Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure

Delivering "Just-In-Time" Smoking Cessation Support Via Mobile Phones: Current Knowledge and Future Directions.

UNLABELLED: Smoking lapses early on during a quit attempt are highly predictive of failing to quit. A large proportion of these lapses are driven by cravings brought about by situational and environmental cues. Use of cognitive-behavioral lapse prevention strategies to combat cue-induced cravings is associated with a reduced risk of lapse, but evidence is lacking in how these strategies can be effectively promoted. Unlike most traditional methods of delivering behavioral support, mobile phones can in principle deliver automated support, including lapse prevention strategy recommendations, Just-In-Time (JIT) for when a smoker is most vulnerable, and prevent early lapse. JIT support can be activated by smokers themselves (user-triggered), by prespecified rules (server-triggered) or through sensors that dynamically monitor a smoker's context and trigger support when a high risk environment is sensed (context-triggered), also known as a Just-In-Time Adaptive Intervention (JITAI). However, research suggests that user-triggered JIT cessation support is seldom used and existing server-triggered JIT support is likely to lack sufficient accuracy to effectively target high-risk situations in real time. Evaluations of mobile phone cessation interventions that include user and/or server-triggered JIT support have yet to adequately assess whether this improves management of high risk situations. While context-triggered systems have the greatest potential to deliver JIT support, there are, as yet, no impact evaluations of such systems. Although it may soon be feasible to learn about and monitor a smoker's context unobtrusively using their smartphone without burdensome data entry, there are several potential advantages to involving the smoker in data collection. IMPLICATIONS: This commentary describes the current knowledge on the potential for mobile phones to deliver automated support to help smokers manage or cope with high risk environments or situations for smoking, known as JIT support. The article categorizes JIT support into three main types: user-triggered, server-triggered, and context-triggered. For each type of JIT support, a description of the evidence and their potential to effectively target specific high risk environments or situations is described. The concept of unobtrusive sensing without user data entry to inform the delivery of JIT support is finally discussed in relation to potential advantages and disadvantages for behavior change.This is the accepted manuscript. The final version is available at http://ntr.oxfordjournals.org/content/early/2016/06/15/ntr.ntw143

The motivation and pleasure dimension of negative symptoms: neural substrates and behavioral outputs.

A range of emotional and motivation impairments have long been clinically documented in people with schizophrenia, and there has been a resurgence of interest in understanding the psychological and neural mechanisms of the so-called "negative symptoms" in schizophrenia, given their lack of treatment responsiveness and their role in constraining function and life satisfaction in this illness. Negative symptoms comprise two domains, with the first covering diminished motivation and pleasure across a range of life domains and the second covering diminished verbal and non-verbal expression and communicative output. In this review, we focus on four aspects of the motivation/pleasure domain, providing a brief review of the behavioral and neural underpinnings of this domain. First, we cover liking or in-the-moment pleasure: immediate responses to pleasurable stimuli. Second, we cover anticipatory pleasure or wanting, which involves prediction of a forthcoming enjoyable outcome (reward) and feeling pleasure in anticipation of that outcome. Third, we address motivation, which comprises effort computation, which involves figuring out how much effort is needed to achieve a desired outcome, planning, and behavioral response. Finally, we cover the maintenance emotional states and behavioral responses. Throughout, we consider the behavioral manifestations and brain representations of these four aspects of motivation/pleasure deficits in schizophrenia. We conclude with directions for future research as well as implications for treatment

Implementing Ethics for a Mobile App Deployment

This paper discusses the ethical dimensions of a research project in which we deployed a personal tracking app on the Apple App Store and collected data from users with whom we had little or no direct contact. We describe the in-app functionality we created for supporting consent and withdrawal, our approach to privacy, our navigation of a formal ethical review, and navigation of the Apple approval process. We highlight two key issues for deployment-based research. Firstly, that it involves addressing multiple, sometimes conflicting ethical principles and guidelines. Secondly, that research ethics are not readily separable from design, but the two are enmeshed. As such, we argue that in-action and situational perspectives on research ethics are relevant to deployment-based research, even where the technology is relatively mundane. We also argue that it is desirable to produce and share relevant design knowledge and embed in-action and situational approaches in design activities

Exploring nonconscious behaviour change interventions on mobile devices

Modern cognitive psychology theories such as Dual Process Theory suggest that the source of much habitual behaviour is the nonconscious. Despite this, most behaviour change interventions using technology (BCITs) focus on conscious strategies to change people’s behaviour. We propose an alternative avenue of research, which focuses on understanding how best to directly target the nonconscious via mobile devices in real-life situations to achieve behaviour change

Towards Multi-modal Anticipatory Monitoring of Depressive States through the Analysis of Human-Smartphone Interaction

Remarkable advances in smartphone technology, especially in terms of passive sensing, have enabled researchers to passively monitor user behavior in real-Time and at a granularity that was not possible just a few years ago. Recently, different approaches have been proposed to investigate the use of different sensing and phone interaction features, including location, call, SMS and overall application usage logs, to infer the depressive state of users. In this paper, we propose an approach for monitoring of depressive states using multi-modal sensing via smartphones. Through a brief literature review we show the sensing modalities that have been exploited in the past studies for monitoring depression. We then present the initial results of an ongoing study to demonstrate the association of depressive states with the smartphone interaction features. Finally, we discuss the challenges in predicting depression through multimodal mobile sensing

Technological advances relevant to transport – understanding what drives them

Transport policy makers are increasingly perplexed by the pace of change in their sector and by the increasing influence of external actors. This leads to a variety of responses, including “business as usual”, technological optimism, technological fatalism and technological ignorance. To explore this perplexity and its justification, we examine four areas of technological advance relevant to transport: mobility as a service; unmanned aerial vehicles (drones); automated vehicles; and telehealth. In each case, we identify the principal underlying shifts which are driving these technological advances, concluding that there is considerable overlap: three of the advances rely on ubiquitous sensing and on artificial intelligence and all four rely, to some degree, on connectedness. We then explore these three “drivers”, finding that progress is steadier than may be generally thought. We discuss the implications for our set of transport-related technological developments, concluding that policy makers could approach the future with greater confidence than is currently typical. They could also draw on the concepts of anticipatory governance to support their management of emerging technology and, at the same time, of the influence of external actors