What increases the risk of having an accident in the workplace? A range of factors has been identified as increasing accident liability, including individual, group and organizational factors. Although incremental improvements to the work environment have effected a significant reduction in workplace accidents, this improvement has now begun to reach a plateau beyond which further improvement has proven difficult to achieve. Given that human error is involved in a high proportion of accidents, there has been a tendency to focus on individuals’ contribution as a risk factor. For example, in their analysis of 100 accidents at sea, Wagenaar and Groeneweg (1987) found that human error contributed to accident causation in 93 percent of cases. Nevertheless, attention has gradually shifted from human error to recognize the role of “sociotechnical” factors which take into account the interaction between the individual and his or her work environment, and the importance of a robust safety management system within organizations (Hale, 2003). It is essential that we develop an understanding of the many ways in which humans interact with elements of the system, not just with their immediate workplace, but also with co-workers, supervisors, organizational processes, and policies. This chapter reviews the contribution of individual, social, and organizational factors to increased accident liability. It then overviews ways in which organizations successfully manage accident risk and identifies recommendations for best practice. Finally, suggestions for further research are offered.
Individual Risk Factors
Early studies of accident data found that the distribution of accidents across individuals was not uniform and consistently identified a subgroup of people as “accident repeaters” (Greenwood and Woods, 1919). This subgroup of the population was involved in a disproportionately high number of accidents, leading to speculation about the prospect that this higher accident liability was due to a stable set of individual characteristics, or “accident proneness” (Farmer and Chambers, 1926). Despite considerable research, the search for a stable profile of the accident-prone individual has proven elusive. Researchers found that many studies failed to control for risk exposure and argued that, given that the accident proneness concept was based on a statistical artifact, it should be debunked (Hale and Hale, 1972). More recently, Visser et al. (2007) conducted a meta-analysis of accident data and concluded that accidents do cluster around individuals. They found that the distribution of accidents failed to match the pattern expected if they were distributed randomly (that is, the Poisson distribution); instead, some individuals were found to suffer injuries more often than would be expected by chance alone.
Taken at face value, this would seem to suggest that accident repeaters might come from specific demographic subgroups of the population. Crash statistics support the increased accident liability of male motorists (Oltedal and Rundmo, 2006), with research indicating that young men in particular commit the highest levels of driving violations, and also have higher accident risk (Chang and Yeh, 2007). Furthermore, as people get older (particularly over 75) their accident liability increases, such that older drivers have an increased accident involvement of 30–45 percent (Li, Braver, and Chen, 2003), even taking into account older people’s increased frailty and susceptibility to injury. However, one must also consider a range of exogenous factors affecting the relationship between demographics and accident involvement. For example, if driving distance is taken into account, the higher accident liability of older drivers disappears (Langford, Methorst, and Hakamies-Blomqvist, 2006). Furthermore, the higher crash rates seen in younger drivers also disappear rapidly with increasing experience; the effects of experience are evidenced in the causes of young people’s accidents, which tend to be largely the result of errors rather than overtly risky behavior, which only accounts for a small proportion of accidents (McKnight and McKnight, 2003). There is also evidence that accidents in the workplace are not consistently related to demographic factors, such as age. Gyekye and Salminen (2009) found that older workers tended to report more positive safety perceptions than younger workers and to be involved in fewer accidents; however, Li et al. (2006) found that pilot error was not related to age.
An alternative explanation for the “accident prone” individual relates to that person’s propensity to take risks (that is, accident proneness is related to a preference for higher levels of risk in activities). Research in this area has supported the proposition that risk-taking is associated with stable dispositional characteristics (Jonah, 1997; Kowert and Hermann, 1997; Nicholson et al., 2005; Soane and Chmiel, 2005). Jonah (1997) found that individuals high in sensation-seeking, who have an increased need for novelty and thrills, have a greater tendency to take risks when driving and so have higher accident liability. In a different context, Lubner (1992) found that US pilots involved in aviation accidents scored significantly higher on the personality trait of thrill- and adventure-seeking. Sensation-seeking is a lower-level facet of extraversion, one of the “Big Five” factors of personality (Costa and McCrae, 1986). Other aspects of the Big Five have also been related to risk-taking. Kowert and Hermann (1997) found that risk-taking was associated with openness, low conscientiousness, and low agreeableness. Nicholson et al. (2005), who looked at risk-taking across six different domains (recreation, health, career, finance, safety, and social), also found that risk-taking across domains was associated with openness, low agreeableness, and low conscientiousness. Soane and Chmiel (2005) showed that only a small proportion (less than 3 percent) of their sample was consistently risk-taking across domains, but that these people were significantly less agreeable and less conscientious than those who were consistently risk-averse. Low conscientiousness was associated with risk-taking across domains (Soane and Chmiel, 2005). Thus, there is some support for the proposition that risk-taking across situations is related to stable personality traits, with most consistent evidence for the influence of low conscientiousness and low agreeableness. Both of these personality characteristics have been associated with increased accident involvement (Clarke and Robertson, 2005), suggesting that such stable dispositions may increase accident liability through the propensity for greater risk-taking behavior. In their meta-analysis, Clarke and Robertson (2005) reported a small-moderate effect size for both low conscientiousness (ϱ = .27) and low agreeableness (ϱ = .26) with higher accident involvement. However, a closer look at the dispositional characteristics of low scorers on conscientiousness and agreeableness suggests other psychological mechanisms that may at least partly explain the link between personality traits and accident liability.
Low scorers on conscientiousness exhibit behaviors that are characterized by a focus on satisfying immediate needs, regardless of future consequences for oneself or others (West, Elander, and French, 1993); they demonstrate little forward planning and have a tendency to ignore rules and regulations (Arthur and Doverspike, 2001). Miller, Lynam, and Jones (2008) found that individuals who are low scorers on conscientiousness are characterized by a lack of impulse control, which is related to higher levels of anti-social and risky behavior. Furthermore, individuals who are low on conscientiousness fail to reflect upon on-task processes and are more vulnerable to cognitive failures, which in turn are predictive of workplace accidents (Wallace and Vodanovich, 2003). Low agreeableness is associated with high emotional arousal and inadequate interpersonal strategies, such that individuals are less able to cooperate with others effectively and more liable to respond aggressively to situations. Such characteristics have been associated with an increased likelihood of anti-social and risky behavior (Miller, Lynam, and Jones, 2008) and accident involvement (Clarke and Robertson, 2005).
A number of studies have supported a positive relationship between neuroticism and accidents for professional drivers (Pestonjee and Singh, 1980; Roy and Choudhary, 1985), motorists (Mayer and Treat, 1977; Selzer, Rogers, and Kern, 1968), and within industrial settings (Hansen, 1989). However, Clarke and Robertson (2005) found that neuroticism was a valid and generalizable predictor of work accidents (ϱ = .28), but not non-occupational traffic accidents. They also noted that this effect was not due to neurotics’ tendency to report accidents, as the data were largely derived from archival sources, rather than self-reports. This finding is consistent with Kaplan et al.’s (2009) meta-analysis, which found that negative affectivity (NA) was significantly associated with occupational injury (ϱ = .20) where NA is a tendency to experience negative emotions, which has been strongly associated with neuroticism. The higher accident liability of neurotics may be related to their distractibility, as they tend to be preoccupied with their own anxieties and worries, and therefore more easily distracted from the task at hand (Hansen, 1989; Iverson and Erwin, 1997). Neuroticism is associated with lower behavioral control, so that individuals high in neuroticism tend to demonstrate approach behavior in relation to threatening stimuli and a decreased latency in disengaging from such stimuli (Derryberry, Reed, and Pilkenton-Taylor, 2003). Such behavior would mean that neurotics tend to find themselves in more dangerous situations. Furthermore, neurotics tend to respond more negatively to threatening situations and use less proactive coping strategies (Bosma, Stansfeld, and Marmot, 1998). Acute reactions to stressors, including anxiety and fatigue, can have the effect of decreasing cognitive and performance capacities, such as reaction times and judgment, increasing the probability of errors (Steffy et al., 1986). Perkins and Corr (2006) report a significant interactive effect of neuroticism and cognitive ability on job performance, such that a high cognitive ability buffers the negative effects of neuroticism on job performance. Furthermore, as neurotics are also less likely to seek active control of the environment (Judge, 1993), this may affect their likelihood of taking adequate precautions to prevent injury (e.g., wearing protective equipment, such as gloves, masks and safety goggles).
Although there is research to suggest that particular personality traits may be associated with accident involvement, there has been limited consideration of combinations of traits. However, recent studies have begun to look more closely at ways in which certain personality traits interact to affect behavior. For example, Ode, Robinson, and Wilkowski (2008) have looked at the interaction between neuroticism and agreeableness. Neurotic individuals are more likely to experience emotions associated with anger and aggression. However, those who are also high in agreeableness will be able to self-regulate their aggressive or angry responses to a situation. This would suggest that a combination of high neuroticism (N) and low agreeableness (Ag) increases the likelihood of an aggressive response. Therefore, this could be a key combination of personality traits in relation to work accidents, where high N/low Ag individuals are unable to control their negative emotional reactions to situations, increasing their accident liability. Grant and Langan-Fox (2006) examined the interactive combinations of neuroticism (N), extraversion (E) and conscientiousness (Cs); they found that combinations of high N/high Cs predicted higher stressor exposure, whilst high N/low Cs generally predicted lower problem-focused coping. As noted previously, neurotics may be more vulnerable to accidents due to their tendency to respond more negatively to threatening situations and use less proactive coping strategies. Research by Grant and Langan-Fox (2006) demonstrates that the effect of high N in combination with high Cs leads to higher stress exposure, but the combination of high N/low Cs is likely to lead to higher accident liability as this combination is most associated with the use of maladaptive coping strategies. The failure to cope with stressors will lead to higher levels of strain, which can result in more procedural violations (unsafe work practices) and higher error propensity (Fogarty and McKeon, 2006). Low strain was consistently associated with low N/high E/high Cs (Grant and Langan-Fox, 2006), and so this combination may be positively associated with reduced liability to errors. In addition to combinations of personality traits, there is also evidence that personality traits interact with cognitive ability to predict job performance (Perkins and Corr, 2006), unsafe behavior and accidents (Wallace and Vodanovich, 2003). However, whilst such research is promising, there is currently insufficient evidence to identify the personality profile of an “accident-prone” individual.
Organizational and Social Risk Factors
Despite some recent resurgence of interest concerning individual risk factors in relation to accident involvement, much research attention has been directed at organizational and social risk factors. Our understanding of the underlying causes of accidents has moved from individual-based explanations, such as the concept of accident proneness, towards accounts of the “organizational accident” (Reason, 1997). Reason (1990, 1997) argues that organizational accidents occur when “latent failures” that have lain dormant within the organization (such as communication failures, inadequate policies and procedures, defective equipment and hardware, and so on) are triggered by “active failures” (unsafe acts, such as errors or violations of procedures) to breach an organization’s defenses and result in an accident. Within this framework, individuals at the “sharp end” of the organization may trigger an accident, but accident causation cannot be understood in its entirety without reference to broader organizational and social issues that exist at a systemic level.
Analyses of major organizational accidents have identified that a poor “safety culture” is often the underlying risk factor that resulted in disaster (e.g., Sheen, 1987; Cullen, 1990). Following the Chernobyl nuclear disaster in 1986, the International Atomic Energy Agency (IAEA, 1986) defined safety culture in terms of the extent to which an organization prioritizes safety such that safety issues receive the attention warranted by their significance. Pidgeon (1991) considered safety culture to be “the constructed system of meanings through which a given people or group understand the hazards of the world” (p. 135). Thus, safety culture is essentially a social phenomenon, as its definition depends on individuals’ perceptions being shared within a group, or in the organizational or societal context. However, decision-making at a senior management level in relation to hazards may be considered as the driving force of the organization’s safety culture (Reason, 1997). Managerial decisions about ways of managing hazards are reflected in the organization’s safety policies, procedures, and practices. Deficiencies in a number of organizational processes, such as the provision of training, safety systems, communication, and human resource practices, have been linked with the occurrence of accidents (e.g., Hofmann and Stetzer, 1996; Vredenburgh, 2002; Zacharatos, Barling, and Iverson, 2005). For example, Vredenburgh (2002) found that management practices (management commitment, rewards, communication and feedback, selection, training, and participation) significantly predicted hospital injury rates (accounting for approximately 17 percent of the variation in injuries). Furthermore, Zacharatos, Barling, and Iverson (2005) demonstrated that human resource practices associated with a high-performance work system (HPWS) accounted for 8 percent of the variance in lost-time injuries in a sample of 138 Canadian manufacturing organizations.
Although little research has explicitly addressed the mechanisms underlying the relationship between organizational attributes and accidents, the concept of “safety climate” has been suggested as an important mediating variable (Zacharatos, Barling, and Iverson, 2005). There has been considerable debate regarding the definition of safety climate (Guldenmund, 2000), but a common feature is the focus on employees’ perceptions of the work environment relating to safety (e.g., Barling, Loughlin, and Kelloway, 2002; Zohar, 1980). Neal and Griffin (2006) define safety climate as “individual perceptions of policies, procedures and practices relating to safety in the workplace” (pp. 946–947). These perceptions reflect the priority that employees believe the organization gives to safety issues in relation to other organizational concerns (such as productivity), and so a safety climate may be regarded as a manifestation of the underlying safety culture (Mearns, Whitaker, and Flin, 2003). Organizational structures and processes would be expected to facilitate the safety climate. For example, open lines of communication and information-sharing within the organization will enhance employees’ perceptions of management commitment to safety (Hofmann and Morgeson, 1999). Similarly, perceptions of organizational support have been linked to safety climate (Wallace, Popp, and Mondore, 2006). Furthermore, other attributes, such as the emphasis on rules and regulations, acceptance of innovation, and creativity, would be interpreted by employees in relation to safety—for example, if an organization places a strong emphasis on rules and regulations, employees will equally perceive that compliance with safety rules is important; an emphasis on innovation would encourage greater willingness to suggest different approaches to resolving safety issues.
The influence of senior management decisions concerning safety in organizations is reflected in the balance between safety and other organizational goals (such as productivity). Zohar (2008) argues that employees’ safety perceptions are fundamentally shaped by daily interactions that reflect the “trade-off” between production and safety. Research indicates that the safety climate has a significant relationship with subsequent safety behavior and accident involvement (e.g., Clarke, 2006; Johnson, 2007; Pousette, Larsson, and Törner, 2008). Clarke’s (2009) meta-analysis demonstrated a moderate effect size for the association between safety climate and safety behavior (ϱ = .38) and a smaller but significant association with occupational accidents (ϱ = .17). This would suggest that the safety climate acts as a psychological mechanism by which individual and organizational factors interact and may ultimately result in accidents. Therefore, a positive safety climate, in which employees perceive that safety is prioritized by the organization, reduces an organization’s vulnerability to accidents.
Reviews have identified some common themes, giving an indication of the likely antecedents of a positive safety climate (Clarke, 2000; Flin et al., 2000). The significance of management is reflected in most definitions of safety climate; in particular, many studies have identified employee perceptions of management commitment to safety as fundamental (e.g., Brown and Holmes, 1986; Dedobeleer and Béland, 1991; Cox and Cheyne, 2000). In addition to “management commitment to safety”, which often emerges as the primary factor, other first-order factors have been identified, including: safety systems, workplace risk, and work pressure (Clarke, 2000; Flin et al., 2000; Guldenmund, 2000).
Leadership style is likely to affect how managers represent their attitudes and how subordinates interpret their actions; thus, it has been argued that leadership style is an important antecedent to the safety climate. Indeed, a number of studies have found that the safety climate fully mediates the relationship between leadership style and occupational injuries (e.g., Barling, Loughlin, and Kelloway, 2002; Zohar, 2002a). In particular, emphasis has been placed on the beneficial role of transformational leadership style in developing a positive safety climate (e.g., Glendon, Clarke, and McKenna, 2006; Zacharatos and Barling, 2004; Zohar, 2003). Zacharatos, Barling, and Iverson (2005) argue that each element of transformational leadership style (Bass, 1985) will have a positive impact on occupational safety. Leaders high in idealized influence will demonstrate the high priority given to safety through their own behavior, whilst those high in inspirational motivation will encourage employees to reach high levels of safety. Intellectual stimulation will lead to employees suggesting new and innovative ways of reaching safety targets, and, finally, leaders high in individualized consideration will demonstrate concern for their employees’ well-being. Although these propositions have not been tested directly, supporting evidence is found in a study conducted by Clarke and Ward (2006). This study found that higher levels of safety participation (that is, willingness to engage in safety-related activities) were reported by the subordinates of leaders using the influence tactics of “inspirational appeal” (related to inspirational motivation) and consultation (related to intellectual stimulation). The level of trust between leaders and their subordinates has been found to moderate the relationship between transformational leadership and safety participation (Conchie and Donald, 2009): in situations of high and moderate trust there was a stronger relationship between leadership style and safety behavior.
The importance of high-quality relationships between leaders and subordinates has been emphasized in terms of its benefits for safety (e.g., Hofmann and Morgeson, 1999; Hofmann, Morgeson, and Gerras, 2003; Zohar, 2002a). Much of this research has drawn on leader-member exchange (LMX) theory (Dansereau, Cashman, and Graen, 1973) and has focused in particular on the supervisor as leader, due to the closeness of this relationship in comparison to senior managers. LMX focuses on the dyadic relationship between the leader and each member of his or her team, assuming that the quality of this relationship will vary across employees. A high-quality LMX is characterized by mutual trust, respect and perceived obligation to each party (Graen and Uhl-Bien, 1995). In relation to safety, supervisors will engage in more interactions associated with safety and will be more receptive to safety suggestions (Hofmann and Morgeson, 1999), whilst employees will follow safety rules and regulations more conscientiously (Simard and Marchand, 1997), and will develop more positive safety perceptions (Hofmann, Morgeson, and Gerras, 2003; Watson et al., 2005). Zohar (2002a) argued that supervisors’ response to safety is an interactive function of their personal concern for their subordinates’ welfare and senior management’s safety priorities. Greater concern for subordinates’ welfare is based on closer individualized relationships, which promote safety-related supervisory practices and so affects workers’ safety behavior. Greater supervisory support found in high-LMX relationships has also been linked to lower levels of occupational injury (Hemingway and Smith, 1999; Iverson and Erwin, 1997; Sherry, 1991) and improved safe working over time (Parker, Axtell, and Turner, 2001).
Given the influence of the supervisor in shaping employees’ safety perceptions, Zohar and colleagues (Zohar, 2000, 2008; Zohar and Luria, 2004, 2005) have argued for a multilevel model of safety climate. This multilevel model proposes that the organizational-level safety climate (as described earlier) must be differentiated from the group-level safety climate, where employees use a different referent for their safety perceptions (that is, their supervisor, rather than senior managers or the organization). The degree of consensus within the group reflects the strength of the safety climate at that level (Zohar and Luria, 2005). However, groups will differ not only because they have different supervisors, but also due to group processes and the internal dynamics of the group. The importance of group processes was emphasized in a study by Hofmann and Stetzer (1996), where group processes comprised: planning and coordinating efforts, making good decisions and solving problems, knowing jobs/roles and doing them well, sharing information about events/situations, commitment to meeting objectives, responding to unusual work demands, and having confidence and trust in fellow team members. Group processes were significantly correlated with both safety climate (r = .49) and unsafe behavior (r = −.49) at a group level (N = 21 teams). Group processes will impact on the development of the safety climate as individuals who work in close-knit teams will feel more involved and personally responsible for their own and their co-workers’ safety. Geller, Roberts, and Gilmore (1996) found that work group characteristics, such as cohesion and co-worker support, were associated with personal responsibility and ownership of safety. The element of employee safety involvement and responsibility has been closely linked with safety climate (e.g., Dedobbeleer and Béland, 1991; Cheyne et al., 1998). Furthermore, group-level social networks have been associated with the strength of group safety climate (Zohar and Tenne-Gazit, 2008).
Although work pressure has emerged consistently as an element of the safety climate (Clarke, 2000; Flin et al., 2000; Guldenmund, 2000), relatively little research has focused on investigating the impact of job characteristics on safety behavior and accidents. However, jobs that are characterized by high role demands (e.g., role ambiguity, role overload, and role conflict) are likely to have a negative impact on safety and increase accident liability (Paoli and Merllié, 2001). Excessive work demands, confusion about role expectations, and conflict between demands (such as safety and production goals) are likely to foster perceptions that production is prioritized over safety goals and lead to a more negative safety climate. Indeed, Clarke’s (2009) meta-analysis found that role demands were associated with a negative safety climate (ϱ = .18), unsafe behavior (ϱ = .13) and accidents (ϱ = .14). On the other hand, high job challenge and autonomy can enhance perceptions that management has confidence in employees and values their contribution, leading to positive safety perceptions. Supporting evidence was reported by Turner, Chmiel, and Walls (2005) who found that employees with high job control were more likely to expand their perceived job role to include safety-related activities. In addition, a significant interaction was found between job demands and job control, whereby expanded job roles were least likely for employees with high-demands/low-control jobs. Furthermore, job autonomy enhances perceptions of employee involvement and ownership of safety (Geller, Roberts, and Gilmore, 1996) and predicts subsequent safe working (Parker, Axtell, and Turner, 2001). Clarke (2009) found a moderate effect size for the relationship between job challenge and safety climate (ϱ = .42). Therefore, although there has been limited research in this area, there is a clear indication that job characteristics can play an important role in shaping safety perceptions and act as a risk factor in accident causation.
Interaction between Individual and Organizational Risk Factors
Few studies have examined the interactions between environmental and individual factors in relation to safety. One exception, however, is a study reported by Wallace and Chen (2006), who looked at the role of both safety climate and conscientiousness on safety performance. Although they did not examine the interactional effects of these variables, they did report a significant correlation (r=.27) between conscientiousness and safety climate. Such a finding would suggest that high scorers on conscientiousness are likely to form more positive perceptions of management commitment to safety. There are a number of possible mechanisms underlying this relationship, and further research is needed to extend our understanding of potential interactive effects.
Early research on the nature of safety climate identified two fundamental dimensions: management commitment to safety; and, workers’ involvement in safety (Dedobeleer and Béland, 1991). The latter related to: involvement in regular safety meetings; perceived control (worker’s perception of control over his or her own safety at work); perception of risk-taking (extent to which risk-taking is viewed as part of the job); and perceived likelihood of injuries. Whilst there has been considerable research focusing on the antecedents of safety climate, most of this work has defined safety climate in terms of employees’ perceptions of management commitment to safety, rather than workers’ involvement. However, there have been a few studies examining the role of perceived control in relation to safety (Huang et al., 2006; Leiter and Robichaud, 1997; Leiter, Zanaletti, and Argentero, 2009), which forms an element of workers’ involvement in safety.
Huang et al. (2006) examined the role of perceived control over safety (that is, the respondent’s belief that he or she is knowledgeable about safety and is capable of controlling his or her safety behavior); they found that perceived safety control fully mediated the relationship between safety climate and self-reported occupational injuries. Thus, employees’ perceptions concerning their ability to successfully control safety-related behavior fully mediates the effects of safety climate on injuries. Further insight is provided by Leiter, Zanaletti, and Argentero (2009) who found that perceptions of safety training (often included as an element of safety climate) were strongly linked to perceived control. Such research highlights the importance of safety interventions that focus on perceived control, as increasing perceptions of control may mitigate a negative safety climate impacting on occupational injuries. Although there is some evidence of the role played by perceived control, there has been no research examining the possible moderating effects of individual differences. One potential candidate in this respect is the concept of core self-evaluation (CSE) which reflects an individual’s overall perception of self-worth and comprises locus of control, self-esteem, generalized self-efficacy, and neuroticism (Judge et al., 2002; Judge, Locke, and Durham, 1997). CSE has been found to influence the types of job that individuals select, the work environments that they experience, and their perceptions of the environment (Dormann et al., 2006). Therefore, it is also likely to affect employees’ safety perceptions, the ways in which they respond to their work environments, and the success of safety interventions. In addition to the research previously reviewed, linking neuroticism to increased accident liability, some research has looked at the role of locus of control. A meta-analysis of traffic accidents (Arthur, Barrett, and Alexander, 1991) found that locus of control had a small-moderate effect on accident liability, suggesting that those with a more external locus of control were more accident-involved. In relation to workplace accidents, Jones and Wuebker (1993) reported a significant relationship between safety-specific locus of control and accident liability, again finding that externals were more accident-involved than internals.
The two-factor model of safety climate (referred to previously) suggests that employees perceive safety to be “a joint responsibility between individuals and management” (Dedobeleer and Béland, 1991, p. 102). Work by Hofmann and Stetzer (1998) indicates that employees’ perceptions of joint responsibility are reflective of a positive safety climate; within a more negative safety climate, employees tend to attribute responsibility for accidents to management (and vice versa). However, research has tended to emphasize the importance of the first dimension, management commitment to safety, over the second, employee involvement in safety. Zohar (2008) argues that “the core meaning of safety climate concerns managerial commitment” (p. 377). Employees’ involvement in safety has been considered as an individual outcome variable (safety participation), which is an element of safety performance (Griffin and Neal, 2000), rather than as an aspect of the safety climate. Safety participation includes: engaging in safety activities, making safety suggestions, helping co-workers, monitoring others’ behavior, and catching mistakes. Although some research links safety climate to safety behavior, including safety participation (Clarke, 2006), there is less insight into the mechanisms underlying this relationship. However, Tucker et al. (2008) found that co-worker support for safety fully mediated the influence of organizational support on employee safety voice (that is, speaking up about perceived unsafe work practices or conditions), suggesting a role for group processes as well as individual processes, such as motivation (Neal, Griffin, and Hart, 2000; Neal and Griffin, 2006).
Longitudinal studies have proven useful in unraveling the processes underlying relationships as they develop over time—for example, Neal and Griffin (2006) found that motivation leads to increased safety participation, which in turn further increases motivation, thus acting as a positive spiral. However, research has tended to assume that psychological mechanisms will operate in a similar fashion across all employees, with little regard to the influence of individual difference variables. Given the importance of perceived control highlighted above, one such individual-level variable would be self-efficacy, which reflects a personal judgment on one’s capability to perform certain tasks and enhances feelings of control. Parker, Williams, and Turner (2006) found that job autonomy and proactive personality were both predictive of self-efficacy, which in turn was significantly related to proactive behavior (that is, showing initiative in developing new ideas and solving problems). Furthermore, self-efficacy has also been associated with making suggestions for improvement (Axtell et al., 2000).
Risky Business: How Organizations Manage Accident Risk
A greater understanding of how organizations successfully manage safety hazards may be drawn from the study of high-reliability organizations (HROs) that maintain an excellent safety record in the face of highly hazardous conditions. Examples include naval aircraft carriers, nuclear submarines, and air traffic control (e.g., Bierly and Spender, 1995; Roberts, 1989; Rochlin, 1989).
It has been argued that the source of high reliability in HROs is organizational culture (Weick, 1987). First, HROs are characterized by a “no-blame culture” as they have error management systems that focus on identifying system failures, rather than blaming individuals for failures. Second, they have a flexible structure in which normal operations are hierarchical in nature, but control is devolved to experts “on the ground” in response to local circumstances. This balance between centralization of control and delegation of control is managed through a “powerful system of selection, training and mutual monitoring, criticism and advice [which results in] extremely efficient communications which gives the system the ability to absorb damage and surprises, and so deliver high reliability” (Bierly and Spender, 1995, p. 655). LaPorte and Consolini (1991) observed that during crises in HROs, decision-making may be devolved to the lowest level where the relevant expertise resides. As personnel maintain situational awareness and are committed to resilience, management is willing to defer to expertise irrespective of where it might reside in the organization (Weick, Sutcliffe, and Obstfeld, 1999). Temporary informal networks may be used to deal with crises. Third, HROs demonstrate organizational learning as employees throughout the organization are trained to recognize and manage errors; there is also a willingness to learn from mistakes. A collective ability to discover and correct errors before they are able to escalate to crisis-point has been described as “collective mindfulness” (Weick, Sutcliffe, and Obstfeld, 1999) or “requisite imagination” (Westrum, 1993). Mindful organizing involves preoccupation with failure, meaning that long periods without incident generate a search for errors, lapses, and possible routes to major failures through the use of well-developed near-miss reporting systems.
Non-HROs may move toward higher reliability through the development of similar organizational characteristics using team-based strategies (Burke, Wilson, and Salas, 2005) and through the development of human resources (Ericksen and Dyer, 2005). Burke, Wilson, and Salas (2005) stress the importance of undergoing a cultural change process, placing particular emphasis on developing a resilient workforce through the use of training in teamworking skills, establishing a learning climate, and promoting expertise. Similarly, Ericksen and Dyer (2005) focus on the importance of employee behaviors as mediating the effect of organizational structures and processes in HROs on their highly reliable performance.
Practical Implications and Recommendations for Best Practice
Research relating to risk factors in accident prevention needs to recognize that the state of “not having an accident” should not be a passive one (e.g., employees passively following existing rules and regulations), but one of ongoing and continuous safety improvement. This state of proactive engagement with safety is a characteristic of HROs (as discussed previously). To achieve this, one needs a workforce that is proactive, engaged in the safety process, and resilient in the face of pressure (that is, better able to cope with difficult situations, recognize hazards, and know how to balance the conflict between production and safety). However, the type of intervention required to develop a resilient workforce is rarely implemented (Clarke, 2008).
Clarke (2008) distinguishes between four different types of safety intervention based on their approach (reactive or preventive) and their target (individual or organizational). Most safety interventions are individual-level and reactive (e.g., behavior-based safety programs, rule enforcement) or organization-level and reactive (e.g., ergonomic interventions, safety audits). Preventive interventions targeted at the individual (e.g., health and safety training aimed at problem-solving or hazard awareness) or the organization (e.g., employee participation) are rare. A few studies have examined the impact of “natural interventions” (that is, those initiated by the company, rather than interventions designed and implemented by a research team) on safety climate or safety attitudes. For example, Harvey et al., (2001) measured safety attitudes prior to the introduction of safety training (involving workshops, feedback, and development programs) within one department of a nuclear power plant; safety attitudes were then measured again after a period of 16 months. The study found that whilst managers’ safety attitudes had become significantly more positive, employees’ attitudes showed no significant change. A further example is illustrated in the study reported by Nielsen et al. (2008). In this case, the differences between two similar plants within the same manufacturing organization were examined. One plant had benefited from a work environment intervention prior to the start of the study, resulting in a more positive safety climate and lower accident rates than its sister plant which had not received the intervention. However, during the “natural intervention” the company transferred improved safety practices from the first plant to the second. Nielsen et al. (2008) found that over a 12- month period the safety climate and accident rate at the two plants converged (although some of this convergence was due to a decline in the first plant). Given the longitudinal nature of these studies, the evidence would support the positive impact of organization-level interventions, such as training on safety climate, which in turn lowers accident rate. However, such a conclusion must be drawn cautiously, given that methodologically rigorous evaluations of organizational-level safety interventions is quite limited.
Individual-based interventions that are reactive in nature can have “bubble-up” effects on the safety culture (DeJoy, 2005), but this tends to be as a byproduct, rather than as the target, of the intervention (Glendon, Clarke, and McKenna, 2006). There has been a distinct tendency among organizations to take a rather narrow view of safety interventions; however, there is growing evidence that at least some are taking a broader perspective. Interventions aimed at altering safety behavior (e.g., reducing violations) can be targeted at changing the safety culture (Parker et al. 1995). Such interventions (e.g., strict enforcement of all rules and regulations) would target the climate within which violations occur, rather than the behavior itself. A safety culture that encouraged over-rigid application of rules and regulations would be likely to create a frame of reference within which behavioral consensus (compliance) is perceived as valued above appropriate (safe) conduct (Höpfl, 1994). Developing a “just culture” involves “an atmosphere of trust in which people are encouraged, even rewarded, for providing essential safety-related information, but in which they are also clear about where the line must be drawn between acceptable and unacceptable behaviour” (Reason, 1997, p. 195). This approach can be reinforced by rewarding acceptable behavior and sanctioning unacceptable behavior, similar to the “no blame culture” adopted by HROs. A safety-based intervention of this kind would be most effective as part of a broader intervention package aimed at improving communication throughout the organization. Other intervention studies have focused on changes to supervisory behavior (e.g., Luria, Zohar, and Erev, 2008; Zohar, 2002b) rather than on organizational-level interventions. Such behavior-based interventions are designed to change behavior at a local level, rather than change climate throughout the organization. However, Zohar (2002b) found that safety climate increased significantly as the result of a change in supervisory behavior, possibly as a result of the “bubble-up” effect described previously.
A risk-management approach to safety should incorporate an emphasis on strategically integrating safety with other organizational objectives and using commitment-driven human resources practices to encourage worker involvement and participation (Glendon, Clarke, and McKenna, 2006). This constitutes a systematic approach to identifying and evaluating risks within an organization. A major obstacle to the successful implementation of safety initiatives has been a failure to explicitly link safety with productivity (Gillen et al., 2004). Hopkins observed that:
… organisational cultures may be detrimental to safety, not because leaders have chosen to sacrifice safety for the sake of production, but because they have not focused their attention on safety at all … if leaders attend to both production and safety, the organisations they lead will exhibit a culture which potentially emphasizes both. (Hopkins, 2005, p. 9)
Therefore, embedding safety as an organizational value should represent the first step toward achieving a positive safety culture.
A major driver of safety culture change is senior managers’ commitment to safety; however, this must be accompanied by both competence and cognizance (Reason, 1997). These factors can be enhanced through an effective risk-management approach to safety, such that relevant knowledge and expertise is drawn from the process of identifying, assessing, and evaluating risks. Although Reason (1997) noted that safety culture is more enduring than the commitment of current senior managers, this would be a point of leverage for changing toward a positive safety culture, as increased evidence of senior management commitment to safety would cascade down the organization through to improvements in safety climate at workforce level. Interventions at this level involve working with senior managers to institute a cultural change throughout the organization. The culture-change style of intervention has been described as a “trickle-down” approach (DeJoy, 2005). There is evidence that interventions at this level can be effective. For example, management training was successful in changing corporate behavior in relation to safety compliance (Stokols et al., 2001). However, one difficulty with this type of model is that it depends on effective communication to the workforce about the safety “vision” of senior managers. Flin (2003) reported on the use of 360˚ feedback and upwards appraisal in one organization to identify and reduce communication failures between senior management and workforce, where the role of middle managers in this process was emphasized.
Another important aspect of ensuring cultural change is managing the relationship between first-line management and the workforce; if enhanced trust can be developed at this level, it can help to cement new cultural values within an organization. Where management’s commitment to safety is clearly demonstrated through visible action, this is likely to lead to more positive employee perceptions of management processes. O’Toole (1999) found that merely providing the opportunity and encouraging workers to participate in the safety process at eight manufacturing sites resulted in lower lost-time injuries and reduced injury severity. Furthermore, O’Toole (2002) provided preliminary evidence of a strong relationship between improved management commitment to safety and a significant reduction in injuries. Whilst demonstrating management commitment to safety can help to build trust between employees and managers, interpersonal trust is a two-way process—managers must also trust their workers. Hofmann and Morgeson (1999) used a social exchange model to suggest that management commitment to safety encouraged return of worker loyalty through safe working behavior. This can be particularly difficult initially as, within poor safety climates, managers tend to view workers as responsible for injuries (and vice versa). However, as safety climate improves, the views of both groups become more realistic and less polarized (Prussia, Brown, and Willis, 2003).
Another driver of safety culture change involves harnessing worker commitment, involvement, and participation (Shaw and Blewitt, 1996; Vecchio-Sadus and Griffiths, 2004). A number of human resource practices can be used to encourage employee commitment, such as empowerment and decentralized decision-making (Vecchio-Sadus and Griffiths, 2004). Kelly (1996) observed that workers were more likely to demonstrate commitment to safety if they were actively involved in decision-making and problem-solving, and that empowerment was greater when workers were managed by principles rather than by rules. Worker empowerment promoted feelings of self-worth and belongingness, promoting the status of safety (Kelly, 1996). Introducing autonomous (or self-managing) teams is rarely undertaken to improve safety; however, positive safety benefits have been documented, particularly associated with team empowerment (Hechanova-Alampay and Beehr, 2002; Pearson, 1992; Roy, 2003). Increased autonomy and worker participation associated with team empowerment can encourage team members to take greater responsibility and ownership of safety, which in turn can serve to enforce behavioral norms (rules or standards established by group members to denote what is acceptable and unacceptable behavior) and promote safety-related behavior, particularly in the face of production pressures. Autonomous teamworking has also been noted as an indicator of high-performing organizations; thus, it may form part of a range of commitment-oriented management systems, which together contribute to a high standard of safety performance and low injury rates.
Employing practices that encourage worker participation can serve to demonstrate that managers value employees’ opinions and suggestions, as well as acknowledging employees’ operational experience and expertise. Reason (1997) discussed how reporting systems could be used to develop feelings of trust through confidentiality, indemnity against disciplinary proceedings, and separating the system from those who impose sanctions. However, this trust will be undermined in a work environment in which, for example, workers repeatedly encounter unworkable rules, managers fail to take action, supervisors put production before safety, or workers are blamed when things go wrong. Positive reinforcement of the safety culture must be seen to work on a daily basis throughout the organization in everything it does, thereby encouraging establishment of new group norms and internalization of safety values. Clarke’s (2006) meta-analysis of the relationship between safety climate and work injuries found the strongest relationship at group level. Thus, interventions should be considered from the perspective of not only the impact they will have on individuals, but also the effect they will have on work groups and intergroup relationships.
Recognizing individual differences in interventions to improve safety can help ensure their success. For example, it has been noted that, for interventions involving enhanced autonomy, workers who find added responsibility a burden rather than a benefit may reject increased control. There is research to suggest that some individuals, particularly those low in self-efficacy, will find that job control acts as an additional stressor, rather than buffering the effects of job demands on strain (Salanova, Peiró, and Schaufeli, 2002). Also, strain increases with job demands for passive employees (who show low levels of proactivity) regardless of the level of job control (Parker and Sprigg, 1999), indicating that interventions aimed at improving job control are likely to have little effect in reducing strain for these employees.
Consideration also needs to be given to individual factors in the design of interventions. For example, goal-focused leadership moderates the relationship between conscientiousness and performance, such that supervisors who set goals and clarify priorities enable the improved performance of conscientious workers (Colbert and Witt, 2009). Determining the personality characteristics of employees at both individual and team level would help in targeting interventions more effectively. In this case, a leadership intervention based on the emphasis of goal-oriented processes would be most effective for highly conscientious workers.
This chapter has reviewed a number of individual, organizational, and social risk factors associated with increased accident liability. Although there is renewed interest in the idea of the “accident-prone” individual, there is currently insufficient evidence to identify a stable psychological profile. However, additional research in this area is warranted, given that personality traits account for a moderate amount of variance in occupational accidents. In contrast, there is well-established evidence to support the role of organizational processes, leadership style, group processes, and (to a lesser extent) job characteristics as antecedents of unsafe behavior/accidents. Furthermore, there is also substantial evidence that the safety climate acts a mediating variable in the relationship between organizational factors and safety-related outcomes, including accidents. Nevertheless, well-designed evaluation studies of the impact of safety interventions are scarce, so our knowledge of the long-term effects of changing these variables is limited. The consideration of potential interactive effects of individual and environmental factors requires further research, as does the influence of other important variables such as perceived control. In relation to safety climate, we have a well-developed understanding of the role of management commitment to safety, but rather less insight to antecedents and outcomes relating to workers’ safety involvement and participation. In particular, little research has considered the possible moderating effects of individual difference variables—such as core self-evaluations, self-efficacy, and locus of control.
Lessons can be learnt from the study of high-reliability organizations, particularly in relation to the establishment and maintenance of a positive safety culture. A key aspect of this safety culture is a resilient and proactive workforce. Relating to the points made above, more research is needed on the type of interventions required to develop such a workforce in non-HROs.
 The preparation of this chapter was supported in part by York University. Several colleagues participated in the design and conduct of the research program: Lisa Fiksenbaum, Mustafa Koyuncu, Zena Burgess, Astrid Richardsen, Stig Matthiesen, and Graeme MacDermid.
 Of course, where “himself”, “his” or “he” and so on is used in the text, “herself”, “her” or “she” can be read as well.
 The other five are routine medicals, transfer testing, post-accident testing, “for cause” testing, and post-treatment or follow-up testing.
 According to the CIPD survey (2007), just over 60 percent of those employees who organizations referred to treatment or supported through rehabilitation remained working for the organization after successfully managing their problem.
 Barab later became a high-ranking safety official of the US Department of Labor in the Obama administration.
 The commission members were Joseph Califano (chairman), Douglas Fraser, B. Hamburg, M.D., D. Hamburg, MD, John E. Robson, and Robert Zoellick. The chairman was a former US Secretary of Health and Human Services.
 Susan Lander of AFSCME, quoted in Denenberg (2005a).
 The views of Keashly and Yamada are summarized in Minneapolis Star Tribune, (2003)