Interaction design and emotional wellbeing

The World Health Organisation has concluded that emotional wellbeing is fundamental to our quality of life. It enables us to experience life as meaningful and is an essential component of social cohesion, peace and stability in the living environment [21]. This workshop will bring together a diverse community to consolidate existing knowledge and identify new opportunities for research on technologies designed to support emotional wellbeing. The workshop will examine uses of technology in mental health settings, but will also consider the importance of emotional needs in physical healthcare and wellbeing more generally. The design of technology to provide social support and to extend traditional care networks will be key workshop themes

Digital collections and digital collection practices

Reference is increasingly made to ‘digital collections’, yet this term encompasses accumulated digital objects of varying form, purpose and value. We review social science literature on mate-rial collections and draw from in-depth interviews with 20 peo-ple in the UK in order to offer a clearer understanding of what constitutes a digital collection and what does not. We develop a taxonomy that presents three distinct types of digital collection and demonstrate ways in which the affordances of digital envi-ronments may facilitate or impede meaningful practices of ac-quisition, curation and exhibition in each case. Through doing so, we present a framework for design in support of collecting prac-tices and the development of more meaningful and valued digital collections

Seven features of safety in maternity units: a framework based on multisite ethnography and stakeholder consultation

Background: Reducing avoidable harm in maternity services is a priority globally. As well as learning from mistakes, it is important to produce rigorous descriptions of ‘what good looks like’. Objective: We aimed to characterise features of safety in maternity units and to generate a plain language framework that could be used to guide learning and improvement. Methods: We conducted a multisite ethnography involving 401 hours of non-participant observations 33 semistructured interviews with staff across six maternity units, and a stakeholder consultation involving 65 semistructured telephone interviews and one focus group. Results: We identified seven features of safety in maternity units and summarised them into a framework, named For Us (For Unit Safety). The features include: (1) commitment to safety and improvement at all levels, with everyone involved; (2) technical competence, supported by formal training and informal learning; (3) teamwork, cooperation and positive working relationships; (4) constant reinforcing of safe, ethical and respectful behaviours; (5) multiple problem-sensing systems, used as basis of action; (6) systems and processes designed for safety, and regularly reviewed and optimised; (7) effective coordination and ability to mobilise quickly. These features appear to have a synergistic character, such that each feature is necessary but not sufficient on its own: the features operate in concert through multiple forms of feedback and amplification. Conclusions: This large qualitative study has enabled the generation of a new plain language framework—For Us—that identifies the behaviours and practices that appear to be features of safe care in hospital-based maternity units

Changing perspectives of time in HCI

The aim of this workshop is to unpack different ways of thinking about time, drawing a distinction between time as experienced, and time as counted by a ticking clock or measured by a computer algorithm. The concept of time is often taken for granted within HCI, yet highlighting the assumptions that underpin it could provide a resource for research and innovation. In this extended abstract, we illustrate how this is so

Engaging with Automation : Understanding and Designing for Operation, Appropriation, and Behaviour Change

| openaire: EC/H2020/101006817/EU//AWARDAutomation has been permeating our everyday lives in various facets. Given both the ubiquity and, in many cases, the indispensability of ubiquitous automated systems, creating engaging experiences with them becomes increasingly relevant. This workshop provides a platform for researchers and practitioners working on (semi-) automated systems and their user experience and allows for cross-discipline networking and knowledge transfer. In a keynote talk, paper presentations, discussions, and hands-on sessions, the participants will explore and discuss user engagement with automation for operation, appropriation, and change. The results of the workshop are a set of research ideas and drafts of joint research projects to drive further automation experience research in a collaborative interdisciplinary manner.Non peer reviewe

Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study

Background A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry. Methods Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected individuals, with sensitivity and specificity as the primary outcome. Mathematical modelling was used to investigate the impact of bio-detection dogs for screening. Results About, 3921 adults were enrolled in the study and odour samples collected from 1097 SARS-CoV-2 infected and 2031 uninfected individuals. OSC sensors were able to distinguish between SARS-CoV-2 infected individuals and uninfected, with sensitivity from 98% (95% CI 95–100) to 100% and specificity from 99% (95% CI 97–100) to 100%. Six dogs were able to distinguish between samples with sensitivity ranging from 82% (95% CI 76–87) to 94% (95% CI 89–98) and specificity ranging from 76% (95% CI 70–82) to 92% (95% CI 88–96). Mathematical modelling suggests that dog screening plus a confirmatory PCR test could detect up to 89% of SARS-CoV-2 infections, averting up to 2.2 times as much transmission compared to isolation of symptomatic individuals only. Conclusions People infected with SARS-CoV-2, with asymptomatic or mild symptoms, have a distinct odour that can be identified by sensors and trained dogs with a high degree of accuracy. Odour-based diagnostics using sensors and/or dogs may prove a rapid and effective tool for screening large numbers of people