The determinants of motorcyclists helmet use: Urban arterial road in Khon Kaen City, Thailand

Unveiling the road to safety: Understanding the factors influencing motorcycle accidents among riders in rural Chiang Mai, Thailand

Background

Motorcycle accidents pose a significant threat to traffic safety in Thailand, particularly in rural areas where the severity of these accidents often results in prolonged medical treatment and a reduction in the quality of life of the affected individual.

Objectives

To investigate the prevalence and the factors associated with motorcycle accidents among motorcycle riders in rural areas in Chiang Mai, Thailand.

Method

A cross-sectional study was conducted from December 2022 to March 2023 via an anonymous survey in Chiang Mai, Thailand. A total of 308 participants engaged with the survey. The data about background information, motorcycle details, personal protective equipment, risky behaviors, attitude toward riding, and history of motorcycle accidents in the prior six months were collected and analyzed by binary logistic regression.

Results

Of 308 participants, the mean age was 56 years old (SD = 14.2), females were 56.8 % (N = 175), 51 % had co-morbidity, and 40.6 % were active alcohol drinkers. The prevalence of individuals who experienced a motorcycle accident within the previous six months was 57.1 %. Notably, the most unsafe riding behavior was not wearing a helmet while riding, which had a prevalence of more than 80 % in both the accident and non-accident groups. The study found significant associated factors for motorcycle accidents in rural communities, including the history of alcohol consumption (aOR 1.71, 95 % CI: 1.05,2.79), changing lanes without using turn signals (aOR 1.93, 95 % CI: 1.07,3.48) and those who strongly disagree with the notion that listening to music while riding is dangerous (aOR 2.80, 95 % CI: 1.06, 7.43).

Conclusion

Over half of motorcycle riders have been in accidents. These findings emphasize the need to enforce drunk-driving and traffic laws. Comprehensive motorcycle rider education and safety training are needed to encourage responsible riding.

Determinants of switching behavior to wear helmets when riding e-bikes, a two-step SEM-ANFIS approach

E-bikes have become one of China's most popular travel modes. The authorities have issued helmet-wearing regulations to increase wearing rates to protect e-bike riders' safety, but the effect is unsatisfactory. To reveal the factors influencing the helmet-wearing behavior of e-bike riders, this study constructed a theoretical Push-Pull-Mooring (PPM) model to analyze the factor's relationship from the perspective of travel behavior switching. A two-step SEM-ANFIS method is proposed to test relationships, rank importance and analyze the combined effect of psychological variables. The Partial Least Squares Structural Equation Model (PLS-SEM) was used to obtain the significant influencing factors. The Adaptive Network-based Fuzzy Inference System (ANFIS), a nonlinear approach, was applied to analyze the importance of the significant influencing factors and draw refined conclusions and suggestions from the analysis of the combined effects. The PPM model we constructed has a good model fit and high model predictive validity (GOF = 0.381, R² = 0.442). We found that three significant factors tested by PLS-SEM, perceived legal norms (β = 0.234, p < 0.001), perceived inconvenience (β = -0.117, p < 0.001) and conformity tendency (β = 0.241, p < 0.05), are the most important factors in the effects of push, mooring and pull. The results also demonstrated that legal norm is the most important factor but has less effect on people with low perceived vulnerability, and low subjective norms will make people with high conformity tendency to follow the crowd blindly. This study could contribute to developing refined interventions to improve the helmet-wearing rate effectively.

Temporal Instability of Motorcycle Crash Fatalities on Local Roadways: A Random Parameters Approach with Heterogeneity in Means and Variances

Motorcycle accidents can impede sustainable development due to the high fatality rate associated with motorcycle riders, particularly in developing countries. Although there has been extensive research conducted on motorcycle accidents on highways, there is a limited understanding of the factors contributing to accidents involving the most commonly used motorcycles on local roads. This study aimed to identify the root causes of fatal motorcycle accidents on local roads. The contributing factors consist of four groups: rider characteristics, maneuvers prior to the crash, temporal and environmental characteristics, and road characteristics. The study employed random parameters logit models with unobserved heterogeneity in means and variances while also incorporating the temporal instability principle. The results revealed that the data related to motorcycle accidents on local roads between 2018 and 2020 exhibited temporal variation. Numerous variables were discovered to influence the means and variances of the unobserved factors that were identified as random parameters. Male riders, riders over 50 years old, foreign riders, and accidents that occurred at night with inadequate lighting were identified as the primary factors that increased the risk of fatalities. This paper presents a clear policy recommendation aimed at organizations and identifies the relevant stakeholders, including the Department of Land Transport, traffic police, local government organizations, and academic groups.

Unhelmeted Riding, Drunk Riding, and Unlicensed Riding among Motorcyclists: A Population Study in Taiwan during 2011-2016

This study aimed to investigate the association between drunk riding, unhelmeted riding, unlicensed riding, and running-off-road (ROR) crashes. Multiple logistic regression was used to calculate the adjusted odds ratio (AOR) by using the National Taiwan Traffic Crash Dataset for 2011-2016. The results revealed that unhelmeted riding was associated with 138% (AOR = 2.38; CI (confidence interval) = 2.34-2.42) and 47% (AOR = 1.47; CI = 1.45-1.49) higher risks of drunk riding and unlicensed riding, respectively. The risk of unhelmeted riding increased with blood alcohol concentrations (BACs), and riders with the minimum BAC (0.031-0.05%) had nearly five times (AOR = 4.99; CI = 4.74-5.26) higher odds of unlicensed riding compared with those of riders with a negative BAC. Unhelmeted riding, drunk riding, and unlicensed riding were associated with 1.21 times (AOR = 1.21; CI = 1.13-1.30), 2.38 times (AOR = 2.38; CI = 2.20-2.57), and 1.13 times (AOR = 1.13; CI = 1.06-1.21) higher odds of ROR crashes, respectively. The three risky riding behaviours (i.e., unhelmeted riding, drunk riding, and unlicensed riding) were significantly related to ROR crashes. The risk of unhelmeted riding and ROR crashes increased with BACs.

Effective factors of improved helmet use in motorcyclists: a systematic review

BACKGROUND

Road traffic injuries (RTI) are one of the most prominent causes of morbidity and mortality, especially among children and young adults. Motorcycle crashes constitute a significant part of RTIs. Policymakers believe that safety helmets are the single most important protection against motorcycle-related injuries. However, motorcyclists are not wearing helmets at desirable rates. This study systematically investigated factors that are positively associated with helmet usage among two-wheeled motorcycle riders.

METHODS

We performed a systematic search on PubMed, Scopus, Web of Science, Embase, and Cochrane library with relevant keywords. No language, date of publication, or methodological restrictions were applied. All the articles that had evaluated the factors associated with helmet-wearing behavior and were published before December 31, 2021, were included in our study and underwent data extraction. We assessed the quality of the included articles using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist for observational studies.

RESULTS

A total of 50 articles were included. Most evidence suggests that helmet usage is more common among drivers (compared to passengers), women, middle-aged adults, those with higher educations, married individuals, license holders, and helmet owners. Moreover, the helmet usage rate is higher on highways and central city roads and during mornings and weekdays. Travelers of longer distances, more frequent users, and riders of motorcycles with larger engines use safety helmets more commonly. Non-helmet-using drivers seem to have acceptable awareness of mandatory helmet laws and knowledge about their protective role against head injuries. Importantly, complaint about helmet discomfort is somehow common among helmet-using drivers.

CONCLUSIONS

To enhance helmet usage, policymakers should emphasize the vulnerability of passengers and children to RTIs, and that fatal crashes occur on low-capacity roads and during cruising at low speeds. Monitoring by police should expand to late hours of the day, weekends, and lower capacity and less-trafficked roads. Aiming to enhance the acceptance of other law-abiding behaviors (e.g., wearing seat belts, riding within the speed limits, etc.), especially among youth and young adults, will enhance the prevalence of helmet-wearing behavior among motorcycle riders. Interventions should put their focus on improving the attitudes of riders regarding safety helmets, as there is acceptable knowledge of their benefits.

10 city analysis of child passenger helmet use

INTRODUCTION

Road traffic injuries are the leading cause of death in children over age five. Most of these deaths occur in low- and middle-income countries. Vulnerable road users, such as motorcyclists and their passengers, are at higher risk. Helmets have significantly decreased morbidity and mortality for motorcyclists; however, they are often unused. The second phase of the Bloomberg Philanthropies Initiative for Global Road Safety was launched in 2015 to improve road safety in 10 cities. This study focuses on child passenger helmet use data from that study to understand the prevalence of helmet use and factors that are associated with helmet use.

METHODS

The 10 cities selected were Accra, Addis Ababa, Bandung, Bangkok, Bogota, Fortaleza, Ho Chi Minh City, Mumbai, Sao Paulo, and Shanghai. Eight rounds of roadside observational data were collected from February 2015 to April 2019. Observers noted correct child motorcycle passenger helmet use and other site observations including weather patterns, traffic volume, and road surface conditions. A multivariable Poisson regression model was used to examine correct helmet use trends over time. A multivariable logistic regression model was fitted for correct child passenger helmet use in all cities controlling for weather, observation time, number of passengers, and driver's correct helmet use.

RESULTS

This dataset contained 99,846 motorcycle child passenger observations across the 10 cities. The highest prevalence of correct child passenger helmet use was in Sao Paulo at 97.33%. Six cities had under 25% correct helmet use for child passengers. Examining helmet use over time, only five cities had a significant increase, four cities had no change, and Ho Chi Minh City demonstrated a decrease. In the multivariable regression model, child passengers had higher odds of wearing helmets in adverse weather conditions, early mornings, if the driver wore a helmet, and if there were fewer passengers.

CONCLUSIONS

The prevalence of correct child passenger helmet utilization shows large variation globally and is concerningly low overall. Enhanced enforcement in combination with media campaigns may have contributed to increasing helmet use prevalence over time. Further research is needed to understand reasons for low child passenger helmet use in most cities.

Salleh MF, Salameh AA, Makhbul ZKM. Predicting the Mass Adoption of eDoctor Apps During COVID-19 in China Using Hybrid SEM-Neural Network Analysis

Technology plays an increasingly important role in our daily lives. The use of technology-based healthcare apps facilitates and empowers users to use such apps and saves the burden on the public healthcare system during COVID-19. Through technology-based healthcare apps, patients can be virtually connected to doctors for medical services. This study explored users' intention and adoption of eDoctor apps in relation to their health behaviors and healthcare technology attributes among Chinese adults. Cross-sectional data were collected through social media, resulting in a total of 961 valid responses for analysis. The hybrid analysis technique of partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) analysis was applied. The obtained results revealed the significant influence of eDoctor apps in terms of usefulness, compatibility, accuracy, and privacy on users' intention to use eDoctor apps. Intention and product value were also found to suggestively promote the adoption of eDoctor apps. This study offered practical recommendations for the suppliers and developers of eHealth apps to make every attempt of informing and building awareness to nurture users' intention and usage of healthcare technology. Users' weak health consciousness and motivation are notable barriers that restrict their intention and adoption of the apps. Mass adoption of eDoctor apps can also be achieved through the integration of the right technology features that build the product value and adoption of eDoctor apps. The limitations of the current study and recommendations for future research are presented at the end of this paper.

Analysis of Crash Frequency and Crash Severity in Thailand: Hierarchical Structure Models Approach

Currently, research on the development of crash models in terms of crash frequency on road segments and crash severity applies the principles of spatial analysis and heterogeneity due to the methods’ suitability compared with traditional models. This study focuses on crash severity and frequency in Thailand. Moreover, this study aims to understand crash frequency and fatality. The result of the intra-class correlation coefficient found that the spatial approach should analyze the data. The crash frequency model’s best fit is a spatial zero-inflated negative binomial model (SZINB). The results of the random parameters of SZINB are insignificant, except for the intercept. The crash frequency model’s significant variables include the length of the segment and average annual traffic volume for the fixed parameters. Conversely, the study finds that the best fit model of crash severity is a logistic regression with spatial correlations. The variances of random effect are significant such as the intersection, sideswipe crash, and head-on crash. Meanwhile, the fixed-effect variables significant to fatality risk include motorcycles, gender, non-use of safety equipment, and nighttime collision. The paper proposes a policy applicable to agencies responsible for driver training, law enforcement, and those involved in crash-reduction campaigns.

Prevalence of unprotected motorcycle riding and its association with other risk behaviors among adolescents in Chiang Mai, Thailand

OBJECTIVES

To determine the prevalence of helmet use in Chiang Mai province in Thailand and identify the association between helmet use, externalized behaviors, and other risk-taking behaviors.

METHODS

A cross-sectional study was conducted using the Youth Risk Behavior Survey, Thai version. Risky motor vehicle behaviors and other risk-taking behaviors of 4,372 adolescents were measured. Behavioral problems from the Youth Self-Report were also obtained from all participants.

RESULTS

A total of 2,981 adolescents (68.2%) reported motorcycle riding, of which, 36.3% reported unprotected riding. Females, younger age, attending secondary school, and those with academic underachievement were related to the unprotected riding group. Unprotected riding was significantly associated with other risky traffic behaviors and also related to other risk-taking behavior such as violence and substance use. Significantly higher behavioral problems scores were found in unprotected riding adolescents (p < 0.001).

CONCLUSIONS

The prevalence of unprotected riding and other risk behaviors in Thai adolescents were high. Safety traffic riding campaigns should start in late primary school focusing on those females with poor academic achievement.

Change in helmet use behavior enforced by CCTV cameras with automatic helmet use detection system on an urban arterial road

OBJECTIVE

Many developing countries experience a high death toll among motorcycle users (both drivers and passengers), primarily due to a relatively low rate of helmet use resulting from ineffective helmet law enforcement. The objectives of this study are to explore the change in helmet use behavior due to helmet use enforcement by closed-circuit television (CCTV) camera technology with an automatic helmet use detection system and to identify the factors associated with helmet use along an urban arterial road in the city of Khon Kaen, Thailand.

METHODS

Data collection was carried out on 49,128 samples by video cameras installed at 5 signalized intersections during 2 periods, namely, before and during the CCTV camera enforcement. The study applied logistic regression analysis to determine factors associated with helmet use and to compare the ratio of helmet use for each variable according to the odds ratio.

RESULTS

The study found that CCTV camera enforcement could increase helmet usage at all study intersections by 5.3%. The results imply that 4 factors, including riding status, number of passengers, day of week, and traffic conditions, significantly affected helmet use both before and during the CCTV camera enforcement. Remarkably, 2 more variables, age and police inspection, significantly affected helmet use during the CCTV camera enforcement period.

CONCLUSIONS

This study confirms that CCTV camera enforcement can be an important driving force for changing helmet use behavior, particularly for child passengers. Moreover, CCTV camera enforcement can support enforcement by extending coverage to a 24-h period and to intersections without police inspection.