Organization behavior
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Who Multi-Tasks and Why? Multi-Tasking Ability, Perceived Multi-Tasking Ability, Impulsivity, and Sensation Seeking David M. Sanbonmatsu, David L. Strayer*, Nathan Medeiros-Ward, Jason M. Watson
Department of Psychology, University of Utah, Salt Lake City, Utah, United States of America
Abstract
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.
Citation: Sanbonmatsu DM, Strayer DL, Medeiros-Ward N, Watson JM (2013) Who Multi-Tasks and Why? Multi-Tasking Ability, Perceived Multi-Tasking Ability, Impulsivity, and Sensation Seeking. PLoS ONE 8(1): e54402. doi:10.1371/journal.pone.0054402
Editor: Chris Chambers, Cardiff University, United Kingdom
Received September 25, 2012; Accepted December 11, 2012; Published January 23, 2013
Copyright: � 2013 Sanbonmatsu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This research was supported by a grant from the American Automobile Association Foundation for Traffic Safety. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: [email protected]
Introduction
People are not always content doing one thing at a time.
Frequently, they multi-task, that is, they engage in multiple tasks
aimed at attaining multiple goals simultaneously. Multi-tasking
involves concurrent performance of two or more functionally
independent tasks with each of the tasks having unique goals
involving distinct stimuli (or stimulus attributes), mental transfor-
mation, and response outputs. Although multi-tasking is common-
place, relatively little is known about when and why people
perform more than one attention-demanding task at a time.
Related to this, little is known about who is most likely to multi-
task. Our research represents an initial examination of important
factors contributing to multi-tasking behavior. We investigated
both the predictors of general multi-tasking and the predictors of a
specific and potentially dangerous form of multi-tasking – the
usage of cellular communications while driving. Decision theory
suggests that people should multi-task when they are good at it and
expect to benefit from it. However, we hypothesize that there are
important motivations and processes contributing to multi-tasking
that have little to do with people’s proficiencies.
Multi-tasking enables people to achieve more goals and to
experience more activities. However, engaging in multiple
attention demanding tasks simultaneously may be cognitively
and physically taxing. Moreover, performance on individual tasks
may suffer such that errors are made and overall productivity is
diminished. Research on decision making [1–3] indicates that the
willingness to multi-task should be contingent, in part, on the
expected outcomes or consequences. Generally, the people who
should be most likely to engage in multiple tasks are those who are
good at multi-tasking and who expect the highest rewards and
lowest costs. The most effective and efficient multi-taskers should
be those who are able to exercise a high level of executive control.
Models of executive attention highlight the role of the frontally
mediated capacity to maintain task goals and to avoid conflicting
distractions [4,5]. Executive attention is central to multi-tasking
because the information and goals relevant to one task must be
actively maintained while other tasks are performed. Additionally,
when task switching occurs, interference from the representations
and stimuli associated with the off task must be minimized. A
simple but elegant measure of working memory and executive
functioning is the Operation Span (OSPAN) task developed by
Engle [6]. The OSPAN task is actually two distinct tasks (memory
and math) that are performed concurrently, have distinct stimuli
(letters and numbers), have different mental transformations
(memorization and arithmetic), have different response outputs
(memory recall accuracy and math verification accuracy) that are
scored independently (i.e., there is a score for memory perfor-
mance and a score for math performance and the two scores are
independent). That is, the OSPAN task is a classic example of
multi-tasking wherein people must simultaneously attempt to
perform two independent tasks that compete for limited capacity
attention [7].
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The notion that people multi-task because they are good at it is
challenged by the important work of Ophir, Nass, and Wagner [8]
who examined the cognitive abilities of chronic multi-taskers.
These researchers developed the Media Survey Questionnaire to
measure media related multi-tasking and to identify individuals
who frequently engage in multiple tasks concurrently. Ophir et al.
[8] found that persons who frequently multi-task actually exhibited
greater switching costs while performing dual tasks than infrequent
multi-taskers. Moreover, chronically high multi-taskers were more
readily distracted by both irrelevant external stimuli and recently
activated internal representations during singular task perfor-
mance. Thus, research suggests that the persons who most
frequently multi-task may be those who are the least cognitively
equipped to effectively carry out multiple tasks simultaneously.
A more proximal determinant of multi-tasking may be the
perceived ability to multi-task. The goals that people pursue and
the tasks that they undertake are heavily influenced by their
conceptions of their traits and their abilities. When individuals
believe that they are capable of multi-tasking successfully, they
should be more apt to take on multiple tasks simultaneously.
Interestingly, self-conceptions of multi-tasking ability and actual
multi-tasking ability may not always work hand in hand to
influence decision making. In many behavioral domains, beliefs
about the self have been found to be only weakly correlated with
actual abilities and traits [9]. This disconnect exists, in part,
because people overestimate the favorableness of their personal
qualities. For example, research has shown that most people
perceive themselves to be more physically attractive than average
[10], better drivers than average [11], and better leaders than
average [12] despite the obvious truth that most people are
average on these dimensions. These findings suggest that people
may generally overestimate their ability to multi-task relative to
others and that the persons who may be most willing to engage in
multiple attention demanding tasks are those who are the most
overconfident about their capabilities.
Generally, multi-tasking will entail greater potential rewards
and greater potential losses than engagement in a singular task.
Individuals, of course, vary significantly in their chronic disposition
toward rewards vs. punishments [13]. Persons with a strong
approach orientation, that is, a strong reward or gain focused
motivational orientation, may be especially enticed to take on
multiple tasks because of the high potential rewards. In contrast,
persons who are avoidance oriented, that is, who are risk averse
and sensitive to losses or punishments, may be more inclined to
focus on a singular task rather than multi-task because of the
higher potential losses and greater effort associated with trying to
do more.
One personality trait that has shown to be been strongly
associated with the approach and avoidance orientations that may
affect the willingness to multi-task is impulsivity. Impulsivity is a
complex construct that is commonly defined a ‘‘as a predisposition
toward rapid, unplanned reactions to internal or external stimuli
without regard to the negative consequences of these reactions’’
[14]. Studies have shown that impulsive individuals are generally
more reward oriented [15,16] and more responsive to the goals
and positive outcomes that are salient in a context than individuals
low in impulsivity [17,18]. At the same time, impulsive individuals
are more apt to engage in risky behavior [19,20], and, hence, may
be less sensitive to the potential losses or costs of taking on multiple
activities.
One of the important rewards that may motivate people to
multi-task is the stimulation afforded by multiple task engagement.
People may often choose to multi-task because it is more
interesting and challenging, and less boring than performing a
singular task. In some instances, they may take on several tasks for
the sheer enjoyment of it, even if their overall productivity suffers.
Thus, workers commonly listen to music or news while performing
a boring job even though it may be distracting and detrimental to
their performance. A personality trait that may be associated with
multi-tasking because of the stimulation that multiple tasks afford
is sensation seeking. Zuckerman [21] characterizes sensation
seeking as ‘‘…a trait defined by the seeking of varied, novel,
complex, and intense sensations and experiences and the
willingness to take physical, social, legal, and financial risks for
the sake of such experiences.’’ High sensation seekers may be
especially apt to multi-task for the sake of the more varied and
complex sensations that are afforded by multiple vs. singular tasks
[22,23]. Moreover, because they are less averse to losses [24,25],
they may be more likely than low sensation seekers to risk the costs
of multi-tasking in order to heighten the enjoyableness of their
experience.
In some instances, people may multi-task despite the potential
losses of doing more because they are unable to focus on a singular
task. Often, engagement in secondary tasks or routines is activated
by the context, specifically by current goals and the stimuli that are
present. People may multi-task in these situations because they are
unable to block out distractions and focus on their primary
endeavor. Individuals with deficits in executive functioning may be
especially apt to multi-task because of an inability to inhibit
secondary task engagement. Recent work by Cain and Mitroff
[26] also indicates that some individuals maintain a wider
attentional scope that contributes to distraction and involvement
in secondary task processing.
Interestingly, the persons who are best able to multi-task may
also be the persons who are best able to not multi-task. Individuals
with a high level of executive control should be able to minimize
the distractions and goal conflicts that are disruptive to task
switching and multi-task performance. At the same time, they
should be able to minimize the distractions and competing goals
that diminish singular task focus and that contribute to secondary
task involvement. This suggests that measures of executive
functioning such as OSPAN task performance could be associated
with greater multi-tasking ability and with lower multi-tasking
activity.
Impulsivity has been associated with lower executive function-
ing [27,28] and reduced behavioral inhibition [29]. This suggests
that highly impulsive individuals may have a diminished capacity
to block out distractions and focus on a primary task than
individuals low in impulsivity. Thus, impulsive individuals may
take on multiple tasks not only because they are more strongly
attracted to the rewards afforded by multi-tasking but also because
they are less able to inhibit secondary task engagement.
In the present study, we attempted to understand why people
multi-task by examining who tends to multi-task. Participants in
our study completed the Media Survey Questionnaire developed
by Ophir et al. [8]. Responses to the questionnaire were used to
calculate the media multi-tasking index, a measure of multi-tasking
in the media context [8]. Participants also reported the frequency
with which they engaged in a particular multi-tasking activity – the
usage of a cell phone while driving. At any daylight hour, over
10% of drivers on U.S. roadways are estimated to talk on their cell
phones [30]. Research has shown that that driving performance is
significantly degraded by cell phone conversations [31,32]. In fact,
the National Safety Council [33] estimates that a minimum of
24% of all accidents and fatalities on U.S. highways are caused by
distracted drivers. Thus, our study examined important predictors
of both general multi-tasking and a specific, socially-relevant form
of multi-tasking.
Who Multi-Tasks and Why?
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The research of Ophir, et al. [8] investigated the association
between multi-tasking activity and cognitive abilities that are likely
to be predictive of multi-tasking, such as task switching. Our study
examined more directly the extent to which multi-tasking ability
predicts multi-tasking activity by having participants engage in the
OSPAN task. Recall that the OSPAN task requires participants to
simultaneously perform two independent tasks that compete for
limited capacity attention and performance on the OSPAN task
has been shown to predict individual differences in real-world
multitasking ability [7]. We tested whether the individuals who
have the executive control necessary to perform multiple tasks
effectively are more apt to multi-task than persons lacking this
control.
Participants’ perceived ability to multi-task was also measured.
We were interested in whether people who believe they are good
as opposed to bad at multi-tasking are generally more likely to
multi-task and whether they are more apt to talk on a cell phone
while driving. A secondary aim was to examine whether multi-
tasking is a domain in which the correspondence between
perceived and actual ability is limited, and in which people are
overconfident.
Our study also examined whether the strong approach
orientation and weak inhibitions of impulsive individuals are
associated with more frequent multi-tasking behavior. Participants
completed the 11 th
version of the Barrett Impulsivity Scale [34],
which measures general impulsivity and three subcomponents:
motor impulsiveness - acting without thinking; attentional
impulsiveness – that inability to focus attention or concentrate;
and non-planning impulsiveness – a lack of future thinking or
forethought. We anticipated that motor and attentional impul-
siveness might be particularly highly associated with multi-tasking.
Finally, the Sensation Seeking Scale (SSS-V) [35] was admin-
istered to examine whether sensation seekers are more apt to
multi-task. This is a multidimensional measure consisting of four
interrelated subscales of boredom susceptibility - an aversion to
repetitive or boring tasks or people, disinhibition – seeking release
or disinhibited social behavior, experience seeking – the pursuit of
an unconventional lifestyle, and thrill and adventure seeking. We
anticipated that risk taking for the sake of varied sensations and
experiences would be associated with greater multi-tasking
activity.
Methods
Three hundred and ten undergraduates (176 female and 134
male) provided informed consent before participating in the
University of Utah IRB approved study for extra course credit.
Participants ranged in age from 18 to 44, with a median age of 21
(SD = 4.7).
Participants completed a series of questionnaires in the context
of a study of driving and driving attitudes. The first set of measures
assessed their level of cell phone use while driving. Participants
indicated ‘‘how often do you use your cell phone while driving?’’
on a 5 point scale anchored by never/rarely when I drive and every time
I drive. They were also asked to report the percentage of the time
they are on the phone while driving, if they use their cell phone
while driving.
The next set of measures assessed participants’ beliefs about
their multi-tasking abilities. Participants ranked their multi-tasking
ability relative to that of other college students on a percentage
scale on which 0 indicated I’m at the very bottom, 50 indicated I’m
exactly average, and 100 indicated I’m at the very top. They also ranked
their abilities relative to other adults in the general population on
the same percentage scale. Finally, participants reported ‘‘how
much difficulty do you have performing multiple tasks simulta-
neously’’ relative to other college students on a 5 point scale
anchored by much less difficulty than average and much more difficulty than
average. The self-assessments of multi-tasking ability were followed
by the two personality scales and the Media Use Questionnaire.
Barratt Impulsivity Scale (BIS) We administered the 11
th version of the BIS – a 30 item self-
report instrument designed to assess general impulsiveness [34].
The 11 th
version consists of 3 subscales measuring attentional
impulsiveness, motor impulsiveness, and non-planning impulsive-
ness (see [36–38] for validation of the three subtrait structure). The
scale has been shown to have strong internal consistency and
reliability, and is probably the most widely used measure of
impulsiveness in research and clinical settings [39].
Sensation Seeking Scale (SSS) The SSS is a self-report instrument designed to measure the
personality construct of sensation seeking [23]. The revised SSS-V
[35] consists of four 10 item subscales of boredom susceptibility,
disinhibition, experience seeking, and thrill and adventure seeking,
and is reported to have good psychometric properties [40].
Media Use Questionnaire The questionnaire of multi-media use developed by Ophir,
Nass, and Wagner [8] assesses the time spent using 12 different
forms of media: computer based applications such as word
processing, web surfing, print media, television, computer based
video, music, nonmusic audio, video or computer games, phone
voice calls, instant messaging, SMS (text messaging), and email.
Respondents report the total number of hours they spent using
each medium. In addition, they indicated the extent to which they
used each of the other types of media while engaging each primary
medium by responding most of the time, some of the time, a little of the
time, or never. Following Ophir et al. [8], text messaging was not
included as a possible primary medium because it could not be
accurately described in terms of hours of use. However, it was still
assessed as a secondary activity that could be engaged during the
use of a primary medium.
Operation Span Task (OSPAN) After completing the questionnaires, participants performed an
automated version of the Operation Span (OSPAN) task [41].
Participants were asked to remember a series of 2–5 letters that
were interspersed with 12 math problems in which an equation
and possible solution were presented for verification. They
indicated whether the solutions to the math problems were true
or false and recalled the letters in the order that they were
presented. For example, in one sequence, participants were
presented with ‘‘is (3/1) 2 1 = 2?’’ followed by ‘‘f’’ followed by
‘‘is (2 * 2) +1 = 4?’’ followed by ‘‘k’’ followed by a recall probe. Participants should have answered ‘‘true’’ and ‘‘false’’ to the math
problems when they were presented and recalled ‘‘f’’ and ‘‘k’’ in
the order that they were presented when probed. Trials were
pseudorandomized such that participants were unable to predict
the set size of upcoming equation–letter pairs. Participants were
given points equal to the set size when all of the letters in that set
were recalled correctly in serial order (i.e., an absolute span score).
Math accuracy was also tracked, and feedback was provided to
participants during the task. This feedback was intended to keep
problem-solving accuracy above 85% and to encourage partici-
pants’ compliance with the dual-task math/memory instructions of
the OSPAN task.
Who Multi-Tasks and Why?
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Results
The OSPAN task served as our measure of multi-tasking ability.
As noted above, the OSPAN task is actually two distinct tasks
(memory and math) that are performed concurrently, have distinct
stimuli (letters and numbers), have different mental transforma-
tions (memorization and arithmetic), have different response
outputs (memory recall accuracy and math verification accuracy)
that are scored independently. Following Unsworth et al. [41], 32
participants who failed to correctly verify at least 80 percent of the
math problems were excluded from the analysis (final n = 277; 156
males and 121 females). The number of memory words recalled in
the correct order were summed to determine the absolute OSPAN
task score. This is the measure most commonly used in the
literature [41] and the measure that was used in the primary
analyses. The absolute score was highly correlated with the total
score, r(276) = .88, p,.01, which sums all of the words correctly
recalled in serial order. The mean absolute score was 44 with a
standard deviation of 16, and the mean total score was 59 with a
standard deviation of 13.
Participants’ ranking of their multi-tasking ability relative to that
of other college students was highly correlated with their ranking
relative to adults in the general population, r(275) = .91, p,.01,
and their estimation of their difficulty in performing multiple tasks
simultaneously which was reversed scored, r(275) = .72, p,.01.
Their rankings of their multi-tasking ability relative to that of
adults in the general population was also highly correlated with
their estimation of their difficulty in performing multiple tasks
simultaneously, r(275) = .70, p,.01. Thus, there was a high degree
of convergence between the three measures of perceived multi-
tasking ability.
The two percentage estimates of relative ability were averaged
to create the primary measure of perceived multi-tasking ability
used in the analyses. The mean percentage estimate of multi-
tasking across all participants was 63.0 (SD = 19). A score of 50 on
the percentage estimate was ‘‘exactly average’’. A comparison of
the mean percentage estimate with 50 indicated that participants’
generally estimated their multi-tasking ability to be significantly
higher than average, t(276) = 11.4, p,.01. Fifty-four participants
estimated that their ability was below average, 30 estimated that
they were exactly average, and 193 estimated that they were above
average. Significantly more participants estimated that their multi-
tasking ability was better than average than would be expected by
chance (binomial test; p,.01). Thus, participants in our study
substantially overestimated their ability to multi-task relative to
others.
The inflated estimations relative to average were not the only
indicators that participants’ perceptions of their multi-tasking
ability were poorly grounded in reality. OSPAN task performance
was not significantly correlated with perceived multi-tasking
ability, r(275) = .08. Hence, participants who believed they were
more capable than others of performing multiple tasks simulta-
neously were not generally better at multi-tasking, as measured by
the OSPAN task, than participants who assessed their ability more
modestly.
An index of media multi-tasking (MMI) was derived from the
responses to the media use questionnaire using the following
formula developed by Ophir, Nass, and Wagner [8]:
MMI ~ X11
i~1
mi � hi htotal
In the formula, hi is the number of hours per week reportedly
spent using primary medium i and htotal is the total number of
hours per week spent with all primary media. mi was based on
participants’ estimations of time spent on other media activities
while engaged with a primary medium. Numeric values were
assigned to participants’ estimations as follows: 1 was assigned to
most of the time,.67 to some of the time,.33 to a little of the time, and 0 to
never. The sum of the estimated activities was the mi. To account
for the amount of time spent engaging in the primary medium or
activity, the MMI adjusts by dividing the sum of the activity by
htotal. The mean level of multi-tasking activity reported on the MMI
was 3.99 with a standard deviation of 1.80.
Participants reported the frequency with which they use their
cell phones while driving and the percentage of the time they are
on the phone while driving. The mean reported frequency of cell
phone use while driving was 2.08 on the 5 point scale with a
standard deviation of.97. The reported percentage of time on the
phone while driving was 13.3 with a standard deviation of 17.3.
The reported frequency of cell phone use while driving was
strongly correlated with the reported percentage of the time on the
phone while driving, r(275) = .61, p,.01. Because the estimated
percentage of time on the cell phone while driving was ostensibly
limited to participants who used their cell phone while driving and
because of the problems with the numerical figures reported by
some participants the first and more inclusive question (the
reported frequency of cell phone use while driving) was used in the
primary analysis. In reporting the percentage of the time spent on
the phone while driving, 70 participants provided figures in
decimals (e.g.,.25%). Rather than assuming that these were
estimations ranging from 0 to 1% of the time while driving, we
assumed that these participants failed to recognize that the
estimates were in percentages. Consequently, we ignored the
decimals in these participants’ figures. Treating these estimations
as whole numbers appears to be correct because it increased the
correlation between participants’ percentage estimates and scale
estimates of time spent on the phone while driving from r = .50 to
r = .61.
Media related multi-tasking as measured by the MMI and the
reported frequency of cell phone use while driving were positively
correlated, r(275) = .20, p,.01. This gives credence to the
assumption that both are measures of multi-tasking activity and
the willingness to multi-task. A series of correlations were
calculated to examine the linkage between multi-tasking activity
as reflected by the MMI and cell phone use while driving, and the
potential predictors of and contributors to multi-tasking. These
correlations are presented in Table 1.
Multi-tasking ability as measured by the OSPAN task was not
positively correlated with multi-tasking activity or cell phone use
while driving. In fact, multi-tasking activity as reflected by the
MMI and cell phone use while driving were significantly
negatively correlated with OSPAN task performance. In contrast,
multi-tasking and cell phone use while driving were positively
correlated with perceived multi-tasking ability. Hence, people who
believe that they are good as opposed to bad at multi-tasking are
more likely to engage in multiple tasks simultaneously and to use a
cell phone while driving.
Multi-tasking activity was significantly correlated with impul-
sivity as measured by the BIS 11. Thus, participants high in
impulsivity reported greater multi-tasking than participants low in
impulsivity. An examination of the subscale responses revealed
that multi-tasking activity was significantly correlated with both
attentional and motor impulsivity. Impulsivity was not significantly
related to reported cell phone usage while driving.
Who Multi-Tasks and Why?
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Finally, multi-tasking activity was significantly correlated with
sensation seeking as measured by the SSS. Sensation seeking was
similarly positively correlated with cell phone usage while driving.
Both multi-tasking activity and cell phone use while driving were
associated with the sensation seeking component of disinhibition.
A companion analysis contrasted participants scoring in the
upper or lower quartiles in multi-tasking activity. These data are
reported in Table 2. Participants in the upper quartile on the MMI
scored significantly lower on the OSPAN task and significantly
higher in perceived ability, attentional and non-planning compo-
nents of impulsivity, and the disinhibition component of sensation
seeking than participants in the lower quartile on the MMI. In
each case, the difference between groups was significant (p,.05)
and reflected a ‘‘medium’’ effect size (e.g., between.4 and.5) [42].
A similar analysis contrasting participants reporting high or low
concurrent use of a cell phone while driving is presented in
Table 3. Participants reporting high concurrent cell-phone use
while driving (i.e., concurrent use of a cell phone often, nearly
every time, or every time while driving) scored significantly lower
on the OSPAN task and significantly higher in the disinhibition
and thrill seeking sub-scales of sensation seeking than participants
reporting lower cell phone use while driving. (i.e., never or rarely
using a cell phone while driving). There was also a trend for high
cell phone users to report higher perceived ability (p = .058). In
each case, the difference between groups reflected a ‘‘medium’’
effect size (e.g., between.3 and.5) [42].
In a final analysis, we used linear regression to determine the
unique contributors to a) multi-tasking activity, and b) cell phone
use while driving. Here, we report the analysis using extreme
groups; note however, that a similar pattern was produced using
continuous measures of multi-tasking activity and cell phone use
while driving. Based upon the univariate analyses reported above,
we included multi-tasking ability (OSPAN), perceived multi-
tasking ability, attentional impulsivity, non-planning impulsivity,
and the disinhibition component of sensation seeking in the
regression analysis. The standardized beta coefficients for the two
regression analyses are provided in Table 4. For multi-tasking
activity, the regression was significant, F(1,5) = 9.5, p,.01,
R = 0.50, SE = 0.44. Examination of the beta coefficients indicates
that all but non-planning impulsivity were significant predictors of
multi-tasking activity. For cell phone use while driving, the
regression was significant, F(1,5) = 3.7, p,.01, R = 0.36, SE = 0.47.
Examination of the beta coefficients indicates that perceived ability
and the disinhibition component of sensation seeking were
significant predictors of the propensity to use a cell phone behind
the wheel of an automobile.
Discussion
The findings provide an understanding of who is most likely to
engage in multi-tasking and who is most likely to talk on the cell
Table 1. Correlations between multi-tasking activity, multi-tasking ability, perceived multi-tasking ability, impulsivity, and sensation seeking.
Measure Subcategory Multi-tasking Activity (MMI) Cell Phone Use While Driving
Multi-tasking ability (OSPAN) 2.19** 2.15*
Perceived multi-tasking ability .19** .15*
Impulsivity (BIS 11) .14* .00
Attentional impulsiveness .14* 2.03
Motor impulsiveness .14* .06
Non planning impulsiveness .09 2.02
Sensation Seeking (SSS) .12* .13*
Boredom susceptibility .06 .02
Disinhibition .19** .20**
Thrill & adventure seeking .03 .11
Experience seeking .04 2.01
N = 277. *Significant at .05 level. **Significant at .01 level. doi:10.1371/journal.pone.0054402.t001
Table 2. Means and standard deviations (in parentheses) for multi-tasking ability (OSPAN), perceived multi-tasking ability, impulsivity, and sensation seeking for participants in the upper and lower quartiles of multi-tasking activity (MMI).
Measure Subcategory Low MMI High MMI df t-score Cohen’s d
OSPAN 48.7 (16.0) 40.3 (16.3) 136 23.04** 0.52
Perceived ability
59.2 (19.5) 69.1 (16.8) 136 3.21** 0.55
Impulsivity 1.96 (0.30) 2.11 (0.32) 135 2.79** 0.48
Attentional 2.04 (0.41) 2.24 (0.46) 135 2.71** 0.46
Motor 1.91 (0.32) 2.01 (0.35) 135 1.75 0.30
Non planning 1.95 (0.39) 2.11 (0.41) 135 2.28* 0.40
Sensation seeking
1.43 (0.18) 1.51 (0.17) 135 2.51** 0.43
Boredom 1.23 (0.20) 1.28 (0.16) 135 1.44 0.28
Disinhibition 1.32 (0.26) 1.47 (0.30) 135 3.52** 0.53
Thrill Seeking 1.67 (0.28) 1.71 (0.29) 135 0.67 0.14
Experience 1.49 (0.24) 1.55 (0.22) 135 1.50 0.26
Also indicated are the degrees of freedom, t-test scores, and the effect size estimate, Cohen’s d. *Significant at .05 level. **Significant at .01 level. doi:10.1371/journal.pone.0054402.t002
Who Multi-Tasks and Why?
PLOS ONE | www.plosone.org 5 January 2013 | Volume 8 | Issue 1 | e54402
phone while driving. In examining who multi-tasks, the study
provides an initial understanding of why people multi-task.
The results indicate that the persons who chronically multi-task
are not those who are the most capable of multi-tasking effectively.
To the contrary, OSPAN task performance was negatively
correlated with self-reported multi-tasking activity. Perhaps more
alarmingly, OSPAN task performance was also negatively
correlated with self-reported usage of cellular communications
while driving. Thus, the persons who talk on the cell phone the
most while driving appear to be those who are the least capable of
multi-tasking. As we mentioned earlier, research has shown that
cell phone use significantly impairs driving performance [43,44]
and that over 24% of all accidents and fatalities on U.S. highways
may be caused by distracted drivers [33]. The negative relation
between cellular communication while driving and multi-tasking
ability appears to further bolster arguments for legislation limiting
the use of cell phones while operating a motor vehicle.
Both media related multi-tasking and cell phone usage while
driving were positively correlated with the perceived ability to
multitask. Perceptions of the ability to multi-task were found to be
badly inflated; in fact, the majority of participants judged
themselves to be above average in the ability to multi-task. These
estimations had little grounding in reality as perceived multi-
tasking ability was not significantly correlated with actual multi-
tasking ability as measured by the OSPAN task. Thus, it appears
that the persons who are most likely to multi-task and most apt to
use a cell phone while driving are those with the most inflated
views of their abilities.
The lack of concordance between perceived and actual
multitasking ability is not surprising given the well-documented
flaws characterizing self-assessments [9]. Research has shown that
the correspondence between judgments of personal abilities and
traits, and actual abilities and behavior is especially weak when the
task or domain is poorly defined [45,46] and when there is an
absence of immediate and objective performance feedback
[47,48]. The concept of multi-tasking may be somewhat nebulous
to laypersons. Moreover, the proper standards for assessing multi-
tasking ability are unclear and objective feedback about the
relative efficacy of performance is rarely received. Consequently,
self-assessments of this seemingly important and desirable personal
ability may be highly susceptible to bias.
Two important and interrelated personality traits were predic-
tive of multi-tasking activity in our study. High sensation seekers,
particularly those scoring high in disinhibition, were more likely
than low sensation seekers to report media related multi-tasking
and cell phone use while driving. As mentioned above, the
disinhibition component of sensation seeking is associated with
‘‘seeking release’’ or ‘‘disinhibited social behavior’’. Impulsivity,
both the attentional and non-planning components of impulsivity,
was also significantly correlated with higher levels of multi-tasking.
Across all analyses, multi-tasking was most strongly associated with
attentional impulsiveness. Thus, the people who are most likely to
multi-task appear to be those who have difficulty focusing
attention or concentrating on a single task.
The findings are consistent with our conceptualization of the
general determinants of multi-tasking. Generally, multiple tasks
present greater opportunity for rewards than singular tasks.
Consequently, individuals who are approach oriented and
attracted to the higher potential rewards of multi-tasking may be
especially motivated to engage in multiple tasks simultaneously.
Thus, impulsivity was significantly correlated with higher levels of
multi-tasking. Moreover, individuals who perceive their multi-
tasking ability to be high and thus, who are likely to anticipate the
greatest rewards from engaging in many tasks concurrently
reported greater multi-tasking activity. Finally, multiple tasks
generally afford greater stimulation and challenge than singular
tasks. Hence, high sensation seekers tended to report greater multi-
tasking activity than low sensation seekers.
People may refrain from multi-tasking because of the risks and
costs associated with taking on too much. Individuals who are less
sensitive or averse to the higher potential losses entailed by
multiple tasks may be more apt to multi-task. Thus, individuals
who perceive their multi-tasking ability to be high and who are
likely to anticipate the lowest costs or losses from engaging in many
tasks concurrently reported greater multi-tasking activity. Addi-
tionally, persons who react with limited consideration of the
negative consequences – high impulsives – reported greater multi-
Table 3. Means and standard deviations (in parentheses) for multi-tasking ability (OSPAN), perceived multi-tasking ability, impulsivity, and sensation seeking for participants in the upper and lower quartiles of cell phone use while driving.
Measure Subcategory Low Cell High Cell df t-score Cohen’s d
OSPAN 45.4 (15.8)38.8 (17.7) 142 22.36* 0.40
Perceived ability
59.7 (16.9)65.8 (21.1) 141 1.90 0.32
Impulsivity 2.07 (0.33)2.07 (0.32) 142 20.03 0.05
Attentional 2.21 (0.47)2.20 (0.31) 142 20.08 0.03
Motor 1.92 (0.31)1.94 (0.33) 142 0.46 0.06
Non planning 2.11 (0.46)2.09 (0.46) 142 20.30 0.04
Sensation seeking
1.43 (0.18)1.50 (0.15) 142 2.38* 0.40
Boredom 1.26 (0.19)1.27 (0.16) 142 0.32 0.06
Disinhibition 1.34 (0.25)1.48 (0.29) 142 3.16** 0.52
Thrill Seeking 1.61 (0.30)1.73 (0.26) 142 2.47** 0.43
Experience 1.51 (0.24)1.51(0.21) 142 0.12 0.00
Also indicated are the degrees of freedom, t-test scores, and the effect size estimate, Cohen’s d. *Significant at .05 level. **Significant at .01 level. doi:10.1371/journal.pone.0054402.t003
Table 4. Linear regression standardized Beta coefficients and corresponding t-scores for multi-tasking ability (OSPAN), perceived multi-tasking ability, attentional impulsivity, non- planning impulsivity, and disinhibition in predicting multi- tasking activity and cell phone use while driving.
Multi-tasking Activity Cell Phone & Driving
Beta t-score Beta t-score
OSPAN 20.246 23.40** 20.079 21.01
Perceived ability
0.327 4.19** 0.214 2.58**
Attentional impulsivity
0.222 2.56** 0.002 0.02
Non-planning impulsivity
0.070 0.86 0.101 0.12
Disinhibition 0.170 2.15* 0.208 2.54**
Beta refers to the standardized coefficients. *Significant at .05 level. **Significant at .01 level. doi:10.1371/journal.pone.0054402.t004
Who Multi-Tasks and Why?
PLOS ONE | www.plosone.org 6 January 2013 | Volume 8 | Issue 1 | e54402
tasking activity than low impulsives. Similarly, high sensation
seekers, particularly those high in the disinhibition component,
reportedly engage in greater multi-tasking than low sensation
seekers. Research suggests that high disinhibitors show evidence of
less excitability in response to threats or potential losses than low
disinhibitors [49]. Others studies have shown that sensation
seeking is generally associated with less negative appraisals of risky
situations, and lower levels of fear and anxiety [24,25]. Hence,
insensitivity to risk may generally contribute to multi-tasking and
the willingness of high sensation seekers to engage in multiple tasks
simultaneously.
Finally, people may engage in multi-tasking because they are
unable to block out distractions and focus on a singular task.
Consequently, individuals who are limited in the ability to inhibit
involvement in secondary activities may be especially likely to
multi-task. Consistent with this analysis, impulsivity was signifi-
cantly associated with greater multi-tasking activity. Moreover,
multi-tasking was shown to be particularly high amongst impulsive
individuals who act without thinking and who have difficulty
regulating their attention. Finally, individuals who scored low on
the OSPAN task and who presumably have lower working
memory capacity and executive control were more likely to engage
in multi-tasking than persons who scored high on the OSPAN
task. These findings clearly suggest that multi-tasking is a matter of
who is able to not multi-task as much as it is a matter of who is able
to multi-task.
The results are consistent with previous research by Ophir et al.
[8] who found that high chronic multi-taskers lack some of the
basic cognitive skills necessary for effective multi-tasking. Our
research extends this important work by providing more direct
evidence that lower multi-tasking ability is associated with greater
multi-tasking activity. Moreover, we extend the findings to an
important applied domain and show that drivers who talk on the
cell phone are not the most capable multi-taskers. Finally, the
negative correlation between OSPAN task performance and multi-
tasking activity provides direct evidence that deficits in working
memory and executive functioning are associated with higher
levels of multi-tasking.
The media multi-tasking index (MMI) developed by Ophir et al.
[8] was originally developed to assess the multiple forms of media
used simultaneously by respondents. It was not designed to be a
broad measure of everyday multitasking activity. Nevertheless,
because media use is ubiquitous, we believe that the level of usage
of multiple media is likely to be a good indicator of multi-tasking in
other behavioral domains. The significant correlation between the
MMI and a common and well known form of multi-tasking
behavior – the usage of cell phones while driving - increases our
confidence that general multi-tasking activity was measured.
As expected, impulsivity was significantly correlated with multi-
tasking activity as measured by the MMI. However, impulsivity
was not correlated with reported cell phone use while driving. For
many people, the usage of cell phones while driving may be a
premeditated behavior in which the decision to talk or not talk on
the cell phone is made beforehand. Thus, it may not typically be a
behavior requiring situational impulse control.
Sensation seeking and impulsivity have long been recognized to
be closely related personality constructs [22]. Thus, following
previous research [39], scores on the Sensation Seeking Scale were
significantly correlated with responding on the BIS-11 in our study
(r = .31). However, sensation seeking takes different forms. In
particular, scholars have distinguished impulsive sensation seeking
from non-impulsive sensation seeking, in part, because the pursuit
of novel, varied, complex and intense experiences is commonly
planned and deliberate [50,21]. Thus, sensation seeking and
impulsivity were not perfectly aligned in their relation to multi-
tasking activity in our study. Specifically, sensation seeking was
significantly correlated with cellular communication while driving
(r = .13) whereas impulsivity was not (r = .00). This suggests that the
sensation seeking underlying some cell phone usage while driving
may be relatively deliberate as opposed to impulsive.
One limitation of our findings is that they are entirely
correlational. Obviously, this limits the conclusions that can be
drawn about the causes of multi-tasking activity. Future research
may need to use experimental designs to examine how the rewards
and costs associated with taking on multiple tasks, and the
controllability of secondary task engagement affects the likelihood
of multi-tasking. We believe that the relation between perceived
multi-tasking ability and multi-tasking activity is one that is
particularly likely to be bidirectional. A vast body of research has
shown that people often draw inferences about their attitudes
[51,52] and self [53] from their behavior. People who frequently
multi-task may infer from their behavior that they like to multi-
task and that they are relatively good at it. Thus, although
perceived multi-tasking ability may increase the willingness to
multi-task, multi-tasking activity may also affect perceptions of
multi-tasking ability.
A final limitation of the study involves our measure of multi-
tasking ability. Although the OSPAN task has traditionally been
used to measure working memory capacity it clearly meets the
criteria for multi-tasking in that it involves multiple tasks
characterized by distinct goals, stimuli, transformations, and
response outputs. Nevertheless, the OSPAN task has not been
psychometrically validated as a multi-tasking instrument. It is
possible that a different ability-activity pattern might emerge with
different measures of multi-tasking ability (or multi-tasking activity)
and it remains for future research to determine if the current
findings generalize to other measures of multi-tasking.
Author Contributions
Conceived and designed the experiments: DLS DMS NMW JMW.
Performed the experiments: DLS DMS NMW. Analyzed the data: DLS
DMS NMW. Contributed reagents/materials/analysis tools: DLS DMS
NMW JMW. Wrote the paper: DMS DLS NMW JMW.
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