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Improving Safety-Related Rules Compliance in the Public Transportation Industry (2011)

Chapter: Chapter 2 - Understanding Rules Noncompliance

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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Suggested Citation:"Chapter 2 - Understanding Rules Noncompliance." National Academies of Sciences, Engineering, and Medicine. 2011. Improving Safety-Related Rules Compliance in the Public Transportation Industry. Washington, DC: The National Academies Press. doi: 10.17226/14593.
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Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

A significant body of research exists regarding the factors that influence safety-related rules noncompliance including the reasons underlying errors and violations and ways to mitigate non- compliance. This chapter summarizes factors and mitigation strategies that are applicable to public transit operations. It describes the factors from a bottom-up perspective, concluding with a discussion of the role of safety culture and safety management in the rules compliance process. Framework for Understanding Noncompliance Just as there is no single cause of an accident, reasons for noncompliance are multifaceted. Non- compliance can be willful, a violation, or it can be unintentional, resulting from human error. Numerous error and violation taxonomies exist that differentiate among the underlying causes of noncompliant behavior. A popular error classification system, known as the skill-, rule-, knowledge-based (SRK) approach, was based on information processing models and is described in a number of publications (Rasmussen 1979, 1980, 1986; Reason 1990). Figure 1 presents an adaptation of the SRK model and includes other types of error classifications in the context of human information processing. Knowledge-based errors occur when someone does not have the correct mental model or infor- mation to assess a situation, resulting in formation of an incorrect plan of action. These errors often occur when an individual has to work out solutions to a problem from “scratch.” High pressure situations exacerbate problem solving by reducing cognitive resources. Inexperienced employees often fall prey to these types of errors. In contrast, rule-based errors occur when an employee has a clear understanding of the situation, but either chooses an incorrect plan to deal with the situation or mis-executes a well-chosen plan. The outcome is poor. These types of decision-based errors arise when an employee is not adequately trained via classroom and field exposure to handle unexpected situations; the employee does not possess the strategies needed to address low-frequency events. Rule-based errors do not refer to an organization’s rules. Rather, rules in the context of the SRK model refer to decision-making strate- gies a person has. (To prevent confusion regarding the term rules, the term strategy-based pro- cessing/errors is used in lieu of the term rule-based for the remainder of the report.) Skill-based errors, also known as slips, occur when performance is highly automatic (as indicated by the dashed line in Figure 1) and a cue in the operational environment triggers the behavior at an inappropriate time (Norman 1981). While slips are errors of commission, lapses are errors of omission, resulting from memory failure. DiFiore and Cardosi (2006) found pilot reports of air traffic control (ATC) personnel who forgot that aircraft were holding in position on the runway (a lapse) and cleared another aircraft to land on the same runway. Employee dis- traction, workload, and fatigue are among the risk factors for these types of incidents and are discussed in subsequent subsections. 6 C H A P T E R 2 Understanding Rules Noncompliance

Reason (1997) makes an important point that “a purely cognitive analysis of error mecha- nisms fails to capture some of the more important human contributions to [accidents]” (p. 204). An examination of violations, that is, deliberate acts of noncompliance, fills this gap. The Uni- versity of Texas has developed a methodology to examine flight operations, the Line Operational Safety Audit (Helmreich 2000). The data from these studies indicate that more than one-half of the in-flight noncompliance observed was intentional. Lawton (1988) distinguishes among three types of violations: situational, exceptional, and routine. The classification is based on data obtained from a survey of United Kingdom (UK) rail shunters’ experience with rule noncompliance. (In the UK, shunters refer to people who work on the ground switching cars in a railroad yard.) For the most part, Lawton argues that viola- tions tend to be perceived as well-intentioned desires to get the job done. Situational violations result from motivations to keep the job going under adverse conditions. There is often an incon- sistent approach to dealing with these types of violations. That is, when the job is completed without incident, the employee is rewarded. However, if an accident occurs, the response is often disciplinary action. This inconsistent response does little to curb these types of violations. Situational violations are frequently observed in the public transportation industry because of the time pressure employees feel trying to adhere to schedules. Exceptional violations occur when unusual circumstances call for an unusual response and the employee knowingly does not comply with the organization’s rules and chooses an alternative action. Routine violations occur when a shortcut presents itself and is taken regularly. This often happens when an employee no longer thinks a rule applies either because of lack of supervisory enforcement or the employee is overconfident in his or her skill. Incident taxonomies provide a framework to identify reasons for noncompliance with safety- related rules and guide appropriate countermeasures. The Human Factors Analysis and Classifi- cation System (HFACS) is a well-known error and violation taxonomy used in aviation and served as the basis for the pilot safety reporting system in the railroad industry that is reviewed in Appen- dix C (Wiegmann and Shappell 2001). With an understanding of the underlying reason, a public transit agency supervisor or safety officer can determine the appropriate strategy to correct or man- age noncompliance. For example, did noncompliance occur because the employee did not under- stand the situation and unintentionally failed to comply (knowledge-based error)? Training is a possible remedy when this is the cause of noncompliance. Was there a willful decision by the employee to disobey the rules because the organization placed more emphasis on getting Understanding Rules Noncompliance 7 Figure 1. Information processing model of human error.

the job done on time than on its safety policies (situational violation)? In this circumstance, the organization’s safety culture may be the cause. Perhaps an employee consistently chooses not to comply because he or she did not understand why the rule is required (routine violation). Closer enforcement and explanation of the rules may prevent this behavior. The following sections describe factors and countermeasures known to influence noncompliance. Perceptual Errors Perception is a psychological construct that describes the neural processes that transform sensory information that enters the brain from sensory organs (e.g., eyes, ears). Most research on perception involves vision and audition (or hearing). Perception occurs as the result of both bottom-up and top-down processes. Bottom-up processing refers to the brain’s ability to com- bine simple, bottom-level features that allows humans to recognize more complex whole patterns. Bottom-level features are the individual components that make up a representation. Visually, it is the simple lines and shapes that form more complex patterns, like a face. An aural example is phonemes, or individual sounds, that make up words. Many times, however, information in our environment at the bottom-level is degraded or obscured. Through top-down-processing, in the form of expectation, the brain fills in the missing information. Top-down processing refers to the brain’s ability to use a person’s knowledge about how the world is organized to identify patterns (Proctor and Van Zandt 1994). Top-down processing provides humans with an efficient way to process in-coming informa- tion. If all information were processed piecemeal as it would be in a totally bottom-up system, human information processing would occur too slowly to allow humans to be able to respond to safety-critical situations, a highly adaptive feature. However, there is a disadvantage regard- ing the role of expectation with respect to safety-critical situations. A person’s expectations, which are based on previous experience, can lead to error (Green 2003). A relevant example of error arising from expectation occurs in the runway environment. Pilots are often familiar with the standard taxi routes at the airports they frequently fly to. However, due to unexpected operational changes, air traffic controllers sometimes instruct pilots to tra- verse a different taxi route. There are reports that describe the scenario where pilots will hear and confirm the non-standard taxi route, but during execution, they will revert to the more familiar taxi route (DiFiore and Cardosi 2006). Often times, they report that they heard what they expected. Expectation is an important contributing factor to rules noncompliance involving safety-critical communication. Top-down processing can also be a source of human error with respect to visual perception. Obscured or degraded signage cannot be processed completely with bottom-up processing (Wickens and Hollands 2000). Therefore, the brain attempts to fill in the missing information via top-down processing. Errors can occur when the brain fills in incorrect information leading to misinterpretation. These types of errors occur in the medical industry where medication labels are often not dissimilar enough with respect to medication or dosage, sometimes resulting in fatalities (Frey et al. 2002). Distraction Vehicle control is a complex activity involving multiple tasks and multichannel information input. Because humans are inherently limited in processing complex tasks simultaneously, activ- ities or conditions that compete for the driver’s attention pose a risk to the driver’s control over the vehicle (Sheridan 2004). Wickens’ multiple resource theory states that tasks that draw on the 8 Improving Safety-Related Rules Compliance in the Public Transportation Industry

same mode or stage of processing will suffer significantly more than tasks that rely on different cognitive resources (Wickens 1984). Previous research has also found that “cognitive load com- bined with the loss of exogenous cues, which can occur when the driver briefly glances away from the roadway, may be particularly detrimental.” (Lee, Lee, and Ng 2007). This diversion can occur willingly, for example, using a cell phone or tuning radio controls, or as a consequence of some environmental stimuli, like passing a billboard or a flashing warning sign (Regan, Lee, and Young 2008). With the increase of technology proliferation into vehicles, driver distraction is becoming more common, leading to an increase of risk exposure. However, even though the effects of driver distraction are well documented, research into fully understanding the sources of distraction, the underlying causal mechanisms, and mitigation techniques are all still undeveloped and lacking (Regan, Lee, and Young 2008). Workload The study of workload has a long history in psychology as well as human factors transporta- tion research. In this project, only mental workload is considered. Gopher and Donchin (1986) define a measure of workload as “the difference between the capacities of the information- processing system that are required for task performance to satisfy expectations and the capacity available at any given time.” There is an optimal level of mental workload. Under circumstances where workload is either too high or too low there are performance decrements. Low-workload conditions do not provide enough arousal to sustain vigilance and high-workload conditions cause employees to over-focus resulting in cognitive tunneling, both of which potentially lead to human error (Proctor and Van Zandt 1994). Cox-Fuenzalida (2007) noted that previous research described a general decrement in per- formance following a decrease in task demand. In an experimental study of workload vari- ability, she confirmed that a condition involving a shift from high workload to low workload impaired performance. Additionally, she observed that abrupt increases or decreases in work- load led to a loss of accuracy and slower response time. The high to low condition may be an arti- fact of fatigue. Regardless, measuring the dynamics of workload is important given the potential for performance decrement. Fatigue Research has documented the performance effects of fatigue. The performance effects of inad- equate sleep can affect an individual’s ability to work safely and efficiently. Belenky et al. (2003) have shown that performance declines initially with mild to moderate sleep restriction of 7 and 5 hours, respectively, and after a few days it stabilizes at a less than fully rested level. The relevant performance effects include the following (Institute of Medicine 2006): • Response time slows • Attention to intensive performance is unstable, with increased errors of commission and omission • Involuntary microsleeps occur • Performance declines in short-term recall of working memory The susceptibility to any of the above becomes an urgent concern when the job carries safety risks for the employee, co-workers, or the public. The job performance of public tran- sit operators getting less than 7 hours of sleep on workdays is likely compromised. Research of Van Dongen, Mullington, and Dinges (2003) has shown that sleep loss-related perfor- mance declines often go unrecognized by the affected individuals making them at increased risk of error. Understanding Rules Noncompliance 9

TCRP Report 81: Toolbox for Transit Operator Fatigue contains approaches for managing oper- ator fatigue (Gertler, Popkin, Nelson, and O’Neil 2002). Workstation Design Workstation design is a potential source of safety-related rules noncompliance. Given that improper securement of wheelchairs is the leading cause of injuries to passengers, Herring and Wolf (2002) conducted an observational study of wheelchair tie down operations in transit buses. They found that the general consensus among bus operators was that systems were very difficult to use, a factor that decreases the probability of compliance. Regarding the vehicle operator’s workstation, it is imperative that it be designed considering the principles of human factors and ergonomics. Bucciaglia et al. (1995) suggest beginning the process with an analysis to identify primary and secondary operator tasks. This provides a basis to ensure that all safety-critical controls and displays are in the primary visual area and are easily accessed (Wickens, Lee, Liu, and Becker 2004). Risk Taking Trimpop (1994) defines risk taking as “any consciously, or non-consciously, controlled behavior with a perceived uncertainty about its outcome, and/or about its possible benefits or costs for the physical, economic or psychosocial well-being of oneself or others.” In essence, risk taking is acting without fully considering the consequences of one’s actions. To a certain extent, we all engage in some form of risk-taking behavior because it is not practical to always fully weigh each and every consequence prior to action. For the sake of efficient and timely behavior, humans engage in heuristic evaluations for decision-making (Matlin 1994). That is, they combine past experience with the present circumstances to take cognitive shortcuts to determine the best possible choice of action. However, because these heuristics are shortcuts, they may exacerbate the uncertainty of the situation at hand. Of interest to public transit agen- cies is the need to identify individuals who may engage heavily in risk-taking behavior to the point that it is either pathological or at least increases the probability of a safety incident during day-to-day operations. Personality and Risk Takers There is a long history in aviation psychology of trying to identify personality features of pilots who are risk takers (Hunter and Burke 1990). Personality is a psychological construct that describes the inherent behavioral attributes of an individual. Personality assumes a set of stable traits that persist across situations. Due to the high risk associated with flight, the avia- tion community was interested in identifying psychometric measures associated with pilots who engaged in risk-taking behavior. However, Besco (1994) conducted a literature review that examined the validity of using personality inventories to predict pilot behavior and found it to be an unreliable method. The approach of looking at personality as the root of error and/or violations comes from Heinrich’s early work that suggested that about 80% of industrial accidents results from the human in-the-loop (Heinrich, Peterson, and Roos 1980). Unfortunately, many researchers began to examine what was wrong with the human that caused the error (i.e., personality and/or character flaws). The rationale for this approach is flawed because of the classification of these original studies; they failed to examine the root cause of the industrial incidents. Therefore, the operator was erroneously assigned blame instead of the many contextual fac- 10 Improving Safety-Related Rules Compliance in the Public Transportation Industry

tors associated with the situation. This is a well-known social psychological phenomenon known as the fundamental attribution error, whereby negative events are attributed to the personal characteristics of the individual involved in the event without considering the situ- ational factors (Jones and Harris 1967). Situational Factors Looking for character flaws using psychometric tools is not useful for predicting risk taking because it perpetuates the act of blaming the employee; however, it is worthwhile to understand the situations that may lead to increased risk-taking behavior. In this light, researchers have begun to examine the factors that moderate risk perception including its effect on rules com- pliance. Diaz and Resnick (2000) used the Johnson Personality Inventory–Revised (JPI-R) and found that the risk-taking scale measures of this test were positively correlated with personal protective equipment (PPE) compliance. The researchers discuss that there are multiple factors that influence risk perception including time on the job without incident. The longer someone is employed, the more likely he or she is to have encountered a hazardous situation and perhaps recovered from it. Recovery from these events can lead to overconfidence in one’s ability or com- placence thereby negatively influencing risk perception as is evident in pilot risk taking during adverse weather (Pauley and O’Hare 2008). Research in driver behavior demonstrates that oper- ator overconfidence is associated with an impaired ability to evaluate a driver’s own performance (Kidd and Monk 2009). Therefore, inflated driver confidence makes it unlikely that mistakes will be acknowledged and recovered from. Gonzalez and Sawicka (2003) refer to risk homeostasis theory that was developed in the con- text of automobile safety. The theory involves a model that presents the actual risk of a situation and contrasts it with the perceived risk. The discrepancy between the two is modulated by the individual’s ability to accurately perceive the risk (perceptual skills) and to make an appropriate decision about what sort of adjustment is necessary (decision-making skills). Both types of skills are heavily influenced by experience, or top-down processing. The aforementioned theory is related to Kahneman and Tversky’s (1979) prospect theory which suggests that people either grossly overestimate the likelihood of improbable events or fail to consider them a possibility at all. The latter is a bias that may lead employees to underestimate the possibility of disastrous events. These biases are evident immediately after safety incidents. Workers often become hypervigilant after an accident followed by a steady decrease in safety vig- ilance as time goes on. As such, a decline in safety vigilance can become an organizational haz- ard where the organization, like individuals, becomes complacent over time underestimating the possibility of an unexpected safety occurrence. Predicting Risk-Taking Behavior While risk perception helps to explain why some people are more likely to take chances than others, past behavior can also be used as a predictor of future behavior. Using a logistic regres- sion analysis of approximately 309,000 pilot records, McFadden (2002) showed that driving while intoxicated (DWI) convictions were associated with alcohol-related aviation accidents. Pilots convicted of driving while intoxicated were 3.5 times more likely than pilots without these types of convictions to have alcohol-related general aviation accidents. In commercial aviation, pilots with a history of DWI were more likely to engage in risky flight maneuvers than pilots with no such history. Most of the research conducted on attitudes involving risk used explicit measures of attitude. Explicit measures rely on self-report and are not always a reliable indicator of a person’s attitude, Understanding Rules Noncompliance 11

because people may respond based on the questionnaire administrator’s expectations. Recent research has focused on the use of implicit measures of attitude. Adapted from the field of social cognition, the implicit attitude test (IAT) measures unconscious attitudes, which are impervi- ous to experimental demand characteristics. Using the IAT, aviation researchers have demon- strated that the use of this tool, at least experimentally, can identify pilots who are likely to make risky flight decisions (Molesworth and Chang 2009). However, this research is still in its infancy and is not ready for practical application. Summary Points • Traditional psychometric inventories are not useful for identifying individuals as having risk-taking personalities; therefore, they do not serve as useful screening tools for the hiring process. • High scores on the risk-taking scales of the JPI-R were associated with failure to comply with PPE requirements. The applicability of this study to public transportation is limited. • Identifying the situational factors that influence risk taking in public transit operations is use- ful. Examples of factors to consider include length of time an organization has without inci- dent, length of time an individual is on the job without incident, and the number of employee incidents he, or she, successfully recovers from. • DWI convictions are predictors of pilot risk-taking behavior; however, there is no empirical evidence to suggest this as a predictor in public transit operations. • The IAT is a promising methodology that may be adapted as a practical tool to identify indi- viduals who may engage in risk-taking behavior. This may lead to improved employee screen- ing and targeted training. Training Training employees is an effective way to promote safety-related rules compliance. Tannenbaum, Beard, McNall, and Salas (2009) report that learning in organizations needs to address four core areas: • Intent to learn • Experience and action • Feedback • Reflection To optimize training effectiveness, employees need to be prepared for the learning experience. An organization can accomplish this by informing employees about upcoming training oppor- tunities and requirements. The information about training should include why the organization is sponsoring it, the goals and objectives, and any potential benefits. Improving Self-Efficacy Research shows that even under optimal training circumstances, individual differences related to an employee’s intention to learn plays a role in training effectiveness. Some individuals have low self-efficacy. This refers to a person’s belief that he or she has the capacity to successfully perform specific behaviors or tasks. Day et al. (2007) describe how Bandura’s (1978) social learning theory can be used to promote behavior modeling to mitigate the effects of low self-efficacy. Behavior modeling fosters confidence and promotes skill development in those with low self-efficacy. These researchers examined the effects of a collaborative training protocol for improving employee self-efficacy. Active interlocked modeling (AIM) requires trainees to practice half of a training task and then observe a partner performing the remaining half of the task. Results from 12 Improving Safety-Related Rules Compliance in the Public Transportation Industry

this study indicate that training with an experienced partner using AIM provides an effective way to increase self-efficacy. Effective Types of Training The type of experience one has during training influences its effectiveness. The three types of action-based, or experiential, training included in the review are on-the-job (OJT), computer- based, and simulation. None of these training techniques should be used alone. Rather a balanced combination of them provides optimal training effectiveness. On-the-Job Training The use of OJT is most appropriate when work procedures need to be passed on to employees and implemented immediately. This can occur during initial job orientation as well as when there are new procedures that need to be trained long after an individual is hired. The advantages of OJT include that the organization does not have to hire trainers or conduct training offsite, which can be costly. However, OJT does take supervisors away from their regular duties and potentially increases supervisor workload. Mullaney and Trask (1992) also point out that supervisors and subject-matter experts are not always exceptional trainers. Their proficiency may cause them to skip certain steps in the process that learners, particularly those with low self-efficacy, need to understand. Additionally, OJT must meet the needs of the trainee so that it builds upon his or her existing skill set. OJT is also a good opportunity to use the commentary drive technique (McKenna, Horswill, and Alexander 2006). During training, instructors in the vehicle (or cab) observe and then give feedback after the session concludes. Observing other employees’ commentary drive sessions is also an effective training tool and is easily implemented using video recording of OJT sessions. Derouin, Parrish, and Salas (2005) provide several guidelines for optimizing the effectiveness of OJT including the following: • Ensure upper management support for OJT. • Standardize OJT programs. • Include training staff in the design and development of OJT programs. • Train the trainer. • Prepare trainees for OJT. • Provide descriptive, but not evaluative, feedback during training. • Encourage practice in a non-evaluative environment, allowing trainees to make errors where possible. • Evaluate OJT effectiveness. Computer-Based Training Computer-based training (CBT) can also be incorporated into a successful training program. It can be conducted during work hours, linked to the Internet for remote access, and incorpo- rated into classroom-led instruction. Fisher et al. (2002) found that PC-based risk awareness training reduces the likelihood of risk-taking behavior, though this research only examined young, inexperienced drivers. Horrey, Lesch, Kramer, and Melton (2009) systematically examined the effectiveness of CBT of distraction mitigation. Research demonstrates that operators may not be aware of the dis- tracting effects of in-vehicle tasks on performance (Horrey, Lesch, and Garabet 2008; Lesch and Hancock 2004). As such, zero-tolerance policies regarding the operation of electronic Understanding Rules Noncompliance 13

equipment during safety-critical tasks may not be as effective as when these policies are combined with a training program that educates individuals on the dangers of operating a vehicle while talking or texting on a cell phone. The following is a list of the information contained within the distraction mitigation training modules, which successfully deterred individuals operat- ing electronic devices while driving: • Distraction facts and information • Video demonstrations of distraction involving others • Interactive demonstrations of distraction • Training how to deal with distraction • Video demonstrations using commentary drives Simulation Simulation is another useful training tool; however, high-fidelity training simulators involv- ing motion and tactile feedback are costly and not widely available. Some studies examined the use of low-cost, low-fidelity simulators and found positive training effects (Chase and Donohoe 2008). The positive effects of low-fidelity simulators are for improving awareness of safety-critical situations not vehicle handling. Simulation provides the opportunity to conduct safety error management training (EMT). This type of training specifically encourages opera- tors to make mistakes so that they learn how to recover from them. Generating one’s own solu- tion to a problem is much more effective than reading or hearing about potential solutions from someone else. This is based on the generation effect in cognitive psychology (Crutcher and Healy 1989). EMT is particularly suited for training novel tasks when compared with error- avoidant methods. Summary Points • Effective training, at a minimum, includes preparing the learner prior to training, providing the optimal training experience based on the science of training, nonevaluative feedback, and encouraging the trainee to reflect on the learning process. • Promote self-efficacy during training by pairing a more experienced partner with one who is less sure of him- or herself. • Follow the recommendations regarding OJT. • CBT and simulator training provide opportunities to train employees about human informa- tion processing limitations and go beyond traditional classroom training to promote effective error recovery strategies. Incentive and Discipline Programs Incentive and discipline programs draw from behavioral management theory, which predicts specific behavioral outcomes based on the effects of reinforcement (increases target behavior) and punishment (decreases target behavior) (Lieberman 1990; Lefrançois 1995). An incentive is a reward, which may be monetary or in some other form, to recognize a specific accomplishment by an employee or a group of employees. The incentive differs from other forms of compensa- tion, because it must be earned during each incentive cycle; whereas salary is generally a constant and guaranteed base compensation. An incentive can be something tangible or intangible. Incentive Best Practices Cash payment is one of the most commonly used incentives (Hartman, Kurtz, and Moser 1994). The amount is small, usually less than $200. Hartman, Kurtz, and Moser reported the following examples of incentives offered by public transit agencies: 14 Improving Safety-Related Rules Compliance in the Public Transportation Industry

• Up to $500 bond based on safety points accumulation • $50 cash for safe driving • $75 to $250 plus 8 hours of extra pay for rewarding attendance, safe driving, and customer service Rewards can also be in the form of special benefits, such as extra days off, a designated parking space, or prizes. For example, safe employees may be offered free restaurant meals, watches, and retail gift cards. Another common form of incentives is recognition rewards. Recognition rewards are “low cost/high impact.” Recognition also can be in the form of an event, like a banquet, or in the form of something tangible, such as shirt patches, certificates, and special nameplates. Employees can be recognized in newsletters, personalized letters of gratitude from management, or even in a press release to the local media. A survey found that respondents viewed recognition rewards more highly than cash payments (Hinze 2002). Common elements of successful incentive programs include the following: • Management support must be visible. • Achievement criteria must be clear and precise with objective metrics. • Incentive cycle or monitoring period must be defined. • Process must be transparent to the employees. • Eligibility to participate must be defined. • Incentive programs can be tiered but the tiers and performance expectations must be well defined. • Smaller, frequent, non-monetary rewards that highlight the employee’s achievement seem to be the most effective. While an effective incentive program may create positive behavior changes in employees, there is contention in the literature about the use of incentives. Some advocate their use while others claim that incentives do more harm than good (Geller 1996). Common criticisms of incentive programs include the following: • Motivation can decline over time and after the incentive is reduced/removed. • Programs may encourage the employees to hide injuries and under report incidents. • In some cases, it can be difficult to define employee vs. group contributions to safety. • The projected budget for these programs may not be enough to cover 100% compliance. • Programs may not take into account factors not under the control of the employee (e.g., other people’s unsafe behavior). Critique of Incentive Programs Traditional behavior theory predicts that the effects of reinforcement, or reward, will dissipate over time if the reinforcement is discontinued. While this criticism is well founded in behavioral theory, cognitive psychologists note that human motivation exists beyond external environmen- tal consequences. Sometimes, motivation is internal and linked to the values of a person. Changing a person’s behavior through reinforcement and their attitudes through education may enhance rules compliance more than either would alone. Many employers view their compensation programs as sufficient motivators for the job roles they define and are not inclined to adopt incentive programs. Some employers believe regular monetary compensation is sufficient to expect that their employees will perform their jobs adequately. However, this view is problematic when compensation programs are not strictly performance-based and linked to safe behavior. For example, an employee initially may be com- pliant with safety-related rules 100% of the time. Over time, the compliance rate may drop due to complacency or poor supervision. If the supervisor does not address the performance Understanding Rules Noncompliance 15

decline immediately, or through a performance-based compensation program, the employee learns that he or she can be less compliant and still reap the same rewards. In this example, the employer is no longer requiring the behavior it would like its employees to exhibit. An incentive program is one option to use as a bridge to improve rules compliance in the short term until a performance-based compensation program can be implemented and supervisor deficiency can be corrected. It is imperative that incentive programs geared toward improving safety link the reward to safe behavior. Many incentive programs exist that reward being incident or accident free. The latter only discourages employees to report accidents or the factors that led to them. Ideally, safe behaviors that lead to rewards or incentives should be linked to the leading indicators that the agency uses to measure the effectiveness of its safety-related rules compliance pro- gram. (See the Measuring Compliance with Leading and Lagging Indicators section.) Linking a point system to the following safety-promoting behaviors is reportedly effective: • Attending safety meetings • Leading a safety meeting • Writing, reviewing, and revising a job safety analysis • Conducting periodic safety audits • Certain safe work habits Using Discipline Effectively Discipline, in the form of punishment, is often used by managers to quell noncompliance. Punishment is most often used as a last resort when other interventions do not prove effec- tive. While punishment is effective for reducing, or eliminating, unwanted behavior, it does not teach the correct behavior. Punishment may be in two forms, positive and negative pun- ishment. Positive punishment occurs when the addition of an aversive stimulus is used to curb a behavior (e.g., adding to the workload of an individual; additional workload must be viewed negatively for this to qualify as punishment). Negative punishment occurs when a val- ued, or pleasant, stimulus is taken away. An example of this is demotion (removal of status), or termination in the extreme. Punishment has its place in the workplace for shaping employee behavior. However, it must be delivered in a specific manner to achieve the desired effect and avoid negative con- sequences. Behavior theory predicts that reward works best when delivered intermittently. Punishment, in contrast, is optimal when it occurs after each instance of the undesirable behavior. Consequently, employees learn they will only be punished when they are caught in the act. They may fail to develop internal monitoring during situations when they are not being directly supervised. Punishment also arouses a strong emotional response. This is particularly true when punish- ment is viewed as unfair or overly harsh. Under these circumstances, employees may harbor resentment or seek retribution. The following are best practices for including punishment as part of the disciplinary process: • It must be administered immediately. • It should be consistently applied across employees. • Negative punishment is a better option than positive punishment. • It should have sufficient intensity, but not perceived as overly harsh. • A rational explanation must accompany delivery, which should be privately conveyed. • Punishment should be used in conjunction with reinforcement, or incentives, to encourage positive safety behavior. 16 Improving Safety-Related Rules Compliance in the Public Transportation Industry

Measuring Compliance with Leading and Lagging Indicators Continuous improvement in safety-related rules compliance requires ways to monitor and measure practices that public transit agencies use to encourage safe behavior. Safety profession- als advocate that “You can’t improve what you don’t measure.” Many safety systems, including those focused on rules compliance, focus on lagging indicators. Lagging indicators are measures of undesirable outcomes that have already occurred (Blair and O’Toole 2010). The numbers of rule violations, vehicle accidents, and injuries are examples. In contrast, leading indicators focus on activities or conditions that, if completed, will prevent or reduce the risk of lagging indicators. They help improve future performance by promoting action to correct the latent factors that cre- ate safety risks. Leading indicators focus on process and are achievement-oriented while lagging indicators are avoidance-oriented. Leading indicators include measures such as number of indi- viduals trained, number of safety meetings, number of safety-related communications, and number of reports to a safety reporting system. Safety Culture, Management, and Rules Compliance While the academic literature does not share a single standard definition regarding safety culture, researchers as well as practitioners agree that safety culture is a subset of organizational culture (see Figure 2). As such, safety culture represents that part of an organization’s culture that relates to safety. Therefore, safety culture encompasses organizational structure as it pertains to safety as well as the way people think, feel, and behave with respect to safety practices (Cooper 2002). Related to the notion of safety culture is safety climate. While these two terms have sometimes been used interchangeably, they are different constructs. According to Flin, Mearns, O’Connor, and Bryden (2000), “safety climate can be regarded as the surface features of the safety culture discerned from the workforce’s attitudes and perceptions at a given point in time.” Given this definition, assessing safety climate provides a “snapshot” of an organization’s safety culture. Safety climate assessment tools provide a way for transit agencies to measure their organizational commitment to safety. A review of the relevant safety culture and climate literature suggests that rules compliance is optimal when an organization addresses the following dimensions of safety culture (Antonsen 2009; Cooper 2002; Flin, Mearns, O’Connor, and Bryden 2000): Understanding Rules Noncompliance 17 ...what people think & feel ...what the organization has ...what people do Behavioral factors Cognitive factors Cognitive Culture Situational Behavioral Situational factors Organizational structure,policies, procedures and management systems Management, supervisory and employee decisions, communication and actions Management, supervisory and employee values, attitudes and beliefs Figure 2. Organizational culture.

Management and Supervision When assessing safety culture, one of the most important factors to consider is the level of com- mitment of management and supervisors to encouraging safe operations. This must be a genuine effort so that employees are able to perceive organizational commitment and internalize this atti- tude into their own set of personal values. Also, leadership style of both upper management and first-line supervisors is an important impetus for worker safety. The types of questions that formal assessment tools must answer include the following: • When it comes to safe operations, do management and supervisors “walk the walk” or just “talk the talk?” • Is there a consistent message regarding safety from top-level management as well as at the level of first-line supervisors? • Do workers perceive that management is specifically committed to safety and in general concerned with their overall well-being? Safety System Safety culture assessments usually involve characterizing the makeup and functionality of an organization’s safety system. Elements of a safety system include a safety management system (SMS), the presence and hierarchical position of safety officials, safety committees, policies, and equipment. Fernández-Muñiz, Montes-Peón, and Vásquez-Ordás (2007) define an SMS as “a set of policies and practices aimed at positively impacting on the employees’ attitudes and behav- iors with regard to risk.” The aim of an SMS is to intervene on the circumstances that result in risks and accidents. This involves identifying and analyzing both latent and visible hazards. Bottani, Monica, and Vignali (2009) surveyed 400 manufacturing firms, some with and some without formal SMSs. The results demonstrated that the attitudes regarding several safety- related variables were better for safety officials from the companies that had formal SMSs. Further research is needed that uses process measures in addition to attitudinal ones. There have been guidelines set forth for conducting a hazard analysis for transit projects (Adduci, Hathaway, and Meadow 2000). Recently, the FTA released a guidebook describing how to implement a transit SMS (Ahmed 2011). The guidebook is an excellent source of informa- tion for public transit agencies interested in adopting a transit SMS including information regarding safety performance measurement. Many safety systems include a program for rewarding safe work practices as a means to encour- age safe behavior. Behavior-based safety (BBS) programs focus on the interaction between people and their working environment. There are functional variations of these programs with the most common using members to monitor the behavior of a workgroup and managers to monitor their own safety-related leadership behavior. The most common employee protocol involves peer obser- vation with on-the-spot feedback. However, there are reports of self-observation approaches where single operators perform their own checklists. The data is compiled over a number of self- observations and the results are used to inform training needs and other remedial action (Cooper, 2007). Self-observations are most appropriate for transit operators. However, there is no empiri- cal data to support the efficacy of the self-observation approach. Cooper (2007) presents the IDEAL components of a BBS program. They include the following: • Identify unsafe behaviors • Develop appropriate observation lists • Educate everyone and train observers • Assess ongoing safety behaviors • Limitless feedback 18 Improving Safety-Related Rules Compliance in the Public Transportation Industry

A safety reporting system, such as those in aviation and the railroad industry, is a proactive element of any safety system. Formalizing the safety system within an organization by means of the aforementioned elements provides protective barriers against unexpected occurrences related to safety-related rule noncompliance. These systems are reviewed in Appendix C. Work Pressure Safety-critical service industries such as public transportation must effectively balance the need for on-time performance with the need to perform safely. Assessing the tension between these two often competing goals provides a way to determine if the effects of top-level manage- ment commitment have “trickled down” to the supervisory and employee level. Sometimes supervisors and top-level management establish safety goals without consulting the workforce to determine if the goals are practical and attainable. When safety and performance compete at the level of the operator, supervisors may choose to look the other way when safety violations occur to maintain on-time performance or keep equipment in service. This in turn sends the message to employees that safety is not truly valued and sacrificing safe operations to stay on schedule is acceptable. Procedures and Rules While not traditionally part of most formal safety culture and climate assessments, the per- ceptions of and attitudes toward safety rules and procedures provide an indicator of whether or not individuals within an organization accept and value them. Rules and procedural adherence can be improved when management partners with labor to create safety rules and procedures. In essence, this process empowers individuals by giving them input to the safety system. Labor feels management respects their opinions as expert operators and they feel ownership of the rules and policies. Therefore, employees are more likely to comply. The rules and procedures in a truly resilient organization empower the employees to deal with unanticipated events. From a behavioral economics perspective, Battmann and Klumb (1993) suggested that procedural and rules violations originate primarily from the following: • Unclear or conflicting rules or constraints • Delayed, ambiguous, or missing feedback • Absence of clear priority rules in cases of conflicts between high-level and low-level safety commitments Dekker (2003) comments that operators fail to adapt procedures when adapting is necessary, or alternatively they attempt procedural adaptations that ultimately prove futile. To improve rules compliance, organizations should avoid increasing pressure to comply. Rather, they should invest in their understanding of the gap between procedures and practice, and help develop operators’ skill at adapting. Employees There are many factors related to the workforce that provide an indicator of safety culture and climate including employee competence, safety training, safety attitudes and risk-taking behavior, and job satisfaction and security. Organizations committed to safety adhere to rigorous screen- ing procedures when hiring to ensure that their employees have the required knowledge, skills, and abilities to perform their jobs. They provide exemplary training to ensure the workforce understands how to operate under both typical and atypical operating circumstances. They train the workforce to recover from unexpected occurrences as well. Finally, employees are more likely Understanding Rules Noncompliance 19

to be committed to their organization’s safety goals if they are satisfied with and feel secure in their jobs. Genuine management commitment to the employee fosters employee commitment to the organization. Summary Points • There must be a top-level management commitment to safety that permeates the public transit agency from the top level all the way down to the employees. • Safety reporting systems, hazard analyses, and safety management systems are all effective ways to improve a public transit agency’s safety culture thereby improving rules compliance. • Safety must be a higher priority than on-time performance at all levels of a public transit agency. • The safety-related rule-making process must involve the employees who are required to follow the rules. • Safety-related rules must be clear, concise, and easily understood by employees. • Genuine management commitment to the employee fosters employee commitment to the public transit agency. 20 Improving Safety-Related Rules Compliance in the Public Transportation Industry

Next: Chapter 3 - Classifying Noncompliance »
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TRB’s Transit Cooperative Research Program (TCRP) Report 149: Improving Safety-Related Rules Compliance in the Public Transportation Industry identifies potential best practices for all of the elements of a comprehensive approach to safety-related rules compliance.

The categories of best practices, which correspond to the elements of a safety-related rules compliance program, include screening and selecting employees, training and testing, communication, monitoring rules compliance, responding to noncompliance, and safety management.

The report also outlines the features of a prototype safety reporting system for public transportation.

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