User Experience Assessment Research Articles

Assessment of digital literacy and user experience in patients with cochlear implants

Abstract Introduction The cochlear implant (CI) is the treatment of choice for people affected by deafness or profound hearing loss. Patients with cochlear implants (PwCIs) can enhance their hearing outcomes using digital hearing training programs (dHTPs). Current technological trends leans towards personalized, AI-driven dHTPs, aiming to optimize user experience (UX) and adherence. This study aims to investigate the digital literacy skills and UX of PwCI before and after testing a prototype of a dHTP with an AI-driven design (TraiCI). Methods Two research-specific questionnaires developed by the Hearing Center Düsseldorf (QDL and QUX) were used to assess digital literacy skills and user experience in TraiCI. Additionally, the User Experience Questionnaire (UEQ) was employed to evaluate general user experience. The UEQ assesses software quality across dimensions such as transparency and stimulation using paired opposites. Results 22 outpatient PwCIs the Hearing Center Düsseldorf with unilateral or bilateral CI (mean age 54 years; SD = 15) were included. In QDL, PmCI demonstrated high levels of digital literacy skills. The majority of PmCI (80.6%) reported prior experience with dHTP. Usage of these programs occurred daily to multiple times per week within the first six months after CI treatment, with session durations predominantly ranging from 10 to 30 minutes. QUX data indicated a smooth initiation process (70.8%) and seamless login experience (95.5%). The UEQ addressed various aspects of user experience, with ‘transparency’ receiving the highest scores (MW = 1.9; SD = 0.6), while ‘stimulation’ received the least positive ratings (MW = 0.0; SD = 2.1). Conclusions The results show a high degree of digital literacy among PwCIs. They encountered minimal challenges in operating hardware and software components. Further refinement is necessary to align with PwCI’s expectations and maximize benefits. Early and iterative involvement of PwCIs in future projects could optimize outcomes. Key messages • The study highlights the proficient digital literacy skills of cochlear implant patients (PwCIs). • Further refinement of dHTPs is needed to better align with PwCIs’ expectations and maximize benefits, emphasizing the importance of iterative involvement for optimized outcomes.

Classification of suicidal ideation severity from Twitter messages using machine learning

Depression has become a major mental health problem in Thailand and can lead to suicidal ideation. As suicidal ideation may vary in intensity and lead to suicide attempts, early detection of suicidal ideation severity should be implemented. This research presents text classification models for the prediction of suicidal ideation severity. A dataset of Twitter messages in Thai was used to develop several classification models. A web application prototype was also developed to predict suicidal ideation severity and introduce self-therapy based on Cognitive Behavioral Therapy to its users for managing negative automatic thoughts. The application prototype received satisfactory feedback during the user experience assessment. The results of this research highlight the importance and need for socio-technical systems to help with early suicidal ideation detection and early therapy in the social environment where mental health support is inadequate.

User experience with HIV molecular epidemiology in research, surveillance, and cluster detection and response: a needs assessment

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.

A Greek Conversational Agent for Hematologic Malignancies: Usability and User Experience Assessment.

Enabling patients to actively document their health information significantly improves understanding of how therapies work, disease progression, and overall life quality affects for those living with chronic disorders such as hematologic malignancies. Advancements in artificial intelligence, particularly in areas such as natural language processing and speech recognition, have resulted in the development of interactive tools tailored for healthcare. This paper introduces an innovative conversational agent tailored to the Greek language. The design and deployment of this tool, which incorporates sentiment analysis, aims at gathering detailed family histories and symptom data from individuals diagnosed with hematologic malignancies. Furthermore, we discuss the preliminary findings from a feasibility study assessing the tool's effectiveness. Initial feedback on the user experience suggests a positive reception towards the agent's usability, highlighting its potential to enhance patient engagement in a clinical setting.

Comparative Analysis Between Using Google Meet and Gather Town Video Conferencing Platforms Viewed from User Experience Using meCUE Questionnaire on Students

The purpose of this study was to determine the comparative results between using the Google Meet and Gather Town video conferencing platforms in terms of user experience using the meCUE questionnaire on students. This research is quantitative research with descriptive analysis and uses comparative study research methods. The data source of this research is High School in Malang. Sampling was taken randomly without regard to the strata in the population (simple random sampling) so that 4 classes consisting of 35 students were obtained. This research data collection technique adapts from a questionnaire instrument to assess the user experience of a service product such as a website or application. The meCUE questionnaire was created based on the Component model of User Experience (CUE) compiled by Thuering & Mahlke. The results of the data obtained through the meCUE questionnaire on the Google Meet and Gather Town video conferencing platform applications will be analysed so as to obtain results that can show the comparison of the two applications. The meCUE questionnaire provides automatic calculations using Microsoft Excel. Based on this research, it can be concluded as follows: (1) The Gather Town application has a better User Experience assessment than the Google Meet application. The overall indicator results on the Gather Town application show an average value of 4.6 where the value is higher than the Google Meet application with an average value of 3.3, (2) There is a difference between using the Google Meet and Gather Town video conferencing platforms in terms of User Experience using the meCUE Questionnaire for students (Sig. = 0.000 <0.05), (3) Google Meet and Gather Town platforms have their respective weaknesses and advantages that can be used alternately according to the learning method used by the teacher. The results of this study can be used as a reference in choosing video conferencing applications to be more effective and optimal in the learning process.

Assessment of User Experience (UX) Design Trends in Mobile Applications

Assessment of User Experience (UX) Design Trends in Mobile Applications

Developing Website English Learning Application with Google Site to Enhance Grammar Understanding

Grammar understanding is the main point to get the English skill. This study explores the development of a website-based English learning application aimed at enhancing grammar understanding, utilizing Google Sites as the platform. The application was developed following the System Development Life Cycle (SDLC) - Waterfall Model, encompassing phases of requirements analysis, system design, implementation, testing, and deployment. The primary objective was to create an accessible, user-friendly platform that provides comprehensive grammar tutorials, interactive exercises, and quizzes to reinforce learning. During the development process, key user needs were identified, leading to the design of a structured and responsive website. The implementation phase focused on integrating multimedia content and interactive elements to engage learners and facilitate effective grammar practice. Testing involved both functionality and user experience assessments, with feedback indicating that the application successfully supported grammar learning, though some improvements were recommended for clarity and content breadth. The study concludes that using Google Sites for educational purposes offers a practical solution for creating accessible learning tools. The application demonstrated significant potential in enhancing grammar understanding among users, with future improvements suggested to expand the range of topics and interactive features. This project provides a foundation for further exploration of web-based language learning applications using low-cost, widely available platforms.

The development of Logix – An application for component-based case logging and surgical trainee assessment

BackgroundThe optimal training program to transform a new resident into a competent and capable surgeon is constantly evolving. Competency-based evaluation represents a change in mindset from quantitative or chronologic metrics for graduate readiness. As surgery becomes more specialized, more dependent on technology, and more public, we must continue to improve our ability to pass on technical skills. Approaching surgery in a component-based fashion enables even the most complex operation to be broken down into smaller sets of steps that range the entire spectrum of complexity. Treating an operation through the lens of its components, emphasizing stepwise forward progression in a trainee's experience, may provide a way to train competent surgeons more efficiently. Current case-logging products do not provide adequate granularity to apply this methodology. MethodsApplication design relied on the involvement of local surgeons from all specialties and subspecialties related to general surgical training. Individual interviews with multiple experts in each field were used to generate a list of most commonly performed operations. Once a consensus was reached, the same surgeons were queried on what they felt were the core steps that make up each operation. This information was utilized to create a novel mobile application which enables the user to record cases by date, attending surgeon, specific operation, and which portions of the operation they were able/allowed to perform. ConclusionComponent-based case logging through the Logix application may be a useful adjunct as we continue to implement competency-based surgical training. Future investigation will assess user experience and compare subjective and objective metrics of training progression between the Logix application and currently utilized products. The information provided by the application stands to benefit not just trainees, but educators, training programs, and regulatory bodies. Key messageComponent-based case logging via a novel mobile application stands to increase the efficiency of surgical training and more effectively assess trainee competency.

A Comprehensive Assessment of Technical Impacts and User Experience with Food Waste Grinders in Multiunit Residential Buildings

A Comprehensive Assessment of Technical Impacts and User Experience with Food Waste Grinders in Multiunit Residential Buildings

Charting User Experience in Physical Human–Robot Interaction

Robots increasingly interact with humans through touch, where people are touching or being touched by robots. Yet, little is known about how such interactions shape a user’s experience. To inform future work in this area, we conduct a systematic review of 44 studies on physical human–robot interaction (pHRI). Our review examines the parameters of the touch (e.g., the role of touch, location), the experimental variations used by researchers, and the methods used to assess user experience. We identify five facets of user experience metrics from the questionnaire items and data recordings for pHRI studies. We highlight gaps and methodological issues in studying pHRI and compare user evaluation trends with the Human–Computer Interaction (HCI) literature. Based on the review, we propose a conceptual model of the pHRI experience. The model highlights the components of such touch experiences to guide the design and evaluation of physical interactions with robots and inform future user experience questionnaire development.

Optimizing User Satisfaction: A Comprehensive Evaluation of the Info BMKG App Using UEQ+ and IPA Methods

An update to the appearance of the BMKG Info app in November 2022 led to a 0.26 drop in the monthly rating, suggesting that the change may not have met users' expectations. This study aims to identify the cause of the rating drop through a user experience (UX) assessment involving 1,237 app users. Using the User Experience Questionnaire Plus (UEQ+) and Importance Performance Analysis (IPA), this study collected and analyzed user feedback related to five aspects of UX: efficiency, novelty, usability, trust in content, and clarity. IPA results show that efficiency is a highly important but underperforming aspect, indicating that interface updates reduce efficiency and negatively impact user satisfaction. Recommendations include prioritizing efficiency improvements, usability evaluations, collecting additional feedback, and using IPA data to drive improvement priorities. The findings of this study contribute to the field of science by demonstrating the importance of a comprehensive UX analysis for updated apps. For future research, it is recommended to conduct longitudinal studies to monitor changes in user satisfaction over time and explore innovative methods to improve the overall user experience.

Characterizing UX Assessment in the Context of Immersive Experiences: A Systematic Mapping Study

An immersive experience is a multisensory experience across a journey or task that’s contextually relevant, enabled by a combination of interactions that create intuitive and emotional value for the user. As the technological landscape has evolved, immersive experiences have become increasingly integrated into our lives. The rise of immersive experiences comes with a focus on how to evaluate those experiences considering User Experience (UX). UX is a multifaceted construct, and its importance differs according to the type of experience. In this scenario, knowing how to evaluate UX is fundamental to understanding whether immersive experiences are pleasant. Despite some attempts to address the UX, a systematic approach to addressing UX in the immersive context still needs to be developed. This paper presents a Systematic Literature Mapping (SLM) to investigate how UX evaluations have been performed and the main UX dimensions that should be considered in immersive experiences, such as engagement, presence, and immersion. Our main result is a theoretical model that we proposed based on the UX definitions and relations from the literature. Our model can help study the relations between UX dimensions, establishing the primary UX dimensions regarding immersive experiences, and as a base for developing new UX evaluation techniques.

Importance Performance Matrix Analysis for Assessing User Experience with Intelligent Voice Assistants: A Strategic Evaluation

Importance Performance Matrix Analysis for Assessing User Experience with Intelligent Voice Assistants: A Strategic Evaluation

Assessing User Experience in Immersive Virtual Reality Environment: A review of interconnected terms and meanings

This article reports a research project aiming to identify aspects that influence User Experience (UX) in Immersive Virtual Reality (IVR) environments.

Facial Coding Study of the Effect of Halal Claims on Purchase Intention of Electronic Products: Linking Maslow's Hierarchy of Needs Theory

Usability testing plays a pivotal role in assessing user experience on websites, providing businesses with invaluable insights into customer perspectives. Eye-tracking, a widely accepted methodology, zeroes in on visual engagement by analyzing specific Areas of Interest (AOI). This study embarked on an exploration of the impact of AOI on dwell time for the latest iteration of the Waters website and further delineated the sections that captivated the most and least user attention. Adopting a quantitative stance, a two-way ANOVA was deployed on a sample comprising 15 master’s students from two distinct academic institutions. Preliminary findings underscore significant disparities in dwell times across different AOIs, implying that specific AOIs retain user attention more robustly. Notably, the research has its constraints, encompassing potential deviations in webcam-based eye-tracking accuracy, the modest sample size, and post-hoc AOI categorization. As an extension, subsequent studies could probe the nuanced factors swaying dwell time within Waters' website AOIs, integrating methodologies such as the WSD thnique and proactive AOI classification.

IDENTIFYING AND FIXING UX-FRICTION EMPLOYEE DEVELOPMENT WEBSITE WITH MIXED APPROACH HEART FRAMEWORK AND USABILITY TESTING

The company website has an important role in the business processes that occur in the company, one of which is managing employee productivity. PT.XYZ utilizes the Kaizen website to improve the quality of its employees. Assessment of user experience while operating the website can be a form of evaluation between expectations and actual conditions related to website feasibility. In this study, the researcher intends to find out what indicators are obstacles in the operation of a web-based application called the Kaizen website at PT.XYZ so that there is inefficiency in its use. This research involved 54 respondents who were employees of PT.XYZ. The combination of HEART and Usability Testing methods is used to identify obstacles experienced by users and evaluate user experience when using the Kaizen website. The results of the analysis are then used to improve website performance in order to create a good user experience. The results showed that the HEART score increased by an average of 9% on each variable. Usability testing assessment also shows that the Kaizen website reaches the acceptable category with a score of 90.5 after improvements are made.

User experience and interface assessment for metaverse platforms on nurses and nursing students: A cross-sectional study

BackgroundThe metaverse, a rapidly evolving virtual environment, offers new opportunities for healthcare education. The effectiveness of the metaverse as a learning tool depends on user readiness and platform characteristics. AimThis study aimed to examine the current use of metaverse platforms among nurses and nursing students in South Korea and explore the relationship between user characteristics and their metaverse experience, focusing on presence, usability, and user experience. DesignThis was a cross-sectional descriptive study. SettingsRegistered nurses and nursing students from various healthcare settings and educational institutions in South Korea participated in this study. ParticipantsThis study included 428 participants, comprising 188 nurses and 240 nursing students. MethodsBetween September and November 2022, participants provided voluntary informed consent. The participants engaged with one of the following two metaverse platforms: ZEPETO (mobile-based) or Gather (screen-based). After four structured exploration phases, the participants completed online questionnaires. These surveys assessed general characteristics, metaverse self-efficacy, sense of presence, usability, and user experience. ResultsMost participants had previous experience with the metaverse and rated their metaverse self-efficacy at 3.60. Nurses scored higher than nursing students in terms of presence, usability, and user experience in the metaverse. Higher work self-efficacy in nurses and academic self-efficacy in nursing students were associated with more positive experiences in the metaverse. Nurses consistently rated higher across all subdomains of presence, usability, and user experience than nursing students. The type of metaverse platform also significantly influenced user experience. ConclusionsA significant proportion of Korean nurses and nursing students are familiar with the metaverse, reflecting a global trend towards virtual environments in education and healthcare. Although the metaverse holds promise for healthcare education, its effectiveness depends on user readiness, platform characteristics, and the development of a reliable, structured, and user-friendly educational programme.

Creating an AI-powered platform for neurosurgery alongside a usability examination: Progressing towards minimally invasive robotics

Recent advancements in artificial intelligence have paved the way for promising applications in neurosurgery, aiming to improve patient outcomes while minimizing risks. This paper introduces a novel AI-driven system designed to assist neurosurgeons in accurately identifying and localizing brain tumors. Leveraging deep learning algorithms, the system was trained on a comprehensive dataset of brain MRI scans for segmentation and classification tasks. Evaluation of the system on an independent set of brain MRI scans revealed an average Dice similarity coefficient of 0.87, indicating high performance. Moreover, a user experience assessment conducted at the Department of Neurosurgery, University Hospital Ulm, demonstrated notable enhancements in accuracy, efficiency, and reduced cognitive load and stress levels among users. Notably, the system showcased adaptability across various surgical scenarios and provided personalized guidance to users. These findings underscore the potential of AI to augment the quality of neurosurgical interventions and ultimately enhance patient outcomes. Future endeavors will focus on integrating this system with robotic surgical tools to facilitate minimally invasive surgeries.

Creating an AI-powered platform for neurosurgery alongside a usability examination: Progressing towards minimally invasive robotics

Recent advancements in artificial intelligence have paved the way for promising applications in neurosurgery, aiming to improve patient outcomes while minimizing risks. This paper introduces a novel AI-driven system designed to assist neurosurgeons in accurately identifying and localizing brain tumors. Leveraging deep learning algorithms, the system was trained on a comprehensive dataset of brain MRI scans for segmentation and classification tasks. Evaluation of the system on an independent set of brain MRI scans revealed an average Dice similarity coefficient of 0.87, indicating high performance. Moreover, a user experience assessment conducted at the Department of Neurosurgery, University Hospital Ulm, demonstrated notable enhancements in accuracy, efficiency, and reduced cognitive load and stress levels among users. Notably, the system showcased adaptability across various surgical scenarios and provided personalized guidance to users. These findings underscore the potential of AI to augment the quality of neurosurgical interventions and ultimately enhance patient outcomes. Future endeavors will focus on integrating this system with robotic surgical tools to facilitate minimally invasive surgeries.

Unsupervised robot-assisted rehabilitation after stroke: feasibility, effect on therapy dose, and user experience

BackgroundUnsupervised robot-assisted rehabilitation is a promising approach to increase the dose of therapy after stroke, which may help promote sensorimotor recovery without requiring significant additional resources and manpower. However, the unsupervised use of robotic technologies is not yet a standard, as rehabilitation robots often show low usability or are considered unsafe to be used by patients independently. In this paper we explore the feasibility of unsupervised therapy with an upper limb rehabilitation robot in a clinical setting, evaluate the effect on the overall therapy dose, and assess user experience during unsupervised use of the robot and its usability.MethodsSubacute stroke patients underwent a four-week protocol composed of daily 45 min-sessions of robot-assisted therapy. The first week consisted of supervised therapy, where a therapist explained how to interact with the device. The second week was minimally supervised, i.e., the therapist was present but intervened only if needed. After this phase, if participants learnt how to use the device, they proceeded to two weeks of fully unsupervised training. Feasibility, dose of robot-assisted therapy achieved during unsupervised use, user experience, and usability of the device were evaluated. Questionnaires to evaluate usability and user experience were performed after the minimally supervised week and at the end of the study, to evaluate the impact of therapists’ absence.ResultsUnsupervised robot-assisted therapy was found to be feasible, as 12 out of the 13 recruited participants could progress to unsupervised training. During the two weeks of unsupervised therapy participants on average performed an additional 360 min of robot-assisted rehabilitation. Participants were satisfied with the device usability (mean System Usability Scale scores > 79), and no adverse events or device deficiencies occurred.ConclusionsWe demonstrated that unsupervised robot-assisted therapy in a clinical setting with an actuated device for the upper limb was feasible and can lead to a meaningful increase in therapy dose. These results support the application of unsupervised robot-assisted therapy as a complement to usual care in clinical settings and pave the way to its application in home settings.Trial registrationRegistered on 13.05.2020 on clinicaltrials.gov (NCT04388891).