2. feedback that is delivered to parents by mail, email, or online. Eva-
luations of these systems have generally found that they are successful
in reducing driving events, which include driving errors and unsafe
behaviors, although the impact on overall driving safety and long-term
outcomes is less clear (Curry et al., 2015; McCartt et al., 2010; Carney
et al., 2010; McGehee et al., 2007; Simons-Morton et al., 2013; Farah
et al., 2014; Shimshoni et al., 2015).
However, few event recorder feedback intervention programs have
involved specific engagement of parents on how to best use the in-
formation to communicate with their teens about the teens’ driving
performance, which is a component this study adds to the existing body
of evidence. One study of young male drivers used an event recorder
without video in a shared family vehicle to provide feedback to teens
and parents about driving performance, feedback to the family (i.e.,
teens and parents could view each other’s performance), and family
feedback with the parents also receiving training on engaging with their
teens about their driving performance. The parent training arm had the
most successful program outcomes, particularly for the most risky teen
drivers (Farah et al., 2014; Shimshoni et al., 2015). Prior research
suggests that good parenting practices can have profound effects on
adolescent development and are strongly tied to reduced risk-taking
behaviors, and that parenting skills such as good communication can be
taught (Burrus et al., 2012; DeVore and Ginsburg, 2005).
This randomized controlled trial evaluated two interventions: one
that provided newly-licensed teen drivers and their parents (i.e., dyads)
with feedback from an event-triggered in-vehicle video system and one
that provided that same feedback after the parents were taught strate-
gies to improve communication with their teen about driving. The
training program is called Steering Teens Safe and teaches parents
techniques from Motivational Interviewing, a communication strategy
that uses active listening to support self-motivated behaviors, to discuss
driving safety and motivate young drivers to prioritize safe driving
(Ramirez et al., 2013; Peek-Asa et al., 2014). Our main hypotheses were
that among dyads assigned to an intervention, teens would have fewer
driving events than those assigned to the control condition (received no
feedback); and, teens whose parents had received instruction on com-
munication techniques would have fewer driving events compared to
teens whose parents did not receive communication training. Studies
have found in-vehicle feedback to have more impact with novice dri-
vers who have high rates of driving events (Carney et al., 2010). We
further hypothesized that adding a parent component would lead to
reduce driving events regardless of the baseline rate.
2. Methods
2.1. Study recruitment and randomization
We recruited parent-teen dyads using passive recruitment techni-
ques at 13 high schools and one healthcare employer from August 2011
to December 2014 in the areas of Iowa City and Des Moines, Iowa.
Parent-teen dyads were eligible if both spoke English, the teen was the
primary driver of their vehicle and expected to drive at least 90 min per
week, and both the parent and teen agreed to participate. Participants
were enrolled just prior to obtaining their Intermediate License, which
allows independent (without adult supervision) driving at a minimum
age of 16, with restrictions (no driving without adult supervision
12:30am-5am). The study protocol was approved by the University of
Iowa and Blank Children’s Hospital Internal Review Boards. Teen par-
ticipants who enrolled during the first 25 months of the study were
compensated $225 while the others were compensated $300. Timing of
study participation and level of incentives were not associated with
study findings.
A total of 400 contacts by interested participants were made with
the study team (Fig. 1). Of these, 239 were excluded due to ineligibility
(32.6%), inability to contact (51.0%), decided not to participate
(14.2%), or were unable or unwilling to begin the study after initially
agreeing (2.1%). The remaining 161 participants were equally rando-
mized into three groups using a random number generator. Loss to
follow-up occurred when the family moved out of the state, the teen
discontinued driving, the teen was in a crash and chose not to return to
the study, and failure of the event recorder. Loss to follow-up was
13.2% for the control group and 3.7% for the two intervention groups.
150 dyads completed the study.
2.2. Study groups
The study included one control group and two intervention groups.
All three groups received the in-vehicle video system which included an
event recorder (DriveCam® by Lytx) to capture driving events and be-
haviors (described below). The control group received no feedback or
intervention. The Event Recorder Feedback (ERF) intervention group
received feedback in two ways. First, the teen driver was alerted in real-
time by a flashing light on the event recorder that it had been triggered
and was recording. Second, the teen’s participating parent received in
the mail a weekly report with a summary of driving errors and unsafe
behaviors along with the videos of that week’s events (videos resulting
from false triggers were excluded).
The Event Recorder Feedback and Steering Teens Safe (ERF + STS)
intervention group received the same feedback as the ERF intervention
group coupled with the Steering Teens Safe communication training.
Steering Teens Safe is an evidence-based program that coaches parents
on effective communication with their teen using techniques of moti-
vational interviewing (Ramirez et al., 2013; Peek-Asa et al., 2014).
Prior randomized studies have found that parents successfully engaged
in the intervention and that the intervention led to improved parent
success in communicating about driving safety and led to moderate
reductions in teen risky driving (Ramirez et al., 2013; Peek-Asa et al.,
2014). Steering Teens Safe includes a 45-minute individualized training
to teach Motivational Interviewing skills including open-ended ques-
tions, affirmations, reflective listening, summarizing, rolling with re-
sistance, and reframing. Training was conducted by a trained traffic
safety specialist, and intervention fidelity was measured in prior studies
(Ramirez et al., 2013). Parents were taught to use these communication
skills to talk about, demonstrate, and supervise their teens on 26 safe
driving topics, which included basic safety principles (take the job of
driving seriously, distraction, seat belt use, impaired driving, passen-
gers), safe driving skills (traffic signals, safe speed, changing lanes,
following too closely, turning, and communicating with other vehicles),
rural driving (2-lane roads, gravel roads, uncontrolled intersections,
trucks and farm equipment), special situations (bad weather, avoiding
animals, emergency vehicles, work zones), and general expectations
(access to the car, who can be in the car, and consequences for not
meeting expectations). Parents received a workbook with an outline
and talking points for each of the 26 lessons as well as a DVD with video
examples of Motivational Interviewing techniques. In addition, parents
could call the traffic safety specialist for assistance and each parent
received three booster calls from the specialist two, six, and ten weeks
after the training session.
Teens reported on their parent’s frequency and success in talking
about each driving topic. Although not the focus of this analysis, we
found that compared with the control group, the ERT + STS group had
significantly more communication frequency and success overall and
for the components of basic safety principles, important skills for safe
driving, and special driving situations. Compared with the ERF only
group, the ERF + STS group had significantly better communication
overall and for important driving skills and general expectations.
2.3. Study protocol
After consent, the study team scheduled a time for equipment in-
stallation, and at this time teen and parent participants filled out
baseline surveys that collected information about sociodemographic
C. Peek-Asa, et al. Accident Analysis and Prevention 131 (2019) 63–69
64
3. characteristics and past driving experiences. This first meeting was
scheduled as close as possible and not more than one month after in-
termediate licensure. The in-vehicle equipment recorded driving events
starting with a four-week baseline period during which the event re-
corder collected data and did not give any feedback. Follow-up was for
four months, during which time teens in the two intervention groups
received feedback when the in-vehicle system was recording, and their
parents received weekly reports. Parents received the Steering Teens
Safe training intervention during the baseline period and received
booster calls during each follow-up month.
2.4. Driving events
The in-vehicle system captured audio and video of both the forward
view and the vehicle cabin when g-force for braking, acceleration, or
steering exceeded 0.5 g. The video files captured 8 s before and 4 s after
the trigger. Driving events were coded as crashes/near crashes, missed
traffic signals, and following too closely. A crash included any physical
contact with an object, moving or not. A near-crash was operationalized
as evasive action taken by the teen or other vehicle to avoid a crash.
Missed traffic signals included actions such as failure to stop or yield, or
running a red or yellow light. Following too closely was operationalized
as the number of frames it took for the teen’s vehicle to reach ap-
proximately the same location as the vehicle ahead. Each driving event
was also coded for unsafe behaviors, which included distracted driving,
speeding/driving too fast, driver and passenger seat belt use, and other
poor conduct. Distraction included any task that took the driver’s
attention away from the driving task and that subjectively appeared to
physically or cognitively distract the driver (e.g. adjusting the radio,
texting). Speeding/driving too fast was assessed as at least 10 mph over
the speed limit, also subjectively assessed as the vehicle speed ex-
ceeding standard safe speeds. Each driving event could have multiple
driving errors and multiple unsafe behaviors.
The first round of video coding was conducted by staff of DriveCam®
by Lytx to remove any videos for which the study participant was not
the driver. The second round of coding identified driving errors and
unsafe behaviors and was conducted by trained and experienced video
coders using a coding structure defined and reported through prior in-
vehicle video work conducted by this team (Carney et al., 2010;
McGehee et al., 2007). Coding was initially conducted by two trained
coders, and a third coder reconciled any disagreement between coders.
All coders were blind to the intervention assignment.
Mileage was accrued using two sources. All teens were asked to
provide a weekly odometer reading via text message or email.
However, these were not always reported in a timely manner and did
not always account for vehicle operation by non-participant drivers.
Trip level data recorded by the event recorder provided information
about the miles for each trip, which was summarized for each week of
the study. Trip-level mileage was the preferred source of mileage be-
cause it was considered more reliable and accurate.
2.5. Analysis
The primary outcome was the rate of driving events per 1000 miles
Fig. 1. Study participation flow diagram.
C. Peek-Asa, et al. Accident Analysis and Prevention 131 (2019) 63–69
65
4. travelled. Driving events and unsafe behaviors were also calculated as
rates. Rates were accumulated in monthly segments, with one month of
baseline and four months of follow-up (post-intervention). The rates
were calculated per participant as the number of events divided by the
miles driven. Group assignment was the main independent variable. For
inferential analyses, generalized linear models were employed, where a
monthly count of driving events served as the outcome. The negative
binomial distribution was specified to account for over dispersion, and
the log link function was employed. The log of the number of miles was
included as an offset to convert the counts to rates. To accommodate for
the repeated measures on subjects, the models were fit using general-
ized estimating equations based on an exchangeable working correla-
tion structure. To account for variation in baseline driving behavior, the
baseline rate was categorized into four groups and included in the
model as a four-level qualitative variable. In the categorization, the first
group consisted of teens with a zero baseline event rate and the re-
maining teens were grouped into tertiles (i.e., low, medium, and high
baseline rates). To account for changes from baseline to follow-up,
monthly segment was included as a four-level qualitative variable to
assess the extent to which event rates differed by intervention status.
The four levels of the variable represent each of the four follow-up
periods. The general structural form of the model can be specified as
follows:
log (error rate) = (baseline rate) + (intervention group) + (inter-
vention group)*(baseline rate) + (monthly segment) + (intervention
group)*(monthly segment)
Finally, the baseline rate was categorized into four groups and in-
cluded in the model to account for variation in baseline driving beha-
vior. The first group consisted of teens with a zero baseline event rate
and the remaining teens were grouped into tertiles (i.e., Low, Medium,
and High baseline rates).
3. Results
The study sample of 150 dyads equally represented males and fe-
males, and approximately 75% of the participants were in the 10th
grade (Table 1). Approximately 90% of the sample was white, with a
slightly lower proportion of non-whites in Event Recorder Feedback
plus Steering Teens Safe (ERF + STS) intervention arm. Participants
showed wide variation in the average number of miles driven, with
averages of between 505 and 633 miles per month, and standard errors
of 286 and 488 respectively. Groups did not differ significantly on any
demographic characteristics.
Fig. 2 shows the event rates (driving events per 1000 miles driven)
by study monthly segment and study arm. The control group, which
received no feedback, had an increase in events from baseline to first
segment of follow-up, and then a slow decline through the rest of the
follow-up period. Both intervention groups had a decrease in events
from baseline to follow-up, with the ERF + STS group showing a lower
rate of events in the first three months of study follow-up.
Driver errors and unsafe behaviors are depicted in Table 2, and
these categories are not mutually exclusive. Crashes or near crashes
were recorded at a rate of approximately one per 1000 miles travelled
during baseline. The control group sh owed no reduction, while the
ERF + STS group decreased to 0.7. Missing a traffic signal was the most
common driver error and occurred during the baseline period at a rate
of 5.1 per 1000 miles travelled (SD = 12.2). Following too closely was
the next most common error at a baseline rate of 2.8 (SD = 7.1). Rates
for missing a traffic signal and following too closely decreased during
follow-up for both the ERF and ERF + STS groups but increased for the
control group.
Distracted driving or driving while not fully aware was recorded at
baseline at a rate of 18.1 per 1000 miles driven and was the most
common unsafe behavior. Driver distraction and speeding rates
increased in the control group. Driver non-seat belt use at baseline was
lowest among the control group (1.3%), but increased at follow-up
(3.4%) and was slightly higher than both the intervention groups (2.2%
and 2.4%, respectively). Percent passenger seat belt non-use decreased
from baseline to follow-up in the control group and was unchanged in
the intervention groups.
Results from the multivariable model indicate that both interven-
tion groups had significantly lower event rates during follow-up than
the control group (controlling for differential baseline rates) (Table 3).
Compared with the control group, the ERF group had a rate ratio of
0.35 (95% CI = 0.24 – 0.50) and the ERF + STS group had a rate ratio
of 0.21 (95% CI = 0.15 – 0.30). Furthermore, the ERF + STS group had
a significantly lower event rate than the ERF group (rate ratio = 0.60,
95% CI = 0.41 – 0.87).
Because previous studies of in-vehicle event recorder feedback in-
terventions have shown stronger impact among high-event drivers, we
examined the impact of the intervention among teen drivers who at
baseline had no events as well as categories of low, medium, and high
event rates. Drivers who had no recorded events during the baseline
period theoretically could not experience a decrease during follow-up.
Fig. 3 shows event rates at baseline and each follow-up period based on
the event rate categories at baseline. Rates for the low, medium, and
high event drivers showed decreases for the ERF and ERF + STS groups
compared with controls. Rates comparing the two intervention groups
were not significantly different. Compared with the control group, the
ERF + STS group had significant decreases in follow-up driving events
for the high (RR = 0.15; 95% CI 0.7 – 0.31); medium (RR = 0.24; 95%
CI 0.13 – 0.46); and low event groups (RR = 0.22; 95% CI 0.11 – 0.44).
The ERF only group showed significant reductions compared with the
controls for the high (RR = 0.21; 95% CI 0.12 – 0.36) and medium
event group (RR = 0.18; 95% CI = 0.09 – 0.35), but not the low event
group.
Table 1
Demographics for Parent-Teen Dyads by Intervention Status.
Control Event
Recorder
Feedback
Event Recorder
Feedback and
Steering Teens
Safe
Total
Teen Characteristics N (%) N (%) N (%) N
Gender
Female 21 (45.7) 29 (55.8) 27 (51.9) 77 (51.3)
Male 25 (54.3) 23 (44.2) 25 (48.1) 73 (48.7)
Grade
10th
38 (82.6) 39 (75.0) 33 (63.5) 110 (73.3)
11th
8 (17.4) 12 (23.1) 18 (34.6) 38 (25.3)
Missing 0 (0) 1 (1.9) 1 (1.9) 2 (1.3)
Race
White 41 (89.1) 45 (86.5) 48 (92.3) 134 (89.3)
Non-white 5 (10.9) 6 (11.5) 3 (5.8) 14 (9.3)
Missing 0 (0) 1 (1.9) 1 (1.9) 2 (1.3)
Age at First Drive
12 or younger 4 (8.7) 1 (1.9) 0 (0) 5 (3.3)
13 5 (10.9) 4 (7.7) 1 (1.9) 10 (6.7)
14 35 (76.1) 42 (80.8) 47 (90.4) 124 (82.7)
15 or older 2 (4.3) 4 (7.7) 3 (5.8) 9 (6.0)
Missing 0 (0) 1 (1.9) 1 (1.9) 2 (1.3)
Average miles driven
in each 1-month
study segment:
Mean (SD)
Baseline (1 month) 538 (233) 532 (311) 630 (321) 568 (294)
Follow-up 1 month 581 (290) 505 (286) 532 (282) 538 (286)
Follow-up 2 months 577 (305) 521 (287) 561 (272) 552 (287)
Follow-up 3 months 553 (304) 543 (378) 562 (275) 552 (321)
Follow-up 4 months 620 (317) 633 (488) 598 (309) 617 (380)
C. Peek-Asa, et al. Accident Analysis and Prevention 131 (2019) 63–69
66
5. 4. Discussion
This study tested the effects of a parent-focused safe driving com-
munication program in conjunction with an in-vehicle feedback system
on reducing driving event rates. Compared with controls, dyads who
received the combination of Event Recorder Feedback and Steering
Teens Safe (ERF + STS) had nearly an 80% lower rate of driving events
and dyads who received ERF only had a 65% lower rate compared to
controls. Dyads who received both interventions had nearly a 40%
lower driving event rate compared the ERF only group. These findings
are consistent with prior studies that have evaluated in-vehicle video
feedback. Using the same technology in a study comparing driving
event rates before and after equipment installation, McGehee found a
58% reduction in driving events in the first 9 weeks and a 75% re-
duction in the second 9 weeks compared with the baseline period
(McGehee et al., 2007). Also using the same technology, Carney et al.
found a 61% reduction in driving event rates using the same pre-post
design, and further found that event rates did not increase following
removal of the feedback component (Carney et al., 2010). They re-
ported that only 22% of teens talked with their parents about safe
driving and only 39% reported reviewing their report card weekly.
Farmer et al examined real-time alerts and web notification of teen
Fig. 2. Teen driving event rates per 1000 miles and standard error bars by follow-up period and study arm.
Table 2
Overall event rates per 1000 miles driven and event rates by type for baseline and follow-up periods, stratified by intervention status (Mean (SD) unless denoted
otherwise.
Driving Events Control Event Recorder Feedback Event Recorder Feedback and Steering Teens Safe Total
Overall Event Rates
Baseline 36.6 (59.6)1
24.5 (41.7) 25.6 (66.4) 28.6 (56.6)
Follow-up 49.4 (85.6)?? 8.2 (19.8) 9.7 (17.1) 21.4 (53.2)
Driver Errors
Crashes/near crashes
Baseline 1.1 (2.7) 1.2 (2.3) 1.2 (2.3) 1.2 (2.4)
Follow-up 1.3 (3.0) 1.0 (2.0) 0.7 (2.0) 1.0 (2.3)
Missed traffic signal/sign
Baseline 5.7 (10.5) 5.1 (10.2) 4.7 (15.4) 5.1 (12.2)
Follow-up 8.2 (17.9) 1.9 (4.6) 1.9 (5.6) 3.9 (11.1)
Following too closely
Baseline 3.6 (6.9) 2.0 (3.7) 2.8 (9.5) 2.8 (7.1)
Follow-up 5.3 (10.8) 1.0 (2.0) 1.4 (4.1) 2.4 (6.8)
Unsafe behaviors
Distracted/not fully aware
Baseline 23.7 (41.2) 13.7 (20.7) 17.5 (43.7) 18.1 (36.4)
Follow-up 32.0 (52.7) 6.6 (12.4) 6.2 (14.8) 14.2 (35.6)
Speeding/Driving too Fast
Baseline 1.5 (4.2) 0.4 (1.5) 0.8 (2.0) 0.9 (2.8)
Follow-up 3.2 (9.1) 0.2 (0.8) 0.5 (1.8) 1.2 (5.3)
Other poor conduct noted
Baseline 2.8 (8.2) 1.8 (5.9) 2.3 (8.4) 2.3 (7.5)
Follow-up 4.0 (12.0) 0.7 (2.3) 0.7 (2.2) 1.7 (7.0)
Percent Driver Seat Belt Non-Use
Baseline 1.3% 3.3% 3.4% 2.5%
Follow-up 3.4% 2.2% 2.4% 3.1%
Percent Passenger Seat Belt Non-Use
Baseline 10.2% 11.5% 11.1% 10.8%
Follow-up 8.2% 11.7% 11.1% 9.1%
1
Bold denotes a p-value of < 0.05 for Wilcoxon Signed Rank Test comparing the baseline with the follow-up period within each intervention arm.
C. Peek-Asa, et al. Accident Analysis and Prevention 131 (2019) 63–69
67
6. driving events, comparing these notifications with and without parent
access (Farmer et al., 2010). Results were mixed, with speeding and
seat belt use showing improvements when parents were notified. These
prior studies indicate that parent engagement is a gap invehicle feed-
back systems.
Only one previous study has examined direct parent training in
combination with in-vehicle feedback. In a sample of teens in Israel,
Farah et al. compared in-vehicle feedback with and without a parent
report card, and parents who received the report card participated in an
in-person training to demonstrate the equipment and report card ele-
ments (Farah et al., 2014). Although the group with parent training had
the lowest post-intervention driving event rates, mean event rates of the
intervention groups did not differ. This is the first study to demonstrate
an augmented impact of in-vehicle feedback systems with a focused
parent communication program.
Prior studies of in-vehicle video feedback systems have found that
reductions in driving event rates were disproportionately influenced by
drivers who had high event rates during baseline (Carney et al., 2010).
These findings suggest that in-vehicle systems may be best suited for
implementation in populations of high risk drivers. To examine this
further, we compared intervention results in sub-categories of drivers
with low, medium, and high baseline event rates. Compared with
controls, dyads who received ERF + STS showed reductions relative to
baseline event rates. Among dyads who received ERF only, both the
high and medium groups experienced significantly lower rates.
This study has important implications for future intervention re-
search. Our study suggests that as technology increasingly enables au-
tomated processes that identify driving events and provide feedback to
improve driving behavior, information to inform and engage drivers
will be an important element to maximize driving behavior change.
Potential audiences and messages for this guidance will be important to
identify. For example, we found that teen’s driving behavior improved
when parents were provided with support in communicating about
driving feedback, but other audiences such as driver’s education in-
structors could also be helpful. Our study focused on the early period of
unsupervised driving. The role of parental influence should also be
studied beyond this period, especially into unsupervised driving periods
in the later teen years.
This intervention was complex and required considerable resources,
including the in-vehicle equipment, analysts to review video events and
generate the weekly reports, and the in-person communication training.
We found that the program was effective for all four levels of baseline
driving event rates, which suggests that this program could be im-
plemented as a universal intervention. However, scaling this intense
intervention to a large population would be prohibitive. These ap-
proaches have strong potential to reduce risky driving in high risk
novice drivers, and a more sustainable use of these technologies might
be as targeted interventions. Studies that focus specifically on high risk
teens can help us better understand how these programs work, and to
help us move towards targeted interventions for high risk youth. For
example, Fabiano developed an intense intervention for children with
ADHD, which required 45-minute in-person parent child sessions twice
a week for eight weeks (Fabiano et al., 2011). Tested on seven families,
the program showed reductions in most of the driving events tested
(e.g. hard acceleration and speeding) and improved family relations
regarding driving.
Potential also exists to develop technology and communication
approaches that are less labor intensive and easier to implement.
Technology to measure g-force events is moving in this direction, in-
cluding the development of equipment that involves a simple plug-in to
the vehicle’s diagnostic port and links to a smartphone application to
provide feedback on behaviors such as hard braking, sudden
Table 3
Rate ratios estimated from a multivariate model for driver error rates comparing the control and two intervention groups.
Outcome Comparison Rate Ratio 95% CI p-value
Event Recorder Feedback Control 0.35 0.24–0.50 < 0.01
Event Recorder Feedback & Steering Teens Safe Control 0.21 0.15–0.30 < 0.01
Event Recorder Feedback & Steering Teens Safe Event Recorder Feedback 0.60 0.41–0.87 0.01
Fig. 3. Each panel displays the mean event rates per 1000 miles for each intervention group across the study period for each study arm.
C. Peek-Asa, et al. Accident Analysis and Prevention 131 (2019) 63–69
68
7. acceleration, and speeding. These newer feedback technologies have
not been widely studied.
Communication strategies can also be simplified, and we are cur-
rently evaluating the use of Steering Teens Safe as a self-guided online
program. Several online parent-focused teen driving programs have
been successful in meeting their goals. For example, the Checkpoints
program led to increased parent engagement with their teen in estab-
lishing shared driving rules and expectation (Simons-Morton et al.,
2013, 2004). The Teen Driving Plan was successful in increasing parent
engagement, and teen acceptance of parent engagement, in supervised
driving, leading to improved driving skill and reduced crashes (Simons-
Morton et al., 2004; Hartos et al., 2009; Zakrajsek et al., 2009; Mirman
et al., 2014, 2018). Steering Teens Safe is the only program that focuses
specifically on parent communication strategies to help self-motivate
teens to embrace safe driving behaviors. With growing evidence that
parent engagement strategies are successful, and that they can enhance
technologically-based interventions, we now need to define which types
of messages and parent assistance is appropriate in different circum-
stances (Burrus et al., 2012). Opportunities to train and engage parents
in an efficient, convenient setting are also needed. States that have
implemented a parent component to their driver’s education programs
(e.g. Massachusetts) provide one such example. Three studies (Hartos
et al., 2009; Zakrajsek et al., 2009, 2013), one that integrated parent-
teen homework assignments and two that integrated a 30-minute
parent training component using the Checkpoints program, found im-
proved parent knowledge about teen driving and led to more parent-
imposed driving restrictions (Hartos et al., 2009).
This study has some limitations that can be overcome with future
research. The sample, which was passively recruited, is unlikely to be
representative of all teens and thus has limited generalizability to the
universal novice driving population. Our sample is likely to be biased
towards families that are interested in driving safety and comfortable
with a research environment, who are likely low risk. Driving events
measured through in-vehicle event records accurately measure kinetic
errors, but these systems do not measure all safety behavior use (e.g.
seat belt use is monitored only when a driving error has occurred) or
errors that do not lead to vehicle g-force changes. The connection be-
tween driving events and crash risk has not been firmly established,
although one study concluded that g-force events can be used to assess
risk (Simons-Morton et al., 2012). The correlation was strongest in the
first six months of driving but did not persist over time. It has been
posited that the presence of in-vehicle feedback systems could alter
driving prior to intervention, leading to biased effect estimates. Ehsani
et al. examined the impact of in-vehicle equipment on driving behavior
and found that awareness of the equipment was unrelated to driving
event rates measured by the system (Ehsani et al., 2017).
5. Conclusion
This randomized trial found that in-vehicle video feedback systems
can reduce the number of driving events among novice drivers faster
than the average learning curve of teen drivers (control group). These
findings are consistent with those from previous studies, but this study
included randomized study groups, a control group with the same
outcome measures but no feedback, and a baseline period for all study
groups; few former studies included all of these elements. We further
found that including the Steering Teens Safe parent-focused commu-
nication program increased the impact of the in-vehicle video feedback
system. While in-vehicle feedback systems can help reduce driving
events in early independent driving, offering parents communication
strategies for talking with their young driver about their driving can
further improve their impact.
Declarations of interest
None.
Acknowledgements
This study was funded by the National Institutes of Health, National
Institute of Child Health and Human Development (R01 HD065095)
and the University of Iowa Injury Prevention Research Center (R49-
CE002108).
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