Analysis of a driving behavior measurement model using a modified driver behavior questionnaire encompassing texting, social media use, and drug and alcohol consumption

Jomnonkwao, Sajjakaj; Uttra, Savalee; Ratanavaraha, Vatanavongs

doi:10.1016/j.trip.2021.100302

Cited by 18 publications

(11 citation statements)

References 49 publications

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“…Followed by the posting of additional signs for anti-drunk driving campaigns, to reduce fatal crashes. Law enforcement and a campaign against drunk drivers is a regular proceeding, mentioned in previous works, namely, Jomnonkwao et al [70], Se et al [71]. To establish the guidelines for determining campaigns developed by Phillips et al [72], healthy organizations such as the Thai Health Promotion Foundation should use personal communication or roadside media as part of their campaign delivery strategy.…”

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confidence: 99%

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

et al. 2021

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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.

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confidence: 99%

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

et al. 2021

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“…2.2.2 Questionnaire. The DBQ [36] was used to gather data, covering four factors: violations, errors, lapses, and aggressiveness from Jomnonkwao et al [39]. Such factors are unsafe driving behaviors.…”

Section: Plos Onementioning

confidence: 99%

“…Researchers have found that driving behaviors can be classified into four categories: violations, lapses, errors, and aggressiveness. The modified DBQ, which consists of 25 questions with the four factors of violations, errors, lapses, and aggressiveness, was used to evaluate driving behavior in Thailand [ 39 ]; it will be applied in further research for this study.…”

Section: Introductionmentioning

confidence: 99%

Applying multilevel analysis and the Driver Behavior Questionnaire (DBQ) on unsafe actions under a road safety policy

Jomnonkwao

Uttra²,

Khampirat³

et al. 2022

PLoS ONE

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The aims of this research are: to investigate and develop a multilevel analysis of unsafe actions or risky behaviors; to study the influence of road safety policy factors on risky behaviors; and to analyze personal characteristics that influence risky behaviors. Data were collected using 1,474 samples from locations countrywide at the district level, including 76 clusters, via the Driver Behavior Questionnaire (DBQ) and road safety policy. The results indicate that, for the district-level model, the participation factor directly and negatively influenced risky behaviors, and government support indirectly had a negative impact through participation. Thus, people’s participation in the area caused a decrease in unsafe behaviors. Meanwhile, safety policy support in the area partially caused people to participate at a significant level. At the personal level, income, having a driver’s license, past violations, and past accidents significantly affected risky behaviors, especially having a driver’s license, which had a negative influence. This meant that people who had a driver’s license facilitated a positive effect in terms of decreasing risky behaviors, while people with past violations and past accidents influenced this situation positively. The more traffic law violations and accidents the participants had, the more they engaged in unsafe actions. Based on the findings, acknowledging and solving the problem of unsafe driving at a spatial level can address the issue by supporting different measures to help people in the area improve the situation. In addition, we should assist people who have a driver’s license by offering them useful training to decrease traffic law violations and inform them about accidents.

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“…Driving rage has been linked to a higher frequency of driving rule violations (Precht, Keinath, & Krems, 2017), and the use of mobile phones and other devices can constitute driving violations if they are activated and used while driving, therefore constituting distracting agents while driving, from the perspective of cognitive load due to multitasking. Texting or calling while driving are actions associated to major risk of driving violations and errors (Shaaban, Gaweesh, & Ahmed, 2020;Jomnonkwao, Uttra, & Ratanavaraha, 2021), however, the relationship between anger and the use of technologies that guide the route to reach the destination has not been studied. The third objective is to recognize the relationship between the use of technologies and the level of subjective well-being as mental health indicators, as these technologies promise shorter driving and journey times that have been associated with fewer negative emotions (Feng & Boyle, 2014;Morris & Guerra, 2015).…”

Section: Introductionmentioning

confidence: 99%

Use of mobile technologies for driving, road accidents, health and psychological variables in Colombian drivers

Pérez

Rodríguez²

2022

Rev. colomb. psicol.

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The aim of this investigation is to show the relationships between the use of Mobile Driving Applications and Devices (mdad) with self-reported road accidents, anger, physical health, and subjective wellbeing, in three types of Colombian drivers. The sample is non-randomized (n = 1149) and 93.2% are male drivers. Results showed that (a) for professional drivers, there is an inverse correlation between the use of mdad with lower driving frequency during weekdays and a higher educational level, (b) for occasional drivers, gps use was directly associated with fatal road accidents and low driving frequency during weekdays, (c) for private drivers, correlations were found between mdad broader usage, higher levels of both aggression and perceived driving difficulty as well as physical health problems mainly hypertension and diabetes. It is necessary to conduct in-depth research on mdad uses, health, and driving styles, by controlling social desirability.

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Analysis of a driving behavior measurement model using a modified driver behavior questionnaire encompassing texting, social media use, and drug and alcohol consumption

Cited by 18 publications

References 49 publications

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

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

Applying multilevel analysis and the Driver Behavior Questionnaire (DBQ) on unsafe actions under a road safety policy

Use of mobile technologies for driving, road accidents, health and psychological variables in Colombian drivers

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