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Exploring Key Factors For Risky Driving
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HOW TO USE THIS RESOURCE

PUBLIC HEALTH APPROACH

BACKGROUND

KEY DEFINITIONS

SOCIO-ECOLOGICAL MODEL FOR DRIVER SAFETY

SHARED RISK FACTORS

SHARED PROTECTIVE FACTORS

BEHAVIOR CHANGE STRATEGIES

RECOMMENDATIONS


APPENDIX A: PROBLEM IDENTIFICATION GUIDE

 

APPENDIX B: EXPLORING KEY FACTORS FOR RISKY DRIVING


COMPLETE RESOURCE DOCUMENT




 

 

Unhealthy family relationships, severity of post-traumatic stress, and negative emotions are also associated with risky driving and motor vehicle crash involvement (Atombo, Wu, Tettehfio, & Agbo, 2017; Hayley, de Ridder, Stough, Ford, & Downey, 2017; Kuhn, Drescher, Ruzek, & Rosen, 2010). Environmental influences (e.g., road conditions, weather), a driver’s health (e.g., ADHD, chronic pain, sleep apnea, obesity), life circumstances (e.g., veterans fresh from deployment, veterans age 65 and older), and psychosocial factors (e.g., stress) also affect the likelihood for risky driving behaviors. These factors combine into a complex and interconnected system that influence driving behaviors, extending even deeper to societal-level characteristics such as structures of inequity or repeat cycles of trauma. This complex network points to the need to examine the deeper, underlying risk and protective factors that address behavior across these six aspects of risky driving in order to truly address the root of the problem.  A profile of the risk and protective factors for each of the six risky driving behaviors is below.

 

Aggressive Driving and Speeding

According to numerous studies, age is a significant risk factor for aggressive driving and speeding. Younger drivers are at risk because they have heightened levels of personality traits that are associated with risky and aggressive behaviors (Constantinou, Panayiotou, Konstantinou, Loutsiou-Ladd, & Kapardis, 2011). Younger drivers (18–34 years) report the highest prevalence of perpetrated driver aggression, whereas older adult drivers (55+ years) report the lowest prevalence of perpetrated driver aggression (Wickens, et al., 2012). Research supports the notion that sex is a key factor in assessing aggressive driving and speeding behaviors. According to Constantinou, et al. (2011) male drivers are more prone to accidents precisely because they have certain personality characteristics that make them under-estimate danger and take more risks (higher sensation seeking and lower sensitivity). For both male and female drivers, those who are unmarried or divorced report a greater prevalence of driver aggression than those who were married. Both male and female drivers with high and medium socioeconomic status (SES) reported more risky driving behaviors, intention, and attitude toward speeding than their peers with low SES (Wickens, et al., 2012; Atombo, Wu, Tettehfio, & Agbo, 2017).

 

Aggressive driving can be related to personality variables such as feelings of anger, hostility, sensation seeking, and competitiveness. Social variables such as driving without passengers and characteristics of the target vehicle (e.g., passengers in the target vehicle, age of individual(s) in target vehicle, etc.) tend to increase aggressive driving behavior. When anger is coupled with other specific risk characteristics (e.g., age or high levels of hostility), it leads to maladaptive changes in driving parameters and worsens driving performance. Finally, environmental variables (e.g., type of road, traffic, and weather), and temporal variables (e.g., time constraints and time of day) can increase the risk for aggressive driving (Harris & Houston, 2010;2018; Sharkin, 2004; Roidl, Siebert, Oehl, & Höger, 2013).

 

Alcohol-Impaired Driving

As supported by Duarte, Escario, & Molina (2016) and Fairlie, Quinlan, Wood, Lawson, & Witt (2010), older adolescents and young adults (21 years or older) have a higher probability of participating in alcohol-impaired driving. Despite this trend, adolescents are less likely to participate in alcohol-impaired driving as the father’s characteristics increase (e.g., education level, present in the home, drinking/smoking behaviors). Research suggests that there is an association between early substance abuse among young adults and relevant risk of driving under the influence of alcohol. The occurrence of high anxiety levels, binge drinking, and using marijuana may have combined influence and function as a significant predictor of impaired driving behaviors, specifically among males (Li, Simons-Morton, Gee, & Hingson, 2016; Oshri, Carlson, Bord, & Zeichner, 2017; Pogue, Hakes, & Sloan, 2017). Finally, a perceived difficulty in obtaining alternative transportation is associated with a greater likelihood of individuals drinking and driving (Fairlie et al., 2010).

 

Distracted Driving

Multivariable analyses reveal that age significantly correlates with an increased risk for distracted driving behavior. More specifically, young white males are less likely to avoid distracting activities while driving (Engelberg, Hill, Rybar, & Styer, 2015; Li, et al., 2018; Young & Lenné, 2010). Developmental stages (adolescents and young adults), type of distracting task (e.g., texting), and the use of mobile technology impairs youth safety on the road (Stavrinos, Pope, Shen, & Schwebel, 2018). Several research studies confirm the high prevalence of this behavior among adolescents. Findings from a study conducted by Carter, Bingham, Zakrajsek, Shope, & Sayer (2014) revealed that ninety-two percent of adolescents reported regularly engaging in distracted driving behavior. Young drivers (18–25 years) are significantly more likely to engage in certain distracting activities, such as: using a mobile phone, using a CD player, eating, and drinking. While older drivers are the most adversely affected by distraction while driving, younger drivers have a higher risk of deliberately violating safe driving practices (Ortiz, Ortiz-Peregrina, Castro, Casares-López, & Salas, 2018; Young & Lenné, 2010).

 

While there are several demographic factors that lead to distracted driving, there are several social and environmental factors that influence these behaviors. Studies show that parent role modeling of distracted driving determines an adolescent’s perceived risk of engaging in distracted driving behaviors. If a teen observed their parent engaging in distracted driving behaviors, they were more likely to repeat the behavior.  Additionally, if teens observe their peers engaging in distracted driving behaviors, they are more likely to engage in the same behaviors (Carter, Bingham, Zakrajsek, Shope, & Sayer, 2014; Hartos, Eitel, & Simons-Morton, 2002).  A study conducted by Li et al. (2018) revealed that the prevalence of texting while driving was higher in states with a lower minimum learner's permit age and in states where a larger percentage of teenagers (specifically high school students) drove. Seat belt use by teens correlated with distracted driving behavior. Infrequent seat belt use increased the likelihood of teens texting while driving. This study also revealed a relationship between alcohol-impaired driving and texting while driving among teens. Regarding older adults (30-64 years), other variables for an increased risk of distracted driving include having children at home, the average number of days a week spent driving, and the obligation felt to take work calls while driving (Engelberg, et al., 2015).

 

Fatigued and Drowsy Driving

Jiang, Ling, Feng, Wang, & Shao (2017) found age to be the only significant predictor of fatigued driving behavior among other demographic variables. Regarding individual demographic factors, being a male is positively associated with an increased likelihood of driving while fatigued (Paterson, Browne, Ferguson, & Dawson, 2016). Paterson et al. (2016) also found that younger age is associated with an increased likelihood of reporting having driven despite feeling too tired.

 

There are several normative beliefs and underlying causes that influence drowsy and fatigued driving. Drivers with poor sleep quality or a history of fatigue all demonstrate a greater tendency to continue driving while fatigued, have a more positive attitude towards driving while fatigued, and perceive a higher level of control while driving fatigued (Jiang et al., 2017). Individuals that report very short (less than 5 hours) and short (6 hour) sleep durations, are more likely to be associated with drowsy driving. Very short sleepers were more likely to report drowsy driving than those that got at least 7 hours of sleep. Very little sleep duration and insufficient sleep place individuals at risk for driving while drowsy or fatigued. Additionally, the physical health of an individual can influence drowsy and fatigued driving behavior. Obstructive sleep apnea increases the likelihood of insufficient sleep.  Characteristics that may predict crash in drivers with obstructive sleep apnea include a high body mass index (BMI), apnea plus hypopnea index, oxygen saturation, and possibly daytime sleepiness (Maia, Grandner, Findley, & Gurubhagavatula, 2013; Tregear, Reston, Schoelles, & Phillips, 2009). Another underlying factor influencing fatigued driving is navigating in a congested traffic flow (Wang, Sun, Fang, Fu, & Stipancic, 2017).

 

Other Drug-Impaired Driving

According to the 2016 National Survey on Drug Use and Health, men are more likely than women to drive under the influence of alcohol or other drugs.  Although illicit drug use has increased among older adults aged 50 to 59, findings also show a higher percentage of young adults aged 18 to 25 driving after taking drugs and/or drinking when compared to the behaviors of adults 26 or older. While age and sex are strong individual factors of drug-impaired driving behavior, there are several other factors that pose a relevant risk for driving under the influence of drugs in all substance groups. These factors include early initiation of lifetime substance use, low education level, unemployment, receiving a disability pension, being divorced, and living alone (Karjalainen, et al., 2011; Li et al., 2016).

 

Seat Belt Nonuse by Adults

Self-reported seat belt use by adults increases with age. Older adults are more likely to wear a seat belt, specifically adults 45 years of age and older (Bhat, Beck, Bergen, & Kresnow, 2015; Chao, Szrek, Leite, Peltzer, & Ramlagan, 2015). Based on findings from (Strine, et al., 2010), significant sociodemographic characteristics among those who reported always wearing seat belts include: being female, being Hispanic or non-white, having some college education or greater; being currently married, being retired, being a homemaker, or being a full-time student. Seat belt use is significantly less likely in obese individuals compared with their normal-weight counterparts (Jehle, Doshi, Karagianis, Consiglio, & Jehle, 2014; Strine, et al., 2010).

 

Behavioral intention to wear a seat belt can be predicted by self-efficacy, instrumental attitudes towards using a seat belt, and social norms around seat belt use. Enforcement of seat belt laws plays a critical role in seat belt use by adults (Okamura, Fujita, Kihira, Kosuge, & Mitsui, 2012). Geographic characteristics also have an impact on seat belt use by adults. As the location became more rural, the prevalence of persons who reported always wearing seat belts became less. After adjusting for all other factors, persons in the largest metropolitan areas were significantly more likely to report always wearing a seat belt than those in the smallest rural areas.

 
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