Understanding Of User Experience Research Articles

Ongoing Assessments: Benefits and Challenges of Using Patron Surveys during the Pandemic

This column discusses the benefits and limitations of continuous assessment by reporting on the authors’ perspectives of ongoing assessment using examples from patron surveys designed to understand user experience in the physical library and to measure whether needs were met throughout the pandemic. This column will be helpful to anyone involved in assessment or who is interested in what factors to consider while carrying out ongoing assessment or using evidence-based data for decision-making.

Developing evidence for building sanitation justice: A multi methods approach to understanding public restroom quantity, quality, accessibility, and user experiences.

Access to basic sanitation is a human right and a critical environmental determinant of health. In this paper, we detail the development of three tools to investigate sanitation justice: (1) our public restroom spatial database, (2) our field assessment tool, and (3) survey of restroom access experiences. We document our process to collect these data in a consistent, health equity-driven framework. Together, these tools comprise a suite of methods for the examination of public restrooms from the macro- to the micro-level, and highlight key opportunities to promote health and well-being among restroom-reliant populations (e.g., people experiencing homelessness) by advancing sanitation justice in the built environment. With an illustrative case study, we demonstrate how methods triangulation, using the tools in concert, can provide a comprehensive assessment of basic sanitation access in a given region-San Diego, CA. We also detail how each tool can also be used separately to assess key sanitation justice and health equity questions that may be of interest to researchers, public health practitioners, policymakers, and advocates, including: (1) where do public restrooms exist (mapping)?; (2) how accessible are public restroom facilities, and what health-supportive features do they have (field assessment)?; and (3) what are the experiences of people most reliant on the available public restroom facilities (survey)? The results of our case study demonstrate that these adaptable tools can be used to provide meaningful data on and a holistic picture of public restroom quantity, quality, accessibility, and the experiences of public restroom users in a given region.

Development of Instruction – Augmenting Project for Faculty Members of the Department of Management Studies: An Action Research

This study aimed to assess the developed e-class record system to help the academic staff of the Cavite State University – CCAT Campus. The researchers wanted to evaluate the said system to determine the effectiveness and ease of use of the e-class record system. This study employed quasi-experimental and phenomenological designs to understand user experience to augment the Technology Acceptance Model (TAM). The intervention employed by the researchers was efficient and saved 0:25:51 of time in minutes, as indicated by the average cumulative usage time of 58:20.8 minutes. The goal of setting the intervention was to use e-class records, which had the desired result. This action research revealed the efficiency with regard to the time stamping with intervention, which helped the faculty improve their target goal of efficiency in recording grades. This study recommended having more knowledge and learning among the faculty using the said e-class record system.

Understanding user experiences and expectations toward patient appointment systems

Patient appointment systems are automated reservation systems which allow people to book healthcare services, such as doctor appointments or outpatient appointments online or in apps. In many cases, patient appointment systems are attached as a function in the websites of hospitals. As a kind of direct-to-user healthcare technology which build interactions with patients, the experiences the systems created can affect patients emotion status and health conditions. Therefore, to investigate how user experience could be improved and how positive experience could be created through Human Computer Interaction (HCI) and user experience design, Clincare, a prototype healthcare website making users feel supportive was designed. To characterize users experience and expectations towards patient appointment systems, user experience study was then conducted using the prototype. The results revealed 4 aspects which could significantly influence participants experience and emotions: Information Display, Aesthetics, Workflow, and Context of Use. Based on the result, 4 design implications were proposed to inform future design works of patient appointment systems.

Understanding user experience of an open design-clothing product.

Few studies related open design to the clothing sector, but none explored how users would experience it. The study reported here aimed to investigate how people with some or without prior sewing knowledge - advanced and amateur users – experience an open design-clothing product. Following four fashion design heuristics, a garment was created and distributed as DIY kits among advanced and amateur users. Data were collected in two stages: assembly and personalization. The results indicate that although skills play a significant role during assembly, other factors, like cross-generational differences and personal taste, influence how users experience an open design product. Furthermore, the study shows that given the necessary support, the open design can be used by a heterogeneous public, amplifying the participation of users with little or without prior sewing skills in clothing co-creation.

Co-designing a shared book reading environment at a community hub

Purpose Community hubs often provide support to families in areas of high vulnerability and can provide unique opportunities for delivering early literacy programs. This study used a co-design process to engage families, staff, and community partners within a community hub to design an environment that supported shared book reading. Method Co-design was enacted in four phases: 1) interviews to understand user experiences relating to shared book reading; 2) focus groups to refine ideas into actions to support shared book reading and prioritise these actions; 3) implementation of changes; and 4) understanding of participants’ experiences of involvement. Result Participant identified changes were implemented within four categories: 1) changing how books are organised, 2) showing families how to share books, 3) giving families information about how books can be borrowed, and 4) running more activities about books. Participants indicated they enjoyed being a part of a co-design process to affect change at the community hub. Conclusion Co-design enabled the development of collaborative changes to support book reading that were valued and owned by families, staff, and community partners. Community hubs can provide unique opportunities to engage with families in areas of vulnerability to support the development of early language and literacy skills.

How Do Users Respond to Mass Vaccination Centers? A Cross-Sectional Study Using Natural Language Processing on Online Reviews to Explore User Experience and Satisfaction with COVID-19 Vaccination Centers

To reach large groups of vaccine recipients, several high-income countries introduced mass vaccination centers for COVID-19. Understanding user experiences of these novel structures can help optimize their design and increase patient satisfaction and vaccine uptake. This study drew on user online reviews of vaccination centers to assess user experience and identify its key determinants over time, by sentiment, and by interaction. Machine learning methods were used to analyze Google reviews of six COVID-19 mass vaccination centers in Berlin from December 2020 to December 2021. 3647 user online reviews were included in the analysis. Of these, 89% (3261/3647) were positive according to user rating (four to five of five stars). A total of 85% (2740/3647) of all reviews contained text. Topic modeling of the reviews containing text identified five optimally latent topics, and keyword extraction identified 47 salient keywords. The most important themes were organization, friendliness/responsiveness, and patient flow/wait time. Key interactions for users of vaccination centers included waiting, scheduling, transit, and the vaccination itself. Keywords connected to scheduling and efficiency, such as "appointment" and "wait", were most prominent in negative reviews. Over time, the average rating score decreased from 4.7 to 4.1, and waiting and duration became more salient keywords. Overall, mass vaccination centers appear to be positively perceived, yet users became more critical over the one-year period of the pandemic vaccination campaign observed. The study shows that online reviews can provide real-time insights into newly set-up infrastructures, and policymakers should consider their use to monitor the population's response over time.

Using digital chatbots to close gaps in healthcare access during the COVID-19 pandemic.

Chatbots have emerged as a first link to care in recent years. The COVID-19 pandemic, and consequent health system disruptions, expanded their use. Socios En Salud (SES) introduced chatbots in Peru, which experienced one of the highest excess COVID mortalities in the world. SES and the government identified unmet population health needs, which could be amenable to virtual interventions. Chatbots were developed to screen individuals for these conditions; we describe the period of deployment, number of screenings, and number of people who received services. Between April 2020 and May 2021, SES deployed nine ChatBots: four for mental health, two for maternal and child health, and three for chronic diseases: breast cancer, hypertension, diabetes mellitus, and obesity. Mental health services were provided to 42,932 people, 99.99% of those offered services. The other ChatBots reached fewer people. Overall, more than 50% of eligible people accepted chatbot-based services. ChatBot use was highest for mental health. Chatbots may increase connections between a vulnerable population and health services; this is likely dependent on several factors, including condition, population, and penetration of smart phones. Future research will be critical to understand user experience and preferences and to ensure that chatbots link vulnerable populations to appropriate, high-quality care.

A MOBILE MUSIC APPLICATION FOR CAREGIVERS OF PERSONS WITH DEMENTIA: A USABILITY TESTING STUDY

Abstract More than 11 million Americans spend an average of 26.3 hours caring for a person with dementia (PWD). Managing behavioral and psychological symptoms of dementia (BPSD) is a significant source of caregiver stress. Music-based interventions (MBIs) have been shown to be a pleasant activity enjoyed by both PWD and their caregivers, with the potential to help alleviate BPSD. However, current commercial music streaming services are not designed for families coping with dementia due to subscription and/or network connection requirements. This mixed-methods usability study tested caregivers’ experience with an open-source Android application (MUsic to Support Engagement and Resilience, or MUSER) as a potential platform for home-based MBI delivered by caregivers of PWD. In-lab and in-home testing sessions were conducted with 6 caregivers (2 former and 4 current caregivers, 1 male and 5 females). Semi-structured interviews were conducted before and after the in-home testing period between July and November 2021 to better understand User Experiences (UX). Family caregivers had a mean age of 57.8 (SD=26.2, range 20-77). The main themes identified from the interviews included ease of use, device and music preferences, and prior experience with technology. Overall, users reported high satisfaction and would recommend the application to other caregivers. Users reported that listening to music on the app elicited positive emotional effects (e.g., calmness and relaxation). The MUSER mobile music application can be used by caregivers to deliver MBI in the community. Future research should test whether a caregiver-delivered MBI would be efficacious in reducing BPSD among PWD.

A Web-Based Self-help Intervention for Coping With the Loss of a Partner: Protocol for Randomized Controlled Trials in 3 Countries.

The death of a partner is a critical life event in later life, which requires grief work as well as the development of a new perspective for the future. Cognitive behavioral web-based self-help interventions for coping with prolonged grief have established their efficacy in decreasing symptoms of grief, depression, and loneliness. However, no study has tested the efficacy for reducing grief after losses occurring less than 6 months ago and the role of self-tailoring of the content. This study aims to evaluate the clinical efficacy and acceptance of a web-based self-help intervention to support the grief process of older adults who have lost their partner. It will compare the outcomes, adherence, and working alliance in a standardized format with those in a self-tailored delivery format and investigate the effects of age, time since loss, and severity of grief at baseline as predictors. Focus groups to understand user experience and a cost-effectiveness analysis will complement the study. The study includes 3 different randomized control trials. The trial in Switzerland comprises a waitlist control group and 2 active arms consisting of 2 delivery formats, standardized and self-tailored. In the Netherlands and in Portugal, the trials follow a 2-arm design that will be, respectively, complemented with focus groups on technology acceptance and cost-effectiveness analysis. The main target group will consist of adults aged >60 years from the general population in Switzerland (n≥85), the Netherlands (n≥40), and Portugal (n≥80) who lost their partner and seek help for coping with grief symptoms, psychological distress, and adaptation problems in daily life. The trials will test the intervention's clinical efficacy for reducing grief (primary outcome) and depression symptoms and loneliness (secondary outcomes) after the intervention. Measurements will take place at baseline (week 0), after the intervention (week 10), and at follow-up (week 20). The trials started in March 2022 and are expected to end in December 2022 or when the needed sample size is achieved. The first results are expected by January 2023. The trials will provide insights into the efficacy and acceptance of a web-based self-help intervention among older adults who have recently lost a partner. Results will extend the knowledge on the role of self-tailoring, working alliance, and satisfaction in the effects of the intervention. Finally, the study will suggest adaptations to improve the acceptance of web-based self-help interventions for older mourners and explore the cost-effectiveness of this intervention. Limitations include a self-selective sample and the lack of cross-cultural comparisons. Switzerland: ClinicalTrials.gov NCT05280041; https://clinicaltrials.gov/ct2/show/NCT05280041; Portugal: ClinicalTrials.gov NCT05156346; https://clinicaltrials.gov/ct2/show/NCT05156346. PRR1-10.2196/37827.

The Contributions of Customer Knowledge and Artificial Intelligence to Customer Satisfaction

Customer knowledge is critical for business and marketing strategy, and companies are turning to Artificial Intelligence (AI)-based data analysis to better understand user experience and behavior in both product and service sectors. This paper discusses the importance of customer knowledge and the tools for obtaining it using AI-based analysis. While AI-based analysis has many benefits, such as advanced and detailed analytics, it also has many drawbacks, such as privacy and the human-biased factor that the machine can learn from interacting with humans. AI is a delicate marketing technology that should be controlled by humans because it cannot replace humans in customer service, relationship management, and critical situations.

Patient Experience and Feedback After Using an Electronic Health Record-Integrated COVID-19 Symptom Checker: Survey Study.

BackgroundSymptom checkers have been widely used during the COVID-19 pandemic to alleviate strain on health systems and offer patients a 24-7 self-service triage option. Although studies suggest that users may positively perceive web-based symptom checkers, no studies have quantified user feedback after use of an electronic health record–integrated COVID-19 symptom checker with self-scheduling functionality.ObjectiveIn this paper, we aimed to understand user experience, user satisfaction, and user-reported alternatives to the use of a COVID-19 symptom checker with self-triage and self-scheduling functionality.MethodsWe launched a patient-portal–based self-triage and self-scheduling tool in March 2020 for patients with COVID-19 symptoms, exposures, or questions. We made an optional, anonymous Qualtrics survey available to patients immediately after they completed the symptom checker.ResultsBetween December 16, 2021, and March 28, 2022, there were 395 unique responses to the survey. Overall, the respondents reported high satisfaction across all demographics, with a median rating of 8 out of 10 and 288/395 (47.6%) of the respondents giving a rating of 9 or 10 out of 10. User satisfaction scores were not associated with any demographic factors. The most common user-reported alternatives had the web-based tool not been available were calling the COVID-19 telephone hotline and sending a patient-portal message to their physician for advice. The ability to schedule a test online was the most important symptom checker feature for the respondents. The most common categories of user feedback were regarding other COVID-19 services (eg, telephone hotline), policies, or procedures, and requesting additional features or functionality.ConclusionsThis analysis suggests that COVID-19 symptom checkers with self-triage and self-scheduling functionality may have high overall user satisfaction, regardless of user demographics. By allowing users to self-triage and self-schedule tests and visits, tools such as this may prevent unnecessary calls and messages to clinicians. Individual feedback suggested that the user experience for this type of tool is highly dependent on the organization's operational workflows for COVID-19 testing and care. This study provides insight for the implementation and improvement of COVID-19 symptom checkers to ensure high user satisfaction.

Design, Development, and Testing of BEST4Baby, an mHealth Technology to Support Exclusive Breastfeeding in India: Pilot Study.

BackgroundExclusive breastfeeding (EBF) at 6 months of age in most low- and middle-income countries, including India, is surprisingly low. There is a relative lack of mobile health apps that specifically focus on leveraging the use of peer counselors (PCs) to support mothers as a means of increasing EBF practices in low- and middle-income countries.ObjectiveThis study aimed to design, develop, and test the usability of Breastfeeding Education Support Tool for Baby (BEST4Baby), a mobile health app specifically designed to support PCs in providing in-home breastfeeding counseling support to mothers in rural India on optimal breastfeeding practices.MethodsA user-centered design process with an agile development methodology was used. The approach involved stakeholders and mothers who were trained to serve as PCs to guide BEST4Baby’s design and development, including the app’s content and features. PCs were engaged through focus groups with interactive wireframes. During the 24-month pilot study period, we conducted a feasibility test of the BEST4Baby app with 22 PCs who supported home visits with mothers residing in rural India. The intervention protocol required PCs to provide education and follow mothers using the BEST4Baby app, with 9 scheduled home visits from the late prenatal stage to 6 months post partum. BEST4Baby’s usability from the PCs’ perspective was assessed using the translated System Usability Scale (SUS).ResultsThe findings of this study align with best practices in user-centered design (ie, understanding user experience, including context with iterative design with stakeholders) to address EBF barriers. This led to the cultural tailoring and contextual alignment of an evidence-based World Health Organization breastfeeding program with an iterative design and agile development of the BEST4Baby app. A total of 22 PCs tested and rated the BEST4Baby app as highly usable, with a mean SUS score of 85.3 (SD 9.1), placing it over the 95th percentile for SUS scores. The approach translated into a highly usable BEST4Baby app for use by PCs in breastfeeding counseling, which also statistically increased EBF practices.ConclusionsThe findings suggest that BEST4Baby was highly usable and accepted by mothers serving as PCs to support other mothers in their EBF practices and led to positive outcomes in the intervention group’s EBF rates. The pilot study demonstrated that using the specially designed BEST4Baby app was an important support tool for mothers to serve as PCs during the 9 home visits.Trial RegistrationClinicaltrials.gov NCT03533725; https://clinicaltrials.gov/ct2/show/NCT03533725

Towards a more Connected Home: User Attitudes and Perceptions after an Integrated Home Technology Exposure

Recent advancements in Internet of Things (IoT) have introduced many smart home technologies that can provide higher levels of care and convenience to residents. This study aims at understanding user experience in a more connected home and the extent to which previous experience with and exposure to smart home systems can influence user acceptance and adoption of smart home technologies. Using a smart home prototype, a 3-week field trial was conducted to simulate an integrated home environment. Data were gathered after self-installation and after completion of the trial. Results show that technology exposure had positive influence on participants’ attitudes and opinions towards using smart home systems for various tasks. Moreover, participants reported high levels of satisfaction with the self-installation process which aimed to address consumers’ complaints regarding complex setup processes. Results will be discussed based on the practical and commercial implications regarding deployment of home devices.

Understanding User Experience and Satisfaction with Urban Infrastructure through Text Mining of Civil Complaint Data

Understanding User Experience and Satisfaction with Urban Infrastructure through Text Mining of Civil Complaint Data

Fabrication of Nāmya: A Bend and Touch-Sensitive Flexible Smartphone-Sized Prototype

In human-computer interaction research, prototypes allow for communicating design ideas and conducting early user studies to understand user experience without developing the actual product. For investigating deformation-based interaction, functional prototyping becomes challenging due to the unavailability of commercial platforms and the marginal availability of flexible electronic components. During functional prototyping, incurred time and cost are essential factors that further depend on the ease of stiffness customization, reproduction, and upgrade. To offer these advantages, this work presents the fabrication workflow of Nāmya, a smartphone-sized flexible prototype that can detect bend gestures and touch-based inputs using off-the-shelf sensors and flexible materials. This do-it-yourself (DIY) approach to fabricating deformable prototypes focuses on addressing the challenges of selecting flexible material, type of sensor, and sensor positions. We also demonstrate that the proposed use of a flexible three-dimensional- (3D-) printed internal structure with sensor pockets and the one-part silicone cast allows the development of robust deformable prototypes. This fabrication process offers the opportunity to easily customize device stiffness, reproduce prototypes with similar physical properties, and upgrade existing prototypes.

User Experience Quantification Model from Online User Reviews

Due to the advancement in information technology and the boom of micro-blogging platforms, a growing number of online reviews are posted daily on product distributed platforms in the form of spontaneous and insightful user feedback, and these can be used as a significant data source to understand user experience (UX) and satisfaction. However, despite the vast amount of online reviews, the existing literature focuses on online ratings and ignores the real textual context in reviews. We proposed a three-step UX quantification model from online reviews to understand customer satisfaction using the effect-based Kano model. First, the relevant online reviews are selected using various filter mechanisms. Second, UX dimensions (UXDs) are extracted using a proposed method called UX word embedding Latent Dirichlet allocation (UXWE-LDA) and sentiment orientation using a transformer-based pipeline. Then, the casual relationships are identified for the extracted UXDs. Third, the UXDs are mapped on the customer satisfaction model (effect-based Kano) to understand the user perspective about the system, product, or services. Finally, the different parts of the proposed quantification model are evaluated to examine the performance of this method. We present different results of the proposed method in terms of accuracy, topic coherence (TC), Topic-wise performance, and expert-based evaluation for the proposed framework validation. For review quality filters, we achieved 98.49% accuracy for the spam detection classifier and 95% accuracy for the relatedness detection classifier. The results show that the proposed method for the topic extractor module always gives a higher TC value than other models such as WE-LDA and LDA. Regarding topic-wise performance measures, UXWE-LDA achieves a 3% improvement on average compared to LDA due to the incorporation of semantic domain knowledge. We also compute the Jaccard coefficient similarity between the extracted dimensions using UXWE-LDA and UX experts-based analysis for checking the mutual agreement, which is 0.3, 0.5, and 0.4, respectively. Based on the Kano model, the presented study has potential implications concerning issues and knowing the product’s strengths and weaknesses in product design.

Exploring user experience in digital libraries through questionnaire and eye-tracking data

In the field of digital libraries, research on user experience is sparse, especially in terms of emotions, impressions, and stimulation evoked by interaction with the digital library. Given the many different methods and tools available for assessing user experience, two questionnaires and eye-tracking were explored to see how each can contribute to understanding user experience in digital libraries. An eye-tracking study with 30 participants was carried out using two digital libraries. Analysis of the questionnaires revealed that overall, one digital library was experienced more positively, with the difference most evident in the hedonic quality. The eye-tracking data revealed different gaze patterns in the two digital libraries, with significant difference in measure values particularly on the search boxes. When eye-tracking was combined with the questionnaire data, several correlations were found, indicating that the search box position and the intuitiveness of the homepage had an impact on the user experience.

User Experiences With an SMS Text Messaging Program for Smoking Cessation: Qualitative Study.

BackgroundMobile health strategies for smoking cessation (eg, SMS text messaging–based interventions) have been shown to be effective in helping smokers quit. However, further research is needed to better understand user experiences with these platforms.ObjectiveThis qualitative study aims to explore the experiences of real-world users of a publicly available smoking cessation program (SmokefreeTXT).MethodsSemistructured phone interviews were conducted with 36 SmokefreeTXT users between March and July 2014. Of these 36 participants, 50% (18/36) of participants completed the SmokefreeTXT program (ie, did not opt out of the program before the 6- to 8-week completion period), and 50% (18/36) did not complete the program (ie, requested to opt out of the program before the completion period). Interview questions focused on smoking behaviors, quitting history, opinions on the program’s content and structure, answering assessment questions, using keywords, reasons for opting out, and perceived usefulness of the program for quitting smoking. A thematic content analysis was conducted, with a focus on themes to increase program engagement and optimization.ResultsThe findings highlighted features of the program that participants found beneficial, as well as some elements that showed opportunities for improvement to boost program retention and successful cessation. Specifically, most participants found the SmokefreeTXT program to be convenient and supportive of cessation; however, some found the messages to be repetitive and reported a desire for more flexibility based on their readiness to quit and cessation progress. We also found that program completion did not necessarily indicate successful smoking cessation and that program opt out, which might be interpreted as a less positive outcome, may occur because of successful cessation. Finally, several participants reported using SmokefreeTXT together with other evidence-based cessation methods or non–evidence-based strategies.ConclusionsQualitative interviews with real-world SmokefreeTXT users showed high program acceptability, engagement with program features, and perceived utility for smoking cessation. Our findings directly informed several program updates, such as adding an adaptive quit date feature and offering supplemental information on live support services for users who prefer human interaction during the cessation process. The study has implications for other digital tobacco cessation interventions and highlights important topics that warrant future research, such as the relationship between program engagement (eg, opt out and retention) and successful cessation.

User Experience, Engagement, and Popularity in Mental Health Apps: Secondary Analysis of App Analytics and Expert App Reviews.

BackgroundUser experience and engagement are critical elements of mental health apps’ abilities to support users. However, work examining the relationships among user experience, engagement, and popularity has been limited. Understanding how user experience relates to engagement with and popularity of mental health apps can demonstrate the relationship between subjective and objective measures of app use. In turn, this may inform efforts to develop more effective and appealing mental health apps and ensure that they reach wide audiences.ObjectiveWe aimed to examine the relationship among subjective measures of user experience, objective measures of popularity, and engagement in mental health apps.MethodsWe conducted a preregistered secondary data analysis in a sample of 56 mental health apps. To measure user experience, we used expert ratings on the Mobile App Rating Scale (MARS) and consumer ratings from the Apple App Store and Google Play. To measure engagement, we acquired estimates of monthly active users (MAU) and user retention. To measure app popularity, we used download count, total app revenue, and MAU again.ResultsMARS total score was moderately positively correlated with app-level revenue (Kendall rank [T]=0.30, P=.002), MAU (T=0.39, P<.001), and downloads (T=0.41, P<.001). However, the MARS total score and each of its subscales (Engagement, Functionality, Aesthetics, and Information) showed extremely small correlations with user retention 1, 7, and 30 days after downloading. Furthermore, the total MARS score only correlated with app store rating at T=0.12, which, at P=.20, did not meet our threshold for significance.ConclusionsMore popular mental health apps receive better ratings of user experience than less popular ones. However, user experience does not predict sustained engagement with mental health apps. Thus, mental health app developers and evaluators need to better understand user experience and engagement, as well as to define sustained engagement, what leads to it, and how to create products that achieve it. This understanding might be supported by better collaboration between industry and academic teams to advance a science of engagement.