The aim of the study reported here was to reflect and report on lessons learned from adapting HCI methods to fit into an agile development process delivering a digital intervention for people managing Long Covid. During the project, we maintained a record of all activities and interim design products. Subsequently, selected records were analysed qualitatively. Challenges included engaging patients managing this complex, debilitating health condition and fitting the digital intervention into different and evolving patient pathways provided by clinics. The key contributions of this paper are a description of the clinically supported self-management app, Living With Covid Recovery, and of adapted methods for user-centred design and testing; narratives on engaging diverse clinics integrating a digital health intervention in their care pathways; reflections on designing for diverse users; implications for design of future technologies for supported self-management; and insights into multidisciplinary working that are rarely discussed within HCI.

Obtaining feedback from time-constrained end-users is a major challenge in evaluating novel systems for specialised applications. The performance and feedback of engineers and surgeons was evaluated through an experiment where participants were asked to identify tumour locations within an anatomically realistic silicon liver model across three different conditions of an Augmented Reality (AR) prototype system (Baseline, Split AR and Full AR). Our findings show that engineers and surgeons share some similarities in their performance, feedback and behaviour, particularly when reliance on the AR system is high for both groups. However, engineers typically focus more on accuracy of the image alignment and are more accurate in their responses when supported by AR. Senior surgeons typically perform faster and use AR as supplementary information, while the performance of junior surgeons is more closely aligned to the performance of engineers. We conclude that engineers could be involved in preliminary evaluations of a surgical system or in evaluations of systems which are aimed at training junior surgeons, but that it is essential to involve surgeons in later evaluations, where ecological validity is a more important consideration.

Augmented Reality (AR) is considered to be a promising technology for the guidance of laparoscopic liver surgery. By overlaying pre-operative 3D information of the liver and internal blood vessels on the laparoscopic view, surgeons can better understand the location of critical structures. In an effort to enable AR, several authors have focused on the development of methods to obtain an accurate alignment between the laparoscopic video image and the pre-operative 3D data of the liver, without assessing the benefit that the resulting overlay can provide during surgery. In this paper, we present a study that aims to assess quantitatively and qualitatively the value of an AR overlay in laparoscopic surgery during a simulated surgical task on a phantom setup. We design a study where participants are asked to physically localise pre-operative tumours in a liver phantom using three image guidance conditions - a baseline condition without any image guidance, a condition where the 3D surfaces of the liver are aligned to the video and displayed on a black background, and a condition where video see-through AR is displayed on the laparoscopic video. Using data collected from a cohort of 24 participants which include 12 surgeons, we observe that compared to the baseline, AR decreases the median localisation error of surgeons on non-peripheral targets from 25.8 mm to 9.2 mm. Using subjective feedback, we also identify that AR introduces usability improvements in the surgical task and increases the perceived confidence of the users. Between the two tested displays, the majority of participants preferred to use the AR overlay instead of navigated view of the 3D surfaces on a separate screen. We conclude that AR has the potential to improve performance and decision making in laparoscopic surgery, and that improvements in overlay alignment accuracy and depth perception should be pursued in the future.

Bringing AI technology into clinical practice has proved challenging for system designers and medical professionals alike. The academic literature has, for example, highlighted the dangers of black-box decision-making and biased datasets. Furthermore, end-users’ ability to validate a system’s performance often disappears following the introduction of AI decision-making. We present the MAP model to understand and describe the three stages through which medical observations are interpreted and handled by AI systems. These stages are Measurement, in which information is gathered and converted into data points that can be stored and processed; Algorithm, in which computational processes transform the collected data; and Presentation, where information is returned to the user for interpretation. For each stage, we highlight possible challenges that need to be overcome to develop Human-Centred AI systems. We illuminate our MAP model through complementary case studies on colonoscopy practice and dementia diagnosis, providing examples of the challenges encountered in real-world settings. By defining Human-AI interaction across these three stages, we untangle some of the inherent complexities in designing AI technology for clinical decision-making, and aim to overcome misalignment between medical end-users and AI researchers and developers.

The use of artificial intelligence (AI) in clinical support systems is increasing. In this article, we focus on AI support for continuous interaction scenarios. A thorough understanding of end-user behaviour during these continuous human-AI interactions, in which user input is sustained over time and during which AI suggestions can appear at any time, is still missing. We present a controlled lab study involving 21 endoscopists and an AI colonoscopy support system. Using a custom-developed application and an off-the-shelf videogame controller, we record participants’ navigation behaviour and clinical assessment across 14 endoscopic videos. Each video is manually annotated to mimic an AI recommendation, being either true positive or false positive in nature. We find that time between AI recommendation and clinical assessment is significantly longer for incorrect assessments. Further, the type of medical content displayed significantly affects decision time. Finally, we discover that the participant’s clinical role plays a large part in the perception of clinical AI support systems. Our study presents a realistic assessment of the effects of imperfect and continuous AI support in a clinical scenario.

Message deletion in mobile messaging apps allows people to “unsay” things they have said. This paper explores how and why people use (or do not use) this feature within remediation strategies after a communication error is identified. We present findings from a multi-stage survey designed to explore people’s general experiences of the message deletion feature (N = 401), peoples’ experiences of using this feature during the remediation of an error (N = 70), and receivers’ perceptions around recent message deletions (N = 68). While people are typically aware of the deletion feature, it is infrequently used. When used, it is primarily done so to improve conversations by reducing confusion between conversation partners. We found people being aware of message deletions creating information-gaps which can provoke curiosity in recipients, causing them to develop narratives to help address the uncertainty. We found concerns amongst senders that these narratives would be of a negative nature, having an undesirable impact on how others perceive them. We use our findings to suggest ways in which mobile messaging apps could improve conversational experiences around erroneous and regrettable messages.

Clinical decision-support tools (DSTs) represent a valuable resource in healthcare. However, lack of Human Factors considerations and early design research has often limited their successful adoption. To complement previous technically focused work, we studied adoption opportunities of a future DST built on a predictive model of Alzheimer’s Disease (AD) progression. Our aim is two-fold: exploring adoption opportunities for DSTs in AD clinical care, and testing a novel combination of methods to support this process. We focused on understanding current clinical needs and practices, and the potential for such a tool to be integrated into the setting, prior to its development. Our user-centred approach was based on field observations and semi-structured interviews, analysed through workflow analysis, user profiles, and a design-reality gap model. The first two are common practice, whilst the latter provided added value in highlighting specific adoption needs. We identified the likely early adopters of the tool as being both psychiatrists and neurologists based in research-oriented clinical settings. We defined ten key requirements for the translation and adoption of DSTs for AD around IT, user, and contextual factors. Future works can use and build on these requirements to stand a greater chance to get adopted in the clinical setting.

Colonoscopy, the visual inspection of the large bowel using an endoscope, offers protection against colorectal cancer by allowing for the detection and removal of pre-cancerous polyps. The literature on polyp detection shows widely varying miss rates among clinicians, with averages ranging around 22%--27%. While recent work has considered the use of AI support systems for polyp detection, how to visualise and integrate these systems into clinical practice is an open question. In this work, we explore the design of visual markers as used in an AI support system for colonoscopy. Supported by the gastroenterologists in our team, we designed seven unique visual markers and rendered them on real-life patient video footage. Through an online survey targeting relevant clinical staff ( N = 36), we evaluated these designs and obtained initial insights and understanding into the way in which clinical staff envision AI to integrate in their daily work-environment. Our results provide concrete recommendations for the future deployment of AI support systems in continuous, adaptive scenarios.

As people's offline and online lives become increasingly entwined, the sensitivity of personal information disclosed online is increasing. Disclosures often occur through structured disclosure fields (e.g., drop-down lists). Prior research suggests these fields may limit privacy, with non-disclosing users being presumed to be hiding undesirable information. We investigated this around HIV status disclosure in online dating apps used by men who have sex with men. Our online study asked participants (N=183) to rate profiles where HIV status was either disclosed or undisclosed. We tested three designs for displaying undisclosed fields. Visibility of undisclosed fields had a significant effect on the way profiles were rated, and other profile information (e.g., ethnicity) could affect inferences that develop around undisclosed information. Our research highlights complexities around designing for non-disclosure and questions the voluntary nature of these fields. Further work is outlined to ensure disclosure control is appropriately implemented around online sensitive information disclosures.

People diagnosed with a chronic health condition have many information needs which healthcare providers, patient groups, and resource designers seek to support. However, as a disease progresses, knowing when, how, and for what purposes patients want to interact with and construct personal meaning from health-related information is still unclear. This paper presents findings regarding the information work of chronic kidney disease patients. We conducted semi-structured interviews with 13 patients and 6 clinicians, and observations at 9 patient group events. We used the stages of the information journey - recognizing need, seeking, interpreting, and using information - to frame our data analysis. We identified two distinct but often overlapping information work phases, 'Learning' and 'Living With' a chronic condition to show how patient information work activities shift over time. We also describe social and individual factors influencing information work, and discuss technology design opportunities including customized education and collaboration tools.

While digital technologies are increasingly being used to provide support and diagnoses remotely, it is unclear whether they offer adequate emotional support and appropriate messages in navigating complex, stigmatised and sensitive conditions that can have a momentous impact on people's lives. In this paper, we investigate how and why people access existing HIV resources, and their experiences of using these resources through a survey with 197 respondents and an interview and think-aloud study with 28 participants. Our findings indicate that many HIV-related resources do not address the anxiety-provoking reasons for access, reinforce stigma and neglect to provide important information and emotional support. We finally discuss potential ways of addressing these issues in the current environment where more sexual health services are being delivered online.

HIV status disclosure fields in online sex-social applications ("apps") are designed to help increase awareness, reduce stigma, and promote sexual health. Public disclosure could also help those diagnosed relate to others with similar statuses to feel less isolated. However, in our interview study (n=28) with HIV positive and negative men who have sex with men (MSM), we found some users preferred to keep their status private, especially when disclosure could stigmatise and disadvantage them, or risk revealing their status to someone they knew offline in a different context. How do users manage these tensions between health, stigma, and privacy? We analysed our interview data using signalling theory as a conceptual framework and identify participants developing 'signal appropriation' strategies, helping them manage the disclosure of their HIV status. Additionally, we propose a set of design considerations that explore the use of signals in the design of sensitive disclosure fields.

Infertility can place a significant burden on couples and individuals when trying to conceive. Approximately 20-30% of all cases of infertility are due to male-related factors. Whatever the cause of difficulty in conceiving, little is known about how men find support when dealing with fertility issues, or when or how online resources are being used. This paper reports on a qualitative study of anonymous online posts (N=603) from forums related to fertility that are used by men. We analysed this data using thematic analysis to understand how men are using online forums as a resource when experiencing fertility issues. We found that online forums play a valued role in facilitating connections between men experiencing an often stigmatised condition. These forums offer men accessible and private spaces which allow for more open discussion, helping them to make sense of their situation. We discuss our findings in relation to Genuis and Bronstein's model of finding a "new normal" and present our elaborated model of finding a "new normal" in the context of experiencing fertility problems.

mHealth applications ("apps") must be searched for and downloaded prior to use, creating a potential barrier to uptake. Integrating health interventions into existing online social environments removes this barrier. However, little is known about the effects of linking sensitive health information to existing online identities. Our qualitative analysis of online comments (n=192) explores the user views of an HIV intervention integrated into the geosocial hookup app Grindr. We find some HIV positive users report keeping their status private to reduce their stigma exposure, whilst others report publicly disclosing their status to avoid being stigmatised by others. Where users keep their status private, we find concerns that social assumptions may develop around these non-disclosures, creating a privacy unraveling effect which restricts disclosure choice. Using Peppet's four proposed limits to privacy unraveling, we develop a set of descriptive conceptual designs to explore the privacy respecting potential of these limits within this context and propose further research to address this privacy challenge.

People interact with information in a myriad of ways [1]. As well as actively seeking information, people also encounter it, and there have been various efforts to design systems that support encountering and keeping track of encountered information [2,3]. But what people engage with depends: on how it fits with their ongoing activities as well as whether they recognize its potential value [4]. Sometimes, people are open to engaging with information, and may experience information encountering as serendipitous; at other times, a similar encounter might feel like overload or distraction [5]. The design of systems that support effective engagement will ideally take account of people's practices and contexts as well as their interests. Perhaps paradoxically, serendipitous encounters rarely happen by chance: people invest in various ways in increasing the likelihood of valuable information encounters that enable them to keep up-to-date and make creative leaps [6,7]; again, good design can facilitate productive interactions with information [8]. In this talk, I will discuss various qualitative studies of how people fit information encountering into their lives, how they experience serendipity, and some of the ways they invest up-front effort in future information interactions; I will also highlight opportunities to design to support people in making best use of information they find.

Keeping up to date with research developments is a central activity of academic researchers, but researchers face difficulties in managing the rapid growth of available scientific information. This study examined how researchers stay up to date, using the information journey model as a framework for analysis and investigating which dimensions influence information behaviors. We designed a 2‐round study involving semistructured interviews and prototype testing with 61 researchers with 3 levels of seniority (PhD student to professor). Data were analyzed following a semistructured qualitative approach. Five key dimensions that influence information behaviors were identified: level of seniority, information sources, state of the project, level of familiarity, and how well defined the relevant community is. These dimensions are interrelated and their values determine the flow of the information journey. Across all levels of professional expertise, researchers used similar hard (formal) sources to access content, while soft (interpersonal) sources were used to filter information. An important “pain point” that future information tools should address is helping researchers filter information at the point of need.

People are increasingly involved in the self-management of their own health, including chronic conditions. With technology advances, the choice of self-management practices, tools, and technologies has never been greater. The studies reported here investigated the information seeking practices of two different chronic health populations in their quest to manage their health conditions. Migraine and diabetes patients and clinicians in the UK and the US were interviewed about their information needs and practices, and representative online communities were explored to inform a qualitative study. We found that people with either chronic condition require personally relevant information and use a broad and varied set of practices and tools to make sense of their specific symptoms, triggers, and treatments. Participants sought out different types of information from varied sources about themselves, their medical condition, and their peers' experiences of the same chronic condition. People with diabetes and migraine expended great effort to validate their personal experiences of their condition and determine whether these experiences were 'normal'. Based on these findings, we discuss the need for future personal health technologies that support people in engaging in meaningful and personalised data collection, information seeking, and information sharing with peers in flexible ways that enable them to better understand their own condition.

This paper reports findings from a study designed to gain broader understanding of sensemaking activities using the Data/Frame Theory as the analytical framework. Although this theory is one of the dominant models of sensemaking, it has not been extensively tested with a range of sensemaking tasks. The tasks discussed here focused on making sense of structures rather than processes or narratives. Eleven researchers were asked to construct understanding of how a scientific community in a particular domain is organized (e.g., people, relationships, contributions, factors) by exploring the concept of “influence” in academia. This topic was chosen because, although researchers frequently handle this type of task, it is unlikely that they have explicitly sought this type of information. We conducted a think‐aloud study and semistructured interviews with junior and senior researchers from the human–computer interaction (HCI) domain, asking them to identify current leaders and rising stars in both HCI and chemistry. Data were coded and analyzed using the Data/Frame Model to both test and extend the model. Three themes emerged from the analysis: novices and experts' sensemaking activity chains, constructing frames through indicators, and characteristics of structure tasks. We propose extensions to the Data/Frame Model to accommodate structure sensemaking.

An increasing number of tools are being developed to help academics interact with information, but little is known about the benefits of those tools for their users. This study evaluated academics' receptiveness to information proposed by a mobile app, the SerenA Notebook: information that is based in their inferred interests but does not relate directly to a prior recognized need. The evaluated app aimed at creating the experience of serendipitous encounters: generating ideas and inspiring thoughts, and potentially triggering follow‐up actions, by providing users with suggestions related to their work and leisure interests. We studied how 20 academics interacted with messages sent by the mobile app (3 per day over 10 consecutive days). Collected data sets were analyzed using thematic analysis. We found that contextual factors (location, activity, and focus) strongly influenced their responses to messages. Academics described some unsolicited information as interesting but irrelevant when they could not make immediate use of it. They highlighted filtering information as their major struggle rather than finding information. Some messages that were positively received acted as reminders of activities participants were meant to be doing but were postponing, or were relevant to ongoing activities at the time the information was received.

Adults with Type 1 Diabetes have choices regarding the technology they use to self-manage their chronic condition. They can use glucose meters, insulin pumps, smartphone apps, and other technologies to support their everyday care. However, little is known about how their social lives might influence what they adopt or how they use technologies. A multi-method study was conducted to examine contextual factors that influence their technology use. While individual differences play a large role in everyday use, social factors were also found to influence use. For example, people can hide their devices in uncertain social situations or show them off to achieve a purpose. We frame these social behaviours using Goffman's theatre metaphor of onstage and offstage behaviour, and discuss how this kind of analysis can inform the design of future mobile medical devices for self-management of chronic conditions.

Habit formation is an important part of behavior change interventions: to ensure an intervention has long-term effects, the new behavior has to turn into a habit and become automatic. Smartphone apps could help with this process by supporting habit formation. To better understand how, we conducted a 4-week study exploring the influence of different types of cues and positive reinforcement on habit formation and reviewed the functionality of 115 habit formation apps. We discovered that relying on reminders supported repetition but hindered habit development, while the use of event-based cues led to increased automaticity; positive reinforcement was ineffective. The functionality review revealed that existing apps focus on self-tracking and reminders, and do not support event-based cues. We argue that apps, and technology-based interventions in general, have the potential to provide real habit support, and present design guidelines for interventions that could support habit formation through contextual cues and implementation intentions.

The motivation for this study was to better understand academics’ searching and sensemaking processes when solving exploratory tasks for which they lack pre‐existing frames. We focus on “influence” tasks because, although they appear to be unfamiliar, they arise in much academic discourse, at least tacitly. We report the processes of academics at different levels of seniority when completing exploratory search tasks that involved identifying influential members of their academic community and “rising stars,” and similarly for an unfamiliar academic community. 11 think‐aloud sessions followed by semi‐structured interviews were conducted to investigate the roles of specific and general domain expertise in shaping information seeking and knowledge construction. Academics defined and completed the tasks through an iterative and interactive process of seeking and sensemaking, during which they constructed an understanding of their communities and determined qualities of “being influential”. The Data/Frame Theory of Sensemaking was used to provide sensitising theoretical constructs. The study shows that both external and internal knowledge resources are essential to define a starting point or frame, make and support decisions, and experience satisfaction. Ill‐defined or non‐existent initial frames may cause unsubstantial or arbitrary decisions, and feelings of uncertainty and lack of confidence.

As healthcare shifts from the hospital to the home, it is becoming increasingly important to understand how patients interact with home medical devices, to inform the safe and patient-friendly design of these devices. Distributed Cognition (DCog) has been a useful theoretical framework for understanding situated interactions in the healthcare domain. However, it has not previously been applied to study interactions with home medical devices. In this study, DCog was applied to understand renal patients' interactions with Home Hemodialysis Technology (HHT), as an example of a home medical device. Data was gathered through ethnographic observations and interviews with 19 renal patients and interviews with seven professionals. Data was analyzed through the principles summarized in the Distributed Cognition for Teamwork methodology. In this paper we focus on the analysis of system activities, information flows, social structures, physical layouts, and artefacts. By explicitly considering different ways in which cognitive processes are distributed, the DCog approach helped to understand patients' interaction strategies, and pointed to design opportunities that could improve patients' experiences of using HHT. The findings highlight the need to design HHT taking into consideration likely scenarios of use in the home and of the broader home context. A setting such as home hemodialysis has the characteristics of a complex and safety-critical socio-technical system, and a DCog approach effectively helps to understand how safety is achieved or compromised in such a system.

The focus of this paper is on the challenges and opportunities presented by developing scenarios of use for interactive medical devices. Scenarios are integral to the international standard for usability engineering of medical devices (IEC 62366:2007), and are also applied to the development of health software (draft standard IEC 82304-1). The 62366 standard lays out a process for mitigating risk during normal use (i.e. use as per the instructions, or accepted medical practice). However, this begs the question of whether "real use" (that which occurs in practice) matches "normal use". In this paper, we present an overview of the product lifecycle and how it impacts on the type of scenario that can be practically applied. We report on the development and testing of a set of scenarios intended to inform the design of infusion pumps based on "real use". The scenarios were validated by researchers and practitioners experienced in clinical practice, and their utility was assessed by developers and practitioners representing different stages of the product lifecycle. These evaluations highlighted previously unreported challenges and opportunities for the use of scenarios in this context. Challenges include: integrating scenario-based design with usability engineering practice; covering the breadth of uses of infusion devices; and managing contradictory evidence. Opportunities included scenario use beyond design to guide marketing, to inform purchasing and as resources for training staff. This study exemplifies one empirically grounded approach to communicating and negotiating the realities of practice.

In most online citizen science projects, a large proportion of participants contribute in small quantities. To investigate how low contributors differ from committed volunteers, we distributed a survey to members of the Old Weather project, followed by interviews with respondents selected according to a range of contribution levels. The studies reveal a complex relationship between motivations and contribution. Whilst high contributors were deeply engaged by social or competitive features, low contributors described a solitary experience of 'dabbling' in projects for short periods. Since the majority of participants exhibit this small-scale contribution pattern, there is great potential value in designing interfaces to tempt lone workers to complete 'just another page', or to lure early drop-outs back into participation. This includes breaking the work into components which can be tackled without a major commitment of time and effort, and providing feedback on the quality and value of these contributions.

A central challenge in weight management is the difficulty of overcoming desires for excessive and unhealthy food. Yet, studies show that when people are able to resist their desires for unhealthy choices, they experience pride and satisfaction. In order to alleviate the former and support the latter, we designed, implemented and tested a mobile application for improving snacking behavior. Our application delivers a food craving reduction intervention at the moment of need and allows users to track how often they successfully resisted cravings. Our craving reduction intervention is based on recent research that shows that food cravings can be reduced through imagery techniques. We conducted a week-long evaluation of our application, comparing the effectiveness of our application to a basic tracking application. We found that our imagery application significantly reduced both overall snacking and unhealthy snacking compared to a simple snack-tracking application.

In this paper, we report on autoethnography as a method to access non-routine usage of mobile devices, such as during business trips, vacations, etc. Autoethnography, a self-study method with the researcher as participant, was employed for the evaluation of a wrist blood pressure monitor used by people with conditions such as hypertension. The findings from the study were surprising, especially with respect to the environmental and social impact on the use of the technology. Although the autoethnographic method can be disruptive for the researcher, it enables them to understand and empathize with the experiences mobile device users can face in difficult to access contexts. This method allows HCI researchers to better understand user experiences with mobile devices, including mobile medical technology, especially during non-routine times that can be difficult to study in-situ with traditional user studies.

Despite the fact that a third of all cases of unintentional medication non-adherence are caused by simple forgetfulness, the majority of interventions neglect this issue. Even though patients have access to smartphone applications ("apps") designed to help them remember medication, neither their quality nor effectiveness has been evaluated yet. We report the findings of a functionality review of 229 medication reminder apps and a thematic analysis of their 1,012 user reviews. Our research highlights the gap between the theory and practice: while the literature shows that many medication regimens are habitual in nature and the presence of daily routines supports remembering, existing apps rely on timer-based reminders. To address this disparity, we present design requirements for building medication reminders that support the routine aspect of medication-taking and its individual nature, and demonstrate how they could be implemented to move from passive alerts to a smarter memory and routine assistant.

Abstract The design of a human–computer interactive system can be unacceptable for a range of reasons. User performance concerns, for example the likelihood of user errors and time needed for a user to complete tasks, are important areas of consideration. For safety-critical systems it is vital that tools are available to support the analysis of such properties before expensive design commitment has been made. In this work, we give a unified formal verification framework for integrating two kinds of analysis: (1) predicting bounds for task-completion times via exhaustive state-space exploration, and (2) detecting user-error related design issues. The framework is based on a generic model of cognitively plausible behaviour that captures assumptions about cognitive behaviour decided through a process of interdisciplinary negotiation. Assumptions made in an analysis, including those relating to the performance consequences of users recovering from likely errors, are also investigated in this framework. We further present a novel way of exploring the consequences of cognitive mismatches, on both correctness and performance grounds. We illustrate our analysis approach with a realistic medical device scenario: programming an infusion pump. We explore an initial pump design and then two variations based on features found in real designs, illustrating how the approach identifies both timing and human error issues.

Serendipity occurs when unexpected circumstances and an “aha” moment of insight result in a valuable, unanticipated outcome. Designing digital information environments to support serendipity can not only provide users with new knowledge, but also propel them in directions they might not otherwise have traveled in—surprising and delighting them along the way. As serendipity involves unexpected circumstances it cannot be directly controlled, but it can be potentially influenced. However, to the best of our knowledge, no previous work has focused on providing a rich empirical understanding of how it might be influenced. We interviewed 14 creative professionals to identify their self‐reported strategies aimed at increasing the likelihood of serendipity. These strategies form a framework for examining ways existing digital environments support serendipity and for considering how future environments can create opportunities for it. This is a new way of thinking about how to design for serendipity; by supporting the strategies found to increase its likelihood rather than attempting to support serendipity as a discrete phenomenon, digital environments not only have the potential to help users experience serendipity but also encourage them to adopt the strategies necessary to experience it more often.

To understand how healthcare technologies are used in practice and evaluate them, researchers have argued for adopting the theoretical framework of Distributed Cognition (DC). This paper describes the methods and results of a study in which a DC methodology, Distributed Cognition for Teamwork (DiCoT), was applied to study the use of infusion pumps by nurses in an Intensive Care Unit (ICU). Data was gathered through ethnographic observations and interviews. Data analysis consisted of constructing the representational models of DiCoT, focusing on information flows, physical layouts, social structures and artefacts. The findings show that there is significant distribution of cognition in the ICU: socially, among nurses; physically, through the material environment; and through technological artefacts. The DiCoT methodology facilitated the identification of potential improvements that could increase the safety and efficiency of nurses' interactions with infusion technology.

Grounded Theory (GT) is used within HCI research, but nuances and more modern interpretations of the method are rarely discussed. This paper has two intentions: to offer guidance on practical issues when applying GT, and to clarify the space of methodological possibilities. We describe an extended GT study on understanding why practitioners choose particular usability evaluation methods. We describe five stages in this study to highlight our experiences and choices made. We draw out seven practical and methodological considerations in applying GT in a CHI context. This challenges the more traditional inductive and objective positions on GT use; it sensitizes novices of GT to these issues; and through the extended case study it provides substance for debate on issues that affect those that use qualitative methods more broadly.

Sensemaking occurs when people face the problem of forming an understanding of a situation. One scenario in which technology has a particularly significant impact on sensemaking and its success is in legal investigations. Legal investigations extend over time, are resource intensive, and require the sifting and re-representation of large collections of electronic evidence and close collaboration between multiple investigators. In this article, we present an account of sensemaking in three corporate legal investigations. We summarize information interaction processes in the form of a model which conceptualizes processes as resource transformations triggered and shaped by both bottom-up and top-down resources. The model both extends upon and validates aspects of a previous account of investigative sensemaking (Pirolli & Card, 2005 Pirolli, P. and Card, S. The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. Paper presented at the International Conference on Intelligence Analysis. McLean, Virginia. May. Retrieved from https://analysis.mitre.org/proceedings/index.html [Google Scholar]) and brings to the fore two kinds of focusing. Data focusing involves identifying and structuring information to draw out facts relevant to a given set of investigation issues. Issue focusing involves revising the issues in the light of new insights. Both are essential in sensemaking. We draw this distinction through detailed accounts of two activities in the investigations: reviewing documents for relevance and the creation and use of external representations. This provides a basis for a number of requirements for sensemaking support systems, particularly in collaborative settings, including document annotation; dynamically associating documents of a given type; interacting with documents in fluid ways; linking external representation elements to evidence; filtering external representations in flexible ways; and viewing external representations at different levels of scale and fidelity. Finally, we use our data to analyze the conceptual elements within a “line of inquiry.” This provides a framework that can form the basis for partitioning information into hierarchically embedded inquiry ‘contexts’ within collaborative sensemaking systems.

While mistakes, and approaches to design and training that reduce them, have been studied extensively, relatively little work in HCI studies ‘slip’ errors, which occur when one intends to do a certain action during a skilled task but unintentionally does another. In this article we examine approaches to training that might reduce the occurrence of a slip error referred to as a ‘device initialization error’. This error occurs when skilled users of a device forget to perform some initialization action, such as positioning the cursor in a text entry box or setting the device into the correct mode, before entering data or performing some other significant activity. We report on an experiment studying the effects of two training interventions on this error, which aim to manipulate the salience of the error–prone action without making any physical changes to the device. In the first intervention participants were given a particular conceptual model of the device’s operation, to evaluate whether having an improved understanding of the effect of each action would lead to fewer errors. In the second, participants were given a new device operation goal requiring them to ‘test’ the device, to evaluate whether attending to the outcome of initialization actions would lead to fewer errors. Only participants who were asked to ‘test’ the device and also given enhanced instructions to enter dummy data after completing initialization actions showed a statistically significant improvement in performance. Post-test interviews and evidence from existing literature suggest that when participants forgot the initialization step it was because they were attending to the subsequent data entry steps. This study highlights the central roles that user goals and attention play in the occurrence (or avoidance) of slip errors.

Haptic feedback has the potential to enhance users’ sense of being engaged and creative in their artwork. Current work on providing haptic feedback in computer-based drawing applications has focused mainly on the realism of the haptic sensation rather than the users’ experience of that sensation in the context of their creative work. We present a study that focuses on user experience of three haptic drawing interfaces. These interfaces were based on two different haptic metaphors, one of which mimicked familiar drawing tools (such as pen, pencil or crayon on smooth or rough paper) and the other of which drew on abstract descriptors of haptic experience (roughness, stickiness, scratchiness and smoothness). It was found that users valued having control over the haptic sensation; that each metaphor was preferred by approximately half of the participants; and that the real world metaphor interface was considered more helpful than the abstract one, whereas the abstract interface was considered to better support creativity. This suggests that future interfaces for artistic work should have user-modifiable interaction styles for controlling the haptic sensation.

It is a pleasure to introduce this special Festschrift edition in honour of John Long’s contribution to Human Computer Interaction and the science of design more broadly. John Long is one of the founders of our discipline in the UK and contributed significantly to the emergence of HCI in the international arena. As readers will see from the collection of papers which review and develop Long’s work, he questioned the nature of HCI at a deep level in proposing, with John Dowell, his well known and much cited ‘conception’ of the discipline (Long and Dowell, 1989; Dowell and Long, 1998). However, John Long’s HCI research started with work on menu design (Barnard et al., 1977), and frameworks of HCI attracted his attention soon afterwards (Morton et al., 1979). In addition to his theory research, Long’s contributions have included method development exploring the convergence of software engineering and HCI (Lim and Long, 1994), evaluation methodology (Denley and Long, 1997), analysis and design of socio-technical systems (Smith et al., 1997), and applying his expertise and knowledge to CSCW (Lambie and Long, 2002) and requirements engineering (Denley and Long, 2001).

Abstract Well-designed interfaces use procedural and sensory cues to increase the cognitive salience of appropriate actions. However, empirical studies suggest that cognitive load can influence the strength of those cues. We formalise the relationship between salience and cognitive load revealed by empirical data. We add these rules to our abstract cognitive architecture, based on higher-order logic and developed for the formal verification of usability properties. The interface of a fire engine dispatch task from the empirical studies is then formally modelled and verified. The outcomes of this verification and their comparison with the empirical data provide a way of assessing our salience and load rules. They also guide further iterative refinements of these rules. Furthermore, the juxtaposition of the outcomes of formal analysis and empirical studies suggests new experimental hypotheses, thus providing input to researchers in cognitive science.

Abstract This article reports on a longitudinal study of information seeking by undergraduate information management students. It describes how they found and used information, and explores their motivation and decision making. We employed a use‐in‐context approach where students were observed conducting, and were interviewed about, information‐seeking tasks carried out during their academic work. We found that participants were reluctant to engage with a complex range of information sources, preferring to use the Internet. The main driver for progress in information seeking was the immediate demands of their work (e.g., assignments). Students used their growing expertise to justify a conservative information strategy, retaining established strategies as far as possible and completing tasks with minimum information‐seeking effort. The time cost of using library material limited the uptake of such resources. New methods for discovering and selecting information were adopted only when immediately relevant to the task at hand, and tasks were generally chosen or interpreted in ways that minimized the need to develop new strategies. Students were driven by the demands of the task to use different types of information resources, but remained reluctant to move beyond keyword searches, even when they proved ineffective. They also lacked confidence in evaluating the relative usefulness of resources. Whereas existing literature on satisficing has focused on stopping conditions, this work has highlighted a richer repertoire of satisficing behaviors.

Formal models of rational user behavior are essential for user-centered reasoning about interactive systems. At an abstract level, planned behavior and reactive behavior are two important aspects of the rational behavior of users for which existing cognitive modeling approaches are too detailed. In this paper, we propose a novel treatment of these aspects within our formal framework of cognitively plausible behavior. We develop an abstract, formal model of rational behavior as a game between two opponents. Intuitively, an Angel abstractly represents the planning aspects, whereas a Demon represents the reactive aspects of user behavior. The formalization is carried out within the MOCHA framework and is illustrated by simple examples of interactive tasks.

Analytical usability evaluation methods (UEMs) can complement empirical evaluation of systems: for example, they can often be used earlier in design and can provide accounts of why users might experience difficulties, as well as what those difficulties are. However, their properties and value are only partially understood. One way to improve our understanding is by detailed comparisons using a single interface or system as a target for evaluation, but we need to look deeper than simple problem counts: we need to consider what kinds of accounts each UEM offers, and why. Here, we report on a detailed comparison of eight analytical UEMs. These eight methods were applied to a robotic arm interface, and the findings were systematically compared against video data of the arm in use. The usability issues that were identified could be grouped into five categories: system design, user misconceptions, conceptual fit between user and system, physical issues, and contextual ones. Other possible categories such as user experience did not emerge in this particular study. With the exception of Heuristic Evaluation, which supported a range of insights, each analytical method was found to focus attention on just one or two categories of issues. Two of the three “home-grown” methods (Evaluating Multimodal Usability and Concept-based Analysis of Surface and Structural Misfits) were found to occupy particular niches in the space, whereas the third (Programmable User Modeling) did not. This approach has identified commonalities and contrasts between methods and provided accounts of why a particular method yielded the insights it did. Rather than considering measures such as problem count or thoroughness, this approach has yielded insights into the scope of each method.

Abstract Information behavior (IB) research involves examining how people look for and use information, often with the sole purpose of gaining insights into the behavior displayed. However, it is also possible to examine IB with the purpose of using the insights gained to design new tools or improve the design of existing tools to support information seeking and use. This approach is advocated by David Ellis who, over two decades ago, presented a model of information seeking behaviors and made suggestions for how electronic tools might be designed to support these behaviors. Ellis also recognized that IBs might be used as the basis for evaluating as well as designing electronic resources. In this article, we present the IB evaluation methods. These two novel methods, based on an extension of Ellis's model, use the empirically observed IBs of lawyers as a framework for structuring user‐centered evaluations of the functionality and usability of electronic resources. In this article, we present the IB methods and illustrate their use through the discussion of two examples. We also discuss benefits and limitations, grounded in specific features of the methods.

As researchers we are constantly working with academic literature. Literature data is growing exponentially. Interacting with this huge amount of information has been a challenge for the field of HCI for years. The goal is to assist users in making sense of this information by producing usable designs. Information Visualization (InfoVis) augments users' cognition when interacting with complex data structures. Although the use of InfoVis as a tool for representing literature data is not new, we have found that most of the existing Literature Knowledge Domain Visualizations (LKDViz) target specialists known as domain analysts who study publication patterns. Our goal is to design a LKDViz tool for academic users. Due to the diversity of academic literature users we captured their experiences and used it as the main source for our design. Interestingly, this method generated design criteria that have not been applied in most of the academic literature visualizations.

Abstract The correct functioning of interactive computer systems depends on both the faultless operation of the device and correct human actions. In this paper, we focus on system malfunctions due to human actions. We present abstract principles that generate cognitively plausible human behaviour. These principles are then formalised in a higher-order logic as a generic , and so retargetable, cognitive architecture, based on results from cognitive psychology. We instantiate the generic cognitive architecture to obtain specific user models. These are then used in a series of case studies on the formal verification of simple interactive systems. By doing this, we demonstrate that our verification methodology can detect a variety of realistic, potentially erroneous actions, which emerge from the combination of a poorly designed device and cognitively plausible human behaviour.

In recent years, there has been great interest in scenario-based design and other forms of user-centred design. However, there are many design processes that, often for good reason, remain technology-centred. We present a case study of introducing scenarios into two digital library development processes. This was found to disrupt established patterns of working and to bring together conflicting value systems. In particular, the human factors approach of identifying users and anticipating what they are likely to do with a system (and what problems they might encounter) did not sit well with a development culture in which the rapid generation and informal evaluation of possible solutions (that are technically feasible and compatible with stable system components) is the norm. We found that developers tended to think in terms of two kinds of user: one who was exploring the system with no particular goal in mind and one who knew as much as the developer; scenarios typically work with richer user descriptions that challenge that thinking. In addition, the development practice of breaking down the design problem into discrete functions to make it manageable does not fit well with a scenario-based approach to thinking about user behaviour and interactions. The compromise reached was scenario-informed design, whereby scenarios were generated to support reasoning about the use of selected functions within the system. These scenarios helped create productive common ground between perspectives.

Abstract A user's understanding of the libraries they work in, and hence of what they can do in those libraries, is encapsulated in their “mental models” of those libraries. In this article, we present a focused case study of users' mental models of traditional and digital libraries based on observations and interviews with eight participants. It was found that a poor understanding of access restrictions led to risk‐averse behavior, whereas a poor understanding of search algorithms and relevance ranking resulted in trial‐and‐error behavior. This highlights the importance of rich feedback in helping users to construct useful mental models. Although the use of concrete analogies for digital libraries was not widespread, participants used their knowledge of Internet search engines to infer how searching might work in digital libraries. Indeed, most participants did not clearly distinguish between different kinds of digital resource, viewing the electronic library catalogue, abstracting services, digital libraries, and Internet search engines as variants on a theme.

As researchers we are constantly working with our literature domains. Making sense and familiarizing ourselves with such domains is a cumbersome but necessary task that is part of every researcher's career, especially novices. Literature knowledge domain visualizations exist which assist users in extracting and interpreting interesting patterns. However, these visualizations tend to be developed without reference to the particular needs of researchers or without addressing the specific challenges of the literature knowledge domain. This paper therefore targets the needs of researchers as they work with their literature. We conducted a qualitative study to understand how researchers make sense of their literature domains. Such information assisted us in coming up with a set of design considerations and guidelines which we believe will assist in building visualizations that are useful for the general research population

One of the long-standing challenges in human-computer interaction has been the integration of usability evaluation methods within design practice. In the work reported here, the question of how to include user concerns within an unstructured, system-focused development process was investigated. The project looked into the use of Claims Analysis as a method for assessing the effects of design decisions on users' experience. Claims Analysis was found to be more difficult than expected to learn, to communicate to systems developers, and to apply effectively in practice. The work has highlighted a tension between user-centered and function-oriented design approaches and differences in values and perspectives between the human factors specialists and traditional developers involved in the study.

This article reports on work studying how technology can empower or exclude its users due to interactions between social context, system design, and implementation. The analysis is based around the introduction and use of digital libraries in four different settings, three clinical and one academic. Across the four settings, in-depth interview and focus group data was collected from 144 users and analyzed with reference to “communities of practice”. The four settings represent three different approaches to digital library implementation: making digital library resources available from existing computer systems in people's offices and the library (a traditional approach); making computer systems, and hence digital libraries, available in shared spaces (in this case, hospital wards); and employing information intermediaries to work with staff and library resources. These different approaches engendered different perceptions of the technology. The traditional approach produced perceptions of technology as being irrelevant for current needs and community practices. Making technology available within shared physical space but with poor design, support, and implementation procedures was widely perceived as a threat to current organizational structures. In contrast, technology implemented within the community which could adapt and change practices according to individual and group needs, supported by an information intermediary, was seen as empowering to both the community and the individual. We relate the findings to a discussion of evolutionary and revolutionary approaches to design and to the concept of communities of practice.

There is need for user-centred visualisation research to engage with the activity context, information needs, knowledge and abilities of target user-groups. With a focus on the work of journalists, we first argue for information-retrieval results visualisation as a suitable browsing framework for journalists' frequently ill-defined needs and high-recall searches. We then describe the design and rationale for a histogram-based visualisation for journalists. We also describe the integration of this idea within a system that structures searching as a two-step query-and-filter operation. This approach is intended to support initial exploratory browsing and refinement in a way that is sympathetic to the systematic focusing that naturally occurs during complex, unstructured task performance. Further, the use of an enduring 'base' results set is intended to encourage structural familiarity with the broader results and therefore to enhance navigation.

We focus on the ability of two analytical usability evaluation methods (UEMs), namely CASSM (Concept-based Analysis for Surface and Structural Misfits) and Cognitive Walkthrough, to identify usability issues underlying the use made of two London Underground ticket vending machines. By setting both sets of issues against the observed interactions with the machines, we assess the similarities and differences between the issues depicted by the two methods. In so doing we de-emphasise the mainly quantitative approach which is typical of the comparative UEM literature. However, by accounting for the likely consequences of the issues in behavioural terms, we reduced the proportion of issues which were anticipated but not observed (the false positives), compared with that achieved by other UEM studies. We assess these results in terms of the limitations of problem count as a measure of UEM effectiveness. We also discuss the likely trade-offs between field studies and laboratory testing.

As more intelligent systems are introduced into the marketplace, it is becoming increasingly urgent to consider usability for such systems. Historically, the two fields of artificial intelligence (AI) and human‐ computer interaction (HCI) have had little in common. In this paper, we consider how established HCI techniques can usefully be applied to the design and evaluation of intelligent systems, and where there is an urgent need for new approaches. Some techniques ‐ notably those for requirements acquisition and empirical evaluation ‐ can usefully be adopted, and indeed are, within many projects. However, many of the tools and techniques developed within HCI to support design and theory‐based evaluation cannot be applied in their present forms to intelligent systems because they are based on inappropriate assumptions; there is consequently a need for new approaches. Conversely, there are approaches that have been developed within AI ‐ e.g. in research on dialogue and on ontologies ‐ that could usefully be adapted and encapsulated to respond to this need. These should form the core of a future research agenda for intelligent interaction design.

Abstract. Much of the behaviour of an interactive system is determined by its user population. This paper describes how assumptions about the user can be brought into system models in order to reason about their behaviour. We describe a system model containing reasonable assumptions about the user as being ‘cognitively plausible’. Before asserting the plausibility of a model however we must first be able to make the assumptions made in that model inspectable. There is a tension between the inspectability of user assumptions and the tractability of models; inspectable models tend to not be very tractable and vice versa . We describe how we can get round this tension, by deriving tractable models from explicit user assumptions. The resulting models may not of themselves be very inspectable to human-factors workers, but the process by which they are derived is inspectable. Hence we claim that we can have both tractability and inspectability. We exemplify our claims using a simple cognitive model and ‘Meeting Maker’, an interactive electronic diary system.

Certain design projects raise difficult user-interface problems that are not easily amenable to designers' intuition or rapid prototyping due to their novelty, conceptual complexity, and the difficulty of conducting appropriate user studies. Interpersonal access control in computer-mediated communication (CMC) systems is just such a problem. We describe a collection of systematic theory-based analyses of a system prototype that inherited its control mechanism from two preexisting systems. We demonstrate that the collective use of system and user modeling techniques provides insight into this complex design problem and enables us to examine the implications of design decisions for users and implementation. The analyses identify a number of weaknesses in the prototype and are used to propose ways of making substantive refinements to improve its simplicity and appropriateness for two tasks: altering one's accessibility and distinguishing between who can make what kinds of connections. We conclude with a discussion of some critical issues that are relevant for CMC systems, and reflect on the process of applying formal human-computer interaction (HCI) techniques in informal, exploratory design contexts.