No abstract

Purpose: Informal caregivers of bedridden elders need a respite. One form of obtaining a respite is through volunteers who are contacted by means of information and communication technology (ICT). Method: A qualitative study was carried out in a low-income district in Santiago, Chile, to learn about how caregivers of bedridden elders perceive the possibility of using ICT to access this respite. In-depth interviews were carried out and transcribed verbatim, then analysed using open coding. Results: The results reveal that caregivers are willing to receive a volunteer in their home and use ICT to communicate with them, although a discrepancy exists between the use of devices connected to the Internet and feature phones. Conclusion: This study concludes that informal caregivers of bedridden elders have a favourable disposition towards accessing a respite system by means of ICT based on a peer-to-peer economy.

No abstract

No abstract

This paper examines 'the routine shop' as part of a project that is exploring automation and autonomy in the Internet of Things. In particular we explicate the 'work' involved in anticipating need using an ethnomethodological analysis that makes visible the mundane, 'seen but unnoticed' methodologies that household members accountably employ to organise list construction and accomplish calculation on the shop floor. We discuss and reflect on the challenges members' methodologies pose for proactive systems that seek to support domestic grocery shopping, including the challenges of sensing, learning and predicting, and gearing autonomous agents into social practice within the home.

Predictions of people's behaviour increasingly drive interactions with a new generation of IoT services designed to support everyday life in the home, from shopping to heating. Based on the premise that such automation is difficult due to the contingent nature of people's practices, in this work we explore the nature of these contingencies in depth. We have designed and conducted a technology probe that made use of simple linear predictions as a provocation, and invited people to track the life of their household essentials over a two-month period. Through a mixed-method approach we demonstrate the challenges of simple predictions, and in turn identify eight categories of contingencies that influenced prediction accuracy. We discuss strategies for how designers of future predictive IoT systems may take the contingencies into account by removing, hiding, revealing, managing, or exploiting the system uncertainty at the core of the issue. CCS CONCEPTS • Human-centered computing → Field studies; Empirical studies in ubiquitous and mobile computing; Empirical studies in HCI .

Pain is usually measured through patient reports during doctor visits, but it requires regular evaluation under real-life conditions to be resolved effectively. Over half of older adults suffer from pain. Chronic conditions such as this one may be monitored through technology; however, elderly users require technology to be specifically designed for them, because many have cognitive and physical limitations and lack digital skills. The purpose of this article is to study whether mobile or wearable devices are appropriate to self-report pain levels and to find which body position is more appropriate for elderly people to wear a device to self-report pain. We implemented three prototypes and conducted two phases of evaluation. We found that users preferred the wearable device over the mobile application and that a wearable to self-report pain should be designed specifically for this purpose. Regarding the placement of the wearable, we found that there was no preferred position overall, although the neck position received the most positive feedback. We believe that the possibility of creating a wearable device that may be placed in different positions may be the best solution to satisfy users’ individual preferences.

BackgroundMonitoring of patients may decrease treatment costs and improve quality of care. Pain is the most common health problem that people seek help for in hospitals. Therefore, monitoring patients with pain may have significant impact in improving treatment. Several studies have studied factors affecting pain; however, no previous study has reviewed the contextual information that a monitoring system may capture to characterize a patient’s situation.ObjectiveThe objective of this study was to conduct a systematic review to (1) determine what types of technologies have been used to monitor adults with pain, and (2) construct a model of the context information that may be used to implement apps and devices aimed at monitoring adults with pain.MethodsA literature search (2005-2015) was conducted in electronic databases pertaining to medical and computer science literature (PubMed, Science Direct, ACM Digital Library, and IEEE Xplore) using a defined search string. Article selection was done through a process of removing duplicates, analyzing title and abstract, and then reviewing the full text of the article.ResultsIn the final analysis, 87 articles were included and 53 of them (61%) used technologies to collect contextual information. A total of 49 types of context information were found and a five-dimension (activity, identity, wellness, environment, physiological) model of context information to monitor adults with pain was proposed, expanding on a previous model. Most technological interfaces for pain monitoring were wearable, possibly because they can be used in more realistic contexts. Few studies focused on older adults, creating a relevant avenue of research on how to create devices for users that may have impaired cognitive skills or low digital literacy.ConclusionsThe design of monitoring devices and interfaces for adults with pain must deal with the challenge of selecting relevant contextual information to understand the user’s situation, and not overburdening or inconveniencing users with information requests. A model of contextual information may be used by researchers to choose possible contextual information that may be monitored during studies on adults with pain.