Target User Population Research Articles

Applying human-centered design to the construction of a cirrhosis management clinical decision support system.

Electronic health record (EHR)-based clinical decision support is a scalable way to help standardize clinical care. Clinical decision support systems have not been extensively investigated in cirrhosis management. Human-centered design (HCD) is an approach that engages with potential users in intervention development. In this study, we applied HCD to design the features and interface for a clinical decision support system for cirrhosis management, called CirrhosisRx. We conducted technical feasibility assessments to construct a visual blueprint that outlines the basic features of the interface. We then convened collaborative-design workshops with generalist and specialist clinicians. We elicited current workflows for cirrhosis management, assessed gaps in existing EHR systems, evaluated potential features, and refined the design prototype for CirrhosisRx. At the conclusion of each workshop, we analyzed recordings and transcripts. Workshop feedback showed that the aggregation of relevant clinical data into 6 cirrhosis decompensation domains (defined as common inpatient clinical scenarios) was the most important feature. Automatic inference of clinical events from EHR data, such as gastrointestinal bleeding from hemoglobin changes, was not accepted due to accuracy concerns. Visualizations for risk stratification scores were deemed not necessary. Lastly, the HCD co-design workshops allowed us to identify the target user population (generalists). This is one of the first applications of HCD to design the features and interface for an electronic intervention for cirrhosis management. The HCD process altered features, modified the design interface, and likely improved CirrhosisRx's overall usability. The finalized design for CirrhosisRx proceeded to development and production and will be tested for effectiveness in a pragmatic randomized controlled trial. This work provides a model for the creation of other EHR-based interventions in hepatology care.

Effects of User-Reported Risk Factors and Follow-Up Care Activities on Satisfaction With a COVID-19 Chatbot: Cross-Sectional Study.

The COVID-19 pandemic influenced many to consider methods to reduce human contact and ease the burden placed on health care workers. Conversational agents or chatbots are a set of technologies that may aid with these challenges. They may provide useful interactions for users, potentially reducing the health care worker burden while increasing user satisfaction. Research aims to understand these potential impacts of chatbots and conversational recommender systems and their associated design features. The objective of this study was to evaluate user perceptions of the helpfulness of an artificial intelligence chatbot that was offered free to the public in response to COVID-19. The chatbot engaged patients and provided educational information and the opportunity to report symptoms, understand personal risks, and receive referrals for care. A cross-sectional study design was used to analyze 82,222 chats collected from patients in South Carolina seeking services from the Prisma Health system. Chi-square tests and multinomial logistic regression analyses were conducted to assess the relationship between reported risk factors and perceived chat helpfulness using chats started between April 24, 2020, and April 21, 2022. A total of 82,222 chat series were started with at least one question or response on record; 53,805 symptom checker questions with at least one COVID-19-related activity series were completed, with 5191 individuals clicking further to receive a virtual video visit and 2215 clicking further to make an appointment with a local physician. Patients who were aged >65 years (P<.001), reported comorbidities (P<.001), had been in contact with a person with COVID-19 in the last 14 days (P<.001), and responded to symptom checker questions that placed them at a higher risk of COVID-19 (P<.001) were 1.8 times more likely to report the chat as helpful than those who reported lower risk factors. Users who engaged with the chatbot to conduct a series of activities were more likely to find the chat helpful (P<.001), including seeking COVID-19 information (3.97-4.07 times), in-person appointments (2.46-1.99 times), telehealth appointments with a nearby provider (2.48-1.9 times), or vaccination (2.9-3.85 times) compared with those who did not perform any of these activities. Chatbots that are designed to target high-risk user groups and provide relevant actionable items may be perceived as a helpful approach to early contact with the health system for assessing communicable disease symptoms and follow-up care options at home before virtual or in-person contact with health care providers. The results identified and validated significant design factors for conversational recommender systems, including triangulating a high-risk target user population and providing relevant actionable items for users to choose from as part of user engagement.

Integrating Usability Assessments into Medical Device Evaluations

ECRI, a non-profit dedicated to advancing effective, evidence-based healthcare globally, has been evaluating medical devices for over a half century. Project officers develop evaluation criteria and then perform laboratory tests to assess device performance, safety, and reliability. To help incorporate usability assessments into ECRI’s evaluations, a human factors consultant provided guidance on selecting assessment technique(s) based upon the type of device being evaluated, the nature of the environment in which it is used (e.g. operating room, intensive care patient area, nursing station), the target user population, and the resources available to support the evaluation. The consultant also developed a decision-tree to help ECRI project officers select among seven freely-available standardized usability questionnaires.

A comparison of approaches to reweighting anthropometric data

The objective of this work is to identify the most effective techniques for reweighting anthropometric data such that it accurately represents a target user population. Seven methods are compared, including uniform weighting, stratification and permutations of nearest neighbour (NN) reweighting. The analysis illuminates the performance of existing and novel approaches to reweighting data specifically for approximating body size and shape (‘anthropometry’). While uniform weighting and stratified sampling are often used in this field, the present analysis indicates that lower-order NN approaches will produce more representative results. Although anthropometric data are crucial to the design of artefacts, tasks and environments, finding appropriate representative data is challenging. Designers and ergonomists are unlikely to find data that are simultaneously accessible, up-to-date, detailed and from the relevant population. The application of new statistical weights – reweighting – is one useful strategy for meeting this shortfall. This research indicates the best methods for reweighting and provides guidance for sampling strategies in future data collection efforts. Practitioner Summary: Reweighting anthropometric data is one strategy for matching available data to a target user population. Stratified sampling is often used as the method for calculating weights, but it has been shown to produce inaccurate estimates. This research examines seven strategies and finds low-order NN approaches are the more accurate methods.

Design and development of an ergonomic neonatal surgical table

In many regions, neonatal surgical procedures are conducted on adult-sized tables because neonatal surgical tables are rare. The objective of this study was to design and develop an ergonomic neonatal surgical table to help neonatal and infant surgeons avoid musculoskeletal disorders and improve effectiveness with neonatal surgeries. AutoCAD design software was used for the design in addition to other production engineering procedures like material selection and acquisition, cutting, welding, and drilling. The design utilised the anthropometric measures of a target user population. The device consists of a table surface, a surface adjustment lever, a linear actuator, and the foot pedal for adjusting table height and was observed to be ergonomically appropriate for the surveyed demographic. The adjustability of the table height, which is an important feature of the design, is also expected to permit a wide range of users who may not have been part of the study. The result of this study has the potential of creating a safer work environment for surgeons who attend to neonates, as well as supporting future studies on the ergonomics of neonatal surgeries.

Cognitive Relevance Transform for Population Re-Targeting.

This work examines the differences between a human and a machine in object recognition tasks. The machine is useful as much as the output classification labels are correct and match the dataset-provided labels. However, very often a discrepancy occurs because the dataset label is different than the one expected by a human. To correct this, the concept of the target user population is introduced. The paper presents a complete methodology for either adapting the output of a pre-trained, state-of-the-art object classification algorithm to the target population or inferring a proper, user-friendly categorization from the target population. The process is called ‘user population re-targeting’. The methodology includes a set of specially designed population tests, which provide crucial data about the categorization that the target population prefers. The transformation between the dataset-bound categorization and the new, population-specific categorization is called the ‘Cognitive Relevance Transform’. The results of the experiments on the well-known datasets have shown that the target population preferred such a transformed categorization by a large margin, that the performance of human observers is probably better than previously thought, and that the outcome of re-targeting may be difficult to predict without actual tests on the target population.

A Mobile Health Approach for Improving Outcomes in Suicide Prevention (SafePlan)

BackgroundSuicide is a prominent cause of death worldwide, particularly among young people. It was the second leading cause of death among those aged 15-29 years globally in 2016. Treatment for patients with suicidal thoughts or behaviors often includes face-to-face psychological therapy with a mental health professional. These forms of interventions may involve maintaining and updating paper-based reports or worksheets in between sessions. Mobile technology can offer a way to support the implementation of evidence-based psychological techniques and the acquisition of protective coping skills.ObjectiveThis study aims to develop a mobile app to facilitate service users’ access to mental health support and safety planning. This process involved eliciting expert input from clinicians who are actively engaged in the provision of mental health care.MethodsA survey was distributed to targeted health care professionals to determine what features should be prioritized in a new mobile app relating to suicide prevention. On the basis of the survey results, a clinical design group, comprising 6 members with experience in fields such as mobile health (mHealth), clinical psychology, and suicide prevention, was established. This group was supplemented with further input from additional clinicians who provided feedback over three focus group sessions. The sessions were centered on refining existing app components and evaluating new feature requests. This process was iterated through regular feedback until agreement was reached on the overall app design and functionality.ResultsA fully functional mobile app, known as the SafePlan app, was developed and tested with the input of clinicians through an iterative design process. The app’s core function is to provide an interactive safety plan to support users with suicidal thoughts or behaviors as an adjunct to face-to-face therapy. A diary component that facilitates the generalization of skills learned through dialectical behavior therapy was also implemented. Usability testing was carried out on the final prototype by students from a local secondary school, who are representative of the target user population in both age and technology experience. The students were asked to complete a system usability survey (SUS) at the end of this session. The mean overall SUS rating was 71.85 (SD 1.38).ConclusionsThe participatory process involving key stakeholders (clinicians, psychologists, and information technology specialists) has resulted in the creation of an mHealth intervention technology that has the potential to increase accessibility to this type of mental health service for the target population. The app has gone through the initial testing phase, and the relevant recommendations have been implemented, and it is now ready for trialing with both clinicians and their patients.

The Meaning of Sleep Quality: A Survey of Available Technologies

Sleep is an important part of the human daily routine. Restoring sleep is strongly related to a better physical, cognitive, and psychological well-being. By contrast, poor or disordered sleep leads to possible impairments of cognitive and psychological functioning and to a worsened general physical health. In this context, understanding changes in sleep quality becomes a research imperative that leads to the need for the definition of what restoring or quality sleep means. This understanding of what “sleep quality” means requires a cross-domain investigation. It arises the need for a comprehensive study that offers a complete taxonomy of sleep monitoring systems, with a focus on sleep quality, and that gives useful insights about which combination of metrics, signals, and sleep variables is the best in relation to different categories of users. The proposed study is focused on systematically categorizing the methods and approaches for sleep quality understanding, with an emphasis on technological approaches, including wearable, on-bed, and actigraphy devices. It offers a systematic review for researchers who are interested in sleep quality identification tasks, and highlights strengths and weaknesses of state-of-the-art metrics and solutions in order to suggest the best choice for new potential research challenges in the field. Another important outcome of the proposed work is the study of the impact on the identified signal metrics and solutions of the different target user populations with their specific user requirements.

VirtualGym: A kinect-based system for seniors exercising at home

Serious games are games with a purpose beyond entertainment, and the sub-category of serious games conceived to motivate physical activity are called “exergames.” To date, numerous exergames have been developed to motivate users to exercise regularly and correctly. This objective becomes more challenging when the target user population involves older adults, in which case the specific exercise routine and intuitive interaction are of critical importance. Personalized exercise routines can be an effective means for remaining healthy; however, specifying exercise sessions for an individual user is a complex and effort-intensive task that requires multiple types of expertise.In this paper, we describe our system that supports exercise experts in specify an exercise routine for older adults and generates an exergame in which a coach avatar fluidly guides seniors through a personalized version of this routine. During the exercise session, the Kinect™ sensor collects data to evaluate the players performance and provide timely feedback. We developed the user interface of the exercise platform, VirtualGym, through an evolutionary process in the context of an empirical feasibility study with ten older adults. Based on the feedback we received from our target users, the original system interface underwent a sequence of changes and we have distilled our experience into a set of practical guidelines, relevant to the design of Kinect™-based exergames for older adults.

Reweighting anthropometric data using a nearest neighbour approach

When designing products and environments, detailed data on body size and shape are seldom available for the specific user population. One way to mitigate this issue is to reweight available data such that they provide an accurate estimate of the target population of interest. This is done by assigning a statistical weight to each individual in the reference data, increasing or decreasing their influence on statistical models of the whole. This paper presents a new approach to reweighting these data. Instead of stratified sampling, the proposed method uses a clustering algorithm to identify relationships between the detailed and reference populations using their height, mass, and body mass index (BMI). The newly weighted data are shown to provide more accurate estimates than traditional approaches. The improved accuracy that accompanies this method provides designers with an alternative to data synthesis techniques as they seek appropriate data to guide their design practice.Practitioner Summary: Design practice is best guided by data on body size and shape that accurately represents the target user population. This research presents an alternative to data synthesis (e.g. regression or proportionality constants) for adapting data from one population for use in modelling another.

BendSketch

Sketch-based modeling provides a powerful paradigm for geometric modeling. Recent research had shown, sketch based modeling methods are most effective when targeting a specific family of surfaces. A large and growing arsenal of sketching tools is available for different types of geometries and different target user populations. Our work augments this arsenal with a new and powerful tool for modeling complex freeform shapes by sketching sparse 2D strokes; our method complements existing approaches in enabling the generation of surfaces with complex curvature patterns that are challenging to produce with existing methods. To model a desired surface patch with our technique, the user sketches the patch boundary as well as a small number of strokes representing the major bending directions of the shape. Our method uses this input to generate a curvature field that conforms to the user strokes and then uses this field to derive a freeform surface with the desired curvature pattern. To infer the surface from the strokes we first disambiguate the convex versus concave bending directions indicated by the strokes and estimate the surface bending magnitude along the strokes. We subsequently construct a curvature field based on these estimates, using a non-orthogonal 4-direction field coupled with a scalar magnitude field, and finally construct a surface whose curvature pattern reflects this field through an iterative sequence of simple linear optimizations. Our framework is well suited for single-view modeling, but also supports multi-view interaction, necessary to model complex shapes portions of which can be occluded in many views. It effectively combines multi-view inputs to obtain a coherent 3D shape. It runs at interactive speed allowing for immediate user feedback. We demonstrate the effectiveness of the proposed method through a large collection of complex examples created by both artists and amateurs. Our framework provides a useful complement to the existing sketch-based modeling methods.

Different underlying motivations and abilities predict student versus teacher persistence in an online course

Free online courses, including Massively Open Online Courses, have great potential to increase the inclusiveness of education, but suffer from very high course dropout rates. A study of 172 K-12 students and 114 K-12 teachers taking the same free, online, summertime programming course finds that student and teacher populations have different underlying motivational models that predict rates of persistence in the course despite having generally similar motivational levels. Student persistence is predicted by prior programming knowledge, intrinsic interest in the subject matter, and mastery approach goals. By contrast, teacher persistence is similarly predicted by intrinsic interest, but then also by self-identity as a programmer, performance approach goals, and negatively by performance avoidance goals. This sub-population discrepancy in predictive factors is novel, and may be reflective of differing environmental conditions or internal mechanisms between students and teachers. Future design of free choice learning environments can take these factors into account to increase rates of user persistence for different target user populations.

A qualitative investigation of users’ discovery, access, and organization of video games as information objects

Video games are popular consumer products as well as research subjects, yet little exists about how players and other stakeholders find video games and what information they need to select, acquire and play video games. With the aim of better understanding people’s game-related information needs and behaviour, we conducted 56 semi-structured interviews with users who find, play, purchase, collect and recommend video games. Participants included gamers, parents, collectors, industry professionals, librarians, educators and scholars. From this user data, we derive and discuss key design implications for video game information systems: designing for target user populations, enabling recommendations based on appeals, offering multiple automatic organization options and providing relationship-based, user-generated, subject and visual metadata. We anticipate this work will contribute to building future video game information systems with new and improved access to games.

The person-based approach to intervention development: application to digital health-related behavior change interventions.

This paper describes an approach that we have evolved for developing successful digital interventions to help people manage their health or illness. We refer to this as the “person-based” approach to highlight the focus on understanding and accommodating the perspectives of the people who will use the intervention. While all intervention designers seek to elicit and incorporate the views of target users in a variety of ways, the person-based approach offers a distinctive and systematic means of addressing the user experience of intended behavior change techniques in particular and can enhance the use of theory-based and evidence-based approaches to intervention development. There are two key elements to the person-based approach. The first is a developmental process involving qualitative research with a wide range of people from the target user populations, carried out at every stage of intervention development, from planning to feasibility testing and implementation. This process goes beyond assessing acceptability, usability, and satisfaction, allowing the intervention designers to build a deep understanding of the psychosocial context of users and their views of the behavioral elements of the intervention. Insights from this process can be used to anticipate and interpret intervention usage and outcomes, and most importantly to modify the intervention to make it more persuasive, feasible, and relevant to users. The second element of the person-based approach is to identify “guiding principles” that can inspire and inform the intervention development by highlighting the distinctive ways that the intervention will address key context-specific behavioral issues. This paper describes how to implement the person-based approach, illustrating the process with examples of the insights gained from our experience of carrying out over a thousand interviews with users, while developing public health and illness management interventions that have proven effective in trials involving tens of thousands of users.

A Tool for Managing Library Information System Resources: Software Measurement Across Local Area Networks (SMALAN)

From the 1994 CAIS Conference: The Information Industry in Transition McGill University, Montreal, Quebec. May 25 - 27, 1994.The increased use of CD-ROM databases in academic libraries comes at a time when dwindling budgets have put pressure on university libraries to justify all expenditures, and particularly the large expenditures associated with these databases. This has hastened the need for better management information about network use of these databases to substantiate hardware and software requirements, remote access desirability, technical support needs, and to reduce their associated costs. This paper examines research being conducted at McGill University to develop a software tool to measure CD-ROM use across a multiple segment local area network with a target user population in excess of 2,000 students and faculty members. The rationale for the project is discussed, details are provided about programming considerations, and examples are given of how the information can be used.

Considering just noticeable difference in assessments of physical accommodation for product design

Configuring products or environments for the size of their human users requires the consideration of several characteristics of the target user population, including body dimensions (anthropometry) and preferred interaction. Users are both adaptable and imperfect observers, which often makes it difficult for them to distinguish between candidate designs. This insensitivity is described by a concept called ‘just noticeable difference’, or JND. This paper presents an implementation of JND modelling and demonstrates how its use in the sizing of products or environments for target user populations can improve expected performance. Two facets of this problem are explored: (1) how experimental measures of JND for dimensional optimisation tasks may be obtained, and (2) how measures of JND may be included in models of user–device interaction for both adjustable and discretely sized products and the assumptions required. A case study demonstrating the collection and modelling of JND for a simple univariate problem is also presented.Practitioner Summary: Since people are adaptable and imperfect observers, there exists a ‘just noticeable difference’ that can be considered when designing products and environments. When JND is modelled for a target population, less variability in design dimensions due to physical user requirements may be necessary. This paper considers JND in quantitative simulations of population accommodation.

Integrating computer-aided modeling and micro-simulation in multi-criteria evaluation of service infrastructure assignment approaches

Purpose: This paper proposes an integrated computer-supported multi-staged approach to the flexible design and multicriteria evaluation of service infrastructure assignment processes/ algorithms. Design/methodology/approach: It involves particularizing a metamodel encompassing the main generic components and relationships into process models and process instances, by incorporating structural data from the real-life system. Existing data on the target user population is fed into a micro-modeling system to generate a matching population of individual “virtual” users, each with its own set of trait values. The micro-simulation of their interaction with the assignment process of both the incumbent and the competitors generates a rich multi-dimensional output, encompassing both “revealed” and non-observable data. This enables a comprehensive multi-criteria evaluation of the foreseeable performance of the designed process/ algorithm, and therefore its iterative improvement. Findings: The research project developed a set of methodologies and associated supporting tools encompassing the modeling, micro-simulation and performance assessment of service infrastructure assignment processes. Originality/value: The proposed approach facilitates, in a multicriteria environment, the flexible modeling/design of situation-specific assignment processes/algorithms and their performance assessment when facing their case-specific user population.

Defining Thumb Reach Envelopes for Handheld Devices

Our objective is to provide thumb reach envelopes to help guide the placement of controls on handheld devices and to provide useful methods to gather and analyze thumb reach data. With the proliferation of handheld, interactive devices, such as cameras, mobile phones, game systems, and remote controls, human factors professionals involved in designing these products need data to help guide the placement of controls. Previous studies have not provided adequate two-dimensional thumb reach envelopes for the primary control surfaces of handheld devices. A total of 90 participants in three groups (adolescent females, young mothers, and young fathers) placed representations of primary controls in preferred locations on a device model and "painted" their individual reach envelopes on a touch-screen device running a paint application. We present two-dimensional thumb reach envelopes on the primary control surface for handheld devices. The primary reach zone for adolescent females is slightly larger and more circular than that of the adults. The preferred location for controls matches the primary thumb reach zones fairly well. The reach envelopes presented are the first of their kind and are likely to be useful to human factors professionals. The method used to obtain the data may also be useful. The thumb reach envelopes should be applicable to the design of many handheld, interactive devices with dimensions similar to the models used in this study. The method presented allows design teams to collect and analyze thumb reach data quickly and inexpensively for different target user populations or product dimensions.

Display configurations in a small footprint clinical driving simulator

Particularly in the health and rehabilitation sector where cost and space are constraints, clinicians need smaller driving simulators. Because of the limited projected field of view (PFOV) afforded by these displays, it was desirable to extend the virtual or geometric field of view (GFOV) beyond that natively afforded by the PFOV. In Study 1, user feedback was gathered from our target user population on two display configurations: (1) a single large LCD; and (2) three smaller LCD screens. Participants were also exposed to four GFOV settings (65°, 80°, 95°, 110°) using either display. The majority of participants preferred and were most comfortable with the three-screen configuration with the highest GFOV setting tested (110°). In order for driving simulation to produce realistic experiences, drivers’ perception of speed should correspond with real world experiences. However, changing the PFOV/GFOV ratio has been shown to alter perceived speed. Therefore, the purpose of Study 2 was to better understand the relationship between speed perception and the GFOV/PFOV ratio in a way that would be useful to simulation practitioners using a small-footprint driving simulator. Using the DriveSafety CDS-250, participants performed a speed matching task using six different GFOV conditions while the PFOV was held constant. Target speeds were presented in three appropriate simulated environments: 25mph in a residential area, 45mph in a commercial area, and 65mph on a freeway. In general, perceived speed was found to decrease with larger GFOVs. However, no GFOV tested produced accurate speed perception; on average, all participants underestimated their speeds using all GFOVs.

Understanding age and technology experience differences in use of prior knowledge for everyday technology interactions

Technology designers must understand relevant prior knowledge in a target user population to facilitate adoption and effective use. To assess prior knowledge used in naturalistic settings, we systematically collected information about technologies used over 10-day periods from older adults with high and low technology experience and younger adults. Technology repertoires for younger adults and high technology older adults were similar; differences reflected typically different needs for kitchen and health care technologies between the age groups. Technology repertoires for low-technology older adults showed substantial technology usage in many categories. Lower usage compared to high-tech older adults for each category was limited primarily to PC and Internet technologies. Experience differences suggest preferences among low-technology older adults for basic technology usage and for working with people rather than technologies. Participants in all groups were generally successful using their everyday technologies to achieve their goals. Prior knowledge was the most common attribution for success, but external information was also commonly referenced. Relevant prior knowledge included technical, functional, strategy, and self knowledge. High tech older adults did not report more problems than younger adults, but they did attribute more problems to insufficient prior knowledge. Younger adults attributed more problems to interference from prior knowledge. Low-tech older adults reported fewer problems, typically attributing them to insufficient prior knowledge or product/system faults. We discuss implications for further research and design improvements to increase everyday technology success and adoption for high-tech and low-tech older adults.