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Objective: Our study addresses the challenges limiting the adoption of Extended Reality (XR) Head-Mounted Displays (HMDs), mainly focusing on device quality and cybersickness. We aim to investigate the impact of hardware and software on user experience and task performance while wearing Video See-Through (VST) HMDs. We employ a novel methodology designed to bridge the gaps identified in previous research.Methods: This study uses a convergent mixed-methods approach, combining qualitative and quantitative data in a within-subjects evaluation involving 20 participants. This comprehensive evaluation examines visual perception, visual quality, and user experience through a range of tasks. Usability, comfort, and cybersickness are assessed, with insights derived from both user performance metrics and subjective measures collected through in-depth interviews and comments. The study includes three distinct HMDs—two prototypes (PD1 and PD2) and one commercial device (CD1)—to provide a broad analysis of the technology.Findings: Our findings reveal that while participants were generally satisfied with VST mode, their preferences varied across devices. CD1 was preferred for its realistic color representation and superior reading task performance due to its high-resolution display and camera. However, visual disturbances and temporal issues differed across devices, with CD1 exhibiting fewer artifacts when stationary but showing more disturbances when participants were moving. Participants found PD1 and PD2 more comfortable for extended use and fewer cybersickness symptoms, but they highlighted color and display resolution issues. These variations underscore the importance of considering both qualitative and quantitative measures in HMD evaluations.Conclusion: This mixed-methods evaluation emphasizes the limitations of relying solely on visual perception performance measures for VST HMDs. By integrating both quantitative and qualitative insights, we offer a more detailed evaluation framework to identify design flaws and user experience issues that quantitative metrics alone might miss. This methodology contributes to the field by illustrating how a mixed-methods approach provides a broader perspective on XR technology, guiding future improvements and enhancing VST adoption in future applications.

Firms are beginning to use chatbots to collect information from users (e.g., online reviews), a task traditionally done through forms. We used two experiments to investigate how collecting reviews using chatbots in place of forms might impact user experience and, in turn, alter the nature of the reviews submitted by users. Study 1 compares chatbots to web forms, finding that chatbots may improve perceived efficiency but otherwise have no discernible effect on satisfaction and usage intention. At the same time, chatbot usage results in shorter, lower-quality reviews. While structured templates enhance form-based reviews, introducing structure to chatbot interactions does not positively impact satisfaction and usage intent, potentially making the process less efficient. Nonetheless, a structured chatbot approach yields longer reviews and mitigates declines in quality. Adding structure to a chatbot takes the chat out of the chatbot, turning the interaction from casual conversation to a formal process, as demonstrated in Study 2. Hence, while this structured approach for chatbots improves review quality without harming satisfaction and usage intent, it may not be the most effective method for enhancing the reviewer experience. Our research shows that the chatbot and structure pulled users towards contradicting genre rules (the social structures that guide technology use) and triggered users to subconsciously enact distinctly different thought patterns as they composed reviews. [ABSTRACT FROM AUTHOR]

Institutions in the GLAM (galleries, libraries, archives, and museums) sector serve the public as institutions for cultural heritage, identity, education, experience, and leisure. The goals of these institutions are becoming more closely aligned and they have shared a turn from being collection-centred to a focus on users and visitors. When these institutions also face similar challenges brought on especially by digitalization, there is increasing discourse in scholarly literature and among GLAM professionals about the drivers, impacts and opportunities of convergence for the sector. There remains however, scant empirical examination of user/visitor perception and experience of such convergence. This research addresses this knowledge gap and investigates a converged GLAM case institution, Te Ara 'Atea in New Zealand through a user/visitor survey. The survey findings suggest that users/visitors perceive and experience fewer issues with convergence relative to benefits. A novel insight from this research is that the concept of GLAM convergence can positively contribute to cultural and community wellbeing. As for perceived issue within the convergence space, of particular interest is the concept of unsanctioned touch of displayed objects/artworks, and the alleged unclear behavioral norms in converged environments. The findings also point to further considerations and implications regarding GLAM disciplinary boundaries. [ABSTRACT FROM AUTHOR]

Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers' cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines. [ABSTRACT FROM AUTHOR]

AbstractArtificial intelligence (AI) decision support systems are crucial in modern decision-making processes. Their increasing human-like adaptability introduces challenges, especially when their recommendations, for whatever reason, need to conflict with user preferences. This study examines the communication strategies AI systems should employ when their recommendations conflict with user preferences. We explored this research question through a hypothetical future interface where ChatGPT offers travel recommendations populated on a map. An online survey-based experiment was conducted, presenting 160 participants with ChatGPT-generated travel recommendations displayed alongside Bing map visuals. We employed a mixed-method experimental design, combining both between-subjects and within-subjects approaches, to investigate the impact of conflicting recommendations and the acknowledgment of user preferences on the acceptance of these recommendations. This effect is especially pronounced when the AI system acknowledges users’ preferences yet still offers conflicting recommendations to them. Contrary to the expectation that acknowledging users’ preferences could buffer the impact of such conflicts, our observations indicate the contrary. The presence of conflict following acknowledgment of users’ preferences, significantly causes a backfire effect, leading users to reject the recommendations. These findings underscore the need for consideration of recommendation delivery strategies in AI decision support systems and offer insights for designing future user interfaces and user experience research in the realm of recommendations provided by AI decision-support systems. [ABSTRACT FROM AUTHOR]

AbstractThis study presents a novel framework to evaluate the usability and user experience of e-learning platforms, focusing on the Duolingo language learning app. By integrating advanced Natural Language Processing (NLP) techniques such as Large Language Models (LLMs), Latent Dirichlet Allocation (LDA), and sentence embedding models, we identified thirteen key usability and user experience topics from a large dataset of user reviews. Our findings reveal that Duolingo is highly rated since users value its enjoyable learning experiences and effectiveness. However, technical issues, lack of explanations, and frustrating features were identified as areas for improvement. The study demonstrates the effectiveness of our framework in analyzing user feedback at scale, offering valuable insights for improving user experience in e-learning platforms and other domains. [ABSTRACT FROM AUTHOR]

Large language model (LLM) based AI applications are being rapidly adopted by various creativity-related sectors, including UX design. However, as newly emerged applications, how UX designers work with LLMs and how to optimize the benefits of LLMs in UX design remain unclear. Leveraging the widely adopted LLM application ChatGPT as a case study, we recruited 12 experienced frontline UX practitioners from IT companies to use ChatGPT in their everyday design activities for 4 to 6 weeks. Through use logs, questionnaires, and interviews, we collected participants’ usage and reflection data. Our analysis reveals the different functions of ChatGPT in facilitating UX design, such as offering design guidelines, constructing user profiles, and simulating stakeholders. Challenges also emerged, such as limitations in understanding complex design problems and prototyping design ideas. Based on the findings, we reflect on the working dynamics between human workers and AI tools and suggest implications for designing more usable LLM-based AI applications. [ABSTRACT FROM AUTHOR]

Despite being able to predict accurate user-item interactions, recommender systems also lead to homogeneous information flow, resulting in negative online experiences. However, users' coping processes for this stressful event remain basically unclear. Drawing on coping theory, this study examines how users appraise two stressors (information narrowing and information redundancy) in homogenous information flow, especially in different user experiences, and thus adopt algorithmic resistance and avoidance coping strategies. Data (N = 407) were collected based on a survey. The empirical results indicate that information narrowing and information redundancy are significantly and negatively related to challenge appraisal, and exert significant and positive effects on threat appraisal. The moderating effect denotes that user experience strengthens the relationship between information narrowing and information redundancy to threat appraisal. Threat appraisal further triggers algorithmic resistance and avoidance of users. The paper provides several implications for theory and research by revealing the mechanism through which recommender systems users cope with homogeneous information flow. Our findings also provide new insights for designers of recommender systems platforms. [ABSTRACT FROM AUTHOR]

Office work often results in long bouts of time spent sitting without moving, accumulating prolonged static posture (PSP), which might cause musculoskeletal discomfort (MSD). Although sit-stand desks (SSD) allow posture changes, employees do not use them sustainably. In order to automate posture adjustments, an intelligent SSD with an interactive system (iSSD) was created. This study assessed the impact of the iSSD on postural hygiene and explored the user experience. Ten office employees working remotely from home (teleworkers) used the iSSD with (phase B) and without (phase A2) automation. The usage data of the iSSD was measured daily by sensors. We assessed MSDs and working conditions through questionnaires. Semi-structured interviews evaluated participants' satisfaction. Results showed a 29% decrease in sitting time and absent PSP for phase B. Subsequently, in phase A2, the sitting time returned close to baseline values. Questionnaires reported MSD alleviation and stability of working conditions. Interviews confirmed automation's benefits for maintaining postural hygiene. Findings suggest that an interactive system can facilitate SSD adoption and promote postural hygiene at the office. HIGHLIGHTS: We added an interactive system to a usual sit-stand desk to force posture change. We tested iSSD usability by teleworkers through data tracked by the system sensors. We conducted qualitative interviews to assess participants' satisfaction with iSSD. Using an iSSD could help office workers reduce prolonged static postures. Participants appreciated automated posture changes imposed by the interactive system. [ABSTRACT FROM AUTHOR]

Assessing User eXperience (UX) maturity is mandatory in the free and open-source software (FOSS) community to avoid wasting resources on projects that may fall short of expectations. Best practices suggest employing UX Capability Maturity Models (UXCMMs), which often specify an evolutionary plateau toward developing a UX-matured system and quantify organizational UX maturity into maturity levels ranging from no or ad hoc improvement to integrated continuous improvement. Numerous generically developed UXCMMs exist. However, none is created for the FOSS community, and less information is available to support their perfect match. Thus, raise suspicions if they have proper UX maturity influencing factors (UXMIFs) for the FOSS community or measure the right thing. The FOSS community differs from traditional software-developing communities and may have different dynamics and UXMIFs, necessitating unique and new methodologies for their discovery. This study, therefore, aims to identify the FOSS community's UXMIFs and evaluate the community's knowledge of UX maturity-related concepts. Its findings may help future researchers, practitioners, and other FOSS developers to develop UXCMMs exclusive to the FOSS community. The study's design is both qualitative and quantitative. It adopted a systematic literature review, interviews, fuzzy Delphi Method, and thematic analysis to collect and analyze data and present the findings. The study's sample included sixty-two active FOSS projects, fifteen FOSS stakeholders, and twelve UX experts. The outcome shows that 84% of UX experts agreed on the thirty-six FOSS's UXMIFs with threshold d = 0.143 and crisp values greater than α-cut = 0.5. User feedback and adopted technologies were ranked first, while learnability and use speed were ranked last. Similarly, FOSS stakeholders have shown a shared understanding of UX maturity, connected concepts, and impacting factors. [ABSTRACT FROM AUTHOR]

Fear of artificial intelligence (AI) has become a predominant term in users' perceptions of emerging AI technologies. Yet we have limited knowledge about how end users perceive different types of fear of AI (e.g., fear of artificial consciousness, fear of job replacement) and what affordances of AI technologies may induce such fears. We conducted a survey (N = 717) and found that while synchronicity generally helps reduce all types of fear of AI, perceived AI control increases all types of AI fear. We also found that perceived bandwidth was positively associated with fear of artificial consciousness, but negatively associated with fear of learning about AI, among other findings. Our study provides theoretical implications by adopting a multi-dimensional fear of AI framework and analyzing the unique effects of perceived affordances of AI applications on each type of fear. We also provide practical suggestions on how fear of AI might be reduced via user experience design. [ABSTRACT FROM AUTHOR]

In practical production applications, the efficiency and success rate of gesture recognition directly affect the user experience and work efficiency. However, the existing gesture recognition models have the problem of a large number of model parameters and high computational complexity, which makes them unable to meet the needs of end‐to‐end industrial deployment. To solve these problems, this article proposes a gesture recognition model based on YOLOv8. First, FasterNet is adopted as the backbone of YOLOv8, which significantlydecrease the number of parameters and made the model more lightweight. By reducing the number of parameters, the computational complexity of the model can be reduced while maintaining the performance of the model, and the operation efficiency of the model can be improved. Second, recombination convolution ScConv is introduced to replace common convolution operations to further improve the model's efficiency. Recombination convolution can reduce the computation and make up for the loss of precision to some extent. Finally, the MDPIoU loss function is used to optimize target location and prediction, to improve the accuracy of the model. The MDPIoU loss function can better deal with the problem of target boundary frame positioning and prediction so that the model can locate and predict gestures more accurately in gesture recognition tasks. Experiments on a data set containing 10 types of gestures show that the number of parameters and floating point calculations of the improved network model are reduced by 45% and 42.7%, respectively, while the accuracy is unchanged. The improved model can be deployed on edge terminals, providing efficient and accurate gesture recognition. [ABSTRACT FROM AUTHOR]

AbstractPurposeMethodResultConclusionPharyngeal residue rating scales are often used to rate pharyngeal residue observed during flexible endoscopic evaluation of swallowing. Despite the widespread use of pharyngeal residue rating scales, there is no data that has systematically explored user experience. The aim of this scoping review was to investigate specific reporting of user experience, user centred design principles, and normative data in the development of pharyngeal residue rating scales.A scoping review was conducted across four electronic databases inclusive of all dates until June 2024. Grey literature searching occurred in March–April 2023 and was repeated in June 2024. This review followed the Preferred Reporting Items for Systematic Review and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) protocol. Titles/abstracts, full texts, and data extraction were reviewed by two independent reviewers.A total of 22 sources were included, with 18 unique pharyngeal residue rating scales identified. Two studies referred to user experience, seven included at least one user centred design principle, and four studies reported on normative data.The findings of this review highlight few pharyngeal residue rating scales include the experience of the intended user and establish normative data in the initial development phase. User experience, user centred design principles, and normative data may be useful considerations to optimise functionality. [ABSTRACT FROM AUTHOR]

Although Virtual Reality (VR) holds massive potential, its applicability still faces challenges because some individuals experience cybersickness. This phenomenon includes general discomfort, disorientation, and/or nausea, and it threatens not only a pleasant user experience but also the user's safety. Thus, predicting a user's susceptibility without relying on screening questionnaires that focus on past experiences, would enable more pleasant, safer VR experiences, especially for first-time users. Hence, the current study uses the participant's controller input in a virtual Rod and Frame Test (RFT) as an effortlessly trackable performance measure. The RFT is an established method for measuring an individual's sense of verticality in visually displaced fields. It has been used in the context of simulator sickness and cybersickness. In line with the literature and the subjective vertical mismatch theory, a lower visual dependency is expected to be correlated positively with cybersickness. To evaluate the potential of the RFT as a screening method for cybersickness, a cybersickness-inducing virtual environment (the City) was deployed. In total, data from 76 participants were eligible for the statistical analysis. The study finds a positive correlation between lower visual dependency and cybersickness, but only for the group that took the RFT after experiencing the City and only for the post-RFT cybersickness ratings. As cybersickness symptoms were VR environment-specific, the predictive validity of the RFT considering the VR-specific attributes is limited. Further, other studies attributed different working mechanisms to explain the connection between visual dependence and cybersickness with conflicting evidence. Although the RFT is not applicable as a cybersickness screening method, the effect sizes suggest that the RFT could serve as an additional objective assessment of the individuals' current state during VR exposure. Future research should systematically explore interconnections between the various factors that contribute to cybersickness, pursuing the idea of open science for context sensitivity. [ABSTRACT FROM AUTHOR]

The widespread use of mobile devices has intensified the demand for literature translation in both academic research and personal learning. However, existing translation applications face significant challenges regarding offline mode and data synchronization. Ensuring translation quality and efficient data synchronization, particularly under unstable or disconnected network conditions, has emerged as a critical issue. Current research predominantly focuses on local storage and update mechanisms in offline mode. However, limitations in storage capacity and update strategies often hinder translation effectiveness. Additionally, data synchronization techniques have been primarily studied in stable network environments, with insufficient attention to strategies that address poor network quality or intermittent connectivity. To address these gaps, this study explores the offline mode and data synchronization technologies in literature translation applications on mobile devices. The study proposes optimized storage and update strategies for the offline mode while enhancing the efficiency and reliability of data synchronization, ultimately improving the usability and user experience of translation applications. [ABSTRACT FROM AUTHOR]

Wearable augmentations (WAs) designed for movement and manipulation, such as exoskeletons and supernumerary robotic limbs, are used to enhance the physical abilities of healthy individuals and substitute or restore lost functionality for impaired individuals. Non-invasive neuro-motor (NM) technologies, including electroencephalography (EEG) and sufrace electromyography (sEMG), promise direct and intuitive communication between the brain and the WA. After presenting a historical perspective, this review proposes a conceptual model for NM-controlled WAs, analyzes key design aspects, such as hardware design, mounting methods, control paradigms, and sensory feedback, that have direct implications on the user experience, and in the long term, on the embodiment of WAs. The literature is surveyed and categorized into three main areas: hand WAs, upper body WAs, and lower body WAs. The review concludes by highlighting the primary findings, challenges, and trends in NM-controlled WAs. This review motivates researchers and practitioners to further explore and evaluate the development of WAs, ensuring a better quality of life. [ABSTRACT FROM AUTHOR]

The compression, transmission and rendering of point clouds is essential for many use cases, notably immersive experience settings in eXtended Reality, telepresence and real-time communication where real world acquired 3D content is displayed in a virtual or real scene. Processing and display for these applications induce visual artifacts and the viewing conditions can impact the visual perception and Quality of Experience of users. Therefore, point cloud codecs, rendering methods, display settings and more need to be evaluated through visual Point Cloud Quality Assessment (PCQA) studies, both subjective and objective. However, the standardization of recommendations and methods to run such studies did not follow the evolution of the research field and new issues and challenges have emerged. In this paper, we make a systematic review of subjective and objective PCQA studies. We collected scientific papers from online libraries (IEEE Xplore, ACM DL, Scopus) and selected a set of relevant papers to analyze. From our observations, we discuss the progress and future challenges in PCQA toward efficient point cloud video coding and rendering for eXtended Reality. Main axes for development include the study of use case specific influential factors and the definition of new test conditions for subjective PCQA, and development of perceptual learning-based methods for objective PCQA metrics as well as more versatile evaluation of their performance and time complexity. [ABSTRACT FROM AUTHOR]

Background: With the penetration of the "Internet+" into social life, the digitization of education has become a trend and national demand. Alongside the rise of the "Everyone Live Streaming" era, online live streaming class platforms have rapidly grown due to favorable user experiences. Methods: Grounded in the Expectation Confirmation Theory, this study employed questionnaire surveys to investigate the influence mechanism of perceived quality, flow experience, and perceived usefulness on individuals' continuance usage intention of online live streaming class platforms. Results: Through the analysis of 773 survey responses, this study reveals several key findings. Firstly, perceived quality significantly and positively affects users' intention to continue using the online live streaming class platforms. Secondly, flow experience partially mediates the relationship between perceived quality and continuance usage intention, underscoring its significance in user decision-making. Additionally, Perceived usefulness negatively moderates the relationship between perceived quality and flow experience, demonstrating varied effects. Conclusion: On the one hand, online live streaming platforms should actively invest in improving the quality of user perception, as this can lead to a better user flow experience and continued willingness to use. On the other hand, they should also pay more attention to the user's flow experience, which has a direct impact on the user's propensity to continue to use. Besides, the perceived usefulness of the online live class by the user should also be taken seriously. [ABSTRACT FROM AUTHOR]

In the new media era, visual communication design (VCD) in interface design (ID) relies on critical design patterns—layout, color, typography, and interactive elements—that are essential for user engagement. This study investigates these design patterns in ID, drawing on responses from 760 professionals, including UI and UX designers, researchers, and industry experts. Data analysis with SPSS revealed key trends, common practices, and areas for innovation, informing strategies for improved user experiences in new media interfaces. By highlighting emerging patterns and addressing literature gaps, the study offers valuable insights into design preferences and challenges faced by professionals, with implications for educational curricula, tool development, cross-disciplinary collaboration, and user-centric guidelines. [ABSTRACT FROM AUTHOR]

With the rapid growth of on-demand delivery, traditional third-party delivery services using electric bicycles face increasing challenges, including increased labor costs and safety issues. To address these issues, we propose two modes for on-demand delivery systems using buses. One is the "bus terminal + professional crowd shippers" (B&P) mode, which involves consolidating parcels from various origins at the bus transfer hub. From there, they are grouped and delivered by buses. The other is the "bus stop + crowdsourced passenger" (B&C) mode, which transports parcels directly from the origin to the destination by passengers without the need for consolidation and sorting at bus transfer hubs. Both modes fully utilize the surplus capacity of buses and employ resources from retail stores and third-party shippers. We evaluated these modes using key performance indicators (KPIs) such as labor costs, cost increases from en-route destination changes, and average delivery time per kilometer. This analysis was based on 18,349 delivery cases in downtown Ningbo, China. Through this evaluation, we identified the strengths, weaknesses, opportunities, and threats associated with each mode. Our findings reveal that both the B&P and B&C modes effectively reduce delivery costs and external impacts while maintaining a user experience and efficiency level comparable to traditional third-party delivery services for mid-to-long-distance (3–10 km) deliveries. However, the use of public transportation may limit the flexibility of the delivery mode. Based on these insights, we provide strategic recommendations for the further development and implementation of B&P and B&C modes. [ABSTRACT FROM AUTHOR]

Extended reality (XR) technologies are emerging as promising platforms for medical training and procedural guidance, particularly in complex cardiac interventions. This paper presents a high-fidelity methodology to perform real-time 3D catheter tracking and visualization during simulated cardiac interventions. A custom 3D-printed setup with mounted cameras enables biplane video capture of a catheter. A computer vision algorithm processes the biplane images in real-time to reconstruct the 3D catheter trajectory represented by any designated number of points along its length. This method accurately localizes the catheter tip within 1 mm and can reconstruct any arbitrary catheter configuration. The tracked catheter data is integrated into an interactive Unity-based scene rendered on the Meta Quest 3 headset. The visualization seamlessly combines a reconstructed 3D patient-specific heart model with the dynamically tracked catheter, creating an immersive extended reality training environment. Our experimental study, involving six participants, demonstrated that the 3D visualization provided by the proposed XR system significantly outperformed 2D visualization in terms of speed and user experience. This suggests that the XR system has the potential to enhance catheterization training by improving spatial comprehension and procedural skills. The proposed system demonstrates the potential of XR technologies to transform percutaneous cardiac interventions through improved visualization and interactivity. [ABSTRACT FROM AUTHOR]

Human activity recognition (HAR) using smartphone inertial sensors, like accelerometers and gyroscopes, enhances smartphones' adaptability and user experience. Data distribution from these sensors is affected by several factors including sensor hardware, software, device placement, user demographics, terrain, and more. Most datasets focus on providing variability in user and (sometimes) device placement, limiting domain adaptation and generalization studies. Consequently, models trained on one dataset often perform poorly on others. Despite many publicly available HAR datasets, cross-dataset generalization remains challenging due to data format incompatibilities, such as differences in measurement units, sampling rates, and label encoding. Hence, we introduce the DAGHAR benchmark, a curated collection of datasets for domain adaptation and generalization studies in smartphone-based HAR. We standardized six datasets in terms of accelerometer units, sampling rate, gravity component, activity labels, user partitioning, and time window size, removing trivial biases while preserving intrinsic differences. This enables controlled evaluation of model generalization capabilities. Additionally, we provide baseline performance metrics from state-of-the-art machine learning models, crucial for comprehensive evaluations of generalization in HAR tasks. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine how different types of user experience in TikTok impact purchase intention via commitment to the influencer and commitment to the platform, with customer type included to determine moderating effects. Three types of user experience are considered: information experience, entertainment experience and parasocial-relationship-based experience. Design/methodology/approach: This study collected 458 valid questionnaires from TikTok users, employing the structural equation modeling approach to examine the proposed research model. Findings: Information experience, entertainment experience and parasocial-relationship-based experience are found to critically stimulate user commitment to the influencer and commitment to the platform, in turn driving TikTok-based purchase intention. Tests incorporating customer type reveal that commitment to the influencer more strongly influences the purchase intention of repeat customers, with commitment to the platform more likely to stimulate purchase intention among potential customers. Research limitations/implications: On a theoretical level, the paper is among the first to examine TikTok-based user purchase intention with customer type as a moderator. On a practical level, the results can guide marketers to effectively promote products using TikTok and inspire TikTok managers to develop customized strategies to stimulate initial and repeat sales. Originality/value: TikTok is moving to the stage of commercialization and monetization by introducing e-commerce features. Although this move should cultivate particularly fertile ground for companies to sell products, TikTok user purchase behavior has yet to receive sufficient research attention, with little currently known about their purchase motivations. The current study uncovers the significant antecedents of users' purchase intention through TikTok, and further reveals the motivational differences among potential and repeat customers. [ABSTRACT FROM AUTHOR]

We designed a microbial science popularization product based on virtual reality technology, "Micro World – Exploring the Microbial Kingdom," and conducted usability tests. Participants used head-mounted VR glasses to experience virtual scenarios teaching microbiological knowledge. The product's user experience was evaluated through a User Experience Questionnaire (UEQ), and the results showed that our product provided both usefulness and enjoyment. In addition, the quality of participants' relevant knowledge acquisition was measured using the Student Education of Educational Quality (SEEQ). The SEEQ results show that "Micro World" is an effective tool for popularizing microbiology science and can actively promote students' independent learning and improve learning quality. [ABSTRACT FROM AUTHOR]

Objective: HIV molecular epidemiology (HIV ME) is a tool that aims to improve HIV research, surveillance, and cluster detection and response. HIV ME is a core pillar of the U.S. initiative to End the HIV Epidemic but faces some challenges and criticisms from stakeholders. We sought to assess user experience to identify the current needs for HIV ME. Methods: Users of HIV ME, including researchers and public health practitioners, were engaged via a structured survey. Needs were assessed via open-ended questions about HIV ME. Data were analyzed using reflexive thematic analysis; the concordance of results was assessed semi-quantitatively. Results: Of 90 possible HIV-ME end-users, 57 completed the survey (response rate = 63%), which included users engaged in research (n = 29) and public health (n = 28). Respondents identified current imperatives, challenges, and strategies to improve HIV ME. Imperatives included characterization of the virus, identification of HIV hotspots, and tailoring of HIV interventions. Challenges encompassed technological issues, ethical concerns, and implementation difficulties. Strategies to improve HIV ME involved improving data access and analysis, enhancing implementation guidance and resources, and fostering community engagement and support. Researchers and public health practitioners prioritized different imperatives, but similarly emphasized the ethical concerns with HIV ME. Conclusion: The imperatives identified by users underscore the necessity of HIV ME, while the challenges highlight the hurdles to be overcome, including ethical concerns which emerged as a shared emphasis across user groups. The strategies outlined offer a roadmap for overcoming these challenges. These insights, drawn from user experience, present a valuable opportunity to inform the development of guidelines for the ethical application of HIV ME in research, surveillance, and cluster detection and response. [ABSTRACT FROM AUTHOR]

This paper provides an in-depth exploration of privacy protection in crossplatform recommender systems. With the rapid development of information technology, cross-platform recommender systems have become a vital tool for providing personalized experiences to users. However, these systems, while collecting vast amounts of personal data for targeted recommendations, pose significant privacy risks. This paper presents a review of the current state-of-the-art techniques for privacy protection, including differential privacy, federated learning, and blockchain-based methods. Each technique's effectiveness and limitations are evaluated, offering insights into their practical application in real-world settings. Additionally, the paper identifies the distinct challenges associated with preserving privacy in cross-platform scenarios due to the complex data-sharing mechanisms among different platforms. These challenges involve multiple aspects, such as user identity linkage, data inconsistency, and diverse privacy policies across platforms. Finally, we propose potential solutions and future research directions to address these challenges, emphasizing the need for balancing effective personalization and stringent privacy protection in cross-platform recommender systems. [ABSTRACT FROM AUTHOR]

Objective: Web-based platforms for delivering physical activity (PA) to people with developmental disabilities have a great potential to improve the lives of many. However, their design, including the content design, lacks sufficient investigation. This study aims to evaluate three online platforms for delivering PA to people with developmental disabilities in terms of content quality and identify relevant barriers and facilitators of PA delivery. Methods: The study used a methodological triangulation approach which involved quantitative evaluations by experts using an evaluation rubric, on-site observations and in-depth interviews with recruited participants. The participants consisted of 15 pairs of individuals, each consisting of a person with developmental disabilities and their primary caregiver. They were instructed to watch and follow five PA video content from each of the three platforms. The on-site observations and interviews were conducted in a large computer-equipped meeting room setting. Results: The quantitative and qualitative analysis identified a set of barriers and facilitators of PA delivery related to content quality. Key barriers identified include a lack of content diversity, insufficient understanding of developmental disabilities among content creators, inappropriate language usage, and resistance to engaging in physical activities in home settings. Significant facilitators were pinpointed, such as incorporating engaging elements for individuals with developmental disabilities, utilising easy-read language, and ensuring sufficient repetition for effective learning. The results from the triangulation showed that the multiple methods were complementary and converged on the same outcome. Discussion: The study findings could contribute to the development of adequately adapted PA content to distribute knowledge to populations with developmental disabilities. IMPLICATIONS FOR REHABILITATION: Content delivered via online platforms has the potential to convey knowledge about physical activity to a significant number of individuals with developmental disabilities without the limitations of time and space. The absence of prescribed content guidelines to effectively impart physical activity to individuals with developmental disabilities impedes the process of online knowledge translation. There is a requirement for varied physical activity content encompassing various individuals with developmental disabilities, considering their diverse learning contexts. It is essential that content development is evaluated with input from experts in developmental disabilities in order to provide quality physical activity information for people with developmental disabilities. [ABSTRACT FROM AUTHOR]

Background: Knowledge-to-action gap exists in delivering physical activity (PA) to people with developmental disabilities via online platforms. Although web-based platforms have great potential in facilitating the delivery of PA for this target group, the lack of knowledge regarding web accessibility poses a challenge in accessing PA-related information online. Objective: This study evaluates the delivery of PA in terms of web accessibility. It also aims to identify barriers and facilitators in delivering PA knowledge to people with developmental disabilities online to improve web accessibility for the target user group. Methods: The study employs a concurrent nested design incorporating both quantitative (web usability questionnaire) and qualitative data (in-depth interviews). Fifteen pairs of individuals consisting of a person with developmental disabilities and a primary caregiver participated in the study, and three web-based platforms were selected for web accessibility tests and in-depth interviews. Results: The nested analysis provides a quantitative comparison of web accessibility and identifies barriers and facilitators of delivering PA for the target user group from the web accessibility perspective. Conclusion: The study findings could inform the development of accessible online platforms that distribute health-related knowledge to populations with developmental disabilities. Additionally, they could help enhance the design of other platforms intended for these populations. IMPLICATIONS FOR REHABILITATION: Online platforms have significant potential to improve the delivery of physical activity information to individuals with developmental disabilities. Barriers to accessing online platforms due to poor web usability impede the process of online knowledge translation to end-users. Web usability can be enhanced by implementing appropriate interventions, such as restructuring navigation and redesigning the user interface. Improving web usability will enhance the accessibility of physical activity knowledge for individuals with developmental disabilities, which consequently will positively impact their health. [ABSTRACT FROM AUTHOR]

Flow experience is one of the most ambitious targets of any user interface designer. However, it has remained elusive to evaluate how well user interfaces give rise to flow experience outside conducting invasive self-reporting-based questionnaires, which remove the users from the flow experience and can't be massively applied. At the same time, otherwise, well-built systems do track the behaviour of users on the interface, and therefore, user behaviour data could act as a reliable proxy for assessing the experience of users. Currently, there is little empirical research or data about which indices of user behaviours might correspond with having a flow experience as well as the different psychological constituents of the flow experience. Therefore, facing the challenge of using users' behaviour data to model users' experience, we investigated the associations between users' behaviour data (e.g. mouse clicks, activity time in the system, and average response time) and their self-reported flow experience by using data mining (i.e. associations rules) analysing data from 204 subjects. Results demonstrate that the speed of users' actions negatively affects the flow experience antecedents while also positively affecting the loss of self-consciousness. Our study advances the literature, providing insights to identify users' flow experience through behaviour data. [ABSTRACT FROM AUTHOR]

Since 2023, the Singapore Management University has been offering the further education program "Emerging Library Leaders' Summer School for Asia-Pacific", which is aimed at librarians in Asia but also allows interested individuals from Europe to participate. The author attended the Summer School in 2024 and reports on the registration process, course fees, and the diverse activities during the five-day program in Singapore. Participants learned about topics such as digitization, AI, user experience, and took part in excursions to various universities and libraries. The Summer School offers a highly recommended opportunity to learn about library work in other countries and to further develop professionally. [Extracted from the article]

The simultaneous use of two or more drugs in clinical treatment may raise the risk of a drug–drug interaction (DDI). DDI prediction is very important to avoid adverse drug events in combination therapy. Recently, deep learning methods have been applied successfully to DDI prediction and improved prediction performance. However, there are still some problems with the present models, such as low accuracy due to information loss during molecular representation or incomplete drug feature mining during the training process. Aiming at these problems, this study proposes an accurate and simple framework named PTB-DDI for drug–drug interaction prediction. The PTB-DDI framework consists of four key modules: (1) ChemBerta tokenizer for molecular representation, (2) Bidirectional Long Short-Term Memory (BiLSTM) to capture the bidirectional context-aware features of drugs, (3) Multilayer Perceptron (MLP) for mining the nonlinear relationship of drug features, and (4) interaction predictor to perform an affine transformation and final prediction. In addition, we investigate the effect of dual-mode on parameter-sharing and parameter-independent within the PTB-DDI framework. Furthermore, we conducted comprehensive experiments on the two real-world datasets (i.e., BIOSNAP and DrugBank) to evaluate PTB-DDI framework performance. The results show that our proposed framework has significant improvements over the baselines based on both datasets. Based on the BIOSNAP dataset, the AUC-ROC, PR-AUC, and F1 scores are 0.997, 0.995, and 0.984, respectively. These metrics are 0.896, 0.873, and 0.826 based on the DrugBank dataset. Then, we conduct the case studies on the three newly approved drugs by the Food and Drug Administration (FDA) in 2024 using the PTB-DDI framework in dual modes. The obtained results indicate that our proposed framework has advantages for predicting drug–drug interactions and that the dual modes of the framework complement each other. Furthermore, a free website is developed to enhance accessibility and user experience. [ABSTRACT FROM AUTHOR]

Hand-held augmented reality (AR) offers accessible, interactive rehabilitation options for patients with upper limb motor deficits. Incorporating hand-involved interactions (e.g., tangible and mid-air interactions) into hand-held AR provides patients with intuitive manners to perform rehabilitation exercises mimicking real-world activities. Previous work has shown the importance of user experience and motor performance in rehabilitation systems, but little was known in the literature regarding the impact of hand-involved interactions in hand-held AR on user experience and motor performance in rehabilitation exercises. Hence, this study aims to evaluate user experience and motor performance when using three types of hand-involved interactions in hand-held AR rehabilitation: (1) tangible cube (i.e., a space-multiplexed tangible interaction with a physical cube acting as a real proxy to manipulate a virtual object in the same form); (2) tangible controller (i.e., a time-multiplexed tangible interaction with a physical controller applied to manipulate a virtual object); and (3) hand motion (i.e., a form of mid-air interaction to move a virtual object with hands). Based on the findings from self-report, electroencephalography (EEG), and performance measures, this study reveals the advantages of the tangible cube over the tangible controller, both superior to the hand motion in hand-held AR rehabilitation regarding user experience and motor performance. This study offers new understanding of the advantages and disadvantages of various interaction techniques in hand-held AR rehabilitation, emphasizing crucial design considerations for these systems, with a focus on user experience and motor performance in upper limb rehabilitation. [ABSTRACT FROM AUTHOR]

Users' motion representation in virtual reality (VR) can be modulated visually by introducing a mismatch with their real motion, which can bring benefits to exercise and rehabilitation and has great potential for exergame applications in VR. Users' experience of control is a critical consideration for user experience in human–computer interaction and should be paid special attention when movement modulation is implemented in VR. However, how movement modulation affects users' experience of control and motor performance has not been fully investigated in detail. This research included 49 participants and investigated how the experience of control is influenced by reaching movement modulation in two types: the enhancement and reduction modes. Different modulation modes were designed to study their influence on the explicit experience of control in self-ratings and the implicit measured experience of control in intentional binding and electroencephalography. Participants' movement trajectory, velocity, and completion time were analyzed for motor performance. The results illustrate a significant effect of movement modulation on the users' motor performance and experience of control in self-ratings and EEG. This study makes a major contribution through a comprehensive analysis of the experience of control with movement modulation and provides important and practical design considerations on movement modulation design in future exercise-based applications with positive controlling experiences in VR. [ABSTRACT FROM AUTHOR]

Electric shared mobility is flourishing in urban transportation. However, the problem of uneven vehicle distribution and untimely vehicle charging hampers user trip experience and system operation efficiency. To overcome these challenges, this study proposed a multi-phase vehicle relocation optimization approach for one-way station-based carsharing systems. In phase one, a micro-level shared travel demand forecasting model was developed to capture the number of orders in the short-term future. In phase two, stations were divided into different categories based on the results of user travel demand forecast. In phase three, the minimization of driving mileage and carbon emissions was taken as the optimization objective, and a solution method combining Gurobi solver and charging priority ranking was designed. Finally, the effectiveness and advantages of the proposed model and algorithm were comprehensively validated through a case study using real passenger orders and geographic data from the city of Shanghai, China. [ABSTRACT FROM AUTHOR]

Pandemics tend to significantly disrupt the global business landscape, but they primarily impact the hospitality industry. Meanwhile, in such a scenario, online purchasing experienced a remarkable surge, particularly through food delivery apps. Fear's impact on food delivery app usage has received little attention. Our study addresses this gap by exploring how fear and perceived threat influence consumers' search efforts for online food, ultimately affecting their experience. We have analyzed data using PLS-SEM, and our results indicate how fear and perceived threats affect customers' search behavior. These findings can help businesses improve user experiences, address fears, and manage uncertainty in food delivery app usage during the pandemic. [ABSTRACT FROM AUTHOR]

Cross reality laboratories are widely used in education, yet research on the usability/user experience (UX) of these laboratories is still lacking. This study wants to start the discussion about challenges for usability/UX by interviewing practitioners from a large project for cross reality laboratories spanning multiple institutes in Germany. A total of 18 challenges were discovered, together with three target groups, namely, developers, maintainers, and learners. In addition, the tension between developers and usability is discussed. Open questions include the need to conduct further research with different target groups and how to increase usability for laboratory developers. [ABSTRACT FROM AUTHOR]

This article examines the experiences of female users of imageboards – online anonymous-by-default bulletin boards. Using thematic analysis on 12 Instant Messaging (IM)–based interviews with female-identifying imageboard users, this study gathers and presents their experiences and perceptions of benefits and drawbacks of use. Major findings include negative perception of mainstream imageboards and a contrastingly positive sentiment towards the platforms investigated as part of this study. Using imageboards represented a unique, entertaining and social experience. Interviewees predominantly used imageboards to be hyperbolic, 'vent', discuss sexuality or explore thoughts they otherwise would not. The study's findings question previous narratives of women on imageboards which position them either as mostly unaffected members of the space or as out-of-place minorities 'getting by' – by virtue of using masculinist strategies. Rather, participants describe ambivalent experiences around navigating these spaces, including benefits of entertainment, sense of belonging and the affinity towards gendered self-experimentation. [ABSTRACT FROM AUTHOR]