Differential impact of personality traits on distracted driving behaviors in teens and older adults

ObjectiveTo determine the impact of personality on distracted driving behaviors.MethodParticipants included 120 drivers (48 teens, 72 older adults) who completed the 45-item Big Five Personality questionnaire assessing self-reported personality factors and the Questionnaire Assessing Distracted Driving (QUADD) assessing the frequency of distracted driving behaviors. Associations for all five personality traits with each outcome (e.g., number of times texting on the phone, talking on the phone, and interacting with the phone while driving) were analyzed separately for teens and older adults using negative binomial or Poisson regressions that controlled for age, gender and education.ResultsIn teens, higher levels of openness and conscientiousness were predictive of greater reported texting frequency and interacting with a phone while driving, while lower levels of agreeableness was predictive of fewer reported instances of texting and interacting with a phone while driving. In older adults, greater extraversion was predictive of greater reported talking on and interacting with a phone while driving. Other personality factors were not significantly associated with distracted driving behaviors.ConclusionsPersonality traits may be important predictors of distracted driving behaviors, though specific traits associated with distracted driving may vary across age groups. The relationship between personality and distracted driving behaviors provides a unique opportunity to target drivers who are more likely to engage in distracted driving behavior, thereby increasing the effectiveness of educational campaigns and improving driving safety.     

Does attention capacity moderate the effect of driver distraction in older drivers?

With age, a decline in attention capacity may occur and this may impact driving performance especially while distracted. Although the effect of distraction on driving performance of older drivers has been investigated, the moderating effect of attention capacity on driving performance during distraction has not been investigated yet. Therefore, the aim was to investigate whether attention capacity has a moderating effect on older drivers’ driving performance during visual distraction (experiment 1) and cognitive distraction (experiment 2). In a fixed-based driving simulator, older drivers completed a driving task without and with visual distraction (experiment 1, N = 17, mean age 78 years) or cognitive distraction (experiment 2, N = 35, mean age 76 years). Several specific driving measures of varying complexity (i.e., speed, lane keeping, following distance, braking behavior, and crashes) were investigated. In addition to these objective driving measures, subjective measures of workload and driving performance were also included. In experiment 1, crash occurrence increased with visual distraction and was negatively related to attention capacity. In experiment 2, complete stops at stop signs decreased, initiation of braking at pedestrian crossings was later, and crash occurrence increased with cognitive distraction. Interestingly, for a measure of lane keeping (i.e., standard deviation of lateral lane position (SDLP)), effects of both types of distraction were moderated by attention capacity. Despite the decrease of driving performance with distraction, participants estimated their driving performance during distraction as good. These results imply that attention capacity is important for driving. Driver assessment and training programs might therefore focus on attention capacity. Nonetheless, it is crucial to eliminate driver distraction as much as possible given the deterioration of performance on several driving measures in those with low and high attention capacity.     

Engrossed in conversation: the impact of cell phones on simulated driving performance

The current study examined the effects of cognitively distracting tasks on various measures of driving performance. Thirty-six college students with a median of 6 years of driving experience completed a driving history questionnaire and four simulated driving scenarios. The distraction tasks consisted of responding to a signal detection task and engaging in a simulated cell phone conversation. Driving performance was measured in terms of four categories of behavior: traffic violations (e.g., speeding, running stop signs), driving maintenance (e.g., standard deviation of lane position), attention lapses (e.g., stops at green lights, failure to visually scan for intersection traffic), and response time (e.g., time to step on brake in response to a pop-up event). Performance was significantly impacted in all four categories when drivers were concurrently talking on a hands-free phone. Performance on the signal detection task was poor and not significantly impacted by the phone task, suggesting that considerably less attention was paid to detecting these peripheral signals. However, the signal detection task did interact with the phone task on measures of average speed, speed variability, attention lapses, and reaction time. The findings lend further empirical support of the dangers of drivers being distracted by cell phone conversations.     

Impact of distracted driving on safety and traffic flow

Studies have documented a link between distracted driving and diminished safety; however, an association between distracted driving and traffic congestion has not been investigated in depth. The present study examined the behavior of teens and young adults operating a driving simulator while engaged in various distractions (i.e., cell phone, texting, and undistracted) and driving conditions (i.e., free flow, stable flow, and oversaturation). Seventy five participants 16–25 years of age (split into 2 groups: novice drivers and young adults) drove a STISIM simulator three times, each time with one of three randomly presented distractions. Each drive was designed to represent daytime scenery on a 4 lane divided roadway and included three equal roadway portions representing Levels of Service (LOS) A, C, and E as defined in the 2000 Highway Capacity Manual. Participants also completed questionnaires documenting demographics and driving history. Both safety and traffic flow related driving outcomes were considered. A Repeated Measures Multivariate Analysis of Variance was employed to analyze continuous outcome variables and a Generalized Estimate Equation (GEE) Poisson model was used to analyze count variables. Results revealed that, in general more lane deviations and crashes occurred during texting. Distraction (in most cases, text messaging) had a significantly negative impact on traffic flow, such that participants exhibited greater fluctuation in speed, changed lanes significantly fewer times, and took longer to complete the scenario. In turn, more simulated vehicles passed the participant drivers while they were texting or talking on a cell phone than while undistracted. The results indicate that distracted driving, particularly texting, may lead to reduced safety and traffic flow, thus having a negative impact on traffic operations. No significant differences were detected between age groups, suggesting that all drivers, regardless of age, may drive in a manner that impacts safety and traffic flow negatively when distracted.     

Driving anger, sensation seeking, impulsiveness, and boredom proneness in the prediction of unsafe driving

The present study investigated the potential contribution of sensation seeking, impulsiveness, and boredom proneness to driving anger in the prediction of aggressive and risky driving. Two hundred and twenty-four college student participants completed measures of trait driving anger, aggressive and risky driving, driving anger expression, sensation seeking, impulsiveness, and boredom proneness. Findings provided additional support for the utility of the Driving Anger Scale (DAS; Deffenbacher, J.L., Oetting, E.R., Lynch, R.S., Development of a driving anger scale, Psychological Reports, 74, 1994, 83-91.) in predicting unsafe driving. In addition, hierarchical multiple regression analyses demonstrated that sensation seeking, impulsiveness, and boredom proneness provided incremental improvements beyond the DAS in the prediction of crash-related conditions, aggressive driving, risky driving, and driving anger expression. Results support the use of multiple predictors in understanding unsafe driving behavior.     

Stuck in the 70s: The role of social norms in distracted driving

Successful campaigns to end distracted driving must understand prevailing social norms for behaviors such as texting and phoning while driving. The current work examined this issue by asking younger drivers to read car crash scenarios and rate the responsibility of the driver for the crash, and to levy fines and assign jail time, as a function of whether the driver was attentive, had been drinking, or was distracted by phoning or texting. In the first experiment, ratings were performed in the absence of injunctive norm information (laws against drunk and distracted driving). In the second experiment, injunctive norm information was included. Impaired drivers were viewed as more responsible in both experiments, with texting drivers viewed as the most responsible. However, drunk drivers received the most fines and jail time. When compared to data from the 1970s, the results show that anti-drunk driving campaigns have changed how younger drivers view drunk driving, but that norms have not yet changed for distracted driving, despite consistent results showing they know the risk of driving distracted. Implications for social norm distracted driving campaigns are discussed.     

Distraction-induced driving error: An on-road examination of the errors made by distracted and undistracted drivers

This study explored the nature of errors made by drivers when distracted versus not distracted. Participants drove an instrumented vehicle around an urban test route both while distracted (performing a visual detection task) and while not distracted. Two in-vehicle observers recorded the driving errors made, and a range of other data were collected, including driver verbal protocols, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, etc.). Classification of the errors revealed that drivers were significantly more likely to make errors when distracted; although driving errors were prevalent even when not distracted. Interestingly, the nature of the errors made when distracted did not differ substantially from those made when not distracted, suggesting that, rather than making different types of errors, distracted drivers simply make a greater number of the same error types they make when not distracted. Avenues for broadening our understanding of the relationship between distraction and driving errors are discussed along with the advantages of using a multi-method framework for studying driver behaviour.     

Navigational conversation impairs concurrent distance judgments

Dual-task performance as it relates to driving, such as tuning a radio or manipulating a cellular phone, forces drivers to divide their attention between the traffic demands and the in-car task. The present study investigated how concurrent spatial or non-spatial cognitive distractions mediated proximity judgments using vehicular stimuli. Utilizing a modified version of the task employed by [Elias, L.J., Robinson, B. in press. Drive on the right side of the road: perceptual asymmetries for judgments of automobile proximity. International Journal of Neuroscience.] the current study examined how mental navigation (spatial distraction) affected accuracy and response time for depth judgments on vehicular stimuli in each visual field. These were compared to a control condition in which no distraction was present, as well as when a semantic (non-spatial) distraction was present. We found that conversation of a navigational nature (i.e., spatial distraction) most negatively impacted accuracy and response time when processing dynamically changing vehicle proximity. Further, these deleterious effects appeared to be uniform throughout the visual field. Findings are related to driving while being distracted, with particular emphasis on the role of cerebral lateralization in dual-task performance.     

Thirty-day self-reported risky driving behaviors of ADHD and non-ADHD drivers

The present study aims to compare differences in reported risky driving behaviors of drivers – males and females – having and not having Attention Deficit Hyperactivity Disorder (ADHD), by using a checklist of driving behaviors based on the Driving Behavior Questionnaire (DBQ). Unlike the studies which employ the DBQ by asking the subjects to fill the questionnaire once, in this present study, the participants were asked to report their behaviors on a daily basis for 30 consequent days. The checklist included two factors of risky driving behavior: Violation and Faults. Thirty-eight drivers – 10 males and 9 females with ADHD, and 9 males and 10 females without ADHD (N-ADHD) as control groups – participated in the study. The results showed that the mean of the unsafe behaviors of ADHD was higher, i.e., less safe driving, compared to that of N-ADHD. However, a statistically significant effect was found only between male ADHD and male N-ADHD for the Faults. In order to check the effect of the length of the study, the 30 days duration of the research was divided into three consecutive periods. The reported driving habits of the female ADHD showed safer behaviors than those of the males. Unlike the findings of N-ADHD of both genders, which showed a tendency towards safer driving reports in the three periods, both genders of the ADHD showed higher rates of Faults, i.e., a decrease in safety driving reports, in the three periods. The findings suggest that ADHD drivers differ from the N-ADHD drivers in making driving mistakes, i.e., Faults, due to their lack of sustained attention, but not in making Violations. However, some of the results in the present study were not very strong. Possible explanations for this as well as methodological considerations are discussed, and further research is suggested.     

Are child occupants a significant source of driving distraction?

Driver distraction represents a well-documented and growing contribution to the road safety problem. This study used a naturalistic, observational approach to examine if children in vehicles are a significant source of driving distraction. Families with children aged between 1 and 8 years drove an instrumented “study vehicle” on their regular trips for 3 weeks. A discrete video recording system in the vehicle provided images of the driver and front seat passenger, the rear seat child passengers and the traffic ahead. The video-recordings inside and outside the vehicle were analysed to identify potential distracting activities, where ‘distraction’ was broadly defined as any activity that distracted the driver or competed for their attention while driving. In addition, all potentially distracting activities that involved the driver looking away from the forward roadway for more than 2 s while the vehicle was in motion were also coded. Video-recordings were analysed for 92 driving journeys undertaken by 12 families including 25 children and 19 drivers. The mean journey duration was approximately 16 min (range: 2 min–3 h 34 min). Most journeys were undertaken during the day (89%), with the mother driving (65%) and without a front seat passenger (64%). Driving journeys were predominantly undertaken in urban areas (97%), on suburban roads/streets (94%), and under low complexity traffic conditions (91%). Most journeys involved some source of potential driver distraction (98%), with drivers distracted for 18% of the driving journey. The most frequent types of distracting activities that drivers engaged in included: touching their head or their face (35%), interacting with child passengers in the rear seat (12%), and engaging with the front seat passenger (9%). Almost three-quarters of these potentially distracting activities were engaged in by the driver while the study vehicle was in motion (72%) and 14% of all potentially distracting activities involved the driver's eyes off the roadway for greater than 2 s while the vehicle was in motion, thereby potentially doubling their crash risk. The most frequent child-related activities that drivers engaged in included: turning to look at the rear seated occupants or viewing the children using the rear-view mirror (76.4%), engaging in conversation with their children (16%), assisting their children (e.g., passing food and drink [7%]) and playing with their children (1%). Drivers spent significantly longer periods of time engaged in non-child occupant-related activities compared with child occupant-related activities and were significantly more likely to have their eyes off the forward roadway for greater than 2 s while engaged in non-child occupant-related activities (14%) compared to child occupant-related activities (10%). The results suggest that drivers need to be educated about the potential crash and injury risks associated with both child occupant-related and non-child occupant-related activities while driving their vehicle.     

A network perspective on the relationship between gaming disorder,depression, alexithymia,boredom, and loneliness among a sample of Chinese university students

Background and aimsBased on previous research, it was hypothesized that negative affect (e.g., depression, anxiety, and loneliness) and low level of emotion regulation (i.e., alexithymia) are risk factors for internet gaming disorder (IGD). Research utilizing a network analysis approach to psychopathology has increased rapidly, and is used to examine the pattern of interactions between causal factors of mental health disorders. Previous research has investigated the relationship between gaming disorder (GD), depression, alexithymia, boredom, and loneliness by pair-wise correlation and correlation of three or four variables. However, to date, network analysis has rarely been utilized to examine the relationship between the aforementioned multi-variables. Therefore, the present study used network analysis to examine the relationship between GD, depression, alexithymia, boredom, and loneliness among a sample of Chinese university students.MethodsA sample comprising 1635 Chinese university students (913 males) completed a survey including the Gaming Disorder Test, Patient Health Questionnaire, and Toronto Alexithymia Scale, alongside single-item measures of loneliness and boredom.ResultsDepression, alexithymia, boredom, and loneliness were significantly and positively associated with GD. Loneliness and boredom had the closest edge intensity, and loneliness was the strongest central node in the domain-level network. The facet-level and the item-level network analysis also showed that GD was connected with depression, alexithymia, boredom, and loneliness. The domain-level network comparison test (NCT) showed the global strengths had significant difference among gender group (males = 1.90 vs. females = 1.77, p = 0.013).ConclusionsThe findings indicate that there is a close relationship between GD, depression, alexithymia, boredom, and loneliness. Negative affect and low emotion regulation may induce or worsen GD, resulting in a vicious cycle. Practitioners developing interventions to overcome GD should consider aspects aimed at adjusting and improving negative emotion, especially loneliness and related negative affect as well as facilitating positive emotion.     

A parametric duration model of the reaction times of drivers distracted by mobile phone conversations

The use of mobile phones while driving is more prevalent among young drivers—a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q advanced driving simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver's peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21–26 years old and split evenly by gender. Drivers’ reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver's age, license type (provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted presents a significant and measurable safety concern that will undoubtedly persist unless mitigated.     

The role of alcohol use on recent trends in distracted driving

Distracted driving is now an increasingly deadly threat to road safety. We provide evidence that intoxicated driving is increasingly responsible for recent increases in fatalities from distracted driving crashes. This study describes trends in deaths on U.S. public roads caused by alcohol-involved and distracted drivers using the Fatality Analysis Reporting System (FARS)—a census of fatal crashes on U.S. public roads. Fatality rates per vehicle-miles traveled are calculated using data from the Federal Highway Administration. Alcohol-involved drivers who are simultaneously distracted were responsible for 1750 deaths in 2009, an increase of more than 63% from 2005 when there were 1072 deaths. Alcohol use while driving is increasingly responsible for a growing number of fatalities from distracted driving, accounting for 32% of deaths from distracted driving in 2009 versus 24% in 2005. The fatality rate from these crashes increased from 35.9 to 59.2 deaths per 100 billion vehicle-miles traveled after 2005. Alcohol use is quickly increasing as an important factor behind distracted driving fatalities. This has implications for policies combating distracted driving that do not address the role of alcohol use in distracted driving.     

Bicycling safety and distracted behavior in The Hague,the Netherlands

As planners and public health officials in many cities around the world seek to increase bicycle ridership, bicyclists who are performing a secondary task (such as listening to a portable music device) may pose a risk to public safety. This study examines bicycling safety and potentially distracted behavior in The Hague, the Netherlands, a place where bicycling is a common, everyday travel mode among all walks of life and where bicycling infrastructure is well developed. Based on 1360 observations of bicycling behavior, this study shows that bicyclists who were using a cell phone, listening to a portable music device, or talking with other bicyclists exhibited more unsafe behaviors than those bicyclists who were not performing a secondary task. Furthermore, bicyclists who were performing a secondary task also more frequently created situations where other people had to evade them to avoid an accident. As with distracted car driving, the performance of a secondary task while bicycling may be unsafe for the person engaging in the behavior as well as for other people around them.     

Investigating the influence of working memory capacity when driving behavior is combined with cognitive load: An LCT study of young novice drivers

Distracted driving has received increasing attention in the literature due to potential adverse safety outcomes. An often posed solution to alleviate distraction while driving is hands-free technology. Interference by distraction can occur however at the sensory input (e.g., visual) level, but also at the cognitive level where hands-free technology induces working memory (WM) load. Active maintenance of goal-directed behavior in the presence of distraction depends on WM capacity (i.e., Lavie's Load theory) which implies that people with higher WM capacity are less susceptible to distractor interference. This study investigated the interaction between verbal WM load and WM capacity on driving performance to determine whether individuals with higher WM capacity were less affected by verbal WM load, leading to a smaller deterioration of driving performance. Driving performance of 46 young novice drivers (17–25 years-old) was measured with the lane change task (LCT). Participants drove without and with verbal WM load of increasing complexity (auditory-verbal response N-back task). Both visuospatial and verbal WM capacity were investigated. Dependent measures were mean deviation in the lane change path (MDEV), lane change initiation (LCI) and percentage of correct lane changes (PCL). Driving experience was included as a covariate. Performance on each dependent measure deteriorated with increasing verbal WM load. Meanwhile, higher WM capacity related to better LCT performance. Finally, for LCI and PCL, participants with higher verbal WM capacity were influenced less by verbal WM load. These findings entail that completely eliminating distraction is necessary to minimize crash risks among young novice drivers.     

In the eye of the beholder: A simulator study of the impact of Google Glass on driving performance

This study examined whether, and to what extent, driving is affected by reading text on Google Glass. Reading text requires a high level of visual resources and can interfere with safe driving. However, it is currently unclear if the impact of reading text on a head-mounted display, such as Google Glass (Glass), will differ from that found with more traditional head-down electronic devices, such as a dash-mounted smartphone. A total of 20 drivers (22–48 years) completed the Lane Change Test while driving undistracted and while reading text on Glass and on a smartphone. Measures of lateral vehicle control and event detection were examined along with subjective workload and secondary task performance. Results revealed that drivers’ lane keeping ability was significantly impaired by reading text on both Glass and the smartphone. When using Glass, drivers also failed to detect a greater number of lane change signs compared to when using the phone or driving undistracted. In terms of subjective workload, drivers rated reading on Glass as subjectively easier than on the smartphone, which may possibly encourage greater use of this device while driving. Overall, the results suggest that, despite Glass allowing drivers to better maintain their visual attention on the forward scene, drivers are still not able to effectively divide their cognitive attention across the Glass display and the road environment, resulting in impaired driving performance.     

Identifying beliefs underlying pre-drivers’ intentions to take risks: An application of the Theory of Planned Behaviour

Novice motorists are at high crash risk during the first few months of driving. Risky behaviours such as speeding and driving while distracted are well-documented contributors to crash risk during this period. To reduce this public health burden, effective road safety interventions need to target the pre-driving period. We use the Theory of Planned Behaviour (TPB) to identify the pre-driver beliefs underlying intentions to drive over the speed limit (N = 77), and while over the legal alcohol limit (N = 72), talking on a hand-held mobile phone (N = 77) and feeling very tired (N = 68). The TPB explained between 41% and 69% of the variance in intentions to perform these behaviours. Attitudes were strong predictors of intentions for all behaviours. Subjective norms and perceived behavioural control were significant, though weaker, independent predictors of speeding and mobile phone use. Behavioural beliefs underlying these attitudes could be separated into those reflecting perceived disadvantages (e.g., speeding increases my risk of crash) and advantages (e.g., speeding gives me a thrill). Interventions that can make these beliefs safer in pre-drivers may reduce crash risk once independent driving has begun.     

Understanding commercial truck drivers’ decision-makin process concerning distracted driving

A concurrent mixed methods design was used to explore personal and workplace factors, informed by the Theory of Planned Behavior, that affect truck drivers’ decision-making about distracted driving on the job. Qualitative data were collected via semi-structured interviews with experts in truck safety and distracted driving, and quantitative data were collected via online survey of truck drivers in the United States. Findings from the interviews illustrated how drivers perceived distractions and the importance of supervisors enforcing organizational distracted driving policies. Survey results found that behavioral intentions were most important in regards to texting and crash and near-crash outcomes, while perceived norms from management best described the correlation between dispatch device use and negative crash-related outcomes. By using a mixed methods design, rather than two separate studies, these findings revealed nuanced differences into the influence of supervisors on distracted driving.     

Young novice driver subtypes: Relationship to driving violations, errors and lapses

The present study aimed to identify, in a large Italian sample of young, novice drivers, specific subtypes of drivers on the basis of combinations of self-reported personality traits (i.e., driving anger, anxiety, angry hostility, excitement-seeking, altruism, normlessness and driving locus of control) and to evaluate their high-risk driving behaviors not only in terms of traffic rule violations and risk-taking behaviors, but also in terms of driving errors and lapses as measured by the Manchester Driver Behavior Questionnaire. Participants were 1008 high school students between the ages of 18 and 23 years, with valid driver's licenses. On the basis of a cluster analysis of the personality variables, three easily interpretable driver subgroups were identified (risky drivers, worried drivers and careful drivers) that differed on self-reported accident involvement, attitudes toward traffic safety and risk perception, as well as on driving violations, errors, and lapses. The inclusion of internal and external driving locus of control, variables not previously considered in similar cluster studies, provided a relevant contribution to the final cluster solution. Further, the use of the Driving Behavior Questionnaire permitted the differentiation between deliberate deviations from safe driving practices and mistakes due to misjudgments or lapses in attention. This distinction was critical for understanding the behavior of each of the three identified subgroups of drivers, and for planning interventions to promote safe driving.