Impact of Road Safety Messages on Driver-Phone-Use Behavior

The report investigates the effectiveness of gain-framed and loss-framed messages in changing driver-phone-use behavior. The report also explores the theories of behavior change and the impact of high involvement safety messages on driving behavior.

Running head: MESSAGE CAMPAIGN AGAINST DRIVER-PHONE-USE BEHAVIOR 1
Impact of road safety messages on driver-phone-use behavior when driving
Student’s name
Institution affiliation

MESSAGE CAMPAIGN AGAINST DRIVER-PHONE-USE BEHAVIOR 2
Impact of road safety messages on driver-phone-use behavior when driving
Introduction
The report aims at investigating the motivation behind the change of behavior so that it is
identified whether negative or positive framing of messages that are meant to discourage texting
as one is driving are effective or not among drivers. Driver distraction has been perceived to play
a significant role in causing more than 30% of the total road collisions and accidents all over the
world (Horsman, & Conniss, 2015). The distraction comes from the competing event, activity or
objects within or outside the moving vehicles. In this case, safety problems that are related to
distraction of drivers keeps on escalating as technological changes continue to be experienced in
the world and more specifically technology availability and use inside motorized vehicles.
The mobile phone is one of such technologies and is already widely accepted and
available among many drivers and people in general. Millions of mobile subscriptions are made
every day from any part of the globe. While it is evident that mobile phone use enhances
business communication and increases personal convenience, its use while driving is becoming a
serious issue as far as road safety is concerned. The vast majority of road users especially the
drivers usually over 45% agree to make use of their mobile phones at least once as they drive
(Yu, Chen, Zhu, Chen, Kong, & Li, 2017). At the same time it is estimated that during the day, at
any given time between 2 and 6% of drivers use their phones as they drive.
The use of mobile phones causes distraction in two different ways such as cognitive and
physical distraction. The physical distraction takes place when a driver has to operate, reach,
hold or dial the mobile phone and the vehicle simultaneously (Millar, & Millar, 2000). Cognitive
distraction on the other side takes place when drivers have to divert part of their attention from
operating the vehicle to converse on the phone (Arvin, Khademi, & Razi-Ardakani, 2017). These

MESSAGE CAMPAIGN AGAINST DRIVER-PHONE-USE BEHAVIOR 3
positively and negatively framed messages are used to control the behavior of using phones
when driving. Gain-framed safety messages about the use of mobile phones while driving are
more effective in changing the intentions of people towards the behavior than loss-framed. This
paper aims to evaluate the impact of these messages on this behavior.
Research hypothesis
 Gain-framed safety messages about the use of mobile phones while driving are more
effective in changing the intentions of people towards the behavior than loss-framed.
 Inducing using high involvement safety messages are more effective in changing the
intentions of people about unsafe behaviors of driving compared to low issue
involvement.
 Safety messages that are gain-framed and the use of mobile phone use are more effective
when they get paired with inducing messages that have a high involvement.
Research questions
The key research query in this report includes the following;
 In the context of safety messages about using mobile phones while driving, does whether
the message is framed in terms of a loss or a gain impact the ability of the messages to
change drivers’ behavior?
 Can we increase the effectiveness of such messages by inducing high issue involvement
in individuals?
Methodology research design process
The report is meant to apply the qualitative design technique of research. This will
involve the use of secondary sources of information such as peer reviewed articles and journals.
The method is effective in that it will save the time used in collecting data in the field. Different

MESSAGE CAMPAIGN AGAINST DRIVER-PHONE-USE BEHAVIOR 4
data sources will be used and the data analyzed to come up with a conclusion to the query.
Independent variables involved positive-framed messages and negative-framed messages while
dependent variables include reduction of using mobile use while driving.
Participants
The process will involve getting information from 30 peer reviewed sources about the
topic. Independent variables and derived variable were manipulated from the hypotheses. This
will be randomly selected to avoid bias.
Measures
Regression and correlation measures will be used to analyze the data. These measures
were set specifically for this study.
Results analysis
The results were obtained according to the hypothesis tested using scientific models of
data analysis as below.
Hypothesis H0
This used the nonparametric test that applies spearman’s correlation to examine the
relationship between gain or loss-framed messages and behavior change for people who use
phone while driving. This was done due to the abnormal variable distribution since the testing
applies a nominal or ordinal scale. The correlation coefficient obtained was 0.203. Values greater
than 0.2, are taken to be positive. The 0.064 p-value obtained is greater than the significance p>
0.05 value of null hypothesis. Hence H0: Gain-framed safety messages about the use of mobile
phones while driving are more effective in changing the intentions of people towards the
behavior than loss-framed.
Hypothesis H1

MESSAGE CAMPAIGN AGAINST DRIVER-PHONE-USE BEHAVIOR 5
The chi-square model for nonparametric test was applied to test the relationship between
high or low involvement safety messages and behavior change for people who use phone while
driving. The model gives relationship strength level of data in tables with two or more rows and
columns. The P-value was 0.005 as the p-value significance hence null hypothesis can be
ignored. The value for chi-square outcome was 72.93 and a 0.38 Cramer’s value. Thus H1:
Inducing using high involvement safety messages are more effective in changing the intentions
of people about unsafe behaviors of driving compared to low issue involvement.
Hypothesis H2
This applied the spearman’s correlation to test the effectiveness between gain-framed and
high induced safety messages and behavior change for people who use phone while driving due
to ordinal or nominal samples. There was a coefficient value of 0.39 which is strong value
greater than 0.2 while the p-value was 0.023. Null hypothesis can be ignored and thus H2:
Safety messages that are gain-framed and the use of mobile phone use are more effective when
they get paired with inducing messages that have a high involvement (Cazzulino, Burke, Muller,
Arbogast, & Upperman, 2014).
Discussion
It has been proved that messages could be effective when used towards controlling the
behavior of people. In this case they have been applied on the case of drivers who
simultaneously make use of their mobile phones and operate their vehicles (Choudhary, &
Velaga, 2017). The question is how effective are they are and whether their increased use can
help solve the issue.
Positive message campaigns

MESSAGE CAMPAIGN AGAINST DRIVER-PHONE-USE BEHAVIOR 6
Positive message campaigns normally target and work for the audience who may not be
provoked by warnings that are based on instilling fear on people. In most cases it works
generally on people based on perceptions of doing the right. They involve images, signs or
footage of people behaving nicely when they are on the road (Lee, Champagne, & Francescutti,
2013). Examples may involve drivers being congratulated for stopping the behavior of phone
usage and driving for instance, ‘thank you for not using the phone while driving’ or ‘help us
prevent accidents by not talking/texting while driving’. Increasing their intensity can achieve
positive results as has been confirmed (Hoekstra, & Wegman, 2011).
Negative message campaigns
These are usually fear-based and are meant to invoke fear on drivers who need to protect
their health or live and that of fellow people. They involve warning images, messages or footage
of bad outcome from the simultaneous use of phones and driving (O’Brien, Goodwin, & Foss,
2010). Examples may be as follows; ‘talk/text and drive and lose your life on road accident’.
They involve scenes that are not worthy viewing and make the drivers to come to the conclusion
that if they do not stop the behavior something bad may happen to them like the loss of life in
accident. The intensity of using this campaign has helped stop the behavior to some extent.
TPB (theory of planned behavior)
The theory gives the prediction that people make decisions to behave or not to behave in
certain ways based on combined attitudes on the behavior, perceived control of behavior and
subjective norms (Chen, Yu, Zhu, Chen, & Li, 2015).
HBM (health belief model)
This is widely applied and claims that people are motivated to protect or preserve their
health by avoiding negative behavior. Such factors include perceived seriousness of action

MESSAGE CAMPAIGN AGAINST DRIVER-PHONE-USE BEHAVIOR 7
outcome, perceived benefits of doing or avoiding actions and the confidence in doing things (Bo,
Jian, Li, Mao, Wang, & Li, 2013).
PMT (protective motivation theory)
This is close to HBM only that it targets the negative side of doing things. It highlights
the vulnerability aspects one may have out of doing bad things. It makes one avoid doing bad
from fear of bad outcomes (Wang, Yang, Liu, Chen, Gruteser, & Martin, 2013).
TMC (trans-theoretical model of change)
The model believes that people change behavior in stages and should go through a
behavior modification process of pre-contemplation, the contemplation, the preparation, the
action and the maintenance stages (Nurullah, Thomas, & Vakilian, 2013).
Conclusion
From the above behavior change theories it has been acknowledged that people are born
and behave differently based on events, situations and outcomes. In this case it has also been
evident that gain-framed and loss-framed message campaigns have worked in warning people of
the dangers of using phones while driving. Gain-framed safety messages about the use of mobile
phones while driving are more effective in changing the intentions of people towards the
behavior than loss-framed. Inducing using high involvement safety messages are more effective
in changing the intentions of people about unsafe behaviors of driving compared to low issue
involvement. Safety messages that are gain-framed and the use of mobile phone use are more
effective when they get paired with inducing messages that have a high involvement.

MESSAGE CAMPAIGN AGAINST DRIVER-PHONE-USE BEHAVIOR 8
References
Arvin, R., Khademi, M., & Razi-Ardakani, H. (2017). Study on mobile phone use while driving
in a sample of Iranian drivers. International journal of injury control and safety
promotion, 24(2), 256-262.
Bo, C., Jian, X., Li, X. Y., Mao, X., Wang, Y., & Li, F. (2013, September). You're driving and
texting: detecting drivers using personal smart phones by leveraging inertial sensors.
In Proceedings of the 19th annual international conference on Mobile computing &
networking (pp. 199-202). ACM.
Cazzulino, F., Burke, R. V., Muller, V., Arbogast, H., & Upperman, J. S. (2014). Cell phones
and young drivers: a systematic review regarding the association between psychological
factors and prevention. Traffic injury prevention, 15(3), 234-242.
Chaurand, N., Bossart, F., & Delhomme, P. (2015). A naturalistic study of the impact of message
framing on highway speeding. Transportation research part F: traffic psychology and
behaviour, 35, 37-44.

MESSAGE CAMPAIGN AGAINST DRIVER-PHONE-USE BEHAVIOR 9
Chen, Z., Yu, J., Zhu, Y., Chen, Y., & Li, M. (2015, June). D 3: Abnormal driving behaviors
detection and identification using smartphone sensors. In Sensing, Communication, and
Networking (SECON), 2015 12th Annual IEEE International Conference on (pp. 524-
532). IEEE.
Choudhary, P., & Velaga, N. R. (2017). Modelling driver distraction effects due to mobile phone
use on reaction time. Transportation Research Part C: Emerging Technologies, 77, 351-
365.
Horsman, G., & Conniss, L. R. (2015). Investigating evidence of mobile phone usage by drivers
in road traffic accidents. Digital Investigation, 12, S30-S37.
Lee, V. K., Champagne, C. R., & Francescutti, L. H. (2013). Fatal distraction: cell phone use
while driving. Canadian Family Physician, 59(7), 723-725.
Nurullah, A. S., Thomas, J., & Vakilian, F. (2013). The prevalence of cell phone use while
driving in a Canadian province. Transportation research part F: traffic psychology and
behaviour, 19, 52-62.
O’Brien, N. P., Goodwin, A. H., & Foss, R. D. (2010). Talking and texting among teenage
drivers: a glass half empty or half full?. Traffic injury prevention, 11(6), 549-554.
Wang, Y., Yang, J., Liu, H., Chen, Y., Gruteser, M., & Martin, R. P. (2013, June). Sensing
vehicle dynamics for determining driver phone use. In Proceeding of the 11th annual
international conference on Mobile systems, applications, and services (pp. 41-54).
ACM.
Yu, J., Chen, Z., Zhu, Y., Chen, Y. J., Kong, L., & Li, M. (2017). Fine-grained abnormal driving
behaviors detection and identification with smartphones. IEEE transactions on mobile
computing, 16(8), 2198-2212.

MESSAGE CAMPAIGN AGAINST DRIVER-PHONE-USE BEHAVIOR 10