Search Results (50)

Background: Undergraduate nursing students (UNSs) often enter clinical training just as they are still mastering the emotional labor of the profession. In Nepal, where teaching hierarchies discourage upward dialogue and hospitals routinely struggle with overcrowding, supply shortages, and outward nurse migration, these learners confront a distinct, under-documented burden of psychological distress. Objective: This study examines how UNSs interpret, negotiate, and cope with the mental health challenges that arise at the intersection of cultural deference, resource scarcity, and migration-fueled uncertainty. Methods: A qualitative design employing reflexive thematic analysis (RTA), guided by the Reflexive Thematic Analysis Reporting Guidelines (RTARG), was used. Fifteen second-, third-, and fourth-year Bachelor of Science in Nursing students at a major urban tertiary institution in Nepal were purposively recruited via on-campus digital flyers and brief in-class announcements that directed students (by QR code) to a secure sign-up form. Participants then completed semi-structured interviews; audio files were transcribed verbatim and iteratively analyzed through an inductive, reflexive coding process to ensure methodological rigor. Results: Four themes portray a continuum from silenced struggle to systemic constraint. First, Shrouded Voices, Quiet Connections captures how students confide only in trusted peers, fearing that formal disclosure could be perceived as weakness or incompetence. Second, Performing Resilience: Masking Authentic Struggles describes the institutional narratives of “strong nurses” that drive students to suppress anxiety, adopting scripted positivity to satisfy assessment expectations. Third, Power, Hierarchy, and the Weight of Tradition reveals that strict authority gradients inhibit questions in classrooms and clinical placements, leaving stress unvoiced and unaddressed. Finally, Overshadowed by Systemic Realities shows how chronic understaffing, equipment shortages, and patient poverty compel students to prioritize patients’ hardships, normalizing self-neglect. Conclusions: Psychological distress among Nepalese UNSs is not an individual failing but a product of structural silence and resource poverty. Educators and policymakers must move beyond resilience-only rhetoric toward concrete reforms that dismantle punitive hierarchies, create confidential support avenues, and embed collaborative pedagogy. Institutional accountability—through regulated workloads, faculty-endorsed wellbeing forums, and systematic mentoring—can shift mental health care from a private struggle to a shared professional responsibility. Multi-site studies across low- and middle-income countries are now essential for testing such system-level interventions and building a globally resilient, compassionate nursing workforce. Full article

Background: Internationally, digital health interventions have increasingly been adopted within hospital settings. Optimising their clinical implementation requires user involvement, but there is a lack of evidence regarding how this should be done. Objectives: This study was carried out to understand the acceptability and usability of a prototype Digital Antibiotic Review Tracking Toolkit and identify modifications required to optimise it ahead of a trial. Methods: The optimisation process involved online semi-structured interviews with a purposive sample of fifteen healthcare professionals recruited from Scotland and England, along with three service users, to gather feedback on the prototype’s design, content and delivery. Participants’ negative views were specifically sought to identify adaptations needed to ensure that the intervention’s components aligned optimally with end-user needs. Data were analysed using Framework Analysis guided by the RE-AIM implementation science framework (Reach, Effectiveness, Adoption, Implementation, and Maintenance) to identify key themes. Results: Participants mostly voiced positive views regarding the prototype, finding it acceptable, feasible and engaging. They also identified concerns relating to its adoption, system functionality, accessibility and maintenance that needed to be addressed. Anticipated low adoption rates were linked to issues surrounding computer literacy. This detailed user feedback informed rapid adjustments to the intervention to enhance its acceptability, perceived future credibility and usability in hospitals. Conclusions: This novel study illustrates how to identify, modify and adapt a digital intervention quickly and efficiently using qualitative iterative methods. Findings highlight the critical importance of contextualising end-user experience with health interventions to facilitate future engagement, uptake, and long-term use. This study also demonstrates how core elements of the MRC framework can be operationalised to help refine prototype digital interventions pre-trial. Full article

This study examines the role of green digital transformational leadership (GDTL) in enhancing sustainability performance in the hotel industry through the mediating mechanism of circular economy (CE) practices and the moderating effects of otel green efficacy (HGE). Grounded in the dynamic capabilities theory, natural resource-based view (NRBV) theory, and social exchange theory, a novel conceptual model that bridges digital innovation, ecological stewardship, and organizational psychology was proposed. The study adopted a quantitative approach and used a self-administered questionnaire survey to collect data from 402 employees across green-certified hotels in Sharm El-Sheikh, Egypt. Participants were recruited using a stratified sampling method to ensure sectoral representation. Data analysis techniques included performing partial least squares structural equation modeling (PLS-SEM) using Smart PLS 3.0. Key findings reveal that GDTL directly influences the three key aspects of sustainability performance in hotels, including environmental, economic, and social aspects. Likewise, CE practices significantly mediate the linkage between GDTL and hotel sustainability performance. Notably, HGE strengthens the GDTL-CE relationship, underscoring the critical role of employee empowerment in translating leadership vision into regenerative practices. These results add to the growing literature on sustainable leadership by revealing how digital tools like AI, blockchain, and closed-loop systems can synergize to support economic growth and conserve natural resources. Full article

In the volatility, uncertainty, complexity, and ambiguity (VUCA) environment, the application of artificial intelligence (AI) technologies is a key engine for shaping supply chain resilience (SCR). This study employs the entropy method to develop an evaluation index system for SCR, incorporating two key dimensions: resistance and recovery capacity. Using a sample of Chinese-listed enterprises from 2009 to 2022, this study reveals that AI significantly enhances SCR, and CEOs’ sports experience can positively moderate the association between AI and SCR. Mechanism examination shows that AI promotes SCR through operational efficiency optimization, information, and knowledge spillover in the supply chain. Heterogeneity analysis reveals that the positive impact of AI is more significant in firms with a high-skilled labor force, firms with high heterogeneity of the executive team’s human capital, high-tech industries, and regions with strong digital infrastructure. Moreover, the AI application has a diffusion effect on the upstream and downstream enterprises of the supply chain, improving AI adoption levels. Our research not only augments the existing literature on the economic ramifications of AI adoption and the strategic value derived from CEOs’ extramural experience but also offers both theoretical frameworks and empirical insights for executive recruitment and fortifying SCR. Full article

Although mobile health (mHealth) technologies have emerged as a revolutionary approach to enhance healthcare delivery, few studies have examined how it is perceived and accepted in different cultures. This study investigated mHealth’s social acceptance among young people in Japan and China, with a focus on cultural influences on technology adoption. A comparative analysis approach was adopted, employing an extended unified theory of acceptance and use of the technology model. University students from both countries, recruited using harmonized sampling methods, completed questionnaires. We employed descriptive statistics to summarize the sample characteristics, confirmatory factor analysis to validate the constructs, multigroup analysis to test for measurement invariance and ensure the applicability of the model in both cultural contexts, and comparative path analysis to explore differences in the various factors influencing mHealth acceptance in each cultural setting. The findings revealed distinct cultural effects on mHealth acceptance. Japanese young people showed cautious acceptance influenced by societal norms and infrastructure, whereas Chinese young people demonstrated strong engagement driven by government support and the growing digital health industry. The study emphasizes the importance of considering cultural and systemic dynamics when integrating mHealth into youth healthcare models and suggests tailored strategies for successful implementation. Full article

Background: Visual impairment can significantly impact an individual’s daily activities. Patients require regular monitoring, typically occurring within hospital eye services. Capacity constraints have necessitated innovative solutions to improve patient care. Existing digital solutions rely on task-based digital home monitoring such as visual acuity testing. These require active involvement from patients and do not typically offer an indication of quality of life. Digital phenotyping refers to the use of personal digital devices to quantify passive behaviour for detecting clinically significant changes in vision and act as biomarkers for disease. Its uniqueness lies in the ability to detect changes passively. The objective was to co-design an accessible smartphone app (OverSight) for the purposes of digital phenotyping in people with sight impairment. Methods: Development of OverSight included stakeholder consultations following principles of user-centred design. Apple iOS software frameworks (HealthKit, ResearchKit, and SensorKit) and a SwiftUI developer toolkit were used to enable the collection of active and passive data streams. Accessibility and usability were assessed using the System Usability Scale (SUS) and feedback following a 3-month pilot study. Consultations with patients informed the design of OverSight, including preferred survey scheduling and the relevancy of patient support resources. Results: Twenty visually impaired participants (mean age 42 ± 19 years) were recruited to the pilot study. The average score on the SUS was 76.8 (±8.9), indicating good usability. There was a statistically significant moderate negative correlation between SUS scores and visual acuity in both the better (r = −0.494; p ≤ 0.001) and worse eye (r = −0.421; p ≤ 0.001). Conclusions: OverSight offers promising potential for collecting patient-generated health data for the purposes of digital phenotyping in patients with eye disease. Through further testing and validation, this novel approach to patient care may ultimately provide opportunities for remote monitoring in ophthalmology. Full article

Introduction: This pilot two-arm, parallel group, randomized clinical trial aimed to compare the efficacy of tooth movement and patient comfort during orthodontic leveling and alignment with the BRIUS™ lingual system (BR) versus labial full fixed appliances (LFFAs). Methods: Patients in the permanent dentition with mild to moderate crowding were recruited at the University at Buffalo and randomly assigned into the BR group (seven patients) or LFFAs group (six patients). The patients’ dental arches were scanned before bonding (T1) and after 18 weeks (T2). Digital dental model superimpositions were performed to three-dimensionally evaluate tooth movement. Changes between T1 and T2 were measured in the x, y, and z planes. Little’s Irregularity Index (LII) was also assessed at T1 and T2. An electronic questionnaire was completed daily for 7 days after T1 to evaluate the patients’ comfort levels. Results: After 18 weeks, similar displacements were observed for all teeth in both groups except for the lower left second premolar (LL5) in the x-axis which showed greater displacement in the BR group (p = 0.016). Groups showed similar changes in LII. Discomfort during the first week after bonding was greater on the tongue in the BR group and on the lips and cheeks in the LFFAs group. Tongue discomfort caused by the BR lasted for around 3 days. Conclusion: The BR and LFFAs showed similar teeth displacements and therefore were equally effective at leveling and aligning teeth. LFFAs caused cheek- and lip-borne discomfort while the BR caused tongue-borne discomfort during the first week after bonding. Larger studies with longer follow-ups are needed to obtain more definitive results. Full article

Evidence is increasing for digital health programs targeting the secondary prevention of stroke. We aimed to determine the feasibility of the novel Care Assistant and support Program for people after Stroke (CAPS) or transient ischaemic attack (TIA) by combining person-centred goal setting and risk-factor monitoring through a web-based clinician portal, SMS messages, a mobile application (app), and a wearable device. We conducted a 12-week mixed-methods, open-label feasibility study. Participants (6 months–3 years after stroke or TIA, access to the internet via a smartphone/tablet) were recruited via the Australian Stroke Clinical Registry. Participants set one or two secondary prevention goals with a researcher and provided access and training in technology use. Feasibility outcomes included recruitment, retention, usability, acceptability, and satisfaction. Secondary outcomes included goal attainment, health outcomes, and program costs. Following 600 invitations, 58 responded, 34/36 (94%) eligible participants commenced the program (one withdrawal; 97% retention), and 10 were interviewed. Participants (27% female, 33% TIA) generally rated the usability of the mobile application as ‘Good’ to ‘Excellent’ (System Usability Scale). Most (94%) agreed the program helped with engagement in health self-monitoring. Overall, 52 goals were set, predominantly regarding exercise (21/52), which were the most frequently achieved (9/21). At 12 weeks, participants reported significant improvements (p < 0.05) in self-efficacy (Cohen’s d = 0.40), cardiovascular health (d = 0.71), and the mental health domain of the PROMIS GH (d = 0.63). CAPS was acceptable, with good retention and engagement of participants. Evaluation of this program in a randomised controlled trial is warranted. Full article

Background: Most people with a stoma worry about leakage, and a quarter experience leakage of stomal effluent outside the baseplate on a monthly basis. Leakage has additional physical and psychosocial consequences, for instance, peristomal skin complications, feeling unable to cope, and self-isolation. Method: An interventional, single-arm, multi-centre study was undertaken in the United Kingdom to evaluate a novel digital leakage notification system for ostomy care, including a support service (=test product) for 12 weeks in patients with a recent stoma formation (≤9 months). Patients completed questionnaires at baseline and after 4, 6, 8, 10, and 12 weeks, evaluating leakage episodes, Ostomy Leak Impact (tool containing three domains), and patient self-management (by PAM-13). Additionally, mental well-being (by WHO-5) and health-related quality of life (QoL) (by EQ-5D-5L) were assessed. Outcomes between baseline and final evaluation were compared by generalised linear and linear mixed models. Results: 92 patients (ITT population) with a mean age of 49.4 years (range 18–81 years) were recruited. Of these, 80% had an ileostomy, and 53% were female. After 12 weeks of using the test product, a significant decrease in mean episodes of leakage outside the baseplate (1.57 versus 0.93, p < 0.046) was observed. Ostomy Leak Impact scores improved across all three domains (p < 0.001), indicating less embarrassment, increased engagement in social activities, and increased control. Patient self-management also improved significantly (PAM-13 score: ∆6.6, p < 0.001), as did the WHO-5 well-being index (∆8.0, p < 0.001). Lastly, EQ-5D-5L profile scores tended to improve (p = 0.075). Conclusions: A new digital leakage notification system demonstrated strong improvements to patients’ stoma self-care, mental well-being, and QoL. Registration number on ClinicalTrials.gov: NCT05135754. Full article

Breastfeeding and human milk are the gold standard for infant feeding. Studying human milk with a systems biology approach in a large longitudinal cohort is needed to understand its complexity and health implications. The Phoenix study is a multicenter cohort study focusing on the interactions of maternal characteristics, human milk composition, infant feeding practices, and health outcomes of Chinese mothers and infants. A total of 779 mother–infant dyads were recruited from November 2021 to September 2022, and 769 mother–infant dyads were enrolled in the study. Scheduled home visits took place at 1, 4, 6, and 12 months postpartum, and 696 dyads (90.5% participants) completed the 12-month visit. At each visit, maternal and infant anthropometry was assessed. Questionnaires were administered to collect longitudinal information on maternal characteristics and lifestyle, infant feeding, and health. Digital diaries were used to record maternal dietary intake, infant feeding, and stool character. Human milk, maternal feces, infant feces, and infant saliva were collected. An external pharmaceutical-level quality assurance approach was implied to ensure the trial quality. Multi-omics techniques (including glycomics, lipidomics, proteomics, and microbiomics) and machine learning algorithms were integrated into the sample and data analysis. The protocol design of the Phoenix study provides a framework for prospective cohort studies of mother–infant dyads and will provide insights into the complex dynamics of human milk and its interplay with maternal and infant health outcomes in the Chinese population. Full article

Cyber–physical systems have become critical across industries. They have driven investments in education services to develop well-trained engineers. Education services for cyber–physical systems require the hiring of expert tutors with multidisciplinary knowledge, as well as acquiring expensive facilities/equipment. In response to the challenges posed by the need for the equipment and facilities, a metaverse-based education service that incorporates digital twins has been explored as a solution. However, the issue of recruiting expert tutors who can enhance students’ achievements remains unresolved, making it difficult to effectively cultivate talent. This paper proposes a reference architecture for a learner-centric educational metaverse with an intelligent tutoring framework as its core feature to address these issues. We develop a novel explainable artificial intelligence scheme for multi-class object detection models to assess learners’ achievements within the intelligent tutoring framework. Additionally, a genetic algorithm-based improvement search method is applied to the framework to derive personalized feedback. The proposed metaverse architecture and framework are evaluated through a case study on drone education. The experimental results show that the explainable AI scheme demonstrates an approximately 30% improvement in the explanation accuracy compared to existing methods. The survey results indicate that over 70% of learners significantly improved their skills based on the provided feedback. Full article

While it is common for blind and visually impaired (BVI) users to use mobile devices to search for information, little research has explored the accessibility issues they encounter in their interactions with information retrieval systems, in particular digital libraries (DLs). This study represents one of the most comprehensive research projects, investigating accessibility issues, especially help-seeking situations BVI users face in their DL search processes. One hundred and twenty BVI users were recruited to search for information in six DLs on four types of mobile devices (iPhone, iPad, Android phone, and Android tablet), and multiple data collection methods were employed: questionnaires, think-aloud protocols, transaction logs, and interviews. This paper reports part of a large-scale study, including the categories of help-seeking situations BVI users face in their interactions with DLs, focusing on seven types of help-seeking situations related to visual interactions on mobile platforms: difficulty finding a toggle-based search feature, difficulty understanding a video feature, difficulty navigating items on paginated sections, difficulty distinguishing collection labels from thumbnails, difficulty recognizing the content of images, difficulty recognizing the content of graphs, and difficulty interacting with multilayered windows. Moreover, corresponding design recommendations are also proposed: placing meaningful labels for icon-based features in an easy-to-access location, offering intuitive and informative video descriptions for video players, providing structure information about a paginated section, separating collection/item titles from thumbnail descriptions, incorporating artificial intelligence image/graph recognition mechanisms, and limiting screen reader interactions to active windows. Additionally, the limitations of the study and future research are discussed. Full article

Digital recruitment systems have revolutionized the hiring paradigm, imparting exceptional efficiencies and extending the reach for both employers and job seekers. This investigation scrutinized the efficacy of classical machine learning methodologies alongside advanced large language models (LLMs) in aligning resumes with job categories. Traditional matching techniques, such as Logistic Regression, Decision Trees, Naïve Bayes, and Support Vector Machines, are constrained by the necessity of manual feature extraction, limited feature representation, and performance degradation, particularly as dataset size escalates, rendering them less suitable for large-scale applications. Conversely, LLMs such as GPT-4, GPT-3, and LLAMA adeptly process unstructured textual content, capturing nuanced language and context with greater precision. We evaluated these methodologies utilizing two datasets comprising resumes and job descriptions to ascertain their accuracy, efficiency, and scalability. Our results revealed that while conventional models excel at processing structured data, LLMs significantly enhance the interpretation and matching of intricate textual information. This study highlights the transformative potential of LLMs in recruitment, offering insights into their application and future research avenues. Full article

This qualitative study investigates technology readiness, i.e., self-management, social support, and digital health literacy, in people with dementia (PwD). PwD are difficult to recruit; therefore, we used an empathic approach to recruit and conduct interviews. The interviews with seven participants with dementia and two informal caregivers, guided by the READHY framework, reveal nuanced insights into their experiences. Participants demonstrate varying degrees of self-management, with informal caregivers playing pivotal roles in facilitating activities and supporting overall well-being. Cognitive challenges, such as concentration and communication difficulties, are prevalent, highlighting the importance of robust support systems. Internal and external support networks significantly influence social integration, yet societal misconceptions impede inclusion, exacerbating feelings of isolation for both participants and caregivers. Limited interaction with technology is observed, primarily reliant on caregivers for assistance. Technology may hold potential for enhancing independence and alleviating caregiver burden. As an empathetic approach eased recruitment and communication with PwD, we recommend using this approach for future studies to include participants who otherwise would not be recruited. Given that the number of participants in this study is limited to only seven PwD with moderate to severe cognitive impairment, further investigation using mixed methods, including the READHY framework, and a larger number of participants is needed to examine the generalizability of the findings. Full article

In conventional engineering education, issues such as the discrepancy between virtual and real environments, rigid practical operations, lack of reflective support, and a disconnect between online and offline learning prevail. Digital twin technology, with its high fidelity and real-time interaction features, presents an innovative instructional aid for engineering education. This study developed a digital twin learning system to assist instructors in implementing project-based teaching models in landscaping technology courses. To assess the effectiveness of this system, a quasi-experiment was designed. Seventy students from a vocational high school majoring in landscaping technology in China were recruited as participants. These students were divided into two groups, each consisting of 35 students, with the same teaching pace. The experimental group utilized the system to supplement the instructor’s teaching of landscaping courses, while the control group received instruction through traditional methods. The experiment lasted for eight weeks, comprising a total of 16 classes. Ultimately, the results indicated that students in the experimental group significantly outperformed those in the control group in critical thinking, cognitive load, learning experience, and academic performance. Additionally, this research examined the acceptance of learners toward using the digital twin learning system and its influencing factors based on the Technology Acceptance Model, aiming to provide insights into enhancing engineering education courses teaching effectiveness and targeted technological development. Full article