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.

Stress can lead to an increase in smartphone use in the context of texting while walking.

Texting while walking (TWW) is a dangerous behavior that can lead to injury and even death. While several studies have examined the relationship between smartphone use and stress, to our knowledge no studies have yet investigated the relationship between stress and TWW. The objective of the present study was to investigate this relationship by examining the effects of stress on TWW, the effects of TWW on subsequent stress, and the effect of stress on multitasking performance. A total of 80 participants completed two sequential tasks in a laboratory while they walked on a treadmill and responded to a biological motion stimulus imitating the movement of another pedestrian. In the unrestricted task, participants were given the choice to use their personal phones. In the controlled task, they carried a text conversation with a research assistant while they walked and responded to the stimulus. Stress was measured via questionnaire and saliva collection for measure of cortisol (a stress hormone) before and after each task. Results show that greater psychological stress and cortisol variations were associated with a greater number of phone uses during the unrestricted task. Greater phone use during the unrestricted task was associated with lower subsequent psychological stress in women and total time of phone use was correlated with subsequent cortisol levels. Stress measured before the controlled task had no effect on multitasking performance, but participants with moderate performance were those with the highest cortisol levels. Our results suggest that stress could be a precursor to TWW and that it could affect a pedestrian's ability to stay safe when using their smartphone.

Analysis of Massive Online Medical Consultation Service Data to Understand Physicians' Economic Return: Observational Data Mining Study.

BACKGROUND: Online health care consultation has become increasingly popular and is considered a potential solution to health care resource shortages and inefficient resource distribution. However, many online medical consultation platforms are struggling to attract and retain patients who are willing to pay, and health care providers on the platform have the additional challenge of standing out in a crowd of physicians who can provide comparable services. OBJECTIVE: This study used machine learning (ML) approaches to mine massive service data to (1) identify the important features that are associated with patient payment, as opposed to free trial-only appointments; (2) explore the relative importance of these features; and (3) understand how these features interact, linearly or nonlinearly, in relation to payment. METHODS: The dataset is from the largest China-based online medical consultation platform, which covers 1,582,564 consultation records between patient-physician pairs from 2009 to 2018. ML techniques (ie, hyperparameter tuning, model training, and validation) were applied with four classifiers-logistic regression, decision tree (DT), random forest, and gradient boost-to identify the most important features and their relative importance for predicting paid vs free-only appointments. RESULTS: After applying the ML feature selection procedures, we identified 11 key features on the platform, which are potentially useful to predict payment. For the binary ML classification task (paid vs free services), the 11 features as a whole system achieved very good prediction performance across all four classifiers. DT analysis further identified five distinct subgroups of patients delineated by five top-ranked features: previous offline connection, total dialog, physician response rate, patient privacy concern, and social return. These subgroups interact with the physician differently, resulting in different payment outcomes. CONCLUSIONS: The results show that, compared with features related to physician reputation, service-related features, such as service delivery quality (eg, consultation dialog intensity and physician response rate), patient source (eg, online vs offline returning patients), and patient involvement (eg, provide social returns and reveal previous treatment), appear to contribute more to the patient's payment decision. Promoting multiple timely responses in patient-provider interactions is essential to encourage payment.

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.

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.

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.

The effects of confrontation and avoidance coping in response to workplace incivility.

Workplace incivility has significant adverse consequences for targets. However, we know remarkably little about how targets of incivility cope and even less about which coping strategies are effective. Drawing on the coping process of the transactional model of stress, we examine confrontation as a form of problem-focused coping and avoidance as a form of emotion-focused coping in response to incivility. We examine the effects of these coping strategies on reoccurrence of incivility, incivility enacted by targets, psychological forgiveness, and emotional exhaustion. Focusing on the target's perspective of a series of uncivil interactions between a target and perpetrator, we conducted a 3-wave study of employees from various occupations. Employing the critical incident technique, participants reported on an incident of workplace incivility, and then answered a series of questions over 3 waves of data collection regarding their interactions with this perpetrator. Our findings suggest that confrontation and avoidance are ineffective in preventing reoccurrence of incivility. Avoidance can additionally lead to increased emotional exhaustion, target-enacted incivility, and lower psychological forgiveness. However, confrontation coping has promise with regards to eliciting positive outcomes such as psychological forgiveness that are beneficial to interpersonal workplace relationships. (PsycINFO Database Record