Neurotics Can't Focus:
An in situ Study of Online Multitasking in the Workplace
Gloria Mark1, Shamsi T. Iqbal2, Mary Czerwinski2, Paul Johns2, Akane Sano3
1Department of Informatics
University of California, Irvine
One Microsoft Way
Massachusetts Institute of Technology
Irvine, CA 92697 USA
Redmond, WA 98052 USA
Cambridge, MA 02139 USA
In HCI research, attention has focused on understanding
external influences on workplace multitasking. We explore
instead how multitasking might be influenced by individual
factors: personality, stress, and sleep. Forty information
workers' online activity was tracked over two work weeks.
The median duration of online screen focus was 40 seconds.
The personality trait of Neuroticism was associated with
shorter online focus duration and Impulsivity-Urgency was
associated with longer online focus duration. Stress and
sleep duration showed trends to be inversely associated
with online focus. Shorter focus duration was associated
with lower assessed productivity at day's end. Factor
analysis revealed a factor of lack of control which
significantly predicts multitasking. Our results suggest that
there could be a trait for distractibility where some
individuals are susceptible to online attention shifting in the
workplace. Our results have implications for information
systems (e.g. educational systems, game design) where
attention focus is key.
Multitasking; focus; information work; personality; stress;
ACM Classification Keywords
H.5.3 [Information Interfaces and Presentation (e.g., HCI)]:
Group and Organization Interfaces; K.4.m [Computers and
In today's information workplace, the surfeit of digital
resources continually compete for people's attention. While
switching among multiple online activities may benefit
productivity, it can also distract people from the task-at-
hand [5, 19]. Multitasking, the switching of attention
among different activities, can be triggered internally (e.g.,
through boredom) or by external sources (e.g. email
notifications). When a person switches between different
activities frequently, their duration of focus on any one
activity reduces as a consequence. In HCI, a fair amount of
attention has been given to examining external influences
on interruptions [5, 6, 15, 19] and to frequency of activity
switching, e.g., [5, 15]. However, research has not explored
individual characteristics to help understand multitasking
behavior in the workplace.
It is not clear whether multitasking is an efficient behavior.
In the workplace, activities were found to shift every three
minutes, on average, including online work and interactions
with people . Evidence shows that switching attention
between different tasks results in a 50% longer time to
finish those tasks, compared to focusing on one task
through to completion before starting the next one .
Some research suggests that cognitive differences could be
an explanation for why some people multitask more than
others. Heavy multitaskers were found to have less ability
to filter out interference from environmental stimuli, which
makes them more susceptible to distractions .
Individual differences also exist in people's ability to
control attention . Laboratory studies have investigated
types of attention, such as selective or divided attention, or
vigilance. However, to our knowledge, few studies have
examined factors related to individual personality and
situations that affect online focus duration in the real world
setting of the workplace, cf . We feel this is important
given the extent to which digital media is used in
In this paper we contribute to understanding multitasking
behavior with empirical results that show that Neuroticism
and Impulsivity relate to shorter online focus. A factor
analysis revealed that a proposed trait described as lack of
control may explain focus duration. This study is part of a
larger project, HealthSense, tracking workplace behavior.
Multitasking can be viewed at different levels of
granularity. From a broad perspective, multitasking refers
to switching among different tasks or projects. At a more
fine-grained level of analysis, multitasking can indicate
switching of attention among different activities, which
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could be within the same task. This finer-grained
perspective can be used as a lens to understand how people
shift their attention when working online. Models of
attentional resource allocation describe that people have
limited attentional resources, and investing resources for
some activities leaves fewer resources available to apply to
other activities . Based on a review of the literature, we
expect that the following personality and physiological
factors can affect resource use, reflected in online focus.
Personality: Neuroticism. In laboratory studies, higher
Neuroticism relates to lower performance in selective
attention tasks . Neuroticism is a personality trait,
assumed to be invariant (and to have a biological basis), is
characterized by anxiety and is a response to emotional
stimuli . Neurotics are more prone to stress, report more
daily problems, and tend to reanalyze prior events over and
over in their minds . Because Neuroticism is considered
an invariant trait, the effects of an experience in one domain
(e.g. home life) can carry over into another domain (e.g. the
workplace) . Investing mental resources, e.g., in
reevaluating prior events, could result in fewer attentional
resources available to focus on the current activity. The
relationship of Neuroticism and attention has not been
investigated in the workplace. We expect that Neuroticism
might become manifest in the workplace as a shorter
duration of focus on any computer screen.
H1: Neuroticism is related to a shorter focus duration.
Personality: Impulsivity. Impulsivity could also influence
multitasking. While considered a personality trait,
impulsivity is viewed as a heterogeneous construct (see 
for a review). Generally speaking, people who are
impulsive lack resources to restrain themselves from
actions . In the workplace, people who are impulsive
may not be able to resist distractions, e.g., checking email
or the Internet, leading to attention shifting and thus shorter
focus duration on any single activity. We draw on the
model of impulsiveness of Whiteside et al.  based on a
factor analysis of previous models, which identified four
impulsivity factors considered to be distinct psychological
processes. We feel the most relevant factors for
understanding workplace multitasking and attentional focus
are the factors of Urgency and (Lack of) Perseverance.
Urgency refers to the tendency to act on strong impulses
(e.g. one cannot control cravings). (Lack of) Perseverance
refers to one's inability to remain on a task until completion.
We feel that less relevant to our fine-grained perspective of
multitasking are the factors of Lack of Premeditation,
which refers to the inability to carefully plan longer term
action (e.g. before going on a trip to Hawaii); and
sensation-seeking, the tendency to seek adventure.
H2a: Impulsivity-urgency is related to shorter focus
H2b: Impulsivity-(lack of) perseverance is related to
shorter focus duration.
Stress. Stress can also impact online focus duration.
Lazarus  defines stress as when external and internal
demands exceed a person's available resources. Theories of
the effect of stress on attention explain that stress uses up
available attentional resources . Some amount of stress
can prolong focus and inhibit attending to irrelevant
information, or distractions . However, alternative
views (capacity-resource view; thought suppression)
explain that stress makes it difficult for people to
selectively focus since stress depletes resources that inhibit
the ability to filter out distractions , and to suppress
irrelevant information . In laboratory studies, stress has
been associated with impaired selective attentional
performance, e.g. , which is consistent with views that
stress depletes attentional resources. In the workplace,
psychological stress has been linked to reduced efficiency,
decreased performance capacity, and low motivation .
Thus, we expect stress to shorten focus.
H3: Stress is related to shorter focus duration.
Physical well-being: sleep. A consistent finding of sleep
deprivation is that it affects psychomotor vigilance [14, 24],
even when sleep loss is relatively minor . Laboratory
studies show that subjects who were sleep deprived showed
deficits in switching between different cognitive tasks, yet
no deficits were found with repetitive tasks . This
suggests that sleep loss impairs cognitive control which
affects the ability to filter out irrelevant stimuli, i.e. to
ignore distractions. Thus, less sleep could impair the ability
to filter out distractions, leading to shorter focus duration.
These results however, are all from laboratory studies. It is
not clear whether these results on sleep duration would
apply to people's behavior in the workplace. We expect that
the effects of sleep duration would be manifest through
shorter durations of focus when working online.
H4: Less sleep is associated with shorter focus duration.
Focus duration and productivity. What might be a
consequence of focus duration? People who switch between
different tasks take longer to finish them, as opposed to
performing tasks in sequential order . Multitasking is
reported to contribute to cognitive overload , which
could also negatively impact productivity. For instance, in a
hospital setting, multitasking resulted in gaps in information
flow and errors . We expect that information workers
who shift their online focus more frequently over the course
of the day should feel less productive at the end of the day.
H5: Shorter focus duration is related to lower assessed
productivity at the end of the day.
Forty volunteers (20 females, 20 males) in a large high tech
U.S. corporation, who responded to an ad, were observed in
situ in their real work environment for about 12 business
days. Their job roles involved information work and were
varied: administrative support, engineering, and
management. Participants were compensated with $250.
Participants' computer activity at work was logged during
all business hours automatically via custom-built Windows
Activity Logging software. This logging software tracks
every open application, which window is in the foreground,
and whether the user is interacting with that window (with
mouse, keyboard, touch, etc.). We measured the total
duration of all applications, defined as the number of
seconds that each application was in the foreground
window, ending when the user either changed windows or
the computer had no keyboard or mouse activity for a
period of five minutes. As participants at times might not be
using their computer for various reasons (e.g., while at a
meeting), we used only those hours of data when the
computer was used (i.e., when logged data showed that
computer duration was greater than zero for that hour).
Focus Duration (online) was measured by dividing total
daily logged computer duration by the number of computer
screen switches. As discussed, we take a fine-grained
perspective on multitasking to view shifting attention
online. We feel that screen switches are a reasonable proxy
for attention duration with computer work.
At the beginning of the study, a general survey was given.
Neuroticism was measured as part of the Big 5 personality
inventory . Impulsivity was measured by the UPPS
Impulsive Behavior Scale , using the dimensions of
Urgency and Perseverance. Stress was measured by the
Perceived Stress Scale (PSS) , a widely-deployed global
measure of the degree to which people perceive stress in
their lives. While these scales could be related to a greater
or lesser degree, we felt that a thorough examination of our
hypothesized variables would tell a more complete story.
Our goal was to discover several lines of converging
evidence that particular factors were significantly at play.
Productivity was measured by six items in the daily end of
day survey, asking about accomplishment, efficiency,
satisfaction, effectiveness, quality, and overall productivity
(e.g., “How efficient do you feel you were today in
performing your work?”). Responses were measured on a
Likert scale, with 1=not at all, and 7=extremely. The item
dimensions were highly correlated (with correlations
ranging from .68 to .94), so we combined them additively
to construct an index measure of Productivity.
Sleep was measured by the Fitbit Flex actigraph which
participants wore 24 hours a day.
Analyses. Focus Duration was our dependent variable for
H1-H4. For H5, Focus Duration was the independent
variable and end-of-day Productivity assessment was the
dependent variable. For the analyses of daily data, we used
only full weekday days of window logging (the time of the
study setup sometimes resulted in partial days of data
collection), and used only days when computer usage was
greater than zero. For analyzing Neuroticism, Impulsivity,
and Stress, we analyzed the data using regression analysis
in SPSS. For analyzing sleep and productivity, which were
daily data, i.e., multiple daily measures per person, we used
Linear Mixed-Effects Models (LMM) in SPSS. This uses
random and fixed effects to account for the repeated
measures within subjects.
Table 1 presents the average duration of focus on any
computer screen for our 40 participants. Averaged over all
workdays per person, and for all applications and online
sites, the median duration of focus is about 40 seconds.
Participants had slightly longer focus on email clients, and
productivity software (Word, Powerpoint, Excel, Visual
Studio, etc.) but had a shorter focus when using
communication software (e.g., Skype, IM, Lync). The SD is
also fairly small. In Table 1 we further divide switching
behavior into switching between applications (e.g., between
Word and email) and switching within applications (e.g.,
opening up different word documents or switching Internet
sites). Switches occur more often between different
applications which could suggest more of a context shift
than switching within applications. Thus, the data shows
that our participants' online activity is characterized by
fairly short durations of focus on their computer screens.
Personality traits and focus
Results of our hypotheses tests are shown in Table 2 with p-
values adjusted by the Holm-Bonferroni sequential
adjustment . The results support H1: the higher the
Neuroticism, the shorter the focus duration, explaining
13.4% of the variance of online focus duration.
We found support for H2a: the trait of Impulsivity-Urgency
is associated with shorter focus duration, explaining 16.5%
of the variance. We reject H2b: Impulsivity-Lack of
Perseverance was not significantly associated with focus.
Stress and focus
We found weak support for H4: a strong trend showed that
higher Stress was related to shorter focus duration,
explaining 10.5% of the variance.
Sleep and focus
Eight outliers were removed from the daily sleep variable.
For this two week study, we found a strong trend that the
less one sleeps, the longer is the focus duration. Thus, we
reject H4. However, this surprising result could be
explained by deadlines. In the workplace, when people have
deadlines, they may sleep less the night before and become
highly focused on work to meet the deadline. Participants
All computer usage
Productivity SW usage
Communication SW usage
Daily switches within apps
Daily switches betw apps
Table 1. Avg. online screen focus duration (sec.) and switches.
were asked at the end of the day how much deadlines
influenced their work that day with a 7-point Likert scale
item. We found that the more deadlines influenced work,
the longer the focus duration: F(1,285)=4.32, p<.04. A
significant sleep by deadline interaction shows that the
combination of less sleep with more influence of deadlines,
the longer the focus: F(1,289)=3.74, p<.05. However, we
are unable to draw conclusions on how sustainable this
would be over a longer period of time as our two-week
study duration limited us from investigating that question.12
Productivity and focus
Using the daily data, three outliers were removed from
focus duration. Productivity assessment was the dependent
variable, and Focus Duration was the independent variable,
controlling for Neuroticism, Impulsivity-Urgency, Stress,
and Sleep. Using LMM, we found a significant relationship,
supporting H5. The Variance Inflation Factor was less than
5, indicating that multicollinearity was not a problem.
We conducted a factor analysis on our observed variables
(including deadlines). Factor analysis enables a researcher
to uncover a structure of unobserved variables among
correlated variables, by explaining the variability through
latent factors . With factor analysis, each variable is
primarily associated with a distinct factor. We used a
Varimax rotation with a Kaiser normalization. A scree plot
revealed that two factors should be used, accounting for
62.4% of the variance (Table 3). We interpret the first
factor as "lack of control" since Neuroticism and Stress may
be responsible for a lack of control in suppressing thoughts
(e.g. in reanalyzing prior events) and Impulsivity-Urgency
refers to a lack of impulse control. The second factor loaded
onto the single variable of deadlines, which we interpret as
"time pressure", i.e., a situational explanation. We next
regressed Focus Duration on these two factors: F(2,
37)=5.51, p<.008, adj. R2=.19. The results show that lack
1 As there is no standard method for determining an R2 in LMM
models  we ran a linear model with fixed effects alone to get an
R2 value. Not including random effects will underestimate the
variance explained as it provides a lower bound.
Lack of Control (Neur, Imp-Urgency, Stress)
Time Pressure (Deadlines)
Table 3. Regression model for Focus Duration, based on the
two factors identified through factor analysis.
of control is a significant factor that can explain online
attention duration (Table 3).
DISCUSSION AND CONCLUSIONS
We found that in information work, online focus is
characterized by short durations, with only a median span
of 40 seconds. Our results build on previous in situ
descriptive studies of multitasking [5, 15] by suggesting
that there may be an inherent trait of distractibility, cf ,
uncovered by a factor we call lack of control. As
personality is difficult to change, the factor of "lack of
control" could represent an invariant trait that makes people
susceptible to online distractions. Given all the potential
distractions that digital media presents to information
workers, our results suggest that inherent traits could make
some people more susceptible to distractions.
A potential consequence of multitasking is that shorter
focus duration positively correlates with lower assessed
productivity at days' end. This is consistent with interviews
that describe that switching activities has a cost, e.g., in
doing redundant work . The result provides empirical
support for costs in information work though more research
is needed to uncover potential underlying factors.
Our results of personality effects have implications for
educational systems and game design, where personality is
found to influence use, e.g. . System design could adapt
to a user depending on one's pattern for focusing attention.
Also, virtual agents could adapt interruptions and
messaging according to a person’s ability to focus.
As our study was only done in one workplace, we can only
generalize to similar workplaces that are high tech, with
educated workers (like our participants). Because
personality traits are assumed invariant, the relationship of
personality and focus duration appears causal (i.e., it is not
likely that one's focus duration changes one's Neuroticism
or Impulsivity trait). However, there could be underlying
variables that influence these relationships which all
warrant further exploration. Nevertheless, this research is a
first step at investigating individual differences that can
influence online focus; we hope that this research can spark
further investigation to unpack explanations for
multitasking and attention focus in the workplace.
This material is based upon work supported by the NSF
under grant #1218705.
H2b: Impul-Lack Persev
H5: Productivity regressed
on focus duration
Table 2. Results of linear regression of Focus Duration based
on each predictor variable for H1-H5. *p-values are
adjusted with the Holm's method .
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