User Experience Research Articles

Enhancing Visual Perception in Immersive VR and AR Environments: AI-Driven Color and Clarity Adjustments Under Dynamic Lighting Conditions

The visual fidelity of virtual reality (VR) and augmented reality (AR) environments is essential for user immersion and comfort. Dynamic lighting often leads to chromatic distortions and reduced clarity, causing discomfort and disrupting user experience. This paper introduces an AI-driven chromatic adjustment system based on a modified U-Net architecture, optimized for real-time applications in VR/AR. This system adapts to dynamic lighting conditions, addressing the shortcomings of traditional methods like histogram equalization and gamma correction, which struggle with rapid lighting changes and real-time user interactions. We compared our approach with state-of-the-art color constancy algorithms, including Barron’s Convolutional Color Constancy and STAR, demonstrating superior performance. Experimental results from 60 participants show significant improvements, with up to 41% better color accuracy and 39% enhanced clarity under dynamic lighting conditions. The study also included eye-tracking data, which confirmed increased user engagement with AI-enhanced images. Our system provides a practical solution for developers aiming to improve image quality, reduce visual discomfort, and enhance overall user satisfaction in immersive environments. Future work will focus on extending the model’s capability to handle more complex lighting scenarios.

The Trail Making Test in Virtual Reality (TMT-VR): The Effects of Interaction Modes and Gaming Skills on Cognitive Performance of Young Adults

Virtual Reality (VR) is increasingly used in neuropsychological assessments due to its ability to simulate real-world environments. This study aimed to develop and evaluate the Trail Making Test in VR (TMT-VR) and investigate the effects of different interaction modes and gaming skills on cognitive performance. A total of 71 young female and male adults (aged 18–35) with high and low gaming skills participated in this study. Participants completed the TMT-VR using three interaction modes as follows: eye-tracking, head movement, and controller. Performance metrics included task completion time and accuracy. User experience, usability, and acceptability of TMT-VR were also examined. Results showed that both eye tracking and head movement modes significantly outperformed the controller in terms of task completion time and accuracy. No significant differences were found between eye tracking and head movement modes. Gaming skills did not significantly influence task performance using any interaction mode. The TMT-VR demonstrates high usability, acceptability, and user experience among participants. The findings suggest that VR-based assessments can effectively measure cognitive performance without being influenced by prior gaming skills, indicating potential applicability for diverse populations.

Views on the Development and Use of a New Digital Adverse Drug Event Reporting Platform in Australia: A Qualitative Study.

Reporting of adverse drug events (ADEs) to regulatory authorities remains low, particularly among consumers. To explore stakeholders' views on the development and use of a digital platform to improve ADE reporting by consumers to the regulatory authority in Australia, i.e., the Therapeutic Goods Administration. A qualitative study was conducted using semi-structured interviews, focus group discussions (FGDs), and co-design workshops with consumers, healthcare professionals (HCPs), and regulators. The interview recordings were transcribed verbatim, coded, and analysed thematically according to the Capability, Opportunity, Motivation, Behaviour model. Findings of the FGDs and co-design workshops were incorporated to enhance and complement the insights gathered from the interviews. A total of 39 participants took part in the study (54 % consumers, 41 % HCPs, and 5 % regulators). Uncovered themes related to ADE reporting in general were: difficulty recognizing ADEs and health literacy, awareness about reporting ADEs (Capability); visibility of ADE reporting, professionals' views on consumer ADE reporting, consumer education (Opportunity); the common good, benefit to the reporter, identifying ADEs worth reporting, and concern about reporting (Motivation). Additional identified themes specific to a new digital platform were: physical abilities (Capability); features that facilitate intuitive use, convenience and accessibility, user experience, integration with existing systems, trust, sharing experiences with others (Opportunity); and concern about using a reporting platform, and feedback loop (Motivation). A cross-section of attitudes and values were obtained regarding ADE reporting in general and a new ADE reporting digital platform for consumers in Australia, which will inform its development, implementation and evaluation.

Cultural and Behavioral Insights into European Social Media Users: Platform Preferences and Personality Types

The study examines European social media personalities based on age, gender, platform preference, and country of origin. The research sample, which consists of respondents from 19 European countries (Albania, Bosnia & Herzegovina, Bulgaria, Czech Republic, Cyprus, France, Georgia, Germany, Greece, Italy, North Macedonia, Poland, Russia, Serbia, Slovenia, Spain, Sweden, Turkey, and the UK) reflects the general population ratio and predominantly includes middle-aged individuals ensuring representative findings. Almost two-thirds of respondents engage with social media daily, highlighting its pervasive role in European life. Analysis of platform preferences reveals that Facebook and Instagram are the most popular, while TikTok and Snapchat are less favored, particularly among older demographics. The study shows that gender differences are significant, with females favoring Facebook, Instagram, TikTok, and Snapchat, while males prefer LinkedIn and Twitter. This delineation underscores the varying social media consumption habits between genders. The study identifies three primary social media personalities: Lurkers, who passively consume content; Ultras, who exhibit obsessive usage; and Deniers, who balance regular use without dependency. Additional personalities include Ranters, Informers, and Peacocks, each representing unique motivations and engagement styles. This diversity in user behaviors highlights the multifaceted nature of social media engagement in Europe. A country-specific analysis reveals cultural and regional differences in social media use, with distinct preferences and behaviors emerging across Europe. For instance, Germans exhibit unique tendencies with a notable presence among Approval Seekers, Changelings, and Ghosts. Such variations underscore the importance of considering cultural contexts in social media strategies. The findings offer valuable insights for stakeholders, including marketers, policymakers, and platform developers. By understanding these diverse usage patterns, more effective campaigns can be designed, privacy and digital literacy issues can be addressed, and user experiences can be enhanced. This study underscores the integral role of social media in European life and provides a foundation for future research and strategy development.

A benchmark for domain adaptation and generalization in smartphone-based human activity recognition

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.

Media frames, AI romantic relationships, and the perspectives of people in relationships; mapping and comparing news media themes with user perspectives

ABSTRACT Human romantic relationships with artificially intelligent (AI) conversational agents and anthropomorphic computers have long been the realm of science fiction. As companies like Luka, Inc. are developing embodied conversational agents called Replika, people’s ability to engage in romantic relationships has garnered news coverage around the phenomenon. Because news is often a place where emerging technologies are first introduced, it is essential to understand the choice of topics and themes these stories focus on (e.g., the ethics of technological development, human desires and vulnerabilities, and what constitutes meaningful and authentic connection). Similarly, the extent to which these articles include user perspectives and how users respond to these frames is also less well understood. This article reports on a mixed-method study that combines content analysis of news articles in 2023 about Replika (1008 search results, n = 104 unique articles) and qualitative semi-structured interviews with users in romantic relationships with their Replika (n = 16), recruited from the Reddit forum ‘ILoveMyReplika.’ Through a frame analysis of these news stories and coding for the types of futures they present, this study first examines some of the key events, themes, and hopes/fears reported in mass media. A thematic analysis of the interview data offers a comparative study to see where there is some overlap between these hopes/fears and user experiences and places where user reports diverge, downplay, and dispute the media characterizations. These studies help us better understand the interrelationship between media narratives, technological frames, and moral panics around a unique subset of and relationship with AI technologies.

Empowering Consumer Decision-Making: Decoding Incentive vs. Organic Reviews for Smarter Choices Through Advanced Textual Analysis

Online reviews play a crucial role in influencing seller–customer dynamics. This research evaluates the credibility and consistency of reviews based on volume, length, and content to understand the impacts of incentives on customer review behaviors, how to improve review quality, and decision-making in purchases. The data analysis reveals major factors such as costs, support, usability, and product features that may influence the impact. The analysis also highlights the indirect impact of company size, the direct impact of user experience, and the varying impacts of changing conditions over the years on the volume of incentive reviews. This study uses methodologies such as Sentence-BERT (SBERT), TF-IDF, spectral clustering, t-SNE, A/B testing, hypothesis testing, and bootstrap distribution to investigate how semantic variances in reviews could be used for personalized shopping experiences. It reveals that incentive reviews have minimal to no impact on purchasing decisions, which is consistent with the credibility and consistency analysis in terms of volume, length, and content. The negligible impact of incentive reviews on purchase decisions underscores the importance of authentic online feedback. This research clarifies how review characteristics sway consumer choices and provides strategic insights for businesses to enhance their review mechanisms and customer engagement.

Exploring accessibility, user experience and engagement of digital media among older patients with depression: a pilot and observational screening study protocol of the DiGA4Aged study

IntroductionThe prevalence of mental health problems is increasing worldwide, particularly in the vulnerable group of older people. The limited availability of therapists, long wait periods and increasing shortage of healthcare...

Research on Landscape Design of Waterfront Public Space in Mountainous Cities Based on User Experience — Taking the Waterfront Landscape Design of Art Peninsula in Chongqing as an Example

Research on Landscape Design of Waterfront Public Space in Mountainous Cities Based on User Experience — Taking the Waterfront Landscape Design of Art Peninsula in Chongqing as an Example

Analysis and Design of Efficient Authentication Techniques for Password Entry with the Qwerty Keyboard for VR Environments.

Authentication in digital security relies heavily on text-based passwords, even with other available methods like biometrics and graphical passwords. While virtual reality (VR) keyboards are typically invisible to onlookers, the presence of inconspicuous sensors, including accelerometers, gyroscopes, and barometers, poses a potential risk of unauthorized observation and recording. Traditional defense shoulder-surfing attack methods typically involve breaking apart the Qwerty layout, which destroys the user's inherent familiarity with the layout. This research addresses the need for secure password entry in VR environments while retaining the Qwerty layout. We explore three keyboard-related position alteration strategies to ensure security while mitigating the decline in user experience. These strategies involve moving the entire keyboard, cursor, and keys. Our theoretical study assesses the effectiveness of these strategies against shoulder-surfing attacks. Two user studies, employing ray-based and position-based text entry methods, respectively, evaluate the practical effectiveness of the three strategies in resisting shoulder-surfing attacks, as well as their impact on typing performance and user experience. Our findings demonstrate that the three strategies achieve shoulder-surfing attack resistance comparable to a random layout keyboard. Moreover, compared to a random layout, the two strategies involving the movement of the entire keyboard and the repositioning of keys support faster entry rates and enhanced user experience.

Virtual Reality Gaming in Occupational Rehabilitation - User Experiences and Perceptions

Virtual Reality Gaming in Occupational Rehabilitation - User Experiences and Perceptions

ChatGPT and me: First-time and experienced users’ perceptions of ChatGPT’s communicative ability as a dialogue partner

Chatbots like ChatGPT have the potential to produce more natural conversational user interface interactions. Yet, we currently know little about perceptions of ChatGPT as a dialogue partner, and if interaction changes these. Through an online, two-stage, mixed methods study conducted in July 2023, in which first-time and experienced users living in the UK or Ireland engaged in tasks with ChatGPT, we show that interaction improves attitudes towards the system for first-time users, while these attitudes are already positive and stable in experienced users. We further show that first-time users’ perceptions of ChatGPT’s communicative ability (competence, human-likeness, and flexibility) are more dynamic than those of experienced users, although the experienced users’ perceptions also peak post-interaction. When reflecting on their interaction experience with ChatGPT, both groups were positive with little mention of limitations. We discuss the implications of these findings for user perceptions of ChatGPT as a dialogue partner, and highlight the potential risks of uncritical adoption of such technology.

Cognitive Training Using Virtual Reality: An Assessment of Usability and Adverse Effects

ObjectiveTo evaluate the usability and adverse effects associated with virtual reality(VR) cognitive training and identify factors influencing them. DesignSurvey-based observational study SettingDepartment of Rehabilitation Medicine in the hospital Participant20 rehabilitation professionals(mean(standard deviation) age; 30.0(4.8) years, male 8(40%) and female 12(60%)) and 10 patients with stroke(mean(standard deviation) age; 64.1(13.6) years, male 2(20%) and female 8(80%)). InterventionsThe participants wore a Head-Mounted Display (Meta Quest2) and consecutively underwent custom-designed five cognitive training. Main outcome measuresAfter the training, participants completed three questionnaires: the Systemic Usability Scale (SUS), User Experience Questionnaire (UEQ), and CyberSickness in Virtual Reality Questionnaire (CSO-VR). ResultsThe mean SUS score was 55.1 and 52.3 for rehabilitation professionals and patients, respectively. For the UEQ, the mean score for each item, including Attractiveness, Perspicuity, Efficiency, Dependability, Stimulation, and Novelty, were 0.9/0.2, 0.6/0.2, 0.5/-0.5, 1.2/0.8, 0.9/0.4, and 0.6/0.8 for rehabilitation professionals/patients, respectively. Rehabilitation professionals had slightly higher scores in most UEQ items. The mean CSQ-VR scores were 18.6 and 19.0 for rehabilitation professionals and patients, respectively. ConclusionsParticipants reported moderate usability and a generally below-average user experience, with mild to moderate VR sickness during VR cognitive training. The rehabilitation professionals rated usability higher than the patient group, while patients experienced more severe VR sickness. These findings may serve as a significant insight for developing virtual reality cognitive training for application to patients in the future.

Adapting the open-source Gen3 platform and kubernetes for the NIH HEAL IMPOWR and MIRHIQL clinical trial data commons: Customization, cloud transition, and optimization

ObjectiveThis study aims to provide the decision-making framework, strategies, and software used to successfully deploy the first combined chronic pain and opioid use data clinical trial data commons using the Gen3 platform. Materials and MethodsThe approach involved adapting the open-source Gen3 platform and Kubernetes for the needs of the NIH HEAL IMPOWR and MIRHIQL networks. Key steps included customizing the Gen3 architecture, transitioning from Amazon to Google Cloud, adapting data ingestion and harmonization processes, ensuring security and compliance for the Kubernetes environment, and optimizing performance and user experience. ResultsThe primary result was a fully operational IMPOWR data commons built on Gen3. Key features include a modular architecture supporting diverse clinical trial data types, automated processes for data management, fine-grained access control and auditing, and researcher-friendly interfaces for data exploration and analysis. DiscussionThe successful development of the Wake Forest IDEA-CC data commons represents a significant milestone for chronic pain and addiction research. Harmonized, FAIR data from diverse studies can be discovered in a secure, scalable repository. Challenges remain in long-term maintenance and governance, but the commons provides a foundation for accelerating scientific progress. Key lessons learned include the importance of engaging both technical and domain experts, the need for flexible yet robust infrastructure, and the value of building on established open-source platforms. ConclusionThe WF IDEA-CC Gen3 data commons demonstrates the feasibility and value of developing a shared data infrastructure for chronic pain and opioid use research. The lessons learned can inform similar efforts in other clinical domains.

RecommendRift: a leap forward in user experience with transfer learning on netflix recommendations

RecommendRift: a leap forward in user experience with transfer learning on netflix recommendations

Research Driven by User Demand for the Design of a Cross-Border Travel Credential Bag

Cross-border travel often presents challenges in document storage, which can burden travelers. This study addresses the issue by designing a credential bag that enhances safety, convenience, and environmental sustainability. Utilizing design research, we applied the KANO model to categorize user needs, employed analytic hierarchy process to prioritize these needs, and used quality functional deployment to translate them into specific design elements. The KANO model has identified a total of 18 demand indicators, including “must-be”, one-dimensional, and attractive. An analytic hierarchy process analysis of the secondary indicators found that demands for the security of anti-theft, partition storage of documents, a variety of carrying methods and green sustainability have relatively high weight. The innovative solutions derived from the KANO-AHP-QFD model improve design practices and user experience in document storage. This approach offers a scientific and practical reference for the sustainable development of travel supplies and the luggage industry.

Web-Based Task Organizer for Enhanced Productivity

The Web-Based Task Organizer for Enhanced Productivity (WBTO) mainly aims to improve task management and overall increase in productivity. In our system we offer features such as task prioritization, categorization, due dates and recurrence options which is integrated into a user friendly interface. We use a full stack approach using java for the back end logic, JavaScript for a dynamic user interface and a SQL database for preserving data storage. It provides key features like task creation, categorization, prioritization, scheduling and progress tracking and interactive functionalities and ensuring data integrity and privacy. As this not only improves individual productivity but also further provides group work collaboration allowing for much faster task tracking, reminders and analytics which improves overall user experience.

Emotional Intelligence in Voice Assistants : Advancing Human-AI Interaction

This article explores the integration of emotional intelligence (EI) into AI voice assistants, examining techniques for emotion recognition from speech, adaptive response generation, and the impact on user experience. It discusses key components including acoustic feature analysis, machine learning approaches, and multimodal systems for emotion detection. The article also addresses ethical considerations such as privacy concerns, potential manipulation, and technical challenges in achieving robust, real-time, and culturally-adaptive EI systems. Applications in mental health support and customer service are examined, highlighting both the potential benefits and necessary precautions. Through a comprehensive review of recent research, this work aims to contribute to the responsible development of emotionally intelligent AI voice assistants that enhance human-AI interaction while prioritizing user well-being.

Research on Driver Emotion Monitoring and Regulation System in Intelligent Assisted Driving

Abstract. With the rapid development of smart connected vehicles, the influence, recognition and regulation of driver's emotions are crucial for intelligent cockpits with "emotional interaction". This review aims to provide a comprehensive analysis of driver emotion monitoring systems in intelligent assisted driving. By summarizing and analyzing related literature, the structure and application of emotion monitoring systems are introduced, their principles and evaluation criteria are discussed in depth, and the advantages and limitations of the three sub-systems, namely, detection, decision-making and regulation, are analyzed in detail. The results show that although emotion monitoring and modulation technologies perform well in enhancing driving safety and comfort, their practical applications still face challenges in terms of technology maturity, cost control, and privacy protection. In addition, the reliability and accuracy of current emotion monitoring systems in complex driving environments have yet to be improved. Future research should focus on interdisciplinary cooperation to integrate the latest achievements in psychology, computer science and engineering. At the same time, it is necessary to develop unified technical standards and evaluation guidelines to promote compatibility and interoperability between different systems and enhance research on privacy protection measures to ensure the security and confidentiality of user data. Through these efforts, the field of intelligent driving is expected to achieve comprehensive development and wide application, further enhancing driver safety and user experience.

Experience of Hyperbaric Chamber Usage in Aesthetic Plastic Surgery Practice for Recovery and Complication Prevention.

Hyperbaric oxygen therapy (HBOT) increases oxygen concentration in affected tissues that enhance the cellular hypoxia recovery process, neovascularization, fibroblast proliferation, increased reactive oxygen species, suppression of proinflammatory states, and vascular compression. The aim of this article is to demonstrate the experience in the use of the hyperbaric chamber as an adjunctive management for the prompt recovery of patients who underwent aesthetic plastic surgery. A retrospective descriptive study was conducted between 2021 and 2023, involving 296 patients who received HBOT after aesthetic surgical procedures, to demonstrate the recuperation time rate and the complication incidence in postoperative patients using HBOT. Most participants were women, with a median age of 33.5 years. Surgical procedures were grouped in liposculpture, abdominoplasty, and breast interventions. Complications related to the surgical event were low (10.7%), with occurrences of hematomas (n = 14, 4.72%), anemias (n = 9, 3.04%), and wound dehiscence (n = 8, 2.70%). There were no reports of surgical site infections or necrosis. Recovery times to get back to work were 10 days for liposuction, 3 days for breast interventions, and 21 days for abdominoplasty. This study demonstrated the experience of using a postoperative hyperbaric chamber in aesthetic plastic surgery to promote recovery processes. The patient cohort in this study showed shortened recovery times than the data obtained from the major international plastic surgery organizations. Also, HBOT patients had a low complication rate, without infections, indicating the potential efficacy of this adjunctive therapy. Overall, this study underscores the promising role of hyperbaric chamber therapy in facilitating postoperative recovery and mitigating complications.