User-centered Study Research Articles

Trustworthiness of EHRs: Key Factors from a User-Centered Study in Germany

Abstract Background The integration of digital technologies, particularly Electronic Health Records (EHRs), promises substantial improvements in patient care and cost reductions. However, the success of EHRs depends heavily on patient trust and usage, which are influenced by their control over data visibility, storage, and sharing. Identifying the factors that enhance the perceived trustworthiness of EHRs is essential for increasing their reliability and acceptance in healthcare settings. Methods Participants (N = 30) first interacted with an interactive EHR prototype, then evaluated its trustworthiness and suggested improvements during semi-structured interviews. These interviews were transcribed and analyzed using thematic analysis to identify key themes affecting perceptions of the EHR’s trustworthiness. Results Through thematic analysis, we developed a categorical system encompassing five principal themes: provider reputation, information quality, system characteristics, user control, and user feedback. The analysis revealed that deficiencies in design and usability indirectly affect perceptions of privacy and data security. Conclusions Our study underscores the critical role of contextual factors-including provider reputation, strategic IT partnerships, and user feedback-in cultivating trust in Electronic Health Record (EHR) systems. Addressing privacy concerns and bolstering user trust necessitates not only a professional approach to design and usability but also clear communication about adherence to rigorous data privacy and security standards. In Germany’s tightly regulated environment, clearly communicating EHR security standards is crucial. Enhancing trust also involves robust customer support, user control over their data, and leveraging social proof like high download rates or positive reviews. These approaches could significantly improve EHR acceptance and trust in digital health across the country. Key messages • The perceived trustworthiness of EHRs is essential for increasing their reliability and acceptance in healthcare settings. • Effective communication and design are critical for building trust in digital health technologies. Trust in EHRs grows with transparent data policies and empowering user controls.

Hiding in plain sight: Cooperative Extension as an underutilized approach to improving cancer survivorship outcomes in underserved populations.

Explore the potential utility of a Cooperative Extension-specific program to support post-active treatment cancer survivors. A user-centered study was conducted to identify barriers to and facilitators of the implementation of a program for adult cancer survivors living post primary cancer treatment ("cancer survivors") via Cooperative Extension("Extension"), including interviews analyzed using the Consolidated Framework for Implementation Research. Participants included Cooperative Extension Educators and adult cancer survivors in Oklahoma who completed data collection from July 2023 to September 2023. N = 20 participants were enrolled. Cancer survivors indicated poor familiarity with Extension, or a primary association with agriculture. Some voiced surprise Extension was not already providing cancer-related programming. Many expressed poor support in their communities due to issues secondary to rurality, often relying on non-cancer programs. Educators voiced a strong capability to deliver cancer-related programming if intentionally designed, with many already providing education on relevant topics (e.g., finances, nutrition, physical activity). A salient barrier was poor connectivity with the healthcare system. There is an immense need for improved survivorship care in underserved communities due to poor social connectedness, support structures, and poor mental health. Cooperative Extension is well-poised to deliver cancer survivorship-specific programming. Cooperative Extension provides an extensive network of professionals who can provide support to cancer survivors, particularly those post-active treatment.

Developing feedback visualizations to support older adults’ medication adherence

BackgroundBlood pressure control is critical for older adults because the prevalence of hypertension and resulting cardiovascular illness increases with age. Antihypertension medications are central to blood pressure treatment. However, nonadherence to antihypertension medications is high. Health technology such as smartphone apps provide an opportunity for users to manage their medication regimen and support processes related to medication-taking. ObjectiveWe implemented a user-centered evaluation approach to develop and refine adherence feedback visualizations for the MEDSReM© medication adherence app for older adults with hypertension. MethodsWe conducted a literature review and iterative usability testing to achieve this objective. We identified adherence goals, information needs, as well as design guidelines by reviewing theoretical frameworks and existing scientific evidence. We then used a two-phase iterative user-centered study and subject matter expert evaluation. Both quantitative and qualitative data were used to select and improve the current prototype and evolve to the next prototype. ResultsThe need for daily, weekly, and monthly adherence performance information as well as visualization formats for conveying this information was identified from the literature review. Overall, the information shown in visualization prototypes was successfully interpreted by participants. Comprehension issues of visualizations were identified and addressed from visual prototype revisions. Insights from both user and subject matter expert groups were used to select and refine the prototypes for the MEDSReM app. ConclusionEvidence-based and user-centered approaches were effective for developing visualizations about adherence performance feedback in the MEDSReM app and provided insight into how the app can be made easy to understand and use by older adults with hypertension, which will be evaluated in future effectiveness testing.

A Scoping Review on Mobile Health Technology for Assessment and Intervention of Upper Limb Motor Function in Children with Motor Impairments.

Upper limb (UL) motor dysfunctions impact residual movement in hands/shoulders and limit participation in play, sports, and leisure activities. Clinical and laboratory assessments of UL movement can be time-intensive, subjective, and/or require specialized equipment and may not optimally capture a child's motor abilities. The restrictions to in-person research experienced during the COVID-19 pandemic have inspired investigators to design inclusive at-home studies with child participants and their families. Relying on the ubiquity of mobile devices, mobile health (mHealth) applications offer solutions for various clinical and research problems. This scoping review article aimed to aggregate and synthesize existing research that used health technology and mHealth approaches to evaluate and assess the hand function and UL movement in children with UL motor impairment. A scoping review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) model was conducted in March 2023 yielding 25 articles (0.32% of 7891 studies). Assessment characteristics included game or task-based tests (13/25, 52%), primarily for neurological disorders (e.g., autism spectrum disorder [ASD], dystonia, dysgraphia) or children with cerebral palsy (CP). Although several mHealth studies were conducted in the clinical environment (10/25, 40%), studies conducted at home or in nonclinical settings (15/25, 60%) reported acceptable and highly satisfactory to the patients as minimizing the potential risks in participation. Moreover, the remaining barriers to clinical translation included object manipulation on a touch screen, offline data analysis, real-world usability, and age-appropriate application design for the wider population. However, the results emphasize the exploration of mHealth over traditional approaches, enabling user-centered study design, family-oriented methods, and large-scale sampling in future research.

Short Take: Designing a Multinational Smartphone App Survey during COVID-19: Rewards, Risks, and Recommendations

Cost-effective and user-friendly, mobile phone-assisted methods have remained underutilized in qualitative social science research. The scarce methodological guidance, together with recruitment and ethical challenges, has arguably stifled advancements in this area. COVID-19 exposed the need to better equip researchers with the expertise and tools to conduct remote research effectively. In 2020, we designed and launched a smartphone survey application to collect real-time data from children’s sector professionals across the globe regarding best practices in, and challenges to, responding to the pandemic. In this short article, we reflect on the efficiency, quality, and acceptability afforded by the smartphone app survey, and outline recommendations for enhancing rigor and feasibility. We also present data snippets illustrating the positive impact of participation on respondents—a seldom-documented aspect of app-based research. Altogether, we advocate a flexible, pragmatic, and user-centered study and app design that aligns with respondents’ specific, situational needs, and preferences.

The Rise of Thinking Machines: A Review of Artificial Intelligence in Contemporary Communication

Artificial intelligence (AI) capabilities in natural language processing are rapidly advancing and transforming communication practices across diverse contexts. This review provides a comprehensive analysis of AI's emerging roles in mediating and participating in direct communication to highlight key opportunities and research priorities around responsible innovation. The study surveys the extensive literature on major applications of AI, including virtual assistants, chatbots, smart replies, sentiment analysis tools, and automatic translation technologies. It also closely examines their current and potential usage and benefits across interpersonal, organizational, and societal communication. The analysis reveals these AI technologies promise enhanced efficiency, personali-zation, accessibility, and new modalities of expression in communication. The study found that if judiciously and ethically applied, they could incrementally improve communication speed, quality, relationships, and even therapists' capabilities over time. However, more rigorous research is still recommended to investigate longitudinal impacts on human well-being, increase accessibility for vulnerable demographic groups, advance multimodality AI systems, and develop tailored guidelines and user-centered studies to ensure ethical, socially responsible progress. Overall, this review synthesizes the current state of the science and pressing research needs in this rapidly emerging field.

Foresights for Location-Based Services in Media Management: Insights from an International Delphi Study

ABSTRACT Digitalization affects media businesses, media marketplaces, and with every single user the entire society, as well. But which of the new technologies, media distribution and usage will last? “Location-based services” (LBS), allowing to localize mobile devices to provide media content tailored to the user’s current context, appear to be a sound approach to meet the demands of fast, flexible and individualized communication. However, due to rapid technological developments, their future – still – remains uncertain. This contribution assesses relevant international LBS-experts in a two-round Delphi study. Findings indicate a strong emphasis on future challenges for (potential) LBS providers and developers, mainly addressing an intraorganizational level – especially with regard to workflows of traditionally oriented media enterprises. Further barriers brought up were privacy and security issues. Regarding the motivation to install LBS apps, scientists consider reliability, ease of use, and fulfillment of human needs to be of importance. Regarding hardware components, the indoor-deployment of LBS was – rather surprisingly – deemed much more promising than an outdoor use. Concerning trends in research, user-centered studies integrating psychological perspectives were brought up, as well as research on socio-ethical implications of LBS.

Evaluating and refining a pain quality information visualization tool with patients and interpreters to facilitate pain assessment in primary care settings

ABSTRACTInformation visualization (InfoViz) tools offer a potential solution to pain communication challenges. Incongruencies in communication styles between patients with limited English proficiency (LEP), interpreters, and providers contribute to significant disparities in pain care and outcomes. This study’s purpose is to evaluate and refine a culturally appropriate InfoViz pain quality assessment tool for LEP Hmong patients. We conducted a three-part iterative user-centered study with LEP Hmong, bilingual Hmong, and Hmong interpreters with (1) participatory design sessions to evaluate and refine pain infographics for inclusion on the tool, (2) card-sorting to organize the infographics to match the mental models of LEP patients, and (3) a tool assessment to identify which tool accurately represented LEP patients’ mental models and was preferred in clinical settings. Fifty-five participants provided three common themes for pain infographics refinement: culturally-relevant colors, infographics resembling human anatomy, and action-specific squiggle lines. The card-sorting sessions revealed three organizational themes: sensation (n = 15; 71.4%), localization (n = 6; 28.6%), and severity of pain quality (n = 5; 24.3%). Most participants selected the localization as the most accurate tool and preferred it in clinical settings. Using a multi-step, user-centered approach resulted in a culturally appropriate pain InfoViz tool for LEP Hmong patients.

Designing a Stress and Anxiety Support Tool to Help Young Adults with Autism in Daily Living

Abstract Individuals with autism may experience higher stress and anxiety levels for longer periods than their neurotypical peers. Traditional techniques to provide stress relief and anxiety management include support, which reminds people of how to face stressful situations. Some technological proposals supporting the user include strategies for detecting and monitoring stress levels. In this research, we conducted an iterative user-centered study aiming to understand how young adults with autism deal with stress in real-life situations. We proposed a set of five design principles that will serve as guidelines to develop assistive anxiety management technology for individuals with autism. We then developed a set of low-fi prototypes and selected SATORI, a support tool composed of three interfaces, to help young adults with autism autonomously manage the anxiety caused by stressful situations in their daily life. We evaluated our proposed design principles using SATORI with eight young adults with autism. The results show a positive perception of the design principles on what SATORI is based on, as participants perceived that SATORI could help them in their daily life to manage stress and channel anxiety.

The Placebo Effect of Artificial Intelligence in Human–Computer Interaction

In medicine, patients can obtain real benefits from a sham treatment. These benefits are known as the placebo effect. We report two experiments (Experiment I: N = 369; Experiment II: N = 100) demonstrating a placebo effect in adaptive interfaces. Participants were asked to solve word puzzles while being supported by no system or an adaptive AI interface. All participants experienced the same word puzzle difficulty and had no support from an AI throughout the experiments. Our results showed that the belief of receiving adaptive AI support increases expectations regarding the participant’s own task performance, sustained after interaction. These expectations were positively correlated to performance, as indicated by the number of solved word puzzles. We integrate our findings into technological acceptance theories and discuss implications for the future assessment of AI-based user interfaces and novel technologies. We argue that system descriptions can elicit placebo effects through user expectations biasing the results of user-centered studies.

Immersive Virtual Reality Avatars for Embodiment Illusions in People With Mild to Borderline Intellectual Disability: User-Centered Development and Feasibility Study.

Immersive virtual reality (IVR) has been investigated as a tool for treating psychiatric conditions. In particular, the practical nature of IVR, by offering a doing instead of talking approach, could support people who do not benefit from existing treatments. Hence, people with mild to borderline intellectual disability (MBID; IQ=50-85) might profit particularly from IVR therapies, for instance, to circumvent issues in understanding relevant concepts and interrelations. In this context, immersing the user into a virtual body (ie, avatar) appears promising for enhancing learning (eg, by changing perspectives) and usability (eg, natural interactions). However, design requirements, immersion procedures, and proof of concept of such embodiment illusion (ie, substituting the real body with a virtual one) have not been explored in this group. Our study aimed to establish design guidelines for IVR embodiment illusions in people with MBID. We explored 3 factors to induce the illusion, by testing the avatar's appearance, locomotion using IVR controllers, and virtual object manipulation. Furthermore, we report on the feasibility to induce the embodiment illusion and provide procedural guidance. We conducted a user-centered study with 29 end users in care facilities, to investigate the avatar's appearance, controller-based locomotion (ie, teleport, joystick, or hybrid), and object manipulation. Overall, 3 iterations were conducted using semistructured interviews to explore design factors to induce embodiment illusions in our group. To further understand the influence of interactions on the illusion, we measured the sense of embodiment (SoE) during 5 interaction tasks. IVR embodiment illusions can be induced in adults with MBID. To induce the illusion, having a high degree of control over the body outweighed avatar customization, despite the participants' desire to replicate their own body image. Similarly, the highest SoE was measured during object manipulation tasks, which required a combination of (virtual) locomotion and object manipulation behavior. Notably, interactions that are implausible (eg, teleport and occlusions when grabbing) showed a negative influence on SoE. In contrast, implementing artificial interaction aids into the IVR avatar's hands (ie, for user interfaces) did not diminish the illusion, presuming that the control was unimpaired. Nonetheless, embodiment illusions showed a tedious and complex need for (control) habituation (eg, motion sickness), possibly hindering uptake in practice. Balancing the embodiment immersion by focusing on interaction habituation (eg, controller-based locomotion) and lowering customization effort seems crucial to achieve both high SoE and usability for people with MBID. Hence, future studies should investigate the requirements for natural IVR avatar interactions by using multisensory integrations for the virtual body (eg, animations, physics-based collision, and touch) and other interaction techniques (eg, hand tracking and redirected walking). In addition, procedures and use for learning should be explored for tailored mental health therapies in people with MBID.

A Mixed Reality Cognitive Orthosis to Support Older Adults in Achieving Their Daily Living Activities: Focus Group Study With Clinical Experts.

BackgroundMixed reality is an emerging technology that allows us to blend virtual objects into the actual user’s environment. This can be realized using head-mounted displays. Many recent studies have suggested the possibility of using this technology to support cognition in people with neurodegenerative disorders (NDs). However, most studies have explored improvements in cognition rather than in independence and safety during the accomplishment of daily living activities. Therefore, it is crucial to document the possibility of using mixed reality to support the independence of older adults in their daily lives.ObjectiveThis study is part of a larger user-centered study of a cognitive orthosis using pure mixed reality to support the independence of people living with NDs. This study aimed to explore (the difficulties encountered by older adults with NDs in their daily life to ensure that pure mixed reality meets their needs, (the most effective interventions with this population to determine what types of assistance should be provided by pure mixed reality technology, how the pure mixed reality technology should provide assistance to promote aging in place, and the main facilitators of and barriers to the use of this technology.MethodsWe conducted a descriptive, qualitative study. A total of 5 focus groups were completed with occupational therapists who had expertise in the disease and its functional impacts (N=29) to gather information. Each focus group met once for a 1-hour period. All sessions were held over a 3-month period. A semistructured interview guide was used. All group interviews were audiotaped with the consent of each participant to facilitate the data analysis. We conducted inductive qualitative analysis in four stages using a thematic analysis approach: full transcription of the audio recordings, first-order coding of the transcribed data, second-order coding from the first-order code list, and data reduction and matrix development.ResultsThe results suggested that the main difficulties encountered by this population were in remembering to complete tasks, initiating the tasks, and planning the tasks. Several interventions are used to improve the independence of this population, such as prevention, simplification or facilitation, adaptation, and compensation. The use of pure mixed reality in older adults with NDs to promote independence and safety at home is promising and may respond to several clinical functions identified by the participants. Finally, pure mixed reality has good potential for use in this population and involves certain facilitators and obstacles, such as resources, technical aspects, and social considerations.ConclusionsThe cognitive orthosis that will be developed in light of this study will act as a proof of concept for the possibility of supporting people with NDs using pure mixed reality.

Automating risk of bias assessment in systematic reviews: a real-time mixed methods comparison of human researchers to a machine learning system.

BackgroundMachine learning and automation are increasingly used to make the evidence synthesis process faster and more responsive to policymakers’ needs. In systematic reviews of randomized controlled trials (RCTs), risk of bias assessment is a resource-intensive task that typically requires two trained reviewers. One function of RobotReviewer, an off-the-shelf machine learning system, is an automated risk of bias assessment.MethodsWe assessed the feasibility of adopting RobotReviewer within a national public health institute using a randomized, real-time, user-centered study. The study included 26 RCTs and six reviewers from two projects examining health and social interventions. We randomized these studies to one of two RobotReviewer platforms. We operationalized feasibility as accuracy, time use, and reviewer acceptability. We measured accuracy by the number of corrections made by human reviewers (either to automated assessments or another human reviewer’s assessments). We explored acceptability through group discussions and individual email responses after presenting the quantitative results.ResultsReviewers were equally likely to accept judgment by RobotReviewer as each other’s judgement during the consensus process when measured dichotomously; risk ratio 1.02 (95% CI 0.92 to 1.13; p = 0.33). We were not able to compare time use. The acceptability of the program by researchers was mixed. Less experienced reviewers were generally more positive, and they saw more benefits and were able to use the tool more flexibly. Reviewers positioned human input and human-to-human interaction as superior to even a semi-automation of this process.ConclusionDespite being presented with evidence of RobotReviewer’s equal performance to humans, participating reviewers were not interested in modifying standard procedures to include automation. If further studies confirm equal accuracy and reduced time compared to manual practices, we suggest that the benefits of RobotReviewer may support its future implementation as one of two assessors, despite reviewer ambivalence. Future research should study barriers to adopting automated tools and how highly educated and experienced researchers can adapt to a job market that is increasingly challenged by new technologies.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12874-022-01649-y.

Physiological instruments meet mixed methods in Media Accessibility

Abstract Mixed methods have an established trajectory in the social sciences. Audiovisual Translation and Media Accessibility (MA) Studies are also increasingly applying the “third research paradigm” (Johnson et al., 2007, 112). Yet, publications in our field often fail to discuss the mixed-method nature of the study in depth, be it because of space limitations or a lack of deliberate integration of the methods. Concurrently, MA has seen a boom in experimental research, as descriptive approaches have given way to reception and user-centred studies that engage in the cognitive processes and immersion of audiences (Orero et al. 2018). This article proposes a methodological basis for MA researchers to design studies employing physiological instruments within a mixed methods framework. The core mixed methods designs (convergent, explanatory, and exploratory) are presented, and examples of their applications to research employing physiological instruments are discussed.

The explainability paradox: Challenges for xAI in digital pathology

The increasing prevalence of digitised workflows in diagnostic pathology opens the door to life-saving applications of artificial intelligence (AI). Explainability is identified as a critical component for the safety, approval and acceptance of AI systems for clinical use. Despite the cross-disciplinary challenge of building explainable AI (xAI), very few application- and user-centric studies in this domain have been carried out. We conducted the first mixed-methods study of user interaction with samples of state-of-the-art AI explainability techniques for digital pathology. This study reveals challenging dilemmas faced by developers of xAI solutions for medicine and proposes empirically-backed principles for their safer and more effective design.

Why Do Software Developers Use Static Analysis Tools? A User-Centered Study of Developer Needs and Motivations

As increasingly complex software is developed every day, a growing number of companies use static analysis tools to reason about program properties ranging from simple coding style rules to more advanced software bugs, to multi-tier security vulnerabilities. While increasingly complex analyses are created, developer support must also be updated to ensure that the tools are used to their best potential. Past research in the usability of static analysis tools has primarily focused on usability issues encountered by software developers, and the causes of those issues in analysis tools. In this article, we adopt a more user-centered approach, and aim at understanding why software developers use analysis tools, which decisions they make when using those tools, what they look for when making those decisions, and the motivation behind their strategies. This approach allows us to derive new tool requirements that closely support software developers (e.g., systems for recommending warnings to fix that take developer knowledge into account), and also open novel avenues for further static-analysis research such as collaborative user interfaces for analysis warnings.

Development of an Online Resource for People Bereaved by Suicide: A Mixed-Method User-Centered Study Protocol.

Introduction: Suicide bereavement is known to be highly distressing and is frequently associated with mental health problems. Despite high-level of need regarding mental and physical health, people bereaved by suicide display low level of help-seeking and perceived support in the aftermath of the loss. The lack of accessibility and reliability of face-to-face counseling resources is notably reported by suicide survivors. Online resources can enhance early access to help and support for people bereaved by suicide. The primary objective of the study is to design and implement an innovative and adaptive online resource for people bereaved by suicide according to their needs and expectation regarding online solutions dedicated to suicide bereavement.Methods: The ESPOIR2S study is a mixed-method user-centered study. ESPOIR2S seeks to build the resource from the perspectives and needs of both people bereaved by suicide and professionals or volunteers working in the field of postvention. The Information System Research (ISR) Framework is used to guide the design of the study through a 3-step research cycle. The structure of the ESPOIR2S study relies on a simultaneous collection of qualitative and quantitative data which will be collected and analyzed during (a) the Relevance cycle through an online questionnaire and focus groups; (b) the Design cycle through focus groups; and (c) and the Rigor cycle through an online questionnaire and semi-structured interviews. The user-centeredness will be ensured by the active participation of people bereaved by suicide, members of associations for bereaved people and professionals of postvention.Discussion: The mixed-method and user-centered design of the ESPOIR2S study will offer an in-depth collection of the needs and expectation of suicide survivors regarding online resources. Through the implementation of an adaptive online solution, we aim to enhance the access to help and support for suicide survivors which are highly correlated with well-being and recovery.

Developing an mHealth Application to Coordinate Nurse-Provided Respite Care Services for Families Coping With Palliative-Stage Cancer: Protocol for a User-Centered Design Study.

BackgroundPatients living with palliative-stage cancer frequently require intensive care from their family caregivers. Without adequate community support services, patients are at risk of receiving inadequate care, and family caregivers are at risk for depression and poor health. For such families, in-home respite care can be invaluable, particularly when the services are flexible and staffed by trusted care providers, such as nurses. Other industries are using mobile apps to make services more flexible. However, few apps have been developed to coordinate nurse-provided respite care services, and to our knowledge, none have been designed in conjunction with families affected by cancer.ObjectiveThe aim of this study is to develop a mobile health (mHealth) app prototype for coordinating flexible and trusted in-home respite care services provided by nurses to families coping with palliative-stage cancer in Québec, Canada.MethodsThis user-centered design research comprises the core component of the iRespite Services iRépit research program. For this study, we are recruiting 20 nurses, 15 adults with palliative-stage cancer, and 20 of their family caregivers, from two palliative oncology hospital departments and one palliative home-care community partner. Overseen by an Expert Council, remote data collection will occur over three research phases guided by the iterative Information Systems Research Framework: Phase 1, brainstorming potential app solutions to challenging respite care scenarios, for better supporting the respite needs of both family caregivers and care recipients; Phase 2, evaluating low-fidelity proofs of concept for potential app designs; and Phase 3, usability testing of a high-fidelity interactive proof of concept that will then be programmed into an app prototype. Qualitative and quantitative data will be descriptively analyzed within each phase and triangulated to refine the app features.ResultsWe anticipate that preliminary results will be available by Spring 2022.ConclusionsAn app prototype will be developed that has sufficient complimentary evidence to support future pilot testing in the community. Such an app could improve the delivery of community respite care services provided to families with palliative-stage cancer in Québec, supporting death at home, which is where most patients and their families wish to be.International Registered Report Identifier (IRRID)PRR1-10.2196/34652

Towards the integration of personal task-lighting in an optimised balance between electric lighting and daylighting: A user-centred study of emotion, visual comfort, interaction and form-factor of task lights

Task-lighting is a well-known strategy to save energy by bringing light where it is most needed, providing adaptable localised light conditions of special interest in the current home-office context. Despite these benefits and in addition to negatively impacting biological rhythms, the generalization of backlit screens has made task lights less demanded, with screen users tending to accept significantly lower amounts of the illuminance standards. In parallel, the advantages of task-lighting may contradict the energy benefits of presence-driven lighting or blinds automation. This pilot experiment aims at evaluating the task light usage patterns and characteristic preferences for both paper and computer work from a user-centered perspective to provide guidelines in terms of luminaires characteristics. Thirteen participants evaluated three different task lights in both paper and computer conditions. Our results emphasize the role of the luminaire’s form factor, interface and lighting control characteristics, providing general recommendations on luminaire design.

Differences in information accessed in a pharmacologic knowledge base using a conversational agent vs traditional search methods

IntroductionClinicians rely on pharmacologic knowledge bases to answer medication questions and avoid potential adverse drug events. In late 2018, an artificial intelligence-based conversational agent, Watson Assistant (WA), was made available to online subscribers to the pharmacologic knowledge base, Micromedex®. WA allows users to ask medication-related questions in natural language. This study evaluated search method-dependent differences in the frequency of information accessed by traditional methods (keyword search and heading navigation) vs conversational agent search. Materials and methodsWe compared the proportion of information types accessed through the conversational agent to the proportion of analogous information types accessed by traditional methods during the first 6 months of 2020. ResultsAddition of the conversational agent allowed early adopters to access 22 different information types contained in the ‘quick answers’ portion of the knowledge base. These information types were accessed 117,550 times with WA during the study period, compared to 33,649,651 times using traditional search methods. The distribution across information types differed by method employed (c2 test, P < .0001). Single drug/dosing, FDA/non-FDA uses, adverse effects, and drug administration emerged as 4 of the top 5 information types accessed by either method. Intravenous compatibility was accessed more frequently using the conversational agent (7.7% vs. 0.6% for traditional methods), whereas dose adjustments were accessed more frequently via traditional methods (4.8% vs. 1.4% for WA). ConclusionIn a widely used pharmacologic knowledge base, information accessed through conversational agents versus traditional methods differed. User-centered studies are needed to understand these differences.