What's that on Your Phone? Effects of Mobile Device Task Type on Pedestrian Performance.

BACKGROUND: The number of accidents due to distracted pedestrian is on the rise and many governments and institutions are enacting public policies which restrict texting while walking. However, pedestrians do more than just texting when they use their mobile devices on the go. OBJECTIVE: Exploring pedestrian multitasking, this paper aims to examine the effects of mobile device task type on pedestrian performance outcomes. METHOD: We performed two studies in lab simulations where 78 participants were asked to perform different tasks on a mobile device (playing a game, reading, writing an email, texting one person, group texting) while performing a pedestrian visual discrimination task while either standing or walking on a treadmill. Behavioral performance as well as neurophysiological data are collected. RESULTS: Results show that compared to a no-phone control, multitasking with any of the tasks on a mobile device leads to poor performance on a pedestrian visual discrimination task. Playing a game is the most cognitively demanding task and leads to the greatest performance degradation. CONCLUSION: Our studies show that multitasking with a mobile device has the potential to negatively impact pedestrian safety, regardless of task type. However, the impacts of different mobile device tasks are not all equivalent. More research is needed to tease out the different effects of these various tasks and to design mobile applications which effectively and safely capture pedestrians' attention. APPLICATION: Public policy, infrastructure, and smart technologies can be used to mitigate the negative effects of mobile multitasking. A more thorough understanding of mobile device task-specific factors at play can help tailor these counter-measures to better aid distracted pedestrians.

Is there collaboration specific neurophysiological activation during collaborative task activity? An analysis of brain responses using electroencephalography and hyperscanning.

Collaboration between two individuals is thought to be associated with the synchrony of two different brain activities. Indeed, prefrontal cortical activation and alpha frequency band modulation has been widely reported, but little is known about interbrain synchrony (IBS) changes occurring during social interaction such as collaboration or competition. In this study, we assess the dynamic of IBS variation in order to provide novel insights into the frequency band modulation underlying collaboration. To address this question, we used electroencephalography (EEG) to simultaneously record the brain activity of two individuals playing a computer-based game facing four different conditions: collaboration, competition, single participation, and passive observation. The computer-based game consisted of a fast button response task. Using data recorded in sensor space, we calculated an IBS value for each frequency band using both wavelet coherence transform and phase-locking value and performed single-subject analysis to compare each condition. We found significant IBS in frontal electrodes only present during collaboration associated with alpha frequency band modulation. In addition, we observed significant IBS in the theta frequency band for both collaboration and competition conditions, along with a significant single-subject cortical activity. Competition is distinguishable through single-subject activity in several regions and frequency bands of the brain. Performance is correlated with single-subject frontal activation during collaboration in the alpha and beta frequency band.

Measuring the Switch Cost of Smartphone Use While Walking.

This paper presents a study protocol to measure the task-switching cost of using a smartphone while walking. This method involves having participants walk on a treadmill under two experimental conditions: a control condition (i.e., simply walking) and a multitasking condition (i.e., texting while walking). During these conditions, the participants must switch between the tasks related to the experimental condition and a direction determining task. This direction task is done with a point-light walker figure, seemingly walking towards the left or the right of the participant. Performance on the direction task represents the participant's task-switching costs. There were two performance measures: 1) correct identification of the direction and 2) response time. EEG data are recorded in order to measure the alpha oscillations and cognitive engagement occurring during the task switch. This method is limited in its ecological validity: pedestrian environments have many stimuli occurring simultaneously and competing for attention. Nonetheless, this method is appropriate for pinpointing task-switching costs. The EEG data allow the study of the underlying mechanisms in the brain that are related to differing task-switching costs. This design allows the comparison between task switching when doing one task at a time, as compared to task switching when multitasking, prior to the stimulus presentation. This allows understanding and pinpointing both the behavioral and neurophysiological impact of these two different task-switching conditions. Furthermore, by correlating the task-switching costs with the brain activity, we can learn more about what causes these behavioral effects. This protocol is an appropriate base for studying the switching cost of different smartphone uses. Different tasks, questionnaires, and other measures can be added to it in order to understand the different factors involved in the task-switching cost of smartphone use while walking.

Using a smartphone while walking: The cost of smartphone-addiction proneness.

Distracted walking is an ever-increasing problem. Studies have already shown that using a smartphone while walking impairs attention and increases the risk of accidents. This study seeks to determine if smartphone-addiction proneness magnifies the risks of using a smartphone while walking. In an experimental design, participants, while walking on a treadmill and engaged in a smartphone task, were required to switch tasks by responding to an external stimulus, i.e., determining the direction of movement of a point-light walker. Participants were chosen to cover a range of smartphone-addiction proneness. Four smartphone-use conditions were simulated: a control condition with no smartphone-use, an individual conversation condition, a gaming condition, and a group conversation condition. Our results show that using a smartphone while walking decreases accuracy and increases the number of missed stimuli. Moreover, participants with higher smartphone-addiction proneness scores were also prone to missing more stimuli, and this effect was found regardless of experimental condition. The effect of the smartphone task on accuracy and the number of missed stimuli was mediated by the emotional arousal caused by the smartphone task. Smartphone-addiction proneness was positively correlated with a declared frequency of smartphone use while walking. Furthermore, of all the smartphone tasks, the gaming condition was found to be the most distracting.

Random forests for homogeneous and non-homogeneous Poisson processes with excess zeros.

We propose a general hurdle methodology to model a response from a homogeneous or a non-homogeneous Poisson process with excess zeros, based on two forests. The first forest in the two parts model is used to estimate the probability of having a zero. The second forest is used to estimate the Poisson parameter(s), using only the observations with at least one event. To build the trees in the second forest, we propose specialized splitting criteria derived from the zero truncated homogeneous and non-homogeneous Poisson likelihood. The particular case of a homogeneous process is investigated in details to stress out the advantages of the proposed method over the existing ones. Simulation studies show that the proposed methods perform well in hurdle (zero-altered) and zero-inflated settings, for both homogeneous and non-homogeneous processes. We illustrate the use of the new method with real data on the demand for medical care by the elderly.

Does Reducing Sedentarity With Standing Desks Hinder Cognitive Performance?

OBJECTIVE: The goal of this study was to determine if using a standing desk would affect the productivity of workers, based on the type of work they perform. BACKGROUND: Standing desks are a promising new health intervention in the workplace, but users and employers often require more specific recommendations related to productivity, such as the type of work that is more suited for the standing desk. METHOD: Thirty-seven young and healthy adults performed eight cognitive tasks in a 2 × 2 × 2 within-subject design of the following independent variables: posture (sitting/standing), task difficulty (easy/hard), and input device (computer mouse/tactile screen) in a counterbalanced order. RESULTS: Our results revealed that using a standing desk had no negative effect on performance or perception, but it did lead to increased brain activity in the alpha band for the parietal region (ß = 0.186, p = .001). CONCLUSION: We conclude that users of standing desks can freely stand for any level of task difficulty for work that involves working memory. However, more research is needed to generalize these results to other types of cognitive abilities and prolonged use of standing desks. APPLICATION: Our results simplify recommendations for workers as they do not need to worry about the type of work they are performing when using a standing desk.

Toward a Hybrid Passive BCI for the Modulation of Sustained Attention Using EEG and fNIRS.

We report results of a study that utilizes a BCI to drive an interactive interface countermeasure that allows users to self-regulate sustained attention while performing an ecologically valid, long-duration business logistics task. An engagement index derived from EEG signals was used to drive the BCI while fNIRS measured hemodynamic activity for the duration of the task. Participants (n = 30) were split into three groups (1) no countermeasures (NOCM), (2) continuous countermeasures (CCM), and (3) event synchronized, level-dependent countermeasures (ECM). We hypothesized that the ability to self-regulate sustained attention through a neurofeedback mechanism would result in greater task engagement, decreased error rate and improved task performance. Data were analyzed by wavelet coherence analysis, statistical analysis, performance metrics and self-assessed cognitive workload via RAW-TLX. We found that when the BCI was used to deliver continuous interface countermeasures (CCM), task performance was moderately enhanced in terms of total 14,785 (σ = 423) and estimated missed sales 7.46% (σ = 1.76) when compared to the NOCM 14,529 (σ = 510), 9.79% (σ = 2.75), and the ECM 14,180 (σ = 875), 9.62% (σ = 4.91) groups. An "actions per minute" (APM) metric was used to determine interface interaction activity which showed that overall the CCM and ECM groups had a higher APM of 3.460 (SE = 0.140) and 3.317 (SE = 0.139) respectively when compared with the NOCM group 2.65 (SE = 0.097). Statistical analysis showed a significant difference between ECM - NOCM and CCM - NOCM (p < 0.001) groups, but no significant difference between the ECM - CCM groups. Analysis of the RAW-TLX scores showed that the CCM group had lowest total score 7.27 (σ = 3.1) when compared with the ECM 9.7 (σ = 3.3) and NOCM 9.2 (σ = 3.4) groups. No statistical difference was found between the RAW-TLX or the subscales, except for self-perceived performance (p < 0.028) comparing the CCM and ECM groups. The results suggest that providing a means to self-regulate sustained attention has the potential to keep operators engaged over long periods, and moderately increase on-task performance while decreasing on-task error.

Texting while walking: An expensive switch cost.

Texting while walking has been highlighted as a dangerous behavior that leads to impaired judgment and accidents. This impairment could be due to task switching which involves activation of the present task and the inhibition of the previous task. However, the relative contributions of these processes and their brain activity have not yet been studied. We addressed this gap by asking participants to discriminate the orientation of an oncoming human shape in a virtual environment while they were: i) walking on a treadmill, or ii) texting while walking on a treadmill. Participants' performance (i.e., correctly identifying if a walker would pass them to their left or right) and electroencephalography (EEG) data was collected. Unsurprisingly, we found that participants performed better while they were only walking than when texting while walking. However, we also found that the diminished performance is differently related to task set inhibition and task set activation in the two conditions. The alpha oscillations, which can be used as an index of task inhibition, have a significantly different relation to performance in the two conditions, the relation being negative when subjects are texting. This may indicate that the more inhibition is needed, the more the performance is affected by texting. To our knowledge, this is the first study to investigate the brain signature of task switching in texting while walking. This finding is the first step in identifying the source of impaired judgment in texting pedestrians and in finding viable solutions to reduce the risks.

Dynamic Threshold Selection for a Biocybernetic Loop in an Adaptive Video Game Context.

Passive Brain-Computer interfaces (pBCIs) are a human-computer communication tool where the computer can detect from neurophysiological signals the current mental or emotional state of the user. The system can then adjust itself to guide the user toward a desired state. One challenge facing developers of pBCIs is that the system's parameters are generally set at the onset of the interaction and remain stable throughout, not adapting to potential changes over time such as fatigue. The goal of this paper is to investigate the improvement of pBCIs with settings adjusted according to the information provided by a second neurophysiological signal. With the use of a second signal, making the system a hybrid pBCI, those parameters can be continuously adjusted with dynamic thresholding to respond to variations such as fatigue or learning. In this experiment, we hypothesize that the adaptive system with dynamic thresholding will improve perceived game experience and objective game performance compared to two other conditions: an adaptive system with single primary signal biocybernetic loop and a control non-adaptive game. A within-subject experiment was conducted with 16 participants using three versions of the game Tetris. Each participant plays 15 min of Tetris under three experimental conditions. The control condition is the traditional game of Tetris with a progressive increase in speed. The second condition is a cognitive load only biocybernetic loop with the parameters presented in Ewing et al. (2016). The third condition is our proposed biocybernetic loop using dynamic threshold selection. Electroencephalography was used as the primary signal and automatic facial expression analysis as the secondary signal. Our results show that, contrary to our expectations, the adaptive systems did not improve the participants' experience as participants had more negative affect from the BCI conditions than in the control condition. We endeavored to develop a system that improved upon the authentic version of the Tetris game, however, our proposed adaptive system neither improved players' perceived experience, nor their objective performance. Nevertheless, this experience can inform developers of hybrid passive BCIs on a novel way to employ various neurophysiological features simultaneously.

A cluster randomized controlled Trial to Evaluate an Ambulatory primary care Management program for patients with dyslipidemia: the TEAM study.

BACKGROUND: Few studies have reported the efficacy of collaborative care involving family physicians and community pharmacists for patients with dyslipidemia. METHODS: We randomly assigned clusters consisting of at least two physicians and at least four pharmacists to provide collaborative care or usual care. Under the collaborative care model, pharmacists counselled patients about their medications, requested laboratory tests, monitored the effectiveness and safety of medications and patients' adherence to therapy, and adjusted medication dosages. After 12 months of follow-up, we assessed changes in low-density lipoprotein (LDL) cholesterol (the primary outcome), the proportion of patients reaching their target lipid levels and changes in other risk factors. RESULTS: Fifteen clusters representing a total of 77 physicians and 108 pharmacists were initially recruited, and a total of 51 physicians and 49 pharmacists were included in the final analyses. The collaborative care teams followed a total of 108 patients, and the usual care teams followed a total of 117 patients. At baseline, mean LDL cholesterol level was higher in the collaborative care group (3.5 v. 3.2 mmol/L, p = 0.05). During the study, patients in the collaborative care group were less likely to receive high-potency statins (11% v. 40%), had more visits with health care professionals and more laboratory tests, were more likely to have their lipid-lowering treatment changed and were more likely to report lifestyle changes. At 12 months, the crude incremental mean reduction in LDL cholesterol in the collaborative care group was -0.2 mmol/L (95% confidence interval [CI] -0.3 to -0.1), and the adjusted reduction was -0.05 (95% CI -0.3 to 0.2). The crude relative risk of achieving lipid targets for patients in the collaborative care group was 1.10 (95% CI 0.95 to 1.26), and the adjusted relative risk was 1.16 (95% CI 1.01 to 1.34). INTERPRETATION: Collaborative care involving physicians and pharmacists had no significant clinical impact on lipid control in patients with dyslipidemia. International Standard Randomized Controlled Trial register no. ISRCTN66345533.

Safety impacts due to the incompatibility of SUVs, minivans, and pickup trucks in two-vehicle collisions.

This research sets out to estimate the effects of vehicle incompatibility on the risk of death or major injury to drivers involved in two-vehicle collisions. Based on data for 2,999,395 drivers, logistic regression was used to model the risk of driver death or major injury (defined has being hospitalized). Our analyses show that pickup trucks, minivans and sport utility vehicles (SUVs) are more aggressive than cars for the driver of the other vehicle and more protective for their own drivers. The effect of the pickups is more pronounced in terms of aggressivity. The point estimates are comparable to those in the Toy and Hammitt study [Toy, E.L., Hammitt, J.K., 2003. Safety impacts of SUVs, minivans, and pickup trucks in two-vehicle crashes. Risk Analysis 23, 641-650], but, in contrast to that study, we are now able to establish that a greater number of these effects are statistically significant with a larger sample size. Like vehicle mass and type, other characteristics of drivers and the circumstances of the collision influence the driver's condition after impact. Male drivers, older drivers, drivers who are not wearing safety belts, collisions occurring in a higher speed zone and head-on collisions significantly increase the risk of death. Except for the driver's sex, all of these categories are also associated with an increased risk of death or of being hospitalized after being involved in a two-vehicle collision. For this risk, a significant increase is associated with female drivers.