We report from the Do Not Disturb Challenge where 30 volunteers disabled notification alerts for 24 hours across all devices. The effect of the absence of notifications on the participants was isolated through an experimental study design: we compared self-reported feedback from the day without notifications against a baseline day. The evidence indicates that notifications have locked us in a dilemma: without notifications, participants felt less distracted and more productive. But, they also felt no longer able to be as responsive as expected, which made some participants anxious. And, they felt less connected with one's social group. In contrast to previous reports, about two third of the participants expressed the intention to change how they manage notifications. Two years later, half of the participants are still following through with their plans.
Kushlev @cite_4 conducted a study in which for one week, 221 participants were asked to maximize interruptions through their phone (enabling alerts, keeping phone in reach) and compared this to a baseline condition, where the same participants were asked to minimize interruptions (disabling alerts, keeping phone out of sight). The results show that with maximized interruptions, participants reported higher levels of inattention and hyperactivity -- symptoms associated with ADHD.
@cite_4
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As smartphones increasingly pervade our daily lives, people are ever more interrupted by alerts and notifications. Using both correlational and experimental methods, we explored whether such interruptions might be causing inattention and hyperactivity-symptoms associated with Attention Deficit Hyperactivity Disorder (ADHD) even in people not clinically diagnosed with ADHD. We recruited a sample of 221 participants from the general population. For one week, participants were assigned to maximize phone interruptions by keeping notification alerts on and their phones within their reach sight. During another week, participants were assigned to minimize phone interruptions by keeping alerts off and their phones away. Participants reported higher levels of inattention and hyperactivity when alerts were on than when alerts were off. Higher levels of inattention in turn predicted lower productivity and psychological well-being. These findings highlight some of the costs of ubiquitous connectivity and suggest how people can reduce these costs simply by adjusting existing phone settings. A common assumption in studies of interruptions is that one is focused in an activity and then distracted by other stimuli. We take the reverse perspective and examine whether one might first be in an attentional state that makes one susceptible to communications typically associated with distraction. We explore the confluence of multitasking and workplace communications from three temporal perspectives -- prior to an interaction, when tasks and communications are interleaved, and at the end of the day. Using logging techniques and experience sampling, we observed 32 employees in situ for five days. We found that certain attentional states lead people to be more susceptible to particular types of interaction. Rote work is followed by more Facebook or face-to-face interaction. Focused and aroused states are followed by more email. The more time in email and face-fo-face interaction, and the more total screen switches, the less productive people feel at the day's end. We present the notion of emotional homeostasis along with new directions for multitasking research. It is well documented that interacting with a mobile phone is associated with poorer performance on concurrently performed tasks because limited attentional resources must be shared between tasks. However, mobile phones generate auditory or tactile notifications to alert users of incoming calls and messages. Although these notifications are generally short in duration, they can prompt task-irrelevant thoughts, or mind wandering, which has been shown to damage task performance. We found that cellular phone notifications alone significantly disrupted performance on an attention-demanding task, even when participants did not directly interact with a mobile device during the task. The magnitude of observed distraction effects was comparable in magnitude to those seen when users actively used a mobile phone, either for voice calls or text messaging. (PsycINFO Database Record Keywords: Driver distraction; Language: en Smartphone users might be interrupted while interacting with an application, either by intended or unintended circumstances. In this paper, we report on a large-scale observational study that investigated mobile application interruptions in two scenarios: (1) intended back and forth switching between applications and (2) unintended interruptions caused by incoming phone calls. Our findings reveal that these interruptions rarely happen (at most 10 of the daily application usage), but when they do, they may introduce a significant overhead (can delay completion of a task by up to 4 times). We conclude with a discussion of the results, their limitations, and a series of implications for the design of mobile phones. Social norm has it that people are expected to respond to mobile phone messages quickly. We investigate how attentive people really are and how timely they actually check and triage new messages throughout the day. By collecting more than 55,000 messages from 42 mobile phone users over the course of two weeks, we were able to predict people's attentiveness through their mobile phone usage with close to 80 accuracy. We found that people were attentive to messages 12.1 hours a day, i.e. 84.8 hours per week, and provide statistical evidence how very short people's inattentiveness lasts: in 75 of the cases mobile phone users return to their attentive state within 5 minutes. In this paper, we present a comprehensive analysis of attentiveness throughout each hour of the day and show that intelligent notification delivery services, such as bounded deferral, can assume that inattentiveness will be rare and subside quickly. Human multitasking is often the result of self-initiated interruptions in the performance of an ongoing task. These self-interruptions occur in the absence of external triggers such as electronic alerts or email notifications. Compared to externally induced interruptions, self-interruptions have not received enough research attention. To address this gap, this paper develops a typology of self-interruptions based on the integration of Flow Theory and Self-regulation Theory. In this new typology, the two major categories stem from positive and negative feelings of task progress and prospects of goal attainment. The proposed classification is validated in an experimental multitasking environment with pre-defined tasks. Empirical findings indicate that negative feelings trigger more self-interruptions than positive feelings. In general, more self-interruptions result in lower accuracy in all tasks. The results suggest that negative internal triggers of self-interruptions unleash a downward spiral that may degrade performance. We describe a study on the influence of instant messaging (IM) on ongoing computing tasks. The study both replicates and extends earlier work on the cost of sending notifications at different times and the sensitivity of different tasks to interruption. We investigate alternative hypotheses about the nature of disruption for a list evaluation task, an activity identified as being particularly costly to interrupt. Our findings once again show the generally disruptive effects of IM, especially during fast, stimulus-driven search tasks. In addition, we show that interruptions coming early during a search task are more likely to result in the user forgetting the primary task goal than interruptions that arrive later on. These findings have implications for the design of user interfaces and notification policies that minimize the disruptiveness of notifications. Visual attention is highly fragmented during mobile interactions, but the erratic nature of attention shifts currently limits attentive user interfaces to adapting after the fact, i.e. after shifts have already happened. We instead study attention forecasting - the challenging task of predicting users' gaze behaviour (overt visual attention) in the near future. We present a novel long-term dataset of everyday mobile phone interactions, continuously recorded from 20 participants engaged in common activities on a university campus over 4.5 hours each (more than 90 hours in total). We propose a proof-of-concept method that uses device-integrated sensors and body-worn cameras to encode rich information on device usage and users' visual scene. We demonstrate that our method can forecast bidirectional attention shifts and predict whether the primary attentional focus is on the handheld mobile device. We study the impact of different feature sets on performance and discuss the significant potential but also remaining challenges of forecasting user attention during mobile interactions. We describe initial results from an ongoing project to use mobile phone sensors to detect stress related situations1. The questions that we address in this stage of our work in progress is whether differences between stressful and non stressful periods can be detected in information readily available on a smartphone such as location traces, BlueTooth devices seen during the day and phone call patterns. We present an experiment with 7 students who were monitored during a two week exam session (stressful situation) and the two following weeks (non stressful period). The results show that a behaviour modification can clearly be seen, although the exact interpretation and generalization requires further work and larger scale experiments. User attention is a scarce resource, and users are susceptible to interruption overload. Systems do not reason about the effects of interrupting a user during a task sequence. In this study, we measure effects of interrupting a user at different moments within task execution in terms of task performance, emotional state, and social attribution. Task models were developed using event perception techniques, and the resulting models were used to identify interruption timings based on a user's predicted cognitive load. Our results show that different interruption moments have different impacts on user emotional state and positive social attribution, and suggest that a system could enable a user to maintain a high level of awareness while mitigating the disruptive effects of interruption. We discuss implications of these results for the design of an attention manager. Much of the stress and strain of student life remains hidden. The StudentLife continuous sensing app assesses the day-to-day and week-by-week impact of workload on stress, sleep, activity, mood, sociability, mental well-being and academic performance of a single class of 48 students across a 10 week term at Dartmouth College using Android phones. Results from the StudentLife study show a number of significant correlations between the automatic objective sensor data from smartphones and mental health and educational outcomes of the student body. We also identify a Dartmouth term lifecycle in the data that shows students start the term with high positive affect and conversation levels, low stress, and healthy sleep and daily activity patterns. As the term progresses and the workload increases, stress appreciably rises while positive affect, sleep, conversation and activity drops off. The StudentLife dataset is publicly available on the web. Abstract In 2 experiments, the development of auditory selective attention in children was assessed. The participants, aged 5, 7, and 9 years, responded to target stimuli in the left ear for 1 series (ignoring the standard stimuli) and in the right ear for the other series. In Experiment 1, event-related potentials (ERPs) evoked by the auditory stimuli were recorded from frontal, central, and pariet al sites. The 9-year-olds showed a greater processing negativity (Nd) to the attended channel compared with the 5-year-olds. Both 7-and 9-year-olds showed significantly larger amplitudes for the P3 component of ERPs in the attended vs. ignored condition. Behaviorally, the 5-year-olds made fewer hits and more false alarms than did older children, and the 9-year-olds made significantly more false alarms than did the 7-year-olds. The results of Experiment 2 showed that the detriment in the performance of the 9-year-olds was a result of task parameters. The inability of 5-year-olds to attend selectively appears to ... Notifications on mobile phones alert users about new messages, emails, social network updates, and other events. However, little is understood about the nature and effect of such notifications on the daily lives of mobile users. We report from a one-week, in-situ study involving 15 mobile phones users, where we collected real-world notifications through a smartphone logging application alongside subjective perceptions of those notifications through an online diary. We found that our participants had to deal with 63.5 notifications on average per day, mostly from messengers and email. Whether the phone is in silent mode or not, notifications were typically viewed within minutes. Social pressure in personal communication was amongst the main reasons given. While an increasing number of notifications was associated with an increase in negative emotions, receiving more messages and social network updates also made our participants feel more connected with others. Our findings imply that avoiding interruptions from notifications may be viable for professional communication, while in personal communication, approaches should focus on managing expectations. We are increasingly in situations of divided attention, subject to interruptions, and having to deal with an abundance of information. Our cognitive load changes in these situations of divided attention, task interruption or multitasking; this is particularly true for older adults. To help mediate our finite attention resources in performing cognitive tasks, we have to be able to measure the real-time changes in the cognitive load of individuals. This paper investigates how to assess real-time cognitive load based on psycho-physiological measurements. We use two different cognitive tasks that test perceptual speed and visio-spatial cognitive processing capabilities, and build accurate models that differentiate an individual's cognitive load (low and high) for both young and older adults. Our models perform well in assessing load every second with two different time windows: 10 seconds and 60 seconds, although less accurately for older participants. Our results show that it is possible to build a real-time assessment method for cognitive load. Based on these results, we discuss how to integrate such models into deployable systems that mediate attention effectively. Recently, multitasking on smart phones during navigation has emerged as a problematic social behavior due to its potential danger. In this paper, we propose to alleviate the situation by employing a sensor system for obstacle detection and aid the multi-tasking user so that one can safely navigate and carry out the on-going secondary task as effectively as possible. As such, we have implemented an ultrasonic sensor system interfaced into the smart phone that can constantly appraise the user of the incoming obstacles. We ran experiments to validate our approach, checking whether such a system would help user bump less into obstacles than without, and observe their multitasking behavior such as the physical attentional switch. Our experiments have shown that with the aid of the sensor system, the user's attention switch was significantly reduced, however, there was no differences in the performance (e.g. no. of collision) because the momentary strategic spatial and path planning was quite effective with slow pace and light pedestrian traffic. We conclude therefore human dual or multitasking ability is sufficient to overlap "casual" video watching and "slow" navigation. However, with more stringent task, e.g. text messaging and heavier traffic, we expect the reduced attention shift to ultimately improve the performance as well. Abstract This paper reports a simulator-based study of the effects of mobile phone use on driving performance. Changes in heart rate indicated that mobile phone use increases the cognitive demand experienced by drivers with, it is argued, consequent reduction in safety margins. However, experimental results also suggested that participants engaged in a process of risk compensation, with driving speed being slower at times of mobile phone conversation while the number of off-road excursions (OFFS) and collisions remained stable. There also was some evidence that the use of a hand-held mobile phone (when compared to a hands-free system) was associated with poorer driving performance. Implications for real world' driving are considered. Background: Ecological momentary assessment (EMA) is a useful method to tap the dynamics of psychological and behavioral phenomena in real-world contexts. However, the response burden of (self-report) EMA limits its clinical utility. Objective: The aim was to explore mobile phone-based unobtrusive EMA, in which mobile phone usage logs are considered as proxy measures of clinically relevant user states and contexts. Methods: This was an uncontrolled explorative pilot study. Our study consisted of 6 weeks of EMA unobtrusive EMA data collection in a Dutch student population (N=33), followed by a regression modeling analysis. Participants self-monitored their mood on their mobile phone (EMA) with a one-dimensional mood measure (1 to 10) and a two-dimensional circumplex measure (arousal valence, –2 to 2). Meanwhile, with participants’ consent, a mobile phone app unobtrusively collected (meta) data from six smartphone sensor logs (unobtrusive EMA: calls short message service (SMS) text messages, screen time, application usage, accelerometer, and phone camera events). Through forward stepwise regression (FSR), we built personalized regression models from the unobtrusive EMA variables to predict day-to-day variation in EMA mood ratings. The predictive performance of these models (ie, cross-validated mean squared error and percentage of correct predictions) was compared to naive benchmark regression models (the mean model and a lag-2 history model). Results: A total of 27 participants (81 ) provided a mean 35.5 days (SD 3.8) of valid EMA unobtrusive EMA data. The FSR models accurately predicted 55 to 76 of EMA mood scores. However, the predictive performance of these models was significantly inferior to that of naive benchmark models. Conclusions: Mobile phone-based unobtrusive EMA is a technically feasible and potentially powerful EMA variant. The method is young and positive findings may not replicate. At present, we do not recommend the application of FSR-based mood prediction in real-world clinical settings. Further psychometric studies and more advanced data mining techniques are needed to unlock unobtrusive EMA’s true potential. [J Med Internet Res 2016;18(3):e72] Attention deficit hypo-activity disorder (ADHD) comprises a deficit in behavioral inhibition. A theoretical model is constructed that links inhibition to 4 executive neuropsychological functions that appear to depend on it for their effective execution: (a) working memory, (b) self-regulation of affect-motivation-arousal, (c) internalization of speech, and (d) reconstitution (behavioral analysis and synthesis). Extended to ADHD, the model predicts that ADHD should be associated with secondary impairments in these 4 executive abilities and the motor control they afford. The author reviews evidence for each of these domains of functioning and finds it to be strongest for deficits in behavioral inhibition, working memory, regulation of motivation, and motor control in those with ADHD. Although the model is promising as a potential theory of self-control and ADHD, far more research is required to evaluate its merits and the many predictions it makes about ADHD. Research has shown that sustained attention or vigilance declines over time on task. Sustained attention is necessary in many environments such as air traffic controllers, cyber operators, and imagery analysts. A lapse of attention in any one of these environments can have harmful consequences. The purpose of this study was to determine if eye blink metrics from an eye-tracker are related to changes in vigilance performance and cerebral blood flow velocities. Nineteen participants performed a vigilance task while wearing an eye-tracker on four separate days. Blink frequency and duration changed significantly over time during the task. Both blink frequency and duration increased as performance declined and right cerebral blood flow velocity declined. These results suggest that eye blink information may be an indicator of arousal levels. Using an eye-tracker to detect changes in eye blinks in an operational environment would allow preventative measures to be implemented, perhaps by providing perceptual warning signals or augmenting human cognition through non-invasive brain stimulation techniques. Language: en Multitasking in user behavior can be represented along a continuum in terms of the time spent on one task before switching to another. In this paper, we present a theory of behavior along the multitasking continuum, from concurrent tasks with rapid switching to sequential tasks with longer time between switching. Our theory unifies several theoretical effects - the ACT-R cognitive architecture, the threaded cognition theory of concurrent multitasking, and the memory-for-goals theory of interruption and resumption - to better understand and predict multitasking behavior. We outline the theory and discuss how it accounts for numerous phenomena in the recent empirical literature.