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Community participation and behavioral changes of helmet use in Thailand
Transport Policy 25 (2013) 111–118
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Transport Policy journal homepage: www.elsevier.com/locate/tranpol
Community participation and behavioral changes of helmet use in Thailand Vatanavongs Ratanavaraha a,n, Sajjakaj Jomnonkwao b a
School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, 111 University Avenue, Suranaree Sub-district, Muang District, Nakhonn Ratchasima 30000, Thailand Department of Logistics Engineering, Faculty of Industrial Technology, Pibulsongkram Rajabhat University, 156 Singhawat Avenue, Playchumphol Sub-district, Muang District, Phitsanulok 65000, Thailand b
a r t i c l e i n f o
abstract
Available online 20 December 2012
The loss of life and property from motorcycle accidents is a significant public issue in countries with a high dependency on motorcycles. This includes Thailand, where the damage from motorcycle accidents has been increasing yearly. Helmets are one of the most effective pieces of equipment in reducing the severity of injuries in each crash. An increase in helmet use amongst motorcycle riders would therefore reduce the loss of life. With this in mind, Thailand has adopted a wide-scale enforcement of laws regarding helmet use, but there are limits to how widely enforcement can work. Community participation is considered key in increasing the rate of helmet usage. In this, people in the community become the driving force behind mechanisms of community safety through community participation, including public information, public consultation, public meetings, and participative decision-making. This study aims to capture the concept of community participation as a means of increasing the rate of helmet use, and to identify economic, social, and environmental factors that affect the helmet usage of people at the local level, including gender, age, location, number of road lanes, time of day, day of the week, and traffic conditions. As a result of this community participation project in the study area, this survey has found an increase of 13.23% in the rates of helmet usage. & 2012 Elsevier Ltd. All rights reserved.
Keywords: Helmet use Motorcyclists Road safety Community participation Logistic regression analysis
1. Introduction 1.1. Background Motorcycles are a popular mode of transport, particularly in most developing Asian countries (Zamani-Alavijeh et al., 2011). Their popularity in Thailand, for instance, seems to increase every year, according to the statistics of newly registered vehicles since 2004, after the nation started to recover from economic recession. Even though the increase in newly registered vehicles dropped slightly during 2007–2009, it continued to increase again in 2010. As well, the number of motorcycle license holders has remarkably shown a greater yearly trends from 2004 to 2007 with the growth rate of 86% in 2007 compared to 2004 as illustrated in Fig. 1. By this year, the total number of registered motorcycles had reached 17.2 million (accounting for approximately 60% of the total cumulative number of registered vehicles). This can be calculated as a motorcycle occupancy to population ratio of 4:1 (Department of Land Transport, 2010; Thailand Road Safety Observatory, 2011b). In parallel with the popular use of motorcycles, some motorcycle accidents are unavoidable because they
n
Corresponding author. Tel.: þ66 0 4422 4238; fax: þ66 0 4422 4608. E-mail addresses: [email protected] (V. Ratanavaraha), [email protected] (S. Jomnonkwao). 0967-070X/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tranpol.2012.11.002
pose a greater risk at having crashes than those vehicles. According to the road accident statistics in 2009, a total of 84,806 accidents were recorded, with the largest number of motorcycle crashes at 37%. In considering personal damages from motorcycle riding, it was identified as 28% of a total of 10,717 fatal crashes, and 77% of a total of 113,048 serious injuries (Office of the Royal Thai Police, 2011; Thailand Road Safety Observatory, 2011a). According to the statistics, if motorcycle riders wear a helmet, the number of deaths and injuries may be decreased because helmets can reduce fatality rates and the severity of injuries (Coben et al., 2007; Keng, 2005; Mayrose, 2008). It was found by a case study in Thailand that helmet wearing can reduce headinjury deaths by 38% for drivers and 58% for passengers (Tanaboriboon et al., 2008). However, helmet use in Thailand is a very concerning issue: there are low rates of helmet-wearing, and statistics show no increase in helmet-wearing during 2003–2009. A 2010 survey of helmet use conducted in 30 sample provinces of Thailand found that the average helmet-wearing rates were 52% and 16% among drivers and passengers, respectively (Thailand Road Safety Observatory, 2011b). To solve the problem of motorcyclists not using helmets, many countries have adopted laws to make helmet-wearing compulsary. This includes Thailand, where helmet-wearing for passengers and drivers has been obligatory since 1992. Based on previous studies, cities that either had no helmet laws or with laws that were not rigorously enforced were found to lower rates
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Number of new motorcycle register 35
120
30
100
25
80
20
60
15
40
10
20
5
Number of new motorcycle register (per 1000population)
Number of motorcycle drivers licenses (per 1000population)
Number of motorcycle drivers licenses 140
0
0
2002
2003
2004
2005
2006
2007
2008
Years Fig. 1. Motorcycle drivers licenses and new motorcycle registration statistics during 2002–2010. Source: Department of Land Transportation.
of helmet-wearing than those with vigorously-enforced laws, and higher serious injury and death rates from accidents (Houston and Richardson, 2008; Mayrose, 2008). Nevertheless, rigorous law enforcement has some limitations, especially in developing countries: because if law enforcement officers are too restrictive, the community is likely to react against them. Therefore, the provision of safety education, making people realize the benefits of helmets, is one of the most effective approaches to increasing the ˚ rates of helmet wearing (Nja˚ and Nesvag, 2007; Oginni et al., 2007; Ranney et al., 2010). In this way, safety awareness can be accepted in a community by word of mouth. The objective of this research is to apply the approach of community participation in increasing the rates of helmet-wearing, using knowledge provision, participation in safety policy decision-making, and discussing factors affecting the helmet use of people in the study area.
1.2. The concept of community participation Community participation is defined as a process enabling people to involve in planning and implementation of development with collaborative thinking and decision-making on their problems. It involves the use of mutually creative generation and knowledge and skill alongside appropriate guiders as well as monitoring organization and related staff’s implementation thus resulting in increasing level of living and rehabilitating community problems (Lisk, 1986; Williams, 1976; Wisner and Adams, 2002). This concept will be reached by participation procedures including public information, public consultation, public meeting and decision making. The four-stage community participation process can be described as:
Cooperative finding problems, causes, and acceptable solutions. Mutual decision-making in selecting approaches and problemsolving plans.
Collaborative implementation following planning activities. Cooperative evaluation of activities/projects (Boonyatikarn et al., 1996). The characteristics of the community participation continuum can encourage empowerment (Rifkin and Pridmore, 2001). It is clear that the ‘participation’ approach can be applied in several ways, including EIA (O’Faircheallaigh, 2010) and public health, where community participation denoted as the importance of basic healthcare for the community (Draper et al., 2010).
In this case, the community participation project at hand was the campaign for ‘sustainable helmet wearing’. People, including young people, in key community areas were encouraged to participate in determining joint targets for future implementation. In order to do this, a knowledge-sharing forum was arranged, which provided feedback about the campaign to different community areas. The role of this study is to monitor and evaluate this project’s performance. 1.3. Hypothesis This research attempts to evaluate the rates of helmet-wearing amongst motorcycle riders and passengers, in the context of a community participation approach being applied. This is based on the underlying hypothesis that knowledge provision, awarenessbuilding, and cooperative approaches and actions by a community may create positive attitudes toward helmet use, and eventually influence helmet-wearing behavior. Therefore, to prove this hypothesis, the rates of helmet use should increase with statistical significance over the course of the study. With the process of safety awareness building, the statistical model (binary logistic regression) is applied by the study to analyze into finding the target groups.
2. Methods 2.1. Study sample In this study, purposive sampling was applied. Three districts or Amphur of Nakhonpathom Province were selected as the study areas based on size, categorized into three sizes, including a large district, Amphur Muang Nakhonpathom, a medium district, Amphur Sam Pran, and a small district, Amphur Don Tum. The study team included researchers and operation teams, including the village leaders and youth groups in the study area, as key parties, to drive and encourage participation in collaborative meetings, training, and collecting data. Also, the study gathered quantitative data through statistical record forms and questionnaires, surveying opinions in the three sample districts, in which sub-districts (Tambon) were chosen by simple random sampling (Amphur Muang Nakhonpathom i.e., Tambon Map Khae and Tambon Pra Pathom Chedi; Amphur Sam Pran i.e., Tambon Kratum Lom and Tambon Rai King; Amphur Don Tum i.e., Tambon Sam Ngam and Tambon Huai Phra). 2.2. Research procedure According to Fig. 2, after completing study area selection, the investigation of helmet-wearing situation was carried out in the target areas through roadside survey. In the next step, set of data was analyzed in statistical format to identify a proportion of helmetwearing and develop binary logistic regression model with the aim of finding factors that might influence helmet-wearing of people in study area. Subsequently, obtained results were applied for planning and implementing community participation process. One year after the process, evaluation was conducted by surveying on whether the number of helmet users would increase. So, its measurement involves the examination of statistically significant changes on helmet usage based on Z-test. Finally, overall performance was concluded and then involved policies were properly suggested. 2.3. Survey design The statistical survey was divided into two stages of observation for the purposes of data collection: first, investigating existing conditions to study helmet-wearing behavior, which is
V. Ratanavaraha, S. Jomnonkwao / Transport Policy 25 (2013) 111–118
Investigating the proportion of current rates of helmet-users and finding factors affecting helmet use behaviors
113
Roadside Survey
- Calculation of proportion of helmet users by descriptive statistic - Analysis of influential factors through developing binary logistics model
Analyzing survey data
- Identification of procedures - Identification of stakeholders - Identification of primary and secondary target groups using data obtained by binary logistics model to support considerations in planning processes)
Communication participation planning
Communication participation process
Surveying the proportion of helmet use rates after one-year communication participation process
Roadside Survey
- Calculation of the proportion with descriptive statistic - Examination of statistically significant changes with Z-test
Analyzing survey results
Providing conclusions, evaluation and policy identification Fig. 2. Methodological framework.
compulsory under law but not enforced, and using this data to identify target groups (those less likely to use helmets) to participate; second, evaluating the performance after the participation process completed together with helmet-wearing behaviors (both motorcycle drivers and passengers), gender and age. The survey data includes a study of helmet-wearing behavior for drivers and passengers, related to gender and age. In terms of timings and other variables, the survey was conducted by daytime and night-time, peak and off-peak hours, weekends and weekdays, including both sections and intersections, and all road sizes (2, 4, and 8 lanes).
each variable group according to ‘Odd Ratio’ as is frequently cited (Fuentes et al., 2010; Hung et al., 2008; Keng, 2005; Lajunen and R¨as¨anen, 2001; Li et al., 2008; Orsi et al., 2011; Tanaboriboon, et al., 2008; Xuequn et al., 2011). The ‘Odd Ratio’ was applied for seeking target groups for the participation process. Next, the performance evaluation was carried out by using the Z-test; likewise all statistical tests were done by the SPSS program.
3. Results 3.1. Roadside survey
2.4. Data analysis After surveying, data were statistically analyzed by average, percentage, and chi-square tests. Also, a model was formulated, designed to forecast helmet use by applying binary logistic regression to find a ‘coefficient affecting helmet-wearing’, predict helmetwearing patterns, and to compare the ratio of helmet-wearing in
Through a roadside survey examining helmet-wearing behavior, 5878 samples were obtained, classified into 3874 drivers (65.9%) and 2004 passengers (34.1%). The survey results are illustrated in Table 1: p-value based on Chi-Square technique is calculated to test the ratio of helmet-wearing variables (null hypothesis: the ratio of people with/or without helmet use is equal in each category).
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Table 1 The proportion of helmet-wearing by drivers and passengers (before project). Drivers
Gender Male Female Age group Child Adolescences Adults Location Segment Intersection Number of lane 2 4 8 Day of week Weekend Weekday Time of day Day Night Traffic time Peak Off-peak Total n
Passengers
Helmet-wearing (%)
Total
Yes
N
No
p-value % 0.001
41.69 35.94
58.31 64.06
2672 1202
68.97 31.03
14.29 31.56 47.26
85.71 68.44 52.74
49 1711 2114
1.26 44.17 54.57
38.62 41.18
61.38 58.82
1924 1950
49.66 50.34
40.47 22.00 50.00
59.53 78.00 50.00
2634 500 740
67.99 12.91 19.10
39.48 40.33
60.52 59.67
1925 1949
49.69 50.31
43.22 33.10
56.78 66.90
2605 1269
67.24 32.76
44.13 37.72 39.31
55.87 62.28 60.09
1321 2553 3874
34.10 65.90
Helmet-wearing (%)
Total
p-value
Yes
No
N
%
19.11 13.19
80.89 86.81
654 1350
32.63 67.37
8.29 14.42 20.68
91.71 85.58 79.32
398 992 614
19.86 49.50 30.64
14.23 15.99
85.77 84.01
991 1013
49.45 50.55
10.25 3.57 34.04
89.75 96.43 65.96
1307 224 473
65.22 11.18 23.60
14.79 15.47
85.21 84.53
1028 976
51.30 48.70
15.11 15.13
84.89 84.87
1310 694
65.37 34.63
16.35 14.49 15.12
83.65 85.51 84.88
679 1325 2004
33.88 66.12
nn
0.001nn
o0.001nn
o 0.001nn
0.103
0.27
o 0.001nn
o0.001nn
0.59
0.669
o0.001nn
0.993
o0.001nn
0.272
Statistically significant at 5%. nn
Statistically significant at 1%.
Regarding each factor with a 95% confidence level, the study found that, for drivers, two factors including location and day of the week are not significant. For passengers, three factors including gender, age group, and number of lane are found to be significant predictors of helmet usage. To consider the ratio of helmet-wearing behavior according to each variable, the findings can be described as follows; Gender: based on this survey of drivers (males 68.97%, females 31.03%) and passengers (males 32.63%, females 67.37%), the study found that, according to the helmet-wearing behaviors of drivers and passengers, males have a greater proportion of helmet use than females do: 41.69% of male drivers and 19.11% of male passengers wore helmets, whereas only 35.94% of female drivers and 13.19% of female passengers wore helmets. Regarding the results from Chi-square difference testing at 0.05 significance level, the study found the differences of helmet use behaviors between males and females in both driver group (p¼0.001) and passenger group (p¼0.001). Age: drivers can be split by age as follows: children (less than 13 years) 1.26%, adolescents (13–18 years) 44.17%, adults (more than 18 years) 54.57%; passengers can be split as follows: children 19.86%, adolescents 49.50%, and adults 30.64. Amongst both drivers and passengers adults have the highest rates of helmet use (47.26% for drivers and 20.68% for passengers), following by adolescences (31.56% for drivers and 14.42% for passengers), with children having the lowest helmet-wearing rates (14.29% for drivers and 8.29% for passengers). According to Chi-square test, the study showed age factor significantly affects helmet use behaviors of a sample group in both drivers (po0.001) and passengers (po0.001), thus it means that there are differences in helmetwearing behaviors between children, adolescent and adult groups. Location on the road: for drivers, 49.66% of survey samples were on road segments, and 50.34% at intersections. For passengers, 49.45% were on segments and 50.55% at intersections.
Helmet-usage was significantly greater at intersections than segments, at 41.18% for drivers and 15.99% for passengers at intersections, compared with 38.62% for drivers and 14.23% for passengers. Drivers and passengers followed the same pattern in this instance. Based on statistical test of differences, the results illustrated that wearing helmets does not depend on the road location and helmet uses at direct routes and intersections are not different for both drivers (p ¼0.103) and passengers (p ¼0.27). Number of lanes: 67.99% of the drivers were surveyed on 2lane roads, compared to 12.91% on 4 lanes and 19.10% on 8 lanes. For passengers, 65.22% were surveyed on 2-lane roads, 11.18% on 4-lane roads and 23.60% on 8-lane roads). Drivers and passengers had similar helmet-wearing behaviors here: 8-lane roads had the greatest proportions of helmet use (50.00% for drivers and 34.04% for passengers), following by 2-lane roads (40.47% for drivers and 10.25% for passengers). Four-lane roads indicated the smallest percentage (22.00% for drivers and 3.57% for passengers). From the study, number of lanes influence helmet use behaviors of a sample group and the results from Chi-square test indicated the differences of helmet use in groups of drivers (po0.001) and passengers (p o0.001) in 2-lane, 4-lane and 8-lane roads. Day of the week: of the drivers surveyed, 50.31% were driving on weekdays, and 49.69% at weekends. For passengers, this was 48.70% on weekdays and 51.30% at weekends. Again, drivers and passengers exhibited similar helmet-wearing behaviors. Helmetwearing was more prevalent on weekdays (40.33% for drivers and 15.47% for passengers) than weekends (39.48% for drivers and 14.79% for passengers). Regarding Chi-square test, day of week is not associated with the helmet use behavior of a sample group, therefore it could be referred that in weekend and weekday, behaviors of helmet-wearing between driver group (p ¼0.59) and passenger group (p ¼0.669) are similar. Time of day: 67.24% of drivers surveyed were in the day-time, compared to 32.76% at night. For passengers, 65.37% were
V. Ratanavaraha, S. Jomnonkwao / Transport Policy 25 (2013) 111–118
surveyed in the day and 34.63% at night. Interestingly, drivers are more likely to wear helmets during the day (43.22%, compared to night-time rates of 33.10%). In contrast, for passengers, rates of helmet-wearing by day or night are relatively similar at roughly 15%. According to the test, helmet use behaviors of a sample of drivers are significantly different between the day and the night (po0.001); while behaviors of passengers in using helmets do not rely on the time of day (p ¼0.993). Traffic conditions: drivers surveyed in peak hours accounted for 34.01%, compared to off-peak hours of 65.90%. For passengers, peak and off-peak hours accounted for 33.38% and 66.12% of those surveyed, respectively. The findings indicate similar helmetwearing patterns for drivers and passengers, and demonstrate that the helmet-wearing rates in peak hours (44.13% for drivers and 16.35% for passengers) are considerably higher than off-peak times (37.72% for drivers and 14.49% for passengers). The results of Chi-square test showed significant divergence in drivers’ helmet-wearing behaviors between peak and off-peak hours (po0.001); on the other hands, there is no difference in passengers’ behaviors in wearing helmets among both periods (p¼ 0.272).
3.2. Helmet use model Table 2 shows the results derived from the development of a helmet-use model using ‘Binary Logistic Regression’. Based on a survey of 5878 samples (3874 drivers and 2004 passengers) and a model coefficient, the findings found that gender and night-time factors affect not using helmets of drivers, indicated as negative values. When considering the odd ratio—defined as the proportion of helmet-wearing related to each variable, the results demonstrate that the ratio of 4-lane roads is 1.743 times larger than that of 2-lane roads; while the ratio of 8-lane roads remarkably shows 4.070 times more than 2-lane roads. Additionally, the odd ratios of females to males, adolescences to children, adults to children and night-time to day-time, equal 0.774, 4.557, 2.149, and 0.626. Table 2 Binary logistic regression model for helmet use (before project). Variable
Driver Coef.
Gender Male Female Age group Child Adolescences Adults Number of lane 2 4 8 Time Day Night Traffic time Peak Off-peak Constant
r2 2LL N n
0.256 0.001nn
3.3. The process of community participation in this study The process of community participation is adopted as a key mechanism for improving helmet-wearing rates in local areas. Based on this effort, implementation stages are identified in Table 3. In step 1, it involves the selection of people within community in collaborative surveying helmet-wearing rates in order to enable them to envisage the actual situations and create awareness for mutually problem solving. Such group would reflect the occurred issues to other people in the community such as family, relatives, friends, etc. This process provides individual information obtained by the community, so it brings the driving forces of cooperative problem solving that could be better than implementation of people outside community. After that, work team becomes involved in the meeting with the community leader to find solutions for helmet-wearing problems of community. The study proposes 2 campaign plans with attention to provide understanding of the benefits of helmet use and proper decisions of purchasing and wearing helmets to community as following:
‘No risk, no death, no embarrassment, just wear a helmet’,
Odd ratio
1.000 0.774
Coef.
p-value
0.435 0.002nn
Odd ratio
1.000 0.647
1.517 0.765
1.000 o 0.001nn 4.557 nn o 0.001 2.149
1.269 0.814
o0.001nn o0.001nn
0.556 1.404
1.000 o 0.001nn 1.743 o 0.001nn 4.070
2.015 2.960
1.000 o0.001nn 7.501 o0.001nn 19.292
0.468
1.000 o 0.001nn 0.626
0.711
o0.001nn
0.025 0.820 0.096 4927.52 3874
Statistically significant at 5%. nn
In case of passengers, no helmet use is influenced by gender, and night-time factors, indicated as negative values. When considering the odd ratio—defined as the proportion of helmetwearing related to each variable, the results demonstrate that the ratio of 4-lane roads is 7.501 times larger than that of 2-lane roads; while the ratio of 8-lane roads remarkably shows 19.292 times more than 2-lane roads. Additionally, the odd ratios of females to males, adolescences to children, adults to children, night-time to day-time, and off-peak times to peak times, equal 0.647, 3.557, 2.256, 0.491, and 2.442, respectively. According to the model results regarding individual factors (i.e., gender and age), the findings found that children have a smaller proportion of helmet-wearing than other age groups by 2–5 times for drivers and 2–4 times for passengers. Therefore, in the participation process, the priority needed to be given to children through the provision of safety education at school, and the activity of ‘community angels’. These can be the parts of the distribution and campaign in the importance of helmet use for adults in local areas.
Passenger p-value
Statistically significant at 1%.
6.164
0.892 o0.001nn 0.073 0.681 0.193 1467.92 2004
115
1.000 3.557 2.256
1.000 0.491 1.000 2.441 1.076
aims (1) to change the attitudes and behaviors of motorcycle riders, especially adolescents; (2) to make adolescents aware of the need for helmet use; and (3) to minimize the accident severity caused by motorcycle riding on roadways. It encompasses the use of media campaign such as mass media (radio broadcasting, local cable media), print media (poster, local newspaper), specialized media(fabric/ink poster, video documentary, internet), activity media(arranging helmet design competition for motorcyclists’ safety and/or helmeted-motorcycle riders parade activity around Nakhon Pathom Province for accident reduction and road safety campaign to make helmet use a higher priority). ‘Someone behind you as a thing in your life’, aims (1) to make local people conscious about the importance of helmet usage while driving themselves and their passengers; and (2) to reduce the rate of injuries and fatalities from motorcycle riding for both drivers and passengers. The project chiefly highlights the use of helmets by passengers through using activity media (giving 1000 free helmets for prototype school with gamesrelated helmet use safety knowledge and accident prevention, and the arrangement of art painting competition for children in the theme of ‘‘Happy Family by Protection of Helmets’’).
After this step, implementation following campaign plans was preceded through ‘community angle’ acted as the leader. This process has continually been conducted about a year since project
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Table 3 Implementation steps, participation approaches and procedures. Steps
Participation techniques
Procedures
1. Cooperative finding problems, causes, and acceptable solutions
Participative decision making
Team work involves the meeting with the head of community to select ‘community angle’ for surveying helmet-wearing rates
2. Mutual decision-making in selecting approaches and problem-solving plans
Public meeting Participative decision making
Team work joins the meeting with the community leader to find solutions for helmet use problems of community
3. Collaborative implementation following planning activities
Public information Work team in cooperation with community angle conduct campaigns for helmet-wearing following the plans
4. Cooperative evaluation of projects
Public meeting Participative decision making
Community angle carries out survey of helmet-wearing rates after one year of project’s implementation Work team joins the meeting with the community leader to evaluate implementation performance and issue policies to promote the sustainability of helmet use in community
started, and then cooperative evaluation was put in place by surveying the proportions of helmet users compared to results before starting a project. 3.4. Community participation evaluation After completing the community participation process, the performance evaluation was conducted. At this stage, the roadside survey technique was applied for examining the helmet-wearing behaviors of 1846 samples within the study area. Its results were compared with the previous survey before starting the participatory project implementation as illustrated in Table 4. Interestingly, the study found a greater proportion of helmet-wearing after the project (44.69%) than before (31.46%), indicating a change of 13.23%. Through estimating the differences in proportions of the two populations with z-test (null hypothesis: The proportion of people using helmets before and after the project is equal), the test shows p-value o0.001, and then rejects null hypothesis at the 95% confidence level. In considering each variable, it demonstrates an increased proportion of all factors with the range of 5.92–32.69%. Only the proportion of helmet wearing on ‘8 lane-roads’ appears to be decreased. This can be explained by the fact that 8-lane roads are large roads with rights-of-way through the local areas, so some populations using it were not included in the community project. Regarding the factor of age, the project prioritized children through the provision of school safety education. The study found a greater proportion of helmet-wearing among children after the project (15%) than before (8.95%), referred to as a 6.05% change rate. In addition, the project suggests that children discussed with their parents about the significance of helmet use, leading to better helmet use performance amongst both adolescences and adults (adolescences by 10.78%, adults by 17.33%). The comparison of helmet use rates between drivers and passengers of Tables 5 and 1 indicates the increase in helmet use rates of drivers of all variables, except for areas of 8-lane roads. When considering chi-square test results, it could be implied by the study that helmet usage seems likely to depend on gender, age, location, number of lane and the time of day. For passengers, the result found a larger proportion of helmetwearing in males, children, adults, intersection, 2-lane roads, 4lane roads, weekday, night time, and off-peak hours. Likewise, results of chi-square test demonstrated that the use of helmets is significantly relied on gender and age. Based on Table 6, factors influencing not using helmets after project implementation for drivers include femininity and night-time period; while only femininity factor affect not using helmets o passengers.
4. Discussion This study has applied the community participation approach for increasing the helmet-wearing rates of people in Thailand, selecting Nakhonpathom Province (one of the central provinces of Thailand) as its target area. Initially, as part of its effort to increase the rates of helmet-wearing rates, the mandatory approach has been used in Thailand for 19 years between 1992 and the present (2011). However, based on the survey of results of helmet-wearing behavior in 2010, the average rates of helmet usage on motorcycles among drivers and passengers was to 52 and 16, respectively (Thailand Road Safety Observatory, 2011b), which is a very low rate internationally. This low rate can be seen as a result of the limitations of law enforcement, especially from the police force. Moreover, in some cases, motorcyclists are acting as if they use helmets to avoid police arrest, but not to prevent harm: they put the helmets in the front baskets and wear them only if they suddenly see the police. This pattern is also seen in Vietnam. Based on this study, 2.1 of motorcyclists have helmets but do not use them (Hung et al., 2008). This phenomenon may result from negative attitudes to helmet use, such as the inconvenience of carrying a helmet, hearing loss, ventilation and vision problems, etc. (Orsi et al., 2011). Therefore, the application of the concept of community participation, through public information related to safe motorcycle riding and participation in safety activities, might be an approach to build better awareness of the benefits of helmet use as opposed to the disadvantages, as a means to achieving sustainable development. This study investigates the existing helmet-wearing behaviors of people in the target area. Based on the observation of 5878 samples overall, it found helmeted motorcycle drivers made up 39.31 of 3874 samples, and helmeted motorcycle passengers made up 15.12 of 2004 samples. This was lower than the national average both for drivers and passengers, and less than in other countries. For example, in China, helmeted motorcycle drivers accounted for 66 (2008) and 72.60 (2011), with rates of 29.50 (2008) and 34.10 (2011) for helmeted passengers (Li et al., 2008; Xuequn et al., 2011). Meanwhile, in Spain, 78.28 of drivers were helmeted, and 80.40 of passengers. Rates of motorcycle helmet usage were relatively high, particularly among adolescents (Fuentes et al., 2010). For the USA, the helmet-wearing rates for both drivers and passengers are similar at 57.40 (Mayrose, 2008). All of this said, the rates of helmet-wearing in Thailand are much higher than in Iran, where helmeted motorcycle drivers and passengers were found at 33.26 and 0.11, respectively (Zamani-Alavijeh et al., 2011). After the survey, the data was used for formulating the model of helmet use, which identified factors affecting not using helmets,
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Table 4 The comparison of proportion of helmet-wearing before and after the application of participation approach. Before
Gender Male Female Age group Child Adolescences Adults Location Segment Intersection Number of lane 2 4 8 Day Weekend Weekday Time Day Night Traffic time Peak Off-peak Total
After
Helmet-wearing (%)
Total
Yes
No
N
37.25 23.90
62.75 76.10
8.95 25.27 41.28
Different
% change
Helmet-wearing (%)
Total
%
Yes
No
N
%
3326 2552
56.58 43.42
55.72 29.82
44.28 70.18
1057 788
57.26 42.69
18.47 5.92
50 25
91.05 74.73 58.72
447 2703 2728
7.60 45.99 46.41
15.00 36.05 58.61
85.00 63.95 41.39
120 907 819
6.50 49.13 44.37
6.05 10.78 17.33
68 43 42
30.33 32.57
69.67 67.43
2915 2963
49.59 50.41
47.45 42.06
52.55 57.94
902 944
48.86 51.14
17.12 9.49
56 29
30.45 16.30 43.78
69.55 83.70 56.22
3941 724 1213
67.05 12.32 20.64
50.00 48.99 22.06
50.00 51.01 77.94
1210 296 340
65.55 16.03 18.42
19.55 32.69 21.72
64 201 50
30.88 32.03
69.12 67.97
2953 2925
50.24 49.76
44.39 45.33
55.61 54.67
1257 589
68.09 31.91
13.51 13.30
44 42
33.82 26.74
66.18 73.26
3915 1963
66.60 33.40
45.31 38.13
54.69 61.88
1686 160
91.33 8.67
11.50 11.38
34 43
34.70 29.78 31.46
65.30 70.22 68.54
2000 3878 5878
34.03 65.97
45.45 44.56 44.69
54.55 55.44 55.31
275 1571 1846
14.90 85.10
10.75 14.77 13.23
31 50 42
Table 5 The proportion of helmet-wearing by drivers and passengers (after project). Drivers
Gender Male Female Age group Child Adolescences Adults Location Segment Intersection Number of lane 2 4 8 Day of week Weekend Weekday Time of day Day Night Traffic time Peak Off-peak Total n
Passengers
Helmet-wearing (%)
Total
Yes
N
No
p value % o 0.001
64.27 51.58
35.73 48.42
848 349
70.78 29.16
28.57 52.64 68.19
71.43 47.36 31.81
14 549 635
1.17 45.83 53.01
64.44 56.76
35.56 43.24
599 599
50.00 50.00
67.54 65.00 28.50
32.46 35.00 71.50
798 200 200
66.61 16.69 16.69
61.45 58.90
38.55 41.10
799 399
66.69 33.31
61.57 50.00
38.43 50.00
1098 100
91.65 8.35
59.30 60.86 60.60
40.70 39.14 39.40
199 999 1,198
16.61 83.39
Helmet-wearing (%)
Total
p-value
Yes
No
N
%
21.05 12.53
78.95 87.47
209 439
32.25 67.75
13.21 10.61 25.54
86.79 89.39 74.46
106 358 184
16.36 55.25 28.40
13.86 16.52
86.14 83.48
303 345
46.76 53.24
16.02 15.63 12.86
83.98 84.38 87.14
412 96 140
63.58 14.81 21.60
14.63 16.84
85.37 83.16
458 190
70.68 29.32
14.97 18.33
85.03 81.67
588 60
90.74 9.26
9.21 16.08 15.28
90.79 83.92 84.72
76 572 648
11.73 88.27
nn
0.005nn
o 0.001nn
o 0.001nn
0.007nn
0.348
o 0.001nn
0.664
0.394
0.476
0.023nn
0.490
0.680
0.118
Statistically significant at 5%. nn
Statistically significant at 1%.
such as passenger position. One reason for this is that, in general, motorcycle owners will buy only one helmet for themselves, not for passengers, as they are trying to be economical. Another factor is the night-time, where drivers might perceive that helmet-wearing would be detrimental to their ability to see the road. Furthermore, police patrols and helmet enforcement are less likely in the
night-time than the day. The model applied the ‘odd ratio’ to find individual factors to seek the target groups for the community participation process. The outstanding factor was age group: the proportion of helmeted children was 2–5 times lower than that of adolescents and adults. It is likely that majority of motorcycle riders are ranged into low-medium income groups, so they cannot
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Acknowledgments
Table 6 Binary logistic regression model for helmet use (after project). Variable
Gender Male Female Age group Child Adolescences Adults Time Day Night Constant
r2 2LL N n
Driver
Passenger
Coef.
p-value
0.536
1.000 o 0.001nn 0.585
0.675 0.003nn
1.713 0.668
1.000 0.004nn 5.544 o 0.001nn 1.951
0.897 1.088
0.498 0.020nn 0.060 0.794 0.064 1548.658 1198
Odd ratio
Coef.
p-value
Odd ratio
1.000 0.509
1.000 0.008nn 2.451 o0.001nn 2.967
1.000 0.608 1.062 0.075 525.566 648
Statistically significant at 5%. nn
Statistically significant at 1%.
afford to buy additional helmets for children (Tanaboriboon et al., 2008). Based on the findings, the study focused on giving priority to children through the provision of information in terms of the importance of helmet-wearing in school areas, as well as promoting the ‘community angel’ scheme (which obtained the training program from the project) to create awareness among children, and then tell their parents to seek helmets for them. Nevertheless, the study did not ignore the other age groups, so the campaign plans, such as ‘No risk, no death, no embarrassment, just wearing a helmet’ and ‘Someone behind you as a thing in your life’ have also been carried out. The performance after the community participation process clearly illustrates the higher rates of helmeted motorcycles in the target area by an increase of 13.23.
5. Conclusion Community participation is a significant approach and has been effectively used in increasing the helmet-wearing rates in the community target areas. This endeavor has been achieved through encouraging both youths and adults in the target area to participate in providing information, indicating the importance and promotion of helmet use, and determining the mutual targets and future implementation through a sharing and learning forum. This enabled the study to feed back information to the community towards the campaign for sustainable helmet use. The study considers the statistical analysis of the helmet-wearing behaviors according to both external and demographical factors, and conducted the survey and the comparison of such behaviors before and after project implementation, in order to evaluate the helmet-wearing behaviors of motorcycle riders. Regarding community participation, success of increase in the proportion of helmet use within community must require the creation of awareness and safety knowledge for the village leaders. After they have more understanding of the importance of helmet use, the next step involves building networks through selection of adolescent groups to participate the preparation of safety plans as well as the provision of budget for continual campaign, in order to naturally change behaviors of motorcycle users in community to have more discipline. The outcomes noticeably demonstrated better helmet-wearing rates. Hence, putting community participation into vigorous practice through collaborative problem solving regarding safe driving may eventually be able to substantially increase the helmet-wearing rates up to 100.
The authors would like to thank Suranaree University of Technology (SUT) and National Health Foundation for the funding of this research project. In particular, we are grateful to Dr. Thanapong Jinvong, Director of Road Safety Thai Organization, National Health Foundation, and Dr. Chintawee Kasemsuk for their valuable advices, comments, and suggestions. We also thank the students and staff at SUT for their continual support in various aspects related to data collection, management, and analyses to complete the study. References Boonyatikarn, S., Boonkob, D., & Srisurin, R. (1996) ‘Management of Community Participation: A Case Study of Projects that Public Affect’, Bangkok, Thailand (in Thai). Coben, J.H., Steiner, C.A., Miller, T.R., 2007. Characteristics of motorcycle-related hospitalizations: comparing states with different helmet laws. Accident Analysis & Prevention 39 (1), 190–196. Department of Land Transport. (2010) ‘Transport Statistics’ Retrieved August 1, 2011, from /http://apps.dlt.go.th/statistics_web/statistics.htmlS (in Thai). Draper, A.K., Hewitt, G., Rifkin, S., 2010. Chasing the dragon: developing indicators for the assessment of community participation in health programmes. Social Science & Medicine 71 (6), 1102–1109. Fuentes, C., Euge nia Gras, M., Font-Mayolas, S., Bertran, C., Sullman, M.J.M., Ballester, D., 2010. Expectations of efficacy, social influence and age as predictors of helmet-use in a sample of Spanish adolescents. Transportation Research Part F: Traffic Psychology and Behaviour 13 (5), 289–296. Houston, D., Richardson, L., 2008. Motorcyclist fatality rates and mandatory helmet-use laws. Accident Analysis & Prevention 40 (1), 200–208. Hung, D., Stevenson, M., Ivers, R., 2008. Barriers to, and factors associated, with observed motorcycle helmet use in Vietnam. Accident Analysis & Prevention 40 (4), 1627–1633. Keng, S., 2005. Helmet use and motorcycle fatalities in Taiwan. Accident Analysis & Prevention 37 (2), 349–355. ¨ anen, ¨ Lajunen, T., Ras M., 2001. Why teenagers owning a bicycle helmet do not use their helmets. Journal of Safety Research 32 (3), 323–332. Li, L., Li, G., Cai, Q., Zhang, A., Lo, S., 2008. Improper motorcycle helmet use in provincial areas of a developing country. Accident Analysis & Prevention 40 (6), 1937–1942. Lisk, F., 1986. Popular Participation in Planning for Basic Needs: Concepts, Methods and Practices. Palgrave Macmillan. Mayrose, J., 2008. The effects of a mandatory motorcycle helmet law on helmet use and injury patterns among motorcyclist fatalities. Journal of Safety Research 39 (4), 429–432. ˚ O., Nesvag, ˚ S.M., 2007. Traffic behaviour among adolescents using mopeds and Nja, light motorcycles. Journal of Safety Research 38 (4), 481–492. O’Faircheallaigh, C., 2010. Public participation and environmental impact assessment: purposes, implications, and lessons for public policy making. Environmental Impact Assessment Review 30 (1), 19–27. Office of the Royal Thai Police. (2011) ‘Accident Statistics’ Retrieved August 1, 2011, from /http://statistic.police.go.th/traff_main.htmS (in Thai). Oginni, F.O., Ugboko, V.I., Adewole, R.A., 2007. Knowledge, attitude, and practice of Nigerian commercial motorcyclists in the use of crash helmet and other safety measures. Traffic Injury Prevention 8 (2), 137–141. Orsi, C., Stendardo, A., Marinoni, A., Gilchrist, M.D., Otte, D., Chliaoutakis, J., et al., 2011. Motorcycle riders’ perception of helmet use: complaints and dissatisfaction. Accident Analysis & Prevention. Ranney, M.L., Mello, M.J., Baird, J.B., Chai, P.R., Clark, M.A., 2010. Correlates of motorcycle helmet use among recent graduates of a motorcycle training course. Accident Analysis & Prevention 42 (6), 2057–2062. Rifkin, S.B., Pridmore, P., 2001. Partners in Planning. Information, Participation and Empowerment. Macmillan Education Ltd, London. Tanaboriboon, Y., Boontob, N., Kanitpong, K., 2008. Helmet use and effectiveness in reducing the severity of head injuries in Thailand. Transportation Research Record: Journal of the Transportation Research Board 2048 (1), 66–76. Thailand Road Safety Observatory, 2011a. Road Accident in Thailand Report 2009. National Health Foundation, Khonkaen, Thailand (in Thai). Thailand Road Safety Observatory, 2011b. Road accident situation in Thailand 2010. National Health Foundation, Bangkok Thailand (in Thai). Williams, E., 1976. Participative Management: Concepts, Theory and Implementation. State University Press, Atlanta: Georgia. Wisner, B., Adams, J., 2002. Environmental Health in Emergencies and Disasters: A Practical Guide. World Health Organization, Geneva. Xuequn, Y., Ke, L., Ivers, R., Du, W., Senserrick, T., 2011. Prevalence rates of helmet use among motorcycle riders in a developed region in China. Accident Analysis & Prevention 43 (1), 214–219. Zamani-Alavijeh, F., Bazargan, M., Shafiei, A., Bazargan-Hejazi, S., 2011. The frequency and predictors of helmet use among Iranian motorcyclists: a quantitative and qualitative study. Accident Analysis & Prevention 43 (4), 1562–1569.
Contents lists available at SciVerse ScienceDirect
Transport Policy journal homepage: www.elsevier.com/locate/tranpol
Community participation and behavioral changes of helmet use in Thailand Vatanavongs Ratanavaraha a,n, Sajjakaj Jomnonkwao b a
School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, 111 University Avenue, Suranaree Sub-district, Muang District, Nakhonn Ratchasima 30000, Thailand Department of Logistics Engineering, Faculty of Industrial Technology, Pibulsongkram Rajabhat University, 156 Singhawat Avenue, Playchumphol Sub-district, Muang District, Phitsanulok 65000, Thailand b
a r t i c l e i n f o
abstract
Available online 20 December 2012
The loss of life and property from motorcycle accidents is a significant public issue in countries with a high dependency on motorcycles. This includes Thailand, where the damage from motorcycle accidents has been increasing yearly. Helmets are one of the most effective pieces of equipment in reducing the severity of injuries in each crash. An increase in helmet use amongst motorcycle riders would therefore reduce the loss of life. With this in mind, Thailand has adopted a wide-scale enforcement of laws regarding helmet use, but there are limits to how widely enforcement can work. Community participation is considered key in increasing the rate of helmet usage. In this, people in the community become the driving force behind mechanisms of community safety through community participation, including public information, public consultation, public meetings, and participative decision-making. This study aims to capture the concept of community participation as a means of increasing the rate of helmet use, and to identify economic, social, and environmental factors that affect the helmet usage of people at the local level, including gender, age, location, number of road lanes, time of day, day of the week, and traffic conditions. As a result of this community participation project in the study area, this survey has found an increase of 13.23% in the rates of helmet usage. & 2012 Elsevier Ltd. All rights reserved.
Keywords: Helmet use Motorcyclists Road safety Community participation Logistic regression analysis
1. Introduction 1.1. Background Motorcycles are a popular mode of transport, particularly in most developing Asian countries (Zamani-Alavijeh et al., 2011). Their popularity in Thailand, for instance, seems to increase every year, according to the statistics of newly registered vehicles since 2004, after the nation started to recover from economic recession. Even though the increase in newly registered vehicles dropped slightly during 2007–2009, it continued to increase again in 2010. As well, the number of motorcycle license holders has remarkably shown a greater yearly trends from 2004 to 2007 with the growth rate of 86% in 2007 compared to 2004 as illustrated in Fig. 1. By this year, the total number of registered motorcycles had reached 17.2 million (accounting for approximately 60% of the total cumulative number of registered vehicles). This can be calculated as a motorcycle occupancy to population ratio of 4:1 (Department of Land Transport, 2010; Thailand Road Safety Observatory, 2011b). In parallel with the popular use of motorcycles, some motorcycle accidents are unavoidable because they
n
Corresponding author. Tel.: þ66 0 4422 4238; fax: þ66 0 4422 4608. E-mail addresses: [email protected] (V. Ratanavaraha), [email protected] (S. Jomnonkwao). 0967-070X/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tranpol.2012.11.002
pose a greater risk at having crashes than those vehicles. According to the road accident statistics in 2009, a total of 84,806 accidents were recorded, with the largest number of motorcycle crashes at 37%. In considering personal damages from motorcycle riding, it was identified as 28% of a total of 10,717 fatal crashes, and 77% of a total of 113,048 serious injuries (Office of the Royal Thai Police, 2011; Thailand Road Safety Observatory, 2011a). According to the statistics, if motorcycle riders wear a helmet, the number of deaths and injuries may be decreased because helmets can reduce fatality rates and the severity of injuries (Coben et al., 2007; Keng, 2005; Mayrose, 2008). It was found by a case study in Thailand that helmet wearing can reduce headinjury deaths by 38% for drivers and 58% for passengers (Tanaboriboon et al., 2008). However, helmet use in Thailand is a very concerning issue: there are low rates of helmet-wearing, and statistics show no increase in helmet-wearing during 2003–2009. A 2010 survey of helmet use conducted in 30 sample provinces of Thailand found that the average helmet-wearing rates were 52% and 16% among drivers and passengers, respectively (Thailand Road Safety Observatory, 2011b). To solve the problem of motorcyclists not using helmets, many countries have adopted laws to make helmet-wearing compulsary. This includes Thailand, where helmet-wearing for passengers and drivers has been obligatory since 1992. Based on previous studies, cities that either had no helmet laws or with laws that were not rigorously enforced were found to lower rates
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Number of new motorcycle register 35
120
30
100
25
80
20
60
15
40
10
20
5
Number of new motorcycle register (per 1000population)
Number of motorcycle drivers licenses (per 1000population)
Number of motorcycle drivers licenses 140
0
0
2002
2003
2004
2005
2006
2007
2008
Years Fig. 1. Motorcycle drivers licenses and new motorcycle registration statistics during 2002–2010. Source: Department of Land Transportation.
of helmet-wearing than those with vigorously-enforced laws, and higher serious injury and death rates from accidents (Houston and Richardson, 2008; Mayrose, 2008). Nevertheless, rigorous law enforcement has some limitations, especially in developing countries: because if law enforcement officers are too restrictive, the community is likely to react against them. Therefore, the provision of safety education, making people realize the benefits of helmets, is one of the most effective approaches to increasing the ˚ rates of helmet wearing (Nja˚ and Nesvag, 2007; Oginni et al., 2007; Ranney et al., 2010). In this way, safety awareness can be accepted in a community by word of mouth. The objective of this research is to apply the approach of community participation in increasing the rates of helmet-wearing, using knowledge provision, participation in safety policy decision-making, and discussing factors affecting the helmet use of people in the study area.
1.2. The concept of community participation Community participation is defined as a process enabling people to involve in planning and implementation of development with collaborative thinking and decision-making on their problems. It involves the use of mutually creative generation and knowledge and skill alongside appropriate guiders as well as monitoring organization and related staff’s implementation thus resulting in increasing level of living and rehabilitating community problems (Lisk, 1986; Williams, 1976; Wisner and Adams, 2002). This concept will be reached by participation procedures including public information, public consultation, public meeting and decision making. The four-stage community participation process can be described as:
Cooperative finding problems, causes, and acceptable solutions. Mutual decision-making in selecting approaches and problemsolving plans.
Collaborative implementation following planning activities. Cooperative evaluation of activities/projects (Boonyatikarn et al., 1996). The characteristics of the community participation continuum can encourage empowerment (Rifkin and Pridmore, 2001). It is clear that the ‘participation’ approach can be applied in several ways, including EIA (O’Faircheallaigh, 2010) and public health, where community participation denoted as the importance of basic healthcare for the community (Draper et al., 2010).
In this case, the community participation project at hand was the campaign for ‘sustainable helmet wearing’. People, including young people, in key community areas were encouraged to participate in determining joint targets for future implementation. In order to do this, a knowledge-sharing forum was arranged, which provided feedback about the campaign to different community areas. The role of this study is to monitor and evaluate this project’s performance. 1.3. Hypothesis This research attempts to evaluate the rates of helmet-wearing amongst motorcycle riders and passengers, in the context of a community participation approach being applied. This is based on the underlying hypothesis that knowledge provision, awarenessbuilding, and cooperative approaches and actions by a community may create positive attitudes toward helmet use, and eventually influence helmet-wearing behavior. Therefore, to prove this hypothesis, the rates of helmet use should increase with statistical significance over the course of the study. With the process of safety awareness building, the statistical model (binary logistic regression) is applied by the study to analyze into finding the target groups.
2. Methods 2.1. Study sample In this study, purposive sampling was applied. Three districts or Amphur of Nakhonpathom Province were selected as the study areas based on size, categorized into three sizes, including a large district, Amphur Muang Nakhonpathom, a medium district, Amphur Sam Pran, and a small district, Amphur Don Tum. The study team included researchers and operation teams, including the village leaders and youth groups in the study area, as key parties, to drive and encourage participation in collaborative meetings, training, and collecting data. Also, the study gathered quantitative data through statistical record forms and questionnaires, surveying opinions in the three sample districts, in which sub-districts (Tambon) were chosen by simple random sampling (Amphur Muang Nakhonpathom i.e., Tambon Map Khae and Tambon Pra Pathom Chedi; Amphur Sam Pran i.e., Tambon Kratum Lom and Tambon Rai King; Amphur Don Tum i.e., Tambon Sam Ngam and Tambon Huai Phra). 2.2. Research procedure According to Fig. 2, after completing study area selection, the investigation of helmet-wearing situation was carried out in the target areas through roadside survey. In the next step, set of data was analyzed in statistical format to identify a proportion of helmetwearing and develop binary logistic regression model with the aim of finding factors that might influence helmet-wearing of people in study area. Subsequently, obtained results were applied for planning and implementing community participation process. One year after the process, evaluation was conducted by surveying on whether the number of helmet users would increase. So, its measurement involves the examination of statistically significant changes on helmet usage based on Z-test. Finally, overall performance was concluded and then involved policies were properly suggested. 2.3. Survey design The statistical survey was divided into two stages of observation for the purposes of data collection: first, investigating existing conditions to study helmet-wearing behavior, which is
V. Ratanavaraha, S. Jomnonkwao / Transport Policy 25 (2013) 111–118
Investigating the proportion of current rates of helmet-users and finding factors affecting helmet use behaviors
113
Roadside Survey
- Calculation of proportion of helmet users by descriptive statistic - Analysis of influential factors through developing binary logistics model
Analyzing survey data
- Identification of procedures - Identification of stakeholders - Identification of primary and secondary target groups using data obtained by binary logistics model to support considerations in planning processes)
Communication participation planning
Communication participation process
Surveying the proportion of helmet use rates after one-year communication participation process
Roadside Survey
- Calculation of the proportion with descriptive statistic - Examination of statistically significant changes with Z-test
Analyzing survey results
Providing conclusions, evaluation and policy identification Fig. 2. Methodological framework.
compulsory under law but not enforced, and using this data to identify target groups (those less likely to use helmets) to participate; second, evaluating the performance after the participation process completed together with helmet-wearing behaviors (both motorcycle drivers and passengers), gender and age. The survey data includes a study of helmet-wearing behavior for drivers and passengers, related to gender and age. In terms of timings and other variables, the survey was conducted by daytime and night-time, peak and off-peak hours, weekends and weekdays, including both sections and intersections, and all road sizes (2, 4, and 8 lanes).
each variable group according to ‘Odd Ratio’ as is frequently cited (Fuentes et al., 2010; Hung et al., 2008; Keng, 2005; Lajunen and R¨as¨anen, 2001; Li et al., 2008; Orsi et al., 2011; Tanaboriboon, et al., 2008; Xuequn et al., 2011). The ‘Odd Ratio’ was applied for seeking target groups for the participation process. Next, the performance evaluation was carried out by using the Z-test; likewise all statistical tests were done by the SPSS program.
3. Results 3.1. Roadside survey
2.4. Data analysis After surveying, data were statistically analyzed by average, percentage, and chi-square tests. Also, a model was formulated, designed to forecast helmet use by applying binary logistic regression to find a ‘coefficient affecting helmet-wearing’, predict helmetwearing patterns, and to compare the ratio of helmet-wearing in
Through a roadside survey examining helmet-wearing behavior, 5878 samples were obtained, classified into 3874 drivers (65.9%) and 2004 passengers (34.1%). The survey results are illustrated in Table 1: p-value based on Chi-Square technique is calculated to test the ratio of helmet-wearing variables (null hypothesis: the ratio of people with/or without helmet use is equal in each category).
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V. Ratanavaraha, S. Jomnonkwao / Transport Policy 25 (2013) 111–118
Table 1 The proportion of helmet-wearing by drivers and passengers (before project). Drivers
Gender Male Female Age group Child Adolescences Adults Location Segment Intersection Number of lane 2 4 8 Day of week Weekend Weekday Time of day Day Night Traffic time Peak Off-peak Total n
Passengers
Helmet-wearing (%)
Total
Yes
N
No
p-value % 0.001
41.69 35.94
58.31 64.06
2672 1202
68.97 31.03
14.29 31.56 47.26
85.71 68.44 52.74
49 1711 2114
1.26 44.17 54.57
38.62 41.18
61.38 58.82
1924 1950
49.66 50.34
40.47 22.00 50.00
59.53 78.00 50.00
2634 500 740
67.99 12.91 19.10
39.48 40.33
60.52 59.67
1925 1949
49.69 50.31
43.22 33.10
56.78 66.90
2605 1269
67.24 32.76
44.13 37.72 39.31
55.87 62.28 60.09
1321 2553 3874
34.10 65.90
Helmet-wearing (%)
Total
p-value
Yes
No
N
%
19.11 13.19
80.89 86.81
654 1350
32.63 67.37
8.29 14.42 20.68
91.71 85.58 79.32
398 992 614
19.86 49.50 30.64
14.23 15.99
85.77 84.01
991 1013
49.45 50.55
10.25 3.57 34.04
89.75 96.43 65.96
1307 224 473
65.22 11.18 23.60
14.79 15.47
85.21 84.53
1028 976
51.30 48.70
15.11 15.13
84.89 84.87
1310 694
65.37 34.63
16.35 14.49 15.12
83.65 85.51 84.88
679 1325 2004
33.88 66.12
nn
0.001nn
o0.001nn
o 0.001nn
0.103
0.27
o 0.001nn
o0.001nn
0.59
0.669
o0.001nn
0.993
o0.001nn
0.272
Statistically significant at 5%. nn
Statistically significant at 1%.
Regarding each factor with a 95% confidence level, the study found that, for drivers, two factors including location and day of the week are not significant. For passengers, three factors including gender, age group, and number of lane are found to be significant predictors of helmet usage. To consider the ratio of helmet-wearing behavior according to each variable, the findings can be described as follows; Gender: based on this survey of drivers (males 68.97%, females 31.03%) and passengers (males 32.63%, females 67.37%), the study found that, according to the helmet-wearing behaviors of drivers and passengers, males have a greater proportion of helmet use than females do: 41.69% of male drivers and 19.11% of male passengers wore helmets, whereas only 35.94% of female drivers and 13.19% of female passengers wore helmets. Regarding the results from Chi-square difference testing at 0.05 significance level, the study found the differences of helmet use behaviors between males and females in both driver group (p¼0.001) and passenger group (p¼0.001). Age: drivers can be split by age as follows: children (less than 13 years) 1.26%, adolescents (13–18 years) 44.17%, adults (more than 18 years) 54.57%; passengers can be split as follows: children 19.86%, adolescents 49.50%, and adults 30.64. Amongst both drivers and passengers adults have the highest rates of helmet use (47.26% for drivers and 20.68% for passengers), following by adolescences (31.56% for drivers and 14.42% for passengers), with children having the lowest helmet-wearing rates (14.29% for drivers and 8.29% for passengers). According to Chi-square test, the study showed age factor significantly affects helmet use behaviors of a sample group in both drivers (po0.001) and passengers (po0.001), thus it means that there are differences in helmetwearing behaviors between children, adolescent and adult groups. Location on the road: for drivers, 49.66% of survey samples were on road segments, and 50.34% at intersections. For passengers, 49.45% were on segments and 50.55% at intersections.
Helmet-usage was significantly greater at intersections than segments, at 41.18% for drivers and 15.99% for passengers at intersections, compared with 38.62% for drivers and 14.23% for passengers. Drivers and passengers followed the same pattern in this instance. Based on statistical test of differences, the results illustrated that wearing helmets does not depend on the road location and helmet uses at direct routes and intersections are not different for both drivers (p ¼0.103) and passengers (p ¼0.27). Number of lanes: 67.99% of the drivers were surveyed on 2lane roads, compared to 12.91% on 4 lanes and 19.10% on 8 lanes. For passengers, 65.22% were surveyed on 2-lane roads, 11.18% on 4-lane roads and 23.60% on 8-lane roads). Drivers and passengers had similar helmet-wearing behaviors here: 8-lane roads had the greatest proportions of helmet use (50.00% for drivers and 34.04% for passengers), following by 2-lane roads (40.47% for drivers and 10.25% for passengers). Four-lane roads indicated the smallest percentage (22.00% for drivers and 3.57% for passengers). From the study, number of lanes influence helmet use behaviors of a sample group and the results from Chi-square test indicated the differences of helmet use in groups of drivers (po0.001) and passengers (p o0.001) in 2-lane, 4-lane and 8-lane roads. Day of the week: of the drivers surveyed, 50.31% were driving on weekdays, and 49.69% at weekends. For passengers, this was 48.70% on weekdays and 51.30% at weekends. Again, drivers and passengers exhibited similar helmet-wearing behaviors. Helmetwearing was more prevalent on weekdays (40.33% for drivers and 15.47% for passengers) than weekends (39.48% for drivers and 14.79% for passengers). Regarding Chi-square test, day of week is not associated with the helmet use behavior of a sample group, therefore it could be referred that in weekend and weekday, behaviors of helmet-wearing between driver group (p ¼0.59) and passenger group (p ¼0.669) are similar. Time of day: 67.24% of drivers surveyed were in the day-time, compared to 32.76% at night. For passengers, 65.37% were
V. Ratanavaraha, S. Jomnonkwao / Transport Policy 25 (2013) 111–118
surveyed in the day and 34.63% at night. Interestingly, drivers are more likely to wear helmets during the day (43.22%, compared to night-time rates of 33.10%). In contrast, for passengers, rates of helmet-wearing by day or night are relatively similar at roughly 15%. According to the test, helmet use behaviors of a sample of drivers are significantly different between the day and the night (po0.001); while behaviors of passengers in using helmets do not rely on the time of day (p ¼0.993). Traffic conditions: drivers surveyed in peak hours accounted for 34.01%, compared to off-peak hours of 65.90%. For passengers, peak and off-peak hours accounted for 33.38% and 66.12% of those surveyed, respectively. The findings indicate similar helmetwearing patterns for drivers and passengers, and demonstrate that the helmet-wearing rates in peak hours (44.13% for drivers and 16.35% for passengers) are considerably higher than off-peak times (37.72% for drivers and 14.49% for passengers). The results of Chi-square test showed significant divergence in drivers’ helmet-wearing behaviors between peak and off-peak hours (po0.001); on the other hands, there is no difference in passengers’ behaviors in wearing helmets among both periods (p¼ 0.272).
3.2. Helmet use model Table 2 shows the results derived from the development of a helmet-use model using ‘Binary Logistic Regression’. Based on a survey of 5878 samples (3874 drivers and 2004 passengers) and a model coefficient, the findings found that gender and night-time factors affect not using helmets of drivers, indicated as negative values. When considering the odd ratio—defined as the proportion of helmet-wearing related to each variable, the results demonstrate that the ratio of 4-lane roads is 1.743 times larger than that of 2-lane roads; while the ratio of 8-lane roads remarkably shows 4.070 times more than 2-lane roads. Additionally, the odd ratios of females to males, adolescences to children, adults to children and night-time to day-time, equal 0.774, 4.557, 2.149, and 0.626. Table 2 Binary logistic regression model for helmet use (before project). Variable
Driver Coef.
Gender Male Female Age group Child Adolescences Adults Number of lane 2 4 8 Time Day Night Traffic time Peak Off-peak Constant
r2 2LL N n
0.256 0.001nn
3.3. The process of community participation in this study The process of community participation is adopted as a key mechanism for improving helmet-wearing rates in local areas. Based on this effort, implementation stages are identified in Table 3. In step 1, it involves the selection of people within community in collaborative surveying helmet-wearing rates in order to enable them to envisage the actual situations and create awareness for mutually problem solving. Such group would reflect the occurred issues to other people in the community such as family, relatives, friends, etc. This process provides individual information obtained by the community, so it brings the driving forces of cooperative problem solving that could be better than implementation of people outside community. After that, work team becomes involved in the meeting with the community leader to find solutions for helmet-wearing problems of community. The study proposes 2 campaign plans with attention to provide understanding of the benefits of helmet use and proper decisions of purchasing and wearing helmets to community as following:
‘No risk, no death, no embarrassment, just wear a helmet’,
Odd ratio
1.000 0.774
Coef.
p-value
0.435 0.002nn
Odd ratio
1.000 0.647
1.517 0.765
1.000 o 0.001nn 4.557 nn o 0.001 2.149
1.269 0.814
o0.001nn o0.001nn
0.556 1.404
1.000 o 0.001nn 1.743 o 0.001nn 4.070
2.015 2.960
1.000 o0.001nn 7.501 o0.001nn 19.292
0.468
1.000 o 0.001nn 0.626
0.711
o0.001nn
0.025 0.820 0.096 4927.52 3874
Statistically significant at 5%. nn
In case of passengers, no helmet use is influenced by gender, and night-time factors, indicated as negative values. When considering the odd ratio—defined as the proportion of helmetwearing related to each variable, the results demonstrate that the ratio of 4-lane roads is 7.501 times larger than that of 2-lane roads; while the ratio of 8-lane roads remarkably shows 19.292 times more than 2-lane roads. Additionally, the odd ratios of females to males, adolescences to children, adults to children, night-time to day-time, and off-peak times to peak times, equal 0.647, 3.557, 2.256, 0.491, and 2.442, respectively. According to the model results regarding individual factors (i.e., gender and age), the findings found that children have a smaller proportion of helmet-wearing than other age groups by 2–5 times for drivers and 2–4 times for passengers. Therefore, in the participation process, the priority needed to be given to children through the provision of safety education at school, and the activity of ‘community angels’. These can be the parts of the distribution and campaign in the importance of helmet use for adults in local areas.
Passenger p-value
Statistically significant at 1%.
6.164
0.892 o0.001nn 0.073 0.681 0.193 1467.92 2004
115
1.000 3.557 2.256
1.000 0.491 1.000 2.441 1.076
aims (1) to change the attitudes and behaviors of motorcycle riders, especially adolescents; (2) to make adolescents aware of the need for helmet use; and (3) to minimize the accident severity caused by motorcycle riding on roadways. It encompasses the use of media campaign such as mass media (radio broadcasting, local cable media), print media (poster, local newspaper), specialized media(fabric/ink poster, video documentary, internet), activity media(arranging helmet design competition for motorcyclists’ safety and/or helmeted-motorcycle riders parade activity around Nakhon Pathom Province for accident reduction and road safety campaign to make helmet use a higher priority). ‘Someone behind you as a thing in your life’, aims (1) to make local people conscious about the importance of helmet usage while driving themselves and their passengers; and (2) to reduce the rate of injuries and fatalities from motorcycle riding for both drivers and passengers. The project chiefly highlights the use of helmets by passengers through using activity media (giving 1000 free helmets for prototype school with gamesrelated helmet use safety knowledge and accident prevention, and the arrangement of art painting competition for children in the theme of ‘‘Happy Family by Protection of Helmets’’).
After this step, implementation following campaign plans was preceded through ‘community angle’ acted as the leader. This process has continually been conducted about a year since project
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Table 3 Implementation steps, participation approaches and procedures. Steps
Participation techniques
Procedures
1. Cooperative finding problems, causes, and acceptable solutions
Participative decision making
Team work involves the meeting with the head of community to select ‘community angle’ for surveying helmet-wearing rates
2. Mutual decision-making in selecting approaches and problem-solving plans
Public meeting Participative decision making
Team work joins the meeting with the community leader to find solutions for helmet use problems of community
3. Collaborative implementation following planning activities
Public information Work team in cooperation with community angle conduct campaigns for helmet-wearing following the plans
4. Cooperative evaluation of projects
Public meeting Participative decision making
Community angle carries out survey of helmet-wearing rates after one year of project’s implementation Work team joins the meeting with the community leader to evaluate implementation performance and issue policies to promote the sustainability of helmet use in community
started, and then cooperative evaluation was put in place by surveying the proportions of helmet users compared to results before starting a project. 3.4. Community participation evaluation After completing the community participation process, the performance evaluation was conducted. At this stage, the roadside survey technique was applied for examining the helmet-wearing behaviors of 1846 samples within the study area. Its results were compared with the previous survey before starting the participatory project implementation as illustrated in Table 4. Interestingly, the study found a greater proportion of helmet-wearing after the project (44.69%) than before (31.46%), indicating a change of 13.23%. Through estimating the differences in proportions of the two populations with z-test (null hypothesis: The proportion of people using helmets before and after the project is equal), the test shows p-value o0.001, and then rejects null hypothesis at the 95% confidence level. In considering each variable, it demonstrates an increased proportion of all factors with the range of 5.92–32.69%. Only the proportion of helmet wearing on ‘8 lane-roads’ appears to be decreased. This can be explained by the fact that 8-lane roads are large roads with rights-of-way through the local areas, so some populations using it were not included in the community project. Regarding the factor of age, the project prioritized children through the provision of school safety education. The study found a greater proportion of helmet-wearing among children after the project (15%) than before (8.95%), referred to as a 6.05% change rate. In addition, the project suggests that children discussed with their parents about the significance of helmet use, leading to better helmet use performance amongst both adolescences and adults (adolescences by 10.78%, adults by 17.33%). The comparison of helmet use rates between drivers and passengers of Tables 5 and 1 indicates the increase in helmet use rates of drivers of all variables, except for areas of 8-lane roads. When considering chi-square test results, it could be implied by the study that helmet usage seems likely to depend on gender, age, location, number of lane and the time of day. For passengers, the result found a larger proportion of helmetwearing in males, children, adults, intersection, 2-lane roads, 4lane roads, weekday, night time, and off-peak hours. Likewise, results of chi-square test demonstrated that the use of helmets is significantly relied on gender and age. Based on Table 6, factors influencing not using helmets after project implementation for drivers include femininity and night-time period; while only femininity factor affect not using helmets o passengers.
4. Discussion This study has applied the community participation approach for increasing the helmet-wearing rates of people in Thailand, selecting Nakhonpathom Province (one of the central provinces of Thailand) as its target area. Initially, as part of its effort to increase the rates of helmet-wearing rates, the mandatory approach has been used in Thailand for 19 years between 1992 and the present (2011). However, based on the survey of results of helmet-wearing behavior in 2010, the average rates of helmet usage on motorcycles among drivers and passengers was to 52 and 16, respectively (Thailand Road Safety Observatory, 2011b), which is a very low rate internationally. This low rate can be seen as a result of the limitations of law enforcement, especially from the police force. Moreover, in some cases, motorcyclists are acting as if they use helmets to avoid police arrest, but not to prevent harm: they put the helmets in the front baskets and wear them only if they suddenly see the police. This pattern is also seen in Vietnam. Based on this study, 2.1 of motorcyclists have helmets but do not use them (Hung et al., 2008). This phenomenon may result from negative attitudes to helmet use, such as the inconvenience of carrying a helmet, hearing loss, ventilation and vision problems, etc. (Orsi et al., 2011). Therefore, the application of the concept of community participation, through public information related to safe motorcycle riding and participation in safety activities, might be an approach to build better awareness of the benefits of helmet use as opposed to the disadvantages, as a means to achieving sustainable development. This study investigates the existing helmet-wearing behaviors of people in the target area. Based on the observation of 5878 samples overall, it found helmeted motorcycle drivers made up 39.31 of 3874 samples, and helmeted motorcycle passengers made up 15.12 of 2004 samples. This was lower than the national average both for drivers and passengers, and less than in other countries. For example, in China, helmeted motorcycle drivers accounted for 66 (2008) and 72.60 (2011), with rates of 29.50 (2008) and 34.10 (2011) for helmeted passengers (Li et al., 2008; Xuequn et al., 2011). Meanwhile, in Spain, 78.28 of drivers were helmeted, and 80.40 of passengers. Rates of motorcycle helmet usage were relatively high, particularly among adolescents (Fuentes et al., 2010). For the USA, the helmet-wearing rates for both drivers and passengers are similar at 57.40 (Mayrose, 2008). All of this said, the rates of helmet-wearing in Thailand are much higher than in Iran, where helmeted motorcycle drivers and passengers were found at 33.26 and 0.11, respectively (Zamani-Alavijeh et al., 2011). After the survey, the data was used for formulating the model of helmet use, which identified factors affecting not using helmets,
V. Ratanavaraha, S. Jomnonkwao / Transport Policy 25 (2013) 111–118
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Table 4 The comparison of proportion of helmet-wearing before and after the application of participation approach. Before
Gender Male Female Age group Child Adolescences Adults Location Segment Intersection Number of lane 2 4 8 Day Weekend Weekday Time Day Night Traffic time Peak Off-peak Total
After
Helmet-wearing (%)
Total
Yes
No
N
37.25 23.90
62.75 76.10
8.95 25.27 41.28
Different
% change
Helmet-wearing (%)
Total
%
Yes
No
N
%
3326 2552
56.58 43.42
55.72 29.82
44.28 70.18
1057 788
57.26 42.69
18.47 5.92
50 25
91.05 74.73 58.72
447 2703 2728
7.60 45.99 46.41
15.00 36.05 58.61
85.00 63.95 41.39
120 907 819
6.50 49.13 44.37
6.05 10.78 17.33
68 43 42
30.33 32.57
69.67 67.43
2915 2963
49.59 50.41
47.45 42.06
52.55 57.94
902 944
48.86 51.14
17.12 9.49
56 29
30.45 16.30 43.78
69.55 83.70 56.22
3941 724 1213
67.05 12.32 20.64
50.00 48.99 22.06
50.00 51.01 77.94
1210 296 340
65.55 16.03 18.42
19.55 32.69 21.72
64 201 50
30.88 32.03
69.12 67.97
2953 2925
50.24 49.76
44.39 45.33
55.61 54.67
1257 589
68.09 31.91
13.51 13.30
44 42
33.82 26.74
66.18 73.26
3915 1963
66.60 33.40
45.31 38.13
54.69 61.88
1686 160
91.33 8.67
11.50 11.38
34 43
34.70 29.78 31.46
65.30 70.22 68.54
2000 3878 5878
34.03 65.97
45.45 44.56 44.69
54.55 55.44 55.31
275 1571 1846
14.90 85.10
10.75 14.77 13.23
31 50 42
Table 5 The proportion of helmet-wearing by drivers and passengers (after project). Drivers
Gender Male Female Age group Child Adolescences Adults Location Segment Intersection Number of lane 2 4 8 Day of week Weekend Weekday Time of day Day Night Traffic time Peak Off-peak Total n
Passengers
Helmet-wearing (%)
Total
Yes
N
No
p value % o 0.001
64.27 51.58
35.73 48.42
848 349
70.78 29.16
28.57 52.64 68.19
71.43 47.36 31.81
14 549 635
1.17 45.83 53.01
64.44 56.76
35.56 43.24
599 599
50.00 50.00
67.54 65.00 28.50
32.46 35.00 71.50
798 200 200
66.61 16.69 16.69
61.45 58.90
38.55 41.10
799 399
66.69 33.31
61.57 50.00
38.43 50.00
1098 100
91.65 8.35
59.30 60.86 60.60
40.70 39.14 39.40
199 999 1,198
16.61 83.39
Helmet-wearing (%)
Total
p-value
Yes
No
N
%
21.05 12.53
78.95 87.47
209 439
32.25 67.75
13.21 10.61 25.54
86.79 89.39 74.46
106 358 184
16.36 55.25 28.40
13.86 16.52
86.14 83.48
303 345
46.76 53.24
16.02 15.63 12.86
83.98 84.38 87.14
412 96 140
63.58 14.81 21.60
14.63 16.84
85.37 83.16
458 190
70.68 29.32
14.97 18.33
85.03 81.67
588 60
90.74 9.26
9.21 16.08 15.28
90.79 83.92 84.72
76 572 648
11.73 88.27
nn
0.005nn
o 0.001nn
o 0.001nn
0.007nn
0.348
o 0.001nn
0.664
0.394
0.476
0.023nn
0.490
0.680
0.118
Statistically significant at 5%. nn
Statistically significant at 1%.
such as passenger position. One reason for this is that, in general, motorcycle owners will buy only one helmet for themselves, not for passengers, as they are trying to be economical. Another factor is the night-time, where drivers might perceive that helmet-wearing would be detrimental to their ability to see the road. Furthermore, police patrols and helmet enforcement are less likely in the
night-time than the day. The model applied the ‘odd ratio’ to find individual factors to seek the target groups for the community participation process. The outstanding factor was age group: the proportion of helmeted children was 2–5 times lower than that of adolescents and adults. It is likely that majority of motorcycle riders are ranged into low-medium income groups, so they cannot
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Acknowledgments
Table 6 Binary logistic regression model for helmet use (after project). Variable
Gender Male Female Age group Child Adolescences Adults Time Day Night Constant
r2 2LL N n
Driver
Passenger
Coef.
p-value
0.536
1.000 o 0.001nn 0.585
0.675 0.003nn
1.713 0.668
1.000 0.004nn 5.544 o 0.001nn 1.951
0.897 1.088
0.498 0.020nn 0.060 0.794 0.064 1548.658 1198
Odd ratio
Coef.
p-value
Odd ratio
1.000 0.509
1.000 0.008nn 2.451 o0.001nn 2.967
1.000 0.608 1.062 0.075 525.566 648
Statistically significant at 5%. nn
Statistically significant at 1%.
afford to buy additional helmets for children (Tanaboriboon et al., 2008). Based on the findings, the study focused on giving priority to children through the provision of information in terms of the importance of helmet-wearing in school areas, as well as promoting the ‘community angel’ scheme (which obtained the training program from the project) to create awareness among children, and then tell their parents to seek helmets for them. Nevertheless, the study did not ignore the other age groups, so the campaign plans, such as ‘No risk, no death, no embarrassment, just wearing a helmet’ and ‘Someone behind you as a thing in your life’ have also been carried out. The performance after the community participation process clearly illustrates the higher rates of helmeted motorcycles in the target area by an increase of 13.23.
5. Conclusion Community participation is a significant approach and has been effectively used in increasing the helmet-wearing rates in the community target areas. This endeavor has been achieved through encouraging both youths and adults in the target area to participate in providing information, indicating the importance and promotion of helmet use, and determining the mutual targets and future implementation through a sharing and learning forum. This enabled the study to feed back information to the community towards the campaign for sustainable helmet use. The study considers the statistical analysis of the helmet-wearing behaviors according to both external and demographical factors, and conducted the survey and the comparison of such behaviors before and after project implementation, in order to evaluate the helmet-wearing behaviors of motorcycle riders. Regarding community participation, success of increase in the proportion of helmet use within community must require the creation of awareness and safety knowledge for the village leaders. After they have more understanding of the importance of helmet use, the next step involves building networks through selection of adolescent groups to participate the preparation of safety plans as well as the provision of budget for continual campaign, in order to naturally change behaviors of motorcycle users in community to have more discipline. The outcomes noticeably demonstrated better helmet-wearing rates. Hence, putting community participation into vigorous practice through collaborative problem solving regarding safe driving may eventually be able to substantially increase the helmet-wearing rates up to 100.
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