Name: Olowu Richard
Student ID: 001260092
Supervisor: Dr Damian Poulter
Driving Behaviour and Mobile Phone Use
Introduction
Distracted driving occurs when a driver engages in an activity unrelated to driving and diverts his or her attention from the necessary tasks at
hand. Road traffic crashes are a serious challenge to public health. There were 1390 fatalities on UK roads and 23,140 serious injuries in 2021
(Department for Transport, 2021). The use of a mobile phone while driving is a major distraction and risk factor for death and injury for drivers,
passengers, and other road users. Despite the dangers, texting while driving is highly prevalent among young adults. The Department for
Transport (2020) estimates cell phone use is most prevalent among drivers aged 20–29. The Theory of Planned Behaviour (TPB; Ajzen, 1991)
has recently become a popular model researchers studying road safety use to explain why individuals choose to text while driving. Given that
moral norm is a social influence variable that has been shown to impact people’s behavioural intentions (Benson et al., 2015; Gauld et al.,
2014), it was added to the TPB framework and would be expected that participants who regard texting while driving as the wrong thing to do
would be less likely to intend to do so. Given the risky nature of using a mobile phone while driving and the prevalence of this behaviour, this
study assessed the impact of an individual’s risk perceptions (perceived crash risk and perceived risk of apprehension) on their decision to use a
mobile phone while driving. This study aimed to examine the usefulness of an extended TPB framework in predicting intentions to engage in,
and subsequent behaviour of, sending and reading texts while driving (TWD) in a sample of young adults.
Methods: Materials: Results:
This was a cross-sectional study. Participants were asked to complete a self- Over 70% of the sample is expected to
Participants (N=120) were recruited via administered online questionnaire report talking on a cell phone and sending
social and public media. Inclusion designed to measure TPB variables with and receiving text messages “at least a few
criteria: All races and ethnicities, ≥18 respect to texting while driving. Online times” while driving within the past week.
years of age, cell phone owner, and surveys comprising standardised ratings However, it is expected that about 20%
licensed driver. using items adapted from (Benson et al., report being stopped and fined by police,
2015; Bergmark et al., 2016; Azjen, 1991) while most participants will perceive that
were used. texting while driving will not result in a
crash or apprehension. Generally, about
50% of the variance in intention to send a
text while driving is expected to be
Discussion:
accounted for by the full TPB model.
This study examined the attitudes of individuals toward texting while driving, and the survey
data is likely to support Ajzen’s (1991) Theory of Planned Behaviour (TPB). The data would
suggest that attitude will predict intention to engage in all distracted driving behaviours
(reading and sending text messages, making and answering cell phone calls, reading/viewing
social media, and posting on social media while driving). Extending the model to include past
behaviour and risk perception is likely to yield an improvement in the prediction of the
distraction variables. The study will provide evidence that emphasises the importance of
incorporating expanded variables into the original TPB model to predict cell phone use
behaviours while driving.
Reference
Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior & Human Decision
Processes 50, 179–211.
Benson, T., McLaughlin, M., & Giles, M. (2015). The factors underlying the decision to text
while driving. Transportation Research Part F: Traffic Psychology and Behaviour, 35, 85–100.
https://doi.org/10.1016/j.trf.2015.10.013
Bergmark, R. W., Gliklich, E., Guo, R., & Gliklich, R. E. (2016). Texting while driving: the
development and validation of the distracted driving survey and risk score among young
adults. Injury Epidemiology, 3(1). https://doi.org/10.1186/s40621-016-0073-8
