Cell-phone use diminishes self-awareness of impaired driving

Abstract

Multitasking diminishes the self-awareness of performance that is often essential for self-regulation and self-knowledge. Participants drove in a simulator while either talking or not talking on a hands-free cell phone. Following previous research, participants who talked on a cell phone made more serious driving errors than control participants who did not use a phone while driving. Control participants’ assessments of the safeness of their driving and general ability to drive safely while distracted were negatively correlated with the actual number of errors made when they were driving. By contrast, cell-phone participants’ assessments of the safeness of their driving and confidence in their driving abilities were uncorrelated with their actual errors. Thus, talking on a cell phone not only diminished the safeness of participants’ driving, it diminished their awareness of the safeness of their driving.

Full text

1 23
Psychonomic Bulletin & Review
ISSN 1069-9384
Volume 23
Number 2
Psychon Bull Rev (2016) 23:617-623
DOI 10.3758/s13423-015-0922-4
Cell-phone use diminishes self-awareness of
impaired driving
David M.Sanbonmatsu, David
L.Strayer, Francesco Biondi, Arwen
A.Behrends & Shannon M.Moore

1 23
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BRIEF REPORT
Cell-phone use diminishes self-awareness of impaired driving
David M. Sanbonmatsu
1
&David L. Strayer
1
&Francesco Biondi
1
&Arwen A. Behrends
1
&
Shannon M. Moore
1
Published online: 18 August 2015
#Psychonomic Society, Inc. 2015
Abstract Multitasking diminishes the self-awareness of per-
formance that is often essential for self-regulation and self-
knowledge. Participants drove in a simulator while either
talking or not talking on a hands-free cell phone. Following
previous research, participants who talked on a cell phone
made more serious driving errors than control participants
who did not use a phone while driving. Control participants’
assessments of the safeness of their driving and general ability
to drive safely while distracted were negatively correlated
with the actual number of errors made when they were driv-
ing. By contrast, cell-phone participants’assessments of the
safeness of their driving and confidence in their driving abil-
ities were uncorrelated with their actual errors. Thus, talking
on a cell phone not only diminished the safeness of partici-
pants’driving, it diminished their awareness of the safeness of
their driving.
Keywords Multi-tasking .Self-regulation .Self-awareness .
Distracted driving
A process that is often central to the pursuit and attainment of
goals is monitoring (Baumeister, Heatherton, & Tice, 1994).
In the monitoring of an activity, individuals track their
thoughts, feelings, behavior, and circumstances, and their
progress toward their goals. When discrepancies are perceived
between goals or standards, and performance, action may be
taken to bring the self into line with those standards (Carver &
Scheier, 1998). The self-awareness characterizing monitoring
also facilitates self-knowledge; by observing themselves, in-
dividuals can gain a better understanding of their skills, abil-
ities, and preferences. When monitoring is lacking, individ-
uals may not recognize the shortcomings oftheir performance,
and, hence, may fail to take immediate corrective action. They
may also fail to learn about themselves, which may hamper
their ability to make sound task-related decisions in the future
(Moore, Behrends, Mazur, & Sanbonmatsu, 2014).
Factors that draw attention awayfrom the self and diminish
monitoring may contribute to self-regulatory failure (e.g.,
Baumeister, Heatherton, & Tice, 1994). Thus, studies have
shown that the ability to monitor may be impaired by strong
emotions or drives (Sayette, Schooler, & Reichle, 2010). Re-
searchers have speculated that self-awareness may be similar-
ly affected by alcohol intoxication and other conditions that
limit the ability to process information (e.g., Sayette & Griffin,
2011).
The monitoring of a particular activity may also be im-
paired by multitasking. Multitasking involves the concurrent
performance of two or more functionally independent
attention-demanding tasks having unique goals and involving
distinct stimuli, mental transformation, and response outputs.
People often multitask to get more done and to experience
more activities (Sanbonmatsu et al., 2013). However, multi-
tasking can be cognitively and physically taxing. Moreover,
performance of the tasks often suffers such that errors are
made and overall productivity is diminished (Crenshaw,
2008). The attentional demands of each task as well as the
inhibitory requirements of task switching may also diminish
task monitoring; because attention is distributed across multi-
ple tasks, the attention given to the self and the task context
may be limited. Consequently, individuals may be less apt to
notice the ways in which their performance is falling short and
*David M. Sanbonmatsu
sanbonmatsu@psych.utah.edu
*David L. Strayer
david.strayer@utah.edu
1
Department of Psychology, University of Utah, 380 S. 1530 E. RM.
502, Salt Lake City, UT 84112-0251, USA
Psychon Bull Rev (2016) 23:617–623
DOI 10.3758/s13423-015-0922-4
Author's personal copy

less likely to make compensatory adjustments. Moreover, be-
cause their self-awareness is diminished, they may beless able
to acquire knowledge of their skills and abilities, including
their general ability to multitask. This may foster persistent
misperceptions about their personal ability to multitask. In-
deed, prior research has shown that people are overconfident
about their ability to multitask effectively and that their self-
assessments are largely unrelated to their actual multitasking
abilities (Sanbonmatsu et al., 2013).
Multitasking behind the wheel
An important applied context in which the self-regulatory fail-
ures associated with multitasking may occur is in the opera-
tion of a motor vehicle. When people are driving, they often
engage in secondary tasks such as eating and grooming. In-
deed, one of the most common multitasking activities behind
the wheel is talking on a cell phone. Estimates suggest that at
any daylight hour 10 % of all drivers on the road are talking on
their cell phone (e.g., Glassbrenner, 2005). This is a public
safety issue because of the heightened crash risk associated
with cell-phone usage (e.g., McEvoy et al., 2005;Redelmeier
& Tibshirani, 1997) and the substantial body of empirical
evidence showing the impairments from talking on a cell
phone (Strayer & Drews, 2007;Strayer,Watson,&Drews,2011).
Recent work (Sanbonmatsu et al., 2015) indicates that
drivers are motivated to use cell phones by a variety of per-
ceived benefits. Talking on a cell phone enables drivers to
connect with family and friends, get work done, and alleviate
the boredom associated with driving. Although people gener-
ally acknowledge the risks, they downplay the dangers of
talking on a cell phone relative to drinking and driving. Most
actually believe they can drive safely while using a cell phone
and regard themselves to be more capable than others of driv-
ing while distracted. Our findings indicate that this overconfi-
dence is one of the strongest predictors of drivers’usage of
cell phones behind the wheel.
An important reason why drivers may be overconfident
about their ability to drive safely while distracted and why
people more generally overestimate their ability to multitask
effectively is diminished monitoring. Drivers generally mon-
itor their performance to ensure that they are driving safely.
However, when they are distracted by a cell phone, they may
be less cognizant of the errors they are making and how poorly
they are driving. Because of their lack of self-awareness, they
may maintain the illusion they can drive safely while talking
on the cell phone and continue engaging in this risky behavior.
Moreover, because their ability to monitor their driving is
impaired, their performance assessments are likely to be guid-
ed by their beliefs and expectations rather than actual
observations.
We conducted a study to examine the impact of multitask-
ing on performance monitoring and assessment. We hypothe-
sized that engagement in multiple tasks diminishes awareness
of task performance and the accuracy of self-performance rat-
ings. Because self-awareness of the costs of multitasking is
limited, overconfidence may prevail. These effects of multi-
tasking were investigated in the ubiquitous context of operat-
ing a motor vehicle. Participants drove in a simulator while
either (a) concurrently talking or (b) not talking on a cell
phone. An experimenter recorded driving errors such as run-
ning a red light and swerving into the oncoming lane. The
errors served as the measure of the actual safeness of partici-
pants’driving. Participants’self-awareness of their driving
safety was measured in two ways. First, they rated the safeness
of their simulator driving. Second, they attempted to remem-
ber the specific driving errors they made. Participants finished
by indicating their general confidence in their ability to drive
safely while distracted.
Following prior research, cell phone use was expected to
increase the driving errors made by participants. More impor-
tantly, cell phone use was expected to diminish the accuracy of
participants’assessments of the safeness of their driving. We
also predicted that control participants who were not using a
cell phone would have better memory of their errors than
participants talking on a cell phone. Finally, control partici-
pants’confidence in their ability to drive safely while distract-
ed was expected to be grounded in the actual safeness of their
driving. However, because cell phone users were expected to
be less aware of the adverse effects of cell phone use on their
driving, it was anticipated that their assessments of their gen-
eral ability and their errors would be uncorrelated.
Method
Participants
One hundred undergraduates (67 females and 33 males) par-
ticipated in the Institutional Review Board-approved study for
extra course credit. They were randomly assigned to either the
cell-phone group or a control group that did not use a cell
phone. The undergraduates ranged in age from 18 to 41 years,
with an average age of 21.8 years. All participants owned
a cell phone. They reported that they drove an average of
70 min each day (SE = 9), and used their cell phone
approximately 22 % (SE = 2.1) of the time that they were
driving.
A power analysis for detecting driving differences between
the cell-phone and control groups was performed adopting an
αof .05 (2-tailed). Following our previous research (e.g.,
Strayer, Drews, & Johnston, 2003), we assumed a moderate
to large effect size. The analysis indicated that a sample of 30
participants in each condition was sufficient to demonstrate
618 Psychon Bull Rev (2016) 23:617–623
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differences in driving performance. A second power analysis
was performed for the planned correlational analyses of the
correspondence between driving performance and assess-
ment. Assuming a moderate to large effect size and adopting
an αof .05 (2-tailed), we determined that 50 participants in
each condition were needed. Note that individuals who were
not able to complete the driving session because of motion
sickness were not included in the participant count.
Stimuli and apparatuses
The DriveSafety™DS-600 simulator was used in this exper-
iment. The DS-600 consists of a Ford Focus cab surrounded
by three large screens encompassing a 270° view. The simu-
lated vehicle is based on the vehicular dynamics of a compact
passenger sedan with automatic transmission.
The driving scenario was designed using DriveSafety Hy-
perDrive Authoring Suite. A city residential road database
simulated an 8.2-km section of road with ten intersections
and both one-way and two-way traffic. Directional arrows
embedded in the driving environment provided instructions
for navigation. Driving was regulated by speed limit, school
zone, stop and yield signs, and traffic lights. The roadways,
sign placement (e.g., distance between the crosswalk and the
pedestrian crossing sign), and crosswalks conformed to the
Manual on Uniform Traffic Control Devices for Streets and
Highways (Federal Highway Administration, 2012).
Participants in the cell-phone group used a hands-free de-
vice provided by the experimenter. Cellular service was pro-
vided by Sprint. The cell phone was an iPhone5 s running iOS
7 and the hands-free earpiece was manufactured by Jawbone.
Participants selected which ear they wished to use for the
hands-free earpiece.
Procedure
Participants began the study by completing a brief survey of
their driving practices and beliefs. They were then familiar-
ized with the driving simulator, using a standardized adapta-
tion sequence designed to reduce the likelihood of motion
sickness, after which commenced a 10-min practice session.
After completing the survey, cell-phone participants were
asked to generate a list of friends or family members they
could talk with during their drive. The call was initiated and
the volume was adjusted before they began the primary driv-
ing session.
There were 12 potentially hazardous driving scenarios or
situations that were encountered by participant drivers. Spe-
cifically, drivers were required to stop for pedestrians at a
crosswalk partially obscured by other vehicles, slow down
in a school zone, yield to an approaching vehicle, stop behind
cars turning left while traveling on a single lane road, slow
down and move over because of construction, avoid a
bicyclist at a crosswalk, pull over for an ambulance, and slow
down for a crosswalk partially obscured by a truck. The entire
8.2-km drive took about 20 min to complete.
The experimenter observed the performance of the driver
from behind the simulator cab. As the participant drove, the
experimenter tabulated the driving errors on a checklist. The
specific errors that were recorded on the checklist are present-
ed in Table 1. The total number of each type of driving error
was tabulated by the experimenter. Immediately after com-
pleting their drive, participants were asked to complete the
same checklist of errors that the experimenter had filled out.
Thus, they attempted to recall the number of driving errors of
each type they had made on the simulator.
Participants finished by assessing the safeness of their driv-
ing, and their general ability to drive safely while talking on a
cell phone. They rated Bthe safeness of your driving during
this experiment using the simulator^on a 7-point scale an-
chored by B−3^=not at all safe and B+3^=highly safe.
Finally, they answered the question: BTo what extent are you
capable of driving safely while engaging in another task such
as talking on the cell phone?^on a 7-point scale anchored by
B1^=not at all capable and B7^=highly capable.
Results
The analyses were limited to participants who completed the
simulator drive or whose drive was not interrupted. Prelimi-
nary analyses indicated that gender did not interact with cell-
phone usage to affect any of the performance or assessment
measures in the study. Consequently, gender was not included
in the reported analyses.
Driving errors and driving safeness
The most basic measure of the actual safeness of participants’
driving on the simulator was the total number of errors they
made. In order to distinguish the severity of the errors and
create more detailed measures of driving safeness, we asked
a different group of 69 respondents to indicate the seriousness
of each of the driving errors or violations on a 6-point scale
anchored by B0^=not at all serious and B5^=highly serious.
The mean rating of each of the driving errors is presented in
Tab le 1. There were two errors (failing to signal and speeding)
that were perceived to be less severe than the others. When the
errors were ordered in terms of judged severity, the only sig-
nificant pair-wise contrast between an error and the next most
serious error was between the errors of speeding and making
an illegal turn, t(68) = 2.17, p=.033,d=.53.Consequently,
failing to signal and speeding were labeled as Bminor^errors
while the remaining ten were labeled as Bserious^errors. The
minor errors have face validity as being less severe in that they
are less likely to directly lead to an accident than more serious
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errors such asfailing to yield toa vehicle with the right of way.
Distinguishing the minor errors from the serious errors was
important, because it was anticipated that the serious errors
would be the primary basisfor participants’assessments of the
safeness of their driving and their confidence in their ability to
drive safely while distracted.
Tab le 2presents the serious and minor driving errors made
in the cell-phone and control groups. A comparison of the
errors in the two groups revealed that cell-phone participants
made significantly more serious errors t(98) = 2.72, p=.008,d
= .55, but not more minor errors, t(98) = .68, p>.250,d=.14,
than control participants.
Participants’assessments of the safeness of their driving
and their estimations of the number of driving errors they
made in the cell-phone and control groups are also presented
in Table 2.Cell-phoneparticipantswereexpectedtoperceive
their driving to be less safe and to report they made more
errors because of the widespread expectation that cell phones
impair driving performance. Somewhat surprisingly, cell-
phone participants did not remember making more serious
errors, t(98) = .67, p>.250,d= .13, or more minor errors
than control participants, t(98) = 1.33, p=.185,d=.27.
However, as anticipated, cell-phone participants perceived
that they drove less safely than control participants, t(98) =
4.97, p=.001,d= .99. The groups also did not differ in terms
of their perceptions of their general ability to dive safely while
distracted following the simulator session, t(98) = 1.67, p=
.097, d=.34.
Relation between perceived and actual driving safeness
Analyses were performed to examine whether participants’
assessments of the safeness of their driving were based on
awareness of the actual safeness of their driving (see
Table 3). Control participants’assessments of their driving
safety were negatively correlated with their serious driving
errors, r(49) = −.37, and uncorrelated with their minor driving
errors. Thus, control participants’assessments of the safeness
of their driving decreased as the number of serious driving
errors they made increased. By contrast, cell-phone partici-
pants’assessments of their driving safety tended to be posi-
tively correlated with their serious driving errors, r(49) = .25,
Tabl e 1 Driving errors and their ratings of severity (N = 69)
Mean
Failing to signal a turn 2.51 [2.20–2.81]
Speeding 10 mph or more over the posted speed limit 2.93 [2.62–3.24]
Making an illegal turn 3.25 [2.96–3.54]
Failing to move over for a bicyclist, pedestrian, or emergency vehicle 3.48 [3.16–3.80]
Failing to stop at a crosswalk for one or more pedestrians 3.90 [3.62–4.18]
Failing to take appropriate action to avoid a hazard 3.99 [3.76–4.23]
Swerving off the road (at least two wheels off the road) 4.13 [3.88–4.38]
Swerving into the wrong lane (at least two wheels in opposite lane) 4.35 [4.15–4.56]
Failing to stop at an intersection for a red light or stop sign 4.42 [4.21–4.64]
Traveling in the wrong direction on a one-way road 4.66 [4.51–4.81]
Moving into a lane (traveling in the same direction) occupied by another vehicle (leading to a near collision or collision) 4.71 [4.58–4.84]
Hitting a vehicle, pedestrian, bicyclist, or object 4.96 [4.90–5.02]
Note Numbers in brackets are 95 % confidence intervals of the means
Tabl e 2 Perceived and actual errors, self-assessments of driving, and perceived ability to drive safely while distracted as a function of talking versus
not talking on a cell phone while driving (N = 100) Note Numbers in brackets are 95 % confidence intervals of the means
Control Cell-phone
Serious driving errors 4.38 [3.80–4.95] 5.86 [4.96–6.76]
Minor driving errors 1.66 [1.17–2.15] 1.92 [1.36–2.48]
Perceived serious driving errors 5.20 [3.97–6.43] 5.80 [4.56–7.04]
Perceived minor driving errors 2.06 [1.48–2.64] 2.63 [2.03–3.23]
Perceived safeness of driving* 1.10 [.74–1.45] -0.27 [-.67–0.14]
Perceived ability to drive safely while using a cell phone** 3.41 [3.01–3.79] 2.93 [2.50–3.30]
*7-point scale anchored by B−3^=not at all safe and B+3^=highly safe
**7-point scale anchored by B1^=not at all capable and B7^=highly capable
620 Psychon Bull Rev (2016) 23:617–623
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and uncorrelated with their minor driving errors. A compari-
son of these correlations revealed that self-assessments of
driving safety were more accurate and better correlated with
the actual driving errors in the control group than the cell-
phone group, F(1,96) = 10.25, p = .002, η
2
=.10.Thatis,
cell-phone participants were less aware of the actual safeness
of their driving than control participants.
Further evidence of cell-phone participants’lack of driving
self-awareness comes from an analysis of their memory of
their driving errors. Control participants’memory of their se-
rious driving errors was positively correlated with their actual
serious driving errors, r(49) = .40, but their memory of their
minor driving errors was not correlated with their actual minor
driving errors. The pattern suggests that control participants
were cognizant of the serious errors they were making. In
contrast, cell-phone participants’memory of their serious
driving errors was not correlated with the actual number of
serious errors they made, r(49) = .05. However, a comparison
of the correlations found that the memory for serious driving
errors did not significantly differ between cell-phone and con-
trol groups, F(1,96) = 3.20, p = .077, η
2
=.03.
Predictors of confidence in driving ability
The final set of analyses focused on the predictors of partici-
pants’general confidence in their ability to drive safely while
distracted. From Table 3it is apparent that both control and
cell-phone participants’confidence in their ability to drive
safety while distracted was negatively correlated with their
perceived serious driving errors. However, only control par-
ticipants’confidence in their ability to drive safely while dis-
tracted was grounded in the actual safeness of their driving.
The confidence of control participants was negatively corre-
lated with their serious driving errors, r(49) = −.32, whereas
the confidence of cell-phone participants was uncorrelated
with their serious driving errors, r(49) = .13. The control and
cell-phone groups differed in the relationship between the as-
sessments of their ability to drive safely while distracted and
their serious driving errors, F(1,96) = 5.04, p = .027, η
2
=.05.
Discussion
Cell-phone use not only impaired the safeness of participants’
driving in our study, it impaired their awareness of the safe-
ness of their driving. The driving safety assessments and
memory of driving errors of cell-phone participants were un-
correlated with the actual errors they made. When drivers are
talking on a cell phone, they are often unaware of the incon-
sistencies in their speed, their weaving across lanes, and their
near misses with other vehicles. As a consequence, they may
persist in believing that they can safely talk or text on a cell
phone behind the wheel.
The study furthers our understanding of the impact of sec-
ondary task engagement on the self-regulation of perfor-
mance. Taking on multiple tasks simultaneously can be phys-
ically taxing and stressful, and contribute to poorer primary-
task performance. Our findings indicate that an additional cost
of multitasking is a decrease in the performance monitoring
that is essential to self-regulation and self-knowledge (e.g.,
Baumeister, Heatherton,&Tice,1994). Because multitaskers
are less self-aware, they may be less apt to make the adjust-
ments necessary to bring their performance in line with their
goals (e.g., Carver & Scheier, 1998) and less likely to acquire
Tabl e 3 Correlations between actual and perceived errors, and memory for errors, self-assessments of driving, and perceived ability to drive safely
while distracted as a function of talking versus not talking on a cell phone while driving (N = 50 in each group)
Actual serious errors Actual minor errors Perceived serious errors Perceived minor errors
Perceived safeness of driving
Cell phone .25* −.32** −.39*** −.24*
Control −.37*** −.07 −.70*** −.17
Δ*** Δ*
Perceived ability to drive safely while distracted
Cell phone .13 −.24* −.44*** −.34**
Control −.32** −.02 −.38*** .05
Δ** Δ*
Memory for errors
Cell phone .05 .29**
Control .40*** .13
Δ*
*Significant at p< .10 level
**Significant at p< .05 level
***Significant at p< .01 level
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the self-knowledge of their shortcomings and abilities that is
essential to decision making and improvement.
Importantly, these findings cast doubt on speculation that
drivers routinely self-regulate their multitasking activities,
such as talking on a cell phone, based upon their real-time
driving performance (Young & Regan, 2007). Because cell-
phone drivers are less aware of their errors, they are less apt to
self-regulate their cell-phone usage based on the real-time de-
mands of driving. Alarmingly, the cell-phone drivers who
made the most errors exhibited a pattern similar to the fictional
cartoon character Mr. Magoo, who was blithely unaware of
his driving impairments.
The research also increases our understanding of the moti-
vations underlying multitasking and the usage of cell phones
while driving. As we discussed previously, people tend to
downplay the risks of multitasking, in part, because of inflated
views of their capacities (Sanbonmatsu et al., 2015). The pres-
ent findings suggest that one of the contributors to overconfi-
dence in the ability to multitask is diminished self-awareness.
People are often unaware of the detrimental effects of doing
many things at once on their performance. Consequently, they
may persist in believing that they are capable of performing
multiple tasks simultaneously with minimal cost. Although
cell-phone participants in our study made more errors than
controls, they were not aware of them. As a result, their as-
sessments of their general driving ability were unrelated to
their unsafe driving. In contrast, control participants’estima-
tions of their ability to drive safely while distracted were sig-
nificantly associated with the actual serious errors they made
on the simulator.
An examination of the group means reveals that the mean
perceived serious errors of cell-phone participants (M=5.86)
was very close to their actual mean serious errors (M=5.80).
This might suggest that cell-phone participants’recollections
of their driving errors were relatively accurate. However, as
we reported above, individual cell-phone participants’estima-
tions of their serious errors were uncorrelated (r= .05) with
their actual serious errors. In contrast, the perceived and actual
serious errors of control participants were highly positively
correlated (r= .40). Thus, it is clear from the correlational
analyses that cell-phone participants were largely guessing
about the driving errors they made and that the similarity of
the group means appears to be happenstance.
People generally acknowledge that cell phone use impairs
driving performance (Sanbonmatsu et al., 2015). This expecta-
tion is likely to have led cell-phone participants to assess their
driving safety less favorably than controls and to estimate a great-
er number of driving errors. However, participants who talked on
acellphonereallyhadlittleideaofhowwellorpoorlytheywere
driving. Multitasking is often attention demanding to the point
that people are unable to monitor themselves and the circum-
stances affecting their behavior. As a consequence, their assess-
ments and accounts of their performance may often be specious.
Acknowledgments This work was supported by a grant from the
Mountain Plains Consortium, a regional University Transportation Center
(UTC) sponsored by the United States Department of Transportation,
Research and Innovative Technology Administration. The authors thank
Shazia Ahmad, Erica Armstrong, Jennifer Buttrick, Daniel Cosentino,
Laura Creamer, Ciera Figge, Brooke Rowley, Tarra Sliwa, and Jennifer
Webb for their assistance in conducting the study.
Author note D.M. Sanbonmatsu and D.L. Strayer developed the study
concept. All authors contributed to the experimental design. Simulator
programming, testing, and data collection were performed by F. Biondi,
A.A. Behrends, and S.M. Moore. All authors contributed to the data
analysis and interpretation. D.M Sanbonmatsu and D.L. Strayer contrib-
uted equally to the writing of the manuscript and the order of authorship
was determined alphabetically. All authors approved the final version of
the manuscript for submission.
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