Restricted accessResearch articleFirst published online 2024-2
Determinants of Helmet Use Intention Among E-Bikers in China: An Application of the Theory of Planned Behavior,the Health Belief Model,and the Locus of Control
Nearly half of electric biker (e-biker)-related crashes caused head injuries that could be preventable by wearing a helmet. This study proposes an integrated Theory of Planned Behavior, Health Belief Model, and locus of control framework to investigate the underlying psychological factors influencing helmet use intention using survey data in Shanghai. Structural equation model estimation and multiple group analyses were conducted to understand these heterogeneous impacting factors. Health motivation, perceived behavioral control, attitude, cues to action, and internality were identified as five key factors affecting the intention to use a helmet. Subgroups of e-bikers based on their age, education, income, and driver’s license were more susceptible to targeted helmet use strategies for some psychological factors compared to their counterparts. Study insights shed light on the one-size-fits-all strategy limitations and may assist policymakers in designing behavioral interventions and safety education schemes to promote helmet use among e-bikers in China.
PCTT. Anti-Preemptive Driving Report of E-Bikes in China. Pine Cone Think Tank, Shanghai, China, 2022.
2.
Ministry of Industry and Information Technology. Safety Technical Specification for Electric Bicycles. Ministry of Industry and Information Technology, China, 2019.
3.
TABMPS. The People’s Republic of China Road Traffic Accident Annual Statistic Report. Traffic Management Bureau of the Ministry of Public Security, Wuxi, China, 2018.
4.
ZuevD.TyfieldD.UrryJ.Where is the Politics? E-Bike Mobility in Urban China and Civilizational Government. Environmental Innovation and Societal Transitions, Vol. 30, 2019, pp. 19–32.
McDermottF. T.LaneJ. C.BrazenoreG. A.DebneyE. A.The Effectiveness of Bicycle Helmets: A Study of 1710 Casualties. Journal of Trauma, Vol. 34, No. 6, 1993, pp. 834–845.
7.
DeutermannW.Motorcycle Helmet Effectiveness Revisited. DOT HS 809 715. U.A. Department of Transportation, Washington, D.C., 2004.
8.
DeMarcoA. L.ChimichD. D.GardinerJ. C.NightingaleR. W.SiegmundG. P.The Impact Response of Motorcycle Helmets at Different Impact Severities. Accident Analysis & Prevention, Vol. 42, 2010, pp. 1778–1784.
9.
ElvikR.Publication Bias and Time-Trend Bias in Meta-Analysis of Bicycle Helmet Efficacy: A Reanalysis of Attewell, Glase and McFadden, 2001. Accident Analysis & Prevention, Vol. 43, No. 3, 2021, pp. 1245–1251.
10.
ElvikR.Road Safety Management by Objectives: A Critical Analysis of the Norwegian Approach. Accident Analysis & Prevention, Vol. 40, No. 3, 2008, pp. 1115–1122.
ZhangY.WuC.The Effects of Sunshields on Red Light Running Behavior of Cyclists and Electric Bike Riders. Accident Analysis & Prevention, Vol. 52, 2013, pp. 210–218.
13.
KohP. P.WongY. D.ChandrasekarP.Safety Evaluation of Pedestrian Behaviour and Violations at Signalised Pedestrian Crossings. Safety Science, Vol. 70, 2014, pp. 143–152.
14.
YangX.HuanM.Abdel-AtyM.PengY.GaoZ.A Hazard-Based Duration Model for Analyzing Crossing Behavior of Cyclists and Electric Bike Riders at Signalized Intersections. Accident Analysis & Prevention, Vol. 74, 2015, pp. 33–41.
15.
WangX.ChenJ.QuddusM.ZhouW.ShenM.Influence of Familiarity with Traffic Regulations on Delivery Riders’ E-Bike Crashes and Helmet Use: Two Mediator Ordered Logit Models. Accident Analysis & Prevention, Vol. 159, 2021, p. 106277.
16.
AjzenI.The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, Vol. 50, No. 2, 1991, pp. 179–211.
17.
RosenstockI. M.The Health Belief Model and Preventive Health Behavior. Health Education Monographs, Vol. 2, No. 4, 1974, pp. 354–386.
18.
RotterJ. B.Generalized Expectancies for Internal Versus External Control of Reinforcement. Psychological Monographs, Vol. 80, 1966, pp. 1–28.
19.
LajunenT.RäsänenM. Can Social Psychological Models be Used to Promote Bicycle Helmet Use Among Teenagers? A Comparison of the Health Belief Model, Theory of Planned Behavior and the Locus of Control. Journal of Safety Research, Vol. 35, No. 1, 2004, pp. 115–123.
20.
MehriA.MazloomyS.MorowatisharifabadA.NadrianH.Determinants of Helmet Use Behavior Among Employed Motorcycle Riders in Yazd, Iran Based on Theory of Planned Behavior. Injury, Vol. 42, No. 9, 2011, pp. 9–15.
21.
AhmedM.AmbakK.RaqibA.SukorN.Helmet Usage Among Adolescents in Rural Road from the Extended Theory of Planned Behaviour. Journal of Applied Sciences, Vol. 13, 2013, pp. 161–166.
22.
BrijsK.BrijsT.SannS.TrinhT. A.WetsG.RuiterR. A. C.Psychological Determinants of Motorcycle Helmet Use Among Young Adults in Cambodia. Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 26, 2014, pp. 273–290.
23.
GhasemzadehS.BabazadehT.AllahverdipourH.Sadeghi–BazarganiH.KouzekananiK.Cognitive–Behavioral Determinants of Using Helmet by Motorcyclists in A Rural Community. Journal of Transport & Health, Vol. 6, 2017, pp. 548–554.
24.
ZavarehM. F.HezavehA. M.NordfjaernT.Intention to Use Bicycle Helmet as Explained by the Health Belief Model, Comparative Optimism and Risk Perception in an Iranian Sample. Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 54, 2018, pp. 248–263.
25.
QuineL.RutterD. R.ArnoldL.Predicting and Understanding Safety Helmet Use Among Schoolboy Cyclists: A Comparison of the Theory of Planned Behaviour and the Health Belief Model. Psychology and Health, Vol. 13, 1998, pp. 251–269.
26.
AmbakK.IsmailR.AbdullahR. A.RahmatO. K.BorhanM. N.Prediction of Helmet Use Among Malaysian Motorcyclist Using Structural Equation Modeling. InternationalJournal of Basic and Applied Sciences, Vol. 4, No. 10, 2010, pp. 5263–5270.
27.
AghamolaeiT.TavafianS. S.MadaniA.Prediction of Helmet Use Among Iranian Motorcycle Drivers: An Application of the Health Belief Model and the Theory of Planned Behavior. Traffic Injury Prevention, Vol. 12, No. 3, 2011, pp. 239–243.
28.
LuszczynskaA.SchwarzerR.Multidimensional Health Locus of Control: Comments on the Construct and Its Measurement. Journal of Health Psychology, Vol. 10, No. 5, 2005, pp. 633–642.
29.
BrittS.CumbieJ.BellM.The Influence of Locus of Control on Student Financial Behavior. College Student Journal, Vol. 47, No. 1, 2013, pp. 178–184.
30.
KeshavarzS.BaharudinR.Perceived Parenting Style of Fathers and Adolescents’ Locus of Control in A Collectivist Culture of Malaysia: The Moderating Role of Fathers’ Education. Journal of Genetic Psychology, Vol. 174, No. 3, 2013, pp. 253–270.
31.
WitteK.StokolsD.ItuarteP.SchneiderM.Testing the Health Belief Model in a Field Study to Promote Bicycle Safety Helmets. Communication Research, Vol. 20, 1993, pp. 564–586.
32.
ArnoldL.QuineL.Predicting Helmet Use Among Schoolboy Cyclists: An Application of the Health Belief Model. Social Psychology and Health: European Perspectives. Avebury/Ashgate Publishing, Brookfield, VT, 1994.
33.
Sissons-JoshiM.BeckettK.MacFarlaneA.Cycle Helmet Wearing in Teenagers: Do Health Beliefs Influence Behaviour?Archives of Disease in Childhood, Vol. 71, 1994, pp. 536–539.
34.
O’CallaghanF. V.NausbaumS.Predicting Bicycle Helmet Wearing Intentions and Behavior Among Adolescents. Journal of Safety Research, Vol. 37, No. 5, 2006, pp. 425–431.
35.
RossL. T.RossT. P.FarberS.DavidsonC.TrevinoM.HawkinsA.The Theory of Planned Behavior and Helmet Use Among College Students. American Journal of Health Behavior, Vol. 35, No. 5, 2011, pp. 581–590.
36.
BlunchN.Introduction to Structural Equation Modeling Using IBM SPSS Statistics and AMOS. Sage, Los Angeles, CA, 2012.
37.
EverettS. A.PriceJ. H.BerginD. A.GrovesB. W.Personal Goals as Motivators: Predicting Bicycle Helmet Use in University Students. Journal of Safety Research, Vol. 27, No. 1, 1996, pp. 43–53.
38.
BergP.WesterlingR.Bicycle Helmet Use Among Schoolchildren—The Influence of Parental Involvement and Children’s Attitudes. Injury Prevention, Vol. 7, 2001, pp. 218–222.
39.
LajunenT.RäsänenM. Why Teenagers Owning a Bicycle Helmet Do Not Use Their Helmets. Journal of Safety Research, Vol. 32, No. 3, 2001, pp. 323–332.
40.
FuentesC.GrasM. E.Font-MayolasS.BertranC.SullmanM. J. M.BallesterD.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, Vol. 13, No. 5, 2010, pp. 289–296.
41.
RitterN.VanceC.The Determinants of Bicycle Helmet Use: Evidence from Germany. Accident Analysis & Prevention, Vol. 43, No. 1, 2011, pp. 95–100.
42.
TeschkeK.BrubacherJ. R.FriedmanS. M.CriptonP. A.Personal and Trip Characteristics Associated with Safety Equipment Use by Injured Adult Bicyclists: A Cross-Sectional Study. BMC Public Health, Vol. 12, No. 1, 2012, p. 765.
43.
RichardJ. B.ThélotB.BeckF.Evolution of Bicycle Helmet Use and Its Determinants in France: 2000-2010. Accident Analysis & Prevention, Vol. 60, 2013, pp. 113–120.
44.
JewettA.BeckL. F.TaylorC.BaldwinG.Bicycle Helmet Use Among Persons 5 Years and Older in The United States, 2012. Journal of Safety Research, Vol. 59, 2016, pp. 1–7.
45.
PopaI.FerraroO. E.ChiaraO.MorandiA.MontomoliC.Bicycle Helmet Use Patterns in Italy. A Description and Analysis of Survey Data from An Italian Friends of Cycling Association. Accident Analysis & Prevention, Vol. 108, 2017, pp. 268–274.
46.
LedesmaR. D.ShinarD.Valero-MoraP. M.HaworthN.FerraroO. E.Psychosocial Factors Associated with Helmet Use by Adult Cyclists. Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 65, 2019, pp. 376–388.
47.
Shanghai Municipal Transport Commission. The 6th Comprehensive Traffic Survey in Shanghai. Shanghai Municipal Transport Commission, Shanghai, China, 2020.
48.
AndersonJ. C.GerbingD. W.Structural Equation Modeling in Practice: A Review and Recommended Two–Step Approach. Psychological Bulletin, Vol. 103, No. 3, 1988, p. 411.
49.
NunnallyJ. C.BernsteinI. H.Psychometric Theory, 3rd ed.McGraw-Hill, New York, NY, 1994.
50.
FornellC.LarckerD. F.Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, Vol. 18, No. 1, 1981, pp. 39–50.
51.
HairJ. F.Jr.HultG. T. M.RingleC.SarstedtM.A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage, Thousand Oaks, CA, 2016.
52.
HuL. T.BentlerP. M.Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Structural Equation Modeling, Vol. 6, 1999, pp. 1–55.
ArbuckleJ. L.AMOS User’s Guide Version 3.6. SmallWaters Corporation, Chicago, IL, 1997.
55.
CheungG. W.RensvoldR. B.Evaluating Goodness–of–Fit Indexes for Testing Measurement Invariance. Structural Equation Modeling, Vol. 9, 2002, pp. 233–255.
56.
ByrneB. M.Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming. Routledge, New York, NY, 2016.
57.
LeeC. K.NgK. K. H.ChanH. K.ChoyK. L.TaiW. C.ChoiL. S.A Multi-Group Analysis of Social Media Engagement and Loyalty Constructs Between Full-Service and Low-Cost Carriers in Hong Kong. Journal of Air Transport Management, Vol. 73, 2018, pp. 46–57.
58.
WangC.ZhanJ.WangH.YangZ.ChuX.LiuW.WangY.Multi-Group Analysis on the Mechanism of Residents’ Low-Carbon Behaviors in Beijing, China. Technological Forecasting and Social Change, Vol. 183, 2022, p. 121956.
59.
GkartzonikasC.Losada-RojasL. L.ChristS.PyrialakouV. D.GkritzaK.A Multi-Group Analysis of the Behavioral Intention to Ride in Autonomous Vehicles: Evidence from Three US Metropolitan Areas. Transportation, Vol. 102, 2022, pp. 1–41.
60.
ElliottM.ArmitageC.BaughanC.Changing Drivers’ Attitudes: Is There Potential for Changing Drivers’ Behavior?Proc., Paper Presented at: Behavioral Research in Road Safety: Twelft Seminar, London, May 8, 2003.
61.
GardnerB.A Review and Analysis of the Use of ‘Habit’ in Understanding, Predicting and Influencing Health–Related Behaviour. Health Psychology Review, Vol. 9, No. 3, 2015, pp. 277–295.
62.
GuoYPeetaS.Impacts of Personalized Accessibility Information on Residential Location Choice and Travel Behavior. Travel Behaviour and Society, Vol. 19, 2020, pp. 99–111.
63.
HofstedeG.Culture’s Consequences, 2nd ed.Sage, Thousand Oaks, CA, 2001.
64.
RuiterR. A. C.AbrahamC.KokG.Scary Warnings and Rational Precautions: A Review of the Psychology of Fear Appeals. Psychology and Health, Vol. 16, 2001, pp. 613–630.
65.
RuiterR. A. C.VerplankenB.De CremerD.KokG.Danger and Fear Control in Response to Fear Appeals: The Role of Need for Cognition. Basic and Applied Social Psychology, Vol. 26, 2004, pp. 13–24.
66.
CareyR. N.McDermottD. T.SarmaK. M.The Impact of Threat Appeals on Fear Arousal and Driver Behavior: A Meta–Analysis of Experimental Research 1990–2011. PLoS One, Vol. 8, No. 5, 2013, p. e62821.
67.
PetersG. J. Y.RuiterR. A. C.KokG.Threatening Communication: A Critical Re–Analysis and a Revised Meta–Analytic Test of Fear Appeal Theory. Health Psychology Review, Vol. 7, No. 1, 2013, pp. S8–S31.
68.
GuoY.QianX.LeiT.GuoS.GongL.Modeling the Preference of Electric Shared Mobility Drivers in Choosing Charging Stations. Transportation Research Part D: Transport and Environment, Vol. 110, 2022, p. 103399.
69.
LiX.XingG.QianX.GuoY.WangW.ChengC.Subway Station Accessibility and Its Impacts on the Spatial and Temporal Variations of Its Outbound Ridership. Journal of Transportation Engineering, Part A: Systems, Vol. 148, No. 12, 2022, p. 04022106.
70.
FengF.LiX.GuoY.ChenC.Understanding Factors That Impact Ridesourcing Service UUsage Frequency: A Case Study in Shanghai. Transportation Planning and Technology, Vol. 46, No. 2, 2023, pp. 1–20.
71.
YangZ.LiX.GuoY.QianX.Understanding Active Transportation Accessibility’s Impacts on Polycentric and Monocentric Cities’ Housing Price. Research in Transportation Economics, Vol. 98, 2023, p. 101282.
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