Media and Communication, 2016, Volume 4, Issue 3, Pages 79-89 79
Media and Communication (ISSN: 2183-2439)
2016, Volume 4, Issue 3, Pages 79-89
Adolescent Cellphone Use While Driving: An Overview of the Literature
and Promising Future Directions for Prevention
M. Kit Delgado 1,*, Kathryn J. Wanner 1 and Catherine McDonald 2
1 Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;
E-Mails: firstname.lastname@example.org (M.D.), Kathryn.Wanner@uphs.upenn.edu (K.J.W.)
2 School of Nursing, University of Pennsylvania, Philadelphia, PA 19104, USA; E-Mail: email@example.com
* Corresponding author
Submitted: 17 December 2015 | Accepted: 11 March 2016 | Published: 16 June 2016
Motor vehicle crashes are the leading cause of death in adolescents, and drivers aged 16–19 are the most likely to die
in distracted driving crashes. This paper provides an overview of the literature on adolescent cellphone use while driv-
ing, focusing on the crash risk, incidence, risk factors for engagement, and the effectiveness of current mitigation strat-
egies. We conclude by discussing promising future approaches to prevent crashes related to cellphone use in adoles-
cents. Handheld manipulation of the phone while driving has been shown to have a 3 to 4-fold increased risk of a near
crash or crash, and eye glance duration greater than 2 seconds increases crash risk exponentially. Nearly half of U.S.
high school students admit to texting while driving in the last month, but the frequency of use according to vehicle
speed and high-risk situations remains unknown. Several risk factors are associated with cell phone use while driving
including: parental cellphone use while driving, social norms for quick responses to text messages, and higher levels of
temporal discounting. Given the limited effectiveness of current mitigation strategies such as educational campaigns
and legal bans, a multi-pronged behavioral and technological approach addressing the above risk factors will be neces-
sary to reduce this dangerous behavior in adolescents.
accidents prevention; adolescent; cell phones; distracted driving; text messaging
This review is part of the issue “Adolescents in the Digital Age: Effects on Health and Development”, edited by Dan
Romer (University of Pennsylvania, USA).
© 2016 by the author(s); licensee Cogitatio (Lisbon, Portugal). This article is licensed under a Creative Commons Attrib-
ution 4.0 International License (CC BY).
Cellphones, and the connectivity they provide, have
become a part of everyday life. In recent years, cell-
phone use, in particular communication by text mes-
saging, has dramatically increased in prevalence and
popularity across the world. In 2014, an estimated
169.3 billion text messages were sent worldwide, com-
pared to 110 billion in 2009 (CTIA, 2013). Adolescents
report that texting is the most common way that they
stay in contact with friends (Lepp, Barkley, & Karpinski,
2014), sending an average of 100 texts per day
(Nielson, 2010). Problematic cellphone use and texting
has been likened to other addictive behaviors, and may
have negative effects on both academic performance
and mental health (Lee, Chang, Lin, & Cheng, 2014;
Lepp, et al., 2014; Walsh, White, & Young, 2008).
However, texting has also become a way that adoles-
cents forge social bonds, and texting between adoles-
cents often serves to promote social cohesion in peer
groups (Ling, 2012). More than half of adolescents text
their friends every day, and many of them are texting
their friends multiple times a day (Lenhart, Smith, An-
derson, Duggan, & Perrin, 2015).
The phenomenon of distracted driving from cell-
phone use has caught the attention of the national
Media and Communication, 2016, Volume 4, Issue 3, Pages 79-89 80
media in the United States (U.S.). There have been
numerous reports on its dangers (CNN, 2014; DePalma,
2014; Muskal, 2015), prevalence (Richtel, 2015), and
possible solutions (Richtel, 2014). The U.S. federal gov-
ernment’s Healthy People 2020 objectives pinpoints
distracted driving related to cellphone use as the top
emerging cause of injury and highlights the need for fu-
ture research (Office of Disease Prevention and Health
Promotion, 2015). Several prominent public awareness
campaigns have been aimed at promoting safety while
driving, and in 2010 there was a national summit that
brought together safety experts, senators, and industry
leaders, to focus on this issue (AAA, 2013). Given the
gravity of the problem of distracted driving, and in con-
cert with this special issue on “Adolescents in the Digi-
tal Age: Effects on Health and Development,” the ob-
jectives of this paper are to provide an overview on the
incidence, crash risk, risk factors for engagement, and
the effectiveness of current mitigation strategies. We
conclude by proposing promising future approaches to
prevent crashes due to cellphone use in adolescents.
2. Public Health Magnitude of Distracted Driving in
Motor vehicle crashes (MVCs) are the leading cause of
death and disability in adolescents in the U.S. and
globally (World Health Organization, 2013). Based on
police crash report data collected by the U.S. National
Highway Traffic Safety Administration (NHTSA), in
2013, 2,650 adolescents, aged 16–19, died as a result
of a motor vehicle collision (MVC), making this the
number one cause of death in the U.S. for this age
group; another 292,000 were treated for injuries (CDC,
2013). A disproportionate amount of MVCs related to
distracted driving involve teenagers: although they
comprise 6% of all drivers killed in MVCs, teenagers ac-
count for 10% of all drivers determined to be distract-
ed at the time of a crash and 11% of all drivers killed in
crashes related to documented cellphone use (NHTSA,
2015b). NHTSA reports that there were a total 45 teen-
age drivers and 161 drivers (aged 20–29) killed in cell-
phone distraction crashes in 2013. These numbers un-
derestimate the true magnitude of the problem since
the statistics are based on documented cellphone use
while driving as measured through police reports.
3. Incidence of Cellphone Use While Driving in
The majority of evidence on the proportion of the ado-
lescent population that uses their cellphone while driv-
ing has been obtained through population-level self-
report surveys. In 2014, 94% of U.S. drivers aged 18–29
reported owning a smartphone (State Farm, 2014). A
Centers for Disease Control and Prevention survey of
8,505 students 16 years of age and younger, found that
42% of U.S. high school students admit to engaging in
texting while driving, which included both text messag-
ing and emailing while driving, at least once per month
(Olsen, Hanowski, Hickman, & Bocanegra, 2009). A
more recent nationally representative survey of 1,243
high school students, funded by the National Institutes
of Health (NIH), found that 83% reported engaging in
electronic device use while driving at least once in the
last 30 days (Ehsani, Li, & Simons-Morton, 2015). Spe-
cifically, 71% made or answered a phone call, 64% read
or sent a text message, 20% read or sent an email, 29%
checked a website, 71% changed music, 12% used a
tablet, and 53% looked at directions or a map. Young
drivers reported using electronic devices while driving
on 19% of the days they drove. Males were more likely
to use a tablet or a computer while driving, teens from
moderate and high affluence households were more
likely to check websites, and rural participants were
less likely to look at directions or a map than urban
participants (Ehsani et al., 2015).
It appears that social media use while driving is in-
creasing among adolescents and young adults based on
a survey, conducted annually since 2009 by the State
Farm insurance company, of 1,000 drivers, aged 18 and
older. According to this survey, the proportion of
young drivers, aged 18–29, who read social media
websites while driving doubled from 21% in 2009 to
41% in 2014 (State Farm, 2014). Likewise, the propor-
tion of this population who actually post to social media
while driving increased from 20% in 2009 to 30% in
2014. This form of communication may eventually sup-
plant text messaging, as the same survey found the pro-
portion of young adults age 18–29 who texted while
driving was 58% in 2014, down from 71% in 2009.
NHTSA’s National Occupant Protection Use Survey
(NOPUS) provides the only nationwide probability-
based observed data on driver electronic device use
in the U.S. Data are collected by trained observers
standing at the roadside of probabilistically sampled
intersections, who are observing drivers while
stopped at the intersection. The overall percentage of
drivers who are text-messaging, or visibly manipulat-
ing handheld devices while driving, increased from 1.7
% in 2013 to 2.2% in 2014. However, among the 16–
24 year old age group, this proportion was much
higher, and increased from 2.9% in 2013 to 4.8% in
2014 (NHTSA, 2015a). These statistics likely underes-
timate the true incidence of handheld cellphone use
since the below eye-level view beneath the windows
and windshield is not captured.
Local roadside observation based studies suggest a
higher prevalence of cellphone use while driving. A
study conducted at 11 intersections in the Birmingham
Alabama metro area found that among drivers pre-
sumed to be less than 30 years olds (N=853), 8.4%
were observed to be texting and another 11.7% were
observed to be talking on the phone (Huisingh, Griffin,
Media and Communication, 2016, Volume 4, Issue 3, Pages 79-89 81
& McGwin, 2015). Among drivers of all ages who were
witnessed to be texting, 49% of these episodes were at
estimated speed of more than 25 miles per hour. A
similar study conducted in one intersection in Pennsyl-
vania in 2014 of 2,000 observed drivers, found 3% of
drivers in motion were texting or visibly manipulating
handheld devices and 5% were engaged in handheld
phone calls. Among the stopped drivers, 14.5% were
texting and 6.3% were talking (Bernstein & Bernstein,
2015). Further work is necessary to describe the pro-
portion of time individual drivers use their phone while
the car is in motion.
Naturalistic studies using non-obtrusive video
event recorders installed in drivers’ cars can provide a
much more nuanced incidence of cellphone use and
other distracted driving behaviors. Typically, the re-
corder runs continuously, it only saves information
when a vehicle movement (decelerating, accelerating,
or turning) produces a g-force that exceeds a prede-
termined threshold. Lower thresholds can be set such
that clips can be recorded intermittently during nor-
mal periods of driving. A naturalistic study using
event-triggered recording in 52 high-school aged
drivers found that cellphone use was present in 6.7%
video clips, followed by adjusting vehicle controls
(6.2%) and grooming (3.8%) (Foss & Goodwin, 2014).
Of episodes of cellphone use, one third involved hold-
ing the phone to the ear, with the rest involving
handheld manipulation. Only 1% of these recorded
episodes involved hands-free talking. Interestingly,
cellphone use while driving was much less likely to
occur if there was a passenger in the vehicle.
A naturalistic study using continuous video record-
ing of young drivers 20–30 years old (n=36) for 4 weeks
in 2006–2007 found that these drivers had a mean 2.1
phone conversations per hour for drive time for a
mean average conversation duration of 2.6 minutes
(Funkhouser & Sayer, 2012). They also had a mean av-
erage of 4.0 visual-manual cellphone use task per hour
of drive time with a mean average duration of 0.51
minutes. When data from all drivers aged 20–70 years
old was analyzed (n=108), it was found that 23% of all
visual manual tasks were initiated when stopped and
another 5% were initiated at 5 miles per hour or less.
Of concern, this indicated that nearly three quarters of
handheld phone use episodes occurred while moving.
In fact, more than 45% of these episodes were initiated
at speeds of more than 25 miles per hour, consistent
with the estimated 49% of texting episodes witnessed
in the roadside observation study from Alabama
(Huisingh et al., 2015). Given that speed is the biggest
predictor of injury severity in motor vehicle collisions
(Kockelman & Kweon, 2002), these findings suggest
that the riskiness of cellphone use episodes in terms of
causing serious crashes is likely to be heterogeneous,
and needs further clarification in future research (see
4. Safety Risk of Engaging in Cellphone Use While
The first large scale study to evaluate the safety risk of
cellphone use while driving was published in the New
England Journal of Medicine in 1997 (Redelmeier &
Tibshirani, 1997). This epidemiologic study compared
detailed time-stamped phone bill usage records of in-
dividuals, moments before a motor vehicle crash as
well as records one week before the crash. The risk of
collision was found to be 4 times higher during a phone
call. However, subsequent research has suggested a bi-
as to this design; study subjects were less likely to have
been driving during the control period, reducing their
potential exposure to a crash (Young, 2012). Since
then, dozens of studies with more robust designs have
been published evaluating the risk of cellphone use
while driving, and in particular texting while driving, in
adult drivers. A meta-analysis of 28 epidemiologic, driv-
ing simulator, and naturalistic studies, which use vehi-
cle instrumentation to measure actual driving, found
that texting while driving increases the risk of crashing
by at least 3 to 4-fold (Caird, Johnston, Wilness, As-
bridge, & Steel, 2014).
Fewer studies have examined the crash risk of cell
phone use among adolescent drivers. Klauer et al.
(2014) recently conducted a systematic review of
quantitative epidemiologic, driving simulator, and nat-
uralistic studies examining secondary task engagement
while driving with adolescents; they identified 15 stud-
ies that met inclusion criteria (Klauer et al., 2014). Alt-
hough this systematic review investigated more than
just cell phone use (secondary task was defined as eat-
ing, using a cellphone, inserting a compact disc), their
findings about the common mechanism that increases
crash risk is notable. Overall, this systematic review
found that secondary tasks while driving, where eyes
were not on the forward roadway, increased crash risk
(e.g. looking down at a phone while texting) (Fitch,
Hanowski, & Guo, 2014; Klauer, Dingus, & Neal, 2006;
Olsen et al., 2009); however, secondary tasks where
eyes were not required to be off the forward roadway
(e.g. talking on a cell phone) did not significantly in-
crease crash risk (Harbluk, Noy, Trbovich, & Eisenman,
2007; Klauer, Ehsani, McGehee, & Manser, 2015).
One of the most rigorous studies included in Klauer
et al.’s review followed 42 newly licensed adolescent
drivers for 18 months immediately after licensure with
in-vehicle event-triggered cameras (Klauer et al., 2014).
This study found that dialing the phone was associated
with the highest risk of a crash or near crash event
(Odds Ratio [OR] 8.32), followed by reaching for the
phone (OR 7.05), and texting or using the Internet (OR
3.87); talking was not associated with the crash risk
(OR 0.61). Secondary analysis of these data revealed
that the duration of glancing away from the forward
roadway steadily increases the risk of a crash beginning
Media and Communication, 2016, Volume 4, Issue 3, Pages 79-89 82
with glances longer than 1 second. Glances of 2 sec-
onds or more while engaging in handheld cellphone
use were associated with a 5.5-fold increase in the risk
of crash or near crash event (Simons-Morton, Guo,
Klauer, Ehsani, & Pradhan, 2014). These important
findings imply that interventions and policies to reduce
the crash risk of distracted driving, and in particular
distraction from cellphone use, need to focus on main-
taining the driver’s eyes on the forward roadway.
5. Knowledge of the Risks of Cellphone Use
Generally, adolescents report that texting or talking on a
handheld phone while driving is dangerous. A survey
found that the 97% of U.S. adolescents know texting and
driving is dangerous based on a survey of 1,200 teenag-
ers aged 15–19 years old (AT&T, 2012). However,
knowledge of safety risks does not necessarily indicate
adolescents will not engage in the behavior. In a focus
group study of 16–18 year olds with less than 1 year of
licensure, participants indicated that they understand
the dangers of cellphone use while driving, however,
they still reported driving while engaging in talking, tex-
ting and social media app use (McDonald & Sommers,
2015). This suggests that simply continuing to raise
awareness of the risks of cellphone use while driving
may not be very effective for reducing this behavior, giv-
en that most adolescents are aware of the risks. A recent
survey of college students found they were much more
likely to text behind the wheel than drink and drive, de-
spite perceiving that the risks of texting were similar to
drinking (Terry & Terry, 2015). Furthermore, participants
perceived their peers as being more accepting toward
cellphone use while driving than themselves, suggesting
that one factor underlying the discrepancy between per-
ceived risk and risk exposure may be the weakness of
social norms opposed to texting while driving.
6. Risk Factors for Engagement: Development, Peers
Adolescents are a particularly vulnerable group at risk
for crashes. Adolescent drivers are at greatest risk for a
crash in the first 6–12 months of licensure (Mayhew,
Simpson, & Pak, 2003; McCartt, Shabanova, & Leaf,
2003; Williams & Tefft, 2014). As adolescents drive,
they acquire more experience and skill; this skill acqui-
sition for newly licensed drivers strongly influences
crash risk reduction in the first year of driving (McKnight
& McKnight, 2003). However, experience is not the only
contributor to crashes, as the developmental changes
during adolescence can influence crash risk.
Major changes in the brain occur throughout ado-
lescence that can lead to increased risk taking and sen-
sation seeking, and a movement towards a greater af-
filiation with their peers (Giedd, 2012). This is not to
indicate that adolescents are taking risks with their cell
phones while driving simply to challenge safety limits.
Rather, adolescents may drive with incomplete matu-
ration of cognitive and motor skills, and decision-
making may be modulated by emotional and social fac-
tors.(Romer, Lee, McDonald, & Winston, 2014) The ad-
olescent pre-frontal cortex has not fully matured; ade-
quate experience in risk assessment may not have
occurred, nor may adolescents fully exert control over
those risks—and all the while, there is a rise in sensa-
tion seeking (Giedd, 2012). Impulsivity and present bi-
ased preferences (Atchley & Warden, 2012), the ten-
dency to place more weight on benefits realized now
and less weight on costs realized in the future, is asso-
ciated with a higher likelihood of engaging in texting
while driving (Hayashi, Russo, & Wirth, 2015). Adoles-
cents are more present-biased than adults indicating a
greater cognitive difficulty with delaying gratification
(Romer, Duckworth, Sznitman, & Park, 2010), and in this
context, delaying checking their phone and/or respond-
ing to a text message until they have stopped driving.
A 2014 systematic review of 29 papers identified
several other psychological factors associated with
cellphone use while driving in young drivers. These in-
cluded the importance of an incoming or outgoing call,
social acceptance, possession attachment, and a positive
attitude toward cellphone use while driving (Cazzulino,
Burke, Muller, Arbogast, & Upperman, 2014). The im-
portance of answering or making the call while driving
was found to have greater weight than the perceived
risk associated with cellphone use while driving.
The proximity of relationship of the individual who
is communicating with the adolescent influences cell-
phone use (Atchley & Warden, 2012; LaVoie, Lee, &
Parker, 2015). In a focus group study, adolescent par-
ticipants indicated that context mattered; the individu-
al involved in the communication, and the reason be-
hind it, would influence whether they would use the
cell phone while driving (McDonald & Sommers, 2015).
A survey study of 395 adolescent drivers found that
adolescents most often spoke to parents while driving
(50%), rather than a significant other (16%) or friend
(21%) (LaVoie et al., 2015). This indicates that reducing
check in calls from parents may reduce cellphone use
while driving. However, adolescent drivers were more
likely to text a significant other (30%) or friend (27%)
rather than their parents (16%) (LaVoie et al., 2015).
Social norms strongly influence texting behavior, as
89% of adolescents expect a response to a text mes-
sage within 5 minutes (Bowen et al., 2009). Together
these findings indicate that interventions to reduce
texting should alleviate the urge to respond immedi-
ately to close social contacts, such as setting up auto-
mated responses to incoming text messages.
Carter, Bingham, Zakrajsek, Shope and Sayer (2014)
also conducted a survey with adolescent–parent dyads
and found that actual and perceived distracted driving
behaviors of parents, and perceived distracted driving
Media and Communication, 2016, Volume 4, Issue 3, Pages 79-89 83
behaviors of peers, were predictive of adolescent dis-
tracted driving behavior. Finally, there is increasing ev-
idence for compulsive cellphone use as a diagnosable
behavioral addiction, given the behavioral and neuro-
biological characteristics of this behavior (Billieux,
Maurage, Lopez-Fernandez, Kuss, & Griffiths, 2015).
Use in dangerous situations, such as while driving, is
measured as a factor in scales of problematic cellphone
use (Merlo, Stone, & Bibbey, 2013). More research is
needed to better determine the correlation between
measures of general problematic or compulsive phone
use and risky cellphone use while driving.
7. Social and Logistical Barriers to Reducing Cellphone
Use While Driving
Understanding why adolescents may not want to ab-
stain from in-vehicle cellphone use provides insights in-
to behavioral strategies that may be more effective for
reducing use while driving. Dominant disadvantages of
abstaining from in-vehicle cellphone use among ado-
lescents include: the inability to communicate location
or letting others know their time of arrival, the inability
to get help if the driver got lost or forgot something,
and increased difficulty for parents to get in touch with
the driver (Hafetz, Jacobsohn, García-España, Curry, &
Winston, 2010). Other disadvantages of abstaining
from in-vehicle cellphone use are giving up the ability
to call for emergency help. This may include calling 911
if being followed by a potential stalker, calling to report
a drunk driver on the road, or calling for emergency
medical care in the case of a MVC. In fact, in the land-
mark 1997 New England Journal of Medicine study on
drivers who owned cellphones and were involved in
MVCs, 39% of drivers called 911 from the scene of the
crash on their cellphone (Redelmeier & Tibshirani,
1997). Therefore, interventions to reduce risky cell-
phone use while driving should make allowances for
calls in emergency situations and should safely balance
needs related to navigation and trip communication.
8. Effectiveness of Current Mitigation Strategies
8.1. Legal Bans
In the U.S., states have enacted policies to help de-
crease cellphone use while driving. For example, ac-
cording to the Insurance Institute of Highway Safety
(2015), as of the end of December 2015, talking on a
hand-held cellphone while driving has been banned for
all drivers in 14 states and the District of Columbia; ad-
ditionally, the use of all cellphones by novice drivers is
restricted in 37 states and the District of Columbia.
Text messaging has been banned for all drivers in 46
states and the District of Columbia. In addition, novice
drivers are banned from texting in Missouri and Texas
(Insurance Institute for Highway Safety, 2015).
There are mixed results on the effectiveness of
cellphone restrictions. One of the earliest studies ex-
amining the effect on the general population investi-
gated the relationship between collision claim frequen-
cies and texting bans in 4 states (Highway Loss Data
Institute, 2010). This study found that texting bans
were actually associated with increased frequencies of
collision claims. The authors posited that this increase
may have stemmed from the unintended consequence
of drivers lowering their phones from view to avoid ci-
tations and fines and, in doing so, taking their eyes off
the road more than they did before the implementa-
tion of the bans. Two other studies using observation
and self-report outcomes in the adolescent driver pop-
ulation showed that laws restricting cellphone use have
not had long-term effects on adolescent drivers’ cell-
phone use while driving (Ehsani, Bingham, Ionides, &
Childers, 2014; Goodwin, O’Brien, & Foss, 2012).
Studies examining the effect of cell phone bans on
MVC fatalities and hospitalizations have demonstrated
modestly positive outcomes. Primary enforced laws
banning all drivers from texting was associated with a
3% reduction in fatalities in all age groups; banning on-
ly young drivers from texting had the greatest impact
on reducing deaths among those aged 15 to 21 years
(Ferdinand et al., 2014). A similar study found an 8%
decrease in fatalities in states that universally banned
texting while driving and made it a primary offense.
However, this effect was only apparent for the law’s
first three months (Abouk & Adams, 2013). The study
also found that this loss of effect was lessened in states
that had universal bans against handheld use of cell
phones. The authors suggest that the lack of effective-
ness of texting bans was due to poor enforcement;
drivers refrained from texting immediately after the
law’s announcement and implementation but returned
to texting if they believed the law was not being en-
forced (Abouk & Adams, 2013). Finally, texting bans
were also significantly associated with reductions in
hospitalizations among those aged 22 to 64 years and
those aged 65 years or older, but did not significantly
reduce hospitalizations for adolescents (Ferdinand et
al., 2015). While in these analyses it cannot be deter-
mined whether the crashes and hospitalizations ana-
lyzed were caused by distracted driving or not, these
studies suggest that bans with primary enforcement
can reduce the burden of injury from cellphone use.
This is further supported by the results of a high visibil-
ity law enforcement campaign “Phone in One Hand,
Ticket in the Other” implemented in Connecticut and
New York, which was shown to have a modest reduc-
tion in observed handheld cellphone usage rates over
the course of a year (Chaudhary, Cassanova-Powell,
Cosgrove, Reagan, & Williams, 2012). Given the logisti-
cal difficulty needed to enforce bans, such as catching a
driver using a phone out of view, additional mitigation
strategies may be necessary.
Media and Communication, 2016, Volume 4, Issue 3, Pages 79-89 84
8.2. Education to Increase Awareness
Several national public health campaigns have
emerged aimed at the prevention of distracted driving.
For example, NHTSA’s distraction.gov is a national
campaign to increase awareness of distracted driving
through informational videos, facts, and personal nar-
ratives (Distraction.gov, 2015). There have been sever-
al industry sponsored campaigns aimed at the preven-
tion of distracted driving, such as AT&T’s “It Can Wait”
wait campaign, which encourages individuals to reach
out to friends and family and to pledge to abstain from
texting and driving (AAA, 2013; AT&T, 2012). These
campaigns consist of online pledges, where individuals
can pledge to abstain from texting and driving, and ed-
ucational videos with the goal of increasing awareness
of the dangers of distracted driving. Despite these ma-
jor investments, there are no data to suggest that
these campaigns have had any effect on cellphone use
while driving. Given 97% of adolescent drivers already
know that cellphone use while driving is dangerous
(AT&T, 2012), solely increasing awareness of risks is un-
likely to lead to wide scale behavior change.
There are few published studies of more targeted
educational interventions in the adolescent driver
population. One effective intervention led by staff from
a pediatric trauma center hospital invited 61 student
leaders from a local high school for a half-day educa-
tional session. The student leaders then went back to
their two high schools to implement a yearlong peer-
to-peer campaign focused on a clear no texting while
driving campaign (Unni, Morrow, Shultz, & Tian, 2013).
There was a decrease in unannounced observation of
actual texting and driving (from 17% to 8%, p<0.001)
among high school students driving on roads near the
school a year after the intervention compared to just
prior to the intervention (Unni, et al., 2013).
8.3. Technological Interventions
Over the last decade, in-vehicle technologies have
been developed and tested with the aim of improving
adolescent driving behavior through monitoring and
feedback. Feedback on g-force events, recorded using
an in-vehicle event triggered video recording device in
which parents were involved in the feedback loop, has
been shown to be effective in reducing the occurrence
of these near-crash events (Simons-Morton et al.,
2013). Some auto insurance companies have moved to
offer use of event-triggered video monitors and paren-
tal feedback on recorded driving errors and distracted
driving behavior (American Family Insurance, 2016).
More recently, in the last five years, smartphone
applications have been developed to directly measure
cellphone use while driving. “Software only” applica-
tions rely on the phone’s sensors (e.g. accelerometer
and GPS) to determine whether the phone is traveling
at a speed consistent with driving (e.g. >25 mph). If
traveling over a certain speed threshold, the applica-
tion can be set to disable the phone unlock screen and
block incoming and outgoing text messaging and calls.
Most of these applications have been developed for
the Android platform and there are currently dozens of
such applications available in the Google Play store.
Because of the more stringent developer restrictions of
the iOS, there are fewer such applications available in
the iTunes store. The major barriers to adoption of
“software only” applications are the current inability to
detect whether the phone is being used on a car vs.
another vehicle such as a bus or train, and battery
drain from continuous use of GPS in the background.
“Software–Hardware” applications have also been de-
veloped to overcome some of these limitations. This
involves the instillation of a device in the car that pairs
with a smartphone application via Bluetooth technolo-
gy. These devices were developed to be installed in the
car’s OBD-II (On-board diagnostics-II) data port and
more recently have included solar powered designs
that can be installed on the windshield.
To our knowledge there are three completed stud-
ies of smartphone applications to block cellphone use
while driving, with all three demonstrating a reduction
in cellphone use while driving at non-zero speeds
(Creaser, Edwards, Morris, & Donath, 2015; Ebel et al.,
2015; Funkhouser & Sayer, 2013). For example, in the
largest study to date, involving 274 novice teen drivers
followed for 1 year, the rate of text messages sent per
mile driven for each given month post licensure was at
least 5 to 10 times higher in the control group (0.05 to
0.20 texts per mile driven) than in the blocking group
(0.0 to 0.02 texts per mile driven) (Creaser et al., 2015).
The number of text messages sent tripled by one year
since licensure in the control group compared with the
first 8 months of driving. On the other hand, the rate
remained stable in the blocking group (Creaser et al.,
2015). However, behavioral engagement strategies will
likely be necessary to enable the success and sustaina-
bility of cellphone blocking indicating a low likelihood
of use beyond the study. In the above mentioned
study, 15% of the teen drivers in the treatment group
were caught trying to game the system either by find-
ing ways to bypass the blocking system or by borrow-
ing a phone (Creaser et al., 2015). In one study of adult
drivers, after an intervention period of blocking was
disabled, there was no lasting behavior change as cell-
phone use while driving returned to baseline levels
(Funkhouser & Sayer, 2013). Furthermore, when sur-
veyed, the adult participants had overall not very posi-
tive views of the blocking technology.
9. Knowledge Gaps in the Science
Despite the widespread emergence of cellphone use
while driving among adolescent drivers over the last
Media and Communication, 2016, Volume 4, Issue 3, Pages 79-89 85
decade, and the associated research activity on this
behavior, several critical knowledge gaps persist. One
of the major challenges in understanding the preva-
lence of this behavior and measuring effectiveness of
intervention strategies is a lack of readily collectable,
reliable, and valid measures of cellphone use while
driving. Despite the ease of collection of survey data on
magnitude of self-reported cellphone use while driving,
there is scant evidence to support its validity. Based on
the comparison between self-reported general
smartphone use episodes and actual recorded epi-
sodes, survey self-report methods likely underestimate
the number of cellphone use episodes (Andrews, Ellis,
Shaw, & Piwek, 2015). The biggest problem with widely
accepted survey self-report measures of cellphone use
while driving is that there is no distinction between use
while stopped vs. use while the car is in motion (Olsen,
Shults, & Eaton, 2013). Only one study to our
knowledge measured self-reported cellphone use and
actual cellphone use while driving using a cellphone
app and in vehicle monitoring device, but these
measures were not directly compared (Creaser et al.,
2015). There is a need for future naturalistic studies to
clarify the correlation between self-reported cellphone
use and actual cellphone use as well as the frequency
and duration of use given the transient risks of the ex-
posure on crash risk.
The association between driving context in which
cellphone use is initiated and crash risk has also not
been well elucidated. For example, it is not known if
handheld use while stopped or in very low speed traffic
actually poses risk of injury. Additionally, it is not
known how type of handheld cellphone use (e.g. tex-
ting vs. checking email vs. looking at GPS directions) af-
fects level of risk in terms eye glance duration, real
driving performance, and near crash and crash events.
These knowledge gaps are difficult to fill because they
would require naturalistic studies with large sample
sizes. Leveraging smartphone apps that can track type
of phone use while driving may be a cost-effective way
to study these questions in larger and broader popula-
tions than have been studied to date in instrumented
vehicle naturalistic studies.
Furthermore, there is a great need to better under-
stand the effectiveness of current countermeasures
and assess why many countermeasures have failed to
reduce this behavior. Specifically, it should be deter-
mined whether cellphone bans have led to the unin-
tended consequence of drivers holding their phone be-
low window-level view to avoid detection when texting
thereby taking their eyes off the road longer. If con-
firmed, this could undermine the effectiveness of en-
forcing cellphone bans. Additionally, further qualitative
research with adolescent drivers and their parents
would shed light on addressable barriers to the adop-
tion of several available smartphone based apps and
settings that limit the temptation to text while driving.
Finally, as smartphone and in-vehicle technology rapid-
ly evolves, there is an urgent need to determine
whether hands-free features actually reduce cognitive
distraction and keep the drivers eyes on the road. Stud-
ies to date suggest that most of these features, such as
voice to text functions, do not reduce distracted driving
and may even increase the risk of distraction (Strayer,
Turrill, Coleman, Ortiz, & Cooper, 2014).
10. Promising Future Directions
Given the limited effectiveness of current isolated miti-
gation strategies, a multi-pronged regulatory, behav-
ioral, and technological approach addressing the above
risk factors will be necessary to reduce this dangerous
behavior in adolescents. For legal bans to be effective,
they must be aggressively enforced. As evidenced by
prior research, bans lose effectiveness shortly after im-
plementation, likely due to lack of enforcement
(Highway Loss Data Institute, 2010). As demonstrated
in a pilot program in two northeastern U.S. states, high
visibility law enforcement campaigns that increase
awareness of the legal and financial repercussions of
texting in addition to actually enforcing the bans, im-
prove the effectiveness of the legal ban (Chaudhary, et
al., 2012). It is also likely that increasing the financial
and legal repercussions of getting caught using a cell-
phone while driving would further increase the effec-
tiveness of legal bans. The combination of these ap-
proaches are theoretically sound given that individuals
value and are more sensitive to losses than equivalent
gains based on the behavioral economic phenomenon
of loss aversion (Tversky & Kahneman, 1991). Never-
theless, the logistical challenges of enforcing bans, par-
ticularly the accurate detection of the behavior (hold-
ing and manipulating phone in hand vs. holding
another object or looking down in car) will continue to
limit the overall effectiveness of bans, necessitating
other strategies to reduce use.
Educational interventions aimed at reducing texting
while driving and distracted driving in general should
focus on targeting the mechanism by which distraction
causes crashes—by getting drivers to keep their eyes
on the forward roadway. Furthermore, efforts to re-
duce cellphone use while driving in adolescents may be
more successful if the intervention also addresses the
parents’ behavior. There is promising evidence that ac-
tive parental involvement enhances the effectiveness
of adolescent driving interventions (Curry, Peek-Asa,
Hamann, & Mirman, 2015). Furthermore, given the
strong correlation between parental engagement with
texting and driving and their child’s behavior, strategies
that enable parents to be better role models for their
children are highly promising (Carter et al., 2014). Edu-
cational interventions that can be delivered online
would increase the scalability of these efforts and po-
tential adoption in driver’s education classes.
Media and Communication, 2016, Volume 4, Issue 3, Pages 79-89 86
While smartphone applications that disable
handheld use while driving are effective in research
settings, it is questionable whether individuals will
continue to use such applications without a behavior-
al strategy to sustain use. This is evidenced by the fact
that a significant proportion of adolescent drivers
tried to bypass cellphone blocking in one study
(Creaser et al., 2015). In the short term, the apps can
be designed to be more user friendly by allowing au-
tomated responses to incoming messages and hands
free navigation, enabling emergency calls, and balanc-
ing functionality with maintaining battery life. Incor-
porating adolescents and young adults into the design
process would like also increased adoption. In the
long term, as with all mobile devices and apps, sus-
taining use will require behavioral engagement strat-
egies (Patel, Asch, & Volpp, 2015). Feedback loops
could be better designed to sustain engagement with
cellphone blocking apps using concepts from behav-
ioral economics. Given that some of those who en-
gage in texting while driving overweigh immediate
benefits (Hayashi et al., 2015), promising intervention
would be to provide frequently delivered (e.g. daily)
rewards to make the cognitive appraisal of abstaining
from handheld phone use more attractive than the
urge to engage in texting while driving (Loewenstein,
Asch, & Volpp, 2013). Making a portion of parental
weekly allowances contingent on good behavior may
be one way to operationalize this through the use of
smartphone based apps that monitor cellphone use
behavior while driving (e.g. $1/day of allowance given
for each day with no measured texting while driving).
In the future, financial rewards could be scaled up and
implemented on a large scale through repurposing ex-
isting auto-insurer teen driver discounts into discounts
or rewards based on actual driving performance, as
measured by in vehicle devices and smartphone appli-
cations (Cambridge Mobile Telematics, 2014). Auto in-
surance and car rental companies are already providing
in-vehicle devices and associated smartphone applica-
tions to reduce cellphone distraction (Insurance and
Technology, 2013; Jackson, 2016).
Cellphones are a mainstay of connectivity in most ado-
lescents’ daily lives, as a form of entertainment, infor-
mation and communication. The pervasiveness of ado-
lescent cellphone use can have negative effects on
driving behavior and increase crash risk. Current strat-
egies to decrease adolescent cellphone use while driv-
ing fall short of what is needed to curb teen driver
crashes and improve adolescent health. Interdiscipli-
nary approaches show promise, and those that inte-
grate cellphone policies, technology, and individual and
family behaviors will be necessary to reduce this dan-
gerous behavior in adolescents.
This work was supported by Research Career Develop-
ment Program in Emergency Medicine of the National
Institutes of Health under award number K12HL109009
(Delgado), as well as the Penn Roybal Center for Behav-
ioral Economics under award number P30AG034546
(Delgado). Catherine C. McDonald was supported by
the National Institute of Nursing Research under award
number R00NR013548. The content is solely the re-
sponsibility of the authors and does not necessarily
represent the official views of the National Institutes of
Conflict of Interests
The authors declare no conflict of interests.
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About the Authors
Dr. M. Kit Delgado
M. Kit Delgado, MD, MS, is an Assistant Professor in the Department of Emergency Medicine at the
University of Pennsylvania. Dr. Delgado has secondary appointments as an Assistant Professor in the
Department of Biostatistics and Epidemiology and as a Senior Fellow in the Leonard Davis Institute of
Health Economics. Dr. Delgado’s research focuses on reducing the public health burden caused by in-
Kathryn J. Wanner
Kathryn J. Wanner, MA, is a Research Project Manager for the Center for Emergency Medicine Policy
Research at the University of Pennsylvania. She received her Master of Art’s in the Sociology of Edu-
cation from New York University.
Dr. Catherine McDonald
Catherine McDonald, PhD, RN is an Assistant Professor at the University of Pennsylvania School of
Nursing and has a secondary appointment at Children’s Hospital of Pennsylvania as an Assistant Pro-
fessor of Nursing in Pediatrics in the Department of Pediatrics. Her work focuses on the factors that
contribute to adolescent morbidity and mortality associated with injury and violence.