Search Results (1,601)

This study examines the role of different factors in supporting the sustainable use of Artificial Intelligence (AI) technologies in higher education, particularly in the context of student interactions with intelligent and human-centered learning tools. Using Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN) within the Technology Acceptance Model (TAM), the research provides a detailed look at how trust influences students’ attitudes and behaviors toward AI-based learning platforms. Data were gathered from 200 students at Occidental Mindoro State College to analyze the effects of social influence, self-efficacy, perceived ease of use, perceived risk, attitude toward use, behavioral intention, acceptance, and actual use. Results from SEM indicate that perceived risk and ease of use have a stronger impact on AI adoption than perceived usefulness and trust. The ANN analysis further shows that acceptance is the most important factor influencing actual AI use, reflecting the complex, non-linear relationships between trust, risk, and adoption. These findings highlight the need for AI systems that are adaptive, transparent, and designed with the user experience in mind. By building interfaces that are more intuitive and reliable, educators and designers can strengthen human–AI interaction and promote responsible and lasting integration of AI in education. Full article

Objective: This study aimed to identify caregivers’ perceptions, preferences, and intentions regarding the use of digital articulation therapy applications for children with DLD. Methods: A cross-sectional online survey was conducted between August and September 2025 among 197 caregivers of children diagnosed with DLD. A 43-item questionnaire was structured into five domains addressing demographics, therapy experience, digital-therapy exposure, and preferences for application-based articulation therapy. Constructs from the Unified Theory of Acceptance and Use of Technology 2, including performance expectancy (PE), social influence (SI), price value (PV), facilitating conditions (FC), and behavioral intention, were analyzed. Results: Most respondents were mothers (96%), and 78.7% of them resided in urban areas. Among them, 84.3% had prior speech therapy experience. Only 15.7% had used educational or therapeutic applications; the main dissatisfaction factors were lack of fun (51.6%) and feedback (19.3%). Caregivers preferred short, engaging sessions (20–40 min per day), video-based (75%) or game-based (64%) content, and feedback every 2 months, with a reasonable monthly cost (20,000–30,000 KRW). Regression analysis revealed that sex (β = −0.451, p = 0.013), PE (β = 0.381, p < 0.001), and PV (β = 0.212, p = 0.034) significantly associated with behavioral intention to use an articulation-therapy application, whereas SI and FC were not significant. Conclusions: Caregivers of children with DLD demonstrated strong willingness to adopt digital articulation therapy applications, particularly when these tools provide meaningful therapeutic outcomes at moderate cost and include motivating, interactive content. Future application design should prioritize treatment functionality, user engagement, and accessibility to enhance adoption and continuity of digital speech-language interventions. Full article

As a financial center of Asia, Hong Kong has been the leading edge of fintech innovation, with the a leading ranking of the Global Innovation Index, which only ranked the fifth among all the payment methods in 2023 whereas mainland China achieved 90% acceptance in 2018. Since Hong Kong is part of China and shares similar origins and cultures, we found the need to study consumer behaviors in both of the two regions. We use comparison study methodology to find out the reasons of the difference in the usage. This research aims to investigate the factors influencing the acceptance of mobile payment services in Hong Kong and its difference in mainland China. In this research, we use the Partial Least Square Structural Equation Modeling methodology which discovers several significant factors influencing the actual use of mobile payment systems in Hong Kong and mainland China and tries to explain this. The findings will contribute to a better understanding of user behaviors and preferences, assisting stakeholders to address the challenges, develop effective strategies to increase the acceptance and use of mobile payment services, and promote payment convenience in Hong Kong. Full article

Research in “cybertherapy” has explored innovative ways to integrate new technologies as innovative tools in psychological treatment, such as virtual reality. Avatars, as digital representations of users within virtual environments, represent an interesting tool for psychotherapists: they could be used to assess aspects of patients’ self-representations (assessment), to promote behavioral change based on an alternative self-image (treatment), or to exercise therapists’ skills in diagnosis and assessment (formation). Yet, the use of avatars in psychotherapy is still not widespread. In the present study, 77 certified psychotherapists evaluated the three possible uses of avatars described above in terms of technology acceptance model (TAM) factors: perceived usefulness, perceived ease of use and intention-to-use. Partially confirming the TAM, the results show that perceived usefulness in particular is an effective predictor of intention to use avatars in psychotherapy for all three possible uses. Attitudes towards avatars as a psychotherapeutic tool were slightly influenced by mental health professionals’ methodological approach, with cognitive-behavioral psychotherapists showing more positive attitudes towards avatars as a training tool. On the other hand, previous experiences with other technologies (e.g., conducting therapy online or not) affected the perception of avatars’ ease of use as a treatment tool. The present study contributes to identifying factors that influence mental health professionals’ attitudes towards technological innovations in the psychotherapy profession, giving directions for future research in cybertherapy adoption. Full article

Manual wheelchair users with spinal cord injury (SCI) often experience upper-limb strain and pain due to repetitive propulsion. A detachable dual-propulsion add-on device has been developed to mitigate this issue by offering an alternative propulsion mechanism, but its user acceptability and practical benefits must be rigorously evaluated. This study will implement a structured mixed-methods usability assessment of the new device with 30 adult wheelchair users with SCI. The evaluation will combine quantitative surveys, objective task-based performance metrics, and qualitative interviews to capture a comprehensive picture of usability. We will conduct a single-arm mixed-methods protocol using a device-specific 45-item usability questionnaire and semi-structured interviews, followed by convergent triangulation to integrate quantitative scores and qualitative themes. Participants will use the dual-propulsion device in realistic scenarios and then complete a 45-item questionnaire covering effectiveness, efficiency, safety, comfort, and psychosocial satisfaction. In addition, semi-structured interviews will explore users’ experiences, perceived benefits, challenges, and suggestions. During a standardized mobility task course (doorway navigation, ramp ascent, threshold crossing, and 50 m level propulsion), objective performance indicators—including task completion time, task success/error rate, number of lever strokes, and self-selected speed—will be recorded as secondary usability outcomes. The use of both a standardized questionnaire and in-depth interviews will ensure both broad and nuanced assessment of the device’s usability. Data from the survey will be analyzed for usability scores across multiple domains, while interview transcripts will undergo thematic analysis to enrich and validate the quantitative findings. This protocol is expected to provide robust evidence of the device’s usability, inform iterative improvements in its design, and highlight the importance of structured usability evaluations for assistive technologies. Full article

Background: Digital technologies can contribute to healthcare democratization in an ethical, safe, and sustainable context. The remote monitoring of implantable cardiac devices enables the follow-up of patients from a distance. Patients with anti-bradycardia pacemakers represent the largest group and have the least access to this technology due to the controversial cost–benefit ratio and barriers to its widespread implementation, such as equipment costs and organizational challenges. In contrast, reimbursed transportation in Portugal reached approximately 82 million euros in 2024. Objectives: The aim of the present study was to assess the financial viability of remote pacemaker follow-up in a Portuguese district hospital, comparing the non-urgent transportation costs and the investment in remote monitoring equipment while measuring user acceptance and satisfaction. Methods: A total of 41 surveys were conducted with patients who received a pacemaker and used publicly reimbursed transportation. The projected costs were calculated for two simulated protocols: the first involved in-person visits every six months, while the second involved in-person visits every two years with remote consultations every six months, over the expected lifespan of the devices. EZR, version 1.61, was used. Results: Our data showed a 74% overall reduction in face-to-face visits. The implementation of remote follow-up would result in a cost saving of EUR 373/patient (21.2%), with total reimbursement (p = 0.01151). The savings increased to 33.3%, reaching EUR 764/patient (p = 0.0002742) for distances greater than 60 km (round trip) for ambulance users with total reimbursement. Acceptance and satisfaction achieved 88%. Conclusions: Remote monitoring of pacemakers can be a financially viable alternative with high acceptance and satisfaction. Full article

The management of age-related macular degeneration (AMD) presents a significant challenge attributable to high disease heterogeneity. Patient realization of symptoms is poor and it is urgent to treat before permanent anatomic damage results in vision loss. This is true for the initial conversion from non-exudative intermediate AMD (iAMD) to exudative AMD (nAMD), and for the recurrence of nAMD undergoing treatment. Starting from the essential requirements that any practical solution needs to fulfill, we will reflect on how persistent navigation towards innovative solutions during a 25-year journey yielded significant advances towards improvements in personalized care. An early insight was that the acute nature of AMD progression requires frequent monitoring and therefore diagnostic testing should be performed at the patient’s home. Four key requirements were identified: (1) A tele-connected home device with acceptable diagnostic performance and a supportive patient user interface, both hardware and software. (2) Automated analytics capabilities that can process large volumes of data. (3) Efficient remote patient engagement and support through a digital healthcare provider. (4) A low-cost medical system that enables digital healthcare delivery through appropriate compensation for both the monitoring provider and the prescribing physician services. We reviewed the published literature accompanying first the development of Preferential Hyperacuity Perimetry (PHP) for monitoring iAMD, followed by Spectral Domain Optical Coherence Tomography (SD-OCT) for monitoring nAMD. Emphasis was given to the review of the validation of the core technologies, the regulatory process, and real-world studies, and how they led to the release of commercial services that are covered by Medicare in the USA. We concluded that while during the first quarter of the 21st century, the two main pillars of management of AMD were anti-VEGF intravitreal injections and in-office OCT, the addition of home-monitoring-based digital health services can become the third pillar. Full article

Food waste is a global issue, and Macau is no exception. Throughout this study, it was found that most local bakeries in Macau employed promotional strategies to reduce surplus bread waste; however, a significant amount of unsold bread was still discarded. Meanwhile, as consumer behavior shifts toward environmental consciousness, technologies such as augmented reality (AR) are reshaping market dynamics. Many apps now incorporate the Sustainable Development Goals (SDGs) to raise consumer awareness. Within this context, this study recorded unsold bread types in real-time for four bakeries in Macau and integrated this information into an app system featuring interactive AR scanning technology to engage users and facilitate operations. Applying the Technology Acceptance Model (TAM), this study surveyed 163 local participants in Macau. Users expressed interest in immersive AR experiences that incorporated entertainment elements, allowing them to quickly search for and purchase surplus bread products, thereby reducing bread waste. However, excessive entertainment features were found to distract users from their purchasing goals, causing operational difficulties. Therefore, integrating AR into a well-structured shopping information system with streamlined operations would be more effective than adding excessive entertainment features. Future enhancements could include the addition of a comment section to facilitate discussion of the role of various virtual interactive systems in explaining surplus food concepts through experience. Emphasis should be placed on integrating sustainable practices into emerging technologies to increase users’ environmental awareness and achieve the Sustainable Development Goals. Full article

The rapid advancement of artificial intelligence (AI) in healthcare delivery has introduced innovative tools to improve patient care, streamline administrative processes, and bridge accessibility gaps. This study assesses how end-users perceive the practicality and usability of a proposed AI-enabled eGuide within Omani healthcare facilities, addressing cultural, linguistic, and regulatory requirements unique to the Sultanate. Through a mixed-methods framework combining stakeholder analysis, technological readiness assessment, and socio-cultural adaptation strategies, the research identifies the operational, economic, and ethical viability of the system. The current research results suggest that regulatory alignment, stakeholder engagement, and proper localization of AI-based eGuides will significantly enhance patient navigation after being tested on a wider dataset or real-world healthcare environments, reduce healthcare delivery bottlenecks, and increase patient satisfaction. Furthermore, digital literacy disparities, data privacy compliance, and infrastructure variability challenges need to be planned strategically and handled with care. This study offers a roadmap for policymakers and healthcare administrators to adopt AI-enabled eGuide systems that are both technically feasible and socially acceptable within the Omani healthcare ecosystem. Full article

This study presents an integrated evaluation framework for textile-based electrical muscle stimulation smartwear electrodes, combining physiological and user-centered assessments to ensure comprehensive performance analysis. Four electrode types—lock stitch, knit, hot stamping, and moss stitch—were examined using a systematic five-step process with nine participants. Quantitative measurements were obtained using electromyography to determine maximum voluntary contraction and tensiomyography to assess muscle contraction velocity. The knit electrode demonstrated a statistically significant reduction in maximum voluntary contraction following stimulation (W = 2.0, p = 0.012, Cohen’s d = 0.58), indicating effective neuromuscular activation and fatigue induction. The moss stitch electrode also showed a notable trend toward reduced muscle activation (W = 6.0, p = 0.055, d = 0.37). In contrast, the lock stitch and hot stamping electrodes exhibited negligible changes. User experience surveys revealed overall high acceptance across all electrode types (4.0–4.5 of mean scores on a 5-point scale), with the moss stitch electrode receiving the highest ratings for perceived safety and minimal skin discomfort, while the hot stamping electrode scored lowest in breathability. The proposed framework enables balanced evaluation of both functional performance and user experience, offering practical design guidance for optimizing textile electrodes across applications ranging from high-intensity athletic training to low-intensity rehabilitation. Full article

This review investigates the application of Explainable Artificial Intelligence (XAI) in biomedical informatics, encompassing domains such as medical imaging, genomics, and electronic health records. Through a systematic analysis of 43 peer-reviewed articles, we examine current trends, as well as the strengths and limitations of methodologies currently used in real-world healthcare settings. Our findings highlight a growing interest in XAI, particularly in medical imaging, yet reveal persistent challenges in clinical adoption, including issues of trust, interpretability, and integration into decision-making workflows. We identify critical gaps in existing approaches and underscore the need for more robust, human-centred, and intrinsically interpretable models, with only 44% of the papers studied proposing human-centred validations. Furthermore, we argue that fairness and accountability, which are key to the acceptance of AI in clinical practice, can be supported by the use of post hoc tools for identifying potential biases but ultimately require the implementation of complementary fairness-aware or causal approaches alongside evaluation frameworks that prioritise clinical relevance and user trust. This review provides a foundation for advancing XAI research on the development of more transparent, equitable, and clinically meaningful AI systems for use in healthcare. Full article

This study investigates the hydraulic transient behavior and optimization of air-vent configurations in the combined tailrace–diversion system of a hydropower station. The inlet flow boundary conditions were derived from the method of characteristics (MOC), and flow variations were incorporated into the CFD model using a user-defined function (UDF). The CFD results were validated by comparing them to MOC-based simulations of surge oscillations in the downstream chamber. Six different air-vent configurations, varying in number and diameter, were tested under high-water-level load-acceptance and load-rejection conditions. The results demonstrate that increasing the vent diameter, particularly to 3 m, significantly improves pressure regulation and air exchange efficiency, enhancing system stability. In contrast, simply increasing the number of vents did not lead to noticeable improvements. Sensitivity analysis of vent height revealed that raising the vent height from 12 m to 15 m provides sufficient freeboard to prevent overflow, without overdesign. These findings provide practical guidance for optimizing air-vent configurations in hydropower tailrace systems, improving hydraulic stability, and ensuring safe operation. Full article

Background: Poor mental health is a major contributor to absenteeism and turnover among nurses. Psychological flexibility may act as a protective factor for work-related well-being. This early-phase feasibility study explored the delivery of an online adaptation of Acceptance and Commitment Therapy (ACT) training for UK nursing professionals. Methods: A self-guided, 4-week online adaptation of an ACT training course was delivered via Moodle. Measures of professional quality of life, work engagement, and work-related psychological flexibility were collected at baseline and post-intervention (6 weeks). Feasibility outcomes included recruitment, retention, intervention adherence, and user engagement, assessed through platform usage statistics and user experience feedback. Results: A total of 43 participants enrolled in this single-group pre–post feasibility study. Recruitment targets were met, and completion of baseline measures was high. Engagement with course content was acceptable for an early-stage digital intervention. Among the well-being outcomes, work engagement showed the clearest indication of potential measure responsiveness. Retention was acceptable for the post-intervention survey but low for the usability survey and follow-up interview, limiting further exploration of engagement drivers. Conclusions: This study supports the feasibility of delivering online ACT training to nursing professionals. Key areas for refinement were identified, including closer integration with existing workplace communication and professional development systems, ongoing stakeholder involvement across study phases, and workplace-embedded engagement mechanisms to improve retention. Future research should further explore how workplace context influences intervention acceptability in larger feasibility trials. Full article

By 2050, most adults aged 65 and older in the United States will want to age independently at home, a goal that will strain healthcare resources. Adults aged 50 and older (N = 112) were recruited for study participation between 2018 and 2022. They completed surveys and participated in discussion sessions to explore their needs and opinions regarding smart home sensors. Survey results indicated that older adults’ comfort with smart home sensors increased with their perceived need for monitoring when home alone (OR = 1.46; p = 0.012) or sick/recovering from an illness (OR = 2.21; p < 0.001). When sick compared to when healthy, individuals were 2.65 times more likely to prefer installing multiple sensors in the living room, 1.75 times more likely in the kitchen, 3.66 times more likely in the bedroom, and 3.41 times more likely in the bathroom (p < 0.05). Regarding data sharing, participants were most willing to share information with healthcare providers and family members on a regular basis (80 and 81%, respectively) and 71% on a regular basis or when sick/recovering. Comfort with data sharing with professional caregivers (OR = 1.67; p = 0.0017) and monitoring companies (OR = 1.34; p = 0.030) significantly increased when sick/recovering. Discussion sessions highlighted overwhelming concerns about personal security/privacy, loss of independence, and ethical issues in data collection. Participants emphasized the need for new systems to be flexible, cost-effective, user-friendly, and respectful of user autonomy, accommodating diverse life stages, comfort levels, home environments, income levels, and support structures. Insights are now informing sensor data collection in our model home. Study findings underscore the importance of involving potential users in technology development to create effective and acceptable solutions for aging in place. Full article

Background/Objectives: The digitization of care opens up new opportunities to support family caregivers, who play a key role in home care. While telemedicine applications have already shown initial relief effects, AI-supported chatbots are increasingly coming into focus as an innovative form of digital support. The aim of this study was to build on an earlier study on the integration of telemedicine into home care and to conduct a complementary study on AI-based chatbots to analyze their acceptance, perceived benefits, and potential barriers from the perspective of family caregivers. Methods: The study comprises two consecutive online surveys with a total of n = 62 family caregivers. The first study assessed the use and acceptance of telemedicine systems; the second complementary survey examined attitudes toward AI-supported chatbots. Both questionnaires were developed based on a systematic literature review and in accordance with the Technology Acceptance Model (TAM). The dimensions of user-friendliness, data protection, communication support, emotional relief, and training needs were among those recorded. The data were evaluated using descriptive statistics, including comparative analyses between the two studies. Results: The results show that family caregivers generally have a positive attitude toward digital health solutions, but at the same time identify specific barriers. While technical barriers and privacy concerns dominated the telemedicine study, the AI results place greater emphasis on psychosocial factors. It also became clear that participants assumed that chatbots would be more acceptable if they were designed to be empathetic and dialogue-oriented. A comparison of the two data sets shows that the perceived benefits of digital systems are shifting from functional support to interactive, emotional support. Conclusions: The results suggest that AI-powered chatbots could offer significant added value to family caregivers by combining information sharing, emotional support, and self-reflection. In doing so, they expand the focus of traditional telemedicine to include a communicative and psychosocial dimension. Future research should examine the actual user experience and effectiveness of such systems in longitudinal and qualitative designs. Despite limitations in terms of sample representativeness and hypothetical usage estimates, the study makes an important contribution to the further development of digital care concepts and the ethically responsible integration of AI into home care. Full article