A large body of evidence suggests that the use of Artificial Intelligence (AI) is essential for shaping individuals’ labour market outcomes and will become even more important in the future. With this in mind, there is a risk that current disparities in AI usage between young men and women will further widen the existing gender wage and employment gaps. This paper examines gender differences in AI usage by analysing data from a large-scale survey conducted in 2024 among youth across 27 European countries. The findings reveal that young men are generally more likely than young women to have used AI-based applications, and this disparity is driven in large part by omitted or difficult-to-observe characteristics. Nonetheless, the size of the gender gap is quite small, and its direction changes depending on the specific tasks for which AI is used. In comparison to young men, young women are less likely to have employed AI for entertainment, creative activities, and personal organization and productivity. Conversely, young women are more likely to have used AI for schoolwork and studying and doing research.
The research focuses on the accessibility requirements in public requests for tenders concerning public online services in Finland from 2017 to 2023. According to Finnish legislation, published public online services must meet accessibility requirements. The study aims to understand the shortcomings of the current state of accessibility in public web services by analyzing the public procurement process. The procurement process sets the foundation by identifying requirements and specifications for development phase. The research examines the inclusion of accessibility requirements in public procurement documentation and how these requirements have evolved over time. The research also investigates the impact of legislation, standards, and guidelines on the procurement process and the accessibility of the resulting public online services in Finland. The study analyzed 66 different sets of tender documents from the period in question. The documents were retrieved from the commercial Mercell database, which compiles historical procurement data from Finland’s official HILMA public procurement system. The documents were selected using the search terms “online service” OR “website”. Based on these search terms, 170 procurement datasets from the selected period were identified fitting the scope, while 104 were excluded. The study points out findings on sanctions for Non-Compliance with accessibility standards, and other potential problems, such as inaccessible prototypes included in the bidding materials and responsibility issues when several different parties are involved in the project and user interface / user experience design. During the reviewed period (2017 to 2023), only half of the public calls for tenders included mandatory, legislation-based accessibility requirements, with varying quality. However, according to the study, the proportion of tenders containing accessibility requirements based on legislation has increased almost every year during the research period, reaching 80
Globalization has increased the flow of cross-cultural populations to various countries. However, most safety signs in each country were designed based on local culture and familiarity, often neglecting the needs of foreign populations. Thus, it is necessary to examine and redesign the signs for appropriate comprehension to ensure the safety of cross-cultural populations. This study aimed to evaluate and validate the original comprehension and the comprehension rate after redesigning based on applying the compatibility concept in ergonomic principles. Fifty-eight foreign participants completed comprehension and ergonomic principles tests on the 40 Chinese public prohibition signs. Familiarity, conceptual and physical compatibility of each sign were collected. Results indicated that 27 signs had poor comprehension rates (low than 67
Social (Pragmatic) Communication Disorder is a kind of communication disorder that predominantly influences the social aspects of language usage in a social environment. Individuals with such deficits are struggling to communicate and use social verbal cues, which might hinder their capacity to form their connections. Therefore, the primary objective of this work is to develop a user-friendly, interactive, and responsive application that can assist individuals with these deficits in enhancing social verbal communication skills. The proposed Android-based intervention focuses on improving social verbal communication skills using visual storytelling. This intervention generates specific words based on scenario images such as a birthday party scene, a scene of a train, a scene of a dining table, and so on. Further, the YOLO-V8 image-based object detection algorithm has been supported for the application backend. The extracted outcome for analyzing the social verbal communication skills has been conducted automatically through an implemented computer vision algorithm. The preliminary study implementing the proposed intervention engaged 29 participants aged 8 to 17 years with pragmatic communication deficits. In a pilot pre-post intervention, the intervention was developed with consideration of guardians’ and professionals’ requirements. The improvement was assessed using specific parameters from the Social Communication Disorder Scale. Additionally, the results were analyzed using statistical measures (mean, standard deviation) and tests (t-test). The intervention resulted in significant improvement in the social verbal skills of individuals with deficits. Before implementing the intervention, the statistical analysis values for the SCDS scale were as follows: a mean of 1.44 and a standard deviation of 0.12, with a t-value of − 6.14. After the intervention, the SCDS values changed to a mean of 1.67 and a standard deviation of 0.21 and a confidence level of 0.05. Based on these statistics, the hypothesis suggests that there has been a significant improvement in the performance of individuals following the successful completion of the intervention. The study concluded that the application effectively promotes social verbal communication skills. The reviews from guardians and professionals indicate that the proposed intervention is acceptable, based on important criteria such as adaptability, user experience, scalability, interface, reliability, responsiveness, time efficiency, and accessibility. The storytelling intervention that was implemented resulted in a significant improvement in social verbal communication skills.
The growing complexity of educational pathways and the increasing diversity of learner profiles have strengthened the need for recommender systems that are not only accurate but also adaptive and explainable. Neuro-symbolic approaches respond to this need by combining explicit symbolic reasoning (e.g., rules, ontologies, and logic) with neural models particularly graph neural networks (GNNs) operating over knowledge graphs (KGs). This systematic literature review analyzes how neuro-symbolic educational recommender systems represent, operationalize, and integrate symbolic and neural components across educational recommendation tasks, and it identifies the methodological and conceptual challenges that remain. Following PRISMA 2020 guidelines, we reviewed 21 peer-reviewed studies published from 2019 to January 2026, retrieved from major scientific databases. The included works were analyzed across five dimensions: recommendation task, target users, knowledge representation, symbolic reasoning mechanism, and fusion strategy. The results show a clear shift toward hybrid KG-centered architectures, while revealing persistent limitations, including shallow or weakly operationalized symbolic reasoning, limited explainability evaluation, static and domain-bounded knowledge graphs, and insufficient integration of pedagogical or policy-driven constraints. Overall, this review provides a structured synthesis of current practices, highlights key research gaps, and outlines actionable directions to support next-generation educational recommender systems that better balance adaptability, semantic grounding, and transparency.
To empirically examine how AR experiential features (presence, interactivity, vividness) affect patient satisfaction with AR-enabled intelligent rehabilitation systems, and assess both the mediating role of perceived rehabilitation effectiveness and the moderating role of gender in these relationships. Drawing on the logic of the Stimulus-Organism-Response (S-O-R) framework and user experience theory, we developed a research model and tested it using data from 323 patients in tertiary hospitals in eastern China, a region noted for its advanced healthcare infrastructure. The model was validated through Structural Equation Modeling (SEM) combined with moderated mediation analysis. All AR experiential features show significantly positive relationships with satisfaction. Perceived rehabilitation effectiveness partially mediated the relationships between experiential presence/interactivity and patient satisfaction. Males show greater sensitivity to the interactivity feature, whereas females show greater sensitivity to the vividness feature when patients perceive the effectiveness of rehabilitation. These findings establish AR experiential features as critical determinants of satisfaction with AR rehabilitation technology, while revealing gender-moderated response patterns. The results theoretically contribute to the research on patient satisfaction in AR healthcare services and the understanding of perceived rehabilitation effectiveness within this domain. Practically, it necessitates gender-responsive design paradigms to optimize therapeutic interfaces, facilitating the development of user-centered rehabilitation technologies that meet patients’ psychological needs and maximize clinical benefits.
This systematic literature review examines the role of cultural dimensions in user interface (UI) design and user experience (UX), with a focus on the comparative effectiveness of culturally adaptive versus culturally neutral interfaces. The review synthesises 19 peer-reviewed empirical articles published between 2020 and 2024, identified through a systematic multi-stage screening process across five leading academic databases, following PRISMA guidelines to ensure transparency and reproducibility. The findings indicate that cultural dimensions, particularly individualism/collectivism, uncertainty avoidance, and power distance, as conceptualised in Hofstede’s framework, significantly influence user interaction behaviours and technology usability. Across the reviewed studies, culturally adaptive interfaces tend to yield higher levels of user satisfaction and engagement compared to culturally neutral designs, although this pattern is most evident within specific regional contexts. The review acknowledges a pronounced geographic concentration, with the majority of included studies drawing on participants from Asia and the Middle East. The findings should therefore be interpreted as regionally situated rather than universally generalisable. This review provides an integrated synthesis across multiple application domains, including mHealth, e-learning, e-commerce, and immersive technologies. It also identifies persistent gaps in cross-cultural UI/UX research, including limited geographic representation, continued reliance on Hofstede’s framework, and the early-stage development of culturally responsive design in augmented reality (AR) and virtual reality (VR) environments.
The global prevalence of visual disabilities is increasing, significantly impacting the quality of life and social inclusion of those affected. Existing technologies, while helpful, continue to face challenges in terms of cost, accessibility, and real-time effectiveness. Individuals with visual impairments face significant barriers in their daily interactions with the environment, limiting their independence and social participation. The lack of adaptable and personalized solutions that address these specific needs remains a significant barrier. This study presents an extension of the Modeling Scenarios of the Internet of Things (MoSIoT) framework, a platform designed to improve the quality of life of people with disabilities by enhancing their interactions with IoT devices. The enhanced MoSIoT framework uses artificial intelligence and augmented reality technologies to significantly improve navigation and environmental interaction, enhancing the well-being of individuals with visual impairments. The proposed enhancements include advanced object detection, scene recognition, and augmented reality geolocation, all tailored to provide a richer and more autonomous user experience. A case study conducted as part of this research illustrates the practical application of these technologies in a real-world scenario, demonstrating how they can be used to support individuals with visual impairments in various everyday contexts. Practical tests conducted using tools such as YOLO for object recognition and Azure IoT for device integration have significantly improved user autonomy and quality of life. The results show that the enhanced framework can facilitate more effective environmental interaction and better social inclusion, highlighting its potential for implementation across different contexts and devices.
In an era where digitalization is transforming mobility, ensuring fair access to digital transport services is crucial. This paper evaluates the inclusivity of various digital transport services using the INDIMO Service Evaluation Tool (SET). Developed through a co-creation process and grounded in Universal Design principles, the SET expands the framework by integrating 'social, spatial, and economic inclusivity' and 'security and data protection' to address accessibility in the digital context. It employs a self-assessment questionnaire with quantitative metrics and provides tailored recommendations for service improvements. Five digital transport services were evaluated by 16 experts in accessibility and mobility, including developers, operators, and policymakers. The services assessed were multimodal route planning (Citymapper), car-sharing (Cambio), ride-sharing (BlaBlaCar), food delivery (Uber Eats), and parcel lockers (Bpost lockers). The results revealed significant variability in inclusivity scores. Cambio scored highest (71
Equitable access to tactile information for persons with visual impairments depends not only on content availability, but critically on the technology chosen to physically reproduce that content in a given institutional context. In practice, technology selection is rarely formalised: decision-makers must simultaneously balance geometric compliance with Braille standards, relief durability, cost, infrastructure requirements, and content-development flexibility, representing criteria that are heterogeneous and partly uncertain. This article presents a reproducible decision-support framework for the preliminary selection of Braille formation technology in the context of universal access to information. The framework integrates the Analytic Hierarchy Process (AHP) with triangular fuzzy logic, formalising linguistic judgements and reducing the influence of subjective interpretation when comparing seven representative technologies: mechanical embossing, thermoforming, electronic tactile displays, manual methods (Slate Stylus), CAD-based modelling, FDM, and SLA/DLP additive manufacturing. Criteria weights were derived through structured pairwise comparisons, subsequently cross-checked with domain specialists; fuzzy scores were assigned using a standardised linguistic scale grounded in established technical specifications and peer-reviewed literature. The framework is demonstrated through scenario analysis corresponding to the production of tactile educational materials in a resource-constrained institutional setting. Sensitivity analysis confirms that the resulting ranking is stable across ten-percent variations in criterion weights. All computations are implemented in a fully reproducible Python/Google Colab environment provided as supplementary material. The proposed approach constitutes a transparent, auditable decision-support tool for pre-selection of Braille production technologies, directly relevant to accessible and inclusive information-society systems.
Sign language is an essential communication tool for individuals with hearing and speech impairments, who often face significant challenges in interacting with others in their daily lives. This study addresses these challenges by developing a recognition system for Turkish Sign Language (TSL) tailored to healthcare settings. To achieve this, surface electromyography (sEMG) and inertial measurement unit (IMU) signals are collected from the Myo armband during dynamic TSL gestures. A dataset is created with recordings from 19 participants performing word-based and sentence-based gestures. The recorded signals are transformed into 2D images—sEMG signals via direct channel summation and IMU (Gyro) signals via 2D Mel spectrogram—and classified using five variants of the YOLOv8 model. In the subject-dependent analysis, the highest classification accuracy for IMU signals is achieved by YOLOv8s and YOLOv8m on the word-based dataset (0.85) and by YOLOv8x on the sentence-based dataset (0.85), while sEMG-based classification accuracy reaches up to 0.76 (YOLOv8n, word-based) and 0.84 (YOLOv8l, sentence-based). For the combined word–sentence dataset, IMU-based classification accuracy achieves up to 0.85 under YOLOv8x and sEMG-based classification accuracy reaches up to 0.75 under YOLOv8x and YOLOv8m. For subject-independent evaluation using the Leave-One-Subject-Out (LOSO), ResNet18 and EfficientNet-B0 achieve the highest Top-1 accuracies—up to 0.94 for IMU and 0.88 for sEMG signals—outperforming YOLOv8m and the raw signal-based 1D-CNN baseline across word-based, sentence-based, and combined datasets. This study provides a detailed evaluation of sEMG and IMU as separate inputs for gesture recognition and demonstrates the potential of Convolutional Neural Network-based to address real-world communication challenges faced by TSL users.
Accessibility barriers in block-based programming environments (BBPEs) continue to hinder equitable participation in computer science education, particularly for learners with disabilities. While prior research has examined accessibility challenges for programmers with visual impairments, BBPEs introduce additional barriers due to their highly visual and drag-and-drop nature. This paper presents a systematic literature review of 22 peer-reviewed studies focusing exclusively on accessibility in virtual BBPEs such as Blockly, Scratch, and App Inventor. The review identifies six core categories of barriers–interaction and input limitations, navigation and orientation difficulties, inaccessible content and outputs, cognitive load, assistive technology conflicts, and educational or technical constraints. It also synthesizes proposed solutions, including accessible keyboard navigation, voice-based interaction, screen reader integration, program navigation models, and inclusive interface design. Despite promising developments, such as Accessible Blockly and Blocks4All, existing research remains fragmented and primarily focuses on visual impairments. This review consolidates the state of knowledge, exposes underexplored disability groups, and outlines a research roadmap for designing universally accessible block-based programming environments that promote inclusive computer science education.
The global population is going through a significant demographic shift and the percentage of individuals aged 65 and over is projected to increase globally. This demographic transition brings forth challenges associated with aging, including an increased prevalence of non-communicable diseases and disabilities. Falls are a particularly common and serious concern for the elderly, highlighting the growing need for comprehensive care and support systems. Such systems should encompass primary, acute, and end-of-life care, as well as assistance with activities of daily living (ADL). There is a growing need for comprehensive care and support systems encompassing primary, acute, and end-of-life care, along with assistance in daily activities. Abnormal Behaviour in Activities of Daily Living (AB-ADL) among elderly individuals present significant health risks and challenges. Nevertheless, minimal published literature is available on a generic context-aware architecture focused mainly for detection of different AB-ADLs in smart-home environment that computer scientists or software developers can utilise and adapt to a particular use case scenario, as most existing context-aware architectures are scenario-specific. To address this gap, a systematic review is conducted in this paper to illustrate the key components of context-aware systems through an architectural representation. Also, this paper aims to explain how systems are designed to effectively detect various types of AB-ADLs among elderly individuals in smart-home environments, using appropriate technologies and methodologies, as well as how these systems are evaluated for performance and effectiveness. For this, 43 recently published papers were systematically reviewed and analysed. Following the review, a generic architecture for context-aware system for performing Abnormal Behaviour Detection in Activities of Daily Living (ABD-ADL) of the elderly in smart-home environment was realised, and it was found that there is no agreed consensus on the tools and technologies used in the build-up of such systems. Similarly, various approaches are used to evaluate such systems and the most common one is through case studies. A lack of frameworks that guide the evaluation process was noted. This paper presents key research concerns and potential for future study based on the data reported.
Blind children in remote mountainous areas suffer from a lack of specialized teachers and learning tools. Traditional distance education often fails to address their specific need for tactile interaction and real-time feedback. This study aims to design and empirically evaluate a collaborative remote Braille learning system to promote educational equity for visually impaired children in underserved areas. This study integrates Quality Function Deployment (QFD) and the Function-Behavior-Structure (FBS) model to bridge the gap between user needs and engineering design. Through interviews with 20 blind students, 16 parents, and 4 teachers, user needs were weighted and translated into functional specifications. Validation via the Critical Incident Technique (CIT) demonstrated that the system’s optimized structural features and real-time audio-tactile feedback loops significantly reduced the cognitive load associated with tactile decoding. This feedback mechanism enabled independent error correction, a critical capability previously unattainable in traditional remote settings. Furthermore, the supporting mobile applications successfully bridged the literacy gap for sighted parents, facilitating data-driven tutoring and continuous monitoring in home environments. This study presents a scalable, low-cost solution to advance remote Braille literacy. While QFD and the FBS model served as effective frameworks for translating complex user needs into engineering parameters, the primary contribution lies in the realization of a synchronized haptic-digital ecosystem. This approach significantly mitigates the geographic and sensory barriers faced by visually impaired children in under-resourced regions, promoting broader educational equity.
The acceleration of digital innovation has widened the accessibility gap between users with and without disabilities, highlighting the need for inclusive software development frameworks that are both adaptable and scalable. This paper presents the MEEXUU framework, an inclusive design methodology that integrates principles from disability interaction, user-centered design, and inclusive design, extending the original MEEXUU approach previously applied to extended reality environments. Drawing on the ACD toolkit as a methodological foundation, the framework introduces a card-based toolkit and contextual support tools designed to simulate situational, temporal, and social constraints in real-world usage scenarios. To validate the framework, an expert evaluation was conducted with nine international specialists in human–computer interaction and inclusive design from Spain, Portugal, and Mexico. Each of the framework’s components was assessed along four dimensions, accuracy, relevance, coherence, and clarity, using a structured questionnaire. Cronbach’s alpha coefficients indicated good to excellent internal consistency in three categories ( α > 0.72 ), while clarity revealed opportunities for refinement ( α = 0.575 ). The results provide promising insights into the MEEXUU framework’s potential as a versatile, theoretically grounded, and empirically supported tool for promoting digital inclusion. The paper contributes to both research and practice by embedding accessibility as a core element throughout the software development lifecycle.
Touchless interactions, like mid-air gestures, show promise in enhancing interaction and communication for individuals with physical disabilities. This study explores how mid-air gestural interaction can improve the accessibility of touchscreen devices, like tablets and other touchscreen tablet-like devices, for individuals with Multiple Sclerosis and dexterity impairments (MS-Dex). Two studies were conducted. The first, assessed the challenges faced by ten MS-Dex participants with conventional tablet interactions. The second, adopting a user-centered design approach, explored mid-air gesture preferences among ten MS-Dex participants, aiming to develop alternative, more accessible interaction methods and to identify potential gestures for a touchless vocabulary. Gesture elicitation sessions were conducted, during which video recordings and Leap Motion Controller tracking were employed to record gesture metrics. This data was used to identify natural hand gestures suitable for 18 common tablet interaction scenarios. Both studies were compared holistically to understand the interplay between user challenges and gesture preferences, informing the development of effective and accessible touchless interaction solutions. The first study identified significant difficulties with activities requiring extensive movement and coordination. The second study showed that the elicited gestures were perceived as effective, intuitive, and easy to execute, confirming their accessibility for MS-Dex participants. Preference for gestures that minimized precise finger coordination and extensive hand movements was noted. This research contributes to understanding the physical aspects of mid-air gestural interactions, suggesting design directions for more accessible tablet interfaces and providing insights into developing a standardized touchless gesture vocabulary, ultimately promoting greater accessibility for individuals with MS-Dex.
To assess the quality of health information regarding hemodialysis on four major social media platforms: TikTok, Bilibili, Kuaishou, and the Little Red Book. This study aimed to analyze the differences in content quality among different platforms and identify the influencing factors, thereby providing a foundation for optimizing the dissemination of medical and health information. In May 2025, videos were retrieved from the four platforms using “hemodialysis” as the keyword. After eliminating duplicates, the videos were comprehensively evaluated and correlations between video quality and characteristics such as duration, number of likes, comments, shares, and year of publication were investigated. Among 388 included videos, the distribution across the four platforms was relatively balanced. In terms of content integrity, six of the eight dimensions exhibited significant platform differences. Kuaishou demonstrated the highest scores in the health education dimension, while Bilibili excelled in vascular access and indications. Kuaishou and Bilibili showed superior reliability and overall quality scores. The reliability of the videos was positively correlated with user interactions. The overall quality of the videos was significantly and positively correlated with the number of shares and video reliability, and significantly and negatively correlated with the year of publication. The quality of health information on hemodialysis across social media platforms is uneven. Platform characteristics, the nature of publishers, and the time of publication all influence information quality. Content review mechanisms should be optimized to enhance the professionalism and reliability of information, enabling the public to access scientific health information.
Grounded in the Technology Acceptance Model 3 (TAM3), this study examines how virtual reality (VR) panoramic video experiences influence behavioral intention (BI) and travel destination decision-making (TDDM) among Chinese middle-aged and older tourists aged 45 and above. Specifically, the study investigates the roles of perceived ease of use, perceived usefulness, perceived immersion, perceived enjoyment, technology anxiety, social influence, and skepticism in shaping VR-related acceptance and downstream travel decision tendencies. A lab-based VR experience experiment and structured questionnaire survey were conducted with 183 valid participants, and the proposed model was tested using partial least squares structural equation modeling (PLS-SEM). The results show that perceived immersion significantly enhances perceived ease of use, perceived usefulness, and behavioral intention, while perceived enjoyment positively influences perceived ease of use. Technology anxiety negatively affects perceived ease of use. In addition, perceived ease of use and perceived usefulness both positively predict behavioral intention, and social influence exerts a significant but relatively modest positive effect on behavioral intention. Behavioral intention, in turn, significantly promotes travel destination decision-making, whereas skepticism significantly and negatively affects travel destination decision-making but does not significantly influence perceived usefulness. These findings suggest that VR panoramic videos can serve as an effective pre-travel decision-support tool for middle-aged and older tourists. The study extends prior VR tourism research by incorporating downstream travel destination decision-making into a TAM3-based framework and by providing empirical evidence from a middle-aged and older user group in China.
With the rapid growth of the aging population, older adults face increasing difficulties in maintaining social connections, overcoming loneliness, and adapting to digital environments. This study investigates how explainable AI (XAI) social assistants influence older adults’ digital interactions, focusing on their effects on social satisfaction, human–AI trust, and digital anxiety. A controlled experiment was conducted in Shenyang, Liaoning Province, China, in January 2025, comparing traditional social assistants with XAI-powered systems. The results demonstrate that older adults using XAI assistants reported higher levels of social satisfaction and AI trust while experiencing reduced digital anxiety. These findings suggest that the transparency and intuitive design of XAI can ease the psychological barriers associated with technology use and enhance social engagement. This study contributes to the advancement of AI-driven social platforms tailored for aging populations, emphasizing the need for AI systems designed to support the psychological well-being and digital adaptation of older adults.
While the use of social media has been researched extensively among older adults, gaining a deeper understanding of their e-health literacy is crucial for promoting meaningful interventions and enhancing their overall well-being. This study addresses this gap by investigating the roles of social media acceptance beliefs and usage satisfaction. The study surveyed 709 adults aged 55 and above from Taiwan (mean age = 69.17; 83
