Nathan Medeiros-Ward

Who Multi-Tasks and Why? Multi-Tasking Ability, Perceived Multi-Tasking Ability, Impulsivity, and Sensation Seeking

The present study examined the relationship between personality and individual differences in multi-tasking ability. Participants enrolled at the University of Utah completed measures of multi-tasking activity, perceived multi-tasking ability, impulsivity, and sensation seeking. In addition, they performed the Operation Span in order to assess their executive control and actual multi-tasking ability. The findings indicate that the persons who are most capable of multi-tasking effectively are not the persons who are most likely to engage in multiple tasks simultaneously. To the contrary, multi-tasking activity as measured by the Media Multitasking Inventory and self-reported cell phone usage while driving were negatively correlated with actual multi-tasking ability. Multi-tasking was positively correlated with participants’ perceived ability to multi-task ability which was found to be significantly inflated. Participants with a strong approach orientation and a weak avoidance orientation – high levels of impulsivity and sensation seeking – reported greater multi-tasking behavior. Finally, the findings suggest that people often engage in multi-tasking because they are less able to block out distractions and focus on a singular task. Participants with less executive control - low scorers on the Operation Span task and persons high in impulsivity - tended to report higher levels of multi-tasking activity.

An Investigation of Driver Distraction Near the Tipping Point of Traffic Flow Stability

Objective: The purpose of this study was to explore the interrelationship between driver distraction and characteristics of driver behavior associated with reduced highway traffic efficiency. Background: Research on the three-phase traffic theory and on behavioral driving suggests that a number of characteristics associated with efficient traffic flow may be affected by driver distraction. Previous studies have been limited, however, by the fact that researchers typically do not allow participants to change lanes, nor do they account for the impact of varying traffic states on driving performance. Methods: Participants drove in three simulated environments with differing traffic congestion while both using and not using a cell phone. Instructed only to obey the speed limit, participants were allowed to vary driving behaviors, such as those involving forward following distance, speed, and lane-changing frequency. Results: Both driver distraction and traffic congestion were found to significantly affect lane change frequency, mean speed, and the likelihood of remaining behind a slower-moving lead vehicle. Conclusions: This research suggests that the behavioral profile of “cell phone drivers,” which is often described as compensatory, may have far-reaching and unexpected consequences for traffic efficiency. Application: By considering the dynamic interplay between characteristics of traffic flow and driver behavior, this research may inform both public policy regarding in-vehicle cell phone use and future investigations of driving behavior.

Assessing cognitive distraction in the automobile

Objective: The objective was to establish a systematic framework for measuring and understanding cognitive distraction in the automobile. Background: Driver distraction from secondary in-vehicle activities is increasingly recognized as a significant source of injuries and fatalities on the roadway. Method: Across three studies, participants completed eight in-vehicle tasks commonly performed by the driver of an automobile. Primary, secondary, subjective, and physiological measures were collected and integrated into a cognitive distraction scale. Results: In-vehicle activities, such as listening to the radio or an audio book, were associated with a low level of cognitive workload; the conversation activities of talking to a passenger in the vehicle or conversing with a friend on a handheld or hands-free cell phone were associated with a moderate level of cognitive workload; and using a speech-to-text interfaced e-mail system involved a high level of cognitive workload. Conclusion: The research established that there are significant impairments to driving that stem from the diversion of attention from the task of operating a motor vehicle and that the impairments to driving are directly related to the cognitive workload of these in-vehicle activities. Moreover, the adoption of voice-based systems in the vehicle may have unintended consequences that adversely affect traffic safety. Application: These findings can be used to help inform scientifically based policies on driver distraction, particularly as they relate to cognitive distraction stemming from the diversion of attention to other concurrent activities in the vehicle.

Hierarchical control and driving.

We manipulated primary task predictability and secondary task workload in the context of driving an automobile. As the driving task became less predictable (by adding wind gusts), more attention was required to maintain lane position. When drivers concurrently engaged in a secondary cognitive task in the windy driving condition, attention was diverted from driving and the ability to maintain lane position was degraded. By contrast, when the driving task was predictable (no wind), lane maintenance actually improved when a secondary cognitive task diverted attention from driving. These data provide evidence for a hierarchical control network that coordinates an interaction between automatic, encapsulated routines and limited capacity attention.

The Impact of Eye Movements and Cognitive Workload on Lateral Position Variability in Driving

Objective: The objective of this work was to understand the relationship between eye movements and cognitive workload in maintaining lane position while driving. Background: Recent findings in driving research have found that, paradoxically, increases in cognitive workload decrease lateral position variability. If people drive where they look and drivers look more centrally with increased cognitive workload, then one could explain the decreases in lateral position variability as a result of changes in lateral eye movements. In contrast, it is also possible that cognitive workload brings about these patterns regardless of changes in eye movements. Method: We conducted three experiments involving a fixed-base driving simulator to independently manipulate eye movements and cognitive workload. Results: Results indicated that eye movements played a modest role in lateral position variability, whereas cognitive workload played a much more substantial role. Conclusions: Increases in cognitive workload decrease lane position variability independently from eye movements. These findings are discussed in terms of hierarchical control theory. Applications: These findings could potentially be used to identify periods of high cognitive workload during driving.

The Crosstalk Hypothesis: Why Language Interferes with Driving.

Performing two cognitive tasks at the same time can degrade performance for either domain-general reasons (e.g., both tasks require attention) or domain-specific reasons (e.g., both tasks require visual working memory). We tested predictions of these two accounts of interference on the task of driving while using language, a naturally occurring dual task. Using language and driving a vehicle use different perceptual and motor skills. As a consequence, a domain-general explanation for interference in this dual task appears most plausible. However, recent evidence from the language processing literature suggests that when people use language with motor content (e.g., language about actions) or visual content (e.g., language about visible objects and events), they engage their motor and perceptual systems in ways specifically reflecting the actions and percepts that the language is about. This raises the possibility that language might interfere with driving for domain-specific reasons when the language has visual or motor content. To test this, we had participants drive a simulated vehicle while simultaneously answering true-false statements that had motor, visual, or abstract content. A domain-general explanation for interference would predict greater distraction in each of these three conditions compared with control, while a domain-specific explanation would predict greater interference in the motor and visual conditions. Both of these predictions were borne out but on different measures of distraction, suggesting that language-driven distraction during driving and dual tasks involving language in general may be the result not only of domain-general causes but also specific interference caused by linguistic content.

On Supertaskers and the Neural Basis of Efficient Multitasking

The present study used brain imaging to determine the neural basis of individual differences in multitasking, the ability to successfully perform at least two attention-demanding tasks at once. Multitasking is mentally taxing and, therefore, should recruit the prefrontal cortex to maintain task goals when coordinating attentional control and managing the cognitive load. To investigate this possibility, we used functional neuroimaging to assess neural activity in both extraordinary multitaskers (Supertaskers) and control subjects who were matched on working memory capacity. Participants performed a challenging dual N-back task in which auditory and visual stimuli were presented simultaneously, requiring independent and continuous maintenance, updating, and verification of the contents of verbal and spatial working memory. With the task requirements and considerable cognitive load that accompanied increasing N-back, relative to the controls, the multitasking of Supertaskers was characterized by more efficient recruitment of anterior cingulate and posterior frontopolar prefrontal cortices. Results are interpreted using neuropsychological and evolutionary perspectives on individual differences in multitasking ability and the neural correlates of attentional control.

Gender Invariance in Multitasking A Comment on Mäntylä (2013)

-back task and concluded that gender differences in multitasking reflect spatial ability. Here, we suggest (a) that there are no gender differences in a ubiquitous real-world version of multitasking (i.e., talking on a cell phone while driving), (b) that the data reported by Mantyla do not, in fact, provide clear and unambiguous evidence for gender differences in multitasking, and (c) that individual differences in the ability to multitask are more likely associated with executive attention.First, in previous work, we (Watson & Strayer, 2010) examined individual differences in the ability to concur-rently operate a motor vehicle and talk on a cell phone, a multitasking activity engaged in by the majority of driv-ers on the roadway (AAA Foundation for Traffic Safety, 2011). Because driving involves spatial processing for route navigation and lane maintenance, it seems reason-able to look for gender differences in multitasking in this context. Table 1 presents difference scores for dual-task minus single-task performance in our 2010 study, sepa-rated by gender. It is important to note that there are no gender differences in multitasking ability (all

Shifting Eyes and Thinking Hard Keep Us in Our Lanes

Previous research suggests that performing a secondary, non-visual task while driving (such as conversing on a hands-free cell phone) may lead to a reduction in lateral vehicle movement. A plausible explanation for this counterintuitive finding involves scanning differences under differing cognitive load. The goal of this study was to dissociate the effects of visual scanning and workload on lateral vehicle control. Eighteen participants drove nine, five minute scenarios in a fixed based driving simulator under varying workload and guided fixation conditions. Consistent with previous finding, increased secondary task load decreased lateral vehicle movement. The active movement of eyes also led to reductions in lateral vehicle movement but only when drivers were concurrently performing one of the secondary tasks. These results suggest that scanning differences under cognitive load cannot fully account for observed reductions in lateral vehicle movement and that multiple interrelated factors likely contribute to lateral vehicle movement.

Dissociating Eye Movements and Workload on Lateral Lane Position Variability

Recent research suggests that performing a secondary, non-visual task while driving may lead to a reduction in lateral vehicle movement. A plausible explanation for this counterintuitive pattern involves the joint findings that (1) increased cognitive load disrupts eye movements, and (2) eye movements often precipitate steering input. However, a partial dissociation of these factors by Cooper et al. (2009) found that increases in workload and eye movements (at a constant eccentricity) both reduce lateral lane variability. This follow-up study examines the contribution of eye movement eccentricity, under varying workload, on lateral lane position variability. Thirty-two participants drove nine, five minute scenarios in a fixed based driving simulator under varying eye movement and workload conditions. Consistent with previous finding, increased workload led to a decrease in lateral vehicle movement. Interestingly, an effect of visual eccentricity on eye movements was only observed in one of the driving measures. This research suggests that the impact of eye movements on lateral vehicle movement is much smaller than previously hypothesized and that impact of workload is much greater even after accounting for lateral shifts in eye movements.