Arranging Icons on Small Displays: Do Hexagonal Layouts Improve Search Performance?

Mobile devices with small displays can use hexagonal layouts of circular icons to use space more efficiently – we test whether this design choice improves people's search performance. An experiment is reported in which 24 participants performed known-item searches of menus that varied along four dimensions: (1) whether icons were arranged using a hexagonal or a grid layout, (2) how closely icons were placed next to each other, (3) the number of icons in the display that shared the same color as the target, and (4) whether icons stayed in the same location or moved between trials. Results show that search times were faster with hexagonal layouts but only when there were many same-color distractors and icons were packed very close to each other. This work contributes new empirical findings on how icon arrangements, in interaction with other critical visual design features, affect search performance

THE APPLICATION OF SMARTWATCH IN MANAGING EMPLOYEE HEALTH MONITORING

ABSTRACTWorkplace health issues have continued to increase, and this has caused problems such as increasing medical cost and medical leaves. In response to these issues, employers are starting to adopt health technology to overcome the problem such as smartwatch. Smartwatch technology is a wrist-worn device provided with a variety of sensors that are available for collecting physical activity and location data in real time. This paper aims to explore the future drivers of the smartwatch application in monitoring and managing employees’ health. The research study used exploratory research design utilizing the foresight methods. STEEPV analysis was used to identify the key drivers of smartwatch application and to develop a descriptive survey for assessing the impact and uncertainty of each driver. The survey was distributed to human resources managers of medium-sized companies in Malaysia. Technology readiness of smart watch adoption was evaluated using Technology Readiness Index (TRI). Thirty-five respondents took part in online survey. From the data analysis, top two drivers had been identified which are “social interaction” and “data transparency”. These drivers were used for developing future scenario of the smartwatch application in monitoring and managing employee health in the next 5 to 10 years. Four scenarios had been discussed in this paper which are healthy workplace environment, unattainable technology adoption, inefficient technology, and low adoption of smartwatch. This research would provide additional information about the future scenario of smartwatch application in managing employee health monitoring in Malaysia. Keywords: Smartwatch; Employee Health Monitoring; Technological Readines

Why are smartphones disruptive? An empirical study of smartphone use in real-life contexts

Notifications are one of the core functionalities of smartphones. Previous research suggests they can be a major disruption to the professional and private lives of users. This paper presents evidence from a mixed-methods study using first-person wearable video cameras, comprising 200 h of audio-visual first-person, and self-confrontation interview footage with 1130 unique smartphone interactions (N = 37 users), to situate and analyse the disruptiveness of notifications in real-world contexts. We show how smartphone interactions are driven by a complex set of routines and habits users develop over time. We furthermore observe that while the duration of interactions varies, the intervals between interactions remain largely invariant across different activity and location contexts, and for being alone or in the company of others. Importantly, we find that 89% of smartphone interactions are initiated by users, not by notifications. Overall this suggests that the disruptiveness of smartphones is rooted within learned user behaviours, not devices

Patterns of multi-device use with the smartphone a video-ethnographic study of young adults’ multi-device use with smartphones in naturally occurring contexts

Using multiple devices at the same time is becoming increasingly common in the daily lives of users, be it for work or for leisure. This paper presents in situ qualitative and quantitative evidence of multi-device use from a dataset of over 200h of first-person and interview recordings (n = 41). We discuss three different ‘patterns’ of multi device use (work, leisure, mixed use) and illustrate the user experience in detail with three participant journeys. We find that the smartphone was always ‘in the mix’; we did not observe multi-device use without the smartphone, or isolated use of other devices. Overall, we suggest that looking at transitions between activities users engage in rather than devices they use is more effective to understand multi-device use. Based on this analysis, we highlight issues around the patterns and experiences of multi-device use in everyday life and provide recommendations for design and further research

Patterns of multi-device use with the smartphone. A video-ethnographic study of young adults’ multi-device use with smartphones in naturally occurring contexts

Using multiple devices at the same time is becoming increasingly common in the daily lives of users, be it for work or for leisure. This paper presents in situ qualitative and quantitative evidence of multi-device use from a dataset of over 200h of first-person and interview recordings (n = 41). We discuss three different ‘patterns’ of multi device use (work, leisure, mixed use) and illustrate the user experience in detail with three participant journeys. We find that the smartphone was always ‘in the mix’; we did not observe multi-device use without the smartphone, or isolated use of other devices. Overall, we suggest that looking at transitions between activities users engage in rather than devices they use is more effective to understand multi-device use. Based on this analysis, we highlight issues around the patterns and experiences of multi-device use in everyday life and provide recommendations for design and further research

Understanding how to design health data visualizations for Chilean older adults on mobile devices

Mobile devices, including activity trackers and smartwatches, can help older adults monitor health parameters passively and unobtrusively. Most user interactions with small devices consist of brief glances at the time or notifications. Consuming information from small displays poses challenges, which have been seldom studied from the perspective of older users. In this paper, we worked with older adults towards creating health data visualizations for them for small devices. We conducted a mixed-methods study with 30 older adults, in which we (1) conducted group discussions to understand participants’ opinions, (2) measured times taken to interpret health data visualizations with and without progress information, (3) measured how much information they could manage to see during brief glances. When data was visualized without progress indicators, participants took less time to understand the data and made fewer errors. Participants preferred health data visualizations that featured peaceful, and positive pictorial representations. We present design opportunities for older adults’ data visualizations in small devices

Smartphones as steady companions: device use in everyday life and the economics of attention

This thesis investigates smartphone use in naturally occurring contexts with a dataset comprising 200 hours of audio-visual first-person recordings from wearable cameras, and self-confrontation interview video footage (N = 41 users). The situated context in which smartphone use takes place has often been overlooked because of the technical difficulty of capturing context of use, actual action of users, and their subjective experience simultaneously. This research project contributes to filling this gap, with a detailed, mixed-methods analysis of over a thousand individual phone engagement behaviours (EB). We observe that (a) the smartphone is a key structuring element in the flow of daily activities. Participants report complex strategies on how they manage engaging with or avoiding their devices. (b) Unexpectedly, we find that the majority of EB (89%) are initiated by users, not devices; users engage with the phone roughly every five minutes regardless of the context they are in. (c) A large portion of EB seems to stem from contextual cues and an unconscious urge to pick up the device, even when there is no clear reason to do so. d) Participants are surprised about, and often unhappy with how frequently they mindlessly reach for the phone. Our in-depth analysis unveils several overlapping layers of motivations and triggers driving EB. Monitoring incoming notifications, managing time use, responding to social pressures, actually completing a task with the phone, design factors, unconscious urges, as well as the accessibility of the device, and most importantly its affordance for distraction all contribute to picking up the phone. This user drive for EB is used by providers to feed the attention economy. So far, keeping the smartphone outside of the visual field and immediate reach has appeared as the only efficient strategy to prevent overuse