Older adults can benefit from technologies that help them to complete everyday tasks. However, they are an often-under-represented population in augmented reality (AR) research. We present the results of a study in which people aged 50 years or older were asked to perform actions by interpreting visual AR prompts in a lab setting. Our results show that users were less successful at completing actions when using ARROW and HIGHLIGHT augmentations than when using ghosted OBJECT or GHOSTHAND augmentations. We found that user confidence in performing actions varied according to action and augmentation type. Users preferred combined AUDIO+TEXT prompts (our control condition) overall, but the GHOSTHAND was the most preferred visual prompt. We discuss reasons for these differences and provide insight for developers of AR content for older adults. Our work provides the first comparative study of AR with older adults in a non-industrial context.

Chronic Fatigue Syndrome (CFS) is a debilitating medical condition that is characterized by a range of physical, cognitive and social impairments. This paper investigates CFS patients' perspectives on the potential for technological support for self-management of their symptoms. We report findings from three studies in which people living with CFS 1) prioritized symptoms that they would like technologies to address, 2) articulated their current approaches to self-management alongside challenges they face, and 3) reflected on their experiences with three commercial smartphone apps related to symptom management. We contribute an understanding of the specific needs of the ME/CFS population and the ways in which they currently engage in self-management using technology. The paper ends by describing five high-level design recommendations for ME/CFS self-management technologies.

Personal informatics systems are tools that capture, aggregate, and analyze data from distinct facets of their users’ lives. This article adopts a mixed-methods approach to understand the problem of information overload in personal informatics systems. We report findings from a 3-month study in which 20 participants collected multifaceted personal tracking data and used a system called Exist to reveal statistical correlations within their data. We explore the challenges that participants faced in reviewing the information presented by Exist, and we identify characteristics that exemplify “interesting” correlations. Based on these findings, we develop automated filtering mechanisms that aim to prevent information overload and support users in extracting interesting insights. Our approach deals with information overload by reducing the number of correlations shown to users by about 55% on average and increases the percentage of displayed correlations rated as interesting to about 81%, representing a 34 percentage point improvement over filters that only consider statistical significance at p < .05. We demonstrate how this curation can be achieved using objective data harvested by the system, including the use of Google Trends data as a proxy for subjective user interest.

We present a revisitation analysis of smartphone use to investigate the question: do smartphones induce usage habits? We analysed three months of application launch logs from 165 users in naturalistic settings. Our analysis reveals distinct clusters of applications and users which share similar revisitation patterns. However, we show that much of smartphone usage on a macro-level is very similar to web browsing on desktops, and thus argue that smartphone usage is driven by innate service needs rather than technology characteristics. On the other hand, on a micro-level we identify unique characteristics in smartphone usage, and we present a rudimentary model that accounts for 92% in the variability of our smartphone use.

This paper describes the development and home testing of the inTouch system, a video link designed specifically for people with dementia to use. Iterative, user centered design of four user interaction models was carried out at a day centre. A touchscreen with a telephone handset model was chosen as the most usable interface for a range of people with dementia. This model was developed into a fully working prototype and tested in two home trials, linking two households together over domestic broadband connections. The recruitment of participants for home testing proved to be a significant challenge with no single reason being given for declining or not continuing. Two in-home evaluations of the system were carried out; the system was perceived as easy to use and participants could see the potential benefits, such as being reassured about each other's wellbeing, and enjoyed engaging visually. The poor reliability of existing broadband connections in the homes was a significant limitation to gathering data within the trials. We have successfully applied user centered design principles to the development of a home video link for people living with dementia and their carers. Developers need to consider practical issues around recruitment and broadband infrastructure when carrying out real world evaluations of ICT systems.

In this paper we investigate how decisions made while using a granular access control mechanism for sharing photographs are influenced by contextual factors and properties relating to the identities of contacts. We develop analytical models using logistic regression to understand relationships between variables that affect sharing decisions. We also investigate how predefined, static groups for privacy control cope with the challenge of sharing large amounts of content associated with numerous different contexts, and test whether they need to be adjusted to suit particular contexts.

This paper presents a study that aims to answer two important questions related to targeted location-sharing privacy attacks: (1) given a group of users and their social graph, is it possible to predict which among them is likely to reveal most about their whereabouts, and (2) given a user, is it possible to predict which among her friends knows most about her whereabouts. To answer these questions we analyse the privacy policies of users of a real-time location sharing application, in which users actively shared their location with their contacts. The results show that users who are central to their network are more likely to reveal most about their whereabouts. Furthermore, we show that the friend most likely to know the whereabouts of a specific individual is the one with most common contacts and/or greatest number of contacts.

Users of social networking sites often want to manage the sharing of information and content with different groups of people based on their differing relationships. However, grouping contacts places a significant configuration burden on the user. Automated approaches to grouping may have the potential to reduce this burden, however, their use remains largely untested. We investigate people's rationales when grouping their contacts for the purpose of controlling their privacy, finding six criteria that they commonly considered. We assess an automated approach to grouping, based on a network clustering algorithm, whose performance may be analogous to the human's use of some of these criteria. We find that the similarity between the groups created by people and those created by the algorithm is correlated with the modularity of their network. We also demonstrate that the particular clustering algorithm, SCAN, which detects hubs and outliers within a network can be beneficial for identifying contacts who are hard to group or for whom privacy preferences are inconsistent with the rest of their group.

With an ever increasing number of mobile services, meaningful audio notifications could effectively inform users of the incoming services while minimising undesired and intrusive interruptions. Therefore, careful design of mobile service notification is needed. In this paper we evaluate two types of audio (auditory icons and earcons) as mobile service notifications, by comparing them on 4 measures: intuitiveness, learnability, memorability and user preference. A 4-stage longitudinal evaluation involving two lab experiments, a field study and a web-based experiment indicated that auditory icons performed significantly better in all measures. Implications for mobile audio notification design are presented.

There are academic and commercial drivers for context-awareness to play a prominent role in the future of mobile services. Implementing a complete model of context remains an unsolved problem, however, some contextual elements such as person, time and place are relatively easy to identify. We develop a simple context model incorporating personal, temporal and spatial dimensions and apply it to a context-aware text messaging service. We report a field study of the service, investigating how applying these fundamental contextual constraints to messages can affect the nature of communication between participants. The results suggest that although contextual constraints are not appropriate for all types of message content, they increase opportunities for situated chat in public spaces, improve group awareness between peers and facilitate conversations between people, some of whom would not otherwise communicate with each other.