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Journal of Psychological Inquiry
2016, Vol.21, No. 2, pp.# 6—14
© Great Plains Behavioral Research Association
Does the Mere Expectation of a Cellphone Call Occupy Working
Memory?
Amy E. Hufstedler and Kenith V. Sobel *
University of Central Arkansas
Abstract—There is extensive evidence that cognitive deficits will occur when one is actively using a
cellphone while trying to divide their attention, particularly for individuals considered to be dependent
on their cellphones. We wondered if the mere anticipation of an incoming phone call would cause similar
impairment. To assess this, we implemented a visual search task (known to test and measure working
memory) to determine if deficits in cognition can be seen even if a participant is not actively using their
phone. Students from the University of Central Arkansas performed a number search task twice; once
with no cellphone and a second time with a cellphone present, anticipating a phone call. We predicted the
anticipation would cause reaction times, as well as error rates, on the task to increase in cellphone
dependent participants. Although there were no effects on reaction times and no indication cellphone
dependency affected performance, the results revealed anticipating a call significantly affects
participants’ accuracy.
Keywords: cellphone dependency, attention, memory, accuracy, number search task
Most people today, particularly young
adults, use cellphones; as of December, 2014 there
were more wireless connections (355 million) than
people (just over 320 million) in the United States
(Bergmann, 2015). People are not only using
cellphones to stay in touch with family and friends,
but also to play games, check the time and
weather, send emails, and hundreds of other
functions for everyday use. With all of these uses,
people have come to depend on their cellphones to
the extent that they often interfere with life in the
“real” world, causing distraction in occupational,
social, and educational settings (Lepp, Barkley, &
Karpinski, 2014). Carrying on a conversation on a
cellphone can distract from other activities
requiring mental processing such as driving a car
(Boiteau, Malone, Peters, & Almor, 2014; Strayer &
Johnston, 2001). Among the 1,506 hospitalizations
attributed to cellphone distraction in 2010 was a
14 year old boy treated for a chest contusion after
he walked off a bridge while focused on his
cellphone (Nasar & Troyer, 2013). Because people
commonly carry their phones with them at all
times, we wondered if the mere expectation of an
incoming call or text message could distract from
other mental processing, and whether the effect of
expectation is more acute for people more
dependent on their cellphones. If the expectation
of a call is sufficient to cause distraction, then
many of the people around us who appear to be
engaged in a mentally taxing activity may in fact
have part of their minds focused elsewhere,
specifically on the anticipation of an incoming
phone call or text message.
Given the prevalence of cellphones and their
apparent importance in daily life worldwide, the
question of the effects of cellphone dependency
has gained global interest. In this spirit, many
scales and surveys have been developed to assess
cellphone dependency, overuse, and addiction
(Jenaro, Flores, Gomez-Vela, Gonzalez-Gil, &
Caballo, 2007; Kawasaki et al., 2006; Merlo, Stone
& Bibbey, 2013; Toda, Monden, Kubo, & Morimoto,
2004; Walsh, White, & Young, 2010). Cellphones
*Kenith V. Sobel served as Faculty Sponsors.
6
HUFSTEDLER & SOBEL
are far more distracting to individuals who are
dependent on them (Merlo et al., 2013), and
distraction is detrimental to many cognitive
functions, including working memory (Yoon,
Curtis, & D’Esposito, 2006). Many daily situations
require the use of working memory, which is
essential to the ability to maintain and process
information.
People use working memory in many
mental tasks throughout the day, such as
following steps in a recipe or mentally solving a
math problem (Cowan, 2008). The ability to
maintain information in working memory can be
affected by many things, including emotional
states (Krause-Utz et al., 2012) and auditory
stimuli (Hughes, Hurlstone, Marsh, Vachon, &
Jones, 2013). The power working memory has
over distraction and multitasking can vary with
the level of task demand and strength of the
distractor (Berti, Roeber, & Schroger, 2004; Berti
& Schroger, 2003). Cellphones would be a strong
distractor, given the levels of dependence
reported. Many studies have explored the effects
cellphone dependency and use can have on
driving ability (Strayer & Johnston, 2001),
situational awareness (Nasar & Troyer, 2013),
relationships (Przybylski & Weinstein, 2012),
anxiety, school performance, and even overall life
satisfaction (Lepp et al., 2014). Though the effects
of actually using a cellphone are well documented,
no studies have investigated whether the mere
expectation of an incoming call can occupy
working memory, thereby interfering with
performance on other tasks requiring mental
processing. This could have serious implications
for how the mere presence of a cellphone in one’s
pocket can undermine the operation of working
memory and other higher cognitive functions
when they are needed most, such as in
educational and occupational settings. This study
sought to expose the effect of cellphone
anticipation on working memory functioning, by
determining whether participants would perform
more slowly and make more errors while they
were anticipating a phone call.
We asked college-aged students to perform
two intervals of a task requiring working memory
and then to complete a survey designed to
measure dependency on cellphones. To test the
|7
effect of cellphone anticipation on working
memory, the participant’s cellphone was located
in the experiment room during one interval of the
working memory task and removed from the
room during the other interval. Furthermore,
during the cellphone-present interval, the
experimenter told the participant she would call
the participant’s cellphone at a randomly
determined time, and the participant should
answer the call as quickly as possible. Because
this design entails two different intervals in time,
we needed to consider order effects.
The first interval could promote either
practice or fatigue (Mackworth, 1948), so even
without our manipulation participants might be
significantly more or less proficient at the
working memory task during the second interval
than the first. To neutralize order effects, ideally
we would counterbalance the order so half of the
participants would do the cellphone-present
interval first and cellphone-absent interval
second, and vice versa for the other half of
participants. We also wanted to expose each
participant to the same number of trials in both
intervals, so in the cellphone-present condition
we wanted to interrupt participants with a phone
call only after they had executed as many trials as
there were in the cellphone-absent condition.
However, because we expected different
participants to carry out the experiment at
different rates, we couldn’t know when to
interrupt participants in the cellphone-present
condition until after they provided a baseline time
by carrying out the cellphone-absent condition.
This constrained us to expose all participants to
the cellphone-absent condition first and the
cellphone-present condition second. We expected
the participant’s cellphones to distract them in the
cellphone-present interval so they should have
longer response times and make more errors than
in the cellphone-absent condition. As mentioned
above, any detriment in performance in the
cellphone-present interval could be attributed to
either the presence of a cellphone or to fatigue.
Fortunately, order effects in visual search tasks
such as the one we used typically reflect practice
rather than fatigue (Menneer, Cave, & Donnelly,
2009; Menneer et al., 2012), so without our
manipulation participants should be more
8|
EXPECTATIONS AND CELLPHONES
proficient (faster responses and fewer errors)
during the second (cellphone-present) interval
than during the first (cellphone-absent) interval. If
instead participants proved to be less proficient
during the second interval, this would support our
hypothesis that the mere anticipation of a
cellphone call is distracting. Our hypotheses were
as follows:
a. Response times will be longer and
error rates will be higher in the
cellphone-present interval compared to
the cellphone-absent interval.
b. Differences between conditions will
increase with cellphone dependency
scores.
Method
Participants
The study was approved by the University
of Central Arkansas Institutional Review Board
prior to recruitment, and all participants were
treated in accordance with the guidelines
described by the APA. A total of 36 undergraduate
students (29 female) between the ages of 18 and
25 (mean = 20.1) volunteered for the experiment
in exchange for course credit. All participants
reported having normal or corrected-to-normal
vision.
Materials
Figure 1. A sample display from the visual search task.
The primary method of data collection was
a computer-based visual search task, previously
shown to rely on working memory (Sobel, Puri, &
Hogan, 2015). In each trial, participants searched
for a single target digit from among several nontarget (i.e., distractor) digits. Each search display
contained one of two target digits (3 or 8) and
four sets of two distractor digits (5 and 6) for a
total of nine items (one target and eight
distractors) arranged on an imaginary circle.
Figure 1 depicts a search display containing one
target digit 3 and four sets of the distractor digits
5 and 6. At the beginning of each trial, the search
display appeared on the computer monitor and
remained visible until the participant made a
response by pressing one of two keys on the
keyboard. Participants were asked to press the ‘/’
key to report the target appeared on the right side
of the display and the ‘z’ key to report it appeared
on the left side of the display. The fixation mark is
situated in the center of the circular array; so in
Figure 1, the target (the digit 3) is on the left side
of the display. The computer measured and
recorded the time between the onset of the search
display and the keypress for each trial. Response
times from error trials (e.g., the target appeared
on the left side of the display but the participant
pressed the key associated with the right side of
the display) were excluded from analysis, but the
number of errors during each interval was
HUFSTEDLER & SOBEL
recorded. In each of the two cellphone anticipation
conditions (absent and present), participants
completed 25 replications with each target digit (3
or 8) and target location (left side or right side) for
a total of 100 trials (= 25 x 2 x 2), lasting
approximately 10 minutes in each condition.
After completing both intervals of the visual
search task, participants completed the Mobile
Phone Dependency Questionnaire developed by
Toda et al. (2004) and revised by Kawasaki et al.
(2006). We further revised the questionnaire to
better adapt its items to a modern American
audience. For example, we replaced the word
“train” with the word “car” and “email” with “text.”
As can be seen from the set of questions contained
in the Appendix, participants provided responses
on a Likert Scale with values ranging from 1 to 5.
The sum of all answers to the survey’s 20
questions represented the level of cellphone
dependence.
Procedure
When participants signed up for the
experiment, they were asked to bring their
cellphones with them to the appointment. After
arriving at the lab, they were asked to give their
cellphone to the experimenter, who held it for
them in a sealed envelope while seated just
outside the experiment room. They were
additionally asked for their cellphone number and
were assured it would not be saved or shared
outside of the context of the experiment.
Participants then completed two intervals of
the visual search task. In the first interval, there
was no cellphone in the testing area. After
completing 100 trials, the computer program
paused and instructed the participants to alert the
experimenter. The experimenter then informed
participants they would be performing the same
task again, only this time they would be receiving a
phone call from the experimenter to the number
provided. Participants were given their cellphones
from the envelope and were directed to answer
the phone call as quickly as possible. As mentioned
previously, we wanted to expose participants to
the same number of trials in the cellphone-present
condition as the cellphone-absent condition. One
way to guarantee both conditions had the same
number of trials would be to deceive participants
|9
by telling them the experimenter would call during
the cellphone-present condition when in fact the
program would just quit after the necessary
number of trials. Because participants were
undergraduate students primarily within the
Psychology and Counseling department, we
believed some participants might discuss the
experiment with friends even though the
debriefing urged them not to do so, thereby
eliminating the sense of anticipation for
participants who had been warned of the
deception. To avoid deception the experimenter
measured the time required to complete the first
interval, then waited that duration before dialing
the telephone during the second interval. All
participants carried out more trials in the
cellphone-present condition than the cellphoneabsent condition, indicating the experimenter
never called any participants prematurely. For the
cellphone-absent condition, the results from only
the first 100 trials were analyzed. Participants
were asked if they happened to receive any phone
calls prior to the experimenter’s call, and all
participants indicated they had not. After the
second interval, participants completed the Mobile
Phone Dependency Questionnaire, then were
provided with a debriefing form and invited to ask
any questions.
Results
We conducted two analyses of variance with
interval as a within-subjects factor and
dependency as a covariate. The analysis of
response times did not support either of our
hypotheses because response times were not
significantly different in the cellphone-present
interval (M = ???, SD ? ???) than the cellphoneabsent interval (M = ????, SD ? ???), p ? ????, and
the interval x dependency interaction was not
significant, p = .908. The analysis of error rates
provided some support for our first hypothesis
because error rates were significantly higher
during the cellphone-present interval (M = ????, SD
? ????) than during the cellphone-absent interval
(M ? ????, SD ? ????), F ? ????, MSE ? ?????, p ? ???
?, but not the second hypothesis because the
interaction between interval and dependency was
not significant, p = .??.
10 |
Discussion
Anticipation of a cellphone call did not
slow responses, but it did induce more errors
compared to the absence of anticipation.
Cellphone dependency did not seem to have an
effect on either response times or error rates.
This is the first empirical evidence of cognitive
deficits being caused by the mere anticipation of a
phone call, without actually requiring the
participant to use the phone while performing a
task. Although the results of the experiment
revealed cellphone anticipation did not appear to
affect the speed of participants’ working memory,
it did affect accuracy. This implies that even when
people are not actively using their cellphones, the
mere anticipation of a call can impair the
accuracy of cognitive tasks. Also, the fact that
accuracy was impaired, while speed was not, has
serious implications on its own. Even if
anticipating a phone call does not slow mental
functioning, anticipation does cause more
mistakes, which might mask the effect of
anticipation. That is, when anticipating a phone
call, people perform mental activities just as
quickly as when not anticipating a phone call so
they may fail to notice any effect of anticipation;
while in fact, the anticipation may be causing
more errors. This could explain why students
bring their phones to class without expecting
they may interfere with their concentration.
It is also worth noting the accuracy deficits
were occurring with no significant relationship to
how dependent a participant was on his or her
cellphone. This could imply that regardless of
whether or not one considers themselves
dependent on a cellphone, having it present while
anticipating its use will cause deficits to occur.
This generalizes the results beyond individuals
who are considered technology-obsessed, to
anyone with a cellphone.
There were limitations to this study, which
did not allow for optimal methodology. This study
was conducted on a college campus with
participants who were exclusively undergraduate
students. This somewhat narrow age range may
not provide an accurate representation of
cellphone use among the total population of
cellphone users. Older adults, or younger
EXPECTATIONS AND CELLPHONES
adolescents, might not be accustomed to the
multitasking cellular phones demand, and
therefore might have had different results. A
broader age range and background for
participants
would
also
provide
more
generalizable data. An additional concern was the
aforementioned lack of counterbalancing and
how both practice and fatigue effects may have
influenced the scores during the second set of
trials. Subsequent studies could assess whether
counterbalancing the conditions might yield
different results.
Future research on the subject of cellphone
anticipation could investigate cognitive functions
other than working memory. For example, other
tests not involving visual search could be used
like reading comprehension, mathematical
problems, verbal skills, or even games such as
Tetris. It is very possible this effect can cause
deficits regardless of what one may be trying to
do. Also, subsequent studies could see if the same
effect exists when participants are in a more
natural setting, such as a classroom or work
environment, to better simulate these real life
situations we all face.
Given the dependency modern society has
developed on cellphones, the growing body of
research on the effects they have on our
functioning is becoming increasingly important.
As cellphones are used for more and more daily
functions to make life easier, we must gather
more empirical evidence regarding how they
might be impairing other areas. This paper has
addressed one such area, however, there are
many more yet to be explored.
References
Bergmann, S. (2015). Mobile wireless
competition: The proof is in the numbers.
Retrieved from http://
www.ctialatest.org/2015/07/14/mobilewireless-competition-the-proof-is-in-thenumbers/
Berti, S., Roeber, U., & Schroger, E. (2004).
Bottom-up influences on working memory:
Behavioral and electrophysiological
distraction varies with distractor strength.
Experimental Psychology, ?????? ???????. doi:
HUFSTEDLER & SOBEL
10.1027/1618-3169.51.4.249
Berti, S., & Schroger, E. (2003). Working memory
controls involuntary attention switching:
Evidence from an auditory distraction
paradigm. European Journal of Neuroscience,
?????? ?????????? doi: 10.1046/j.14609568.2003.02527.x
Boiteau, T. W., Malone, P. S., Peters, S. A., & Almor,
A. (2014). Interference between conversation
and a concurrent visuomotor task. Journal of
Experimental Psychology: General, ???? ??????
?. doi: 10.1037/a0031858
Cowan, N. (2008). What are the differences
between long-term, short-term, and working
memory? Progress in Brain Research, ???? 323
-338. doi:10.1016/S0079-6123( …
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