Running head: Media multitasking and cognitive control Accepted Pending Minor Revisions in the Journal of Experimental Psychology: Human Perception and Performance. Please Do Not Cite Without Permission The Association between Media Multitasking, Task-Switching, and Dual-Task Performance

The recent rise in media use has prompted researchers to investigate its influence on users’ basic cognitive processes, such as attention and cognitive control. However, most of these investigations have failed to consider that the rise in media use has been accompanied by an even more dramatic rise in media multitasking (engaging with multiple forms of media simultaneously). Here we investigate how one’s ability to switch between two tasks and to perform two tasks simultaneously is associated with media multitasking experience. Participants saw displays comprised of a number-letter pair and classified the number as odd or even and/or the letter as a consonant or vowel. In task-switching blocks, a cue indicated which classification to perform on each trial. In dual-task blocks, participants performed both classifications. Heavy and light media multitaskers showed comparable performance in the dual-task. Across two experiments, heavy media multitaskers were better able to switch between tasks in the taskswitching paradigm. Thus, while media multitasking was not associated with increased ability to process two tasks in parallel, it was associated with an increased ability to shift between discrete tasks. The Association Between 3 As technology has become more readily accessible and mobile, media use has increased dramatically. For example, in the past decade the amount of time US youth spend interacting with media has increased by about 20% to 8 hours per day (Rideout, Foehr, & Roberts, 2010). The ubiquitous use of media has also become a global phenomenon, involving individuals of all ages and occupations (Rogers, 2009). It has permeated the workplace and the classroom alike, and has transformed the way in which we interact and communicate (Benson, Johnson, & Kuchinke, 2002; Duhaney, 2000). This rise has prompted concern about the impact that media use is having on user’s mental health and brain function. This concern is buttressed by work demonstrating that prolonged exposure to an environment (Blakemore & Van Sluyters, 1975) and learning new skills (Draganski & May, 2008) can lead to dramatic cortical reorganization. Although research has not yet fully addressed whether media use is impacting mental health and cognition, initial reports suggest that this concern may be valid (Biocca, 2000). In the mental health field, it has been suggested that heavy media use is associated with decreased social well-being and impaired psychosocial functioning (Moody, 2001; Kraut, et al., 1998). Research in the education domain has found evidence that media use is impacting the way students process information and learn (Prensky, 2001). In addition, researchers in the cognitive domain suggest that extensive exposure to media and technology use are influencing basic cognitive processes. For instance, some argue that technologies such as mobile devices and vehicle navigation systems are lowering the need for human memory and spatial skills, thus reducing the cognitive effort required to complete daily tasks (Rogers, 2009). Recent work has suggested that the internet is becoming a primary form of external memory, thereby changing the way our brains remember information (Sparrow, Liu, & The Association Between 4 Wegner, 2011). Furthermore, several reports have provided evidence that the habitual use of one form of media, video games, can influence performance on a range of cognitive tasks and alter visual attention processes (Green & Bavelier, 2003). In short, a number of findings indicate the pervasive use of media may have profound influences on media users. To date, most of the research investigating the influence of media use on users has focused on the absolute amount of time spent with media, thereby ignoring a major trend that has accompanied the rise in media use: the simultaneous use of several media forms. While absolute time spent with media has increased, time spent multitasking with media has grown even more rapidly. Within the past decade, there has been a 120% increase in the time that youth between the ages of 8 and 18-years-old media multitask (Rideout, Foehr, & Roberts, 2010). This rapid increase in multitasking with media raises the question of whether this method of interacting with media may be influencing users’ mental health and cognitive systems. The few reports that have investigated the specific effect of media multitasking suggest that media multitasking is uniquely impacting both mental health and cognitive processes. In terms of mental health, a recent report suggested that multitasking with media is associated with higher symptoms of depression and social anxiety, even after accounting for overall media use (Becker, Alzahabi, & Hopwood, 2012). Also, increased media use, and particularly media multitasking, is associated with negative social well-being in young girls (Pea et al., 2012). In terms of cognitive processes, multitasking with media, particularly instant messaging, was found to have detrimental effects on academic performance in college students (Junco & Cotten, 2010); and people who frequently multitask with media have been reported to have a decreased ability to effectively filter irrelevant information (Ophir, Nass, & Wagner, 2009). The Association Between 5 In one of the few laboratory-based investigations of the association between media multitasking and cognition, Ophir, Nass, & Wagner (2009) found that heavy media multitaskers had difficulty switching back and forth between tasks in a commonly used task-switching paradigm. In the number-letter task-switching paradigm used by Ophir et al. (2009), participants were presented with a number-letter pair and had to classify either the number (as even or odd) or the letter (as a consonant or vowel). A cue informing participants about which classification to perform was presented just before the stimuli appeared on each trial. In some trials, the classification required was identical to the previous trial (a repeat trial), and in other trials, the classification was different from the previous trial (a switch trial). In this task, people generally take longer to perform the classification for switch trials than repeat trials, presumably because switch trials require one to mentally reconfigure the task set involved (Monsell, 2003). Using this task, Ophir and colleagues (2009) found that heavy media multitaskers showed an even greater task-switching cost than light media multitaskers. They suggested that this finding was counter-intuitive and striking, since it would imply that extensive practice with switching (between forms of media, in this case) produces a reduction, rather than a boost, in task-switching ability. One possible explanation of this counter-intuitive claim is to posit that frequent practice with multiple streams of media improves users’ ability to process streams of information in parallel, reducing the need for switching. This view is consistent with some recent work documenting a small population of “super-taskers” who are able to simultaneously drive and converse on a cell phone without showing any deficits (Watson & Strayer, 2010). This explanation suggests that media multitasking is akin to practicing parallel processing rather than task-switching. If so, there would be no reason to believe that heavy media multitaskers should show fewer task-switching costs, and might, in fact, show increased taskThe Association Between 6 switching costs in a lab-based task-switching paradigm. In the task-switching paradigm, two stimuli are presented, but the participant must respond to only one of the items. Processing the irrelevant item may require the inhibition of the irrelevant item in order to decide which response to make or may produce response conflict (particularly on incongruent trials in which the two stimuli are mapped to opposite button presses). Under either of these scenarios, one would expect greater task-switching costs for people who have increased ability to process both tasks in parallel. If this explanation is correct, heavy media multitaskers might show increased taskswitching costs because they are processing both tasks in parallel, leading to response conflict. At the same time the explanation predicts that heavy media multitaskers should actually perform better in a dual-task paradigm, in which they are asked to classify both stimuli. If heavy media multitaskers are able to perform dual-tasks more efficiently and only show deficits in a task-switching paradigm, then we would have support for the conclusion that extensive dual-task practice can lead to the ability to parallel process. Alternatively, if heavy media multitaskers show a task-switching deficit without a dual-task benefit, it would add additional evidence to Ophir and colleagues’ (2009) counterintuitive finding and suggest that extensive practice switching between multiple forms of media leads to an impairment in one’s ability to effectively switch attention to the pertinent information for one’s current task. To investigate these possibilities, we designed an experiment in which participants responded to blocks of task-switching and dual-task trials. The task-switch paradigm was similar to that used by Ophir, et al. (2009), in which participants switched between classifying numbers as odd or even and letters as consonant or vowel. Our dual-task paradigm consisted of the same number-letter task, but required participants to perform both classifications on each trial. If The Association Between 7 media multitasking results in parallel processing, we would expect that multitaskers would show deficits in a task-switching paradigm, but would show better dual-task performance.