The Association Between Risk-taking Behavior and Helmet Use Among Motorcyclist

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IOP Conference Series: Earth and Environmental Science PAPER OPEN ACCESS The Association Between Risk-taking Behavior and Helmet Use Among Motorcyclist To cite this article: Tu Anh Trinh and Thi Phuong Linh Le 2018 IOP Conf. Ser.: Earth Environ. Sci. 143 012069 View the article online for updates and enhancements. This content was downloaded from IP address 148.251.232.83 on 09/10/2018 at 20:38

The Association Between Risk-taking Behavior and Helmet Use Among Motorcyclist Tu Anh Trinh 1, Thi Phuong Linh Le 2 1 Urban and Regional Planning Department, Faculty of Civil Engineering, Ton Duc Thang University, 19 Nguyen Huu Tho, Tan Phong Ward, District No 7, Hochiminh city, Vietnam. Email: trinhtuanh@tdt.edu.vn 2 Faculty of Airport, Vietnam Aviation Academy, 104 Nguyen Van Troi, Phu Nhuan District, Hochiminh city, Vietnam Abstract. The central aim of the research was to examine speeding behavior without helmet wearing among motorcycle riders in Ho Chi Minh City. The research model expanded the Theory of Planned Behavior by both psychological flow theory and sensation-seeking. 268 motorcyclists were involved in the research. A Confirmatory factor analysis and a Structural equation modeling were employed for model specification. The findings indicated a significant effect between predictors and the intention of speeding without helmet wearing. In addition, there was direct relation between intention and actual behavior. Also, sensation-seeking proved to be important in moderating predictors between the low-sensation-seeking motorcyclists and high-sensationseeking ones. A deeper understanding of why motorcycle riders exceed the speed limit without wearing helmet played key role in changing their behavior. 1. Introduction Due to the features of low price, high mobility, motorcycle riding has become popular and convenient means of transportation in many countries, including Vietnam. However, the increasing number of motorcycles are expected to lead to an increasing number of motorcycle accident. Various studies have demonstrated that motorcyclists were at higher risk of being killed or injured in a road traffic crash compared with others [1]. To prevent head injury from accidents, wearing a helmet while riding a motorcycle has been regarded as one of the best solutions. [2] confirmed that riders who have accidents while not wearing helmets were more likely to suffer critical head injury or death than were riders wearing helmets. Vietnam is a motorcycle-dependent country. Motorcycle-related accidents and deaths account for a substantial proportion of road accidents. In attempts to tackle with traffic accident, several policies and programs have been implemented such as the promulgation of the compulsory helmet legislation in December 2007 and annual national road safety campaigns; however, according to Vietnamese National Traffic Safety Committee, only in 2014, 25.322 traffic accidents related to motorcycles and more than 8.996 road users killed on the were recorded and most of these traffic accident deaths were attributed by risk-taking behaviors, particularly speeding without helmet wearing which accounted for 25%. Although speeding without helmet wearing is the primary cause of traffic accidents, there have been no more research efforts to gain a better understanding of motorcycle helmet use and their correlation with speeding among citizen. This study aimed to fill this gap by specifically investigating speeding Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by Ltd 1

behavior without helmet wearing among motorcycle riders in Ho Chi Minh City (HCMC), Vietnam. To achieve the central aim of the research, the extended Theory of Planned Behavior proposed by Chen and Chen (2010) were employed as theoretical framework. By doing so, the research expected to better gain insights of motorcyclist s speeding behavior in conjunction with their neglects of helmet use that would help government implement solutions to change motorcyclist s risk behavior. The following section details the study s theoretical frameworks and then its hypothesized model. 1.1 Theory of planned behavior The Theory of Planned Behavior (TPB) is a robust theory that has been used across multiple contexts to explain a wide range of behaviors [3] [4]. The TPB model assumes that behavior depends on intention, and that intention, in turn, is determined by a person s attitudes, subjective norms, and perceived behavioral control [5] (Figure 1). Attitude Subjective norm Behavioral intention Behavior behavioral control Figure 1. The theory of planned behavior In this context, attitudes refer to an individual s evaluation of a behavior, which are informed by behavioral beliefs concerning a behavior's outcome and behavioral beliefs pertaining to the experience of a behavior [4]. Subjective norms refer to people s beliefs about how their significant others think they should engage in the behavior [4]. Last, behavioral control refers to a person s perception of his or her ability and resources to perform a behavior and are reflected in an individual s control beliefs [5]. The Theory of Planned Behavior (TPB) has been successful applied to predict a variety of behaviors in the field of social science, health, education and transportation. In the field of traffic psychology many previous studies have used the TPB as a frame of reference [1] [6] [7]. 1.2 The extended Theory of Planned Behavior [8] was developed the extended Theory of Planned Behavior on the basic of Theory of Planned Behavior [5] to explore speeding behavior of heavy motorcycle riders by adding the variables of psychological flow theory to explore intrinsic motivations among motorcyclists, and (2) the sensation seeking and riding experiences to investigate differences of groups in the influence of affecting factors on speeding behavior (Figure 2). Regarding Psychological flow theory, [8] argues that intrinsic motivations instead of extrinsic motivations might better explain and/or predict the related speeding behavior. Thus, the author took into account perceived enjoyment and concentration to construct the flow of heavy motorcycle riders. According to [9] (as cited in [8]), enjoyment is defined as when, under conditions of playfulness, an individual will find an action intrinsically interesting, and thus will engage in it for pleasure and enjoyment rather than extrinsic rewards, and Concentration is defined as when an individual loses self-consciousness, becomes absorbed in the activity, and is more intensely aware of their mental processes when in a playful state. In terms of sensation-seeking and riding experience, both of them were regarded as an important factor influencing rider behavior. In his work, [8] stated that sensation-seeking individual tended to seek 2

and enjoy high stimulus, exciting, novel and diverse experiences and stimuli. The greater sensationseeking individual was, the higher possibility he was involved in risky driving behavior. Similarly, an experienced motorcyclist who felt confident in controlling their motorcycle due to past experience would be highly likely to exceed speed limit compared with those had less riding experiences. Hence, [8] did add two dimensions in his model to investigate their moderating role in heavy motorcycle riders behavior. To examine the moderating effect of sensation-seeking, based on the mean level of sensationseeking, the sample would be divided into two groups: high and low. In the context of Vietnam - a motorcycle-dependent country, motorcycle is the major transport mode of citizen for various purposes; therefore, the current study only focused on high-sensation-seeking motorcycle riders and low-sensation-seeking ones. Respondents would be experienced motorcycle riders who have at least 5-year motorcycle driving experience. Novices (less than 5-year motorcycle driving experience) would be excluded in this study. 1.3 Hypothesis Based on the literature review aforementioned above, the current study proposed a conceptual framework (Figure 2) with the following hypotheses. Specifically: H1: enjoyment has a positive effect on attitude toward speeding without helmet wearing. H2: enjoyment has a positive effect on intention of speeding without helmet wearing. H3: Concentration has a positive effect on attitude toward speeding without helmet wearing. H4: Concentration has a positive effect on intention of speeding without helmet wearing. enjoyment (PE) Concentration (CON) H2 H1 H3 H4 Attitude toward speeding without helmet use (ATS) H8 Intention of speeding without helmet use (IS) H9 Actual speeding behavior without helmet use (AS) H5 Subjective norm (SN) H6 H7 behavior control (PBC) Figure 2. Conceptual framework H5: Subjective norm has a negative effect on intention of speeding without helmet wearing. H6: behavioral control has a positive effect on intention of speeding without helmet wearing. H7: behavioral control has a positive effect on actual speeding behavior without helmet wearing. H8: Attitude has a positive effect on intention of speeding without helmet wearing. H9: Intention of speeding without helmet wearing has a positive effect on actual speeding behavior without helmet wearing. 3

2. Method 2.1 Data collection The population of this study was selected at HCMC. The survey was conducted from June 2017-July 2017. Thirty minutes face-to-face interview were applied for data collection. The author visited the gas stations, shopping malls, super markets, bookshops and entertainment places to conduct interview. Pilot study were carried out to make sure that the measuring instrument represented the goal of the study. Total 300 respondents randomly selected were involved in this survey. The final sample size for the study was 268, whereas 32 observations (of the 300 collected) dropped due to incomplete informations. There were 63.1% male and 36.9% female respondents. Riders aged 22 35 (66.3%) and 36 53 (33.7%) accounted for the majority of the sample. 14% of respondents had less than 5 year s experience, followed by 52.4% with 5-10 years and 43.6% with more than 10 years experience. 2.2 Measures The dependent variable in the study was motorcycle rider s actual speeding behavior without helmet wearing. The predictors were perceived enjoyment, concentration, attitude toward speeding without helmet wearing, perceived behavioral control, subjective norms, and intention of speeding without helmet wearing. The dependent variable and predictors mentioned below were designed on the basic of literature review and items adapted from [8]. The variables measured with multiple items were examined with Cronbach s alpha reliability for internal consistency: Actual speeding behavior was measured by asking rider about the frequency they speeded without wearing helmet during the six months before the interview. Actual speeding behavior was measured on a 5-rating scale ranging from 1 (very infrequent) to 5 (very frequent). The single item stated that Within the past six months, how frequently did you exceed the speed limit when riding a heavy motorcycle? (M=3.8, SD=1.3). Attitude was assessed through items rated on a 4-point scale ranging from 1 (Totally disagree) to 4 (Totally agree) that asked the motorcyclist position on speeding without helmet wearing (e.g. To exceed the speed limit when riding without helmet wearing (a) I would feel enjoyable, (b) I would feel comfortable, (c) I would feel acceptable) (Cronbach s α =.65). Subjective norm was measured with items rated on a 4-point scale ranging from 1 (Totally disagree) to 4 (Totally agree) (e.g. (a) Most people who are important to me think that I should not speed without helmet wearing, (b) Most people who are important to me do not support me speeding without helmet wearing, (c) Most people who are important to me will not speed without helmet wearing) (Cronbach s α =.64). behavioral control was measured with items rated on a 4-point scale ranging from 1 (Totally disagree) to 4 (Totally agree) (e.g. (a) When speeding without helmet wearing, I believe my driving skills can meet the challenge, (b) When speeding without helmet wearing, I feel in total control of what I am doing, (c) When speeding without helmet wearing, I am capable of manipulating the vehicle without thinking how to do it) (Cronbach s α =.72) Intention was measured by items rated on a 4-point scale ranging from 1 (Totally disagree) to 4 (Totally agree) (e.g. (a) When riding without helmet wearing, I am likely to speed, (b) When riding without helmet wearing, I intend to speed, if possible, (c) When riding without helmet wearing, I will try to speed) (Cronbach s α =.77). Concentration was measured by items rated on a 4-point scale ranging from 1 (Totally disagree) to 4 (Totally agree) (e.g. (a) During speeding without helmet wearing, I concentrate fully on the activity, (b) During speeding without helmet wearing, I am usually absorbed intensely in the activity, (c) During speeding, I am deeply engrossed in the activity) (Cronbach s α =.68). enjoyment was measured with items rated on a 4-point scale ranging from 1 (Totally disagree) to 4 (Totally agree) (e.g. (a) I find riding heavy motorcycles to be enjoyable, (b) I have fun riding a heavy motorcycle, (b) The process of riding a heavy motorcycle is pleasant) (Cronbach s α =.86). 4

Sensation seeking (SS) was assessed through items rated on a 4-point scale ranging from 1 (Totally disagree) to 4 (Totally agree) (e.g. (a) I would like to try bungee jumping, (b) I would love to have new and exciting experiences, even if they are illegal). (Cronbach s α =.65). 2.3 Data analysis A Confirmatory factor analysis (CFA) and a Structural equation modeling (SEM) were employed in this study. CFA was used to confirm the relationship between the latent factors (e.g. psychological flow variables, TPB variables, intention) and their observed indicators (e.g. the measurement items). SEM was utilized to test the hypothesized relationships between the predictors and behavioral intention, actual behavior. Goodness-of-fit index (GFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA) were used to examine SEM. For assessing goodness of fit, the author did follow the criteria proposed by [10] that values of GFI and CFI of 0.9 or above, RMSEA of 0.05 or less confirm a good fit between the model and the data. 3. Model Specification 3.1 Confirmatory factor analysis CFA was employed in this stage to verify the factor structure. Table 1 present the results of CFA for the whole sample. Table 1. Goodness of fit index Model χ 2 df RMSEA CFI GFI NFI CFA 640.24 186 (p<.001).09.959.81.96 3.2 Model Specification After fitting the model, we utilized structural equation modeling to test the hypothesized model for the whole sample (n=268). The proposed model indicated a reasonably good fit (Table 2). Table 2. Goodness of fit index Model 1 χ 2 df RMSEA CFI GFI NFI SEM 329.22 190 (P<.001).09.960.80.95 As mentioned above, the current research focused on high-sensation-seeking groups and lowsensation-seeking groups. To examine the moderating effect of sensation-seeking, the sample was divided into two groups based on the mean level of sensation-seeking: high and low. Therefore, Model 2 and Model 3 were performed to examine the moderating effect of sensation-seeking (Table 3). Table 3. Estimated results of the models Path Model 2 (n=116) (low SS) Model 3 (n=152) (high SS) PE ATS.27.32 PE IS.33.40 CON ATS.10.13 CON IS.50.37 SN IS -.04 -.16 PBC IS -.10.08 PBC AS -.05.04 ATS IS.30.13 SBI AS.59.55 5

Path Model 2 (n=116) (low SS) Model 3 (n=152) (high SS) χ 2 χ = 386.42, df=192(p<.001) 2 = 395.64, df=192(p<.001) RMSEA=.08 RMSEA=.09 Goodness of fit index CFI=.970 CFI=.980 GFI=.70 GFI=.81 NFI=.95 NFI=.90 enjoyment (PE).45.52 Concentration (CON).41.37 Attitude toward speeding without helmet use (ATS).32 Intention of.59 speeding without helmet use (IS) Actual speeding behavior without helmet use (AS) -.02 Subjective norm (SN).15.10 behavior control (PBC) -------- n.s non significant significant at p <.001 Figure 3. Structural equation model for whole sample 4. Discussion Eight out of nine hypotheses in Model 1 were found to be supported. Regarding TPB variables, attitude had a positive effect on intention of speeding without helmet wearing. This finding suggested that to exceed the speed limit when riding without helmet wearing, motorcyclist rider would feel enjoyable, comfortable, and acceptable. In support of Hypothesis 5, the findings revealed a negative effect of subjective norm on intention of speeding without helmet wearing. The finding showed that the advice from people who are important to rider did not affect the intention of speeding among motorcycle riders. The effects perceived behavioral control on intention of speeding without helmet wearing was significant. This finding was proved to be consistent with those of previous studies that perceived behavioral control had generally been a significant correlate of behavioral intention. In this research, it was highly likely that when speeding without helmet wearing, respondent believed their driving skills that could meet the challenge, or when speeding without helmet wearing, they felt in total control of what they were doing. With respect to psychological flow variables, perceived enjoyment and concentration were significant predictors of intention of speeding without helmet wearing. During speeding without helmet wearing, respondent seemed to be absorbed intensely and deeply engrossed in 6

the activity. Also, they found riding heavy motorcycles enjoyable and even more pleasant. The psychological flow variables did demonstrate their direct and indirect effects on intention of speeding without helmet wearing and motorcyclists actual speeding behavior. The outcome supported previous researches that intrinsic motivations (perceived enjoyment and cognitive concentration) instead of extrinsic motivations confirmed better explanation of speeding behavior with/without helmet use among motorcycle riders. In terms of the correlate between intention and actual behavior, there was significantly direct relation between intention of speeding without helmet wearing and actual speeding behavior without helmet wearing. It revealed that when riding without helmet wearing, motorcyclist was likely to/intend to/and try to speed, if possible. The findings of the moderating effect investigation of sensation-seeking between low-sensationseeking and high-sensation-seeking group showed that there was a significant difference in the sensation-seeking level among the groups and the whole sample. The outcomes presented in Table 3 showed that the relationship between predictors was in line with Model 1, while it was inconsistent for low-sensation-seeking group. Regarding low-sensation-seeking motorcyclists, there was a positive effect of subjective norm on speeding without helmet wearing among them. In other words, the intention and actual behavior of low-sensation-seeking motorcyclists was highly likely to change owing to the advice or recommendation from people who were important to them (e.g. family, spouse, close friends). In addition, although perceived behavioral control (e.g. belief in skills that could meet the challenge, or in capability of manipulating the vehicle without thinking how to do it) seemed to motivate highsensation-seeking group to be involved in speeding without helmet wearing, the same could not be said with low-sensation-seeking group. 5. Conclusion In the context of speeding without helmet wearing among motorcycle rider, this study tested the mechanisms through which TPB variables, psychological flow variables and sensation seeking had a significant effect on intention of speeding without helmet wearing. The analysis revealed that (1) perceived enjoyment and concentration had a positive effect on attitude, (2) attitude, perceived behavioral control, perceived enjoyment and concentration were significant predictors of intention of speeding without helmet wearing, (3) subjective norm proved to have a negative effect on intention of speeding without helmet wearing, (4) there was significantly direct relation between intention of speeding without helmet wearing and actual speeding behavior without helmet wearing. Moreover, the findings indicated that sensation-seeking played important role in clarify the differences among the lowsensation-seeking and high-sensation-seeking group and the whole sample. The finding spurred implication for policy-makers to propose solutions on reduction of speeding without helmet wearing. Specifically, road safety interventions, driver education and training programs, or social campaigns should be designed aiming at (1) both motorcyclist and their close people, (2) perceived behavioral control characteristics to discourage them from the involvement of speeding without helmet, (3) highlighting the benefits of helmet wearing such as health protection, aesthetic values, fashion. 6. Limitation of the study The current research possesses some limitations. Firstly, the survey data are limited, the data was collected in downtown and urban areas in HCMC while respondent living in suburban areas was not included in the sample. Secondly, the coefficients for the paths in question are very small leading to a less robust research finding. Additionally, the research did not consider the young generation aging from 18-21 although this group have tendency to involve in speeding without wearing helmet. Additionally, groups with different social and demographic characteristics like education background, occupation, income levels were not investigated in the study. In fact, group differences in speeding behavior without helmet wearing with respect to these characteristics are believed to be evident, but unfortunately are not investigated in this study due to data unavailability. 7

References [1] Elliott MA, Baughan CJ, Sexton BF 2007 Errors and Violations in Relation to Motorcyclists Crash Risk Accid. Anal. Prev. 39 491 499 [2] Rowland, J., F. Rivara, P. Salzberg, R. Soderberg, R. Maier, and T. Koepsell 1996 Motorcycle helmet use and injury outcome and hospitalization costs from crashes in Washington State American Journal of Public Health 86:41-45 [3] Armitage, C. J., & Conner, M. 2001 Efficacy of the theory of planned behaviour: A meta analytic review British Journal of Social Psychology 40 471 499 [4] Fishbein, M., Ajzen, I. 2010 Predicting and Changing Behavior: The Reasoned Action Approach Taylor & Francis Group: New York, NY, USA [5] Ajzen, I. 1991 The theory of planned behavior Organizational Behavior and Human Decision Processes 50 179 211 [6] Wallen Warner, H., Aberg, L. 2006 Drivers decision to speed: a study inspired by the theory of planned behavior Transportation Research Part F: Traffic Psychology and Behaviour 9 6 427 433 [7] Ambak, K., I. Rozmi, A.R. Atiq and B.M. Nazri 2011 Using structural equation modeling and the behavioral sciences theories in predicting helmet use. Proceeding of International Conference on Advanced Science Engineering and Information Technology, Bangi, Malaysia, pp: 639-645 [8] Chen, Ching-Fu, and Cheng-Wen Chen 2011 Speeding for fun? Exploring the speeding behavior of riders of heavy motorcycles using the theory of planned behavior and psychological flow theory Accident Analysis & Prevention 43.3: 983-990 [9] Moon, J.-W., Kim, Y.-G 2001 Extending the TAM for a World-Wide-Web Context Information & Management 38 4 217 230 [10] Hair, J.F., Black, B., Babin, B., Anderson, R.E., Tatham, R.L. 2006 Multivariate Data Analysis, 6th ed. Pearson Education Inc., NJ. Acknowledgments We wish to thank the reviewers helpful suggestions in improving this paper. Thanks also to the interviewees who were willings to complete the questionnaire used in the research. 8