Mobile phone use while riding a motorcycle and crashes among
Long T. Truong a*, Hang T. T. Nguyen b, Chris De Gruyter c
a School of Engineering and Mathematical Sciences, La Trobe University, Bundoora, Victoria 3086, Australia
b Institute of Construction Engineering, University of Transport and Communications, Hanoi, Vietnam
c School of Global, Urban and Social Studies, RMIT University, Melbourne, Victoria 3001, Australia
* Corresponding author. E-mail: L.Truong@latrobe.edu.au (L.T. Truong)
Objective: Motorcycle crashes are a significant road safety challenge, particularly in many low and middle-
income countries where motorcycles represent the vast majority of their vehicle fleet. While risky riding
behaviours, such as speeding and riding under influence of alcohol, have been identified as an important
contributor to motorcycle crashes, little is understood about the effect of using a mobile phone while riding on
motorcycle crash involvement. This paper investigates crash involvement among motorcycle riders with risky
riding behaviours, particularly using a mobile phone while riding.
Methods: Data is obtained from an online survey of university students’ risky riding behaviours in Vietnam that
was administered between March and May 2016 (n=665).
Results: Results show that 40% of motorcycle riders reported to have experienced a crash/fall and nearly 24% of
motorcycle riders indicated that they had been injured in a crash/fall. Effects of mobile phone use while riding on
safety of motorcycle riders are highlighted. Specifically, more frequent use of a mobile phone for texting or
searching for information while riding is associated with a higher chance of being involved in a crash/fall. The
results also show that drink riding is associated with a higher chance of being injured.
Conclusions: Overall this paper reveals significant safety issues of using a mobile phone while riding a
motorcycle, providing valuable insight for designing education and publicity campaigns.
Keywords: risky behaviour; motorcycle; mobile phone; crash; injury
Please cite this article as: Truong, L.T., Nguyen, H.T.T., De Gruyter, C. Mobile phone use while riding a
motorcycle and crashes among university students. Traffic Injury Prevention. 2019, doi:
Motorcycles are a popular means of transport worldwide although they can serve different purposes in different
world regions. While in high-income countries, they are often used for leisure or recreation, they are commonly
used for transporting people and goods in low and middle-income countries (OECD/ITF, 2015). Most motorcycles
in high-income countries are high-powered (over 250cc), representing over 50% of the motorcycle fleet in North
American and European countries compared to 5% in South East Asia (WHO, 2017). Globally, there are over 500
million registered motorcycles, representing 29% of all registered vehicles (WHO, 2015). The vast majority of
the world’s motorcycle fleet (88%) are contributed by low and middle-income countries (WHO, 2015). Among
the world’s regions, South East Asia has the highest proportion of registered motorcycles (around 74.5% of all
registered vehicles) as well as the highest growth (WHO, 2015). Particularly in Vietnam, 95% of the vehicle fleet
are motorcycles with an average of 7,500 motorcycles being registered each day (NTSC, 2015; WHO, 2015).
While motorcycles are essential for moving people and goods, they also are a major contributor to road traffic
fatalities and injuries. Each year, over 286,000 motorcyclists die on the world’s roads, representing nearly a
quarter of all road traffic fatalities (WHO, 2015), while many more are injured or seriously injured. Most
motorcycle-related fatalities (90%) are from low and middle-income countries, which is attributed to their large
motorcycle fleets (WHO, 2015). According to WHO data, South East Asia and the Western Pacific have the
highest proportion of motorcycle fatalities among all road traffic fatalities at 34% (WHO, 2015). Within South
East Asia, the proportion of motorcycle fatalities is much higher in Vietnam, Malaysia, Cambodia, and Thailand
with 58%, 58%, 70%, and 73% respectively (Ngo et al., 2012; Abdul Manan et al., 2013; WHO, 2015). Since
2010, the proportion of motorcycle fatalities has remained stable in most world regions (WHO, 2015), suggesting
that motorcycle crashes continue to be a global safety issue.
Among a number of factors contributing to motorcycle crashes, risk-taking behaviours have been found to be an
important contributor (Lin and Kraus, 2009). Thus, there has been a growing body of literature investigating risky
riding behaviours of motorcyclists in high-income countries (Moskal et al., 2012; Stephens et al., 2017) as well
as in low and middle-income countries (Vu and Shimizu, 2007; Roehler et al., 2015; Tongklao et al., 2016). For
example, in a study in Hanoi, Vietnam, Vu and Shimizu (2007) found that habits and intentions were strong
predictors of risky-taking behaviours such as speeding, running red lights, and reckless overtaking. A study in
Malaysia reported high prevalence of street racing under the influence of alcohol and stunt riding (Wong, 2011).
In Indonesia, Susilo et al. (2015) found that young adults and students were more likely to violate traffic
regulations while examining a range of traffic violations among motorcyclists.
While mobile phone use while driving a car has been a subject of much research (McEvoy et al., 2005; Backer-
Grøndahl and Sagberg, 2011; Harrison, 2011; Zhou et al., 2012; Ismeik et al., 2015; Beck and Watters, 2016),
mobile phone use while riding a motorcycle has only been investigated in recent research. It was observed that
the prevalence of mobile phone use while riding in three Mexican cities was 0.64% (Pérez-Núñez et al., 2013)
compared to 8.66% in Hanoi, Vietnam (Truong et al., 2016b). Self-reported prevalence of mobile phone use while
riding, at any time rather than a specific time of observation, was much higher. About 40% of high school students
in Vientiane, Laos (Phommachanh et al., 2016) and nearly 81% of university students in Hanoi and Ho Chi Minh
City reported using a mobile phone while riding a motorcycle (Truong et al., 2017). Effects of gender, risk
perceptions, and social networks on mobile phone use while riding have also been highlighted (De Gruyter et al.,
2017; Truong et al., 2017). Mobile phone use while riding can also be affected by situational factors. For example,
motorcycle riders would be more likely to use a mobile phone while stopping at an intersection compared to while
moving through the intersection (Truong et al., 2016b).
A number of studies have further explored associations between risk-taking behaviours and crash involvement
given their importance to the identification of interventions and priorities. Using French crash data, Moskal et al.
(2012) found that motorcycle riders who were males, did not wear a helmet, or exceeded the alcohol concentration
limit had a higher risk of being involved in a crash. With a survey of motorcycle riders in New South Wales,
Australia, Stephens et al. (2017) showed that riders with stunt behaviours and speed violation were more likely to
be involved in a crash and near-crash respectively. According to a study of school children in India, tailgating and
aggressive attitudes towards other motorcycle riders were associated with crash involvement (Rathinam et al.,
2007). It was found in Taipei, Taiwan that female motorcycle riders or riders with a higher tendency to engage in
risky riding behaviours were more likely to be involved in a crash (Chang and Yeh, 2007). A recent study in
France however suggested that female riders were less likely to be involved in injured crashes and particularly
fatal crashes (Coquelet et al., 2018). In a study of fatal motorcycle crashes in Cambodia, Roehler et al. (2015)
identified that speeding and drink riding were major contributing factors to motorcycle fatalities. A study of risky
behaviours among students in Thailand reported that not wearing a helmet, speeding, and riding under the
influence of alcohol were associated with motorcycle injuries (Tongklao et al., 2016).
While the associations between a range of risk-taking behaviours and motorcycle crash involvement have been
extensively investigated, little is understood about crash involvement among motorcyclists who use a mobile
phone while riding. This understanding is particularly important in regions such as South East Asia where
motorcycling is the dominant transport mode coupled with high prevalence of mobile phone use while riding
(Phommachanh et al., 2016; Truong et al., 2017). To address the research gap, this paper investigates crash
involvement and severity among motorcyclists with risky riding behaviours, particularly mobile phone use while
riding. Data from a survey of university students’ risky riding behaviours in Vietnam is utilised for the
investigation since Vietnam has motorcycle-dominated traffic (NTSC, 2015; WHO, 2015) and young adults are
more likely to engage in risky riding behaviours (Chang and Yeh, 2007; Truong et al., 2016b).
In Vietnam, motorcycles contribute to around 95% of over 43 million registered vehicles and the vast majority of
motorcycles are powered with an engine of less than 150cc (NTSC, 2015; WHO, 2017). Motorcycling is
particularly important for mobility of young adults where most young adults aged 21-30 years old (58-77%)
possess a motorcycle (Tran, 2013) and many students (40%) use one for travel to university (Ohmori et al., 2011).
In 2014, Vietnam had over 25,000 reported traffic crashes and about 9,000 fatalities (NTSC, 2015). Motorcyclists
were involved in more than 70% of traffic crashes (Hung et al., 2008; Truong et al., 2016a) and contributed to
about 58% of traffic fatalities (Ngo et al., 2012). Traffic regulations in Vietnam specify penalties for risky riding
behaviours such as not wearing a helmet, speeding, drink riding, running red lights, and using a mobile phone or
portable music device while riding. However, while helmet use has been well-reported (Hung et al., 2008; Nguyen
et al., 2012), little information is available about the compliance levels of other risk-taking behaviours.
Data was obtained from an online survey of university students’ risky riding behaviours in Vietnam that was
administered between March and May 2016 (De Gruyter et al., 2017; Truong et al., 2017; Truong et al., 2018).
Students at the University of Transport and Communications’ campuses in Hanoi and Ho Chi Minh City, the two
largest cities in Vietnam, were recruited using several methods, including flyers, in-class announcements, and
group emails to classes. There are nearly 20,000 students in the two campuses. As this is an anonymous survey,
ethics approval was not required by the University of Transport and Communications. The survey could be
completed by using various devices, e.g. smartphones, tablets, computers, and laptops. As young students are very
likely to have a smartphone (Google, 2015; Nielsen, 2017), there was little concern with regards to an over-
representation of participants who had a mobile phone in the survey sample. No incentive was provided to students
to participate in the survey. To prevent duplicate responses, each device was allowed to submit only one response.
The online survey, as part of a wider research project, had 18 questions, taking participants approximately 10-15
minutes to complete. This paper focuses on questions related to crash involvement and risk-taking behaviours.
Participants were asked about their demographic information (e.g. age, gender, and the number of years having a
motorcycle license) and motorcycle use. If participants reported that they rode a motorcycle, they were asked how
frequently they engaged in risk-taking behaviours while riding a motorcycle (never=1, a few times a year=2,
monthly=3, weekly=4, daily=5). These behaviours included using a mobile phone (for calling, texting, and
searching for information), not wearing a helmet, speeding, running red lights, riding on the wrong side of a road,
riding while under the influence of alcohol, recklessly overtaking, and riding on sidewalks. Survey participants
were asked about mobile phone use in general; they were not asked to specify whether they used it in hands-free
Participants were then asked if they had been involved in a crash/fall while riding a motorcycle in the last 24
months. If so, participants were asked if they fell from their motorcycle without contact with either an obstacle or
another road user, if they fell from their motorcycle as a result of hitting an obstacle, if they crashed into another
road user, and if some other road user crashed into them. Participants were asked if they were engaging in any
risky riding behaviour when the most recent crash/fall occurred. It is noted that participants might engage in
several risky riding behaviours. This was followed up with a question about the severity of the most recent
crash/fall (injured or not). Questions regarding crash/fall involvement were adapted from a previous survey of
portable electronic device use among cyclists (Goldenbeld et al., 2012).
The proportion of motorcycle riders who were involved in a crash/fall while riding in the last 24 months and the
proportion who were injured in the most recent crash/fall were estimated together with 95% confidence intervals
(CI). The proportion of riders with crash involvement when they were engaging in each risky riding behaviour
was also determined with the 95% CI. Similarly, the proportion of riders who were injured in the most recent
crash/fall while engaging in each risky riding behaviour was calculated with the 95% CI. Binary logistic regression
was then used to explore potential associations between crash involvement and the frequency of risky riding
behaviours. Potential associations between crash severity and risky riding behaviours that participants were
engaging in when the crash occurred were also investigated using binary logistic regression. In the development
of these two logistic regression models, a step-wise approach was adopted for variable selection. Multicollinearity
was tested using the variance inflation factor (VIF), in which VIF values of less than five indicate no issue of
multicollinearity among explanatory variables. While descriptive statistics were analysed in the R statistical
environment (R Core Team, 2017), logistic regression was conducted using JASP statistical software (JASP Team,
There were 741 survey participants with valid responses after removing invalid and missing data responses from
157 participants. Nearly 90% of participants (665) indicated that they rode a motorcycle, providing the basis for
the data analysis in this paper. The distribution of motorcycle riders across the two campuses was relatively even
with 361 (54.3%) from Hanoi campus and 304 (45.7%) from Ho Chi Minh City campus. Among motorcycle
riders, there were 384 males (57.7%) and 281 females (42.3%), suggesting a relatively well-balanced gender split.
The average age was 21.9 years and the average number of years having a motorcycle license was 2.7 years.
Fig. 1 presents a summary of the frequency of risky riding behaviours among the 665 motorcycle riders. The
proportion of riders who reported that they had never engaged in each of the considered risky riding behaviours
ranged between 26% (for calling while riding) and 66.8% (for reckless overtaking).
Approximately half of riders indicated they had never texted while riding, searched for information on their mobile
phone while riding, ridden without a helmet, run red lights, or ridden under the influence of alcohol. More than
10% of riders used a mobile phone for calling while riding on a daily basis, followed by speeding (6.9%), texting
while riding (5.3%), and searching for information on a mobile phone (4.2%). These behaviours also had high
prevalence on a monthly and weekly basis. The frequency of riding on sidewalks was relatively high among
motorcycle riders with 10.8%, 6.5%, and 2.8% engaging in this behaviour on a monthly, weekly, and daily basis
Out of the 665 participants who were motorcycle riders, 266 (40%, 95%CI: 36.28-43.72%) indicated that they
were involved in a crash/fall while riding in the last 24 months, and 157 (23.61%, 95%CI: 20.38-26.84%) reported
that they were injured in the last crash/fall. This suggests around 60% of riders involved in a crash/fall were
injured. Fig. 2 shows a summary of crash/fall types experienced by motorcycle riders. Note that survey participants
could report more than one type of crash/fall that they were involved in within the last 24 months. Being hit by
other road users was the most common type whereas crashing into another road user was the least common. Being
hit by other road users occurred about 1.5 times more frequently than crashing into another road user. Falls either
without contact or due to hitting an obstacle occurred around 1.2 times more frequently than crashing into another
road user. Results also suggested an even split between single-vehicle crashes/falls and multi-vehicle crashes.
Table 1 summaries the proportion of motorcycle riders who were injured when engaging in risk-taking behaviours.
Results showed that 3.76% (95%CI: 2.31-5.21%) of riders reported that they had been injured in a crash/fall when
calling. This further suggests the effect of calling on both crash involvement and crash injury. The proportion of
riders who had been injured in a crash/fall when speeding, reckless overtaking, or drink riding is 2.86% (95% CI:
1.59-4.12%). This was lower when compared to calling, but higher when compared to other risky riding
behaviours. Approximately 1% and 1.2% of riders reported being injured in the last crash/fall when using a mobile
phone for texting and searching information respectively.
Associations Between Risky Behaviours And Crash Involvement And Severity
Table 2 presents logistic regression model results for crash/fall involvement by the frequency of risky riding
behaviours. The number of years having a motorcycle license and age, which can be a proxy for riding experience
and mileage, were not significant and therefore not included in the final model. Three variables were selected in
this final model using the step-wise approach, including the frequency of texting, searching for information on a
mobile phone, and running red lights. The model was statistically significant at p<0.0001 (Chi-square=36.9,
degrees of freedom=3). VIF values were less than two, indicating no issue of multicollinearity.
The results showed that a higher frequency of texting while riding was associated with a higher chance of being
involved in a crash/fall (coefficient=0.197, p-value=0.02). In other words, compared to motorcycle riders who did
not text while riding, those who texted only a few times a year increased the likelihood of crash/fall involvement
by approximately 1.2 times while those who texted on a daily basis increased the likelihood by 2.2 times (as
presented in the method section regarding frequencies, never was coded as 1, few times a year was coded as 2,
and daily was coded as 5). Similarly, motorcycle riders who frequently search for information on their mobile
phone while riding were more likely to be involved in a crash/fall (coefficient=0.2, p-value=0.022). For example,
those who used a mobile phone for searching for information a few times a year were about 1.2 times as likely to
get involved in a crash/fall when compared to those who had never engaged in this risky behaviour. In addition,
a higher frequency of running red lights was slightly associated with a higher risk of being involved in a crash/fall,
which however was not statistically significant (p-value=0.066).
Table 3 presents logistic regression model results for crash/fall severity by risky riding behaviours that riders were
engaging in when the crash/fall occurred. In this final model developed using the step-wise approach, four
variables were selected, including calling, riding on the wrong side of a road, riding under the influence of alcohol,
and riding on sidewalks. The model was statistically significant (Chi-square = 17.2, degrees of freedom = 4, p-
value=0.0018). Riders who indicated that they were using a mobile phone for calling when a crash/fall occurred
would be more than two times as likely to be injured (adjusted odds ratio=2.021), which however was not
statistically significant (p-value=0.077). This suggests that calling while riding might have an influence on the
severity of motorcycle crashes/falls (injured versus not injured). The impact of drink riding was also significant
as riders who reported to have experienced a crash/fall when riding under the influence of alcohol were nearly
three times as likely to be injured (adjusted odds ratio=2.798, p-value=0.031).
Interestingly, riders who reported to have experienced a crash/fall when they were riding on the wrong side of a
road or riding on sidewalks were less likely to be injured (adjusted odds ratios=0.289, p-value=0.026 and 0.313
respectively, p-value=0.018). A possible explanation is that when riding on the wrong side of a road, motorcycle
riders travel either at low speeds or when traffic is very light, leading to a lower severity level in case of a crash/fall.
In addition, sidewalks in major Vietnamese cities such as Hanoi and Ho Chi Minh City are often occupied by
street vendors and quite narrow. Thus riding on sidewalks is likely to be at low speeds. Nevertheless, future
research should be undertaken to confirm these possible explanations.
This paper has investigated self-reported crash involvement among motorcycle riders who have engaged in risky
riding behaviours, using data from a survey of university students in Vietnam. The paper has also explored the
associations between the severity of motorcycle crashes (injured versus not injured) and risky riding behaviours.
Results showed that 40% of motorcycle riders reported to have experienced a crash/fall and nearly 24% of
motorcycle riders indicated that they had been injured in a crash/fall. These rates are higher compared to the self-
reported crash rate among motorcycle riders in India (15%) (Rathinam et al., 2007) and the injured crash rate
among cyclists in the Netherlands (5%) (Goldenbeld et al., 2012). However, they are lower when compared to
self-reported crash rates and injured crash rates among motorcycle riders in Laos (45.3% and 31.5% respectively)
(Phommachanh et al., 2016). Nevertheless, the results suggest relatively high rates of both crash involvement and
injury crashes among motorcycle riders in Vietnam, highlighting a key road safety challenge for the country.
Motorcycle riders reported an almost even split between single-vehicle crashes/falls and multi-vehicle crashes.
This is consistent with findings of studies in Australia where single-vehicle crashes account for 44% of motorcycle
crashes (Bambach et al., 2012), and in the US where single-vehicle crashes account for 46% of fatal motorcycle
crashes (Redelmeier and Shafir, 2017). However, in Malaysia, single-vehicle crashes only account for 26% of
motorcycle crashes (Abdul Manan et al., 2017). It is noted that traffic and roadway characteristics, and traffic
regulations might be different among these countries. Most motorcycles in Vietnam have an engine of less than
150cc, which can be considered as scooters in high-income countries. In addition, motivations of riding a
motorcycle can vary significantly in different countries, e.g. leisure or recreation in the US and Australia, and
primary means of travel in several South East Asian countries.
Results also showed that around 5% of motorcycle riders reported to have experienced a crash/fall when they
were using a mobile phone for calling, with 3.8% of riders indicating that they were injured while doing so. These
proportions for calling while riding were the largest compared to other risky riding behaviours, which could be
attributed to the fact that calling while riding was the most prevalent risky behaviour among motorcycle riders
(more than 10% of riders engaged in calling while riding on a daily basis). However, there was limited evidence
that calling while riding increases the likelihood of being injured in a crash/fall. The effects of other forms of
mobile phone use while riding on crash involvement were also significant. More frequent use of a mobile phone
for texting or searching for information while riding was associated with a higher chance of being involved in a
crash/fall. The results suggest a strong influence of mobile phone use while riding on safety of motorcycle riders.
Around half of the motorcycle riders indicated that they had run red lights or rode under the influence of alcohol.
It was further found that drink riding increases the chance of being injured. There was also limited evidence that
running red lights increases the risk of being involved in a crash/fall. While these findings corroborate previous
research conducted in Asia (Chang and Yeh, 2007; Roehler et al., 2015; Tongklao et al., 2016), they confirm that
red light running and drink riding are major road safety issues in Vietnam.
While this paper contributes to understanding the association between crash involvement and mobile phone use
while riding a motorcycle, it is also subject to several limitations. The survey results are self-reported and therefore
may be biased towards socially desirable responses associated with not using a mobile phone while riding.
Crash/fall rates may also be underreported given that motorcyclists who have been seriously injured or killed
while engaging in risky riding behaviours would not have been surveyed as part of this study. While younger
people are more likely to engage in risky riding behaviours, this research only considered university students. In
addition, the analysis was based on a relatively small survey sample size. A larger sample of survey participants
from a broader range of age groups should therefore be targeted in future research. Definitions of several risky
riding behaviours, such as reckless overtaking and riding under the influence of alcohol, would be more specific
to reduce subjectivity. Finally, there was no information regarding injury levels and locations of crashes/falls. To
further investigate the safety effects of risky riding behaviours, different injury levels (serious or minor) should
be considered in future research.
In conclusion, this study has highlighted a number of associations between crash involvement and risky riding
behaviours among motorcyclists, in particular the use of mobile phones for calling while riding. The findings
suggest a number of key challenges for road safety in Vietnam, not least the relatively high rate of crash and injury
involvement associated with mobile phone use while riding a motorcycle. Addressing these challenges is an
important task given the dominance of motorcycle use in Vietnam and their increasing numbers each year. The
findings of this study provide solid evidence on safety issues of mobile phone use while riding a motorcycle,
which should be utilised in educational programs and publicity campaigns. Given the relatively high crash and
injury risk of this behaviour, stronger police enforcement efforts should also be prioritised.
Abdul Manan, M.M., Jonsson, T., Várhelyi, A. Development of a safety performance function for motorcycle
accident fatalities on malaysian primary roads. Safety Science. 2013;60(Supplement C):13-20.
Abdul Manan, M.M., Várhelyi, A., Çelik, A.K., Hashim, H.H. Road characteristics and environment factors
associated with motorcycle fatal crashes in malaysia. IATSS Research. 2017.
Backer-Grøndahl, A., Sagberg, F. Driving and telephoning: Relative accident risk when using hand-held and
hands-free mobile phones. Safety Science. 2011;49(2):324-330.
Bambach, M.R., Grzebieta, R., Tebecis, R., Friswell, R. Crash characteristics and causal factors of motorcycle
fatalities in australia. In Australasian Road Safety Research, Policing and Education Conference. 2012;
Wellington, New Zealand.
Beck, K.H., Watters, S. Characteristics of college students who text while driving: Do their perceptions of a
significant other influence their decisions? Transportation Research Part F: Traffic Psychology and
Chang, H.-L., Yeh, T.-H. Motorcyclist accident involvement by age, gender, and risky behaviors in taipei, taiwan.
Transportation Research Part F: Traffic Psychology and Behaviour. 2007;10(2):109-122.
Coquelet, C., Granié, M.-A., Griffet, J. Conformity to gender stereotypes, motives for riding and aberrant
behaviors of french motorcycle riders. Journal of Risk Research. 2018:1-12.
De Gruyter, C., Truong, L.T., Nguyen, H.T.T. Who’s calling? Social networks and mobile phone use among
motorcyclists. Accident Analysis & Prevention. 2017;103(Supplement C):143-147.
Goldenbeld, C., Houtenbos, M., Ehlers, E., De Waard, D. The use and risk of portable electronic devices while
cycling among different age groups. Journal of Safety Research. 2012;43(1):1-8.
Google. Consumer barometer: Country report - vietnam. 2015.
Harrison, M.A. College students’ prevalence and perceptions of text messaging while driving. Accident Analysis
& Prevention. 2011;43(4):1516-1520.
Hung, D.V., Stevenson, M.R., Ivers, R.Q. Barriers to, and factors associated, with observed motorcycle helmet
use in vietnam. Accident Analysis & Prevention. 2008;40(4):1627-1633.
Ismeik, M., Al-Kaisy, A., Al-Ansari, K. Perceived risk of phoning while driving: A case study from jordan. Safety
JASP Team. Jasp (version 0.8.3.1). Department of Psychological Methods, University of Amsterdam; 2017.
Lin, M.-R., Kraus, J.F. A review of risk factors and patterns of motorcycle injuries. Accident Analysis &
McEvoy, S.P., Stevenson, M.R., McCartt, A.T., Woodward, M., Haworth, C., Palamara, P., Cercarelli, R. Role of
mobile phones in motor vehicle crashes resulting in hospital attendance: A case-crossover study. BMJ.
Moskal, A., Martin, J.-L., Laumon, B. Risk factors for injury accidents among moped and motorcycle riders.
Accident Analysis & Prevention. 2012;49(Supplement C):5-11.
Ngo, A.D., Rao, C., Phuong Hoa, N., Hoy, D.G., Thi Quynh Trang, K., Hill, P.S. Road traffic related mortality in
vietnam: Evidence for policy from a national sample mortality surveillance system. BMC Public Health.
Nguyen, H.T., Passmore, J., Cuong, P.V., Nguyen, N.P. Measuring compliance with viet nam's mandatory
motorcycle helmet legislation. International Journal of Injury Control and Safety Promotion.
Nielsen. Vietnam smartphone insights report. 2017.
NTSC. Traffic safety statistics report. Hanoi: National Transportation Safety Committee of Vietnam; 2015.
OECD/ITF. Improving safety for motorcycle, scooter and moped riders. Paris: The Organisation for Economic
Co-operation and Development/International Transport Forum; 2015.
Ohmori, N., Harata, N., Sugitani, Y., Kunimoto, N. Travel behavior of university students on rainy days: A
preliminary study on international comparison between east asian countries. Journal of the Eastern Asia
Society for Transportation Studies. 2011;9:483-498.
Pérez-Núñez, R., Hidalgo-Solórzano, E., Vera-López, J.D., Lunnen, J.C., Chandran, A., Híjar, M., Hyder, A.A.
The prevalence of mobile phone use among motorcyclists in three mexican cities. Traffic Injury Prevention.
Phommachanh, S., Ichikawa, M., Nakahara, S., Mayxay, M., Kimura, A. Student motorcyclists’ mobile phone
use while driving in vientiane, laos. International Journal of Injury Control and Safety Promotion. 2016:1-
R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for
Statistical Computing; 2017.
Rathinam, C., Nair, N., Gupta, A., Joshi, S., Bansal, S. Self-reported motorcycle riding behaviour among school
children in india. Accident Analysis & Prevention. 2007;39(2):334-339.
Redelmeier, D.A., Shafir, E. The full moon and motorcycle related mortality: Population based double control
study. BMJ. 2017;359.
Roehler, D.R., Ear, C., Parker, E.M., Sem, P., Ballesteros, M.F. Fatal motorcycle crashes: A growing public health
problem in cambodia. International Journal of Injury Control and Safety Promotion. 2015;22(2):165-171.
Stephens, A.N., Brown, J., de Rome, L., Baldock, M.R.J., Fernandes, R., Fitzharris, M. The relationship between
motorcycle rider behaviour questionnaire scores and crashes for riders in australia. Accident Analysis &
Prevention. 2017;102(Supplement C):202-212.
Susilo, Y.O., Joewono, T.B., Vandebona, U. Reasons underlying behaviour of motorcyclists disregarding traffic
regulations in urban areas of indonesia. Accident Analysis & Prevention. 2015;75:272-284.
Tongklao, A., Jaruratanasirikul, S., Sriplung, H. Risky behaviors and helmet use among young adolescent
motorcyclists in southern thailand. Traffic Injury Prevention. 2016;17(1):80-85.
Tran, N.L. Context dependencies of travel behavior: A case study on motorcycle in hanoi. PhD thesis, Graduate
School for International Development and Cooperation, Hiroshima University; 2013.
Truong, L.T., De Gruyter, C., Nguyen, H.T.T. Calling, texting, and searching for information while riding a
motorcycle: A study of university students in vietnam. Traffic Injury Prevention. 2017;18(6):593-598.
Truong, L.T., Kieu, L.-M., Vu, T.A. Spatiotemporal and random parameter panel data models of traffic crash
fatalities in vietnam. Accident Analysis & Prevention. 2016a;94:153-161.
Truong, L.T., Nguyen, H.T.T., De Gruyter, C. Mobile phone use among motorcyclists and electric bike riders: A
case study of hanoi, vietnam. Accident Analysis & Prevention. 2016b;91:208-215.
Truong, L.T., Nguyen, H.T.T., De Gruyter, C. Correlations between mobile phone use and other risky behaviours
while riding a motorcycle. Accident Analysis & Prevention. 2018;118:125-130.
Vu, T.A., Shimizu, T. Towards development and evaluation of the motorcycle drivers re-education program in
vietnam: Modeling of motorcycle driver's undesired behaviors. In 11th World Conference on Transport
Research (WCTR). 2007; Berkeley, California.
WHO. Global status report on road safety 2015. Geneva: World Health Organization; 2015.
WHO. Powered two- and three-wheeler safety: A road safety manual for decision-makers and practitioners.
Geneva: World Health Organization; 2017.
Wong, L.P. Socio-demographic and behavioural characteristics of illegal motorcycle street racers in malaysia.
BMC Public Health. 2011;11(1):446.
Zhou, R., Rau, P.-L.P., Zhang, W., Zhuang, D. Mobile phone use while driving: Predicting drivers’ answering
intentions and compensatory decisions. Safety Science. 2012;50(1):138-149.
Table 1 Frequency and proportion of motorcycle riders who reported to be injured in the most recent
crash/fall when engaging in risky behaviours
Risky riding behaviour
Injured in a crash/fall
2.31 - 5.21
0.28 - 1.83
0.37 - 2.03
0.79 - 2.82
1.59 - 4.12
0.18 - 1.62
0.01 - 1.19
1.59 - 4.12
1.59 - 4.12
0.37 - 2.03
Table 2 Logistic regression results for being involved in a crash/fall by risky behaviours
Adjusted Odds Ratio
Frequency of texting
Frequency of searching
Frequency of red-light running
Note: n = 665; Null deviance = 895.1, residual deviance = 858.2, model was significant (Chi-square = 36.9,
degrees of freedom = 3, p<0.0001); * p<0.05, ** p<0.01
Table 3 Logistic regression results for being injured in the most recent crash/fall by risky behaviours
Adjusted Odds Ratio
Note: n = 266; Null deviance = 360, residual deviance = 342.8, model was significant (Chi-square = 17.2,
degrees of freedom = 4, p=0.0018); * p<0.05, ** p<0.01
Fig. 1 Frequency of risky behaviours while riding a motorcycle
Fig. 2 Types of crashes/falls experienced by motorcycle riders