Original Article

Utilizing Beta Regression in Predicting the Underlying Factors of Motorcycle Rider Behavior

Abstract

Introduction: Motorcyclists have the highest proportion of casualty toll caused by street accidents in Iran, and they endanger themselves and others by those risky behaviors. Health and safety education will not be sufficient without knowing the causes of such behaviors. Since no studies have been carried out based on accurate statistical methods on bounded response variables for motorcyclists' high-risk behaviors in Iran, this study aimed to predict MRBQ by ADHD and the underlying predictors using the Beta Regression as an alternative strategy.

Methods: The present sectional study included 311 Motorcyclists randomly selected using a cluster sampling method in Bukan city to evaluating the relationship between the limited response MRBQ with ADHD and its subscales. We used an innovative beta regression method for the analysis and carried out unadjusted and adjusted modeling.

Results: Direct and significant relationships were observed between MRBQ score and ADHD score and its subscales, including (DSS score) (coefficients ranged over 0.01 to 0.6, All P<0.05). Additionally, the riding period (coefficients ranged over -0.32 to -0.48, P<0.05), hours of riding (coefficients ranged over: 0.31 to 0.34, P<0.05), using the helmet (coefficients: 0.26 to 0.31, P<0.05), and sub-accident (coefficients ranged over 0.35 to 0.37, P<0.05) also turned out to be significant predictors of MRBQ score.

Conclusion: ADHD score and riding parameters can be taken into account when contriving actions on the motorcycle rider behaviors as measured by MRBQ.

1. Ferrando J, Plasència A, Ricart I, Canaleta X, Seguí-Gómez M, editors. Motor-vehicle injury patterns in emergency-department patients in a south-European urban setting. Annual Proceedings/Association for the Advancement of Automotive Medicine; 2000: Association for the Advancement of Automotive Medicine.
2. Mohammad Fam A, Ghazizadeh A. An epidemiological of traffic accident leading to death in Tehran province in 1999. Scientific Journal Kordestan university medical sciences. 2002;6(23):33-5.
3. Oruogi M, Hekmatpou D, Javaheri J. The implication of health belief model to promote the performance of motorcyclists using helmets in Markazi Province (arak) in Iran. Iranian Journal of Epidemiology. 2014;9(3):37-44.
4. World Health Organization Global status report on road safety. 2013. Accessed June 30. Available from: http://www.who.int/violence_injury_prevention/road_safety_status/2013/en/.
5. Montazeri A. Road-traffic-related mortality in Iran: a descriptive study. Public health. 2004;118(2):110-3.
6. Zamani AF, Niknami S, Mohammadi I, Montazeri A, Ahmadi FE, Ghofranipour F, et al. High risk behaviours among Iranian motorcyclists: a qualitative study. 2010.
7. Gordon H. Psychiatry, the law and death on the roads. Advances in Psychiatric treatment. 2004 Nov;10(6):439-45.
8. Trifiletti LB, Gielen AC, Sleet DA, Hopkins K. Behavioral and social sciences theories and models: are they used in unintentional injury prevention research? Health Education Research. 2005;20(3):298-307.
9. Mangus R, Simons CJ, Jacobson LE, Streib EW, Gomez G. Current helmet and protective equipment usage among previously injured ATV and motorcycle riders. Injury prevention. 2004;10(1):56-8.
10. Evans L. The dominant role of driver behavior in traffic safety. American Journal of Public Health. 1996;86(6):784-6.
11. Kopits E, Cropper M. Traffic fatalities and economic growth. 2003.
12. Ranney TA, Mazzae E, Garrott R, Goodman MJ, editors. NHTSA driver distraction research: Past, present, and future. Driver distraction internet forum; 2000.
13. Motevalian SA, Asadi-Lari M, Rahimi H, Eftekhar M, editors. Validation of a persian version of motorcycle rider behavior questionnaire. InAnnals of Advances in Automotive Medicine/Annual Scientific Conference 2011 Oct (Vol. 55, p. 91). Association for the Advancement of Automotive Medicine.
14. Motevalian A. Questionnaire validation motorcyclists driving behavior. MSc thesis in epidemiology, Tehran:Iran university of Medical Sciences; 2010. [Persian].
15. Shappell SA, Wiegmann DA. A human error approach to aviation accident analysis: The human factors analysis and classification system: Ashgate Publishing, Ltd.; 2012.
16. Fathalla MF, Fathalla MM. A practical guide for health researchers: World Health Organization, Regional Office for the Eastern Mediterranean; 2004.
17. Anderson JA. An introduction to neural networks. 1995. Massachusetts Institute of Technology, MA. 1996.
18. Sakashita C, Senserrick T, Lo S, Boufous S, de Rome L, Ivers R. The Motorcycle Rider Behavior Questionnaire: Psychometric properties and application amongst novice riders in Australia. Transportation research part F: traffic psychology and behaviour. 2014;22:126-39.
19. Sadeghi-Bazargani H, Abedi L, Mahini M, Amiri S, Khorasani-Zavareh D. Adult attention-deficit hyperactivity disorder, risky behaviors, and motorcycle injuries: a case-control study. Neuropsychiatric disease and treatment. 2015;11:2049.
20. Safiri S, Sadeghi-Bazargani H, Amiri S, Khanjani N, Safarpour H, Karamzad N, et al. Association between Adult Attention Deficit-Hyperactivity Disorder and motorcycle traffic injuries in Kerman, Iran: a case-control study. Journal of Clinical Research & Governance. 2013;2(1):17-21.
21. Bottai M, Cai B, McKeown RE. Logistic quantile regression for bounded outcomes. Statistics in medicine. 2010;29(2):309-17.
22. Smithson M, Merkle EC. Generalized linear models for categorical and continuous limited dependent variables: Chapman and Hall/CRC; 2013.
23. Babajanpour M, Jafarabadi MA, Bazargani HS. Predictive ability of underlying factors of motorcycle rider behavior: an application of logistic quantile regression for bounded outcomes. Health promotion perspectives. 2017;7(4):230.
24. Elliott MA, Baughan CJ, Sexton BF. Errors and violations in relation to motorcyclists' crash risk. Accident Analysis & Prevention. 2007;39(3):491-9.
25. Özkan T, Lajunen T, Doğruyol B, Yıldırım Z, Çoymak A. Motorcycle accidents, rider behaviour, and psychological models. Accident Analysis & Prevention. 2012;49:124-32.
26. Sadeghi-Bazargani H, Amiri S, Hamraz S, Malek A, Abdi S, Shahrokhi H. Validity and reliability of the Persian version of Conner's adult ADHD rating scales: observer and self-report screening versions. Journal of Clinical Research & Governance. 2014;3(1):42-7.
27. changes%20from%20dsm-iv-tr%20to%20dsm-5.pdf. Accessed May 16, 2015. APAHoCfD-TtD-AfhwdoD.
28. Orsini N, Bottai M. Logistic quantile regression in Stata. Stata Journal. 2011;11(3):327-44.
29. Nazari R, Bijani A, HAJI HF, Beheshti Z, Sharifnia S, Hojati H. Mortality and injury severity in the accident victims referred to the hefdah shahrivar hospital of amol; 2007. 2011.
30. Zhou J-H, Zhao X, Wang Z, Zhu P, Jian H, Liu D, et al. The analysis of epidemiological characteristics of road traffic crashes in a mountain city in western China. Chinese journal of traumatology= Zhonghua chuang shang za zhi. 2003;6(6):355-8.
31. Reeder AI, Chalmers D, Marshall SW, Langley JD. Psychological and social predictors of motorcycle use by young adult males in New Zealand. Social Science & Medicine. 1997;45(9):1357-76.
32. Lardelli-Claret P, Jimenez-Moleon JJ, de Dios Luna-del-Castillo J, García-Martín M, Bueno-Cavanillas A, Gálvez-Vargas R. Driver dependent factors and the risk of causing a collision for two wheeled motor vehicles. Injury Prevention. 2005;11(4):225-31.
33. Watson BC, Tunnicliff DJ, White KM, Schonfeld CC, Wishart DE. Psychological and social factors influencing, motorcycle rider intentions and behaviour.
2007.
34. Yau KK. Risk factors affecting the severity of single vehicle traffic accidents in Hong Kong. Accident Analysis & Prevention. 2004;36(3):333-40.
35. Coopersmith HG, Korner-Bitensky NA, Mayo NE. Determining medical fitness to drive: physicians' responsibilities in Canada. CMAJ: Canadian Medical Association journal. 1989;140(4):375.
36. Watson BC TD, White KM, Schonfeld CC, Wishart DE. Psychological and social factors influencing, motorcycle rider intentions and behaviour. 2007. doi: 10.1016/j.aap.2011.03.012.
37. Davtalab-Esmaeili E, Salari-Lak SH, Sadeghi- Bazargani H. Assessment of Hospital death and determint survival predictors in traffic injury patients in East Azarbaijan. MSc thesis in epidemiology, Tabriz: Tabriz university of Medical Sciences; 2016. [Persian].
38. Gaffari-Fam S, Salari-Lak SH, Sadeghi Bazargani H, Malek A. Investigating of effective factors on pedestrian injuries in road traffic injuries: a casw control study in Tabriz-Iran. MSc thesis in epidemiology, Tabriz: Tabriz university of Medical Sciences; 2015. [Persian].
39. Hatamabadi H, Vafaee R, Haddadi M, Abdalvand A, Esnaashari H, Soori H. Epidemiologic study of road traffic injuries by road user type characteristics and road environment in Iran: a community-based approach. Traffic injury prevention. 2012;13(1):61-4.
40. Chang L-Y, Wang H-W. Analysis of traffic injury severity: An application of non-parametric classification tree techniques. Accident Analysis & Prevention. 2006;38(5):1019-27.
41. McDermott BM, Cvitanovich A. Posttraumatic stress disorder and emotional problems in children following motor vehicle accidents: an extended case series. Australian & New Zealand Journal of Psychiatry. 2000;34(3):446-52.
42. Hervey AS, Epstein JN, Curry JF. Neuropsychology of adults with attention-deficit/hyperactivity disorder: a meta-analytic review. Neuropsychology. 2004;18(3):485.
43. Schoechlin C, Engel RR. Neuropsychological performance in adult attention-deficit hyperactivity disorder: Meta-analysis of empirical data. Archives of Clinical Neuropsychology. 2005;20(6):727-44.
44. Hodgkins P, Montejano L, Sasané R, Huse D. Risk of injury associated with attention-deficit/hyperactivity disorder in adults enrolled in employer-sponsored health plans: a retrospective analysis. The primary care companion to CNS disorders. 2011;13(2).
45. Feizi A, Aliyari R, Roohafza H. Association of perceived stress with stressful life events, lifestyle and sociodemographic factors: a large-scale community-based study using logistic quantile regression. Computational and mathematical methods in medicine. 2012.
46. Agresti A, Kateri M. Categorical data analysis: Springer; 2011.
47. Simas AB, Barreto-Souza W, Rocha AV. Improved estimators for a general class of beta regression models. Computational Statistics & Data Analysis. 2010;54(2):348-66.
48. Schmid M, Wickler F, Maloney KO, Mitchell R, Fenske N, Mayr A. Boosted beta regression. PloS one. 2013;8(4):e61623.
Files
IssueVol 7 No 1 (2021) QRcode
SectionOriginal Article(s)
Published2021-05-15
DOI https://doi.org/10.18502/jbe.v7i1.6291
Keywords
Beta regression Bounded outcomes variables Motorcycle Injuries Adulthood ADHD MRBQ

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
1.
Babajanpour M, Iraji Z, Sadeghi-Bazargani H, Asghari Jafarabadi M. Utilizing Beta Regression in Predicting the Underlying Factors of Motorcycle Rider Behavior. jbe. 7(1):7-24.