1.1.Background of the study Road traffic injuries and fatalities has become a global public health phenomenon as the authorities begin to concern about the increment number of killed and injured people on the road.
According to World Health Organization (WHO) (2007a), fatalities of the road traffic injury estimated to rise from 5.1 million in 1990 to 8.4 million in 2020. A research conducted by Sivak and Schoettle (2014) at University of Michigan reported that among the top 25 most dangerous countries for the road crashes, Malaysia in the rank of 17 with 30 fatalities per 100,000 individuals. Accumulation of elements often leads to road accidents. The elements involved includes human, infrastructure, vehicles and environmental factors (Munteanu, Rosu, Panaitescu & Punga, 2014). However, human factors and behaviours plays major roles in contributing to a road accident (Masuri, Dahlan, Danis & Md Isa, 2017). The major risk factors of human which contribute to fatal road accidents consists of male gender, age between 30-39 years old, low educational level, inattention, excessive speed while driving, alcohol consumption and failure to observe traffic rule.
However, this study focuses on two human factors which lead to Road Traffic Accident (RTA) which is attitude towards safe driving and sociodemographic characteristics. Attitudes of the drivers become the crucial issues in order to reduce road crashes and achieve road safety target. Redhwan and Karim, (2010) reported that high speed, drivers’ lack of awareness about traffic regulation and laws, and drivers’ non-compliance with traffiic rules and regulation become the significant factors that lead to traffic accidents. On the other hands, the components of the demographic characteristics which discussed in this study were year of driving experiences and annual driving distance. According to a research done by Nik Mahdi, Bachok, Mohamed and Shafei (2014), near miss incident were relatively high among long distance bus driver in Malaysia.
Besides, the factors which explain the higher risk of road accident among younger drivers is their lacking in driving experiences. Hence, this human factors was believes as the contributing factors in determining the attitudes towards safe driving. 1.2.Problem statement The majority of RTA were caused by human error. Masuri, Dahlan, Danis, and Isa (2016) has stated that the drivers’ error as an important human component that need to be further investigated due to this condition.
Up to now, number of local research and evidence supporting the elements of driver’s attitudes and behavior analysis still limited (Masuri, Dahlan, Danis and Isa, 2015). Previous study shows that, different factors such as socio-demographic issues brought significant effects on driving behaviour (Al-Naggar, Bobryshev, and Mohd Noor, 2013). There was also strong evidence that influences from internal and external stimulus contributing to road violence action which includes their sociodemographic characteristics (Masuri, Abang Mustaffa, Dahlan, and Md. Isa, 2016). In relation to sociodemographic issue, according to Tseng (2012) on the results of logistic regression model, a driver’s driving experience was the most important factor that lead to at fault accident risk. The previous study also indicate that a driver’s yearly driving kilometers had significant association with at fault accident risk.
This study shows that too little or too much experience and annual driving distance reflects bad safety performance and higher at fault accident risk. However, whether annual driving distance and driving experienced was associated with attitude towards safe driving remain unclear. 1.3.Research Question The study is designed to answer the following questions: 1.Is the year of driving experience will affect the attitude towards safe driving? 2.Is the annual driving distance will affect the attitude towards safe driving? 1.4.Research Objectives There are a few objectives in this study which are: 1.To determine whether there is association between year of driving experience and attitude towards safe driving 2.To determine whether there is association between annual driving distance and attitude towards safe driving 1.5.Significance of the study This study may help to provide information regarding issues that may contribute to the RTA. This study also may identify how attitude of drivers in Malaysia and identify the offenses committed while driving. This is very crucial for citizens to take prevention and precaution to reduce the RTA that may occurs due to human error.
Results of this study will enable Occupational Therapy to further explore regarding the behavior of driver by using driving stimulation. Driving stimulation is very helpful in preventing the behavioral issues among drivers as it can discover the skills of the driver such as anticipate hazards, manage speed, and maintain attention while driving. Furthermore, in order to assess the real performance of the driver in real situations, on road driving performance also can be done. In other hand, this study also promote appropriate intervention, in reducing RTA.
Hence, it is vital to understand the human attitudes related to driving behavior. Commercial transportation company also will get benefit from this study in order to develop near miss management system as a preventive scheme in road safety. CHAPTER ? LITERATURE REVIEW 2.1.Road Traffic Accidents (RTA) phenomena RTA are a major global public health problem but being neglected. This problem require concerted efforts for effective and sustainable prevention (Srinivasa Kumar and Srinivasan, 2013). Based on WHO, accidents can be define as “unpremeditated event resulting in recognizable damage” as cited by (Aggarwal, Oberoi, Kumar and Sharma, 2009).
Meanwhile, the definition stated by WHO (2007b) of road traffic injuries is “fatal or non-fatal injuries incurred as a result of a road traffic crash” and road traffic crash can be defined as “collision or incident that may or may not lead to injury, occur on a public road and involving at least one moving vehicle” WHO (2015) also reported that global road fatalities occur around 85% and 90% of the disability-adjusted life years lost due to crashes. Road traffic injuries are currently estimated to be the ninth leading cause of death across all age groups globally, and are expected to become the seventh leading cause of death by 2030 as reported in Global Status Report on Road Safety 2015. RTA have been identified as the leading factor of decease in Malaysia, after coronary/heart disease, stroke, influenza and pneumonia (Nasa, 2014). Result of a research by the Malaysian Institute of Road Safety (MIROS) indicated that an average of 18 people were killed on Malaysian roads everyday and surprisingly this figure is expected to ascent to 29 by 2020. The research also predicted that road mortalities would account for 10,716 deaths in 2020 compared with an average of 6,915 annual fatalities in recent years. Babulal (2018) reported in 2016, there were total of 7,152 fatalities in Malaysia road accidents.
This showed an alarming increase from 6,706 deaths in the year before. There was also reported that an increase of accidents were recorded from 489,606 in 2015 to a total of 521,466 in 2016. A total of 80.6 per cent of this road accidents were due to human error. 2.2.Attitude towards safe driving and RTA issues According to Mohd Soid, Isah and Liew (2016), attitudes involves the cognitive and affective components. Cognitive component refers to the mental process of perception, conceptions and beliefs regarding the attitudinal object.
For this case, regarding traffic safety. Meanwhile, the affective or emotional component, which collects all those emotions and feelings that stimulate traffic safety. Attitudes also referred as a learned predisposition to respond to a social object, such as a person, group, idea and physical object,in either a positive or negative manner in particular situations. In order to develop more appropriate planning and intervention for reducing the prevalence of RTA, understanding of human attitudes related with driving behavior is very crucial (Masuri et al. 2016).
In a survey done by Iversen and Rundmo (2004) of Norwegian drivers related to attitude towards traffic safety, an attitude contributing to the safe behavior is an ideal attitude . From the survey, a total of 11% of the respondents reported ‘non-ideal’ attitudes related to rule violations and speeding. Meanwhile, for attitudes related to the careless driving behavior of others only 3% had ‘non-ideal’ , and 4% related to drinking and driving. These results indicated that despite positive attitudes toward traffic safety issues, there are potentials for improvement, especially related to violations of rules and speeding. Another study done by Verma, Chakrabarty, Velmurugan, Bhat B and Kumar H.D (2017) reveal that the person with extreme levels of boredom are susceptible to road crashes. Multiple dangerous traffic violations such as failing to stop at closed gates and bumping at curbs among drivers are the effect of boredom susceptibility.
Besides, falling asleep while driving, lack of attention and losing steering control are some of the leading consequences of boredom susceptibility which are risky to road safety. Furthermore, altruistic and anxious individual has higher tendency to have risk related to traffic accidents as well as having positive attitude towards traffic safety (Danciu, Popa, Micle and Preda, 2012). But in contrast, individual who scoring high in seeking sensation and normlessness which shows a negative attitude towards traffic safety have low risk related to traffic accidents. 2.3.Years of driving experience related with RTA As stated by Tseng (2012) results of logistic regression model discovered that a driver’s driving experience was the most influential contributor to at fault accident risk. The most common measure of driving experience is the time in years since an individual passing a driving test (Clarke, Ward, Bartle and Truman, 2006).
Driving experiences did not measured by age as 24 year old with 6 months driving experience did not have the same risk of an injury accident as a 17 year old with equivalent experience. This can be proven by the effect of accident statistics because there are more accident occurrence among 17 year old individual with only 6 months driving experience than 24 year old individual with 6 months experience. According to Isler cited by Ali, El-Badawy and Shawaly (2014) risky driving among young inexperienced drivers significantly amplify their risk of having a crash. Contrary to research done by Issa (2016), individual with higher driving experience and higher educational level had more tendency to involve in accidents.
Result of survey done by Tseng (2012) among bus driver revealed that not only inexperienced individual had associated with a higher at fault risk accident, but too much experience also had high risk of accident propensity. Beginner drivers with less than 3 years of experiences held the highest at fault accident rate. Meanwhile,the second highest at fault accident rate is the senior drivers with more than 20 years of experiences. Drivers with less than 15 years and more than 5 years of experiences had relative low accident rate. Next, individual with 6-8 years of experience group possessed the lowest accident rate.
Although we usually assume that young/inexperienced drivers are both less skilled and willing to take more risks, it may also be that as experience increases, certain types of risk taking may increase as skill levels increase (Clarke et al. 2006). Distinction in experience also shown different improvement in different types of accident. It was found that increasing in driver experience showed the quickest improvement in cross-flow turn accidents, whereas accidents occurring in darkness with no street lighting showed the slowest rate of improvement. 2.4.Annual driving distance related with RTA Some of individuals assumed that driver had more experience as a result of driving a greater distance. In fact, the greater the distance travelled, the more likely an individual will have an accident (Clarke et al.
2006). When the users decrease their time or exposure on the road, the potential of being involved in accidents is reduces (Masuri, Isa and Tahir, 2012). According to Abang Abdullah and Von (2011) the job responsibilities of bus drivers lead to fatigue. Driver fatigue has been proven to be involved in 15-30%of all crashes (Smith and Smith, 2017). Among commercial drivers, driving fatigue is one of the contributors of accidents. During the last 12 months of driving, over a quarter of long distance lorry drivers reported falling asleep due to fatigue at wheel.
Due to the high annual mileage exposure and other factors such as long trips, the risk of being involved in a fatigue-related crash in bus drivers’ is higher than non-commercial drivers. The relationship between the capability of the driver and the task demand is very crucial for road safety. If the demand exceeds capability, the task is very difficult to be performed and accident is prone to be happened. Generally, fatigue, or tiredness, pertaining the inability or disinclination to continue an activity is due to the activity has been going on for “too long”. Nik Mahdi et. al (2014) reported that near miss incident were relatively high among long distance bus driver in Malaysia.
Within a year, at least one near miss incident experienced by more than a quarter of long distance bus drivers in Malaysia. Based on the same research, individual who drive more than 400 km per day had tendency to involve in a near miss incident. Besides, low mileage drivers were significantly more likely to describe themselves as worse drivers relative to high mileage drivers (Langford & Koppel, 2004). However, Langford, Methorst & Hakamies-Blomqvist (2006) state that drivers who travelling more kilometers will typically have reduced crash rate per kilometre, compared to those driving less kilometres. Based on a survey among bus drivers by Tseng (2012), the drivers whose yearly driving kilometres more than 60,000 had the highest at fault accident rate, followed by the group of less than 30,000 km. Meanwhile, the lowest at fault accident rate is the group yearly driving kilometres from 30,000 to 59,999.
the result indicate that both low and high annual mileage possessed risk of at fault accident. CHAPTER ? METHODOLOGY 3.1.Study design The research study that applied in this study is cross-sectional study design. A cross-sectional study design is a study of a stratified group of the subject at one point in time and draws the conclusion about a population by comparing the characteristic of those strata over the short period of time. The design is suitable to use as it is easy to conducted, short period needed and inexpensive to be implemented and useful in determining the association between year of driving experience, annual driving distance and attitude towards safe driving.
Hence, a set of questionnaires had been distributed among drivers in Malaysia. 3.2.Study location The questionnaire were distributed among the drivers at Central, West, South, and East region of peninsular Malaysia. This location chosen as to fulfill the requirement needed which includes several states which is Selangor, Kuala Lumpur, Johor, Pahang, Terengganu and Kelantan. 3.3.Sample 3.3.1.Sample size calculation The sample size required in this study is 170. The determination of this sample size is based on previous research by Masuri, Dahlan, Danis & Md Isa, 2017 as the amount of population is corresponding with this study. The sample size of previous research is 139 .
Hence, 20% of sample size is added from the previous one. This is done in order to avoid insufficient sample size due to incomplete returned questionnaire. 3.3.2.Sampling method The sampling method used in this study was simple random sampling method. The respondents have been chosen based on the requirements that needed by the questionnaires.
In this study, the respondents were chosen based on the inclusion and exclusion criteria 3.3.3.Subject The inclusion criteria for the subjects for this study are the individual who engage in driving and also a driving license holder in peninsular Malaysia with the age of 17 years old and above. Meanwhile, the exclusion criteria includes individual who involve or become a witness in any RTA within last 12 months. 3.4.Research instruments There are two sections in this study which includes demographic data and one set of questionnaire. The validated questionnaire used in this study is Attitude towards Safe Driving Scale (ASDS-46). This questionnaire is used to assess the attitude of driving for the subjects.
3.4.1.Section 1 – Demographic Data This section consists several questions which required to be filled by the respondents. The questions are related to the respondent’s personal data. This demographic data consists of respondent’s age, occupation, level of education, income, driving license class, driving experiences, annual driving distance, purpose of driving, types of transport used, involvement in accident or being witness of an accident and number of accident involved. 3.4.2.Section 2- Attitude towards Safe Driving Scale (ASDS-46) ASDS-46 consists of 46 questions. This questionnaire is designed to assess the attitudes on safe driving among the drivers.
This questionnaires use 5-point Likert Scale which are “sangat tidak setuju”, “tidak setuju”, “tidak pasti”, “setuju”, and “sangat setuju”. If the questions being left unfilled by the respondent, “tidak pasti” point will be given as a neutral response. 3.5.Psychometric properties of the instrument 3.5.1.Attitude towards Safe Driving (ASDS-46) Based on a study done by Masuri, Dahlan, Danis and Md Isa (2016), item and person value for validity and reliability test of ASDS-46 by using Rasch model shows .80 followed by .84 Cronbach’s Alpha value. This indicates that this assessment has high validity and reliability. Hence, suggested to be used as a great potential to be a predictor in understanding human response.
3.6.Procedure of data analysis This study had been used self-administered questionnaires. The consent form and questionnaires had been distributed by online medium using Google Form. The distribution done by using mobile phone and the answer of the respondent had been kept automatically through the Google Form driver. Besides, some of the questionnaires had been distributed personally to the sample which the respondents will be given a set of paper and pen. The respondents fill in the consent form, demographic data and answer the questionnaires given.
After completing, the respondents returned the questionnaire in the same day or the can give later on. In addition, research aim and description of the study had been attached with the questionnaires. A telephone number also being provided in order to assist the respondents if there as any doubt in completing the questionnaires. 3.7.Statistical data analysis A set of questionnaires that consists of three sections are used in this study which are demographic data and ASDS-46.
This study used Statistical Package for the Social Sciences (SPSS) version 22.0 for data analysis as well as interpreting the results which obtained after data collection. The data was being analyzed by inferential analysis. For inferential statistical analysis, the data were being analyzed based on the objectives of this study. In order to identify the correlation between experience, mileage and attitude, Anova test had been used. 3.8.Ethical consideration Before the research had been conducted, the approval letter from Faculty of Health Science and Institute of Research, Management ; Innovation (IRMI), Universiti Teknologi Mara (UiTM) was obtained. Moreover, a consent form had be given to all the respondents which to be filled before answering the questionnaires.
All the information gathered from the respondents will be kept confidential. CHAPTER ?V DATA ANALYSIS There were two objectives in this study. One of the objectives is to determine whether there is association between year of driving experience and attitude towards safe driving. Another objectives was to determine the association between annual driving distance and attitude towards safe driving.
The total number of questionnaire which had been distributed directly to respondents were 115 while 72 respondents were obtained from online medium. However, only 98 out of 115 questionnaire distributed had been returned and filled completely. Thus, the total respondents whose involves in this study are 170. 4.1.Respondents demographic data A total of 73 (42.9) male and 97 (57.1) female individual who hold various driving license class take part in this study. Most of the participants age ranged from 17-30 years old. Table 1 presents the details the respondents demographic data (gender, age, careers, level of education, monthly income, purpose of driving, driving license class, RTA offenses, year of driving experiences and annual driving distance) from this study.
Table 1. Demographic Data Characteristics (N=170) Frequency (percentage) Gender Male female 73 (42.9) 97 (57.1) Age 17-30 31-40 41-50 51 and above 136 (80.0) 18 (10.6) 8 (4.7) 8 (4.7) Careers Agriculture, food and natural resources Architecture and construction Business management and administration Education and training Finance Government and public administration Health science Hospitality and tourism Human services Information technology Law, public safety, corrections and security Manufacturing Science, technology, engineering and mathematics Transportation, distribution and logistics Public transport drivers Others 4 (2.4) 8 (4.7) 5 (2.9) 16 (9.4) 6 (3.5) 9 (5.3) 17 (10.0) 2 (1.2) 3 (1.8) 1 (0.6) 4 (2.4) 2 (1.2) 17 (10.0) 3 (1.8) 8 (4.7) 65 (38.2) Level of education Foundation Diploma Degree Master PhD Others 6 (3.5) 36 (21.2) 104 (61.2) 8 (4.7) 2 (1.2) 14 (8.2) Monthly income RM6000 61 (35.9) 45 (26.5) 26 (15.3) 13 (7.6) 11 (6.5) 5 (2.9) 9 (5.3) Purpose of driving (yes answer) Education Work Recreation Others 74 (43.5) 75 (44.1) 33 (19.4) 59 (34.7) Driving license class (yes answer) B B2 D Others 11 (6.5) 75 (44.1) 140 (82.4) 8 (4.7) RTA offenses (yes answer) Speeding Against red light Do not use safety belt Use mobile phone Carelessness Overtaking queue Overtake on double line Signaling Use emergency lane No respect to other drivers Not wear helmet All of the offenses above 104 (61.2) 88 (51.8) 75 (44.1) 80 (47.1) 49 (28.8) 29 (17.1) 37 (21.8) 18 (10.6) 16 (9.4) 13 (7.6) 31 (18.2) 5 (2.9) Year of driving experiences ; 3 years 3-5 years 6-8 years 9-11 years 12 years and above 42 (24.7) 70 (41.2) 24 (14.1) 8 (4.7) 26 (8.8) Annual driving distance ; 5 000km 5 000km-15 000km 15 001km-30 000km 30 001km-59 999km 60 000km and above 64 (37.6) 44 (25.9) 31 (18.2) 14 (8.2) 17 (10.0) There are 18 classes of careers (Agriculture, food and natural resources, architecture and construction, business management and administration, education and training, finance, government and public administration, health science, hospitality and tourism, human services, information technology, law, public safety, corrections and security, manufacturing, science, technology, engineering and mathematics, transportation, distribution and logistics, public transport drivers and others) among the respondents. 65 (38.2%) of the respondents are in the others class of careers which is the highest. The second highest for the class of careers are health science and science, technology, engineering and mathematics which is 17 (10%) equally.
Meanwhile, information technology class is the lowest which is only one (0.6%) respondent. Near half of the career classes share the same value with each other which are agriculture, food and natural resources with law (2.4%), architecture and construction with public transport drivers (4.7%), hospitality and tourism with manufacturing (1.2%), and human services with transportation, distribution and logistics (1.8%). Most of the respondents, 61.2% (n=104) were degree holders. Meanwhile, 21.2% (n=36) were diploma holder. The third highest level of education was others category followed by master, 8.2% and 4.7% respectively.
Foundation was the lowest level of education among the respondents (3.5%). Near half of the respondents, 35.9%n(n=61) had less than RM1000 income per month followed by 45 (26.5%) of respondents in the category of RM1001 to RM2000 monthly income. Other category of monthly income are RM2001-RM3000 (26), RM3001-RM4000 (13), RM4001-RM5000 (11),RM5001-RM6000 (5), and more than RM6000 (9). The respondent who drive for recreation show the least, 19.4% (n=33).
Meanwhile, near half of the respondents perform driving for education and work, 43.5% and 44.1% respectively. Most of the respondents, 82.4% (n=140) had D driving class license. The frequency for individual holding B, B2 and other driving license class were as follows: (11, 75, and 8) respectively. Another demographic data being surveyed among respondents is RTA offenses. Surprisingly, most of the respondents 61.2% (n=104) perform speeding. The second highest RTA offenses was against red light followed by use mobile phone, 51.8% and 47.1% respectively.
The other common RTA offenses were, do not use safety belt (75), carelessness (49),overtaking queue (29), overtake on double line (37), signaling (18), use emergency lane (16), no respect to other drivers (13) and does not wear helmet (31). Year of driving experiences were divided into 5 groups which are less than three years, three to five years, six to eight years, nine to eleven years and 12 years and above category. Near half of the respondents, 41.2% (n=70) were in three to 5 years of driving experience category followed by 24.7% (n=42) were in less than three years of driving experiences. The lowest total frequency of respondents for year of driving experiences category is 8 which nine to eleven years of driving distance category. Another category of driving experience were six to eight years (14.1%) and 12 years and above of experience (8.8%).
With regards to annual driving distance category, more than one-fourth, 64 (37.6%) travel less than 5 000km in the period of one year. Approximately, one-fourth of the respondents, 44 (25.9) travel around three to five years in the period of one year. The third highest percentage of annual driving distance was 15 001km to 30 000km followed by 30 001km to 59 999km, 18.2% and 8.2% respectively. Whereas, 60 000km and above annual driving distance is the lowest in percentage (10%). .
4.2.ASDS-46 Domain Score Based on reliability test, ASDS-46 is a high reliability instruments with the Cronbach’s Alpha value of 0.839 for 46 items (Masuri et al., 2016). The Table 2 below shows the total score of ASDS-46 domains which comprise the mean, median, mode, standard deviation, minimum, maximum and sum. The mean score for each domain of all six domain was as follows (47.7, 46.9, 22.5, 22.4, and 12.5) respectively. Meanwhile, the mode score for each domain was as follows (54.0, 44.0, 24.0, 25.0, 12.0, and 16.0) respectively. The minimum and maximum raw score for each domain of ASDS-46 were as follows: (D1: 13-65, D2: 21-60, D3: 7-30, D4: 15-25, D5: 5-20, D6: 7-20).
Later, transform score will be converted from those total raw score from each domain. These transform score consist of two level i) high risk ii) low risk. Table 2:ASDS-46 score for six domains ASDS D1 D2 D3 D4 D5 D6 Mean Median Mode Std. Deviation Minimum Maximum Sum 47.67 48.00 54.00 10.18 13.00 65.00 8104.00 46.88 47.00 44.00 6.32 21.00 60.00 7969.00 22.56 22.00 24.00 4.05 7.00 30.00 3818.00 22.44 23.00 25.00 2.47 15.00 25.00 3814.00 12.46 12.00 12.00 2.93 5.00 20.00 2118.00 13.79 14.00 16.00 2.53 7.00 20.00 2345.00 (D1: self-compliant, D2: self-confidence, D3: self-benefit, D4:self-concern, D5: driving style, D6: self-preparedness) Table 3 below shows the frequency and percentage of the respondents whose with low risk and high risk towards RTA for each domain in ASDS-46. For D1, there were 81 respondents (47.6%) had high risk towards RTA. Meanwhile, there were 89 respondents (52.4%) had low risk towards RTA.
Next, the frequency and percentage of respondents with high and low risk for D2 were as follows: (78 and 45.9) followed by (45.9% and 54.1%) respectively. Surprisingly, more than half of the respondents 54.1% (n=92) and 51.2% (n=87) fall into high risk level towards RTA in D3 and D5 respectvely. Meanwhile, only 78 respondents (45.9%) for D3 followed by 83 respondents (48.8%) fall into low risk level towards RTA. D4 and D6 share the same percentage of respondents in high and low risk levels towards RTA, 44.1% and 55.9% respectively. Table 3: risk level of ASDS-46 ASDS-46 Domain Frequency Percentage D1 D2 D3 D4 D5 D6 High risk 81 47.6 Low risk 89 52.4 High Risk 78 45.9 Low risk 92 54.1 High risk 92 54.1 Low risk 78 45.9 High risk 75 44.1 Low risk 95 55.9 High risk 87 51.2 Low risk 83 48.8 High risk 75 44.1 Low risk 95 55.9 4.3.Association Between Year of Driving Experience and Attitude Towards Safe Driving using ASDS-46 One way ANOVA was conducted to analyse the association between year of driving experiences and attitude towards safe driving in less than three years, three to five years, six to eight years, nine to eleven years and 12 years and above category. Table 4 below present the calculation to test the null hypothesis of the population means are equal.
Table 4: Association between year of driving experience and ASDS-46 domains ASDS Domain D1 D2 D3 D4 D5 D6 Year of driving experiences Sig. df between groups df within groups F ratio 0.38 4 165 1.06 0.01 4 165 3.85 0.38 4 165 1.06 0.44 4 165 0.95 0.06 4 165 2.27 0.68 4 165 0.58 According to table 4, one of the domain in ASDS which is D2 is significantly associated with year of driving experiences. The significant association is tagged in bold. The analysis of variance showed that the effect of year of driving experiences on D2 was significant at the p0.05 level were as follows F(4, 165) = 1.06, p = 0.38, F(4, 165) = 1.06, p = 0.38, F(4, 165) = 0.95, p = 0.44, F(4, 165) = 2.27, p = 0.06 and F(4, 165) = 0.58, p = 0.68 respectively.
Table 5: Mean and standard deviation value for year of driving experiences in D2 D2 Year of driving experiences Mean Std. Deviation < 3 years 3-5 years 6-8 years 9-11 years 12 years and above 45.12 46.09 48.54 46.38 50.46 7.28 5.87 4.83 2.00 6.49 Table 6: Significance or p value of year of driving experiences Year of driving experiences (sig.) < 3 years 3-5 years 6-8 years 9-11 years 12 years and above 0.05 level were as follows F(4, 165) = 0.60, p = 0.66, F(4, 165) = 1.63, p = 0.17, F(4, 165) = 1.79, p = 0.13, F(4, 165) = 0.71, p = 0.58, F(4, 165) = 1.18, p = 0.32 and F(4, 165) = 0.91, p = 0.46 respectively. As there was no significant difference of annual driving distance on all domain in ASDS-46, post hoc test is not necessary to be done. 4.5.Association Between Year of Driving Experience and Risk Level of Offenses Chi-square test had been used to analyse the association between year of driving experience and risk level of offenses. Table 8 below present the calculation to test whether year of driving experiences and risk level of offenses in domain of ASDS-46 are independent of one another. Table 8: Association between year of driving experience and risk level of offenses ASDS Domain D1 risk D2 risk D3 risk D4 risk D5 risk D6 risk Year of driving experiences Asymptotic significance df Chi-square value 0.63 4 2.58 0.21 4 5.90 0.25 4 5.40 0.18 4 6.23 0.01 4 12.84 0.36 4 4.33 Table 9: percentage of risk level of offenses within year of driving experiences of D5 Percentage within year of driving experiences (%) Year of driving experiences < 3 years High risk 50.00 Low risk 50.00 3-5 years High risk 55.70 Low risk 44.30 6-8 years High risk 45.80 Low risk 54.20 9-11 years High risk 100.00 Low risk 0.00 12 years and above High risk 30.80 Low risk 69.20 According to table 8, one of the risk level of offenses in domain of ASDS-46 is significantly associated with year of driving experiences.
The significant correlation are tagged in bold. The Chi-square test shows that significant interaction was found between years of driving experience and risk level of D5 of ASDS-46 domain X² (4, N = 170) = 12.84, p =0.01. Based on table 9, individual in nine to eleven years of driving experiences category had highest risk of offenses in D5 (100%). Meanwhile, category of three to five years of experiences had lowest risk of offenses in D5 (44.3%).
4.6.Inferential Statistics For this study, the data had been transforms to normalize the data. According to Kwak and Kim (2017), the central limit theorem stipulate if the sample size is large which exceeds 30. Hence, the data were considered as normally distributed as the sample collected through random sampling and probability distribution may use normal distribution. Then the parametric test was carried out to identify the association between year of driving experiences and annual driving distance with attitude towards safe driving by using one way ANOVA. CHAPTER V DISCUSSION 5.1.RTA Offenses and Risk Level of ASDS-46 RTA offenses which had been analyse in this study includes speeding, against red light , do not use safety belt or signaling, use mobile phone or emergency lane, carelessness, overtaking queue, overtake on double line, no respect to other drivers and not wear helmet for motorcycle user.
There are a lot of factors which may lead to an accident that may cause injury and fatality such as using mobile phone, not wearing safety belt and speeding (Masuri, Dahlan, Danis and Md Isa, 2016). Surprisingly, most of the drivers perform speeding while driving with the total number of respondents is 104. Speeding or higher speed lead drivers to have less time to identify and respond to what is happening and may takes longer time to stop the vehicle. Excessive speeding among drivers tend to turns near misses into crashes.
In addition to this condition, the injury of that individual and other users resulting from the crashes will be more severe compared to normal speed crash. (The Royal Society for the Prevention of Accidents (ROSPA), 2018) The second highest offenses among the respondents is against red light with the percentage of 51.8% out of 170 respondents followed by use mobile phone during driving with the total number of respondents is 80. According to Rolison, Regev, Moutari & Feeney (2018), various type of driver distraction may elevate the risk of a crash or near misses. One of the type of driver distraction is mobile phone use during driving. Besides, risk taking such as overtaking queue, overtake on double line, signaling and does not wear helmet also viewed as contributing factors in RTA with the percentage of yes answer in this study was 17.1%, 21.8%, 10.6% and 18.2% respectively. Hence, based on the result, we can conclude that the attitude of driving gave high impact on the involvement in RTA.
5.2.Year of Driving Experience and ASDS-46 For this study, year of driving experiences had been divided into 5 category which are less than three years, three to five years, six to eight years, nine to eleven years and 12 years and above. ASDS-46 also been used in this study to determine attitude towards safe driving among the drivers. This instruments consists of 46 question and comprise of 6 domain of driving attitude. Domain 1 is for self-compliant, D2 for self-confidence, D3 for self-benefit, D4 for self-concern, D5 for driving style and D6 for self-preparedness. Based on the findings of this study, there was significant association between year of driving experience with D2 which denote self confidence towards RTA offenses. The analysis of variance showed that the effect of year of driving experiences on D2 was significant with the p value of 0.05 which means that year of driving experiences gave contribution to self confidence towards RTA.
Post hoc comparisons using the Scheffe test denote that the mean score for the less than three years of driving experience category (M = 45.12, SD = 7.28) was significantly different than the 12 years and above category (M = 50.46, SD = 6.49). The mean score for the three to 5 years of driving experience category (M = 46.09, SD = 5.87) was also shows significant different than the 12 years and above category (M = 50.46, SD = 6.49). This will increase the tendency of a driver to involve in accidents for the category of 12 years and above as they had higher self confidence in RTA offenses. The finding is coincide with a study done by Lancaster & Ward(2002) that report that an individual with higher level of driving confidence tend to commit driving violations.
Another study also revealed that increasing in occupational driving experience had positive association with the levels of traffic safety (Li & Itoh, 2013). With regards of self driving confidence, De Craen, Twisk, Hagenzieker, Elffers and Brookhuis (2011), reported that overconfident drivers shows more violating behaviour than the insecure drivers and the drivers who is well calibrated of their confident level and driving kills. Furthermore, drivers who are overconfident also showed inadequate adaptation to traffic complexity and task demand. Recent study done by McKenna (2018) among new driver also revealed that as driving confidence is increased over time, the tendency to violate become increase. Whereas, there was high avoidance of challenging driving tasks which easily avoided among the driver with self-reported low driving confidence (Gwyther & Holland, 2012).
However,increases in risk taking behaviour such as speeding risk attitudes among novice driver for male and female did not necessarily resulting from increases in driver self-confidence (Park, Allen & Rosenthal, 2015). Hence,this study had affirmed the findings of this study as higher experienced driver with high driving self confidence had more tendency in performing offenses than novice driver who had approximately same confident level. 5.3.Year of driving experience and risk level of ASDS-46 Based on the findings of this study, there were significant association between year of driving experience with D5 which denote attitude of having barrier to change driving style. According to the findings, individual in nine to eleven years of driving experiences category had highest risk of offenses in D5.
Meanwhile, category of three to five years of experiences had lowest risk of offenses in D5. 5.4.Annual driving distance and ASDS-46 Based on the findings in this study, there were no significant association between annual driving distance and all of the 6 domain of ASDS-46. This explains that annual driving distance does not influence the attitude towards safe driving. There were lack of investigation conducted on driving distance or mileage and attitude locally and globally. However, many research done on distance and RTA or near miss accident.
One of the research regarding this issue was done by Tseng (2012) in Taiwan proved that too little or too much annual driving distance reflects bad safety performance and higher at fault accident risk. The result of that study is coincide with a study done by Keall & Frith, (2006), which prove that low and high kilometre driving patterns shows identical risk of RTA. However, there result of a study done by Masuri, Isa and Tahir (2012) was contrary with that research, When the users decrease their time or exposure on the road, the potential of being involved in accidents is reduces. Next, Nik Mahdi et. al (2014) also reported that near miss incident were relatively high among long distance driver in Malaysia.
But the study was only among the bus drivers. Meanwhile, a study done by Kalyoncuoglu and Tigdemir (2014) revealed that low mileages represent the most risky environments for any drivers regardless of age. A large number of km associated with a minimal exposure to RTA. Regarding the findings of this study, it might be the attitude of driving among Malaysian is truly not associated with annual driving distance. Furthermore, this issue might be because of the small sample size in this study. Hence, further research should be done with a larger sample size and same amount of sample in each category of annual driving distance in order to get better validation of the result.
CHAPTER VI CONCLUSION 6.1.Conclusion As the conclusion, year of driving experiences may influence the attitude towards safe driving among the drivers. Longer period of driving experiences lead the drivers to have high self confident towards RTA offenses. Meanwhile, the middle category of year of experiences shows association with the attitudes of an individual driving style. This category shows high risk of attitude of having barrier to change their driving style. However, this condition will not be a obstruction for an individual with more driving experiences and middle category of experiences to be allowed to perform driving. But, the individual with this range of experiences must be aware of the risk as the prevention from traffic accidents and maintaining good attitude towards safe driving.
6.2.Limitation of the study There are several limitations identified from this study. The respondents claim that ASDS-46 is a long survey questionnaires and had repetition in question. Some of the respondents have limited time to complete the questionnaire. Besides, some of the respondents just completing the questionnaire without reading the question properly.
Hence, the questionnaires should be converted into a shorter form. Next, the respondents from online medium might not understand a few question from the questionnaire and simply answer the question without comprehending them. 6.3.Recommendation In order to enhance the attitude of safe driving, several step and effort should be taken. Collaboration between Occupational Therapist and Authorities in designing appropriate intervention and strategies will bring good driving practice among Malaysian. These can be done by implementation of PreSiM Model proposed by Masuri, Dahlan, Danis & Isa (2015) regarding the licensing process. This proposed model still keeping the current licensing process, yet initiate three elements of control known as prevention and screening, rehabilitation and maintenance.
Driver who are in high risk driver category such as driver with the driving experience of 12 years and above should go through rehabilitation program. The rehabilitation program comprise several components which are driving rehabilitation program, support group, psychological support, and module or exam based assessment. Meanwhile, good or competence driver were expected to self-reevaluate their driving performance at re-evaluation stage or maintenance stage in PreSiM Model. Occupational Therapist and authorities also should play an active role in managing this issue by instilling and educating Malaysian on attitude towards safe driving. One of the effort is by organizing program focusing on attitude changes and risk taking behaviour.
Next, Occupational Therapist also may use the result of this study and another study regarding the driving attitude in the implementation of intervention. They may use the findings to explore the attitude of driving among the clients and patients during driving stimulation. This will help them to determine whether the clients and patients are qualified to perform driving or require another intervention in order to have safe driving attitude. Not only Occupational Therapist, commercial transportation company also may use the findings of this study and another study regarding driving attitude to improve their quality of services. This can be done by developing near miss management system. 6.4.Recommendation for future research For further depth, the gender and type of transportation used by the respondents may be used to identify which group had higher self confidence towards RTA among the drivers in the 12 years and above category of driving experiences.
Next, online medium is not encourage to be used in order to gain the data as the respondents unable to understand the question clearly. A shorter version of questionnaire should be used in further study to get more valid answer from respondents. Furthermore, the respondent of further study should be distributed evenly between category of driving experiences and annual driving distance.