From Reactive to Proactive: Using Safety Survey to Assess Effectiveness of Airline SMS *

Transcription

1 Journal of Aeronautics, Astronautics and Aviation, Series A, Vol.40, No.1, pp (2008) 41 From Reactive to Proactive: Using Safety Survey to Assess Effectiveness of Airline SMS * Yueh-Ling Hsu ** Department of Air Transportation, Kainan University No. 1 Kainnan Road, Luzhu, Taoyuan County, Taiwan, 33857, R.O.C ABSTRACT The systemic origins of many accidents have led to heightened interest in the way in which organizations identify and manage risks within the airline industry, and to the development of safety management system (SMS). The purpose of this study is to probe into the evolution of proactive safety within airline SMS, uncover the critical organizational factors that influences proactive safety, and provide a practical application and validation of proactive safety approach for the airline industry. With a Taiwanese carrier cooperation, a safety perception survey was developed to assess the cultural and organizational factors as they relate to pilots at the carrier. The result of survey showed a response rate of 72 percent (651/908), and a principal component of factor analysis (PCA) followed by varimax rotation was performed on the questionnaire to interpreting the results. It identifies a framework for understanding the factors that underlie proactive safety mechanism within the airline safety management system. Moreover, specific factors reveal areas requiring organizational attention for managerial improvement. These target issues include areas of vulnerability perceived by the pilots, like cost/stress etc. Future efforts in this area will allow researchers to proactively pinpoint specific latent organizational factors in need of improvement for overall safety. Keywords: Safety Management System (SMS), Organizational safety culture; Crew attitude survey; Proactive safety I. INTRODUCTION With global aviation activity forecast continuing to rise, there is concern that traditional methods for reducing risks to an acceptable level may not be sufficient; new methods for understanding and managing safety are evolving. In particular within the airline industry, the systemic origins of many accidents have led to heightened interest in the way in which organizations identify and manage risks, and to the development of safety management system (SMS). In light of the importance of SMS, ICAO has a new safety requirement, which, with effect from 23 Nov 2006, demands that safety service providers (operators/organizations) are responsible to establish a Safety Management System (SMS), and States are responsible of the acceptance and oversight of providers SMS. To design, develop, and implement a Safety Management System that complies with ICAO requirements and applies a system safety approach to deliver services has therefore become the most important goal within the airline industry. By definition in ICAO Safety Management Manual (Doc 9859-AN/460) 1 that aims to provide States with guidance material on safety management, safety is the risk reduced to an acceptable level through a continuing process of hazard identification and risk management; Safety Management System is defined as a systematic approach to managing safety, including the necessary organizational structures, accountabilities, policies and procedures. As such, there exists three main characteristics of SMS, they are: 1) Systematic: safety management activities are in accordance with a * Manuscript received, Dec. 11, 2006, final revision, Aug. 16, 2007 ** To whom correspondence should be addressed, irishsu@mail.knu.edu.tw

2 42 Yueh-Ling Hsu pre-determined plan, and applied in a consistent manner throughout the organization; 2) Proactive: emphasizing prevention, through hazards identification and risk control and mitigation measures, before events that affect safety occur; and 3) Explicit: all safety management activities are documented, visible and performed independently from other management activities. Within SMS, safety management is considered from two different perspectives, namely Reactive and Proactive. To further clarify how reactive approaches are evolved to proactive concept and their application methods, this study aims to probe into reactive and proactive safety concepts/approaches within safety management system by synthesizing research in this area, and assess the critical organizational factors that influence proactive safety and further to airline SMS. As these factors are consistent across time and situation, they should also serve as the predictors of safety performance from proactive point of view. II. EVOLUTION OF SMS: FROM REACTIVE TO PROACTIVE Studies have shown that most safety systems are reactive [2,3], i.e. response to errors. Johnson [2] reveals the result of a survey, in which 83 percent of respondents indicated that safety programmes are reactive, isolated within organizations and preoccupied with quick fixes and putting out fires. There is no denying that fatal or serious accidents/incidents often catalyze the improvement of a safety system. Investigators seek to discover the potentially detrimental behaviors of operational personnel in order to identify and manage risks. Risk management tools are thus developed to collect the safety information and prevent the identified errors. Such events are traditionally adapted to assess the impact of human performance on safety, and can cause an airline either temporarily or permanently to change the management of its safety system. However, looking only at data after the fact (i.e. after an accident) is a little like trying to design a good celebration by focusing on the sweeping up after the parade [4]. Since the mid of nineties, researchers have emphasized the importance of a proactive approach to safety in aviation [5-9]. Johnston [6] further proposes that proactive and systemic risk management approaches will be more effective in preventing accidents than ad hoc reactions to individual acts of failures, or reactive interventions directed to individual workers. Other researchers emphasized the concept of organizational accident, such as Reason s model [10,11]features that all accidents result from a combination of specific situations that consist of individual actions and workplace conditions. Beaty [12]further puts it, Modern aircraft accidents result from collective mistakes rather than individual errors. Also, Edkins [13]points out that aircraft accidents have a positive correlation with latent failures, arising from the broad management functions of an organization. The latent failure/condition has changed the trend in favor of finding systemic or organizational problems. It also illustrates the effects that management s efforts can have on instilling a culture where safety is an operational value. Despite lack of explicit definition, proactive safety generally means to systematically eliminate latent situations or errors before incidents/accidents occur. It is deemed that cultural and organizational dimensions are two crucial elements in proactive safety [14]. Lots of efforts have been made in defining layers of cultures. In particular, safety culture is commonly viewed as an enduring characteristic of an organization that is reflected in its consistent way of dealing with critical safety issues [15]. It is generally agreed that similar underlying elements of a safety culture contain: beliefs, attitudes, norms, and values [16-18]. Some definitions also encompass the tangible manifestations of culture: priorities, behaviors and practices [19, 7]. Yet it is not easy to measure how good a good organizational safety culture is or how bad is a bad organizational safety culture. Reason [20] and Maurino [21] therefore suggests that measuring attitudes about teamwork, and the overall context of work is an important step in improving safety, i.e. the quality of safety performance is investigated within the framework of systems and contextual factors that provide the environments in which errors and adverse event occur, such as safety climate, morale, managerial support, etc. III. SAFETY SURVEY AS PROACTIVE ASSESSMENT One of the most commonly used methods of organizational assessment to assess safety critical factors of high-risk organizations is the survey approach. This approach allows access to a large distribution and broad cross section of the population [22]. Bailey and Petersen [23] suggest that a perception survey is a better measure of safety performance and a much better predictor of safety result, as it can identify the strengths and weaknesses of elements of a safety system. In other words, a safety survey is essentially used to review the extent of satisfaction with operations, and to diagnose any problems that may be apparent or suspected. By assessing safety attitudes, the real safety level of an organization can be determined. Zohar [24], who was the first to develop a safety climate survey, used it to establish the high agreement in employees perceptions regarding the safety climate in their company. Meanwhile, several questionnaires have been developed in various industries in an attempt to determine the key factors that comprise safety climate. Safety climate scales have been developed primarily on the basis of attitude items (e.g. Niskanen [25]), or based exclusively upon safety-related perceptions, with both attitudinal and perception items (e.g. Williamson et al., [26]). Within the airline industry, the Flight Management Attitudes Questionnaire (FMAQ) developed by University of Texas (UT) is a traditional human factors survey. Thaden et al. [22]also used to conduct Commercial Aviation Safety Survey (CASS) to assess safety culture.

3 From reactive to proactive: Using Safety Survey to Assess Effectiveness of Airline SMS Design of the Questionnaire In keeping with the aim of assessing organizational factors related to proactive safety in SMS of the airline industry, the concept of the perception survey is adapted for questionnaire development in this research. Cooperation was obtained from a Taiwanese carrier, which is striving for SMS and proactive safety. As there is unlikely to have all staff in the airline tested by the survey at one go, the first selected group to test is flight crewmembers. Therefore, the survey items were generated by FMAQ, review of the safety climate surveys and round table discussion with subject-matter personnel in the airline. This generates a pool of over 300 items. Redundant items were removed. The remaining items were then grouped by dimensions [27]and conducted with a pilot test. A statement was constructed for each item (potential concern) so that participants could be asked to rate the extent to which these aspects of their working environment were considered when making choices at work. The response format consisted of a six point Likert scale which ranged from Strongly disagree (1) to Strongly agree (6), plus N/A (0). Subject-matter personnel and selected pilots in the airline supplied the feedback of pilot test regarding the items and their appropriateness to include in a survey of airline pilots and management. Once the feedback was received, the items were revised, resulting in the 46-item (contain 12 dimensions: Communication, Financial concern, Crew leadership and command structure, Morale, Perception of management, Rule adherence, Stress recognition, Team work, Training, Information sharing, Working condition and Perceived safety culture) together with demographics information (Fleet, Nationality, Position, Status, Years within the company, Years employed in aviation and Background) crew attitude survey. Meanwhile, the last question, Q47, is the self safety performance rating, i.e. crew perceived safety performance compared to the industry, which is evaluated by a 6-point Likert scale ranging from Below average (1) to Above average (6). In this way, the relationship between airline safety management system and proactive safety mechanism and safety performance should become clear. 3.2 Method Nine hundred and eight Crew Safety Attitude Survey were distributed to all line pilots, based in Taiwan, across 4 fleets in the participant airline, excluding those who were based in US, taking initial training and part-time instructor pilots. A copy of the survey was placed in each pilot s mail folder where acts as one of the main communication system between crew and the airline. A letter from the management accompanied the survey, explaining the organizational and research purposes of the survey, and most importantly, encouraging employees to participate. Returned survey was required to drop in the collection point. In total it took around 3 months to complete the whole survey project. IV. RESULTS AND ANALYSES 4.1 Respondent Demographics Of the 908 surveys distributed, 651 were returned. All survey returned were in usable condition and included in the analysis. The average response rate in fleet is 71.7 percent, which is considered very good in this type of exercise. The survey also included a demographic section to provide additional information. Of the 651 survey returned, 78.6 percent respondents described their nationality as Taiwanese, 50.9 % Captain, and 88.3 % line pilot without any position. Around 35 % had been employed by the airline between 5-10 years, 29.6 % 0-5 years % are employed in aviation between 5-10 years, 23.8 % years. Most of them (41.5%) indicated that they are from military, 32.3 % ab-initio. 4.2 Factor Analysis and Internal Reliability In keeping with the aim of this research, Principal Component Analysis, followed by a varimax rotation, was performed on the 46-item questionnaire data from 651 respondents in order to examine the organizational factor structure. The data were deemed to be suitable for the analysis, as indicated by the Kaiser-Meyer-Olkin Measure of Sampling Adequacy value of 0.96 (Hair et al., 1995). The Bartlett Test of Sphericity was significant (χ 2 = , P< 0.05), indicating that correlations exist among some of the response categories. The factor analysis yielded a six-factor solution. To judge the internal reliability of these factors, Cronbach s Alpha statistics were calculated for the factors. For example, factor 1, with all items loaded onto it demonstrated an internal consistency of.898. Similarly the other factors all demonstrated acceptable levels of internal consistency (factor 2=.881, factor 3=.844, factor 4=.868, factor 5=.62, factor 6=.22). Since the sixth factor only contains two items plus reliability test less than 0.3, this factor was deleted for the further analysis. For the remaining 5 factors, the items loading primarily onto each factor were then examined to see if the factors made theoretical sense. According to the grouped items to those factors obtained with eigenvalues greater than 1, each factor was labelled in terms of its common underlying dimension nature. For factor 1, items loading into this factor were combined from the three out of twelve initial dimensions: leadership, teamwork and information sharing. They were mostly related to the crew performance in the cockpit and working environment; this factor was named F1: Crew safety compliance and participation. For factor 2, items loading onto this factor were associated with the decisional activities of managers on cost, rules and stress. It was therefore labeled as F2: Managerial decisions. For factor 3, items loading onto this factor were associated with the issues of policy, training and report functioning in the system. Thus, this factor was called F3: Operational system. For factor 4, items loading onto this factor were related to communication system and transmitting of operating procedures. This factor was thus called F4: Communication. For factor 5, items loading onto this factor were associated with the impact of management leadership and commitment on

4 44 Yueh-Ling Hsu safety performance. This factor was thus named F5: Management leadership and commitment. 4.3 Scale Scores (Mean score of factors) Scale scores for the airline on each of the five factors were determined by calculating the mean of the participants responses to the items in each factor. Means and standard deviation for each factor appear in Table 1. It shows that F2: Managerial decision, regarding management s decisional activities on cost, rules and stress gains the lowest rating, plus larger variance among crew as well. The detailed analyses and implication from the result will be provided in section 5.2. Table 1 Means and standard deviation of factors Factors Mean Std. Dev. F1: Crew safety compliance and participation F2: Managerial decision F3: Operational system F4: Communication F5: Management leadership and commitment Table 2 Post-hoc results on five factors across crew demographics F 1 F 2 F 3 F 4 F 5 Fleet 3>1 4>1 2>1 3>1 Nationality 1>2, 1>2, 1>3, 4>1 1>4 1>3 4>3 Position Status 1>2 Years within the company 1>3 Years 1>2, 1>3, 1>2, employed in aviation 1>5 5>3 1>3 Background 1>2, 1>3, 1>2, 3>2 2>3 3>2 1>2 Note: Fleet- largest fleet:1, fleet 2:2, fleet 3:3, fleet 4:4 Nationality- TW:1, nation 2:2, nation 3:3, nation 4:4 Status- CP:1, Line pilot:2 Years within the company- most junior:1, 10-15:3 Years employed in aviation- most junior:1, most senior:5 Background- Militatry:1. Non-military: 2& One-way Analysis of Variance (ANOVA) Across Crew Demographics In order to see whether these organizational factors differed across crew demographics, one-way Analysis of Variance (ANOVA) were conducted for each factor across Fleet, Nationality, Position, Status, Years with the company, Years employed in aviation and Background. When the effects are significant, the means must be then examined in order to determine the nature of the effects, by employing the post hoc multiple comparison- LSD. Table 2 shows the groups within the factors having significant mean difference at.05 levels and the results of post hoc analyses. The results indicate that there exists no variability within different positions (Captain, F/O and Relief pilot) towards the five factors. Meanwhile, in terms of F2: Managerial decision, it shows group differences in every aspect apart from position and status. This result echoes to section 4.3, and it also shows the variability may come from different fleet, nationality, years within the company and background. More details will be discussed in section Self-rated (perceived) Safety Performance In the end of survey, a question of self-rated safety performance (Q47) was included as stated in the previous section. The mean score for this item is It is one of the aims of this study to explore the relationship between the organizational factors and safety performance through the survey. As it is not possible to identify the safety performance from the anonymous survey, self-rated safety performance is therefore adopted. It was thought that an examination of the factors identified in the study were the biggest predictors of self-rated (perceived) safety performance, i.e. what organizational factors contributed to the explanation of the perceived safety performance, and to what degree, would provide some interesting insights into influential factors of proactive safety within SMS. One-way ANOVA were firstly conducted in this section in order to see whether perceived safety performance differed across crew demographics. Results of one-way ANOVA indicate significant differences in the perceived safety performance and different Nationality, Years in the company, Years employed in aviation and Background. Meanwhile stepwise multiple regression procedure was used. This part of the research was intended only as a guide to indicate which factors were the best predictors of perceived safety performance. By applying the standard multiple regression analysis, the dependent variable was the self-rated safety performance, and the independent variables were the organizational factors. Table 3 shows the model summary. The result of multiple regression and variance accounted by the factor scores in the regression equation was significant (F 5, 640 = , P<0.05). It indicates that there is a relationship between perceived safety performance and organizational factors. The perceived safety performance scale was significantly correlated to all factors except factor 5. V. DISCUSSIONS 5.1 Perceived Safety Performance From the result of this study, it is apparent that the overall perceived safety performance in this airline is a

5 From reactive to proactive: Using Safety Survey to Assess Effectiveness of Airline SMS 45 Table 3 Multiple regression result - model summary R R 2 Adjust R 2 ed R 2 F B Beta Change C 3.74 F F F F F F 1 F 2 F 3 F 4 F 5 Correlation with Q47.386**.160**.340**.277**.087 Contribution rate to Q % 2.6% 11.6 % 7.7 % 0.8% Note: ** Correlation is significant at the 0.01 level bit higher than average when compared to the industry (3.71> 3.5, see Figure 1). However, there exists some significantly statistical differences (ANOVA) within demographic groups. Taiwanese pilots and Military background pilots tend to have significant high scores than other groups, i.e. higher confidence on self-rated safety performance. Pilots from Europe/North America, junior pilots with 0-5 years in the company, senior pilots employed in aviation over 20 years, and civilian background pilots tend to have lower scores; also these groups with lower scores are largely overlapped. It is apparent that in the airline, crew are divided into two groups, namely national and expatriate, when self-rated safety performance is concerned. The reason behind may be that expatriate pilots usually pose various international airline experiences, plus Europe/North America carriers tend to have higher safety margin. Consequently, crew s self-confidence of safety performance in the participant carrier seems to be in an inverse proportion to the numbers of previous airline to work with. The other interesting observation is that management have higher mean score (mean=4) than any other status pilots (Line pilot/instructor Pilot/Check Pilot), although their mean differences are not significant. It appears that the management have higher confidence in company s safety performance compared to line crew. 5.2 Organizational Factors The data collected from 651 respondents within the airline identify five organizational factors and their mean scores are as shown in Figure 1. Among these five factors, two are regarding the system (F3 & F4), two are related to the management (F5 & F2), and one is about crew safety behavior (F1). The mean scores on two factors, F5: Management leadership & commitment and F1: Crew safety compliance and participation, were above the midpoint (3.5), indicating that respondents hold a generally positive opinion of their safety perception in regard to F1 F2 F3 F4 F5 Q47 Note: F1: Crew safety compliance and participation (3.9) F2: Managerial decision (2.83) F3: Operational system (3.08) F4: Communication (3.59) F5: Management leadership and commitment (4.12) Q47: Perceived safety performance Figure 1 Mean score on the five factors and Q 47 these two aspects. Two factors including F2: Managerial decision and F3: Operational system were below the neutral point; the former particularly received a lower score below three. It represents crew s lower agreement on decision makers and operational system. Communication is around the average score, showing the generally ordinary attitude toward this factor. Referring to the underlying nature of each factor, this result suggests that crewmembers highly agreed with the impact of management leadership and commitment on safety, and crew s compliance and participation in safety regarding leadership, teamwork and information sharing. However, there was an issue with decisional activities of managers, and operational system about policy, training and report system. It also reflects the consensus that crewmembers perceived the importance of management s leadership and commitment, but felt a bit disappointed about managerial decision, particularly on financial issues (cost) and stress recognition. Meanwhile, those factors with lower factor scores (Factor 2, 3, 4) were found to have higher standard deviations greater than 1 (see Table 1), revealing that there was some variability in response within these factors. For example, Table 2 shows the largest fleet has significant mean difference from other fleet on Factor 2 & 4. Examining their mean scores, it is found this fleet has the lowest satisfaction rate on factor 2,3 & 4, compared to other smaller fleets. It may be resulting from this fleet s longer flight pattern and schedule (long haul flights), which not only causes difficulties of communication channel but also increase the risk of rumor or non-precise perception to the company. Edkins and Coakes (2000) pointed out [28], It is easier to distribute, manage and communicate safety information with a smaller group of people. It is also easier to form and maintain closer links with management and be aware

6 46 Yueh-Ling Hsu of all safety activities within a smaller organization. Results of this research reflect their finding. On the other hand, junior pilots and military background pilots tended to have higher recognition on Factor 2,3 and 4. It seems that lower seniority and previous principle training cause the high level of consensus. Furthermore, the results of this study found that management (including check pilot) shared higher consensus towards three factors (Managerial decision, Operational system and Communication). It shows again the different recognition between management level and line pilots. This finding appears to be logical in the sense that management create and check standards, while line pilots obey the instructions and standards. Therefore, remedial strategies may be needed to fill the gap between crew and management on these issues mentioned above. Another similar findings to perceived safety performance (Q47) is that national and expatriate pilots seem to also form two different groups in terms of these five factors. Taiwanese crewmembers tended to value higher score associated with crew compliance and performance, operational system and management leadership, but rated lower score on managerial decision. Expatriate pilots were on the contrary. The reason behind that may be related to crew s loyalty. Expatriate pilots are usually more pay-oriented. They have more flexibility to choose different companies. Therefore, their main concerns are not managers style on cost and stress, but policy, training and report functioning in the system of the airline. In addition, there also exist group differences between military vs. ab-initio background pilots, and ab-initio vs. civilian background pilots. These are the areas that management should pay more attention too. 5.3 Perceived Safety Performance vs. Organizational Factors The present study also examined the link between perceived safety performance and organizational factors identified. Perceived safety in the criterion sense refers to the degree with which we can predict a respondent s perception of safety performance from the five organizational factors. Knowing which factors are most strongly related to perceived safety performance suggests an area of focus to improve safety attitudes and indicate the relative importance of each factor to the perceived safety. According to the result of multiple regression (see Table 3), an equation is developed as follows: Perceived Safety performance =.387*(F1:Crew safety compliance & participation) +.341*(F3:Operational system) +.276*(F4:Communication) +.161*(F2:Managerial decision) +.088*(F5:Management leadership& commitment) Although the correlation is not very strong, a positive relationship does exist between perceived safety and organizational factors. It indicates that higher factor scores are related to higher perceived safety performance, i.e. when the consensuses of crew safety compliance & participation (behavior) increase, perceived safety performance will increase as a result and so on. In addition, the contribution rates in Table 3 present to what extent perceived safety performance is predicted; for example, crew safety compliance & participation can predict 14.9% of perceived safety performance, which is regarded as the most influential predictor to safety performance. Since the rating score of perceived safety performance is medium-high, it also shows crewmembers have confidence in their proficiency- safety compliance and participation. Management commitment and leadership however seem to contribute the least (0.8 %) to perceived safety performance. Although management commitment is often deemed as the most important attribute in SMS, this result implies that crewmembers perceive the compliance to the regulations & policies and their proficiency as well as operational system counts more than commitment and leadership of management in safety performance achievement. More efforts are therefore required to clarify in this area in future research. VI. CONCLUSIONS Given the systematic and proactive characteristics of SMS, conducting safety survey is one of the recommended practical steps to operate a Safety Management System by ICAO [1], because safety survey can help to identify actual and potential safety hazards, suggest remedial actions and provide for continuous monitoring and regular assessment. Therefore, the objectives of this study are threefold: (1) to identify the evolution of proactive safety management in SMS; (2) to provide a practical and empirical application and validation of proactive safety approach by means of safety survey; and (3) to evaluate the current state of safety attitude and organizational factors among pilots at the airline. Three objectives are achieved, even with the existence of some constraints of this project. A number of important considerations are apparent from this study in regard to proactive safety management within the airline SMS. First, the results demonstrate that the proactive safety mechanism is a factor-structure concept, where employees have similar groups of attitudes and norms about the safety of their working environment. The airline example suggests a 5 factors construct: Crew safety compliance & participation, Operational system, Communication, Managerial decision and Management leadership & commitment; i.e. 3 categories, namely Management related, System related and Crew safety behavior. This result confirmed the effects that management s efforts can have on instilling a culture where safety is an operational value. Second, within these factors, significant differences and variation between various groups in the company do exist and are also identified through statistical test. Issues like National pilots vs. Expatriate pilots, Pay vs. Morale, Airline Seniority vs. Airline experiences, Military background vs. Commercial background and so on, these differences usually are not easy to be detected through safety audits, since they are sort of the latent conditions hidden in the organization. Third, perceived safety performance has a

7 From reactive to proactive: Using Safety Survey to Assess Effectiveness of Airline SMS 47 relationship with organizational factor mechanism, which embodies the relative importance of each factor to the perceived safety and provides the proactively focused area for remedial actions in SMS. In the case airline, crew safety compliance and participation (behavior) contribute to the most to the perceived safety performance, which appears to be logical. However, safety factor mechanism indicates that some managerial strategies and actions must be taken. Employees need to have more access to relevant information regarding managerial decision, and more sufficient opportunities to voice their concerns toward operational system, such as impact of cost concern and stress recognition. Meanwhile, with the increasing number of expatriate pilots in the airline, a more harmony team consensus is needed in-between national and expatriate pilots. Although the nature of the factors may vary according to the size and structure of the organization, to proactively maintain the effectiveness of SMS, it is important to be aware of the strengths and weaknesses of the system. Proactive approaches to safety are more like genetic engineering before a baby is even born, in order to create the right personality. This is the essence of proactive safety management and ultimate goal of SMS. Although present survey is only for pilots, the final objective of this project is to develop set of instruments that can be made available to other safety system related divisions in the airline (maintenance for example), and/or a variety of airlines to enable their SMS to evolve at a fundamental, genetic level. REFERENCES [1] International Civil Aviation Organization (ICAO), Safety Management Manual, ICAO, Montreal, Canada (Doc 9859-AN/460) [2] Johnson, D., Turning Safety on Its Head, Industrial Safety & Hygiene News. October [3] Earnest, R. 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