Helmet Usage among Adolescents in Rural Road from the Extended Theory of Planned Behaviour
Mohamad Baharin Ahmed,
Nur Sabahiah Sukor
Motorcyclists are more prone to crash injuries than car drivers because motorcycles are unenclosed, leaving riders vulnerable to contact hard road surfaces. This study was conducted based on safety helmet issues among adolescents. Theory on behavioral sciences like Theory of Planned Behaviour (TPB) is useful in understanding why adolescent motorcyclist regardless helmet safety usage. A cross-sectional study was carried out with a sample size of 288 adolescents was chosen in this study. The data collected were carried using a questionnaire survey. The descriptive analysis shows, more than half of respondents are those aged between 17 to 18 years old. Majority (80%) of them do not have motorcycle licenses. This means that they are riding a motorcycle without a basic knowledge of road traffic regulations. Over 65% respondents were riding a motorcycle every day or almost daily during the last 12 months. The correlation analysis shows, there are strong positive relationship between intention and behaviour of respondent. Sometimes they wear helmets, however rarely to wear helmets especially in a short distance (less than 2 km). In addition, the hierarchical multiple regression analysis shows all variables including descriptive norm were found significant (p<0.05), except perceived behaviour control shows insignificant relationship to intention to use a safety helmet. As conclusion, attitude, subjective norm and intention remained a significant predictor of behaviour. However, perceived behaviour control and descriptive norm were not significant in predicting such behaviour (safety helmet usage).
Received: July 24, 2012;
Accepted: December 01, 2012;
Published: February 01, 2013
Malaysia has a complete land transportation network that link among cities
and towns. Passenger transport may be public, where operators provide scheduled
services, or private vehicle. According to Ministry of Transport Malaysia, in
year 2010 a total numbers of registered shows the private transport are 498,041
for motorcycle and 585,304 for car respectively (Ministry
of Transport Malaysia, 2010). This statistics shows the private vehicle
contributes about 93.5% of total vehicle registered in that year. Its reveals
that private vehicle is favored and preferable mode of transportation in the
country. The impact from this scenario, it contributes to congestion and accident
rates (Nurdden et al., 2007; Abbas
et al., 2012). It is very important for Malaysia to have a very safe
and comfort road to users as one of the criteria in order to archive Vision
2020 in the near future.
Furthermore, increasing the number of private vehicles, the accident rate increased
correspondingly. Ironically, motorcyclists are more prone to crash injuries
than car drivers because motorcycles are unenclosed, leaving riders vulnerable
to contact hard road surfaces (Ambak et al., 2009,
2010a, b). In Ops Sikap 24 which
held between 23 August 2011 to 6 September 2011, a number of 289 fatal were
recorded and 178 of them were motorcyclists rider and pillion (Royal
Malaysia Police, 2011). This amount accounted for 62% of fatal accidents
in the period. Based on the increasing number of road accident among motorcyclist
indicates the need for a study on the practice of safety helmet usage among
motorcyclist. Wearing a motorcycle helmet can reduce the risk of death from
a motorcycle crash (Hefny et al., 2012). So,
what were the contributing factors that affect the usage of safety helmet among
motorcyclist? These are some gaps that should be investigated using the behavioral
sciences approach especially in traffic safety behavior.
The Theory of Planned Behavior (TPB) is an extension of the theory of reasoned
action (Ajzen, 1991). The TPB has been applied extensively
and successfully to the prediction of a variety of behaviours such as social
science, transportation, education and health. For example, truck driving behaviour
(Poulter et al., 2008), bicycle helmet use among
teenagers (Lajunen and Rasanen, 2004), motorcyclists
intention to speed (Elliott, 2010), speeding behaviour
of riders of heavy motorcycle (Chen and Chen, 2011)
and predicting proper safety helmet usage (Ambak et al.,
2011a, b). However, in several study showed that
it is needed to add the social influence (descriptive norm) as an element in
TPB (Hamilton and White, 2008; Rivis
and Sheeran, 2003; Moan and Rise, 2011).
Therefore, this study was aimed to investigate the factors affecting why most adolescents (school students) are not wearing a safety helmet by using Theory of Planned Behavior. Also, to introduce additional variable namely social influences (descriptive norm) in Theory of Planned Behaviour model as extended version.
QUESTIONNAIRE DESIGN AND MEASUREMENT
The most important part of the Theory of Planned Behaviour is how the questions
were developed to describe the factors. According to Ajzen
(2002), the behaviour of interest is defined in terms of its Target, Action,
Context and Time (TACT) elements. All the questions in this questionnaire was
taken and processed based on previous research.
This study was conducted on September 2011 to June 2012. The respondents in this study were secondary school students which was selected school (name of each school is not reveals, confidential). Then, the data were collected in classrooms by teachers. Every student in the school received a questionnaire and the teachers told the students about the purpose of the study (to investigate the wearing helmet behaviour among adolescents). The students were assured about anonymity and confidentiality (students did not write their names to the forms) and were asked to fill the forms carefully and honestly. Survey time was between 25-35 min. All respondents returned a completed questionnaire. Since the aim of the study was to investigate reasons for not using a helmet when riding a motorcycle, all the students who have experience in riding a motorcycle were asked. The population of this study was selected among the adolescents at rural area in Batu Pahat, Johor, Malaysia.
The beginning expectation adolescents involve in this study was targeted to
be 500 samples. There are several studies that using lesser sample are; public
attitudes towards motorcyclists safety by Musselwhite
et al. (2012) using (N = 228), motorcycle rider intentions by Tunnicliff
et al. (2012) using (N = 233), safety helmet usage by Ambak
et al. (2011a, b) using (N = 292), truck
driver behaviour using by Poulter et al. (2008)
using (N = 232) and rider intention to accelerate (N = 110) by Elliott
In this study, we used quantitative method (statistical analysis) to quantify the variables in the model (TPB) to be highlighted as a strong predictor. The details analysis includes descriptive statistics, reliability (coefficient alpha), correlation and hierarchical multiple regression. The analyses of data were then using software called Statistical Package for Science Social (SPSS) version 19.
RESULTS AND DISCUSSION
This section is explain about the result from descriptive, correlation and hierarchical multiple analysis. Then, a detail discussion on the finding is explained and highlighted.
Descriptive analysis: Table 1 shows the descriptive
analysis on adolescent motorcyclists characteristic. From the descriptive
analysis, more than half (57.3%) respondents who participated in this survey
are those aged 17 to 18 years old. Most respondents (55.7%) who have experience
riding a motorcycle for more than 4 years. More than 80% of them do not posses
a motorcycle license. A study carried by Ambak et al.
(2011a) showed there were about 20% respondents who do not possess any driving
license. This is critical, meanings that they are riding a motorcycle without
a basic knowledge of road traffic regulations. It is to be considered they are
riding in a risky behavior not only for their self, perhaps other road users.
Alarmingly, over 65% of them were rode a motorcycle in every day or almost daily
during the last 12 months. Sometimes they wear helmets, however rarely wear
helmets especially in short distance (within less than 2 km). Kulanthayan
et al. (2000, 2001) also mentioned that a
short distance (<2 km) will affect the compliance of proper safety helmet
usage. Apart, type of road also affected the usage of safety helmet, particularly
on rural road, local road and as well in district level (Li
et al., 2008a, b; Kanitpong
et al., 2008; Keng, 2005). However, Hung
et al. (2006) claimed in their study it was found that National
road shows higher safety helmet usage compared to others provincial and district
Correlation analysis: Correlation is to measure the strength of the
relationship between two or more variables. From Table 2 shows
there is a moderate positive relationship between intention and behaviour of
respondent (r = 0.430) and found statistically significant at 5% significant
|| Socio-demographic of respondents
|| Correlation between each variable
|**Correlation is significant at the 0.01 level (2-tailed),
*Correlation is significant at the 0.05 level (2-tailed), ve -: Value is
mean indirect relationship between variables in the TPB model
Those who have intention to wearing a helmet while riding motorcycle are tending
to do it. Also, a positive relationship between subjective norm (r = 0.393,
p (0.000) <0.01) and descriptive norm (r = 0.266, p (0.000) <0.01) with
behaviour. This is means by seeing the people around the respondent, it will
reflect their behaviour. Similarly, Ambak et al.
(2011b) and Lajunen and Rasanen (2004) stated in
their study, subjective norm shows there is a positive relationship and statistically
significant factor in the Theory of Planned Behavior model.
Also, Table 3 demonstrates some insignificant item. For example,
the correlation between perceived behaviour control and subjective norm found
to be insignificant with r = -0.260 and p (0.664) >0.05, descriptive norm
with r = 0.580 and p (0.328) >0.05 and intention with r = -0.320 and p (0.593)
>0.05. This finding in line with the studied done by Ambak
et al. (2010a, b) and Lajunen
and Rasanen (2004).
|| Model summary of multiple regressions toward intention
|aPredictors: (Constant), perceived behaviour control,
Subjective norm, attitude, bPredictors: (Constant), perceived
behaviour control, subjective norm, attitude, descriptive norm
Regression analysis predicting intention: A hierarchical multiple regression analysis was performed to examine the proposed predictors toward intention. The standard TPB variables were entered at Step 1 and additional predictor; descriptive norm entered at Step 2. Table 3 shows the model summary of multiple regressions toward intention. Table 4 shows the summary of ANOVA analysis toward intention.
The Step 1 variables (R2) accounted for 15% of the variance in intentions,
F (3, 284) = 16.25, p<0.001, with two TPB predictors (attitude and subjective
norm) reported as significant.
|| Summary of ANOVA analysis toward intention
|aPredictors: (Constant), Perceived behaviour control,
subjective norm, attitude , b Predictors: (Constant), perceived
behaviour control, subjective norm, attitude, descriptive norm cDepandent
|| Hierarchical multiple regression coefficient toward intention
|aDependent variable: Intention, PBC: Perceived
behaviour control, SN: Subjective norm, ATT: Attitude, DN: Descriptive norm
The Step 2 variables significantly accounted for an additional 6% of the variance
in intentions, F (4, 283) = 18.38, p<0.001.
Table 5 shows the hierarchical multiple regression coefficients toward intention. At step 1, attention and subjective norm were significant and the perceived behaviour control was insignificant towards intention. In step 2, attitude, subjective norm and descriptive norm were significant and perceived behaviour control was not significant towards intentions.
Hierarchical multiple regression analysis predicting behaviour: An additional regression analysis was conducted to explore the effect of descriptive norm towards behaviour. Intention, attitude, subjective norm and perceived behaviour control were entered at Step 1 and additional descriptive norm entered at Step 2. Table 6 shows the model summary of multiple regressions toward behaviour. Table 7 shows the summary of ANOVA analysis toward intention.
As shown in Table 6 and 7, Step 1 explained a significant proportion of variance (30%), F (4, 283) = 29.69, p<0.001, with attitude, subjective norm and intention reported as significant. Step 2 accounted same of the variance (30%) in behaviour, F (5, 282) = 23.76, p<0.001.
|| Model summary of multiple regressions toward behaviour
|aPredictors: (Constant), intention, perceived behaviour
control, subjective norm, attitude bPredictors: (Constant), intention,
perceived behaviour control, subjective norm, attitude, descriptive norm
|| Summary of ANOVA analysis toward behaviour
|aPredictors: (Constant), intention, perceived behaviour
control, subjective norm, attitude, bPredictors: (Constant),
intention, perceived behaviour control, subjective norm, attitude, descriptive
norm, cDependent variable: behaviour
|| Hierarchical multiple regression coefficient toward behaviour
|aDependent Variable: Behaviour (BHV), Predictor:
ATT: Attitude, PBC: Perceived behaviour control, SN: Subjective norm, INT:
Intention, DN: Descriptive norm
Attitude, subjective norm and intention remained a significant predictor of
behaviour. However, perceived behaviour control and descriptive norm were not
significant toward behaviour. Similarly these finding are found in (Ambak
et al., 2011a, b; Lajunen
and Rasanen, 2004). Contradict finding is found in Ali
et al. (2011) studied that perceived behaviour control also found
Table 8 shows the hierarchical multiple regression coefficients
toward behaviour. At step 1, intention, attitude and subjective norm were found
statistically significant (p<0.05). However, perceived behaviour control
was found statistically insignificant (p>0.05) towards behaviour. In step
2, only attitude, subjective norm and intention were found statistically significant
(p<0.05). Again, perceived behaviour control and descriptive norm were not
significant towards intentions.
This study demonstrates that all the preceding factors in TPB are within the
average mean score (greater than 3) between agreed (5) and disagreed (1) using
5-point Likert scale. Correlation analysis shows there are strong positive relationship
between intention (r = -and behaviour of respondent. Those who have intention
to wearing a helmet while riding motorcycle are tending to do it. There is a
positive relationship between subjective norm and descriptive norm with behaviour.
That means by seeing the people around the respondent, it will reflect their
behaviour. As mentioned in many studies (Ambak et al.,
2011b; Ali et al., 2011; Lajunen
and Rasanen, 2004).
By using the hierarchical multiple regressions, researcher found that all variable including descriptive norm were found significant except perceived behaviour control toward the intention with the subjective and descriptive norm have a very strong significant number. However, attitude, subjective norm and intention remained a significant predictor of behaviour but perceived behaviour control and descriptive norm were not significant toward behaviour.
It is vital to concern on safety helmet usage among the adolescent especially in rural area, whereby there is lack of enforcement activity has been carried out. Even though, the respondents have good enough knowledge and attitude regarding the importance of safety helmet. However, when its translated into their daily practices might be the other way around. Its can be concludes that adolescents are easily influenced by attitude and their surroundings either from the family or close friends (subjective norm) and other people (descriptive norm) in the intention to do something. Nevertheless, when it is translated into action, they are still under the influence of attitude, intention and the immediate the influence of the family (subjective norm). Strictly on law enforcement of motorcycle helmet is needed in order to tackle the problem regarding the improper behaviour of wearing motorcycle safety helmet among the adolescent.
This study presents part of result for on going research to develop a behavioral intention model toward proper helmet usage among adolescents motorcyclist in school. Future research needs to focus on how to educate the adolescents to ensure they are willing to wear safety helmet. This approach should be done by inculcate and advocates the adolescents to have a mind set as a safety culture in their daily practice, even for a short trips. Parents should be aware and feel concerns to their children by showing a good example and good practice (i.e to use a safety helmet). This because adolescents are easily influenced by the behaviour performed by the person close to them. A similar study could be conducted to other road users behaviour especially for pedestrian to cross a over-bridge, the usage of seat belts, lane discipline (i.e overtaking, turn left or right maneuvers), the usage of signal when do the turning maneuvers and many more.
Also, the usage of extended theory of planned behaviour can be further tested.
For instance, any additional psychological factor such as past behaviour, sensation
seeking (Cestac et al., 2011) and group norms
(Baker and White, 2010; Johnston
and White, 2003).
The author would like to thank Universiti Tun Hussein Onn Malaysia (UTHM) and Mara Higher Skill College (KKTM), Seri Gading who provides a facility and a good research group to accomplish this study.
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