Developing Employer-Based Behavioral Traffic Safety Programs for Drivers in the Workplace (2022)

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7 SECTION 2: STATE-OF-THE-PRACTICE LITERATURE REVIEW Millions of workers drive on roads as part of their jobs, including professional drivers (e.g., truck drivers, transit drivers) and employees who drive as a job function (e.g., real estate agents). This occupation-related driving exposes workers to increased risk of being involved in a crash. Overall, the leading cause of work-related deaths in the United States is motor vehicle crashes (National Institute for Occupational Safety and Health [NIOSH], 2019). From 2003– 2017, more than 27,000 employees died on U.S. roads due to motor vehicle crashes (NIOSH, 2019). A majority of those killed in a work-related motor vehicle crash were not professional drivers (e.g., truck drivers), but people driving as an ancillary part of their job (e.g., real estate agents) (NIOSH, 2019). Occupational crashes are particularly devastating, with severe impacts on employees, their coworkers, their families, their communities, and their employers. It is estimated that on average, occupational crashes cost $671,000 per death and $65,000 per nonfatal injury (Bureau of Labor Statistics, 2018; NIOSH, 2019). Legally, employers may also be held accountable for these costs (National Safety Council [NSC], 2019a). As long as employees are on roadways, occupational crashes will occur, but employers can reduce the risk through training and promoting safe driving behaviors. Preventing occupational crashes requires a combination of strategies, including the application or adoption of traffic safety principles and safety management practices (Occupational Safety & Health Administration [OSHA], n.d.-b). Several government agencies and safety organizations have proposed the implementation of employer traffic safety programs (e.g., training for employees who drive as part of their job function) to address occupational crashes, including the National Highway Traffic Safety Administration (NHTSA), OSHA, NIOSH, the Network of Employers for Traffic Safety (NETS), and NSC (NHTSA, n.d.-a; NSC, 2019d, 2019f; OSHA, n.d.-a). This section presents findings from the literature review (Task 1). The objectives of the literature review were to (a) understand the state of the practice with respect to employer-based behavioral traffic safety programs, (b) identify behavioral change theories that have been applied in the field, and (c) identify measures of program effectiveness used in the field. For the purposes of this project, an employer traffic safety program is defined as a safety program or training made available by employers for employees who drive as their primary job function or as part of their job. BACKGROUND OF EMPLOYER PROGRAMS To respond to occupational crashes, many employers are developing or purchasing pre- packaged commercially available employer driver safety programs. There are no employer programs that cover all traffic safety concerns, but there are resources available to assist employers in developing programs, as well as pre-packaged commercially available programs. The following sections summarize available resources provided by identified government agencies and safety organizations, as well as commonly utilized pre-packaged commercially available employer driver safety programs. This section provides an overview of materials and programs commonly referenced. Resources were identified while conducting the literature review, as well as through resources cited during the state-of-the-practice employer interviews. This is not an exhaustive list of available materials and programs, and there may be other materials and programs available that are less well known and cited.

8 Available Resources The identification of available resources was restricted to government agencies and safety organizations that had information on employer driving training materials or programs, including materials from NHTSA, OSHA, NIOSH, NETS, and NSC. Government Agencies To respond to the risk of occupational crashes, a joint effort between NETS, NHTSA, and OSHA resulted in the publication of Guidelines for Employers to Reduce Motor Vehicle Crashes (NETS, NHTSA, & OSHA, 2006). This document provides useful recommendations for employers to address occupational crashes. Recommendations include (a) establishing a safe driving program, (b) promoting safe driving, and (c) conducting a cost analysis of crashes versus training opportunities. In addition, the document provides guidance to assist employers starting programs, as well as resources for additional information. The document outlines the NETS 10 steps that an employer can take to create an employee driver safety program (NETS et al., 2006). Figure 1 displays the steps outlined. Real-life examples of employer-based traffic safety programs are also highlighted, as well as the process for calculating organizational losses from driving crashes. Four companies were identified as success stories, which were defined as companies that benefited from the guidelines outlined; the companies were Nationwide Insurance, Charter Communications, General Motors Corporation, and Pike Industries (NETS et al., 2006). These examples include a quick summary of each company’s safety program developed and the results. Figure 1. NETS 10 Steps for Employers to Address Traffic Safety. Senior Management Commitment & Employee Involvement Written Policies and Procedures Driver Agreements Motor Vehicle Record Checks Crash Reporting and Investigation Vehicle Selection, Maintenance, and Inspection Disciplinary Action System Reward/Incentive Program Driver Training/ Communication Regulatory Compliance

9 National Highway Traffic Safety Administration In partnership with NETS, NHTSA provides a document titled Employer Traffic Safety Programs (NHTSA, n.d.-a), with case studies of employer traffic safety programs from the United Parcel Service and Loctite Corporation. The document highlights the opportunity that employers have to reduce employee vehicle crashes through employer support, employee awareness, and education. While not specifically addressing behavioral changes, NHTSA has reference materials focused on improved occupational driving, including (a) Vehicle Training for Bus Drivers, which provides an instructor guide for school bus driver safety training; and (b) Development of Performance Requirements for Commercial Vehicle Safety Applications, which includes information on vehicle-to-vehicle technology and performance measurements that could be used for crash avoidance (Bowman et al., 2013; NHTSA, n.d.-b). National Institute for Occupational Safety and Health NIOSH has a Center for Motor Vehicle Safety, which provides guidance for preventing occupational crashes, with a focus on truck drivers, EMS, law enforcement, oil and gas extraction, and light-vehicle drivers (e.g., sales, real estate) (NIOSH, 2019). The center publishes publicly available resources, including crash facts (e.g., injury/fatality statistics, associated costs), social media images (e.g., GIFS designed to be shared), publications (e.g., infographics, journal articles, reports, etc.), and relevant resources from state partners and grantees (NIOSH, 2019). Occupational Safety & Health Administration OSHA has several publications that address occupational motor vehicle safety, including fact sheets, safety brochures, and short safety briefs (OSHA, 2019). These materials could be utilized by employers; however, there is no information that specifically addresses employer driver safety programs. Safety Organizations DRIVE SMART Virginia DRIVE SMART Virginia provides resources that address occupational crashes, including an employer cell phone policy driving toolkit, a document with tips for traffic safety in the workplace, and a brief guide to employee transportation safety (DRIVE SMART Virginia, 2019). Network of Employers for Traffic Safety To respond to occupational crashes, NHTSA founded NETS, which is an employer-led road safety organization (NETS, 2019a). NETS’s mission is to “advance road safety among occupational (non-regulated) drivers, all employees and their families, and the communities where employees live and work” (NETS, 2019a). NETS members have access to (a) the NETS road safety leaders’ online forum to exchange solutions with other members; (b) benchmark data through the NETS annual strength in numbers fleet safety benchmark program; and (c) online downloadable resources to help develop or improve programs (NETS, 2019b). National Safety Council NSC provides several training opportunities for employers, including packaged and custom curriculum (NSC, 2019f). NSC offers defensive driving opportunities to train employees, including (a) an online course; (b) a program for employers to become certified defensive driving

10 course instructors; (c) on-site training; (d) a DVD-based self-study course; and (e) local trainings when available (NSC, 2019d). In addition, Oklahoma and Texas NSC offices produce Our Driving Concern, which is designed to supply employers with the tools and information required to build a traffic safety program (NSC, 2019e). Our Driving Concern provides employers with drug impairment training opportunities, online learning opportunities, printed materials (e.g., posters, safety coach cards), and transportation safety training (NSC, 2019e). Pre-packaged Commercially Available Employer Driver Safety Programs Commercially available programs were restricted to programs identified during the literature review, as well as during the preliminary telephone interviews being conducted for Task 2. eDriving eDriving is an organization that provides a patented five-stage driver safety approach to employers for purchase (eDriving, 2019b). Taking a risk management approach, eDriving uses behavioral insights and analytics to reduce driving collision, injuries, license violations, and costs (eDriving, 2019a). More than 30 best-practice guides related to braking, distracted driving, acceleration, driving at night, and long-distance trucking, to name a few, are available. More than 10 organizational case studies from organizations such as Nestle, Pfizer, and GlaxoSmithKline are also available on the eDriving website (see https://www.edriving.com). MarshPACE Marsh Risk Consulting provides fleet management strategies in the form of developing, implementing, and monitoring fleet safety driver programs (Marsh, 2019). In addition to evaluating current organizational fleet safety practices and working with drivers, managers, and supervisors to improve safe driving, Marsh’s services include conducting a fleet safety gap analysis, benchmarking, providing driver hiring standards, recruiting and retaining drivers, and training. Smith System Smith System offers driver training in more than 22 languages and 100 countries based on the following five principles of driver safety training: (1) aim high in steering, (2) get the big picture, (3) keep your eyes moving, (4) leave yourself an out, and (5) make sure they see you (Smith System, 2019). Available training opportunities include in-house driver training courses, classroom teaching, behind-the-wheel instruction, and e-learning. Smith System also provides automated driver data collection through global positioning system (GPS) and telematics tracking aimed to reduce crashes, decrease injuries, reduce vehicle maintenance and fuel costs, and ultimately save driver lives. Fleet Management Platforms This section describes a few of the available fleet management platforms that utilize cloud-based cameras, vehicle sensors, and GPS to help improve professional driver safety on roads. Several companies utilize this approach, and this section is not an exhaustive list of platforms, and does not imply endorsement of these platforms.

11 Lytx Lytx collects billions of miles of data each year on over 3,000 fleets through cloud-based dash cams and vehicle sensors and uses these data to help fleets improve safety operations (Lytx, 2019). The Lytx website also offers a variety of articles that discuss different types of fleet safety programs, fleet tracking technologies, and best practices for a fleet safety program. Samsara Samsara provides artificial intelligence (AI) dash cams to collect road and driver behavior in real time, which helps to improve driver safety (Samsara Networks, 2019). Samsara also developed a driver safety and coaching platform that is a video-based driver safety program that encourages safe driving and methods for mitigating risk (Samsara Networks, 2019). Forward Thinking Systems Forward Thinking Systems has FleetCam®, which is a built-in camera system that offers live streaming, recordings of driving behaviors, cab alerts when undesired driving behaviors are detected, and a built-in coaching system (Forward et al., 2009). The company also has other services that promote fleet safety, including fleet reports and driver reports. BACKGROUND OF THEORIES Behaviors that are repeated ultimately become habits (Verplanken, 2018), such as putting on a seatbelt when getting into the car. While being rather easy to develop, habits can be extremely difficult to modify (Adrianse & Verhoeven, 2018). Generally, behavior change efforts require that attention be paid to multiple interacting components to be effective (Craig et al., 2008; Michie & Johnston, 2012). To change habitual behavior, psychologists and other researchers have developed and tested multiple behavioral change theories. These theories attempt to explain the origins of behaviors and how they can be modified. Behavioral change theories have been widely used across psychology and public health fields to develop injury prevention programs (Gielen & Sleet, 2003; Kidd et al., 2003; Trifiletti et al., 2005). Specifically, behavioral change theories have been used to address or identify traffic safety behaviors (Iversen et al., 2005; Nathanail & Adamos, 2013), such as speeding (Parker et al., 1996), distracted driving (Chen et al., 2016; Sinelnikov & Wells, 2017; Tian & Robinson, 2017), and helmet use (Ross et al., 2011). The following section provides a brief overview of common behavioral change theories. The theories are presented in alphabetical order. This review does not promote one theory over another. Each theory has its own strengths and limitations, and some may be more applicable to specific situations than others. Behavioral Change Theories Diffusion of Innovation Theory The Diffusion of Innovation Theory focuses on explaining how an innovation (e.g., idea or behavior) diffuses throughout a population (Rogers, 2010). The theory consists of four components that influence the diffusion of an innovation (see Figure 2): • The innovation or idea. • The communication channels used to spread the innovation. • The time needed for diffusion to occur. • The social system that influences adoption of the innovation.

12 Primary Source: Rogers (2010). Figure 2. Diffusion of Innovation Theory. Kotter’s Eight-Step Change Model Kotter’s eight-step change model is an eight-step organizational change model (Kotter, 1996), the steps of which are shown below (also see Figure 3): • Create urgency by making employees aware of the existing problem and possible solution. • Form a powerful coalition with a wide range of skills. • Form a strategic vision that is easy for all employees to understand. • Enlist a volunteer army to communicate the vision. • Enable action by removing obstacles. • Generate short-term wins through rewards and short-term targets. • Sustain acceleration by building upon changes. • Institute lasting change by anchoring changes in organizational culture. Primary Source: Kotter (1996). Figure 3. Kotter’s Eight-Step Change Model. Lewin’s Three-Step Change Theory Lewin’s three-step change theory operates on the premise that behavior change is influenced by driving and hindering forces (Lewin, 1951). There are three steps to Lewin’s model, with the first involving an unfreezing of current behavior and ensuring that individual and group influence promotes change (Schein, 1996). During the second step, behavioral change occurs through programs or policies. Last, there is a refreezing of the new behavior to ensure long-term commitment. Figure 4 shows the stages of Lewin’s three-step change theory. Innovation or Idea Communica- tion Channels Time Social System Diffusion of Innovation Create Urgency Form a Guiding Coalition Form a Strategic Vision Enlist a Volunteer Army Enable Action Generate Short-Term Wins Sustain Acceleration Institute Lasting Change

13 Primary Source: Lewin (1951). Figure 4. Lewin’s Three-Step Change Theory. Nudge Theory Nudge theory provides a process to influence behavior change without imposing strict regulations (see Figure 5). Recognizing that biases influence a person’s likelihood of engaging in behaviors, nudges provide non-monetary and non-regulatory interventions where behavior is gently influenced (Halpern, 2015). This is a cost-effective method that ultimately maintains an individual’s freedom to choose his or her behavior. Primary Source: Halpern (2015). Figure 5. Nudge Theory. Social Cognitive Theory Social cognitive theory seeks to explain people’s behavior through behavioral, environmental, and personal factors including the regulation of behavior through control and reinforcement in order to achieve goal-directed and long-term behavior change (see Figure 6) (Bandura, 1977, 1991). Additional aspects of the model are: • Reciprocal determinism. • Behavioral capability. • Observational learning. •Determine needed changes •Gain management support •Create a need for change •Manage concerns Unfreeze •Communicate changes of policies and programs •Involve employees •Empower action Change •Anchor the change into culture •Sustain changes with support and training •Recognize success Refreeze Recognize Biases Implement Non-Monetary Regulations Implement Non- Regulatory Interventions Nudge Theory

14 • Behavioral reinforcement. • Expectations and consequences of behavior. • Self-efficacy to perform behavior. Primary Sources: Bandura (1977, 1991). Figure 6. Social Cognitive Theory. Health Belief Model The health belief model presents a behavior change framework for understanding why individuals engage in healthy behaviors and how to promote the likelihood of engaging in healthy behaviors (Rosenstock, 1966). This framework comprises a person’s perceived susceptibility and severity to health-related problems, perceived self-efficacy, cues to action that influence behavior acceptance, and perceived benefits minus barriers (Janz & Becker, 1984). These variables will influence the likelihood of a person engaging in healthy behaviors. Figure 7 shows the health belief model. Primary Source: Rosenstock (1966). Figure 7. The Health Belief Model. Behavioral Factors Environmental Factors Personal Factors/ Cognitive Factors Perceived benefits minus perceived barriers Increased likelihood of health-related behavior Perceived Self- Efficacy Perceived Threat Cues to Action Perceived Susceptibility and Severity

15 Social-Ecological Model The social-ecological model explains an individual’s behavior through five personal and environmental factors (McLeroy et al., 1988). Beginning at the individual level, a person’s knowledge, attitudes, and developmental history influence behavior. Each progressing level involves influence from larger domains of people, such as family, institutions, community, and public policy (McLeroy et al., 1988). Figure 8 shows the personal and environmental factor relationships of the social-ecological model. Primary Source: McLeroy et al. (1988). Figure 8. The Social-Ecological Model. Transtheoretical Model of Change The transtheoretical model of change describes a six-step change process to an individual’s behavior (Prochaska & DiClemente, 1983). As shown in Figure 9, the six steps are: • Precontemplation stage, where the individual is not yet ready to change. • Contemplation stage, where the individual is getting ready to change. • Preparation stage, where the individual is ready to change. • Action stage, where behavior change is initiated. • Maintenance stage, where behavior change is monitored. • Termination stage, where old behavior is no longer present. Primary Source: Prochaska & DiClemente (1983). Figure 9. The Transtheoretical Model of Change. Policy Community Institutional Interpersonal Individual Precontemplation Contemplation Preparation Action Maintenance Termination

16 Workplace Health Model The workplace health model is a four-step process designed to improve employee health and safety in the workplace (Centers for Disease Control and Prevention, 2016). The model begins with a workplace health assessment, followed by program planning and management, and then implementation of the program. After implementation, program evaluation takes place to determine program outcomes (Centers for Disease Control and Prevention, 2016). Figure 10 displays the process and components of the workplace health model. Primary Source: Centers for Disease Control and Prevention (2016). Figure 10. The Workplace Health Model. Theory of Planned Behavior The theory of planned behavior views behavior as a function of one’s behavioral intentions to participate in the behavior, which are shaped by attitudes toward the behavior, subjective norms, and perceived behavioral control. Attitudes refer to how favorably or unfavorably an individual perceives the behavior (Ajzen, 1985). Subjective norms refer to the social expectations regarding the behavior that a person perceives from influential others (Ajzen, 1985). Perceived behavioral control refers to someone’s perception of factors that limit and facilitate his or her engagement in a certain behavior (Ajzen, 1985). Figure 11 shows the stages of the theory of planned behavior. Planning and Management Program Implementation Program Evaluation Workplace Health Assessment

17 Primary Source: Ajzen (1985). Figure 11. Theory of Planned Behavior. Applicability and Relevance to Traffic Safety Traffic safety programs are about changing behavior. However, there is a lack of theories of behavioral change that directly address traffic safety. Theories of behavioral change created to address other specific issues, including the ones described above, are still relevant and applicable to traffic safety because they address the fundamental elements of behavioral change. PROGRAM EFFECTIVENESS BACKGROUND Program effectiveness measures are used to determine if a training program achieves the intended goal. An example would be measuring the reduction in texting and driving following implementation of training designed to reduce texting while driving. There are two evaluation taxonomies commonly used to assess outcomes from training or educational programs. Both taxonomies seek to answer the question of “effective in terms of what?”—recognizing that a training or educational program or intervention that may be effective in terms of one outcome (criterion) may not be effective on others. Kraiger et al.’s (1993) taxonomy proposes cognitive (e.g., knowledge), skill-based (e.g., procedure), and affective (e.g., attitude changes) outcomes. Kirkpatrick’s (1976, 1996) taxonomy identifies outcomes, specifically (a) reactions, (b) learning, (c) behaviors, and (d) results. In addition to the preceding, the Centers for Disease Control and Prevention (n.d.) highlight four types of evaluation that can be conducted—formative, process, outcome, and impact. Formative evaluations determine if the program is feasible and appropriate before being fully implemented; an example of formative evaluation is pilot testing an activity before implementing it on a wider scale (Centers for Disease Control and Prevention, n.d.). Process evaluations focus on determining if the program or activity was implemented correctly. Outcome evaluations measure the effects of the program on the population (e.g., did knowledge or self- reported behaviors change following a program) (Centers for Disease Control and Prevention, n.d.). Last, impact evaluation determines if the program met its intended goal (e.g., did the program successfully reduce crashes) (Centers for Disease Control and Prevention, n.d.). Behavior Intentions Attitudes Subjective Norms Perceived Behavioral Control

18 LITERATURE REVIEW FINDINGS Summary of Theory-Based Programs The following sections provide an overview of the state of practice of employer-based behavioral traffic safety programs and behavioral change theories that have been applied in the field. The sections also indicate the level of analysis (e.g., individual, organizational) at which the program was targeted. This information is important when identifying potential programs because programs that target individual behaviors and outcomes will differ significantly from those that target organizational behaviors and outcomes. The methods utilized for identifying articles included in this section are summarized in Appendix A. The articles identified in this section are also summarized in the annotated bibliography in Appendix B for quick reference. Lewin’s Three-Step Change Theory Lewin’s three-step change theory posits that behavior changes are influenced by driving and hindering forces (Lewin, 1951). There were no articles that specifically mentioned Lewin’s three-step change theory; however, four articles used Lewin’s group-discussion approach, which argues that a group discussion could change attitudes more than a lecture or less-dynamic discussion (Geller & Hahn, 1984; Gregersen et al., 1996; Lewin, 1947; Salminen, 2008; Salminen, 2013). More recently, Salminen (2013) conducted a study to compare three methods to improve driving by postal van operators. The interventions included a discussion, improved discussion (discussion with a defensive driving course), and defensive driving course. The improved discussion method was the only intervention that resulted in reducing crashes from 12 (one year before the intervention) to four (two years after the intervention). In a previous nonexperimental study, Salminen (2008) outlined two employer-based interventions aimed at improving the safe driving behavior of electricians at two different companies. The first intervention program utilized group discussions that resulted in a 72 percent reduction in occupational crashes over an eight-year period during and after the intervention. During the three years prior to the intervention, 18 occupational crashes occurred, followed by seven crashes during the two-year intervention period and five crashes during the three years following the intervention. The second organizational intervention included a three-hour lecture and five hours of practice driving on an anticipatory course that included the effects of snow, ice, and visibility concerns. Drivers in the second intervention responded positively to the training program and claimed to be using what they learned. Gregersen et al. (1996) reviewed four different types of safety interventions: training, discussions, safety campaigns, and incentives (e.g., bonuses). Each of the four were examined for their ability to influence crash-free driving in four separate groups of drivers, each consisting of approximately 900 drivers from a Swedish telephone company. The group-discussion intervention was the only one of the four interventions that was based on Lewin’s (1951) theory. The group discussions were designed to make group norms more explicit and influence drivers’ decisions to alter their behavior behind the wheel. Drivers exchanged information on aberrant driving behavior and worked to come to conclusions regarding its dangers. The most effective intervention identified was the group discussions (Gregersen et al., 1996). Last, Geller and Hahn (1984) compared the effects of a seatbelt incentive program for blue-collar and white-collar employees at two different plants. The seatbelt program used by both plants involved incentivizing seatbelt use, and one plant also utilized awareness sessions for blue-collar workers. The plant without awareness sessions reported that seatbelt use doubled during the incentive

19 period, while the plant with both incentives and awareness sessions tripled seatbelt use for blue- collar workers. Consistent with Lewin’s (1951) theory, research examining traffic safety programs shows evidence that group discussions may be an effective activity to be incorporated into employer- based interventions. Social Cognitive Theory Social cognitive theory aims to explain behavioral change through control and reinforcement to achieve goal-directed and long-term behavior change (Bandura, 1977, 1991). One identified resource utilized social cognitive theory in regard to evaluating a driver training or educational program. A study reported in an unpublished master’s thesis used a driving simulation to examine student truck drivers’ confidence, safety, skill attainment, and cost savings (Anibas, 2008). The training was offered through Chippewa Valley Technical College and was eight to 10 weeks long. The purpose of the thesis was to evaluate the addition of virtual simulation to the existing training. The evaluation incorporated the tenets of social cognitive theory by exploring student confidence levels through a survey measuring driver confidence (e.g., self-efficacy) following the simulation. The survey results found that there were statistically significant increases in 10 out of 11 measures of confidence, providing support for the use of virtual simulation in training (Anibas, 2008). Social Learning Theory Social cognitive theory is an expansion of social learning theories proposed by Rotter and Bandura (Bandura, 1977; Rotter, 1954, 1990). Social learning theories are predicated on the idea that behavior is learned. Two articles utilized social learning theory. Huang and Ford (2012) conducted a study to investigate whether a defensive driving training program for truck drivers could influence locus of control beliefs regarding crashes and ultimately improve behaviors. A total of 112 truck drivers enrolled in the training program and completed pre- and post-tests. Changes in driving locus of control were associated with statistically significant changes in safe driving behaviors. In another study, Calé (2012) based an intervention on social learning theory but also integrated the theory of cognitive dissonance. The study included 48 employees who drove as a function of their job at Dead Sea Works, a large potash plant in Israel. The intervention included an assessment of driving skills focused on assessing neuro-cognitive and psychological functions essential for driving. These results were shared with the participants, along with suggestions for improving driving. Participants also took part in three workshops and one project focused on promoting transportation safety in their community. The study found the intervention resulted in improvements in safety behaviors, such as an increase in drivers wearing a seatbelt from 5.2 percent to 49.8 percent (𝜒𝜒2 = 21.25; p < 0.0001). While traffic safety program research literature shows limited use of social cognitive theory and social learning theories, there is evidence that these theories can be helpful when developing training. The available evidence supports further research on the use of social cognitive theory to promote confidence along with skills. Health Belief Model As previously described, the health belief model is a psychological health behavior change model that provides a framework for understanding why individuals engage in healthy behaviors, as well as how to promote healthy behaviors (Rosenstock, 1966). The health belief

20 model was not used in the design of training or educational programs for employers or any professional driver traffic safety programs. The health belief model has been used as a basis in the evaluation of safe driving campaigns and the theoretical model on which some surveys have been designed (Adamos et al., 2013, 2014; Razmara et al., 2018). First, Adamos et al. (2013, 2014) evaluated the same national road safety campaign focused on fatigued driving among both professional drivers and other drivers. The campaign ran for a total of eight weeks through newspapers, electronic messaging panels, event ticket messages, messages on buses, and online. The evaluations were designed around the health belief model, with measures focusing on knowledge, behavioral beliefs, risk comprehension (e.g., perceived threat), behavioral intentions, past behavior, and self-reported behaviors before, during, and after the campaign. Following the campaign, professional drivers reported they were more likely to use rest periods when becoming fatigued while driving (p = 0.001). There were also significant differences in several of the components of the health belief model, including beliefs, risk comprehension, intentions, and self-reported behaviors (Adamos et al., 2013). Adamos et al. (2014) discussed the importance of considering past behavior when measuring professional drivers’ likelihood of resting when fatigued. Drivers do not respond to campaigns in the same way, and past behavior is an important response predictor. When predicting past behavior of falling asleep at the wheel, variance was associated with behavioral beliefs, risk comprehension, and behavioral intention. Next, Razmara et al. (2018) conducted a survey to determine factors associated with safe driving among 184 taxi drivers. While the researchers did not conduct a training or program, their survey was designed based on the health belief model. Cues to action (r = 0.38), perceived benefits (r = 0.37), and perceived barriers (r = −0.31) were all significantly correlated with safe driving. In addition, multiple regression revealed that these components accounted for 31 percent of the variance in safe driving behavior. The authors simply noted that the findings of the survey resulted in recommendations for future campaigns and programs for taxi drivers to take into consideration the health belief model. Existing literature did not contain any utilization of the health belief model to develop an educational training or program that addresses occupational driving safety. However, the model has been used to evaluate media campaigns and determine factors associated with safe driving. These articles demonstrate how the health belief model can be used to understand the relationship between road safety campaign interventions and professional driver behavior by focusing on drivers at an individual level. Based on the available findings from the published articles, consideration should be given to incorporating the health belief model into future educational programs. The Transtheoretical Model of Change The transtheoretical model of change proposes that there are six steps required to change a behavior: precontemplation, contemplation, preparation, action, maintenance, and termination (Prochaska & DiClemente, 1983). The literature review identified seven articles that addressed occupational driving and the transtheoretical model of change. Of these, three had a training or educational program based on this model. To address body weight and driving concerns among truck drivers, two articles reported on the impact of the same intervention with a basis in the transtheoretical model of behavior change (Olson et al., 2009a, 2009b). The intervention consisted of a body weight loss competition, safe driving competition, computer-based training, and motivational interviewing.

21 The computer-based training units began with information that addressed the contemplative and preparatory stages, then progressed to include information for the action and maintenance stages. In addition, the motivational interviewing component involved working with drivers individually to increase their likelihood of engaging with the safety program (Olson et al., 2009a, 2009b). There were significant improvements in weight loss, body mass index (BMI), fat and sugar consumption, and hard braking among those in the intervention group. Rowland et al.’s (2009) intervention, founded in the transtheoretical model of change, was designed to spark behavioral changes by assisting taxi drivers with using a diary to understand traffic risks. The study found that following the driving diary program, participants reported safer behaviors and attitudes, as well as safer perceptions of the safety climate and driver pressure issues. These findings should be interpreted with caution due to a small sample size (n = 24) and the short period (time period not specified in conference proceeding) between the pre- and post-surveys. In addition, two articles described surveys, based on the transtheoretical model of behavior change, designed to evaluate an employer-based training. Most recently, Pylkkönen et al. (2018) conducted an alertness training for long-haul truck drivers that had an evaluation component. Specifically, the survey focused on changes in skills and competencies by evaluating the participants’ stage of behavior change before the training (e.g., five to six months before intervention), two months after the training, and at follow-up (e.g., four to five months after intervention). The multilevel regression models found no significant intervention-related changes. Roberts and York (1998) designed and evaluated a driver wellness program for commercial bus and truck drivers in the United States. Their survey included questions adapted from the transtheoretical model of behavior change. The topics identified through the survey guided the development and content of the program. In addition, the transtheoretical model of behavior change was included in an information booklet that provided four steps corresponding to the stages. This study focused largely on improving the health of employees and not on driving outcomes. There was also one article that included interview questions based on the transtheoretical model of behavior change. Banks et al. (2008) examined the utility of the transtheoretical model of change in understanding employee driver behavior changes. The study hypothesized that (a) the model would provide a method for identifying employee readiness to engage in change, and (b) the theory would provide a framework for explaining perceived effectiveness of safety initiatives. The study consisted of interviews of professional drivers aimed at assessing the participants’ stage of change. The study found that the theory could provide a framework for classifying employee readiness to engage in road safety behavior change. In addition, employees’ perceptions of safety initiative effectiveness varied in relation to the individual’s stage of readiness. Managers and employees may not be in the same stage of change due to the fact that managers spend more time in contemplation and preparation phases prior to an initiative compared to employees. One study used the transtheoretical model of change at the organizational level. Lang et al. (2009) developed and evaluated the Work-Related Road Safety (WRRS) CD-ROM. The CD-ROM was developed for managers of organizations with vehicle fleets. It provided case studies, as well as information on why and how to manage work-related road safety at an organizational level. Interviewees were given four statements and asked which statement described their organization’s position before and after the intervention to assess their stage of change. The project found that the developed CD-ROM was used differently by participants

22 based on the stage of change they were in; thus, individual differences should be considered. For example, those in the action stage used the material to make changes or update their existing procedures, whereas those in the contemplation stage used the material to develop an actual procedure. The transtheoretical model was found to be used in occupational traffic safety training or educational programs that address both individual- and organizational-level factors believed to be related to traffic safety, indicating that the theory has merit for changing employee driving behaviors. Theory of Planned Behavior The theory of planned behavior describes how behaviors are guided by behavioral intentions, which are based on attitudes, subjective norms, and perceived behavioral control (Ajzen, 1985). Eleven articles referenced both the theory of planned behavior and professional drivers. Of the identified articles, three specifically included a driver safety training or program that was evaluated using the theory of planned behavior (Adamos & Nathanail, 2015, 2017; Sunmola, 2014). Two articles evaluated the same fatigue management training conducted with 162 professional drivers at a Greek building materials company (Adamos & Nathanail, 2015, 2017). Earlier work by Adamos utilized the health belief model. The fatigue management training consisted of a two-hour training, open discussion, as well as recommendations to visit a sleep clinic to be tested for potential sleep apnea. To evaluate the program, participant responses were collected via survey before and two months after the training to assess the impact the program had on participants’ attitudes toward the risks of driving while fatigued, their beliefs about the safety of potential fatigue management strategies, and their intentions for managing fatigue in the future. The surveys were developed around the extended theory of planned behavior, which also explores the role of past behaviors and descriptive norms (Forward et al., 2009). The pre-post tests found that the training significantly increased knowledge (p = 0.000). Ordinal variables also had a positive direction of change for behavioral beliefs, risk comprehension, and behavioral intentions. These studies found that the theory of planned behavior was helpful in understanding driver behavior before and after the training program (Adamos & Nathanail, 2015, 2017). The studies also support that individual differences should be considered when implementing an intervention. For example, drivers may require training using different components of the theory of planned behavior based on different histories and feelings toward traffic safety risks, such as fatigue. In addition, a doctoral dissertation by Sunmola (2014) explored three behavioral theories—social cognitive theory, theory of reasoned action, and theory of planned behavior—to better understand the influence of Nigeria’s Federal Road Safety Commission’s (FRSC’s) enlightenment program on commercial drivers’ behavior. The purpose was to determine the effectiveness of the program; ultimately, the dissertation focused on using the theory of planned behavior to explain the changes in commercial drivers’ behaviors. The enlightenment program included television, radio, motor park rallies, billboards, and other outreach efforts. Evaluation was done through survey questions based on the theory of planned behavior, focus group discussions, and interviews. The evaluation found the program had significant effects on drivers’ behaviors (p < 0.05), and 87 percent of the variation in behavior was accounted for by the program.

23 Whereas a limited number of articles discussed programs developed or evaluated based on the theory of planned behavior, several nonexperimental studies used the theory as a framework for a survey or interview (Bomel Ltd., 2004; Douglas & Swartz, 2009; Meng et al., 2015; Newnam et al., 2004; Newnam et al., 2008; Stewart et al., 2005; Swartz & Douglas, 2009; Warner et al., 2007; Wills et al., 2009). Meng et al. (2015) conducted a survey to explore the attitude of professional drivers in China on driving fatigue. The survey focused on characterizing attitudes but suggested using the findings for future educational opportunities. Douglas and Swartz (2009) developed a survey that was based on the theory of planned behavior and the general theory of marketing ethics to assess commercial motor vehicle (CMV) drivers’ attitudes toward safety regulations. The goal was to ultimately develop a measurement scale to assess attitudes toward safety regulations. The team found the initial measurement produced reliable scores, but this was not rigorously tested. The article also supports further exploration of the behavioral aspects of truck driver safety. Swartz and Douglas (2009) used the theory of planned behavior in a survey administered to 281 CMV owner-operators to predict five unsafe driving behaviors. Attitudes had a strong relationship with behavioral intentions (r = 0.48). Stewart et al. (2005) conducted a survey—designed around the theory of planned behavior—to better understand taxi drivers’ crashes. Interestingly, their survey had a section dedicated to training to determine if the drivers found the training useful and if they completed subsequent training. Unfortunately, the article focused on the development of the survey and did not present survey findings. Last, a study conducted for the Department of Transport in London included a survey of seven companies and their drivers to assess safety culture, as well as interviews of drivers to measure driver attitudes based on the theory of planned behavior. Questions focused on behavioral beliefs, normative beliefs, and control beliefs (Bomel Ltd., 2004). The study also reviewed company crash data in comparison to the survey and interview results. The study found that companies with the fewest negative drivers (attitude to driving safety) had the lowest crash rate, and those with higher negative drivers had higher crash rates. Whereas a majority of the traffic safety research literature including the theory of planned behavior did not include a training component, the research provides some evidence that the theory of planned behavior can be used for advancing the understanding of professional drivers’ safety behavior, as well as predicting unsafe driving behaviors. Other Theories The literature review identified four additional theories beyond the most commonly utilized behavioral change theories among employer-based behavioral driving programs: the antecedent-behavior-consequences (A-B-C) model, the elaboration likelihood model, Hockey’s cognitive energetical framework, and the theory of cognitive dissonance. The following sections briefly describe each theory and summarize the identified literature. Two articles utilized the Haddon matrix, commonly used in injury prevention, which aims to reduce injuries by exploring personal factors, vectors or agents (e.g., vehicles/equipment), and environmental factors (Murray et al., 2009, 2012). While the Haddon matrix is not a behavioral theory, the literature supports the use of the matrix in addressing occupational transportation safety concerns. The literature review also identified Cooper’s (2000) reciprocal safety culture model, which is discussed below in the Summary of Safety Culture and Safety Climate section.

24 Antecedent-Behavior-Consequences Model The A-B-C model consists of antecedents (e.g., cues for behaviors), behaviors, and consequences, as stated in the name (Ludwig & Geller, 1991, 2001). One article used the A-B-C model in the design and evaluation of an intervention. Newnam and Watson (2009) evaluated a work-related driver intervention focused on speed reduction. The intervention utilized a modified A-B-C model by using goal setting and providing feedback to achieve a reduction in self- reported driving speeds. The researchers found that the intervention group had a statistically significant reduction in speeding from pre- to post-test (p = 0.018), whereas the control group had a nonsignificant decrease in self-reported speeding. The findings support the use of the A-B- C model (e.g., awareness and feedback) in addressing speeding. Elaboration Likelihood Model The elaboration likelihood model contends that attitudes can be changed through the central route (e.g., intrinsic routes) and the peripheral route (e.g., extrinsic factors) (Newnam et al., 2006; Petty & Cacioppo, 1986). The model focuses on how persuasion can be achieved. One article explored using the elaboration likelihood model to evaluate fleet safety initiatives, including informational campaigns, among fleet managers and included a newsletter and an incentive program (Newnam et al., 2006). Data collection included surveying fleet safety managers. The results indicated that fleet managers had a positive attitude change if they also perceived the newsletter to be relevant. The authors contended that the findings support addressing attitude changes through improving information campaigns (Newnam et al., 2006). Hockey’s Cognitive Energetical Framework Hockey’s cognitive energetical framework aims to explore the effects of stress and workload on human performance or behaviors (Hockey, 1997). The literature review did not find articles that utilized the framework specific to a training or educational program; however, two articles utilized Hockey’s cognitive energetical framework to create a scale and questionnaire to measure occupational driver behavior. A new scale of occupational driver behaviors was developed based on Hockey’s cognitive energetical model (Newnam et al., 2011, 2012). The scale was tested to identify driver behaviors most likely to change with a driver being overloaded (e.g., fast, hard, large amount of work, limited time) (Newnam et al., 2011, 2012). The findings contributed to the validation of the scale, indicating a reliable and valid measure of occupational driver behavior. Theory of Cognitive Dissonance The theory of cognitive dissonance is a social psychology theory wherein cognitions (e.g., beliefs, ideas, knowledge) can contradict one another, and the contradiction will need to be addressed (Harmon-Jones & Mills, 2019). Calé (2012) based an intervention on the social learning theory but also integrated the theory of cognitive dissonance. The intervention, which included workshops, is described in detail in the previous section on social learning theory. The theory of cognitive dissonance was one of the goals of the workshops by having participants take on the role of promoters of safety. Implications for Educational Programs The four additional theories that were identified may be relevant for employer-based traffic safety programs. There is potential for future research efforts to explore these theories further.

25 Summary of Measures of Program Effectiveness The following section provides an overview of the measures of traffic safety training program effectiveness reported in the research literature. Effectiveness measures for driver safety programs fall into three general categories: those that rely on self-reported information, those that use “other-reported” data, and those that rely on organizational records or archived data. In many cases, a program evaluation will include measures from more than one of these categories. Self-reported measures are most often obtained through surveys of participants, generally before and after a training program or other intervention. Self-reported measures used to evaluate driver training programs may include one or more of the following: • Attitudes and perceptions, such as participants’ attitudes about driving risks or behaviors, opinions about effectiveness of a safety intervention, perceptions of safety culture, morale, and stress levels. • Behaviors and intentions, including participants’ reports of their past, current, or future driving behaviors; safety or health-related behaviors; and compliance with company policies. • Performance or outcomes, such as drivers’ own reports of their crash or incident history, close calls or errors, or other health and safety outcomes. The data for other-reported measures and knowledge assessments may come from vehicle monitoring systems, observations of driver behavior, participants’ responses to knowledge-related questions, or ratings of their performance on skills-related tests by someone else. Vehicle crash and incident reports and company, agency, or insurance records of crash- related costs and lost-time injuries are examples of archival data that can be used to evaluate the success of driver safety programs. Table 1 summarizes the frequency with which different types of effectiveness measures were used to assess the impact of employer-based driver safety and health training programs reviewed in the literature. Table 1. Measures Used in Training Program Evaluations. Effectiveness Measures Frequency in Reported Studies Self-Reported Data Attitudes, perceptions, beliefs 7 Behaviors and performance 10 Managerial changes 2 Other-Reported Data and Knowledge Assessments Responses to knowledge-based questions 3 Electronic monitoring 4 Observations of behavior 3 Archival Data Crash reports 3 Insurance claims/costs 1 Lost-time injury records 1 Self-Reported Measures The most frequently used measures in the reviewed studies involved self-reported data, usually in the form of participant responses to survey questions.

26 One measure of a program’s effectiveness can be a change in attitudes or beliefs of its participants. A training program on driving fatigue conducted with 162 professional drivers at a Greek building materials company compared participants’ responses to surveys conducted before and two months after the training, to assess the impact the program had on their attitudes toward the risks of driving while fatigued, their beliefs about the safety of potential fatigue management strategies, and their intentions for managing fatigue in the future (Adamos & Nathanail, 2015). In a review of 20 fleet safety programs across 12 companies in Australia, frequently reported outcomes included improved attitudes among drivers toward vehicle safety (Wright et al., 2005). Self-reported improvements in attitudes toward safety were also seen in questionnaires completed by ambulance drivers in Sweden after completing an e-learning tool called the Driver Access Recording Tool (DART) (Albertsson & Sundström, 2011). Self-reported behaviors or changes in behavior have also been used to rate training program effectiveness. In addition to improved driver attitudes regarding safety in the companies, several companies reported increased regulatory and safety compliance within their fleets following driver safety programs (Wright et al., 2005). In the post-training questionnaire for the e-learning DART, the participating ambulance drivers reported changes in their own driving behaviors following the training (Albertsson & Sundström, 2011). The DART tool utilizes sensors on the ambulance to record the route, which is viewed later using a website that helps to analyze drivers’ behavior (Albertsson & Sundström, 2011). In a research study with work-related drivers in Australia, drivers who completed a training program to reduce speeding later reported a decrease in speeding behavior, while a control group of drivers who did not participate in the training reported a nonsignificant increase in speeding during the same time period (Newnam & Watson, 2009). A research study of commercial driver safety in China compared self-reported frequency of 10 safety-related behaviors (such as remembering to carry a driver’s license, avoiding cell phone conversations while driving, and not slowing down in the fast lane) between drivers who had completed some form of driver safety training in the past and drivers who had not received training (Shi et al., 2010). Truck drivers who participated in the Safety & Health Involvement for Truckers (SHIFT) pilot study self-reported health-related behaviors such as exercise and dietary changes as part of the program’s effectiveness assessment (Olson et al., 2009a). The WRRS CD-ROM distributed to managers and drivers at 37 participating organizations in the United Kingdom was evaluated using a before-and-after survey that included participants’ self-reported driving errors (Lang et al., 2009). Minibus drivers in Lagos, Nigeria, self-reported their adherence to speed limits before and after their participation in a post-licensing training program (Okafor et al., 2014). While not a training program per se, a targeted outreach campaign intended to reduce speeding among community care nurses in an Australian nursing vehicle fleet was assessed based on nurses’ and supervisors’ self-reported changes in awareness and perception of speeding risks, as well as on self-reported changes in speeding behavior (Lewis & Newnam, 2011). A survey of commercial drivers in Nigeria examined the effects of FRSC’s public enlightenment program (PEP), a targeted outreach program that focused on good driving habits; drivers participating in the survey reported on their compliance with driving behaviors encouraged in the PEP (Sunmola, 2014). Additionally, participants’ subjective assessment of a program’s effectiveness may be used as a measure. The addition of a driving simulation module to an existing commercial driver’s license (CDL) course at Chippewa Valley Training College was evaluated in part through students’ reported confidence levels upon completing the course (Anibas, 2008). An

27 assessment of school bus driver training in Virginia surveyed drivers who had completed different types of driver training programs. Survey questions asked drivers for their assessment of the adequacy of the training they had received for their CDL, as well as their on-the-job crash histories (Crews, 1997). Drivers employed by a transport company in Melbourne, Australia, were asked how they perceived the effectiveness of post-license driving training courses that were implemented as part of a fleet management package (Manders, 1986). Bus drivers at a transit company in Finland who had completed a three-day training program were asked to assess the training’s effectiveness and to indicate whether the training duration was appropriate (Lähdeniemi, 1995). Shi et al.’s (2010) study used questionnaire responses to assess how well freight drivers remembered important topics from driver training they had received in the past, and how their recall varied according to how their training was administered. An e-learning module designed to educate commercial truck drivers in Wyoming about connected vehicle systems collected subjective evaluations from participants regarding the training’s effectiveness (Ahmed et al., 2019). Most self-reported measures used in program evaluations capture drivers’ individual employee attitudes and behaviors in response to the training or other intervention. However, some training programs that were targeted at fleet or other organization managers also relied on self-reported measures. Bus company managers in Rio de Janeiro who participated in training courses about bus-related crash risks reported subsequent changes in fleet management procedures; one company also reported a decrease in crashes (Braga & Sa, 1996). Fleet supervisors who participated in the newly developed Safety Management for the Occupational Driver (SMOD) program reported improvements in their leadership skills pertaining to fleet safety, as well as increases in their overall safety climate awareness (Newnam & Oxley, 2016). Other-Reported Measures and Knowledge Assessments Participant surveys can be a source of other-reported information through the inclusion of knowledge-based questions. The before-and-after survey used to assess the WRRS CD-ROM included knowledge-based questions about traffic safety; the percentage of correct responses to those questions before and after the training was used as one metric of the CD-ROM’s effectiveness as a training tool (Lang et al., 2009). The training evaluation for minibus drivers in Nigeria included questions about traffic laws and road signs to compare knowledge levels before and after the training (for the training group) and between the training group and a control group that did not receive the training intervention (Okafor et al., 2014). The connected vehicle e- learning module for truck drivers in Wyoming contained a quiz section to test participants on concepts covered in the module (Ahmed et al., 2019). The Michigan Center for Truck Safety used observations of truck driver behaviors as a pre-training assessment and as an evaluative measure following training. Observers used a standardized assessment tool to rate driver behaviors such as visual search patterns, speed control, and direction control (Irwin & Ford, 2005). An observational process was similarly used as an evaluative measure for behavior-based safety training programs at the BP Fabrics and Fibers plant in Georgia (Chandler & Huntebrinker, 2003) and at a construction company in China (Chen & Ren, 2015). Shi et al. (2010) employed observations and analyses of selected driver behaviors to assess each driver’s accident risk relative to the type of training he or she had received. Electronic monitoring has been used to measure certain types of driver behaviors before and after training programs. An in-vehicle event data recorder (EDR) recorded instances of

28 speeding and abrupt braking, along with other trip metrics, for drivers of a truck fleet in Brazil; metrics for each driver were collected before and after a training program that taught drivers about the use of the EDR as well as safe driving and eco-driving techniques (de Oliveira et al., 2019). A similar in-vehicle monitoring system measured steering, braking, and acceleration behaviors among bus drivers prior to and following a safety training program. These metrics were used to identify “normal” and “dangerous” drivers prior to training, to customize the training program for each participating driver, and to assess the effects of the training on drivers’ subsequent behaviors (Kim et al., 2016). Speeding and hard-braking events were recorded by in- vehicle monitoring systems as part of the SHIFT pilot study (Olson et al., 2009a). Electronic activity monitors worn by long-haul truck drivers in Finland measured the drivers’ sleep between duty hours during time periods before and after their participation in alertness management training (Pylkkönen et al., 2018). Archival Data Measures Archival data such as number of crashes and crash costs have been used in a few training program evaluations as a measure of program success. A defensive driving training program provided to all drivers in a Finnish bus company was evaluated in part through a comparison of company-wide crash numbers from the four years prior to the training versus the two years following the training (Lähdeniemi, 1995). Similarly, the evaluation of a fleet management package implemented at a Melbourne transport company examined crash rates for drivers before and after completing two post-license driver training programs (Manders, 1986). Some of the companies that participated in a review of heavy-vehicle fleet safety programs in Australia tracked changes in crash rates, crash costs, and/or lost-time injuries to assess the effectiveness of driver training and other safety interventions they had implemented (Wright et al., 2005). Program Effectiveness Summary A majority of the research studies examining traffic safety programs rely on self-report measures of attitudes and intentions; however, a handful of studies incorporated more rigorous measures like observational data and organizational records. When paired with more rigorous experimental study designs, the latter measures are likely to contribute to more confident conclusions about the value of any specific training program. SAFETY CULTURE AND SAFETY CLIMATE Industrial/organizational psychologists distinguish between safety culture and safety climate (Denison, 1996; Guldenmund, 2000). Safety culture is defined as shared assumptions, values, and beliefs that characterize an organization (Pettigrew, 1979; Schein, 1985). Theoretically, safety climate is the more proximal situational variable to behavior that can be measured with a questionnaire. However, the phrase safety culture is used much more frequently (yet erroneously) than safety climate in the safety literature. For this report, both terms were searched, and any sources found with either of the terms are included in the review. For summarizing the studies in this report, the terms used in the study are used here as well. Safety climate is one facet of organizational climate, which is defined as a set of shared perceptions about an organization’s policies, procedures, and practices about safety among the organization’s members (Reichers & Schneider, 1990). Raising awareness among occupational drivers and managers about the importance and benefits of prioritizing safety in occupational driving can be challenging, particularly when practices and programs appear to increase costs. A

29 survey of long-haul truck drivers in the United States found that many had experienced crashes (2.6 percent in the preceding year), near misses (24 percent in the previous seven days), and moving violations (17 percent in the preceding year), as well as high-risk behaviors such as driving while fatigued (24 percent) (Chen et al., 2015). Many of the responding drivers also reported inadequate training (38 percent) and unreasonably tight schedules (73 percent) (Chen et al., 2015). Safety climate as a factor in work-related driving may help to guide workplace countermeasures for reducing high-risk driving behaviors, to improve support of and compliance with safe driving programs and policies, and ultimately to reduce crashes and injuries associated with work-related driving. A study examining causes of and countermeasures for cargo tank truck rollovers identified safety culture as the “single best practice” an organization can develop for preventing rollover crashes (Pape, 2012). Several definitions and models of safety culture have been developed. Cooper’s (2000) reciprocal safety culture model, referenced in a number of organizational safety culture and safety climate studies, can be applied/adapted to a variety of settings. Cooper’s model illustrates reciprocal relationships among the person (psychological factors, perceptions), the situation (e.g., organizational policies, priorities, and communications; external factors), and observable behaviors (job tasks, driving tasks, decisions, errors, violations). This model provides a framework for assessing the elements within each of these three domains. Professional Driver Safety Culture/Climate Measurement Tools Several approaches have been developed to assess safety culture/climate within the context of employment-related driving. Wills et al. (2005) tested a modified version of the Safety Climate Questionnaire (SCQ) (Glendon & Litherland, 2001) with 231 employees from three different organizations and industries to assess its applicability to employee driver safety. Glendon and Litherland’s (2001) SCQ included communication and support, adequacy of procedures, work pressure, personal protective equipment, relationships, and safety rules as factors in workplace safety climate. Wills et al.’s (2005) modified questionnaire ultimately included communication and procedures, work pressure, management commitment, relationships, driver training, and safety rules as safety climate factors. Some of the scale items within the factors were also modified from the original SCQ to refer specifically to driver and motor vehicle safety. The analysis found the modified SCQ factors to be consistent elements of driving-related safety climate across all three organizations and also found that responses to questions about management commitment and driver training provided additional information about an organization’s overall safety climate (including aspects unrelated to driving). Rowland (2018) also developed a driving-focused version of the SCQ to use in a study of drivers employed at governmental organizations in Queensland, Australia. The Transportation Companies’ Climate Scale (TCCS) was developed to measure dimensions of organizational driver safety climate (Öz et al., 2013). The scale was tested, in conjunction with elements of the Manchester Driver Behavior Questionnaire (DBQ) and the Driver Skill Inventory, by surveying 223 professional drivers working for eight public and private transportation organizations in Ankara, Turkey. Based on survey results, the TCCS ultimately included 31 scale items grouped under three organizational factors: general safety management, specific safety-related practices and precautions, and work and time pressure. Safety culture within an organization traditionally includes elements that pertain to a shared work environment and regular interaction among coworkers and between workers and managers or supervisors. Huang et al. (2013) developed a safety climate scale specifically for

30 “lone workers,” such as long-haul truck drivers, who spend most of their working time away from others in their organization and communicate only remotely with managers or supervisors. The modified scale, tested with 8,095 truck drivers from eight companies, identified three organizational-level safety climate dimensions (proactive practices regarding driver safety, driver safety priority, and promotion of supervisory care) and three group or supervisor-level dimensions (safety promotion, delivery limits, and cell phone disapproval) that predicted driver behaviors (Huang et al., 2013). Driver behavior questions are often asked in conjunction with safety climate assessment questions to identify relationships between a driver’s behaviors and his or her perceptions of safety climate. The DBQ includes questions about specific driving errors and violations and how frequently a driver commits each of those (Reason et al., 1990). Sullman (2003) employed the DBQ when studying the relationships of individual personality traits and safety climate on the behavior of New Zealand truck drivers. Caird and Kline (2004) used a version of the DBQ that included only driver errors (not violations) in their study of safety among corporate drivers in Canada. Öz and Lajunen (2008) used the DBQ, along with their Positive Driver Behaviours Scale (Özkan & Lajunen, 2005), in a study of safety culture among professional taxi and cargo drivers in Turkey. Newnam and VonSchuckmann (2012) developed the Occupational Driver Behaviour Questionnaire (ODBQ), based on the DBQ, as a tool for collecting self-reported driver behaviors specific to the workplace environment. Rowland (2018) used the Modified Driver Behavior Questionnaire (MDBQ), which includes additional behaviors related to fatigue, distraction, and multitasking (Banks, 2008; Freeman et al., 2003). Seibokaite and Endriulaitiene (2012) used the SCQ, along with the Big Five Inventory (personality traits), the DBQ, and a work motivation questionnaire, in their study of 166 professional drivers in Lithuania. Several studies of safety climate in the context of occupational driving measure driver attitudes about safety. Rowland (2018) employed the Driver Attitude Questionnaire (DAQ) (Parker et al., 1996) in a study of light-vehicle drivers at governmental agencies in Australia. The DAQ, based on the theory of planned behavior, addresses driver attitudes toward impaired driving, tailgating, risky passing/overtaking maneuvers, and speeding. Bomel Ltd. (2004) used the Health and Safety Executive’s (HSE’s) Health and Safety Climate Survey Tool (HSCST) to assess elements of organizational safety climate among drivers, managers, and non-driving staff at seven companies (HSE, 1997). Safety climate factors identified by the HSCST include organizational commitment and communication, line management commitment, supervisors’ role, personal role, workmates’ influence, competence, risk-taking behavior and contributory influences, obstacles to safe behavior, permit-to-work systems, and reporting of accidents and near misses. Assessments of Professional Driver Safety Culture/Climate Arboleda et al. (2003) surveyed employees at three hierarchical levels (drivers, dispatchers, and safety directors) within 116 trucking firms about their perceptions of the importance of safety in their organizations. The results indicated that driver fatigue training, driver opportunity for safety input, and top management commitment to safety were the factors that significantly influenced perceived safety culture among employees at all three levels. Boyle et al. (2010) surveyed 30 safety managers (25 at trucking companies, five at motor coach companies) on their perceptions of safety and safety climate as it pertained to their companies and industries. Four factors emerged that together accounted for 81.8 percent of the variance in the managers’ perceptions of safety: the financial impact of safety (27.3 percent of

31 variance, α = 0.68), internal awareness of safety (19.4 percent of variance, α = 0.62), demand for safety among the drivers (17.6 percent of variance, α = 0.59), and safety culture in the industry (17.5 percent of variance, α = 0.69). A study by Murphy et al. (2018) examined a variety of issues within the trucking industry to identify those that had an effect on safety climate. Kleiner’s macroergonomic analysis and design framework was used to develop the protocol for qualitative interviews with 28 representatives (drivers, supervisors, operations personnel, executives, and safety personnel) from two long-haul trucking companies. In all, 19 themes regarding participants’ areas of concern pertaining to jobs, roles, conflicts, challenges, and priorities were identified from the initial interview results; a subsequent set of interviews with the same participants ranked those themes in importance. The ranked list of themes was then compared to the trucking-specific safety climate scale developed by Huang et al. (2013). Several of the themes ranked highest by trucking-industry representatives did not match up with any of the safety climate elements from Huang et al.’s scale, including balancing work and family personal time and sense of belonging in the company. The study indicates that while safety climate is considered important, there are other considerations for those working in the trucking industry that should be factored. Bin Mahamad Husin and binti Raml (n.d.) surveyed 41 bus drivers in Kuala Lumpur, Malaysia, to examine the relationship between the drivers’ self-reported work commitment and their perceptions of safety. The survey results showed that there was no significant correlation between the two factors; however, the study was limited by a small sample size and the use of a translated rating scale that was tested in the United States. Spielholz et al. (2008) examined 359 trucking-industry employers’ and 397 truck drivers’ perceptions of safety culture as part of a study that also examined other aspects of non-crash- related injuries and illness among commercial truck drivers. Survey responses to nine safety climate measures revealed that the employers perceived safety climate more positively than did drivers; for example, 98 percent of trucking company employers agreed with the statement “workers’ safety practices are important to the management of my company,” while 69 percent of drivers agreed with the statement. The largest difference was seen in responses to the expectation of being in a crash or being injured in the next year with 2 percent of employers agreeing and 42 percent of drivers agreeing. Freeman et al. (2016) conducted an online safety climate survey with 679 employees from four organizations in Australia. The questionnaire asked participants to rate the fleet safety climate within their organizations using a 36-item fleet safety climate scale developed by Freeman et al. (2006). It also included questions about the participants’ own crash involvement and traffic-related fines over the past 12 months and their ratings of potential effectiveness of various fleet safety-based initiatives. Results indicated that safety culture was correlated with participants’ perceptions of effectiveness of certain safety initiatives, but not with their self- reported crash involvement or traffic fines. Rowland (2018) explored safety culture among light-vehicle drivers working for multiple government agencies in Queensland, Australia. The three-part study explored factors that influenced roadway safety for work-related driving, analyzed specific risk factors, and examined barriers to and facilitators for potential interventions to improve work-related roadway safety. The authors found that organizational priorities and procedures were highly influential in the overall safety culture for work-related driving and could be significant barriers to or facilitators of the success of any interventions attempted. Major barriers to improving the safety culture within an organization included the prioritization of production over safety, lack of management

32 commitment to and support of driver safety, and poor communication with employees about driving safety. Safety Culture/Climate Effects on Driver Behavior and Outcomes The effects of safety culture and climate on driving safety can be measured by reductions in crashes and injuries, and/or in terms of driver behaviors. Driver behaviors measured in prior studies have included errors, violations of traffic laws, and decisions related to distraction, fatigue, and seatbelt use. A survey of 323 drivers in three fleets in Queensland, Australia, examined the relationships of six dimensions of safety culture (communication and procedures, work pressures, relationships, safety rules, driver training, and management commitment) to occupational driving outcomes including traffic violations, driver errors, distracted driving, and pre-trip vehicle maintenance. Results indicated that all six safety culture dimensions were significantly related to driver safety, and that safety culture was a stronger predictor of their work-related driving behavior (r = 0.42) than other driver-based (sociodemographic, psychological) factors (Wills et al., 2004). Safety rules, communication and procedures (particularly communication regarding safety), and management commitment to safety were especially predictive of safe driving behaviors, and safety culture was most strongly associated with self-reported driver distraction (Wills et al., 2006). A later study again explored the influence of safety culture on fleet drivers based on the theory of planned behavior and Cooper’s reciprocal safety culture model. The survey specifically addressed attitudes, behavioral intentions, and subjective norms, and found a moderate relationship between safety culture with safety of a current driver (r = 0.40) and future driving intentions (r = 0.29). A logistic regression model illustrated that attitude was a stronger predictor than safety climate for future driving predictions, β = 0.28 and β = 0.18, respectively (Wills et al., 2009). Seibokaite and Endriulaitiene (2012) found that drivers who were more socially oriented (as measured by the Big Five personality inventory) were also more influenced by safety climate, compared to drivers who scored higher on the neurotic scale (e.g., were less emotionally stable). In a survey of 73 taxi and freight drivers in Turkey, Öz and Lajunen (2008) found that drivers’ perceptions of general safety climate within their companies were negatively correlated with DBQ-specified driving errors (r = −0.34, p < 0.01) and crashes (r = −0.26, p < 0.05). Newnam and VonSchuckmann (2012) administered the DBQ and the ODBQ, plus questions regarding workplace safety climate and role overload, to a sample of 248 drivers from a community nursing program in Australia. Study results showed that participants’ responses to safety climate and role overload questions were significant predictors of driving errors and violations as recorded in DBQ and ODBQ results; however, safety climate and role overload accounted for a greater percentage of the variance in ODBQ results (11 percent) than in DBQ results (7 percent). Öz et al.’s (2013) survey of 223 drivers using the TCCS found significant relationships between the safety climate scale factor “work and time pressure” and driver violations and errors, and between the factor “general safety management” and driver safety skills. Sullman’s (2003) survey of 382 New Zealand truck drivers found significant negative correlations between perceived safety climate and driver errors, violations, aggressive violations, lapses, inconsiderate driving behaviors, and risky driving. A later survey of 339 New Zealand truck drivers found that safety climate significantly predicted risky driving behaviors, which in turn predicted drivers’ involvement in crashes (Sullman et al., 2017).

33 Varmazyar et al.’s (2016) survey of 628 bus drivers from a public transportation company in Iran found that safety culture factors (e.g., leadership style, values, safety policy) were all significantly and negatively correlated with crash involvement. Organizational support for safety was an indirect predictor of on-the-job crashes and fatigue in a survey of professional truck drivers in Canada (Caird & Kline, 2004). Bomel Ltd.’s (2004) safety climate assessment of seven companies in the United Kingdom included a survey of 283 drivers, managers, and non- driving staff at the participating companies, plus qualitative interviews with a subset of survey participants. The data collected were largely qualitative but pointed to a moderately strong relationship between safety climate and driver attitudes regarding work-related driver safety. The authors also found, however, that general safety climate within an organization was not sufficient for reducing on-road risk unless a driving safety component was specifically included in the organization’s safety programs and systems. The effects of safety climate on driving behaviors may be very different depending on the level of interaction drivers have with coworkers and supervisors. Newnam et al. (2008) used Neal and Griffin’s (2006) safety motivation scale in an examination of how safety motivation and perceived safety values at multiple levels of an organization affect the on-road behaviors and the safety records of fleet drivers. The survey, administered to 380 drivers, 88 workgroup supervisors, and 47 fleet managers in Australia, found that not only did drivers’ own motivations regarding safe driving predict their likelihood of crashes but also drivers’ motivations to drive safely were increased by the perceived value that supervisors and fleet managers placed on safety. Zohar et al. (2014) surveyed long-haul “lone worker” truck drivers to examine effects of safety climate antecedents (such as leadership from dispatchers and the drivers’ level of ownership in their work) on their trucking safety climate perceptions, and ultimately on their driving behaviors. The survey found that distant-leadership style (characterized by responses to the Leader-Member Exchange questionnaire, or LMX-7) and drivers’ perceptions of work ownership influenced drivers’ perceptions of safety climate. Distant-leadership style, work ownership, and driving safety were significantly related to trucking safety climate. Whereas trucking safety climate was not directly related to hard-braking frequency, it was indirectly related through driving safely. Using a subset of data from the 2014 study (3,841 truck drivers), Zohar et al. (2015) examined the influences of perceived organizational safety climate (likened to extrinsic motivation) and employee engagement (likened to intrinsic motivation) on driving safety among long-haul truck drivers. Both safety climate and employee engagement predicted safe driving behaviors and reduced road injuries. Furthermore, in a favorable organizational safety climate, employee engagement had no significant effect on driver safety, but in a less favorable safety climate, a higher level of employee engagement significantly improved driver safety and outcomes. Swartz and Douglas (2009) found that organizational safety climate had less influence among independent (owner-operator) truck drivers who hauled loads via contract, compared to truck drivers who were employees of an organization. A survey of 281 independent truck drivers found that the only elements of a client/contracting organization’s safety climate that influenced drivers’ behavioral intentions were “supportive” safety practices such as training or safety communication/outreach programs. Other elements of safety climate, including subjective norms and directive practices, had no significant effect on independent drivers. A study by Şimşekoğlu and Nordfjærn (2017) provided an example of how safety culture can vary across different jobs in the same industry. A survey of truck and tanker drivers in the

34 Turkish petroleum industry found very different safety cultures exhibited in the two groups: tanker drivers, who transport highly flammable substances such as oil or liquid petroleum gas, were more highly influenced by safety culture factors than were truck drivers, who transport less-dangerous materials. Tanker drivers also tended to report better perceptions of traffic risk and lower frequencies of unsafe driving behaviors compared to truck drivers. Safety climate has been studied in conjunction with specific unsafe driver behaviors such as driving while fatigued and driving distracted. Morrow and Crum (2004) examined factors leading to driver fatigue among commercial drivers in the United States, including elements of commercial driver safety culture that may contribute to drivers’ violations of hours-of-service regulations designed to reduce fatigued driving. Drivers’ perceptions of a weak safety climate were associated with a greater frequency of fatigued driving (β = −.25, p < .01). Other results suggested that a strong safety climate may have the potential to mitigate factors leading to fatigued driving. Strahan et al. (2008) examined the effects of safety culture and occupational stress on driver fatigue through a survey of 219 drivers from two governmental organizations in Australia. The survey combined questions from Kahn et al.’s (1964) job-related tension scale and Glendon and Litherland’s (2001) SCQ, as well as questions pertaining to fatigue-related behaviors and near-miss incidents over the past six months. The study found that occupational stress and safety climate accounted for 29 percent of the variance in self-reported fatigue and associated behaviors. In addition, these factors were significant predictors of near misses associated with fatigued driving. From an online survey of 239 truck drivers representing multiple U.S. companies, Swedler et al. (2015) found that lower safety climate scores for drivers were significantly associated with crash involvement, as well as with distraction-related swerving. Chung and Wong (2011) examined personal and environmental factors affecting the health of professional bus drivers. A survey of 785 bus drivers collected information on demographics, driving experience, working environments, physical and psychological conditions, and specific health problems. The study’s results identified perceived company safety culture as one of the factors significantly affecting participants’ self-reported health status. Evaluating Traffic Safety Interventions Using Safety Culture/Climate Metrics Safety training programs have been shown to improve safety culture practices and perceptions within organizations. In their evaluation of the WRRS CD-ROM training program, Lang et al. (2009) conducted assessments of before-and-after practices associated with managing WRRS in the participating organizations. The baseline evaluation before the CD-ROM program found that small and medium-sized private-sector organizations tended to have stronger safety cultures than did large private-sector and public-sector organizations, as evidenced by existing safety rules and procedures and managers’ knowledge of them, and by managers’ and drivers’ attitudes regarding the importance of safe driving behaviors. Following the training provided via the CD-ROM, participating large private-sector organizations showed some improvements in safety culture, more closely matching the baseline levels of the smaller private-sector organizations; large public-sector organizations did not improve as consistently. Banks et al. (2006) found that fleet drivers’ perceptions of safety climate in their organizations were higher when those organizations provided driver safety education. Specifically, drivers associated employer-provided driver education with more positive perceptions of organizational commitment to safety, appropriate work demands, trusting relationships, and good communication.

35 Newnam and Oxley (2016) developed and tested the SMOD training program, which focused on improving supervisors’ knowledge about their role in the safety climate and their skills in communicating and promoting safety to drivers. The program was based on earlier research that identified the roles of supervisors in safety management of occupational drivers (Newnam et al., 2008, 2012). The SMOD was piloted with 36 supervisors, with before-and-after data collected from eight participants regarding their levels of prosocial motivation for managing driver safety among their employees, levels of confidence in their driver safety leadership, attention to safety climate, and clarity regarding their roles and responsibilities in managing work-related driver safety. Although results were limited by the size of the sample, improvements in each of these metrics were reported by a majority of participants. Surveys of 182 taxi drivers in Queensland, Australia, collected self-reported data about the drivers’ attitudes toward safety and about their driving behaviors before and after a driving diary intervention (Rowland et al., 2009). In the survey following the intervention, participating drivers showed improvements in self-reported attitudes, safety perceptions, and driving behaviors. Olson et al. (2009a) examined both safety climate and health climate among 29 long- haul truck drivers as part of the SHIFT pilot study. Surveys of participating drivers before and after the health and safety intervention program included participants’ ratings of safety climate within their companies. The study found that safety climate ratings from the participants were positively correlated with safety-related behaviors such as safety belt use (r = .50, P = .006). LITERATURE REVIEW SUMMARY This literature review summarized the current state of the research concerning employer- based behavioral traffic safety programs and identified the types and extent of behavioral change theories and measures of program effectiveness currently in use. The role and relevance of safety culture/climate in these studies was also identified. A limited number of studies of employer-based behavioral traffic safety programs explicitly cited behavioral change theories. However, nine different theories were cited in this body of literature: social cognitive theory, social learning theory, health belief model, transtheoretical model of change, theory of planned behavior, A-B-C model, elaboration likelihood model, Hockey’s cognitive energetical framework, and theory of cognitive dissonance. The latter four theories were less likely to be cited within the context of employer- based traffic safety programs. Four theories were cited in relation to designing a training or educational program: transtheoretical model of change, theory of planned behavior, A-B-C model, and social learning theory. Four articles reported on studies of programs that based their training or education program on the transtheoretical model of change (Lang et al., 2009; Olson et al., 2009a, 2009b; Rowland et al., 2009). The theory was applied at both the individual and organizational level. Three articles reported on studies of programs that based their training or educational program on the theory of planned behavior with application at the individual level (Adamos & Nathanail, 2015; Adamos & Nathanail, 2017; Sunmola, 2014). Two other theories, social learning theory (Calé, 2012) and the A-B-C model (Newnam & Watson, 2009), had one article each that included a training or educational program. Calé (2012) also included the theory of cognitive dissonance. Taken together, there is evidence that some traffic safety programs are based on behavioral change theories, but there is insufficient research evidence to determine the relative effectiveness of theory-based programs compared to each other or to non-theory-based programs.

36 Measures of program effectiveness for driver safety can be organized into three categories: self-reported measures, other-reported measures, and archived data. The most common measures were self-reported data, including information on attitudes, perceptions, beliefs, behaviors and performance, and managerial changes. Self-reported data were most frequently obtained through surveys. Several studies relied on theories to guide the variable included in the study, including attitudes, perceptions, knowledge, and behaviors. These theories were the social cognitive theory, social learning theory, health belief model, elaboration likelihood model, and Hockey’s cognitive energetical framework. These studies found that the use of these behavioral change theories improved occupational driver safety, thus supporting future research on the design of programs using these theories. The need to consider individual driver differences when designing employer-based behavioral traffic safety programs was a key finding in the literature (Adamos & Nathanail, 2015, 2017). Thus, programs designed to be a one-size-fits-all package may not be as effective as others. The literature indicates the concept of safety climate, properly understood in all its dimensions, is critical. A review of relevant articles that discussed safety climate in the field found four overarching themes: safety climate and the effects on driver behaviors, perceptions of safety climate, use of safety climate to evaluate interventions, and use of safety climate metrics to design assessment tools. In summary, the review of the literature described the current state of the practice as follows: • There is limited explicit use of behavioral change theory in designing or evaluating employer-based driver safety programs. • Evidence of the effectiveness of behavioral change theory in general exists but is insufficient to determine the relative effectiveness of the specific theories. • Many nonexperimental traffic safety program studies rely on survey methodology and incorporate behavioral change theory variables. • General or one-size-fits-all driver safety programs may not be effective for employee- based programs, based on behavioral change theory’s demonstration of the need to consider individual differences (e.g., stage of change). • Safety climate captures employees’ perceptions of what the organization rewards and supports. Safety climate is consistently associated with both safe and unsafe driver behaviors, the importance of safety, and the effectiveness of traffic safety programs. • Relatively few traffic safety programs have undergone a rigorous evaluation using a between-subjects experimental study design (experimental vs. control group) or a pre- post within-subjects experimental study design.