Driver prototypes and behavioral willingness: Young driver risk perception and reported engagement in risky driving

A novel hazard avoidance model based on young drivers' characteristics: A driving simulator study

This paper aims to examine the key factors influencing young drivers' hazard avoidance in Iran. In this study, a hazard avoidance index is defined and calculated for investigating the effect of impulsiveness, behavioral, and psychological characteristics on driving hazard avoidance. A questionnaire and go-no-go and flanker computer tests as well as a driving simulator are used for collecting data from 173 Iranian drivers under the age of 30. For this purpose, different scenarios were used, such as pedestrian crossing, the presence of fixed obstacles, and animals crossing the road, whose various characteristics are also changed. Structural equation modeling and the partial least squares method are applied for investigating the relationship between different variables and the hazard avoidance index. The results show that the driver hazard avoidance index is mostly affected by variables such as inhibitory control, opposite directional response, attentional impulsiveness, motion impulsiveness, non-planning impulsiveness, disregarding the law, and lapses and error. The results could help policymakers to assess diving hazard avoidance and improve training programs related to traffic safety based on the variables that are more effective on inexperienced and novice drivers' hazard avoidance.

Comparing attentional disengagement between Prolific and MTurk samples

Attention often disengages from primary tasks in favor of secondary tasks (i.e., multitasking) and task-unrelated thoughts (i.e., mind wandering). We assessed whether attentional disengagement, in the context of a cognitive task, can substantially differ between samples from commonly used online participant recruitment platforms, Prolific and Mechanical Turk (MTurk). Initially, eighty participants were recruited through Prolific to perform an attention task in which the risk of losing points for errors was varied (high risk = 80% chance of loss, low risk = 20% chance of loss). Attentional disengagement was measured via task performance along with self-reported mind wandering and multitasking. On Prolific, we observed surprisingly low levels of disengagement. We then conducted the same experiment on MTurk. Strikingly, MTurk participants exhibited more disengagement than Prolific participants. There was also an interaction between risk and platform, with the high-risk group exhibiting less disengagement, in terms of better task performance, than the low-risk group, but only on MTurk. Platform differences in individual traits related to disengagement and relations among study variables were also observed. Platform differences persisted, but were smaller, after increasing MTurk reputation criteria and remuneration in a second experiment. Therefore, recruitment platform and recruitment criteria could impact results related to attentional disengagement.

Extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior

Low-speed driving is an underestimated dangerous behavior that may cause safety issues, such as speed dispersion and traffic flow bottlenecks. To investigate the influence mechanism of low-speed driving behavior, this study constructed the low-speed specific model (LSSM) by extending theory of planned behavior (TPB). The LSSM incorporated two factors, namely, risk perception and behavior habit, into the standard TPB components (attitude, subjective norm, perceived behavioral control, and behavior intention). Web-based questionnaires were used to collect data from a valid sample of 374, of which males accounted for 50%. The participants were aged from 18 to 65 years (M = 35.40, SD = 0.88). The structural equation model was applied to calculate and validate the interrelationships among the components of LSSM. Results showed that the LSSM could explain the variance in low-speed driving behavior and behavior intention by 46% and 76%, respectively. Meanwhile, attitude (β = 0.52, p < 0.001) and behavior habit (β = 0.48, p < 0.001) had the strongest positive influence and prediction power over low-speed driving behavior, respectively, whereas subjective norm (β = 0.05, p > 0.01) and perceived behavioral control (β = -0.12, p > 0.01) showed few significant in influencing the intention. LSSM also showed that people who were sensitive to driving risk perception would avoid low-speed driving behaviors and attitudes. Our findings may provide theoretical support for interventions on low-speed driving behavior.

Relations between risk perception, perceptions of peers' driving, and risky driving among Cambodian adolescents

Introduction

Traffic accidents are a leading cause of death globally, with substantial economic impact particularly in low-and-middle-income countries (LMIC). Adolescents are at particular risk, partly due to their tendency to engage in risky driving. However, most research designed to identify potential causes of risky adolescent driving has been conducted in Western, high-income countries, which often have substantial cultural differences from LMIC that potentially influence risky adolescent driving.

Methods

The present study, one of the first focused on this topic in Southeast Asia, cross-sectionally assessed 425 adolescent motorbike drivers in the Southeast Asian LMIC Cambodia. Adolescents' (a) beliefs about peers' driving (social norms) and (b) driving risk perception were assessed as predictors of four risky driving behaviors: aggressive driving; distracted driving; intoxicated driving; violating driving laws.

Results

Canonical correlation analysis identified a general relation between (a) beliefs about peers' driving, and (b) all four risky driving behaviors, with R2 = 0.35 indicating over one-third of the variance in risky driving was explained by perceptions of peers' driving. Risk perception was not involved in the significant canonical relation, however. Gender moderated two of the underlying relations, with females showing larger relations between perceptions of friends' driving, and distracted driving and violating driving laws.

Discussion

These findings provide useful directions for future research (e.g., assessing the accuracy of Cambodian adolescents' perceptions of peers' driving) useful for helping stakeholders tailor road safety programs (e.g., providing adolescent drivers with accurate information regarding their peers' actual driving behaviors) for adolescent motorcyclists in Cambodia and similar countries.

How Does Being under the Influence Affect Willingness to Experience Overlapping Effects of Alcohol and Marijuana?

OBJECTIVE

This study tested how individuals anticipate they will respond to opportunities to engage in simultaneous alcohol and marijuana (SAM) use.

METHODS

Two studies utilizing a within-subjects design were conducted. Study 1 was conducted in Spring 2021 and a replication (Study 2) was conducted in Fall 2021. Participants were presented with pairs of scenarios. One scenario pair compared how willing participants expected to be to get drunk if they were sober vs. high. Another pair compared how willing participants would be to take a hit of marijuana if they were sober vs. drunk. College attending young adults (Study 1: N = 173; female = 81%; Study 2: N = 212; female = 49.1%) with varying degrees of substance use experience were recruited.

RESULTS

In Study 1 participants reported greater willingness to get drunk when sober than when high. This was qualified by a statistically significant interaction whereby differences were greater among those who had more experience with past 30-day heavy drinking. Similar findings emerged for willingness to use marijuana. Participants anticipated greater willingness to use marijuana when sober than when drunk. This was also qualified by a statistically significant interaction whereby differences were greater among experimental or established users of marijuana than among abstainers. Study 2 findings replicated those from Study 1.

CONCLUSIONS

College attending young adults state greater willingness to remain under the influence of one substance than to engage in SAM use when opportunities arise. Simultaneous use of alcohol and marijuana among college students is likely an exception, not the rule. Implications for prevention are discussed.

The prototype willingness model: An application to adolescent driver speeding

INTRODUCTION

Many young drivers are involved in crashes due to speeding. Some studies have used the Prototype Willingness Model (PWM) to explain the risky driving behavior of young people. However, many have measured PWM constructs in a manner inconsistent with its formulation. The PWM asserts that the social reaction pathway is underpinned by a heuristic comparison of oneself with a cognitive prototype of someone who engages in a risky behavior. This proposition has not been comprehensively examined and few PWM studies specifically examine social comparison. The current study investigates intentions, expectations, and willingness to speed by teen drivers using operationalizations of PWM constructs more aligned with their original conceptualizations. Additionally, the influence of dispositional social comparison tendency on the social reaction pathway is examined to further test the original propositions underpinning the PWM.

METHOD

Two hundred and eleven independently driving adolescents completed an online survey including items measuring PWM constructs and social comparison tendency. Hierarchical multiple regression was used to investigate the influence of perceived vulnerability, descriptive and injunctive norms, and prototypes on speeding intentions, expectations, and willingness. A moderation analysis examined the effect of social comparison tendency on the association between prototype perceptions and willingness.

RESULTS

The regression models explained substantial amounts of variance in intentions (39%), expectations (49%), and willingness (30%) to speed. There was no evidence that social comparison tendency influences the relationship between prototypes and willingness.

CONCLUSIONS

The PWM is useful for predicting teenage risky driving. More studies should confirm that social comparison tendency does not moderate the social reaction pathway. However, there may be need for further theoretical development of the PWM.

PRACTICAL APPLICATIONS

The study suggests that it may be possible to develop interventions to reduce adolescent driver speeding based on manipulation of PWM constructs such as speeding driver prototypes.

Intentions and willingness to engage in risky driving behaviour among high school adolescents: evaluating the bstreetsmart road safety programme

OBJECTIVE

To investigate the impact of a road safety programme on adolescents' willingness to engage in risky behaviour as probationary drivers, adjusted for covariates of interest.

METHOD

The bstreetsmart is a road safety programme delivered to around 25 000 adolescent students annually in New South Wales. Using a smartphone-based app, student and teacher participation incentives, students were surveyed before and after programme attendance. Mixed-methods linear regression analysed pre/post-modified Behaviour of Young Novice Driver (BYNDS_M) scores.

RESULTS

2360 and 1260 students completed pre-event and post-event surveys, respectively. Post-event BYNDS_M scores were around three points lower than pre-event scores (-2.99, 95% CI -3.418 to -2.466), indicating reduced intention to engage in risky driving behaviours. Covariates associated with higher stated intentions of risky driving were exposure to risky driving as a passenger (1.21, 95% CI 0.622 to 2.011) and identifying as non-binary gender (2.48, 95% CI 1.879 to 4.085), adjusting for other predictors.

CONCLUSIONS

Trauma-informed, reality-based injury prevention programmes can be effective in changing short-term stated intentions to engage in risky driving, among a pre-independent driving student population. The adolescent novice driver age group is historically challenging to engage, and injury prevention action must be multipronged to address the many factors influencing their behaviour.

Road users' engagement in prosocial and altruistic behaviors: A systematic review

INTRODUCTION

Engagement in prosocial and altruistic on-road behaviors is a new area of research with potential safety benefits for road users. This paper systematically reviewed studies on road users' engagement in prosocial and altruistic behaviors to provide guidance regarding the next steps in this area of research, particularly to inform targeted interventions. The objective was to identify the types of on-road prosocial and altruistic behaviors that have been studied, and the factors associated with these behaviors. Road users were defined as drivers, passengers, or vulnerable road users (e.g., pedestrian, motorcyclists, and bicyclists).

METHOD

The database search was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRIMSA) guidelines and was conducted in June 2021. A total of 23,090 articles were identified in four databases including APA PsycINFO, Embase, Web of Science, and the Transportation Research Information Database. Eleven articles (13 studies) published between 2004 and 2021 met the inclusion criteria and were included in the review.

RESULTS

Six studies focused on intervening behaviors, specifically relating to passengers' willingness or intentions to speak up to a driver engaging in unsafe driving behaviors, four studies focused on drivers' yielding behaviors at crosswalks, and one study each focused on altruistic driving behaviors, prosocial driving behavior at long-wait stops, and prosocial behavior towards cyclists. Studies typically examined characteristics of the prosocial road user, including self-esteem, efficacy, and subjective norms, as well as contextual factors, such as other road users' behaviors and on-road messaging.

CONCLUSIONS

This review highlights specific factors that may predict road users' engagement in prosocial and altruistic on-road behaviors.

PRACTICAL APPLICATIONS

The outcomes from this review may be used to guide the development of future road safety public education messages designed to encourage greater participation in prosocial and altruistic on-road behaviors that act to benefit all road users.

Demographics of road injuries and micromobility injuries among China, India, Japan, and the United States population: evidence from an age-period-cohort analysis

BACKGROUND

Micromobility sharing platforms have involved skyrocketing numbers of users in multiple countries since 2010. However, few studies have examined the overall impact of the growing micromobility market on road injuries.

METHOD

We use road injury data from the Global Burden of Disease Study database to examine the effect of age, period, and cohort on micromobility injury-related deaths and incidence. We compared four countries that vary in demographic background and road infrastructure. By comparing the countries, we analyzed the relationship between the trends in road injuries and these factors.

RESULTS

We found an overall upward trend in micromobility injuries. A higher risk of micromobility-related injuries was witnessed in China and the US in 2015-2019, and people older than 45 showed a growing micromobility-related mortality and incidence rate in China, India, and the US. Cohorts after 1960 showed higher micromobility injury incidence risks in China and India, but the population born after 1990 in India showed a slightly lower risk compared to those before it.

CONCLUSIONS

The boosted usage of micromobility devices explains these increasing trends. Road infrastructure and separated traffic ease the collisions from micromobility devices. The overall situation calls for improvement in legislation as well as road infrastructure.

Underestimated Risk Perception Characteristics of Drivers Based on Extended Theory of Planned Behavior

Aggressive driving behaviors due to drivers’ underestimation of risks are one of the major causes of traffic accidents. Due to the complexity of factors influencing risk perception, the mechanism of risk underestimation remains unclear. In this study, the theory of planned behavior (TPB) was extended by adding a new variable, namely drivers’ normlessness, forming an extended TPB (ETPB) framework to analyze the factors influencing risk underestimation and the extent of their influence. A total of 376 drivers’ perceived characteristics of risk underestimation were collected through an online survey, and a structural equation model was applied to investigate the effects of normlessness, behavioral attitudes, subjective norm, and perceived behavioral control on the tendency to underestimate the risk. The results showed that the ETPB model can explain the variance in the underestimation risk behavior by 69%; perceptual behavior control, attitude, and subjective norm (in descending order) had significant positive effects on driver’s tendency to underestimate risk; the normlessness variable can directly promote attitude and underestimated risk behavior; drivers with low annual mileage, complete insurance coverage, and no prior accident experience were more likely to underestimate driving risk. The study contributes to understanding of risk perception characteristics and provide theoretical basis for reducing underestimated risk behavior.

The Analysis of Spatial Patterns and Significant Factors Associated with Young-Driver-Involved Crashes in Florida

Over the last three decades, traffic crashes have been one of the leading causes of fatalities and economic losses in the U.S.; compared with other age groups, this is especially concerning for the youth population (those aged between 16 and 24), mostly due to their inexperience, greater inattentiveness, and riskier behavior while driving. This research intends to investigate this issue around selected Florida university campuses. We employed three methods: (1) a comparative assessment for three selected counties using both planar Euclidean Distance and Roadway Network Distance-based Kernel Density Estimation methods to determine high-risk crash locations, (2) a crash density ratio difference approach to compare the maxima-normalized crash densities for the youth population and those victims that are 25 and up, and (3) a logistic regression approach to identify the statistically significant factors contributing to young-driver-involved crashes. The developed GIS maps illustrate the difference in spatial patterns of young-driver crash densities compared to those for other age groups. The statistical findings also reveal that intersections around university areas appear to be significantly problematic for youth populations, regardless of the differences in the general perspective of the characteristics of the selected counties. Moreover, the speed limit countermeasures around universities could not effectively prevent young-driver crash occurrences. Hence, the results of this study can provide valuable insights to transportation agencies in terms of pinpointing the high-risk locations around universities, assessing the effectiveness of existing safety countermeasures, and developing more reliable plans with a focus on the youth population.

Effects of an integrated collision warning system on risk compensation behavior: An examination under naturalistic driving conditions

Collision warning systems can improve traffic safety, while their safety benefit may be lessened due to improper risk compensation or system misuse. There are limited studies of advanced safety systems increasing unexpected risky driving behavior, especially with adolescent drivers. This study is designed to address this research gap in two main areas: 1) it seeks to examine whether and how the introduction of advanced driver-assistance systems influences drivers' risk compensation behavior (e.g., increase of hard braking frequency), and 2) it investigates key factors (e.g., distraction) that contribute to changes in hard braking frequency during driving for both teen and adult drivers. Naturalistic driving data from two previous studies were analyzed in this study with two methods: a hierarchical logistic regression model was used to evaluate the effects of an integrated collision warning system on hard braking behavior, while a Random forests algorithm was applied to model hard braking behavior and to rank the contributing factors by calculating the importance scores. No statistical evidence was observed that the integrated collision warning system significantly changed the likelihood of hard braking for teen or adult drivers. Other factors like distraction, especially visual-manual distraction, had the largest impact on the hard braking behavior, followed by speeding and roadway segments (i.e., at intersections or not). Short time-headways and driving in high-density traffic significantly increased the likelihood of hard braking. Furthermore, the rate of hard braking behavior on surface roads was much higher than on highways, as expected. Compared with straight road segments, hard braking behavior was less likely to occur on curve roads. This study applied an analytical strategy by using both machine learning and statistical analysis methods to achieve high model accuracy and facilitate inference concerning the relationships among variables. Findings in this study can help to improve the design of integrated collision warning systems and the use of autonomous braking systems, and to apply appropriate analysis methods in understanding teen drivers' behavior changes with those safety systems.

Research on factors affecting the risk-taking behavior of personnel working in the forest products sector

Objectives. The fact that occupational accidents are a permanent problem in the forest products sector encouraged this research to be conducted on the factors affecting the risk-taking behavior (RTB) of employees in the sector. Understanding the RTB of employees in the sector would help managers to reduce occupational accidents and to develop effective safety interventions. Therefore, this study aimed to determine the effects of individual, organizational and workplace factors and sub-factors on the RTB of employees by using the structural equation model (SEM). Methods. A survey was conducted on 623 employees of the forest products sector in 64 enterprises in the provinces of Düzce, Bolu, Sakarya, Kocaeli and Yalova. Results. The results revealed that organizational and workplace factors had a significant effect on the RTB of the employees. However, no effect was found for individual factors, although the sub-factor of cognitive bias had a positive impact on RTB. In contrast, safety climate, safety training, use of personal protective equipment (PPE)-1 and working conditions negatively impacted the RTB of the employees. Conclusions. In terms of occupational health and safety, this study could serve to guide both sector managers and decision-makers on ways to improve the safety perception of their employees.

Assessing Willingness to Engage in Risky Driving Behaviour Using Naturalistic Driving Footage: The Role of Age and Gender

Young novice drivers are more prone than older drivers to get involved in a risky driving situation. Some young drivers underestimate risk while overestimating their driving abilities, increasing the likelihood of engaging in risky behaviour. Age and inexperience both influence risk estimation, though it is not clear which of these variables is more important. Can drivers’ willingness to engage in risky behaviour be assessed in a similar way to hazard perception skill using video-based risky situations? The aim of the current study was to assess whether a video-based tool could measure the willingness to participate in risky driving situations and whether it can distinguish between different types of risky driving scenarios across gender and driver age groups. We also explored the moderating effect of age and gender on drivers’ experience in relation to the risky manoeuvres and participants’ willingness to engage in risky situations. Participants were presented with naturalistic videos from the perspective of the driver that contained active risky situations (result of driver’s own actions) and were asked to make a decision regarding a potential action (to overtake a bus/bicycle or pass through an amber light) and whether they would accelerate at this point. Participants reported that they were more willing to accelerate and overtake cyclists and buses and less willing to pass a light in amber. Young drivers were more willing to both engage in the risky behaviours and accelerate than older drivers, with young males reporting higher scores than the other groups. Gender differences were observed, with males being more prone to overtake and pass through a light in amber than females; however, this difference was not observed for the intention to accelerate. All the above effects remained when we tested the impact of experience on decision making while controlling for age and gender, although driving experience was no longer significant. These results demonstrate that drivers’ intention to assume risk can indeed be measured in a similar video-based methodology to that used by hazard perception tests. The findings raise the possibility of assessing and training drivers on a wider range of safety-related behaviours.

Integration of Theory of Planned Behavior, Sensation Seeking, and Risk Perception to Explain the Risky Driving Behavior of Truck Drivers

Truck-related accidents account for a substantial portion of traffic accidents. Risky driving behavior is a main cause of traffic accidents. Understanding the risky driving behavior of truck drivers is therefore important in reducing truck-related accidents. This study aimed to propose and validate a research model that integrated a theory of planned behavior, sensation seeking, and risk perception to explain the risky driving behavior of truck drivers. A total of 471 valid data were collected from Chinese truck drivers in this study. Structural equation modeling and mediation analysis were used to examine the influence of factors in the research model on the risky driving behavior of truck drivers. Results showed that sensation seeking and risk perception of truck drivers were influential in shaping their intention to drive riskily with the mediation of attitude toward risky driving. Risk perception and attitude toward risky driving also had a negative influence and positive influence on the intention, respectively. On the basis of the findings, practical recommendations for reducing the risky driving behavior of truck drivers were provided for concerned parties.

The mediating effect of driver characteristics on risky driving behaviors moderated by gender, and the classification model of driver's driving risk

High-risk drivers are more likely to be involved in traffic accidents, and the driving risk level of drivers could be affected by many potential factors, such as demographics and personality traits. Based on the Structural Equation Model (SEM), this study involves a sample of 3150 drivers from the Strategic Highway Research Program 2 (SHRP 2), to explore the relationships among drivers' demographic characteristics (gender, age, and cumulative driving years), sensation seeking, risk perception, and risky driving behaviors. More specifically, the mediation model of driver characteristics on risky driving behaviors moderated by gender is constructed by the SEM. The results show that the effects of driving experience on risky driving behaviors are partially mediated by sensation seeking and risk perception for male drivers, while those are completely mediated by sensation seeking and risk perception for female drivers. Moreover, the development trend of risky driving behavior engagements declines greater with the growing of driving experience for female drivers than male drivers. Finally, a classification model of the driver's driving risk is proposed by the Random Forest classifier, in which the driving risk level of the driver evaluated by the crash and near-crash rate could be classified through the driver's self-reported demographics, sensation seeking, risk perception, and risky driving behaviors. The classification accuracy achieves up to 90 percent, which offers an alternative approach to identifying potential high-risk drivers to reduce property losses, injuries, and death caused by traffic accidents.

Prediction of vehicle occupants injury at signalized intersections using real-time traffic and signal data

Intersections are among the most dangerous roadway facilities due to the existence of complex movements of traffic. Most of the previous intersection safety studies are conducted based on static and highly aggregated data such as average daily traffic and crash frequency. The aggregated data may result in unreliable findings because they are based on averages and might not necessarily represent the actual conditions at the time of the crash. This study uses real-time event-based detection records, and crash data to develop predictive models for the vehicle occupants' injury severity. The three-year (2017-2019) data were acquired from the arterial highways in the City of Tallahassee, Florida. Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) classifiers were used to identify the important factors on the vehicle occupants' injury severity prediction. The performance comparison of the two classifiers revealed that the XGBoost has a higher balanced accuracy score than RF. Using the XGBoost classifier, five topmost influential factors on injury prediction were identified. The factors are the manner of the collision, through and right-turn traffic volume, arrival on red for through and right-turn traffic, split failure for through traffic, and delays for through and right-turn traffic. Moreover, the partial dependency plots of the influential variables are presented to reveal their impact on vehicle occupant injury prediction. The knowledge gained from this study will be useful in developing effective proactive countermeasures to mitigate intersection-related crash injuries in real-time.

Safety Doesn't Happen by Accident: A Longitudinal Investigation on the Antecedents of Safety Behavior

Research recognizes the shared perceptions of the priority attributed to safety in comparison to other organizational goals (i.e., safety climate) as a potential antecedent of safety behavior among construction workers. This type of climate can dismantle barriers to the promotion of effective strategies to mitigate workplace hazards. On the other hand, the current understanding of the underlying process that links the perception of a safety climate to the implementation of safety behavior is far from being exhaustive. Accordingly, this study aimed to explore the role of risk perception and safety knowledge in explaining the positive impact of safety climate before attending a training course (Time 0) and safety behavior after the training completion (Time 1). Data were collected at two time-points on a sample of N = 278 construction workers taking part in different safety training courses promoted by a vocational training organization in Northern Italy. The hypothesized relationships were tested using a serial mediation model bootstrapping approach. The obtained results indicated that the perception of a safety climate at Time 0 (T0) among construction workers is associated with higher risk perception and safety knowledge that, in turn, resulted in a higher implementation of safety behavior at Time 1 (T1). These findings contribute to the understanding of those factors that constitute a fertile ground for preventing injuries and accidents in the construction sector.

Quantification of risk perception: Development and validation of the construction worker risk perception (CoWoRP) scale

INTRODUCTION

The construction sector is leading in the number of accidents and fatalities; risk perception is the key to driving these numbers. Previous construction safety studies on risk perception quantification have not considered affective risk perception of construction workers or conducted comprehensive reliability and validity testing. Thus, this study aims to fill this need by developing a psychometrically sound instrument - the Construction Worker Risk Perception (CoWoRP) Scale - to assess the risk perception of construction workers.

METHOD

Four phases of scale development, namely, item development, factor analysis, reliability assessment, and validity assessment were conducted with the collection and testing of data from a group (n = 469) of voluntary construction workers in Hong Kong.

RESULTS

The CoWoRP Scale with 13 items was shown to have acceptable test-retest reliability, internal consistency reliability, as well as content, convergent, discriminant, and criterion-related validity. Also, the CoWoRP Scale was affirmed to have three dimensions of worker risk perception, namely risk perception - probability, risk perception - severity, risk perception - worry and unsafe. These three dimensions of worker risk perception were negatively correlated with their risk-taking behavior.

CONCLUSIONS

The CoWoRP Scale is a reliable and valid instrument for measuring the risk perception of construction workers and is expected to facilitate the construction safety studies that take risk perception of construction workers into account. Practical applications: The CoWoRP Scale could serve as an aptitude test to identify the characteristics of construction workers most likely to perceive lower risk in risky work situations. In turn, this information could help safety management provide safety training programs to those workers to enhance their risk perception and thereby minimizing their risk-taking behavior, reducing unnecessary training costs, and improving the construction safety performance.

Are Co-users of Alcohol and Marijuana More Willing to Experience Consequences From Drinking? A Longitudinal Examination Among First-Year College Students

BACKGROUND

Alcohol and marijuana co-users are at heightened vulnerability for experiencing a variety of negative alcohol use outcomes including heavier alcohol use and driving under the influence. The current study explored willingness to experience negative consequences as a potential factor underlying the association between co-user status and negative consequences in an effort to guide future intervention work. From a longitudinal study of first-year college students, we examined willingness to experience consequences at Time 2 as a mediator of co-user status at Time 1 and experience of negative consequences at Time 3.

METHODS

First-year college student drinkers (n = 1,914) at a large university completed surveys in the fall and spring of their freshman year and the fall of their sophomore year.

RESULTS

Alcohol and marijuana co-users reported higher willingness to experience consequences than alcohol-only users. Willingness to experience consequences partially explained the association between alcohol and marijuana couse and consequences.

CONCLUSIONS

The current study was the first to compare co-users of alcohol and marijuana to alcohol-only users on willingness to experience consequences, and examine the role of willingness as a mediator between co-user status and consequences experienced. Co-users were more willing to experience adverse effects from drinking, in turn predicting more consequences. Intervention work targeting consequences may be less effective for co-users; thus, additional work is needed to identify other potential mechanisms for change for this at-risk group.

Construction Worker Risk-Taking Behavior Model with Individual and Organizational Factors

Behavioral-based safety is an important application of behavioral science that can be used to address safety problems in the construction sector. An understanding of construction worker risk-taking behavior is deemed to be a crucial basis on which concerned authorities and construction companies can develop effective safety interventions to reduce construction accidents. However, no studies have been conducted to examine the effects of safety climate, work condition, attitude toward risk, cognitive bias, and risk perception on construction worker risk-taking behavior through a quantitative approach. Accordingly, this study aims to propose a research model that explains construction worker risk-taking behavior. A total of 188 valid datasets were obtained through a series of questionnaire surveys conducted in representative construction projects in Hong Kong. Confirmatory factor analysis with structural equation modeling was adopted to validate the hypothesized research model. Results show that attitudes toward risk and cognitive bias have a positive influence, whereas risk perception and work conditions have a negative influence on construction worker risk-taking behavior. In addition, safety climate was negatively correlated with construction worker risk-taking behavior. Practical recommendations for reducing construction worker risk-taking behavior are also discussed in this paper.

The risk factors Finnish paramedics recognize when performing emergency response driving

OBJECTIVE

Paramedics face several safety risks in their occupation, and crashes during emergency response driving (ERD) are quite common. However, there is a need for more research to develop educational and implementation suggestions to determine how these risks can be reduced and managed. In this study, we examined what risk factors Finnish paramedics recognize when performing ERD.

METHODS

The study material consisted of 161 pages of material that had been written by experienced paramedics (n = 44) who were master's degree students of South-Eastern Finland University of Applied Sciences in fall 2017. They wrote essays based solely on their own thoughts and experiences regarding the risk factors associated with ERD. The material was analyzed via inductive content analysis.

RESULTS

Two main categories were found: Crew-related risk factors and environmental risk factors. These categories could be further divided into eight sub-categories. The crew-related risk factors consisted of lack of education and training for ERD, insufficient concentration on driving, irresponsibility and indifference, crew member's inability to take collective responsibility for safety as a team, and excessive load experienced by the driver. Environmental risk factors consisted of demanding handling of ambulance, poor visibility, and other road users.

CONCLUSIONS

Finnish paramedics recognized several risk factors in ERD. Some of the factors have been noted in previous literature regarding ambulance crashes and should be addressed as a matter of urgency to improve safety. Overall, better knowledge regarding these risks needs to be developed worldwide. The results led to several further study suggestions.